6778769ff6e6483dab735bc0c4c4fd5a		2024-12-06 19:20:38.740817	2024-12-06 19:20:30.661691	{"sigma":"1.5","train_data_folder":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/","geo_coord":"x,y","cluster_result":"/onesis/kt4/job_results/air-02-1206.csv","variable":"u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2","X":"2","Y":"2","iVariables":"/onesis/kt4/job_results/air-area-1206.json","air_quality":"PM2.5","k":"100","N_epoch":"100","best_arg":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/best_arg.json"}	t	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.variable: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2\nFinal variables: ['u10', 'v10', 't2m', 'sp', 'tp', 'AQI', 'PM10', 'NO2', 'CO', 'O3', 'SO2']\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\nchina_sites_2017010311.csv\nchina_sites_2017010416.csv\nchina_sites_2017010415.csv\nchina_sites_2017010418.csv\nchina_sites_2017010316.csv\nchina_sites_2017010413.csv\nchina_sites_2017010420.csv\nchina_sites_2017010320.csv\nchina_sites_2017010315.csv\nchina_sites_2017010310.csv\nchina_sites_2017010319.csv\nchina_sites_2017010312.csv\nchina_sites_2017010313.csv\nchina_sites_2017010417.csv\nchina_sites_2017010414.csv\nchina_sites_2017010411.csv\nchina_sites_2017010314.csv\nchina_sites_2017010419.csv\nchina_sites_2017010412.csv\nchina_sites_2017010317.csv\nchina_sites_2017010321.csv\nchina_sites_2017010318.csv\nchina_sites_2017010410.csv\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n{'AQI': 0.9939953734386318, 'PM10': 0.9702703712733087, 'NO2': 0.6916964527542312, 'CO': 0.6785650379279617}\n          u10       v10         t2m  ...         x        y  region\n0   -1.504657 -0.878221  273.013794  ...  117.4570  38.8394       1\n1    0.786217 -0.177140  271.731135  ...  114.3541  37.9097       2\n2   -0.908226 -0.827674  269.900488  ...  118.1997  39.6295       1\n3   -1.807954 -2.599573  274.702684  ...  119.5259  39.8283       1\n4   -0.631055 -2.190917  271.465984  ...  119.7624  40.0181       0\n..        ...       ...         ...  ...       ...      ...     ...\n231  0.601761 -0.591802  260.612814  ...   86.0697  44.3075       0\n232  0.702411 -1.409642  257.096259  ...   87.5475  44.1756       3\n233 -0.982240  0.603175  283.314504  ...  101.7227  26.5670       2\n234 -1.112682 -1.291874  289.298598  ...  118.0936  24.5058       2\n235 -1.192497  0.397621  272.886470  ...  113.1569  36.1912       1\n\n[236 rows x 15 columns]\n	38551381-f4bd-3728-850c-c2d4460669b8	Geo-SOM时空聚类与分区-192029	空气质量自变量: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 聚类分区的行数: 2; 聚类分区的列数: 2; GeoSOM算法迭代次数: 100; 地理邻域大小参数: 100; 初始邻域大小阈值: 1.5; 历史空气质量数据文件夹: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/; 最优自变量和权重结果: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/best_arg.json; 聚类分区结果: /onesis/kt4/job_results/air-02-1206.csv; 各分区中的最优自变量和权重结果: /onesis/kt4/job_results/air-area-1206.json; 	\N	6	\N
9e35f7ca3f404d01b8f2ceedcadd5430		2024-12-08 21:01:44.589571	2024-12-08 20:53:38.970968	{"op":"/onesis/kt4/data/rf_workflow/process_data/","c":"gini","mwfl":"0.0","msl":"1","mss":"2","v":"0","ne":"100","md":"3","rfm":"/onesis/kt4/data/rf_workflow/process_data/op1865741528526356480.tif","tl":"/onesis/kt4/data/rf_workflow/origin_data/expansion/expansion.tif","tfm":"/onesis/kt4/data/rf_workflow/origin_data/temp/temp.tif","sfm":"/onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif","ca":"0.0","wfm":"/onesis/kt4/data/rf_workflow/process_data/op1865741528366972928.tif"}	f	\N	1ff85b32-db18-370f-8fa9-84cb0ded6ce1	土地利用类型发展潜力（随机森林算法）	坡度样本: /onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif; 道路样本: /onesis/kt4/data/rf_workflow/process_data/op1865741528526356480.tif; 水体样本: /onesis/kt4/data/rf_workflow/process_data/op1865741528366972928.tif; 温度样本: /onesis/kt4/data/rf_workflow/origin_data/temp/temp.tif; 训练标签: /onesis/kt4/data/rf_workflow/origin_data/expansion/expansion.tif; 树木数量: 100; 不纯度方法: gini; 最大深度: 3; 拆分内节点最少样本数: 2; 叶节点最小样本数: 1; 最小加权分数: 0.0; 详细程度: 0; 复杂度参数: 0.0; 输出路径: /onesis/kt4/data/rf_workflow/process_data/; 	\N	9	2903307a-802e-47a8-8b31-7a79feb4f90a
d067bc7c417f4853b0261716b962971d		2024-12-06 19:32:06.905058	2024-12-06 19:31:29.898545	{"sigma":"1.5","train_data_folder":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/","geo_coord":"x,y","cluster_result":"/onesis/kt4/job_results/cluster_result1864996077866975232.csv","variable":"u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2","X":"2","Y":"2","iVariables":"/onesis/kt4/job_results/iVariables1864996077866975232.json","air_quality":"PM2.5","k":"100","best_arg":"/onesis/kt4/job_results/best_arg1864996077808254976.json","N_epoch":"100"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.variable: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2\nFinal variables: ['u10', 'v10', 't2m', 'sp', 'tp', 'AQI', 'PM10', 'NO2', 'CO', 'O3', 'SO2']\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\nchina_sites_2017010311.csv\nchina_sites_2017010416.csv\nchina_sites_2017010415.csv\nchina_sites_2017010418.csv\nchina_sites_2017010316.csv\nchina_sites_2017010413.csv\nchina_sites_2017010420.csv\nchina_sites_2017010320.csv\nchina_sites_2017010315.csv\nchina_sites_2017010310.csv\nchina_sites_2017010319.csv\nchina_sites_2017010312.csv\nchina_sites_2017010313.csv\nchina_sites_2017010417.csv\nchina_sites_2017010414.csv\nchina_sites_2017010411.csv\nchina_sites_2017010314.csv\nchina_sites_2017010419.csv\nchina_sites_2017010412.csv\nchina_sites_2017010317.csv\nchina_sites_2017010321.csv\nchina_sites_2017010318.csv\nchina_sites_2017010410.csv\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n{'AQI': 0.9939953734386318, 'PM10': 0.9702703712733087, 'NO2': 0.6916964527542312, 'CO': 0.6785650379279617}\n          u10       v10         t2m  ...         x        y  region\n0   -1.504657 -0.878221  273.013794  ...  117.4570  38.8394       1\n1    0.786217 -0.177140  271.731135  ...  114.3541  37.9097       2\n2   -0.908226 -0.827674  269.900488  ...  118.1997  39.6295       1\n3   -1.807954 -2.599573  274.702684  ...  119.5259  39.8283       1\n4   -0.631055 -2.190917  271.465984  ...  119.7624  40.0181       0\n..        ...       ...         ...  ...       ...      ...     ...\n231  0.601761 -0.591802  260.612814  ...   86.0697  44.3075       0\n232  0.702411 -1.409642  257.096259  ...   87.5475  44.1756       3\n233 -0.982240  0.603175  283.314504  ...  101.7227  26.5670       2\n234 -1.112682 -1.291874  289.298598  ...  118.0936  24.5058       2\n235 -1.192497  0.397621  272.886470  ...  113.1569  36.1912       1\n\n[236 rows x 15 columns]\n	38551381-f4bd-3728-850c-c2d4460669b8	Geo-SOM时空聚类与分区	最优自变量和权重结果: /onesis/kt4/job_results/best_arg1864996077808254976.json; 空气质量自变量: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 聚类分区的行数: 2; 聚类分区的列数: 2; GeoSOM算法迭代次数: 100; 地理邻域大小参数: 100; 初始邻域大小阈值: 1.5; 聚类分区结果: /onesis/kt4/job_results/cluster_result1864996077866975232.csv; 各分区中的最优自变量和权重结果: /onesis/kt4/job_results/iVariables1864996077866975232.json; 历史空气质量数据文件夹: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/; 	\N	6	bd5c2ba8-c84d-492f-88cd-1cea6f2a96c3
8dfb5ff2c74a4d2e820bec66ee881808		2024-12-06 19:32:11.96053	2024-12-06 19:31:29.692877	{"cluster_result":"/onesis/kt4/job_results/cluster_result1864996077866975232.csv","geo_coord":"x,y","output_pred":"/onesis/kt4/job_results/air-wl-1206.csv","iVariables":"/onesis/kt4/job_results/iVariables1864996077866975232.json","air_quality":"PM2.5","pred_data_path":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode3_multiple_liner_predication/data/china_sites_2017010421.csv"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\n分区: 2 参数: [-9.17260618e+01  1.15499769e+00 -7.40924971e-02  2.99461750e-01\n -1.52553604e+00] r2: 0.04847284127008744\n分区: 1 参数: [-1.14783449e+01  1.03024321e+00 -1.77088043e-01  8.22878304e-03\n -7.51832896e-01] r2: 0.1362039547508621\n分区: 0 参数: [-16.20075884   0.95799733  -0.11488578   0.04130823   0.50384864] r2: 0.12968084093122045\n分区: 3 参数: [-6.72655057  0.88644638 -0.06857409 -0.07571871  1.39279085] r2: 0.13450412913640308\n[-16.20075884   0.95799733  -0.11488578   0.04130823   0.50384864]\n(236, 4)\n(5,)\n(236,)\n[396.17703522 440.11946815 465.78721446 149.03330726 239.2668603\n 411.39272227 557.69985264 198.12144644 126.69475322 320.41926066\n 171.61539574 167.18630816 113.70423662 103.22910083 156.62455397\n 152.23310223 106.19298763 275.74487015 209.77656399 271.03594089\n 158.31059713 197.40603472 222.63380295 256.44311477 260.1729824\n 331.11126276 254.43295789 431.16323707 418.62896274 309.31697001\n 236.08356268  78.78841984  60.03903233  64.8285143  148.37529542\n 141.52021318 312.78381693 227.76116587 105.06769494 146.28788292\n 833.97199623 424.09415782 463.79435731 202.71642708 234.34897757\n 280.69036558 350.75215705  97.03563916 102.97617794  93.95096881\n  91.3990686  100.43586958 351.05256207 118.08563428 118.61950159\n 125.70559466 146.71765689 157.13819144  77.93290573 276.18537576\n 403.46214467 390.36298146 544.25834349  96.99605583  45.26018141\n 145.5668589  843.39800678 848.70295619 416.25326901 317.30945353\n 267.59200806 225.23289553 191.26128042 149.50221839 102.74888203\n 351.86295938 572.73696958 508.38880794 485.6235902  604.13122463\n 694.14006136 154.4216226  401.48954481 438.14847849 420.46670392\n 106.44329187  74.48481909  68.20073605  91.52043078 141.01019813\n 143.58265439  95.1365097  153.74951554 239.79164642 109.34951\n 107.48138924 103.50260982 221.95156767 245.26226003 201.71236032\n 529.84144821 396.5102584  206.08247047 272.45981367 266.80406409\n 491.74598665 448.9110954  349.55809293 392.57367448 388.18399575\n 397.23489106 457.20939221 770.78712227 276.74119245  67.45542648\n 380.36229495 476.59524164  43.48904215 640.88797899 280.06835662\n 845.44415635 749.43622287 402.5170224  700.70622244 839.7164304\n 310.04455601 201.44935419 188.48758681 445.29015938  96.1750258\n 178.36481854 166.65283042 174.84143746 246.92569813 162.00815874\n 353.88387704 332.95704806 291.27950985 185.18374818 581.4469131\n 254.11136302  94.48195865 259.91685583 180.71111809 196.92510013\n  72.38242603 364.29761555 242.55990169 149.79238673 498.03252546\n  55.89859889  69.40310519 308.3773301  267.07341838 274.40345295\n 339.40426836 376.78302989 357.02368093 325.82452504 276.62242526\n 332.61486537 125.99811546 144.61993618 118.52033303 135.19517623\n 120.835986   120.33575073 300.16128656 459.06235963 396.68253605\n 541.48335696 369.40599752 395.55008862 330.79240091 322.48031196\n 450.03666446 375.22849345 414.42847136 220.84641959 127.21178498\n 323.08086731 459.36437395 181.22939056 459.48752461 236.26781916\n 450.1962574  320.79503976 506.16126829 336.63394473 373.47717222\n 670.49744871 265.28517739 135.90710619 274.94896314 250.71209262\n 328.73968982 163.74610484 296.72835586 255.25745771 297.99748595\n 407.45734092 651.26657424 473.82825884 351.1842736  125.40313417\n  80.05780964  60.8731675  106.6258979  298.50186774  80.61790271\n  58.83653333  87.8784506   64.29725017  71.26237703  76.19169259\n 274.43725859 145.23515721 161.33597113 193.74639693 227.59942663\n 507.98745965 354.32328377 139.54759323 340.54707414 306.34871899\n 108.64584096 232.33494846 135.05560146 150.90761716 195.18844667\n 222.18795846 547.43333005 449.88763781  54.61502136 147.90030662\n 382.6595909 ]\n	e064bcfe-b606-39a2-b35f-09f1f9944f89	空气质量多元线性回归预测	各分区中的最优自变量和权重结果: /onesis/kt4/job_results/iVariables1864996077866975232.json; 聚类分区结果文件: /onesis/kt4/job_results/cluster_result1864996077866975232.csv; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 待预测的空气质量数据集: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode3_multiple_liner_predication/data/china_sites_2017010421.csv; 空气质量预测结果输出文件: /onesis/kt4/job_results/air-wl-1206.csv; 	\N	6	bd5c2ba8-c84d-492f-88cd-1cea6f2a96c3
ab22a571eda34ac1937db0ec7c35ffee		2024-12-08 20:55:18.506158	2024-12-08 20:53:39.151817	{"op":"/onesis/kt4/data/rf_workflow/process_data/op1865741528526356480.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/road/road.shp","height":"69"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=64849e5d1b124e9e98fe45a7dab6f8e6, listenThread=thread13}\n        managedFields: null\n        name: 64849e5d1b124e9e98fe45a7dab6f8e6\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=64849e5d1b124e9e98fe45a7dab6f8e6}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-np, 1, d8flowdir, -fel, /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif, -sd8, /data/onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/taudem_ext:5.3.9\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: 64849e5d1b124e9e98fe45a7dab6f8e6\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)	输入文件: /onesis/kt4/data/rf_workflow/origin_data/road/road.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/op1865741528526356480.tif; 	\N	7	2903307a-802e-47a8-8b31-7a79feb4f90a
efd17755150b48ef99d63d1ec4a75ae1		2024-12-08 21:22:46.561975	2024-12-08 21:21:50.724568	{"op":"/onesis/kt4/data/rf_workflow/process_data/op1865748622948302848.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/water/waterways.shp","height":"69"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=c4a0dfc4ae114ba4a083d7f81352ce5c, listenThread=thread10}\n        managedFields: null\n        name: c4a0dfc4ae114ba4a083d7f81352ce5c\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=c4a0dfc4ae114ba4a083d7f81352ce5c}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-np, 1, d8flowdir, -fel, /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif, -sd8, /data/onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/taudem_ext:5.3.9\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: c4a0dfc4ae114ba4a083d7f81352ce5c\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	9b6f0379-c38c-304f-baf0-0a95fd17ac30	欧氏距离分析(水流)	输入文件: /onesis/kt4/data/rf_workflow/origin_data/water/waterways.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/op1865748622948302848.tif; 	\N	7	74ce2c17-430f-4ecf-9ad9-ced80ea0499c
ddfc832ff67e46349bb6e503745d266b		2024-12-08 20:55:18.480002	2024-12-08 20:53:39.193473	{"op":"/onesis/kt4/data/rf_workflow/process_data/op1865741528366972928.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/water/waterways.shp","height":"69"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=64849e5d1b124e9e98fe45a7dab6f8e6, listenThread=thread13}\n        managedFields: null\n        name: 64849e5d1b124e9e98fe45a7dab6f8e6\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=64849e5d1b124e9e98fe45a7dab6f8e6}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-np, 1, d8flowdir, -fel, /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif, -sd8, /data/onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/taudem_ext:5.3.9\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: 64849e5d1b124e9e98fe45a7dab6f8e6\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	9b6f0379-c38c-304f-baf0-0a95fd17ac30	欧氏距离分析(水流)	输入文件: /onesis/kt4/data/rf_workflow/origin_data/water/waterways.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/op1865741528366972928.tif; 	\N	7	2903307a-802e-47a8-8b31-7a79feb4f90a
64849e5d1b124e9e98fe45a7dab6f8e6		2024-12-08 20:53:43.752848	2024-12-08 20:53:39.224791	{"sd8":"/onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif","fel":"/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif has geographic coordinate system.\nNodata value input to create partition from file: -340282306073709652508363335590014353408.000000\nNodata value recast to float used in partition raster: -340282306073709652508363335590014353408.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nERROR 4: Attempt to create new tiff file `/data/onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif' failed: No error information\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetProjection'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetGeoTransform'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALGetRasterBand'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALSetRasterNoDataValue'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALFlushCache'.\n\nAll slopes evaluated. 3090 flats to resolve.\nRaterIO trouble: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nDraining flats towards lower adjacent terrain\n.......\nDraining flats away from higher adjacent terrain\n.........\nSetting directions\nIteration complete. Number of flats remaining: 6\nDraining flats towards lower adjacent terrain\n.\nDraining flats away from higher adjacent terrain\n..\nSetting directions\nProcessors: 1\nHeader read time: 0.079850\nData read time: 0.000577\nCompute Slope time: 0.001106\nWrite Slope time: 0.010737\nResolve Flat time: 0.008620\nWrite Flat time: 0.001539\nTotal time: 0.102430\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif; 坡度栅格: /onesis/kt4/data/rf_workflow/process_data/sd81865741528446664704.tif; 	\N	6	2903307a-802e-47a8-8b31-7a79feb4f90a
e45153e87076470dab85fdd2b7c3a317		2024-12-08 21:58:57.396173	2024-12-08 21:58:53.784718	{"epsg":"0","file":"/onesis/kt4/job_results/1d8_flow_meixi_1208.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/gdal.py:312: FutureWarning: Neither gdal.UseExceptions() nor gdal.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\n1d8_flow_meixi_1208.tif is in WGS84 or based on WGS84.\nProject done.\n	84641a52-bd00-3734-9c49-597a3f5d2e73	reproject:367a2a653be946fdb733b7ea94725492	数据路径: /onesis/kt4/job_results/1d8_flow_meixi_1208.tif; EPSG号: 0; 	\N	6	\N
a398606ba163413385a225412d1c433d		2024-12-08 21:12:30.511181	2024-12-08 21:11:36.092453	{"op":"/onesis/kt4/data/rf_workflow/process_data/op1865746046303469568.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/road/road.shp","height":"69"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=a7fb63aa1d6e4c1ca554e56b6a5f8665, listenThread=thread6}\n        managedFields: null\n        name: a7fb63aa1d6e4c1ca554e56b6a5f8665\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=a7fb63aa1d6e4c1ca554e56b6a5f8665}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-np, 1, d8flowdir, -fel, /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif, -sd8, /data/onesis/kt4/data/rf_workflow/process_data/sd81865746046458658816.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/taudem_ext:5.3.9\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: a7fb63aa1d6e4c1ca554e56b6a5f8665\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)	输入文件: /onesis/kt4/data/rf_workflow/origin_data/road/road.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/op1865746046303469568.tif; 	\N	7	dff839e2-1cf5-4a90-8aa1-ebde54892168
c4a0dfc4ae114ba4a083d7f81352ce5c		2024-12-08 21:21:55.26012	2024-12-08 21:21:50.79856	{"sd8":"/onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif","fel":"/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif has geographic coordinate system.\nNodata value input to create partition from file: -340282306073709652508363335590014353408.000000\nNodata value recast to float used in partition raster: -340282306073709652508363335590014353408.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nERROR 4: Attempt to create new tiff file `/data/onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif' failed: No error information\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetProjection'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetGeoTransform'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALGetRasterBand'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALSetRasterNoDataValue'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nRaterIO trouble: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALFlushCache'.\n\nAll slopes evaluated. 3090 flats to resolve.\nDraining flats towards lower adjacent terrain\n.......\nDraining flats away from higher adjacent terrain\nProcessors: 1\nHeader read time: 0.125074\nData read time: 0.000770\nCompute Slope time: 0.001947\nWrite Slope time: 0.015256\nResolve Flat time: 0.012307\nWrite Flat time: 0.002042\nTotal time: 0.157397\n.........\nSetting directions\nIteration complete. Number of flats remaining: 6\nDraining flats towards lower adjacent terrain\n.\nDraining flats away from higher adjacent terrain\n..\nSetting directions\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif; 坡度栅格: /onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif; 	\N	6	74ce2c17-430f-4ecf-9ad9-ced80ea0499c
792d00c3674e46af96404e13f9421c7c		2024-12-08 21:37:08.045999	2024-12-08 21:36:14.240778	{"op":"/onesis/kt4/data/rf_workflow/process_data/road_distance.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/road/road.shp","height":"69"}	t	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=792d00c3674e46af96404e13f9421c7c, listenThread=thread8}\n        managedFields: null\n        name: 792d00c3674e46af96404e13f9421c7c\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=792d00c3674e46af96404e13f9421c7c}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-sfp, /data/onesis/kt4/data/rf_workflow/origin_data/road/road.shp, -width, 94, -height, 69, -op, /data/onesis/kt4/data/rf_workflow/process_data/road_distance.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/distance_analysis:1.0-scipy\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: 792d00c3674e46af96404e13f9421c7c\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)-213613	输入文件: /onesis/kt4/data/rf_workflow/origin_data/road/road.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/road_distance.tif; 	\N	7	\N
e9dafa992276412080a06b0d0fa5e563		2024-12-08 21:56:39.176157	2024-12-08 21:56:34.903652	{"epsg":"0","file":"/onesis/kt4/job_results/d8_flow.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/gdal.py:312: FutureWarning: Neither gdal.UseExceptions() nor gdal.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\nd8_flow.tif is in WGS84 or based on WGS84.\nProject done.\n	84641a52-bd00-3734-9c49-597a3f5d2e73	reproject:da62169b583d4d41868c7273ef8cd945	数据路径: /onesis/kt4/job_results/d8_flow.tif; EPSG号: 0; 	\N	6	\N
7ab0b4a22ba54c049f71cf36d98300cd		2024-12-08 21:31:40.057556	2024-12-08 21:30:46.775201	{"op":"/onesis/kt4/data/rf_workflow/process_data/distance_road.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/road/road.shp","height":"69"}	t	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=7ab0b4a22ba54c049f71cf36d98300cd, listenThread=thread0}\n        managedFields: null\n        name: 7ab0b4a22ba54c049f71cf36d98300cd\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=7ab0b4a22ba54c049f71cf36d98300cd}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-sfp, /data/onesis/kt4/data/rf_workflow/origin_data/road/road.shp, -width, 94, -height, 69, -op, /data/onesis/kt4/data/rf_workflow/process_data/distance_road.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/distance_analysis:1.0-scipy\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: 7ab0b4a22ba54c049f71cf36d98300cd\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)-213045	输入文件: /onesis/kt4/data/rf_workflow/origin_data/road/road.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/distance_road.tif; 	\N	7	\N
abad0af77323473c943ffd329be03b14		2024-12-08 21:26:26.049397	2024-12-08 21:25:32.699436	{"op":"/onesis/kt4/data/rf_workflow/process_data/distance_road.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/road/road.shp","height":"69"}	t	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=abad0af77323473c943ffd329be03b14, listenThread=thread9}\n        managedFields: null\n        name: abad0af77323473c943ffd329be03b14\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=abad0af77323473c943ffd329be03b14}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-sfp, /data/onesis/kt4/data/rf_workflow/origin_data/road/road.shp, -width, 94, -height, 69, -op, /data/onesis/kt4/data/rf_workflow/process_data/distance_road.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/distance_analysis:1.0-scipy\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: abad0af77323473c943ffd329be03b14\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)-212529	输入文件: /onesis/kt4/data/rf_workflow/origin_data/road/road.shp; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/distance_road.tif; 	\N	7	\N
1789efd9deb84e008fe5ed845922886d		2025-01-05 17:08:56.704127	2025-01-05 17:07:52.85823	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875831570775015424.tif","o":"/onesis/kt4/xuancheng/result/o1875831571307692032.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	Z 转换因子: 1; 输入栅格 DEM 文件: /onesis/kt4/xuancheng/result/fel1875831570775015424.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875831571307692032.tif; 	\N	7	220aef12-09ad-434c-aa2d-04914a69bc6c
8c05ad159b2b4d8a9e84ae4cf46eab82		2025-01-08 15:26:14.838804	2024-12-08 21:21:50.557803	{"op":"/onesis/kt4/data/rf_workflow/process_data/","c":"gini","mwfl":"0.0","msl":"1","mss":"2","v":"0","ne":"100","md":"3","rfm":"/onesis/kt4/data/rf_workflow/process_data/op1865748622600175616.tif","tl":"/onesis/kt4/data/rf_workflow/origin_data/expansion/expansion.tif","tfm":"/onesis/kt4/data/rf_workflow/origin_data/temp/temp.tif","sfm":"/onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif","ca":"0.0","wfm":"/onesis/kt4/data/rf_workflow/process_data/op1865748622948302848.tif"}	f	\N	1ff85b32-db18-370f-8fa9-84cb0ded6ce1	土地利用类型发展潜力（随机森林算法）	坡度样本: /onesis/kt4/data/rf_workflow/process_data/sd81865748623250292736.tif; 道路样本: /onesis/kt4/data/rf_workflow/process_data/op1865748622600175616.tif; 水体样本: /onesis/kt4/data/rf_workflow/process_data/op1865748622948302848.tif; 温度样本: /onesis/kt4/data/rf_workflow/origin_data/temp/temp.tif; 训练标签: /onesis/kt4/data/rf_workflow/origin_data/expansion/expansion.tif; 树木数量: 100; 不纯度方法: gini; 最大深度: 3; 拆分内节点最少样本数: 2; 叶节点最小样本数: 1; 最小加权分数: 0.0; 详细程度: 0; 复杂度参数: 0.0; 输出路径: /onesis/kt4/data/rf_workflow/process_data/; 	\N	9	74ce2c17-430f-4ecf-9ad9-ced80ea0499c
6d7cabd96f5b45b495a4c70e1ce62c72		2024-12-08 21:50:28.048623	2024-12-08 21:49:34.076284	{"op":"/onesis/kt4/data/rf_workflow/process_data/road_distance.tif","width":"94","sfp":"/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif","height":"69"}	t	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nclass V1Job {\n    apiVersion: null\n    kind: Job\n    metadata: class V1ObjectMeta {\n        annotations: null\n        clusterName: null\n        creationTimestamp: null\n        deletionGracePeriodSeconds: null\n        deletionTimestamp: null\n        finalizers: null\n        generateName: null\n        generation: null\n        labels: {security=6d7cabd96f5b45b495a4c70e1ce62c72, listenThread=thread7}\n        managedFields: null\n        name: 6d7cabd96f5b45b495a4c70e1ce62c72\n        namespace: modelengine\n        ownerReferences: null\n        resourceVersion: null\n        selfLink: null\n        uid: null\n    }\n    spec: class V1JobSpec {\n        activeDeadlineSeconds: null\n        backoffLimit: 0\n        completionMode: null\n        completions: null\n        manualSelector: null\n        parallelism: null\n        selector: null\n        suspend: null\n        template: class V1PodTemplateSpec {\n            metadata: class V1ObjectMeta {\n                annotations: null\n                clusterName: null\n                creationTimestamp: null\n                deletionGracePeriodSeconds: null\n                deletionTimestamp: null\n                finalizers: null\n                generateName: null\n                generation: null\n                labels: {security=6d7cabd96f5b45b495a4c70e1ce62c72}\n                managedFields: null\n                name: null\n                namespace: null\n                ownerReferences: null\n                resourceVersion: null\n                selfLink: null\n                uid: null\n            }\n            spec: class V1PodSpec {\n                activeDeadlineSeconds: 43200\n                affinity: null\n                automountServiceAccountToken: null\n                containers: [class V1Container {\n                    args: [-sfp, /data/onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif, -width, 94, -height, 69, -op, /data/onesis/kt4/data/rf_workflow/process_data/road_distance.tif]\n                    command: null\n                    env: null\n                    envFrom: null\n                    image: registry.cn-hangzhou.aliyuncs.com/onesis-geomodels/distance_analysis:1.0-scipy\n                    imagePullPolicy: IfNotPresent\n                    lifecycle: null\n                    livenessProbe: null\n                    name: 6d7cabd96f5b45b495a4c70e1ce62c72\n                    ports: null\n                    readinessProbe: null\n                    resources: null\n                    securityContext: null\n                    startupProbe: null\n                    stdin: null\n                    stdinOnce: null\n                    terminationMessagePath: null\n                    terminationMessagePolicy: null\n                    tty: null\n                    volumeDevices: null\n                    volumeMounts: [class V1VolumeMount {\n                        mountPath: /data\n                        mountPropagation: null\n                        name: pvc-oss-runmodel\n                        readOnly: null\n                        subPath: null\n                        subPathExpr: null\n                    }]\n                    workingDir: null\n                }]\n                dnsConfig: null\n                dnsPolicy: null\n                enableServiceLinks: null\n                ephemeralContainers: null\n                hostAliases: null\n                hostIPC: null\n                hostNetwork: null\n                hostPID: null\n                hostname: null\n                imagePullSecrets: null\n                initContainers: null\n                nodeName: null\n                nodeSelector: null\n                os: null\n                overhead: null\n                preemptionPolicy: null\n                priority: null\n                priorityClassName: null\n                readinessGates: null\n                restartPolicy: Never\n                runtimeClassName: null\n                schedulerName: null\n                securityContext: null\n                serviceAccount: null\n                serviceAccountName: null\n                setHostnameAsFQDN: null\n                shareProcessNamespace: null\n                subdomain: null\n                terminationGracePeriodSeconds: null\n                tolerations: null\n                topologySpreadConstraints: null\n                volumes: [class V1Volume {\n                    awsElasticBlockStore: null\n                    azureDisk: null\n                    azureFile: null\n                    cephfs: null\n                    cinder: null\n                    configMap: null\n                    csi: null\n                    downwardAPI: null\n                    emptyDir: null\n                    ephemeral: null\n                    fc: null\n                    flexVolume: null\n                    flocker: null\n                    gcePersistentDisk: null\n                    gitRepo: null\n                    glusterfs: null\n                    hostPath: null\n                    iscsi: null\n                    name: pvc-oss-runmodel\n                    nfs: null\n                    persistentVolumeClaim: class V1PersistentVolumeClaimVolumeSource {\n                        claimName: modelengine-pvc\n                        readOnly: null\n                    }\n                    photonPersistentDisk: null\n                    portworxVolume: null\n                    projected: null\n                    quobyte: null\n                    rbd: null\n                    scaleIO: null\n                    secret: null\n                    storageos: null\n                    vsphereVolume: null\n                }]\n            }\n        }\n        ttlSecondsAfterFinished: 50\n    }\n    status: null\n}	a12bb857-2e6e-3c1b-b998-2464a04038a5	欧氏距离分析(道路)-214933	输入文件: /onesis/kt4/data/rf_workflow/origin_data/dem/dem.tif; 图像宽度: 94; 图像高度: 69; 输出文件: /onesis/kt4/data/rf_workflow/process_data/road_distance.tif; 	\N	7	\N
