aafitrans 0.1.1

match coordinate lists

Aafitrans (AstroAlign FInd TRANSform)

Aafitrans is a Python package that provides a modified version of the find_transform function from the Astroalign package. The modifications made to the function are as follows:

• The RANSAC algorithm was modified so that the obtained solution corresponds to the one with the minimum sum of squared residuals.
• Supports all transformations available in the skimage library.
• The kdtree_search_radius parameter can be set to achieve faster matches.
• The seed parameter can be set during each run to ensure the reproducibility of results.
• The sep and bottleneck packages are no longer required as dependencies.

Please see the original Astroalign software at https://github.com/quatrope/astroalign

Citation:

Astroalign: A Python module for astronomical image registration.
Beroiz, M., Cabral, J. B., & Sanchez, B.
Astronomy & Computing, Volume 32, July 2020, 100384.

Installation

pip install aafitrans

Usage

It is similar to Astroalign's find_transform function. However, there are many parameters available for the user to modify.

from aafitrans import find_transform
transf, (matched_source_xy, matched_target_xy) = find_transform(source_xy, target_xy,
                                                                max_control_points=50,
                                                                ttype='similarity',
                                                                pixel_tolerance=2,
                                                                min_matches=4,
                                                                num_nearest_neighbors=8,
                                                                kdtree_search_radius=0.02,
                                                                n_samples=1,
                                                                get_best_fit=True,
                                                                seed=None)

Documentation for find_transform function

The find_transform function estimates the transform between two sets of control points, source, and target. It returns a GeometricTransform object T (see scikit-image documenation for details) that maps pixel x, y indices from the source image s = (x, y) into the target (destination) image t = (x, y).

Parameters:

• source: An iterable of (x, y) coordinates of the source control points.
• target: An iterable of (x, y) coordinates of the target control points.
• max_control_points: Default value is 50. The maximum number of control point-sources to find the transformation.
• ttype: Default value is similarity. The type of Transform to be estimated. One of the following should be set: {‘euclidean’, similarity’, ‘affine’, ‘piecewise-affine’, ‘projective’, ‘polynomial’}. For details, see scikit-image documentation.
• pixel_tolerance: The maximum residual error for the estimated tranform.
• min_matches: The minimum number of matches to be found. A value of 1 refers to 1 triangle, corresponding to 3 pairs of coordinates.
• num_nearest_neighbors: The number of nearest neighbors of a given star (including itself) to construct the triangle invariants.
• kdtree_search_radius: The default is 0.02. This radius is used to find nearest neighbours while conducting a KD tree search of invariant features.
• n_samples: The minimum number of data points to fit the model to. A value of 1 refers to 1 triangle, corresponding to 3 pairs of coordinates.
• get_best_fit: Whether to minimize the total error.
• seed: Seed value for Numpy Random Generator.

Returns:

• T: GeometricTransform object that maps pixel x, y indices from the source image s = (x, y) into the target (destination) image t = (x, y). It contains parameters of the transformation.
• (source_pos_array, target_pos_array): A tuple of corresponding star positions in source and target.

Raises:

• TypeError: If input type of source or target is not supported.
• ValueError: If it cannot find more than 3 stars on any input.
• MaxIterError: If no transformation is found.