# xrspatial.focal.focal_stats#

xrspatial.focal.focal_stats(agg, kernel, stats_funcs=['mean', 'max', 'min', 'range', 'std', 'var', 'sum'])[source]#

Calculates statistics of the values within a specified focal neighborhood for each pixel in an input raster. The statistics types are Mean, Maximum, Minimum, Range, Standard deviation, Variation and Sum.

Parameters
• agg (xarray.DataArray) – 2D array of input values to be analysed. Can be a NumPy backed, Cupy backed, or Dask with NumPy backed DataArray.

• kernel (numpy.array) – 2D array where values of 1 indicate the kernel.

• stats_funcs (list of string) – List of statistics types to be calculated. Default set to [‘mean’, ‘max’, ‘min’, ‘range’, ‘std’, ‘var’, ‘sum’].

Returns

stats_agg – 3D array with dimensions of (stat, y, x) and with values indicating the focal stats.

Return type

xarray.DataArray of same type as agg

Examples

```>>> import numpy as np
>>> import xarray as xr
>>> from xrspatial.convolution import circle_kernel
>>> kernel = circle_kernel(1, 1, 1)
>>> kernel
array([[0., 1., 0.],
[1., 1., 1.],
[0., 1., 0.]])
>>> data = np.array([
[0, 0, 0, 0, 0, 0],
[1, 1, 2, 2, 1, 1],
[2, 2, 1, 1, 2, 2],
[3, 3, 0, 0, 3, 3],
])
>>> from xrspatial.focal import focal_stats
>>> focal_stats(xr.DataArray(data), kernel, stats_funcs=['min', 'sum'])
<xarray.DataArray 'focal_apply' (stats: 2, dim_0: 4, dim_1: 6)>
array([[[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[1., 1., 0., 0., 1., 1.],
[2., 0., 0., 0., 0., 2.]],
[[1., 1., 2., 2., 1., 1.],
[4., 6., 6., 6., 6., 4.],
[8., 9., 6., 6., 9., 8.],
[8., 8., 4., 4., 8., 8.]]])
Coordinates:
* stats    (stats) object 'min' 'sum'
Dimensions without coordinates: dim_0, dim_1
```