Initialize empty matrix in Python

I am trying to convert a MATLAB code in Python. I don't know how to initialize empty matrix in Python.

MATLAB Code:

demod4(1) = [];

I tried in Python

demod4[0] = array([])

but it gives error:

only length-1 arrays can be converted to Python scalars

If you are using numpy arrays, you initialize to 0, by specifying the expected matrix size:

import numpy as np
d = np.zeros((2,3))

>>> d
    [[ 0.  0.  0.]
     [ 0.  0.  0.]]

This would be the equivalent of MATLAB 's:

d = zeros(2,3);

You can also initialize an empty array, again using the expected dimensions/size

d = np.empty((2,3))

If you are not using numpy, the closest somewhat equivalent to MATLAB's d = [] (i.e., a zero-size matrix) would be using an empty list and then

append values (for filling a vector)

d = []
d.append(0)
d.append(1)
>>> d                                                                     
[0, 1]

or append lists (for filling a matrix row or column):

d = []                                                                
d.append(range(0,2))                                                    
d.append(range(2,4))                                                  
>>> d                                                                     
[[0, 1], [2, 3]]

See also:

initialize a numpy array (SO)

NumPy array initialization (fill with identical values) (SO)

How do I create an empty array/matrix in NumPy? (SO)

NumPy for MATLAB users

You could use a nested list comprehension:

# size of matrix n x m
matrix = [ [ 0 for i in range(n) ] for j in range(m) ]

What about initializing a list, populating it, then converting to an array.

demod4 = []  

Or, you could just populate at initialization using a list comprehension

demod4 = [[func(i, j) for j in range(M)] for i in range(N)]

Or, you could initialize an array of all zeros if you know the size of the array ahead of time.

demod4 = [[0 for j in range(M)] for i in range(N)]

or

demod4 = [[0 for i in range(M)]*N]

Or try using numpy.

import numpy as np

N, M = 100, 5000
np.zeros((N, M))