tests/test_AnalyzerResult.py: add more tests

diff --git a/tests/test_AnalyzerResult.py b/tests/test_AnalyzerResult.py
index de06f89dd9226709fb661fca2a236d3f6db41221..94f953d356df5bcb2f9ee448a263f722fd71eed3 100755 (executable)
--- a/tests/test_AnalyzerResult.py
+++ b/tests/test_AnalyzerResult.py
@@ -2,6 +2,8 @@
 
 from unit_timeside import *
 from timeside.analyzer.core import *
+from numpy import ones, array
+from math import pi
 
 verbose = 0
 
@@ -35,9 +37,93 @@ class TestAnalyzerResult(TestCase):
         "list of lists result"
         self.result.value = [[0,1], [0,1,2]]
 
+    def testOnNumpyVectorOfFloat(self):
+        "numpy vector of float"
+        self.result.value = ones(2, dtype = 'float') * pi
+
+    def testOnNumpy2DArrayOfFloat64(self):
+        "numpy 2d array of float64"
+        self.result.value = ones([2,3], dtype = 'float64') * pi
+
+    def testOnNumpy3DArrayOfInt32(self):
+        "numpy 3d array of int32"
+        self.result.value = ones([2,3,2], dtype = 'int32') * pi
+
+    def testOnNumpyArrayOfStrings(self):
+        "numpy array of strings"
+        self.result.value = array(['hello', 'hola'])
+
+    def testOnEmptyList(self):
+        "empty list"
+        self.result.value = []
+
+    def testOnNone(self):
+        "None"
+        self.result.value = None
+
+    def testOnUnicode(self):
+        "None"
+        self.result.value = None
+
     def tearDown(self):
         pass
 
+good_numpy_data_types = [
+    'float64',
+    'float32',
+    'float16',
+    'int64',
+    'int16',
+    'int32',
+    'int8',
+    'uint16',
+    'uint32',
+    'uint64',
+    'uint8',
+]
+
+bad_numpy_data_types = [
+    # not understood by json or yaml
+    'float128',
+    # complex can not be serialized in json
+    'complex256',
+    'complex128',
+    'complex64',
+    # ?
+    'datetime64',
+    'timedelta64',
+    ]
+
+def create_good_method_func (numpy_data_type):
+    def method(self):
+        "numpy %s" % numpy_data_type
+        import numpy
+        self.result.value = getattr(numpy, numpy_data_type)(pi)
+    return method
+
+def create_bad_method_func (numpy_data_type):
+    def method(self):
+        "numpy %s" % numpy_data_type
+        import numpy
+        try:
+            value = getattr(numpy, numpy_data_type)(pi)
+        except ValueError:
+            value = getattr(numpy, numpy_data_type)()
+        self.assertRaises(TypeError, self.result.__setattr__, 'value', value)
+    return method
+
+for numpy_data_type in good_numpy_data_types:
+    test_method = create_good_method_func (numpy_data_type)
+    test_method.__name__ = 'testOnNumpy_%s' % numpy_data_type
+    test_method.__doc__ = 'groks a numpy %s' % numpy_data_type
+    setattr (TestAnalyzerResult, test_method.__name__, test_method)
+
+for numpy_data_type in bad_numpy_data_types:
+    test_method = create_bad_method_func (numpy_data_type)
+    test_method.__name__ = 'testOnNumpy_%s' % numpy_data_type
+    test_method.__doc__ = 'gasps on numpy %s' % numpy_data_type
+    setattr (TestAnalyzerResult, test_method.__name__, test_method)
+
 class TestAnalyzerResultNumpy(TestAnalyzerResult):
     """ test AnalyzerResult numpy serialize """