pktools  2.6.3
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  commands = [os.path.join(pktoolsUtils.pktoolsPath(), self.cliName())]
80 
81  input=self.getParameterValue(self.INPUT)
82  if input != "":
83  commands.append('-i')
84  commands.append(input)
85 
86  commands.append('-t')
87  training=self.getParameterValue(self.TRAINING)
88 
89  if(str(training).find('|')>0):
90  if self.getParameterValue(self.ITERATE):
91  trainingname=str(training)
92  commands.append(trainingname[:trainingname.find('|')])
93  else:
94  trainingname=str(training).replace("|layername"," -ln")
95  commands.append(trainingname)
96  else:
97  commands.append(training)
98 
99  commands.append('-label')
100  commands.append(str(self.getParameterValue(self.LABEL)))
101  # if self.getParameterValue(self.CV):
102  # commands.append("-cv 2")
103  commands.append('-g')
104  commands.append(str(self.getParameterValue(self.GAMMA)))
105  commands.append('-cc')
106  commands.append(str(self.getParameterValue(self.COST)))
107 
108  mask = str(self.getParameterValue(self.MASK))
109  if mask != "None":
110  commands.append('-m')
111  commands.append(mask)
112  msknodata=str(self.getParameterValue(self.MSKNODATA))
113  msknodataValues = msknodata.split(';')
114  for msknodataValue in msknodataValues:
115  commands.append('-msknodata')
116  commands.append(msknodataValue)
117 
118  extra = str(self.getParameterValue(self.EXTRA))
119  if len(extra) > 0:
120  commands.append(extra)
121 
122  output=str(self.getParameterValue(self.OUTPUT))
123  if output != "":
124  commands.append('-o')
125  commands.append(self.getOutputValue(self.OUTPUT))
126 
127  f=open('/tmp/a','w')
128  for item in commands:
129  print >> f, item
130  f.close()
131  pktoolsUtils.runpktools(commands, progress)
string TRAINING
Definition: pksvm.py:42
string EXTRA
Definition: pksvm.py:55
string MASK
Definition: pksvm.py:49
string GAMMA
Definition: pksvm.py:46
string ITERATE
Definition: pksvm.py:43
string MSKNODATA
Definition: pksvm.py:50
string COST
Definition: pksvm.py:47
string LABEL
Definition: pksvm.py:44
string INPUT
Definition: pksvm.py:41
string OUTPUT
Definition: pksvm.py:48