mirror of
https://github.com/pyMC-dev/pyMC_Repeater.git
synced 2026-06-26 04:51:34 +02:00
add heatmap chat
This commit is contained in:
Lloyd
+3
-1
@@ -29,14 +29,16 @@ classifiers = [
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keywords = ["mesh", "networking", "lora", "repeater", "daemon", "iot"]
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dependencies = [
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"pymc_core[hardware]>=1.0.2",
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"pymc_core[hardware] @ git+https://github.com/rightup/pyMC_core.git@feat/cad",
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"pyyaml>=6.0.0",
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"cherrypy>=18.0.0",
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]
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[project.optional-dependencies]
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dev = [
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"pytest>=7.4.0",
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+226
-79
@@ -58,14 +58,14 @@ class CADCalibrationEngine:
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self.calibration_thread = None
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def get_test_ranges(self, spreading_factor: int):
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"""Get CAD test ranges based on spreading factor"""
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"""Get CAD test ranges based on spreading factor - comprehensive coverage"""
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sf_ranges = {
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7: (range(16, 29, 1), range(6, 15, 1)),
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8: (range(16, 29, 1), range(6, 15, 1)),
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9: (range(18, 31, 1), range(7, 16, 1)),
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10: (range(20, 33, 1), range(8, 16, 1)),
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11: (range(22, 35, 1), range(9, 17, 1)),
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12: (range(24, 37, 1), range(10, 18, 1)),
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7: (range(17, 26, 1), range(7, 15, 1)), # Full range coverage
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8: (range(17, 26, 1), range(7, 15, 1)), # Full range coverage
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9: (range(19, 28, 1), range(8, 16, 1)), # Full range coverage
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10: (range(21, 30, 1), range(9, 17, 1)), # Full range coverage
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11: (range(23, 32, 1), range(10, 18, 1)), # Full range coverage
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12: (range(25, 34, 1), range(11, 19, 1)), # Full range coverage
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}
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return sf_ranges.get(spreading_factor, sf_ranges[8])
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@@ -75,12 +75,12 @@ class CADCalibrationEngine:
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for _ in range(samples):
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try:
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result = await radio.perform_cad(det_peak=det_peak, det_min=det_min, timeout=0.6)
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result = await radio.perform_cad(det_peak=det_peak, det_min=det_min, timeout=0.3)
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if result:
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detections += 1
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except Exception:
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pass
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await asyncio.sleep(0.03)
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await asyncio.sleep(0.01) # Reduced sleep time
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return {
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'det_peak': det_peak,
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@@ -92,13 +92,12 @@ class CADCalibrationEngine:
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def broadcast_to_clients(self, data):
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"""Send data to all connected SSE clients"""
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message = f"data: {json.dumps(data)}\n\n"
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for client in self.clients.copy():
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try:
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client.write(message.encode())
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client.flush()
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except Exception:
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self.clients.discard(client)
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# Store the message for clients to pick up
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self.last_message = data
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# Also store in a queue for clients to consume
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if not hasattr(self, 'message_queue'):
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self.message_queue = []
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self.message_queue.append(data)
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def calibration_worker(self, samples: int, delay_ms: int):
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"""Worker thread for calibration process"""
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@@ -129,60 +128,105 @@ class CADCalibrationEngine:
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self.broadcast_to_clients({
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"type": "status",
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"message": f"Starting calibration: SF{sf}, {total_tests} tests"
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"message": f"Starting calibration: SF{sf}, {total_tests} tests",
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"test_ranges": {
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"peak_min": min(peak_range),
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"peak_max": max(peak_range),
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"min_min": min(min_range),
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"min_max": max(min_range),
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"spreading_factor": sf,
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"total_tests": total_tests
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}
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})
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current = 0
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# Run calibration in event loop
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import random
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peak_list = list(peak_range)
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min_list = list(min_range)
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# Create all test combinations
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test_combinations = []
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for det_peak in peak_list:
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for det_min in min_list:
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test_combinations.append((det_peak, det_min))
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# Sort by distance from center for center-out pattern
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peak_center = (max(peak_list) + min(peak_list)) / 2
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min_center = (max(min_list) + min(min_list)) / 2
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def distance_from_center(combo):
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peak, min_val = combo
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return ((peak - peak_center) ** 2 + (min_val - min_center) ** 2) ** 0.5
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# Sort by distance from center
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test_combinations.sort(key=distance_from_center)
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band_size = max(1, len(test_combinations) // 8) # Create 8 bands
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randomized_combinations = []
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for i in range(0, len(test_combinations), band_size):
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band = test_combinations[i:i + band_size]
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random.shuffle(band) # Randomize within each band
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randomized_combinations.extend(band)
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# Run calibration in event loop with center-out randomized pattern
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if self.event_loop:
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for det_peak in peak_range:
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for det_peak, det_min in randomized_combinations:
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if not self.running:
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break
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for det_min in min_range:
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if not self.running:
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break
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current += 1
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self.progress["current"] = current
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current += 1
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self.progress["current"] = current
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# Update progress
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self.broadcast_to_clients({
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"type": "progress",
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"current": current,
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"total": total_tests,
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"peak": det_peak,
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"min": det_min
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})
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# Run the test
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future = asyncio.run_coroutine_threadsafe(
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self.test_cad_config(radio, det_peak, det_min, samples),
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self.event_loop
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)
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try:
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result = future.result(timeout=30) # 30 second timeout per test
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# Update progress
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# Store result
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key = f"{det_peak}-{det_min}"
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self.results[key] = result
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# Send result to clients
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self.broadcast_to_clients({
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"type": "progress",
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"current": current,
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"total": total_tests,
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"peak": det_peak,
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"min": det_min
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"type": "result",
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**result
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})
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except Exception as e:
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logger.error(f"CAD test failed for peak={det_peak}, min={det_min}: {e}")
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# Run the test
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future = asyncio.run_coroutine_threadsafe(
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self.test_cad_config(radio, det_peak, det_min, samples),
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self.event_loop
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)
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try:
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result = future.result(timeout=30) # 30 second timeout per test
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# Store result
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key = f"{det_peak}-{det_min}"
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self.results[key] = result
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# Send result to clients
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self.broadcast_to_clients({
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"type": "result",
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**result
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})
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except Exception as e:
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logger.error(f"CAD test failed for peak={det_peak}, min={det_min}: {e}")
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# Delay between tests
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if self.running and delay_ms > 0:
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time.sleep(delay_ms / 1000.0)
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# Delay between tests
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if self.running and delay_ms > 0:
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time.sleep(delay_ms / 1000.0)
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if self.running:
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self.broadcast_to_clients({"type": "completed", "message": "Calibration completed"})
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# Find best result
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best_result = None
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if self.results:
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best_result = max(self.results.values(), key=lambda x: x['detection_rate'])
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self.broadcast_to_clients({
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"type": "completed",
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"message": "Calibration completed",
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"results": {"best": best_result} if best_result else None
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})
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else:
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self.broadcast_to_clients({"type": "status", "message": "Calibration stopped"})
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@@ -200,6 +244,7 @@ class CADCalibrationEngine:
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self.running = True
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self.results.clear()
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self.progress = {"current": 0, "total": 0}
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self.clear_message_queue() # Clear any old messages
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# Start calibration in separate thread
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self.calibration_thread = threading.Thread(
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@@ -217,15 +262,10 @@ class CADCalibrationEngine:
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if self.calibration_thread:
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self.calibration_thread.join(timeout=2)
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def add_client(self, response_stream):
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"""Add SSE client"""
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self.clients.add(response_stream)
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def remove_client(self, response_stream):
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"""Remove SSE client"""
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self.clients.discard(response_stream)
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def clear_message_queue(self):
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"""Clear the message queue when starting a new calibration"""
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if hasattr(self, 'message_queue'):
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self.message_queue.clear()
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class APIEndpoints:
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def __init__(
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@@ -235,13 +275,15 @@ class APIEndpoints:
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config: Optional[dict] = None,