60114e9715834a52b0a9cbfa7394c23d		2024-12-09 17:17:32.380108	2024-12-09 17:16:37.383106	{"d":"/onesis/kt4/test_data/regr/_whhp/whhp.shp","t":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298156879872.csv","i":"OBJECTID","j":"id","o":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nLinking to GEOS 3.10.3, GDAL 3.5.3, PROJ 9.0.0; sf_use_s2() is TRUE\n\nAttaching package: ‘dplyr’\n\nThe following objects are masked from ‘package:stats’:\n\n    filter, lag\n\nThe following objects are masked from ‘package:base’:\n\n    intersect, setdiff, setequal, union\n\nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	96a25d86-5c91-3a5a-b9e8-9b88894afe55	数据连接	输入矢量数据: /onesis/kt4/test_data/regr/_whhp/whhp.shp; 目标数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298156879872.csv; 连接字段: OBJECTID; 对应字段: id; 结果数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
911fe9d817234f1c89752847805d78ab		2024-12-09 17:17:25.288046	2024-12-09 17:16:37.441949	{"d":"/onesis/kt4/test_data/regr/_whhp/whhp.shp","t":"/onesis/kt4/test_data/regr/_whhp/res/r1866049298093965312.shp","i":"OBJECTID","o":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298156879872.csv"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nLinking to GEOS 3.10.3, GDAL 3.5.3, PROJ 9.0.0; sf_use_s2() is TRUE\n	0295f9ea-4ca6-3301-ac31-bc768bf9254c	最近距离计算	输入矢量数据: /onesis/kt4/test_data/regr/_whhp/whhp.shp; 目标矢量数据: /onesis/kt4/test_data/regr/_whhp/res/r1866049298093965312.shp; 结果数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298156879872.csv; 保留的id变量: OBJECTID; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
866bdeb0b6cb4120929bb92ab3bddedb		2024-12-09 17:18:26.545356	2024-12-09 17:16:37.275204	{"b":"20","r":"/onesis/kt4/test_data/regr/_whhp/res/corr1656.shp","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp","i":"Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds"}	f	\N	04b3ed6d-9a2d-3142-9a70-88bc14549199	地理加权相关性分析	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp; 自变量: Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds; 带宽大小: 20; 结果空间数据: /onesis/kt4/test_data/regr/_whhp/res/corr1656.shp; 	\N	7	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
b62eb43f58d34617940059fc0f88f46e		2024-12-09 17:16:42.868509	2024-12-09 17:16:37.476368	{"a":"lng","b":"lat","r":"/onesis/kt4/test_data/regr/_whhp/res/r1866049298093965312.shp","c":"EPSG:4326","f":"/onesis/kt4/test_data/regr/_whhp/school.csv"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\nSimple feature collection with 80 features and 3 fields\nGeometry type: POINT\nDimension:     XY\nBounding box:  xmin: 114.179 ymin: 30.4531 xmax: 114.45 ymax: 30.6445\nGeodetic CRS:  WGS 84\nFirst 10 features:\n   FID fclass sid                geometry\n1    0 school   1 POINT (114.386 30.4572)\n2    1 school   2 POINT (114.424 30.5197)\n3    2 school   3 POINT (114.409 30.5178)\n4    3 school   4 POINT (114.339 30.5526)\n5    4 school   5 POINT (114.341 30.5522)\n6    5 school   6 POINT (114.338 30.5512)\n7    6 school   7 POINT (114.302 30.6087)\n8    7 school   8 POINT (114.408 30.5179)\n9    8 school   9   POINT (114.36 30.534)\n10   9 school  10  POINT (114.36 30.5343)\n	0a6495c7-e59d-3cd4-94c6-c060e262e98b	点数据csv转换成shp	点数据: /onesis/kt4/test_data/regr/_whhp/school.csv; 经度或x坐标: lng; 纬度或y坐标: lat; 结果矢量: /onesis/kt4/test_data/regr/_whhp/res/r1866049298093965312.shp; 坐标系: EPSG:4326; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
b77fd9f5ad3742a8bf02854e798d53a2		2024-12-09 17:18:11.964009	2024-12-09 17:16:37.410067	{"r":"/onesis/kt4/test_data/regr/_whhp/res/r1866049298307874816.pdf","d":"Avg_HP_","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp","i":"Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds","o":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.3-2.\nLinking to GEOS 3.9.1, GDAL 3.2.3, PROJ 7.2.1; sf_use_s2() is TRUE\nNow calibrating the model: \n Avg_HP_~Avg_Pop \nNow calibrating the model: \n Avg_HP_~Avg_AQI \nNow calibrating the model: \n Avg_HP_~Avg_Gr_ \nNow calibrating the model: \n Avg_HP_~Av_GDP_ \nNow calibrating the model: \n Avg_HP_~Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Av_GDP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_Ln_+Avg_AQI \nThere were 16 warnings (use warnings() to see them)\n	c0486560-a036-3dee-9d57-ca7f3e5dc144	地理加权回归变量优选	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp; 因变量: Avg_HP_; 自变量: Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds; 结果图像: /onesis/kt4/test_data/regr/_whhp/res/r1866049298307874816.pdf; 顺序结果: /onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
8fa0ae2ae72f44749844091258476dd2	e90216d682a74f59915ec2b6fa2f87c5	2024-09-30 19:02:52.082702	2024-09-30 19:02:48.303603	{"sca":"/onesis/kt4/test_data/terr/terr/acc_d8.tif","slope":"/onesis/kt4/test_data/terr/terr/slope_degree.tif","exponent":"1.0","o":"/onesis/kt4/results/10_1_1.tif"}	t	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nfailed to create fsnotify watcher: too many open files	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	梅溪流域-水流功率指数-09301902	集水区指数: 1.0; 输入单位汇水面积 sca 文件: /onesis/kt4/test_data/terr/terr/acc_d8.tif; 输入坡度 slope 文件: /onesis/kt4/test_data/terr/terr/slope_degree.tif; 输出栅格文件: /onesis/kt4/results/10_1_1.tif; 	\N	6	\N
aa894a6dd52e42f9831cc09efb1e7a00		2024-12-09 17:18:27.191851	2024-12-09 17:16:37.127599	{"r":"/onesis/kt4/test_data/regr/_whhp/res/gwr_1209.shp","d":"Avg_HP_","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp","h":"/onesis/kt4/test_data/regr/_whhp/res/gwr_1209.txt","i":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.4-2.\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\nAdaptive bandwidth: 608 CV score: 4931652259 \nAdaptive bandwidth: 384 CV score: 4621822585 \nAdaptive bandwidth: 243 CV score: 4317770528 \nAdaptive bandwidth: 159 CV score: 3999864046 \nAdaptive bandwidth: 103 CV score: 3555264484 \nAdaptive bandwidth: 73 CV score: 3112592636 \nAdaptive bandwidth: 49 CV score: 2677670093 \nAdaptive bandwidth: 40 CV score: 2480203795 \nAdaptive bandwidth: 28 CV score: 2137250825 \nAdaptive bandwidth: 27 CV score: 2102239615 \nAdaptive bandwidth: 20 CV score: 1853862103 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 25 CV score: 2034885238 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 24 CV score: 1996840684 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 21 CV score: 1890399406 \nAdaptive bandwidth: 21 CV score: 1890399406 \nAdaptive bandwidth: 20 CV score: 1853862103 \n   ***********************************************************************\n   *                       Package   GWmodel                             *\n   ***********************************************************************\n   Program starts at: 2024-12-09 09:18:23 \n   Call:\n   gwr.basic(formula = gwrformula, data = spdata, bw = bw, kernel = kernel, \n    adaptive = adaptive, parallel.method = "omp")\n\n   Dependent (y) variable:  Avg_HP_\n   Independent variables:  nrst_ds Avg_Gr_ Av_GDP_\n   Number of data points: 973\n   ***********************************************************************\n   *                    Results of Global Regression                     *\n   ***********************************************************************\n\n   Call:\n    lm(formula = formula, data = data)\n\n   Residuals:\n    Min      1Q  Median      3Q     Max \n-7060.0 -1462.6   -49.1  1402.0  8474.4 \n\n   Coefficients:\n                 Estimate Std. Error t value Pr(>|t|)    \n   (Intercept)  1.527e+04  1.610e+02  94.793  < 2e-16 ***\n   nrst_ds     -1.025e+00  4.449e-02 -23.036  < 2e-16 ***\n   Avg_Gr_      2.898e+03  6.784e+02   4.272 2.12e-05 ***\n   Av_GDP_      2.672e-01  7.199e-02   3.711 0.000218 ***\n\n   ---Significance stars\n   Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 \n   Residual standard error: 2375 on 969 degrees of freedom\n   Multiple R-squared: 0.3857\n   Adjusted R-squared: 0.3838 \n   F-statistic: 202.8 on 3 and 969 DF,  p-value: < 2.2e-16 \n   ***Extra Diagnostic information\n   Residual sum of squares: 5464608038\n   Sigma(hat): 2372.302\n   AIC:  17892.82\n   AICc:  17892.88\n   BIC:  16978.62\n   ***********************************************************************\n   *          Results of Geographically Weighted Regression              *\n   ***********************************************************************\n\n   *********************Model calibration information*********************\n   Kernel function: gaussian \n   Adaptive bandwidth: 20 (number of nearest neighbours)\n   Regression points: the same locations as observations are used.\n   Distance metric: Euclidean distance metric is used.\n\n   ****************Summary of GWR coefficient estimates:******************\n                    Min.     1st Qu.      Median     3rd Qu.       Max.\n   Intercept  1.0674e+04  1.3557e+04  1.5206e+04  1.6345e+04 21833.2078\n   nrst_ds   -3.0572e+00 -8.8351e-01 -4.6088e-01  4.2278e-03     1.4104\n   Avg_Gr_   -3.2202e+03  3.1662e+02  1.8977e+03  3.5756e+03 10513.6440\n   Av_GDP_   -2.2696e+00 -2.3138e-01  4.0109e-02  2.7502e-01     1.3326\n   ************************Diagnostic information*************************\n   Number of data points: 973 \n   Effective number of parameters (2trace(S) - trace(S'S)): 121.6069 \n   Effective degrees of freedom (n-2trace(S) + trace(S'S)): 851.3931 \n   AICc (GWR book, Fotheringham, et al. 2002, p. 61, eq 2.33): 16846.29 \n   AIC (GWR book, Fotheringham, et al. 2002,GWR p. 96, eq. 4.22): 16739.18 \n   BIC (GWR book, Fotheringham, et al. 2002,GWR p. 61, eq. 2.34): 16279.37 \n   Residual sum of squares: 1542237099 \n   R-square value:  0.8266273 \n   Adjusted R-square value:  0.8018349 \n\n   ***********************************************************************\n   Program stops at: 2024-12-09 09:18:23 \nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	7bc9fe36-321c-3222-a938-32033f92aa03	地理加权回归(txt输入自变量)	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp; txt变量顺序: /onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt; 因变量: Avg_HP_; 结果空间数据: /onesis/kt4/test_data/regr/_whhp/res/gwr_1209.shp; 模型诊断信息: /onesis/kt4/test_data/regr/_whhp/res/gwr_1209.txt; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
ee42b2ab18fc492da82dd9b97b12db89		2024-12-09 17:26:19.050117	2024-12-09 17:25:25.301469	{"epsg":"0","file":"/onesis/kt4/job_results/neardist12091725.csv"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTraceback (most recent call last):\n  File "/project/project.py", line 197, in <module>\n    project(args.file)\n  File "/project/project.py", line 15, in project\n    new_epsg = detect_epsg_from_csv(filepath)\n               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File "/project/project.py", line 40, in detect_epsg_from_csv\n    with open(filepath, 'r') as csvfile:\n         ^^^^^^^^^^^^^^^^^^^\nFileNotFoundError: [Errno 2] No such file or directory: '/data/onesis/kt4/job_results/neardist12091725.csv'\n	84641a52-bd00-3734-9c49-597a3f5d2e73	reproject:1b62d9d8220c4741b39a55b950ac16d7	数据路径: /onesis/kt4/job_results/neardist12091725.csv; EPSG号: 0; 	\N	7	\N
963aa025ed2b447590f13b711e5918d4		2024-12-09 17:26:53.066914	2024-12-09 17:26:48.708171	{"epsg":"0","file":"/onesis/kt4/job_results/joined_12091726.shp"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\n/data/onesis/kt4/job_results/joined_12091726.shp is in WGS84 or based on WGS84.\nProject done.\n	84641a52-bd00-3734-9c49-597a3f5d2e73	reproject:7d6064cc4aeb476da8637a2ff389720b	数据路径: /onesis/kt4/job_results/joined_12091726.shp; EPSG号: 0; 	\N	6	\N
c8d6ae49dfa44fd2808cefa9a48715c0		2024-12-09 17:35:08.350942	2024-12-09 17:35:01.708587	{"a":"lng","b":"lat","r":"/onesis/kt4/test_data/regr/_whhp/res/r1866053930014867456.shp","c":"EPSG:4326","f":"/onesis/kt4/test_data/regr/_whhp/school.csv"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\nSimple feature collection with 80 features and 3 fields\nGeometry type: POINT\nDimension:     XY\nBounding box:  xmin: 114.179 ymin: 30.4531 xmax: 114.45 ymax: 30.6445\nGeodetic CRS:  WGS 84\nFirst 10 features:\n   FID fclass sid                geometry\n1    0 school   1 POINT (114.386 30.4572)\n2    1 school   2 POINT (114.424 30.5197)\n3    2 school   3 POINT (114.409 30.5178)\n4    3 school   4 POINT (114.339 30.5526)\n5    4 school   5 POINT (114.341 30.5522)\n6    5 school   6 POINT (114.338 30.5512)\n7    6 school   7 POINT (114.302 30.6087)\n8    7 school   8 POINT (114.408 30.5179)\n9    8 school   9   POINT (114.36 30.534)\n10   9 school  10  POINT (114.36 30.5343)\n	0a6495c7-e59d-3cd4-94c6-c060e262e98b	点数据csv转换成shp	点数据: /onesis/kt4/test_data/regr/_whhp/school.csv; 经度或x坐标: lng; 纬度或y坐标: lat; 结果矢量: /onesis/kt4/test_data/regr/_whhp/res/r1866053930014867456.shp; 坐标系: EPSG:4326; 	\N	6	74b2e657-daf3-4e0d-b5dd-725dfe6afcd6
1efcad6132884bb79bd951e94038bd62		2024-12-09 17:38:15.729862	2024-12-09 17:35:01.500759	{"b":"20","r":"/onesis/kt4/test_data/regr/_whhp/res/corr1656.shp","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp","i":"Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.4-2.\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	04b3ed6d-9a2d-3142-9a70-88bc14549199	地理加权相关性分析	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp; 自变量: Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds; 带宽大小: 20; 结果空间数据: /onesis/kt4/test_data/regr/_whhp/res/corr1656.shp; 	\N	6	74b2e657-daf3-4e0d-b5dd-725dfe6afcd6
a25df0e5ae5148388f9adf3ee6fd3f5d		2024-12-09 17:36:23.085716	2024-12-09 17:35:01.546468	{"d":"/onesis/kt4/test_data/regr/_whhp/whhp.shp","t":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930098753536.csv","i":"OBJECTID","j":"id","o":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nLinking to GEOS 3.10.3, GDAL 3.5.3, PROJ 9.0.0; sf_use_s2() is TRUE\n\nAttaching package: ‘dplyr’\n\nThe following objects are masked from ‘package:stats’:\n\n    filter, lag\n\nThe following objects are masked from ‘package:base’:\n\n    intersect, setdiff, setequal, union\n\nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	96a25d86-5c91-3a5a-b9e8-9b88894afe55	数据连接	输入矢量数据: /onesis/kt4/test_data/regr/_whhp/whhp.shp; 目标数据: /onesis/kt4/test_data/regr/_whhp/res/o1866053930098753536.csv; 连接字段: OBJECTID; 对应字段: id; 结果数据: /onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp; 	\N	6	74b2e657-daf3-4e0d-b5dd-725dfe6afcd6
dc9cc0114ad74c5da3dae22edc327a0e		2024-12-09 17:44:29.805364	2024-12-09 17:35:01.593303	{"r":"/onesis/kt4/test_data/regr/_whhp/res/r1866053930266525696.pdf","d":"Avg_HP_","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp","i":"Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds","o":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930266525696.txt"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.3-2.\nLinking to GEOS 3.9.1, GDAL 3.2.3, PROJ 7.2.1; sf_use_s2() is TRUE\nNow calibrating the model: \n Avg_HP_~Avg_Pop \nNow calibrating the model: \n Avg_HP_~Avg_AQI \nNow calibrating the model: \n Avg_HP_~Avg_Gr_ \nNow calibrating the model: \n Avg_HP_~Av_GDP_ \nNow calibrating the model: \n Avg_HP_~Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Av_GDP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_AQI \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_Ln_ \nNow calibrating the model: \n Avg_HP_~nrst_ds+Avg_Gr_+Av_GDP_+Avg_Pop+Avg_HP_+Avg_Ln_+Avg_AQI \nThere were 16 warnings (use warnings() to see them)\n	c0486560-a036-3dee-9d57-ca7f3e5dc144	地理加权回归变量优选	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp; 因变量: Avg_HP_; 自变量: Avg_Pop,Avg_AQI,Avg_Gr_,Av_GDP_,Avg_Ln_,Avg_HP_,nrst_ds; 结果图像: /onesis/kt4/test_data/regr/_whhp/res/r1866053930266525696.pdf; 顺序结果: /onesis/kt4/test_data/regr/_whhp/res/o1866053930266525696.txt; 	\N	6	74b2e657-daf3-4e0d-b5dd-725dfe6afcd6
0befaab0552c484087d6899063aa8399		\N	2025-01-05 20:05:44.322885	{"sca":"/onesis/kt4/xuancheng/result/ad81875876330583752704.tif","slope":"/onesis/kt4/xuancheng/result/sd81875876331124817920.tif","exponent":"1.0","o":"/onesis/kt4/xuancheng/result/o1875876331217092608.tif"}	f	\N	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	集水区指数: 1.0; 输入单位汇水面积 sca 文件: /onesis/kt4/xuancheng/result/ad81875876330583752704.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875876331217092608.tif; 输入坡度 slope 文件: /onesis/kt4/xuancheng/result/sd81875876331124817920.tif; 	\N	0	2cf6be48-1562-40b9-a416-ef2ce4ac609f
04f0b04d827c4d53ac9ca950c79cbe81		2024-12-10 04:11:46.207427	2024-12-09 17:16:37.248662	{"r":"/onesis/kt4/test_data/regr/_whhp/res/mgwr_1209.shp","d":"Avg_HP_","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp","h":"/onesis/kt4/test_data/regr/_whhp/res/mgwr_1209.txt","i":"/onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.4-2.\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\n------ Calculate the initial bandwidths for each independent variable ------\nNow select an optimum bandwidth for the model:  Avg_HP_~1 \n[1] "bws0[i]<-bw.gwr(Avg_HP_~1,data=regression.points,kernel=kernel,approach=approach,adaptive=adaptive,dMat=dMats[[var.dMat.indx[i]]], parallel.method=parallel.method,parallel.arg=parallel.arg)"\nAdaptive bandwidth (number of nearest neighbours): 608 AICc value: 18299.55 \nAdaptive bandwidth (number of nearest neighbours): 384 AICc value: 18260.68 \nAdaptive bandwidth (number of nearest neighbours): 243 AICc value: 18209.78 \nAdaptive bandwidth (number of nearest neighbours): 159 AICc value: 18139.43 \nAdaptive bandwidth (number of nearest neighbours): 103 AICc value: 18016.53 \nAdaptive bandwidth (number of nearest neighbours): 73 AICc value: 17891.42 \nAdaptive bandwidth (number of nearest neighbours): 49 AICc value: 17718.69 \nAdaptive bandwidth (number of nearest neighbours): 40 AICc value: 17574.95 \nAdaptive bandwidth (number of nearest neighbours): 28 AICc value: 17263.57 \nAdaptive bandwidth (number of nearest neighbours): 27 AICc value: 17236.96 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17056.31 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17112.86 \nAdaptive bandwidth (number of nearest neighbours): 25 AICc value: 17186.07 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17138.03 \nAdaptive bandwidth (number of nearest neighbours): 24 AICc value: 17162.1 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17138.03 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17138.03 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17112.86 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17112.86 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17083.57 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17083.57 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17056.31 \nNow select an optimum bandwidth for the model:  Avg_HP_~nrst_ds \n[1] "bws0[i]<-bw.gwr(Avg_HP_~nrst_ds,data=regression.points,kernel=kernel,approach=approach,adaptive=adaptive,dMat=dMats[[var.dMat.indx[i]]], parallel.method=parallel.method,parallel.arg=parallel.arg)"\nAdaptive bandwidth (number of nearest neighbours): 608 AICc value: 17810.04 \nAdaptive bandwidth (number of nearest neighbours): 384 AICc value: 17750.68 \nAdaptive bandwidth (number of nearest neighbours): 243 AICc value: 17692.35 \nAdaptive bandwidth (number of nearest neighbours): 159 AICc value: 17626.43 \nAdaptive bandwidth (number of nearest neighbours): 103 AICc value: 17515.19 \nAdaptive bandwidth (number of nearest neighbours): 73 AICc value: 17363.8 \nAdaptive bandwidth (number of nearest neighbours): 49 AICc value: 17189.96 \nAdaptive bandwidth (number of nearest neighbours): 40 AICc value: 17108.97 \nAdaptive bandwidth (number of nearest neighbours): 28 AICc value: 16958.06 \nAdaptive bandwidth (number of nearest neighbours): 27 AICc value: 16941.56 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 16812.46 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 16854.6 \nAdaptive bandwidth (number of nearest neighbours): 25 AICc value: 16908.88 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 16872.68 \nAdaptive bandwidth (number of nearest neighbours): 24 AICc value: 16888.9 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 16872.68 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 16872.68 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 16854.6 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 16854.6 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 16832.33 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 16832.33 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 16812.46 \nNow select an optimum bandwidth for the model:  Avg_HP_~Avg_Gr_ \n[1] "bws0[i]<-bw.gwr(Avg_HP_~Avg_Gr_,data=regression.points,kernel=kernel,approach=approach,adaptive=adaptive,dMat=dMats[[var.dMat.indx[i]]], parallel.method=parallel.method,parallel.arg=parallel.arg)"\nAdaptive bandwidth (number of nearest neighbours): 608 AICc value: 18288.38 \nAdaptive bandwidth (number of nearest neighbours): 384 AICc value: 18250.24 \nAdaptive bandwidth (number of nearest neighbours): 243 AICc value: 18201.17 \nAdaptive bandwidth (number of nearest neighbours): 159 AICc value: 18132.91 \nAdaptive bandwidth (number of nearest neighbours): 103 AICc value: 18008.87 \nAdaptive bandwidth (number of nearest neighbours): 73 AICc value: 17884.83 \nAdaptive bandwidth (number of nearest neighbours): 49 AICc value: 17714.94 \nAdaptive bandwidth (number of nearest neighbours): 40 AICc value: 17572.88 \nAdaptive bandwidth (number of nearest neighbours): 28 AICc value: 17268.76 \nAdaptive bandwidth (number of nearest neighbours): 27 AICc value: 17242.3 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17076.92 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17129.74 \nAdaptive bandwidth (number of nearest neighbours): 25 AICc value: 17195.41 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17151.63 \nAdaptive bandwidth (number of nearest neighbours): 24 AICc value: 17173.62 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17151.63 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17151.63 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17129.74 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17129.74 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17102.67 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17102.67 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17076.92 \nNow select an optimum bandwidth for the model:  Avg_HP_~Av_GDP_ \n[1] "bws0[i]<-bw.gwr(Avg_HP_~Av_GDP_,data=regression.points,kernel=kernel,approach=approach,adaptive=adaptive,dMat=dMats[[var.dMat.indx[i]]], parallel.method=parallel.method,parallel.arg=parallel.arg)"\nAdaptive bandwidth (number of nearest neighbours): 608 AICc value: 18259.82 \nAdaptive bandwidth (number of nearest neighbours): 384 AICc value: 18214.62 \nAdaptive bandwidth (number of nearest neighbours): 243 AICc value: 18153.52 \nAdaptive bandwidth (number of nearest neighbours): 159 AICc value: 18074.02 \nAdaptive bandwidth (number of nearest neighbours): 103 AICc value: 17949.8 \nAdaptive bandwidth (number of nearest neighbours): 73 AICc value: 17837.02 \nAdaptive bandwidth (number of nearest neighbours): 49 AICc value: 17680.15 \nAdaptive bandwidth (number of nearest neighbours): 40 AICc value: 17550.1 \nAdaptive bandwidth (number of nearest neighbours): 28 AICc value: 17262.7 \nAdaptive bandwidth (number of nearest neighbours): 27 AICc value: 17236.42 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17066.01 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17120.28 \nAdaptive bandwidth (number of nearest neighbours): 25 AICc value: 17188.14 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17143.37 \nAdaptive bandwidth (number of nearest neighbours): 24 AICc value: 17165.78 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17143.37 \nAdaptive bandwidth (number of nearest neighbours): 23 AICc value: 17143.37 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17120.28 \nAdaptive bandwidth (number of nearest neighbours): 22 AICc value: 17120.28 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17092.01 \nAdaptive bandwidth (number of nearest neighbours): 21 AICc value: 17092.01 \nAdaptive bandwidth (number of nearest neighbours): 20 AICc value: 17066.01 \n------            The end for the initial selections              ------\nCalculate the initial beta0 from the above bandwidths.\nEnd of calculating the inital beta0.\nFind the optimum bandwidths for each independent variable.\n\tIteration 1\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 20 and the difference in bandwidths is: 12\nThe bandwidth for variable Intercept will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 20 and the difference in bandwidths is: 12\nThe bandwidth for variable nrst_ds will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 545\nThe bandwidth used in the last iteration is: 20 and the difference in bandwidths is: 525\nThe bandwidth for variable Avg_Gr_ will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 8\nThe bandwidth used in the last iteration is: 20 and the difference in bandwidths is: 12\nThe bandwidth for variable Av_GDP_ will be continually selected in the next iteration.\nIteration 1 change of RSS (dCVR) is 0.227236.\n\tIteration 2\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable Intercept seems to be converged for 1 times. It will be continually optimized in the next 4 times\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable nrst_ds seems to be converged for 1 times. It will be continually optimized in the next 4 times\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 81\nThe bandwidth used in the last iteration is: 545 and the difference in bandwidths is: 464\nThe bandwidth for variable Avg_Gr_ will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 2\nThe bandwidth for variable Av_GDP_ will be continually selected in the next iteration.\nIteration 2 change of RSS (dCVR) is 0.130641.\n\tIteration 3\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable Intercept seems to be converged for 2 times. It will be continually optimized in the next 3 times\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable nrst_ds seems to be converged for 2 times. It will be continually optimized in the next 3 times\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 69\nThe bandwidth used in the last iteration is: 81 and the difference in bandwidths is: 12\nThe bandwidth for variable Avg_Gr_ will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 10 and the difference in bandwidths is: 0\nThe bandwidth for variable Av_GDP_ seems to be converged for 1 times. It will be continually optimized in the next 4 times\nIteration 3 change of RSS (dCVR) is 0.0698372.\n\tIteration 4\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable Intercept seems to be converged for 3 times. It will be continually optimized in the next 2 times\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable nrst_ds seems to be converged for 3 times. It will be continually optimized in the next 2 times\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 69\nThe bandwidth used in the last iteration is: 69 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 1 times. It will be continually optimized in the next 4 times\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 10 and the difference in bandwidths is: 0\nThe bandwidth for variable Av_GDP_ seems to be converged for 2 times. It will be continually optimized in the next 3 times\nIteration 4 change of RSS (dCVR) is 0.0830211.\n\tIteration 5\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable Intercept seems to be converged for 4 times. It will be continually optimized in the next 1 times\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable nrst_ds seems to be converged for 4 times. It will be continually optimized in the next 1 times\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 69\nThe bandwidth used in the last iteration is: 69 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 2 times. It will be continually optimized in the next 3 times\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 10 and the difference in bandwidths is: 0\nThe bandwidth for variable Av_GDP_ seems to be converged for 3 times. It will be continually optimized in the next 2 times\nIteration 5 change of RSS (dCVR) is 0.0585722.\n\tIteration 6\nNow select an optimum bandwidth for the variable: Intercept\nThe newly selected bandwidth for variable: Intercept is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable Intercept seems to be converged and will be kept the same in the following iterations.\nNow select an optimum bandwidth for the variable: nrst_ds\nThe newly selected bandwidth for variable: nrst_ds is 8\nThe bandwidth used in the last iteration is: 8 and the difference in bandwidths is: 0\nThe bandwidth for variable nrst_ds seems to be converged and will be kept the same in the following iterations.\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 69\nThe bandwidth used in the last iteration is: 69 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 3 times. It will be continually optimized in the next 2 times\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 10 and the difference in bandwidths is: 0\nThe bandwidth for variable Av_GDP_ seems to be converged for 4 times. It will be continually optimized in the next 1 times\nIteration 6 change of RSS (dCVR) is 0.0420334.\n\tIteration 7\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 69 and the difference in bandwidths is: 6\nThe bandwidth for variable Avg_Gr_ will be continually selected in the next iteration.\nNow select an optimum bandwidth for the variable: Av_GDP_\nThe newly selected bandwidth for variable: Av_GDP_ is 10\nThe bandwidth used in the last iteration is: 10 and the difference in bandwidths is: 0\nThe bandwidth for variable Av_GDP_ seems to be converged and will be kept the same in the following iterations.\nIteration 7 change of RSS (dCVR) is 0.0129626.\n\tIteration 8\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 63 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 1 times. It will be continually optimized in the next 4 times\nIteration 8 change of RSS (dCVR) is 0.0288156.\n\tIteration 9\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 63 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 2 times. It will be continually optimized in the next 3 times\nIteration 9 change of RSS (dCVR) is 0.0157794.\n\tIteration 10\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 63 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 3 times. It will be continually optimized in the next 2 times\nIteration 10 change of RSS (dCVR) is 0.00166599.\n\tIteration 11\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 63 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged for 4 times. It will be continually optimized in the next 1 times\nIteration 11 change of RSS (dCVR) is 0.0108984.\n\tIteration 12\nNow select an optimum bandwidth for the variable: Avg_Gr_\nThe newly selected bandwidth for variable: Avg_Gr_ is 63\nThe bandwidth used in the last iteration is: 63 and the difference in bandwidths is: 0\nThe bandwidth for variable Avg_Gr_ seems to be converged and will be kept the same in the following iterations.\nIteration 12 change of RSS (dCVR) is 0.0134445.\n\tIteration 13\nIteration 13 change of RSS (dCVR) is 0.0145317.\n\tIteration 14\nIteration 14 change of RSS (dCVR) is 0.0149677.\n\tIteration 15\nIteration 15 change of RSS (dCVR) is 0.0150649.\n\tIteration 16\nIteration 16 change of RSS (dCVR) is 0.0149756.\n\tIteration 17\nIteration 17 change of RSS (dCVR) is 0.0147825.\n\tIteration 18\nIteration 18 change of RSS (dCVR) is 0.0145329.\n\tIteration 19\nIteration 19 change of RSS (dCVR) is 0.0142544.\n\tIteration 20\nIteration 20 change of RSS (dCVR) is 0.013963.\n\tIteration 21\nIteration 21 change of RSS (dCVR) is 0.0136678.\n\tIteration 22\nIteration 22 change of RSS (dCVR) is 0.0133738.\n\tIteration 23\nIteration 23 change of RSS (dCVR) is 0.0130836.\n\tIteration 24\nIteration 24 change of RSS (dCVR) is 0.0127986.\n\tIteration 25\nIteration 25 change of RSS (dCVR) is 0.012519.\n\tIteration 26\nIteration 26 change of RSS (dCVR) is 0.0122449.\n\tIteration 27\nIteration 27 change of RSS (dCVR) is 0.0119762.\n\tIteration 28\nIteration 28 change of RSS (dCVR) is 0.0117125.\n\tIteration 29\nIteration 29 change of RSS (dCVR) is 0.0114537.\n\tIteration 30\nIteration 30 change of RSS (dCVR) is 0.0111995.