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118 lines
4.7 KiB
Python
118 lines
4.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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NearestNeighbourAnalysis.py
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---------------------
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Date : August 2012
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Copyright : (C) 2012 by Victor Olaya
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Email : volayaf at gmail dot com
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***************************************************************************
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* *
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* This program is free software; you can redistribute it and/or modify *
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* it under the terms of the GNU General Public License as published by *
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* the Free Software Foundation; either version 2 of the License, or *
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* (at your option) any later version. *
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* *
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***************************************************************************
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"""
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__author__ = 'Victor Olaya'
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__date__ = 'August 2012'
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__copyright__ = '(C) 2012, Victor Olaya'
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# This will get replaced with a git SHA1 when you do a git archive
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__revision__ = '$Format:%H$'
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import math
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from qgis.core import *
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from sextante.core.GeoAlgorithm import GeoAlgorithm
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from sextante.core.QGisLayers import QGisLayers
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from sextante.parameters.ParameterVector import ParameterVector
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from sextante.outputs.OutputHTML import OutputHTML
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from sextante.outputs.OutputNumber import OutputNumber
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from sextante.algs.ftools import FToolsUtils as utils
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class NearestNeighbourAnalysis(GeoAlgorithm):
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POINTS = "POINTS"
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OUTPUT = "OUTPUT"
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OBSERVED_MD = "OBSERVED_MD"
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EXPECTED_MD = "EXPECTED_MD"
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NN_INDEX = "NN_INDEX"
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POINT_COUNT = "POINT_COUNT"
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Z_SCORE = "Z_SCORE"
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#===========================================================================
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# def getIcon(self):
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# return QtGui.QIcon(os.path.dirname(__file__) + "/icons/neighbour.png")
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#===========================================================================
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def defineCharacteristics(self):
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self.name = "Nearest neighbour analysis"
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self.group = "Vector analysis tools"
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self.addParameter(ParameterVector(self.POINTS, "Points", ParameterVector.VECTOR_TYPE_POINT))
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self.addOutput(OutputHTML(self.OUTPUT, "Result"))
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self.addOutput(OutputNumber(self.OBSERVED_MD, "Observed mean distance"))
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self.addOutput(OutputNumber(self.EXPECTED_MD, "Expected mean distance"))
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self.addOutput(OutputNumber(self.NN_INDEX, "Nearest neighbour index"))
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self.addOutput(OutputNumber(self.POINT_COUNT, "Number of points"))
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self.addOutput(OutputNumber(self.Z_SCORE, "Z-Score"))
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def processAlgorithm(self, progress):
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layer = QGisLayers.getObjectFromUri(self.getParameterValue(self.POINTS))
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output = self.getOutputValue(self.OUTPUT)
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spatialIndex = utils.createSpatialIndex(layer)
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neighbour = QgsFeature()
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distance = QgsDistanceArea()
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sumDist = 0.00
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A = layer.extent()
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A = float(A.width() * A.height())
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current = 0
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features = QGisLayers.features(layer)
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count = len(features)
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total = 100.0 / float(len(features))
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for feat in features:
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neighbourID = spatialIndex.nearestNeighbor(feat.geometry().asPoint(), 2)[1]
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request = QgsFeatureRequest().setFilterFid(neighbourID)
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neighbour = layer.getFeatures(request).next()
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sumDist += distance.measureLine(neighbour.geometry().asPoint(), feat.geometry().asPoint())
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current += 1
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progress.setPercentage(int(current * total))
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do = float(sumDist) / count
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de = float(0.5 / math.sqrt(count / A))
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d = float(do / de)
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SE = float(0.26136 / math.sqrt(( count ** 2) / A))
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zscore = float((do - de) / SE)
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data = []
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data.append("Observed mean distance: " + unicode(do))
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data.append("Expected mean distance: " + unicode(de))
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data.append("Nearest neighbour index: " + unicode(d))
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data.append("Number of points: " + unicode(count))
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data.append("Z-Score: " + unicode(zscore))
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self.createHTML(output, data)
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self.setOutputValue(self.OBSERVED_MD, float( data[ 0 ].split( ": " )[ 1 ] ) )
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self.setOutputValue(self.EXPECTED_MD, float( data[ 1 ].split( ": " )[ 1 ] ) )
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self.setOutputValue(self.NN_INDEX, float( data[ 2 ].split( ": " )[ 1 ] ) )
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self.setOutputValue(self.POINT_COUNT, float( data[ 3 ].split( ": " )[ 1 ] ) )
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self.setOutputValue(self.Z_SCORE, float( data[ 4 ].split( ": " )[ 1 ] ) )
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def createHTML(self, outputFile, algData):
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f = open(outputFile, "w")
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for s in algData:
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f.write("<p>" + str(s) + "</p>")
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f.close()
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