fix: divide by zero in log10

plot_utils.py

@@ -0,0 +1,41 @@
+import numpy as np
+import torch
+from scipy.signal import freqz
+from typing import Iterable
+
+from modules import fx
+from modules.functional import (
+    highpass_biquad_coef,
+    lowpass_biquad_coef,
+    highshelf_biquad_coef,
+    lowshelf_biquad_coef,
+    equalizer_biquad_coef,
+)
+
+
+def get_log_mags_from_eq(eq: Iterable, worN=1024, sr=44100):
+    get_ba = lambda xs: torch.cat([x.view(1) for x in xs]).view(2, 3)
+
+    def f(biquad):
+        params = biquad.params
+        match type(biquad):
+            case fx.HighPass:
+                coeffs = highpass_biquad_coef(sr, params.freq, params.Q)
+            case fx.LowPass:
+                coeffs = lowpass_biquad_coef(sr, params.freq, params.Q)
+            case fx.HighShelf:
+                coeffs = highshelf_biquad_coef(sr, params.freq, params.gain, biquad.Q)
+            case fx.LowShelf:
+                coeffs = lowshelf_biquad_coef(sr, params.freq, params.gain, biquad.Q)
+            case fx.Peak:
+                coeffs = equalizer_biquad_coef(sr, params.freq, params.gain, params.Q)
+            case _:
+                raise ValueError(biquad)
+
+        b, a = get_ba(coeffs)
+        w, h = freqz(b.numpy(), a.numpy(), worN, fs=sr)
+        log_h = 20 * np.log10(np.abs(h) + 1e-10)
+        return w, log_h
+
+    log_mags = list(map(f, eq))
+    return log_mags[0][0], [x for _, x in log_mags]