Added test to reject float16; fixed typos

jorisvandenbossche · Dec 16, 2016 · ffcf0c2 · ffcf0c2
1 parent 1f208a8
commit ffcf0c2
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Showing 2 changed files with 31 additions and 23 deletions.
diff --git a/pandas/tools/merge.py b/pandas/tools/merge.py
@@ -1013,7 +1013,7 @@ def _asof_by_function(on_type, by_type):
     'object': _ensure_object,
 }
 
-_cyton_types = {
+_cython_types = {
     'uint8': 'uint8_t',
     'uint32': 'uint32_t',
     'uint16': 'uint16_t',
@@ -1031,7 +1031,7 @@ def _asof_by_function(on_type, by_type):
 def _get_cython_type(dtype):
     """ Given a dtype, return a C name like 'int64_t' or 'double' """
     type_name = _get_dtype(dtype).name
-    ctype = _cyton_types.get(type_name, 'object')
+    ctype = _cython_types.get(type_name, 'object')
     if ctype == 'error':
         raise MergeError('unsupported type: ' + type_name)
     return ctype

diff --git a/pandas/tools/tests/test_merge_asof.py b/pandas/tools/tests/test_merge_asof.py
@@ -657,7 +657,7 @@ def test_on_specialized_type(self):
         # GH13936
         for dtype in [np.uint8, np.uint16, np.uint32, np.uint64,
                       np.int8, np.int16, np.int32, np.int64,
-                      np.float32, np.float64]:
+                      np.float16, np.float32, np.float64]:
             df1 = pd.DataFrame({
                 'value': [5, 2, 25, 100, 78, 120, 79],
                 'symbol': list("ABCDEFG")},
@@ -672,22 +672,26 @@ def test_on_specialized_type(self):
 
             df1 = df1.sort_values('value').reset_index(drop=True)
 
-            result = pd.merge_asof(df1, df2, on='value')
+            if dtype == np.float16:
+                with self.assertRaises(MergeError):
+                    pd.merge_asof(df1, df2, on='value')
+            else:
+                result = pd.merge_asof(df1, df2, on='value')
 
-            expected = pd.DataFrame({
-                'symbol': list("BACEGDF"),
-                'value': [2, 5, 25, 78, 79, 100, 120],
-                'result': list('xxxxxyz')},
-                columns=['symbol', 'value', 'result'])
-            expected.value = dtype(expected.value)
+                expected = pd.DataFrame({
+                    'symbol': list("BACEGDF"),
+                    'value': [2, 5, 25, 78, 79, 100, 120],
+                    'result': list('xxxxxyz')},
+                    columns=['symbol', 'value', 'result'])
+                expected.value = dtype(expected.value)
 
-            assert_frame_equal(result, expected)
+                assert_frame_equal(result, expected)
 
     def test_on_specialized_type_by_int(self):
         # GH13936
         for dtype in [np.uint8, np.uint16, np.uint32, np.uint64,
                       np.int8, np.int16, np.int32, np.int64,
-                      np.float32, np.float64]:
+                      np.float16, np.float32, np.float64]:
             df1 = pd.DataFrame({
                 'value': [5, 2, 25, 100, 78, 120, 79],
                 'key': [1, 2, 3, 2, 3, 1, 2],
@@ -704,17 +708,21 @@ def test_on_specialized_type_by_int(self):
 
             df1 = df1.sort_values('value').reset_index(drop=True)
 
-            result = pd.merge_asof(df1, df2, on='value', by='key')
-
-            expected = pd.DataFrame({
-                'symbol': list("BACEGDF"),
-                'key': [2, 1, 3, 3, 2, 2, 1],
-                'value': [2, 5, 25, 78, 79, 100, 120],
-                'result': [np.nan, 'x', np.nan, np.nan, np.nan, 'y', 'x']},
-                columns=['symbol', 'key', 'value', 'result'])
-            expected.value = dtype(expected.value)
-
-            assert_frame_equal(result, expected)
+            if dtype == np.float16:
+                with self.assertRaises(MergeError):
+                    pd.merge_asof(df1, df2, on='value', by='key')
+            else:
+                result = pd.merge_asof(df1, df2, on='value', by='key')
+
+                expected = pd.DataFrame({
+                    'symbol': list("BACEGDF"),
+                    'key': [2, 1, 3, 3, 2, 2, 1],
+                    'value': [2, 5, 25, 78, 79, 100, 120],
+                    'result': [np.nan, 'x', np.nan, np.nan, np.nan, 'y', 'x']},
+                    columns=['symbol', 'key', 'value', 'result'])
+                expected.value = dtype(expected.value)
+
+                assert_frame_equal(result, expected)
 
     def test_on_float_by_int(self):
         # type specialize both "by" and "on" parameters