matlab里建立缓冲区,在numpy中是否有一个Matlab的缓冲区等价物？

我编写了以下例程来处理我需要的用例，但是我还没有实现/测试“underlap”。在

请随时提出改进建议。在def buffer(X, n, p=0, opt=None):

'''Mimic MATLAB routine to generate buffer array

MATLAB docs here: https://se.mathworks.com/help/signal/ref/buffer.html

Parameters

x: ndarray

Signal array

n: int

Number of data segments

p: int

Number of values to overlap

opt: str

Initial condition options. default sets the first `p` values to zero,

while 'nodelay' begins filling the buffer immediately.

Returns

-

result : (n,n) ndarray

Buffer array created from X

'''

import numpy as np

if opt not in [None, 'nodelay']:

raise ValueError('{} not implemented'.format(opt))

i = 0

first_iter = True

while i < len(X):

if first_iter:

if opt == 'nodelay':

# No zeros at array start

result = X[:n]

i = n

else:

# Start with `p` zeros

result = np.hstack([np.zeros(p), X[:n-p]])

i = n-p

# Make 2D array and pivot

result = np.expand_dims(result, axis=0).T

first_iter = False

continue

# Create next column, add `p` results from last col if given

col = X[i:i+(n-p)]

if p != 0:

col = np.hstack([result[:,-1][-p:], col])

i += n-p

# Append zeros if last row and not length `n`

if len(col) < n:

col = np.hstack([col, np.zeros(n-len(col))])

# Combine result with next row

result = np.hstack([result, np.expand_dims(col, axis=0).T])

return result