.

pipeline/download/noise.py

@@ -85,24 +85,24 @@ RESOLUTION = NATIVE_RESOLUTION
 
 # Defra encodes TRUE "no data" with this sentinel (NOT 0.0). A 0.0 cell that is
 # otherwise inside the raster means "modelled below the lowest reporting band",
-# i.e. genuinely quiet — see noise_overlay_tiles.py:167.
+# i.e. genuinely quiet (see noise_overlay_tiles.py:167).
 NOISE_NODATA_SENTINEL = np.float32(-96.0)
 
 # Lowest modelled Defra Lden reporting band (dB). Verified against the actual
 # rasters: the minimum positive in-coverage value is 40.0 dB with NO values in
-# (0, 40) — below the band, cells are encoded as 0.0 (genuinely quiet). We floor
+# (0, 40). Below the band, cells are encoded as 0.0 (genuinely quiet). We floor
 # in-coverage cells to 40.0 so a below-band 0.0 surfaces as "we know it's quiet"
 # (~40 dB) instead of collapsing to null ("we don't know"), WITHOUT inflating the
 # ~35% of genuine 40-44.99 dB readings that a 45.0 floor would wrongly bump to 45.
 # NB: 45.0 is the overlay's lowest *paint* stop (noise_overlay_tiles.
-# NOISE_COLOR_STOPS[0]) — a rendering threshold, not the data's reporting floor.
+# NOISE_COLOR_STOPS[0]), a rendering threshold, not the data's reporting floor.
 NOISE_QUIET_FLOOR_DB = np.float32(40.0)
 
 # Sample noise at the postcode representative point itself (no neighbourhood
 # window). A 50m MAX-of-window grabbed the single loudest 10m cell within ~1.2 ha
 # of every postcode; because Defra road contours hug every modelled road and
 # representative points sit on/near streets, that inflated postcode noise by
-# roughly +9 dB (log scale) — making ~94% of England read >=55 dB Lden and
+# roughly +9 dB (log scale), making ~94% of England read >=55 dB Lden and
 # collapsing the metric's discrimination at the quiet end. Radius 0 ->
 # filter_size 1 -> the maximum_filter is skipped and each postcode reads the
 # 10m cell it actually sits in.
@@ -110,8 +110,8 @@ POSTCODE_NOISE_RADIUS_M = 0
 
 # Adjacent download tiles overlap by the sampling radius so every postcode's
 # sampling footprint is fully contained in at least one tile. With point
-# sampling (radius 0) this is 0 — a representative point falls inside exactly
-# one tile — but the relationship is kept so any future non-zero radius keeps
+# sampling (radius 0) this is 0 (a representative point falls inside exactly
+# one tile), but the relationship is kept so any future non-zero radius keeps
 # its window seam-safe.
 TILE_OVERLAP_M = POSTCODE_NOISE_RADIUS_M
 
@@ -273,7 +273,7 @@ def _download_tile(
             NoGeoTiffError,
             httpx.HTTPStatusError,
             # TransportError is the superset of TimeoutException, ConnectError,
-            # ReadError and ProtocolError — including RemoteProtocolError, raised
+            # ReadError and ProtocolError, including RemoteProtocolError, raised
             # when the WCS server closes the connection mid-stream ("incomplete
             # chunked read"). All are transient; retry/split rather than letting
             # one flaky tile crash the whole raster download.
@@ -446,7 +446,7 @@ def sample_noise_at_postcodes(
             # Defra rasters encode TRUE nodata as the -96.0 sentinel (and
             # occasionally non-finite / dataset.nodata); genuinely quiet ground
             # below the model's lowest reporting band is encoded as 0.0. Only
-            # the former is "we don't know" — the latter is a real "we know it's
+            # the former is "we don't know". The latter is a real "we know it's
             # quiet" reading and must not collapse to null. So treat ONLY true
             # nodata as -inf (it never wins a max and never counts as coverage),
             # and clamp every in-coverage cell up to NOISE_QUIET_FLOOR_DB so a
@@ -555,7 +555,7 @@ def main() -> None:
 
             if not tile_paths:
                 print(
-                    f"[{label}] WARNING: No tiles downloaded — column will be all null"
+                    f"[{label}] WARNING: No tiles downloaded; column will be all null"
                 )
                 series = pl.Series(col_name, [None] * len(lat), dtype=pl.Float32)
             else: