set params manually or get random fractals
# Uncomment if you wan to generate fractals with constant params
# provide lists one value for each fractal
# size of grid for given fractal
grids = [64]
# max tieration for a given pixel
max_iters = [8]
# power of the complex number
powers = [1]
#abs values for cut off for fractals
abs_values = [2]
# offset in the real space x,y,z
off = [[0,0,0]]
# offset in the plotting the fractal
offset = [[0,0,0]]
num_voxels = len(grids)
# Uncomment if you wan to generate fractals with random params
# number of fractals, all fractals would be stack
# together with offets provided
num_voxels = 4
# size of grid for given fractal
grids = np.sort(np.random.randint(8, 64, size=num_voxels))
max_iters = np.random.randint(8, 256, size=num_voxels)
powers = np.sort(np.random.randint(1, 3, size=num_voxels))
offset = np.random.randint(0, np.max(grids), size=(num_voxels, 3))
off = np.random.randint(0, 3, size=(num_voxels, 3))
abs_values = np.random.randint(1, 2, size=num_voxels)
# valcanic type shapes
mandelbrot_data[i, j, k] = \
mandel(complex(cz*cx*cz, cz*cy*cz), power, max_iter)
# valcanic type shapes
mandelbrot_data[i, j, k] = \
mandel(complex(cz*cx*cz*cz, cz*cy*cz*cz), power, max_iter)
#symmteric shapes
#mandelbrot_data[i, j, k] = \
# mandel(complex(cx*cy*cz, cz*cx*cy), power, max_iter)
#mandelbrot_data[i, j, k] = \
# mandel(complex(cz*cx*cx, cz*cx*cx), power, max_iter)