Validation of image simulation in SLSim¶
Most of the functions in the image simulation take Lens class as an input. So, we need to
supply all the dc2 galaxy information in the form of Lens class. So, here we mimic Lens class only with necessary Lens class parts which are necessary for image simulation.
Before runing this notebook, please download all the data needed from the following link:
Then, please change data path to your storage path.
[1]:
import os
import numpy as np
import matplotlib.pyplot as plt
import pickle
from astropy.table import Table
from slsim.image_simulation import (
image_data_class,
lens_image,
rgb_image_from_image_list,
)
[2]:
## lens_class for validation
class Lens1(object):
def __init__(
self, kwargs_model, kwargs_lens, kwargs_source, kwargs_lens_light, kwargs_ps
):
self.kwargs_model = kwargs_model
self.kwargs_lens = kwargs_lens
self.kwargs_source = kwargs_source
self.kwargs_lens_light = kwargs_lens_light
self.kwargs_ps = kwargs_ps
def lenstronomy_kwargs(self, band=None):
self.band = band
kwargs_params = {
"kwargs_lens": self.kwargs_lens,
"kwargs_source": self.kwargs_source,
"kwargs_lens_light": self.kwargs_lens_light,
"kwargs_ps": self.kwargs_ps,
}
return self.kwargs_model, kwargs_params
class Lens2(object):
def __init__(self, kwargs_model):
self.kwargs_model = kwargs_model
def lenstronomy_kwargs(self, band=None):
return self.kwargs_model, None
Let’s get dc2 galaxy center in slsim image grid¶
[3]:
kwargs_model = {
"lens_light_model_list": ["SERSIC_ELLIPSE", "SERSIC_ELLIPSE"],
"lens_model_list": ["EPL", "SHEAR", "CONVERGENCE"],
"source_light_model_list": ["SERSIC_ELLIPSE", "SERSIC_ELLIPSE"],
}
[4]:
kwarg_model = Lens2(kwargs_model)
[5]:
data_class = image_data_class(
kwarg_model,
band="i",
mag_zero_point=27,
delta_pix=0.2,
num_pix=35,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
)
[6]:
galaxy_center_pix_x_1 = 17.43411518
galaxy_center_pix_y_1 = 16.92526535
galaxy_center_pix_x_2 = 16.84335831
galaxy_center_pix_y_2 = 16.52869664
center_cood_x_1, center_coord_y_1 = data_class.map_pix2coord(
galaxy_center_pix_x_1, galaxy_center_pix_y_1
)
center_cood_x_2, center_coord_y_2 = data_class.map_pix2coord(
galaxy_center_pix_x_2, galaxy_center_pix_y_2
)
Load dc2 galaxies¶
[7]:
dp0_data_path = os.path.abspath("/Users/sanchez/Devel/DESC/data_public")
[8]:
with open(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/galaxy_sample_dc2_new_all_angle.txt",
),
"rb",
) as file:
# Use pickle.load() to load the data from the file
dc2_galaxies = pickle.load(file)
[9]:
dc2_galaxies = Table(dc2_galaxies)
[10]:
dc2_galaxies[2]["ra"], dc2_galaxies[2]["dec"]
[10]:
(61.99284796403353, -36.9900209621661)
SLSim coordinate system¶
SLsim follows the same coordinate convention as DP0. The ra aligned with the East towards left and
North twords up. The position angle goes from North to East.
[11]:
