Welcome to tweakwcs documentation!

tweakwcs is a package that provides core algorithms for computing and applying corrections to WCS objects such as to minimize mismatch between image and reference catalogs. Currently only aligning images with FITS WCS and JWST gWCS are supported.

Content

imalign

A module that provides functions for “aligning” images: specifically, it provides functions for computing corrections to image WCS so that image catalogs “align” to the reference catalog on the sky.

Authors

Mihai Cara

License

LICENSE

tweakwcs.imalign.align_wcs(wcscat, refcat=None, ref_tpwcs=None, enforce_user_order=True, expand_refcat=False, minobj=None, match=<tweakwcs.matchutils.TPMatch object>, fitgeom='general', nclip=3, sigma=(3.0, 'rmse'))

Align (groups of) image catalogs by adjusting the parameters of their WCS based on fits between matched sources in these catalogs and a reference catalog which may be automatically created from one of the input wcscat catalogs.

Warning

This function modifies the wcs attribute of each item in the input wcscat list!

Upon completion, this function will add a field 'fit_info' to the meta attribute of the input WCS correctors (except of the one chosen as a reference catalog when refcat is None) containing a dictionary describing matching and fit results. For a description of the items in this dictionary, see tweakwcs.wcsimage.WCSGroupCatalog.align_to_ref(). In addition to the status set by align_to_ref(), this function may set status to 'REFERENCE' for an input image used as a reference image when a reference catalog is not provided. In this case no other fields in the 'fit_info' will be present because a reference image is not being aligned. When alignment failed, the reason for failure is provided after alignment status.

Warning

Unless status in 'fit_info' is 'SUCCESS', there is no guarantee that other fields in 'fit_info' are present or valid. Therefore, it is advisable verify that status is 'SUCCESS' before attempting to access other items, for example:

>>> fit_info = wcscat[0].meta.get('fit_info')  # noqa
>>> if fit_info['status'] == 'SUCCESS':
...     print("shifts: [{}, {}]".format(*fit_info['shift']))
... else:
...     print("tweak info not available for this image")

Parameters

wcscat: tweakwcs.tpwcs.TPWCS, list of tweakwcs.tpwcs.TPWCS

A list of all TPWCS-derived WCS correctors whose meta dictionary must contain 'catalog' item with a non-empty table value of type astropy.table.Table. This catalog must contain 'x' and 'y' columns which indicate source coordinates (in pixels) in the associated image. An optional column in the catalog is the 'weight' column, which when present, will be used in fitting. See Notes section for further details. In addition to 'catalog', the following items in the meta dictionary are recognized/supported: 'name' and 'group_id'. 'name' is catalog’s name and it used to identify catalog during logging. If 'name' value is None or not present at all in the meta of a catalog, the name of that catalog will reported as 'Unknown'. Group ID that may be used for identifying catalogs that need to be aligned together. group_id must be hashable. If 'group_id' is None or not provided, each input WCS/catalog will be aligned individually.

Note

Upon completion this function will add 'fit_info' item (a dictionary) to input object’s meta dictionary. See Notes section for more details.

Warning

This function modifies the WCS of TPWCS objects by calling their set_correction() method.

refcat: astropy.table.Table, optional

A reference source catalog. The catalog must contain 'RA' and 'DEC' columns which indicate reference source world coordinates (in degrees). An optional column in the catalog is the 'weight' column, which when present, will be used in fitting. See Notes section for further details.

ref_tpwcs: TPWCS, None, optional

A reference WCS of the type TPWCS that provides the tangent plane in which matching will be performed and corrections will be defined. When not provided (i.e., set to None), reference tangent plane will be defined from the first TPWCS object in the re-ordered (if enforce_user_order was set to True) input list wcscat.

enforce_user_order: bool, optional

Specifies whether images should be aligned in the order specified in the file input parameter or align should optimize the order of alignment by intersection area of the images. Default value (True) will align images in the user specified order, except when some images cannot be aligned in which case align will optimize the image alignment order. Alignment order optimization is available only when expand_refcat is True.

expand_refcat: bool, optional

Specifies whether to add new sources from just matched images to the reference catalog to allow next image to be matched against an expanded reference catalog. By delault, the reference catalog is not being expanded.

If refcat is not None and contains an 'id' column, then sources being added to the reference catalog will be assigned consecutive IDs that continue maximum ID in the refcat.

If one desires to uniquely associate source in the expanded catalog to their original catalogs, it is recommended that one assign unique IDs to all sources in all input catalogs and in the reference catalog in a separate column such as 'uuid'.

minobj: int, None, optional

Minimum number of identified objects from each input image to use in matching objects from other images. If the default None value is used then align will automatically deternmine the minimum number of sources from the value of the fitgeom parameter.

match: MatchCatalogs, function, None, optional

A callable that takes two arguments: a reference catalog and an image catalog. Both catalogs will have columns 'TPx' and 'TPy' that represent the source coordinates in some common (to both catalogs) coordinate system.

fitgeom: {‘shift’, ‘rshift’, ‘rscale’, ‘general’}, optional

The fitting geometry to be used in fitting the matched object lists. This parameter is used in fitting the offsets, rotations and/or scale changes from the matched object lists. The ‘general’ fit geometry allows for independent scale and rotation for each axis.

nclip: int, None, optional

Number (a non-negative integer) of clipping iterations in fit. Clipping will be turned off if nclip is either None or 0.

sigma: float, tuple of the form (float, str), optional

When a tuple is provided, first value (a positive number) indicates the number of “fit error estimates” to use for clipping. The second value (a string) indicates the statistic to be used for “fit error estimate”. Currently the following values are supported: 'rmse', 'mae', and 'std' - see iter_linear_fit for more details.

When sigma is a single number, it must be a positive number and the default error estimate 'rmse' is assumed.

This parameter is ignored when nclip is either None or 0.

Returns

eff_refcat: astropy.table.Table

Effective reference catalog used for aligning all images. Depending on the values of the input parameters refcat, enforce_user_order, and expand_refcat, effective reference catalog may be one of the input image catalogs, the original refcat catalog, an expanded refcat with a combination of source positions from all input images.

Notes

1. Weights:

When fitting image sources to reference catalog sources, we can specify which sources have higher weights. This can be done by assigning a “weight” to each source by specifying these values in the optional 'weight' column of either the reference catalog, image catalog, or both.

When weights are not provided, all sources are weighed equally. When only either image or reference catalog weights are provided, the sources will be weighted with the specified weights. When both image and reference catalogs specify weights for the same sources, the two weights will be combined into a single weight as:

\[1/w = 1/w_i + 1/w_r\]

Warning

Keep in mind that when a group catalog is created from individual catalogs, weights of the group catalog are created by concatenating weights of individual catalogs. Therefore, for the weighting of groups of catalogs to work correctly, the weights of individual catalogs should be scaled in such a way that when individual catalogs are combined into a single “group catalog”, weights preserve their relative values.

For example, let’s say a group is formed from two individual catalogs. Let’s say first catalog contains four sources with equal weights [1,1,1,1] and the second catalog contains two sources with weights [1,1] then the group’s catalogs sources will also have equal weights [1,1,1,1,1,1]. However, if each individual catalog’s weights were normalized such that sum of all weights is 1, then group’s sources will be weighed unequally: [0.25,0.25,0.25,0.25,0.5,0.5].

Warning

When image catalogs contain optional 'weight' column, then all image catalogs in a group must contain this column.

