Changeset 86420e in git

Timestamp:

Aug 7, 2019, 10:18:55 AM (4 years ago)

Author:

Murray Heymann <heymann.murray@…>

Branches:

(u'jengelh-datetime', 'ceac47cbc86fe4a15902392bdbb9bd2ae0ea02c6')(u'spielwiese', '0604212ebb110535022efecad887940825b97c3f')

Children:

0696a360fd5622a1c1f3cf64fc8282f0ecf1b8bd

Parents:

bb8cdbbda3604b0b59579d1fa969c8d5ca30f07b

Message:

Update python testing

Location:

machine_learning

Files:

• ml_python/common/lookuptable.py (modified) (1 diff)
• ml_python/tests/common/test_lookuptable.py (modified) (1 diff)
• ml_python/tests/model/test_predictor.py (modified) (1 diff)
• mlpredict.c (modified) (5 diffs)
• mlpredict.h (modified) (1 diff)
• testml.c (modified) (2 diffs)

machine_learning/ml_python/common/lookuptable.py

@@ -116 +116 @@
         vectors, file_list = create_table(dictionary=dictionary,
                                           attempt_cached=False)
+
+def is_lookup_initialised():
+    """
+    Check whether the various files exist, return True if so, False
+    otherwise.
+    """
+    retvalue = True
+    tbz2_path = os.path.join(HELP_FILE_PATH, "helpfiles.tbz2")
+    if not os.path.isdir(HELP_FILE_PATH) or not os.path.isfile(tbz2_path):
+        retvalue = False
+    if not os.path.isfile(KEYWORDS_FILE):
+        retvalue = False
+    if not os.path.isfile(VECTORS_NPY) or not os.path.isfile(HELPFILE_NPY):
+        retvalue = False
+
+    return retvalue

machine_learning/ml_python/tests/common/test_lookuptable.py

@@ -47 +47 @@
         init_table_on_system()
 
+    def test_is_lookup_initialised(self):
+        tbz2_path = os.path.join(HELP_FILE_PATH, "helpfiles.tbz2")
+        os.remove(tbz2_path)
+        self.assertFalse(is_lookup_initialised())
+        init_table_on_system()
+        self.assertTrue(is_lookup_initialised())
+
+        os.remove(KEYWORDS_FILE)
+        self.assertFalse(is_lookup_initialised())
+        init_table_on_system()
+        self.assertTrue(is_lookup_initialised())
+
+        os.remove(VECTORS_NPY)
+        self.assertFalse(is_lookup_initialised())
+        init_table_on_system()
+        self.assertTrue(is_lookup_initialised())
+        
 
 if __name__ == '__main__':

machine_learning/ml_python/tests/model/test_predictor.py

@@ -33 +33 @@
         files = np.array(["file1", "file2", "file3"])
 
-        testvec = normalise_vector(np.array([1, 1, 1]))
+        testvec1 = normalise_vector(np.array([1, 1, 1]))
+        testvec2 = normalise_vector(np.array([1, 3, 10]))
 
         print("distance to 1")
-        print(vector_distance(testvec, vector1))
+        print("vec1:", vector_distance(testvec1, vector1))
+        print("vec2:", vector_distance(testvec2, vector1))
         print()
         print("distance to 2")
-        print(vector_distance(testvec, vector2))
+        print("vec1:", vector_distance(testvec1, vector2))
+        print("vec2:", vector_distance(testvec2, vector2))
         print()
         print("distance to 3")
-        print(vector_distance(testvec, vector3))
+        print("vec1:", vector_distance(testvec1, vector3))
+        print("vec2:", vector_distance(testvec2, vector2))
         print()
 
         predictor.fit(vectors, files)
-        prediction = predictor.predict(np.array([testvec]))
+        prediction = predictor.predict(np.array([]))
+        self.assertEqual(len(prediction), 0)
+        prediction = predictor.predict(np.array([testvec1]))
+        self.assertEqual(prediction[0], "file2")
+        self.assertEqual(len(prediction), 1)
+        prediction = predictor.predict(np.array([testvec1, testvec2]))
         print("Prediction:")
         print(prediction)
         self.assertEqual(prediction[0], "file2")
+        self.assertEqual(prediction[1], "file1")
+        self.assertEqual(len(prediction), 2)
 
