ruff formatting

Author: jscheidtmann

python/PiFinder/server.py

@@ -851,26 +851,39 @@ def list_log_configs():
             import glob
 
             configs = []
-            active = os.path.realpath("pifinder_logconf.json") if os.path.exists("pifinder_logconf.json") else None
+            active = (
+                os.path.realpath("pifinder_logconf.json")
+                if os.path.exists("pifinder_logconf.json")
+                else None
+            )
             for path in sorted(glob.glob("logconf_*.json")):
-                stem = path[len("logconf_"):-len(".json")]
+                stem = path[len("logconf_") : -len(".json")]
                 display = stem.replace("_", " ").title()
-                configs.append({
-                    "file": path,
-                    "name": display,
-                    "active": os.path.realpath(path) == active,
-                })
+                configs.append(
+                    {
+                        "file": path,
+                        "name": display,
+                        "active": os.path.realpath(path) == active,
+                    }
+                )
             return {"configs": configs}
 
         @app.route("/logs/switch_config", method="post")
         @auth_required
         def switch_log_config():
             """Atomically repoint pifinder_logconf.json to the chosen config, then restart."""
             logconf_file = request.forms.get("logconf_file", "").strip()
-            if not logconf_file or not logconf_file.startswith("logconf_") or not logconf_file.endswith(".json"):
+            if (
+                not logconf_file
+                or not logconf_file.startswith("logconf_")
+                or not logconf_file.endswith(".json")
+            ):
                 return {"status": "error", "message": "Invalid log config file name"}
             if not os.path.exists(logconf_file):
-                return {"status": "error", "message": f"Log config file not found: {logconf_file}"}
+                return {
+                    "status": "error",
+                    "message": f"Log config file not found: {logconf_file}",
+                }
             try:
                 link = "pifinder_logconf.json"
                 tmp = link + ".tmp"
@@ -891,9 +904,15 @@ def upload_log_config():
                 return {"status": "error", "message": "No file provided"}
             filename = upload.filename
             if not filename.startswith("logconf_") or not filename.endswith(".json"):
-                return {"status": "error", "message": "File must be named logconf_<name>.json"}
+                return {
+                    "status": "error",
+                    "message": "File must be named logconf_<name>.json",
+                }
             if os.path.exists(filename):
-                return {"status": "error", "message": f"File already exists: {filename}"}
+                return {
+                    "status": "error",
+                    "message": f"File already exists: {filename}",
+                }
             try:
                 upload.save(filename, overwrite=False)
                 logger.info("Uploaded log config: %s", filename)

python/PiFinder/sqm/save_sweep_metadata.py

@@ -80,7 +80,8 @@ def save_sweep_metadata(
     # Noise floor estimation details (from NoiseFloorEstimator)
     if noise_floor_details is not None:
         metadata["noise_floor_estimator"] = {
-            k: v for k, v in noise_floor_details.items()
+            k: v
+            for k, v in noise_floor_details.items()
             if k != "request_zero_sec_sample"  # Exclude internal flags
         }
         if camera_type is not None:

python/PiFinder/sqm/sqm.py

@@ -65,7 +65,9 @@ def _load_calibration(self) -> bool:
         )
 
         if not calibration_file.exists():
-            logger.debug(f"No calibration file found at {calibration_file}, using defaults")
+            logger.debug(
+                f"No calibration file found at {calibration_file}, using defaults"
+            )
             return False
 
         try:
@@ -193,7 +195,9 @@ def _measure_star_flux_with_local_background(
 
             # Check for saturation in aperture
             aperture_pixels = image_patch[aperture_mask]
-            max_aperture_pixel = np.max(aperture_pixels) if len(aperture_pixels) > 0 else 0
+            max_aperture_pixel = (
+                np.max(aperture_pixels) if len(aperture_pixels) > 0 else 0
+            )
 
             if max_aperture_pixel >= saturation_threshold:
                 # Mark saturated star with flux=-1 to be excluded from mzero calculation
@@ -202,7 +206,6 @@ def _measure_star_flux_with_local_background(
                 n_saturated += 1
                 continue
 
-
             # Total flux in aperture (includes background)
             total_flux = np.sum(aperture_pixels)
 