2. 'fit_info':

Upon completion, this function will add 'fit_info' item (itself a dictionary) to input object’s meta dictionary. If input objects are TPWCS WCS correctors, then TPWCS.meta['fit_info'] will be set to a dictionary containing fit information.

Note

For TPWCS that are aligned in a group, the 'matrix' and 'shift' items in the 'fit_info' dictionary may differ from the values of the same items in TPWCS.meta dictionary. This is normal since WCS corrections (in TPWCS) are applied in the image’s WCS plane while fit may be performed in a slightly different tangent plane.

tweakwcs.imalign.fit_wcs(refcat, imcat, tpwcs, ref_tpwcs=None, fitgeom='general', nclip=3, sigma=(3.0, 'rmse'))

“Tweak” a single image’s WCS by fitting image catalog to a reference catalog. This is a simplified version of align_wcs that does not perform matching and is limited to the fitting part.

Note

Both reference and image catalogs must have been matched prior to calling fit_wcs(). This means that the lengths of both refcat and imcat catalogs must be equal and that coordinates with the same indices in both catalogs correspond to the same source.

Warning

If tpwcs.meta dictionary contains 'catalog' keyword, it will be ignored.

Parameters

refcat: astropy.table.Table

A reference source catalog. The catalog must contain 'RA' and 'DEC' columns which indicate reference source world coordinates (in degrees). An optional column in the catalog is the 'weight' column, which when present, will be used in fitting. See Notes section for further details.

imcat: astropy.table.Table

Source catalog associated with an image whose WCS needs to be aligned by fitting a linear transformation to imcat source positions so as to align them to the same sources from the refcat catalog. Must contain 'x' and 'y' columns which indicate source coordinates (in pixels) in the associated image. An optional column in the catalog is the 'weight' column, which when present, will be used in fitting. See Notes section for further details.

tpwcs: TPWCS

A WCS associated with the image from which the catalog was derived. This TPWCS-subclassed WCS corrector object must also define a tangent plane that will be used for fitting the two catalogs’ sources and in which WCS corrections will be applied.

ref_tpwcs: TPWCS, None, optional

A reference WCS of the type TPWCS that provides the tangent plane in which matching will be performed and corrections will be defined. When not provided (i.e., set to None), reference tangent plane will be the same as defined by tpwcs argument.

fitgeom: {‘shift’, ‘rshift’, ‘rscale’, ‘general’}, optional

The fitting geometry to be used in fitting the matched object lists. This parameter is used in fitting the offsets, rotations and/or scale changes from the matched object lists. The ‘general’ fit geometry allows for independent scale and rotation for each axis.

nclip: int, None, optional

Number (a non-negative integer) of clipping iterations in fit. Clipping will be turned off if nclip is either None or 0.

sigma: float, tuple of the form (float, str), optional

When a tuple is provided, first value (a positive number) indicates the number of “fit error estimates” to use for clipping. The second value (a string) indicates the statistic to be used for “fit error estimate”. Currently the following values are supported: 'rmse', 'mae', and 'std' - see iter_linear_fit for more details.

When sigma is a single number, it must be a positive number and the default error estimate 'rmse' is assumed.

This parameter is ignored when nclip is either None or 0.

Returns

twwcs: TPWCS

“Tweaked” (aligned) WCS that contains tangent-plane corrections so that reference and image catalog sources better align in the tangent plane and therefore on the sky as well.

Notes

When fitting image sources to reference catalog sources, we can specify which sources have higher weights. This can be done by assigning a “weight” to each source by specifying these values in the optional 'weight' column of either the reference catalog, image catalog, or both.

When weights are not provided, all sources are weighed equally. When only either image or reference catalog weights are provided, the sources will be weighted with the specified weights. When both image and reference catalogs specify weights for the same sources, the two weights will be combined into a single weight as:

\[1/w = 1/w_i + 1/w_r\]

Warning

Keep in mind that when a group catalog is created from individual catalogs, weights of the group catalog are created by concatenating weights of individual catalogs. Therefore, for the weighting of groups of catalogs to work correctly, the weights of individual catalogs should be scaled in such a way that when individual catalogs are combined into a single “group catalog”, weights preserve their relative values.

For example, let’s say a group is formed from two individual catalogs. Let’s say first catalog contains four sources with equal weights [1,1,1,1] and the second catalog contains two sources with weights [1,1] then the group’s catalogs sources will also have equal weights [1,1,1,1,1,1]. However, if each individual catalog’s weights were normalized such that sum of all weights is 1, then group’s sources will be weighed unequally: [0.25,0.25,0.25,0.25,0.5,0.5].

Upon successful completion, this function will set the 'fit_info' key value of the meta attribute of the returned TPWCS object. 'fit_info' is a dictionary with the following items:

• ‘shift’: A numpy.ndarray with two components of the computed shift.

• ‘matrix’: A 2x2 numpy.ndarray with the computed generalized rotation matrix.

• ‘proper_rot’: Rotation angle (degree) as if the rotation is proper.

• ‘rot’: A tuple of (rotx, roty) - the rotation angles with regard to the X and Y axes.

• ‘<rot>’: Arithmetic mean of the angles of rotation around X and Y axes.

• ‘scale’: A tuple of (sx, sy) - scale change in the direction of the X and Y axes.

• ‘<scale>’: Geometric mean of scales sx and sy.

• ‘skew’: Computed skew.

• ‘proper’: a boolean indicating whether the rotation is proper.

• ‘fitgeom’: Fit geometry (allowed transformations) used for fitting data (to minimize residuals). This is copy of the input argument fitgeom.

• ‘center’: Center of rotation in the tangent plane of the computed linear transformations.

• ‘fitmask’: A boolean array indicating which source positions where used for fitting (True) and which were clipped out (False). NOTE: For weighted fits, positions with zero weights are automatically excluded from the fits.

• ‘eff_nclip’: Effective number of clipping iterations

• ‘rmse’: fit Root-Mean-Square Error in tangent plane coordinates of corrected image source positions from reference source positions.

• ‘mae’: fit Mean Absolute Error in tangent plane coordinates of corrected image source positions from reference source positions.

• ‘std’: Norm of the standard deviation of the residuals in tangent plane along each axis.

• ‘resids’: An array of residuals of the fit in the tangent plane.

  NOTE: Only the residuals for the “valid” points are reported here. Therefore the length of this array may be smaller than the length of input arrays of positions.

• ‘fit_RA’: first (corrected) world coordinate of input source positions used in fitting.

• ‘fit_DEC’: second (corrected) world coordinate of input source positions used in fitting.

• ‘status’: Alignment status. Currently two possible status are possible 'SUCCESS' or 'FAILED: reason for failure'. When alignment failed, the reason for failure is provided after alignment status.

tpwcs

This module provides support for manipulating tangent-plane corrections of WCS.

Authors

Mihai Cara

License

LICENSE

class tweakwcs.tpwcs.FITSWCS(wcs, meta=None)

A class for holding FITS WCS information and for managing tangent-plane corrections.

Note

Currently only WCS objects that have CPDIS, DET2IM, and SIP distortions before the application of the CD or PC matrix are supported.

Parameters

wcs: astropy.wcs.WCS

An astropy.wcs.WCS object.

property bounding_box

Get the bounding box (if any) of the underlying image for which the original WCS is defined.

det_to_tanp(x, y)

Convert detector (pixel) coordinates to tangent plane coordinates.

det_to_world(x, y)

Convert pixel coordinates to sky coordinates using full (i.e., including distortions) transformations.

set_correction(matrix=[[1, 0], [0, 1]], shift=[0, 0], ref_tpwcs=None, meta=None, **kwargs)

Computes a corrected (aligned) wcs based on the provided linear transformation. In addition, this function updates the meta attribute of the FITSWCS object with the the values of keyword arguments except for the argument meta which is merged with the attribute meta.

