import numpy as np
import xarray as xr
from xrspatial.convolution import convolve_2d
from xrspatial.utils import _validate_raster
# -- Sobel kernels ----------------------------------------------------------
SOBEL_X = np.array([[-1, 0, 1],
[-2, 0, 2],
[-1, 0, 1]], dtype=np.float64)
SOBEL_Y = np.array([[-1, -2, -1],
[ 0, 0, 0],
[ 1, 2, 1]], dtype=np.float64)
# -- Prewitt kernels ---------------------------------------------------------
PREWITT_X = np.array([[-1, 0, 1],
[-1, 0, 1],
[-1, 0, 1]], dtype=np.float64)
PREWITT_Y = np.array([[-1, -1, -1],
[ 0, 0, 0],
[ 1, 1, 1]], dtype=np.float64)
# -- Laplacian kernel --------------------------------------------------------
LAPLACIAN_KERNEL = np.array([[0, 1, 0],
[1, -4, 1],
[0, 1, 0]], dtype=np.float64)
[docs]
def sobel_x(agg, name='sobel_x', boundary='nan'):
"""Compute the horizontal gradient of a raster using the Sobel operator.
Detects vertical edges by convolving with the Sobel-X kernel::
[[-1, 0, 1],
[-2, 0, 2],
[-1, 0, 1]]
Parameters
----------
agg : xarray.DataArray
2D raster. Supports NumPy, CuPy, Dask+NumPy, and Dask+CuPy backends.
name : str, default='sobel_x'
Name for the output DataArray.
boundary : str, default='nan'
How to handle edges: 'nan', 'nearest', 'reflect', or 'wrap'.
Returns
-------
xarray.DataArray
Horizontal gradient with the same shape and backend as the input.
"""
_validate_raster(agg, func_name='sobel_x', name='agg')
out = convolve_2d(agg.data, SOBEL_X, boundary)
return xr.DataArray(out, name=name, coords=agg.coords,
dims=agg.dims, attrs=agg.attrs)
[docs]
def sobel_y(agg, name='sobel_y', boundary='nan'):
"""Compute the vertical gradient of a raster using the Sobel operator.
Detects horizontal edges by convolving with the Sobel-Y kernel::
[[-1, -2, -1],
[ 0, 0, 0],
[ 1, 2, 1]]
Parameters
----------
agg : xarray.DataArray
2D raster. Supports NumPy, CuPy, Dask+NumPy, and Dask+CuPy backends.
name : str, default='sobel_y'
Name for the output DataArray.
boundary : str, default='nan'
How to handle edges: 'nan', 'nearest', 'reflect', or 'wrap'.
Returns
-------
xarray.DataArray
Vertical gradient with the same shape and backend as the input.
"""
_validate_raster(agg, func_name='sobel_y', name='agg')
out = convolve_2d(agg.data, SOBEL_Y, boundary)
return xr.DataArray(out, name=name, coords=agg.coords,
dims=agg.dims, attrs=agg.attrs)
[docs]
def laplacian(agg, name='laplacian', boundary='nan'):
"""Compute edges using the Laplacian (second-derivative) operator.
Omnidirectional edge detector using the kernel::
[[ 0, 1, 0],
[ 1, -4, 1],
[ 0, 1, 0]]
Parameters
----------
agg : xarray.DataArray
2D raster. Supports NumPy, CuPy, Dask+NumPy, and Dask+CuPy backends.
name : str, default='laplacian'
Name for the output DataArray.
boundary : str, default='nan'
How to handle edges: 'nan', 'nearest', 'reflect', or 'wrap'.
Returns
-------
xarray.DataArray
Laplacian response with the same shape and backend as the input.
"""
_validate_raster(agg, func_name='laplacian', name='agg')
out = convolve_2d(agg.data, LAPLACIAN_KERNEL, boundary)
return xr.DataArray(out, name=name, coords=agg.coords,
dims=agg.dims, attrs=agg.attrs)
[docs]
def prewitt_x(agg, name='prewitt_x', boundary='nan'):
"""Compute the horizontal gradient of a raster using the Prewitt operator.
Detects vertical edges by convolving with the Prewitt-X kernel::
[[-1, 0, 1],
[-1, 0, 1],
[-1, 0, 1]]
Parameters
----------
agg : xarray.DataArray
2D raster. Supports NumPy, CuPy, Dask+NumPy, and Dask+CuPy backends.
name : str, default='prewitt_x'
Name for the output DataArray.
boundary : str, default='nan'
How to handle edges: 'nan', 'nearest', 'reflect', or 'wrap'.
Returns
-------
xarray.DataArray
Horizontal gradient with the same shape and backend as the input.
"""
_validate_raster(agg, func_name='prewitt_x', name='agg')
out = convolve_2d(agg.data, PREWITT_X, boundary)
return xr.DataArray(out, name=name, coords=agg.coords,
dims=agg.dims, attrs=agg.attrs)
[docs]
def prewitt_y(agg, name='prewitt_y', boundary='nan'):
"""Compute the vertical gradient of a raster using the Prewitt operator.
Detects horizontal edges by convolving with the Prewitt-Y kernel::
[[-1, -1, -1],
[ 0, 0, 0],
[ 1, 1, 1]]
Parameters
----------
agg : xarray.DataArray
2D raster. Supports NumPy, CuPy, Dask+NumPy, and Dask+CuPy backends.
name : str, default='prewitt_y'
Name for the output DataArray.
boundary : str, default='nan'
How to handle edges: 'nan', 'nearest', 'reflect', or 'wrap'.
Returns
-------
xarray.DataArray
Vertical gradient with the same shape and backend as the input.
"""
_validate_raster(agg, func_name='prewitt_y', name='agg')
out = convolve_2d(agg.data, PREWITT_Y, boundary)
return xr.DataArray(out, name=name, coords=agg.coords,
dims=agg.dims, attrs=agg.attrs)
