def test_there_are_no_files_of_dither_1(self):
"""
:return:
"""
prfs_d = {'fits_dir': 'fits_dir'}
misc.extract_settings = MagicMock(return_value=prfs_d)
right_files_list = [
'm_20-21_CCD1_d2.fits', 'm_20-21_CCD2_d2.fits',
'm_20-21_CCD3_d2.fits', 'm_20-21_CCD4_d2.fits'
]
os.listdir = MagicMock(return_value=right_files_list)
return_get_fits = misc_fits.get_fits_d('20-21', 1)
statement_1 = self.assertEqual(type(return_get_fits), list)
statement_2 = self.assertEqual(len(return_get_fits), 0)
return statement_1 and statement_2
def check_stars(self, mag, complete):
"""
:param mag:
:param complete:
:return:
"""
input_d = self.input_catalogue
for dither_ in input_d.keys():
catalog = genfromtxt(input_d[dither_])
list_x = catalog[:, 0]
list_y = catalog[:, 1]
list_mag = catalog[:, 2]
list_pm = catalog[:, 3]
x_values = []
y_values = []
stars = range(0, 12471, 1)
indexes = sorted(stars)
s1 = Series(list_x, name='X_IMAGE', dtype=float64)
s2 = Series(list_y, name='Y_IMAGE', dtype=float64)
s3 = Series(list_mag, name='MAG_VALUES', dtype=float64)
s4 = Series(list_pm, name='PM_INPUT', dtype=float64)
sources_df = concat([s1, s2, s3, s4], axis=1)
sources_df = sources_df.iloc[indexes, :]
ccd_loc = 'mag_{}_CCD_x0_y0_d1.fits'.format(mag)
fits_loc = '{}/{}/CCDs/{}'.format(self.prfs_d['fits_dir'], mag,
ccd_loc)
hdulist = fits.open(fits_loc)
w = WCS(hdulist[0].header)
regions_list = []
for source_num in range(sources_df['X_IMAGE'].as_matrix().size):
x_value = sources_df['X_IMAGE'].as_matrix()[source_num]
y_value = sources_df['Y_IMAGE'].as_matrix()[source_num]
regions_list.append([x_value, y_value])
input_regions = w.all_pix2world(regions_list, 1)
alpha_list = []
delta_list = []
for idx, regions in enumerate(input_regions):
alpha_list.append(regions[0])
delta_list.append(regions[1])
x_values.append(regions_list[idx][0])
y_values.append(regions_list[idx][1])
fits_files_all = get_fits_d(mag_=mag, dither=dither_)
fits_dict = {}
for fits_ in fits_files_all:
fits_loc = '{}/{}/CCDs'.format(self.prfs_d['fits_dir'], mag)
fits_file = '{}/{}'.format(fits_loc, fits_)
ccd = fits_[-13:-8]
fits_dict[ccd] = get_fits_limits(fits_file)
i = 0
ccd_list = []
for alpha_, delta_ in zip(alpha_list, delta_list):
i += 1
flag = True
for key_ in fits_dict.keys():
below_ra = fits_dict[key_]['below_ra']
above_ra = fits_dict[key_]['above_ra']
below_dec = fits_dict[key_]['below_dec']
above_dec = fits_dict[key_]['above_dec']
alpha_comp = below_ra < alpha_ < above_ra
delta_comp = below_dec < delta_ < above_dec
if alpha_comp and delta_comp:
ccd_list.append(key_)
flag = False
if flag:
ccd_list.append('False')
# Creates a list for all sources
source_list = range(0, len(alpha_list), 1)
# Populates a list for all sources with the dither number
dither_list = []
for dither_idx in range(len(alpha_list)):
dither_list.append(dither_)
cats = [['x0_y0', 1, 1], ['x0_y0', 2, 2], ['x0_y0', 3, 3],
['x0_y0', 4, 4], ['x0_y1', 1, 5], ['x0_y1', 2, 6],
['x0_y1', 3, 7], ['x0_y1', 4, 8], ['x0_y2', 1, 9],
['x0_y2', 2, 10], ['x0_y2', 3, 11], ['x0_y2', 4, 12],
['x1_y0', 1, 13], ['x1_y0', 2, 14], ['x1_y0', 3, 15],
['x1_y0', 4, 16], ['x1_y1', 1, 17], ['x1_y1', 2, 18],
['x1_y1', 3, 19], ['x1_y1', 4, 20], ['x1_y2', 1, 21],
['x1_y2', 2, 22], ['x1_y2', 3, 23], ['x1_y2', 4, 24],
['x2_y0', 1, 25], ['x2_y0', 2, 26], ['x2_y0', 3, 27],
['x2_y0', 4, 28], ['x2_y1', 1, 29], ['x2_y1', 2, 30],
['x2_y1', 3, 31], ['x2_y1', 4, 32], ['x2_y2', 1, 33],
['x2_y2', 2, 34], ['x2_y2', 3, 35], ['x2_y2', 4, 36]]
cats_list = []
for dither_, CCD_ in zip(dither_list, ccd_list):
flag = True
for cat_ in cats:
if cat_[1] == dither_ and cat_[0] == CCD_:
flag = False
cats_list.append(cat_[2])
if flag:
cats_list.append(False)
# Creates a serie of Pandas Series
series_source = Series(source_list, name='source')
series_alpha_j2000 = Series(alpha_list, name='alpha_j2000')
series_delta_j2000 = Series(delta_list, name='delta_j2000')
series_mag = Series(sources_df['MAG_VALUES'].tolist(),
