Merge pull request #27 from kouwenhovenlab/master

sync from lab repo

plottr/data/datadict.py

@@ -936,7 +936,8 @@ def guess_shape_from_datadict(data: DataDict) -> \
 
 def datadict_to_meshgrid(data: DataDict,
                          target_shape: Union[Tuple[int, ...], None] = None,
-                         inner_axis_order: Union[None, List[str]] = None) \
+                         inner_axis_order: Union[None, List[str]] = None,
+                         use_existing_shape: bool = False) \
         -> MeshgridDataDict:
     """
     Try to make a meshgrid from a dataset.
@@ -951,6 +952,10 @@ def datadict_to_meshgrid(data: DataDict,
                              specified axes in all but order.
                              The data is then transposed to conform to the
                              specified order.
+    :param use_existing_shape: if ``True``, simply use the shape that the data
+                               already has. For numpy-array data, this might
+                               already be present.
+                               if ``False``, flatten and reshape.
     :return: the generated ``MeshgridDataDict``.
     """
 
@@ -961,6 +966,11 @@ def datadict_to_meshgrid(data: DataDict,
     if not data.axes_are_compatible():
         raise ValueError('Non-compatible axes, cannot grid that.')
 
+    if not use_existing_shape and data.is_expandable():
+        data = data.expand()
+    elif use_existing_shape:
+        target_shape = data.dependents()[0].shape
+
     # guess what the shape likely is.
     if target_shape is None:
         shp_specs = guess_shape_from_datadict(data)

plottr/data/qcodes_dataset.py

@@ -159,7 +159,7 @@ def get_data_from_ds(ds: DataSet, start: Optional[int] = None,
     with `start` and `end` only a subset of rows in the DB can be specified.
     """
     names = [n for n, v in ds.paramspecs.items()]
-    return {n : ds.get_data(n, start=start, end=end) for n in names}
+    return {n : np.squeeze(ds.get_data(n, start=start, end=end)) for n in names}
 
 
 def get_all_data_from_ds(ds: DataSet) -> Dict[str, List[List]]:
@@ -171,39 +171,39 @@ def get_all_data_from_ds(ds: DataSet) -> Dict[str, List[List]]:
     return get_data_from_ds(ds)
 
 
-def expand(data: Dict[str, List[List]],
-           copy=True) -> Dict[str, np.ndarray]:
-    """
-    Expands data to get us everying expanded into columns of the same length.
-    To achieve the same length, data will be repeated along the most inner
-    axis if necessary.
-
-    Arguments:
-        data: dictionary in the form {'name' : [[row1], [row2], ...], ...}.
-            the values are thus exactly what dataset.get_data('name') will return.
-    """
-    if copy:
-        data = deepcopy(data)
-
-    inner_len = 1
-    for k, v in data.items():
-        if len(v) == 0:
-            return data
-
-        if type(v[0][0]) not in [list, np.ndarray]:
-            continue
-        else:
-            inner_len = len(v[0][0])
-            break
-
-    for k, v in data.items():
-        v = np.array(v)
-        if inner_len > 1 and v.shape[-1] == 1:
-            v = np.repeat(v, inner_len, axis=-1)
-        v = v.reshape(-1)
-        data[k] = v
-
-    return data
+# def expand(data: Dict[str, List[List]],
+#            copy=True) -> Dict[str, np.ndarray]:
+#     """
+#     Expands data to get us everying expanded into columns of the same length.
+#     To achieve the same length, data will be repeated along the most inner
+#     axis if necessary.
+#
+#     Arguments:
+#         data: dictionary in the form {'name' : [[row1], [row2], ...], ...}.
+#             the values are thus exactly what dataset.get_data('name') will return.
+#     """
+#     if copy:
+#         data = deepcopy(data)
+#
+#     inner_len = 1
+#     for k, v in data.items():
+#         if len(v) == 0:
+#             return data
+#
+#         if type(v[0][0]) not in [list, np.ndarray]:
+#             continue
+#         else:
+#             inner_len = len(v[0][0])
+#             break
+#
+#     for k, v in data.items():
+#         v = np.array(v)
+#         if inner_len > 1 and v.shape[-1] == 1:
+#             v = np.repeat(v, inner_len, axis=-1)
+#         v = v.reshape(-1)
+#         data[k] = v
+#
+#     return data
 
 
 def ds_to_datadict(ds: DataDict, start: Optional[int] = None,
@@ -212,7 +212,8 @@ def ds_to_datadict(ds: DataDict, start: Optional[int] = None,
     Make a datadict from a qcodes dataset.
     `start` and `end` allow selection of only a subset of rows.
     """
-    data = expand(get_data_from_ds(ds, start=start, end=end))
+    # data = expand(get_data_from_ds(ds, start=start, end=end))
+    data = get_data_from_ds(ds, start=start, end=end)
     struct = get_ds_structure(ds)
     datadict = DataDict(**struct)
     for k, v in data.items():

plottr/node/dim_reducer.py

@@ -612,7 +612,7 @@ def validateOptions(self, data):
                 self.logger().debug(f'x-Axis is None. this will result in empty output data.')
                 return False
             elif self._xyAxes[0] not in availableAxes:
-                self.logger().warning(f'x-Axis {self._xyAxis[0]} not present in data')
+                self.logger().warning(f'x-Axis {self._xyAxes[0]} not present in data')
                 return False
 
             if self._xyAxes[1] is None: