import numpy as np import h5py from util.util import get_grid_values, get_grid_values_all import glob mod_res_params = ['M07', 'M08', 'M10', 'M12', 'M13', 'M14', 'M15', 'M16'] img_res_params = ['M07_highres', 'M08_highres', 'M10_highres', 'M12_highres', 'M13_highres', 'M14_highres', 'M15_highres', 'M16_highres'] def run_all(directory): mod_files = glob.glob(directory+'*.uwssec.nc') img_files = glob.glob(directory+'*.uwssec.highres.nc') mod_tiles = [] img_tiles = [] for idx, mfile in enumerate(mod_files): ifile = img_files[idx] run(mfile, ifile, mod_tiles, img_tiles) mod_nda = np.stack(mod_tiles) img_nda = np.stack(img_tiles) mod_mean = mod_nda.mean() img_mean = img_nda.mean() mod_std = mod_nda.std() img_std = img_nda.std() mod_nda = (mod_nda - mod_mean) / mod_std img_nda = (img_nda - img_mean) / img_std return mod_nda, img_nda def run(mod_res_filename, img_res_filename, mod_tiles, img_tiles): mod_h5f = h5py.File(mod_res_filename, 'r') img_h5f = h5py.File(img_res_filename, 'r') mod_tile_width = 64 img_tile_width = mod_tile_width * 2 mod_param = 'observation_data/M15' img_param = 'observation_data/M15_highres' mod_num_lines = mod_h5f[mod_param].shape[0] mod_num_pixels = mod_h5f[mod_param].shape[1] img_num_lines = img_h5f[img_param].shape[0] img_num_pixels = img_h5f[img_param].shape[1] mod_num_y_tiles = int(mod_num_lines / mod_tile_width) mod_num_x_tiles = int(mod_num_pixels / mod_tile_width) mod_data = get_grid_values(mod_h5f, mod_param, 0, 0, None, mod_num_lines, mod_num_pixels, range_name=None) img_data = get_grid_values(img_h5f, img_param, 0, 0, None, img_num_lines, img_num_pixels, range_name=None) for j in range(mod_num_y_tiles): j_m = j * mod_tile_width j_i = j_m * 2 for i in range(mod_num_x_tiles): i_m = i * mod_tile_width i_i = i_m * 2 nda = mod_data[j_m:j_m+mod_tile_width, i_m:i_m+mod_tile_width] mod_tiles.append(nda) nda = img_data[j_i:j_i+img_tile_width, i_i:i_i+img_tile_width] img_tiles.append(nda) mod_h5f.close() img_h5f.close() def run_test(directory): files = glob.glob(directory + 'clavrx_snpp_viirs*.h5') for file in files: h5f = h5py.File(file, 'r') try: opd_nl = get_grid_values_all(h5f, 'cld_opd_nlcomp') reff_nl = get_grid_values_all(h5f, 'cld_reff_nlcomp') except: print('PROBLEM with: ', file) continue if np.sum(np.isnan(opd_nl)) < opd_nl.size and np.sum(np.isnan(reff_nl)) < reff_nl.size: print(file) h5f.close()