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.

2 files changed, 15 insertions, 20 deletions

diff --git a/gn3/api/heatmaps.py b/gn3/api/heatmaps.py
index 43ac580..0493f8a 100644
--- a/gn3/api/heatmaps.py
+++ b/gn3/api/heatmaps.py
@@ -1,3 +1,4 @@
+import io
 from flask import jsonify
 from flask import request
 from flask import Blueprint
@@ -20,4 +21,9 @@ def clustered_heatmaps():
         return "{dataset_name}::{trait_name}".format(
             dataset_name=name_parts[1], trait_name=name_parts[0])
     traits_fullnames = [parse_trait_fullname(trait) for trait in traits_names]
-    return jsonify(build_heatmap(traits_fullnames, conn)), 200
+
+    with io.StringIO() as io_str:
+        _filename, figure = build_heatmap(traits_fullnames, conn)
+        figure.write_json(io_str)
+        fig_json = io_str.getvalue()
+    return fig_json, 200
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()):
     """