xrspatial.perlin.perlin¶
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xrspatial.perlin.perlin(width: int, height: int, freq: tuple = (1, 1), seed: int = 5) → xarray.core.dataarray.DataArray[source]¶ Generate perlin noise aggregate.
- width: int
Width of output aggregate array.
- height: int
Height of output aggregate array.
- freq: tuple (default = (1,1))
(x, y) frequency multipliers.
- seed: int (default = 5)
Seed for random number generator.
- xarray.DataArray
2D array, of the same type as the input, of calculated perlin
noise values.
Algorithm References: - numba-ized from Paul Panzer example available here: #noqa
tgirod, Panzer, Paul, StackOverflow, https://stackoverflow.com/questions/42147776/producing-2d-perlin-noise-with-numpy, Accessed Apr. 21, 2021. # noqa
Nighbert, JS, Bureau of Land Management, Portland, OR, Using “Materials and Textures” in Cartographic Presentations A.K.A. “Bump Mapping”, http://www.mountaincartography.org/mt_hood/pdfs/nighbert_bump1.pdf, Accessed Apr. 21, 2021. # noqa
Imports >>> import numpy as np >>> import xarray as xr >>> from xrspatial import perlin
Generate Perlin Aggregate >>> print(perlin(5, 5)) <xarray.DataArray (y: 5, x: 5)> array([[0.38502038, 0.3235394 , 0.13230299, 0.02275815, 0.13502038],
[0.69650136, 0.6169794 , 0.34002832, 0.10065245, 0.10962136], [1. , 0.90777853, 0.55206348, 0.16047902, 0.01192 ], [1. , 0.92388163, 0.60956174, 0.21797728, 0. ], [0.69650136, 0.6604194 , 0.50362745, 0.29227467, 0.15306136]])
Dimensions without coordinates: y, x .. attribute:: res
1