@@ -263,9 +266,7 @@ def _calculate_mzero(
         # Flux-weighted mean: brighter stars contribute more
         valid_mzeros_arr = np.array(valid_mzeros)
         valid_fluxes_arr = np.array(valid_fluxes)
-        weighted_mzero = float(
-            np.average(valid_mzeros_arr, weights=valid_fluxes_arr)
-        )
+        weighted_mzero = float(np.average(valid_mzeros_arr, weights=valid_fluxes_arr))
 
         return weighted_mzero, mzeros
 
@@ -540,7 +541,9 @@ def calculate(
         # Following ASTAP: zenith is reference point where extinction = 0
         # Only ADDITIONAL extinction below zenith is added: 0.28 * (airmass - 1)
         # This allows comparing measurements at different altitudes
-        extinction_for_altitude = self._atmospheric_extinction(altitude_deg)  # 0.28*(airmass-1)
+        extinction_for_altitude = self._atmospheric_extinction(
+            altitude_deg
+        )  # 0.28*(airmass-1)
 
         # Main SQM value: no extinction correction (raw measurement)
         sqm_final = sqm_uncorrected

python/PiFinder/ui/sqm.py

@@ -262,7 +262,9 @@ def _is_calibrated(self) -> bool:
         camera_type = self.shared_state.camera_type()
         camera_type_processed = f"{camera_type}_processed"
         calibration_file = (
-            Path.home() / "PiFinder_data" / f"sqm_calibration_{camera_type_processed}.json"
+            Path.home()
+            / "PiFinder_data"
+            / f"sqm_calibration_{camera_type_processed}.json"
         )
         return calibration_file.exists()
 

python/PiFinder/ui/sqm_calibration.py

@@ -701,7 +701,9 @@ def _analyze_calibration(self):
             # 2. Compute read noise using temporal variance (not spatial)
             # Spatial std includes fixed pattern noise (PRNU), which is wrong.
             # Temporal variance at each pixel measures true read noise.
-            temporal_variance = np.var(bias_stack, axis=0)  # variance across frames per pixel
+            temporal_variance = np.var(
+                bias_stack, axis=0
+            )  # variance across frames per pixel
             self.read_noise = float(np.sqrt(np.mean(temporal_variance)))
 
             # 3. Compute dark current rate

python/PiFinder/ui/sqm_sweep.py

@@ -288,7 +288,8 @@ def _add_detailed_metadata(self):
             # Find the sweep directory
             captures_dir = Path(utils.data_dir) / "captures"
             sweep_dirs = [
-                d for d in captures_dir.glob("sweep_*")
+                d
+                for d in captures_dir.glob("sweep_*")
                 if d.stat().st_ctime >= (self.start_time - 1)
             ]
             if not sweep_dirs:
@@ -313,7 +314,8 @@ def _add_detailed_metadata(self):
                     "pifinder_value": sqm_state.value,
                     "reference_value": self.reference_sqm,
                     "difference": (self.reference_sqm - sqm_state.value)
-                                  if self.reference_sqm and sqm_state.value else None,
+                    if self.reference_sqm and sqm_state.value
+                    else None,
                     "source": sqm_state.source,
                 }
 
@@ -327,7 +329,8 @@ def _add_detailed_metadata(self):
             if image_metadata:
                 metadata["image"] = {
                     "exposure_us": image_metadata.get("exposure_time"),
-                    "exposure_sec": image_metadata.get("exposure_time", 0) / 1_000_000.0,
+                    "exposure_sec": image_metadata.get("exposure_time", 0)
+                    / 1_000_000.0,
                     "gain": image_metadata.get("gain"),
                     "imu_delta": image_metadata.get("imu_delta"),
                 }
@@ -348,8 +351,11 @@ def _add_detailed_metadata(self):
             # Add NoiseFloorEstimator output
             camera_type = self.shared_state.camera_type()
             camera_type_processed = f"{camera_type}_processed"
-            exposure_sec = (image_metadata.get("exposure_time", 500000) / 1_000_000.0
-                          if image_metadata else 0.5)
+            exposure_sec = (
+                image_metadata.get("exposure_time", 500000) / 1_000_000.0
+                if image_metadata
+                else 0.5
+            )
 
             if self.camera_image is not None:
                 image_array = np.array(self.camera_image.convert("L"))

python/tests/test_sqm.py

@@ -256,7 +256,9 @@ def test_calculate_extinction_applied(self):
 
         # Check extinction values (ASTAP convention: 0 at zenith)
         # Pickering airmass at 30° ≈ 1.995, so extinction ≈ 0.28 * 0.995 ≈ 0.279
-        assert details_zenith["extinction_for_altitude"] == pytest.approx(0.0, abs=0.001)
+        assert details_zenith["extinction_for_altitude"] == pytest.approx(
+            0.0, abs=0.001
+        )
         expected_ext_30 = 0.28 * (sqm._pickering_airmass(30.0) - 1)
         assert details_30deg["extinction_for_altitude"] == pytest.approx(
             expected_ext_30, abs=0.001