add operation on numpy functions

src/pymodaq_data/numpy_func.py

@@ -170,3 +170,25 @@ def _allclose(dwa_a: 'DataWithAxes', dwa_b: 'DataWithAxes', *args,
                                         *args, **kwargs)) for ind in range(len(dwa_a))])
 
     return dwa
+
+
+# *************** other numpy function ****************
+
+@implements('flipud')
+def _flipud(dwa: 'DataWithAxes', *args, **kwargs):
+    dwa_func = dwa.deepcopy_with_new_data([np.flipud(data_array) for data_array in dwa])
+    return dwa_func
+
+
+@implements('fliplr')
+def _fliplr(dwa: 'DataWithAxes', *args, **kwargs):
+    dwa_func = dwa.deepcopy_with_new_data([np.fliplr(data_array) for data_array in dwa])
+    return dwa_func
+
+
+@implements('transpose')
+def _transpose(dwa: 'DataWithAxes', *args, **kwargs):
+    dwa_func = dwa.deepcopy_with_new_data([np.transpose(data_array) for data_array in dwa])
+    return dwa_func
+
+

tests/data_test.py

@@ -1578,4 +1578,19 @@ def test_all_close(self):
 
         assert not np.allclose(dwa_a, dwa_b * 0.1)
 
+    def test_flip_transpose_rotate(self):
+        dwa = data_mod.DataRaw('raw', units='', data=[DATA2D])
+
+        dwa_transform = np.flipud(dwa)
+        for ind in range(len(dwa)):
+            assert np.allclose(np.flipud(dwa[ind]), dwa_transform[ind])
+
+        dwa_transform = np.fliplr(dwa)
+        for ind in range(len(dwa)):
+            assert np.allclose(np.fliplr(dwa[ind]), dwa_transform[ind])
+
+        dwa_transform = np.transpose(dwa)
+        for ind in range(len(dwa)):
+            assert np.allclose(np.transpose(dwa[ind]), dwa_transform[ind])
+