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event_loop=None,
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daemon_instance=None,
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config_path=None,
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):
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self.stats_getter = stats_getter
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self.send_advert_func = send_advert_func
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self.config = config or {}
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self.event_loop = event_loop # Store reference to main event loop
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self.daemon_instance = daemon_instance # Store reference to daemon instance
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self.event_loop = event_loop
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self.daemon_instance = daemon_instance
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self._config_path = config_path or '/etc/pymc_repeater/config.yaml'
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# Initialize CAD calibration engine
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self.cad_calibration = CADCalibrationEngine(daemon_instance, event_loop)
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@@ -395,6 +437,72 @@ class APIEndpoints:
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logger.error(f"Error stopping CAD calibration: {e}")
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return {"success": False, "error": str(e)}
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@cherrypy.expose
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@cherrypy.tools.json_out()
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@cherrypy.tools.json_in()
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def save_cad_settings(self):
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"""Save CAD calibration settings to config"""
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if cherrypy.request.method != "POST":
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return {"success": False, "error": "Method not allowed"}
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try:
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data = cherrypy.request.json or {}
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peak = data.get("peak")
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min_val = data.get("min_val")
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detection_rate = data.get("detection_rate", 0)
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if peak is None or min_val is None:
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return {"success": False, "error": "Missing peak or min_val parameters"}
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# Update the radio immediately if available
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if self.daemon_instance and hasattr(self.daemon_instance, 'radio') and self.daemon_instance.radio:
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if hasattr(self.daemon_instance.radio, 'set_custom_cad_thresholds'):
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self.daemon_instance.radio.set_custom_cad_thresholds(peak=peak, min_val=min_val)
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logger.info(f"Applied CAD settings to radio: peak={peak}, min={min_val}")
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# Update the in-memory config
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if "radio" not in self.config:
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self.config["radio"] = {}
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if "cad" not in self.config["radio"]:
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self.config["radio"]["cad"] = {}
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self.config["radio"]["cad"]["peak_threshold"] = peak
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self.config["radio"]["cad"]["min_threshold"] = min_val
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# Save to config file
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config_path = getattr(self, '_config_path', '/etc/pymc_repeater/config.yaml')
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self._save_config_to_file(config_path)
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logger.info(f"Saved CAD settings to config: peak={peak}, min={min_val}, rate={detection_rate:.1f}%")
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return {
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"success": True,
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"message": f"CAD settings saved: peak={peak}, min={min_val}",
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"settings": {"peak": peak, "min_val": min_val, "detection_rate": detection_rate}
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}
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except Exception as e:
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logger.error(f"Error saving CAD settings: {e}")
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return {"success": False, "error": str(e)}
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def _save_config_to_file(self, config_path):
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"""Save current config to YAML file"""
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try:
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import yaml
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import os
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# Ensure directory exists
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os.makedirs(os.path.dirname(config_path), exist_ok=True)
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# Write config to file
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with open(config_path, 'w') as f:
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yaml.dump(self.config, f, default_flow_style=False, indent=2)
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logger.info(f"Configuration saved to {config_path}")
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except Exception as e:
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logger.error(f"Failed to save config to {config_path}: {e}")
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raise
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@cherrypy.expose
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def cad_calibration_stream(self):
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"""Server-Sent Events stream for real-time updates"""
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@@ -404,25 +512,62 @@ class APIEndpoints:
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cherrypy.response.headers['Access-Control-Allow-Origin'] = '*'
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def generate():
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# Add client to calibration engine
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response = cherrypy.response
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self.cad_calibration.add_client(response)
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if not hasattr(self.cad_calibration, 'message_queue'):
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self.cad_calibration.message_queue = []
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try:
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# Send initial connection message
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yield f"data: {json.dumps({'type': 'connected', 'message': 'Connected to CAD calibration stream'})}\n\n"
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# Keep connection alive - the calibration engine will send data
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if self.cad_calibration.running:
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config = getattr(self.cad_calibration.daemon_instance, 'config', {})
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radio_config = config.get("radio", {})
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sf = radio_config.get("spreading_factor", 8)
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peak_range, min_range = self.cad_calibration.get_test_ranges(sf)
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total_tests = len(peak_range) * len(min_range)
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status_message = {
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"type": "status",
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"message": f"Calibration in progress: SF{sf}, {total_tests} tests",
