def init_tri_complex(width, height):
"""
initialize 2d complex in dumbest possible way
"""
# initialize complex to use for persistence calculations
axis_x = np.arange(0, width)
axis_y = np.arange(0, height)
grid_axes = np.array(np.meshgrid(axis_x, axis_y))
grid_axes = np.transpose(grid_axes, (1, 2, 0))
# creation of a complex for calculations
tri = Delaunay(grid_axes.reshape([-1, 2]))
return unique_simplices(tri.simplices, 2)
def delaunay_complex(x, maxdim=2):
"""
compute Delaunay triangulation
fill in simplices as appropriate
if x is 1-dimensional, defaults to 1D Delaunay
inputs:
x - pointcloud
maxdim - maximal simplex dimension (default = 2)
"""
if x.shape[1] == 1:
x = x.flatten()
return alpha_complex_1d(x)
tri = Delaunay(x)
return unique_simplices(tri.simplices, maxdim)