slsim.ImageSimulation package

Submodules

slsim.ImageSimulation.image_quality_lenstronomy module

slsim.ImageSimulation.image_quality_lenstronomy.kwargs_single_band(band, observatory='LSST', **kwargs)

This is the function for returning the band information.

Parameters:

• band (str) – ‘u’, ‘g’, ‘r’, ‘i’, ‘z’ or ‘y’ supported. Determines imaging bands.

• observatory (str) – observatory chosen

• kwargs (dict) – additional keyword arguments for the bands

Returns:

configuration of imaging data

Return type:

dict

slsim.ImageSimulation.image_simulation module

slsim.ImageSimulation.image_simulation.centered_coordinate_system(num_pix, transform_pix2angle)

Returns dictionary for Coordinate Grid such that (0,0) is centered with given input orientation coordinate transformation matrix.

Parameters:

• num_pix (int) – number of pixels

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

Returns:

dict with ra_at_xy_0, dec_at_xy_0, transfrom_pix2angle

slsim.ImageSimulation.image_simulation.deflector_images_with_different_zeropoint(lens_class, band, mag_zero_point, delta_pix, num_pix)

Creates deflector images with different magnitude zero point. This function is useful when one wants to simulate variable lens images. For this, we need to simulate delctor images for different exposure (where we want to inject lenses) and those exposure could have different magnitude zero point.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – list of magnitude zero point in band for sequence of exposure

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

Returns:

list of deflector images with different zero point

slsim.ImageSimulation.image_simulation.image_data_class(lens_class, band, mag_zero_point, delta_pix, num_pix, transform_pix2angle)

Provides data class for image.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

Returns:

image data class

slsim.ImageSimulation.image_simulation.image_plus_poisson_noise(image, exposure_time, gain=1, coadd_zero_point=27, single_visit_zero_point=27)

Creates an image with possion noise.

Parameters:

• image – an image

• exposure_time – exposure time or exposure map for an image

• band – imaging band

• gain – Amplifier gain (default 1).

• coadd_zero_point – Zero point of the coadded image (default 27).

• single_visit_zero_point – Zero point of the single-visit image (default 27 for g-band).

Returns:

image with possion noise. The function returns ADU/sec in all cases, regardless of whether gain = 1 or not. The noise is applied in the electron domain, but the final image is converted back to ADU/sec.

slsim.ImageSimulation.image_simulation.image_plus_poisson_noise_for_list_of_image(images, exposure_times)

Creates an image with possion noise.

Parameters:

• images – list of images

• exposure_time – list of exposure times or exposure maps

Returns:

list of images with possion noise

slsim.ImageSimulation.image_simulation.lens_image(lens_class, band, mag_zero_point, num_pix, psf_kernel, transform_pix2angle, exposure_time=None, t_obs=None, std_gaussian_noise=None, with_source=True, with_deflector=True, gain=0.7, single_visit_mag_zero_points={'g': 32.33, 'i': 31.85, 'r': 32.17, 'y': 30.63, 'z': 31.45})

Creates lens image on the basis of given information. It can simulate both static lens image and variable lens image.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point for the exposure

• num_pix – number of pixels per axis

• psf_kernels – psf kernel for the exposures being.

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

• exposure_time – exposure time for for the exposure. It could be single exposure time or a exposure map.

• t_obs – an observation time [day]. This is applicable only for variable source. In case of point source, if we do not provide t_obs, considers no variability in the lens.

• std_gaussian_noise – standard deviation for a gaussian noise

• with_source – If True, simulates image with extended source in lens configuration.

• with_deflector – If True, simulates image with deflector.

• gain – Amplifier gain (default 0.7 for LSST).

• single_visit_mag_zero_points – Zero points of the single-visit image in different bands. It is a dictionary of the form: { ‘g’: 32.33, ‘r’: 32.17, ‘i’: 31.85, ‘z’: 31.45, ‘y’: 30.63 }. It sould contain at least values for the band in which one need to simulate images. Default values are average magnitude zero points for LSST single visists in each band.

Returns:

lens image

slsim.ImageSimulation.image_simulation.lens_image_series(lens_class, band, mag_zero_point, num_pix, psf_kernel, transform_pix2angle, exposure_time=None, t_obs=None, std_gaussian_noise=None, with_source=True, with_deflector=True, gain=0.7, single_visit_mag_zero_points={'g': 32.33, 'i': 31.85, 'r': 32.17, 'y': 30.63, 'z': 31.45})

Creates lens image on the basis of given information. This function is designed to simulate time series images of a lens.

Parameters:

• lens_class – Lens() object

• band – imaging band (or list of bands). if float: assumed to apply to the full image series.

• mag_zero_point – list of magnitude zero point for sequence of exposure

• num_pix – number of pixels per axis

• psf_kernels – list of psf kernel for each exposure.

• transform_pix2angle – list of transformation matrix (2x2) of pixels into coordinate displacements for each exposure

• exposure_time – list of exposure time for each exposure. It could be single exposure time or a exposure map.

