From bb259274ba35c8d8a3e9729af2715be6d917b090 Mon Sep 17 00:00:00 2001 From: veenstrajelmer Date: Mon, 12 Aug 2024 17:20:21 +0200 Subject: [PATCH] updated notebook --- docs/notebooks/modelbuilder_example.ipynb | 247 +++++++++++++++------- 1 file changed, 170 insertions(+), 77 deletions(-) diff --git a/docs/notebooks/modelbuilder_example.ipynb b/docs/notebooks/modelbuilder_example.ipynb index 298a6462e..9d76631e8 100644 --- a/docs/notebooks/modelbuilder_example.ipynb +++ b/docs/notebooks/modelbuilder_example.ipynb @@ -125,8 +125,8 @@ "name": "stdout", "output_type": "stream", "text": [ - ">> reading coastlines: 2.97 sec\n", - ">> reading coastlines: 2.94 sec\n" + ">> reading coastlines: 3.06 sec\n", + ">> reading coastlines: 3.00 sec\n" ] }, { @@ -169,7 +169,7 @@ "name": "stdout", "output_type": "stream", "text": [ - ">> reading coastlines: 2.91 sec\n" + ">> reading coastlines: 3.05 sec\n" ] }, { @@ -216,8 +216,8 @@ "name": "stdout", "output_type": "stream", "text": [ - ">> reading coastlines: 2.89 sec\n", - ">> reading coastlines: 2.90 sec\n" + ">> reading coastlines: 3.33 sec\n", + ">> reading coastlines: 3.51 sec\n" ] }, { @@ -255,7 +255,7 @@ "name": "stdout", "output_type": "stream", "text": [ - ">> reading coastlines: 2.91 sec\n" + ">> reading coastlines: 3.17 sec\n" ] }, { @@ -331,7 +331,7 @@ "> interp mfdataset to all PolyFile points (lat/lon coordinates)\n", "> actual extraction of data from netcdf with .load() (for 71 plipoints at once, this might take a while)\n", ">>time passed: 0.00 sec\n", - "Converting 71 plipoints to hcdfm.ForcingModel(): 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71. >> done in 0.12 sec\n" + "Converting 71 plipoints to hcdfm.ForcingModel(): 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71. >> done in 0.13 sec\n" ] } ], @@ -358,7 +358,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:12:33Z - You are already logged in. Skipping login.\n" + "INFO - 2024-08-12T14:59:46Z - You are already logged in. Skipping login.\n" ] }, { @@ -372,15 +372,15 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:12:33Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:12:33Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:12:35Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:12:39Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:12:39Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:12:41Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:12:45Z - Dataset version was not specified, the latest one was selected: \"202406\"\n", - "INFO - 2024-08-12T14:12:45Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:12:47Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n" + "INFO - 2024-08-12T14:59:47Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T14:59:47Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T14:59:49Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T14:59:53Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T14:59:53Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T14:59:55Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T14:59:59Z - Dataset version was not specified, the latest one was selected: \"202406\"\n", + "INFO - 2024-08-12T14:59:59Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:01Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n" ] }, { @@ -394,12 +394,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:12:52Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:12:52Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:12:54Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:12:58Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:12:58Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:00Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" + "INFO - 2024-08-12T15:00:06Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:06Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:08Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T15:00:12Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:12Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:15Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" ] }, { @@ -416,7 +416,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:04Z - You are already logged in. Skipping login.\n" + "INFO - 2024-08-12T15:00:20Z - You are already logged in. Skipping login.\n" ] }, { @@ -430,12 +430,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:05Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:05Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:07Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:13:11Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:11Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:13Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" + "INFO - 2024-08-12T15:00:21Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:21Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:23Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T15:00:27Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:27Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:29Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" ] }, { @@ -452,7 +452,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:17Z - You are already logged in. Skipping login.