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"test_ranges": {
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"peak_min": min(peak_range),
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"peak_max": max(peak_range),
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"min_min": min(min_range),
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"min_max": max(min_range),
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"spreading_factor": sf,
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"total_tests": total_tests
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}
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}
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yield f"data: {json.dumps(status_message)}\n\n"
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last_message_index = len(self.cad_calibration.message_queue)
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while True:
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time.sleep(1)
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# Send keepalive every second
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yield f"data: {json.dumps({'type': 'keepalive'})}\n\n"
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current_queue_length = len(self.cad_calibration.message_queue)
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if current_queue_length > last_message_index:
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for i in range(last_message_index, current_queue_length):
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message = self.cad_calibration.message_queue[i]
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yield f"data: {json.dumps(message)}\n\n"
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last_message_index = current_queue_length
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else:
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yield f"data: {json.dumps({'type': 'keepalive'})}\n\n"
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time.sleep(0.5)
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except Exception as e:
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logger.error(f"SSE stream error: {e}")
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finally:
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# Remove client when connection closes
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self.cad_calibration.remove_client(response)
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pass
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return generate()
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@@ -443,6 +588,7 @@ class StatsApp:
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config: Optional[dict] = None,
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event_loop=None,
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daemon_instance=None,
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config_path=None,
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):
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self.stats_getter = stats_getter
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@@ -453,7 +599,7 @@ class StatsApp:
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self.config = config or {}
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# Create nested API object for routing
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self.api = APIEndpoints(stats_getter, send_advert_func, self.config, event_loop, daemon_instance)
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self.api = APIEndpoints(stats_getter, send_advert_func, self.config, event_loop, daemon_instance, config_path)
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# Load template on init
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if template_dir:
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@@ -671,12 +817,13 @@ class HTTPStatsServer:
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config: Optional[dict] = None,
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event_loop=None,
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daemon_instance=None,
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config_path=None,
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):
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self.host = host
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self.port = port
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self.app = StatsApp(
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stats_getter, template_dir, node_name, pub_key, send_advert_func, config, event_loop, daemon_instance
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stats_getter, template_dir, node_name, pub_key, send_advert_func, config, event_loop, daemon_instance, config_path
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)
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def start(self):
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+13
-12
@@ -12,12 +12,6 @@ from pymc_core.protocol.constants import MAX_PATH_SIZE, ROUTE_TYPE_DIRECT
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logger = logging.getLogger("RepeaterDaemon")
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|
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|
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|
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logger = logging.getLogger("RepeaterDaemon")
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class RepeaterDaemon:
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def __init__(self, config: dict, radio=None):
|
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@@ -53,8 +47,13 @@ class RepeaterDaemon:
|
||||
|
||||
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if hasattr(self.radio, 'set_custom_cad_thresholds'):
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self.radio.set_custom_cad_thresholds(peak=23, min_val=11)
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logger.info("CAD thresholds set: peak=23, min=11")
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# Load CAD settings from config, with defaults
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||||
cad_config = self.config.get("radio", {}).get("cad", {})
|
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peak_threshold = cad_config.get("peak_threshold", 23)
|
||||
min_threshold = cad_config.get("min_threshold", 11)
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||||
|
||||
self.radio.set_custom_cad_thresholds(peak=peak_threshold, min_val=min_threshold)
|
||||
logger.info(f"CAD thresholds set from config: peak={peak_threshold}, min={min_threshold}")
|
||||
else:
|
||||
logger.warning("Radio does not support CAD configuration")
|
||||
|
||||
@@ -361,7 +360,6 @@ class RepeaterDaemon:
|
||||
else:
|
||||
pub_key_formatted = pub_key_hex
|
||||
|
||||
# Get the current event loop (the main loop where the radio was initialized)
|
||||
current_loop = asyncio.get_event_loop()
|
||||
|
||||
self.http_server = HTTPStatsServer(
|
||||
@@ -372,9 +370,10 @@ class RepeaterDaemon:
|
||||
node_name=node_name,
|
||||
pub_key=pub_key_formatted,
|
||||
send_advert_func=self.send_advert,
|
||||
config=self.config, # Pass the config reference
|
||||
event_loop=current_loop, # Pass the main event loop
|
||||
daemon_instance=self, # Pass the daemon instance for CAD calibration
|
||||
config=self.config,
|
||||
event_loop=current_loop,
|
||||
daemon_instance=self,
|
||||
config_path=getattr(self, 'config_path', '/etc/pymc_repeater/config.yaml'),
|
||||
)
|
||||
|
||||
try:
|
||||
@@ -410,12 +409,14 @@ def main():
|
||||
|
||||
# Load configuration
|
||||
config = load_config(args.config)
|
||||
config_path = args.config if args.config else '/etc/pymc_repeater/config.yaml'
|
||||
|
||||
if args.log_level:
|
||||
config["logging"]["level"] = args.log_level
|
||||
|
||||
# Don't initialize radio here - it will be done inside the async event loop
|
||||
daemon = RepeaterDaemon(config, radio=None)
|
||||
daemon.config_path = config_path
|
||||
|
||||
# Run
|
||||
try:
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -26,7 +26,7 @@
|
||||
<div class="info-box" style="background: var(--accent-color); color: white; border: none;">
|
||||
<strong>CAD Calibration Tool Available</strong>
|
||||
<p style="margin: 8px 0 0 0;">
|
||||
Optimize your Channel Activity Detection settings for better mesh performance.
|
||||
Optimize your Channel Activity Detection settings.
|
||||
<a href="/cad-calibration" style="color: white; text-decoration: underline;">Launch CAD Calibration Tool →</a>
|
||||
</p>
|
||||
</div>
|
||||
|
||||
Reference in New Issue
Block a user