convolution of .mat file and 1D array

Question

my code is:

import numpy as np
import scipy.io as spio

x=np.zeros((22113,1),float)

x= spio.loadmat('C:\\Users\\dell\\Desktop\\Rabia Ahmad spring 2016\\'
                'FYP\\1. Matlab Work\\record work\\kk.mat')

print(x)

x = np.reshape(len(x),1);

h = np.array([0.9,0.3,0.1],float)

print(h)

h = h.reshape(len(h),1);

dd = np.convolve(h,x)

and the error I encounter is " ValueError: object too deep for desired array " kindly help me in this reguard.

Answer 1

{'__globals__': [], '__version__': '1.0', 'ans': array([[ 0.13580322,
 0.13580322], [ 0.13638306, 0.13638306], [ 0.13345337, 0.13345337], 
 ..., [ 0.13638306, 0.13638306], [ 0.13345337, 0.13345337], ..., [   
 0.13638306, 0.13638306], [ 0.13345337, 0.13345337], ..., [-0.09136963,    
-0.09136963], [-0.12442017, -0.12442017], [-0.15542603, -0.15542603]])}

See {}? That means x from the loadmat is a dictionary.

x['ans'] will be an array

array([[ 0.13580322,
     0.13580322], [ 0.13638306, 0.13638306], [ 0.13345337, 0.13345337],...]])

which, if I count the [] right is a (n,2) array of floats.

The following line does not make sense:

x = np.reshape(len(x),1);

I suspect you mean x = x.reshape(...) as you do with h . But that would give an error with the dictionary x .

When you say the shape of x is (9,) and its dtype is uint16 - where in your code you verifying that?

Answer 2

x = np.reshape(len(x),1); doesn't do anything useful. That completely discards the data in x, and creates an array of shape (1,) , with the only element being len(x) .

In your code, you reshape h to (3, 1) , which is a 2D array, not a 1D array, which is why convolve complains.

Remove both of your reshape s, and instead just pass squeeze=True to scipy.io.loadmat - this is needed because matlab does not have the concept as 1d arrays, and squeeze tells scipy to try and flatten (N, 1) and (1, N) arrays to (N,) arrays