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style: apply ruff-format to entire codebase

Browse Source 
First-time run of ruff-format via pre-commit hook normalises quote
style, trailing commas, and whitespace across 188 Python files.
No logic changes.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
James Smith
2026-07-05 14:48:11 +01:00
parent 82e64104fe
commit 96172ca593
189 changed files with 19883 additions and 19552 deletions
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utils/sstv/dsp.py
+16 -15
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@@ -18,8 +18,7 @@ from .constants import (
)
def goertzel(samples: np.ndarray, target_freq: float,
sample_rate: int = SAMPLE_RATE) -> float:
def goertzel(samples: np.ndarray, target_freq: float, sample_rate: int = SAMPLE_RATE) -> float:
"""Compute Goertzel energy at a single target frequency.
O(N) per frequency - more efficient than FFT when only a few
@@ -56,8 +55,7 @@ def goertzel(samples: np.ndarray, target_freq: float,
return s1 * s1 + s2 * s2 - coeff * s1 * s2
def goertzel_mag(samples: np.ndarray, target_freq: float,
sample_rate: int = SAMPLE_RATE) -> float:
def goertzel_mag(samples: np.ndarray, target_freq: float, sample_rate: int = SAMPLE_RATE) -> float:
"""Compute Goertzel magnitude (square root of energy).
Args:
@@ -71,8 +69,9 @@ def goertzel_mag(samples: np.ndarray, target_freq: float,
return math.sqrt(max(0.0, goertzel(samples, target_freq, sample_rate)))
def detect_tone(samples: np.ndarray, candidates: list[float],
sample_rate: int = SAMPLE_RATE) -> tuple[float | None, float]:
def detect_tone(
samples: np.ndarray, candidates: list[float], sample_rate: int = SAMPLE_RATE
) -> tuple[float | None, float]:
"""Detect which candidate frequency has the strongest energy.
Args:
@@ -98,16 +97,20 @@ def detect_tone(samples: np.ndarray, candidates: list[float],
others = [e for f, e in energies.items() if f != max_freq]
avg_others = sum(others) / len(others) if others else 0.0
ratio = max_energy / avg_others if avg_others > 0 else float('inf')
ratio = max_energy / avg_others if avg_others > 0 else float("inf")
if ratio >= MIN_ENERGY_RATIO:
return max_freq, ratio
return None, ratio
def estimate_frequency(samples: np.ndarray, freq_low: float = 1000.0,
freq_high: float = 2500.0, step: float = 25.0,
sample_rate: int = SAMPLE_RATE) -> float:
def estimate_frequency(
samples: np.ndarray,
freq_low: float = 1000.0,
freq_high: float = 2500.0,
step: float = 25.0,
sample_rate: int = SAMPLE_RATE,
) -> float:
"""Estimate the dominant frequency in a range using Goertzel sweep.
Sweeps through frequencies in the given range and returns the one
@@ -168,8 +171,7 @@ def freq_to_pixel(frequency: float) -> int:
return max(0, min(255, int(normalized * 255 + 0.5)))
def samples_for_duration(duration_s: float,
sample_rate: int = SAMPLE_RATE) -> int:
def samples_for_duration(duration_s: float, sample_rate: int = SAMPLE_RATE) -> int:
"""Calculate number of samples for a given duration.
Args:
@@ -182,8 +184,7 @@ def samples_for_duration(duration_s: float,
return int(duration_s * sample_rate + 0.5)
def goertzel_batch(audio_matrix: np.ndarray, frequencies: np.ndarray,
sample_rate: int = SAMPLE_RATE) -> np.ndarray:
def goertzel_batch(audio_matrix: np.ndarray, frequencies: np.ndarray, sample_rate: int = SAMPLE_RATE) -> np.ndarray:
"""Compute Goertzel energy for multiple audio segments at multiple frequencies.
Vectorized implementation using numpy broadcasting. Processes all
@@ -212,7 +213,7 @@ def goertzel_batch(audio_matrix: np.ndarray, frequencies: np.ndarray,
s2 = np.zeros_like(s1)
for n in range(N):
samples_n = audio_matrix[:, n:n + 1] # (M, 1) — broadcasts with (M, F)
samples_n = audio_matrix[:, n : n + 1] # (M, 1) — broadcasts with (M, F)
s0 = samples_n + coeff * s1 - s2
s2 = s1
s1 = s0