# -*- coding: utf-8 -*- """ *************************************************************************** PointDistance.py --------------------- Date : August 2012 Copyright : (C) 2012 by Victor Olaya Email : volayaf 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 next from builtins import str from builtins import range __author__ = 'Victor Olaya' __date__ = 'August 2012' __copyright__ = '(C) 2012, Victor Olaya' # This will get replaced with a git SHA1 when you do a git archive __revision__ = '$Format:%H$' import os import math from qgis.PyQt.QtGui import QIcon from qgis.core import QgsFeatureRequest, QgsDistanceArea, QgsFeatureSink, QgsProcessingUtils from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm from processing.core.parameters import ParameterNumber from processing.core.parameters import ParameterVector from processing.core.parameters import ParameterSelection from processing.core.parameters import ParameterTableField from processing.core.outputs import OutputTable from processing.tools import dataobjects pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0] class PointDistance(QgisAlgorithm): INPUT_LAYER = 'INPUT_LAYER' INPUT_FIELD = 'INPUT_FIELD' TARGET_LAYER = 'TARGET_LAYER' TARGET_FIELD = 'TARGET_FIELD' MATRIX_TYPE = 'MATRIX_TYPE' NEAREST_POINTS = 'NEAREST_POINTS' DISTANCE_MATRIX = 'DISTANCE_MATRIX' def icon(self): return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'matrix.png')) def group(self): return self.tr('Vector analysis tools') def __init__(self): super().__init__() self.mat_types = [self.tr('Linear (N*k x 3) distance matrix'), self.tr('Standard (N x T) distance matrix'), self.tr('Summary distance matrix (mean, std. dev., min, max)')] self.addParameter(ParameterVector(self.INPUT_LAYER, self.tr('Input point layer'), [dataobjects.TYPE_VECTOR_POINT])) self.addParameter(ParameterTableField(self.INPUT_FIELD, self.tr('Input unique ID field'), self.INPUT_LAYER, ParameterTableField.DATA_TYPE_ANY)) self.addParameter(ParameterVector(self.TARGET_LAYER, self.tr('Target point layer'), dataobjects.TYPE_VECTOR_POINT)) self.addParameter(ParameterTableField(self.TARGET_FIELD, self.tr('Target unique ID field'), self.TARGET_LAYER, ParameterTableField.DATA_TYPE_ANY)) self.addParameter(ParameterSelection(self.MATRIX_TYPE, self.tr('Output matrix type'), self.mat_types, 0)) self.addParameter(ParameterNumber(self.NEAREST_POINTS, self.tr('Use only the nearest (k) target points'), 0, 9999, 0)) self.addOutput(OutputTable(self.DISTANCE_MATRIX, self.tr('Distance matrix'))) def name(self): return 'distancematrix' def displayName(self): return self.tr('Distance matrix') def processAlgorithm(self, parameters, context, feedback): inLayer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.INPUT_LAYER), context) inField = self.getParameterValue(self.INPUT_FIELD) targetLayer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.TARGET_LAYER), context) targetField = self.getParameterValue(self.TARGET_FIELD) matType = self.getParameterValue(self.MATRIX_TYPE) nPoints = self.getParameterValue(self.NEAREST_POINTS) outputFile = self.getOutputFromName(self.DISTANCE_MATRIX) if nPoints < 1: nPoints = QgsProcessingUtils.featureCount(targetLayer, context) self.writer = outputFile.getTableWriter([]) if matType == 0: # Linear distance matrix self.linearMatrix(context, inLayer, inField, targetLayer, targetField, matType, nPoints, feedback) elif matType == 1: # Standard distance matrix self.regularMatrix(context, inLayer, inField, targetLayer, targetField, nPoints, feedback) elif matType == 2: # Summary distance matrix self.linearMatrix(context, inLayer, inField, targetLayer, targetField, matType, nPoints, feedback) def linearMatrix(self, context, inLayer, inField, targetLayer, targetField, matType, nPoints, feedback): if matType == 0: self.writer.addRecord(['InputID', 'TargetID', 'Distance']) else: self.writer.addRecord(['InputID', 'MEAN', 'STDDEV', 'MIN', 'MAX']) index = QgsProcessingUtils.createSpatialIndex(targetLayer, context) inIdx = inLayer.fields().lookupField(inField) outIdx = targetLayer.fields().lookupField(targetField) distArea = QgsDistanceArea() features = QgsProcessingUtils.getFeatures(inLayer, context) total = 100.0 / inLayer.featureCount() if inLayer.featureCount() else 0 for current, inFeat in enumerate(features): inGeom = inFeat.geometry() inID = str(inFeat.attributes()[inIdx]) featList = index.nearestNeighbor(inGeom.asPoint(), nPoints) distList = [] vari = 0.0 request = QgsFeatureRequest().setFilterFids(featList).setSubsetOfAttributes([outIdx]) for outFeat in targetLayer.getFeatures(request): outID = outFeat.attributes()[outIdx] outGeom = outFeat.geometry() dist = distArea.measureLine(inGeom.asPoint(), outGeom.asPoint()) if matType == 0: self.writer.addRecord([inID, str(outID), str(dist)]) else: distList.append(float(dist)) if matType != 0: mean = sum(distList) / len(distList) for i in distList: vari += (i - mean) * (i - mean) vari = math.sqrt(vari / len(distList)) self.writer.addRecord([inID, str(mean), str(vari), str(min(distList)), str(max(distList))]) feedback.setProgress(int(current * total)) def regularMatrix(self, context, inLayer, inField, targetLayer, targetField, nPoints, feedback): index = QgsProcessingUtils.createSpatialIndex(targetLayer, context) inIdx = inLayer.fields().lookupField(inField) distArea = QgsDistanceArea() first = True features = QgsProcessingUtils.getFeatures(inLayer, context) total = 100.0 / inLayer.featureCount() if inLayer.featureCount() else 0 for current, inFeat in enumerate(features): inGeom = inFeat.geometry() inID = str(inFeat.attributes()[inIdx]) featList = index.nearestNeighbor(inGeom.asPoint(), nPoints) if first: first = False data = ['ID'] for i in range(len(featList)): data.append('DIST_{0}'.format(i + 1)) self.writer.addRecord(data) data = [inID] for i in featList: request = QgsFeatureRequest().setFilterFid(i) outFeat = next(targetLayer.getFeatures(request)) outGeom = outFeat.geometry() dist = distArea.measureLine(inGeom.asPoint(), outGeom.asPoint()) data.append(str(float(dist))) self.writer.addRecord(data) feedback.setProgress(int(current * total))