>>>importnumpyasnp>>>fromscipyimportsignal>>>importmatplotlib.pyplotasplt >>>x = np.linspace(0,10,20, endpoint=False)>>>y = np.cos(-x**2/6.0)>>>f_fft = signal.resample(y,100)>>>f_poly = signal.resample_poly(y,100,20)>>>xnew = np.linspace(0,10,100, endpoint=False) >>...
python import numpy as np import matplotlib.pyplot as plt from scipy.signal import resample_poly # 生成一个示例信号,例如一个正弦波 fs_original = 100 # 原始采样频率 t_original = np.linspace(0, 1, fs_original, endpoint=False) signal_original = np.sin(2 * np.pi * 5 * t_original) # ...
在循环中,我们首先从输入流中读取音频数据,然后将其转换为numpy数组。接下来,我们使用scipy库的signal.resample_poly函数对音频数据进行音调变换。最后,我们将变换后的音频数据转换为字节流,并写入输出流中。 甘特图 以下是本教程中实现实时变声的甘特图:
SciPy 有大量的信号处理方法。这里最相关的是decimate和resample_poly。我在下面使用后者 from scipy.signal import resample_poly factors = [(1, 2), (1, 2), (2, 1)] for k in range(3): array = resample_poly(array, factors[k][0], factors[k][1], axis=k) 因素(必须是整数)是上采样和下...
使用scipy库改变音频信号的基频audio_signal_changed=scipy.signal.resample_poly(audio_signal,int(sample_rate),int(sample_rate*(new_pitch/pitch)))# 将音频信号转换为音频文件output_audio_file='./changed_audio.wav'librosa.output.write_wav(output_audio_file,audio_signal_changed,sample_rate)# 可视化结果...
>>> points = 100 >>> a = 4.0 >>> vec2 = signal.ricker(points, a) >>> print(len(vec2)) 100 >>> plt.plot(vec2) >>> plt.show()相关用法 Python SciPy signal.residue用法及代码示例 Python SciPy signal.residuez用法及代码示例 Python SciPy signal.resample_poly用法及代码示例 Python ...
知乎学术咨询:https://www.zhihu.com/consult/people/792359672131756032?isMe=1 担任《Mechanical System and Signal Processing》等审稿专家,擅长领域:现代信号处理,机器学习,深度学习,数字孪生,时间序列分析,设备缺陷检测、设备异常检测、设备智能故障诊断与健康管理PHM等。
_datapoint = polynomial.fit_transform(datapoint) poly_linear_model = linear_model.LinearRegression() poly_linear_model.fit(X_train_transformed, y_train) print("\nLinear regression:\n", reg_linear_mul.predict(datapoint)) print("\nPolynomial regression:\n", poly_linear_model.predict(poly_...
(degree=2) X_train_poly = polynomial_features.fit_transform(X_train) X_test_poly = polynomial_features.transform(X_test) model_poly = LinearRegression() model_poly.fit(X_train_poly, y_train) y_pred_poly = model_poly.predict(X_test_poly) # 评估模型 mse_linear = mean_squared_error(y...
y = signal.resample_poly(x,up,down)--类似于MATLAB 中的resample 函数。x表示需重新 采样的数据,参数up表示目标采样率,down表示当前采样率。 参考例程: %对简单的线性序列进行为原采样率3/2倍的重采样 from scipy import signal # 从scipy库中导入signal模块 x = [i for i in range(1,11)] # 构建[...