QGIS/python/plugins/processing/algs/qgis/ZonalStatistics.py
Nyall Dawson 377b181c4e Port more processing dataobjects methods to c++
Also
- simplify and add tests
- remove large memory leak (persistant store of all non-project layers)
- remove broken support for direct loading postgres/virtual layers
by string (Python version was very broken and would never match
a postgres/virtual layer)
2017-04-05 19:50:46 +10:00

279 lines
11 KiB
Python

# -*- coding: utf-8 -*-
"""
***************************************************************************
ZonalStatistics.py
---------------------
Date : August 2013
Copyright : (C) 2013 by Alexander Bruy
Email : alexander dot bruy at gmail dot com
***************************************************************************
* *
* 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 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************
"""
from builtins import str
__author__ = 'Alexander Bruy'
__date__ = 'August 2013'
__copyright__ = '(C) 2013, Alexander Bruy'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
import numpy
try:
from scipy.stats.mstats import mode
hasSciPy = True
except:
hasSciPy = False
from osgeo import gdal, ogr, osr
from qgis.core import (QgsApplication,
QgsRectangle,
QgsGeometry,
QgsFeature)
from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.parameters import ParameterVector
from processing.core.parameters import ParameterRaster
from processing.core.parameters import ParameterString
from processing.core.parameters import ParameterNumber
from processing.core.parameters import ParameterBoolean
from processing.core.outputs import OutputVector
from processing.tools.raster import mapToPixel
from processing.tools import dataobjects, vector
class ZonalStatistics(GeoAlgorithm):
INPUT_RASTER = 'INPUT_RASTER'
RASTER_BAND = 'RASTER_BAND'
INPUT_VECTOR = 'INPUT_VECTOR'
COLUMN_PREFIX = 'COLUMN_PREFIX'
GLOBAL_EXTENT = 'GLOBAL_EXTENT'
OUTPUT_LAYER = 'OUTPUT_LAYER'
def icon(self):
return QgsApplication.getThemeIcon("/providerQgis.svg")
def svgIconPath(self):
return QgsApplication.iconPath("providerQgis.svg")
def group(self):
return self.tr('Raster tools')
def name(self):
return 'zonalstatistics'
def displayName(self):
return self.tr('Zonal Statistics')
def defineCharacteristics(self):
self.addParameter(ParameterRaster(self.INPUT_RASTER,
self.tr('Raster layer')))
self.addParameter(ParameterNumber(self.RASTER_BAND,
self.tr('Raster band'), 1, 999, 1))
self.addParameter(ParameterVector(self.INPUT_VECTOR,
self.tr('Vector layer containing zones'),
[dataobjects.TYPE_VECTOR_POLYGON]))
self.addParameter(ParameterString(self.COLUMN_PREFIX,
self.tr('Output column prefix'), '_'))
self.addParameter(ParameterBoolean(self.GLOBAL_EXTENT,
self.tr('Load whole raster in memory')))
self.addOutput(OutputVector(self.OUTPUT_LAYER, self.tr('Zonal statistics'), datatype=[dataobjects.TYPE_VECTOR_POLYGON]))
def processAlgorithm(self, feedback):
""" Based on code by Matthew Perry
https://gist.github.com/perrygeo/5667173
"""
layer = dataobjects.getLayerFromString(self.getParameterValue(self.INPUT_VECTOR))
rasterPath = str(self.getParameterValue(self.INPUT_RASTER))
bandNumber = self.getParameterValue(self.RASTER_BAND)
columnPrefix = self.getParameterValue(self.COLUMN_PREFIX)
useGlobalExtent = self.getParameterValue(self.GLOBAL_EXTENT)
rasterDS = gdal.Open(rasterPath, gdal.GA_ReadOnly)
geoTransform = rasterDS.GetGeoTransform()
rasterBand = rasterDS.GetRasterBand(bandNumber)
noData = rasterBand.GetNoDataValue()
cellXSize = abs(geoTransform[1])
cellYSize = abs(geoTransform[5])
rasterXSize = rasterDS.RasterXSize
rasterYSize = rasterDS.RasterYSize
rasterBBox = QgsRectangle(geoTransform[0],
geoTransform[3] - cellYSize * rasterYSize,
geoTransform[0] + cellXSize * rasterXSize,
geoTransform[3])
rasterGeom = QgsGeometry.fromRect(rasterBBox)
crs = osr.SpatialReference()
crs.ImportFromProj4(str(layer.crs().toProj4()))
if useGlobalExtent:
xMin = rasterBBox.xMinimum()
xMax = rasterBBox.xMaximum()
yMin = rasterBBox.yMinimum()
yMax = rasterBBox.yMaximum()
(startColumn, startRow) = mapToPixel(xMin, yMax, geoTransform)
(endColumn, endRow) = mapToPixel(xMax, yMin, geoTransform)
width = endColumn - startColumn
