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pep8 --ignore=E111,E128,E201,E202,E203,E211,E221,E222,E225,E226,E227,E231,E241,E261,E265,E272,E302,E303,E501,E701 \
--exclude="ui_*.py,debian/*,python/ext-libs/*" \
.
230 lines
8.6 KiB
Python
230 lines
8.6 KiB
Python
# -*- coding: utf-8 -*-
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"""
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***************************************************************************
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SpatialJoin.py
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---------------------
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Date : October 2013
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Copyright : (C) 2013 by Joshua Arnott
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Email : josh at snorfalorpagus dot net
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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__ = 'Joshua Arnott'
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__date__ = 'October 2013'
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__copyright__ = '(C) 2013, Joshua Arnott'
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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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from PyQt4.QtCore import QVariant
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from qgis.core import QGis, QgsFields, QgsField, QgsFeature, QgsGeometry, NULL
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from processing.core.GeoAlgorithm import GeoAlgorithm
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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 ParameterString
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from processing.core.outputs import OutputVector
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from processing.tools import dataobjects, vector
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class SpatialJoin(GeoAlgorithm):
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TARGET = "TARGET"
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JOIN = "JOIN"
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SUMMARY = "SUMMARY"
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STATS = "STATS"
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KEEP = "KEEP"
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OUTPUT = "OUTPUT"
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SUMMARYS = [
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'Take attributes of the first located feature',
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'Take summary of intersecting features'
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]
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KEEPS = [
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'Only keep matching records',
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'Keep all records (including non-matching target records)'
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]
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def defineCharacteristics(self):
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self.name = "Join attributes by location"
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self.group = "Vector general tools"
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self.addParameter(ParameterVector(self.TARGET,
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'Target vector layer', [ParameterVector.VECTOR_TYPE_ANY]))
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self.addParameter(ParameterVector(self.JOIN,
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'Join vector layer', [ParameterVector.VECTOR_TYPE_ANY]))
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self.addParameter(ParameterSelection(self.SUMMARY,
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'Attribute summary', self.SUMMARYS))
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self.addParameter(ParameterString(self.STATS,
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'Statistics for summary (comma separated)',
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'sum,mean,min,max,median'))
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self.addParameter(ParameterSelection(self.KEEP,
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'Output table', self.KEEPS))
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self.addOutput(OutputVector(self.OUTPUT, 'Output layer'))
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def processAlgorithm(self, progress):
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target = dataobjects.getObjectFromUri(
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self.getParameterValue(self.TARGET))
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join = dataobjects.getObjectFromUri(
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self.getParameterValue(self.JOIN))
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summary = self.getParameterValue(self.SUMMARY) == 1
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keep = self.getParameterValue(self.KEEP) == 1
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sumList = self.getParameterValue(self.STATS).lower().split(',')
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targetProvider = target.dataProvider()
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joinProvider = join.dataProvider()
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targetFields = targetProvider.fields()
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joinFields = joinProvider.fields()
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fieldList = QgsFields()
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if not summary:
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joinFields = vector.testForUniqueness(targetFields, joinFields)
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seq = range(0, len(targetFields) + len(joinFields))
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targetFields.extend(joinFields)
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targetFields = dict(zip(seq, targetFields))
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else:
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numFields = {}
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for j in xrange(len(joinFields)):
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if joinFields[j].type() in [QVariant.Int, QVariant.Double]:
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numFields[j] = []
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for i in sumList:
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field = QgsField(i + unicode(joinFields[j].name()), QVariant.Double, '', 24, 16)
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fieldList.append(field)
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field = QgsField('count', QVariant.Double, '', 24, 16)
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fieldList.append(field)
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joinFields = vector.testForUniqueness(targetFields, fieldList)
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targetFields.extend(fieldList)
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seq = range(0, len(targetFields))
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targetFields = dict(zip(seq, targetFields))
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fields = QgsFields()
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for f in targetFields.values():
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fields.append(f)
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writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(
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fields, targetProvider.geometryType(), targetProvider.crs())
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outFeat = QgsFeature()
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inFeatB = QgsFeature()
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inGeom = QgsGeometry()
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index = vector.spatialindex(join)
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mapP2 = dict()
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features = vector.features(join)
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for f in features:
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mapP2[f.id()] = QgsFeature(f)
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features = vector.features(target)
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total = 100.0 / len(features)
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for c, f in enumerate(features):
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inGeom = f.geometry()
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atMap1 = f.attributes()
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outFeat.setGeometry(inGeom)
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none = True
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joinList = []
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if inGeom.type() == QGis.Point:
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joinList = index.intersects(inGeom.buffer(10, 2).boundingBox())
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if len(joinList) > 0:
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check = 0
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else:
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check = 1
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else:
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joinList = index.intersects(inGeom.boundingBox())
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if len(joinList) > 0:
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check = 0
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else:
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check = 1
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if check == 0:
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count = 0
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for i in joinList:
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inFeatB = mapP2[i]
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if inGeom.intersects(inFeatB.geometry()):
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count = count + 1
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none = False
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atMap2 = inFeatB.attributes()
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if not summary:
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atMap = atMap1
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atMap2 = atMap2
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atMap.extend(atMap2)
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atMap = dict(zip(seq, atMap))
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break
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else:
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for j in numFields.keys():
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numFields[j].append(atMap2[j])
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if summary and not none:
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atMap = atMap1
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for j in numFields.keys():
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for k in sumList:
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if k == 'sum':
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atMap.append(sum(self._filterNull(numFields[j])))
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elif k == 'mean':
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try:
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nn_count = sum( 1 for _ in self._filterNull(numFields[j]) )
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atMap.append(sum(self._filterNull(numFields[j])) / nn_count)
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except ZeroDivisionError:
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atMap.append(NULL)
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elif k == 'min':
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try:
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atMap.append(min(self._filterNull(numFields[j])))
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except ValueError:
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atMap.append(NULL)
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elif k == 'median':
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atMap.append(self._median(numFields[j]))
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else:
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try:
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atMap.append(max(self._filterNull(numFields[j])))
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except ValueError:
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atMap.append(NULL)
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numFields[j] = []
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atMap.append(count)
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atMap = dict(zip(seq, atMap))
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if none:
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outFeat.setAttributes(atMap1)
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else:
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outFeat.setAttributes(atMap.values())
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if keep:
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writer.addFeature(outFeat)
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else:
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if not none:
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writer.addFeature(outFeat)
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progress.setPercentage(int(c * total))
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del writer
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def _filterNull(self, values):
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"""Takes an iterator of values and returns a new iterator
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returning the same values but skipping any NULL values"""
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return (v for v in values if v != NULL)
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def _median(self, data):
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count = len(data)
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if count == 1:
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return data[0]
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data.sort()
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median = 0
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if count > 1:
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if ( count % 2 ) == 0:
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median = 0.5 * ((data[count / 2 - 1]) + (data[count / 2]))
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else:
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median = data[(count + 1) / 2 - 1]
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return median
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