• t_obs – array of image observation time [day] for a lens.

• std_gaussian_noise – array of standard deviation for gaussian noise for each image

• with_source – If True, simulates image with extended source in lens configuration.

• with_deflector – If True, simulates image with deflector.

• gain – Amplifier gain (default 0.7 for LSST).

• single_visit_mag_zero_points –

  Zero points of the single-visit image in different bands. It is a dictionary of the form: {

  ’g’: 32.33, ‘r’: 32.17, ‘i’: 31.85, ‘z’: 31.45, ‘y’: 30.63

  }. It sould contain at least values for the band in which one need to simulate images. Default values are average magnitude zero points for LSST single visists in each band.

Returns:

list of series of images of a lens

slsim.ImageSimulation.image_simulation.point_source_coordinate_properties(lens_class, band, mag_zero_point, delta_pix, num_pix, transform_pix2angle)

Provides pixel coordinates for deflector and images. Currently, this function only works for point source.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

Returns:

Dictionary of deflector and image coordinate in pixel unit and other coordinate properties.

slsim.ImageSimulation.image_simulation.point_source_image_at_time(lens_class, band, mag_zero_point, delta_pix, num_pix, psf_kernel, transform_pix2angle, time)

Creates lensed point source images with variability at a given time on the basis of given information.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• psf_kernel – psf kernel for the given exposure.

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

• time – time is an image observation time [day].

Returns:

point source images with variability

slsim.ImageSimulation.image_simulation.point_source_image_with_variability(lens_class, band, mag_zero_point, delta_pix, num_pix, psf_kernels, transform_pix2angle, t_obs)

Creates lensed point source images with variability for series of time on the basis of given information.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point for each exposure

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• psf_kernels – psf kernels in the sequence of exposures being simulated.

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

• t_obs – array of image observation time [day].

Returns:

array of point source images with variability

slsim.ImageSimulation.image_simulation.point_source_image_without_variability(lens_class, band, mag_zero_point, delta_pix, num_pix, psf_kernel, transform_pix2angle)

Creates lensed point source images without variability on the basis of given information.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• psf_kernel – psf kernel for an image.

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

Returns:

point source images

slsim.ImageSimulation.image_simulation.rgb_image_from_image_list(image_list, stretch)

Creates a rgb image using list of images in r, g, and b.

Parameters:

image_list – images in r, g, and b band. Here, ‘i’, ‘r’, and ‘g’ band are consider as r, g, and b respectively.

Returns:

rgb image

slsim.ImageSimulation.image_simulation.sharp_image(lens_class, band, mag_zero_point, delta_pix, num_pix, with_source=True, with_deflector=True)

Creates an unconvolved image of a selected lens. Point source image is not included in this function.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

• with_source – bool, if True computes source

• with_deflector – bool, if True includes deflector light

Returns:

2d array unblurred image

slsim.ImageSimulation.image_simulation.sharp_rgb_image(lens_class, rgb_band_list, mag_zero_point, delta_pix, num_pix)

Creates an unconvolved rgb image of a selected lens.

Parameters:

• lens_class – Lens() object

• rgb_band_list – imaging band list. Here, ‘i’, ‘r’, and ‘g’ band are consider as r, g, and b respectively.

• mag_zero_point – magnitude zero point in band

• delta_pix – pixel scale of image generated

• num_pix – number of pixels per axis

Returns:

rgb image

slsim.ImageSimulation.image_simulation.simulate_image(lens_class, band, num_pix, add_noise=True, observatory='LSST', kwargs_psf=None, kwargs_numerics=None, **kwargs)

Creates an image of a selected lens with noise.

Parameters:

• lens_class – class object containing all information of the lensing system (e.g., Lens())

• band – imaging band

• num_pix – number of pixels per axis

• add_noise – if True, add noise

• observatory (str) – telescope type to be simulated

• kwargs_psf (dict) – (optional) specific PSF quantities to overwrite default options (“psf_type”, “kernel_point_source”, “point_source_supersampling_factor”)

• kwargs (dict) – additional keyword arguments for the bands

• kwargs_numerics (dict) – options are “point_source_supersampling_factor”, “supersampling_factor”, and more in lenstronomy.ImSim.Numerics.numerics class

Returns:

simulated image

Return type:

2d numpy array

slsim.ImageSimulation.roman_image_simulation module

slsim.ImageSimulation.roman_image_simulation.add_roman_background(image, band, detector, num_pix, exposure_time, ra, dec, date)

Adds a sky and thermal background to image, corresponding to a specific band, detector, date, and coordinate in the sky.

