# -*- coding: utf-8 -*- """ *************************************************************************** MeanCoords.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 str __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 from qgis.PyQt.QtGui import QIcon from qgis.PyQt.QtCore import QVariant from qgis.core import (QgsField, QgsFeature, QgsGeometry, QgsPointXY, QgsWkbTypes, QgsFeatureRequest, QgsFeatureSink, QgsFields, QgsProcessing, QgsProcessingParameterFeatureSink, QgsProcessingParameterField, QgsProcessingParameterFeatureSource, QgsProcessingException) from processing.algs.qgis.QgisAlgorithm import QgisAlgorithm from processing.tools import vector pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0] class MeanCoords(QgisAlgorithm): INPUT = 'INPUT' WEIGHT = 'WEIGHT' OUTPUT = 'OUTPUT' UID = 'UID' WEIGHT = 'WEIGHT' def icon(self): return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'mean.png')) def group(self): return self.tr('Vector analysis tools') def __init__(self): super().__init__() def initAlgorithm(self, config=None): self.addParameter(QgsProcessingParameterFeatureSource(self.INPUT, self.tr('Input layer'))) self.addParameter(QgsProcessingParameterField(self.WEIGHT, self.tr('Weight field'), parentLayerParameterName=MeanCoords.INPUT, type=QgsProcessingParameterField.Numeric, optional=True)) self.addParameter(QgsProcessingParameterField(self.UID, self.tr('Unique ID field'), parentLayerParameterName=MeanCoords.INPUT, optional=True)) self.addParameter(QgsProcessingParameterFeatureSink(MeanCoords.OUTPUT, self.tr('Mean coordinates'), QgsProcessing.TypeVectorPoint)) def name(self): return 'meancoordinates' def displayName(self): return self.tr('Mean coordinate(s)') def processAlgorithm(self, parameters, context, feedback): source = self.parameterAsSource(parameters, self.INPUT, context) weight_field = self.parameterAsString(parameters, self.WEIGHT, context) unique_field = self.parameterAsString(parameters, self.UID, context) attributes = [] if not weight_field: weight_index = -1 else: weight_index = source.fields().lookupField(weight_field) if weight_index >= 0: attributes.append(weight_index) if not unique_field: unique_index = -1 else: unique_index = source.fields().lookupField(unique_field) if unique_index >= 0: attributes.append(unique_index) field_list = QgsFields() field_list.append(QgsField('MEAN_X', QVariant.Double, '', 24, 15)) field_list.append(QgsField('MEAN_Y', QVariant.Double, '', 24, 15)) if unique_index >= 0: field_list.append(QgsField('UID', QVariant.String, '', 255)) (sink, dest_id) = self.parameterAsSink(parameters, self.OUTPUT, context, field_list, QgsWkbTypes.Point, source.sourceCrs()) features = source.getFeatures(QgsFeatureRequest().setSubsetOfAttributes(attributes)) total = 100.0 / source.featureCount() if source.featureCount() else 0 means = {} for current, feat in enumerate(features): if feedback.isCanceled(): break feedback.setProgress(int(current * total)) if unique_index == -1: clazz = "Single class" else: clazz = str(feat.attributes()[unique_index]).strip() if weight_index == -1: weight = 1.00 else: try: weight = float(feat.attributes()[weight_index]) except: weight = 1.00 if weight < 0: raise QgsProcessingException( self.tr('Negative weight value found. Please fix your data and try again.')) if clazz not in means: means[clazz] = (0, 0, 0) (cx, cy, totalweight) = means[clazz] geom = QgsGeometry(feat.geometry()) geom = vector.extractPoints(geom) for i in geom: cx += i.x() * weight cy += i.y() * weight totalweight += weight means[clazz] = (cx, cy, totalweight) current = 0 total = 100.0 / len(means) if means else 1 for (clazz, values) in list(means.items()): if feedback.isCanceled(): break outFeat = QgsFeature() cx = values[0] / values[2] cy = values[1] / values[2] meanPoint = QgsPointXY(cx, cy) outFeat.setGeometry(QgsGeometry.fromPoint(meanPoint)) attributes = [cx, cy] if unique_index >= 0: attributes.append(clazz) outFeat.setAttributes(attributes) sink.addFeature(outFeat, QgsFeatureSink.FastInsert) current += 1 feedback.setProgress(int(current * total)) return {self.OUTPUT: dest_id}