{ "outputs": [ { "case": "stats", "http_url": "http://adam.noveltis.fr/web-output//20200223073139.746347/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/20200223073139.746347/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//20200223073139.746347/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/20200223073139.746347/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//20200223073139.746347/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/20200223073139.746347/ADAM_netcdf_M01_Lon_-2.25_-2.15_Lat_36.55_36.85.nc" } ], "log": [ "0.0064: job_output_dir is None : CREATION", "0.0065: job_output_dir is now /home/www/data/adam/web-root/web-output//20200223073139.746347", "0.0066: begin BRDF job on host: virtprod1.noveltis.loc", "0.0066: 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'}", "0.0066: parsing BRDF input", "0.0071: all input was validated", "0.0071: extent is: -2.30000, 36.50000, -2.10000, 36.90000", "0.0071: month_index is: 0", "0.0075: spectral ranges are: [[300 400]]", "0.0077: sza is: [ 40.]", "0.0079: phi is: [ 1.]", "0.0079: compute error is: True", "0.0079: generate graphs is: True", "0.0079: begin loading requested data from source file", "0.0080: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc in reading", "0.0080: adam_io.py line 38 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.2593: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_climato.nc", "0.2594: ADAM_IO : Open NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc in reading", "0.2594: adam_io.py line 145 : netCDF4.Dataset /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "0.6141: ADAM_IO : Close NetCDF4 /data_no_saved/adam/adam-data/ADAM_V4_errLand_M01.nc", "0.6150: 4 land pixels, 4 ocean pixels, 0 snow pixels", "0.6150: begin calculating reflectance spectra", "0.6150: process_reflectance.main Initialisation", "0.6150: process_reflectance.main flatten to 2d and 1d arrays", "0.6151: process_reflectance.main initialise the variable to be returned", "0.6151: process_reflectance.main if do_compute_error", "0.6152: process_reflectance.main Land", "0.7341: process_reflectance.main Snow", "0.7341: process_reflectance.main Ocean", "0.7769: reflectance_spectrum_ocean : End", "0.7770: process_reflectance.reflectance_spectrum_ocean Done", "0.7770: process_reflectance.main Reshape", "0.7773: define_vza_hotspot", "0.7773: begin calculating brdf and brdf error", "0.7825: perform BRDF stats analysis", "0.7828: draw graph, transect plane, case stats", "1.1390: saving netcdf data 2", "1.2853: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.2854: output_var[:] = self.dataNC[u'longitude'].T[:]", "1.3527: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.3528: output_var[:] = self.dataNC[u'latitude'].T[:]", "1.3563: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.3564: sf = 0.000100", "1.3564: offset = 0.000000", "1.3565: missval = -8421", "1.3565: data = np.ma.masked_equal(self.data[u'ref_land'], missval)", "1.3565: type of self.data[u'ref_land'] = ", "1.3578: 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)", "1.3690: output_var[:] = self.dataNC[u'ref_land'].T[:]", "1.3731: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.3732: sf = 0.001436", "1.3732: offset = 47.068424", "1.3732: missval = -32768", "1.3732: data = np.ma.masked_equal(self.data[u'chloro_conc'], missval)", "1.3733: type of self.data[u'chloro_conc'] = ", "1.3737: self.data[u'chloro_conc'] = array([[ nan, nan, 0.686627 , 0.67513533],\n [ nan, nan, 0.62342284, 0.63778742]])", "1.3740: output_var[:] = self.dataNC[u'chloro_conc'].T[:]", "1.3791: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.3791: sf = 0.000530", "1.3791: offset = 17.755947", "1.3791: missval = -32768", "1.3792: data = np.ma.masked_equal(self.data[u'wind_speed'], missval)", "1.3792: type of self.data[u'wind_speed'] = ", "1.3795: self.data[u'wind_speed'] = array([[ nan, nan, 6.95105396, 7.07605787],\n [ nan, nan, 6.89437846, 6.99236881]])", "1.3797: output_var[:] = self.dataNC[u'wind_speed'].T[:]", "1.3836: if var_name in [u'ref_land',u'chloro_conc','wind_speed']:", "1.3836: output_var[:] = self.dataNC[u'qf'].T[:]", "1.4908: job finished, took 1.49080514908 seconds" ], "success": "true" }