QGIS/python/plugins/processing/algs/qgis/ftools/RandomExtractWithinSubsets.py

135 lines
5.0 KiB
Python

# -*- coding: utf-8 -*-
"""
***************************************************************************
RandomSelectionWithinSubsets.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. *
* *
***************************************************************************
"""
__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 random
from PyQt4.QtCore import *
from qgis.core import *
from processing.core.GeoAlgorithm import GeoAlgorithm
from processing.core.GeoAlgorithmExecutionException import \
GeoAlgorithmExecutionException
from processing.parameters.ParameterSelection import ParameterSelection
from processing.parameters.ParameterVector import ParameterVector
from processing.parameters.ParameterNumber import ParameterNumber
from processing.parameters.ParameterTableField import ParameterTableField
from processing.outputs.OutputVector import OutputVector
from processing.tools import dataobjects, vector
class RandomExtractWithinSubsets(GeoAlgorithm):
INPUT = 'INPUT'
METHOD = 'METHOD'
NUMBER = 'NUMBER'
FIELD = 'FIELD'
OUTPUT = 'OUTPUT'
METHODS = ['Number of selected features',
'Percentage of selected features']
def defineCharacteristics(self):
self.name = 'Random extract within subsets'
self.group = 'Vector selection tools'
self.addParameter(ParameterVector(self.INPUT, 'Input layer',
[ParameterVector.VECTOR_TYPE_ANY]))
self.addParameter(ParameterTableField(self.FIELD, 'ID Field',
self.INPUT))
self.addParameter(ParameterSelection(self.METHOD, 'Method',
self.METHODS, 0))
self.addParameter(ParameterNumber(self.NUMBER,
'Number/percentage of selected features', 1, None,
10))
self.addOutput(OutputVector(self.OUTPUT, 'Selection'))
def processAlgorithm(self, progress):
filename = self.getParameterValue(self.INPUT)
layer = dataobjects.getObjectFromUri(filename)
field = self.getParameterValue(self.FIELD)
method = self.getParameterValue(self.METHOD)
index = layer.fieldNameIndex(field)
features = vector.features(layer)
featureCount = len(features)
unique = vector.getUniqueValues(layer, index)
value = int(self.getParameterValue(self.NUMBER))
if method == 0:
if value > featureCount:
raise GeoAlgorithmExecutionException(
'Selected number is greater that feature count. \
Choose lesser value and try again.')
else:
if value > 100:
raise GeoAlgorithmExecutionException(
"Percentage can't be greater than 100. Set correct \
value and try again.")
value = value / 100.0
output = self.getOutputFromName(self.OUTPUT)
writer = output.getVectorWriter(layer.fields(),
layer.geometryType(), layer.crs())
selran = []
current = 0
total = 100.0 / float(featureCount * len(unique))
features = vector.features(layer)
if not len(unique) == featureCount:
for classValue in unique:
classFeatures = []
for i, feature in enumerate(features):
attrs = feature.attributes()
if attrs[index] == classValue:
classFeatures.append(i)
current += 1
progress.setPercentage(int(current * total))
if method == 1:
selValue = int(round(value * len(classFeatures), 0))
else:
selValue = value
if selValue >= len(classFeatures):
selFeat = classFeatures
else:
selFeat = random.sample(classFeatures, selValue)
selran.extend(selFeat)
else:
selran = range(0, featureCount)
features = vector.features(layer)
for (i, feat) in enumerate(features):
if i in selran:
writer.addFeature(feat)
progress.setPercentage(100 * i / float(featureCount))
del writer