opticam.plotting.plots

Functions

plot_catalogs(out_directory, stacked_images, catalogs, ...)	Plot the source catalogs.
plot_time_between_files(out_directory, camera_files, ...)	Plot the times between files. Useful for identifying gaps.
plot_backgrounds(out_directory, camera_files, ...)	Plot the time-varying background for each camera.
plot_background_meshes(out_directory, filters, ...)	Plot the background meshes on top of the catalog images.
plot_growth_curves(image, cat, targets, psf_params)	Plot the growth curves given a (stacked) image and a source catalog.
plot_psf(catalog, source_indx, stacked_image, fltr, a, ...)	Plot the PSF for given source.
plot_rms_vs_median_flux(lc_dir, save_dir, phot_label)	Plot the RMS as a function of the median flux for all catalog sources.
get_lc_rms_and_flux_dict(lc_dir)	Get the RMS and median flux for a series of light curves.
plot_snrs(out_directory, files, background, ...[, show])	Plot the S/N for each source.
plot_noise(out_directory, files, background, ...[, show])	Plot the various noise contributions and compare them to the measured noise for a series of images.

Module Contents

opticam.plotting.plots.plot_catalogs(out_directory, stacked_images, catalogs, show, save)

Plot the source catalogs.

Parameters

out_directorystr

The directory path to which the resulting plot will be saved.

filtersList[str]

The catalog filters.

stacked_imagesDict[str, NDArray]

The stacked images for each filter {filter: image}.

showbool

Whether to show the plot.

savebool

Whether to save the plot.

Parameters:

• out_directory (str)

• stacked_images (Dict[str, numpy.typing.NDArray])

• catalogs (Dict[str, astropy.table.QTable])

• show (bool)

• save (bool)

Return type:

None

opticam.plotting.plots.plot_time_between_files(out_directory, camera_files, bmjds, show, save)

Plot the times between files. Useful for identifying gaps.

Parameters

out_directorystr

The directory path to which the resulting plot will be saved.

camera_filesDict[str, List[str]]

The file paths separated by camera {filter: file paths}.

bmjdsDict[str, float]

The file time stamps {file path: time stamp}.

showbool

Whether to show the plot.

savebool

Whether to save the plot.

Parameters:

• out_directory (str)

• camera_files (Dict[str, List[str]])

• bmjds (Dict[str, float])

• show (bool)

• save (bool)

Return type:

None

opticam.plotting.plots.plot_backgrounds(out_directory, camera_files, background_median, background_rms, bmjds, t_ref, show, save)

Plot the time-varying background for each camera.

Parameters

camera_filesDict[str, str]

The files for each camera {fltr: file}.

background_medianDict[str, List]

The median background for each camera.

background_rmsDict[str, List]

The background RMS for each camera.

bmjdsDict[str, float]

The Barycentric MJD dates for each image {file: BMJD}.

t_reffloat

The reference BMJD.

out_directorystr

The directory to which the resulting files will be saved.

show: bool

Whether to display the plot.

savebool

Whether to save the plot.

Parameters:

• out_directory (str)

• camera_files (Dict[str, List[str]])

• background_median (Dict[str, Dict[str, numpy.typing.NDArray]])

• background_rms (Dict[str, Dict[str, numpy.typing.NDArray]])

• bmjds (Dict[str, float])

• t_ref (float)

• show (bool)

• save (bool)

Return type:

None

opticam.plotting.plots.plot_background_meshes(out_directory, filters, stacked_images, background, show, save)

Plot the background meshes on top of the catalog images.

Parameters

stacked_imagesDict[str, NDArray]

The stacked images for each camera.

showbool

Whether to display the plot.

Parameters:

• out_directory (str)

• filters (List[str])

• stacked_images (Dict[str, numpy.typing.NDArray])

• background (opticam.background.global_background.BaseBackground)

• show (bool)

• save (bool)

Return type:

None

opticam.plotting.plots.plot_growth_curves(image, cat, targets, psf_params)

Plot the growth curves given a (stacked) image and a source catalog.

