healpix_geo.ring.vertices#

healpix_geo.ring.vertices(ipix, depth, ellipsoid, step=1, num_threads=0)#

Get the longitudes and latitudes of the vertices of some HEALPix cells at a given depth.

This method returns the 4 vertices of each cell in ipix.

Parameters:

  • ipix (numpy.ndarray) – The HEALPix cell indexes given as a np.uint64 numpy array.

  • depth (int, or numpy.ndarray) – The depth of the HEALPix cells. If given as an array, should have the same shape than ipix

  • ellipsoid (str, default: "sphere") – Reference ellipsoid to evaluate healpix on. If "sphere", this will return the same result as cdshealpix.ring.vertices().

  • step (int, default: 1) – The number of vertices returned per HEALPix side. By default it is set to 1 meaning that it will only return the vertices of the cell. 2 means that it will return the vertices of the cell plus one more vertex per edge (the center of the edge). More generally, the number of vertices returned is 4 * step.

  • num_threads (int, optional) – Specifies the number of threads to use for the computation. Default to 0 means it will choose the number of threads based on the RAYON_NUM_THREADS environment variable (if set), or the number of logical CPUs (otherwise)

Returns:

longitude, latitude (numpy.ndarray) – The sky coordinates of the 4 vertices of the HEALPix cells. lon and lat are of shape \(N\) x \(4\) numpy arrays where N is the number of HEALPix cell given in ipix.

Raises:

ValueError – When the HEALPix cell indexes given have values out of \([0, 4^{29 - depth}[\).

Examples

>>> from healpix_geo.ring import vertices
>>> import numpy as np
>>> ipix = np.array([42, 6, 10])
>>> depth = 12
>>> lon, lat = vertices(ipix, depth, ellipsoid="sphere")
>>> np.stack([lon, lat], axis=-1)
array([[[ 45.        ,  89.93147196],
        [ 54.        ,  89.9428933 ],
        [ 45.        ,  89.95431464],
        [ 36.        ,  89.9428933 ]],

       [[120.        ,  89.96573598],
        [135.        ,  89.97715732],
        [ 90.        ,  89.98857866],
        [ 90.        ,  89.97715732]],

       [[300.        ,  89.96573598],
        [315.        ,  89.97715732],
        [270.        ,  89.98857866],
        [270.        ,  89.97715732]]])