Correction Girds

Define Sampling Points

The correction grid is generated along with a set of half-light radii and Sersic indices. The generator loops through the Sersic indices for each half-light radius in the radius list. For this documentation, we define a small set of values, with the Sersic indices of a Gaussian and de Vaucouleurs’ profile.

[2]:

import numpy as np

r_eff_list = np.array([15, 20, 25])
n_list = np.array([1, 2, 4])

Correction Grid

We do a simple API call to generate the correction grid. We provide a PSF and oversampling rule as well. Oversampling becomes important for small half-light radii since the model needs to be sampled well in the center.

Load PSF

We load an HST F105W PSF:

[3]:

from astropy.io import fits

from matplotlib import pyplot as plt

# Load PSF image (2D array)
PSF = fits.getdata('data/f105w_psf.fits.gz')

# Normalize PSF
PSF = PSF / PSF.sum()

# Note that the PSF shape is odd on all sides
print("PSF Shape = {}".format(PSF.shape))

# Plot PSF and use vmax and vmin to show difraction spikes
plt.imshow(PSF, vmin=0, vmax=5e-4)
plt.show()

PSF Shape = (51, 51)
_images/correction_grids_6_1.png

Generate Correction Grid

The generate_petrosian_sersic_correction grid follows the following steps to generate the correction grid:

  • Computes the total flux (total_flux) of an ideal Sersic profile with the sampling points using the petrofit.modeling.models.sersic_enclosed function and setting the radius to np.inf.

  • Computes the radius equal to total_flux * 0.99.

  • Makes a PSF convolved Sersic Model image and measures the photometry.

  • Measures the uncorrected Petrosian radius ().

  • Computes the correct epsilon value as corrected_epsilon = r_total_flux / r_petrosian.

  • It also saves other values, such as the uncorrected C2080 which can be used to mapto the Sersic index.

[4]:

from petrofit.correction import generate_petrosian_sersic_correction

petrosian_grid = generate_petrosian_sersic_correction(
    output_yaml_name='temp/example_correction_gid.yaml',
    psf=PSF,
    r_eff_list=r_eff_list,
    n_list=n_list,
    oversample=('x_0', 'y_0', 10, 5),
    plot=False,

)


temp/example_correction_gid.yaml

Test Grid

We test the correction grid by loading it into a PetrosianCorrection and using it estimate values.

[5]:

from petrofit.petrosian import PetrosianCorrection

pc = PetrosianCorrection('temp/example_correction_gid.yaml')

[6]:

corrected_epsilon = pc.estimate_epsilon(
    r_hl_pet=15,
    c2080pet=3,
    verbose=True
)

print(corrected_epsilon)

r_eff = 15
2.2269257045984805