python - 如何修复错误'AttributeError：'list'对象没有属性'shape'？

Question

我有一个 1 和 0 的数组，所以基本上我有一个方波，我想平滑它。总变量是我调用 Savitzky Golay 函数过滤的数据，我不断收到此错误：

File "<ipython-input-45-d4d2478bab0e>", line 1, in <module>

  Zf = sgolay2d( total, window_size=29, order=3)


File "<ipython-input-44-545942e8da4f>", line 34, in sgolay2d

  new_shape = z.shape[0] + 2*half_size, z.shape[1] + 2*half_size


AttributeError: 'list' object has no attribute 'shape'

我的数据是：

 total = [0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1]

''''''''''''''''''''''''''''''

该代码包含定义函数并调用它并绘制它。但是，它不接受数组的格式（我认为）！。有小费吗？

  def sgolay2d ( z, window_size, order, derivative=None):

    """
    """
    # number of terms in the polynomial expression
    n_terms = ( order + 1 ) * ( order + 2)  / 2.0

    if  window_size % 2 == 0:
        raise ValueError('window_size must be odd')

    if window_size**2 < n_terms:
        raise ValueError('order is too high for the window size')

    half_size = window_size // 2

    # exponents of the polynomial. 
    # p(x,y) = a0 + a1*x + a2*y + a3*x^2 + a4*y^2 + a5*x*y + ... 
    # this line gives a list of two item tuple. Each tuple contains 
    # the exponents of the k-th term. First element of tuple is for x
    # second element for y.
    # Ex. exps = [(0,0), (1,0), (0,1), (2,0), (1,1), (0,2), ...]
    exps = [ (k-n, n) for k in range(order+1) for n in range(k+1) ]

    # coordinates of points
    ind = np.arange(-half_size, half_size+1, dtype=np.float64)
    dx = np.repeat( ind, window_size )
    dy = np.tile( ind, [window_size, 1]).reshape(window_size**2, )

    # build matrix of system of equation
    A = np.empty( (window_size**2, len(exps)) )
    for i, exp in enumerate( exps ):
        A[:,i] = (dx**exp[0]) * (dy**exp[1])

    # pad input array with appropriate values at the four borders
    new_shape = z.shape[0] + 2*half_size, z.shape[1] + 2*half_size
    Z = np.zeros( (new_shape) )
    # top band
    band = z[0, :]
    Z[:half_size, half_size:-half_size] =  band -  np.abs( np.flipud( 
    z[1:half_size+1, :] ) - band )
    # bottom band
    band = z[-1, :]
    Z[-half_size:, half_size:-half_size] = band  + np.abs( np.flipud( z[- 
    half_size-1:-1, :] )  -band )
    # left band
    band = np.tile( z[:,0].reshape(-1,1), [1,half_size])
    Z[half_size:-half_size, :half_size] = band - np.abs( np.fliplr( z[:, 
    1:half_size+1] ) - band )
    # right band
    band = np.tile( z[:,-1].reshape(-1,1), [1,half_size] )
    Z[half_size:-half_size, -half_size:] =  band + np.abs( np.fliplr( z[:, 
  -half_size-1:-1] ) - band )
    # central band
    Z[half_size:-half_size, half_size:-half_size] = z

    # top left corner
    band = z[0,0]
    Z[:half_size,:half_size] = band - np.abs( 
    np.flipud(np.fliplr(z[1:half_size+1,1:half_size+1]) ) - band )
    # bottom right corner
    band = z[-1,-1]
    Z[-half_size:,-half_size:] = band + np.abs( np.flipud(np.fliplr(z[- 
    half_size-1:-1,-half_size-1:-1]) ) - band )

    # top right corner
    band = Z[half_size,-half_size:]
    Z[:half_size,-half_size:] = band - np.abs( 
    np.flipud(Z[half_size+1:2*half_size+1,-half_size:]) - band )
    # bottom left corner
    band = Z[-half_size:,half_size].reshape(-1,1)
    Z[-half_size:,:half_size] = band - np.abs( np.fliplr(Z[-half_size:, 
    half_size+1:2*half_size+1]) - band )

    # solve system and convolve
    if derivative == None:
        m = np.linalg.pinv(A)[0].reshape((window_size, -1))
        return scipy.signal.fftconvolve(Z, m, mode='valid')
    elif derivative == 'col':
        c = np.linalg.pinv(A)[1].reshape((window_size, -1))
        return scipy.signal.fftconvolve(Z, -c, mode='valid')
    elif derivative == 'row':
        r = np.linalg.pinv(A)[2].reshape((window_size, -1))
        return scipy.signal.fftconvolve(Z, -r, mode='valid')
    elif derivative == 'both':
        c = np.linalg.pinv(A)[1].reshape((window_size, -1))
        r = np.linalg.pinv(A)[2].reshape((window_size, -1))
        return scipy.signal.fftconvolve(Z, -r, mode='valid'), 
        scipy.signal.fftconvolve(Z, -c, mode='valid')

##########
Zf = sgolay2d( total, window_size=29, order=3)
plt.plot(total)
plt.ylabel('amp')
plt.xlabel('Frames')
plt.show()

标签： pythonsignal-processing