make_l2¶

romanisim.image.make_l2(resultants, read_pattern, read_noise=None, gain=None, flat=None, linearity=None, darkrate=None, dq=None)¶

Simulate an image in a filter given resultants.

This routine does idealized ramp fitting on a set of resultants.

Parameters:

resultantsnp.ndarray[nresultants, nx, ny]: resultants array
read_patternlist[list] (int): list of list of indices of reads entering each resultant
read_noisenp.ndarray[nx, ny] (float): read_noise image to use. If None, use galsim.roman.read_noise.
flatnp.ndarray[nx, ny] (float): flat field to use
linearityromanisim.nonlinearity.NL object or None: non-linearity correction to use.
darkratenp.ndarray[nx, ny] (float): dark rate image to subtract from ramps (electron / s)
dqnp.ndarray[nresultants, nx, ny] (int): DQ image corresponding to resultants

Returns: