def test_raise(self):
with self.assertRaises(ValueError):
kernel = np.zeros((2, 2))
kernel_util.center_kernel(kernel, iterations=1)
with self.assertRaises(ValueError):
kernel_super = np.ones((9, 9))
kernel_util.split_kernel(kernel_super, supersampling_kernel_size=2, supersampling_factor=3)
with self.assertRaises(ValueError):
kernel_util.split_kernel(kernel_super, supersampling_kernel_size=3, supersampling_factor=0)
with self.assertRaises(ValueError):
image = np.ones((10, 10))
kernel_util.cutout_source(x_pos=3, y_pos=2, image=image, kernelsize=2)
with self.assertRaises(ValueError):
kernel_util.fwhm_kernel(kernel=np.ones((4, 4)))
with self.assertRaises(ValueError):
kernel_util.fwhm_kernel(kernel=np.ones((5, 5)))
def fwhm(self):
"""
:return: full width at half maximum of kernel (in units of pixel)
"""
if self.psf_type == 'GAUSSIAN':
return self._fwhm
else:
return kernel_util.fwhm_kernel(self.kernel_point_source) * self._pixel_size
def __init__(self, kernel, truncation=4):
"""
:param kernel: 2d kernel
:param truncation: sigma scaling of kernel truncation
"""
fwhm = kernel_util.fwhm_kernel(kernel)
self._sigma = util.fwhm2sigma(fwhm)
self._truncation = truncation
def test_fwhm_kernel():
x_grid, y_gird = Util.make_grid(101, 1)
sigma = 20
flux = gaussian.function(x_grid, y_gird, amp=1, sigma=sigma)
kernel = Util.array2image(flux)
kernel = kernel_util.kernel_norm(kernel)
fwhm_kernel = kernel_util.fwhm_kernel(kernel)
fwhm = Util.sigma2fwhm(sigma)
npt.assert_almost_equal(fwhm/fwhm_kernel, 1, 2)
def test_fwhm_kernel():
x_grid, y_gird = Util.make_grid(101, 1)
sigma = 20
from lenstronomy.LightModel.Profiles.gaussian import Gaussian
gaussian = Gaussian()
flux = gaussian.function(x_grid,
y_gird,
amp=1,
sigma_x=sigma,
sigma_y=sigma)
kernel = Util.array2image(flux)
kernel = kernel_util.kernel_norm(kernel)
fwhm_kernel = kernel_util.fwhm_kernel(kernel)
fwhm = Util.sigma2fwhm(sigma)
npt.assert_almost_equal(fwhm / fwhm_kernel, 1, 2)
def psf_fwhm(kwargs, deltaPix):
"""
:param kwargs_psf:
:return: psf fwhm in units of arcsec
"""
psf_type = kwargs.get('psf_type', 'NONE')
if psf_type == 'NONE':
fwhm = 0
elif psf_type == 'GAUSSIAN':
fwhm = kwargs['fwhm']
elif psf_type == 'PIXEL':
kernel = kwargs['kernel_point_source']
fwhm = kernel_util.fwhm_kernel(kernel) * deltaPix
else:
raise ValueError('PSF type %s not valid!' % psf_type)
return fwhm
def psf_fwhm(kwargs, deltaPix):
"""
:param kwargs: keyword arguments of the PSF() class
:param deltaPix: pixel size (in the case of subsampled PSF, this is the subsampled pixel size)
:return: psf fwhm in units of the deltaPix argument
"""
psf_type = kwargs.get('psf_type', 'NONE')
if psf_type == 'NONE':
fwhm = 0
elif psf_type == 'GAUSSIAN':
fwhm = kwargs['fwhm']
elif psf_type == 'PIXEL':
if 'kernel_point_source_subsampled' in kwargs:
kernel = kwargs['kernel_point_source_subsampled']
else:
kernel = kwargs['kernel_point_source']
fwhm = kernel_util.fwhm_kernel(kernel) * deltaPix
else:
raise ValueError('PSF type %s not valid!' % psf_type)
return fwhm