# The slsim coordinate system and dp0 coordinate system are the same.
rotation_angle_1 = np.pi * (dc2_galaxies[2]["position_angle_true_dc2"]) / 180
rotation_angle_2 = np.pi * (dc2_galaxies[7]["position_angle_true_dc2"]) / 180
[12]:
## axis ratios of disk dominated galaxy
q_disk_1 = dc2_galaxies[2]["size_minor_disk_true"] / dc2_galaxies[2]["size_disk_true"]
q_bulge_1 = (
dc2_galaxies[2]["size_minor_bulge_true"] / dc2_galaxies[2]["size_bulge_true"]
)
q_1 = dc2_galaxies[2]["size_minor_true"] / dc2_galaxies[2]["size_true"]
## axis ratios of bulge dominated galaxy
q_disk_2 = dc2_galaxies[7]["size_minor_disk_true"] / dc2_galaxies[7]["size_disk_true"]
q_bulge_2 = (
dc2_galaxies[7]["size_minor_bulge_true"] / dc2_galaxies[7]["size_bulge_true"]
)
q_2 = dc2_galaxies[7]["size_minor_true"] / dc2_galaxies[7]["size_true"]
[13]:
## Disk dominated galaxy
epsilon_disk_1 = (1 - q_disk_1) / (1 + q_disk_1)
epsilon_bulge_1 = (1 - q_bulge_1) / (1 + q_bulge_1)
epsilon_1 = (1 - q_1) / (1 + q_1)
## Bulge dominated galaxy
epsilon_disk_2 = (1 - q_disk_2) / (1 + q_disk_2)
epsilon_bulge_2 = (1 - q_bulge_2) / (1 + q_bulge_2)
epsilon_2 = (1 - q_2) / (1 + q_2)
[14]:
## disk dominated
e1_disk_1 = epsilon_disk_1 * np.cos(2 * rotation_angle_1)
e2_disk_1 = epsilon_disk_1 * np.sin(2 * rotation_angle_1)
e1_bulge_1 = epsilon_bulge_1 * np.cos(2 * rotation_angle_1)
e2_bulge_1 = epsilon_bulge_1 * np.sin(2 * rotation_angle_1)
e1_1 = epsilon_1 * np.cos(2 * rotation_angle_1)
e2_1 = epsilon_1 * np.sin(2 * rotation_angle_1)
## Bulge dominated
e1_disk_2 = epsilon_disk_2 * np.cos(2 * rotation_angle_2)
e2_disk_2 = epsilon_disk_2 * np.sin(2 * rotation_angle_2)
e1_bulge_2 = epsilon_bulge_2 * np.cos(2 * rotation_angle_2)
e2_bulge_2 = epsilon_bulge_2 * np.sin(2 * rotation_angle_2)
e1_2 = epsilon_2 * np.cos(2 * rotation_angle_2)
e2_2 = epsilon_2 * np.sin(2 * rotation_angle_2)
[15]:
dc2_galaxies[7]["ra"], dc2_galaxies[7]["dec"]
[15]:
(62.00273461841879, -37.00827463174009)
Prepare lenstronomy kwargs from a dc2 galaxy¶
We select galaxies centered at (ra, dec) = (62.00273461841879, -37.00827463174009)
and (61.99284796403353, -36.9900209621661) degree. One can find image of this galaxy in DP0
data. We download image of this galaxy from DP0 and compare it with image of the same galaxy
silulated using slsim.
[16]:
## lenstronomy kwargs for disk dominated galaxy
kwargs_lens_1 = [
{
"theta_E": 1,
"gamma": 2,
"e1": -e1_1,
"e2": e2_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
{
"gamma1": dc2_galaxies[2]["shear_1"],
"gamma2": dc2_galaxies[2]["shear_2"],
"ra_0": 0,
"dec_0": 0,
},
{"kappa": dc2_galaxies[2]["convergence"], "ra_0": 0, "dec_0": 0},
]
kwargs_source_1 = None
flux_i_1 = 10 ** (-dc2_galaxies[2]["mag_true_i_lsst"] / 2.5)
mag_bulge_i_1 = -2.5 * np.log10(dc2_galaxies[2]["bulge_to_total_ratio_i"] * flux_i_1)
mag_disk_i_1 = -2.5 * np.log10(
(1 - dc2_galaxies[2]["bulge_to_total_ratio_i"]) * flux_i_1
)
kwargs_lens_light_i_1 = [
{
"magnitude": mag_bulge_i_1,
"R_sersic": dc2_galaxies[2]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_1,
"e2": e2_bulge_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
{
"magnitude": mag_disk_i_1,
"R_sersic": dc2_galaxies[2]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_1,
"e2": e2_disk_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
]
flux_r_1 = 10 ** (-dc2_galaxies[2]["mag_true_r_lsst"] / 2.5)
mag_bulge_r_1 = -2.5 * np.log10(dc2_galaxies[2]["bulge_to_total_ratio_i"] * flux_r_1)
mag_disk_r_1 = -2.5 * np.log10(
(1 - dc2_galaxies[2]["bulge_to_total_ratio_i"]) * flux_r_1
)
kwargs_lens_light_r_1 = [
{
"magnitude": mag_bulge_r_1,
"R_sersic": dc2_galaxies[2]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_1,
"e2": e2_bulge_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
{
"magnitude": mag_disk_r_1,
"R_sersic": dc2_galaxies[2]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_1,
"e2": e2_disk_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
]
flux_g_1 = 10 ** (-dc2_galaxies[2]["mag_true_g_lsst"] / 2.5)
mag_bulge_g_1 = -2.5 * np.log10(dc2_galaxies[2]["bulge_to_total_ratio_i"] * flux_g_1)
mag_disk_g_1 = -2.5 * np.log10(
