import numpy as np
from matplotlib.path import Path
[docs]
def disk(r, ctr, size, status=False):
"""
This function returns a boolean array containing a disk.
The disk is centered at (ctr[0], ctr[1]), and has radius r. The array is
(size[0], size[1]) in size and has boolean type. Pixel values of False
indicate that the center of a pixel is within r of (ctr[0], ctr[1]). Pixel
values of True indicate the opposite. The center of each pixel is the
integer position of that pixel.
Parameters
----------
r : float
The radius of the disk.
ctr : tuple, list, or array
The x,y position of the center of the disk, 2-element vector.
size : tuple, list, or array
The x,y size of the output array, 2-element vector.
status : bool; optional
If True, return the status optional output.
Returns
-------
ret : ndarray
A boolean array where True if outside the disk or False if inside
the disk.
retstatus : int; optional
Set to 1 if any part of the disk is outside the image boundaries.
Only returned if status==True.
Notes
-----
History:
- 2003 April 4; Joseph Harrington, jh@oobleck.astro.cornell.edu
Initial version.
- 2004 Feb 27; jh
Added alternate input method
- 2005 Nov 16; jh
Added STATUS, simplified disk calculation,
use double precision
"""
# check if disk is off image
retstatus = int(ctr[0] - r < 0 or ctr[0] + r > size[0]-1 or
ctr[1] - r < 0 or ctr[1] + r > size[1]-1)
# calculate pixel distance from center
# print('disk size:', size)
ind = np.indices(size)
fdisk = (ind[0]-ctr[0])**2.0 + (ind[1]-ctr[1])**2.0
# return mask disk (and status if requested)
ret = fdisk > r**2.0
if status:
ret = ret, retstatus
return ret
[docs]
def hex(r, ctr, size, status=False):
"""
This function returns a byte array containing a hexagon.
The hexagon is centered at (ctr[0], ctr[1]), and is circumscribed by a
circle of radius r. The array is (size[0], size[1]) in size and has byte
type. Pixel values of 1 indicate that the center of a pixel is within the
hexagonal aperture. Pixel values of 0 indicate the opposite. The center
of each pixel is the integer position of that pixel.
Parameters
----------
r : float
The radius of the circle circumscribing the hexagon.
ctr : tuple, list, or array
The x,y position of the center of the hexagon, 2-element vector.
size : tuple, list, or array
The x,y size of the output array, 2-element vector.
status : bool; optional
If True, return the status optional output.
Returns
-------
ret : ndarray
A boolean array where False if outside the hexagon or True if inside
the hexagon.
retstatus : int; optional
Set to 1 if any part of the hexagon is outside the image boundaries.
Only returned if status==True.
Notes
-----
History:
- 2024-06-05: Yoni Brande, jbrande@ku.edu
Initial version, adapted from a snippet by Ian Crossfield
"""
# check if hex is off image (same check as disk, for now)
retstatus = int(ctr[0] - r < 0 or ctr[0] + r > size[0]-1 or
ctr[1] - r < 0 or ctr[1] + r > size[1]-1)
# make hexagon, oriented like the JWST mirrors (corner vertex at 12:00)
yvert = ctr[1] + r*np.cos(2*np.pi*np.arange(6)/6)
xvert = ctr[0] - r*np.sin(2*np.pi*np.arange(6)/6)
hexverts = np.vstack((xvert, yvert)).T
# use matplotlib Path to make hexagon
poly_path = Path(hexverts)
# get list of coordinates for each pixel in image
ind = np.indices(size)
coors = np.hstack((ind[0].reshape(-1, 1), ind[1].reshape(-1, 1)))
# use matplotlib.path to do easy masking
ret = ~poly_path.contains_points(coors).reshape(size[0], size[1])
# return mask disk (and status if requested)
if status:
ret = ret, retstatus
return ret