sourcefinder.utility.sourceparams#

Attributes#

_source_params_descriptions

file_fields

Classes#

SourceParams

Enumeration of source parameters that can be measured and stored.

Functions#

describe_dataframe_columns(→ dict[str, str])

make_measurements_dataframe(moments_of_sources, ...)

Create a Pandas DataFrame with parameters related to detected sources

Module Contents#

class sourcefinder.utility.sourceparams.SourceParams[source]#

Bases: str, enum.Enum

Enumeration of source parameters that can be measured and stored.

describe() → str[source]#

Return a description of the source parameter.

Return type:

str

CHISQ = 'chisq'[source]#
DEC = 'dec'[source]#
DEC_ERR = 'dec_err'[source]#
ERROR_RADIUS = 'error_radius'[source]#
FLUX = 'flux'[source]#
FLUX_ERR = 'flux_err'[source]#
PEAK = 'peak'[source]#
PEAK_ERR = 'peak_err'[source]#
RA = 'ra'[source]#
RA_ERR = 'ra_err'[source]#
REDUCED_CHISQ = 'reduced_chisq'[source]#
SIG = 'sig'[source]#
SMAJ = 'smaj'[source]#
SMAJ_ASEC = 'smaj_asec'[source]#
SMAJ_ASEC_ERR = 'smaj_asec_err'[source]#
SMAJ_DC = 'smaj_dc'[source]#
SMAJ_DC_ERR = 'smaj_dc_err'[source]#
SMAJ_ERR = 'smaj_err'[source]#
SMIN = 'smin'[source]#
SMIN_ASEC = 'smin_asec'[source]#
SMIN_ASEC_ERR = 'smin_asec_err'[source]#
SMIN_DC = 'smin_dc'[source]#
SMIN_DC_ERR = 'smin_dc_err'[source]#
SMIN_ERR = 'smin_err'[source]#
THETA = 'theta'[source]#
THETA_CELES = 'theta_celes'[source]#
THETA_CELES_ERR = 'theta_celes_err'[source]#
THETA_DC = 'theta_dc'[source]#
THETA_DC_CELES = 'theta_dc_celes'[source]#
THETA_DC_CELES_ERR = 'theta_dc_celes_err'[source]#
THETA_DC_ERR = 'theta_dc_err'[source]#
THETA_ERR = 'theta_err'[source]#
X = 'x'[source]#
X_ERR = 'x_err'[source]#
Y = 'y'[source]#
Y_ERR = 'y_err'[source]#
sourcefinder.utility.sourceparams.describe_dataframe_columns(df: pandas.DataFrame) → dict[str, str][source]#
Parameters:

df (pandas.DataFrame)

Return type:

dict[str, str]

sourcefinder.utility.sourceparams.make_measurements_dataframe(moments_of_sources, sky_barycenters, ra_errors, dec_errors, smaj_asec, errsmaj_asec, smin_asec, errsmin_asec, theta_celes_values, theta_celes_errors, theta_dc_celes_values, theta_dc_celes_errors, error_radii, sig, chisq, reduced_chisq)[source]#

Create a Pandas DataFrame with parameters related to detected sources from a subset of the tuple of Numpy ndarrays returned by the extract.source_measurements_vectorised function.

sourcefinder.utility.sourceparams._source_params_descriptions[source]#
sourcefinder.utility.sourceparams.file_fields = ['PEAK', 'PEAK_ERR', 'FLUX', 'FLUX_ERR', 'X', 'Y', 'RA', 'RA_ERR', 'DEC', 'DEC_ERR',...[source]#