height = endRow - startRow
srcOffset = (startColumn, startRow, width, height)
srcArray = rasterBand.ReadAsArray(*srcOffset)
srcArray = srcArray * rasterBand.GetScale() + rasterBand.GetOffset()
newGeoTransform = (
geoTransform[0] + srcOffset[0] * geoTransform[1],
geoTransform[1],
0.0,
geoTransform[3] + srcOffset[1] * geoTransform[5],
0.0,
geoTransform[5],
)
memVectorDriver = ogr.GetDriverByName('Memory')
memRasterDriver = gdal.GetDriverByName('MEM')
fields = layer.fields()
(idxMin, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'min', 21, 6)
(idxMax, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'max', 21, 6)
(idxSum, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'sum', 21, 6)
(idxCount, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'count', 21, 6)
(idxMean, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'mean', 21, 6)
(idxStd, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'std', 21, 6)
(idxUnique, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'unique', 21, 6)
(idxRange, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'range', 21, 6)
(idxVar, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'var', 21, 6)
(idxMedian, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'median', 21, 6)
if hasSciPy:
(idxMode, fields) = vector.findOrCreateField(layer, fields,
columnPrefix + 'mode', 21, 6)
writer = self.getOutputFromName(self.OUTPUT_LAYER).getVectorWriter(
fields.toList(), layer.wkbType(), layer.crs())
outFeat = QgsFeature()
outFeat.initAttributes(len(fields))
outFeat.setFields(fields)
features = vector.features(layer)
total = 100.0 / len(features)
for current, f in enumerate(features):
geom = f.geometry()
intersectedGeom = rasterGeom.intersection(geom)
ogrGeom = ogr.CreateGeometryFromWkt(intersectedGeom.exportToWkt())
if not useGlobalExtent:
bbox = intersectedGeom.boundingBox()
xMin = bbox.xMinimum()
xMax = bbox.xMaximum()
yMin = bbox.yMinimum()
yMax = bbox.yMaximum()
(startColumn, startRow) = mapToPixel(xMin, yMax, geoTransform)
(endColumn, endRow) = mapToPixel(xMax, yMin, geoTransform)
width = endColumn - startColumn
height = endRow - startRow
if width == 0 or height == 0:
continue
srcOffset = (startColumn, startRow, width, height)
srcArray = rasterBand.ReadAsArray(*srcOffset)
srcArray = srcArray * rasterBand.GetScale() + rasterBand.GetOffset()
newGeoTransform = (
geoTransform[0] + srcOffset[0] * geoTransform[1],
geoTransform[1],
0.0,
geoTransform[3] + srcOffset[1] * geoTransform[5],
0.0,
geoTransform[5],
)
# Create a temporary vector layer in memory
memVDS = memVectorDriver.CreateDataSource('out')
memLayer = memVDS.CreateLayer('poly', crs, ogr.wkbPolygon)
ft = ogr.Feature(memLayer.GetLayerDefn())
ft.SetGeometry(ogrGeom)
memLayer.CreateFeature(ft)
ft.Destroy()
# Rasterize it
rasterizedDS = memRasterDriver.Create('', srcOffset[2],
srcOffset[3], 1, gdal.GDT_Byte)
rasterizedDS.SetGeoTransform(newGeoTransform)
gdal.RasterizeLayer(rasterizedDS, [1], memLayer, burn_values=[1])
rasterizedArray = rasterizedDS.ReadAsArray()
srcArray = numpy.nan_to_num(srcArray)
masked = numpy.ma.MaskedArray(srcArray,
mask=numpy.logical_or(srcArray == noData,
numpy.logical_not(rasterizedArray)))
outFeat.setGeometry(geom)
attrs = f.attributes()
v = float(masked.min())
attrs.insert(idxMin, None if numpy.isnan(v) else v)
v = float(masked.max())
attrs.insert(idxMax, None if numpy.isnan(v) else v)
v = float(masked.sum())
attrs.insert(idxSum, None if numpy.isnan(v) else v)
attrs.insert(idxCount, int(masked.count()))
v = float(masked.mean())
attrs.insert(idxMean, None if numpy.isnan(v) else v)
v = float(masked.std())
attrs.insert(idxStd, None if numpy.isnan(v) else v)
attrs.insert(idxUnique, numpy.unique(masked.compressed()).size)
v = float(masked.max()) - float(masked.min())
attrs.insert(idxRange, None if numpy.isnan(v) else v)
v = float(masked.var())
attrs.insert(idxVar, None if numpy.isnan(v) else v)
v = float(numpy.ma.median(masked))
attrs.insert(idxMedian, None if numpy.isnan(v) else v)
if hasSciPy:
attrs.insert(idxMode, float(mode(masked, axis=None)[0][0]))
outFeat.setAttributes(attrs)
writer.addFeature(outFeat)
memVDS = None
rasterizedDS = None
feedback.setProgress(int(current * total))
rasterDS = None
del writer