Question regarding the number of octaves in fractal noise generator

[rubeea]

Hi,

As per the documentation of generate_fractal_noise_2d function, the third argument is the number of octaves in the noise. If the number of octaves is 1, will this function generate the perlin noise since the fractal noise is nothing but multiple octaves of perlin noise combined. So, when the octave is 1 is the perlin noise generated?

Thanks in advance

[pvigier]

Yes, it is!

We will enter only once in the for loop:

perlin-numpy/perlin_numpy/perlin2d.py

Lines 87 to 96 in 6f077f8

	noise = np.zeros(shape)
	frequency = 1
	amplitude = 1
	for _ in range(octaves):
	noise += amplitude * generate_perlin_noise_2d(
	shape, (frequency*res[0], frequency*res[1]), tileable, interpolant
	)
	frequency *= lacunarity
	amplitude *= persistence
	return noise

[rubeea]

Yes, it is!

We will enter only once in the for loop:

perlin-numpy/perlin_numpy/perlin2d.py

Lines 87 to 96 in 6f077f8

	noise = np.zeros(shape)
	frequency = 1
	amplitude = 1
	for _ in range(octaves):
	noise += amplitude * generate_perlin_noise_2d(
	shape, (frequency*res[0], frequency*res[1]), tileable, interpolant
	)
	frequency *= lacunarity
	amplitude *= persistence
	return noise

Hi,
Noted with thanks. I have one more question regarding other parameters (lacunarity and persistence) in the fractal noise generator. I want to generate fractal noise of shape (256,256,3) and for that I wrote the following code snippet:
noise = generate_fractal_noise_3d(
(256, 256, 3), (4, 4, 1), octaves=4, lacunarity=1, tileable=(True, False, False)
)
The default lacunarity in your code is 2 but with lacunarity=2 the output shape of (256,256,3) is not possible as shape must be a multiple of (lacunarity**(octaves-1)*res) for 3D fractal noise. Is there any other configuration via which I can achieve an out shape of (256,256,3) using a lacunarity>1? And if I use lacunarity=1 is that a valid config for the fractal noise?

Thanks in advance :)

[pvigier]

Sorry for the delay.

You can generate more, for instance (256, 256, 8) with lacunarity=2 if I am not mistaken, and then keep only what you need.