(1 - dc2_galaxies[2]["bulge_to_total_ratio_i"]) * flux_g_1
)
kwargs_lens_light_g_1 = [
{
"magnitude": mag_bulge_g_1,
"R_sersic": dc2_galaxies[2]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_1,
"e2": e2_bulge_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
{
"magnitude": mag_disk_g_1,
"R_sersic": dc2_galaxies[2]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_1,
"e2": e2_disk_1,
"center_x": center_cood_x_1,
"center_y": center_coord_y_1,
},
]
kwargs_ps_1 = None
[17]:
## lenstronomy kwargs for bulge dominated galaxy
kwargs_lens_2 = [
{
"theta_E": 1,
"gamma": 2,
"e1": -e1_2,
"e2": e2_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
{
"gamma1": dc2_galaxies[7]["shear_1"],
"gamma2": dc2_galaxies[7]["shear_2"],
"ra_0": 0,
"dec_0": 0,
},
{"kappa": dc2_galaxies[7]["convergence"], "ra_0": 0, "dec_0": 0},
]
kwargs_source_2 = None
flux_i_2 = 10 ** (-dc2_galaxies[7]["mag_true_i_lsst"] / 2.5)
mag_bulge_i_2 = -2.5 * np.log10(dc2_galaxies[7]["bulge_to_total_ratio_i"] * flux_i_2)
mag_disk_i_2 = -2.5 * np.log10(
(1 - dc2_galaxies[7]["bulge_to_total_ratio_i"]) * flux_i_2
)
kwargs_lens_light_i_2 = [
{
"magnitude": mag_bulge_i_2,
"R_sersic": dc2_galaxies[7]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_2,
"e2": e2_bulge_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
{
"magnitude": mag_disk_i_2,
"R_sersic": dc2_galaxies[7]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_2,
"e2": e2_disk_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
]
flux_r_2 = 10 ** (-dc2_galaxies[7]["mag_true_r_lsst"] / 2.5)
mag_bulge_r_2 = -2.5 * np.log10(dc2_galaxies[7]["bulge_to_total_ratio_i"] * flux_r_2)
mag_disk_r_2 = -2.5 * np.log10(
(1 - dc2_galaxies[7]["bulge_to_total_ratio_i"]) * flux_r_2
)
kwargs_lens_light_r_2 = [
{
"magnitude": mag_bulge_r_2,
"R_sersic": dc2_galaxies[7]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_2,
"e2": e2_bulge_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
{
"magnitude": mag_disk_r_2,
"R_sersic": dc2_galaxies[7]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_2,
"e2": e2_disk_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
]
flux_g_2 = 10 ** (-dc2_galaxies[7]["mag_true_g_lsst"] / 2.5)
mag_bulge_g_2 = -2.5 * np.log10(dc2_galaxies[7]["bulge_to_total_ratio_i"] * flux_g_2)
mag_disk_g_2 = -2.5 * np.log10(
(1 - dc2_galaxies[7]["bulge_to_total_ratio_i"]) * flux_g_2
)
kwargs_lens_light_g_2 = [
{
"magnitude": mag_bulge_g_2,
"R_sersic": dc2_galaxies[7]["size_bulge_true"],
"n_sersic": 4.0,
"e1": -e1_bulge_2,
"e2": e2_bulge_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
{
"magnitude": mag_disk_g_2,
"R_sersic": dc2_galaxies[7]["size_disk_true"],
"n_sersic": 1.0,
"e1": -e1_disk_2,
"e2": e2_disk_2,
"center_x": center_cood_x_2,
"center_y": center_coord_y_2,
},
]
kwargs_ps_2 = None
Initiate Lens class for each band¶
[18]:
## disk dominated galaxy
lens_class_i_1 = Lens1(
kwargs_model, kwargs_lens_1, kwargs_source_1, kwargs_lens_light_i_1, kwargs_ps_1
)
lens_class_r_1 = Lens1(
kwargs_model, kwargs_lens_1, kwargs_source_1, kwargs_lens_light_r_1, kwargs_ps_1
)
lens_class_g_1 = Lens1(
kwargs_model, kwargs_lens_1, kwargs_source_1, kwargs_lens_light_g_1, kwargs_ps_1
)
## Bulge dominated galaxy
lens_class_i_2 = Lens1(
kwargs_model, kwargs_lens_2, kwargs_source_2, kwargs_lens_light_i_2, kwargs_ps_2
)
lens_class_r_2 = Lens1(
kwargs_model, kwargs_lens_2, kwargs_source_2, kwargs_lens_light_r_2, kwargs_ps_2
)
lens_class_g_2 = Lens1(
kwargs_model, kwargs_lens_2, kwargs_source_2, kwargs_lens_light_g_2, kwargs_ps_2
)
Load psf and variance map for a dc2 galaxy¶
[19]:
## disk dominated galaxy
psf_kernel_i_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_kernel_i.npy",
)
)
psf_kernel_r_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_kernel_r.npy",
)
)
psf_kernel_g_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_kernel_g.npy",
)
)
## Bulge dominated galaxy
psf_kernel_i_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_kernel_i.npy",
)
)
psf_kernel_r_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_kernel_r.npy",
)
)