Parameters

matrix: list, numpy.ndarray

A 2x2 array or list of lists coefficients representing scale, rotation, and/or skew transformations.

shift: list, numpy.ndarray

A list of two coordinate shifts to be applied to coordinates after matrix transformations are applied.

ref_tpwcs: TPWCS, None, optional

A reference WCS of the type TPWCS that provides the tangent plane in which corrections (matrix and shift) were defined. When not provided (i.e., set to None), it is assumed that the transformations are being applied directly to this image WCS’ tangent plane.

meta: dict, None, optional

Dictionary that will be merged to the object’s meta fields.

**kwargs: optional parameters

Optional parameters for the WCS corrector. FITSWCS ignores these arguments (except for storing them in the meta attribute).

tanp_to_det(x, y)

Convert tangent plane coordinates to detector (pixel) coordinates.

tanp_to_world(x, y)

Convert tangent plane coordinates to world coordinates.

world_to_det(ra, dec)

Convert sky coordinates to image’s pixel coordinates using full (i.e., including distortions) transformations.

world_to_tanp(ra, dec)

Convert tangent plane coordinates to detector (pixel) coordinates.

class tweakwcs.tpwcs.JWSTgWCS(wcs, wcsinfo, meta=None)

A class for holding JWST gWCS information and for managing tangent-plane corrections.

Parameters

wcs: GWCS

A GWCS object.

wcsinfo: dict

A dictionary containing reference angles of JWST instrument provided in the wcsinfo property of JWST meta data.

This dictionary must contain the following keys and values:

‘v2_ref’: float

V2 position of the reference point in arc seconds.

‘v3_ref’: float

V3 position of the reference point in arc seconds.

‘roll_ref’: float

Roll angle in degrees.

meta: dict, None, optional

Dictionary that will be merged to the object’s meta fields.

property bounding_box

Get the bounding box (if any) of the underlying image for which the original WCS is defined.

det_to_tanp(x, y)

Convert detector (pixel) coordinates to tangent plane coordinates.

det_to_world(x, y)

Convert pixel coordinates to sky coordinates using full (i.e., including distortions) transformations.

property ref_angles

Return a wcsinfo-like dictionary of main WCS parameters.

set_correction(matrix=[[1, 0], [0, 1]], shift=[0, 0], ref_tpwcs=None, meta=None, **kwargs)

Sets a tangent-plane correction of the GWCS object according to the provided liniar parameters. In addition, this function updates the meta attribute of the JWSTgWCS object with the values of keyword arguments except for the argument meta which is merged with the attribute meta.

Parameters

matrix: list, numpy.ndarray

A 2x2 array or list of lists coefficients representing scale, rotation, and/or skew transformations.

shift: list, numpy.ndarray

A list of two coordinate shifts to be applied to coordinates after matrix transformations are applied.

ref_tpwcs: TPWCS, None, optional

A reference WCS of the type TPWCS that provides the tangent plane in which corrections (matrix and shift) were defined. When not provided (i.e., set to None), it is assumed that the transformations are being applied directly to this image WCS’ tangent plane.

meta: dict, None, optional

Dictionary that will be merged to the object’s meta fields.

**kwargs: optional parameters

Optional parameters for the WCS corrector. JWSTgWCS ignores these arguments (except for storing them in the meta attribute).

tanp_to_det(x, y)

Convert tangent plane coordinates to detector (pixel) coordinates.

tanp_to_world(x, y)

Convert tangent plane coordinates to world coordinates.

world_to_det(ra, dec)

Convert sky coordinates to image’s pixel coordinates using full (i.e., including distortions) transformations.

world_to_tanp(ra, dec)

Convert tangent plane coordinates to detector (pixel) coordinates.

class tweakwcs.tpwcs.TPWCS(wcs, meta=None)

A class that provides common interface for manipulating WCS information and for managing tangent-plane corrections.

Parameters

wcs: ``WCS object``

A WCS object supported by a child class.

meta: dict, None, optional

Dictionary that will be merged to the object’s meta fields.

property bounding_box

Get the bounding box (if any) of the underlying image for which the original WCS is defined.

copy()

Returns a deep copy of this object.

abstract det_to_tanp(x, y)

Convert detector (pixel) coordinates to tangent plane coordinates.

abstract det_to_world(x, y)

Convert pixel coordinates to sky coordinates using full (i.e., including distortions) transformations.

property meta

property original_wcs

Get original WCS object.

abstract set_correction(matrix=[[1, 0], [0, 1]], shift=[0, 0], ref_tpwcs=None, meta=None, **kwargs)

Sets a tangent-plane correction of the WCS object according to the provided liniar parameters. In addition, this function updates the meta attribute of the TPWCS-derived object with the values of keyword arguments except for the argument meta which is merged with the attribute meta.

Parameters

matrix: list, numpy.ndarray, optional

A 2x2 array or list of lists coefficients representing scale, rotation, and/or skew transformations.

shift: list, numpy.ndarray, optional

A list of two coordinate shifts to be applied to coordinates after matrix transformations are applied.

ref_tpwcs: TPWCS, None, optional

A reference WCS of the type TPWCS that provides the tangent plane in which corrections (matrix and shift) were defined. When not provided (i.e., set to None), it is assumed that the transformations are being applied directly to this image WCS’ tangent plane.

meta: dict, None, optional

Dictionary that will be merged to the object’s meta fields.

**kwargs: optional parameters

Optional parameters for the WCS corrector.

property tanp_center_pixel_scale

Estimate pixel scale in the tangent plane near a location in the detector’s coordinate system corresponding to the origin of the tangent plane.

Returns

pscale: float

Pixel scale [in units used in the tangent plane coordinate system] in the tangent plane near a location in the detector’s plane corresponding to the origin of the tangent plane.

tanp_pixel_scale(x, y)

Estimate pixel scale in the tangent plane near a location in the detector’s coordinate system given by parameters x and y.

Parameters

x: int, float

X-coordinate of the pixel in the detector’s coordinate system near which pixel scale in the tangent plane needs to be estimated.

y: int, float

Y-coordinate of the pixel in the detector’s coordinate system near which pixel scale in the tangent plane needs to be estimated.

Returns

pscale: float

Pixel scale [in units used in the tangent plane coordinate system] in the tangent plane near a location specified by detector coordinates x and y.

abstract tanp_to_det(x, y)

Convert tangent plane coordinates to detector (pixel) coordinates.

abstract tanp_to_world(x, y)

Convert tangent plane coordinates to world coordinates.

property wcs

Get current WCS object.

abstract world_to_det(ra, dec)

Convert sky coordinates to image’s pixel coordinates using full (i.e., including distortions) transformations.

abstract world_to_tanp(ra, dec)

Convert tangent plane coordinates to detector (pixel) coordinates.

matchutils

A module that provides algorithms matching catalogs and for initial estimation of shifts based on 2D histograms.

License

LICENSE

class tweakwcs.matchutils.MatchCatalogs

A class that provides common interface for matching catalogs.

class tweakwcs.matchutils.TPMatch(searchrad=3.0, separation=0.5, use2dhist=True, xoffset=0.0, yoffset=0.0, tolerance=1.0)

Catalog source matching in tangent plane. Uses xyxymatch algorithm to cross-match sources between this catalog and a reference catalog.

