Comprehensive Cosmo Utils Reference/API
cosmo_utils.utils Package
cosmo_utils.utils.file_readers Module
Functions
IDL_read_file
(idl_file)
Reads an IDL file and converts it to a Python dictionary
fast_food_reader
(key, nitems, filename)
Reads in fastfood
-type file and converts it to an array
read_pandas_hdf5
(hdf5_file[, key, ret])
Reads a HDF5 file that contains one or many datasets.
read_hdf5_file_to_pandas_DF
(hdf5_file[, key])
Reads content of HDF5 file and converts it to a Pandas DataFrame
pandas_file_to_hdf5_file
(df_file, hdf5_file)
Converts a HDF5 with pandas format and converts it to normal HDF5 file
pandas_df_to_hdf5_file
(df, hdf5_file[, key, …])
Saves a pandas.DataFrame
into a pandas
HDF5 FILE.
concatenate_pd_df
(directory[, filetype, …])
Concatenates pandas DataFrames into a single DataFrame
cosmo_utils.utils.file_utils Module
Functions
Program_Msg
(filename)
Program message for filename
Index
(pathdir, datatype[, sort, basename])
Indexes the files in a directory pathdir
with a specific data type datatype
.
get_immediate_subdirectories
(pathdir[, sort])
Immediate subdirectories to a given directory path
Path_Folder
(pathdir[, time_sleep])
Creates a folder if it does not exist already
File_Exists
(filename)
Detrmines if file exists or not
File_Download_needed
(localpath, remotepath)
Determines if there exists a local copy of a file.
Classes
MarkParametrize
(argname, argvalues)
Parametrizes a set of values and changes the input variables of a function.
Class Inheritance Diagram
Inheritance diagram of cosmo_utils.utils.file_utils.MarkParametrize
cosmo_utils.utils.stats_funcs Module
Functions
myceil
(x[, base])
Determines the upper-bound interger for a given number with a given base.
myfloor
(x[, base])
Determines the lower-bound interger for a given number with a given base.
Bins_array_create
(arr[, base])
Generates an evenly-spaced array between the minimum and maximum value of a given array,
sigma_calcs
(data_arr[, type_sigma, …])
Calcualates the 1-, 2-, and 3-sigma ranges for data_arr
Stats_one_arr
(x, y[, base, arr_len, …])
Calculates statistics for 2 arrays
cosmo_utils.utils.work_paths Module
Functions
git_root_dir
([path])
Determines the path to the main .git folder of the project.
cookiecutter_paths
([path])
Paths to main folders in the Data Science
cookiecutter template.
get_code_c
()
Path to the directory that holds scripts written in the C-language
get_sdss_catl_dir
([path])
Extracts the path to the set of SDSS catalogues
get_output_path
()
Extracts path of SDSS catalogues within a directory
cosmo_utils.utils.geometry Module
Functions
flip_angles
(ang[, unit])
Ensures that an angle is always between 0 and 360 degrees.
Ang_Distance
(ra1, ra2, dec1, dec2[, unit, …])
Calculates angular separation between two sets of points with given right ascensions and declinations.
Coord_Transformation
(ra, dec, dist, ra_cen, …)
Transforms spherical coordinates (ra, dec, dist) into cartesian coordinates.
cosmo_utils.utils.gen_utils Module
Functions
reshape_arr_1d
(arr)
Transforms the array intoa 1-dimensional array, if necessary.
array_insert
(arr1, arr2[, axis])
Joins the two arrays into a single
multi-dimensional array.
cosmo_utils.custom_exceptions Module
Classes for all LSS_Utils-specific exceptions
Classes
LSSUtils_Error
(message)
Base class of all LSS_Utils-specific exceptions
Class Inheritance Diagram
Inheritance diagram of cosmo_utils.custom_exceptions.LSSUtils_Error
cosmo_utils.mock_catalogues Package
cosmo_utils.mock_catalogues.mags_calculations Module
cosmo_utils.mock_catalogues.spherematch Module
Functions
spherematch
(ra1, dec1, ra2, dec2[, tol, …])
Determines the matches between two catalogues of sources with <ra, dec> coordinates.
cosmo_utils.mock_catalogues.abundance_matching Module
cosmo_utils.mock_catalogues.catls_utils Module
Functions
catl_keys
(catl_kind[, perf_opt, return_type])
Dictionary keys for the different types of catalogues
catl_keys_prop
(catl_kind[, catl_info, …])
Dictionary keys for the diffeent galaxy and group properties of catalogues.
catl_sdss_dir
([catl_kind, catl_type, …])
Extracts the path to the synthetic catalogues.
extract_catls
([catl_kind, catl_type, …])
Extracts a list of synthetic catalogues given input parameters
sdss_catl_clean
(catl_pd, catl_kind[, …])
Cleans the catalogue by removing failed
values.
sdss_catl_clean_nmin
(catl_pd, catl_kind[, …])
Cleans the catalogue removing failed
values, and only includes galaxies that are in groups/halos above a nmin
threshold.
catl_sdss_merge
(catl_pd_ii[, catl_kind, …])
Merges the member and group catalogues for a given set of input parameters, and returns a modified version of the galaxy group catalogues with added info about the galaxy groups.
cosmo_utils.mock_catalogues.pair_counters Package
Functions
pairwise_distance_rp
Cython engine for returning pairs of points separated in projected radial bins with an observer at (0,0,0).
cosmo_utils.mock_catalogues.shmr_funcs Module
Functions
Behroozi_relation
(log_mstar[, z])
Returns the halo mass of a central galaxy as a function of its stellar mass.
cosmo_utils.ml Package
cosmo_utils.ml.ml_utils Module
Functions
data_preprocessing
(feat_arr[, pre_opt, reshape])
Preprocess the data used, in order to clean and make the data more suitable for the machine learning algorithms
train_test_dataset
(pred_arr, feat_arr[, …])
Function to create the training and testing datasets for a given set of features array and predicted array.
scoring_methods
(truth_arr[, feat_arr, …])
Determines the overall score for given arrays, i.e.