adler.objectdata.objectdata_utilities

Attributes

logger

Functions

get_data_table(sql_query[, service, sql_filename])	Gets a table of data based on a SQL query. Table is pulled from either the RSP or a local SQL database:
get_from_table(data_table, column_name, data_type[, ...])	Retrieves information from the data_table and forces it to be a specified type.
get_from_dictionary(data_dict, key_name, data_type[, ...])	Retrieves information from a dictionary and forces it to be a specified type.
check_value_populated(data_val, data_type, ...)	Checks to see if data_val populated properly and prints a helpful warning if it didn't.
convertTime(timestamps[, input_fmt, input_scale, ...])	Convenience function for converting timestamps between formats and scales.
sqlite_column_exists(conn, table, column)	Function for checking if column exists in a given table in a given database connection.
add_column_if_not_exists(conn, table, column, coltype)	Function for adding a column to a given table in a given database if it does not exist.
mpc_file_preprocessing(sql_filename)	Function for performing pre-processing steps on the obs_sbn table in the MPC file format.
flux_to_magnitude(flux[, flux_err])	Converts a flux measurement (with units of nanoJanskys) and its associated error
generate_summary_csvs(sql_filepath, output_file_root)	Function for generating the CSV files that summarise the contents of the outlier detection SQLite database.
get_tap_service_api(rsp_tap_path, api_token_path)	Returns a pyvo.dal.TAPService object linked to the RSP if provided with the desired API path and valid API token. For use with querying the RSP remotely.

Module Contents

logger

get_data_table(sql_query, service=None, sql_filename=None)

Gets a table of data based on a SQL query. Table is pulled from either the RSP or a local SQL database: this behaviour is controlled by the service and sql_filename parameters, one of which must be supplied.

Parameters:

• sql_query (str) – The SQL query made to the RSP or SQL database.

• service (pyvo.dal.tap.TAPService object or None) – TAPService object linked to the RSP. Default=None.

• sql_filename (str or None) – Filepath to a SQL database. Default=None.

Returns:

data_table – Data table containing the results of the SQL query.

Return type:

DALResultsTable or Pandas dataframe

get_from_table(data_table, column_name, data_type, table_name='default')

Retrieves information from the data_table and forces it to be a specified type.

Parameters:

• data_table (DALResultsTable or Pandas dataframe) – Data table containing columns of interest.

• column_name (str) – Column name under which the data of interest is stored.

• data_type (type) – Data type. Should be int, float, str or np.ndarray.

• table_name (str) – Name of the table. This is mostly for more informative error messages. Default=”default”.

Returns:

data_val – The data requested from the table cast to the type required.

Return type:

str, float, int or nd.array

get_from_dictionary(data_dict, key_name, data_type, table_name='default')

Retrieves information from a dictionary and forces it to be a specified type.

Parameters:

• data_dict (dict or dict-like object) – Dictionary containing columns of interest.

• key_name (str) – Key name under which the data of interest is stored.

• data_type (type) – Data type. Should be int, float, str or np.ndarray.

• table_name (str) – Name of the table or dictionary. This is mostly for more informative error messages. Default=”default”.

Returns:

data_val – The data requested from the dictionary cast to the type required.

Return type:

str, float, int or nd.array

check_value_populated(data_val, data_type, column_name, table_name)

Checks to see if data_val populated properly and prints a helpful warning if it didn’t. Usually this will trigger because the RSP or Cassandra database hasn’t populated that field for this particular object.

Parameters:

• data_val (str, float, int or nd.array) – The value to check.

• data_type (type) – Data type. Should be int, float, str or np.ndarray.

• column_name (str) – Column name under which the data of interest is stored.

• table_name (str) – Name of the table. This is mostly for more informative error messages. Default=”default”.

Returns:

data_val – Either returns the original data_val or an np.nan if it detected that the value was not populated.

Return type:

str, float, int, nd.array or np.nan

convertTime(timestamps, input_fmt='mjd', input_scale='utc', output_fmt='mjd', output_scale='tai')

Convenience function for converting timestamps between formats and scales.

Parameters:

• timestamps (float, int or nd.array) – Timestamp(s) to be converted.

