def create_map(start, end, ar_obs, ar_instr, sp_obs, sp_instr):
# setting active regions
data = DataAccess(start, end, 'AR', ar_obs, ar_instr)
chain_encoded = prep.decode_and_split(data.get_chain_code())
ar_carr_synthesis, ar_pix_synthesis = ar.get_shapes(chain_encoded, data.get_pixel_start_x(),
data.get_pixel_start_y(), data.get_filename(),
data.get_noaa_number(), data.get_ar_id(), data.get_date())
# setting sunspots
sp_data = DataAccess(start, end, 'SP', sp_obs, sp_instr)
sp_chain_encoded = prep.decode_and_split(sp_data.get_chain_code())
sp_carr, sp_pix = sp.get_shapes(sp_chain_encoded, sp_data.get_pixel_start_x(), sp_data.get_pixel_start_y(),
sp_data.get_filename(), sp_data.get_sp_id(), sp_data.get_date())
sp_synthesis = sp.make_sp_synthesis(ar_contour=ar_carr_synthesis, sp_carr=sp_carr)
prep.display_object(ar_carr_synthesis, sp_synthesis)
return sunspots
if __name__ == '__main__':
# Active region + Sunspot testing
from DataAccess import DataAccess
import ActiveRegion as ar
# setting active regions
data = DataAccess('2003-10-21T00:00:00', '2003-10-24T00:00:00', 'AR',
'SOHO', 'MDI')
chain_encoded = prep.decode_and_split(data.get_chain_code())
ar_carr_synthesis, ar_pix_synthesis = ar.get_shapes(
chain_encoded, data.get_pixel_start_x(), data.get_pixel_start_y(),
data.get_filename(), data.get_noaa_number(), data.get_ar_id(),
data.get_date())
# setting sunspots
sp_data = DataAccess('2003-10-21T00:00:00', '2003-10-24T00:00:00', 'SP',
'SOHO', 'MDI')
sp_chain_encoded = prep.decode_and_split(sp_data.get_chain_code())
sp_carr, sp_pix = get_shapes(sp_chain_encoded, sp_data.get_pixel_start_x(),
sp_data.get_pixel_start_y(),
sp_data.get_filename(), sp_data.get_sp_id(),
sp_data.get_date())
sp_synthesis = make_sp_synthesis(ar_contour=ar_carr_synthesis,
sp_carr=sp_carr)
ar.append([xpos, ypos])
print("AR", ar)
return ar
if __name__ == '__main__':
from DataAccess import DataAccess
data = DataAccess('2003-09-27T00:00:00', '2003-09-29T00:00:00', 'FIL')
chain_encoded = prep.encode_and_split(data.get_chain_code())
mer = get_shapes(chain_encoded, data.get_pixel_start_x(),
data.get_pixel_start_y(), data.get_filename(),
data.get_track_id(), data.get_fil_id(), data.get_date())
make_synthesis(mer)
# for id, coords in mer.items():
# carrington.append(coords[0][0])
# for x in range(1,6):
# carrington.append(mer["50988"][x][0])
#
# prep.display_object(carrington, "")
# npa = np.array([pix[0]], dtype=np.int32)
# npa2 = np.array([pix[1]], dtype=np.int32)
# print(npa)
