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| author | Frederick Muriuki Muriithi | 2021-09-22 07:03:53 +0300 |
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| committer | Frederick Muriuki Muriithi | 2021-09-22 07:03:53 +0300 |
| commit | 920be820e9cefe1dcde86d9a252f098c67a2bb8b (patch) | |
| tree | ffa17fce2a2dca25974370cf8a1677fdb3d0b0ac /gn3/heatmaps.py | |
| parent | 8442204492a28153e995f3147e06c9758cd3bd28 (diff) | |
| download | genenetwork3-920be820e9cefe1dcde86d9a252f098c67a2bb8b.tar.gz | |
Return serialized plotly figure
Issue: https://github.com/genenetwork/gn-gemtext-threads/blob/main/topics/gn1-migration-to-gn2/clustering.gmi * gn3/api/heatmaps.py: Serialize the figure to JSON * gn3/heatmaps.py: Return the figure object Serialize the Plotly figure into JSON, and return that, so that it can be used on the client to display the image.
Diffstat (limited to 'gn3/heatmaps.py')
| -rw-r--r-- | gn3/heatmaps.py | 27 |
1 files changed, 8 insertions, 19 deletions
diff --git a/gn3/heatmaps.py b/gn3/heatmaps.py index 205a3b3..cd93b3f 100644 --- a/gn3/heatmaps.py +++ b/gn3/heatmaps.py @@ -187,38 +187,27 @@ def build_heatmap(traits_names, conn: Any): genotype_filename, traits_filename, separate_nperm_output=True) qtlresults = parse_reaper_main_results(main_output) - # permudata = parse_reaper_permutation_results(permutations_output) organised = organise_reaper_main_results(qtlresults) traits_ids = [# sort numerically, but retain the ids as strings str(i) for i in sorted({int(row["ID"]) for row in qtlresults})] chromosome_names = sorted( {row["Chr"] for row in qtlresults}, key=chromosome_sorter_key_fn) - # loci_names = sorted({row["Locus"] for row in qtlresults}) ordered_traits_names = dict( zip(traits_ids, [traits[idx]["trait_fullname"] for idx in traits_order])) - # return generate_clustered_heatmap( - # process_traits_data_for_heatmap( - # organised, traits_ids, chromosome_names), - # clustered, - # "single_heatmap_{}".format(random_string(10)), - # y_axis=tuple( - # ordered_traits_names[traits_ids[order]] - # for order in traits_order), - # y_label="Traits", - # x_axis=chromosome_names, - # x_label="Chromosomes") - return { - "clustering_data": clustered, - "heatmap_data": process_traits_data_for_heatmap( + return generate_clustered_heatmap( + process_traits_data_for_heatmap( organised, traits_ids, chromosome_names), - "traits": tuple( + clustered, + "single_heatmap_{}".format(random_string(10)), + y_axis=tuple( ordered_traits_names[traits_ids[order]] for order in traits_order), - "chromosomes": chromosome_names - } + y_label="Traits", + x_axis=chromosome_names, + x_label="Chromosomes") def compute_traits_order(slink_data, neworder: tuple = tuple()): """ |