tests, limiter

tests/test_plotting.py

@@ -0,0 +1,96 @@
+import pytest
+from torchvision.transforms import ToPILImage
+from .conftest import TestData
+from ..core.plotting import get_spectogram, get_wave, save_image
+from ..visuals.SignalProcessingSpectrogram import SignalProcessingSpectrogram
+
+TEST_NAME = "plotting"
+
+
+@pytest.mark.parametrize(
+    "n_fft, n_mels, xlim",
+    [
+        (4096, 128 * 1, 8192),
+        (4096, 128 * 2, 8192),
+        (4096, 128 * 4, 8192),
+        (4096, 128 * 6, 8192),
+    ],
+)
+def test_plotting_spectogram_general(
+    test_data: TestData, n_fft: int, n_mels: int, xlim: int
+) -> None:
+
+    waveform = test_data["audio"]["waveform"].squeeze(0)
+    sample_rate = test_data["audio"]["sample_rate"]
+
+    print("waveform", waveform.shape)
+
+    spectogram = get_spectogram(
+        waveform, sample_rate=sample_rate, n_fft=n_fft, n_mels=n_mels, xlim=xlim
+    )
+
+    pest_param_str = test_data["pest_param_str"]
+    output_filepath = test_data["output_root"] / f"{pest_param_str}.png"
+
+    save_image(output_filepath, spectogram)
+
+    assert output_filepath.exists(), f"Output file {output_filepath} was not created."
+    assert output_filepath is not None, "Processed audio output is None."
+
+    print(f"test_plotting_spectogram_general {test_data['output_root']}")
+
+
+@pytest.mark.parametrize(
+    "stretch_factor, window_size_seconds",
+    [(8.0, 0.25)],
+)
+def test_plotting_waveform_general(
+    test_data: TestData, stretch_factor: float, window_size_seconds: float
+) -> None:
+
+    waveform = test_data["audio"]["waveform"].squeeze(0)
+    sample_rate = test_data["audio"]["sample_rate"]
+
+    print("waveform", waveform.shape)
+
+    spectogram = get_wave(waveform, sample_rate=sample_rate, xlim=4096)
+
+    pest_param_str = test_data["pest_param_str"]
+    output_filepath = test_data["output_root"] / f"{pest_param_str}.png"
+
+    save_image(output_filepath, spectogram)
+
+    assert output_filepath.exists(), f"Output file {output_filepath} was not created."
+    assert output_filepath is not None, "Processed audio output is None."
+
+    print(f"test_plotting_spectogram_general {test_data['output_root']}")
+
+
+@pytest.mark.parametrize(
+    "stretch_factor, window_size_seconds",
+    [(8.0, 0.25)],
+)
+def test_plotting_waveform_node_general(
+    test_data: TestData, stretch_factor: float, window_size_seconds: float
+) -> None:
+
+    node = SignalProcessingSpectrogram()
+
+    output = node.process(audio_input=test_data["audio"])[0]
+
+    pest_param_str = test_data["pest_param_str"]
+    output_filepath = test_data["output_root"] / f"{pest_param_str}.png"
+
+    to_pil = ToPILImage()
+    print("rgb_image[0] -----------------------------", output[0].shape)
+    rgb_image = output[0][..., :3]
+    rgb_image = rgb_image.permute(2, 0, 1)
+    print("rgb_image -----------------------------", rgb_image.shape)
+    spectogram = to_pil(rgb_image)
+    print("spectogram -----------------------------", spectogram)
+    save_image(output_filepath, spectogram)
+
+    assert output_filepath.exists(), f"Output file {output_filepath} was not created."
+    assert output is not None, "Processed audio output is None."
+
+    print(f"test_pitch_shift_general {test_data['output_root']}")