\n\tIteration 31\nIteration 31 change of RSS (dCVR) is 0.0109496.\n\tIteration 32\nIteration 32 change of RSS (dCVR) is 0.0107041.\n\tIteration 33\nIteration 33 change of RSS (dCVR) is 0.0104627.\n\tIteration 34\nIteration 34 change of RSS (dCVR) is 0.0102254.\n\tIteration 35\nIteration 35 change of RSS (dCVR) is 0.00999205.\n\tIteration 36\nIteration 36 change of RSS (dCVR) is 0.00976268.\n\tIteration 37\nIteration 37 change of RSS (dCVR) is 0.00953724.\n\tIteration 38\nIteration 38 change of RSS (dCVR) is 0.0093157.\n\tIteration 39\nIteration 39 change of RSS (dCVR) is 0.00909803.\n\tIteration 40\nIteration 40 change of RSS (dCVR) is 0.00888422.\n\tIteration 41\nIteration 41 change of RSS (dCVR) is 0.00867424.\n\tIteration 42\nIteration 42 change of RSS (dCVR) is 0.00846807.\n\tIteration 43\nIteration 43 change of RSS (dCVR) is 0.00826568.\n\tIteration 44\nIteration 44 change of RSS (dCVR) is 0.00806705.\n\tIteration 45\nIteration 45 change of RSS (dCVR) is 0.00787216.\n\tIteration 46\nIteration 46 change of RSS (dCVR) is 0.00768095.\n\tIteration 47\nIteration 47 change of RSS (dCVR) is 0.00749341.\n\tIteration 48\nIteration 48 change of RSS (dCVR) is 0.00730949.\n\tIteration 49\nIteration 49 change of RSS (dCVR) is 0.00712914.\n\tIteration 50\nIteration 50 change of RSS (dCVR) is 0.00695234.\n\tIteration 51\nIteration 51 change of RSS (dCVR) is 0.00677903.\n\tIteration 52\nIteration 52 change of RSS (dCVR) is 0.00660916.\n\tIteration 53\nIteration 53 change of RSS (dCVR) is 0.00644269.\n\tIteration 54\nIteration 54 change of RSS (dCVR) is 0.00627957.\n\tIteration 55\nIteration 55 change of RSS (dCVR) is 0.00611974.\n\tIteration 56\nIteration 56 change of RSS (dCVR) is 0.00596316.\n\tIteration 57\nIteration 57 change of RSS (dCVR) is 0.00580977.\n\tIteration 58\nIteration 58 change of RSS (dCVR) is 0.00565952.\n\tIteration 59\nIteration 59 change of RSS (dCVR) is 0.00551235.\n\tIteration 60\nIteration 60 change of RSS (dCVR) is 0.00536821.\n\tIteration 61\nIteration 61 change of RSS (dCVR) is 0.00522705.\n\tIteration 62\nIteration 62 change of RSS (dCVR) is 0.00508881.\n\tIteration 63\nIteration 63 change of RSS (dCVR) is 0.00495343.\n\tIteration 64\nIteration 64 change of RSS (dCVR) is 0.00482086.\n\tIteration 65\nIteration 65 change of RSS (dCVR) is 0.00469105.\n\tIteration 66\nIteration 66 change of RSS (dCVR) is 0.00456393.\n\tIteration 67\nIteration 67 change of RSS (dCVR) is 0.00443946.\n\tIteration 68\nIteration 68 change of RSS (dCVR) is 0.00431758.\n\tIteration 69\nIteration 69 change of RSS (dCVR) is 0.00419824.\n\tIteration 70\nIteration 70 change of RSS (dCVR) is 0.00408138.\n\tIteration 71\nIteration 71 change of RSS (dCVR) is 0.00396694.\n\tIteration 72\nIteration 72 change of RSS (dCVR) is 0.00385488.\n\tIteration 73\nIteration 73 change of RSS (dCVR) is 0.00374515.\n\tIteration 74\nIteration 74 change of RSS (dCVR) is 0.00363768.\n\tIteration 75\nIteration 75 change of RSS (dCVR) is 0.00353242.\n\tIteration 76\nIteration 76 change of RSS (dCVR) is 0.00342934.\n\tIteration 77\nIteration 77 change of RSS (dCVR) is 0.00332836.\n\tIteration 78\nIteration 78 change of RSS (dCVR) is 0.00322945.\n\tIteration 79\nIteration 79 change of RSS (dCVR) is 0.00313254.\n\tIteration 80\nIteration 80 change of RSS (dCVR) is 0.0030376.\n\tIteration 81\nIteration 81 change of RSS (dCVR) is 0.00294456.\n\tIteration 82\nIteration 82 change of RSS (dCVR) is 0.00285339.\n\tIteration 83\nIteration 83 change of RSS (dCVR) is 0.00276402.\n\tIteration 84\nIteration 84 change of RSS (dCVR) is 0.00267642.\n\tIteration 85\nIteration 85 change of RSS (dCVR) is 0.00259052.\n\tIteration 86\nIteration 86 change of RSS (dCVR) is 0.00250628.\n\tIteration 87\nIteration 87 change of RSS (dCVR) is 0.00242365.\n\tIteration 88\nIteration 88 change of RSS (dCVR) is 0.00234258.\n\tIteration 89\nIteration 89 change of RSS (dCVR) is 0.00226302.\n\tIteration 90\nIteration 90 change of RSS (dCVR) is 0.00218492.\n\tIteration 91\nIteration 91 change of RSS (dCVR) is 0.00210823.\n\tIteration 92\nIteration 92 change of RSS (dCVR) is 0.00203288.\n\tIteration 93\nIteration 93 change of RSS (dCVR) is 0.00195884.\n\tIteration 94\nIteration 94 change of RSS (dCVR) is 0.00188605.\n\tIteration 95\nIteration 95 change of RSS (dCVR) is 0.00181444.\n\tIteration 96\nIteration 96 change of RSS (dCVR) is 0.00174396.\n\tIteration 97\nIteration 97 change of RSS (dCVR) is 0.00167455.\n\tIteration 98\nIteration 98 change of RSS (dCVR) is 0.00160614.\n\tIteration 99\nIteration 99 change of RSS (dCVR) is 0.00153867.\n\tIteration 100\nIteration 100 change of RSS (dCVR) is 0.00147207.\n\tIteration 101\nIteration 101 change of RSS (dCVR) is 0.00140625.\n\tIteration 102\nIteration 102 change of RSS (dCVR) is 0.00134112.\n\tIteration 103\nIteration 103 change of RSS (dCVR) is 0.0012766.\n\tIteration 104\nIteration 104 change of RSS (dCVR) is 0.00121258.\n\tIteration 105\nIteration 105 change of RSS (dCVR) is 0.00114893.\n\tIteration 106\nIteration 106 change of RSS (dCVR) is 0.00108552.\n\tIteration 107\nIteration 107 change of RSS (dCVR) is 0.00102219.\n\tIteration 108\nIteration 108 change of RSS (dCVR) is 0.000958721.\n\tIteration 109\nIteration 109 change of RSS (dCVR) is 0.000894887.\n\tIteration 110\nIteration 110 change of RSS (dCVR) is 0.000830376.\n\tIteration 111\nIteration 111 change of RSS (dCVR) is 0.000764786.\n\tIteration 112\nIteration 112 change of RSS (dCVR) is 0.000697573.\n\tIteration 113\nIteration 113 change of RSS (dCVR) is 0.000627961.\n\tIteration 114\nIteration 114 change of RSS (dCVR) is 0.000554773.\n\tIteration 115\nIteration 115 change of RSS (dCVR) is 0.000476059.\n\tIteration 116\nIteration 116 change of RSS (dCVR) is 0.000388119.\n\tIteration 117\nIteration 117 change of RSS (dCVR) is 0.000281994.\n\tIteration 118\nIteration 118 change of RSS (dCVR) is 0.000114165.\n\tIteration 119\nIteration 119 change of RSS (dCVR) is 0.000221502.\n\tIteration 120\nIteration 120 change of RSS (dCVR) is 0.000327105.\n\tIteration 121\nIteration 121 change of RSS (dCVR) is 0.000401232.\n\tIteration 122\nIteration 122 change of RSS (dCVR) is 0.000459607.\n\tIteration 123\nIteration 123 change of RSS (dCVR) is 0.000507886.\n\tIteration 124\nIteration 124 change of RSS (dCVR) is 0.000548912.\n\tIteration 125\nIteration 125 change of RSS (dCVR) is 0.000584366.\n\tIteration 126\nIteration 126 change of RSS (dCVR) is 0.000615352.\n\tIteration 127\nIteration 127 change of RSS (dCVR) is 0.000642641.\n\tIteration 128\nIteration 128 change of RSS (dCVR) is 0.000666802.\n\tIteration 129\nIteration 129 change of RSS (dCVR) is 0.000688273.\n\tIteration 130\nIteration 130 change of RSS (dCVR) is 0.000707395.\n\tIteration 131\nIteration 131 change of RSS (dCVR) is 0.000724447.\n\tIteration 132\nIteration 132 change of RSS (dCVR) is 0.000739656.\n\tIteration 133\nIteration 133 change of RSS (dCVR) is 0.000753215.\n\tIteration 134\nIteration 134 change of RSS (dCVR) is 0.000765284.\n\tIteration 135\nIteration 135 change of RSS (dCVR) is 0.000776004.\n\tIteration 136\nIteration 136 change of RSS (dCVR) is 0.000785495.\n\tIteration 137\nIteration 137 change of RSS (dCVR) is 0.000793862.\n\tIteration 138\nIteration 138 change of RSS (dCVR) is 0.000801199.\n\tIteration 139\nIteration 139 change of RSS (dCVR) is 0.00080759.\n\tIteration 140\nIteration 140 change of RSS (dCVR) is 0.000813106.\n\tIteration 141\nIteration 141 change of RSS (dCVR) is 0.000817816.\n\tIteration 142\nIteration 142 change of RSS (dCVR) is 0.000821779.\n\tIteration 143\nIteration 143 change of RSS (dCVR) is 0.000825049.\n\tIteration 144\nIteration 144 change of RSS (dCVR) is 0.000827675.\n\tIteration 145\nIteration 145 change of RSS (dCVR) is 0.000829704.\n\tIteration 146\nIteration 146 change of RSS (dCVR) is 0.000831176.\n\tIteration 147\nIteration 147 change of RSS (dCVR) is 0.000832129.\n\tIteration 148\nIteration 148 change of RSS (dCVR) is 0.000832598.\n\tIteration 149\nIteration 149 change of RSS (dCVR) is 0.000832616.\n\tIteration 150\nIteration 150 change of RSS (dCVR) is 0.000832212.\n\tIteration 151\nIteration 151 change of RSS (dCVR) is 0.000831415.\n\tIteration 152\nIteration 152 change of RSS (dCVR) is 0.00083025.\n\tIteration 153\nIteration 153 change of RSS (dCVR) is 0.00082874.\n\tIteration 154\nIteration 154 change of RSS (dCVR) is 0.00082691.\n\tIteration 155\nIteration 155 change of RSS (dCVR) is 0.000824778.\n\tIteration 156\nIteration 156 change of RSS (dCVR) is 0.000822365.\n\tIteration 157\nIteration 157 change of RSS (dCVR) is 0.00081969.\n\tIteration 158\nIteration 158 change of RSS (dCVR) is 0.000816769.\n\tIteration 159\nIteration 159 change of RSS (dCVR) is 0.000813618.\n\tIteration 160\nIteration 160 change of RSS (dCVR) is 0.000810252.\n\tIteration 161\nIteration 161 change of RSS (dCVR) is 0.000806687.\n\tIteration 162\nIteration 162 change of RSS (dCVR) is 0.000802934.\n\tIteration 163\nIteration 163 change of RSS (dCVR) is 0.000799007.\n\tIteration 164\nIteration 164 change of RSS (dCVR) is 0.000794917.\n\tIteration 165\nIteration 165 change of RSS (dCVR) is 0.000790676.\n\tIteration 166\nIteration 166 change of RSS (dCVR) is 0.000786294.\n\tIteration 167\nIteration 167 change of RSS (dCVR) is 0.000781781.\n\tIteration 168\nIteration 168 change of RSS (dCVR) is 0.000777147.\n\tIteration 169\nIteration 169 change of RSS (dCVR) is 0.0007724.\n\tIteration 170\nIteration 170 change of RSS (dCVR) is 0.00076755.\n\tIteration 171\nIteration 171 change of RSS (dCVR) is 0.000762602.\n\tIteration 172\nIteration 172 change of RSS (dCVR) is 0.000757566.\n\tIteration 173\nIteration 173 change of RSS (dCVR) is 0.000752449.\n\tIteration 174\nIteration 174 change of RSS (dCVR) is 0.000747257.\n\tIteration 175\nIteration 175 change of RSS (dCVR) is 0.000741996.\n\tIteration 176\nIteration 176 change of RSS (dCVR) is 0.000736672.\n\tIteration 177\nIteration 177 change of RSS (dCVR) is 0.000731292.\n\tIteration 178\nIteration 178 change of RSS (dCVR) is 0.000725861.\n\tIteration 179\nIteration 179 change of RSS (dCVR) is 0.000720384.\n\tIteration 180\nIteration 180 change of RSS (dCVR) is 0.000714865.\n\tIteration 181\nIteration 181 change of RSS (dCVR) is 0.00070931.\n\tIteration 182\nIteration 182 change of RSS (dCVR) is 0.000703722.\n\tIteration 183\nIteration 183 change of RSS (dCVR) is 0.000698107.\n\tIteration 184\nIteration 184 change of RSS (dCVR) is 0.000692467.\n\tIteration 185\nIteration 185 change of RSS (dCVR) is 0.000686807.\n\tIteration 186\nIteration 186 change of RSS (dCVR) is 0.00068113.\n\tIteration 187\nIteration 187 change of RSS (dCVR) is 0.00067544.\n\tIteration 188\nIteration 188 change of RSS (dCVR) is 0.000669739.\n\tIteration 189\nIteration 189 change of RSS (dCVR) is 0.000664031.\n\tIteration 190\nIteration 190 change of RSS (dCVR) is 0.000658319.\n\tIteration 191\nIteration 191 change of RSS (dCVR) is 0.000652604.\n\tIteration 192\nIteration 192 change of RSS (dCVR) is 0.000646891.\n\tIteration 193\nIteration 193 change of RSS (dCVR) is 0.000641181.\n\tIteration 194\nIteration 194 change of RSS (dCVR) is 0.000635477.\n\tIteration 195\nIteration 195 change of RSS (dCVR) is 0.00062978.\n\tIteration 196\nIteration 196 change of RSS (dCVR) is 0.000624093.\n\tIteration 197\nIteration 197 change of RSS (dCVR) is 0.000618419.\n\tIteration 198\nIteration 198 change of RSS (dCVR) is 0.000612757.\n\tIteration 199\nIteration 199 change of RSS (dCVR) is 0.000607111.\n\tIteration 200\nIteration 200 change of RSS (dCVR) is 0.000601483.\n\tIteration 201\nIteration 201 change of RSS (dCVR) is 0.000595872.\n\tIteration 202\nIteration 202 change of RSS (dCVR) is 0.000590282.\n\tIteration 203\nIteration 203 change of RSS (dCVR) is 0.000584714.\n\tIteration 204\nIteration 204 change of RSS (dCVR) is 0.000579168.\n\tIteration 205\nIteration 205 change of RSS (dCVR) is 0.000573646.\n\tIteration 206\nIteration 206 change of RSS (dCVR) is 0.00056815.\n\tIteration 207\nIteration 207 change of RSS (dCVR) is 0.000562679.\n\tIteration 208\nIteration 208 change of RSS (dCVR) is 0.000557236.\n\tIteration 209\nIteration 209 change of RSS (dCVR) is 0.000551822.\n\tIteration 210\nIteration 210 change of RSS (dCVR) is 0.000546436.\n\tIteration 211\nIteration 211 change of RSS (dCVR) is 0.000541081.\n\tIteration 212\nIteration 212 change of RSS (dCVR) is 0.000535756.\n\tIteration 213\nIteration 213 change of RSS (dCVR) is 0.000530463.\n\tIteration 214\nIteration 214 change of RSS (dCVR) is 0.000525202.\n\tIteration 215\nIteration 215 change of RSS (dCVR) is 0.000519974.\n\tIteration 216\nIteration 216 change of RSS (dCVR) is 0.000514779.\n\tIteration 217\nIteration 217 change of RSS (dCVR) is 0.000509619.\n\tIteration 218\nIteration 218 change of RSS (dCVR) is 0.000504493.\n\tIteration 219\nIteration 219 change of RSS (dCVR) is 0.000499402.\n\tIteration 220\nIteration 220 change of RSS (dCVR) is 0.000494346.\n\tIteration 221\nIteration 221 change of RSS (dCVR) is 0.000489327.\n\tIteration 222\nIteration 222 change of RSS (dCVR) is 0.000484343.\n\tIteration 223\nIteration 223 change of RSS (dCVR) is 0.000479396.\n\tIteration 224\nIteration 224 change of RSS (dCVR) is 0.000474486.\n\tIteration 225\nIteration 225 change of RSS (dCVR) is 0.000469613.\n\tIteration 226\nIteration 226 change of RSS (dCVR) is 0.000464778.\n\tIteration 227\nIteration 227 change of RSS (dCVR) is 0.00045998.\n\tIteration 228\nIteration 228 change of RSS (dCVR) is 0.000455219.\n\tIteration 229\nIteration 229 change of RSS (dCVR) is 0.000450497.\n\tIteration 230\nIteration 230 change of RSS (dCVR) is 0.000445813.\n\tIteration 231\nIteration 231 change of RSS (dCVR) is 0.000441167.\n\tIteration 232\nIteration 232 change of RSS (dCVR) is 0.000436559.\n\tIteration 233\nIteration 233 change of RSS (dCVR) is 0.000431989.\n\tIteration 234\nIteration 234 change of RSS (dCVR) is 0.000427458.\n\tIteration 235\nIteration 235 change of RSS (dCVR) is 0.000422966.\n\tIteration 236\nIteration 236 change of RSS (dCVR) is 0.000418512.\n\tIteration 237\nIteration 237 change of RSS (dCVR) is 0.000414096.\n\tIteration 238\nIteration 238 change of RSS (dCVR) is 0.000409719.\n\tIteration 239\nIteration 239 change of RSS (dCVR) is 0.00040538.\n\tIteration 240\nIteration 240 change of RSS (dCVR) is 0.000401079.\n\tIteration 241\nIteration 241 change of RSS (dCVR) is 0.000396817.\n\tIteration 242\nIteration 242 change of RSS (dCVR) is 0.000392594.\n\tIteration 243\nIteration 243 change of RSS (dCVR) is 0.000388408.\n\tIteration 244\nIteration 244 change of RSS (dCVR) is 0.00038426.\n\tIteration 245\nIteration 245 change of RSS (dCVR) is 0.000380151.\n\tIteration 246\nIteration 246 change of RSS (dCVR) is 0.000376079.\n\tIteration 247\nIteration 247 change of RSS (dCVR) is 0.000372045.\n\tIteration 248\nIteration 248 change of RSS (dCVR) is 0.000368049.\n\tIteration 249\nIteration 249 change of RSS (dCVR) is 0.00036409.\n\tIteration 250\nIteration 250 change of RSS (dCVR) is 0.000360169.\n\tIteration 251\nIteration 251 change of RSS (dCVR) is 0.000356285.\n\tIteration 252\nIteration 252 change of RSS (dCVR) is 0.000352438.\n\tIteration 253\nIteration 253 change of RSS (dCVR) is 0.000348627.\n\tIteration 254\nIteration 254 change of RSS (dCVR) is 0.000344853.\n\tIteration 255\nIteration 255 change of RSS (dCVR) is 0.000341116.\n\tIteration 256\nIteration 256 change of RSS (dCVR) is 0.000337415.\n\tIteration 257\nIteration 257 change of RSS (dCVR) is 0.00033375.\n\tIteration 258\nIteration 258 change of RSS (dCVR) is 0.000330121.\n\tIteration 259\nIteration 259 change of RSS (dCVR) is 0.000326527.\n\tIteration 260\nIteration 260 change of RSS (dCVR) is 0.000322969.\n\tIteration 261\nIteration 261 change of RSS (dCVR) is 0.000319447.\n\tIteration 262\nIteration 262 change of RSS (dCVR) is 0.000315959.\n\tIteration 263\nIteration 263 change of RSS (dCVR) is 0.000312506.\n\tIteration 264\nIteration 264 change of RSS (dCVR) is 0.000309088.\n\tIteration 265\nIteration 265 change of RSS (dCVR) is 0.000305703.\n\tIteration 266\nIteration 266 change of RSS (dCVR) is 0.000302353.\n\tIteration 267\nIteration 267 change of RSS (dCVR) is 0.000299037.\n\tIteration 268\nIteration 268 change of RSS (dCVR) is 0.000295755.\n\tIteration 269\nIteration 269 change of RSS (dCVR) is 0.000292506.\n\tIteration 270\nIteration 270 change of RSS (dCVR) is 0.00028929.\n\tIteration 271\nIteration 271 change of RSS (dCVR) is 0.000286106.\n\tIteration 272\nIteration 272 change of RSS (dCVR) is 0.000282956.\n\tIteration 273\nIteration 273 change of RSS (dCVR) is 0.000279838.\n\tIteration 274\nIteration 274 change of RSS (dCVR) is 0.000276752.\n\tIteration 275\nIteration 275 change of RSS (dCVR) is 0.000273698.\n\tIteration 276\nIteration 276 change of RSS (dCVR) is 0.000270675.\n\tIteration 277\nIteration 277 change of RSS (dCVR) is 0.000267684.\n\tIteration 278\nIteration 278 change of RSS (dCVR) is 0.000264724.\n\tIteration 279\nIteration 279 change of RSS (dCVR) is 0.000261795.\n\tIteration 280\nIteration 280 change of RSS (dCVR) is 0.000258896.\n\tIteration 281\nIteration 281 change of RSS (dCVR) is 0.000256028.\n\tIteration 282\nIteration 282 change of RSS (dCVR) is 0.00025319.\n\tIteration 283\nIteration 283 change of RSS (dCVR) is 0.000250382.\n\tIteration 284\nIteration 284 change of RSS (dCVR) is 0.000247603.\n\tIteration 285\nIteration 285 change of RSS (dCVR) is 0.000244854.\n\tIteration 286\nIteration 286 change of RSS (dCVR) is 0.000242133.\n\tIteration 287\nIteration 287 change of RSS (dCVR) is 0.000239442.\n\tIteration 288\nIteration 288 change of RSS (dCVR) is 0.000236779.\n\tIteration 289\nIteration 289 change of RSS (dCVR) is 0.000234144.\n\tIteration 290\nIteration 290 change of RSS (dCVR) is 0.000231538.\n\tIteration 291\nIteration 291 change of RSS (dCVR) is 0.000228959.\n\tIteration 292\nIteration 292 change of RSS (dCVR) is 0.000226408.\n\tIteration 293\nIteration 293 change of RSS (dCVR) is 0.000223884.\n\tIteration 294\nIteration 294 change of RSS (dCVR) is 0.000221387.\n\tIteration 295\nIteration 295 change of RSS (dCVR) is 0.000218917.\n\tIteration 296\nIteration 296 change of RSS (dCVR) is 0.000216473.\n\tIteration 297\nIteration 297 change of RSS (dCVR) is 0.000214056.\n\tIteration 298\nIteration 298 change of RSS (dCVR) is 0.000211664.\n\tIteration 299\nIteration 299 change of RSS (dCVR) is 0.000209299.\n\tIteration 300\nIteration 300 change of RSS (dCVR) is 0.000206959.\n\tIteration 301\nIteration 301 change of RSS (dCVR) is 0.000204644.\n\tIteration 302\nIteration 302 change of RSS (dCVR) is 0.000202354.\n\tIteration 303\nIteration 303 change of RSS (dCVR) is 0.00020009.\n\tIteration 304\nIteration 304 change of RSS (dCVR) is 0.000197849.\n\tIteration 305\nIteration 305 change of RSS (dCVR) is 0.000195633.\n\tIteration 306\nIteration 306 change of RSS (dCVR) is 0.000193441.\n\tIteration 307\nIteration 307 change of RSS (dCVR) is 0.000191273.\n\tIteration 308\nIteration 308 change of RSS (dCVR) is 0.000189129.\n\tIteration 309\nIteration 309 change of RSS (dCVR) is 0.000187008.\n\tIteration 310\nIteration 310 change of RSS (dCVR) is 0.00018491.\n\tIteration 311\nIteration 311 change of RSS (dCVR) is 0.000182835.\n\tIteration 312\nIteration 312 change of RSS (dCVR) is 0.000180783.\n\tIteration 313\nIteration 313 change of RSS (dCVR) is 0.000178753.\n\tIteration 314\nIteration 314 change of RSS (dCVR) is 0.000176746.\n\tIteration 315\nIteration 315 change of RSS (dCVR) is 0.00017476.\n\tIteration 316\nIteration 316 change of RSS (dCVR) is 0.000172797.\n\tIteration 317\nIteration 317 change of RSS (dCVR) is 0.000170854.\n\tIteration 318\nIteration 318 change of RSS (dCVR) is 0.000168934.\n\tIteration 319\nIteration 319 change of RSS (dCVR) is 0.000167034.\n\tIteration 320\nIteration 320 change of RSS (dCVR) is 0.000165155.\n\tIteration 321\nIteration 321 change of RSS (dCVR) is 0.000163297.\n\tIteration 322\nIteration 322 change of RSS (dCVR) is 0.00016146.\n\tIteration 323\nIteration 323 change of RSS (dCVR) is 0.000159642.\n\tIteration 324\nIteration 324 change of RSS (dCVR) is 0.000157845.\n\tIteration 325\nIteration 325 change of RSS (dCVR) is 0.000156068.\n\tIteration 326\nIteration 326 change of RSS (dCVR) is 0.00015431.\n\tIteration 327\nIteration 327 change of RSS (dCVR) is 0.000152572.\n\tIteration 328\nIteration 328 change of RSS (dCVR) is 0.000150853.\n\tIteration 329\nIteration 329 change of RSS (dCVR) is 0.000149153.\n\tIteration 330\nIteration 330 change of RSS (dCVR) is 0.000147472.\n\tIteration 331\nIteration 331 change of RSS (dCVR) is 0.000145809.\n\tIteration 332\nIteration 332 change of RSS (dCVR) is 0.000144165.\n\tIteration 333\nIteration 333 change of RSS (dCVR) is 0.000142539.\n\tIteration 334\nIteration 334 change of RSS (dCVR) is 0.000140931.\n\tIteration 335\nIteration 335 change of RSS (dCVR) is 0.000139342.\n\tIteration 336\nIteration 336 change of RSS (dCVR) is 0.000137769.\n\tIteration 337\nIteration 337 change of RSS (dCVR) is 0.000136215.\n\tIteration 338\nIteration 338 change of RSS (dCVR) is 0.000134677.\n\tIteration 339\nIteration 339 change of RSS (dCVR) is 0.000133157.\n\tIteration 340\nIteration 340 change of RSS (dCVR) is 0.000131654.\n\tIteration 341\nIteration 341 change of RSS (dCVR) is 0.000130167.\n\tIteration 342\nIteration 342 change of RSS (dCVR) is 0.000128697.\n\tIteration 343\nIteration 343 change of RSS (dCVR) is 0.000127243.\n\tIteration 344\nIteration 344 change of RSS (dCVR) is 0.000125806.\n\tIteration 345\nIteration 345 change of RSS (dCVR) is 0.000124385.\n\tIteration 346\nIteration 346 change of RSS (dCVR) is 0.000122979.\n\tIteration 347\nIteration 347 change of RSS (dCVR) is 0.000121589.\n\tIteration 348\nIteration 348 change of RSS (dCVR) is 0.000120215.\n\tIteration 349\nIteration 349 change of RSS (dCVR) is 0.000118856.\n\tIteration 350\nIteration 350 change of RSS (dCVR) is 0.000117513.\n\tIteration 351\nIteration 351 change of RSS (dCVR) is 0.000116184.\n\tIteration 352\nIteration 352 change of RSS (dCVR) is 0.00011487.\n\tIteration 353\nIteration 353 change of RSS (dCVR) is 0.000113571.\n\tIteration 354\nIteration 354 change of RSS (dCVR) is 0.000112287.\n\tIteration 355\nIteration 355 change of RSS (dCVR) is 0.000111017.\n\tIteration 356\nIteration 356 change of RSS (dCVR) is 0.000109761.\n\tIteration 357\nIteration 357 change of RSS (dCVR) is 0.000108519.\n\tIteration 358\nIteration 358 change of RSS (dCVR) is 0.000107291.\n\tIteration 359\nIteration 359 change of RSS (dCVR) is 0.000106077.\n\tIteration 360\nIteration 360 change of RSS (dCVR) is 0.000104877.\n\tIteration 361\nIteration 361 change of RSS (dCVR) is 0.00010369.\n\tIteration 362\nIteration 362 change of RSS (dCVR) is 0.000102516.\n\tIteration 363\nIteration 363 change of RSS (dCVR) is 0.000101356.\n\tIteration 364\nIteration 364 change of RSS (dCVR) is 0.000100208.\n\tIteration 365\nIteration 365 change of RSS (dCVR) is 9.90736e-05.\n\tIteration 366\nIteration 366 change of RSS (dCVR) is 9.79518e-05.\n\tIteration 367\nIteration 367 change of RSS (dCVR) is 9.68426e-05.\n\tIteration 368\nIteration 368 change of RSS (dCVR) is 9.5746e-05.\n\tIteration 369\nIteration 369 change of RSS (dCVR) is 9.46616e-05.\n\tIteration 370\nIteration 370 change of RSS (dCVR) is 9.35895e-05.\n\tIteration 371\nIteration 371 change of RSS (dCVR) is 9.25294e-05.\n\tIteration 372\nIteration 372 change of RSS (dCVR) is 9.14812e-05.\n\tIteration 373\nIteration 373 change of RSS (dCVR) is 9.04449e-05.\n\tIteration 374\nIteration 374 change of RSS (dCVR) is 8.94202e-05.\n\tIteration 375\nIteration 375 change of RSS (dCVR) is 8.84071e-05.\n\tIteration 376\nIteration 376 change of RSS (dCVR) is 8.74053e-05.\n\tIteration 377\nIteration 377 change of RSS (dCVR) is 8.64149e-05.\n\tIteration 378\nIteration 378 change of RSS (dCVR) is 8.54357e-05.\n\tIteration 379\nIteration 379 change of RSS (dCVR) is 8.44674e-05.\n\tIteration 380\nIteration 380 change of RSS (dCVR) is 8.35101e-05.\n\tIteration 381\nIteration 381 change of RSS (dCVR) is 8.25636e-05.\n\tIteration 382\nIteration 382 change of RSS (dCVR) is 8.16277e-05.\n\tIteration 383\nIteration 383 change of RSS (dCVR) is 8.07024e-05.\n\tIteration 384\nIteration 384 change of RSS (dCVR) is 7.97876e-05.\n\tIteration 385\nIteration 385 change of RSS (dCVR) is 7.88831e-05.\n\tIteration 386\nIteration 386 change of RSS (dCVR) is 7.79888e-05.\n\tIteration 387\nIteration 387 change of RSS (dCVR) is 7.71045e-05.\n\tIteration 388\nIteration 388 change of RSS (dCVR) is 7.62303e-05.\n\tIteration 389\nIteration 389 change of RSS (dCVR) is 7.53659e-05.\n\tIteration 390\nIteration 390 change of RSS (dCVR) is 7.45113e-05.\n\tIteration 391\nIteration 391 change of RSS (dCVR) is 7.36664e-05.\n\tIteration 392\nIteration 392 change of RSS (dCVR) is 7.28309e-05.\n\tIteration 393\nIteration 393 change of RSS (dCVR) is 7.2005e-05.\n\tIteration 394\nIteration 394 change of RSS (dCVR) is 7.11883e-05.\n\tIteration 395\nIteration 395 change of RSS (dCVR) is 7.03809e-05.\n\tIteration 396\nIteration 396 change of RSS (dCVR) is 6.95826e-05.\n\tIteration 397\nIteration 397 change of RSS (dCVR) is 6.87934e-05.\n\tIteration 398\nIteration 398 change of RSS (dCVR) is 6.8013e-05.\n\tIteration 399\nIteration 399 change of RSS (dCVR) is 6.72415e-05.\n\tIteration 400\nIteration 400 change of RSS (dCVR) is 6.64787e-05.\n\tIteration 401\nIteration 401 change of RSS (dCVR) is 6.57245e-05.\n\tIteration 402\nIteration 402 change of RSS (dCVR) is 6.49789e-05.\n\tIteration 403\nIteration 403 change of RSS (dCVR) is 6.42417e-05.\n\tIteration 404\nIteration 404 change of RSS (dCVR) is 6.35128e-05.\n\tIteration 405\nIteration 405 change of RSS (dCVR) is 6.27922e-05.\n\tIteration 406\nIteration 406 change of RSS (dCVR) is 6.20797e-05.\n\tIteration 407\nIteration 407 change of RSS (dCVR) is 6.13753e-05.\n\tIteration 408\nIteration 408 change of RSS (dCVR) is 6.06788e-05.\n\tIteration 409\nIteration 409 change of RSS (dCVR) is 5.99903e-05.\n\tIteration 410\nIteration 410 change of RSS (dCVR) is 5.93095e-05.\n\tIteration 411\nIteration 411 change of RSS (dCVR) is 5.86365e-05.\n\tIteration 412\nIteration 412 change of RSS (dCVR) is 5.7971e-05.\n\tIteration 413\nIteration 413 change of RSS (dCVR) is 5.73131e-05.\n\tIteration 414\nIteration 414 change of RSS (dCVR) is 5.66627e-05.\n\tIteration 415\nIteration 415 change of RSS (dCVR) is 5.60196e-05.\n\tIteration 416\nIteration 416 change of RSS (dCVR) is 5.53838e-05.\n\tIteration 417\nIteration 417 change of RSS (dCVR) is 5.47552e-05.\n\tIteration 418\nIteration 418 change of RSS (dCVR) is 5.41337e-05.\n\tIteration 419\nIteration 419 change of RSS (dCVR) is 5.35192e-05.\n\tIteration 420\nIteration 420 change of RSS (dCVR) is 5.29117e-05.\n\tIteration 421\nIteration 421 change of RSS (dCVR) is 5.23111e-05.\n\tIteration 422\nIteration 422 change of RSS (dCVR) is 5.17173e-05.\n\tIteration 423\nIteration 423 change of RSS (dCVR) is 5.11302e-05.\n\tIteration 424\nIteration 424 change of RSS (dCVR) is 5.05498e-05.\n\tIteration 425\nIteration 425 change of RSS (dCVR) is 4.9976e-05.\n\tIteration 426\nIteration 426 change of RSS (dCVR) is 4.94086e-05.\n\tIteration 427\nIteration 427 change of RSS (dCVR) is 4.88477e-05.\n\tIteration 428\nIteration 428 change of RSS (dCVR) is 4.82932e-05.\n\tIteration 429\nIteration 429 change of RSS (dCVR) is 4.77449e-05.\n\tIteration 430\nIteration 430 change of RSS (dCVR) is 4.72028e-05.\n\tIteration 431\nIteration 431 change of RSS (dCVR) is 4.66669e-05.\n\tIteration 432\nIteration 432 change of RSS (dCVR) is 4.61371e-05.\n\tIteration 433\nIteration 433 change of RSS (dCVR) is 4.56132e-05.\n\tIteration 434\nIteration 434 change of RSS (dCVR) is 4.50953e-05.\n\tIteration 435\nIteration 435 change of RSS (dCVR) is 4.45833e-05.\n\tIteration 436\nIteration 436 change of RSS (dCVR) is 4.40771e-05.\n\tIteration 437\nIteration 437 change of RSS (dCVR) is 4.35766e-05.\n\tIteration 438\nIteration 438 change of RSS (dCVR) is 4.30818e-05.\n\tIteration 439\nIteration 439 change of RSS (dCVR) is 4.25926e-05.\n\tIteration 440\nIteration 440 change of RSS (dCVR) is 4.2109e-05.\n\tIteration 441\nIteration 441 change of RSS (dCVR) is 4.16308e-05.\n\tIteration 442\nIteration 442 change of RSS (dCVR) is 4.11581e-05.\n\tIteration 443\nIteration 443 change of RSS (dCVR) is 4.06907e-05.\n\tIteration 444\nIteration 444 change of RSS (dCVR) is 4.02286e-05.\n\tIteration 445\nIteration 445 change of RSS (dCVR) is 3.97718e-05.\n\tIteration 446\nIteration 446 change of RSS (dCVR) is 3.93202e-05.\n\tIteration 447\nIteration 447 change of RSS (dCVR) is 3.88736e-05.\n\tIteration 448\nIteration 448 change of RSS (dCVR) is 3.84322e-05.\n\tIteration 449\nIteration 449 change of RSS (dCVR) is 3.79957e-05.\n\tIteration 450\nIteration 450 change of RSS (dCVR) is 3.75642e-05.\n\tIteration 451\nIteration 451 change of RSS (dCVR) is 3.71376e-05.\n\tIteration 452\nIteration 452 change of RSS (dCVR) is 3.67158e-05.\n\tIteration 453\nIteration 453 change of RSS (dCVR) is 3.62989e-05.\n\tIteration 454\nIteration 454 change of RSS (dCVR) is 3.58866e-05.\n\tIteration 455\nIteration 455 change of RSS (dCVR) is 3.5479e-05.\n\tIteration 456\nIteration 456 change of RSS (dCVR) is 3.50761e-05.\n\tIteration 457\nIteration 457 change of RSS (dCVR) is 3.46777e-05.\n\tIteration 458\nIteration 458 change of RSS (dCVR) is 3.42839e-05.\n\tIteration 459\nIteration 459 change of RSS (dCVR) is 3.38945e-05.\n\tIteration 460\nIteration 460 change of RSS (dCVR) is 3.35095e-05.\n\tIteration 461\nIteration 461 change of RSS (dCVR) is 3.31289e-05.\n\tIteration 462\nIteration 462 change of RSS (dCVR) is 3.27526e-05.\n\tIteration 463\nIteration 463 change of RSS (dCVR) is 3.23806e-05.\n\tIteration 464\nIteration 464 change of RSS (dCVR) is 3.20128e-05.\n\tIteration 465\nIteration 465 change of RSS (dCVR) is 3.16492e-05.\n\tIteration 466\nIteration 466 change of RSS (dCVR) is 3.12897e-05.\n\tIteration 467\nIteration 467 change of RSS (dCVR) is 3.09343e-05.\n\tIteration 468\nIteration 468 change of RSS (dCVR) is 3.0583e-05.\n\tIteration 469\nIteration 469 change of RSS (dCVR) is 3.02356e-05.\n\tIteration 470\nIteration 470 change of RSS (dCVR) is 2.98921e-05.\n\tIteration 471\nIteration 471 change of RSS (dCVR) is 2.95526e-05.\n\tIteration 472\nIteration 472 change of RSS (dCVR) is 2.92169e-05.\n\tIteration 473\nIteration 473 change of RSS (dCVR) is 2.8885e-05.\n\tIteration 474\nIteration 474 change of RSS (dCVR) is 2.85569e-05.\n\tIteration 475\nIteration 475 change of RSS (dCVR) is 2.82325e-05.\n\tIteration 476\nIteration 476 change of RSS (dCVR) is 2.79118e-05.\n\tIteration 477\nIteration 477 change of RSS (dCVR) is 2.75948e-05.\n\tIteration 478\nIteration 478 change of RSS (dCVR) is 2.72813e-05.\n\tIteration 479\nIteration 479 change of RSS (dCVR) is 2.69714e-05.\n\tIteration 480\nIteration 480 change of RSS (dCVR) is 2.6665e-05.\n\tIteration 481\nIteration 481 change of RSS (dCVR) is 2.63621e-05.\n\tIteration 482\nIteration 482 change of RSS (dCVR) is 2.60627e-05.\n\tIteration 483\nIteration 483 change of RSS (dCVR) is 2.57666e-05.\n\tIteration 484\nIteration 484 change of RSS (dCVR) is 2.54739e-05.\n\tIteration 485\nIteration 485 change of RSS (dCVR) is 2.51845e-05.\n\tIteration 486\nIteration 486 change of RSS (dCVR) is 2.48984e-05.\n\tIteration 487\nIteration 487 change of RSS (dCVR) is 2.46156e-05.\n\tIteration 488\nIteration 488 change of RSS (dCVR) is 2.4336e-05.\n\tIteration 489\nIteration 489 change of RSS (dCVR) is 2.40595e-05.\n\tIteration 490\nIteration 490 change of RSS (dCVR) is 2.37862e-05.\n\tIteration 491\nIteration 491 change of RSS (dCVR) is 2.3516e-05.\n\tIteration 492\nIteration 492 change of RSS (dCVR) is 2.32488e-05.\n\tIteration 493\nIteration 493 change of RSS (dCVR) is 2.29847e-05.\n\tIteration 494\nIteration 494 change of RSS (dCVR) is 2.27236e-05.\n\tIteration 495\nIteration 495 change of RSS (dCVR) is 2.24654e-05.\n\tIteration 496\nIteration 496 change of RSS (dCVR) is 2.22102e-05.\n\tIteration 497\nIteration 497 change of RSS (dCVR) is 2.19579e-05.\n\tIteration 498\nIteration 498 change of RSS (dCVR) is 2.17085e-05.\n\tIteration 499\nIteration 499 change of RSS (dCVR) is 2.14619e-05.\n\tIteration 500\nIteration 500 change of RSS (dCVR) is 2.1218e-05.\n\tIteration 501\nIteration 501 change of RSS (dCVR) is 2.0977e-05.