Coadd¶

class spizzle.Coadd(out_shape, n_var=0, fillval=nan, context=False)¶

Bases: object

Weighted mean of drizzled exposures on one output grid, in float64.

Parameters:

out_shapetuple of int: (ny_out, nx_out).
n_varint: Number of variance planes given with each exposure.
fillvalfloat: Value of output pixels without weight, in out_img and out_var.
contextbool: Keep drizzle’s context, one int32 plane of the output size per 32 exposures, as out_ctx.

Attributes Summary

`out_ctx`	ndarray of int32, shape (n_planes,) + out_shape: bit `k % 32` of plane `k // 32` set where exposure k lands.
`out_img`	ndarray, shape out_shape: weighted mean of the data, fillval without weight.
`out_var`	list of ndarray, shape out_shape: variance of out_img from each variance plane.
`out_wht`	ndarray, shape out_shape: sum of the weights.

Methods Summary

add(W, data[, variances, iscale])

Add one exposure.

Attributes Documentation

out_ctx¶

ndarray of int32, shape (n_planes,) + out_shape: bit k % 32 of plane k // 32 set where exposure k lands.

None unless the Coadd was made with context=True.

out_img¶: ndarray, shape out_shape: weighted mean of the data, fillval without weight.

out_var¶: list of ndarray, shape out_shape: variance of out_img from each variance plane.

Methods Documentation

add(W, data, variances=(), iscale=1.0)¶

Add one exposure.

Parameters:

WOperator or scipy.sparse array: The exposure’s operator, from drizzle_operator or build_operator, or a sparse array of shape (ny_out * nx_out, ny * nx) on the whole output grid.
datandarray, shape (ny, nx): Science data.
variancessequence of ndarray or None: One variance plane per n_var, each of shape (ny, nx); None adds nothing to that plane.
iscalefloat: Factor applied to the data, and its square to the variances.

spizzle