2 files changed, 91 insertions, 0 deletions
diff --git a/wqflask/tests/unit/wqflask/correlation/test_correlation_gn3.py b/wqflask/tests/unit/wqflask/correlation/test_correlation_gn3.py
new file mode 100644
index 00000000..e1bd6d86
--- /dev/null
+++ b/wqflask/tests/unit/wqflask/correlation/test_correlation_gn3.py
@@ -0,0 +1,14 @@
+"""this module contains tests for code used in integrating to gn3 api"""
+from unittest import TestCase
+from base.data_set import create_dataset
+
+class TestCorrelation(TestCase):
+
+    def test_create_dataset(self):
+        """test for creating datasets"""
+
+        pass
+    def test_fetch_dataset_info(self):
+        """test for fetching dataset info data"""
+
+        pass
diff --git a/wqflask/wqflask/correlation/correlation_gn3_api.py b/wqflask/wqflask/correlation/correlation_gn3_api.py
new file mode 100644
index 00000000..4cf6533c
--- /dev/null
+++ b/wqflask/wqflask/correlation/correlation_gn3_api.py
@@ -0,0 +1,77 @@
+"""module that calls the gn3 api's to do the correlation """
+from base import data_set
+from base.trait import create_trait
+from base.trait import retrieve_sample_data
+
+
+
+
+
+
+
+def compute_sample_r(start_vars,target_dataset, trait_data, target_samplelist, method="pearson"):
+    import requests
+    from wqflask.correlation.correlation_gn3_api import compute_correlation
+
+    cor_results = compute_correlation(start_vars)
+
+    data = {
+        "target_dataset": target_dataset,
+        "target_samplelist": target_samplelist,
+        "trait_data": {
+            "trait_sample_data": trait_data,
+            "trait_id": "HC_Q"
+        }
+    }
+    requests_url = f"http://127.0.0.1:8080/api/correlation/sample_x/{method}"
+
+    results = requests.post(requests_url, json=data)
+
+    data = results.json()
+
+    print(data)
+
+    return data
+
+
+def process_samples(start_vars,sample_names,excluded_samples=None):
+    sample_data = {}
+    if not excluded_samples:
+        excluded_samples = ()
+
+        sample_vals_dict  = json.loads(start_vars["sample_vals"])
+
+        for sample in sample_names:
+            if sample not in excluded_samples:
+                val = sample_val_dict[sample]
+                if not val.strip().lower() == "x":
+                    sample_data[str(sample)]=float(value)
+
+    return sample_data
+
+
+def create_fetch_dataset_data(dataset_name):
+    this_dataset  = data_set.create_dataset(dataset_name=dataset_name)
+
+    this_dataset.get_trait_data()
+
+
+def create_target_this_trait(start_vars):
+    """this function prefetch required data for correlation"""
+
+    this_dataset = data_set.create_dataset(dataset_name=start_vars['dataset'])
+    target_dataset = data_set.create_dataset(
+        dataset_name=start_vars['corr_dataset'])
+
+    this_trait = create_trait(dataset=this_dataset,
+                              name=start_vars['trait_id'])
+
+    this_trait = retrieve_sample_data(this_trait, this_dataset)
+
+    target_dataset.get_trait_data()
+
+    return (this_dataset,this_trait,target_dataset)
+def compute_correlation(start_vars):
+
+    this_dataset, this_trait, target_dataset = create_target_this_trait(
+        start_vars=start_vars)