diff options
Diffstat (limited to 'gn3')
| -rw-r--r-- | gn3/api/heatmaps.py | 18 | ||||
| -rw-r--r-- | gn3/heatmaps.py | 25 |
2 files changed, 23 insertions, 20 deletions
diff --git a/gn3/api/heatmaps.py b/gn3/api/heatmaps.py index f053241..eea3ebe 100644 --- a/gn3/api/heatmaps.py +++ b/gn3/api/heatmaps.py @@ -15,15 +15,9 @@ def clustered_heatmaps(): "message": "You need to provide at least one trait name." }), 400 conn, _cursor = database_connector() - _heatmap_file, heatmap_fig = build_heatmap(traits_names, conn) - - # stream the heatmap data somehow here. - # Can plotly actually stream the figure data in a way that can be used on - # remote end to display the image without necessarily being html? - # return jsonify( - # { - # "query": heatmap_request, - # "output_png": heatmap_fig.to_image(format="png"), - # "output_svg": heatmap_fig.to_image(format="svg") - # }), 200 - return jsonify({"output_filename": _heatmap_file}), 200 + def setup_trait_fullname(trait): + name_parts = trait.split(":") + return "{dataset_name}::{trait_name}".format( + dataset_name=trait[1], trait_name=trait[0]) + traits_fullnames = [parse_trait_fullname(trait) for trait in traits_names] + return jsonify(build_heatmap(traits_fullnames, conn)), 200 diff --git a/gn3/heatmaps.py b/gn3/heatmaps.py index c4fc67d..205a3b3 100644 --- a/gn3/heatmaps.py +++ b/gn3/heatmaps.py @@ -199,17 +199,26 @@ def build_heatmap(traits_names, conn: Any): zip(traits_ids, [traits[idx]["trait_fullname"] for idx in traits_order])) - return generate_clustered_heatmap( - process_traits_data_for_heatmap( + # 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( organised, traits_ids, chromosome_names), - clustered, - "single_heatmap_{}".format(random_string(10)), - y_axis=tuple( + "traits": tuple( ordered_traits_names[traits_ids[order]] for order in traits_order), - y_label="Traits", - x_axis=chromosome_names, - x_label="Chromosomes") + "chromosomes": chromosome_names + } def compute_traits_order(slink_data, neworder: tuple = tuple()): """ |