else:
indices[wave_name][differencing_type] = 15
# Storage for the maps
maps = {}
# Go through each wave
for i, wave_name in enumerate(wave_names):
# Storage by wave name
print("\n----------------")
print("Loading and accumulating {:s} data".format(wave_name))
maps[wave_name] = {}
# Load observational data from file
euv_wave_data = aware_utils.create_input_to_aware_for_test_observational_data(wave_name, spatial_summing, temporal_summing)
# Accumulate the AIA data
mc = euv_wave_data['finalmaps']
# Go through each of the differencing types
for differencing_type in differencing_types:
# Which layer in the mapcube to use
index = indices[wave_name][differencing_type]
if differencing_type == 'RD':
mc_diff = mapcube_tools.running_difference(mc)
elif differencing_type == 'BD':
mc_diff = mapcube_tools.base_difference(mc)
elif differencing_type == 'RDP':
print(" - Saving test waves.")
file_path = os.path.join(otypes_dir['dat'], otypes_filename['dat'] + '.pkl')
print('Saving to %s' % file_path)
f = open(file_path, 'wb')
pickle.dump(euv_wave_data, f)
f.close()
else:
print(" - Loading test waves.")
file_path = os.path.join(otypes_dir['dat'], otypes_filename['dat'] + '.pkl')
print('Loading from %s' % file_path)
f = open(file_path, 'rb')
out = pickle.load(f)
f.close()
else:
# Load observational data from file
euv_wave_data = aware_utils.create_input_to_aware_for_test_observational_data(wave_name)
# Transform parameters used to convert HPC image data to HG data.
# The HPC data is transformed to HG using the location below as the
# "pole" around which the data is transformed
transform_hpc2hg_parameters['epi_lon'] = euv_wave_data['epi_lon'] * u.deg
transform_hpc2hg_parameters['epi_lat'] = euv_wave_data['epi_lat'] * u.deg
# Storage for the results from all methods and polynomial fits
final = {}
for method in griddata_methods:
print(' - Using the griddata method %s.' % method)
final[method] = []
# Which data to use
idir = os.path.join(idir, loc)
filename = filename + loc + '.'
filename = filename[0: -1]
if not(os.path.exists(idir)):
os.makedirs(idir)
otypes_dir[ot] = idir
otypes_filename[ot] = filename
#
# Load in data
#
index = 20
create = False
if create:
mc = aware_utils.create_input_to_aware_for_test_observational_data(wave_name)['finalmaps']
develop = {'img': os.path.join(otypes_dir['img'], otypes_filename['img']),
'dat': os.path.join(otypes_dir['dat'], otypes_filename['dat'])}
aware_processed, develop_filepaths = aware3.processing(mc,
develop=develop,
radii=radii,
func=intensity_scaling_function,
histogram_clip=histogram_clip)
else:
print('Loading datasets.')
develop_filepaths = {}
root = os.path.join(otypes_dir['dat'], otypes_filename['dat'])
develop_filepaths['rdpi_mc'] = root + "_rdpi_mc.pkl"
develop_filepaths['np_median_dc'] = root + "_np_median_dc_0.npy"
develop_filepaths['np_meta'] = root + "_np_meta.pkl"
develop_filepaths['np_nans'] = root + "_np_nans.npy"
