test model

fonction.py

@@ -1,18 +1,28 @@
 from sklearn.linear_model import LinearRegression
 import pandas as pd 
 import numpy as np
+import json
+from datetime import datetime
+import requests
 
-def generateModele(dataJson:dict[str,str]):
+def generateModele(dataJson):
     # -- Préparation des données 
     arrayBpm = []
     arrayStartTime = []
     arrayTimeOfActivity = []
 
-    for data in dataJson["Data"]:
-        arrayBpm.append(data["BpmAvg"])
-        arrayTimeOfActivity.append(data["TimeOfActivity"])
+    for data in dataJson:
+        
+      info = json.loads(data["json"])
 
-        arrayStartTime.append(data["StartTime"])
+      arrayBpm.append(int(info["bpmAvg"]))
+      arrayTimeOfActivity.append(float(info["timeOfActivity"]))
+
+      # Convertir la chaîne en objet datetime
+      dt_object = datetime.strptime(info["startTime"], "%Y-%m-%dT%H:%M:%S.%f")
+      # Convertir l'objet datetime en millisecondes depuis l'époque
+      milliseconds_since_epoch = int(dt_object.timestamp() * 1000)
+      arrayStartTime.append(milliseconds_since_epoch)
     # -- DataFrame 
     data = pd.DataFrame({
         "Bpm": arrayBpm,
@@ -21,4 +31,31 @@ def generateModele(dataJson:dict[str,str]):
     # -- Régression linéaire 
     model = LinearRegression()
     model.fit(np.array(arrayStartTime).reshape(-1,1),data)
-    return model
+    return model
+
+
+def generateJsonModel(model:LinearRegression):
+    listCoef = []
+    listIntercept = []
+    for i in range(0,len(model.coef_)):
+        listCoef.append(model.coef_[i][0])
+        listIntercept.append(model.intercept_[i])
+    json = {"coef":listCoef,"intercept":listIntercept}
+    return json
+
+
+
+def getUserWithData(url:str):
+    response = requests.get(url)
+    if ( response.status_code != 200):
+        print('problème lors de l extraction des données avec l api !! ->  "getUserWithData" (status_code != 200)')
+        exit()
+    return response.json()
+
+def sendJsonToApi(url,json):
+    header = {"Content-type": "application/json"}
+    response = requests.post(url,json,headers=header)
+    if ( response.status_code != 200):
+        print('Problème lors de l envoi des données avec l api !! -> "sendJsonToApi" (status_code != 200)')
+        exit()
+    return 

testFinal.py

@@ -3,68 +3,13 @@
 from sklearn.linear_model import LinearRegression
 import pandas as pd 
 import numpy as np
-import requests
 import logging
 import json
 from datetime import datetime
+from fonction import getUserWithData,generateJsonModel,generateModele,sendJsonToApi
 
-# --------------- Fonction -----------------  #
-def generateJsonModel(model:LinearRegression):
-    listCoef = []
-    listIntercept = []
-    for i in range(0,len(model.coef_)):
-        listCoef.append(model.coef_[i][0])
-        listIntercept.append(model.intercept_[i])
-    json = {"coef":listCoef,"intercept":listIntercept}
-    return json
-
-def generateModele(dataJson):
-    # -- Préparation des données 
-    arrayBpm = []
-    arrayStartTime = []
-    arrayTimeOfActivity = []
-
-    for data in dataJson:
-        
-      info = json.loads(data["json"])
-
-      arrayBpm.append(int(info["bpmAvg"]))
-      arrayTimeOfActivity.append(float(info["timeOfActivity"]))
-
-      # Convertir la chaîne en objet datetime
-      dt_object = datetime.strptime(info["startTime"], "%Y-%m-%dT%H:%M:%S.%f")
-      # Convertir l'objet datetime en millisecondes depuis l'époque
-      milliseconds_since_epoch = int(dt_object.timestamp() * 1000)
-      arrayStartTime.append(milliseconds_since_epoch)
-    # -- DataFrame 
-    data = pd.DataFrame({
-        "Bpm": arrayBpm,
-        "TimeOfActivity": arrayTimeOfActivity
-    })
-    # -- Régression linéaire 
-    model = LinearRegression()
-    model.fit(np.array(arrayStartTime).reshape(-1,1),data)
-    return model
-
-
-def getUserWithData(url:str):
-    response = requests.get(urlGetAllData)
-    if ( response.status_code != 200):
-        print('problème lors de l extraction des données avec l api !! ->  "getUserWithData" (status_code != 200)')
-        exit()
-    return response.json()
-
-def sendJsonToApi(url,json):
-    header = {"Content-type": "application/json"}
-    response = requests.post(url,json,headers=header)
-    if ( response.status_code != 200):
-        print('Problème lors de l envoi des données avec l api !! -> "sendJsonToApi" (status_code != 200)')
-        exit()
-    return 
 
