Functions | |
def | rand |
Returns a random integer in the range [0, n-1] inclusive. | |
def | sqr_dist |
The square of the distance between the given points. | |
def | sqr_dist_3d |
The square of the distance between the given points. | |
def | sample_poisson_uniform |
Gives a Poisson sample of points of a rectangle. | |
def | sample_poisson |
Gives a Poisson sample of points of a rectangle with an arbitrary distance function between points. | |
def | sample_poisson_3d |
Gives a Poisson sample of points of a box (3D rectangle). |
Tutorial: http://www.luma.co.za/labs/2008/02/27/poisson-disk-sampling/
def poisson_disk.rand | ( | n | ) |
Returns a random integer in the range [0, n-1] inclusive.
Definition at line 27 of file poisson_disk.py.
def poisson_disk.sample_poisson | ( | width, | ||
height, | ||||
r_grid, | ||||
k | ||||
) |
Gives a Poisson sample of points of a rectangle with an arbitrary distance function between points.
width | The width of the rectangle to sample | |
height | The height of the rectangle to sample | |
r_grid | r_grid[x, y] is the mimum distance between points around x, y, in terms of rectangle units. | |
k | The algorithm generates k points around points already in the sample, and then check if they are not too close to other points. Typically, k = 30 is sufficient. The larger k is, the slower th algorithm, but the more sample points are produced. |
Definition at line 137 of file poisson_disk.py.
def poisson_disk.sample_poisson_3d | ( | width, | ||
height, | ||||
depth, | ||||
r_grid, | ||||
k | ||||
) |
Gives a Poisson sample of points of a box (3D rectangle).
width | The width of the box to sample | |
height | The height of the box to sample | |
depth | The depth of the box to sample. | |
r_grid | r_grid[x, y, z] is the mimum distance between points around x, y, z, in terms of rectangle units. | |
k | The algorithm generates k points around points already in the sample, and then check if they are not too close to other points. Typically, k = 30 is sufficient. The larger k is, the slower th algorithm, but the more sample points are produced. |
Definition at line 220 of file poisson_disk.py.
def poisson_disk.sample_poisson_uniform | ( | width, | ||
height, | ||||
r, | ||||
k | ||||
) |
Gives a Poisson sample of points of a rectangle.
width | The width of the rectangle to sample | |
height | The height of the rectangle to sample | |
r | The mimum distance between points, in terms of rectangle units. For example, in a 10 by 10 grid, a mimum distance of 10 will probably only give you one sample point. | |
k | The algorithm generates k points around points already in the sample, and then check if they are not too close to other points. Typically, k = 30 is sufficient. The larger k is, the slower th algorithm, but the more sample points are produced. |
Definition at line 59 of file poisson_disk.py.
def poisson_disk.sqr_dist | ( | x0, | ||
y0, | ||||
x1, | ||||
y1 | ||||
) |
def poisson_disk.sqr_dist_3d | ( | x0, | ||
y0, | ||||
z0, | ||||
x1, | ||||
y1, | ||||
z1 | ||||
) |