def test_two_concatenate_decyear_and_jd():
data = DecimalYearData(scan_angle=np.arange(3), epoch=pd.DataFrame(np.arange(1991, 1994)),
residuals=np.arange(2, 5))
data2 = DataParser(scan_angle=np.arange(3), epoch=pd.DataFrame(np.arange(2456951, 2456954)),
residuals=np.arange(2, 5))
data3 = data + data2
assert np.allclose(data3.julian_day_epoch()[:len(data)], data.julian_day_epoch())
assert np.allclose(data3.julian_day_epoch()[len(data):], data2.julian_day_epoch())
def test_add_to_empty():
data = DataParser(scan_angle=np.arange(3), epoch=pd.DataFrame(np.arange(1991, 1994)),
residuals=np.arange(2, 5),
inverse_covariance_matrix=np.array([[1, 2], [3, 4]]) * np.ones((3, 2, 2)),
along_scan_errs=np.arange(3, 6))
new_data = DataParser()
new_data += data
assert np.allclose(new_data.scan_angle, data.scan_angle)
assert len(new_data) == len(data)
def test_read_on_many_filepaths(self, fake_glob, fake_load):
test_data_directory = os.path.join(os.getcwd(), 'path/')
fake_glob.return_value = ['/fake/path/1232.dat', '/fake/path/23211.dat', '/fake/path/232.dat']
DataParser().read_intermediate_data_file('232', test_data_directory, None, None, None)
fake_load.assert_called_with('/fake/path/232.dat', sep=None, skiprows=None, header=None, engine='python')
# Test hip2 style names
fake_glob.return_value = ['H075/HIP075290.d', 'H075/HIP075293.d', 'H107/HIP107529.d', 'H007/HIP007529.d', 'H117/HIP117529.d']
DataParser().read_intermediate_data_file('7529', test_data_directory, None, None, None)
fake_load.assert_called_with('H007/HIP007529.d', sep=None, skiprows=None, header=None, engine='python')
def test_write_with_missing_info():
data = DataParser(scan_angle=np.arange(3), epoch=np.arange(1991, 1994),
residuals=np.arange(2, 5),
inverse_covariance_matrix=None,
along_scan_errs=None)
with tempfile.TemporaryDirectory() as tmp_dir:
data.write(os.path.join(tmp_dir, 'out.csv'))
t = Table.read(os.path.join(tmp_dir, 'out.csv'))
assert np.allclose(t['residuals'], data.residuals)
assert np.allclose(t['julian_day_epoch'], data.julian_day_epoch())
assert np.allclose(t['scan_angle'], data.scan_angle)
assert len(t.colnames) == 5
def test_concatenating_data():
data = DataParser(scan_angle=np.arange(3), epoch=np.arange(1991, 1994),
residuals=np.arange(2, 5),
inverse_covariance_matrix=np.array([[1, 2], [3, 4]]) * np.ones((3, 2, 2)),
along_scan_errs=np.arange(3, 6))
new_data = sum([data, data])
assert np.allclose(new_data.scan_angle, [*data.scan_angle, *data.scan_angle])
assert np.allclose(new_data.residuals, [*data.residuals, *data.residuals])
assert len(new_data.inverse_covariance_matrix) == 2*len(data.inverse_covariance_matrix)
data += data
assert np.allclose(new_data.scan_angle, data.scan_angle)
assert np.allclose(new_data.residuals, data.residuals)
data.calculate_inverse_covariance_matrices()
def test_write():
data = DataParser(scan_angle=np.arange(3), epoch=np.arange(1991, 1994),
residuals=np.arange(2, 5),
inverse_covariance_matrix=np.array([[1, 2], [3, 4]]) * np.ones((3, 2, 2)),
along_scan_errs=np.arange(3, 6))
with tempfile.TemporaryDirectory() as tmp_dir:
data.write(os.path.join(tmp_dir, 'out.csv'))
t = Table.read(os.path.join(tmp_dir, 'out.csv'))
assert np.allclose(t['residuals'], data.residuals)
assert np.allclose(t['julian_day_epoch'], data.julian_day_epoch())
assert np.allclose(t['scan_angle'], data.scan_angle)
assert np.allclose(t['along_scan_errs'], data.along_scan_errs)
icovs = [np.array(literal_eval(icov)) for icov in t['icov']]
assert np.allclose(icovs, data.inverse_covariance_matrix)
assert len(t.colnames) == 5
def parse_and_instantiate(cls, star_id: str,
intermediate_data_directory: str, **kwargs):
filepath = DataParser.get_intermediate_data_file_path(
star_id, intermediate_data_directory)
CorrectDataParser = cls.get_appropriate_parser(filepath)
return CorrectDataParser.parse_and_instantiate(
star_id, intermediate_data_directory, **kwargs)
def test_concatenating_data_with_missing():
data = DataParser(scan_angle=np.arange(3), epoch=pd.DataFrame(np.arange(1991, 1994)),
residuals=np.arange(2, 5))
new_data = sum([data, data])
assert np.allclose(new_data.scan_angle, [*data.scan_angle, *data.scan_angle])
assert np.allclose(new_data.residuals, [*data.residuals, *data.residuals])
data += data
assert np.allclose(new_data.scan_angle, data.scan_angle)
assert np.allclose(new_data.residuals, data.residuals)
def refit_hip_fromdata(data: DataParser, fit_degree, cntr_RA=Angle(0, unit='degree'), cntr_Dec=Angle(0, unit='degree'),
use_parallax=False):
data.calculate_inverse_covariance_matrices()