• input_fmt (str) – Input format of timestamps. See https://docs.astropy.org/en/latest/api/astropy.time.Time.html for allowable formats. Default ‘mjd’.

• input_scale (str) – Input scale of timestamps. See https://docs.astropy.org/en/latest/api/astropy.time.Time.html for allowable scales. Default ‘utc’.

• output_fmt (str) – Desired format of output values. See https://docs.astropy.org/en/latest/api/astropy.time.Time.html for allowable formats. Default ‘mjd’.

• output_scale (str) – Desired scale of output values. See https://docs.astropy.org/en/latest/api/astropy.time.Time.html for allowable scales. Default ‘tai’.

Returns:

output_timestamps – The output timestamps in the desired format and scale as an astropy.time.Time object.

Return type:

astropy.time.Time object

sqlite_column_exists(conn, table, column)

Function for checking if column exists in a given table in a given database connection.

Parameters:

• conn (sqlite3.Connection object) – The connection to the database that we wish to check for a given column.

• table (str) – The name of the table we wish to check for the given column in.

• column (str) – The name of the column we wish to check for.

Returns:

result – Boolean flag for whether the collect exists or not.

Return type:

bool

add_column_if_not_exists(conn, table, column, coltype)

Function for adding a column to a given table in a given database if it does not exist.

Parameters:

• conn (sqlite3.Connection object) – The connection to the database that we wish to add the column to in the given table.

• table (str) – The name of the table we wish add the column to.

• column (str) – The name of the column we wish to add.

• coltype (str) – SQlite datatype for the column we wish to add. See https://sqlite.org/datatype3.html

Return type:

None

mpc_file_preprocessing(sql_filename)

Function for performing pre-processing steps on the obs_sbn table in the MPC file format. The function strips the leading ‘L’ from the band in the obs_sbn file; adds a mjd_tai column with the observation time in MJD in the TAI scale; and checks the topocentricDist, heliocentricDist and phaseAngle are present (renaming columns if need be).

Parameters:

sql_filename (str) – Filepath to the local SQL database.

Return type:

None

flux_to_magnitude(flux, flux_err=np.nan)

Converts a flux measurement (with units of nanoJanskys) and its associated error into AB magnitudes. If no flux error is provided, the returned magnitude error will be NaN.

Parameters:

• flux (float or astropy.units.Quantity) – Flux value in nanoJanskys (can be specified with Astropy units of nanoJanskys (u.nJy).

• flux_err (float or astropy.units.Quantity, optional) – Flux error with units of nanoJanskys (u.nJy). Default is np.nan (dimensionless), in which case the magnitude error will be returned as NaN.

Returns:

• magnitude (float) – The flux converted into AB magnitude (unitless scalar).

• magnitude_err (float) – The propagated uncertainty in AB magnitude (unitless scalar). Returns NaN if flux_err is not provided.

generate_summary_csvs(sql_filepath, output_file_root, output_cols=['ssObjectId'], filter_list=['u', 'g', 'r', 'i', 'z', 'y'])

Function for generating the CSV files that summarise the contents of the outlier detection SQLite database.

Parameters:

• sql_filepath (str) – Filepath to the SQLite database

• output_file_root (str) – Desired path for the output file. Default in example notebook is f”{output_dir}/{planetoid.AdlerData.modelId}”.

• output_cols (list of str, optional) – List of columns desired for output file. Default: [“ssObjectId”]. If default chosen, only DISTINCT ssObjectIds will be written out.

• filter_list (list of str, optional) – A comma-separated list of the filters of interest.

get_tap_service_api(rsp_tap_path, api_token_path)

Returns a pyvo.dal.TAPService object linked to the RSP if provided with the desired API path and valid API token. For use with querying the RSP remotely.

Parameters:

• rsp_tap_path (str) – End of the API url, ‘ssotap’ for DP0.3, ‘tap’ for DP1. Set by schema choice in AdlerPlanetoid.

• api_token_path (str) – User-provided path to their RSP TAP API token. If specified as, e.g., ‘~/.rsp_tap.token’ this will be expanded by the code.

Returns:

rsp_tap_service – TAPService object linked to the RSP.

Return type:

pyvo.dal.TAPService