flystar.stitch_method2

Functions

align_starlists(starlist, ref[, transModel, order, ...])	Transforming a starlist(label.dat) into a reference frame.
weighted_mean(df, x, xe, frames_in_use)
normal_mean(df, x, frames_in_use)
stitch(all_starlists, name_initial_ref[, N_iter, ...])

Module Contents

flystar.stitch_method2.align_starlists(starlist, ref, transModel=transforms.PolyTransform, order=2, N_loop=2, dr_tol=1.0, briteN=None, weights='both')

Transforming a starlist(label.dat) into a reference frame.

Parameters:

starlist: Table

Starlist we would like to transform into the reference frame, eg:label.dat

ref: Table

Starlist that defines the reference frame.

transModel: transformation class (default: transforms.polyTransform)

Defines which transformation model to use. Both the four-parameter and polynomial transformations are supported

order: int (default=1)

Order of the polynomial transformation. Only used for polynomial transform

N_loop: int (default=2)

How many times to iterate on the transformation calculation. Ideally, each iteration adds more stars and thus a better transform, to some limit.

dr_tol: float(default=1.0)

the distance tolerance for matching two stars in align.transform_and_match

briteN: int (default=100)

the number of stars used in blind matching

weights: string (default=’both’)

if weights==’both’, we use both position error in transformed starlist and

reference starlist as uncertanty. And weights is the reciprocal of this uncertanty.

if weights==’starlist’, we only use postion error in transformed starlist. if weights==’reference’, we only use position error in reference starlist. if weights==None, we don’t use weights.

flystar.stitch_method2.weighted_mean(df, x, xe, frames_in_use)

flystar.stitch_method2.normal_mean(df, x, frames_in_use)

flystar.stitch_method2.stitch(all_starlists, name_initial_ref, N_iter=5, corr_thresh=0.8, outMaster='./master.lis')