`scipy.io.matlab._miobase:matdims`

source: /scipy/io/matlab/_miobase.py :259

Signature

def matdims ( arr , oned_as = column )

Summary

Determine equivalent MATLAB dimensions for given array

Parameters

arr : ndarray: Input array
oned_as : {'column', 'row'}, optional: Whether 1-D arrays are returned as MATLAB row or column matrices. Default is 'column'.

Returns

dims : tuple: Shape tuple, in the form MATLAB expects it.

Notes

We had to decide what shape a 1 dimensional array would be by default. np.atleast_2d thinks it is a row vector. The default for a vector in MATLAB (e.g., >> 1:12) is a row vector.

Versions of scipy up to and including 0.11 resulted (accidentally) in 1-D arrays being read as column vectors. For the moment, we maintain the same tradition here.

Examples

import numpy as np
from scipy.io.matlab._miobase import matdims
matdims(np.array(1)) # NumPy scalar
matdims(np.array([1])) # 1-D array, 1 element
matdims(np.array([1,2])) # 1-D array, 2 elements
matdims(np.array([[2],[3]])) # 2-D array, column vector
matdims(np.array([[2,3]])) # 2-D array, row vector
matdims(np.array([[[2,3]]])) # 3-D array, rowish vector
matdims(np.array([])) # empty 1-D array

✓

matdims(np.array([[]])) # empty 2-D array
matdims(np.array([[[]]])) # empty 3-D array

✗

Optional argument flips 1-D shape behavior.

matdims(np.array([1,2]), 'row') # 1-D array, 2 elements

✓

The argument has to make sense though

matdims(np.array([1,2]), 'bizarre')

✓

Aliases

scipy.io.matlab._mio4.matdims