Convert matlab zeros function to Python equivalent

Hi Could you pleas elet me know what would be a similar conversion of matlab zeros to np.zeros for datatype. I am getting an error while doing this.

Matlab code:

Shifts = zeros(length(Filters)-1,1,'int16');

Python code:

Shifts = np.zeros(len(Filters)-1,1,dtype = np.int16)

[Raghunandan V]

Hey,

I tried the same. It works!

[Prb]

I am not quite sure why it isn't working for me!

[Rik]

You should post this to a python forum.

[Murugan C]

hi,

I think we have to create zeros as like below syntax.

Shifts = np.zeros(len(Filters)-1,dtype = np.int16)

[Prb]

It took only the negative dimensions and which is not allowed.

[Murugan C]

What is size of the Filters. If lenght of "Filters" is empty or zeros, then only you will get negative dimensitons.

>>> import numpy

>>> Filters = [ ]

>>> Shifts = numpy.zeros(len(Filters)-1,dtype = numpy.int16)

Traceback (most recent call last):

File "<pyshell#20>", line 1, in <module>

Shifts = numpy.zeros(len(Filters)-1,dtype = numpy.int16)

ValueError: negative dimensions are not allowed

>>>

%%

>>> Filters = [5, 6, 4, 5,6]

>>> Shifts = numpy.zeros(len(Filters)-1,dtype = numpy.int16)

>>> Shifts

array([0, 0, 0, 0], dtype=int16)

Answer 1

[Stephen23]

You need to read the numpy zeros documentation, because your syntax does not actually match its specification:

import numpy as np
Filters = [1,2,3];
Shifts = np.zeros((len(Filters)-1,1),dtype=np.int16)
%                 ^                ^ The shape needs to be ONE iterable!

Most likely you do not need a 2D numpy array, and a simple 1D array would suffice:

Shifts = np.zeros(len(Filters)-1,dtype=np.int16)