Source code for lenstronomy.Util.simulation_util

import lenstronomy.Util.util as util
import lenstronomy.Util.image_util as image_util

import numpy as np

from lenstronomy.Util.package_util import exporter

export, __all__ = exporter()




@export
def data_configure_simple(
    numPix,
    deltaPix,
    exposure_time=None,
    background_rms=None,
    center_ra=0,
    center_dec=0,
    inverse=False,
):
    """Configures the data keyword arguments with a coordinate grid centered at zero.

    :param numPix: number of pixel (numPix x numPix)
    :param deltaPix: pixel size (in angular units)
    :param exposure_time: exposure time
    :param background_rms: background noise (Gaussian sigma)
    :param center_ra: RA at the center of the image
    :param center_dec: DEC at the center of the image
    :param inverse: if True, coordinate system is ra to the left, if False, to the right
    :return: keyword arguments that can be used to construct a Data() class instance of
        lenstronomy
    """

    # 1d list of coordinates (x,y) of a numPix x numPix square grid, centered to zero
    (
        x_grid,
        y_grid,
        ra_at_xy_0,
        dec_at_xy_0,
        x_at_radec_0,
        y_at_radec_0,
        Mpix2coord,
        Mcoord2pix,
    ) = util.make_grid_with_coordtransform(
        numPix=numPix,
        deltapix=deltaPix,
        center_ra=center_ra,
        center_dec=center_dec,
        subgrid_res=1,
        inverse=inverse,
    )
    # mask (1= model this pixel, 0= leave blanck)
    # exposure_map = np.ones((numPix, numPix)) * exposure_time  # individual exposure time/weight per pixel

    kwargs_data = {
        "background_rms": background_rms,
        "exposure_time": exposure_time,
        "ra_at_xy_0": ra_at_xy_0,
        "dec_at_xy_0": dec_at_xy_0,
        "transform_pix2angle": Mpix2coord,
        "image_data": np.zeros((numPix, numPix)),
    }
    return kwargs_data





@export
def simulate_simple(
    image_model_class,
    kwargs_lens=None,
    kwargs_source=None,
    kwargs_lens_light=None,
    kwargs_ps=None,
    no_noise=False,
    source_add=True,
    lens_light_add=True,
    point_source_add=True,
):
    """

    :param image_model_class:
    :param kwargs_lens:
    :param kwargs_source:
    :param kwargs_lens_light:
    :param kwargs_ps:
    :param no_noise:
    :param source_add:
    :param lens_light_add:
    :param point_source_add:
    :return:
    """

    image = image_model_class.image(
        kwargs_lens,
        kwargs_source,
        kwargs_lens_light,
        kwargs_ps,
        source_add=source_add,
        lens_light_add=lens_light_add,
        point_source_add=point_source_add,
    )
    # add noise
    if no_noise:
        return image
    else:
        poisson = image_util.add_poisson(
            image, exp_time=image_model_class.Data.exposure_map
        )
        bkg = image_util.add_background(
            image, sigma_bkd=image_model_class.Data.background_rms
        )
        return image + bkg + poisson