Merge pull request 'bettwaage-sidequest' (#2) from bettwaage-sidequest into master

Reviewed-on: #2

bettwaage-plotter/bett.py

@@ -1,27 +0,0 @@
-import requests as r
-from time import sleep
-
-bett_ip = "http://192.168.178.110:80"
-mash_ip = "http://192.168.178.84:9587"
-
-while True:
-    try:
-        tl = r.get(f"{bett_ip}/sensor/tl/").json()["value"]
-        tr = r.get(f"{bett_ip}/sensor/tr/").json()["value"]
-        br = r.get(f"{bett_ip}/sensor/br/").json()["value"]
-        
-        print(f"tl = {tl}")
-        print(f"tr = {tr}")
-        # print(f"tl = {tl}")
-        print(f"br = {br}")
-        print("==========")
-        print(f"total = {tl + tr + br * 2}")
-        print("==========")
-        
-        s = r.post(f"{mash_ip}/bettwaage/add?tl={int(tl * 1000)}&tr={int(tr * 1000)}&bl={int(br * 1000)}&br={int(br * 1000)}")
-        
-        sleep(1)
-    except KeyboardInterrupt:
-        exit()
-    except:
-        pass

bettwaage-plotter/main.py

@@ -2,72 +2,78 @@ import requests
 import matplotlib.pyplot as plt
 from datetime import datetime
 import json
+import os
 
+latest_history_path = "latest_history.json"
 
-file_path = "history.json"
+file_path = latest_history_path
 history_url = "http://192.168.178.84:9587/bettwaage/history"
 
+focus_on_latest_bed_data = False
+
 convert_time_to_seconds = True
 
-# Script
+# Get data
 data = None
-
+if file_path is None or not os.path.exists(file_path):
-if file_path is None:
+    print("Fetching data ...")
     data = requests.get(history_url)
     data = data.json()
+
+    print("Saving latest data ...")
+    with open(latest_history_path, "w", encoding="UTF-8") as fp:
+        json.dump(data, fp)
 else:
+    print("Reading data ...")
     with open(file_path, "r") as fp:
         data = json.load(fp)
 
 
-# Experiment: Solving for missing foot with known total weight
+print("Processing data ...")
-bed_weight = 78290
+
-person_weight = 63000
+# Get rough value for empty bed weight per leg
-known_total_weight = bed_weight + person_weight
+rough_bed_weight = 80
 bed_only_weight = {}
 for d in data:
-    if d["total"] == bed_weight:
+    if d["total"] < rough_bed_weight:
         bed_only_weight = {
             "tl": d["tl"],
             "tr": d["tr"],
-            "bl": bed_weight - (d["tl"] + d["tr"] + d["br"]),
+            "bl": d["bl"],
             "br": d["br"],
         }
+        total_bed_only_weight = sum(bed_only_weight.values())
         break
 
-in_bed_data = None
+if focus_on_latest_bed_data:
-threshhold = 100000
+    # Collect all coherent sequences of someone being in bed
-min_length = 100
+    in_bed_datas: list[list[dict]] = []
-for d in data:
+    is_in_bed_sequence = False
+    threshhold = 100.0
+    for d in data:
         t = d["total"]
         if t >= threshhold:
-        if in_bed_data is None:
+            if not is_in_bed_sequence:
-            in_bed_data = []
+                in_bed_datas.append([])
-        in_bed_data.append(d)
+                is_in_bed_sequence = True
-    elif in_bed_data is not None:
+            in_bed_datas[-1].append(d)
-        if len(in_bed_data) < min_length:
+        elif is_in_bed_sequence:
-            in_bed_data = []
+            is_in_bed_sequence = False
-        else:
+
-            break
+    # Pick latest with minimum length/duration
+    min_length = 100
+    for sequence in in_bed_datas:
+        if len(sequence) >= min_length:
+            data = sequence
 
