final = {}
for method in griddata_methods:
print(' - Using the griddata method %s.' % method)
final[method] = []
# Which data to use
for source in analysis_data_sources:
print('Using the %s data source' % source)
if source == 'finalmaps':
# Get the final map out from the wave simulation
mc = euv_wave_data['finalmaps']
# Accumulate the data in space and time to increase the signal
# to noise ratio
print(' - Performing spatial summing of HPC data.')
mc = mapcube_tools.accumulate(mapcube_tools.superpixel(mc, spatial_summing), temporal_summing)
if develop is not None:
aware_utils.write_movie(mc, img_filepath + '_accummulated_data')
# Swing the position of the start of the longitudinal
# unwrapping
for ils, longitude_start in enumerate(longitude_starts):
# Which angle to start the longitudinal unwrapping
transform_hpc2hg_parameters['longitude_start'] = longitude_start
# Which version of AWARE to use
if aware_version == 0:
#
# AWARE version 0 - first do the image processing
# to isolate the wave front, then do the transformation into
# heliographic co-ordinates to measure the wavefront.
def create_input_to_aware_for_test_observational_data(wave_name,
spatial_summing, temporal_summing,
instrument='AIA',
wavelength=211,
event_type='FL',
root_directory=eitwave_data_root):
# Set up the data
if wave_name == 'longetal2014_figure4':
hek_record_index = 0
time_range = ['2011-06-07 06:16:00', '2011-02-15 07:16:00']
if wave_name == 'longetal2014_figure7':
hek_record_index = 0
time_range = ['2011-02-13 17:28:00', '2011-02-13 18:28:00']
if wave_name == 'longetal2014_figure8a':
hek_record_index = 0
# time_range = ['2011-02-15 01:48:00', '2011-02-15 02:14:34']
time_range = ['2011-02-15 01:48:00', '2011-02-15 02:48:00']
if wave_name == 'longetal2014_figure6':
hek_record_index = 0
# time_range = ['2011-02-08 21:05:00', '2011-02-08 21:15:00']
time_range = ['2011-02-08 21:05:00', '2011-02-08 22:05:00']
if wave_name == 'longetal2014_figure8e':
hek_record_index = 0
# time_range = ['2011-02-16 14:22:36', '2011-02-16 14:39:48']
time_range = ['2011-02-16 14:22:36', '2011-02-16 15:22:36']
if wave_name == 'byrneetal2013_figure12':
hek_record_index = 0
# time_range = ['2010-08-14 09:40:18', '2010-08-14 10:32:00']
time_range = ['2010-08-14 09:40:18', '2010-08-14 10:40:18']
# Where the data is stored
wave_info_location = os.path.join(root_directory, wave_name)
# Get the FITS files we are interested in
fits_location = os.path.join(wave_info_location, instrument, str(wavelength), 'fits', '1.0')
fits_file_list = aware_get_data.get_file_list(fits_location, '.fits')
if len(fits_file_list) == 0:
instrument_measurement, qr = aware_get_data.find_fits(time_range, instrument, wavelength)
print('Downloading {:n} files'.format(len(qr)))
fits_file_list = aware_get_data.download_fits(qr, instrument_measurement=instrument_measurement)
# Get the source information
source_location = os.path.join(wave_info_location, event_type)
source_path = aware_get_data.get_file_list(source_location, '.pkl')
if len(source_path) == 0:
print('Querying HEK for trigger data.')
hek_record = aware_get_data.download_trigger_events(time_range)
else:
f = open(source_path[0], 'rb')
hek_record = pickle.load(f)
f.close()
analysis_time_range = TimeRange(hek_record[hek_record_index]['event_starttime'],
time_from_file_name(fits_file_list[-1].split(os.path.sep)[-1]))
print('Analysis time range')
print(analysis_time_range)
for_analysis = []
for f in fits_file_list:
g = f.split(os.path.sep)[-1]
if (time_from_file_name(g) <= analysis_time_range.end) and (time_from_file_name(g) >= analysis_time_range.start):
for_analysis.append(f)
return {'finalmaps': mapcube_tools.accumulate(mapcube_tools.superpixel(Map(for_analysis, cube=True), spatial_summing), temporal_summing),
'epi_lat': hek_record[hek_record_index]['hgs_y'],
'epi_lon': hek_record[hek_record_index]['hgs_x']}
def spatial_summing(self, dimension, **kwargs):
return self.__init__(mapcube_tools.superpixel(self.mc, dimension, **kwargs))
