Separates old files

src/old/philips_hue_counter.py

@@ -1,6 +1,6 @@
 from datetime import datetime, time, timedelta
 from typing import Dict
-from services.philips_hue import PhilipsHue
+from old.philips_hue import PhilipsHue
 from sensors import PeopleCounter, Directions, VL53L1XSensor
 import logging
 import json

src/old/statistics/statistics.py

@@ -15,13 +15,14 @@ with open(FILE_PATH, "r") as file:
     content = file.readlines()
 
 
-def parse_log_entry(entry: Dict) -> Dict:
+def parse_log_entry(entry: Dict) -> Dict | bool:
     # Only keep last record of a sequence
     if not is_last_in_sequence(entry):
         return False
 
     entry["dateTime"] = datetime.strptime(
-        str(entry["dateTime"])[:19], "%Y-%m-%d %H:%M:%S")
+        str(entry["dateTime"])[:19], "%Y-%m-%d %H:%M:%S"
+    )
     if entry["dateTime"] < datetime(2022, 1, 1):
         return False
 
@@ -47,20 +48,20 @@ def is_last_in_sequence(entry: Dict) -> Boolean:
 
 
 # Collect
-log = [json.loads(line.strip("\x00")) for line in content]
+log: list[Dict] = [json.loads(line.strip("\x00")) for line in content]
 print("Number of total entries:", len(log))
 
 # Parse & Filter
-log = [parse_log_entry(entry) for entry in log if parse_log_entry(entry)]
+log = [parse_log_entry(entry) for entry in log if parse_log_entry(entry)]  # type: ignore
 print("Number of filtered entries:", len(log))
 
 # Render
 fig, ax = plt.subplots()  # Create a figure containing a single axes.
 times: list[datetime] = [entry["dateTime"] for entry in log]
 counts: list[int] = [entry["previousPeopleCount"] for entry in log]
-ax.step(times, counts, where="pre")
+ax.step(times, counts, where="pre")  # type: ignore
 plt.show()
-print("-"*20)
+print("-" * 20)
 
 
 # Print stats
@@ -70,12 +71,11 @@ walk_unders = [entry for entry in log if entry["countChange"] == 0]
 print("Number of walk-ins:", len(walk_ins))
 print("Number of walk-outs:", len(walk_outs))
 print("Number of walk-unders:", len(walk_unders))
-print("-"*20)
+print("-" * 20)
 
 # Calculate faults
 for c, n in zip(list(range(len(log))), list(range(len(log)))[1:]):
-    estimated_count: int = log[c]["previousPeopleCount"] + \
+    estimated_count: int = log[c]["previousPeopleCount"] + log[c]["countChange"]
-        log[c]["countChange"]
     faulty: bool = estimated_count != log[n]["previousPeopleCount"]
     log[c]["faulty"] = faulty
     log[c]["faultyCount"] = log[c]["previousPeopleCount"] if faulty else None
@@ -85,11 +85,9 @@ fault_count = sum(1 for entry in log if entry["faulty"])
 print("Number of faults:", fault_count)
 print("Percentage of faults:", fault_count / len(log) * 100, "%")
 
-print("-"*20)
+print("-" * 20)
-faulty_off = [entry for entry in log if entry["faulty"]
+faulty_off = [entry for entry in log if entry["faulty"] and entry["faultyCount"] == 0]
-              and entry["faultyCount"] == 0]
+faulty_on = [entry for entry in log if entry["faulty"] and entry["faultyCount"] != 0]
-faulty_on = [entry for entry in log if entry["faulty"]
-             and entry["faultyCount"] != 0]
 print("Number of false-0:", len(faulty_off))
 print("Number of false-1:", len(faulty_on))
 print("Percentage of false-0:", len(faulty_off) / fault_count * 100, "%")