 
-# Calculate bottom left
+# Prepare data for plotting
-for d in data:
-    d["bl"] = known_total_weight - (d["br"] + d["tr"] + d["tl"])
-    # Set known total weight
-    d["total"] = known_total_weight
-
-
-data = in_bed_data
-
-
-# Array data
 x = [d["timestamp"] for d in data]
-x = [datetime.strptime(d, "%Y-%m-%d %H:%M:%S.%f") for d in x]
+# x = [datetime.strptime(d, "%Y-%m-%d %H:%M:%S.%f") for d in x]
 
-if convert_time_to_seconds:
+# if convert_time_to_seconds:
-    max_time = max(x)
+#     max_time = max(x)
-    x = [(d - max_time).total_seconds() for d in x]
+#     x = [(d - max_time).total_seconds() for d in x]
 
 total = [d["total"] for d in data]
 tl = [d["tl"] for d in data]
@@ -80,20 +86,35 @@ left = [t + b for t, b in zip(tl, bl)]
 right = [t + b for t, b in zip(tr, br)]
 
 
+fig, ax = plt.subplots()
+
+person_weight = [t - total_bed_only_weight for t in total]
+
+ax.set_xlabel("Time (s)")
+ax.set_ylabel("Weight (kg)")
+
+ax.plot(x, person_weight, color="tab:blue")
+
+plt.show()
+exit()
+
 # Experiment: Calculate position over time
 bed_size = (140, 200)
 left_bed_only = bed_only_weight["tl"] + bed_only_weight["bl"]
 top_bed_only = bed_only_weight["tr"] + bed_only_weight["tl"]
+right_bed_only = bed_only_weight["tr"] + bed_only_weight["br"]
+bottom_bed_only = bed_only_weight["br"] + bed_only_weight["bl"]
 position_over_time = []
-for t, l in zip(top, left):
+for t, b, l, r in zip(top, bottom, left, right):
+    horizontal_weight = l - left_bed_only + r - right_bed_only
+    vertical_weight = t - top_bed_only + b - bottom_bed_only
     position_over_time.append(
         (
-            bed_size[0] * (l - left_bed_only) / person_weight,
+            bed_size[0] * (l - left_bed_only) / horizontal_weight,
-            bed_size[1] * (t - top_bed_only) / person_weight,
+            bed_size[1] * (t - top_bed_only) / vertical_weight,
         )
     )
 
-
 # Plot data
 fig, (ax0, ax1) = plt.subplots(nrows=2)
 
@@ -112,7 +133,6 @@ ax0.legend(
     ["Total", "Top Left", "Top Right", "Bottom Left", "Bottom Right", "Top", "Bottom"]
 )
 
-
 # Experiment: Plot position
 import math
 import colorsys

bettwaage-plotter/requirements.txt

@@ -1,3 +1,4 @@
 matplotlib
 requests
 numpy
+PyQt5

requirements.txt

@@ -1,7 +1,11 @@
-# For Philips Hue Counter
+# For Philips Hue
 phue
 
+# For Fritz.Box API
+fritzconnection
+
 # API
+requests
 fastapi
 uvicorn[standard]
 

src/endpoints/bettwaage.py

@@ -1,28 +1,14 @@
+import asyncio
 from fastapi.responses import HTMLResponse, JSONResponse
 from fastapi import APIRouter
 
-from datetime import datetime
 import os
 import csv
+from .handlers.bett import file_path, local_history, log_bed_weights
 
 
 router = APIRouter()
-
+asyncio.create_task(log_bed_weights())
-file_path = "bettwaage.csv"
-header = "timestamp;tl;tr;bl;br;total;"
-
-latest_values = []
-zero_values = [0, 0, 0, 0]
-scale_values = [1, 1, 1, 1]
-
-
-def add_line_to_history(line: str) -> None:
-    with open(file_path, "a") as fp:
-        fp.write(line + "\n")
-
-
-def convert_to_weight(value: int, zero_value: int, scale: float) -> float:
-    return (value - zero_value) * scale
 
 
 @router.get("/file", tags=["file"])
@@ -32,7 +18,8 @@ async def get_file():
 
