76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
import json
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import os
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import tempfile
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import numpy as np
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import pytest
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from pathlib import Path
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from fft_analysis import io_utils
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def test_load_audio_file_wav(monkeypatch):
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# Mock scipy.io.wavfile.read to return synthetic data
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import scipy.io.wavfile as wavfile
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sample_rate = 44100
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data = np.array([0, 32767, -32768], dtype=np.int16)
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def mock_read(file_path):
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assert isinstance(file_path, (str, Path))
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return sample_rate, data
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monkeypatch.setattr(wavfile, 'read', mock_read)
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arr, sr = io_utils.load_audio_file("dummy.wav")
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assert isinstance(arr, np.ndarray)
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assert sr == sample_rate
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assert np.allclose(arr, data.astype(np.float32) / np.max(np.abs(data)))
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def test_load_audio_file_invalid_path():
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with pytest.raises(FileNotFoundError):
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io_utils.load_audio_file("nonexistent_path.wav")
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def test_save_spectrum_to_json_and_verify(tmp_path):
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spectrum = np.array([0.1, 0.5, 0.9, 0.2])
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output_file = tmp_path / "spectrum.json"
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io_utils.save_spectrum_to_json(spectrum, str(output_file))
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assert output_file.exists()
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with open(output_file, "r", encoding="utf-8") as f:
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data = json.load(f)
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assert isinstance(data, dict)
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assert 'frequencies' in data and 'magnitudes' in data
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assert isinstance(data['frequencies'], list)
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assert isinstance(data['magnitudes'], list)
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assert len(data['frequencies']) == len(data['magnitudes']) == len(spectrum)
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def test_save_spectrum_to_json_invalid_path():
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spectrum = np.array([0.1, 0.2, 0.3])
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invalid_path = "/invalid_directory/output.json"
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with pytest.raises((OSError, IOError)):
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io_utils.save_spectrum_to_json(spectrum, invalid_path)
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def test_load_audio_file_normalization(monkeypatch):
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import scipy.io.wavfile as wavfile
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sample_rate = 48000
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data = np.array([0, 1000, -1000], dtype=np.int16)
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def mock_read(file_path):
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return sample_rate, data
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monkeypatch.setattr(wavfile, 'read', mock_read)
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arr, sr = io_utils.load_audio_file("file.wav")
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assert sr == sample_rate
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assert np.isclose(np.max(arr), 1.0, atol=0.01) or np.isclose(np.max(arr), 0.0)
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assert np.isclose(np.min(arr), -1.0, atol=0.01) or np.isclose(np.min(arr), 0.0)
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