\n\tIteration 502\nIteration 502 change of RSS (dCVR) is 2.07386e-05.\n\tIteration 503\nIteration 503 change of RSS (dCVR) is 2.05031e-05.\n\tIteration 504\nIteration 504 change of RSS (dCVR) is 2.02701e-05.\n\tIteration 505\nIteration 505 change of RSS (dCVR) is 2.00398e-05.\n\tIteration 506\nIteration 506 change of RSS (dCVR) is 1.98122e-05.\n\tIteration 507\nIteration 507 change of RSS (dCVR) is 1.95871e-05.\n\tIteration 508\nIteration 508 change of RSS (dCVR) is 1.93646e-05.\n\tIteration 509\nIteration 509 change of RSS (dCVR) is 1.91446e-05.\n\tIteration 510\nIteration 510 change of RSS (dCVR) is 1.8927e-05.\n\tIteration 511\nIteration 511 change of RSS (dCVR) is 1.8712e-05.\n\tIteration 512\nIteration 512 change of RSS (dCVR) is 1.84995e-05.\n\tIteration 513\nIteration 513 change of RSS (dCVR) is 1.82893e-05.\n\tIteration 514\nIteration 514 change of RSS (dCVR) is 1.80815e-05.\n\tIteration 515\nIteration 515 change of RSS (dCVR) is 1.78761e-05.\n\tIteration 516\nIteration 516 change of RSS (dCVR) is 1.7673e-05.\n\tIteration 517\nIteration 517 change of RSS (dCVR) is 1.74722e-05.\n\tIteration 518\nIteration 518 change of RSS (dCVR) is 1.72737e-05.\n\tIteration 519\nIteration 519 change of RSS (dCVR) is 1.70774e-05.\n\tIteration 520\nIteration 520 change of RSS (dCVR) is 1.68834e-05.\n\tIteration 521\nIteration 521 change of RSS (dCVR) is 1.66916e-05.\n\tIteration 522\nIteration 522 change of RSS (dCVR) is 1.65019e-05.\n\tIteration 523\nIteration 523 change of RSS (dCVR) is 1.63145e-05.\n\tIteration 524\nIteration 524 change of RSS (dCVR) is 1.61291e-05.\n\tIteration 525\nIteration 525 change of RSS (dCVR) is 1.59459e-05.\n\tIteration 526\nIteration 526 change of RSS (dCVR) is 1.57647e-05.\n\tIteration 527\nIteration 527 change of RSS (dCVR) is 1.55856e-05.\n\tIteration 528\nIteration 528 change of RSS (dCVR) is 1.54085e-05.\n\tIteration 529\nIteration 529 change of RSS (dCVR) is 1.52334e-05.\n\tIteration 530\nIteration 530 change of RSS (dCVR) is 1.50604e-05.\n\tIteration 531\nIteration 531 change of RSS (dCVR) is 1.48893e-05.\n\tIteration 532\nIteration 532 change of RSS (dCVR) is 1.47201e-05.\n\tIteration 533\nIteration 533 change of RSS (dCVR) is 1.45529e-05.\n\tIteration 534\nIteration 534 change of RSS (dCVR) is 1.43875e-05.\n\tIteration 535\nIteration 535 change of RSS (dCVR) is 1.4224e-05.\n\tIteration 536\nIteration 536 change of RSS (dCVR) is 1.40624e-05.\n\tIteration 537\nIteration 537 change of RSS (dCVR) is 1.39027e-05.\n\tIteration 538\nIteration 538 change of RSS (dCVR) is 1.37447e-05.\n\tIteration 539\nIteration 539 change of RSS (dCVR) is 1.35886e-05.\n\tIteration 540\nIteration 540 change of RSS (dCVR) is 1.34341e-05.\n\tIteration 541\nIteration 541 change of RSS (dCVR) is 1.32815e-05.\n\tIteration 542\nIteration 542 change of RSS (dCVR) is 1.31306e-05.\n\tIteration 543\nIteration 543 change of RSS (dCVR) is 1.29814e-05.\n\tIteration 544\nIteration 544 change of RSS (dCVR) is 1.28339e-05.\n\tIteration 545\nIteration 545 change of RSS (dCVR) is 1.26881e-05.\n\tIteration 546\nIteration 546 change of RSS (dCVR) is 1.2544e-05.\n\tIteration 547\nIteration 547 change of RSS (dCVR) is 1.24014e-05.\n\tIteration 548\nIteration 548 change of RSS (dCVR) is 1.22606e-05.\n\tIteration 549\nIteration 549 change of RSS (dCVR) is 1.21212e-05.\n\tIteration 550\nIteration 550 change of RSS (dCVR) is 1.19835e-05.\n\tIteration 551\nIteration 551 change of RSS (dCVR) is 1.18474e-05.\n\tIteration 552\nIteration 552 change of RSS (dCVR) is 1.17127e-05.\n\tIteration 553\nIteration 553 change of RSS (dCVR) is 1.15797e-05.\n\tIteration 554\nIteration 554 change of RSS (dCVR) is 1.14481e-05.\n\tIteration 555\nIteration 555 change of RSS (dCVR) is 1.13181e-05.\n\tIteration 556\nIteration 556 change of RSS (dCVR) is 1.11894e-05.\n\tIteration 557\nIteration 557 change of RSS (dCVR) is 1.10623e-05.\n\tIteration 558\nIteration 558 change of RSS (dCVR) is 1.09366e-05.\n\tIteration 559\nIteration 559 change of RSS (dCVR) is 1.08124e-05.\n\tIteration 560\nIteration 560 change of RSS (dCVR) is 1.06895e-05.\n\tIteration 561\nIteration 561 change of RSS (dCVR) is 1.0568e-05.\n\tIteration 562\nIteration 562 change of RSS (dCVR) is 1.0448e-05.\n\tIteration 563\nIteration 563 change of RSS (dCVR) is 1.03293e-05.\n\tIteration 564\nIteration 564 change of RSS (dCVR) is 1.02119e-05.\n\tIteration 565\nIteration 565 change of RSS (dCVR) is 1.00959e-05.\n\tIteration 566\nIteration 566 change of RSS (dCVR) is 9.98123e-06.\n   ***********************************************************************\n   *                       Package   GWmodel                             *\n   ***********************************************************************\n   Program starts at: 2024-12-09 09:18:19 \n   Call:\n   gwr.multiscale(formula = mgwrformula, data = spdata, kernel = kernel, \n    adaptive = adaptive, parallel.method = parallelmethod, parallel.arg = parallelarg)\n\n   Dependent (y) variable:  Avg_HP_\n   Independent variables:  nrst_ds Avg_Gr_ Av_GDP_\n   Number of data points: 973\n   ***********************************************************************\n   *                       Multiscale (PSDM) GWR                          *\n   ***********************************************************************\n\n   *********************Model calibration information*********************\n   Kernel function: gaussian \n   Adaptive bandwidths for each coefficient(number of nearest neighbours): \n              (Intercept) nrst_ds Avg_Gr_ Av_GDP_\n   Bandwidth            8       8      63      10\n\n   *************Summary of multiscale GWR coefficient estimates:***************\n                    Min.     1st Qu.      Median     3rd Qu.       Max.\n   Intercept  9.1775e+03  1.3535e+04  1.5142e+04  1.6548e+04 22736.2527\n   nrst_ds   -3.3579e+00 -7.7424e-01 -4.6883e-01 -4.8999e-02     1.5050\n   Avg_Gr_   -1.5374e+03  5.8256e+01  6.9691e+02  1.1548e+03  2822.1162\n   Av_GDP_   -1.0748e+00 -1.4344e-01  2.9361e-02  1.9283e-01     1.6643\n   ************************Diagnostic information*************************\n   Number of data points: 973 \n   Effective number of parameters (2trace(S) - trace(S'S)): 204.9156 \n   Effective degrees of freedom (n-2trace(S) + trace(S'S)): 768.0844 \n   AICc value:  16359.65 \n   AIC value:  16155.4 \n   BIC value:  16052.46 \n   Residual sum of squares:  795233782 \n   R-square value:  0.9106027 \n   Adjusted R-square value:  0.8867215 \n\n   ***********************************************************************\n   Program stops at: 2024-12-09 20:10:51 \nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	cec1667f-dfc0-37f4-98d6-b9d0895d3e9c	多尺度地理加权回归(txt输入自变量)	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866049298232377344.shp; txt变量顺序: /onesis/kt4/test_data/regr/_whhp/res/o1866049298307874816.txt; 因变量: Avg_HP_; 结果空间数据: /onesis/kt4/test_data/regr/_whhp/res/mgwr_1209.shp; 模型诊断信息: /onesis/kt4/test_data/regr/_whhp/res/mgwr_1209.txt; 	\N	6	b1f2781c-58ed-48f6-8615-a77ebdbffdb4
7c4275b7497e4a71b1538e7ba3bc9fbf		2024-12-09 17:44:56.734869	2024-12-09 17:35:01.416406	{"r":"/onesis/kt4/test_data/regr/_whhp/res/gwr_1209.shp","d":"Avg_HP_","f":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp","h":"/onesis/kt4/test_data/regr/_whhp/res/gwr_1209.txt","i":"/onesis/kt4/test_data/regr/_whhp/res/o1866053930266525696.txt"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nWelcome to GWmodel version 2.4-2.\nLinking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE\nAdaptive bandwidth: 608 CV score: 4931652259 \nAdaptive bandwidth: 384 CV score: 4621822585 \nAdaptive bandwidth: 243 CV score: 4317770528 \nAdaptive bandwidth: 159 CV score: 3999864046 \nAdaptive bandwidth: 103 CV score: 3555264484 \nAdaptive bandwidth: 73 CV score: 3112592636 \nAdaptive bandwidth: 49 CV score: 2677670093 \nAdaptive bandwidth: 40 CV score: 2480203795 \nAdaptive bandwidth: 28 CV score: 2137250825 \nAdaptive bandwidth: 27 CV score: 2102239615 \nAdaptive bandwidth: 20 CV score: 1853862103 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 25 CV score: 2034885238 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 24 CV score: 1996840684 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 23 CV score: 1964631132 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 22 CV score: 1931146014 \nAdaptive bandwidth: 21 CV score: 1890399406 \nAdaptive bandwidth: 21 CV score: 1890399406 \nAdaptive bandwidth: 20 CV score: 1853862103 \n   ***********************************************************************\n   *                       Package   GWmodel                             *\n   ***********************************************************************\n   Program starts at: 2024-12-09 09:44:51 \n   Call:\n   gwr.basic(formula = gwrformula, data = spdata, bw = bw, kernel = kernel, \n    adaptive = adaptive, parallel.method = "omp")\n\n   Dependent (y) variable:  Avg_HP_\n   Independent variables:  nrst_ds Avg_Gr_ Av_GDP_\n   Number of data points: 973\n   ***********************************************************************\n   *                    Results of Global Regression                     *\n   ***********************************************************************\n\n   Call:\n    lm(formula = formula, data = data)\n\n   Residuals:\n    Min      1Q  Median      3Q     Max \n-7060.0 -1462.6   -49.1  1402.0  8474.4 \n\n   Coefficients:\n                 Estimate Std. Error t value Pr(>|t|)    \n   (Intercept)  1.527e+04  1.610e+02  94.793  < 2e-16 ***\n   nrst_ds     -1.025e+00  4.449e-02 -23.036  < 2e-16 ***\n   Avg_Gr_      2.898e+03  6.784e+02   4.272 2.12e-05 ***\n   Av_GDP_      2.672e-01  7.199e-02   3.711 0.000218 ***\n\n   ---Significance stars\n   Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 \n   Residual standard error: 2375 on 969 degrees of freedom\n   Multiple R-squared: 0.3857\n   Adjusted R-squared: 0.3838 \n   F-statistic: 202.8 on 3 and 969 DF,  p-value: < 2.2e-16 \n   ***Extra Diagnostic information\n   Residual sum of squares: 5464608038\n   Sigma(hat): 2372.302\n   AIC:  17892.82\n   AICc:  17892.88\n   BIC:  16978.62\n   ***********************************************************************\n   *          Results of Geographically Weighted Regression              *\n   ***********************************************************************\n\n   *********************Model calibration information*********************\n   Kernel function: gaussian \n   Adaptive bandwidth: 20 (number of nearest neighbours)\n   Regression points: the same locations as observations are used.\n   Distance metric: Euclidean distance metric is used.\n\n   ****************Summary of GWR coefficient estimates:******************\n                    Min.     1st Qu.      Median     3rd Qu.       Max.\n   Intercept  1.0674e+04  1.3557e+04  1.5206e+04  1.6345e+04 21833.2078\n   nrst_ds   -3.0572e+00 -8.8351e-01 -4.6088e-01  4.2278e-03     1.4104\n   Avg_Gr_   -3.2202e+03  3.1662e+02  1.8977e+03  3.5756e+03 10513.6440\n   Av_GDP_   -2.2696e+00 -2.3138e-01  4.0109e-02  2.7502e-01     1.3326\n   ************************Diagnostic information*************************\n   Number of data points: 973 \n   Effective number of parameters (2trace(S) - trace(S'S)): 121.6069 \n   Effective degrees of freedom (n-2trace(S) + trace(S'S)): 851.3931 \n   AICc (GWR book, Fotheringham, et al. 2002, p. 61, eq 2.33): 16846.29 \n   AIC (GWR book, Fotheringham, et al. 2002,GWR p. 96, eq. 4.22): 16739.18 \n   BIC (GWR book, Fotheringham, et al. 2002,GWR p. 61, eq. 2.34): 16279.37 \n   Residual sum of squares: 1542237099 \n   R-square value:  0.8266273 \n   Adjusted R-square value:  0.8018349 \n\n   ***********************************************************************\n   Program stops at: 2024-12-09 09:44:52 \nWarning message:\nIn abbreviate_shapefile_names(obj) :\n  Field names abbreviated for ESRI Shapefile driver\n	7bc9fe36-321c-3222-a938-32033f92aa03	地理加权回归(txt输入自变量)	矢量空间数据: /onesis/kt4/test_data/regr/_whhp/res/o1866053930174251008.shp; txt变量顺序: /onesis/kt4/test_data/regr/_whhp/res/o1866053930266525696.txt; 因变量: Avg_HP_; 结果空间数据: /onesis/kt4/test_data/regr/_whhp/res/gwr_1209.shp; 模型诊断信息: /onesis/kt4/test_data/regr/_whhp/res/gwr_1209.txt; 	\N	6	74b2e657-daf3-4e0d-b5dd-725dfe6afcd6
a77ba1980de241a4988097c2f9b69e8c		2024-12-25 14:53:02.921547	2024-12-25 14:52:43.287776	{"p":"/onesis/kt4/job_results/1_ipsm/p1871811290398326784.tif","ad8":"/onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/p1871811290398326784.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.071414\nCompute time: 0.193248\nWrite time: 0.053623\nTotal time: 0.318285\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1871811290398326784.tif; d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
54d760430658497abfb4aa0e7657cf3f		2024-12-25 14:52:48.041474	2024-12-25 14:52:43.24894	{"z":"/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.033465\nData read time: 0.109032\nCompute time: 0.163665\nWrite time: 0.084923\nTotal time: 0.391085\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif; 数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
f916eeef9e4e421c8e1db8ef7d6c409a		2024-12-25 14:40:09.288269	2024-12-25 14:39:39.316576	{"train_data_folder":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode1_argument_select/data/","geo_coord":"x,y","variable":"u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2","air_quality":"PM2.5","best_arg":"/onesis/kt4/job_results/best_arg1871807999299944448.json"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.variable: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2\nFinal variables: ['u10', 'v10', 't2m', 'sp', 'tp', 'AQI', 'PM10', 'NO2', 'CO', 'O3', 'SO2']\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\nchina_sites_2017010311.csv\nchina_sites_2017010416.csv\nchina_sites_2017010415.csv\nchina_sites_2017010418.csv\nchina_sites_2017010316.csv\nchina_sites_2017010413.csv\nchina_sites_2017010420.csv\nchina_sites_2017010421.csv\nchina_sites_2017010320.csv\nchina_sites_2017010315.csv\nchina_sites_2017010310.csv\nchina_sites_2017010319.csv\nchina_sites_2017010312.csv\nchina_sites_2017010313.csv\nchina_sites_2017010417.csv\nchina_sites_2017010414.csv\nchina_sites_2017010411.csv\nchina_sites_2017010314.csv\nchina_sites_2017010419.csv\nchina_sites_2017010412.csv\nchina_sites_2017010317.csv\nchina_sites_2017010321.csv\nchina_sites_2017010318.csv\nchina_sites_2017010410.csv\n            x        y\n0    117.4570  38.8394\n1    114.3541  37.9097\n2    118.1997  39.6295\n3    119.5259  39.8283\n4    119.7624  40.0181\n..        ...      ...\n231   86.0697  44.3075\n232   87.5475  44.1756\n233  101.7227  26.5670\n234  118.0936  24.5058\n235  113.1569  36.1912\n\n[236 rows x 2 columns]\ntrain_data:           u10       v10         t2m  ...       PM2.5         x        y\n0   -1.640743 -0.860563  273.150461  ...  203.458333  117.4570  38.8394\n1    0.790372 -0.217611  271.790785  ...   86.875000  114.3541  37.9097\n2   -0.990183 -0.839658  269.928228  ...  282.583333  118.1997  39.6295\n3   -1.980586 -2.696221  274.631896  ...  146.250000  119.5259  39.8283\n4   -0.705750 -2.260111  271.373622  ...  130.833333  119.7624  40.0181\n..        ...       ...         ...  ...         ...       ...      ...\n231  0.648333 -0.588518  260.514139  ...  178.041667   86.0697  44.3075\n232  0.748970 -1.401752  256.965202  ...  190.125000   87.5475  44.1756\n233 -0.965013  0.604648  283.207503  ...   41.958333  101.7227  26.5670\n234 -1.055777 -1.273097  289.279029  ...   58.291667  118.0936  24.5058\n235 -1.215249  0.367138  272.866162  ...  186.625000  113.1569  36.1912\n\n[236 rows x 14 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.640743 -0.860563  273.150461  ...   6.833333  20.125000  203.458333\n1  0.790372 -0.217611  271.790785  ...  98.500000  57.125000   86.875000\n2 -0.990183 -0.839658  269.928228  ...  10.250000  48.250000  282.583333\n3 -1.980586 -2.696221  274.631896  ...  31.583333  57.333333  146.250000\n4 -0.705750 -2.260111  271.373622  ...  19.083333  64.291667  130.833333\n\n[5 rows x 12 columns]\nbest_threshold: 0.475\nbest_r2: 0.11221544152212798\n	87892310-b9ea-3b28-8fce-b7c6c3c9ec3a	相关性分析与特征选择	历史空气质量数据文件夹: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode1_argument_select/data/; 空气质量自变量: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 最优自变量和权重结果: /onesis/kt4/job_results/best_arg1871807999299944448.json; 	\N	6	c59aa852-e823-4121-a2e7-7da16b1815ab
78724b56e9614e7ab4677cc110463347		2024-12-25 14:52:53.77984	2024-12-25 14:52:43.172631	{"i":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif","o":"/onesis/kt4/job_results/1_ipsm/o1871811289601409024.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to ProfileCurvature *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.75s\n	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	输入栅格 DEM 文件: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 输出栅格文件: /onesis/kt4/job_results/1_ipsm/o1871811289601409024.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
71a41f104051434fb580aa206e450d7c		2024-12-25 14:52:53.843808	2024-12-25 14:52:43.121902	{"zfactor":"1","i":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif","o":"/onesis/kt4/job_results/1_ipsm/o1871811289827901440.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n****************************\n* Welcome to Aspect        *\n* Powered by WhiteboxTools *\n* www.whiteboxgeo.com      *\n****************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.73s\n	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	输入数据: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 输出数据: /onesis/kt4/job_results/1_ipsm/o1871811289827901440.tif; z因子: 1; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
ddc9053216b443fbb461ea842e35b894		2024-12-30 13:20:09.472629	2024-12-30 10:51:32.277791	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif","METHOD":"0","RESULT":"/onesis/kt4/job_results/1_ipsm/RESULT1873562531868573696.tif"}	f	\N	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 计算方式: 0; 邻域窗口大小: 0; 地形结构指数: /onesis/kt4/job_results/1_ipsm/RESULT1873562531868573696.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
63438fb5d52a4dd99bb7ed51b56a3ff2		2024-12-25 14:53:08.037727	2024-12-25 14:52:43.197378	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif","slope":"/onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif","o":"/onesis/kt4/job_results/1_ipsm/o1871811290633207808.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to StreamPowerIndex *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nProgress: 0%\nProgress: 1%\nProgress: 2%\nProgress: 3%\nProgress: 4%\nProgress: 5%\nProgress: 6%\nProgress: 7%\nProgress: 8%\nProgress: 9%\nProgress: 10%\nProgress: 11%\nProgress: 12%\nProgress: 13%\nProgress: 14%\nProgress: 15%\nProgress: 16%\nProgress: 17%\nProgress: 18%\nProgress: 19%\nProgress: 20%\nProgress: 21%\nProgress: 22%\nProgress: 23%\nProgress: 24%\nProgress: 25%\nProgress: 26%\nProgress: 27%\nProgress: 28%\nProgress: 29%\nProgress: 30%\nProgress: 31%\nProgress: 32%\nProgress: 33%\nProgress: 34%\nProgress: 35%\nProgress: 36%\nProgress: 37%\nProgress: 38%\nProgress: 39%\nProgress: 40%\nProgress: 41%\nProgress: 42%\nProgress: 43%\nProgress: 44%\nProgress: 45%\nProgress: 46%\nProgress: 47%\nProgress: 48%\nProgress: 49%\nProgress: 50%\nProgress: 51%\nProgress: 52%\nProgress: 53%\nProgress: 54%\nProgress: 55%\nProgress: 56%\nProgress: 57%\nProgress: 58%\nProgress: 59%\nProgress: 60%\nProgress: 61%\nProgress: 62%\nProgress: 63%\nProgress: 64%\nProgress: 65%\nProgress: 66%\nProgress: 67%\nProgress: 68%\nProgress: 69%\nProgress: 70%\nProgress: 71%\nProgress: 72%\nProgress: 73%\nProgress: 74%\nProgress: 75%\nProgress: 76%\nProgress: 77%\nProgress: 78%\nProgress: 79%\nProgress: 80%\nProgress: 81%\nProgress: 82%\nProgress: 83%\nProgress: 84%\nProgress: 85%\nProgress: 86%\nProgress: 87%\nProgress: 88%\nProgress: 89%\nProgress: 90%\nProgress: 91%\nProgress: 92%\nProgress: 93%\nProgress: 94%\nProgress: 95%\nProgress: 96%\nProgress: 97%\nProgress: 98%\nProgress: 99%\nProgress: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.25s\n	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif; 输入坡度 slope 文件: /onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif; 输出栅格文件: /onesis/kt4/job_results/1_ipsm/o1871811290633207808.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
3ceef5e802dd4821994faa621260cc98		2024-12-25 14:40:19.408819	2024-12-25 14:39:39.17648	{"train_data_folder":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/","sigma":"1.5","geo_coord":"x,y","cluster_result":"/onesis/kt4/job_results/cluster_result1871807999425773568.csv","variable":"u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2","X":"2","Y":"2","iVariables":"/onesis/kt4/job_results/iVariables1871807999425773568.json","air_quality":"PM2.5","k":"100","best_arg":"/onesis/kt4/job_results/best_arg1871807999299944448.json","N_epoch":"100"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.variable: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2\nFinal variables: ['u10', 'v10', 't2m', 'sp', 'tp', 'AQI', 'PM10', 'NO2', 'CO', 'O3', 'SO2']\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\nchina_sites_2017010311.csv\nchina_sites_2017010416.csv\nchina_sites_2017010415.csv\nchina_sites_2017010418.csv\nchina_sites_2017010316.csv\nchina_sites_2017010413.csv\nchina_sites_2017010420.csv\nchina_sites_2017010320.csv\nchina_sites_2017010315.csv\nchina_sites_2017010310.csv\nchina_sites_2017010319.csv\nchina_sites_2017010312.csv\nchina_sites_2017010313.csv\nchina_sites_2017010417.csv\nchina_sites_2017010414.csv\nchina_sites_2017010411.csv\nchina_sites_2017010314.csv\nchina_sites_2017010419.csv\nchina_sites_2017010412.csv\nchina_sites_2017010317.csv\nchina_sites_2017010321.csv\nchina_sites_2017010318.csv\nchina_sites_2017010410.csv\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n        u10       v10         t2m  ...         O3        SO2       PM2.5\n0 -1.504657 -0.878221  273.013794  ...   6.304348  20.347826  204.826087\n1  0.786217 -0.177140  271.731135  ...  98.173913  57.086957   81.782609\n2 -0.908226 -0.827674  269.900488  ...  10.260870  49.130435  285.565217\n3 -1.807954 -2.599573  274.702684  ...  31.130435  58.869565  150.000000\n4 -0.631055 -2.190917  271.465984  ...  19.521739  66.434783  131.913043\n\n[5 rows x 12 columns]\n{'AQI': 0.9939953734386318, 'PM10': 0.9702703712733087, 'NO2': 0.6916964527542312, 'CO': 0.6785650379279617}\n          u10       v10         t2m  ...         x        y  region\n0   -1.504657 -0.878221  273.013794  ...  117.4570  38.8394       1\n1    0.786217 -0.177140  271.731135  ...  114.3541  37.9097       2\n2   -0.908226 -0.827674  269.900488  ...  118.1997  39.6295       1\n3   -1.807954 -2.599573  274.702684  ...  119.5259  39.8283       1\n4   -0.631055 -2.190917  271.465984  ...  119.7624  40.0181       0\n..        ...       ...         ...  ...       ...      ...     ...\n231  0.601761 -0.591802  260.612814  ...   86.0697  44.3075       0\n232  0.702411 -1.409642  257.096259  ...   87.5475  44.1756       3\n233 -0.982240  0.603175  283.314504  ...  101.7227  26.5670       2\n234 -1.112682 -1.291874  289.298598  ...  118.0936  24.5058       2\n235 -1.192497  0.397621  272.886470  ...  113.1569  36.1912       1\n\n[236 rows x 15 columns]\n	38551381-f4bd-3728-850c-c2d4460669b8	Geo-SOM时空聚类与分区	历史空气质量数据文件夹: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode2_clusters/data/; 最优自变量和权重结果: /onesis/kt4/job_results/best_arg1871807999299944448.json; 空气质量自变量: u10,v10,t2m,sp,tp,AQI,PM10,NO2,CO,O3,SO2; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 聚类分区的行数: 2; 聚类分区的列数: 2; GeoSOM算法迭代次数: 100; 地理邻域大小参数: 100; 初始邻域大小阈值: 1.5; 聚类分区结果: /onesis/kt4/job_results/cluster_result1871807999425773568.csv; 各分区中的最优自变量和权重结果: /onesis/kt4/job_results/iVariables1871807999425773568.json; 	\N	6	c59aa852-e823-4121-a2e7-7da16b1815ab
66e0d6f57f4d4938bca093571d291101		2024-12-25 14:40:24.744424	2024-12-25 14:39:38.578684	{"cluster_result":"/onesis/kt4/job_results/cluster_result1871807999425773568.csv","geo_coord":"x,y","output_pred":"/onesis/kt4/job_results/air_wl_1211.csv","iVariables":"/onesis/kt4/job_results/iVariables1871807999425773568.json","air_quality":"PM2.5","pred_data_path":"/onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode3_multiple_liner_predication/data/china_sites_2017010421.csv"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nargs.geo_coord: x,y\nFinal geo_coord: ['x', 'y']\n分区: 2 参数: [-9.17260618e+01  1.15499769e+00 -7.40924971e-02  2.99461750e-01\n -1.52553604e+00] r2: 0.04847284127008744\n分区: 1 参数: [-1.14783449e+01  1.03024321e+00 -1.77088043e-01  8.22878304e-03\n -7.51832896e-01] r2: 0.1362039547508621\n分区: 0 参数: [-16.20075884   0.95799733  -0.11488578   0.04130823   0.50384864] r2: 0.12968084093122045\n分区: 3 参数: [-6.72655057  0.88644638 -0.06857409 -0.07571871  1.39279085] r2: 0.13450412913640308\n[-16.20075884   0.95799733  -0.11488578   0.04130823   0.50384864]\n(236, 4)\n(5,)\n(236,)\n[396.17703522 440.11946815 465.78721446 149.03330726 239.2668603\n 411.39272227 557.69985264 198.12144644 126.69475322 320.41926066\n 171.61539574 167.18630816 113.70423662 103.22910083 156.62455397\n 152.23310223 106.19298763 275.74487015 209.77656399 271.03594089\n 158.31059713 197.40603472 222.63380295 256.44311477 260.1729824\n 331.11126276 254.43295789 431.16323707 418.62896274 309.31697001\n 236.08356268  78.78841984  60.03903233  64.8285143  148.37529542\n 141.52021318 312.78381693 227.76116587 105.06769494 146.28788292\n 833.97199623 424.09415782 463.79435731 202.71642708 234.34897757\n 280.69036558 350.75215705  97.03563916 102.97617794  93.95096881\n  91.3990686  100.43586958 351.05256207 118.08563428 118.61950159\n 125.70559466 146.71765689 157.13819144  77.93290573 276.18537576\n 403.46214467 390.36298146 544.25834349  96.99605583  45.26018141\n 145.5668589  843.39800678 848.70295619 416.25326901 317.30945353\n 267.59200806 225.23289553 191.26128042 149.50221839 102.74888203\n 351.86295938 572.73696958 508.38880794 485.6235902  604.13122463\n 694.14006136 154.4216226  401.48954481 438.14847849 420.46670392\n 106.44329187  74.48481909  68.20073605  91.52043078 141.01019813\n 143.58265439  95.1365097  153.74951554 239.79164642 109.34951\n 107.48138924 103.50260982 221.95156767 245.26226003 201.71236032\n 529.84144821 396.5102584  206.08247047 272.45981367 266.80406409\n 491.74598665 448.9110954  349.55809293 392.57367448 388.18399575\n 397.23489106 457.20939221 770.78712227 276.74119245  67.45542648\n 380.36229495 476.59524164  43.48904215 640.88797899 280.06835662\n 845.44415635 749.43622287 402.5170224  700.70622244 839.7164304\n 310.04455601 201.44935419 188.48758681 445.29015938  96.1750258\n 178.36481854 166.65283042 174.84143746 246.92569813 162.00815874\n 353.88387704 332.95704806 291.27950985 185.18374818 581.4469131\n 254.11136302  94.48195865 259.91685583 180.71111809 196.92510013\n  72.38242603 364.29761555 242.55990169 149.79238673 498.03252546\n  55.89859889  69.40310519 308.3773301  267.07341838 274.40345295\n 339.40426836 376.78302989 357.02368093 325.82452504 276.62242526\n 332.61486537 125.99811546 144.61993618 118.52033303 135.19517623\n 120.835986   120.33575073 300.16128656 459.06235963 396.68253605\n 541.48335696 369.40599752 395.55008862 330.79240091 322.48031196\n 450.03666446 375.22849345 414.42847136 220.84641959 127.21178498\n 323.08086731 459.36437395 181.22939056 459.48752461 236.26781916\n 450.1962574  320.79503976 506.16126829 336.63394473 373.47717222\n 670.49744871 265.28517739 135.90710619 274.94896314 250.71209262\n 328.73968982 163.74610484 296.72835586 255.25745771 297.99748595\n 407.45734092 651.26657424 473.82825884 351.1842736  125.40313417\n  80.05780964  60.8731675  106.6258979  298.50186774  80.61790271\n  58.83653333  87.8784506   64.29725017  71.26237703  76.19169259\n 274.43725859 145.23515721 161.33597113 193.74639693 227.59942663\n 507.98745965 354.32328377 139.54759323 340.54707414 306.34871899\n 108.64584096 232.33494846 135.05560146 150.90761716 195.18844667\n 222.18795846 547.43333005 449.88763781  54.61502136 147.90030662\n 382.6595909 ]\n	e064bcfe-b606-39a2-b35f-09f1f9944f89	空气质量多元线性回归预测	各分区中的最优自变量和权重结果: /onesis/kt4/job_results/iVariables1871807999425773568.json; 聚类分区结果文件: /onesis/kt4/job_results/cluster_result1871807999425773568.csv; 待预测的空气质量数据集: /onesis/kt4/test_data/basic/air_quatity_prediction_work_flow/mode3_multiple_liner_predication/data/china_sites_2017010421.csv; 待预测的空气质量指标: PM2.5; 气象站点地理坐标: x,y; 空气质量预测结果输出文件: /onesis/kt4/job_results/air_wl_1211.csv; 	\N	6	c59aa852-e823-4121-a2e7-7da16b1815ab
c7f7db8b9dcf438581c5c75bd6ee95db		2024-12-25 14:49:13.495108	2024-12-25 14:49:02.901069	{"fel":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif","plan":"/onesis/kt4/job_results/1_ipsm/plan1871810365747232768.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nCurvature -h version 5.3.9, by Liangjun Zhu, Apr 8, 2015\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nProcessors: 1\nRead time: 0.252702\nCompute time: 0.208431\nWrite time: 0.185052\nTotal time: 0.646185\n	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; 平面曲率栅格: /onesis/kt4/job_results/1_ipsm/plan1871810365747232768.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
2b4b9c5c17ff4e4a86f5207e7c891378		2024-12-25 14:52:54.414926	2024-12-25 14:52:43.147956	{"fel":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif","plan":"/onesis/kt4/job_results/1_ipsm/plan1871811289718849536.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nCurvature -h version 5.3.9, by Liangjun Zhu, Apr 8, 2015\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nProcessors: 1\nRead time: 0.569299\nCompute time: 0.113872\nWrite time: 0.229368\nTotal time: 0.912540\n	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 平面曲率栅格: /onesis/kt4/job_results/1_ipsm/plan1871811289718849536.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
654047965e5d4defa796de65fdfe2fe4		2024-12-25 14:49:07.507041	2024-12-25 14:49:02.958032	{"z":"/onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.066945\nData read time: 0.065699\nCompute time: 0.120332\nWrite time: 0.086305\nTotal time: 0.339281\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif; 数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
f542c644835b45ceb50c1d367dd79ca0		2024-12-25 15:24:04.52173	2024-12-25 15:23:59.296839	{"z":"/onesis/kt4/dem/dem_meixi.tif","fel":"/onesis/kt4/results/fel1871819159214620672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dem/dem_meixi.tif has geographic coordinate system.\nNodata value input to create partition from file: 32767.000000\nNodata value recast to float used in partition raster: 32767.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.096967\nData read time: 0.072931\nCompute time: 0.304287\nWrite time: 0.096482\nTotal time: 0.570668\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dem/dem_meixi.tif; 数字高程模型: /onesis/kt4/results/fel1871819159214620672.tif; 	\N	6	7ad44567-dbab-468b-aac1-0c2cfc813e44
00caf7ed4fc14a4d9389a64dd8ddf038		2024-12-25 15:24:13.377813	2024-12-25 15:23:59.265477	{"p":"/onesis/kt4/results/p1871819159264952320.tif","fel":"/onesis/kt4/results/fel1871819159214620672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871819159214620672.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.065178\nData read time: 0.173224\nCompute Slope time: 0.400722\nWrite Slope time: 0.116688\nResolve Flat time: 2.511391\nWrite Flat time: 0.047059\nTotal time: 3.314262\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/results/fel1871819159214620672.tif; D8单流向栅格: /onesis/kt4/results/p1871819159264952320.tif; 	\N	6	7ad44567-dbab-468b-aac1-0c2cfc813e44
6fe8e8cf7db14f56954b898b30aafffa		2024-12-25 14:49:12.804174	2024-12-25 14:49:02.929287	{"i":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif","o":"/onesis/kt4/job_results/1_ipsm/o1871810365638180864.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to ProfileCurvature *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.33s\n	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	输入栅格 DEM 文件: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; 输出栅格文件: /onesis/kt4/job_results/1_ipsm/o1871810365638180864.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