Parameters:

• image (galsim Image class) – image to add the background to

• band (string) – imaging band

• detector (integer from 1 to 18) – The specific Roman detector being used to generate the psf

• num_pix (integer) – number of pixels per axis

• ra (float between 15 and 45) – Coordinate in space used to generate sky background

• dec (float between -45 and -15) – Coordinate in space used to generate sky background

• date (datetime.datetime class) – Date used to generate sky background

Returns:

image with added background

Return type:

galsim Image class

slsim.ImageSimulation.roman_image_simulation.get_bandpass(band)

Parameters:

band (string) – imaging band

Returns:

galsim bandpass object corresponding to specific band

Return type:

galsim Bandpass class

slsim.ImageSimulation.roman_image_simulation.get_bandpass_key(band)

Translates the Roman bands to keys used in galsim.

Parameters:

band (string) – The Roman band to be translated

Returns:

Translated band

Return type:

string

slsim.ImageSimulation.roman_image_simulation.get_psf(band, detector, detector_pos, oversample, psf_directory)

Obtain galsim psf corresponding to specific band, using stpsf.

Parameters:

• band (string) – The specific band corresponding to the psf

• detector (integer from 1 to 18) – The specific Roman detector being used to generate the psf

• detector_pos (integer between 4 + num_pix * oversample and 4092 - num_pix * oversample) – The position of the detector being used to generate the psf

• oversample (integer) – Number of times that each pixel’s side is subdivided for higher accuracy psf convolution

• psf_directory (string) – Path to directory containing psf file(s) where the psf can be loaded. Otherwise, the psf will be generated by stpsf which is very slow

Returns:

An image of the psf generated by stpsf

Return type:

galsim’s InterpolatedImage class

slsim.ImageSimulation.roman_image_simulation.lens_image_roman(lens_class, band, mag_zero_point, num_pix, transform_pix2angle, detector=1, detector_pos=(2000, 2000), oversample=5, psf_directory=None, t_obs=None, with_source=True, with_deflector=True, ra=30, dec=-30, date=datetime.datetime(2027, 7, 7, 0, 0), add_noise=True, poisson_noise=True, seed=None)

Creates lens image on the basis of given information. It can simulate both static lens image and variable lens image.

Note: This function might evolve in near future.

Note: This function might be changed in future.

Parameters:

• lens_class – Lens() object

• band – imaging band

• mag_zero_point – magnitude zero point for the exposure

• num_pix – number of pixels per axis

• transform_pix2angle – transformation matrix (2x2) of pixels into coordinate displacements

• detector (integer from 1 to 18) – The specific Roman detector being used to generate the psf

• detector_pos (integer between 4 + num_pix * oversample and 4092 - num_pix * oversample) – The position of the detector being used to generate the psf

• oversample (integer) – Number of times that each pixel’s side is subdivided for higher accuracy psf convolution

• psf_directory (string) –

  Path to directory containing psf file(s) where the psf can be loaded. the user can download psfs from cached_webb_psf (https://github.com/LSST-strong-lensing/data_public/stpsf), where the

  psfs have been generated ahead of time so that they can be loaded from a file. The directory containing these psfs should be passed into the “psf_directory”.

• t_obs – an observation time [day]. This is applicable only for variable source. In case of point source, if we do not provide t_obs, considers no variability in the lens.

• with_source – If True, simulates image with extended source in lens configuration.

• with_deflector – If True, simulates image with deflector.

• ra (float between 15 and 45) – Coordinate in space used to generate sky background

• dec (float between -45 and -15) – Coordinate in space used to generate sky background

• date (datetime.datetime class) – Date used to generate sky background

• add_noise – determines whether sky background and detector effects are added or not

• poisson_noise (bool) – determines whether poisson noise is added or not

• seed (integer or None) – An rng seed used for generating detector effects in galsim

Returns:

lens image in roman filter

slsim.ImageSimulation.roman_image_simulation.simulate_roman_image(lens_class, band, num_pix, observatory='Roman', oversample=3, add_noise=True, with_source=True, with_deflector=True, detector=1, detector_pos=(2000, 2000), seed=None, ra=30, dec=-30, date=datetime.datetime(2027, 7, 7, 0, 0), psf_directory=None, **kwargs)

Creates an image of a selected lens with noise.

Parameters:

• lens_class – class object containing all information of the lensing system (e.g., Lens())

• band (string) – imaging band

• num_pix (integer) – number of pixels per axis

• add_noise – determines whether sky background and detector effects are added or not

• with_source (bool) – determines whether source is included in image

• with_deflector (bool) – determines whether deflector is included in image

• detector (integer from 1 to 18) – The specific Roman detector being used to generate the psf

• detector_pos (integer between 4 + num_pix * oversample and 4092 - num_pix * oversample) – The position of the detector being used to generate the psf

• seed (integer or None) – An rng seed used for generating detector effects in galsim

• ra (float between 15 and 45) – Coordinate in space used to generate sky background

• dec (float between -45 and -15) – Coordinate in space used to generate sky background

• date (datetime.datetime class) – Date used to generate sky background

• psf_directory (string) – Path to directory containing psf file(s) where the psf can be loaded. Otherwise, the psf will be generated by stpsf which is very slow

• kwargs (dict) – additional keyword arguments for the bands

Returns:

simulated image

Return type:

2d numpy array

Module contents