Note

The tangent plane is a plane tangent to the celestial sphere and it must be not distorted, that is, if image coordinates are distorted, then distortion correction must be applied to them before tangent plane coordinates are computed. Alternatively, one can think that undistorted world coordinates are projected from the sphere onto the tangent plane.

Parameters

searchrad: float, optional

The search radius for a match (in units of the tangent plane).

separation: float, optional

The minimum separation in the tangent plane (in units of the tangent plane) for sources in the image and reference catalogs in order to be considered to be disctinct sources. Objects closer together than separation distance are removed from the image and reference coordinate catalogs prior to matching. This parameter gets passed directly to xyxymatch() for use in matching the object lists from each image with the reference catalog’s object list.

use2dhist: bool, optional

Use 2D histogram to find initial offset?

xoffset: float, optional

Initial estimate for the offset in X (in units of the tangent plane) between the sources in the image and the reference catalogs. This offset will be used for all input images provided. This parameter is ignored when use2dhist is True.

yoffset: float, optional

Initial estimate for the offset in Y (in units of the tangent plane) between the sources in the image and the reference catalogs. This offset will be used for all input images provided. This parameter is ignored when use2dhist is True.

tolerance: float, optional

The matching tolerance (in units of the tangent plane) after applying an initial solution derived from the ‘triangles’ algorithm. This parameter gets passed directly to xyxymatch() for use in matching the object lists from each image with the reference image’s object list.

wcsimage

This module provides support for working with image footprints on the sky and source catalogs.

Authors

Mihai Cara

License

LICENSE

class tweakwcs.wcsimage.RefCatalog(catalog, name=None, footprint_tol=1.0)

An object that holds a reference catalog and provides tools for coordinate convertions using reference WCS as well as catalog manipulation and expansion.

Parameters

catalog: astropy.table.Table

Reference catalog.

Note

Reference catalogs (Table) must contain both 'RA' and 'DEC' columns.

name: str, None, optional

Name of the reference catalog.

footprint_tol: float, optional

Matching tolerance in arcsec. This is used to estimate catalog’s footprint when catalog contains only one or two sources.

calc_bounding_polygon()

Calculate bounding polygon of the sources in the catalog.

calc_tanp_xy(tanplane_wcs)

Compute x- and y-positions of the sources from the reference catalog in the tangent plane provided by the tanplane_wcs. This creates the following columns in the catalog’s table: 'TPx' and 'TPy'.

Parameters

tanplane_wcs: TPWCS

A TPWCS object that will provide transformations to the tangent plane to which sources of this catalog a should be “projected”.

property catalog

Get/set image’s catalog.

expand_catalog(catalog)

Expand current reference catalog with sources from another catalog.

If current catalog is empty, then the catalog being added will become the new reference catalog. In this case if the catalog does have id column, those ID values will be preserved. If the catalog does not contain an ID column, then the new IDs will be assigned in increasing order starting with 1.

If the existing reference catalog is not empty, then the IDs from the catalog being added will be discarded and new IDs will be assigned in the increasing order such as to continue the numbering of existing source positions in the reference catalog.

Parameters

catalog: astropy.table.Table

A catalog of new sources to be added to the existing reference catalog. catalog must contain both 'RA' and 'DEC' columns.

intersection(wcsim)

Compute intersection of this WCSImageCatalog object and another WCSImageCatalog, WCSGroupCatalog, RefCatalog, or SphericalPolygon object.

Parameters

wcsim: WCSImageCatalog, WCSGroupCatalog, RefCatalog, SphericalPolygon

Another object that should be intersected with this WCSImageCatalog.

Returns

polygon: SphericalPolygon

A SphericalPolygon that is the intersection of this WCSImageCatalog and wcsim.

intersection_area(wcsim)

Calculate the area of the intersection polygon.

property name

Get/set RefCatalog object’s name.

property poly_area

Area of the bounding polygon (in srad).

property polygon

Get image’s (or catalog’s) bounding spherical polygon.

class tweakwcs.wcsimage.WCSGroupCatalog(images, name=None)

A class that holds together WCSImageCatalog image catalog objects whose relative positions are fixed and whose source catalogs should be fitted together to a reference catalog.

Parameters

images: list of WCSImageCatalog

A list of WCSImageCatalog image catalogs.

name: str, None, optional

Name of the group.

align_to_ref(refcat, ref_tpwcs=None, match=None, minobj=None, fitgeom='rscale', nclip=3, sigma=(3.0, 'rmse'))

Matches sources from the image catalog to the sources in the reference catalog, finds the affine transformation between matched sources, and adjusts images’ WCS according to this fit.

Upon successful return, this function will also set the following fields of the fit_info attribute of each member WCSImageCatalog object:

• ‘fitgeom’: the value of the fitgeom argument

• ‘eff_minobj’: effective value of the minobj parameter

• ‘matrix’: computed rotation matrix

• ‘shift’: shift (offset) along X- and Y-axis

• ‘rot’: A tuple of (rotx, roty) - the rotation angles with regard to the X and Y axes.

• ‘<rot>’: Arithmetic mean of the angles of rotation around X and Y axes.

• ‘proper_rot’: rotation angle as if rotation is a proper rotation.

• ‘proper’: Indicates whether the rotation is a proper rotation (boolean)

• ‘scale’: A tuple of (sx, sy) - scale change in the direction of the X and Y axes.

• ‘<scale>’: Geometric mean of scales sx and sy.

• ‘skew’: Computed skew - an angle in the range [-180, 180).

• ‘center’: Center of rotation in the tangent plane of the computed linear transformations.

• ‘fitmask’: boolean array indicating (with True) sources used for fitting

• ‘nmatches’ [when match is not None]: number of matched sources

• ‘matched_ref_idx’ [when match is not None]: indices of the matched sources in the reference catalog

• ‘matched_input_idx’ [when match is not None]: indices of the matched sources in the “input” catalog (the catalog from image to be aligned)

• ‘fit_ref_idx’: indices of the sources from the reference catalog used for fitting (a subset of ‘matched_ref_idx’ indices, when match is not None, left after clipping iterations performed during fitting)

• ‘fit_input_idx’: indices of the sources from the “input” (image) catalog used for fitting (a subset of ‘matched_input_idx’ indices, when match is not None, left after clipping iterations performed during fitting)

• ‘rmse’: fit Root-Mean-Square Error in tangent plane coordinates of corrected image source positions from reference source positions.

• ‘mae’: fit Mean Absolute Error in tangent plane coordinates of corrected image source positions from reference source positions.

• ‘std’: Norm of the STandard Deviation of the residuals in tangent plane along each axis.

• ‘fit_RA’: first (corrected) world coordinate of input source positions used in fitting.

• ‘fit_DEC’: second (corrected) world coordinate of input source positions used in fitting.

• ‘status’: Alignment status. Currently two possible status are possible 'SUCCESS' or 'FAILED: reason for failure'. When alignment failed, the reason for failure is provided after alignment status.

Note

A 'SUCCESS' status does not indicate a “good” alignment. It simply indicates that alignment algortithm has completed without errors. Use other fields to evaluate alignment: fit RMSE and MAE values, number of matched sources, etc.

