[eval_records]

- refactored

eval_records.py

@@ -2,6 +2,7 @@
 import os
 import json
 import numpy as np
+from datetime import datetime, timedelta
 import dateutil.parser as dup
 from jay_diff import jay_merge_full
 from matplotlib import pyplot as plot
@@ -45,7 +46,8 @@ def convert(_filename: str) -> int:
 
 
 class Endpoint:
-	def __init__(self, _ep_spec: dict, _ts_format='%Y-%m-%dT%H:%M:%S.%f%z'):
+	def __init__(self, _name: str, _ep_spec: dict, _ts_format='%Y-%m-%dT%H:%M:%S.%f%z'):
+		self._name = _name
 		self._ep_path = _ep_spec["values"]
 		self._ep_path_keys = self.to_keys(self._ep_path)
 		self._timestamps = []
@@ -57,6 +59,10 @@ class Endpoint:
 	def timestamps_str(self) -> str:
 		return f"{self._ep_path}:{len(self._timestamps)}: {self._timestamps}"
 
+	@property
+	def name(self):
+		return self._name
+
 	@property
 	def timestamps(self) -> list[int]:
 		return self._timestamps
@@ -126,7 +132,7 @@ def check_sel(root_path, sel: list):
 	return res
 
 
-def process(end_points, base_path: str, user: str, vin: str, sel_years=None, sel_months=None, sel_days=None, sel_hours=None):
+def process(end_points: list[Endpoint], base_path: str, user: str, vin: str, sel_years=None, sel_months=None, sel_days=None, sel_hours=None):
 	_path = os.path.join(base_path, user)
 	root_path = os.path.join(_path, vin)
 
@@ -172,44 +178,67 @@ def process(end_points, base_path: str, user: str, vin: str, sel_years=None, sel
 							vehicle_data = jay_merge_full(last, vehicle_diff)
 							last = vehicle_data
 							try:
-								for k in end_points.keys():
+								for ep in end_points:
-									end_points[k].assign({'info': record['info'], 'data': vehicle_data})
+									ep.assign({'info': record['info'], 'data': vehicle_data})
 							except KeyError:
 								pass
 
-	for k in end_points.keys():
+	for ep in end_points:
-		end_points[k].remove_dups()
+		ep.remove_dups()
+
+
+def find_ep_by_name(end_points: list[Endpoint], name: str):
+	for ep in end_points:
+		if name in ep.name:
+			return ep
+
+	return None
+
+
+def process_events(_ep_dict: dict, ts_from: datetime, ts_to: datetime, ts_step: timedelta):
+	for ep_key in _ep_dict:
+		for ep in _ep_dict[ep_key]:
+			now = ts_from
+			while now < ts_to:
+				print(f"Date/time: {now}")
+				now += ts_step
 
 
 if __name__ == '__main__':
-	end_points = {}
+	end_points = []
 	for k in settings.eps.keys():
-		end_points[k] = Endpoint(settings.eps[k])
+		end_points.append(Endpoint(k, settings.eps[k]))
 
 	process(end_points, settings.BASE, settings.USER, settings.VIN, sel_days=settings.sel_days)
 
+#	process_events(end_points, datetime(2024, 10, 25, 0, 0, 0), datetime(2024, 10, 26, 0, 0, 0), timedelta(hours=1))
+
 	speed = [0]
 	_speed = 0
-	for i in range(1, len(end_points['odo'].timestamps)):
+	ep_odo = find_ep_by_name(end_points, name="odo")
-		dt = float(end_points['odo'].timestamps[i] - end_points['odo'].timestamps[i-1])/(60*100000000)
+	ep_soc = find_ep_by_name(end_points, name="soc")
-		dv = end_points['odo'].values[i] - end_points['odo'].values[i-1]
+	ep_range = find_ep_by_name(end_points, name="range")
+
+	for i in range(1, len(ep_odo.timestamps)):
+		dt = float(ep_odo.timestamps[i] - ep_odo.timestamps[i-1])/(60*100000000)
+		dv = ep_odo.values[i] - ep_odo.values[i-1]
 		_speed = 0.9*_speed + 0.1*dv/dt
 		speed.append(_speed)
 
 	plot.subplot(4, 1, 1)
-	plot.plot(np.array(end_points['odo'].timestamps) - end_points['odo'].timestamps[0], np.array(end_points['odo'].values) - end_points['odo'].values[0])
+	plot.plot(np.array(ep_odo.timestamps) - ep_odo.timestamps[0], np.array(ep_odo.values) - ep_odo.values[0])
 	plot.title("Kilometerstand")
 	plot.grid()
 	plot.subplot(4, 1, 2)
-	plot.plot(np.array(end_points['odo'].timestamps) - end_points['odo'].timestamps[0], speed)
+	plot.plot(np.array(ep_odo.timestamps) - ep_odo.timestamps[0], speed)
 	plot.title("Speed")
 	plot.grid()
 	plot.subplot(4, 1, 3)
-	plot.plot(np.array(end_points['soc'].timestamps) - end_points['soc'].timestamps[0], end_points['soc'].values)
+	plot.plot(np.array(ep_soc.timestamps) - ep_soc.timestamps[0], ep_soc.values)
 	plot.title("Akkustand")
 	plot.grid()
 	plot.subplot(4, 1, 4)
-	plot.plot(np.array(end_points['range'].timestamps) - end_points['range'].timestamps[0], end_points['range'].values)
+	plot.plot(np.array(ep_range.timestamps) - ep_range.timestamps[0], ep_range.values)
 	plot.title("Range")
 	plot.grid()
 

eval_records_settings.py

@@ -13,18 +13,18 @@ eps = {
 		{
 			"values": "data/measurements/odometerStatus/value/odometer",
 			"timestamps": "data/measurements/odometerStatus/value/carCapturedTimestamp"
+#			"timestamps": "info/timestamp"
 		},
 	"soc":
 		{
 			"values": "data/measurements/fuelLevelStatus/value/currentSOC_pct",
 			"timestamps": "data/measurements/fuelLevelStatus/value/carCapturedTimestamp"
+#			"timestamps": "info/timestamp"
 		},
 	"range":
 		{
 			"values": "data/fuelStatus/rangeStatus/value/totalRange_km",
 			"timestamps": "data/fuelStatus/rangeStatus/value/carCapturedTimestamp"
+#			"timestamps": "info/timestamp"
 		}
 }
-
-#	'odo': Endpoint('data/measurements/odometerStatus/value/odometer','info/timestamp'),
-#	'soc': Endpoint('data/measurements/fuelLevelStatus/value/currentSOC_pct','info/timestamp'),