name='mag_values')
series_pm = Series(sources_df['PM_INPUT'].tolist(),
name='pm_values')
series_dither = Series(dither_list, name='dither_values')
series_ccd = Series(ccd_list, name='CCD')
series_cat = Series(cats_list, name='catalog')
if complete:
sources_df = concat([
series_source, series_cat, series_alpha_j2000,
series_delta_j2000, series_mag, series_pm, series_dither,
series_ccd
],
axis=1)
sources_df = sources_df[~sources_df['CCD'].isin(['False'])]
else:
sources_df = concat([series_alpha_j2000, series_delta_j2000],
axis=1)
input_d[dither_] = sources_df
return input_d
def check_ssos(self, mag_, complete):
"""
:param mag_:
:param complete:
:return:
"""
input_d = self.input_catalogue
for dither_ in input_d.keys():
catalog = genfromtxt(input_d[dither_])
list_x = catalog[:, 0]
list_y = catalog[:, 1]
list_mag = catalog[:, 2]
list_pm = catalog[:, 3]
list_angle = catalog[:, 4]
total_length = len(list_x)
list_alpha_pm = range(0, total_length, 1)
list_delta_pm = range(0, total_length, 1)
x_values = []
y_values = []
speed_0_001 = range(self.prfs_d['first_sso'], 137378, 73)
speed_0_003 = range(self.prfs_d['first_sso'] + 10, 137388, 73)
speed_0_01 = range(self.prfs_d['first_sso'] + 20, 137398, 73)
speed_0_03 = range(self.prfs_d['first_sso'] + 30, 137408, 73)
speed_0_1 = range(self.prfs_d['first_sso'] + 40, 137418, 73)
speed_0_3 = range(self.prfs_d['first_sso'] + 50, 137428, 73)
speed_1 = range(self.prfs_d['first_sso'] + 60, 137438, 73)
speed_3 = range(self.prfs_d['first_sso'] + 67, 137445, 73)
speed_10 = range(self.prfs_d['first_sso'] + 68, 137446, 73)
speed_30 = range(self.prfs_d['first_sso'] + 69, 137447, 73)
# Gets proper angles
list_angle = [(angle_ + 180) for angle_ in list_angle]
# Gets proper motion
for index in speed_0_001:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.001
list_alpha_pm[index] = 0.001 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.001 * sin(radians(list_angle[index]))
for index in speed_0_003:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.003
list_alpha_pm[index] = 0.003 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.003 * sin(radians(list_angle[index]))
for index in speed_0_01:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.01
list_alpha_pm[index] = 0.01 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.01 * sin(radians(list_angle[index]))
for index in speed_0_03:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.03
list_alpha_pm[index] = 0.03 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.03 * sin(radians(list_angle[index]))
for index in speed_0_1:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.1
list_alpha_pm[index] = 0.1 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.1 * sin(radians(list_angle[index]))
for index in speed_0_3:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 0.3
list_alpha_pm[index] = 0.3 * cos(radians(list_angle[index]))
list_delta_pm[index] = 0.3 * sin(radians(list_angle[index]))
for index in speed_1:
list_mag[index] = list_mag[index] - 2.5
list_pm[index] = 1
list_alpha_pm[index] = 1 * cos(radians(list_angle[index]))
list_delta_pm[index] = 1 * sin(radians(list_angle[index]))
for index in speed_3:
list_pm[index] = list_pm[index] - 1000
list_alpha_pm[index] = 3 * cos(radians(list_angle[index]))
list_delta_pm[index] = 3 * sin(radians(list_angle[index]))
for index in speed_10:
list_pm[index] = list_pm[index] - 1000
list_alpha_pm[index] = 10 * cos(radians(list_angle[index]))
list_delta_pm[index] = 10 * sin(radians(list_angle[index]))
for index in speed_30:
list_pm[index] = list_pm[index] - 1000
list_alpha_pm[index] = 30 * cos(radians(list_angle[index]))
list_delta_pm[index] = 30 * sin(radians(list_angle[index]))
indexes = (speed_0_001 + speed_0_003 + speed_0_01 + speed_0_03 +
speed_0_1 + speed_0_3 + speed_1 + speed_3 + speed_10 +
speed_30)
indexes = sorted(indexes)
s1 = Series(list_x, name='X_IMAGE', dtype=float64)
s2 = Series(list_y, name='Y_IMAGE', dtype=float64)