Parameters

refcat: RefCatalog

A RefCatalog object that contains a catalog of reference sources.

ref_tpwcsTPWCS

A TPWCS object that defines a projection tangent plane to be used for matching and fitting during alignment.

match: MatchCatalogs, function, None, optional

A callable that takes two arguments: a reference catalog and an image catalog.

minobj: int, None, optional

Minimum number of identified objects from each input image to use in matching objects from other images. If the default None value is used then align will automatically deternmine the minimum number of sources from the value of the fitgeom parameter. This parameter is used to interrupt alignment process (catalog fitting, WCS “tweaking”) when the number of matched sources is smaller than the value of minobj in which case this method will return False.

fitgeom: {‘shift’, ‘rscale’, ‘general’}, optional

The fitting geometry to be used in fitting the matched object lists. This parameter is used in fitting the offsets, rotations and/or scale changes from the matched object lists. The ‘general’ fit geometry allows for independent scale and rotation for each axis. This parameter is ignored if match is False.

nclip: int, None, optional

Number (a non-negative integer) of clipping iterations in fit. Clipping will be turned off if nclip is either None or 0.

This parameter is ignored if match is False.

sigma: float, tuple of the form (float, str), optional

When a tuple is provided, first value (a positive number) indicates the number of “fit error estimates” to use for clipping. The second value (a string) indicates the statistic to be used for “fit error estimate”. Currently the following values are supported: 'rmse', 'mae', and 'std' - see iter_linear_fit for more details.

When sigma is a single number, it must be a positive number and the default error estimate 'rmse' is assumed.

This parameter is ignored when nclip is either None or 0 or when match is False.

Returns

bool

Returns True if the number of matched sources is larger or equal to minobj and all steps have been performed, including catalog fitting and WCS “tweaking”. If the number of matched sources is smaller than minobj, this function will return False.

apply_affine_to_wcs(ref_tpwcs, matrix, shift, meta=None)

Applies a general affine transformation to the WCS.

calc_tanp_xy(tanplane_wcs)

Compute x- and y-positions of the sources from the image catalog in the tangent plane. This creates the following columns in the catalog’s table: 'TPx' and 'TPy'.

Parameters

tanplane_wcs: TPWCS

A TPWCS object that will provide transformations to the tangent plane to which sources of this catalog a should be “projected”.

property catalog

Get/set image’s catalog.

create_group_catalog()

Combine member’s image catalogs into a single group’s catalog.

Returns

group_catalog: astropy.table.Table

Combined group catalog.

fit2ref(refcat, tanplane_wcs, fitgeom='general', nclip=3, sigma=(3.0, 'rmse'))

Perform linear fit of this group’s combined catalog to the reference catalog. When either/both group’s catalog or/and the reference catalog contain 'weight' column, weigted fitting will be performed. See Notes section for further details.

Parameters

refcat: RefCatalog

A RefCatalog object that contains a catalog of reference sources.

tanplane_wcs: TPWCS

A TPWCS object that will provide transformations to the tangent plane to which sources of this catalog a should be “projected”.

fitgeom: {‘shift’, ‘rscale’, ‘general’}, optional

The fitting geometry to be used in fitting the matched object lists. This parameter is used in fitting the offsets, rotations and/or scale changes from the matched object lists. The ‘general’ fit geometry allows for independent scale and rotation for each axis.

nclip: int, None, optional

Number (a non-negative integer) of clipping iterations in fit. Clipping will be turned off if nclip is either None or 0.

sigma: float, tuple of the form (float, str), optional

When a tuple is provided, first value (a positive number) indicates the number of “fit error estimates” to use for clipping. The second value (a string) indicates the statistic to be used for “fit error estimate”. Currently the following values are supported: 'rmse', 'mae', and 'std' - see iter_linear_fit for more details.

When sigma is a single number, it must be a positive number and the default error estimate 'rmse' is assumed.

This parameter is ignored when nclip is either None or 0.

Notes

When fitting image sources to reference catalog sources, we can specify which sources have higher weights. This can be done by assigning a “weight” to each source by specifying these values in the optional 'weight' column of either the reference catalog, image catalog, or both.

When weights are not provided, all sources are weighed equally. When only one of image or reference catalog weights are provided, the sources will be weighted with the specified weights. When both image and reference catalogs specify weights for the same sources, the two weights will be combined into a single weight as:

\[1/w = 1/w_i + 1/w_r\]

Warning

Keep in mind that when a group catalog is created from individual catalogs, weights of the group catalog are created by concatenating weights of individual catalogs. Therefore, for the weighting of groups of catalogs to work correctly, the weights of individual catalogs should be scaled in such a way that when individual catalogs are combined into a single “group catalog”, weights preserve their relative values.

For example, let’s say a group is formed from two individual catalogs. Let’s say first catalog contains four sources with equal weights [1,1,1,1] and the second catalog contains two sources with weights [1,1] then the group’s catalogs sources will also have equal weights [1,1,1,1,1,1]. However, if each individual catalog’s weights were normalized such that sum of all weights is 1, then group’s sources will be weighed unequally: [0.25,0.25,0.25,0.25,0.5,0.5].

get_matched_cat()

Retrieve only those sources from the catalog that have been matched to the sources in the reference catalog.

get_unmatched_cat()

Retrieve only those sources from the catalog that have not been matched to the sources in the reference catalog.

intersection(wcsim)

Compute intersection of this WCSGroupCatalog object and another WCSImageCatalog, WCSGroupCatalog, or SphericalPolygon object.

Parameters

wcsim: WCSImageCatalog, WCSGroupCatalog, SphericalPolygon

Another object that should be intersected with this WCSGroupCatalog.

Returns

polygon: SphericalPolygon

A SphericalPolygon that is the intersection of this WCSGroupCatalog and wcsim.

intersection_area(wcsim)

Calculate the area of the intersection polygon.

match2ref(refcat, match=None)

Uses xyxymatch to cross-match sources between this catalog and

a reference catalog.

Parameters

refcat: RefCatalog

A RefCatalog object that contains a catalog of reference sources as well as a valid reference WCS.

match: MatchCatalogs, function, None, optional

A callable that takes two arguments: a reference catalog and an image catalog. Both catalogs will have columns 'TPx' and 'TPy' that represent the source coordinates in some common (to both catalogs) coordinate system.

property name

Get/set WCSImageCatalog object’s name.

property polygon

Get image’s (or catalog’s) bounding spherical polygon.

recalc_catalog_radec()

Recalculate RA and DEC of the sources in the catalog.

update_bounding_polygon()

Recompute bounding polygons of the member images.

class tweakwcs.wcsimage.WCSImageCatalog(catalog, tpwcs, name=None, group_id=None, meta={})

A class that holds information pertinent to an image WCS and a source catalog of the sources found in that image.

Warning

If tpwcs.meta dictionary contains any of the following keywords 'catalog', 'name', or 'group_id', they will be ignored without warning.

