# Source code for fmask.fillminima

```
"""
Module to implement filling of local minima in a raster surface.
The algorithm is from
Soille, P., and Gratin, C. (1994). An efficient algorithm for drainage network
extraction on DEMs. J. Visual Communication and Image Representation.
5(2). 181-189.
The algorithm is intended for hydrological processing of a DEM, but is used by the
Fmask cloud shadow algorithm as part of its process for finding local minima which
represent potential shadow objects.
"""
# This file is part of 'python-fmask' - a cloud masking module
# Copyright (C) 2015 Neil Flood
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 3
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
import os
import numpy
from scipy.ndimage import grey_dilation
# Fail slightly less drastically when running from ReadTheDocs
if os.getenv('READTHEDOCS', default='False') != 'True':
from . import _fillminima
[docs]def fillMinima(img, nullval, boundaryval):
"""
Fill all local minima in the input img. The input
array should be a numpy 2-d array. This function returns
an array of the same shape and datatype, with the same contents, but
with local minima filled using the reconstruction-by-erosion algorithm.
"""
(nrows, ncols) = img.shape
dtype = img.dtype
nullmask = (img == nullval)
nonNullmask = numpy.logical_not(nullmask)
(hMax, hMin) = (int(img[nonNullmask].max()), int(img[nonNullmask].min()))
boundaryval = max(boundaryval, hMin)
img2 = numpy.zeros((nrows, ncols), dtype=dtype)
img2.fill(hMax)
if nullmask.sum() > 0:
nullmaskDilated = grey_dilation(nullmask, size=(3, 3))
innerBoundary = nullmaskDilated ^ nullmask
(boundaryRows, boundaryCols) = numpy.where(innerBoundary)
else:
img2[0, :] = img[0, :]
img2[-1, :] = img[-1, :]
img2[:, 0] = img[:, 0]
img2[:, -1] = img[:, -1]
(boundaryRows, boundaryCols) = numpy.where(img2!=hMax)
# on some systems (32 bit only?) numpy.where returns int32
# rather than int64. Convert so we don't have to handle both in C.
boundaryRows = boundaryRows.astype(numpy.int64)
boundaryCols = boundaryCols.astype(numpy.int64)
_fillminima.fillMinima(img, img2, hMin, hMax, nullmask, boundaryval,
boundaryRows, boundaryCols)
img2[nullmask] = nullval
return img2
```