{ "outputs": [ { "case": "stats", "http_url": "http://adam.noveltis.fr/web-output//20200525053437.885621/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/20200525053437.885621/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//20200525053437.885621/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/20200525053437.885621/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//20200525053437.885621/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/20200525053437.885621/ADAM_netcdf_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.nc" } ], "log": [ "0.2927: job_output_dir is None : CREATION", "0.2929: job_output_dir is now /home/www/data/adam/web-root/web-output//20200525053437.885621", "0.2930: begin BRDF job on host: virtprod1.noveltis.loc", "0.2930: 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'}", "0.2930: parsing BRDF input", "0.2936: all input was validated", "0.2936: extent is: -2.30000, 36.50000, -2.10000, 36.90000", "0.2936: month_index is: 0", "0.2940: spectral ranges are: [[300 400]]", "0.2943: sza is: [ 40.]", "0.2944: phi is: [ 1.]", "0.2944: compute error is: True", "0.2944: generate graphs is: True", "0.2945: begin loading requested data from source file", "0.2945: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc in reading", "0.2945: adam_io.py line 38 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "1.4687: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "1.4688: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc in reading", "1.4688: adam_io.py line 145 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "1.5476: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "1.5483: 4 land pixels, 4 ocean pixels, 0 snow pixels", "1.5483: begin calculating reflectance spectra", "1.5483: process_reflectance.main Initialisation", "1.5483: process_reflectance.main flatten to 2d and 1d arrays", "1.5484: process_reflectance.main initialise the variable to be returned", "1.5484: process_reflectance.main if do_compute_error", "1.5484: process_reflectance.main Land", "1.6886: process_reflectance.main Snow", "1.6887: process_reflectance.main Ocean", "1.6910: reflectance_spectrum_ocean : End", "1.6911: process_reflectance.reflectance_spectrum_ocean Done", "1.6911: process_reflectance.main Reshape", "1.6914: define_vza_hotspot", "1.6915: begin calculating brdf and brdf error", "1.6970: perform BRDF stats analysis", "1.6972: draw graph, transect plane, case stats", "3.1353: saving netcdf data 2", "3.2039: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.2039: output_var[:] = self.dataNC['longitude'].T[:]", "3.7209: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.7210: output_var[:] = self.dataNC['latitude'].T[:]", "3.7220: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.7220: sf = 0.000100", "3.7221: offset = 0.000000", "3.7221: missval = -8421", "3.7221: data = np.ma.masked_equal(self.data['ref_land'], missval)", "3.7221: type of self.data['ref_land'] = ", "3.7235: 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)", "3.7239: output_var[:] = self.dataNC['ref_land'].T[:]", "3.7247: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.7248: sf = 0.001436", "3.7248: offset = 47.068424", "3.7248: missval = -32768", "3.7248: data = np.ma.masked_equal(self.data['chloro_conc'], missval)", "3.7248: type of self.data['chloro_conc'] = ", "3.7252: self.data['chloro_conc'] = array([[ nan, nan, 0.686627 , 0.67513533],\n [ nan, nan, 0.62342284, 0.63778742]])", "3.7255: output_var[:] = self.dataNC['chloro_conc'].T[:]", "3.7265: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.7265: sf = 0.000530", "3.7265: offset = 17.755947", "3.7266: missval = -32768", "3.7266: data = np.ma.masked_equal(self.data['wind_speed'], missval)", "3.7266: type of self.data['wind_speed'] = ", "3.7269: self.data['wind_speed'] = array([[ nan, nan, 6.95105396, 7.07605787],\n [ nan, nan, 6.89437846, 6.99236881]])", "3.7272: output_var[:] = self.dataNC['wind_speed'].T[:]", "3.7279: if var_name in ['ref_land','chloro_conc','wind_speed']:", "3.7279: output_var[:] = self.dataNC['qf'].T[:]", "3.7669: job finished, took 3.76692986488 seconds" ], "success": "true" }