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Algorithms and other processing code should use this method (instead of dataobjects.getLayerFromString) to retrieve layers from a string, as it considers the processing context and allows resolving strings to temporarily stored layers. This permits processing models to function correctly when intermediate results are stored as memory layers. Subsequent model algorithms can then access these temporary layers as inputs. All temporary layers will be removed when the context object is destroyed after the model algorithm is run.
265 lines
10 KiB
Python
265 lines
10 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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from builtins import str
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from builtins import zip
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from builtins import range
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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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import os
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from qgis.PyQt.QtGui import QIcon
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from qgis.PyQt.QtCore import QVariant
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from qgis.core import QgsFields, QgsField, QgsFeature, QgsGeometry, NULL, QgsWkbTypes, QgsProcessingUtils
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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 ParameterNumber
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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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pluginPath = os.path.split(os.path.split(os.path.dirname(__file__))[0])[0]
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class SpatialJoin(GeoAlgorithm):
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TARGET = "TARGET"
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JOIN = "JOIN"
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PREDICATE = "PREDICATE"
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PRECISION = 'PRECISION'
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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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def icon(self):
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return QIcon(os.path.join(pluginPath, 'images', 'ftools', 'join_location.png'))
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def group(self):
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return self.tr('Vector general tools')
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def name(self):
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return 'joinattributesbylocation'
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def displayName(self):
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return self.tr('Join attributes by location')
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def defineCharacteristics(self):
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self.predicates = (
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('intersects', self.tr('intersects')),
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('contains', self.tr('contains')),
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('equals', self.tr('equals')),
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('touches', self.tr('touches')),
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('overlaps', self.tr('overlaps')),
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('within', self.tr('within')),
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('crosses', self.tr('crosses')))
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self.summarys = [
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self.tr('Take attributes of the first located feature'),
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self.tr('Take summary of intersecting features')
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]
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self.keeps = [
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self.tr('Only keep matching records'),
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self.tr('Keep all records (including non-matching target records)')
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]
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self.addParameter(ParameterVector(self.TARGET,
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self.tr('Target vector layer')))
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self.addParameter(ParameterVector(self.JOIN,
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self.tr('Join vector layer')))
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self.addParameter(ParameterSelection(self.PREDICATE,
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self.tr('Geometric predicate'),
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self.predicates,
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multiple=True))
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self.addParameter(ParameterNumber(self.PRECISION,
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self.tr('Precision'),
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0.0, None, 0.0))
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self.addParameter(ParameterSelection(self.SUMMARY,
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self.tr('Attribute summary'), self.summarys))
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self.addParameter(ParameterString(self.STATS,
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self.tr('Statistics for summary (comma separated)'),
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'sum,mean,min,max,median', optional=True))
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self.addParameter(ParameterSelection(self.KEEP,
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self.tr('Joined table'), self.keeps))
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self.addOutput(OutputVector(self.OUTPUT, self.tr('Joined layer')))
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def processAlgorithm(self, context, feedback):
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target = dataobjects.QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.TARGET), context)
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join = dataobjects.QgsProcessingUtils.mapLayerFromString(self.getParameterValue(self.JOIN), context)
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predicates = self.getParameterValue(self.PREDICATE)
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precision = self.getParameterValue(self.PRECISION)
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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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targetFields = target.fields()
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joinFields = join.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 = list(range(len(targetFields) + len(joinFields)))
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targetFields.extend(joinFields)
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targetFields = dict(list(zip(seq, targetFields)))
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else:
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numFields = {}
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for j in range(len(joinFields)):
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if joinFields[j].type() in [QVariant.Int, QVariant.Double, QVariant.LongLong, QVariant.UInt, QVariant.ULongLong]:
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numFields[j] = []
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for i in sumList:
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field = QgsField(i + str(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 = list(range(len(targetFields)))
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targetFields = dict(list(zip(seq, targetFields)))
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fields = QgsFields()
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for f in list(targetFields.values()):
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fields.append(f)
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writer = self.getOutputFromName(self.OUTPUT).getVectorWriter(fields, target.wkbType(), target.crs(), context)
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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 = QgsProcessingUtils.getFeatures(join, context)
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for f in features:
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mapP2[f.id()] = QgsFeature(f)
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features = QgsProcessingUtils.getFeatures(target, context)
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total = 100.0 / QgsProcessingUtils.featureCount(target, context)
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for c, f in enumerate(features):
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atMap1 = f.attributes()
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outFeat.setGeometry(f.geometry())
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inGeom = vector.snapToPrecision(f.geometry(), precision)
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none = True
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joinList = []
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if inGeom.type() == QgsWkbTypes.PointGeometry:
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bbox = inGeom.buffer(10, 2).boundingBox()
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else:
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bbox = inGeom.boundingBox()
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bufferedBox = vector.bufferedBoundingBox(bbox, 0.51 * precision)
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joinList = index.intersects(bufferedBox)
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if len(joinList) > 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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inGeomB = vector.snapToPrecision(inFeatB.geometry(), precision)
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res = False
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for predicate in predicates:
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res = getattr(inGeom, predicate)(inGeomB)
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if res:
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break
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if res:
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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(list(zip(seq, atMap)))
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break
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else:
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for j in list(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 list(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(list(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(list(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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feedback.setProgress(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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