\n" + "INFO - 2024-08-12T15:00:34Z - You are already logged in. Skipping login.\n" ] }, { @@ -466,12 +466,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:18Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:18Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:20Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:13:24Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:24Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:26Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" + "INFO - 2024-08-12T15:00:35Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:35Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:37Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T15:00:41Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:41Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:43Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" ] }, { @@ -488,7 +488,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:31Z - You are already logged in. Skipping login.\n" + "INFO - 2024-08-12T15:00:50Z - You are already logged in. Skipping login.\n" ] }, { @@ -502,12 +502,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:32Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:32Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:33Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:13:38Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:38Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:39Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" + "INFO - 2024-08-12T15:00:51Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:51Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:52Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T15:00:57Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:00:57Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:00:59Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" ] }, { @@ -524,7 +524,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:44Z - You are already logged in. Skipping login.\n" + "INFO - 2024-08-12T15:01:03Z - You are already logged in. Skipping login.\n" ] }, { @@ -538,12 +538,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "INFO - 2024-08-12T14:13:44Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:44Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:46Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", - "INFO - 2024-08-12T14:13:50Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", - "INFO - 2024-08-12T14:13:50Z - Dataset part was not specified, the first one was selected: \"default\"\n", - "INFO - 2024-08-12T14:13:53Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" + "INFO - 2024-08-12T15:01:04Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:01:04Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:01:06Z - Service was not specified, the default one was selected: \"arco-geo-series\"\n", + "INFO - 2024-08-12T15:01:11Z - Dataset version was not specified, the latest one was selected: \"202311\"\n", + "INFO - 2024-08-12T15:01:11Z - Dataset part was not specified, the first one was selected: \"default\"\n", + "INFO - 2024-08-12T15:01:12Z - Service was not specified, the default one was selected: \"arco-time-series\"\n" ] }, { @@ -634,8 +634,8 @@ "name": "stdout", "output_type": "stream", "text": [ - ">> reading coastlines: 3.09 sec\n", - ">> reading coastlines: 2.94 sec\n" + ">> reading coastlines: 2.97 sec\n", + ">> reading coastlines: 3.06 sec\n" ] }, { @@ -735,21 +735,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "loading mfdataset of 0 files with pattern(s) c:\\DATA\\dfm_tools\\docs\\notebooks\\Vietnam_model\\data\\cmems\\cmems_{ncvarname}_*.nc\n" - ] - }, - { - "ename": "OSError", - "evalue": "no files to open", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mOSError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[13], line 7\u001b[0m\n\u001b[0;32m 3\u001b[0m ext_old \u001b[38;5;241m=\u001b[39m hcdfm\u001b[38;5;241m.\u001b[39mExtOldModel()\n\u001b[0;32m 5\u001b[0m \u001b[38;5;66;03m# CMEMS - initial conditions\u001b[39;00m\n\u001b[0;32m 6\u001b[0m \u001b[38;5;66;03m# salinity/temperature can only be added in case of 3D model and iniwithnudge\u001b[39;00m\n\u001b[1;32m----> 7\u001b[0m ext_old \u001b[38;5;241m=\u001b[39m \u001b[43mdfmt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcmems_nc_to_ini\u001b[49m\u001b[43m(\u001b[49m\u001b[43mext_old\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mext_old\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43mdir_output\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdir_output\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mlist_quantities\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mwaterlevelbnd\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# list_quantities,\u001b[39;49;00m\n\u001b[0;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43mtstart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdate_min\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 11\u001b[0m \u001b[43m \u001b[49m\u001b[43mdir_pattern\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdir_pattern\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 13\u001b[0m \u001b[38;5;66;03m# ERA5 - download spatial fields of air pressure, wind speeds and Charnock coefficient\u001b[39;00m\n\u001b[0;32m 14\u001b[0m dir_output_data_era5 \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mpath\u001b[38;5;241m.\u001b[39mjoin(dir_output_data, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mERA5\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", - "File \u001b[1;32mC:\\DATA\\dfm_tools\\dfm_tools\\modelbuilder.py:127\u001b[0m, in \u001b[0;36mcmems_nc_to_ini\u001b[1;34m(ext_old, dir_output, list_quantities, tstart, dir_pattern, conversion_dict)\u001b[0m\n\u001b[0;32m 125\u001b[0m varname \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 126\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 127\u001b[0m data_xr \u001b[38;5;241m=\u001b[39m \u001b[43mdfmt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset_extra\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdir_pattern\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdir_pattern\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mquantity\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mquan_bnd\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 128\u001b[0m \u001b[43m \u001b[49m\u001b[43mtstart\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtstart_round\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtstop\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtstop_round\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 129\u001b[0m \u001b[43m \u001b[49m\u001b[43mconversion_dict\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconversion_dict\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 130\u001b[0m quantity \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124minitial\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquan_bnd\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbnd\u001b[39m\u001b[38;5;124m\"\u001b[39m,\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 131\u001b[0m varname \u001b[38;5;241m=\u001b[39m quantity\n", - "File \u001b[1;32mC:\\DATA\\dfm_tools\\dfm_tools\\interpolate_grid2bnd.py:375\u001b[0m, in \u001b[0;36mopen_dataset_extra\u001b[1;34m(dir_pattern, quantity, tstart, tstop, conversion_dict, refdate_str, chunks)\u001b[0m\n\u001b[0;32m 372\u001b[0m file_list_nc \u001b[38;5;241m=\u001b[39m glob\u001b[38;5;241m.\u001b[39mglob(\u001b[38;5;28mstr\u001b[39m(dir_pattern))\n\u001b[0;32m 373\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mloading mfdataset of \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mlen\u001b[39m(file_list_nc)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m files with pattern(s) \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdir_pattern\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m--> 375\u001b[0m data_xr \u001b[38;5;241m=\u001b[39m \u001b[43mxr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_mfdataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile_list_nc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchunks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mchunks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjoin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mexact\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m#TODO: does chunks argument solve \"PerformanceWarning: Slicing is producing a large chunk.