 
 @router.get("/history")
-async def get_history(count: int = None) -> []:
+async def get_history(count: int = None) -> list[dict]:
+
     points = []
     with open(file_path, "r", encoding="UTF-8") as fp:
         reader = csv.DictReader(fp, delimiter=";")
@@ -57,61 +44,15 @@ async def get_history(count: int = None) -> []:
         return points
 
 
-@router.post("/add")
-async def add_weight(tl: int, tr: int, bl: int, br: int):
-    global latest_values
-    latest_values = [tl, tr, bl, br]
-
-    tl = convert_to_weight(tl, zero_values[0], scale_values[0])
-    tr = convert_to_weight(tr, zero_values[1], scale_values[1])
-    bl = convert_to_weight(bl, zero_values[2], scale_values[2])
-    br = convert_to_weight(br, zero_values[3], scale_values[3])
-
-    sum = tl + tr + bl + br
-    add_line_to_history(f"{str(datetime.now())};{tl};{tr};{bl};{br};{sum};")
-    return "Added data"
-
-
 @router.get("/latest")
 async def get_latest():
-    if not latest_values:
+    if len(local_history) == 0:
         return HTMLResponse(status_code=200, content="No data given yet")
-    total = sum(latest_values)
+    return JSONResponse(local_history[-1])
-    return JSONResponse(
+
-        {
-            "tl": latest_values[0],
-            "tr": latest_values[1],
-            "bl": latest_values[2],
-            "br": latest_values[3],
-            "total": total,
-        }
-    )
 
 
 @router.delete("/delete", tags=["file"])
 async def delete_file():
     os.remove(file_path)
-    add_line_to_history(header)
+    return "Deleted file"
-    return "Deleted file and created new file with headers"
-
-
-@router.post("/zero", tags=["calibration"])
-async def set_zero():
-    if not latest_values:
-        return HTMLResponse(
-            status_code=400, content="Requiring data before setting zeros."
-        )
-    global zero_values
-    zero_values = latest_values
-    return "Set zeroes to: " + " | ".join(str(v) for v in zero_values)
-
-
-@router.post("/scales", tags=["calibration"])
-async def set_scales(tl: float, tr: float, bl: float, br: float):
-    global scale_values
-    scale_values = [tl, tr, bl, br]
-    return "Set scales to: " + " | ".join(str(v) for v in scale_values)
-
-
-if not os.path.exists(file_path):
-    add_line_to_history(header)

src/endpoints/handlers/bett.py

@@ -0,0 +1,171 @@
+import asyncio
+from datetime import datetime
+import math
+import os
+from statistics import median
+from typing import Optional
+import requests as r
+from ..hue import hue
+import logging
+
+file_path: str = "bettwaage.csv"
+header: str = "timestamp;tl;tr;bl;br;total;\n"
+
+bett_ip: str = "http://192.168.178.110:80"
+matrix_clock_api: str = "http://192.168.178.84:8000"
+
+empty_weight: Optional[float] = None
+local_history = []
+history_max_length: int = 24 * 60 * 60  # 24 hours
+min_noticable_difference: float = 25  # In kg
+initial_scale_coutndown: int = (
+    0  # Number of updates for the scale, until return to clock, should be a multiple of 3
+)
+current_scale_countdown: int = 0
+
+average_person_weight: float = 75
+
+sexy_mode_detection: bool = False  # Turn lights "sexy" if two people are in bed
+
+is_warning_active: int = -1
+leg_capacity_limit_patterns = [
+    # {"limit": 80, "pattern": 110, "duration": 250},
+    # {"limit": 90, "pattern": 110, "duration": 100},
+    # {"limit": 100, "pattern": 10, "duration": 50},
+]
+
+
+def get_clusters(data: list[float], min_delta: float) -> dict:
+    clusters = {}
+    for point in data:
+        for known in clusters.keys():
+            if math.fabs(point - known) < min_delta:
+                clusters[known].append(point)
+                continue
+        clusters[point] = [point]
+    return clusters
+
+
+def show_time():
+    r.post(f"{matrix_clock_api}/time")
+
+
+def show_scale(weight: float):
+    r.post(f"{matrix_clock_api}/message", json={"message": f"{weight:3.1f}kg"})
+
+
+def is_capacity_reached() -> bool:
+    latest = local_history[-1]
+    highest_limit = None
+    for value in [latest["tl"], latest["tr"], latest["br"], latest["bl"]]:
+        for limit in leg_capacity_limit_patterns:
+            if value >= limit["limit"] and (
+                highest_limit is None or limit["limit"] > highest_limit["limit"]
+            ):
+                highest_limit = limit
+
+    global is_warning_active
+    if highest_limit is None:
+        if is_warning_active:
+            is_warning_active = 0
+            show_time()
+        return False
+
+    if is_warning_active != highest_limit["limit"]:
+        is_warning_active = highest_limit["limit"]
+        r.post(
+            f"{matrix_clock_api}/pattern?pattern={highest_limit['pattern']}&step_ms={highest_limit['duration']}"
+        )
+
+    return True
+
+
+def check_for_change():
+    # Check for capicity limits
+    if is_capacity_reached():
+        logging.info(f"Capacity reached")
+        return
+
+    if len(local_history) < 2:
+        return
+
+    global current_scale_countdown
+    global empty_weight
+    latest = local_history[-1]
+    if current_scale_countdown > 0:
+        if current_scale_countdown % 3 == 0:
+            show_scale(latest["total"] - empty_weight)
+        current_scale_countdown -= 1
+
+    # Is triggered?
+    delta = latest["total"] - local_history[-2]["total"]
+    if math.fabs(delta) < min_noticable_difference:
+        return
+
+    # Changed weight up or down?
+    weight_increased = delta > 0
+
+    # Make sure there is a bed_weight
+    if empty_weight is None:
+        clusters = get_clusters(
+            [d["total"] for d in local_history], min_noticable_difference
+        )
+        empty_weight = min([median(cluster) for cluster in clusters.values()])
+    logging.info(f"Empty weight: {empty_weight}")
+
+    # Determine number of people
+    number_of_people = round((latest["total"] - empty_weight) / average_person_weight)
+    logging.info(f"Number of people: {number_of_people}")
+
+    # Show scale?
+    if number_of_people == 1 and weight_increased and current_scale_countdown == 0:
+        current_scale_countdown = initial_scale_coutndown
+    else:
+        current_scale_countdown = 0
+
+    # Make room sexy
+    if sexy_mode_detection:
+        if number_of_people >= 2 and weight_increased:
+            hue.in_room_activate_scene("Max Zimmer", "Sexy")
+        elif number_of_people == 1 and not weight_increased:
+            hue.in_room_activate_scene("Max Zimmer", "Tageslicht")
+
+
+def add_line_to_bed_history(line: str) -> None:
+    exists = os.path.exists(file_path)
+    with open(file_path, "a") as fp:
+        if not exists:
+            fp.write(header)
+        fp.write(line + "\n")
+
+
+def add_weights_to_log(tl: float, tr: float, bl: float, br: float):
+    total = tl + tr + bl + br
+    timestamp = datetime.now()
+
+    global local_history
+    local_history.append({"tl": tl, "tr": tr, "bl": bl, "br": br, "total": total})
+    if len(local_history) > history_max_length:
+        local_history = local_history[len(local_history) - history_max_length :]
+
+    add_line_to_bed_history(f"{str(timestamp)};{tl};{tr};{bl};{br};{total};")
+
+
+async def log_bed_weights():
+    while True:
+        try:
+            tl = r.get(f"{bett_ip}/sensor/tl/").json()["value"]
+            tr = r.get(f"{bett_ip}/sensor/tr/").json()["value"]
+            bl = r.get(f"{bett_ip}/sensor/bl/").json()["value"]
+            br = r.get(f"{bett_ip}/sensor/br/").json()["value"]
+
+            # Sanity check
+            if min([tl, tr, bl, br]) <= 0:
+                continue
+
+            add_weights_to_log(tl, tr, bl, br)
+            check_for_change()
+        except Exception as ex:
+            logging.exception(ex)
+        finally:
+            await asyncio.sleep(1)

