Add fft_analysis/src/fft_analysis/io_utils.py

fft_analysis/src/fft_analysis/io_utils.py

@@ -0,0 +1,66 @@
+import json
+import os
+from pathlib import Path
+from typing import Tuple, List
+
+import numpy as np
+from scipy.io import wavfile
+
+
+class FFTSpectrum:
+    """Datenmodell für FFT-Spektrumsausgabe."""
+    def __init__(self, frequencies: List[float], magnitudes: List[float]):
+        self.frequencies = frequencies
+        self.magnitudes = magnitudes
+
+    def to_dict(self) -> dict:
+        return {
+            "frequencies": self.frequencies,
+            "magnitudes": self.magnitudes
+        }
+
+
+def load_audio_file(file_path: str) -> Tuple[np.ndarray, int]:
+    """Lädt eine WAV- oder FLAC-Datei als normalisiertes NumPy-Array und gibt (audio_data, sample_rate) zurück."""
+    path = Path(file_path)
+    if not path.exists() or not path.is_file():
+        raise FileNotFoundError(f"Audio file not found: {file_path}")
+
+    if path.suffix.lower() != ".wav":
+        raise ValueError("Only WAV files are supported for this implementation.")
+
+    sample_rate, data = wavfile.read(file_path)
+    if data.ndim > 1:
+        data = np.mean(data, axis=1)
+
+    data = data.astype(np.float32)
+    max_val = np.max(np.abs(data))
+    if max_val > 0:
+        data /= max_val
+
+    assert isinstance(sample_rate, int), "Sample rate must be an integer."
+    assert isinstance(data, np.ndarray), "Audio data must be a NumPy array."
+    return data, sample_rate
+
+
+def save_spectrum_to_json(spectrum: np.ndarray, output_path: str) -> None:
+    """Speichert das Frequenzspektrum als JSON-Datei im FFTSpectrum-Format."""
+    if not isinstance(spectrum, np.ndarray):
+        raise TypeError("Spectrum must be a numpy.ndarray.")
+
+    if spectrum.ndim != 1:
+        raise ValueError("Spectrum must be a 1D numpy array.")
+
+    frequencies = np.fft.fftfreq(len(spectrum)).tolist()
+    magnitudes = np.abs(spectrum).tolist()
+
+    fft_obj = FFTSpectrum(frequencies=frequencies, magnitudes=magnitudes)
+
+    output_dir = os.path.dirname(output_path)
+    if output_dir:
+        os.makedirs(output_dir, exist_ok=True)
+
+    with open(output_path, 'w', encoding='utf-8') as f:
+        json.dump(fft_obj.to_dict(), f, ensure_ascii=False, indent=2)
+
+    assert Path(output_path).exists(), "JSON output file was not created successfully."