Parameters

catalog: astropy.table.Table

Source catalog associated with an image. Must contain 'x' and 'y' columns which indicate source coordinates (in pixels) in the associated image.

tpwcs: TPWCS

TPWCS-derived tangent-plane WCS corrector object associated with the image from which the catalog was derived.

name: str, None, optional

Image catalog’s name. This is used to identify catalog during logging. If name is None, the name of this WCSImageCatalog object will be set to 'Unknown'.

group_id: hashable, None, optional

Group ID that may be used for identifying catalogs that need to be aligned together. group_id must be hashable.

meta: dict, optional

Additional information about image, catalog, and/or WCS to be stored (for convenience) within WCSImageCatalog object.

property bb_radec

Get a 2xN numpy.ndarray of RA and DEC of the vertices of the bounding polygon.

calc_bounding_polygon()

Calculate bounding polygon of the image or of the sources in the catalog (if catalog was set).

property catalog

Get/set image’s catalog.

det_to_tanp(x, y)

Convert detector (pixel) coordinates to tangent plane coordinates.

det_to_world(x, y)

Convert pixel coordinates to sky coordinates using full (i.e., including distortions) transformations.

property fit_info

Get fit information - a dictionary. This class sets only the 'status' field but fitting routines may set additional fields.

property fit_status

Get/Set fit status. This property is a shortcut to the 'status' key value in the fit_info dictionary. When the WCSImageCatalog object is created, fit_status is initially set to 'SKIPPED'. Alignment tools are reponsible for updating catalog’s fit status.

property group_id

Get/set WCSImageCatalog object’s group ID that may be used for identifying catalogs that need to be aligned together. group_id must be hashable.

intersection(wcsim)

Compute intersection of this WCSImageCatalog object and another WCSImageCatalog, WCSGroupCatalog, or SphericalPolygon object.

Parameters

wcsim: WCSImageCatalog, WCSGroupCatalog, SphericalPolygon

Another object that should be intersected with this WCSImageCatalog.

Returns

polygon: SphericalPolygon

A SphericalPolygon that is the intersection of this WCSImageCatalog and wcsim.

intersection_area(wcsim)

Calculate the area of the intersection polygon.

property name

Get/set catalog’s name. This is used to identify catalog during logging. Upon setting, the value will be converted to a str. When setting to None, the name will be set to 'Unknown'.

property polygon

Get image’s (or catalog’s) bounding spherical polygon.

tanp_to_det(x, y)

Convert tangent plane coordinates to detector (pixel) coordinates.

tanp_to_world(x, y)

Convert tangent plane coordinates to world coordinates.

property tpwcs

Get TPWCS WCS.

world_to_det(ra, dec)

Convert sky coordinates to image’s pixel coordinates using full (i.e., including distortions) transformations.

world_to_tanp(ra, dec)

Convert tangent plane coordinates to detector (pixel) coordinates.

tweakwcs.wcsimage.convex_hull(x, y, wcs=None, min_separation=None)

Computes the convex hull of a set of 2D points.

Implements Andrew’s monotone chain algorithm. The algorithm has O(n log n) complexity.

Credit: http://en.wikibooks.org/wiki/Algorithm_Implementation/Geometry/Convex_hull/Monotone_chain

Parameters

x: list, tuple, numpy.ndarray

An iterable sequence of x-coordinates of points.

y: list, tuple, numpy.ndarray

An iterable sequence of y-coordinates of points.

wcsfunction

A function that takes two arguments (x, y) and converts them to “world” coordinates. If provided, returned convex hull vertex coordnates will be in “world” coordinates.

min_separationNone, float

A non-negative number or None. When provided as a number, it specifies the minimum separation in both x and y coordinates between adjacent verices in the hull. Vertices too close to their neighbors will be removed. This operation is performed _before_ convertion to “world” coordinates. When min_separation is None, all vertices are kept.

Returns

Output: list

A list of vertices of the convex hull in counter-clockwise order, starting from the vertex with the lexicographically smallest coordinates. When a coordinate conversion function is supplied via the wcs argument, the returned values are those of the converted vertex coordinates.

linearfit

A module that provides algorithms for performing linear fit between sets of 2D points.

Authors

Mihai Cara, Warren Hack

License

LICENSE

tweakwcs.linearfit.build_fit_matrix(rot, scale=1)

Create an affine transformation matrix (2x2) from the provided rotation angle(s) and scale(s):

\[\begin{split}M = \begin{bmatrix} s_x \cos(\theta_x) & s_y \sin(\theta_y) \\ -s_x \sin(\theta_x) & s_y \cos(\theta_y) \end{bmatrix}\end{split}\]

Parameters

rot: tuple, float, optional

Rotation angle in degrees. Two values (one for each axis) can be provided as a tuple.

scale: tuple, float, optional

Scale of the liniar transformation. Two values (one for each axis) can be provided as a tuple.

Returns

matrix: numpy.ndarray

A 2x2 numpy.ndarray containing coefficients of a liniear transformation.

tweakwcs.linearfit.iter_linear_fit(xy, uv, wxy=None, wuv=None, fitgeom='general', center=None, nclip=3, sigma=(3.0, 'rmse'), clip_accum=False)

Compute linear transformation parameters that “best” (in the sense of minimizing residuals) transform uv source position to xy sources iteratively using sigma-clipping.

More precisely, this functions attempts to find a 2x2 matrix F and a shift vector s that minimize the residuals between the transformed reference source coordinates uv

(1)\[\mathbf{xy}'_k = \mathbf{F}\cdot(\mathbf{uv}_k-\mathbf{c})+\ \mathbf{s} + \mathbf{c}\]

and the “observed” source positions xy:

(2)\[\epsilon^2 = \Sigma_k w_k \|\mathbf{xy}_k-\mathbf{xy}'_k\|^2.\]

In the above equations, \(\mathbf{F}\) is a 2x2 matrix while \(\mathbf{xy}_k\) and \(\mathbf{uv}_k\) are the position coordinates of the k-th source (row in input xy and uv arrays).

One of the two catalogs (xy or uv) contains what we refer to as “image” source positions and the other one as “reference” source positions. The meaning assigned to xy and uv parameters are up to the caller of this function.

Parameters

xy: numpy.ndarray

A (N, 2)-shaped array of source positions (one 2-coordinate position per line).

uv: numpy.ndarray

A (N, 2)-shaped array of source positions (one 2-coordinate position per line). This array must have the same length (shape) as the xy array.

wxy: numpy.ndarray, None, optional

A 1-dimensional array of weights of the same length (N) as xy array indicating how much a given coordinate should be weighted in the fit. If not provided or set to None, all positions will be contribute equally to the fit if wuv is also set to None. See Notes section for more details.

wuv: numpy.ndarray, None, optional

A 1-dimensional array of weights of the same length (N) as xy array indicating how much a given coordinate should be weighted in the fit. If not provided or set to None, all positions will be contribute equally to the fit if wxy is also set to None. See Notes section for more details.

fitgeom: {‘shift’, ‘rshift’, ‘rscale’, ‘general’}, optional

The fitting geometry to be used in fitting the matched object lists. This parameter is used in fitting the shifts (offsets), rotations and/or scale changes from the matched object lists. The ‘general’ fit geometry allows for independent scale and rotation for each axis.

center: tuple, list, numpy.ndarray, None, optional

A list-like container with two X- and Y-positions of the center (origin) of rotations in the uv and xy coordinate frames. If not provided, center is estimated as a (weighted) mean position in the uv frame.

nclip: int, None, optional

Number (a non-negative integer) of clipping iterations in fit. Clipping will be turned off if nclip is either None or 0.

sigma: float, tuple of the form (float, str), optional

When a tuple is provided, first value (a positive number) indicates the number of “fit error estimates” to use for clipping. The second value (a string) indicates the statistic to be used for “fit error estimate”. Currently the following values are supported: 'rmse', 'mae', and 'std' - see Notes section for more details.

When sigma is a single number, it must be a positive number and the default error estimate 'rmse' is assumed.

This parameter is ignored when nclip is either None or 0.

clip_accum: bool, optional

Indicates whether or not to reset the list of “bad” (clipped out) sources after each clipping iteration. When set to True the list only grows with each iteration as “bad” positions never re-enter the pool of available position for the fit. By default the list of “bad” source positions is purged at each iteration.

