Mercurial > repos > goeckslab > squidpy_scatter
view squidpy_scatter.py @ 0:6fe0d4f464f4 draft
planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/squidpy commit 721eaced787aa3b04d96ad91f6b4540f26b23949
author | goeckslab |
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date | Thu, 11 Jul 2024 22:22:53 +0000 |
parents | |
children | b84c324b58bd |
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import argparse import ast import json import warnings import squidpy as sq from anndata import read_h5ad def main(inputs, output_plot): """ inputs : str File path to galaxy tool JSON inputs config file output_plot: str File path to save the plotting image """ warnings.simplefilter('ignore') # read inputs JSON with open(inputs, 'r') as param_handler: params = json.load(param_handler) # collapse param dict hierarchy, parse inputs plot_opts = params.pop('plot_opts') legend_opts = params.pop('legend_opts') aes_opts = params.pop('aesthetic_opts') options = {**params, **plot_opts, **legend_opts, **aes_opts} # read input anndata file adata_fh = options.pop('anndata') adata = read_h5ad(adata_fh) # ensure spatial coords in anndata.obsm['spatial'] # if not, populate with user provided X/Y coord column names x, y = options.pop('x_coord'), options.pop('y_coord') if 'spatial' not in adata.obsm: try: adata.obsm['spatial'] = adata.obs[[x, y]].values except Exception as e: print(e) # scan thru tool params, # replace None values, and reformat specific parameters for k, v in options.items(): if not isinstance(v, str): continue if v in ('', 'none'): options[k] = None continue if k == 'groups': options[k] = [e.strip() for e in v.split(',')] elif k == 'crop_coord': # split str on commas into tuple of coords # then nest in list (expected by squidpy function) options[k] = [tuple([int(e.strip()) for e in v.split(',')])] elif k == 'figsize': options[k] = ast.literal_eval(v) # not exposing this parameter for now. Only useful to change for ST data # and can otherwise just be problematic. # Explicitly setting to None is necessary to avoid an error options['shape'] = None # call squidpy spatial scatter function, unpack tool params sq.pl.spatial_scatter( adata=adata, save='image.png', **options ) if __name__ == '__main__': aparser = argparse.ArgumentParser() aparser.add_argument( "-i", "--inputs", dest="inputs", required=True) aparser.add_argument( "-p", "--output_plot", dest="output_plot", required=False) args = aparser.parse_args() main(args.inputs, args.output_plot)