1815311819dc4816b574b9dc93cf7960		2024-12-25 14:49:13.47083	2024-12-25 14:49:02.873079	{"sd8":"/onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 786 flats to resolve.\nDraining flats towards lower adjacent terrain\n............................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 31\nDraining flats towards lower adjacent terrain\n...\nDraining flats away from higher adjacent terrain\n..\nSetting directions\nProcessors: 1\nHeader read time: 0.072522\nData read time: 0.116542\nCompute Slope time: 0.291726\nWrite Slope time: 0.138217\nResolve Flat time: 0.126797\nWrite Flat time: 0.039407\nTotal time: 0.785211\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
c60c37213132415786305827d3990ffa		2024-12-25 14:49:13.474088	2024-12-25 14:49:03.096802	{"p":"/onesis/kt4/job_results/1_ipsm/p1871810366091165696.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 786 flats to resolve.\nDraining flats towards lower adjacent terrain\n............................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 31\nDraining flats towards lower adjacent terrain\n...\nDraining flats away from higher adjacent terrain\n..\nSetting directions\nProcessors: 1\nHeader read time: 0.068057\nData read time: 0.141462\nCompute Slope time: 0.318583\nWrite Slope time: 0.089560\nResolve Flat time: 0.123919\nWrite Flat time: 0.032777\nTotal time: 0.774357\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1871810366091165696.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
70125ff37b0743f1bc65f8692932dcf1		2024-12-25 14:49:18.901938	2024-12-25 14:49:03.011299	{"p":"/onesis/kt4/job_results/1_ipsm/p1871810366091165696.tif","ad8":"/onesis/kt4/job_results/1_ipsm/ad81871810366149885952.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/p1871810366091165696.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.062414\nCompute time: 0.146260\nWrite time: 0.054408\nTotal time: 0.263082\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1871810366091165696.tif; d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81871810366149885952.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
8eae56f3fb2d4988862ffd71abeb56be		2024-12-30 13:20:09.497655	2024-12-30 10:51:32.414483	{"p":"/onesis/kt4/job_results/1_ipsm/p1873562532011180032.tif","ad8":"/onesis/kt4/job_results/1_ipsm/ad81873562532086677504.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873562532011180032.tif; d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81873562532086677504.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
77102b2d08bc4e31a7fdb5b2ace0dc24		2024-12-25 14:49:24.015039	2024-12-25 14:49:02.843375	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81871810366149885952.tif","slp":"/onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif","twi":"/onesis/kt4/job_results/1_ipsm/twi1871810366204411904.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/job_results/1_ipsm/ad81871810366149885952.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.022881\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif; 汇流累积量: /onesis/kt4/job_results/1_ipsm/ad81871810366149885952.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1871810366204411904.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
db8aa8b516dc4072ac0f60eead734344		2024-12-25 14:49:31.891949	2024-12-25 14:49:02.653274	{"uncmap":"/onesis/kt4/job_results/1_ipsm/ipsm_hs_unc01.tif","inlayer1":"/onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif","inlayer0":"/onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif","inlayer7":"/onesis/kt4/job_results/1_ipsm/twi1871810366204411904.tif","inlayer5":"/onesis/kt4/job_results/1_ipsm/o1871810365638180864.tif","simithred":"0.3","predmap":"/onesis/kt4/job_results/1_ipsm/ipsm_hs_som01.tif","inlayer4":"/onesis/kt4/job_results/1_ipsm/plan1871810365747232768.tif","sample":"/onesis/kt4/dsm_case/heshan/hs_samples_900913.csv","target":"SOM"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: 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29.1%\rCompleted   100%	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/heshan/hs_samples_900913.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/job_results/1_ipsm/ipsm_hs_som01.tif; 空间推测不确定性: /onesis/kt4/job_results/1_ipsm/ipsm_hs_unc01.tif; DEM栅格: /onesis/kt4/job_results/1_ipsm/fel1871810365524934656.tif; 剖面曲率: /onesis/kt4/job_results/1_ipsm/o1871810365638180864.tif; 平面曲率: /onesis/kt4/job_results/1_ipsm/plan1871810365747232768.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81871810365864673280.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1871810366204411904.tif; 	\N	6	30aa6ea3-1717-43d4-ad1e-70af213df875
c5900bd26fa244238a0a8363e8cd7327		2024-12-25 14:52:57.532146	2024-12-25 14:52:43.363379	{"p":"/onesis/kt4/job_results/1_ipsm/p1871811290398326784.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 110608 flats to resolve.\nDraining flats towards lower adjacent terrain\n...................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 3414\nDraining flats towards lower adjacent terrain\n.....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.088793\nData read time: 0.203282\nCompute Slope time: 0.323814\nWrite Slope time: 0.119928\nResolve Flat time: 4.012328\nWrite Flat time: 0.083555\nTotal time: 4.831700\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1871811290398326784.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
3f09b4d6507f40c38246bd0b2550a67c		2024-12-25 14:52:58.52657	2024-12-25 14:52:43.223104	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif","METHOD":"0","RESULT":"/onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n____________________________\n\n   #####   ##   #####    ##\n  ###     ###  ##       ###\n   ###   # ## ##  #### # ##\n    ### ##### ##    # #####\n ##### #   ##  ##### #   ##\n____________________________\n\nSAGA Version: 8.1.0\n\n____________________________\nlibrary path: /usr/local/lib/saga/\nlibrary name: libta_morphometry\nlibrary     : ta_morphometry\ntool        : Convergence Index\nidentifier  : 1\nauthor      : O.Conrad (c) 2001\nprocessors  : 8 [8]\n____________________________\n\nloading: fel1871811289551077376\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%[Convergence Index] Execution started...\n\n__________\n[Convergence Index] Parameters:\n\nGrid System: 105.014471; 1257x 954y; 13187390.056515x 3573570.727172y\nElevation: fel1871811289551077376\nConvergence Index: Convergence Index\nMethod: Aspect\nGradient Calculation: 2 x 2\n\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\r101%\n__________\ntotal execution time: 4000 milliseconds (04s)\n\n[Convergence Index] Execution succeeded (04s)\nSaving grid: /data/onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif...\nExport GeoTIFF\n\n__________\n[Export GeoTIFF] Parameters:\n\nGrid System: 105.014471; 1257x 954y; 13187390.056515x 3573570.727172y\nGrid(s): 1 object (RESULT1871811290293469184)\nFile: /data/onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif\nCreation Options: \n\nBand 1\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\n[Export GeoTIFF] execution time: less than 1 millisecond\nokay\n	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 计算方式: 0; 邻域窗口大小: 0; 地形结构指数: /onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
b9157c4d4a324316827043432408c09b		2024-12-25 15:28:21.180826	2024-12-25 15:28:02.779128	{"p":"/onesis/kt4/results/p1871820181471363072.tif","ad8":"/onesis/kt4/results/ad81871820181525889024.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/results/p1871820181471363072.tif has geographic coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.117440\nCompute time: 0.304402\nWrite time: 0.075176\nTotal time: 0.497018\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/results/p1871820181471363072.tif; d8汇流累积量栅格: /onesis/kt4/results/ad81871820181525889024.tif; 	\N	6	7af1abc5-978d-403b-ad32-bbecd75132e7
7ce6a6017cb949eb8d2046ec3b0b4a9e		2024-12-30 13:20:09.521608	2024-12-30 10:51:32.576879	{"p":"/onesis/kt4/job_results/1_ipsm/p1873562532011180032.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif"}	f	\N	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873562532011180032.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
e195791829694de4a00b587d0992bd51		2024-12-25 14:52:59.162365	2024-12-25 14:52:43.095715	{"sd8":"/onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 110608 flats to resolve.\nDraining flats towards lower adjacent terrain\n...................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 3414\nDraining flats towards lower adjacent terrain\n.....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.092406\nData read time: 0.212717\nCompute Slope time: 0.315793\nWrite Slope time: 0.200880\nResolve Flat time: 4.060873\nWrite Flat time: 0.040108\nTotal time: 4.922779\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
ed6c89780ec24b33b8ea0ea9f8859455		2024-12-25 14:53:08.12195	2024-12-25 14:52:43.068273	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif","slp":"/onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif","twi":"/onesis/kt4/job_results/1_ipsm/twi1871811290503184384.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.041351\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif; 汇流累积量: /onesis/kt4/job_results/1_ipsm/ad81871811290452852736.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1871811290503184384.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
958a48a84fac4e918f24ea2a325bad22		2024-12-25 14:53:24.076097	2024-12-25 14:52:42.965845	{"inlayer3":"/onesis/kt4/job_results/1_ipsm/o1871811289827901440.tif","inlayer2":"/onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif","inlayer1":"/onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif","inlayer0":"/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif","inlayer7":"/onesis/kt4/job_results/1_ipsm/twi1871811290503184384.tif","inlayer6":"/onesis/kt4/job_results/1_ipsm/o1871811290633207808.tif","inlayer5":"/onesis/kt4/job_results/1_ipsm/o1871811289601409024.tif","simithred":"0.3","inlayer4":"/onesis/kt4/job_results/1_ipsm/plan1871811289718849536.tif","sample":"/onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv","target":"SOM","uncmap":"/onesis/kt4/job_results/1_ipsm/ipsm_xc_unc01.tif","predmap":"/onesis/kt4/job_results/1_ipsm/ipsm_xc_som01.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif/data/onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif\nLoading data ...\nTransformation operator() function called.\ncompute layer size: 96 126\nrank 0. avg compt load: 172236\n\nRunning prediction method ...\n\rCompleted     0%\rCompleted   0.1%\rCompleted   0.2%\rCompleted   0.3%\rCompleted   0.4%\rCompleted   0.5%\rCompleted   0.6%\rCompleted   0.7%\rCompleted   0.8%\rCompleted   0.9%\rCompleted     1%\rCompleted   1.1%\rCompleted   1.2%\rCompleted   1.3%\rCompleted   1.4%\rCompleted   1.5%\rCompleted   1.6%\rCompleted   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25.2%\rCompleted  25.3%\rCompleted  25.4%\rCompleted  25.5%\rCompleted  25.6%\rCompleted  25.7%\rCompleted  25.8%\rCompleted  25.9%\rCompleted    26%\rCompleted  26.1%\rCompleted  26.2%\rCompleted  26.3%\rCompleted  26.4%\rCompleted  26.5%\rCompleted  26.6%\rCompleted  26.7%\rCompleted  26.8%\rCompleted  26.9%\rCompleted    27%\rCompleted  27.1%\rCompleted  27.2%\rCompleted  27.3%\rCompleted  27.4%\rCompleted  27.5%\rCompleted  27.6%\rCompleted  27.7%\rCompleted  27.8%\rCompleted  27.9%\rCompleted    28%\rCompleted  28.1%\rCompleted  28.2%\rCompleted  28.3%\rCompleted  28.4%\rCompleted  28.5%\rCompleted  28.6%\rCompleted  28.7%\rCompleted  28.8%\rCompleted  28.9%\rCompleted    29%\rCompleted  29.1%\rCompleted  29.2%\rCompleted  29.3%\rCompleted  29.4%\rCompleted  29.5%\rCompleted  29.6%\rCompleted  29.7%\rCompleted  29.8%\rCompleted  29.9%\rCompleted    30%\rCompleted  30.1%\rCompleted  30.2%\rCompleted  30.3%\rCompleted  30.4%\rCompleted  30.5%\rCompleted  30.6%\rCompleted  30.7%\rCompleted  30.8%\rCompleted  30.9%\rCompleted    31%\rCompleted  31.1%\rCompleted  31.2%\rCompleted  31.3%\rCompleted  31.4%\rCompleted  31.5%\rCompleted  31.6%\rCompleted  31.7%\rCompleted  31.8%\rCompleted  31.9%\rCompleted    32%\rCompleted  32.1%\rCompleted  32.2%\rCompleted  32.3%\rCompleted  32.4%\rCompleted  32.5%\rCompleted  32.6%\rCompleted  32.7%\rCompleted  32.8%\rCompleted  32.9%\rCompleted    33%\rCompleted  33.1%\rCompleted  33.2%\rCompleted  33.3 30.2%\rCompleted  30.3%\rCompleted  30.4%\rCompleted  30.5%\rCompleted  30.6%\rCompleted  30.7%\rCompleted  30.8%\rCompleted  30.9%\rCompleted    31%\rCompleted  31.1%\rCompleted  31.2%\rCompleted   100%\nWrite out result ...\n\nProcesses:4\n    Read time:2.836005\n    Compute time:8.524161\n    Write time:0.000000\n 15.2%\rCompleted  15.3%\rCompleted  15.4%\rCompleted  15.5%\rCompleted  15.6%\rCompleted  15.7%\rCompleted  15.8%\rCompleted  15.9%\rCompleted    16%\rCompleted  16.1%\rCompleted  16.2%\rCompleted  16.3%\rCompleted  16.4%\rCompleted  16.5%\rCompleted  16.6%\rCompleted   100%%\rCompleted  33.4%\rCompleted  33.5%\rCompleted  33.6%\rCompleted  33.7%\rCompleted  33.8%\rCompleted  33.9%\rCompleted    34%\rCompleted  34.1%\rCompleted  34.2%\rCompleted  34.3%\rCompleted  34.4%\rCompleted  34.5%\rCompleted  34.6%\rCompleted  34.7%\rCompleted  34.8%\rCompleted  34.9%\rCompleted    35%\rCompleted  35.1%\rCompleted  35.2%\rCompleted  35.3%\rCompleted  35.4%\rCompleted  35.5%\rCompleted  35.6%\rCompleted  35.7%\rCompleted  35.8%\rCompleted  35.9%\rCompleted    36%\rCompleted  36.1%\rCompleted  36.2%\rCompleted  36.3%\rCompleted  36.4%\rCompleted   100% 15.2%\rCompleted  15.3%\rCompleted  15.4%\rCompleted  15.5%\rCompleted  15.6%\rCompleted   100%	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/job_results/1_ipsm/ipsm_xc_som01.tif; 空间推测不确定性: /onesis/kt4/job_results/1_ipsm/ipsm_xc_unc01.tif; 剖面曲率: /onesis/kt4/job_results/1_ipsm/o1871811289601409024.tif; 平面曲率: /onesis/kt4/job_results/1_ipsm/plan1871811289718849536.tif; 坡向: /onesis/kt4/job_results/1_ipsm/o1871811289827901440.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1871811290503184384.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81871811289936953344.tif; 水动力指数: /onesis/kt4/job_results/1_ipsm/o1871811290633207808.tif; DEM栅格: /onesis/kt4/job_results/1_ipsm/fel1871811289551077376.tif; 汇聚指数: /onesis/kt4/job_results/1_ipsm/RESULT1871811290293469184.tif; 	\N	6	0301a9b8-87c9-4a74-8207-d9fd9088c5b7
2ed6ab6c3b0b40e5b0d3a5501b9d9fe5		2024-12-25 15:24:22.85379	2024-12-25 15:23:59.069628	{"sca":"/onesis/kt4/results/ad81871819159311089664.tif","slp":"/onesis/kt4/results/sd81871819159407558656.tif","twi":"/onesis/kt4/results/rst-202412251523.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/results/sd81871819159407558656.tif has geographic coordinate system.\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nInput file /data/onesis/kt4/results/ad81871819159311089664.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.038108\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	地形湿度指数: /onesis/kt4/results/rst-202412251523.tif; 汇流累积量: /onesis/kt4/results/ad81871819159311089664.tif; 坡度: /onesis/kt4/results/sd81871819159407558656.tif; 	\N	6	7ad44567-dbab-468b-aac1-0c2cfc813e44
e1cdffbfdaa042d6a7fa281088d0fda1		2024-12-25 15:24:17.709219	2024-12-25 15:23:59.206139	{"p":"/onesis/kt4/results/p1871819159264952320.tif","ad8":"/onesis/kt4/results/ad81871819159311089664.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/results/p1871819159264952320.tif has geographic coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.162465\nCompute time: 0.304853\nWrite time: 0.072962\nTotal time: 0.540280\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/results/p1871819159264952320.tif; d8汇流累积量栅格: /onesis/kt4/results/ad81871819159311089664.tif; 	\N	6	7ad44567-dbab-468b-aac1-0c2cfc813e44
1b1f90182c2241f2bf5835e07f23a5cf		2024-12-25 15:24:12.353044	2024-12-25 15:23:59.235019	{"sd8":"/onesis/kt4/results/sd81871819159407558656.tif","fel":"/onesis/kt4/results/fel1871819159214620672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871819159214620672.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.064565\nData read time: 0.178502\nCompute Slope time: 0.374609\nWrite Slope time: 0.121672\nResolve Flat time: 2.608929\nWrite Flat time: 0.051676\nTotal time: 3.399952\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/results/fel1871819159214620672.tif; 坡度栅格: /onesis/kt4/results/sd81871819159407558656.tif; 	\N	6	7ad44567-dbab-468b-aac1-0c2cfc813e44
e0748a45a60b496e905cb88113cec968		2024-12-25 15:28:07.9089	2024-12-25 15:28:02.861245	{"z":"/onesis/kt4/dem/dem_meixi.tif","fel":"/onesis/kt4/results/fel1871820181416837120.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dem/dem_meixi.tif has geographic coordinate system.\nNodata value input to create partition from file: 32767.000000\nNodata value recast to float used in partition raster: 32767.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.140868\nData read time: 0.080884\nCompute time: 0.339113\nWrite time: 0.094697\nTotal time: 0.655562\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dem/dem_meixi.tif; 数字高程模型: /onesis/kt4/results/fel1871820181416837120.tif; 	\N	6	7af1abc5-978d-403b-ad32-bbecd75132e7
859878aa044c4a688607d05ee250c6a6		2024-12-25 15:28:15.873334	2024-12-25 15:28:02.830689	{"p":"/onesis/kt4/results/p1871820181471363072.tif","fel":"/onesis/kt4/results/fel1871820181416837120.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871820181416837120.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.089565\nData read time: 0.180743\nCompute Slope time: 0.430041\nWrite Slope time: 0.110843\nResolve Flat time: 2.522700\nWrite Flat time: 0.047216\nTotal time: 3.381108\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/results/fel1871820181416837120.tif; D8单流向栅格: /onesis/kt4/results/p1871820181471363072.tif; 	\N	6	7af1abc5-978d-403b-ad32-bbecd75132e7
cf8f96d754dc4ec4af37f5afadfa92ef		2024-12-25 15:28:15.861495	2024-12-25 15:28:02.803851	{"sd8":"/onesis/kt4/results/sd81871820181630746624.tif","fel":"/onesis/kt4/results/fel1871820181416837120.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871820181416837120.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.071305\nData read time: 0.184417\nCompute Slope time: 0.413596\nWrite Slope time: 0.131541\nResolve Flat time: 2.533670\nWrite Flat time: 0.049972\nTotal time: 3.384502\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/results/fel1871820181416837120.tif; 坡度栅格: /onesis/kt4/results/sd81871820181630746624.tif; 	\N	6	7af1abc5-978d-403b-ad32-bbecd75132e7
2448c5b53eb84176a2a7ef3ae2cd355c		2024-12-25 15:30:13.437059	2024-12-25 15:30:08.787797	{"z":"/onesis/kt4/dem/dem_meixi.tif","fel":"/onesis/kt4/results/fel1871820709534236672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dem/dem_meixi.tif has geographic coordinate system.\nNodata value input to create partition from file: 32767.000000\nNodata value recast to float used in partition raster: 32767.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.049970\nData read time: 0.067652\nCompute time: 0.309109\nWrite time: 0.095296\nTotal time: 0.522028\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dem/dem_meixi.tif; 数字高程模型: /onesis/kt4/results/fel1871820709534236672.tif; 	\N	6	78d1ab87-9334-4ee6-8ff7-93dcb6ab4baa
0f3c98d11a5d4f51be491f6f859c4e40		2024-12-25 15:28:26.305153	2024-12-25 15:28:02.731983	{"sca":"/onesis/kt4/results/ad81871820181525889024.tif","slp":"/onesis/kt4/results/sd81871820181630746624.tif","twi":"/onesis/kt4/results/rst-20241225.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/results/sd81871820181630746624.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/results/ad81871820181525889024.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.047221\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	地形湿度指数: /onesis/kt4/results/rst-20241225.tif; 汇流累积量: /onesis/kt4/results/ad81871820181525889024.tif; 坡度: /onesis/kt4/results/sd81871820181630746624.tif; 	\N	6	7af1abc5-978d-403b-ad32-bbecd75132e7
c93da586dd3f4cc8b9860d363488ce3a		2024-12-25 15:30:21.384724	2024-12-25 15:30:08.726695	{"sd8":"/onesis/kt4/results/sd81871820709748146176.tif","fel":"/onesis/kt4/results/fel1871820709534236672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871820709534236672.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.065437\nData read time: 0.179033\nCompute Slope time: 0.364143\nWrite Slope time: 0.117754\nResolve Flat time: 2.533544\nWrite Flat time: 0.049899\nTotal time: 3.309809\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/results/fel1871820709534236672.tif; 坡度栅格: /onesis/kt4/results/sd81871820709748146176.tif; 	\N	6	78d1ab87-9334-4ee6-8ff7-93dcb6ab4baa
aea20e71f9d749afa08648fa19d64a7a		2024-12-25 15:30:26.73738	2024-12-25 15:30:08.690216	{"p":"/onesis/kt4/results/p1871820709588762624.tif","ad8":"/onesis/kt4/results/ad81871820709643288576.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/results/p1871820709588762624.tif has geographic coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.114548\nCompute time: 0.298881\nWrite time: 0.072914\nTotal time: 0.486343\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/results/p1871820709588762624.tif; d8汇流累积量栅格: /onesis/kt4/results/ad81871820709643288576.tif; 	\N	6	78d1ab87-9334-4ee6-8ff7-93dcb6ab4baa
e52a504a230a4960ab50345f26a5cd29		2024-12-25 15:30:21.396672	2024-12-25 15:30:08.756645	{"p":"/onesis/kt4/results/p1871820709588762624.tif","fel":"/onesis/kt4/results/fel1871820709534236672.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/results/fel1871820709534236672.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.084279\nData read time: 0.153573\nCompute Slope time: 0.392242\nWrite Slope time: 0.108359\nResolve Flat time: 2.490477\nWrite Flat time: 0.043870\nTotal time: 3.272800\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/results/fel1871820709534236672.tif; D8单流向栅格: /onesis/kt4/results/p1871820709588762624.tif; 	\N	6	78d1ab87-9334-4ee6-8ff7-93dcb6ab4baa
1b0441317c504598b1344d4a88d529ed		2024-12-25 15:30:31.836727	2024-12-25 15:30:08.649556	{"sca":"/onesis/kt4/results/ad81871820709643288576.tif","slp":"/onesis/kt4/results/sd81871820709748146176.tif","twi":"/onesis/kt4/results/202412251530.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/results/sd81871820709748146176.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/results/ad81871820709643288576.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.037364\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	地形湿度指数: /onesis/kt4/results/202412251530.tif; 汇流累积量: /onesis/kt4/results/ad81871820709643288576.tif; 坡度: /onesis/kt4/results/sd81871820709748146176.tif; 	\N	6	78d1ab87-9334-4ee6-8ff7-93dcb6ab4baa
37fd657c65894135ae16271b97e84223		\N	2025-01-05 20:05:44.405365	{"p":"/onesis/kt4/xuancheng/result/p1875876330533421056.tif","ad8":"/onesis/kt4/xuancheng/result/ad81875876330583752704.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/xuancheng/result/p1875876330533421056.tif; d8汇流累积量栅格: /onesis/kt4/xuancheng/result/ad81875876330583752704.tif; 	\N	0	2cf6be48-1562-40b9-a416-ef2ce4ac609f
987b76481c3c469db9c6ff6943f15d79		2024-12-25 22:13:47.761507	2024-12-25 22:12:59.656986	{"p":"/onesis/kt4/dsm_case/xuancheng/p1871922055398686720.tif","ad8":"/onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/p1871922055398686720.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.409161\nCompute time: 0.113222\nWrite time: 0.107392\nTotal time: 0.629775\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/dsm_case/xuancheng/p1871922055398686720.tif; d8汇流累积量栅格: /onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
f35cd9ee534a4c30885761b67eed771b		2024-12-25 22:13:07.168148	2024-12-25 22:12:59.455402	{"z":"/onesis/kt4/dsm_case/dem_xc.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/dem_xc.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.102157\nData read time: 0.333567\nCompute time: 0.087903\nWrite time: 0.165292\nTotal time: 0.688919\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/dem_xc.tif; 数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
0948b501e55a4b1ab28ca2bae14135bd		2024-12-25 22:13:28.99467	2024-12-25 22:12:58.604097	{"zfactor":"1","i":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871922059064508416.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n****************************\n* Welcome to Aspect        *\n* Powered by WhiteboxTools *\n* www.whiteboxgeo.com      *\n****************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.27s\n	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	输入数据: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; z因子: 1; 输出数据: /onesis/kt4/dsm_case/xuancheng/o1871922059064508416.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
69fefbe94883492c93d3d77b15971d34		2024-12-25 22:19:01.798644	2024-12-25 22:18:51.7296	{"z":"/onesis/kt4/dsm_case/dem_xc.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/dem_xc.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.108144\nData read time: 0.624602\nCompute time: 0.117463\nWrite time: 0.353653\nTotal time: 1.203862\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/dem_xc.tif; 数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
ecdafae5bc5f442189e215a3fca571cb		2024-12-25 22:19:35.901975	2024-12-25 22:18:50.747665	{"zfactor":"1","i":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871923535111389184.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n****************************\n* Welcome to Aspect        *\n* Powered by WhiteboxTools *\n* www.whiteboxgeo.com      *\n****************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.397s\n	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	输入数据: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; z因子: 1; 输出数据: /onesis/kt4/dsm_case/xuancheng/o1871923535111389184.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
1889126f4f094666b50544741521aef5		2024-12-25 22:19:32.200601	2024-12-25 22:18:50.915193	{"fel":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif","plan":"/onesis/kt4/dsm_case/xuancheng/plan1871923534234779648.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nCurvature -h version 5.3.9, by Liangjun Zhu, Apr 8, 2015\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nProcessors: 1\nRead time: 7.488454\nCompute time: 0.997378\nWrite time: 5.793698\nTotal time: 14.279529\n	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 平面曲率栅格: /onesis/kt4/dsm_case/xuancheng/plan1871923534234779648.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
4148b8b982b3447cbc97dfee95ecf753		2024-12-25 22:13:20.298767	2024-12-25 22:12:58.775152	{"fel":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif","plan":"/onesis/kt4/dsm_case/xuancheng/plan1871922058208870400.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nCurvature -h version 5.3.9, by Liangjun Zhu, Apr 8, 2015\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nProcessors: 1\nRead time: 1.941599\nCompute time: 0.051925\nWrite time: 0.436633\nTotal time: 2.430157\n	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 平面曲率栅格: /onesis/kt4/dsm_case/xuancheng/plan1871922058208870400.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
0f4bb8cc482c4404bbb64e36ff3ed700		\N	2024-12-25 22:12:58.912864	{"i":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871922057487450112.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to ProfileCurvature *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.10s\n	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	输入栅格 DEM 文件: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 输出栅格文件: /onesis/kt4/dsm_case/xuancheng/o1871922057487450112.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
c5587106590240cfa0da3f982fa6f504		2024-12-25 22:19:36.499833	2024-12-25 22:18:51.137741	{"i":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871923533588856832.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to ProfileCurvature *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nPerforming analysis: 0%\nPerforming analysis: 1%\nPerforming analysis: 2%\nPerforming analysis: 3%\nPerforming analysis: 4%\nPerforming analysis: 5%\nPerforming analysis: 6%\nPerforming analysis: 7%\nPerforming analysis: 8%\nPerforming analysis: 9%\nPerforming analysis: 10%\nPerforming analysis: 11%\nPerforming analysis: 12%\nPerforming analysis: 13%\nPerforming analysis: 14%\nPerforming analysis: 15%\nPerforming analysis: 16%\nPerforming analysis: 17%\nPerforming analysis: 18%\nPerforming analysis: 19%\nPerforming analysis: 20%\nPerforming analysis: 21%\nPerforming analysis: 22%\nPerforming analysis: 23%\nPerforming analysis: 24%\nPerforming analysis: 25%\nPerforming analysis: 26%\nPerforming analysis: 27%\nPerforming analysis: 28%\nPerforming analysis: 29%\nPerforming analysis: 30%\nPerforming analysis: 31%\nPerforming analysis: 32%\nPerforming analysis: 33%\nPerforming analysis: 34%\nPerforming analysis: 35%\nPerforming analysis: 36%\nPerforming analysis: 37%\nPerforming analysis: 38%\nPerforming analysis: 39%\nPerforming analysis: 40%\nPerforming analysis: 41%\nPerforming analysis: 42%\nPerforming analysis: 43%\nPerforming analysis: 44%\nPerforming analysis: 45%\nPerforming analysis: 46%\nPerforming analysis: 47%\nPerforming analysis: 48%\nPerforming analysis: 49%\nPerforming analysis: 50%\nPerforming analysis: 51%\nPerforming analysis: 52%\nPerforming analysis: 53%\nPerforming analysis: 54%\nPerforming analysis: 55%\nPerforming analysis: 56%\nPerforming analysis: 57%\nPerforming analysis: 58%\nPerforming analysis: 59%\nPerforming analysis: 60%\nPerforming analysis: 61%\nPerforming analysis: 62%\nPerforming analysis: 63%\nPerforming analysis: 64%\nPerforming analysis: 65%\nPerforming analysis: 66%\nPerforming analysis: 67%\nPerforming analysis: 68%\nPerforming analysis: 69%\nPerforming analysis: 70%\nPerforming analysis: 71%\nPerforming analysis: 72%\nPerforming analysis: 73%\nPerforming analysis: 74%\nPerforming analysis: 75%\nPerforming analysis: 76%\nPerforming analysis: 77%\nPerforming analysis: 78%\nPerforming analysis: 79%\nPerforming analysis: 80%\nPerforming analysis: 81%\nPerforming analysis: 82%\nPerforming analysis: 83%\nPerforming analysis: 84%\nPerforming analysis: 85%\nPerforming analysis: 86%\nPerforming analysis: 87%\nPerforming analysis: 88%\nPerforming analysis: 89%\nPerforming analysis: 90%\nPerforming analysis: 91%\nPerforming analysis: 92%\nPerforming analysis: 93%\nPerforming analysis: 94%\nPerforming analysis: 95%\nPerforming analysis: 96%\nPerforming analysis: 97%\nPerforming analysis: 98%\nPerforming analysis: 99%\nPerforming analysis: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.296s\n	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	输入栅格 DEM 文件: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 输出栅格文件: /onesis/kt4/dsm_case/xuancheng/o1871923533588856832.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
31785594bda245288af5eba35a1e4699		2024-12-25 22:13:45.251006	2024-12-25 22:12:59.250879	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif","METHOD":"0","RESULT":"/onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n____________________________\n\n   #####   ##   #####    ##\n  ###     ###  ##       ###\n   ###   # ## ##  #### # ##\n    ### ##### ##    # #####\n ##### #   ##  ##### #   ##\n____________________________\n\nSAGA Version: 8.1.0\n\n____________________________\nlibrary path: /usr/local/lib/saga/\nlibrary name: libta_morphometry\nlibrary     : ta_morphometry\ntool        : Convergence Index\nidentifier  : 1\nauthor      : O.Conrad (c) 2001\nprocessors  : 16 [16]\n____________________________\n\nloading: fel1871922054098452480\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%[Convergence Index] Execution started...\n\n__________\n[Convergence Index] Parameters:\n\nGrid System: 90; 1242x 928y; 640437.684x 3381957.072204y\nElevation: fel1871922054098452480\nConvergence Index: Convergence Index\nMethod: Aspect\nGradient Calculation: 2 x 2\n\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\r101%\n__________\ntotal execution time: 26000 milliseconds (26s)\n\n[Convergence Index] Execution succeeded (26s)\nSaving grid: /data/onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif...\nExport GeoTIFF\n\n__________\n[Export GeoTIFF] Parameters:\n\nGrid System: 90; 1242x 928y; 640437.684x 3381957.072204y\nGrid(s): 1 object (RESULT1871922054748569600)\nFile: /data/onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif\nCreation Options: \n\nBand 1\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\n[Export GeoTIFF] execution time: 01s\nokay\n	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 计算方式: 0; 邻域窗口大小: 0; 地形结构指数: /onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
