ramjet.data_interface.tess_data_interface¶

Classes¶

Functions¶

class TessFluxType[source]¶

Bases: enum.Enum

An enum to represent the types of available fluxes in TESS two minute data.

SAP = SAP_FLUX¶

PDCSAP = PDCSAP_FLUX¶

class ColumnName[source]¶

Bases: enum.StrEnum

An enum for the names of the columns produced by the data interface class.

TIC_ID = TIC ID¶

SECTOR = Sector¶

is_common_mast_connection_error(exception: Exception) → bool[source]¶

Returns if the passed exception is a common MAST connection error. Made for deciding whether to retry a function.

Parameters:	exception – The exception to check.
Returns:	A boolean stating if the exception is a common MAST connection error.

exception NoDataProductsFoundException[source]¶

Bases: Exception

An exception when no data products are found from MAST.

class TessDataInterface[source]¶

A class for common interfacing with TESS data, such as downloading, sorting, and manipulating.

__init__(self)[source]¶

Initialize self. See help(type(self)) for accurate signature.

get_all_tess_time_series_observations(self, tic_id: Union[int, List[int]] = None)[source]¶

Gets all TESS time-series observations, limited to science data product level. Breaks large queries up to make the communication with MAST smoother.

Parameters:	tic_id – An optional TIC ID or list of TIC IDs to limit the query to.
Returns:	The list of time series observations as rows in a Pandas data frame.

static get_all_tess_time_series_observations_chunk(tic_id: Union[int, List[int]] = None)[source]¶

Gets all TESS time-series observations, limited to science data product level. Repeats download attempt on error.

Parameters:	tic_id – An optional TIC ID or list of TIC IDs to limit the query to.
Returns:	The list of time series observations as rows in a Pandas data frame.

get_product_list(self, observations: pd.DataFrame)[source]¶

A wrapper for MAST’s get_product_list, allowing the use of Pandas DataFrames instead of AstroPy Tables. Breaks large queries up to make the communication with MAST smoother.

Parameters:	observations – The data frame of observations to get. Will be converted from DataFrame to Table for query.
Returns:	The data frame of the product list. Will be converted from Table to DataFrame for use.

static get_product_list_chunk(observations: pd.DataFrame)[source]¶

A wrapper for MAST’s get_product_list, allowing the use of Pandas DataFrames instead of AstroPy Tables. Retries on error when communicating with the MAST server.

Parameters:	observations – The data frame of observations to get. Will be converted from DataFrame to Table for query.
Returns:	The data frame of the product list. Will be converted from Table to DataFrame for use.

static download_products(data_products: pd.DataFrame, data_directory: Path)[source]¶

A wrapper for MAST’s download_products, allowing the use of Pandas DataFrames instead of AstroPy Tables. Retries on error when communicating with the MAST server.

Parameters:	data_products – The data frame of data products to download. Will be converted from DataFrame to Table for sending the request to MAST. data_directory – The path to download the data to.
Returns:	The manifest of the download. Will be converted from Table to DataFrame for use.

static filter_for_single_sector_observations(time_series_observations: pd.DataFrame)[source]¶

Filters a data frame of observations to get only the single sector observations.

Parameters:	time_series_observations – A data frame of observations to filter for single sector observations.
Returns:	The data frame of single sector observations.

static filter_out_twenty_second_cadence_observations(time_series_observations: pd.DataFrame)[source]¶

Removes 20-second cadence data from the observation data frame.

Parameters:	time_series_observations – A data frame of observations to filtered.
Returns:	The data frame without 20-second cadence data.

static filter_for_multi_sector_observations(time_series_observations: pd.DataFrame)[source]¶

Filters a data frame of observations to get only the multi sector observations.

Parameters:	time_series_observations – A data frame of observations to filter for multi sector observations.
Returns:	The data frame of multi sector observations.

static get_tic_id_from_single_sector_obs_id(obs_id: str)[source]¶

Extracts the TIC ID from a single-sector obs_id string.

Parameters:	obs_id – The obs_id to extract from.
Returns:	The extracted TIC ID.

static get_sector_from_single_sector_obs_id(obs_id: str)[source]¶

Extracts the sector from a single-sector obs_id string.

Parameters:	obs_id – The obs_id to extract from.
Returns:	The extracted sector number.

add_tic_id_column_to_single_sector_observations(self, data_frame: pd.DataFrame)[source]¶

Adds a column with the TIC ID the row is related to.

Parameters:	data_frame – The data frame of single-sector entries.
Returns:	The table with the added TIC ID column.

add_sector_column_to_single_sector_observations(self, observations: pd.DataFrame)[source]¶

Adds a column with the sector the data was taken from.

Parameters:	observations – The table of single-sector observations.
Returns:	The table with the added sector column.

load_light_curve_from_fits_file(self, light_curve_path: Union[str, Path])[source]¶

Loads a light_curve from a FITS file in a dictionary form with the structure of the FITS arrays.

