hpmcm.wcs_match module

class hpmcm.wcs_match.WcsMatch(match_wcs, **kwargs)[source]

Class to do N-way matching using a provided WCS.

This uses the provided WCS to define a Skymap that covers the full region begin matched.

Notes

This expectes a list of parquet files with pandas DataFrames that contain the following columns.

Column name	Description
id	source ID
ra	RA in degrees
dec	DEC in degress
snr	Signal-to-Noise of source, used for filtering and centroiding

Parameters:

classmethod create(ref_dir, region_size, pixel_size, **kwargs)[source]

Helper function to create a Match object.

This will use the provided arguments to create a WCS, and then create and return a WcsMatch matcher.

Return type:

WcsMatch

Parameters:

ref_dir (tuple[float, float]) – Reference Direction (RA, DEC) in degrees
region_size (tuple[float, float]) – Size of match region, in degrees
pix_size – Pixel size in degrees
pixel_size (float)
kwargs (Any)

Return type:

Object to create matches for the requested region

pixToWorld(x_pix, y_pix)[source]

Convert local coords in pixels to world coordinates (RA, DEC)

Return type:

tuple[ndarray, ndarray]

Parameters:

reduceDataFrame(df)[source]

Reduce a single input DataFrame

Notes

This applies a trivial cut on signal-to-noise (snr>1). and adds the pixel coordinates to the DataFrame.

This will add these columns to the output dataframes

Column	Description
id	Index of object inside catalog
ra	Source RA
dec	Source DEC
x_pix	X-coordinate in global WCS frame
y_pix	Y-coordinate in global WCS frame
snr	Signal-to-noise ratio

hpmcm.wcs_match.createGlobalWcs(ref_dir, pix_size, n_pix)[source]

Helper function to create the WCS used to project the sources in a skymap

Return type:

WCS

Parameters:

ref_dir (tuple[float, float]) – Reference Direction (RA, DEC) in degrees
pix_size (float) – Pixel size in degrees
n_pix (ndarray) – Number of pixels in x, y

Return type:

WCS to create the pixel grid