5f5ef812bc1c4281931d28e3dfe338a0		2024-12-26 11:10:32.329271	2024-12-26 11:10:23.527612	{"op":"/onesis/kt4/dsm_case/2024_12_25/out/op1872117707936235520.tif","width":"424","sfp":"/onesis/kt4/dsm_case/2024_12_25/road_Priolo.shp","height":"317"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n欧氏距离分析完成，结果保存为 /data/onesis/kt4/dsm_case/2024_12_25/out/op1872117707936235520.tif\n	827a0ed4-eb81-3cd5-b84f-871166368115	欧氏距离分析	输入文件: /onesis/kt4/dsm_case/2024_12_25/road_Priolo.shp; 图像宽度: 424; 图像高度: 317; 输出文件: /onesis/kt4/dsm_case/2024_12_25/out/op1872117707936235520.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
dc7692876ebe46af97b998190d0c968f		2024-12-26 11:10:55.957193	2024-12-26 11:10:24.162525	{"ssa":"/onesis/kt4/dsm_case/2024_12_25/out/ad81872117709748174848.tif","src":"/onesis/kt4/dsm_case/2024_12_25/out/src1872117710134050816.tif","thresh":"2000.0"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nThreshold version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/ad81872117709748174848.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nCompute time: 0.000888\n	19a662d0-b39e-35cb-a063-0e1c13ee9e6b	河网提取（栅格）	d8汇流累积量栅格: /onesis/kt4/dsm_case/2024_12_25/out/ad81872117709748174848.tif; 阈值: 2000.0; 提取的河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/src1872117710134050816.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
786dff35e824411f913c59c829574798		2024-12-26 11:10:48.10185	2024-12-26 11:10:24.543822	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif","ad8":"/onesis/kt4/dsm_case/2024_12_25/out/ad81872117709748174848.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.106600\nCompute time: 0.009037\nWrite time: 0.061835\nTotal time: 0.177472\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif; d8汇流累积量栅格: /onesis/kt4/dsm_case/2024_12_25/out/ad81872117709748174848.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
8670da0abcf54eec856716bce0e84bee		\N	2025-01-05 17:32:19.987248	{"sca":"/onesis/kt4/xuancheng/result/ad81875837723831566336.tif","slope":"/onesis/kt4/xuancheng/result/sd81875837724427157504.tif","o":"/onesis/kt4/xuancheng/result/o1875837724527820800.tif"}	f	\N	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/xuancheng/result/ad81875837723831566336.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875837724527820800.tif; 输入坡度 slope 文件: /onesis/kt4/xuancheng/result/sd81875837724427157504.tif; 	\N	0	2b175d24-3d52-45a5-ac1b-446c73264fe6
23815089c70f430fa37f0c300f775cc3		2024-12-26 11:11:04.455872	2024-12-26 11:10:23.357457	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif","src":"/onesis/kt4/dsm_case/2024_12_25/out/src1872117710134050816.tif","dist":"/onesis/kt4/dsm_case/2024_12_25/out/dist1872117710389903360.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8DistDownToStream version 5.3.9, added by Liangjun Zhu, Apr 2, 2015\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/src1872117710134050816.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int32_t used in partition raster: -32768\nProcessors: 1\nRead time: 0.148504\nCompute time: 0.003935\nWrite time: 0.059983\nTotal time: 0.212422\n	99792477-6354-3e47-8097-07adbb5e11cb	至河流的距离计算	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif; D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif; 提取的河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/src1872117710134050816.tif; 至河网距离的栅格: /onesis/kt4/dsm_case/2024_12_25/out/dist1872117710389903360.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
94662ca21907455fbd78221015ea746d		2024-12-25 22:13:34.200309	2024-12-25 22:12:59.978552	{"p":"/onesis/kt4/dsm_case/xuancheng/p1871922055398686720.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 113218 flats to resolve.\nDraining flats towards lower adjacent terrain\n.................................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 2188\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.050547\nData read time: 2.103636\nCompute Slope time: 0.115574\nWrite Slope time: 0.029199\nResolve Flat time: 11.246036\nWrite Flat time: 0.813947\nTotal time: 14.358939\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; D8单流向栅格: /onesis/kt4/dsm_case/xuancheng/p1871922055398686720.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
bb92c012f8e14b2fa363f9b12bafe463		2024-12-26 11:31:32.414515	2024-12-26 11:31:23.583205	{"op":"/onesis/kt4/dsm_case/2024_12_25/out/op1872122997293318144.tif","width":"424","sfp":"/onesis/kt4/dsm_case/2024_12_25/road_Priolo.shp","height":"317"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n欧氏距离分析完成，结果保存为 /data/onesis/kt4/dsm_case/2024_12_25/out/op1872122997293318144.tif\n	827a0ed4-eb81-3cd5-b84f-871166368115	欧氏距离分析	输入文件: /onesis/kt4/dsm_case/2024_12_25/road_Priolo.shp; 图像宽度: 424; 图像高度: 317; 输出文件: /onesis/kt4/dsm_case/2024_12_25/out/op1872122997293318144.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
922c90de886f4bceb116063631d972a5		2024-12-26 11:31:49.744064	2024-12-26 11:31:24.659826	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif","ad8":"/onesis/kt4/dsm_case/2024_12_25/out/ad81872122999763763200.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.130427\nCompute time: 0.009307\nWrite time: 0.058083\nTotal time: 0.197817\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif; d8汇流累积量栅格: /onesis/kt4/dsm_case/2024_12_25/out/ad81872122999763763200.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
b9d2d12572d540a9b1537300f8e3676e		2024-12-25 22:13:38.297235	2024-12-25 22:12:58.494443	{"sd8":"/onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 113218 flats to resolve.\nDraining flats towards lower adjacent terrain\n.................................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 2188\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.154859\nData read time: 2.044806\nCompute Slope time: 0.098841\nWrite Slope time: 0.220454\nResolve Flat time: 14.134273\nWrite Flat time: 0.189330\nTotal time: 16.842564\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 坡度栅格: /onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
61f0a1ad47af466f8d506f0bc6c3221b		2024-12-26 10:48:57.649732	2024-12-26 10:45:49.94025	{"r":"liangping","c":"/onesis/kt4/test_data/basic/data/zxd_config.csv","d":"/onesis/kt4/test_data/basic/data/crop_data_n.csv","i":"/onesis/kt4/test_data/basic/data/o1872111542821060608.shp","o":"/onesis/kt4/test_data/basic/data/o1872111543215325184.shp"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\n	b3e67d4d-3b66-3f96-9875-cd036de39e95	添加物候置信度	输入矢量文件: /onesis/kt4/test_data/basic/data/o1872111542821060608.shp; 置信度配置文件: /onesis/kt4/test_data/basic/data/zxd_config.csv; 作物占比文件: /onesis/kt4/test_data/basic/data/crop_data_n.csv; 行政区域名称: liangping; 输出矢量文件: /onesis/kt4/test_data/basic/data/o1872111543215325184.shp; 	\N	6	f04369d5-50b1-4205-8980-07e28816c959
b0bbaefbc7fa45fa8bfcad9a029dbdeb		2024-12-25 22:13:59.514001	2024-12-25 22:12:59.051404	{"sca":"/onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif","slope":"/onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871922060352159744.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to StreamPowerIndex *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nProgress: 0%\nProgress: 1%\nProgress: 2%\nProgress: 3%\nProgress: 4%\nProgress: 5%\nProgress: 6%\nProgress: 7%\nProgress: 8%\nProgress: 9%\nProgress: 10%\nProgress: 11%\nProgress: 12%\nProgress: 13%\nProgress: 14%\nProgress: 15%\nProgress: 16%\nProgress: 17%\nProgress: 18%\nProgress: 19%\nProgress: 20%\nProgress: 21%\nProgress: 22%\nProgress: 23%\nProgress: 24%\nProgress: 25%\nProgress: 26%\nProgress: 27%\nProgress: 28%\nProgress: 29%\nProgress: 30%\nProgress: 31%\nProgress: 32%\nProgress: 33%\nProgress: 34%\nProgress: 35%\nProgress: 36%\nProgress: 37%\nProgress: 38%\nProgress: 39%\nProgress: 40%\nProgress: 41%\nProgress: 42%\nProgress: 43%\nProgress: 44%\nProgress: 45%\nProgress: 46%\nProgress: 47%\nProgress: 48%\nProgress: 49%\nProgress: 50%\nProgress: 51%\nProgress: 52%\nProgress: 53%\nProgress: 54%\nProgress: 55%\nProgress: 56%\nProgress: 57%\nProgress: 58%\nProgress: 59%\nProgress: 60%\nProgress: 61%\nProgress: 62%\nProgress: 63%\nProgress: 64%\nProgress: 65%\nProgress: 66%\nProgress: 67%\nProgress: 68%\nProgress: 69%\nProgress: 70%\nProgress: 71%\nProgress: 72%\nProgress: 73%\nProgress: 74%\nProgress: 75%\nProgress: 76%\nProgress: 77%\nProgress: 78%\nProgress: 79%\nProgress: 80%\nProgress: 81%\nProgress: 82%\nProgress: 83%\nProgress: 84%\nProgress: 85%\nProgress: 86%\nProgress: 87%\nProgress: 88%\nProgress: 89%\nProgress: 90%\nProgress: 91%\nProgress: 92%\nProgress: 93%\nProgress: 94%\nProgress: 95%\nProgress: 96%\nProgress: 97%\nProgress: 98%\nProgress: 99%\nProgress: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.6s\n	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif; 输入坡度 slope 文件: /onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif; 输出栅格文件: /onesis/kt4/dsm_case/xuancheng/o1871922060352159744.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
23280cf9bee242dabfe09b06b190b6b9		2024-12-25 22:13:58.340621	2024-12-25 22:12:58.32331	{"sca":"/onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif","slp":"/onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif","twi":"/onesis/kt4/dsm_case/xuancheng/twi1871922060872253440.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.011233\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif; 汇流累积量: /onesis/kt4/dsm_case/xuancheng/ad81871922055788756992.tif; 地形湿度指数: /onesis/kt4/dsm_case/xuancheng/twi1871922060872253440.tif; 	\N	6	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
ca38fdf5235846f5bde73a9f0506b9c5		2024-12-25 22:15:27.588986	2024-12-25 22:12:57.668347	{"inlayer3":"/onesis/kt4/dsm_case/xuancheng/o1871922059064508416.tif","inlayer2":"/onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif","inlayer1":"/onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif","inlayer0":"/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif","inlayer7":"/onesis/kt4/dsm_case/xuancheng/twi1871922060872253440.tif","inlayer6":"/onesis/kt4/dsm_case/xuancheng/o1871922060352159744.tif","inlayer5":"/onesis/kt4/dsm_case/xuancheng/o1871922057487450112.tif","simithred":"0.3","inlayer4":"/onesis/kt4/dsm_case/xuancheng/plan1871922058208870400.tif","sample":"/onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv","target":"SOM","uncmap":"/onesis/kt4/dsm_case/xuancheng/ipsm1225_unc.tif","predmap":"/onesis/kt4/dsm_case/xuancheng/ipsm1225_pre.tif"}	f	Pod Status: Running\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif\nLoading data ...\nTransformation operator() function called.\ncompute layer size: 93 125\nrank 0. avg compt load: 171972\nInput parameter error. Target name does not exist in the file.\nInput parameter error. Target name does not exist in the file.\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 3 in communicator MPI_COMM_WORLD\nwith errorcode -1.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nInput parameter error. Target name does not exist in the file.\n[ca38fdf5235846f5bde73a9f0506b9c5-654xz:00007] 2 more processes have sent help message help-mpi-api.txt / mpi-abort\n[ca38fdf5235846f5bde73a9f0506b9c5-654xz:00007] Set MCA parameter "orte_base_help_aggregate" to 0 to see all help / error messages\n/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/dsm_case/xuancheng/ipsm1225_pre.tif; 空间推测不确定性: /onesis/kt4/dsm_case/xuancheng/ipsm1225_unc.tif; DEM栅格: /onesis/kt4/dsm_case/xuancheng/fel1871922054098452480.tif; 汇聚指数: /onesis/kt4/dsm_case/xuancheng/RESULT1871922054748569600.tif; 水动力指数: /onesis/kt4/dsm_case/xuancheng/o1871922060352159744.tif; 地形湿度指数: /onesis/kt4/dsm_case/xuancheng/twi1871922060872253440.tif; 剖面曲率: /onesis/kt4/dsm_case/xuancheng/o1871922057487450112.tif; 平面曲率: /onesis/kt4/dsm_case/xuancheng/plan1871922058208870400.tif; 坡向: /onesis/kt4/dsm_case/xuancheng/o1871922059064508416.tif; 坡度栅格: /onesis/kt4/dsm_case/xuancheng/sd81871922059769151488.tif; 	\N	7	4c9f86f5-2c8c-4c47-b34e-c28f4ee0279e
422a7ec30297450cb5e00701a1f57afa		2024-12-25 22:20:12.007164	2024-12-25 22:18:51.30422	{"sca":"/onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif","slope":"/onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif","o":"/onesis/kt4/dsm_case/xuancheng/o1871923536763944960.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to StreamPowerIndex *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nProgress: 0%\nProgress: 1%\nProgress: 2%\nProgress: 3%\nProgress: 4%\nProgress: 5%\nProgress: 6%\nProgress: 7%\nProgress: 8%\nProgress: 9%\nProgress: 10%\nProgress: 11%\nProgress: 12%\nProgress: 13%\nProgress: 14%\nProgress: 15%\nProgress: 16%\nProgress: 17%\nProgress: 18%\nProgress: 19%\nProgress: 20%\nProgress: 21%\nProgress: 22%\nProgress: 23%\nProgress: 24%\nProgress: 25%\nProgress: 26%\nProgress: 27%\nProgress: 28%\nProgress: 29%\nProgress: 30%\nProgress: 31%\nProgress: 32%\nProgress: 33%\nProgress: 34%\nProgress: 35%\nProgress: 36%\nProgress: 37%\nProgress: 38%\nProgress: 39%\nProgress: 40%\nProgress: 41%\nProgress: 42%\nProgress: 43%\nProgress: 44%\nProgress: 45%\nProgress: 46%\nProgress: 47%\nProgress: 48%\nProgress: 49%\nProgress: 50%\nProgress: 51%\nProgress: 52%\nProgress: 53%\nProgress: 54%\nProgress: 55%\nProgress: 56%\nProgress: 57%\nProgress: 58%\nProgress: 59%\nProgress: 60%\nProgress: 61%\nProgress: 62%\nProgress: 63%\nProgress: 64%\nProgress: 65%\nProgress: 66%\nProgress: 67%\nProgress: 68%\nProgress: 69%\nProgress: 70%\nProgress: 71%\nProgress: 72%\nProgress: 73%\nProgress: 74%\nProgress: 75%\nProgress: 76%\nProgress: 77%\nProgress: 78%\nProgress: 79%\nProgress: 80%\nProgress: 81%\nProgress: 82%\nProgress: 83%\nProgress: 84%\nProgress: 85%\nProgress: 86%\nProgress: 87%\nProgress: 88%\nProgress: 89%\nProgress: 90%\nProgress: 91%\nProgress: 92%\nProgress: 93%\nProgress: 94%\nProgress: 95%\nProgress: 96%\nProgress: 97%\nProgress: 98%\nProgress: 99%\nProgress: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.4s\n	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif; 输入坡度 slope 文件: /onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif; 输出栅格文件: /onesis/kt4/dsm_case/xuancheng/o1871923536763944960.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
2e333e5a2f4c42b28e3fa13176964789		2024-12-25 22:19:43.993445	2024-12-25 22:18:50.618455	{"sd8":"/onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 113218 flats to resolve.\nDraining flats towards lower adjacent terrain\n.................................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 2188\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.080117\nData read time: 4.555938\nCompute Slope time: 0.083602\nWrite Slope time: 2.456427\nResolve Flat time: 18.790025\nWrite Flat time: 0.107806\nTotal time: 26.073915\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 坡度栅格: /onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
d34abd15997346e29a7248828713d4e3		\N	2024-12-25 22:18:52.403659	{"p":"/onesis/kt4/dsm_case/xuancheng/p1871923531403624448.tif","fel":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 113218 flats to resolve.\nDraining flats towards lower adjacent terrain\n.................................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 2188\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.122492\nData read time: 4.613993\nCompute Slope time: 0.093646\nWrite Slope time: 0.029855\nResolve Flat time: 16.103832\nWrite Flat time: 1.101818\nTotal time: 22.065635\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; D8单流向栅格: /onesis/kt4/dsm_case/xuancheng/p1871923531403624448.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
8729d810595c4814b11add8e7a1dbc10		2024-12-25 22:19:59.996258	2024-12-25 22:18:51.503003	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif","METHOD":"0","RESULT":"/onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n____________________________\n\n   #####   ##   #####    ##\n  ###     ###  ##       ###\n   ###   # ## ##  #### # ##\n    ### ##### ##    # #####\n ##### #   ##  ##### #   ##\n____________________________\n\nSAGA Version: 8.1.0\n\n____________________________\nlibrary path: /usr/local/lib/saga/\nlibrary name: libta_morphometry\nlibrary     : ta_morphometry\ntool        : Convergence Index\nidentifier  : 1\nauthor      : O.Conrad (c) 2001\nprocessors  : 16 [16]\n____________________________\n\nloading: fel1871923530099195904\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%[Convergence Index] Execution started...\n\n__________\n[Convergence Index] Parameters:\n\nGrid System: 90; 1242x 928y; 640437.684x 3381957.072204y\nElevation: fel1871923530099195904\nConvergence Index: Convergence Index\nMethod: Aspect\nGradient Calculation: 2 x 2\n\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\r101%\n__________\ntotal execution time: 41000 milliseconds (41s)\n\n[Convergence Index] Execution succeeded (41s)\nSaving grid: /data/onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif...\nExport GeoTIFF\n\n__________\n[Export GeoTIFF] Parameters:\n\nGrid System: 90; 1242x 928y; 640437.684x 3381957.072204y\nGrid(s): 1 object (RESULT1871923530753507328)\nFile: /data/onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif\nCreation Options: \n\nBand 1\n\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\r  1%\r  2%\r  3%\r  4%\r  5%\r  6%\r  7%\r  8%\r  9%\r 10%\r 11%\r 12%\r 13%\r 14%\r 15%\r 16%\r 17%\r 18%\r 19%\r 20%\r 21%\r 22%\r 23%\r 24%\r 25%\r 26%\r 27%\r 28%\r 29%\r 30%\r 31%\r 32%\r 33%\r 34%\r 35%\r 36%\r 37%\r 38%\r 39%\r 40%\r 41%\r 42%\r 43%\r 44%\r 45%\r 46%\r 47%\r 48%\r 49%\r 50%\r 51%\r 52%\r 53%\r 54%\r 55%\r 56%\r 57%\r 58%\r 59%\r 60%\r 61%\r 62%\r 63%\r 64%\r 65%\r 66%\r 67%\r 68%\r 69%\r 70%\r 71%\r 72%\r 73%\r 74%\r 75%\r 76%\r 77%\r 78%\r 79%\r 80%\r 81%\r 82%\r 83%\r 84%\r 85%\r 86%\r 87%\r 88%\r 89%\r 90%\r 91%\r 92%\r 93%\r 94%\r 95%\r 96%\r 97%\r 98%\r 99%\r100%\n\n[Export GeoTIFF] execution time: 01s\nokay\n	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	数字高程模型: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 计算方式: 0; 邻域窗口大小: 0; 地形结构指数: /onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
7d746de0841445e99bab8f864e00183b		2024-12-25 22:20:00.448914	2024-12-25 22:18:51.994468	{"p":"/onesis/kt4/dsm_case/xuancheng/p1871923531403624448.tif","ad8":"/onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/p1871923531403624448.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.410980\nCompute time: 0.114103\nWrite time: 0.144201\nTotal time: 0.669285\n	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/dsm_case/xuancheng/p1871923531403624448.tif; d8汇流累积量栅格: /onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
9dec752ecaf24b258828ca856c8f18fa		2024-12-25 22:20:10.041425	2024-12-25 22:18:50.427032	{"sca":"/onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif","slp":"/onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif","twi":"/onesis/kt4/dsm_case/xuancheng/twi1871923537565057024.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.012596\n	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif; 汇流累积量: /onesis/kt4/dsm_case/xuancheng/ad81871923531793694720.tif; 地形湿度指数: /onesis/kt4/dsm_case/xuancheng/twi1871923537565057024.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
a0ab563b17094f5399eb813612570d7c		2024-12-25 22:20:48.51072	2024-12-25 22:18:49.326469	{"inlayer3":"/onesis/kt4/dsm_case/xuancheng/o1871923535111389184.tif","inlayer2":"/onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif","inlayer1":"/onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif","inlayer0":"/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif","inlayer7":"/onesis/kt4/dsm_case/xuancheng/twi1871923537565057024.tif","inlayer6":"/onesis/kt4/dsm_case/xuancheng/o1871923536763944960.tif","inlayer5":"/onesis/kt4/dsm_case/xuancheng/o1871923533588856832.tif","simithred":"0.3","inlayer4":"/onesis/kt4/dsm_case/xuancheng/plan1871923534234779648.tif","sample":"/onesis/kt4/dsm_case/xuancheng/xuancheng_samples.csv","target":"SOM","uncmap":"/onesis/kt4/dsm_case/xuancheng/ipsm1225_unc.tif","predmap":"/onesis/kt4/dsm_case/xuancheng/ipsm1225_pre.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif/data/onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif\nLoading data ...\nTransformation operator() function called.\ncompute layer size: 93 125\nrank 0. avg compt load: 171972\n\nRunning prediction method 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25.1%\rCompleted  25.2%\rCompleted  25.3%\rCompleted  25.4%\rCompleted  25.5%\rCompleted  25.6%\rCompleted  25.7%\rCompleted  25.8%\rCompleted  25.9%\rCompleted    26%\rCompleted  26.1%\rCompleted  26.2%\rCompleted  26.3%\rCompleted  26.4%\rCompleted  26.5%\rCompleted  26.6%\rCompleted  26.7%\rCompleted  26.8%\rCompleted  26.9%\rCompleted    27%\rCompleted  27.1%\rCompleted  27.2%\rCompleted  27.3%\rCompleted  27.4%\rCompleted  27.5%\rCompleted  27.6%\rCompleted  27.7%\rCompleted  27.8%\rCompleted  27.9%\rCompleted    28%\rCompleted  28.1%\rCompleted  28.2%\rCompleted  28.3%\rCompleted  28.4%\rCompleted  28.5%\rCompleted  28.6%\rCompleted  28.7%\rCompleted  28.8%\rCompleted  28.9%\rCompleted    29%\rCompleted  29.1%\rCompleted  29.2%\rCompleted  29.3%\rCompleted  29.4%\rCompleted  29.5%\rCompleted  29.6%\rCompleted  29.7%\rCompleted  29.8%\rCompleted  29.9%\rCompleted    30%\rCompleted  30.1%\rCompleted  30.2%\rCompleted  30.3%\rCompleted  30.4%\rCompleted  30.5%\rCompleted  30.6%\rCompleted  30.7%\rCompleted  30.8%\rCompleted  30.9%\rCompleted    31%\rCompleted  31.1%\rCompleted  31.2%\rCompleted  31.3%\rCompleted  31.4%\rCompleted  31.5%\rCompleted  31.6%\rCompleted  31.7%\rCompleted  31.8%\rCompleted  31.9%\rCompleted    32%\rCompleted  32.1%\rCompleted  32.2%\rCompleted  32.3%\rCompleted  32.4%\rCompleted  32.5%\rCompleted  32.6%\rCompleted  32.7%\rCompleted  32.8%\rCompleted  32.9%\rCompleted    33%\rCompleted  33.1%\rCompleted  33.2%\rCompleted  33.3%\rCompleted  24.2%\rCompleted  24.3%\rCompleted  24.4%\rCompleted  24.5%\rCompleted  24.6%\rCompleted  24.7%\rCompleted  24.8%\rCompleted  24.9%\rCompleted    25%\rCompleted  25.1%\rCompleted  25.2%\rCompleted  25.3%\rCompleted  25.4%\rCompleted  25.5%\rCompleted  25.6%\rCompleted  25.7%\rCompleted  25.8%\rCompleted  25.9%\rCompleted    26%\rCompleted  26.1%\rCompleted  26.2%\rCompleted  26.3%\rCompleted  26.4%\rCompleted  26.5%\rCompleted  26.6%\rCompleted  26.7%\rCompleted  26.8%\rCompleted  26.9%\rCompleted    27%\rCompleted  27.1%\rCompleted  27.2%\rCompleted  27.3%\rCompleted  27.4%\rCompleted  27.5%\rCompleted  27.6%\rCompleted  27.7%\rCompleted  27.8%\rCompleted  27.9%\rCompleted    28%\rCompleted  28.1%\rCompleted  28.2%\rCompleted  28.3%\rCompleted  28.4%\rCompleted  28.5%\rCompleted  28.6%\rCompleted  28.7%\rCompleted  28.8%\rCompleted  28.9%\rCompleted    29%\rCompleted  29.1%\rCompleted  29.2%\rCompleted  29.3%\rCompleted  29.4%\rCompleted  29.5%\rCompleted  29.6%\rCompleted  29.7%\rCompleted  29.8%\rCompleted  29.9%\rCompleted    30%\rCompleted   100%\nWrite out result ...\n\nProcesses:4\n    Read time:28.291535\n    Compute time:1.240548\n    Write time:0.000000\n 15.2%\rCompleted  15.3%\rCompleted  15.4%\rCompleted  15.5%\rCompleted  15.6%\rCompleted  15.7%\rCompleted  15.8%\rCompleted  15.9%\rCompleted    16%\rCompleted   100%%\rCompleted  33.4%\rCompleted  33.5%\rCompleted  33.6%\rCompleted  33.7%\rCompleted  33.8%\rCompleted  33.9%\rCompleted    34%\rCompleted  34.1%\rCompleted  34.2%\rCompleted  34.3%\rCompleted  34.4%\rCompleted  34.5%\rCompleted  34.6%\rCompleted  34.7%\rCompleted  34.8%\rCompleted  34.9%\rCompleted    35%\rCompleted  35.1%\rCompleted  35.2%\rCompleted  35.3%\rCompleted  35.4%\rCompleted  35.5%\rCompleted   100% 15.2%\rCompleted  15.3%\rCompleted  15.4%\rCompleted  15.5%\rCompleted  15.6%\rCompleted  15.7%\rCompleted  15.8%\rCompleted  15.9%\rCompleted    16%\rCompleted  16.1%\rCompleted  16.2%\rCompleted  16.3%\rCompleted  16.4%\rCompleted  16.5%\rCompleted  16.6%\rCompleted  16.7%\rCompleted  16.8%\rCompleted  16.9%\rCompleted    17%\rCompleted  17.1%\rCompleted  17.2%\rCompleted  17.3%\rCompleted  17.4%\rCompleted  17.5%\rCompleted  17.6%\rCompleted  17.7%\rCompleted  17.8%\rCompleted  17.9%\rCompleted    18%\rCompleted  18.1%\rCompleted  18.2%\rCompleted  18.3%\rCompleted   100%	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/xuancheng/xuancheng_samples.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/dsm_case/xuancheng/ipsm1225_pre.tif; 空间推测不确定性: /onesis/kt4/dsm_case/xuancheng/ipsm1225_unc.tif; DEM栅格: /onesis/kt4/dsm_case/xuancheng/fel1871923530099195904.tif; 汇聚指数: /onesis/kt4/dsm_case/xuancheng/RESULT1871923530753507328.tif; 水动力指数: /onesis/kt4/dsm_case/xuancheng/o1871923536763944960.tif; 地形湿度指数: /onesis/kt4/dsm_case/xuancheng/twi1871923537565057024.tif; 剖面曲率: /onesis/kt4/dsm_case/xuancheng/o1871923533588856832.tif; 平面曲率: /onesis/kt4/dsm_case/xuancheng/plan1871923534234779648.tif; 坡向: /onesis/kt4/dsm_case/xuancheng/o1871923535111389184.tif; 坡度栅格: /onesis/kt4/dsm_case/xuancheng/sd81871923536109633536.tif; 	\N	6	0b108e5a-9bc2-45af-94a1-77e7eeb39b14
4582c630e271454bbe6e8956fcdcd4f3		2024-12-25 22:48:27.485705	2024-12-25 22:22:43.751381	{"c":"/onesis/kt4/test_data/basic/data/grade.csv","f":"land_dem","i":"/onesis/kt4/test_data/basic/data/input_wgs.shp","l":"middle","o":"/onesis/kt4/job_results/o1871924515873882112.str"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\nWarning 1: Value 1059.04999999999995 of field land_lengt of feature 14380 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1009.44000000000005 of field land_lengt of feature 14653 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1138.59999999999991 of field land_lengt of feature 14686 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1210.75999999999999 of field land_lengt of feature 14697 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1055.44000000000005 of field land_lengt of feature 14827 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1149.67000000000007 of field land_lengt of feature 15399 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1226.44000000000005 of field land_lengt of feature 18224 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1290.75999999999999 of field land_lengt of feature 18249 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1212.92000000000007 of field land_lengt of feature 19129 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1063.3599999999999 of field land_lengt of feature 19897 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1312.31999999999994 of field land_lengt of feature 20054 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1049.20000000000005 of field land_lengt of feature 21924 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1301.47000000000003 of field land_lengt of feature 21941 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1011.97000000000003 of field land_lengt of feature 22069 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1007.86000000000001 of field land_lengt of feature 22102 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1030.93000000000006 of field land_lengt of feature 27251 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1457.22000000000003 of field land_lengt of feature 28491 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1059.04999999999995 of field land_lengt of feature 14380 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1009.44000000000005 of field land_lengt of feature 14653 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1138.59999999999991 of field land_lengt of feature 14686 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1210.75999999999999 of field land_lengt of feature 14697 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1055.44000000000005 of field land_lengt of feature 14827 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1149.67000000000007 of field land_lengt of feature 15399 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1226.44000000000005 of field land_lengt of feature 18224 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1290.75999999999999 of field land_lengt of feature 18249 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1212.92000000000007 of field land_lengt of feature 19129 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1063.3599999999999 of field land_lengt of feature 19897 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1312.31999999999994 of field land_lengt of feature 20054 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1049.20000000000005 of field land_lengt of feature 21924 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1301.47000000000003 of field land_lengt of feature 21941 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1011.97000000000003 of field land_lengt of feature 22069 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1007.86000000000001 of field land_lengt of feature 22102 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1030.93000000000006 of field land_lengt of feature 27251 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1457.22000000000003 of field land_lengt of feature 28491 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\nmiddle\n	70050be4-e818-32e1-a631-c99d0d94d5de	添加物候信息	输入矢量文件: /onesis/kt4/test_data/basic/data/input_wgs.shp; 物候配置文件: /onesis/kt4/test_data/basic/data/grade.csv; 高程字段名: land_dem; 区域信息: middle; 输出矢量文件: /onesis/kt4/job_results/o1871924515873882112.str; 	\N	6	95a00467-da7f-42eb-988c-7496d1ecd64b
5d8d0c3782eb4d45bdf20ed4b7310134		2024-12-25 23:21:39.971106	2024-12-25 22:22:43.201872	{"c":"/onesis/kt4/test_data/basic/data/config.csv","t":"474069,302376,98444,394334","i":"/onesis/kt4/job_results/o1871924516071014400.str","z":"1,2,3,9","o":"/onesis/kt4/job_results/zw_result.shp"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTraceback (most recent call last):\n  File "/venv/lib/python3.9/runpy.py", line 239, in _get_main_module_details\n    return _get_module_details(main_name)\n  File "/venv/lib/python3.9/runpy.py", line 141, in _get_module_details\n    raise error("No module named %s" % mod_name)\nImportError: No module named __main__\n\nThe above exception was the direct cause of the following exception:\n\nTraceback (most recent call last):\n  File "/venv/lib/python3.9/runpy.py", line 190, in _run_module_as_main\n    mod_name, mod_spec, code = _get_main_module_details(_Error)\n  File "/venv/lib/python3.9/runpy.py", line 242, in _get_main_module_details\n    raise error("can't find %r module in %r" %\nrunpy._Error: can't find '__main__' module in '/data/onesis/kt4/job_results/o1871924516071014400.str'\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File "/venv/lib/python3.9/runpy.py", line 193, in _run_module_as_main\n    sys.exit(msg)\nSystemExit: /venv/bin/python: can't find '__main__' module in '/data/onesis/kt4/job_results/o1871924516071014400.str'\n>>> \n	3f83271b-4116-359e-9bd1-a4744506f0cd	地块面积赋值	输入矢量文件: /onesis/kt4/job_results/o1871924516071014400.str; 配置文件: /onesis/kt4/test_data/basic/data/config.csv; 要进行的操作索引: 1,2,3,9; 操作对应的面积阈值: 474069,302376,98444,394334; 输出矢量文件: /onesis/kt4/job_results/zw_result.shp; 	\N	6	95a00467-da7f-42eb-988c-7496d1ecd64b
