Mercurial > repos > imgteam > projective_transformation_points
changeset 0:ed8a71e13f7b draft
planemo upload for repository https://github.com/BMCV/galaxy-image-analysis/tools/projective_transformation_points/ commit c3f4b766f03770f094fda6bda0a5882c0ebd4581
| author | imgteam |
|---|---|
| date | Sat, 09 Feb 2019 14:45:19 -0500 |
| parents | |
| children | f1744c5654b9 |
| files | projective_transformation_points.py projective_transformation_points.xml test-data/out.tsv test-data/out2.tsv test-data/points_tsv.tsv test-data/warp_matrix.tsv |
| diffstat | 6 files changed, 97 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/projective_transformation_points.py Sat Feb 09 14:45:19 2019 -0500 @@ -0,0 +1,35 @@ +from skimage.transform import ProjectiveTransform +import numpy as np +import pandas as pd +import argparse + + +def warp_coords_batch(coord_map, coords, dtype=np.float64, batch_size=1000000): + tf_coords = coords.astype(np.float32) + + for i in range(0, (tf_coords.shape[0]//batch_size+1)): + tf_coords[batch_size*i:batch_size*(i+1)] = coord_map(tf_coords[batch_size*i:batch_size*(i+1)]) + + return np.unique(np.round(tf_coords).astype(coords.dtype),axis=0) + + +def transform(coords, warp_matrix, out): + indices = np.array(pd.read_csv(coords, delimiter="\t")) + a_matrix = np.array(pd.read_csv(warp_matrix, delimiter="\t", header=None)) + + trans = ProjectiveTransform(matrix=a_matrix) + warped_coords = warp_coords_batch(trans, indices) + + df = pd.DataFrame() + df['x'] = warped_coords[:,0] + df['y'] = warped_coords[:,1] + df.to_csv(out, index = False, sep="\t") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Transform coordinates") + parser.add_argument("coords", help="Paste path to .csv with coordinates to transform (tab separated)") + parser.add_argument("warp_matrix", help="Paste path to .csv that should be used for transformation (, separated)") + parser.add_argument("out", help="Paste path to file in which transformed coords should be saved (tab separated)") + args = parser.parse_args() + transform(args.coords, args.warp_matrix, args.out)
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/projective_transformation_points.xml Sat Feb 09 14:45:19 2019 -0500 @@ -0,0 +1,38 @@ +<tool id="ip_projective_transformation_points" name="Projective Transformation" version="0.0.2"> + <description>of input points</description> + <requirements> + <requirement type="package" version="0.14.2">scikit-image</requirement> + <requirement type="package" version="0.23.4">pandas</requirement> + <requirement type="package" version="1.15.2">numpy</requirement><!--conflict of 1.15.4 with mkl_fft!?--> + </requirements> + <command> + <![CDATA[ + python '$__tool_directory__/projective_transformation_points.py' + '$moving_points' + '$warp_matrix' + '$out' + ]]> + </command> + <inputs> + <param name="moving_points" type="data" format="tabular" label="Moving Points" /> + <param name="warp_matrix" type= "data" format="tabular" label="Warp Matrix" /> + </inputs> + <outputs> + <data format="tabular" name="out" /> + </outputs> + <tests> + <test> + <param name="moving_points" value="points_tsv.tsv" /> + <param name="warp_matrix" value="warp_matrix.tsv" /> + <output name="out" value="out.tsv" ftype="tabular" /> + </test> + </tests> + <help> + **What it does** + + This tool performs a projective transformation of the input (moving) points. + </help> + <citations> + <citation type="doi">10.1016/j.jbiotec.2017.07.019</citation> + </citations> +</tool>
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out.tsv Sat Feb 09 14:45:19 2019 -0500 @@ -0,0 +1,7 @@ +x y +18 24 +18 25 +18 26 +18 27 +20 22 +25 35
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/test-data/out2.tsv Sat Feb 09 14:45:19 2019 -0500 @@ -0,0 +1,7 @@ +x y +18 24 +18 25 +18 26 +18 27 +20 22 +25 35