Namespace all modules under gn2.

We move all modules under a gn2 directory. This is important for
"correct" packaging and deployment as a Guix service.

2 files changed, 95 insertions, 0 deletions

diff --git a/gn2/wqflask/comparison_bar_chart/__init__.py b/gn2/wqflask/comparison_bar_chart/__init__.py
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/gn2/wqflask/comparison_bar_chart/__init__.py
diff --git a/gn2/wqflask/comparison_bar_chart/comparison_bar_chart.py b/gn2/wqflask/comparison_bar_chart/comparison_bar_chart.py
new file mode 100644
index 00000000..3fb3cb40
--- /dev/null
+++ b/gn2/wqflask/comparison_bar_chart/comparison_bar_chart.py
@@ -0,0 +1,95 @@
+# Copyright (C) University of Tennessee Health Science Center, Memphis, TN.
+#
+# This program is free software: you can redistribute it and/or modify it
+# under the terms of the GNU Affero General Public License
+# as published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+# See the GNU Affero General Public License for more details.
+#
+# This program is available from Source Forge: at GeneNetwork Project
+# (sourceforge.net/projects/genenetwork/).
+#
+# Contact Dr. Robert W. Williams at rwilliams@uthsc.edu
+#
+#
+# This module is used by GeneNetwork project (www.genenetwork.org)
+
+from pprint import pformat as pf
+
+from gn2.base.trait import create_trait
+from gn2.base import data_set
+from gn2.utility import webqtlUtil, helper_functions, corr_result_helpers
+import gn2.utility.webqtlUtil  # this is for parallel computing only.
+from gn2.wqflask.correlation import correlation_functions
+
+from flask import Flask, g
+
+
+class ComparisonBarChart:
+
+    def __init__(self, start_vars):
+        trait_db_list = [trait.strip()
+                         for trait in start_vars['trait_list'].split(',')]
+
+        helper_functions.get_trait_db_obs(self, trait_db_list)
+
+        self.all_sample_list = []
+        self.traits = []
+        self.insufficient_shared_samples = False
+        # ZS: Getting initial group name before verifying all traits are in the same group in the following loop
+        this_group = self.trait_list[0][1].group.name
+        for trait_db in self.trait_list:
+
+            if trait_db[1].group.name != this_group:
+                self.insufficient_shared_samples = True
+                break
+            else:
+                this_group = trait_db[1].group.name
+            this_trait = trait_db[0]
+            self.traits.append(this_trait)
+
+            this_sample_data = this_trait.data
+
+            for sample in this_sample_data:
+                if sample not in self.all_sample_list:
+                    self.all_sample_list.append(sample)
+
+        if self.insufficient_shared_samples:
+            pass
+        else:
+            self.sample_data = []
+            for trait_db in self.trait_list:
+                this_trait = trait_db[0]
+                this_sample_data = this_trait.data
+
+                this_trait_vals = []
+                for sample in self.all_sample_list:
+                    if sample in this_sample_data:
+                        this_trait_vals.append(this_sample_data[sample].value)
+                    else:
+                        this_trait_vals.append('')
+                self.sample_data.append(this_trait_vals)
+
+            self.js_data = dict(traits=[trait.name for trait in self.traits],
+                                samples=self.all_sample_list,
+                                sample_data=self.sample_data,)
+
+    def get_trait_db_obs(self, trait_db_list):
+
+        self.trait_list = []
+        for i, trait_db in enumerate(trait_db_list):
+            if i == (len(trait_db_list) - 1):
+                break
+            trait_name, dataset_name = trait_db.split(":")
+            #print("dataset_name:", dataset_name)
+            dataset_ob = data_set.create_dataset(dataset_name)
+            trait_ob = create_trait(dataset=dataset_ob,
+                                    name=trait_name,
+                                    cellid=None)
+            self.trait_list.append((trait_ob, dataset_ob))
+
+        #print("trait_list:", self.trait_list)