# generate parallax motion
jyear_epoch = time.Time(data.julian_day_epoch(), format='jd', scale='tcb').jyear
# note that ra_motion and dec_motion are in degrees here.
# generate sky path
year_epochs = jyear_epoch - time.Time(1991.25, format='decimalyear', scale='tcb').jyear
ra_motion, dec_motion = parallactic_motion(jyear_epoch, cntr_RA.degree, cntr_Dec.degree, 'degree',
time.Time(1991.25, format='decimalyear', scale='tcb').jyear,
ephemeris=earth_ephemeris) # Hipparcos was in a geostationary orbit.
ra_resid = Angle(data.residuals.values * np.sin(data.scan_angle.values), unit='mas')
dec_resid = Angle(data.residuals.values * np.cos(data.scan_angle.values), unit='mas')
# instantiate fitter
fitter = AstrometricFitter(data.inverse_covariance_matrix, year_epochs,
use_parallax=use_parallax, fit_degree=fit_degree,
parallactic_pertubations={'ra_plx': Angle(ra_motion, 'degree').mas,
'dec_plx': Angle(dec_motion, 'degree').mas})
fit_coeffs, errors, chisq, refit_residuals = fitter.fit_line(ra_resid.mas, dec_resid.mas, return_all=True)
parallax_factors = ra_motion * np.sin(data.scan_angle.values) + dec_motion * np.cos(data.scan_angle.values)
# technically this could be data.parallax_factors.values, but then we have to deal with
# getting the RA and Dec components of that.
if not use_parallax:
fit_coeffs = np.hstack([[0], fit_coeffs])
errors = np.hstack([[0], errors])
parallax_factors = np.zeros_like(parallax_factors)
# pad so coeffs and errors are 9 long.
errors = np.pad(errors, (0, 9 - len(fit_coeffs)))
fit_coeffs = np.pad(fit_coeffs, (0, 9 - len(fit_coeffs)))
# calculate the chisquared partials
sin_scan = np.sin(data.scan_angle.values)
cos_scan = np.cos(data.scan_angle.values)
dt = data.epoch - 1991.25
chi2_vector = (2 * data.residuals.values / data.along_scan_errs.values ** 2 * np.array(
[parallax_factors, sin_scan, cos_scan, dt * sin_scan, dt * cos_scan])).T
chi2_partials = np.sum(chi2_vector, axis=0) ** 2
return fit_coeffs, errors, chisq, chi2_partials
def test_calculate_inverse_covariances(mock_cov_matrix):
parser = DataParser()
parser.calculate_inverse_covariance_matrices()
assert np.allclose(parser.inverse_covariance_matrix[0], np.ones((2, 2)))
def test_call_jd_dates_gaia():
parser = DataParser()
parser._epoch = pd.DataFrame(data=[2447892.5, 2447893], index=[5, 6])
jd_epochs = parser.julian_day_epoch()
assert np.isclose(jd_epochs[0], 2447892.5)
assert np.isclose(jd_epochs[1], 2447893)
def test_len(self):
assert len(DataParser()) == 0
assert len(DataParser(epoch=pd.DataFrame(np.arange(4)))) == 4
def test_read_on_irregular_paths(self, fake_glob, fake_load):
test_data_directory = os.path.join(os.getcwd(), 'path/')
fake_glob.return_value = ['/fake/path/SSADSx1232.dat', '/fake/path/WDASxs23211.dat', '/fake/path/OMGH232.dat']
DataParser().read_intermediate_data_file('232', test_data_directory, None, None, None)
fake_load.assert_called_with('/fake/path/OMGH232.dat', sep=None, skiprows=None, header=None, engine='python')
def test_read_on_couple_similar_filepaths(self, fake_glob, fake_load):
test_data_directory = os.path.join(os.getcwd(), 'path/')
DataParser().read_intermediate_data_file('27321', test_data_directory, None, None, None)
fake_load.assert_called_with('path/27321.dat', sep=None, skiprows=None, header=None, engine='python')
def test_scale_along_scan_errors_raises_on_empty(self):
parser = DataParser()
with pytest.raises(ValueError):
parser.scale_along_scan_errs(1)
def test_file_exists(self):
path = "htof/test/data_for_tests/Hip1/IntermediateData"
file_doesnt_exist = not DataParser.file_exists(star_id="1800001", intermediate_data_directory=path)
assert file_doesnt_exist
assert DataParser.file_exists(star_id="004391", intermediate_data_directory=path)
