PMMLBasicsTest.py

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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright (C) 2007-2025  CEA, EDF
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with this library; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307 USA
#
# See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
#
 
# imports Salomé
from PMML import PMMLlib, kANN, kLR
 
# imports python
import unittest
import os
import shutil
import platform
import tempfile
 
class PMMLBasicsTest(unittest.TestCase):
 
    def setUp(self):
        self.resourcesDirresourcesDir = ".." + os.sep + "Test" + os.sep + "samples" + os.sep ;
        self.tmpDirtmpDir = tempfile.mkdtemp(suffix="PmmlUnitTest")
 
    def tearDown(self):
        if ( os.path.exists(self.tmpDirtmpDir) ):
            shutil.rmtree(self.tmpDirtmpDir);
            pass 
        pass
 
    def testExportPythonNeuralNet(self):
        pmmlFile = self.resourcesDirresourcesDir + "ann_model.pmml";
        model = "sANNName";
        exportPyScript = self.tmpDirtmpDir + "swigTestExportPythonNeuralNet.py";
        refPyFilename = self.resourcesDirresourcesDir + "unittest_ref_ann_model.py";
        with open(refPyFilename,"r") as f:
            refLines = f.readlines(); 
        #
        p = PMMLlib( pmmlFile );
        p.SetCurrentModel( model, kANN );
        p.ExportPython( exportPyScript, "myTestFunc", 
                        "File used by unit test\n PMMLBasicsTest1::testExportNeuralNetworkPython" );
        with open(exportPyScript,"r") as f:
            myLines = f.readlines();
        self.assertEqual( len(myLines), len(refLines) );
        for (i,line) in enumerate(myLines):
            self.assertEqual( line, refLines[i] );
            pass
        pass
  
    def testExportPythonRegression(self):
        pmmlFile = self.resourcesDirresourcesDir + "lr_model.pmml";
        model = "Modeler[LinearRegression]Tds[steamplant]Predictor[x6:x8:x6x8:x6x6x8]Target[x1]";
        exportPyScript = self.tmpDirtmpDir + "swigTestExportPythonRegression.py";
        refPyFilename = self.resourcesDirresourcesDir + "unittest_ref_lr_model.py";
        with open(refPyFilename,"r") as f:
            refLines = f.readlines(); 
        #
        p = PMMLlib( pmmlFile );
        p.SetCurrentModel( model, kLR );
        p.ExportPython( exportPyScript, "myTestFunc", 
                               "File used by unit test\n PMMLBasicsTest1::testExportLinearRegressionPython" );
        with open(exportPyScript,"r") as f:
            myLines = f.readlines();
        self.assertEqual( len(myLines), len(refLines) );
        for (i,line) in enumerate(myLines):
            self.assertEqual( line, refLines[i] );
            pass
        pass
 
    def testPmmlFileNotReadable(self):
        self.assertRaises( RuntimeError, PMMLlib, "0.mml" );
        pass
 
    def testPmmlFileNotReadable(self):
        pmmlFile = self.resourcesDirresourcesDir + "ann_model.pmml";
        model = "sANNName";
        p = PMMLlib(pmmlFile);
        self.assertRaises( RuntimeError, p.SetCurrentModel, model, kLR );
        pass
 
    def testPmmlFileNotWritable(self):
        p = PMMLlib();
        self.assertRaises( RuntimeError, p.Write );
        pass
    pass
 
unittest.main()