Returns

fit: dict

• 'shift': A numpy.ndarray with two components of the computed shift.

• 'shift_ld': A numpy.ndarray with two components of the computed shift of type numpy.longdouble.

• 'matrix': A 2x2 numpy.ndarray with the computed generalized rotation matrix.

• 'matrix_ld': A 2x2 numpy.ndarray with the computed generalized rotation matrix of type numpy.longdouble.

• 'proper_rot': Rotation angle (degree) as if the rotation is proper.

• 'rot': A tuple of (rotx, roty) - the rotation angles with regard to the X and Y axes.

• '<rot>': Arithmetic mean of the angles of rotation around X and Y axes.

• 'scale': A tuple of (sx, sy) - scale change in the direction of the X and Y axes.

• '<scale>': Geometric mean of scales sx and sy.

• 'skew': Computed skew.

• 'proper': a boolean indicating whether the rotation is proper.

• 'fitgeom': Fit geometry (allowed transformations) used for fitting data (to minimize residuals). This is copy of the input argument fitgeom.

• 'center': Center of rotation

• 'center_ld': Center of rotation as a numpy.longdouble.

• 'fitmask': A boolean array indicating which source positions where used for fitting (True) and which were clipped out (False). NOTE For weighted fits, positions with zero weights are automatically excluded from the fits.

• 'eff_nclip': Effective number of clipping iterations

• 'rmse': Root-Mean-Square Error

• 'mae': Mean Absolute Error

• 'std': Standard Deviation of the residuals

• 'resids': An array of residuals of the fit. NOTE: Only the residuals for the “valid” points are reported here. Therefore the length of this array may be smaller than the length of input arrays of positions.

Notes

Weights

Weights can be provided for both “image” source positions and “reference” source positions. When no weights are given, all positions are weighted equally. When only one set of positions have weights (i.e., either wxy or wuv is not None) then weights in (2) are set to be equal to the provided set of weights. When weights for both “image” source positions and “reference” source positions are provided, then the combined weight that is used in (2) is computed as:

\[1/w = 1/w_{xy} + 1/w_{uv}.\]

Statistics for clipping

Several statistics are available for clipping iterations and all of them are reported in the returned fit dictionary regardless of the setting in sigma:

\[\mathrm{RMSE} = \sqrt{\Sigma_k w_k \|\mathbf{r}_k\|^2}\]

\[\mathrm{MAE} = \sqrt{\Sigma_k w_k \|\mathbf{r}_k\|}\]

\[\mathrm{STD} = \sqrt{\Sigma_k w_k \|\mathbf{r}_k - \ \mathbf{\overline{r}}\|^2}/(1-V_2)\]

where \(\mathbf{r}_k=\mathbf{xy}_k-\mathbf{xy}'_k\), \(\Sigma_k w_k = 1\), and \(V_2=\Sigma_k w_k^2\).

wcsutils

A module that provides utility functions for WCS transformations.

Authors

Mihai Cara (contact: help@stsci.edu)

License

LICENSE

tweakwcs.wcsutils.planar_rot_3d(angle, axis)

Create a 3D rotation matrix that performs a rotation in a plane perpendicular to the specified axis.

linalg

This module provides general purpose and/or specialized linear algebra routines.

Authors

Mihai Cara (contact: help@stsci.edu)

License

LICENSE

tweakwcs.linalg.inv(m)

This function computes inverse matrix using Gauss-Jordan elimination with full pivoting. Computations are performed using numpy.longdouble precision. On systems on which numpy.longdouble is equivalent to numpy.double this function reverts to numpy.linalg.inv for performance reasons.

Parameters

m: numpy.ndarray

A 2D square matrix of type numpy.ndarray.

Returns

invm: numpy.ndarray

Inverse matrix of the input matrix m: a 2D square numpy.ndarray of type numpy.longdouble on systems on which it is more accurate than numpy.double.

LICENSE

Copyright (C) 2018, Association of Universities for Research in Astronomy

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Development Notes

Release Notes

0.7.4 (13-April-2022)

This is almost exclusively a maintenance release except for close vertices in the convex hull issue to make the code more robust.

• Set gwcs min version to 0.14. [#158]

• Set astropy min version to 5.0.4. [#153]

• Remove consecutive convex hull vertices that are very close to each other. [#147]

0.7.3 (12-August-2021)

• Fix a bug due to which minobj parameter to WCSGroupCatalog.align_to_ref() and align_wcs() was ignored. [#144]

• Make peak finding code switch to center-of-mass algorithm when estimated 2D parabolic fit estimates a peak outside of the fit box. Reduce accuracy loss in computation. [#143]

0.7.2 (13-May-2021)

• Make code more robust to exceptions in the spherical_geometry package. [#138]

• Fixed a bug in matchutils._find_peak() due to which it could return coordinates of the peak that were outside of the image. [#136]

• Fixed a bug in how re-projection was computed when center of the transformations was provided. [#135]

0.7.1 (16-February-2021)

• Added support for detecting and using velocity aberration corrected V2-V3 frames when available in JWST WCS ('v2v3vacorr'). [#130]

0.7.0 (11-November-2020)

• Added linearfit.fit_rshift function to support a new fitgeom fitting mode 'rshift' that fits only for shifts and a rotation. [#128]

0.6.5 (09-September-2020)

• Added ref_tpwcs parameter to imalign.fit_wcs(), imalign.align_wcs(), wcsimage.WCSGroupCatalog.align_to_ref() to allow alignment to be performed in user-specified distortion-free tangent plane. [#125]

• Renamed tanplane_wcs parameter in wcsimage.WCSGroupCatalog.apply_affine_to_wcs() to ref_tpwcs. tanplane_wcs parameter was deprecated and will be removed in a future release. [#125]

0.6.4 (14-May-2020)

• Bug fix: Unable to initialize JWSTgWCS tangent-plane corrector from an already corrected WCS. [#122]

• Fix a bug in how corrections are applied to a previously corrected JWST WCS. [#120]

• Do not attempt to extract center of linear transformation when not available in 'fit_info'. [#119]

0.6.3 (14-April-2020)

• Fixed a bug due to which reprojection transformation for JWST gWCS was computed at wrong location in the tangent plane. [#118]

0.6.2 (07-April-2020)

• When WCS has valid bounding box, estimate scale at the center of the bounding box. [#117]

• Adjust the point at which tangent plane-to-tangent plane transformation is computed by 1/2 pixels for JWST corrections. This correction should have no measurable impact on computed corrections. [#115]

0.6.1 (09-March-2020)

• Fixed a bug in applying JWST correction for the case when alignment is performed twice on the same image. Due to this bug the inverse transformation was not updated. [#112]

0.6.0 (25-February-2020)

• Fix a possible crash when aligning FITS WCS images due to an unusual way stwcs.wcsutil.all_world2pix handles (or not) scalar arguments. [#110]

• Modified the angle at which the reported rotation angles are reported. Now rotation angles have the range [-180, 180] degrees. [#109]

• Added support FITS WCS that use PC matrix instead of the CD matrix used in HSTs WCS. [#108]

• Bug fix for alignment of multi-chip FITS images: correction of how transformations from the reference tangent plane are converted to individual images’ tangent planes. [#106]