psf_kernel_g_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_kernel_g.npy",
)
)
[20]:
## disk dominated galaxy
dc2_galaxy_variance_i_1 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_variance_i.npy",
)
)
)
dc2_galaxy_variance_g_1 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_variance_g.npy",
)
)
)
dc2_galaxy_variance_r_1 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_variance_r.npy",
)
)
)
## Bulge dominated galaxy
dc2_galaxy_variance_i_2 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_variance_i.npy",
)
)
)
dc2_galaxy_variance_g_2 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_variance_g.npy",
)
)
)
dc2_galaxy_variance_r_2 = np.sqrt(
np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_galaxy_variance_r.npy",
)
)
)
Simulate image of a dc2 galaxy using slsim¶
[21]:
## disk dominated galaxy images
dc2_galaxy_image_from_slsim_i_1 = lens_image(
lens_class_i_1,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_i_1,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_1 = lens_image(
lens_class_g_1,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_g_1,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_1 = lens_image(
lens_class_r_1,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_r_1,
with_source=False,
with_deflector=True,
)
/Users/sanchez/.virtualenvs/slsim/lib/python3.12/site-packages/lenstronomy/Data/psf.py:80: UserWarning: Input PSF model has at least one negative element, which is unphysical except for a PSF of an interferometric array.
warnings.warn(
[22]:
## disk dominated galaxy images
dc2_galaxy_image_from_slsim_i_1_test = lens_image(
lens_class_i_1,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_i_1,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_1_test = lens_image(
lens_class_g_1,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_g_1,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_1_test = lens_image(
lens_class_r_1,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_r_1,
with_source=False,
with_deflector=True,
)
[23]:
## Bulge dominated galaxy images
dc2_galaxy_image_from_slsim_i_2 = lens_image(
lens_class_i_2,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_i_2,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_2 = lens_image(
lens_class_g_2,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_g_2,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_2 = lens_image(
lens_class_r_2,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_r_2,
with_source=False,
with_deflector=True,
)
[24]:
## Bulge dominated galaxy images for noise testing
dc2_galaxy_image_from_slsim_i_2_test = lens_image(
lens_class_i_2,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_i_2,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_2_test = lens_image(
lens_class_g_2,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_g_2,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_2_test = lens_image(
lens_class_r_2,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=None,
t_obs=None,
std_gaussian_noise=dc2_galaxy_variance_r_2,
with_source=False,
with_deflector=True,
)
Load dc2 galaxy image from DP0¶
[25]:
## disk dominated galaxy
dc2_galaxy_image_from_dp0_i_1 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_i.npy"
)
)
dc2_galaxy_image_from_dp0_r_1 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_r.npy"
)
)
dc2_galaxy_image_from_dp0_g_1 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_2_g.npy"
)
)
## Bulge dominated galaxy
dc2_galaxy_image_from_dp0_i_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_i.npy"
)
)
dc2_galaxy_image_from_dp0_r_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_r.npy"
)
)
dc2_galaxy_image_from_dp0_g_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_galaxy_g.npy"
)
)
Compute the difference between two different realization of SLSim.¶
[26]:
##disk dominated galaxy
diff_i_1_test = dc2_galaxy_image_from_slsim_i_1 - dc2_galaxy_image_from_slsim_i_1_test
diff_r_1_test = dc2_galaxy_image_from_slsim_r_1 - dc2_galaxy_image_from_slsim_r_1_test
diff_g_1_test = dc2_galaxy_image_from_slsim_g_1 - dc2_galaxy_image_from_slsim_g_1_test
