src/pmml/pmml_swig/PMMLBasicsTest.py

   1 # -*- coding: utf-8 -*-
   2
   3 # imports Salomé
   4 from PMML import PMMLlib, kANN, kLR
   5
   6 # imports python
   7 import unittest
   8 import exceptions
   9 from exceptions import RuntimeError
  10 import os
  11 import shutil
  12
  13 class PMMLBasicsTest(unittest.TestCase):
  14
  15     def setUp(self):
  16         pmmlRootDir = os.getenv("YACS_ROOT_DIR");
  17         self.resourcesDir = os.path.join(pmmlRootDir,"share","salome","resources","pmml");
  18         self.resourcesDir += os.sep ;
  19         self.tmpDir = "/tmp/";
  20         self.tmpDir += os.environ['LOGNAME']; # ("USER");
  21         self.tmpDir += "/PmmlUnitTest/";
  22         if ( not os.path.exists(self.tmpDir) ):
  23             os.mkdir(self.tmpDir);
  24             pass
  25         pass
  26
  27     def tearDown(self):
  28         if ( os.path.exists(self.tmpDir) ):
  29             shutil.rmtree(self.tmpDir);
  30             pass
  31         pass
  32
  33     def testExportPythonNeuralNet(self):
  34         pmmlFile = self.resourcesDir + "ann_model.pmml";
  35         model = "sANNName";
  36         exportPyScript = self.tmpDir + "swigTestExportPythonNeuralNet.py";
  37         refPyFilename = self.resourcesDir + "unittest_ref_ann_model.py";
  38         refLines = file(refPyFilename).readlines();
  39         #
  40         p = PMMLlib( pmmlFile );
  41         p.SetCurrentModel( model, kANN );
  42         p.ExportPython( exportPyScript, "myTestFunc",
  43                         "File used by unit test\n PMMLBasicsTest1::testExportNeuralNetworkPython" );
  44         myLines = file(exportPyScript).readlines();
  45         self.assertEqual( len(myLines), len(refLines) );
  46         for (i,line) in enumerate(myLines):
  47             self.assertEqual( line, refLines[i] );
  48             pass
  49         pass
  50
  51     def testExportPythonRegression(self):
  52         pmmlFile = self.resourcesDir + "lr_model.pmml";
  53         model = "Modeler[LinearRegression]Tds[steamplant]Predictor[x6:x8:x6x8:x6x6x8]Target[x1]";
  54         exportPyScript = self.tmpDir + "swigTestExportPythonRegression.py";
  55         refPyFilename = self.resourcesDir + "unittest_ref_lr_model.py";
  56         refLines = file(refPyFilename).readlines();
  57         #
  58         p = PMMLlib( pmmlFile );
  59         p.SetCurrentModel( model, kLR );
  60         p.ExportPython( exportPyScript, "myTestFunc",
  61                                "File used by unit test\n PMMLBasicsTest1::testExportLinearRegressionPython" );
  62         myLines = file(exportPyScript).readlines();
  63         self.assertEqual( len(myLines), len(refLines) );
  64         for (i,line) in enumerate(myLines):
  65             self.assertEqual( line, refLines[i] );
  66             pass
  67         pass
  68
  69     def testPmmlFileNotReadable(self):
  70         self.assertRaises( RuntimeError, PMMLlib, "0.mml" );
  71         pass
  72
  73     def testPmmlFileNotReadable(self):
  74         pmmlFile = self.resourcesDir + "ann_model.pmml";
  75         model = "sANNName";
  76         p = PMMLlib(pmmlFile);
  77         self.assertRaises( RuntimeError, p.SetCurrentModel, model, kLR );
  78         pass
  79
  80     def testPmmlFileNotWritable(self):
  81         p = PMMLlib();
  82         self.assertRaises( RuntimeError, p.Write );
  83         pass
  84     pass
  85
  86 unittest.main()