\"? {'time':1} is not a convenient chunking to use for timeseries extraction\u001b[39;00m\n\u001b[0;32m 377\u001b[0m data_xr \u001b[38;5;241m=\u001b[39m ds_apply_conventions(data_xr\u001b[38;5;241m=\u001b[39mdata_xr)\n\u001b[0;32m 378\u001b[0m data_xr \u001b[38;5;241m=\u001b[39m ds_apply_conversion_dict(data_xr\u001b[38;5;241m=\u001b[39mdata_xr, conversion_dict\u001b[38;5;241m=\u001b[39mconversion_dict, quantity\u001b[38;5;241m=\u001b[39mquantity)\n", - "File \u001b[1;32m~\\Anaconda3\\envs\\dfm_tools_env\\Lib\\site-packages\\xarray\\backends\\api.py:1019\u001b[0m, in \u001b[0;36mopen_mfdataset\u001b[1;34m(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)\u001b[0m\n\u001b[0;32m 1016\u001b[0m paths \u001b[38;5;241m=\u001b[39m _find_absolute_paths(paths, engine\u001b[38;5;241m=\u001b[39mengine, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 1018\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m paths:\n\u001b[1;32m-> 1019\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mOSError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mno files to open\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 1021\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m combine \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnested\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[0;32m 1022\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(concat_dim, (\u001b[38;5;28mstr\u001b[39m, DataArray)) \u001b[38;5;129;01mor\u001b[39;00m concat_dim \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "\u001b[1;31mOSError\u001b[0m: no files to open" + "loading mfdataset of 3 files with pattern(s) c:\\DATA\\dfm_tools\\docs\\notebooks\\Vietnam_model\\data\\cmems\\cmems_zos_*.nc\n", + "variable zos renamed to waterlevelbnd\n", + "writing file\n", + "found ECMWF API-key and authorization successful\n", + "retrieving data from 2022-11 to 2022-11 (freq=)\n", + "\"era5_msl_2022-11.nc\" found and overwrite=False, continuing.\n", + "found ECMWF API-key and authorization successful\n", + "retrieving data from 2022-11 to 2022-11 (freq=)\n", + "\"era5_u10n_2022-11.nc\" found and overwrite=False, continuing.\n", + "found ECMWF API-key and authorization successful\n", + "retrieving data from 2022-11 to 2022-11 (freq=)\n", + "\"era5_v10n_2022-11.nc\" found and overwrite=False, continuing.\n", + "found ECMWF API-key and authorization successful\n", + "retrieving data from 2022-11 to 2022-11 (freq=)\n", + "\"era5_chnk_2022-11.nc\" found and overwrite=False, continuing.\n", + ">> opening multifile dataset of 4 files (can take a while with lots of files): 0.08 sec\n", + ">> writing file (can take a while): 0.04 sec\n" ] } ], @@ -791,10 +793,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "aa42e934", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ">> reading coastlines: 3.44 sec\n", + ">> reading coastlines: 3.35 sec\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# plot converted ERA5 data\n", "file_era5 = os.path.join(dir_output,'ERA5*.nc')\n", @@ -824,10 +845,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "630f7aa2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " x y name\n", + "2692 106.631250 17.939755 x106p63_y17p94\n", + "4442 106.065626 18.372601 x106p07_y18p37\n", + "786 106.327084 18.158794 x106p33_y18p16\n", + "4426 106.023439 18.359728 x106p02_y18p36\n", + "3470 106.428127 18.143503 x106p43_y18p14\n", + "2493 106.243750 18.455523 x106p24_y18p46\n", + "4842 106.515626 17.994318 x106p52_y17p99\n", + "7243 106.220313 18.250958 x106p22_y18p25\n", + "6457 106.526564 17.915335 x106p53_y17p92\n", + "7501 105.970314 18.422648 x105p97_y18p42\n", + ">> reading coastlines: 3.07 sec\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# generate obspoints on all grid faces\n", "xpts = xu_grid_uds.grid.face_x\n", @@ -866,7 +916,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "0f01a183", "metadata": {}, "outputs": [], @@ -925,10 +975,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "402cdb08", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing dimr_config.xml\n", + "no dimrset_folder provided, cannot write bat/sh file\n" + ] + } + ], "source": [ "nproc = 1 # number of processes\n", "dimrset_folder = None # alternatively r\"c:\\Program Files\\Deltares\\Delft3D FM Suite 2023.03 HMWQ\\plugins\\DeltaShell.Dimr\\kernels\" #alternatively r\"p:\\d-hydro\\dimrset\\weekly\\2.25.17.78708\"\n", @@ -945,10 +1004,44 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "25bcaec2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " c:\\DATA\\dfm_tools\\docs\\notebooks\\Vietnam_model\\Vietnam.mdu\n", + " Geometry\n", + " ∟ Vietnam_net.nc\n", + " ExternalForcing\n", + " ∟ Vietnam_old.ext\n", + " ∟ ExtOldForcing\n", + " ∟ initialwaterlevel_2022-11-01_00-00-00.nc\n", + " ∟ ExtOldForcing\n", + " ∟ era5_msl_u10n_v10n_chnk_20221101to20221103_ERA5.nc\n", + " ∟ Vietnam_new.ext\n", + " ∟ Boundary\n", + " ∟ Vietnam.pli\n", + " ∟ tide_tpxo80_opendap.bc\n", + " ∟ Boundary\n", + " ∟ Vietnam.pli\n", + " ∟ waterlevelbnd_CMEMS.bc\n", + " ∟ Boundary\n", + " ∟ Vietnam.pli\n", + " ∟ salinitybnd_CMEMS.bc\n", + " ∟ Boundary\n", + " ∟ Vietnam.pli\n", + " ∟ temperaturebnd_CMEMS.bc\n", + " ∟ Boundary\n", + " ∟ Vietnam.pli\n", + " ∟ uxuyadvectionvelocitybnd_CMEMS.bc\n", + " Output\n", + " ∟ Vietnam_obs.xyn\n" + ] + } + ], "source": [ "# visualize the model tree, show_tree is available for all HYDROLIB-core model components\n", "mdu_obj = hcdfm.FMModel(mdu_file)\n",