4eb764468c5642abbbc17ea739b1e280		2024-12-25 23:22:22.164827	2024-12-25 22:22:43.472281	{"r":"liangping","c":"/onesis/kt4/test_data/basic/data/zxd_config.csv","d":"/onesis/kt4/test_data/basic/data/crop_data_n.csv","i":"/onesis/kt4/job_results/o1871924515873882112.str","o":"/onesis/kt4/job_results/o1871924516071014400.str"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\nWarning 1: Value 1059.04999999999995 of field land_lengt of feature 14380 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1009.44000000000005 of field land_lengt of feature 14653 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1138.59999999999991 of field land_lengt of feature 14686 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1210.75999999999999 of field land_lengt of feature 14697 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1055.44000000000005 of field land_lengt of feature 14827 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1149.67000000000007 of field land_lengt of feature 15399 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1226.44000000000005 of field land_lengt of feature 18224 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1290.75999999999999 of field land_lengt of feature 18249 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1212.92000000000007 of field land_lengt of feature 19129 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1063.3599999999999 of field land_lengt of feature 19897 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1312.31999999999994 of field land_lengt of feature 20054 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1049.20000000000005 of field land_lengt of feature 21924 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1301.47000000000003 of field land_lengt of feature 21941 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1011.97000000000003 of field land_lengt of feature 22069 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1007.86000000000001 of field land_lengt of feature 22102 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1030.93000000000006 of field land_lengt of feature 27251 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1457.22000000000003 of field land_lengt of feature 28491 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1059.04999999999995 of field land_lengt of feature 14380 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1059.04999999999995 of field land_lengt of feature 14380 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1009.44000000000005 of field land_lengt of feature 14653 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1009.44000000000005 of field land_lengt of feature 14653 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1138.59999999999991 of field land_lengt of feature 14686 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1138.59999999999991 of field land_lengt of feature 14686 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1210.75999999999999 of field land_lengt of feature 14697 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1210.75999999999999 of field land_lengt of feature 14697 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1055.44000000000005 of field land_lengt of feature 14827 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1055.44000000000005 of field land_lengt of feature 14827 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1149.67000000000007 of field land_lengt of feature 15399 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1149.67000000000007 of field land_lengt of feature 15399 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1032.8900000000001 of field land_lengt of feature 15842 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1212.92000000000007 of field land_lengt of feature 19129 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1212.92000000000007 of field land_lengt of feature 19129 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1063.3599999999999 of field land_lengt of feature 19897 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1063.3599999999999 of field land_lengt of feature 19897 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1312.31999999999994 of field land_lengt of feature 20054 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1312.31999999999994 of field land_lengt of feature 20054 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1049.20000000000005 of field land_lengt of feature 21924 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1049.20000000000005 of field land_lengt of feature 21924 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1301.47000000000003 of field land_lengt of feature 21941 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1301.47000000000003 of field land_lengt of feature 21941 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1011.97000000000003 of field land_lengt of feature 22069 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1011.97000000000003 of field land_lengt of feature 22069 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1007.86000000000001 of field land_lengt of feature 22102 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1007.86000000000001 of field land_lengt of feature 22102 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1097.5 of field land_lengt of feature 22655 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1006.35000000000002 of field land_lengt of feature 22656 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1030.93000000000006 of field land_lengt of feature 27251 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1030.93000000000006 of field land_lengt of feature 27251 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1457.22000000000003 of field land_lengt of feature 28491 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1457.22000000000003 of field land_lengt of feature 28491 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1081.25 of field land_lengt of feature 28566 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\nWarning 1: Value 1257.3900000000001 of field land_lengt of feature 29062 not successfully written. Possibly due to too larger number with respect to field width\n	b3e67d4d-3b66-3f96-9875-cd036de39e95	添加物候置信度	输入矢量文件: /onesis/kt4/job_results/o1871924515873882112.str; 置信度配置文件: /onesis/kt4/test_data/basic/data/zxd_config.csv; 作物占比文件: /onesis/kt4/test_data/basic/data/crop_data_n.csv; 行政区域名称: liangping; 输出矢量文件: /onesis/kt4/job_results/o1871924516071014400.str; 	\N	6	95a00467-da7f-42eb-988c-7496d1ecd64b
5c81e01c8ff04b18b3010a1dca02fbe8		2024-12-26 09:33:13.994765	2024-12-26 09:33:09.149921	{"epsg":"0","file":"/onesis/kt4/job_results/demfel.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/gdal.py:312: FutureWarning: Neither gdal.UseExceptions() nor gdal.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\ndemfel.tif is in WGS84 or based on WGS84.\nProject done.\n	84641a52-bd00-3734-9c49-597a3f5d2e73	reproject:d46c5019473f4697a157a046a26f88eb	数据路径: /onesis/kt4/job_results/demfel.tif; EPSG号: 0; 	\N	6	\N
f35e1d18cb0c440caceb527c39bf9140		2024-12-26 10:47:25.026687	2024-12-26 10:45:50.2342	{"c":"/onesis/kt4/test_data/basic/data/grade.csv","f":"land_dem","i":"/onesis/kt4/test_data/basic/data/input_small.shp","l":"middle","o":"/onesis/kt4/test_data/basic/data/o1872111542821060608.shp"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\nmiddle\n	70050be4-e818-32e1-a631-c99d0d94d5de	添加物候信息	输入矢量文件: /onesis/kt4/test_data/basic/data/input_small.shp; 物候配置文件: /onesis/kt4/test_data/basic/data/grade.csv; 高程字段名: land_dem; 区域信息: middle; 输出矢量文件: /onesis/kt4/test_data/basic/data/o1872111542821060608.shp; 	\N	6	f04369d5-50b1-4205-8980-07e28816c959
1640bf6d171146f0a3789474f1c1ba62		2024-12-26 10:49:06.090507	2024-12-26 10:45:49.718786	{"c":"/onesis/kt4/test_data/basic/data/config.csv","t":"474069,302376,98444,394334","i":"/onesis/kt4/test_data/basic/data/o1872111543215325184.shp","z":"1,2,3,9","o":"/onesis/kt4/test_data/basic/data/zw_result_small.shp"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nSyntaxError: Non-UTF-8 code starting with '\\xa8' in file /data/onesis/kt4/test_data/basic/data/o1872111543215325184.shp on line 3, but no encoding declared; see https://python.org/dev/peps/pep-0263/ for details\n>>> \n	3f83271b-4116-359e-9bd1-a4744506f0cd	地块面积赋值	输入矢量文件: /onesis/kt4/test_data/basic/data/o1872111543215325184.shp; 配置文件: /onesis/kt4/test_data/basic/data/config.csv; 要进行的操作索引: 1,2,3,9; 操作对应的面积阈值: 474069,302376,98444,394334; 输出矢量文件: /onesis/kt4/test_data/basic/data/zw_result_small.shp; 	\N	6	f04369d5-50b1-4205-8980-07e28816c959
4adc4012053e4b5c84bcd755f6f44533		2024-12-26 11:10:30.749841	2024-12-26 11:10:23.869886	{"z":"/onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif has projected coordinate system.\nNodata value input to create partition from file: -340282306073709652508363335590014353408.000000\nNodata value recast to float used in partition raster: -340282306073709652508363335590014353408.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.470208\nData read time: 0.409660\nCompute time: 0.012460\nWrite time: 0.242095\nTotal time: 1.134424\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif; 数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
615f284fa5b7438086597cc6918641df		2024-12-26 11:31:30.593428	2024-12-26 11:31:23.938975	{"z":"/onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif has projected coordinate system.\nNodata value input to create partition from file: -340282306073709652508363335590014353408.000000\nNodata value recast to float used in partition raster: -340282306073709652508363335590014353408.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.203915\nData read time: 0.064254\nCompute time: 0.006445\nWrite time: 0.218798\nTotal time: 0.493412\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/dem_priolo.tif; 数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
dee1598f1e3747278ca9ed743d1dd96b		2024-12-26 11:11:15.14487	2024-12-26 11:10:22.777436	{"op":"/onesis/kt4/dsm_case/2024_12_25/out/","c":"gini","mwfl":"0.0","msl":"1","mss":"2","v":"0","ne":"100","md":"3","tl":"/onesis/kt4/dsm_case/2024_12_25/priolo_00-15_landuse_1to2.tif","rfm":"/onesis/kt4/dsm_case/2024_12_25/out/op1872117707936235520.tif","sfm":"/onesis/kt4/dsm_case/2024_12_25/out/sd81872117711040020480.tif","ca":"0.0","sr":"0.5","wfm":"/onesis/kt4/dsm_case/2024_12_25/out/dist1872117710389903360.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nrandom_forest.py:302: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n  rfc_out=rfc.fit(x_train, y_train)\n	a732c661-90df-32da-b10f-33eaae839b21	面向土地利用类型扩张的随机森林	土地扩张标签: /onesis/kt4/dsm_case/2024_12_25/priolo_00-15_landuse_1to2.tif; 采样率: 0.5; 树木数量: 100; 不纯度方法: gini; 最大深度: 3; 拆分内节点最少样本数: 2; 叶节点最小样本数: 1; 最小加权分数: 0.0; 详细程度: 0; 复杂度参数: 0.0; 输出路径: /onesis/kt4/dsm_case/2024_12_25/out/; 道路栅格: /onesis/kt4/dsm_case/2024_12_25/out/op1872117707936235520.tif; 河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/dist1872117710389903360.tif; 坡度栅格: /onesis/kt4/dsm_case/2024_12_25/out/sd81872117711040020480.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
60532d2a086443b7801ec1a92bb61bfa		2024-12-26 11:32:05.56778	2024-12-26 11:31:23.316273	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif","src":"/onesis/kt4/dsm_case/2024_12_25/out/src1872123000220942336.tif","dist":"/onesis/kt4/dsm_case/2024_12_25/out/dist1872123000552292352.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8DistDownToStream version 5.3.9, added by Liangjun Zhu, Apr 2, 2015\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/src1872123000220942336.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int32_t used in partition raster: -32768\nProcessors: 1\nRead time: 0.161145\nCompute time: 0.004104\nWrite time: 0.067396\nTotal time: 0.232645\n	99792477-6354-3e47-8097-07adbb5e11cb	至河流的距离计算	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif; D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif; 提取的河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/src1872123000220942336.tif; 至河网距离的栅格: /onesis/kt4/dsm_case/2024_12_25/out/dist1872123000552292352.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
1ebede66eb79456cae6696fb6b76694e		2024-12-26 11:31:57.417039	2024-12-26 11:31:24.244305	{"ssa":"/onesis/kt4/dsm_case/2024_12_25/out/ad81872122999763763200.tif","src":"/onesis/kt4/dsm_case/2024_12_25/out/src1872123000220942336.tif","thresh":"2000.0"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nThreshold version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/ad81872122999763763200.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nCompute time: 0.000670\n	19a662d0-b39e-35cb-a063-0e1c13ee9e6b	河网提取（栅格）	d8汇流累积量栅格: /onesis/kt4/dsm_case/2024_12_25/out/ad81872122999763763200.tif; 阈值: 2000.0; 提取的河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/src1872123000220942336.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
ce8d0fdcb8354035aaf2b17dfee8c17a		2025-01-05 20:06:44.963939	2025-01-05 20:05:44.25191	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif","o":"/onesis/kt4/xuancheng/result/o1875876331024154624.tif"}	f	Pod Status: Pending\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n****************************\n* Welcome to Aspect        *\n* Powered by WhiteboxTools *\n* www.whiteboxgeo.com      *\n****************************\nReading data...\nthread 'main' panicked at 'No such file or directory (os error 2)', whitebox-tools-app/src/main.rs:72:21\nnote: run with `RUST_BACKTRACE=1` environment variable to display a backtrace\nfailed to create fsnotify watcher: too many open files	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	z因子: 1; 输入数据: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 输出数据: /onesis/kt4/xuancheng/result/o1875876331024154624.tif; 	\N	7	2cf6be48-1562-40b9-a416-ef2ce4ac609f
676e0edb08494eceb43565a10d32fbd2		2024-12-26 11:31:40.725515	2024-12-26 11:31:24.077297	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.031969\nData read time: 0.174742\nCompute Slope time: 0.007769\nWrite Slope time: 0.006969\nResolve Flat time: 0.209316\nWrite Flat time: 0.079133\nTotal time: 0.509898\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif; D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872122998866182144.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
e0fa5923867445c9a2380cd140ccad14		2024-12-26 11:10:39.530584	2024-12-26 11:10:23.729848	{"sd8":"/onesis/kt4/dsm_case/2024_12_25/out/sd81872117711040020480.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.074301\nData read time: 0.108602\nCompute Slope time: 0.007115\nWrite Slope time: 0.054170\nResolve Flat time: 0.229345\nWrite Flat time: 0.004651\nTotal time: 0.478184\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif; 坡度栅格: /onesis/kt4/dsm_case/2024_12_25/out/sd81872117711040020480.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
af011da0361c477a88ed5ffeffc4e57d		2024-12-26 11:10:39.541721	2024-12-26 11:10:24.037078	{"p":"/onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.077137\nData read time: 0.110499\nCompute Slope time: 0.007104\nWrite Slope time: 0.006909\nResolve Flat time: 0.235467\nWrite Flat time: 0.062894\nTotal time: 0.500011\n	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872117708259196928.tif; D8单流向栅格: /onesis/kt4/dsm_case/2024_12_25/out/p1872117708900925440.tif; 	\N	6	132e9d2e-8cca-471f-a485-cc7d54e379a6
ef070f5a9a9b462ea143c6181a219d53		2024-12-30 10:51:37.940115	2024-12-30 10:51:32.329031	{"z":"/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.056925\nData read time: 0.093532\nCompute time: 0.159421\nWrite time: 0.076524\nTotal time: 0.386402\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif; 数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 	\N	6	f80ddfab-a1a2-4117-a7b1-7f57d6847384
a55b407e92f94b6386d068cf11e40e32		2024-12-30 16:45:06.119024	2024-12-30 16:45:01.776176	{"z":"/onesis/kt4/data/rf_workflow/2024_12_25/dem_priolo.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/data/rf_workflow/2024_12_25/dem_priolo.tif has projected coordinate system.\nNodata value input to create partition from file: -340282306073709652508363335590014353408.000000\nNodata value recast to float used in partition raster: -340282306073709652508363335590014353408.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.038518\nData read time: 0.008119\nCompute time: 0.012674\nWrite time: 0.021849\nTotal time: 0.081160\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif; 数字高程模型: /onesis/kt4/data/rf_workflow/2024_12_25/dem_priolo.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
fe0c415c2bdb4a2988c9314e6dd4d34a		2024-12-26 11:31:40.846351	2024-12-26 11:31:23.815061	{"sd8":"/onesis/kt4/dsm_case/2024_12_25/out/sd81872123001206603776.tif","fel":"/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nNodata value recast to float used in partition raster: -9999.000000\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.096540\nData read time: 0.142874\nCompute Slope time: 0.007830\nWrite Slope time: 0.098858\nResolve Flat time: 0.209202\nWrite Flat time: 0.004849\nTotal time: 0.560153\n	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/dsm_case/2024_12_25/out/fel1872122997821800448.tif; 坡度栅格: /onesis/kt4/dsm_case/2024_12_25/out/sd81872123001206603776.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
70f0613a7d6b4f8cb370493c325ebd04		2024-12-26 11:32:16.598936	2024-12-26 11:31:22.762723	{"op":"/onesis/kt4/dsm_case/2024_12_25/out/","c":"gini","mwfl":"0.0","msl":"1","mss":"2","v":"0","ne":"100","md":"3","tl":"/onesis/kt4/dsm_case/2024_12_25/priolo_00-15_landuse_1to2.tif","rfm":"/onesis/kt4/dsm_case/2024_12_25/out/op1872122997293318144.tif","sfm":"/onesis/kt4/dsm_case/2024_12_25/out/sd81872123001206603776.tif","ca":"0.0","sr":"0.5","wfm":"/onesis/kt4/dsm_case/2024_12_25/out/dist1872123000552292352.tif"}	f	Pod Status: Succeeded\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nrandom_forest.py:302: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n  rfc_out=rfc.fit(x_train, y_train)\n	a732c661-90df-32da-b10f-33eaae839b21	面向土地利用类型扩张的随机森林	土地扩张标签: /onesis/kt4/dsm_case/2024_12_25/priolo_00-15_landuse_1to2.tif; 采样率: 0.5; 树木数量: 100; 不纯度方法: gini; 最大深度: 3; 拆分内节点最少样本数: 2; 叶节点最小样本数: 1; 最小加权分数: 0.0; 详细程度: 0; 复杂度参数: 0.0; 输出路径: /onesis/kt4/dsm_case/2024_12_25/out/; 道路栅格: /onesis/kt4/dsm_case/2024_12_25/out/op1872122997293318144.tif; 河网栅格: /onesis/kt4/dsm_case/2024_12_25/out/dist1872123000552292352.tif; 坡度栅格: /onesis/kt4/dsm_case/2024_12_25/out/sd81872123001206603776.tif; 	\N	6	3a10687c-f44c-46dc-adb7-664d36cf7330
651e64f4e28644b2b29badcd1a4db2b5		2024-12-30 10:53:52.167288	2024-12-30 10:53:47.565418	{"z":"/onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873563101576691712.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.028843\nData read time: 0.062947\nCompute time: 0.127199\nWrite time: 0.070112\nTotal time: 0.289102\n	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/heshan/dem_heshan_900913.tif; 数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873563101576691712.tif; 	\N	6	a3ee365e-19fe-4a0c-b527-4858a59265e1
f67715c1a0d14947a9a92b048234f078		2024-12-30 13:20:04.972133	2024-12-30 10:53:47.416186	{"uncmap":"/onesis/kt4/job_results/1_ipsm/test_unc_hs_1230.tif","inlayer1":"/onesis/kt4/job_results/1_ipsm/sd81873563101920624640.tif","inlayer0":"/onesis/kt4/job_results/1_ipsm/fel1873563101576691712.tif","inlayer7":"/onesis/kt4/job_results/1_ipsm/twi1873563102268751872.tif","inlayer5":"/onesis/kt4/job_results/1_ipsm/o1873563101689937920.tif","simithred":"0.1","predmap":"/onesis/kt4/job_results/1_ipsm/test_pre_hs_1230.tif","inlayer4":"/onesis/kt4/job_results/1_ipsm/plan1873563101803184128.tif","sample":"/onesis/kt4/dsm_case/heshan/hs_samples_900913.csv","target":"SOM"}	f	\N	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/heshan/hs_samples_900913.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.1; 土壤属性空间分布: /onesis/kt4/job_results/1_ipsm/test_pre_hs_1230.tif; 空间推测不确定性: /onesis/kt4/job_results/1_ipsm/test_unc_hs_1230.tif; DEM栅格: /onesis/kt4/job_results/1_ipsm/fel1873563101576691712.tif; 剖面曲率: /onesis/kt4/job_results/1_ipsm/o1873563101689937920.tif; 平面曲率: /onesis/kt4/job_results/1_ipsm/plan1873563101803184128.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81873563101920624640.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1873563102268751872.tif; 	\N	9	a3ee365e-19fe-4a0c-b527-4858a59265e1
f794d3855c20411cbceff304fb6cfea9		2024-12-30 13:20:05.313604	2024-12-30 10:53:47.448996	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81873563102210031616.tif","slp":"/onesis/kt4/job_results/1_ipsm/sd81873563101920624640.tif","twi":"/onesis/kt4/job_results/1_ipsm/twi1873563102268751872.tif"}	f	\N	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/1_ipsm/sd81873563101920624640.tif; 汇流累积量: /onesis/kt4/job_results/1_ipsm/ad81873563102210031616.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1873563102268751872.tif; 	\N	9	a3ee365e-19fe-4a0c-b527-4858a59265e1
117266b0a2ad4e599392ae2c6786eaaa		2025-01-05 22:05:18.268935	2025-01-05 22:04:15.932268	{"sd8":"/onesis/kt4/xuancheng/sd81875906159655911424.tif","fel":"/onesis/kt4/xuancheng/fel1875906158779301888.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nError opening file /data/onesis/kt4/xuancheng/fel1875906158779301888.tif.\nERROR 4: /data/onesis/kt4/xuancheng/fel1875906158779301888.tif: No such file or directory\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD\nwith errorcode 21.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nfailed to create fsnotify watcher: too many open files	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/xuancheng/fel1875906158779301888.tif; 坡度栅格: /onesis/kt4/xuancheng/sd81875906159655911424.tif; 	\N	7	2f2eafa3-cefd-4a0c-a429-6d20e166c686
c00b72eab6c7414cb8d0510aa82d38f7		2024-12-30 13:20:09.553922	2024-12-30 10:51:31.679901	{"inlayer3":"/onesis/kt4/job_results/1_ipsm/o1873562531180707840.tif","inlayer2":"/onesis/kt4/job_results/1_ipsm/RESULT1873562531868573696.tif","inlayer1":"/onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif","inlayer0":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif","inlayer7":"/onesis/kt4/job_results/1_ipsm/twi1873562532308975616.tif","inlayer6":"/onesis/kt4/job_results/1_ipsm/o1873562532162174976.tif","inlayer5":"/onesis/kt4/job_results/1_ipsm/o1873562532447387648.tif","simithred":"0.1","inlayer4":"/onesis/kt4/job_results/1_ipsm/plan1873562532589993984.tif","sample":"/onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv","target":"SOM","uncmap":"/onesis/kt4/job_results/1_ipsm/test_unc_1230.tif","predmap":"/onesis/kt4/job_results/1_ipsm/test_pred_1230.tif"}	f	\N	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/dsm_case/xuancheng/xc_samples_900913.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.1; 土壤属性空间分布: /onesis/kt4/job_results/1_ipsm/test_pred_1230.tif; 空间推测不确定性: /onesis/kt4/job_results/1_ipsm/test_unc_1230.tif; 坡向: /onesis/kt4/job_results/1_ipsm/o1873562531180707840.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif; 水动力指数: /onesis/kt4/job_results/1_ipsm/o1873562532162174976.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1873562532308975616.tif; DEM栅格: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 汇聚指数: /onesis/kt4/job_results/1_ipsm/RESULT1873562531868573696.tif; 剖面曲率: /onesis/kt4/job_results/1_ipsm/o1873562532447387648.tif; 平面曲率: /onesis/kt4/job_results/1_ipsm/plan1873562532589993984.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
16f61c61d87b4bbdaabd7ade0d03457b		2024-12-30 13:20:09.573696	2024-12-30 10:51:31.772313	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81873562532086677504.tif","slp":"/onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif","twi":"/onesis/kt4/job_results/1_ipsm/twi1873562532308975616.tif"}	f	\N	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif; 汇流累积量: /onesis/kt4/job_results/1_ipsm/ad81873562532086677504.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1873562532308975616.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
bfc1bea22c5f4cb3989a98f57bd022c1		2024-12-30 13:20:09.597471	2024-12-30 10:51:31.854003	{"sd8":"/onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif"}	f	\N	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81873562531356868608.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
87332e39b3434cba8d35bb9c9e76e953		2024-12-30 13:20:09.620862	2024-12-30 10:51:31.953576	{"zfactor":"1","i":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif","o":"/onesis/kt4/job_results/1_ipsm/o1873562531180707840.tif"}	f	\N	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	输入数据: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 输出数据: /onesis/kt4/job_results/1_ipsm/o1873562531180707840.tif; z因子: 1; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
ee85bc343d834e249e03438acc65e6d8		2024-12-30 13:20:09.643416	2024-12-30 10:51:32.049613	{"fel":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif","plan":"/onesis/kt4/job_results/1_ipsm/plan1873562532589993984.tif"}	f	\N	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 平面曲率栅格: /onesis/kt4/job_results/1_ipsm/plan1873562532589993984.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
eb4473a752124158a01d80c388b2c0b6		2024-12-30 13:20:09.666555	2024-12-30 10:51:32.119912	{"i":"/onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif","o":"/onesis/kt4/job_results/1_ipsm/o1873562532447387648.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	输入栅格 DEM 文件: /onesis/kt4/job_results/1_ipsm/fel1873562531088433152.tif; 输出栅格文件: /onesis/kt4/job_results/1_ipsm/o1873562532447387648.tif; 	\N	9	f80ddfab-a1a2-4117-a7b1-7f57d6847384
7a0568441e594d949563d2144151aa18		2024-12-30 16:43:13.950525	2024-12-30 16:42:46.921726	{"p":"/onesis/kt4/job_results/p1873650925118291968.tif","ad8":"/onesis/kt4/job_results/ad81873650925369950208.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/job_results/p1873650925118291968.tif has geographic coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.112890\nCompute time: 0.310845\nWrite time: 0.083524\nTotal time: 0.507259\nfailed to create fsnotify watcher: too many open files	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/p1873650925118291968.tif; d8汇流累积量栅格: /onesis/kt4/job_results/ad81873650925369950208.tif; 	\N	6	da7c1e77-2f35-4a6c-90a2-3f7f328628d1
7e278dc171714d5b980baa27f72f207a		2024-12-30 16:45:52.382827	2024-12-30 16:45:01.610656	{"op":"/onesis/kt4/job_results/1_ipsm/op1873651491902980096.tif","width":"424","sfp":"/onesis/kt4/data/rf_workflow/2024_12_25/road_Priolo.shp","height":"317"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n欧氏距离分析完成，结果保存为 /data/onesis/kt4/job_results/1_ipsm/op1873651491902980096.tif\nfailed to create fsnotify watcher: too many open files	827a0ed4-eb81-3cd5-b84f-871166368115	欧氏距离分析	图像宽度: 424; 图像高度: 317; 输出文件: /onesis/kt4/job_results/1_ipsm/op1873651491902980096.tif; 输入文件: /onesis/kt4/data/rf_workflow/2024_12_25/road_Priolo.shp; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
b271992c11944f5bbd302310a81d7669		2024-12-30 16:42:57.657774	2024-12-30 16:42:47.094765	{"z":"/onesis/kt4/test_data/terr/dem.tif","fel":"/onesis/kt4/job_results/fel1873650924405260288.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/test_data/terr/dem.tif has geographic coordinate system.\nNodata value input to create partition from file: 32767.000000\nNodata value recast to float used in partition raster: 32767.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.042983\nData read time: 0.067574\nCompute time: 0.304922\nWrite time: 0.089999\nTotal time: 0.505478\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/job_results/fel1873650924405260288.tif; 数字高程模型: /onesis/kt4/test_data/terr/dem.tif; 	\N	6	da7c1e77-2f35-4a6c-90a2-3f7f328628d1
e2dbf49ab3684024afee70fa2ec1d16b		\N	2025-01-05 20:05:44.179693	{"inlayer3":"/onesis/kt4/xuancheng/result/o1875876331024154624.tif","inlayer2":"/onesis/kt4/xuancheng/result/RESULT1875876330436952064.tif","inlayer1":"/onesis/kt4/xuancheng/result/sd81875876331124817920.tif","inlayer0":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif","inlayer7":"/onesis/kt4/xuancheng/result/twi1875876331309367296.tif","inlayer6":"/onesis/kt4/xuancheng/result/o1875876331217092608.tif","inlayer5":"/onesis/kt4/xuancheng/result/o1875876330827022336.tif","simithred":"0.3","inlayer4":"/onesis/kt4/xuancheng/result/plan1875876330927685632.tif","sample":"/onesis/kt4/xuancheng/input/xc_samples.csv","target":"SOM","uncmap":"/onesis/kt4/xuancheng/result/2.tif","predmap":"/onesis/kt4/xuancheng/result/1.tif"}	f	\N	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/xuancheng/input/xc_samples.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/xuancheng/result/1.tif; 空间推测不确定性: /onesis/kt4/xuancheng/result/2.tif; DEM栅格: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 汇聚指数: /onesis/kt4/xuancheng/result/RESULT1875876330436952064.tif; 水动力指数: /onesis/kt4/xuancheng/result/o1875876331217092608.tif; 地形湿度指数: /onesis/kt4/xuancheng/result/twi1875876331309367296.tif; 剖面曲率: /onesis/kt4/xuancheng/result/o1875876330827022336.tif; 平面曲率: /onesis/kt4/xuancheng/result/plan1875876330927685632.tif; 坡向: /onesis/kt4/xuancheng/result/o1875876331024154624.tif; 坡度栅格: /onesis/kt4/xuancheng/result/sd81875876331124817920.tif; 	\N	0	2cf6be48-1562-40b9-a416-ef2ce4ac609f
a7d936775d694727a4afc62615f2a879		2025-01-05 17:33:21.984429	2025-01-05 17:32:19.877377	{"sd8":"/onesis/kt4/xuancheng/result/sd81875837724427157504.tif","fel":"/onesis/kt4/xuancheng/result/fel1875837723567325184.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nError opening file /data/onesis/kt4/xuancheng/result/fel1875837723567325184.tif.\nERROR 4: /data/onesis/kt4/xuancheng/result/fel1875837723567325184.tif: No such file or directory\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD\nwith errorcode 21.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nfailed to create fsnotify watcher: too many open files	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/xuancheng/result/fel1875837723567325184.tif; 坡度栅格: /onesis/kt4/xuancheng/result/sd81875837724427157504.tif; 	\N	7	2b175d24-3d52-45a5-ac1b-446c73264fe6
c4aef5d39951430391f229307cd4909c		\N	2025-01-05 20:05:44.206996	{"sca":"/onesis/kt4/xuancheng/result/ad81875876330583752704.tif","slp":"/onesis/kt4/xuancheng/result/sd81875876331124817920.tif","twi":"/onesis/kt4/xuancheng/result/twi1875876331309367296.tif"}	f	\N	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	汇流累积量: /onesis/kt4/xuancheng/result/ad81875876330583752704.tif; 地形湿度指数: /onesis/kt4/xuancheng/result/twi1875876331309367296.tif; 坡度: /onesis/kt4/xuancheng/result/sd81875876331124817920.tif; 	\N	0	2cf6be48-1562-40b9-a416-ef2ce4ac609f
9e06c514d1de44b483eb4f084f1e91a3		2025-01-05 17:33:23.424628	2025-01-05 17:32:20.014094	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/xuancheng/result/fel1875837723567325184.tif","METHOD":"0","RESULT":"/onesis/kt4/xuancheng/result/RESULT1875837723672182784.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n____________________________\n\n   #####   ##   #####    ##\n  ###     ###  ##       ###\n   ###   # ## ##  #### # ##\n    ### ##### ##    # #####\n ##### #   ##  ##### #   ##\n____________________________\n\nSAGA Version: 8.1.0\n\nError: input file [/data/onesis/kt4/xuancheng/result/fel1875837723567325184.tif]\nError: Elevation\n____________________________\nlibrary path: /usr/local/lib/saga/\nlibrary name: libta_morphometry\nlibrary     : ta_morphometry\ntool        : Convergence Index\nidentifier  : 1\nauthor      : O.Conrad (c) 2001\nprocessors  : 8 [8]\n____________________________\n\n\nUsage: saga_cmd ta_morphometry 1 [-ELEVATION <str>] [-RESULT <str>] [-METHOD <str>] [-NEIGHBOURS <str>]\n  -ELEVATION:<str> \tElevation\n\tGrid, input\n  -RESULT:<str>    \tConvergence Index\n\tGrid, output\n  -METHOD:<str>    \tMethod\n\tChoice\n\tAvailable Choices:\n\t[0] Aspect\n\t[1] Gradient\n\tDefault: 0\n  -NEIGHBOURS:<str>\tGradient Calculation\n\tChoice\n\tAvailable Choices:\n\t[0] 2 x 2\n\t[1] 3 x 3\n\tDefault: 0\nfailed to create fsnotify watcher: too many open files	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	计算方式: 0; 邻域窗口大小: 0; 数字高程模型: /onesis/kt4/xuancheng/result/fel1875837723567325184.tif; 地形结构指数: /onesis/kt4/xuancheng/result/RESULT1875837723672182784.tif; 	\N	7	2b175d24-3d52-45a5-ac1b-446c73264fe6
0c6b8af020284f2fb5745343a0162ed1		2025-01-05 17:33:23.480144	2025-01-05 17:32:19.957979	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875837723567325184.tif","o":"/onesis/kt4/xuancheng/result/o1875837724100001792.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	Z 转换因子: 1; 输入栅格 DEM 文件: /onesis/kt4/xuancheng/result/fel1875837723567325184.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875837724100001792.tif; 	\N	7	2b175d24-3d52-45a5-ac1b-446c73264fe6