Parameters:	light_curve_path – The path to the FITS file.
Returns:	The light_curve.

load_fluxes_and_times_from_fits_file(self, light_curve_path: Union[str, Path], flux_type: TessFluxType = TessFluxType.PDCSAP, remove_nans: bool = True)[source]¶

Extract the flux and time values from a TESS FITS file.

Parameters:	light_curve_path – The path to the FITS file. flux_type – The flux type to extract from the FITS file. remove_nans – Whether or not to remove nans.
Returns:	The flux and times values from the FITS file.

load_fluxes_flux_errors_and_times_from_fits_file(self, light_curve_path: Union[str, Path], flux_type: TessFluxType = TessFluxType.PDCSAP, remove_nans: bool = True)[source]¶

Extract the flux and time values from a TESS FITS file.

Parameters:	light_curve_path – The path to the FITS file. flux_type – The flux type to extract from the FITS file. remove_nans – Whether or not to remove nans.
Returns:	The flux and times values from the FITS file.

download_two_minute_cadence_light_curve(self, tic_id: int, sector: int = None, save_directory: Union[Path, str] = None)[source]¶

Downloads a light curve from MAST.

Parameters:	tic_id – The TIC ID of the light curve target to download. sector – The sector to download. If not specified, downloads first available sector. save_directory – The directory to save the FITS file to. If not specified, uses the system temporary directory.
Returns:	The path to the downloaded file.

plot_light_curve_from_mast(self, tic_id: int, sector: int = None, exclude_flux_outliers: bool = False, base_data_point_size=3)[source]¶

Downloads and plots a light curve from MAST.

Parameters:	tic_id – The TIC ID of the light curve target to download. sector – The sector to download. If not specified, downloads first available sector. exclude_flux_outliers – Whether or not to exclude flux outlier data points when plotting. base_data_point_size – The size of the data points to use when plotting (and related sizes).

create_pdcsap_and_sap_comparison_figure_from_mast(self, tic_id: int, sector: int = None)[source]¶

Creates a comparison figure containing both the PDCSAP and SAP signals.

Parameters:	tic_id – The TIC ID of the light curve to plot. sector – The sector of the light curve to plot.
Returns:	The generated figure.

show_pdcsap_and_sap_comparison_from_mast(self, tic_id: int, sector: int = None)[source]¶

Shows a comparison figure containing both the PDCSAP and SAP signals.

Parameters:	tic_id – The TIC ID of the light curve to plot. sector – The sector of the light curve to plot.

show_light_curve(self, light_curve_path: Path)[source]¶

Shows a figure of the light curve at the passed path.

Parameters:	light_curve_path – The path of the light curve.

static get_target_coordinates(tic_id: int)[source]¶

Get the sky coordinates of the target by a TIC ID.

Parameters:	tic_id – The target’s TIC ID.
Returns:	The coordinates of the target.

static get_tess_input_catalog_row(tic_id: int)[source]¶

Get the TIC row for a TIC ID.

Parameters:	tic_id – The target’s TIC ID.
Returns:	The row of a the TIC corresponding to the TIC ID.

static get_variable_data_frame_for_coordinates(coordinates, radius='21s')[source]¶

Gets a data frame containing all known variables within a radius of the given coordinates.

Parameters:	coordinates – The coordinates to search. radius – The radius to search. TESS has a pixel size of 21 arcseconds across.
Returns:	The data frame of the variables. Returns an empty data frame if none exist.

get_variable_data_frame_for_tic_id(self, tic_id)[source]¶

Gets a data frame containing all known variables near a TIC target (including the target if applicable).

Parameters:	tic_id – The TIC target to search for variables near.
Returns:	A data frame of the variables near the target (including the target if applicable).

print_variables_near_tess_target(self, tic_id)[source]¶

Prints all variable stars near a given TESS target (including the target if applicable).

Parameters:	tic_id – The TIC target to search for variables near.

download_two_minute_cadence_light_curves(self, save_directory: Path, limit: Union[None, int] = None)[source]¶

Downloads all two minute cadence light curves from TESS.

Parameters:	save_directory – The directory to save the light curves to. limit – Limits the number of light curves downloaded. Default of None will download all light curves.

get_sectors_target_appears_in(self, tic_id: int)[source]¶

Gets the list of sectors a TESS target appears in.

Parameters:	tic_id – The TIC ID of the target.
Returns:	The list of sectors.

get_all_two_minute_single_sector_observations(self, tic_ids: List[int] = None)[source]¶

Gets the data frame containing all the single sector observations, with TIC ID and sector columns.

Parameters:	tic_ids – The TIC IDs to get observations for.
Returns:	The data frame containing the observation information.

verify_light_curve(self, light_curve_path: Path)[source]¶

The light_curve is checked if it’s malformed, and if it is, it is re-downloaded.

Parameters:	light_curve_path – The path of the light_curve.

static get_tic_id_and_sector_from_file_path(file_path: Union[Path, str])[source]¶

Gets the TIC ID and sector from commonly encountered file name patterns.

Parameters:	file_path – The path of the file to extract the TIC ID and sector.
Returns:	The TIC ID and sector. The sector might be omitted (as None).

tess_data_interface¶