Module: fake_data_creator

A class for creating fake data sets.

The FakeDataSet class allows the user to create fake data sets for testing, including generating images with random noise and adding artificial objects. The fake data can be saved to files or used directly.

class kbmod.fake_data.fake_data_creator.FakeDataSet(width, height, times, noise_level=2.0, psf_val=0.5, use_seed=False)

This class creates fake data sets for testing and demo notebooks.

Methods

get_work_unit([config])	Create a WorkUnit from the fake data.
insert_object(trj)	Insert a fake object given the trajectory.
insert_random_object(flux)	Create a fake object and insert it into the image.
make_fake_ImageStack()	Make a stack of fake layered images.
save_fake_data_to_work_unit(filename[, config])	Create the fake data in a WorkUnit file.
set_wcs(new_wcs)	Set a new fake WCS to be used for this data.

get_work_unit(config=None)

Create a WorkUnit from the fake data.

Parameters:

filenamestr

The name of the resulting WorkUnit file.

configSearchConfiguration, optional

The configuration parameters to use. If None then uses default values.

insert_object(trj)

Insert a fake object given the trajectory.

Parameters:

trjTrajectory

The trajectory of the fake object to insert.

insert_random_object(flux)

Create a fake object and insert it into the image.

Parameters:

fluxfloat

The flux of the object.

Returns:

tTrajectory

The trajectory of the inserted object.

make_fake_ImageStack()

Make a stack of fake layered images.

Returns:

stackImageStack

save_fake_data_to_work_unit(filename, config=None)

Create the fake data in a WorkUnit file.

Parameters:

filenamestr

The name of the resulting WorkUnit file.

configSearchConfiguration, optional

The configuration parameters to use. If None then uses default values.

set_wcs(new_wcs)

Set a new fake WCS to be used for this data.

Parameters:

new_wcsastropy.wcs.WCS

The WCS to use.

kbmod.fake_data.fake_data_creator.add_fake_object(img, x, y, flux, psf=None)

Add a fake object to a LayeredImage or RawImage

Parameters:

imgRawImage or LayeredImage

The image to modify.

xint or float

The x pixel location of the fake object.

yint or float

The y pixel location of the fake object.

fluxfloat

The flux value.

psfnumpy.ndarray

The PSF’s kernel for the image.

kbmod.fake_data.fake_data_creator.create_fake_times(num_times, t0=0.0, obs_per_day=1, intra_night_gap=0.01, inter_night_gap=1)

Create a list of times based on a cluster of obs_per_day observations each night spaced out intra_night_gap within a night and inter_night_gap data between observing nights.

Parameters:

num_timesint

The number of time steps (number of images).

t0float

The time stamp of the first observation [default=0.0]

obs_per_dayint

The number of observations on the same night [default=1]

intra_night_gapfloat

The time (in days) between observations in the same night [default=0.01]

inter_night_gapint

The number of days between observing runs [default=1]

Returns:

result_timeslist

A list of num_times floats indicating the different time stamps.

kbmod.fake_data.fake_data_creator.make_fake_layered_image(width, height, noise_stdev, pixel_variance, obstime, psf, seed=None)

Create a fake LayeredImage with a noisy background.

Parameters:

widthint

Width of the images (in pixels).

height`int

Height of the images (in pixels).

noise_stdev: `float`

Standard deviation of the image.

pixel_variance: `float`

Variance of the pixels, assumed uniform.

obstimefloat

Observation time.

psfnumpy.ndarray

The PSF’s kernel for the image.

seedint, optional

The seed for the pseudorandom number generator.

Returns:

imgLayeredImage

The fake image.

Raises:

Raises ValueError if any of the parameters are invalid.