xrspatial.perlin.perlin#

xrspatial.perlin.perlin(agg: DataArray, freq: tuple = (1, 1), seed: int = 5, name: str = 'perlin') → DataArray[source]#

Generate perlin noise aggregate.

Parameters:

agg (xr.DataArray) – 2D array of size width x height, will be used to determine height/ width and which platform to use for calculation.
freq (tuple, default=(1,1)) – (x, y) frequency multipliers.
seed (int, default=5) – Seed for random number generator.

Returns:

perlin_agg – 2D array of perlin noise values.

Return type:

xarray.DataArray

References

Paul Panzer: https://stackoverflow.com/questions/42147776/producing-2d-perlin-noise-with-numpy # noqa
ICA: http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf # noqa

Examples

>>> import numpy as np
>>> import xarray as xr
>>> from xrspatial import perlin

>>> W = 4
>>> H = 3
>>> data = np.zeros((H, W), dtype=np.float32)
>>> raster = xr.DataArray(data, dims=['y', 'x'])

>>> perlin_noise = perlin(raster)
>>> print(perlin_noise)
<xarray.DataArray 'perlin' (y: 3, x: 4)>
array([[0.        , 0.58311844, 0.96620274, 0.58311844],
       [0.        , 0.5796199 , 1.        , 0.7346118 ],
       [0.        , 0.5172636 , 0.83896613, 0.697184  ]], dtype=float32)
Dimensions without coordinates: y, x