PMML feature

[modules/yacs.git] / src / pmml / pmml_swig / PMMLBasicsTest.py

diff --git a/src/pmml/pmml_swig/PMMLBasicsTest.py b/src/pmml/pmml_swig/PMMLBasicsTest.py
new file mode 100755 (executable)
index 0000000..59a4a18
--- /dev/null
+++ b/src/pmml/pmml_swig/PMMLBasicsTest.py
@@ -0,0 +1,86 @@
+# -*- coding: utf-8 -*-
+
+# imports Salomé
+from PMML import PMMLlib, kANN, kLR
+
+# imports python
+import unittest
+import exceptions
+from exceptions import RuntimeError
+import os
+import shutil
+
+class PMMLBasicsTest(unittest.TestCase):
+
+    def setUp(self):
+        pmmlRootDir = os.getenv("YACS_ROOT_DIR");
+        self.resourcesDir = os.path.join(pmmlRootDir,"share","salome","resources","pmml");
+        self.resourcesDir += os.sep ;
+        self.tmpDir = "/tmp/";
+        self.tmpDir += os.environ['LOGNAME']; # ("USER");
+        self.tmpDir += "/PmmlUnitTest/";
+        if ( not os.path.exists(self.tmpDir) ):
+            os.mkdir(self.tmpDir);
+            pass
+        pass
+
+    def tearDown(self):
+        if ( os.path.exists(self.tmpDir) ):
+            shutil.rmtree(self.tmpDir);
+            pass 
+        pass
+
+    def testExportPythonNeuralNet(self):
+        pmmlFile = self.resourcesDir + "ann_model.pmml";
+        model = "sANNName";
+        exportPyScript = self.tmpDir + "swigTestExportPythonNeuralNet.py";
+        refPyFilename = self.resourcesDir + "unittest_ref_ann_model.py";
+        refLines = file(refPyFilename).readlines(); 
+        #
+        p = PMMLlib( pmmlFile );
+        p.SetCurrentModel( model, kANN );
+        p.ExportPython( exportPyScript, "myTestFunc", 
+                        "File used by unit test\n PMMLBasicsTest1::testExportNeuralNetworkPython" );
+        myLines = file(exportPyScript).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.resourcesDir + "lr_model.pmml";
+        model = "Modeler[LinearRegression]Tds[steamplant]Predictor[x6:x8:x6x8:x6x6x8]Target[x1]";
+        exportPyScript = self.tmpDir + "swigTestExportPythonRegression.py";
+        refPyFilename = self.resourcesDir + "unittest_ref_lr_model.py";
+        refLines = file(refPyFilename).readlines(); 
+        #
+        p = PMMLlib( pmmlFile );
+        p.SetCurrentModel( model, kLR );
+        p.ExportPython( exportPyScript, "myTestFunc", 
+                               "File used by unit test\n PMMLBasicsTest1::testExportLinearRegressionPython" );
+        myLines = file(exportPyScript).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.resourcesDir + "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()