# SciPy_Wav

reference: https://officeguide.cc/python-scipy-read-wav-file-plot-waveform-spectrum-spectrogram-tutorial-examples/

Colab:
https://colab.research.google.com/drive/1ZvrP-rLa4cfD6eLht-kVIzJKNuQ9gnJ3?usp=sharing

SciPy:
---

- Import:
- `from scipy.io.wavfile import read`
- Load wav:
- `rate, data = read("bubbs.wav")`
- Show:
- frequency:
- `print("Sample rate: {} Hz".format(rate))`
- data type:
- `print("Data type: {}".format(data.dtype))`
- Draw:
- waveform

        import matplotlib.pyplot as plt
        # 繪製前 1024 點資料的波形圖
        plt.figure(figsize=(15, 5))
        plt.plot(data[0:1024])
        plt.show()

- spectrum

        # 傅立葉轉換
        from scipy.fftpack import fft
        dataFFT = fft(data[0:1024])
        dataFFTAbs = abs(dataFFT[1:512])

        # 繪製頻譜圖
        plt.figure(figsize=(15, 5))
        plt.plot(dataFFTAbs, 'r')
        plt.show()

- spectrogram

        import matplotlib.pyplot as plt
        import numpy as np

        # 產生時間資料
        time = np.arange(0, len(data)) / rate

        plt.figure(figsize=(15, 5))

        # 繪製波形圖
        plotA = plt.subplot(211)
        plotA.plot(time, data)
        plotA.set_ylabel("Amplitude")
        plotA.set_xlim(0, len(data) / rate)

        # 繪製時頻譜圖
        plotB = plt.subplot(212)
        plotB.specgram(data, NFFT=1024, Fs=rate, noverlap=900)
        plotB.set_ylabel("Frequency")
        plotB.set_xlabel("Time")

        plt.show()