- class darkmappy.forward_models.PlanarForwardModel(n, mask=None, ngal=None, supersample=1, sigma_e=0.37)
Weak Gravitational Lensing planar Forward model
Supports additional complexity which should simply be appended to the dir_op and adj_op objects appropriately (e.g. psf degridding step, psf deconvolution etc.)
- __init__(n, mask=None, ngal=None, supersample=1, sigma_e=0.37)
Construct class to hold the spherical forward and forward adjoint operators.
- Parameters
n (int) – Pixel count along each axis (square images)
mask (int array) – Map of realspace masking.
ngal (int array) – Map of galaxy observation count.
supersample (float) – Degree of supersampling.
sigma_e (float) – intrinsic ellipticity dispersion
- Raises
ValueError – Raised if map is of size 0.
ValueError – Raised if mask is the wrong shape.
ValueError – Raised if ngal is the wrong shape.
WarningLog – Raised if L is very large.
- adj_op(gamma)
Planar weak lensing adjoint measurement operator
- Parameters
gamma (complex array) – Shear Observations (cov weighted)
- compute_fourier_kernels()
Computes fourier space kernel mappings.
Returns as a tuple {forward, inverse}.
- cov_weight(x)
Applies covariance weighting to observations.
Assumes no intrinsic correlation between pixels.
- Parameters
x (array) – pixel space map to be inverse covariance weighted.
- dir_op(kappa)
Planar weak lensing measurement operator
- Parameters
kappa (complex array) – Convergence signal
- ks_estimate(gamma)
Computes Kaiser-Squires estimator (as a first estimate)
- Parameters
gamma (complex array) – Shear Observations (patch)
- mask_adjoint(x)
Applies given mask adjoint to observations
- Parameters
x (complex array) – Set of observations.
- Raises
ValueError – Raised if signal is nan
- mask_forward(f)
Applies given mask to a field.
- Parameters
f (complex array) – Realspace Signal
- Raises
ValueError – Raised if signal is nan
ValueError – Raised if signal is of incorrect shape.
- ngal_to_inv_cov(ngal)
Converts galaxy number density map to data covariance.
Assumes no intrinsic correlation between pixels.
- Parameters
ngal (real array) – pixel space map of observation counts per pixel.
- class darkmappy.forward_models.SphericalForwardModel(L, mask=None, ngal=None, sigma_e=0.37)
Weak Gravitational Lensing spherical Forward model
Supports additional complexity which should simply be appended to the dir_op and adj_op objects appropriately (e.g. psf degridding step, psf deconvolution etc.)
- __init__(L, mask=None, ngal=None, sigma_e=0.37)
Construct class to hold the spherical forward and forward adjoint operators.
- Parameters
L (int) – Spherical harmonic bandlimit
mask (int array) – Map of realspace masking.
ngal (int array) – Map of galaxy observation count.
sigma_e (float) – intrinsic ellipticity dispersion
- Raises
ValueError – Raised if L is not positive
ValueError – Raised if mask is the wrong shape.
WarningLog – Raised if L is very large.
- adj_op(gamma)
Spherical weak lensing adjoint measurement operator
- Parameters
gamma (complex array) – Shear Observations (cov weighted)
- compute_harmonic_kernel()
Compuptes harmonic space kernel mapping
- Returns
Harmonic space weak lensing kernel
- cov_weight(x)
Applies covariance weighting to observations.
Assumes no correlation between pixels.
- Parameters
x (array) – pixel space map to be inverse covariance weighted.
- Returns
Inverse covariance weighted observations y’ = y * sigma^-1/2
- dir_op(kappa)
Spherical weak lensing measurement operator
- Parameters
kappa (complex array) – Convergence signal
- harmonic_inverse_mapping(flm)
Applys harmonic space inverse mapping.
- Parameters
flm (complex array) – harmonic coefficients.
- Returns
Inverse mapped harmonic coefficients glm = flm / K
- harmonic_mapping(flm)
Applys harmonic space mapping.
- Parameters
flm (complex array) – harmonic coefficients.
- Returns
Mapped harmonic coefficients glm = flm * K
- mask_adjoint(x)
Applies given mask adjoint to observations
- Parameters
x (complex array) – Set of observations.
- Raises
ValueError – Raised if signal is nan
- Returns
Gridded full-sky map of observations
- mask_forward(f)
Applies given mask to a field.
- Parameters
f (complex array) – Realspace Signal
- Raises
ValueError – Raised if signal is nan
ValueError – Raised if signal is of incorrect shape.
- Returns
Array of observations only.
- ngal_to_inv_cov(ngal)
Converts galaxy number density map to data covariance.
Assumes no correlation between pixels.
- Parameters
ngal (real array) – pixel space map of number of observations per pixel
- Returns
Data covariance, assuming no correlations and Gaussian noise
- sks_estimate(gamma)
Computes spherical Kaiser-Squires estimator (as a first estimate)
- Parameters
gamma (complex array) – Shear Observations (full-sky)