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authorAlexander Kabui2021-11-23 13:38:36 +0300
committerAlexander Kabui2021-11-23 13:38:36 +0300
commitb7a4fa3007e2a3364e7a827b0bf4b3a54fcc272d (patch)
tree7db2748dac8cded711c4388dd494023b99e8a9c2 /wqflask
parent24d87cb4e75136f822b316a3c9f936b8e5efb5e9 (diff)
downloadgenenetwork2-b7a4fa3007e2a3364e7a827b0bf4b3a54fcc272d.tar.gz
merge commit :added some logic that takes into account corr_sample_group when determining which samples to use when getting sample_data
Diffstat (limited to 'wqflask')
-rw-r--r--wqflask/wqflask/correlation/correlation_gn3_api.py31
1 files changed, 25 insertions, 6 deletions
diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
index 635ef5ed..32a55b44 100644
--- a/wqflask/wqflask/correlation/correlation_gn3_api.py
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -64,20 +64,27 @@ def test_process_data(this_trait, dataset, start_vars):
return sample_data
-def process_samples(start_vars, sample_names, excluded_samples=None):
- """process samples"""
+def process_samples(start_vars,sample_names = [],excluded_samples = []):
+ """code to fetch correct samples"""
sample_data = {}
- if not excluded_samples:
- excluded_samples = ()
- sample_vals_dict = json.loads(start_vars["sample_vals"])
+ sample_vals_dict = json.loads(start_vars["sample_vals"])
+ if sample_names:
for sample in sample_names:
- if sample not in excluded_samples and sample in sample_vals_dict:
+ if sample in sample_vals_dict and sample not in excluded_samples:
+ val = sample_vals_dict[sample]
+ if not val.strip().lower() == "x":
+ sample_data[str(sample)] = float(val)
+
+ else:
+ for sample in sample_vals_dict.keys():
+ if sample not in excluded_samples:
val = sample_vals_dict[sample]
if not val.strip().lower() == "x":
sample_data[str(sample)] = float(val)
return sample_data
+
def merge_correlation_results(correlation_results, target_correlation_results):
corr_dict = {}
@@ -153,6 +160,18 @@ def lit_for_trait_list(corr_results, this_dataset, this_trait):
def fetch_sample_data(start_vars, this_trait, this_dataset, target_dataset):
+ corr_samples_group = start_vars["corr_samples_group"]
+ if corr_samples_group == "samples_primary":
+ sample_data = process_samples(
+ start_vars, this_dataset.group.all_samples_ordered())
+
+ elif corr_samples_group == "samples_other":
+ sample_data = process_samples(
+ start_vars, excluded_samples = this_dataset.group.samplelist)
+
+ else:
+ sample_data = process_samples(start_vars)
+
sample_data = process_samples(
start_vars, this_dataset.group.all_samples_ordered())