 # ---------------- Main ------------------- #
-logging.error("RUNNNNNNNN !")
-
 urlGetAllData = "https://codefirst.iut.uca.fr/containers/SmartFit-smartfit_api/ai/data"
 
 # --- Call Api 
@@ -96,14 +41,13 @@ dataUser = [{
 logging.error("Nombre de User : "+str(len(dataUser)))
 i = 0
 
+
 for user in dataUser:
 
   userUUID = user["uuid"]
 
   for category in user["categories"]:
       jsonTmp = {}
-      #Mettre la condition longueur ici
-      
       model = generateModele(category["infos"])
 
       jsonTmp["uuid"] = userUUID

testUnitaire.py

@@ -1,9 +1,16 @@
 import unittest
-from fonction import generateModele
+from fonction import generateModele,generateJsonModel
 
 class Testing(unittest.TestCase):
     def test_model(self):
-        self.assertEqual(generateModele(),1)
+        data = [{'json': '{"bpmAvg":114,"bpmMax":145,"bpmMin":79,"denivelePositif":449.00000000000114,"deniveleNegatif":70.00000000000114,"altitudeMax":402.4,"altitudeMin":369.20000000000005,"altitudeAvg":382.2932358318101,"temperatureMax":22,"temperatureMin":18,"temperatureAvg":20,"vitesseMax":4.62,"vitesseMin":0.0,"vitesseAvg":1.3393414634146392,"startTime":"2023-12-10T03:12:54.000","timeOfActivity":2061.82,"distance":2131.0,"calories":215,"steps":1168}'}, {'json': '{"bpmAvg":118,"bpmMax":146,"bpmMin":102,"denivelePositif":448.80000000000007,"deniveleNegatif":55.80000000000007,"altitudeMax":406.6,"altitudeMin":375.4,"altitudeAvg":386.7921763869132,"temperatureMax":24,"temperatureMin":21,"temperatureAvg":22,"vitesseMax":2.3,"vitesseMin":0.0,"vitesseAvg":1.7642135231316907,"startTime":"2023-12-12T17:17:43.000","timeOfActivity":1445.47,"distance":2449.0,"calories":170,"steps":1368}'}, {'json': '{"bpmAvg":111,"bpmMax":122,"bpmMin":103,"denivelePositif":395.19999999999993,"deniveleNegatif":23.799999999999955,"altitudeMax":375.20000000000005,"altitudeMin":369.79999999999995,"altitudeAvg":372.7532258064513,"temperatureMax":30,"temperatureMin":23,"temperatureAvg":25,"vitesseMax":2.56,"vitesseMin":0.0,"vitesseAvg":1.7127125506072893,"startTime":"2023-12-09T19:16:43.000","timeOfActivity":255.62,"distance":466.0,"calories":30,"steps":255}'}]
+        model = generateJsonModel(generateModele(data))
+        self.assertEqual(model["coef"][0],2.4008223334695094e-08)
+        self.assertEqual(model["coef"][1],1.8702979299828552e-06)
+        self.assertEqual(model["intercept"][0],-40753.409070545466)
+        self.assertEqual(model["intercept"][1],-3182440.4230727013)
 
 if __name__ == '__main__':
-    unittest.main()
+    unittest.main()
+
+#python -m unittest testUnitaire.py