• Significant re-organization of the fit_info dictionary. rot now becomes proper_rot and rotxy now becomes rot containing only rotx and roty. Also, scale now is a tuple of only two scales sx and sy. The geometric mean scale is now a separate field '<scale>' as well as the arithmetic mean of rotation angles ('<rot>'). Finally, 'offset' in the fit functions from the linearfit module was renamed to 'shift' in order to match the same field returned by functions from the imalign module. [#105]

• Linear fit functions now return the fit matrix F instead of its transpose. [#100]

• Linear fit functions (in the linearfit module) use longdouble for internal computations. [#100]

• Re-designed the JWSTgWCS corrector class to rely exclusively on basic models available in astropy and gwcs instead of the TPCorr class provided by the jwst pipeline. This eliminates the need to install the jwst pipeline in order to align JWST images. [#96, #98]

0.5.3 (15-November-2019)

• Added logic to allow some input catalogs to be empty and to allow the alignment to proceed as long as there are at least two non-empty (image or group) input catalogs. [#94]

0.5.2 (26-July-2019)

• Fixed a deprecation issue in logging and added logic to compute image group’s catalog name using a common prefix (if exists) of the names of constituent images. [#92]

• Package version is now handled by setuptools_scm. [#93]

0.5.1 (08-May-2019)

• Fixed a bug in the “2dhist” algorithm resulting in a crash when 2D histogram has multiple maxima of the same value and no other value larger than one. [#90]

0.5.0 (22-April-2019)

• Fixed a bug due to which a warning log message “Failed to align catalog…” would be issued for successful alignments. [#84]

• Fixed a bug in creation of WCS image groups with empty catalogs. [#84]

• Fixed a bug in match2ref when it was run in a non-matching mode (match=None) dute to which it was impossible to detect the case when reference catalog has a different length from a supposedly matched WCS group catalog. [#84]

• Fixed a bug in computation of the bounding polygon of a reference catalog containing only two sources. [#84]

• Fixed a bug in convex_hull() resulting in incorrect type being returned in case of empty input coordinate lists or whne only one point is provided. [#84]

• Implemented a more robust estimate of the maximum type supported by numpy.linalg.inv. [#82]

• Renamed wcsutils.planar_rot_3D to wcsutils.planar_rot_3d. [#75]

• Renamed wcsutils.cartesian2spherical to wcsutils.cartesian_to_spherical and wcsutils.spherical2cartesian to wcsutils.spherical_to_cartesian. [#71]

• Improved “2dhist” algorithm that performs simple catalog pre-alignment used for source matching. [#69]

• Changed the default value of the searchrad parameter in matchutils.TPMatch to 3. [#69]

0.4.5 (14-March-2019)

• Fixed incorrect pointer type introduced in previous release [#67].

0.4.4 (13-March-2019)

• Fixed VS2017 compiler error, "void *": unknown size. [#62, #63, #64]

0.4.3 (13-March-2019)

• Package maintenance release.

0.4.2 (21-February-2019)

• Fixed a bug due to which the fitting code would crash is wuv were provided but wxy were set to None. [#60]

0.4.1 (14-February-2019)

• Code cleanup: removed debug print statements. [#59]

0.4.0 (08-February-2019)

• Matched indices, linear fit results and fit residuals are now set in the input “WCS catalogs” meta['fit_info'] instead of meta['tweakwcs_info']. [#57]

• Updated example notebook to reflect changes to API. [#57]

• Allow TPWCS classes to set meta during object instantiation. This allows attaching, for example, a source catalog to the tangent-plane WCS corrector object. [#57]

• align_wcs no longer supports NDData input. Instead catalogs can be provided directly in the meta attribute of TPWCS-derived WCS “correctors”. This fundamentally transfers the responsibility of instantiating the correct tangent-plane WCS to the caller. This, in turn, will allow future WCS to be supported by providing a custom TPWCS-derived corrector defined externally to tweakwcs package. Second benefit is that image data no longer need to be kept in memory in NDData objects as image data are not needed for image alignment once catalogs have been created. [#57]

• Renamed tweak_wcs to fit_wcs and tweak_image_wcs to align_wcs. [#57]

• Fixed a bug due to which the code might crash due to an undefined ra variable, see issue #55. [#56]

• tweak_image_wcs() now returns effective reference catalog used for image alignment. [#54]

• Modified how IDs are assigned to the reference catalog source positions when expand_refcat is True: instead of having all sources numbered consecutively starting with 1, now the code will attempt to preserve the original IDs (if any) of the input reference catalog (refcat) or an input image used as a reference catalog and consecutively number only the sources being added to the refcat. [#54]

• Modified the clipping algorithm to start with all valid sources at each iteration. In other words, clippings do not accumulate by default. Old behavior can be replicated by setting clip_accum to True. [#53]

• Cleaned-up iter_linear_fit interface as well as simplified the fit dictionary returned by iter_linear_fit. [#53]

• Added option to specify statistics used for clipping. [#51, #52]

0.3.3 (21-January-2019)

• Corrected a bug in the non-weighted rscale fit. [#49]

• Corrected a bug in the computation of RMSE for the “general” fit. [#47]

• Added computation of MAE of the fit (in addition to RMSE), see [Mean Absolute Error](https://en.wikipedia.org/wiki/Mean_absolute_error). [#47]

• Renamed RMSD to RMSE (Root-Mean-Square Error). [#47]

0.3.2 (15-January-2019)

• Fixed the formula for computing RMSD of non-weighted fit. [#46]

0.3.1 (14-January-2019)

• Fixed Read-The-Docs build failure. [#45]

0.3.0 (14-January-2019)

• Implemented higher-accuracy matrix inversion. [#42]

• Bug fix related to not switching to using bounding_box instead of pixel_shape. [#41]

• Added support for optional 'weight' column in catalogs indicating the weight of each source in fitting linear transformations. [#41]

• Add support for weights to the linear fitting routines. [#40]

• Replaced the use of RMS for each axis with a single RMSD value, see [Root-Mean-Square Deviation](https://en.wikipedia.org/wiki/Root-mean-square_deviation). [#40]

• Rely on pixel_bounds [see APE 14](https://github.com/astropy/astropy-APEs/blob/master/APE14.rst) when available for computation of image’s bounding box. [#39]

• Fix a bug in the computation of the world coordinates of the fitted (aligned) sources. [#36]

0.2.0 (20-December-2018)

• Fix swapped reported reference and input indices of sources used for fitting. [#34]

• Fix for non-initialized C arrays. [#34]

• Changelog correction. [#33]

0.1.1 (11-December-2018)

• Fixeded a bug due to which 'fit_ref_idx' and 'fit_input_idx' fields in the fit dictionary were never updated. [#31]

• jwst (pipeline) package is no longer a hard dependency. [#30]

• Removed unnecessary install dependencies. [#30]

• Documentation improvements. [#30, #32]

• Corrected ‘RA’, ‘DEC’ units used to compute bounding polygon for the reference catalog. [#30]

• Updated C code to avoid numpy deprecation warnings. [#30]

0.1.0 (08-December-2018)

• Added support for aligning FITS WCS. [#15, #16]

• Added keywords to meta attributes of the TPWCS and NDData to allow easy access to the match and fit information. [#20, #21, #28]

• Package and setup re-design. Support for readthedocs. [#23]

• Documentation improvements. [#17, #18]

• Numerous other bug fixes, code clean-up, documentation improvements and enhancements. [#2, #3, #4, #5, #6, #7, #8, #9, #10, #11, #12, #13, #14, #19, #22, #24, #25, #26, #27, #28, #29]

0.0.1 (25-April-2018)

Initial release. [#1]

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