pktools  2.6.5
Processing Kernel for geospatial data
pksvm.py
1 # -*- coding: utf-8 -*-
2 
3 """
4 ***************************************************************************
5  pksvm.py
6  ---------------------
7  Date : April 2015
8  Copyright : (C) 2015 by Pieter Kempeneers
9  Email : kempenep at gmail dot com
10 ***************************************************************************
11 * *
12 * This program is free software; you can redistribute it and/or modify *
13 * it under the terms of the GNU General Public License as published by *
14 * the Free Software Foundation; either version 2 of the License, or *
15 * (at your option) any later version. *
16 * *
17 ***************************************************************************
18 """
19 
20 __author__ = 'Pieter Kempeneers'
21 __date__ = 'April 2015'
22 __copyright__ = '(C) 2015, Pieter Kempeneers'
23 # This will get replaced with a git SHA1 when you do a git archive
24 __revision__ = '$Format:%H$'
25 
26 import os
27 from pktoolsUtils import pktoolsUtils
28 from pktoolsAlgorithm import pktoolsAlgorithm
29 from processing.core.parameters import ParameterMultipleInput
30 from processing.core.parameters import ParameterVector
31 from processing.core.parameters import ParameterRaster
32 from processing.core.outputs import OutputRaster
33 from processing.core.parameters import ParameterSelection
34 from processing.core.parameters import ParameterNumber
35 from processing.core.parameters import ParameterString
36 from processing.core.parameters import ParameterBoolean
37 from processing.core.parameters import ParameterExtent
38 
39 class pksvm(pktoolsAlgorithm):
40 
41  INPUT = "INPUT"
42  TRAINING = "TRAINING"
43  ITERATE = "ITERATE"
44  LABEL = "LABEL"
45 # CV = "CV"
46  GAMMA = "GAMMA"
47  COST = "COST"
48  OUTPUT = "OUTPUT"
49  MASK = "MASK"
50  MSKNODATA = "MSKNODATA"
51 # NODATA = "NODATA"
52 
53 # SVM_TYPE_OPTIONS = ["C_SVC", "nu_SVC,one_class", "epsilon_SVR", "nu_SVR"]
54 # KERNEL_TYPE_OPTIONS = ["linear", "polynomial", "radial", "sigmoid"]
55  EXTRA = 'EXTRA'
56 
57  def cliName(self):
58  return "pksvm"
59 
60  def defineCharacteristics(self):
61  self.name = "Support vector machine"
62  self.group = "[pktools] supervised classification"
63  self.addParameter(ParameterRaster(self.INPUT, 'Input layer raster data set',ParameterRaster))
64  self.addParameter(ParameterVector(self.TRAINING, 'Training vector file.'))
65  self.addParameter(ParameterBoolean(self.ITERATE, "Iterate over all layers",True))
66  self.addParameter(ParameterString(self.LABEL, "Attribute name for class label in training vector file","label"))
67  self.addParameter(ParameterNumber(self.GAMMA, "Gamma in kernel function",0,100,1.0))
68  self.addParameter(ParameterNumber(self.COST, "The parameter C of C_SVC",0,100000,1000.0))
69  self.addParameter(ParameterRaster(self.MASK, "Mask raster dataset",optional=True))
70  self.addParameter(ParameterString(self.MSKNODATA, "Mask value(s) not to consider for classification (e.g., 0;255)","0"))
71  self.addOutput(OutputRaster(self.OUTPUT, "Output raster data set"))
72  self.addParameter(ParameterString(self.EXTRA,
73  'Additional parameters', '-of GTiff', optional=True))
74 
75 # self.addParameter(ParameterSelection(self.KERNEL_TYPE,"Type of kernel function (linear,polynomial,radial,sigmoid)",self.KERNEL_TYPE_OPTIONS, 2))
76 # self.addParameter(ParameterSelection(self.SVM_TYPE,"Type of SVM (C_SVC, nu_SVC,one_class, epsilon_SVR, nu_SVR)",self.SVM_TYPE_OPTIONS, 0))
77 
78  def processAlgorithm(self, progress):
79  cliPath = '"' + os.path.join(pktoolsUtils.pktoolsPath(), self.cliName()) + '"'
80  commands = [cliPath]
81 
82  input=self.getParameterValue(self.INPUT)
83  if input != "":
84  commands.append('-i')
85  commands.append('"' + input + '"')
86 
87  commands.append('-t')
88  training=self.getParameterValue(self.TRAINING)
89 
90  if(str(training).find('|')>0):
91  if self.getParameterValue(self.ITERATE):
92  trainingname=str(training)
93  commands.append(trainingname[:trainingname.find('|')])
94  else:
95  trainingname=str(training).replace("|layername"," -ln")
96  commands.append(trainingname)
97  else:
98  commands.append(training)
99 
100  commands.append('-label')
101  commands.append(str(self.getParameterValue(self.LABEL)))
102  # if self.getParameterValue(self.CV):
103  # commands.append("-cv 2")
104  commands.append('-g')
105  commands.append(str(self.getParameterValue(self.GAMMA)))
106  commands.append('-cc')
107  commands.append(str(self.getParameterValue(self.COST)))
108 
109  mask = str(self.getParameterValue(self.MASK))
110  if mask != "None":
111  commands.append('-m')
112  commands.append(mask)
113  msknodata=str(self.getParameterValue(self.MSKNODATA))
114  msknodataValues = msknodata.split(';')
115  for msknodataValue in msknodataValues:
116  commands.append('-msknodata')
117  commands.append(msknodataValue)
118 
119  extra = str(self.getParameterValue(self.EXTRA))
120  if len(extra) > 0:
121  commands.append(extra)
122 
123  output=self.getOutputValue(self.OUTPUT)
124  if output != "":
125  commands.append('-o')
126  commands.append('"' + output + '"')
127 
128  pktoolsUtils.runpktools(commands, progress)