diff_list_1_test = [diff_i_1_test, diff_r_1_test, diff_g_1_test]
slsim_slsim_diff_rgb_1 = rgb_image_from_image_list(
image_list=diff_list_1_test, stretch=0.5
)
##Bulge dominated galaxy
diff_i_2_test = dc2_galaxy_image_from_slsim_i_2 - dc2_galaxy_image_from_slsim_i_2_test
diff_r_2_test = dc2_galaxy_image_from_slsim_r_2 - dc2_galaxy_image_from_slsim_r_2_test
diff_g_2_test = dc2_galaxy_image_from_slsim_g_2 - dc2_galaxy_image_from_slsim_g_2_test
diff_list_2_test = [diff_i_2_test, diff_r_2_test, diff_g_2_test]
slsim_slsim_diff_rgb_2 = rgb_image_from_image_list(
image_list=diff_list_2_test, stretch=0.5
)
Compute the difference between slsim and DP0¶
images of the same galaxy¶
[27]:
##disk dominated galaxy
diff_i_1 = dc2_galaxy_image_from_slsim_i_1 - dc2_galaxy_image_from_dp0_i_1
diff_r_1 = dc2_galaxy_image_from_slsim_r_1 - dc2_galaxy_image_from_dp0_r_1
diff_g_1 = dc2_galaxy_image_from_slsim_g_1 - dc2_galaxy_image_from_dp0_g_1
##Bulge dominated galaxy
diff_i_2 = dc2_galaxy_image_from_slsim_i_2 - dc2_galaxy_image_from_dp0_i_2
diff_r_2 = dc2_galaxy_image_from_slsim_r_2 - dc2_galaxy_image_from_dp0_r_2
diff_g_2 = dc2_galaxy_image_from_slsim_g_2 - dc2_galaxy_image_from_dp0_g_2
Plot images and residual in i-band¶
[28]:
##Disk dominated
# This is a comparision of an image of a galaxy from DP0 at
# (ra, dec)= (61.99284796403353, -36.9900209621661) degree. This comparision is in
# i-band.
global_min = min(
dc2_galaxy_image_from_slsim_i_1.min(),
dc2_galaxy_image_from_dp0_i_1.min(),
diff_i_1.min(),
)
global_max = max(
dc2_galaxy_image_from_slsim_i_1.max(),
dc2_galaxy_image_from_dp0_i_1.max(),
diff_i_1.max(),
)
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(
dc2_galaxy_image_from_slsim_i_1, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(
dc2_galaxy_image_from_dp0_i_1, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(diff_i_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
[28]:
(-0.5, 34.5, -0.5, 34.5)
[29]:
# This is a comparision of an image of a galaxy from DP0 at
# (ra, dec)= (62.00273461841879, -37.00827463174009) degree. This comparision is in
# i-band.
global_min = min(
dc2_galaxy_image_from_slsim_i_2.min(),
dc2_galaxy_image_from_dp0_i_2.min(),
diff_i_2.min(),
)
global_max = max(
dc2_galaxy_image_from_slsim_i_2.max(),
dc2_galaxy_image_from_dp0_i_2.max(),
diff_i_2.max(),
)
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(
dc2_galaxy_image_from_slsim_i_2, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(
dc2_galaxy_image_from_dp0_i_2, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(diff_i_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
Visualize these images in RGB color¶
[30]:
## disk dominated
slsim_image_list_1 = [
dc2_galaxy_image_from_slsim_i_1,
dc2_galaxy_image_from_slsim_r_1,
dc2_galaxy_image_from_slsim_g_1,
]
## Bulge dominated
slsim_image_list_2 = [
dc2_galaxy_image_from_slsim_i_2,
dc2_galaxy_image_from_slsim_r_2,
dc2_galaxy_image_from_slsim_g_2,
]
[31]:
## disk dominated
slsim_rgb_image_1 = rgb_image_from_image_list(
image_list=slsim_image_list_1, stretch=0.5
)
## Bulge dominated
slsim_rgb_image_2 = rgb_image_from_image_list(
image_list=slsim_image_list_2, stretch=0.5
)
[32]:
## disk dominated
dp0_image_list_1 = [
dc2_galaxy_image_from_dp0_i_1,
dc2_galaxy_image_from_dp0_r_1,
dc2_galaxy_image_from_dp0_g_1,
]
## Bulge dominated
dp0_image_list_2 = [
dc2_galaxy_image_from_dp0_i_2,
dc2_galaxy_image_from_dp0_r_2,
dc2_galaxy_image_from_dp0_g_2,
]
[33]:
## disk dominated
dp0_rgb_image_1 = rgb_image_from_image_list(image_list=dp0_image_list_1, stretch=0.5)
## Bulge dominated
dp0_rgb_image_2 = rgb_image_from_image_list(image_list=dp0_image_list_2, stretch=0.5)
[34]:
## disk dominated
diff_list_1 = [diff_i_1, diff_r_1, diff_g_1]
## Bulge dominated
diff_list_2 = [diff_i_2, diff_r_2, diff_g_2]
[35]:
## disk dominated
rgb_diff_1 = rgb_image_from_image_list(image_list=diff_list_1, stretch=0.5)
## bulge dominated
rgb_diff_2 = rgb_image_from_image_list(image_list=diff_list_2, stretch=0.5)
[36]:
## disk dominated
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (61.99284796403353, -36.9900209621661) degree.
