improve motion detection examples

examples/motion_detector.py

@@ -3,24 +3,48 @@ This example shows how to use the CSI framework to connect to a FeitCSI host and
 detect changes in the environment
 """
 
-from queue import Queue
-
 import numpy as np
 import numpy.typing as npt
 
 from where_fi.application import CSIApplication
 from where_fi.collection.ingest import RealtimeCSIProducer
+from where_fi.config import config
+from where_fi.visualise import server as visualise
 
 # Connect to a FeitCSI host
 app = CSIApplication(visualise_raw=True)
 
+# Register visualisations
+app.register_figure(
+    "magn-diff",
+    visualise.figures.PerAntennaFigure(
+        [
+            visualise.figures.SimpleLineChart(
+                "Magnitude diff", "Subcarrier", "Magnitude"
+            ),
+        ],
+        [lambda x: x],
+    ),
+)
+app.register_figure(
+    "phase-diff",
+    visualise.figures.PerAntennaFigure(
+        [
+            visualise.figures.SimpleLineChart("Phase diff", "Subcarrier", "Phase"),
+        ],
+        [lambda x: x],
+    ),
+)
+
+MAGN_THRESHOLD = 0.2
+PHASE_THRESHOLD = 0.02
+QUEUE_SIZE = 20
 
 # Stores historical data for each receiving antenna, for each subcarrier
-historical: dict[tuple[int, int], Queue[np.complex64]] = {}
+historical = np.zeros(
-
+    (QUEUE_SIZE, config.subcarriers, config.antennas.count, 1), dtype=np.complex64
-MAGN_THRESHOLD = 20
+)
-PHASE_THRESHOLD = 0.5
+sample_position = 0
-QUEUE_SIZE = 20
 
 
 @app.on_process
@@ -34,39 +58,20 @@ def _(sample: npt.NDArray[np.complex64]) -> None:
     It is used to detect changes in the environment caused by motion, by comparing each
     entry in the matrix with a moving average
     """
-    change = False
+    global historical
-    for antenna in range(sample.shape[1]):
+    global sample_position
-        for subcarrier in range(sample.shape[0]):
-            # Get the current subcarrier data
-            current = sample[subcarrier, antenna, 0]
 
-            # Get the historical data for this antenna and subcarrier
+    historical[sample_position] = sample
-            if (antenna, subcarrier) not in historical:
+    sample_position = (sample_position + 1) % QUEUE_SIZE
-                historical[(antenna, subcarrier)] = Queue(maxsize=QUEUE_SIZE)
-            historical_data = historical[(antenna, subcarrier)]
 
-            # Calculate the average of the historical data for this antenna and
+    mean = np.mean(historical, axis=0)
-            # subcarrier
+    magn_diff = np.abs(mean - sample)
-            mean = np.mean(historical_data.queue)
+    phase_diff = np.abs(np.angle(mean) - np.angle(sample))
 
-            # If we have enough historical data, compare it with the current data
+    app.visualise_data(magn_diff, "magn-diff")
-            if historical_data.full():
+    app.visualise_data(phase_diff, "phase-diff")
-                historical_data.get()
 
-            # Add the current sample to the historical data
+    if (magn_diff > MAGN_THRESHOLD).any() or (phase_diff > PHASE_THRESHOLD).any():
-            historical_data.put(current)
-
-            # Compare the current data with the historical data
-            if (
-                np.abs(mean - current) > MAGN_THRESHOLD
-                or np.abs(np.angle(mean) - np.angle(current)) > PHASE_THRESHOLD
-            ):
-                print(
-                    f"Change detected in antenna {antenna}, subcarrier {subcarrier}: "
-                    f"magn: {np.abs(mean - current)}, angle: {np.abs(np.angle(mean) - np.angle(current))}"
-                )
-                change = True
-    if change:
         print("Motion detected!")
     else:
         print("No motion detected!")

examples/motion_detector_home_assistant.py

@@ -1,24 +1,51 @@
 """Motion Detection example
 This example shows how to use the CSI framework to connect to a FeitCSI host and
 detect changes in the environment
-
-Once motion is detected, the application will log the change to Home Assistant
-through an HTTP request.
 """
 
-import os
-from queue import Queue
-
 import numpy as np
 import numpy.typing as npt
 import requests
 
 from where_fi.application import CSIApplication
 from where_fi.collection.ingest import RealtimeCSIProducer
+from where_fi.config import config
+from where_fi.visualise import server as visualise
 
 # Connect to a FeitCSI host
-producer = RealtimeCSIProducer()
+app = CSIApplication(visualise_raw=True)
-app = CSIApplication(producer)
+
+# Register visualisations
+app.register_figure(
+    "magn-diff",
+    visualise.figures.PerAntennaFigure(
+        [
+            visualise.figures.SimpleLineChart(
+                "Magnitude diff", "Subcarrier", "Magnitude"
+            ),
+        ],
+        [lambda x: x],
+    ),
+)
+app.register_figure(
+    "phase-diff",
+    visualise.figures.PerAntennaFigure(
+        [
+            visualise.figures.SimpleLineChart("Phase diff", "Subcarrier", "Phase"),
+        ],
+        [lambda x: x],
+    ),
+)
+
+MAGN_THRESHOLD = 0.2
+PHASE_THRESHOLD = 0.02
+QUEUE_SIZE = 20
+
+# Stores historical data for each receiving antenna, for each subcarrier
+historical = np.zeros(
+    (QUEUE_SIZE, config.subcarriers, config.antennas.count, 1), dtype=np.complex64
+)
+sample_position = 0
 
 
 class HomeAssistantBinarySensor:
@@ -55,14 +82,8 @@ class HomeAssistantBinarySensor:
         requests.post(self.url, json=data, headers=self.headers)
 
 
-# Stores historical data for each receiving antenna, for each subcarrier
-historical: dict[tuple[int, int], Queue[np.complex64]] = {}
 sensor = HomeAssistantBinarySensor("motion_detector", "Room Motion Detector")
 
-MAGN_THRESHOLD = 20
-PHASE_THRESHOLD = 0.5
-QUEUE_SIZE = 2000
-
 
 @app.on_process
 def _(sample: npt.NDArray[np.complex64]) -> None:
@@ -75,36 +96,28 @@ def _(sample: npt.NDArray[np.complex64]) -> None:
     It is used to detect changes in the environment caused by motion, by comparing each
     entry in the matrix with a moving average
     """
-    change = False
+    global sample_position
-    for antenna in range(sample.shape[1]):
-        for subcarrier in range(sample.shape[0]):
-            # Get the current subcarrier data
-            current = sample[subcarrier, antenna, 0]
 
-            # Get the historical data for this antenna and subcarrier
+    historical[sample_position] = sample
-            if (antenna, subcarrier) not in historical:
+    sample_position = (sample_position + 1) % QUEUE_SIZE
-                historical[(antenna, subcarrier)] = Queue(maxsize=QUEUE_SIZE)
-            historical_data = historical[(antenna, subcarrier)]
 
-            # Calculate the average of the historical data for this antenna and
+    mean = np.mean(historical, axis=0)
-            # subcarrier
+    magn_diff = np.abs(mean - sample)
-            mean = np.mean(historical_data.queue)
+    phase_diff = np.abs(np.angle(mean) - np.angle(sample))
 
-            # If we have enough historical data, compare it with the current data
+    app.visualise_data(magn_diff, "magn-diff")
-            if historical_data.full():
+    app.visualise_data(phase_diff, "phase-diff")
-                historical_data.get()
 
-            # Add the current sample to the historical data
+    if (magn_diff > MAGN_THRESHOLD).any() or (phase_diff > PHASE_THRESHOLD).any():
-            historical_data.put(current)
+        print("Motion detected!")
-
+        sensor.update(True)
-            # Compare the current data with the historical data
+    else:
-            if (
+        print("No motion detected!")
-                np.abs(mean - current) > MAGN_THRESHOLD
+        sensor.update(False)
-                or np.abs(np.angle(mean) - np.angle(current)) > PHASE_THRESHOLD
-            ):
-                change = True
-
-    sensor.update(change)
 
