test for significance using londFDR before sending response

run.py

@@ -2,12 +2,15 @@
 #from old_feed.computation_request import computation_request
 from interface import computational_request
 # from comp_req import comp_req
+from epivizFeed import LondFDR
 from flask_cache import Cache
 from flask_sockets import Sockets
 import time
 import ujson
 import logging
 import os
+import pandas as pd
+import json
 
 app = Flask(__name__)
 cache = Cache(app, config={'CACHE_TYPE': 'simple', 'CACHE_DEFAULT_TIMEOUT': 0})
@@ -20,37 +23,61 @@
 @sockets.route('/getdata')
 def feed(websocket):
     message = ujson.loads(websocket.receive())
+
     with open( os.getcwd() + "/epiviz.json", "r") as config_file:
         measurements = ujson.loads(config_file.read())
+
     logging.info(message)
+
     data = message['data']
     start = data['start']
     end = data['end']
     chromosome = data['chr']
     gene_name = data['gene']
     seqID = message['seq']
+    pval_disc = data['significant']
+    pval_count = data['totalTests']
     logging.info ("parameters")
+
     key = chromosome + '-' + str(start) + '-' + str(end)
     cached = cache.get(key)
+    pValFDR = LondFDR(R = pval_disc, N = pval_count)
     if cached:
+        significantCount = 0
+        for cr in cached:
+            if cr[u"significance"]:
+                significantCount += 1
         websocket.send(ujson.dumps(cached))
-        websocket.send(ujson.dumps(seqID))
+        websocket.send(ujson.dumps({"seq": seqID, "significant": significantCount, "totalTests": len(cached)}))
         return
+
     results = computational_request(start, end, chromosome, gene_name, measurements=measurements)
     cache_results = []
     logging.info (results)
+
     for result in results:
         logging.info ("send back!")
         logging.info (time.time())
         logging.info ("\n")
         # emit('returned_results', result)
-        cache_results.extend(result)
-        websocket.send(ujson.dumps(result))
+        significant_result =pd.DataFrame()
 
-    cache.set(key, cache_results)
+        if len(result) > 1:
+            logging.info("batch is > 1, FDR")
+            pvalues = result["pvalue"].tolist()
+            cor_pval = pValFDR.batchLondStar(pval = pvalues)
+            result["adjusted_testing_levels"] = cor_pval[1]
+            result["significance"] = cor_pval[2]
+            # significant_result = result.loc[result['significance'] == True]
 
-    websocket.send(ujson.dumps(seqID))
 
+        comp_res = result.to_json(orient='records')
+        parse_res = json.loads(comp_res)
+        cache_results.extend(parse_res)
+        websocket.send(ujson.dumps(parse_res))
+
+    cache.set(key, cache_results)
+    websocket.send(ujson.dumps({"seq": seqID, "significant": pValFDR.R, "totalTests": pValFDR.N}))
 
 if __name__ == "__main__":
     from gevent import pywsgi