global_min = min(slsim_rgb_image_1.min(), dp0_rgb_image_1.min(), rgb_diff_1.min())
global_max = max(slsim_rgb_image_1.max(), dp0_rgb_image_1.max(), rgb_diff_1.max())
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(slsim_rgb_image_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(dp0_rgb_image_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(rgb_diff_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
[37]:
## Bulge dominated
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (62.00273461841879, -37.00827463174009) degree.
global_min = min(slsim_rgb_image_2.min(), dp0_rgb_image_2.min(), rgb_diff_2.min())
global_max = max(slsim_rgb_image_2.max(), dp0_rgb_image_2.max(), rgb_diff_2.max())
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(slsim_rgb_image_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(dp0_rgb_image_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(rgb_diff_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
Quantitative comparision of SLSim and DP0 images.¶
[38]:
pixel_slsim_disk = slsim_rgb_image_1.flatten()
pixel_slsim_bulge = slsim_rgb_image_2.flatten()
pixel_dp0_disk = dp0_rgb_image_1.flatten()
pixel_dp0_bulge = dp0_rgb_image_2.flatten()
pixel_diff_disk = rgb_diff_1.flatten()
pixel_diff_bulge = rgb_diff_2.flatten()
[39]:
## Comparision of pixel values of a disk dominated galaxy.
plt.title("Pixel value comparison of a disk dominated galaxy")
plt.hist(pixel_slsim_disk, bins=20, histtype="step", label="SLSim pixel values")
plt.hist(pixel_dp0_disk, bins=20, ls="--", histtype="step", label="DP0 pixel values")
plt.xlabel("Pixel value")
plt.ylabel("Number (N)")
plt.legend()
[39]:
<matplotlib.legend.Legend at 0x14ab57b90>
[40]:
## Comparision of pixel values of bulge dominated galaxy.
plt.title("Pixel value comparison of a bulge dominated galaxy.")
plt.hist(
pixel_slsim_bulge,
bins=20,
histtype="step",
label="SLSim pixel values",
color="magenta",
)
plt.hist(
pixel_dp0_bulge,
ls="--",
bins=20,
histtype="step",
label="DP0 pixel values",
color="green",
)
plt.xlabel("Pixel value")
plt.ylabel("Number (N)")
plt.legend()
[40]:
<matplotlib.legend.Legend at 0x14ad7c950>
[41]:
## Histogram of pixel difference. "SLSim-DP0 diff. for a disk dominated galaxy." is a
# histogram of pixel difference between SLSim and DP0 galaxy image for a disk dominated
# galaxy. "SLSim-DP0 diff. for a bulge dominated galaxy." is a
# histogram of pixel difference between SLSim and DP0 galaxy image for a bulge dominated
# galaxy. "SLSim-SLSim diff. for a disk dominated galaxy." is a
# histogram of pixel difference between two realization of a disk dominated galaxy noise
# using SLSim. "SLSim-SLSim diff. for a bulge dominated galaxy." is a
# histogram of pixel difference between two realization of a bulge dominated galaxy
# noise using SLSim.
# plt.title("Pixel difference")
plt.hist(
pixel_diff_disk,
bins=20,
histtype="step",
label="SLSim-DP0 diff. for a disk dominated galaxy.",
)
plt.hist(
pixel_diff_bulge,
ls="--",
bins=20,
histtype="step",
label="SLSim-DP0 diff. for a bulge dominated galaxy.",
)
plt.hist(
slsim_slsim_diff_rgb_1.flatten(),
bins=20,
histtype="step",
label="SLSim-SLSim diff. for a disk dominated galaxy.",
)
plt.hist(
slsim_slsim_diff_rgb_2.flatten(),
ls="--",
bins=20,
histtype="step",
label="SLSim-SLSim diff. for a bulge dominated galaxy.",
)
plt.xlabel("Difference in pixel value")
plt.ylabel("Number (N)")
plt.legend()
[41]:
<matplotlib.legend.Legend at 0x14ae06d50>
Let’s simulate an image of a DC2 galaxy using DP0¶
cutout for background noise and exposure map for¶
poisson noise.¶
In above method, we directly used variance map to simulate DP0 background noise. Now,
we simulate an image of the same galaxy with the different approach. Here, we take a
DP0 cutout close to the galaxy image and we use this cutout as a background noise for
our simulation. We take the exposure map of the DP0 galaxy image with specified pixel
size and use this exposure map to generate poisson noise for our simulated image.
Finally, our simulated image have both background noise from DC2 data and poisson noise.
This is the approach we use in lens injection in DP0 field.
[42]:
## Disk dominated galaxy
## These are DP0 cutouts close to the dp0 galaxy which we want to simulate using slsim.
dc2_galaxy_background_i_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_background_i.npy",
)
)
dc2_galaxy_background_g_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_background_g.npy",
)
)
dc2_galaxy_background_r_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_background_r.npy",
)
)
## These are exposure map of the dp0 galaxy with in (35, 35) pixel size.
dc2_galaxy_exposure_i_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_exposure_time_i.npy",
)
)
dc2_galaxy_exposure_g_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_exposure_time_g.npy",
)
)
dc2_galaxy_exposure_r_1 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_2_exposure_time_r.npy",
)
)
[43]:
## Bulge dominated galaxy
## These are DP0 cutouts close to the dp0 galaxy which we want to simulate using slsim.
dc2_galaxy_background_i_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_background_i.npy"
)
)
dc2_galaxy_background_g_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_background_g.npy"
)
)
dc2_galaxy_background_r_2 = np.load(
os.path.join(
dp0_data_path, "dp0_images_data_for_slsim_image_validation/dc2_background_r.npy"
)
)
## These are exposure map of the dp0 galaxy with in (35, 35) pixel size.
dc2_galaxy_exposure_i_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_exposure_time_i.npy",
)
)
dc2_galaxy_exposure_g_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_exposure_time_g.npy",
)
)
dc2_galaxy_exposure_r_2 = np.load(
os.path.join(
dp0_data_path,
"dp0_images_data_for_slsim_image_validation/dc2_exposure_time_r.npy",
)
)
[44]:
## Here we simulate disk dominated galaxy image using slsim and this includes
# poisson noise.
dc2_galaxy_image_from_slsim_i_21 = lens_image(
lens_class_i_1,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_i_1,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_21 = lens_image(
lens_class_g_1,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_g_1,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_21 = lens_image(
lens_class_r_1,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_1,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_r_1,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
[45]:
## Here we simulate bulge dominated galaxy image using slsim and this includes
# poisson noise.
dc2_galaxy_image_from_slsim_i_22 = lens_image(
lens_class_i_2,
band="i",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_i_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_i_2,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_g_22 = lens_image(
lens_class_g_2,
band="g",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_g_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_g_2,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
dc2_galaxy_image_from_slsim_r_22 = lens_image(
lens_class_r_2,
band="r",
mag_zero_point=27,
num_pix=35,
psf_kernel=psf_kernel_r_2,
transform_pix2angle=np.array([[0.2, 0], [0, 0.2]]),
exposure_time=dc2_galaxy_exposure_r_2,
t_obs=None,
std_gaussian_noise=None,
with_source=False,
with_deflector=True,
)
[46]:
# Let's add dp0 background/cutouts to the simulated disk galaxy image
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1 = (
dc2_galaxy_image_from_slsim_i_21 + dc2_galaxy_background_i_1
)
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_1 = (
dc2_galaxy_image_from_slsim_g_21 + dc2_galaxy_background_g_1
)
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_1 = (
dc2_galaxy_image_from_slsim_r_21 + dc2_galaxy_background_r_1
)
[47]:
# Let's add dp0 background/cutouts to the simulated bulge galaxy image
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2 = (
dc2_galaxy_image_from_slsim_i_22 + dc2_galaxy_background_i_2
)
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_2 = (
dc2_galaxy_image_from_slsim_g_22 + dc2_galaxy_background_g_2
)
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_2 = (
dc2_galaxy_image_from_slsim_r_22 + dc2_galaxy_background_r_2
)
[48]:
##disk dominated
## compute the difference between dp0 image and slsim image in each band
diff_i_n_1 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1
- dc2_galaxy_image_from_dp0_i_1
)
diff_r_n_1 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_1
- dc2_galaxy_image_from_dp0_r_1
)
diff_g_n_1 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_1
- dc2_galaxy_image_from_dp0_g_1
)
[49]:
##bulge dominated
## compute the difference between dp0 image and slsim image in each band
diff_i_n_2 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2
- dc2_galaxy_image_from_dp0_i_2
)
diff_r_n_2 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_2
- dc2_galaxy_image_from_dp0_r_2
)
diff_g_n_2 = (
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_2
- dc2_galaxy_image_from_dp0_g_2
)
[50]:
# disk dominated
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (61.99284796403353, -36.9900209621661) degree.
