From 2ef22d061c0c1e218f905ccaed11fb966cd42956 Mon Sep 17 00:00:00 2001
From: Pritimay Sarkar <pritimay@sminnovations.in>
Date: Thu, 12 Oct 2023 13:41:44 +0530
Subject: [PATCH] download coefficents

---
 scripts/coefficients.py | 29 +----------------------------
 1 file changed, 1 insertion(+), 28 deletions(-)

diff --git a/scripts/coefficients.py b/scripts/coefficients.py
index 34dd083..711f1f4 100644
--- a/scripts/coefficients.py
+++ b/scripts/coefficients.py
@@ -8,7 +8,7 @@ from datetime import datetime
 import sys
 
 # Initialize Firebase Admin SDK
-cred = credentials.Certificate(os.getcwd() + '/' + 'keys/hpos-preprod-firebase-adminsdk.json')  # Replace with your own service account key path
+cred = credentials.Certificate(os.getcwd() + '/' + 'keys/hpos-prod-firebase-adminsdk.json')  # Replace with your own service account key path
 firebase_admin.initialize_app(cred)
 
 # Get a reference to the Firestore database
@@ -16,35 +16,13 @@ db = firestore.client()
 
 # Specify the collections
 patient_collection = db.collection("devices")
-# test_collection = db.collection("testData")
-# start_date = sys.argv[1] # '2023-09-12' #input("Please enter the start date (yyyy-mm-dd): ")
-# end_date = sys.argv[2] #'2023-07-16' #input("Please enter the end date (yyyy-mm-dd): ")
-
-# query = test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
 docs = patient_collection.stream()
 
 # Prepare data to store in CSV
 data = []
 for doc in docs:
     doc_data = doc.to_dict()
-    # patient_id = patient_data["_id"]
 
-    # # Query the document from testData collection based on the common _id
-    # test_docs = test_collection.where("_id", "==", patient_id).stream()
-
-    # for test_doc in test_docs:
-    #     print(test_doc)
-    #     test_data = test_doc.to_dict()
-
-    #     # Combine the data from both collections into a single dictionary
-    #     combined_data = {**patient_data, **test_data}
-
-    #     # Fill empty fields in test_data with corresponding values from patient_data
-    #     for key, value in combined_data.items():
-    #         if value == "" and key in patient_data:
-    #             combined_data[key] = patient_data[key]
-
-    #     data.append(combined_data)
     data.append(doc_data)
 
 # Convert the data to a DataFrame
@@ -52,11 +30,6 @@ df = pd.DataFrame(data)
 print(df)
 print(df.size)
 
-# df = df[["_id", "classificationResult", "calculatedRatio", "deviceId", "deviceRatio", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "deviceSerialNumber", "name", "testTime", "resultData"]]
-# # df = df.groupby(["classificationResult"]).describe()
-# df_count = df.groupby(["classificationResult"]).describe()["calculatedRatio"]["count"]
-# print(df.groupby(["classificationResult"]).describe()["calculatedRatio"]["count"])
-
 # print("duplicates", len(df['_id']) - len(df['_id'].drop_duplicates()))
 
 # Save the DataFrame to a CSV file