{ "outputs": [ { "case": "stats", "http_url": "http://adam.noveltis.fr/web-output//20191212230105.92422/ADAM_BRDFplane_land_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.png", "title": "BRDF Transect Plane - land", "type": "brdf_transect_plane", "filename": "/home/www/data/adam/web-root/web-output/20191212230105.92422/ADAM_BRDFplane_land_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.png" }, { "case": "stats", "http_url": "http://adam.noveltis.fr/web-output//20191212230105.92422/ADAM_BRDFplane_ocean_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.png", "title": "BRDF Transect Plane - ocean", "type": "brdf_transect_plane", "filename": "/home/www/data/adam/web-root/web-output/20191212230105.92422/ADAM_BRDFplane_ocean_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.png" }, { "case": null, "http_url": "http://adam.noveltis.fr/web-output//20191212230105.92422/ADAM_netcdf_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.nc", "title": null, "type": "netcdf_output", "filename": "/home/www/data/adam/web-root/web-output/20191212230105.92422/ADAM_netcdf_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.nc" } ], "log": [ "0.0369: job_output_dir is None : CREATION", "0.0374: job_output_dir is now /home/www/data/adam/web-root/web-output//20191212230105.92422", "0.0376: begin BRDF job on host: virtprod1.noveltis.loc", "0.0376: received request dictionary: {'fieldLonMax': '-2.1', 'fieldLatMin': '36.5', 'fieldLatMax': '36.9', 'fieldGenerateGraphs': 'true', 'fieldOperationType': 'brdf', 'fieldMonth': 'jan', 'fieldBRDFType': 'plane', 'fieldSunZenith': '40', 'fieldRelAzimuth': '1', 'fieldComputeError': 'true', 'fieldSpectralDomain': '300-400', 'fieldViewZenith': '20', 'fieldLonMin': '-2.3'}", "0.0376: parsing BRDF input", "0.0389: all input was validated", "0.0390: extent is: -2.30000, 36.50000, -2.10000, 36.90000", "0.0390: month_index is: 0", "0.0403: spectral ranges are: [[300 400]]", "0.0405: sza is: [ 40.]", "0.0407: phi is: [ 1.]", "0.0407: compute error is: True", "0.0407: generate graphs is: True", "0.0407: begin loading requested data from source file", "0.0410: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc in reading", "0.0410: adam_io.py line 38 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.4391: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.4393: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc in reading", "0.4393: adam_io.py line 145 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "0.7863: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "0.7880: 4 land pixels, 4 ocean pixels, 0 snow pixels", "0.7880: begin calculating reflectance spectra", "0.7880: process_reflectance.main Initialisation", "0.7881: process_reflectance.main flatten to 2d and 1d arrays", "0.7881: process_reflectance.main initialise the variable to be returned", "0.7881: process_reflectance.main if do_compute_error", "0.7882: process_reflectance.main Land", "0.8829: process_reflectance.main Snow", "0.8829: process_reflectance.main Ocean", "0.9377: reflectance_spectrum_ocean : End", "0.9378: process_reflectance.reflectance_spectrum_ocean Done", "0.9380: process_reflectance.main Reshape", "0.9393: define_vza_hotspot", "0.9395: begin calculating brdf and brdf error", "0.9554: perform BRDF stats analysis", "0.9559: draw graph, transect plane, case stats", "1.4862: saving netcdf data 2", "1.4917: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.4918: output_var[:] = self.dataNC[u'longitude'].T[:]", "1.4969: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.4970: output_var[:] = self.dataNC[u'latitude'].T[:]", "1.5003: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.5003: sf = 0.000100", "1.5003: offset = 0.000000", "1.5004: missval = -8421", "1.5004: data = np.ma.masked_equal(self.data[u'ref_land'], missval)", "1.5004: type of self.data[u'ref_land'] = ", "1.5015: self.data[u'ref_land'] = array([[[ 0.0774 , 0.1236 , 0.15789999, 0.24249999, 0.26109999,\n 0.25329998, 0.19029999],\n [ 0.055 , 0.0844 , 0.1096 , 0.1831 , 0.22149999,\n 0.2181 , 0.16579999],\n [ nan, nan, nan, nan, nan,\n nan, nan],\n [ nan, nan, nan, nan, nan,\n nan, nan]],\n\n [[ 0.0608 , 0.09429999, 0.12109999, 0.2075 , 0.2489 ,\n 0.2428 , 0.1758 ],\n [ 0.054 , 0.0835 , 0.10439999, 0.1741 , 0.19649999,\n 0.18979999, 0.14229999],\n [ nan, nan, nan, nan, nan,\n nan, nan],\n [ nan, nan, nan, nan, nan,\n nan, nan]]], dtype=float32)", "1.5104: output_var[:] = self.dataNC[u'ref_land'].T[:]", "1.5139: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.5139: sf = 0.001436", "1.5139: offset = 47.068424", "1.5140: missval = -32768", "1.5140: data = np.ma.masked_equal(self.data[u'chloro_conc'], missval)", "1.5140: type of self.data[u'chloro_conc'] = ", "1.5143: self.data[u'chloro_conc'] = array([[ nan, nan, 0.686627 , 0.67513533],\n [ nan, nan, 0.62342284, 0.63778742]])", "1.5146: output_var[:] = self.dataNC[u'chloro_conc'].T[:]", "1.5190: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.5191: sf = 0.000530", "1.5191: offset = 17.755947", "1.5191: missval = -32768", "1.5191: data = np.ma.masked_equal(self.data[u'wind_speed'], missval)", "1.5191: type of self.data[u'wind_speed'] = ", "1.5195: self.data[u'wind_speed'] = array([[ nan, nan, 6.95105396, 7.07605787],\n [ nan, nan, 6.89437846, 6.99236881]])", "1.5197: output_var[:] = self.dataNC[u'wind_speed'].T[:]", "1.5233: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.5234: output_var[:] = self.dataNC[u'qf'].T[:]", "1.5940: job finished, took 1.5939707756 seconds" ], "success": "true" }