{ "outputs": [ { "case": "stats", "http_url": "http://adam.noveltis.fr/web-output//20201205175834.38391/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/20201205175834.38391/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//20201205175834.38391/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/20201205175834.38391/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//20201205175834.38391/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/20201205175834.38391/ADAM_netcdf_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.nc" } ], "log": [ "0.0536: job_output_dir is None : CREATION", "0.0537: job_output_dir is now /home/www/data/adam/web-root/web-output//20201205175834.38391", "0.0875: begin BRDF job on host: virtprod1.noveltis.loc", "0.0876: 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'}", "0.0876: parsing BRDF input", "0.0884: all input was validated", "0.0885: extent is: -2.30000, 36.50000, -2.10000, 36.90000", "0.0885: month_index is: 0", "0.0902: spectral ranges are: [[300 400]]", "0.0909: sza is: [ 40.]", "0.0914: phi is: [ 1.]", "0.0915: compute error is: True", "0.0915: generate graphs is: True", "0.0915: begin loading requested data from source file", "0.0916: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc in reading", "0.0916: adam_io.py line 38 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.9832: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.9833: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc in reading", "0.9833: adam_io.py line 145 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "1.2273: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "1.2282: 4 land pixels, 4 ocean pixels, 0 snow pixels", "1.2282: begin calculating reflectance spectra", "1.2282: process_reflectance.main Initialisation", "1.2282: process_reflectance.main flatten to 2d and 1d arrays", "1.2282: process_reflectance.main initialise the variable to be returned", "1.2283: process_reflectance.main if do_compute_error", "1.2284: process_reflectance.main Land", "1.3760: process_reflectance.main Snow", "1.3761: process_reflectance.main Ocean", "1.3784: reflectance_spectrum_ocean : End", "1.3785: process_reflectance.reflectance_spectrum_ocean Done", "1.3785: process_reflectance.main Reshape", "1.3789: define_vza_hotspot", "1.3790: begin calculating brdf and brdf error", "1.3854: perform BRDF stats analysis", "1.3857: draw graph, transect plane, case stats", "1.9431: saving netcdf data 2", "1.9460: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9461: output_var[:] = self.dataNC['longitude'].T[:]", "1.9473: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9473: output_var[:] = self.dataNC['latitude'].T[:]", "1.9481: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9481: sf = 0.000100", "1.9482: offset = 0.000000", "1.9482: missval = -8421", "1.9482: data = np.ma.masked_equal(self.data['ref_land'], missval)", "1.9482: type of self.data['ref_land'] = ", "1.9493: self.data['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)", "1.9496: output_var[:] = self.dataNC['ref_land'].T[:]", "1.9504: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9504: sf = 0.001436", "1.9505: offset = 47.068424", "1.9505: missval = -32768", "1.9505: data = np.ma.masked_equal(self.data['chloro_conc'], missval)", "1.9505: type of self.data['chloro_conc'] = ", "1.9508: self.data['chloro_conc'] = array([[ nan, nan, 0.686627 , 0.67513533],\n [ nan, nan, 0.62342284, 0.63778742]])", "1.9511: output_var[:] = self.dataNC['chloro_conc'].T[:]", "1.9520: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9520: sf = 0.000530", "1.9521: offset = 17.755947", "1.9521: missval = -32768", "1.9521: data = np.ma.masked_equal(self.data['wind_speed'], missval)", "1.9521: type of self.data['wind_speed'] = ", "1.9524: self.data['wind_speed'] = array([[ nan, nan, 6.95105396, 7.07605787],\n [ nan, nan, 6.89437846, 6.99236881]])", "1.9527: output_var[:] = self.dataNC['wind_speed'].T[:]", "1.9534: if var_name in ['ref_land','chloro_conc','wind_speed']:", "1.9534: output_var[:] = self.dataNC['qf'].T[:]", "1.9960: job finished, took 1.99597501755 seconds" ], "success": "true" }