pymodalib.implementations.python.matlab_compat module

backslash(x, y)

Imitates the MATLAB backslash operator.

carr(arr)

farr(arr)

fminsearch(func, x0, xtol, disp=0)

interp1(x, y, xq)

is_arraylike(value)

is_number(s)

isempty(value)

Imitates MATLAB’s isempty function by returning whether the object is empty - if it has a length - or whether it is None.

nextpow2(x)

quadgk(func, x0, x1, limit, epsabs, epsrel)

The function relies on the SciPy implementatioon of Gauss-Kronrod method. The method relies on Fortran implementation and it does not handle complex numbers. In the contex of PyMODA it is expected that the method should handle complex functions. The simpliest approach is to integrate the real and immaginary parts separrately and then return the sum.

rand(d0, d1, ..., dn)

Random values in a given shape.

Note

This is a convenience function for users porting code from Matlab, and wraps random_sample. That function takes a tuple to specify the size of the output, which is consistent with other NumPy functions like numpy.zeros and numpy.ones.

Create an array of the given shape and populate it with random samples from a uniform distribution over [0, 1).

Parameters:d0, d1, …, dn (int, optional) – The dimensions of the returned array, must be non-negative. If no argument is given a single Python float is returned. Returns:out – Random values. Return type:ndarray, shape (d0, d1, ..., dn)

See also

random()

Examples

>>> np.random.rand(3,2)
array([[ 0.14022471,  0.96360618],  #random
       [ 0.37601032,  0.25528411],  #random
       [ 0.49313049,  0.94909878]]) #random

sort2d(arr, descend=False)

sqrt(n)