 
+if __name__ == "__main__":
+    # Start the application
+    print("Starting app")
+    app.set_producer(RealtimeCSIProducer())
     app.start()

where_fi/processing/preprocess.py

@@ -222,7 +222,7 @@ class Preprocessor:
                 case "bandpass":
                     h_hat = self.bandpass(h_hat)
 
-        logger.info(f"CSI shape: {h_hat.shape}")
+        logger.debug(f"CSI shape: {h_hat.shape}")
 
         self._last_sample = h_hat
 

where_fi/visualise/server/__init__.py

@@ -67,6 +67,10 @@ class Webapp:
     def add_data(
         self, dtype: figures.FigureId, new_data: npt.NDArray[np.complex128]
     ) -> None:
+        self.logger.debug(f"Adding data to figure server {dtype}")
+        if dtype not in figures.all_figures:
+            self.logger.error(f"Figure {dtype} not found")
+            return
         updates = figures.all_figures[dtype].update(new_data)
         for fig_id, update in updates.items():
             for client in self.figure_server.clients.get(fig_id, []):
@@ -76,7 +80,7 @@ class Webapp:
         while self.active:
             self.logger.debug("Listening for data")
             try:
-                data = data_queue.get(timeout=0.5)
+                data = data_queue.get(timeout=0.1)
                 self.add_data(data.dtype, data.data)
             except queue.Empty:
                 pass

where_fi/visualise/server/figures.py

@@ -103,7 +103,28 @@ class PerSubcarrierFigure(SpecificFigure):
         return reduce((lambda a, b: a | b), updates)
 
 
-class PerAntennaFigure(SpecificFigure):
+class LabelledMultiLineChart(SpecificFigure):
+    def __init__(
+        self,
+        figures: Sequence[SimpleLineChart],
+        funcs: list[Callable[[npt.NDArray[Any]], npt.NDArray[Any]]],
+        labels: Sequence[str],
+    ) -> None:
+        self.charts = figures
+        self.figures = [figure.figure for figure in figures]
+        self.funcs = funcs
+        self.labels = labels
+
+    def update(self, new_data: npt.NDArray[np.complex128]) -> FigureUpdate:
+        data_by_antenna = new_data[:, :, 0].T
+        updates = [
+            figure.update(func(data_by_antenna), labels=self.labels)
+            for func, figure in zip(self.funcs, self.charts, strict=True)
+        ]
+        return reduce((lambda a, b: a | b), updates)
+
+
+class PerAntennaFigure(LabelledMultiLineChart):
     """A figure that plots data for each antenna separately.
 
     This allows creating multiple figures, each having one line per antenna.
@@ -118,18 +139,9 @@ class PerAntennaFigure(SpecificFigure):
         figures: Sequence[SimpleLineChart],
         funcs: list[Callable[[npt.NDArray[Any]], npt.NDArray[Any]]],
     ) -> None:
-        self.charts = figures
+        super().__init__(
-        self.figures = [figure.figure for figure in figures]
+            figures, funcs, [f"Antenna {i + 1}" for i in range(config.antennas.count)]
-        self.funcs = funcs
+        )
-
-    def update(self, new_data: npt.NDArray[np.complex128]) -> FigureUpdate:
-        data_by_antenna = new_data[:, :, 0].T
-        antenna_labels = [f"Antenna {i}" for i in range(data_by_antenna.shape[0])]
-        updates = [
-            figure.update(func(data_by_antenna), labels=antenna_labels)
-            for func, figure in zip(self.funcs, self.charts, strict=True)
-        ]
-        return reduce((lambda a, b: a | b), updates)
 
 
 class MusicEigenvalueHistogram(SpecificFigure):