global_min = min(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1.min(),
dc2_galaxy_image_from_dp0_i_1.min(),
diff_i_n_1.min(),
)
global_max = max(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1.max(),
dc2_galaxy_image_from_dp0_i_1.max(),
diff_i_n_1.max(),
)
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1,
origin="lower",
vmin=global_min,
vmax=global_max,
)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(
dc2_galaxy_image_from_dp0_i_1, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(diff_i_n_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
[51]:
# Bulge dominated
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (62.00273461841879, -37.00827463174009) degree.
global_min = min(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2.min(),
dc2_galaxy_image_from_dp0_i_2.min(),
diff_i_n_2.min(),
)
global_max = max(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2.max(),
dc2_galaxy_image_from_dp0_i_2.max(),
diff_i_n_2.max(),
)
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2,
origin="lower",
vmin=global_min,
vmax=global_max,
)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(
dc2_galaxy_image_from_dp0_i_2, origin="lower", vmin=global_min, vmax=global_max
)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(diff_i_n_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
[52]:
## Disk dominated
## Produce RGB color image for slsim
slsim_image_list_n_1 = [
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_1,
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_1,
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_1,
]
slsim_rgb_image_n_1 = rgb_image_from_image_list(
image_list=slsim_image_list_n_1, stretch=0.5
)
[53]:
## Bulge dominated
## Produce RGB color image for slsim
slsim_image_list_n_2 = [
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_i_2,
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_r_2,
dc2_galaxy_image_from_slsim_with_dp0_background_cutout_g_2,
]
slsim_rgb_image_n_2 = rgb_image_from_image_list(
image_list=slsim_image_list_n_2, stretch=0.5
)
[54]:
## Disk dominated
diff_n_list_1 = [diff_i_n_1, diff_r_n_1, diff_g_n_1]
## Bulge dominated
diff_n_list_2 = [diff_i_n_2, diff_r_n_2, diff_g_n_2]
[55]:
## Disk dominated
rgb_diff_nn_1 = rgb_image_from_image_list(image_list=diff_n_list_1, stretch=0.5)
## bulge dominated
rgb_diff_nn_2 = rgb_image_from_image_list(image_list=diff_n_list_2, stretch=0.5)
[56]:
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (61.99284796403353, -36.9900209621661) degree.
global_min = min(slsim_rgb_image_n_1.min(), dp0_rgb_image_1.min(), rgb_diff_nn_1.min())
global_max = max(slsim_rgb_image_n_1.max(), dp0_rgb_image_1.max(), rgb_diff_nn_1.max())
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(slsim_rgb_image_n_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(dp0_rgb_image_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(rgb_diff_nn_1, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
[57]:
# This is a comparision of an image of galaxy from DP0 at
# (ra, dec)= (62.00273461841879, -37.00827463174009) degree.
global_min = min(slsim_rgb_image_n_2.min(), dp0_rgb_image_2.min(), rgb_diff_nn_2.min())
global_max = max(slsim_rgb_image_n_2.max(), dp0_rgb_image_2.max(), rgb_diff_nn_2.max())
# Plotting the images
plt.figure(figsize=(12, 4))
plt.subplot(1, 3, 1)
plt.imshow(slsim_rgb_image_n_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from slsim")
plt.axis("off") # Turn off axis labels
plt.subplot(1, 3, 2)
plt.imshow(dp0_rgb_image_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Galaxy image from DP0")
plt.axis("off")
plt.subplot(1, 3, 3)
plt.imshow(rgb_diff_nn_2, origin="lower", vmin=global_min, vmax=global_max)
plt.title("Residual")
plt.axis("off")
plt.show()