src/endpoints/handlers/fritz.py

@@ -0,0 +1,78 @@
+import asyncio
+import logging
+from fritzconnection import FritzConnection
+from datetime import datetime
+from ..hue import hue
+
+
+refresh_every_seconds: int = 60  # Every x seconds devices are polled again
+trigger_away_after_seconds: int = (
+    3 * 60
+)  # After all away-devices are gone for x seconds
+away_triggered = False
+away_devices = ["B2:06:77:EE:A9:0F"]  # Max' iPhone
+macaddresses_to_track = ["B2:06:77:EE:A9:0F"]  # Max' iPhone
+
+fritz_api = FritzConnection(address="192.168.178.1")
+
+# Referenced documentation: https://avm.de/fileadmin/user_upload/Global/Service/Schnittstellen/hostsSCPD.pdf
+
+
+devices_last_online = {}
+
+
+def get_all_devices() -> list:
+    numberOfDevices = fritz_api.call_action("Hosts", "GetHostNumberOfEntries")[
+        "NewHostNumberOfEntries"
+    ]
+    devices = []
+    for i in range(numberOfDevices):
+        devices.append(
+            fritz_api.call_action("Hosts", "GetGenericHostEntry", NewIndex=i)
+        )
+    return devices
+
+
+def get_specific_device(mac_address: str) -> dict:
+    return fritz_api.call_action(
+        "Hosts", "GetSpecificHostEntry", NewMACAddress=mac_address
+    )
+
+
+def check_for_change():
+    # Check if devices are away for away-mode
+    all_away = True
+    for device in away_devices:
+        last_online = devices_last_online[device]
+        if (datetime.now() - last_online).total_seconds() < trigger_away_after_seconds:
+            all_away = False
+            break
+
+    # Execute away mode
+    global away_triggered
+    if all_away:
+        if not away_triggered:
+            away_triggered = True
+            hue.in_room_deactivate_lights("Max Zimmer")
+    else:
+        away_triggered = False
+
+async def track_network_devices():
+    global devices_last_online
+
+    # Initial values to avoid None
+    for macaddress in macaddresses_to_track:
+        devices_last_online[macaddress] = datetime(1970, 1, 1, 0, 0, 0)
+
+    while True:
+        try:
+            for macaddress in macaddresses_to_track:
+                is_online = get_specific_device(macaddress)["NewActive"]
+                if is_online:
+                    devices_last_online[macaddress] = datetime.now()
+
+            check_for_change()
+        except Exception as ex:
+            logging.exception(ex)
+        finally:
+            await asyncio.sleep(refresh_every_seconds)

src/main.py

@@ -1,13 +1,14 @@
-from core.mash import MaSH
+import asyncio
-from hue.hue_feature import HueModule
+from fastapi import FastAPI
-from matrix_clock.matrix_clock_feature import MatrixClockModule
+from endpoints.hue import router as hue_router
+from endpoints.bettwaage import router as bettwaage_router
+from endpoints.handlers.fritz import track_network_devices
 
-mash: MaSH = MaSH("config.yaml")
+app = FastAPI()
-
+asyncio.create_task(track_network_devices())
-mash.add_module(HueModule())
-mash.add_module(MatrixClockModule())
 
+app.include_router(hue_router, prefix="/hue", tags=["hue"])
 app.include_router(bettwaage_router, prefix="/bettwaage", tags=["bett"])
 
 if __name__ == "__main__":
-    mash.run()
+    app.run()

start.sh

@@ -0,0 +1,5 @@
+cd /home/pi/mash-server/src
+
+source ../.env/bin/activate
+
+python3 -m uvicorn main:app --reload --host 0.0.0.0 --port 9587