s3 = Series(list_mag, name='MAG_VALUES', dtype=float64)
s4 = Series(list_pm, name='PM_INPUT', dtype=float64)
s5 = Series(list_alpha_pm, name='PM_ALPHA', dtype=float64)
s6 = Series(list_delta_pm, name='PM_DELTA', dtype=float64)
s7 = Series(list_angle, name='ANGLE_INPUT', dtype=float64)
sources_df = concat([s1, s2, s3, s4, s5, s6, s7], axis=1)
sources_df = sources_df.iloc[indexes, :]
ccd_loc = 'mag_{}_CCD_x0_y0_d1.fits'.format(mag_)
fits_loc = '{}/{}/CCDs/{}'.format(self.prfs_d['fits_dir'], mag_,
ccd_loc)
hdulist = fits.open(fits_loc)
w = WCS(hdulist[0].header)
regions_list = []
for source_num in range(sources_df['X_IMAGE'].as_matrix().size):
x_value = sources_df['X_IMAGE'].as_matrix()[source_num]
y_value = sources_df['Y_IMAGE'].as_matrix()[source_num]
regions_list.append([x_value, y_value])
input_regions = w.all_pix2world(regions_list, 1)
alpha_list = []
delta_list = []
for idx, regions in enumerate(input_regions):
alpha_list.append(regions[0])
delta_list.append(regions[1])
x_values.append(regions_list[idx][0])
y_values.append(regions_list[idx][1])
fits_files_all = get_fits_d(mag_, dither=dither_)
fits_dict = {}
for fits_ in fits_files_all:
CCD = fits_[-13:-8]
fits_file = '{}/{}/CCDs/{}'.format(self.prfs_d['fits_dir'],
mag_, fits_)
fits_dict[CCD] = get_fits_limits(fits_file)
i = 0
CCD_list = []
for alpha_, delta_ in zip(alpha_list, delta_list):
i += 1
flag = True
for key_ in fits_dict.keys():
below_ra = fits_dict[key_]['below_ra']
above_ra = fits_dict[key_]['above_ra']
below_dec = fits_dict[key_]['below_dec']
above_dec = fits_dict[key_]['above_dec']
alpha_comp = below_ra < alpha_ < above_ra
delta_comp = below_dec < delta_ < above_dec
if alpha_comp and delta_comp:
CCD_list.append(key_)
flag = False
if flag:
CCD_list.append('False')
# Creates a list for all sources
source_list = range(0, len(alpha_list), 1)
# Populates a list for all sources with the dither number
dither_list = []
for dither_idx in range(len(alpha_list)):
dither_list.append(dither_)
cats = [['x0_y0', 1, 1], ['x0_y0', 2, 2], ['x0_y0', 3, 3],
['x0_y0', 4, 4], ['x0_y1', 1, 5], ['x0_y1', 2, 6],
['x0_y1', 3, 7], ['x0_y1', 4, 8], ['x0_y2', 1, 9],
['x0_y2', 2, 10], ['x0_y2', 3, 11], ['x0_y2', 4, 12],
['x1_y0', 1, 13], ['x1_y0', 2, 14], ['x1_y0', 3, 15],
['x1_y0', 4, 16], ['x1_y1', 1, 17], ['x1_y1', 2, 18],
['x1_y1', 3, 19], ['x1_y1', 4, 20], ['x1_y2', 1, 21],
['x1_y2', 2, 22], ['x1_y2', 3, 23], ['x1_y2', 4, 24],
['x2_y0', 1, 25], ['x2_y0', 2, 26], ['x2_y0', 3, 27],
['x2_y0', 4, 28], ['x2_y1', 1, 29], ['x2_y1', 2, 30],
['x2_y1', 3, 31], ['x2_y1', 4, 32], ['x2_y2', 1, 33],
['x2_y2', 2, 34], ['x2_y2', 3, 35], ['x2_y2', 4, 36]]
cats_list = []
for dither_, CCD_ in zip(dither_list, CCD_list):
flag = True
for cat_ in cats:
if cat_[1] == dither_ and cat_[0] == CCD_:
flag = False
cats_list.append(cat_[2])
if flag:
cats_list.append(False)
# Creates a serie of Pandas Series
series_source = Series(source_list, name='source')
series_alpha_j2000 = Series(alpha_list, name='alpha_j2000')
series_delta_j2000 = Series(delta_list, name='delta_j2000')
series_mag = Series(sources_df['MAG_VALUES'].tolist(),
name='mag_values')
series_pm = Series(sources_df['PM_INPUT'].tolist(),
name='pm_values')
series_pm_alpha = Series(sources_df['PM_ALPHA'].tolist(),
name='pm_alpha')
series_pm_delta = Series(sources_df['PM_DELTA'].tolist(),
name='pm_delta')
series_angle = Series(sources_df['ANGLE_INPUT'].tolist(),
name='angle_values')
series_dither = Series(dither_list, name='dither_values')
series_ccd = Series(CCD_list, name='CCD')
series_cat = Series(cats_list, name='catalog')
if complete:
sources_df = concat([
series_source, series_cat, series_alpha_j2000,
series_delta_j2000, series_mag, series_pm, series_pm_alpha,
series_pm_delta, series_angle, series_dither, series_ccd
],
axis=1)
sources_df = sources_df[~sources_df['CCD'].isin(['False'])]
else:
sources_df = concat([series_alpha_j2000, series_delta_j2000],
axis=1)
input_d[dither_] = sources_df
return input_d