ENH: Add to numpy simple functions for transform coordinate systems

It would be convenient to have these functions as a part of numpy mathematical routines.

cart2pol – Transform Cartesian to polar coordinates

def cart2pol(x, y):
    theta = np.arctan2(y, x)
    rho = np.hypot(x, y)
    return theta, rho

pol2cart – Transform polar to Cartesian coordinates

def pol2cart(theta, rho):
    x = rho * np.cos(theta)
    y = rho * np.sin(theta)
    return x, y

cart2sph – Transform Cartesian to spherical coordinates

def cart2sph(x, y, z):
    hxy = np.hypot(x, y)
    r = np.hypot(hxy, z)
    el = np.arctan2(z, hxy)
    az = np.arctan2(y, x)
    return az, el, r

sph2cart – Transform spherical to Cartesian coordinates

def sph2cart(az, el, r):
    rcos_theta = r * np.cos(el)
    x = rcos_theta * np.cos(az)
    y = rcos_theta * np.sin(az)
    z = r * np.sin(el)
    return x, y, z

[espdev]

I understand what you are talking about. However, these functions are used very often while working with the coordinate systems in geometric algorithms, computer graphics software, etc. Generalization on n-dimensions is required infrequently. In MATLAB these functions exist and, I should say, they are rather convenient. I consider these functions as simple mathematical routines, for example, functions rad2deg and deg2rad. These functions, as you know, are frequently used functions and exist in numpy.

[juliantaylor]

I’m not sure this is something that needs to be in numpy, the functions are simple enough to implement yourself optimally. If we add them were do we draw the line on which transformations to add? there are an infinite amount of them.