c49774bcbd71494eb5aeff68f93ae40c		2024-12-30 16:43:08.496905	2024-12-30 16:42:47.046468	{"p":"/onesis/kt4/job_results/p1873650925118291968.tif","fel":"/onesis/kt4/job_results/fel1873650924405260288.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/fel1873650924405260288.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.070639\nData read time: 0.188191\nCompute Slope time: 0.389377\nWrite Slope time: 0.096048\nResolve Flat time: 2.553446\nWrite Flat time: 0.050479\nTotal time: 3.348180\nfailed to create fsnotify watcher: too many open files	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/fel1873650924405260288.tif; D8单流向栅格: /onesis/kt4/job_results/p1873650925118291968.tif; 	\N	6	da7c1e77-2f35-4a6c-90a2-3f7f328628d1
e8dd8d1c84204840981cb6fea3824074		2024-12-30 16:43:08.511136	2024-12-30 16:42:46.984587	{"sd8":"/onesis/kt4/job_results/sd81873650924640141312.tif","fel":"/onesis/kt4/job_results/fel1873650924405260288.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/fel1873650924405260288.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 49338 flats to resolve.\nDraining flats towards lower adjacent terrain\n.............................................................................................................................................................\nDraining flats away from higher adjacent terrain\n......\nSetting directions\nIteration complete. Number of flats remaining: 1323\nDraining flats towards lower adjacent terrain\n....\nDraining flats away from higher adjacent terrain\n...\nSetting directions\nProcessors: 1\nHeader read time: 0.067471\nData read time: 0.205105\nCompute Slope time: 0.371497\nWrite Slope time: 0.105550\nResolve Flat time: 2.569334\nWrite Flat time: 0.049774\nTotal time: 3.368731\nfailed to create fsnotify watcher: too many open files	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/job_results/fel1873650924405260288.tif; 坡度栅格: /onesis/kt4/job_results/sd81873650924640141312.tif; 	\N	6	da7c1e77-2f35-4a6c-90a2-3f7f328628d1
9a85ad515cc94ac297196c8629b0a9f7		2024-12-30 17:02:22.159011	2024-12-30 17:01:20.703272	{"r":"liangping","c":"/onesis/kt4/test_data/basic/zw_kt5/zxd_config.csv","d":"/onesis/kt4/test_data/basic/zw_kt5/crop_data_n.csv","i":"/onesis/kt4/job_results/1_ipsm/o1873655599384887296.shp","o":"/onesis/kt4/job_results/1_ipsm/o1873655599481356288.shp"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n/usr/lib/python3.12/site-packages/osgeo/ogr.py:601: FutureWarning: Neither ogr.UseExceptions() nor ogr.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n  warnings.warn(\nfailed to create fsnotify watcher: too many open files	b3e67d4d-3b66-3f96-9875-cd036de39e95	添加物候置信度	输入矢量文件: /onesis/kt4/job_results/1_ipsm/o1873655599384887296.shp; 行政区域名称: liangping; 输出矢量文件: /onesis/kt4/job_results/1_ipsm/o1873655599481356288.shp; 置信度配置文件: /onesis/kt4/test_data/basic/zw_kt5/zxd_config.csv; 作物占比文件: /onesis/kt4/test_data/basic/zw_kt5/crop_data_n.csv; 	\N	6	3edd4fed-576c-4a6e-994c-e5701843e198
98f0eac82dd34b7a952c2705422c20ce		2025-01-05 16:15:56.727301	2025-01-05 16:14:52.456742	{"p":"/onesis/kt4/xuancheng/result/p1875818229683847168.tif","fel":"/onesis/kt4/xuancheng/result/fel1875818229461549056.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nERROR 4: /data/onesis/kt4/xuancheng/result/fel1875818229461549056.tif: No such file or directory\nError opening file /data/onesis/kt4/xuancheng/result/fel1875818229461549056.tif.\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD\nwith errorcode 21.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nfailed to create fsnotify watcher: too many open files	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/xuancheng/result/fel1875818229461549056.tif; D8单流向栅格: /onesis/kt4/xuancheng/result/p1875818229683847168.tif; 	\N	7	f4011d59-b2a7-4550-b84a-8aa50f742864
dd8775c7fc124977adc2e0026fb882e8		2024-12-30 16:43:19.754793	2024-12-30 16:42:46.447575	{"sca":"/onesis/kt4/job_results/ad81873650925369950208.tif","slp":"/onesis/kt4/job_results/sd81873650924640141312.tif","twi":"/onesis/kt4/job_results/twi1230.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/job_results/sd81873650924640141312.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/job_results/ad81873650925369950208.tif has geographic coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.040779\nfailed to create fsnotify watcher: too many open files	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/sd81873650924640141312.tif; 汇流累积量: /onesis/kt4/job_results/ad81873650925369950208.tif; 地形湿度指数: /onesis/kt4/job_results/twi1230.tif; 	\N	6	da7c1e77-2f35-4a6c-90a2-3f7f328628d1
bf5223c5c45145d4bcab11190e568a25		2025-01-05 16:15:55.448892	2025-01-05 16:14:52.192755	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875818229461549056.tif","o":"/onesis/kt4/xuancheng/result/o1875818230254272512.tif"}	f	\N	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	z因子: 1; 输入数据: /onesis/kt4/xuancheng/result/fel1875818229461549056.tif; 输出数据: /onesis/kt4/xuancheng/result/o1875818230254272512.tif; 	\N	7	f4011d59-b2a7-4550-b84a-8aa50f742864
0f670b4ddcff47e7a8dd1f0d0ec16606		2025-01-05 16:15:56.608669	2025-01-05 16:14:52.219911	{"fel":"/onesis/kt4/xuancheng/result/fel1875818229461549056.tif","plan":"/onesis/kt4/xuancheng/result/plan1875818230132637696.tif"}	f	\N	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/xuancheng/result/fel1875818229461549056.tif; 平面曲率栅格: /onesis/kt4/xuancheng/result/plan1875818230132637696.tif; 	\N	7	f4011d59-b2a7-4550-b84a-8aa50f742864
6199b95d7d0744ba8c84cec0c14dd071		\N	2025-01-05 17:07:52.971377	{"p":"/onesis/kt4/xuancheng/result/p1875831571005702144.tif","ad8":"/onesis/kt4/xuancheng/result/ad81875831571056033792.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/xuancheng/result/p1875831571005702144.tif; d8汇流累积量栅格: /onesis/kt4/xuancheng/result/ad81875831571056033792.tif; 	\N	0	220aef12-09ad-434c-aa2d-04914a69bc6c
bd59c705416b4b328fb117ce7ef6550d		2025-01-05 19:43:17.446005	2025-01-05 19:42:14.551136	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875870416887742464.tif","o":"/onesis/kt4/xuancheng/result/o1875870417462362112.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	Z 转换因子: 1; 输入栅格 DEM 文件: /onesis/kt4/xuancheng/result/fel1875870416887742464.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875870417462362112.tif; 	\N	7	935d54c3-d3ca-4f45-b904-677b16f7e628
5d3a20f7fad8418686aa7dd8e44b0eb9		2024-12-30 16:45:17.249613	2024-12-30 16:45:02.052589	{"p":"/onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif","ad8":"/onesis/kt4/job_results/1_ipsm/ad81873651492343382016.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.039823\nCompute time: 0.017780\nWrite time: 0.018042\nTotal time: 0.075644\nfailed to create fsnotify watcher: too many open files	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif; d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81873651492343382016.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
4b774bbd4aa0488fb5e47208e90e2907		2024-12-30 16:45:11.857136	2024-12-30 16:45:01.699849	{"sd8":"/onesis/kt4/job_results/1_ipsm/sd81873651492943167488.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.048014\nData read time: 0.015964\nCompute Slope time: 0.025427\nWrite Slope time: 0.022236\nResolve Flat time: 0.512593\nWrite Flat time: 0.010365\nTotal time: 0.634599\nfailed to create fsnotify watcher: too many open files	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81873651492943167488.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
cff7406ae4b9414984bfdf91ea1780e0		2024-12-30 16:45:27.379488	2024-12-30 16:45:01.659918	{"p":"/onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif","src":"/onesis/kt4/job_results/1_ipsm/src1873651492418879488.tif","dist":"/onesis/kt4/job_results/1_ipsm/dist1873651492787978240.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif","m":"s","thresh":"1.0"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8DistDownToStream version 5.3.9, added by Liangjun Zhu, Apr 2, 2015\nInput file /data/onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nInput file /data/onesis/kt4/job_results/1_ipsm/src1873651492418879488.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int32_t used in partition raster: -32768\nProcessors: 1\nRead time: 0.093316\nCompute time: 0.007134\nWrite time: 0.018219\nTotal time: 0.118670\nfailed to create fsnotify watcher: too many open files	99792477-6354-3e47-8097-07adbb5e11cb	至河流的距离计算	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif; 提取的河网栅格: /onesis/kt4/job_results/1_ipsm/src1873651492418879488.tif; 距离计算方法: s; 阈值: 1.0; 至河网距离的栅格: /onesis/kt4/job_results/1_ipsm/dist1873651492787978240.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
9958576201ff48748199040cec804533		2024-12-30 16:45:22.319487	2024-12-30 16:45:01.860931	{"ssa":"/onesis/kt4/job_results/1_ipsm/ad81873651492343382016.tif","src":"/onesis/kt4/job_results/1_ipsm/src1873651492418879488.tif","thresh":"3000"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nThreshold version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/ad81873651492343382016.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nCompute time: 0.001210\nfailed to create fsnotify watcher: too many open files	19a662d0-b39e-35cb-a063-0e1c13ee9e6b	河网提取（栅格）	d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81873651492343382016.tif; 阈值: 3000; 提取的河网栅格: /onesis/kt4/job_results/1_ipsm/src1873651492418879488.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
3e122cfbd6874039b50fdf2076264cba		2025-01-05 20:05:49.616173	2025-01-05 20:05:44.368499	{"z":"/onesis/kt4/xuancheng/input/dem_xc.tif","fel":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/xuancheng/input/dem_xc.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nERROR 4: Attempt to create new tiff file `/data/onesis/kt4/xuancheng/result/fel1875876330323705856.tif' failed: No error information\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetProjection'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetGeoTransform'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALGetRasterBand'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALSetRasterNoDataValue'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nRaterIO trouble: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nProcesses: 1\nHeader read time: 0.046472\nData read time: 0.082591\nCompute time: 0.149344\nWrite time: 0.009709\nTotal time: 0.288116\nERROR 10: Pointer 'hDS' is NULL in 'GDALFlushCache'.\n\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/xuancheng/input/dem_xc.tif; 数字高程模型: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 	\N	6	2cf6be48-1562-40b9-a416-ef2ce4ac609f
6432700e62314426b5cbe4057cb74019		\N	2025-01-05 22:02:47.240311	{"inlayer3":"/onesis/kt4/xuancheng/o1875905787788918784.tif","inlayer2":"/onesis/kt4/xuancheng/RESULT1875905787138801664.tif","inlayer1":"/onesis/kt4/xuancheng/sd81875905787914747904.tif","inlayer0":"/onesis/kt4/xuancheng/fel1875905787033944064.tif","inlayer7":"/onesis/kt4/xuancheng/twi1875905788120268800.tif","inlayer6":"/onesis/kt4/xuancheng/o1875905788019605504.tif","inlayer5":"/onesis/kt4/xuancheng/o1875905787566620672.tif","simithred":"0.3","inlayer4":"/onesis/kt4/xuancheng/plan1875905787675672576.tif","sample":"/onesis/kt4/xuancheng/input/xc_samples.csv","target":"SOM","uncmap":"/onesis/kt4/xuancheng/2.tif","predmap":"/onesis/kt4/xuancheng/1.tif"}	f	\N	7d9c8b88-f377-3870-81a6-ac7db3b9956a	基于样点个体代表性的地理空间特征空间推测(iPSM)	土壤样点: /onesis/kt4/xuancheng/input/xc_samples.csv; 待推测土壤属性: SOM; 不确定性阈值参数: 0.3; 土壤属性空间分布: /onesis/kt4/xuancheng/1.tif; 空间推测不确定性: /onesis/kt4/xuancheng/2.tif; DEM栅格: /onesis/kt4/xuancheng/fel1875905787033944064.tif; 汇聚指数: /onesis/kt4/xuancheng/RESULT1875905787138801664.tif; 水动力指数: /onesis/kt4/xuancheng/o1875905788019605504.tif; 地形湿度指数: /onesis/kt4/xuancheng/twi1875905788120268800.tif; 剖面曲率: /onesis/kt4/xuancheng/o1875905787566620672.tif; 平面曲率: /onesis/kt4/xuancheng/plan1875905787675672576.tif; 坡向: /onesis/kt4/xuancheng/o1875905787788918784.tif; 坡度栅格: /onesis/kt4/xuancheng/sd81875905787914747904.tif; 	\N	0	f4b71fd7-895e-451a-b72b-b546e3588f58
7a6c65b77586498aadba64a2f7a39e14		\N	2025-01-05 22:02:47.274225	{"sca":"/onesis/kt4/xuancheng/ad81875905787306573824.tif","slp":"/onesis/kt4/xuancheng/sd81875905787914747904.tif","twi":"/onesis/kt4/xuancheng/twi1875905788120268800.tif"}	f	\N	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	汇流累积量: /onesis/kt4/xuancheng/ad81875905787306573824.tif; 地形湿度指数: /onesis/kt4/xuancheng/twi1875905788120268800.tif; 坡度: /onesis/kt4/xuancheng/sd81875905787914747904.tif; 	\N	0	f4b71fd7-895e-451a-b72b-b546e3588f58
447f7b44de124d479dc91c7496a6a709		\N	2025-01-05 19:56:26.449319	{"sca":"/onesis/kt4/xuancheng/result/ad81875873990623494144.tif","slope":"/onesis/kt4/xuancheng/result/sd81875873991214891008.tif","o":"/onesis/kt4/xuancheng/result/o1875873991315554304.tif"}	f	\N	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/xuancheng/result/ad81875873990623494144.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875873991315554304.tif; 输入坡度 slope 文件: /onesis/kt4/xuancheng/result/sd81875873991214891008.tif; 	\N	0	3b1e6d8e-4054-4109-a136-99153f37b35c
64de25ee7cf6435cba50ab2dc431f9b5		\N	2025-01-05 19:56:26.531034	{"p":"/onesis/kt4/xuancheng/result/p1875873990564773888.tif","ad8":"/onesis/kt4/xuancheng/result/ad81875873990623494144.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/xuancheng/result/p1875873990564773888.tif; d8汇流累积量栅格: /onesis/kt4/xuancheng/result/ad81875873990623494144.tif; 	\N	0	3b1e6d8e-4054-4109-a136-99153f37b35c
b1c71dde2adb4f569bc7da1e70c724c8		2025-01-05 20:06:46.129829	2025-01-05 20:05:44.300157	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif","o":"/onesis/kt4/xuancheng/result/o1875876330827022336.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	Z 转换因子: 1; 输入栅格 DEM 文件: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875876330827022336.tif; 	\N	7	2cf6be48-1562-40b9-a416-ef2ce4ac609f
faa788fc8c4148da8ae8235a1fb47a45		2025-01-05 19:43:16.139794	2025-01-05 19:42:14.496463	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875870416887742464.tif","o":"/onesis/kt4/xuancheng/result/o1875870417705631744.tif"}	f	Pod Status: Pending\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n****************************\n* Welcome to Aspect        *\n* Powered by WhiteboxTools *\n* www.whiteboxgeo.com      *\n****************************\nReading data...\nthread 'main' panicked at 'No such file or directory (os error 2)', whitebox-tools-app/src/main.rs:72:21\nnote: run with `RUST_BACKTRACE=1` environment variable to display a backtrace\nfailed to create fsnotify watcher: too many open files	b69e1bf4-06cf-3d70-be83-81a23ad61ab1	坡向（三阶二元泰勒多项式）	z因子: 1; 输入数据: /onesis/kt4/xuancheng/result/fel1875870416887742464.tif; 输出数据: /onesis/kt4/xuancheng/result/o1875870417705631744.tif; 	\N	7	935d54c3-d3ca-4f45-b904-677b16f7e628
e5040733edd441799a1e5d0b9fa4483c		2025-01-05 19:56:32.259589	2025-01-05 19:56:26.495533	{"z":"/onesis/kt4/xuancheng/input/dem_xc.tif","fel":"/onesis/kt4/xuancheng/result/fel1875873990355058688.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/xuancheng/input/dem_xc.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nERROR 4: Attempt to create new tiff file `/data/onesis/kt4/xuancheng/result/fel1875873990355058688.tif' failed: No error information\nRaterIO trouble: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nProcesses: 1\nHeader read time: 0.062713\nData read time: 0.091994\nCompute time: 0.187248\nWrite time: 0.010051\nTotal time: 0.352006\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetProjection'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetGeoTransform'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALGetRasterBand'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALSetRasterNoDataValue'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALFlushCache'.\n\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/xuancheng/input/dem_xc.tif; 数字高程模型: /onesis/kt4/xuancheng/result/fel1875873990355058688.tif; 	\N	6	3b1e6d8e-4054-4109-a136-99153f37b35c
cdb30921343b406ba885ae8ab09b5cb6		\N	2025-01-05 22:02:47.407178	{"sca":"/onesis/kt4/xuancheng/ad81875905787306573824.tif","slope":"/onesis/kt4/xuancheng/sd81875905787914747904.tif","o":"/onesis/kt4/xuancheng/o1875905788019605504.tif"}	f	\N	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/xuancheng/ad81875905787306573824.tif; 输出栅格文件: /onesis/kt4/xuancheng/o1875905788019605504.tif; 输入坡度 slope 文件: /onesis/kt4/xuancheng/sd81875905787914747904.tif; 	\N	0	f4b71fd7-895e-451a-b72b-b546e3588f58
5d3059bab23941478ff1f28c6945529c		2024-12-30 16:45:11.866385	2024-12-30 16:45:01.822252	{"p":"/onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 39308 flats to resolve.\nDraining flats towards lower adjacent terrain\n........................................\nDraining flats away from higher adjacent terrain\n..............\nSetting directions\nIteration complete. Number of flats remaining: 340\nDraining flats towards lower adjacent terrain\n......\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.051783\nData read time: 0.012650\nCompute Slope time: 0.023587\nWrite Slope time: 0.017741\nResolve Flat time: 0.522052\nWrite Flat time: 0.014774\nTotal time: 0.642587\nfailed to create fsnotify watcher: too many open files	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873651492171415552.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873651492263690240.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
73155d07ccac4d93a0b674d0e138780d		\N	2025-01-05 20:02:09.83931	{"p":"/onesis/kt4/xuancheng/result/p1875875430439976960.tif","ad8":"/onesis/kt4/xuancheng/result/ad81875875430490308608.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/xuancheng/result/p1875875430439976960.tif; d8汇流累积量栅格: /onesis/kt4/xuancheng/result/ad81875875430490308608.tif; 	\N	0	eca378da-de4b-439c-86a0-4260ab89d621
c21df44a33ed4988809b6248f6584834		2024-12-30 16:46:27.977417	2024-12-30 16:45:01.454578	{"op":"/onesis/kt4/job_results/1_ipsm/","c":"gini","mwfl":"0.0","msl":"1","mss":"2","v":"0","ne":"100","md":"3","tl":"/onesis/kt4/data/rf_workflow/2024_12_25/priolo_00-15_landuse_1to2.tif","rfm":"/onesis/kt4/job_results/1_ipsm/op1873651491902980096.tif","sfm":"/onesis/kt4/job_results/1_ipsm/sd81873651492943167488.tif","ca":"0.0","sr":"0.5","wfm":"/onesis/kt4/job_results/1_ipsm/dist1873651492787978240.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nrandom_forest.py:302: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n  rfc_out=rfc.fit(x_train, y_train)\nfailed to create fsnotify watcher: too many open files	a732c661-90df-32da-b10f-33eaae839b21	面向土地利用类型扩张的随机森林	采样率: 0.5; 树木数量: 100; 不纯度方法: gini; 最大深度: 3; 拆分内节点最少样本数: 2; 叶节点最小样本数: 1; 最小加权分数: 0.0; 详细程度: 0; 复杂度参数: 0.0; 土地扩张标签: /onesis/kt4/data/rf_workflow/2024_12_25/priolo_00-15_landuse_1to2.tif; 输出路径: /onesis/kt4/job_results/1_ipsm/; 道路栅格: /onesis/kt4/job_results/1_ipsm/op1873651491902980096.tif; 河网栅格: /onesis/kt4/job_results/1_ipsm/dist1873651492787978240.tif; 坡度栅格: /onesis/kt4/job_results/1_ipsm/sd81873651492943167488.tif; 	\N	6	a85b64d9-5902-4a05-b7d3-db7ea34b089d
b526fdf0e0474c5a957c88daed3ea3a8		2025-01-05 20:06:47.507095	2025-01-05 20:05:44.34547	{"NEIGHBOURS":"0","ELEVATION":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif","METHOD":"0","RESULT":"/onesis/kt4/xuancheng/result/RESULT1875876330436952064.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n____________________________\n\n   #####   ##   #####    ##\n  ###     ###  ##       ###\n   ###   # ## ##  #### # ##\n    ### ##### ##    # #####\n ##### #   ##  ##### #   ##\n____________________________\n\nSAGA Version: 8.1.0\n\nError: input file [/data/onesis/kt4/xuancheng/result/fel1875876330323705856.tif]\nError: Elevation\n____________________________\nlibrary path: /usr/local/lib/saga/\nlibrary name: libta_morphometry\nlibrary     : ta_morphometry\ntool        : Convergence Index\nidentifier  : 1\nauthor      : O.Conrad (c) 2001\nprocessors  : 8 [8]\n____________________________\n\n\nUsage: saga_cmd ta_morphometry 1 [-ELEVATION <str>] [-RESULT <str>] [-METHOD <str>] [-NEIGHBOURS <str>]\n  -ELEVATION:<str> \tElevation\n\tGrid, input\n  -RESULT:<str>    \tConvergence Index\n\tGrid, output\n  -METHOD:<str>    \tMethod\n\tChoice\n\tAvailable Choices:\n\t[0] Aspect\n\t[1] Gradient\n\tDefault: 0\n  -NEIGHBOURS:<str>\tGradient Calculation\n\tChoice\n\tAvailable Choices:\n\t[0] 2 x 2\n\t[1] 3 x 3\n\tDefault: 0\nfailed to create fsnotify watcher: too many open files	2dbff9e6-c834-33a7-b5f1-b4b54c0b2612	地形汇聚指数	计算方式: 0; 邻域窗口大小: 0; 数字高程模型: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 地形结构指数: /onesis/kt4/xuancheng/result/RESULT1875876330436952064.tif; 	\N	7	2cf6be48-1562-40b9-a416-ef2ce4ac609f
98473bd78ab5475b85eae429af0bad17		2025-01-05 20:02:15.429453	2025-01-05 20:02:09.803251	{"z":"/onesis/kt4/xuancheng/input/dem_xc.tif","fel":"/onesis/kt4/xuancheng/result/fel1875875430238650368.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/xuancheng/input/dem_xc.tif has geographic coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nERROR 4: Attempt to create new tiff file `/data/onesis/kt4/xuancheng/result/fel1875875430238650368.tif' failed: No error information\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetProjection'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALSetGeoTransform'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALGetRasterBand'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALSetRasterNoDataValue'.\n\nERROR 10: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nERROR 10: Pointer 'hDS' is NULL in 'GDALFlushCache'.\n\nRaterIO trouble: Pointer 'hBand' is NULL in 'GDALRasterIO'.\n\nProcesses: 1\nHeader read time: 0.046073\nData read time: 0.085095\nCompute time: 0.152833\nWrite time: 0.009979\nTotal time: 0.293980\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/xuancheng/input/dem_xc.tif; 数字高程模型: /onesis/kt4/xuancheng/result/fel1875875430238650368.tif; 	\N	6	eca378da-de4b-439c-86a0-4260ab89d621
4667c58512a94f7085e382360ed6f1fc		\N	2025-01-05 22:02:47.508251	{"p":"/onesis/kt4/xuancheng/p1875905787252047872.tif","ad8":"/onesis/kt4/xuancheng/ad81875905787306573824.tif"}	f	\N	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/xuancheng/p1875905787252047872.tif; d8汇流累积量栅格: /onesis/kt4/xuancheng/ad81875905787306573824.tif; 	\N	0	f4b71fd7-895e-451a-b72b-b546e3588f58
3096cf98574c4982aae11a0108fd02ae		2025-01-05 20:06:47.607676	2025-01-05 20:05:44.230071	{"sd8":"/onesis/kt4/xuancheng/result/sd81875876331124817920.tif","fel":"/onesis/kt4/xuancheng/result/fel1875876330323705856.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nError opening file /data/onesis/kt4/xuancheng/result/fel1875876330323705856.tif.\nERROR 4: /data/onesis/kt4/xuancheng/result/fel1875876330323705856.tif: No such file or directory\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD\nwith errorcode 21.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nfailed to create fsnotify watcher: too many open files	d3639683-4569-3091-84dd-3bf440f04df0	坡度（最大下坡）	已填洼数字高程模型: /onesis/kt4/xuancheng/result/fel1875876330323705856.tif; 坡度栅格: /onesis/kt4/xuancheng/result/sd81875876331124817920.tif; 	\N	7	2cf6be48-1562-40b9-a416-ef2ce4ac609f
2c4781292ade489088590d752f138d49		2025-01-05 21:15:59.257765	2025-01-05 21:14:53.995064	{"p":"/onesis/kt4/xuancheng/result/p1875893733791236096.tif","fel":"/onesis/kt4/xuancheng/result/fel1875893733577326592.tif"}	f	Pod Status: Running\nPodReadyToStartContainers: True\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nError opening file /data/onesis/kt4/xuancheng/result/fel1875893733577326592.tif.\nERROR 4: /data/onesis/kt4/xuancheng/result/fel1875893733577326592.tif: No such file or directory\n--------------------------------------------------------------------------\nMPI_ABORT was invoked on rank 0 in communicator MPI_COMM_WORLD\nwith errorcode 21.\n\nNOTE: invoking MPI_ABORT causes Open MPI to kill all MPI processes.\nYou may or may not see output from other processes, depending on\nexactly when Open MPI kills them.\n--------------------------------------------------------------------------\nfailed to create fsnotify watcher: too many open files	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/xuancheng/result/fel1875893733577326592.tif; D8单流向栅格: /onesis/kt4/xuancheng/result/p1875893733791236096.tif; 	\N	7	9a866cc3-c9a0-4c5f-ae94-8a39f6ad2923
645f4baf6e624143abc11d754607b6d6		2024-12-30 16:47:46.093187	2024-12-30 16:47:19.59194	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif","slope":"/onesis/kt4/job_results/1_ipsm/sd81873652070633046016.tif","o":"/onesis/kt4/job_results/1_ipsm/o1873652071543209984.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\n*******************************\n* Welcome to StreamPowerIndex *\n* Powered by WhiteboxTools    *\n* www.whiteboxgeo.com         *\n*******************************\nReading data...\nProgress: 0%\nProgress: 1%\nProgress: 2%\nProgress: 3%\nProgress: 4%\nProgress: 5%\nProgress: 6%\nProgress: 7%\nProgress: 8%\nProgress: 9%\nProgress: 10%\nProgress: 11%\nProgress: 12%\nProgress: 13%\nProgress: 14%\nProgress: 15%\nProgress: 16%\nProgress: 17%\nProgress: 18%\nProgress: 19%\nProgress: 20%\nProgress: 21%\nProgress: 22%\nProgress: 23%\nProgress: 24%\nProgress: 25%\nProgress: 26%\nProgress: 27%\nProgress: 28%\nProgress: 29%\nProgress: 30%\nProgress: 31%\nProgress: 32%\nProgress: 33%\nProgress: 34%\nProgress: 35%\nProgress: 36%\nProgress: 37%\nProgress: 38%\nProgress: 39%\nProgress: 40%\nProgress: 41%\nProgress: 42%\nProgress: 43%\nProgress: 44%\nProgress: 45%\nProgress: 46%\nProgress: 47%\nProgress: 48%\nProgress: 49%\nProgress: 50%\nProgress: 51%\nProgress: 52%\nProgress: 53%\nProgress: 54%\nProgress: 55%\nProgress: 56%\nProgress: 57%\nProgress: 58%\nProgress: 59%\nProgress: 60%\nProgress: 61%\nProgress: 62%\nProgress: 63%\nProgress: 64%\nProgress: 65%\nProgress: 66%\nProgress: 67%\nProgress: 68%\nProgress: 69%\nProgress: 70%\nProgress: 71%\nProgress: 72%\nProgress: 73%\nProgress: 74%\nProgress: 75%\nProgress: 76%\nProgress: 77%\nProgress: 78%\nProgress: 79%\nProgress: 80%\nProgress: 81%\nProgress: 82%\nProgress: 83%\nProgress: 84%\nProgress: 85%\nProgress: 86%\nProgress: 87%\nProgress: 88%\nProgress: 89%\nProgress: 90%\nProgress: 91%\nProgress: 92%\nProgress: 93%\nProgress: 94%\nProgress: 95%\nProgress: 96%\nProgress: 97%\nProgress: 98%\nProgress: 99%\nProgress: 100%\nSaving data...\nOutput file written\nElapsed Time (excluding I/O): 0.28s\nfailed to create fsnotify watcher: too many open files	e4d5b0ab-6d31-3fae-9c44-817b0a0b4df7	水流功率指数	输入单位汇水面积 sca 文件: /onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif; 输入坡度 slope 文件: /onesis/kt4/job_results/1_ipsm/sd81873652070633046016.tif; 输出栅格文件: /onesis/kt4/job_results/1_ipsm/o1873652071543209984.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
098acf061dc84720965f96f63e131af1		2024-12-30 16:47:24.789641	2024-12-30 16:47:19.667753	{"z":"/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nPitRemove version 5.3.9\nInput file /data/onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nProcesses: 1\nHeader read time: 0.030671\nData read time: 0.094121\nCompute time: 0.159553\nWrite time: 0.064028\nTotal time: 0.348374\nfailed to create fsnotify watcher: too many open files	cc241952-4ff2-36f3-ba31-d23ccd3919df	填洼（坡度抬升填平）	数字高程模型: /onesis/kt4/dsm_case/xuancheng/dem_xc_900913.tif; 数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
cf173a3aea0f49929d1176bf97685327		2025-01-05 20:03:12.404726	2025-01-05 20:02:09.728936	{"zfactor":"1","i":"/onesis/kt4/xuancheng/result/fel1875875430238650368.tif","o":"/onesis/kt4/xuancheng/result/o1875875430754549760.tif"}	f	\N	9db5af17-3f21-3265-924b-afa40e7ddf8a	剖面曲率	Z 转换因子: 1; 输入栅格 DEM 文件: /onesis/kt4/xuancheng/result/fel1875875430238650368.tif; 输出栅格文件: /onesis/kt4/xuancheng/result/o1875875430754549760.tif; 	\N	7	eca378da-de4b-439c-86a0-4260ab89d621
8e089fec0aa8430a9db3c05f7d024c6a		2024-12-30 16:47:34.61768	2024-12-30 16:47:19.813264	{"p":"/onesis/kt4/job_results/1_ipsm/p1873652071362854912.tif","fel":"/onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nD8FlowDir version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nAll slopes evaluated. 110608 flats to resolve.\nDraining flats towards lower adjacent terrain\n...................................................................................................\nDraining flats away from higher adjacent terrain\n........\nSetting directions\nIteration complete. Number of flats remaining: 3414\nDraining flats towards lower adjacent terrain\n.....\nDraining flats away from higher adjacent terrain\n....\nSetting directions\nProcessors: 1\nHeader read time: 0.047197\nData read time: 0.168500\nCompute Slope time: 0.283699\nWrite Slope time: 0.075916\nResolve Flat time: 3.574122\nWrite Flat time: 0.042254\nTotal time: 4.191689\nfailed to create fsnotify watcher: too many open files	eb43c54f-a81c-3c0f-9d7d-69f305c7fd5e	流向(D8)	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif; D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873652071362854912.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
9a9b8994f3a6497080cb11af7d6ee6ff		2024-12-30 16:47:31.664109	2024-12-30 16:47:19.516127	{"fel":"/onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif","plan":"/onesis/kt4/job_results/1_ipsm/plan1873652070389776384.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nCurvature -h version 5.3.9, by Liangjun Zhu, Apr 8, 2015\nInput file /data/onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif has projected coordinate system.\nNodata value input to create partition from file: -9999.000000\nNodata value recast to float used in partition raster: -9999.000000\nProcessors: 1\nRead time: 0.729661\nCompute time: 0.117577\nWrite time: 0.328920\nTotal time: 1.176157\nfailed to create fsnotify watcher: too many open files	d8bcff1d-3318-35bf-ae69-540b08d4c3ec	平面曲率	数字高程模型: /onesis/kt4/job_results/1_ipsm/fel1873652070217809920.tif; 平面曲率栅格: /onesis/kt4/job_results/1_ipsm/plan1873652070389776384.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
5b007ad87ba943cc81df9faada9f9491		2024-12-30 16:47:40.305517	2024-12-30 16:47:19.718903	{"p":"/onesis/kt4/job_results/1_ipsm/p1873652071362854912.tif","ad8":"/onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nAreaD8 version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/p1873652071362854912.tif has projected coordinate system.\nNodata value input to create partition from file: -32768.000000\nNodata value recast to int16_t used in partition raster: -32768\nNumber of Processes: 1\nRead time: 0.077755\nCompute time: 0.196079\nWrite time: 0.056074\nTotal time: 0.329908\nfailed to create fsnotify watcher: too many open files	6665e8c4-ef1d-3c7a-9bfc-35ad56239a8c	汇流累积量_D8（栅格）	D8单流向栅格: /onesis/kt4/job_results/1_ipsm/p1873652071362854912.tif; d8汇流累积量栅格: /onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
e8c38a11122444f78d553f14f97dbf00		2024-12-30 16:47:46.109575	2024-12-30 16:47:19.418947	{"sca":"/onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif","slp":"/onesis/kt4/job_results/1_ipsm/sd81873652070633046016.tif","twi":"/onesis/kt4/job_results/1_ipsm/twi1873652071669039104.tif"}	f	Pod Status: Succeeded\nPodReadyToStartContainers: False\nInitialized: True\nReady: False\nContainersReady: False\nPodScheduled: True\nTopographic Wetness Index version 5.3.9\nInput file /data/onesis/kt4/job_results/1_ipsm/sd81873652070633046016.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nThis run may take on the order of 1 minutes to complete.\nThis estimate is very approximate. \nRun time is highly uncertain as it depends on the complexity of the input data \nand speed and memory of the computer. This estimate is based on our testing on \na dual quad core Dell Xeon E5405 2.0GHz PC with 16GB RAM.\nInput file /data/onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif has projected coordinate system.\nNodata value input to create partition from file: -1.000000\nNodata value recast to float used in partition raster: -1.000000\nCompute time: 0.031594\nfailed to create fsnotify watcher: too many open files	da1949e3-a546-335b-8507-c1231c35e2a8	地形湿度指数	坡度: /onesis/kt4/job_results/1_ipsm/sd81873652070633046016.tif; 汇流累积量: /onesis/kt4/job_results/1_ipsm/ad81873652071450935296.tif; 地形湿度指数: /onesis/kt4/job_results/1_ipsm/twi1873652071669039104.tif; 	\N	6	00a5931e-c9be-4f6d-847f-31f5b9d8e4ff
