Mercurial > repos > goeckslab > squidpy_scatter
comparison 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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-1:000000000000 | 0:6fe0d4f464f4 |
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1 import argparse | |
2 import ast | |
3 import json | |
4 import warnings | |
5 | |
6 import squidpy as sq | |
7 from anndata import read_h5ad | |
8 | |
9 | |
10 def main(inputs, output_plot): | |
11 | |
12 """ | |
13 inputs : str | |
14 File path to galaxy tool JSON inputs config file | |
15 output_plot: str | |
16 File path to save the plotting image | |
17 """ | |
18 warnings.simplefilter('ignore') | |
19 | |
20 # read inputs JSON | |
21 with open(inputs, 'r') as param_handler: | |
22 params = json.load(param_handler) | |
23 | |
24 # collapse param dict hierarchy, parse inputs | |
25 plot_opts = params.pop('plot_opts') | |
26 legend_opts = params.pop('legend_opts') | |
27 aes_opts = params.pop('aesthetic_opts') | |
28 options = {**params, **plot_opts, **legend_opts, **aes_opts} | |
29 | |
30 # read input anndata file | |
31 adata_fh = options.pop('anndata') | |
32 adata = read_h5ad(adata_fh) | |
33 | |
34 # ensure spatial coords in anndata.obsm['spatial'] | |
35 # if not, populate with user provided X/Y coord column names | |
36 x, y = options.pop('x_coord'), options.pop('y_coord') | |
37 if 'spatial' not in adata.obsm: | |
38 try: | |
39 adata.obsm['spatial'] = adata.obs[[x, y]].values | |
40 except Exception as e: | |
41 print(e) | |
42 | |
43 # scan thru tool params, | |
44 # replace None values, and reformat specific parameters | |
45 for k, v in options.items(): | |
46 if not isinstance(v, str): | |
47 continue | |
48 | |
49 if v in ('', 'none'): | |
50 options[k] = None | |
51 continue | |
52 | |
53 if k == 'groups': | |
54 options[k] = [e.strip() for e in v.split(',')] | |
55 | |
56 elif k == 'crop_coord': | |
57 # split str on commas into tuple of coords | |
58 # then nest in list (expected by squidpy function) | |
59 options[k] = [tuple([int(e.strip()) for e in v.split(',')])] | |
60 | |
61 elif k == 'figsize': | |
62 options[k] = ast.literal_eval(v) | |
63 | |
64 # not exposing this parameter for now. Only useful to change for ST data | |
65 # and can otherwise just be problematic. | |
66 # Explicitly setting to None is necessary to avoid an error | |
67 options['shape'] = None | |
68 | |
69 # call squidpy spatial scatter function, unpack tool params | |
70 sq.pl.spatial_scatter( | |
71 adata=adata, | |
72 save='image.png', | |
73 **options | |
74 ) | |
75 | |
76 | |
77 if __name__ == '__main__': | |
78 | |
79 aparser = argparse.ArgumentParser() | |
80 aparser.add_argument( | |
81 "-i", "--inputs", dest="inputs", required=True) | |
82 aparser.add_argument( | |
83 "-p", "--output_plot", dest="output_plot", required=False) | |
84 | |
85 args = aparser.parse_args() | |
86 | |
87 main(args.inputs, args.output_plot) |