catl_clean_nmin¶
-
sdss_catl_utils.mocks_manager.catl_utils.
catl_clean_nmin
(catl_pd, catl_kind, catl_info='memb', reindex=True, nmin=1, perf_opt=False)[source] [edit on github]¶ Cleans and removed the
bad
rows withfailed
values, i.e. those that containfailed
entries. This method also includes galaxies from groups above thenmin
galaxy number threshold.Parameters: - catl_pd :
pandas.DataFrame
DataFrame containing the information about galaxies or galaxy groups.
- catl_kind : {
data
,mocks
}str
, optional Type of the catalogue being analyzed. This variable corresponds to whether a
real
orsynthetic/mock
catalogue is being read/analyzed.- Options:
data
: Catalogue(s) from the SDSSreal
cataloguesmocks
: Catalogue(s) from themock
catalogues.
- catl_info : {
memb
,groups
}bool
, optional Option for which type of catalogue is being analyzed. This variable correspondos to whether a
galaxy
-catalogue or agroup
-catalogue is being analyzed. This variable is set tomemb
by default.- Options:
memb
: Galaxy catalogue with themember
galaxies of groups.groups
: Catalogues withgroup
information.
- reindex :
bool
, optional If
True
, the output catalogue is reindexed from the original dataframecatl_pd
. This variable is set toTrue
by default.- nmin :
int
, optional Minimum group richness to have in the (galaxy) group catalogue. This variable is set to
1
by default, and must be larger than1
.- perf_opt :
bool
, optional Option for using a
perfect
mock catalogue. This variable is set toFalse
by default.
Returns: - catl_pd_mod :
pandas.DataFrame
Version of
catl_pd
after having removed thefailed
values ofsSFR
andMstar
, and also after having chosen only galaxies and groups with group richnesses larger thannmin
.
Raises: - SDSSCatlUtils_Error : Exception from
SDSSCatlUtils_Error
Program exception if input parameters are
not
accepted.
Examples
Before using this function, one needs to have read one of the (galaxy) group catalogues. If for example, one wants to create a new object from the
data
real
SDSS catalogue with galaxies from groups withn > 10
, one can do:>>> from cosmo_utils.utils import file_readers as cfr >>> from sdss_catl_utils.mocks_manager.catl_utils import catl_clean_nmin >>> nmin = 10 # Minimum number of galaxies in file >>> catl_pd = cfr.read_hdf5_file_to_pandas_DF('/path/to/file') # doctest: +SKIP >>> catl_mod = catl_clean_nmin(catl_pd, 'data', nmin=nmin) # doctest: +SKIP
Now, the resulting catalogue will only include galaxies from groups with
n > 10
.- catl_pd :