Parameters

imageNDArray

The image.

catQTable

The catalog corresponding to image.

targetsint | List[int]

The target(s) for which growth curves are to be computed.

psf_paramsDict

The PSF parameters.

Returns

Figure

The growth curve plots.

Parameters:

• image (numpy.typing.NDArray)

• cat (astropy.table.QTable)

• targets (int | List[int])

• psf_params (Dict)

Return type:

matplotlib.figure.Figure

opticam.plotting.plots.plot_psf(catalog, source_indx, stacked_image, fltr, a, b, out_directory)

Plot the PSF for given source.

Parameters

catalogQTable

The source catalog.

source_indxint

The index of the source in the catalog.

stacked_imageNDArray

The catalog image.

fltrstr

The filter.

afloat

The semimajor standard deviation of the PSF.

bfloat

The semiminor standard deviation of the PSF.

out_directorystr,

The save path.

Parameters:

• catalog (astropy.table.QTable)

• source_indx (int)

• stacked_image (numpy.typing.NDArray)

• fltr (str)

• a (float)

• b (float)

• out_directory (str)

Return type:

None

opticam.plotting.plots.plot_rms_vs_median_flux(lc_dir, save_dir, phot_label, show=True)

Plot the RMS as a function of the median flux for all catalog sources.

Parameters

lc_dirstr

The light curve directory path.

save_dirstr

The output directory path.

phot_labelstr

The photometry label.

showbool, optional

Whether to show the plot, by default True.

Parameters:

• lc_dir (str)

• save_dir (str)

• phot_label (str)

• show (bool)

Return type:

None

opticam.plotting.plots.get_lc_rms_and_flux_dict(lc_dir)

Get the RMS and median flux for a series of light curves.

Parameters

lc_dirstr

The directory path to the light curves.

Returns

Dict[str, Dict[str, Dict[str, float]]]

The median and RMS flux values for each light curve grouped by filter.

Parameters:

lc_dir (str)

Return type:

Dict[str, Dict[str, Dict[str, float]]]

opticam.plotting.plots.plot_snrs(out_directory, files, background, psf_params, catalogs, show=False)

Plot the S/N for each source.

Parameters

out_directorystr

The output directory.

filesDict[str, str]

The reference files for each filter {filter: path to image}.

backgroundBaseBackground | Callable

The global background estimator.

psf_paramsDict[str, Dict[str, float]]

The PSF parameters for each filter {filter: psf parameters}.

catalogsDict[str, QTable]

The catalogs for each filter {filter: catalog}.

photometerBasePhotometer

The photometer to use for measuring noise.

showbool, optional

Whether to show the plot, by default False.

Parameters:

• out_directory (str)

• files (Dict[str, str])

• background (opticam.background.global_background.BaseBackground | Callable)

• psf_params (Dict[str, Dict[str, float]])

• catalogs (Dict[str, astropy.table.QTable])

• show (bool)

opticam.plotting.plots.plot_noise(out_directory, files, background, psf_params, catalogs, show=False)

Plot the various noise contributions and compare them to the measured noise for a series of images.

Parameters

out_directorystr

The output directory.

filesDict[str, str]

The reference files for each filter {filter: path to image}.

backgroundBaseBackground | Callable

The global background estimator.

psf_paramsDict[str, Dict[str, float]]

The PSF parameters for each filter {filter: psf parameters}.

catalogsDict[str, QTable]

The catalogs for each filter {filter: catalog}.

photometerBasePhotometer

The photometer to use for measuring noise.

showbool, optional

Whether to show the plot, by default False.

Parameters:

• out_directory (str)

• files (Dict[str, str])

• background (opticam.background.global_background.BaseBackground | Callable)

• psf_params (Dict[str, Dict[str, float]])

• catalogs (Dict[str, astropy.table.QTable])

• show (bool)