 

machine_learning/mlpredict.c

@@ -21 +21 @@
 int ml_is_initialised()
 {
-        /*
-         * TODO
-         */
-        return 1;
+        int retvalue = 1;
+        int t_value = 0;
+        PyObject *pValue = NULL;
+
+        if (!Py_IsInitialized()) {
+                retvalue = 0;
+        } else {
+                /* python system is initialised */
+                pValue = call_python_function(LOOKUPTABLE, IS_LOOKUP_INITIALISED);
+                /* is this a boolean? */
+                if (pValue != NULL && PyBool_Check(pValue)) {
+                        t_value = PyObject_IsTrue(pValue);
+                        /* errors? */
+                        if (t_value == -1) {
+                                PyErr_Print();
+                                retvalue = 0;
+                        } else {
+                                /* no errors */
+                                retvalue = t_value;
+                        }
+                        Py_DECREF(pValue);
+                } else {
+                        retvalue = 0;
+                }
+        }
+        return retvalue;
 }
 
@@ -38 +60 @@
 int ml_initialise()
 {
-        char lookuptable[] = "common.lookuptable";
-        char init_table_on_system[] = "init_table_on_system";
         PyObject *pValue = NULL;
 
@@ -45 +65 @@
                 Py_Initialize();
         }
-        pValue = call_python_function(lookuptable, init_table_on_system);
+        pValue = call_python_function(LOOKUPTABLE, INIT_TABLE_ON_SYSTEM);
         if (pValue != NULL) {
                 Py_DECREF(pValue);
@@ -56 +76 @@
 
 /**
- * Finalize the python interpreter
+ * A wrapper for Py_Finalize, checking whether it is necessary in the first
+ * place.
  *
  * @return An integer: 1 if successful, 0 if not.
@@ -62 +83 @@
 int ml_finalise()
 {
+        int retvalue = 1;
         if (Py_IsInitialized()) {
                 Py_Finalize();
+                retvalue = 1;
+        } else {
+                retvalue = 0;
         }
-        return 1;
+        return retvalue;
 }
 

machine_learning/mlpredict.h

@@ -17 +17 @@
 #define HELP_FILE_URL   "ftp://jim.mathematik.uni-kl.de/pub/Math/Singular/src/4-1-2/doc.tbz2" 
 #define HELP_FILE_PATH  "helpfiles/singular"
+
+#define LOOKUPTABLE "common.lookuptable"
+#define IS_LOOKUP_INITIALISED "is_lookup_initialised"
+#define INIT_TABLE_ON_SYSTEM "init_table_on_system"
 
 /**

machine_learning/testml.c

@@ -1 +1 @@
 #include <stdio.h>
+#include <Python.h>
 #include "mlpredict.h"
 
@@ -9 +10 @@
                 return 1;
         }
+
+        i = ml_is_initialised();
+        printf("Returnvalue for ml_is_initialised: %d\n", i);
+        Py_Initialize();
+
+        i = ml_is_initialised();
+        printf("Returnvalue for ml_is_initialised: %d\n", i);
+
         i = ml_initialise();
-        printf("Returnvalue for initialise: %d\n", i);
+        printf("Returnvalue for ml_initialise: %d\n", i);
+
+        i = ml_is_initialised();
+        printf("Returnvalue for ml_is_initialised: %d\n", i);
 
         i = ml_finalise();
-        printf("Returnvalue for finalise: %d\n", i);
+        printf("Returnvalue for ml_finalise: %d\n", i);
 
         return 0;