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1e13d733c2
initAlgorithm() method This allows 2 benefits: - algorithms can be subclassed and have subclasses add additional parameters/outputs to the algorithm. With the previous approach of declaring parameters/outputs in the constructor, it's not possible to call virtual methods to add additional parameters/ outputs (since you can't call virtual methods from a constructor). - initAlgorithm takes a variant map argument, allowing the algorithm to dynamically adjust its declared parameters and outputs according to this configuration map. This potentially allows model algorithms which can be configured to have variable numbers of parameters and outputs at run time. E.g. a "router" algorithm which directs features to one of any number of output sinks depending on some user configured criteria.
201 lines
8.5 KiB
Python
201 lines
8.5 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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PointDistance.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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from builtins import next
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from builtins import str
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from builtins import range
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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 os
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import math
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from qgis.PyQt.QtGui import QIcon
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from qgis.core import QgsFeatureRequest, QgsDistanceArea, QgsFeatureSink, QgsProcessingUtils
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from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm
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from processing.core.parameters import ParameterNumber
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from processing.core.parameters import ParameterVector
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from processing.core.parameters import ParameterSelection
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from processing.core.parameters import ParameterTableField
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from processing.core.outputs import OutputTable
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from processing.tools import dataobjects
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pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
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class PointDistance(QgisAlgorithm):
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INPUT_LAYER = 'INPUT_LAYER'
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INPUT_FIELD = 'INPUT_FIELD'
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TARGET_LAYER = 'TARGET_LAYER'
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TARGET_FIELD = 'TARGET_FIELD'
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MATRIX_TYPE = 'MATRIX_TYPE'
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NEAREST_POINTS = 'NEAREST_POINTS'
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DISTANCE_MATRIX = 'DISTANCE_MATRIX'
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def icon(self):
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return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'matrix.png'))
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def group(self):
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return self.tr('Vector analysis tools')
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def __init__(self):
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super().__init__()
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def initAlgorithm(self, config=None):
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self.mat_types = [self.tr('Linear (N*k x 3) distance matrix'),
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self.tr('Standard (N x T) distance matrix'),
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self.tr('Summary distance matrix (mean, std. dev., min, max)')]
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self.addParameter(ParameterVector(self.INPUT_LAYER,
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self.tr('Input point layer'), [dataobjects.TYPE_VECTOR_POINT]))
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self.addParameter(ParameterTableField(self.INPUT_FIELD,
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self.tr('Input unique ID field'), self.INPUT_LAYER,
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ParameterTableField.DATA_TYPE_ANY))
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self.addParameter(ParameterVector(self.TARGET_LAYER,
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self.tr('Target point layer'), dataobjects.TYPE_VECTOR_POINT))
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self.addParameter(ParameterTableField(self.TARGET_FIELD,
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self.tr('Target unique ID field'), self.TARGET_LAYER,
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ParameterTableField.DATA_TYPE_ANY))
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self.addParameter(ParameterSelection(self.MATRIX_TYPE,
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self.tr('Output matrix type'), self.mat_types, 0))
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self.addParameter(ParameterNumber(self.NEAREST_POINTS,
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self.tr('Use only the nearest (k) target points'), 0, 9999, 0))
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self.addOutput(OutputTable(self.DISTANCE_MATRIX, self.tr('Distance matrix')))
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def name(self):
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return 'distancematrix'
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def displayName(self):
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return self.tr('Distance matrix')
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def processAlgorithm(self, parameters, context, feedback):
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inLayer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.INPUT_LAYER), context)
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inField = self.getParameterValue(self.INPUT_FIELD)
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targetLayer = QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.TARGET_LAYER), context)
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targetField = self.getParameterValue(self.TARGET_FIELD)
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matType = self.getParameterValue(self.MATRIX_TYPE)
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nPoints = self.getParameterValue(self.NEAREST_POINTS)
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outputFile = self.getOutputFromName(self.DISTANCE_MATRIX)
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if nPoints < 1:
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nPoints = QgsProcessingUtils.featureCount(targetLayer, context)
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self.writer = outputFile.getTableWriter([])
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if matType == 0:
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# Linear distance matrix
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self.linearMatrix(context, inLayer, inField, targetLayer, targetField,
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matType, nPoints, feedback)
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elif matType == 1:
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# Standard distance matrix
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self.regularMatrix(context, inLayer, inField, targetLayer, targetField,
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nPoints, feedback)
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elif matType == 2:
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# Summary distance matrix
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self.linearMatrix(context, inLayer, inField, targetLayer, targetField,
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matType, nPoints, feedback)
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def linearMatrix(self, context, inLayer, inField, targetLayer, targetField,
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matType, nPoints, feedback):
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if matType == 0:
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self.writer.addRecord(['InputID', 'TargetID', 'Distance'])
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else:
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self.writer.addRecord(['InputID', 'MEAN', 'STDDEV', 'MIN', 'MAX'])
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index = QgsProcessingUtils.createSpatialIndex(targetLayer, context)
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inIdx = inLayer.fields().lookupField(inField)
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outIdx = targetLayer.fields().lookupField(targetField)
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distArea = QgsDistanceArea()
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features = QgsProcessingUtils.getFeatures(inLayer, context)
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total = 100.0 / inLayer.featureCount() if inLayer.featureCount() else 0
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for current, inFeat in enumerate(features):
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inGeom = inFeat.geometry()
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inID = str(inFeat.attributes()[inIdx])
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featList = index.nearestNeighbor(inGeom.asPoint(), nPoints)
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distList = []
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vari = 0.0
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request = QgsFeatureRequest().setFilterFids(featList).setSubsetOfAttributes([outIdx])
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for outFeat in targetLayer.getFeatures(request):
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outID = outFeat.attributes()[outIdx]
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outGeom = outFeat.geometry()
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dist = distArea.measureLine(inGeom.asPoint(),
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outGeom.asPoint())
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if matType == 0:
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self.writer.addRecord([inID, str(outID), str(dist)])
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else:
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distList.append(float(dist))
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if matType != 0:
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mean = sum(distList) / len(distList)
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for i in distList:
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vari += (i - mean) * (i - mean)
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vari = math.sqrt(vari / len(distList))
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self.writer.addRecord([inID, str(mean),
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str(vari), str(min(distList)),
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str(max(distList))])
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feedback.setProgress(int(current * total))
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def regularMatrix(self, context, inLayer, inField, targetLayer, targetField,
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nPoints, feedback):
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index = QgsProcessingUtils.createSpatialIndex(targetLayer, context)
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inIdx = inLayer.fields().lookupField(inField)
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distArea = QgsDistanceArea()
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first = True
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features = QgsProcessingUtils.getFeatures(inLayer, context)
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total = 100.0 / inLayer.featureCount() if inLayer.featureCount() else 0
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for current, inFeat in enumerate(features):
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inGeom = inFeat.geometry()
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inID = str(inFeat.attributes()[inIdx])
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featList = index.nearestNeighbor(inGeom.asPoint(), nPoints)
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if first:
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first = False
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data = ['ID']
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for i in range(len(featList)):
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data.append('DIST_{0}'.format(i + 1))
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self.writer.addRecord(data)
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data = [inID]
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for i in featList:
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request = QgsFeatureRequest().setFilterFid(i)
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outFeat = next(targetLayer.getFeatures(request))
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outGeom = outFeat.geometry()
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dist = distArea.measureLine(inGeom.asPoint(),
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outGeom.asPoint())
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data.append(str(float(dist)))
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self.writer.addRecord(data)
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feedback.setProgress(int(current * total))
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