Fix bugs with pint quantity input, column iteration

proplot/axes/plot.py

@@ -1153,6 +1153,16 @@ def _load_objects():
 
 
 # Standardization utilities
+def _is_array(data):
+    """
+    Test whether input is numpy array or pint quantity.
+    """
+    # NOTE: This is used in _iter_columns to identify 2D matrices that
+    # should be iterated over and omit e.g. scalar marker size or marker color.
+    _load_objects()
+    return isinstance(data, ndarray) or ndarray is not Quantity and isinstance(data, Quantity)  # noqa: E501
+
+
 def _is_numeric(data):
     """
     Test whether input is numeric array rather than datetime or strings.
@@ -1222,6 +1232,7 @@ def _safe_mask(mask, *args):
     Safely apply the mask to the input arrays, accounting for existing masked
     or invalid values. Values matching ``False`` are set to `np.nan`.
     """
+    _load_objects()
     invalid = ~mask  # True if invalid
     args_masked = []
     for arg in args:
@@ -1248,6 +1259,7 @@ def _safe_range(data, lo=0, hi=100, automin=True, automax=True):
     for masked values. Use min and max functions when possible for speed. Return
     ``None`` if we faile to get a valid range.
     """
+    _load_objects()
     units = 1
     if ndarray is not Quantity and isinstance(data, Quantity):
         data, units = data.magnitude, data.units
@@ -1369,10 +1381,10 @@ def _get_labels(data, axis=0, always=True):
     # data values metadata but that is incorrect. The paradigm for 1D plots
     # is we have row coordinates representing x, data values representing y,
     # and column coordinates representing individual series.
-    if axis not in (0, 1, 2):
-        raise ValueError(f'Invalid axis {axis}.')
     labels = None
     _load_objects()
+    if axis not in (0, 1, 2):
+        raise ValueError(f'Invalid axis {axis}.')
     if isinstance(data, (ndarray, Quantity)):
         if not always:
             pass
@@ -1446,6 +1458,7 @@ def _get_units(data):
     Get the unit string from the `xarray.DataArray` attributes or the
     `pint.Quantity`. Format the latter with :rcraw:`unitformat`.
     """
+    _load_objects()
     # Get units from the attributes
     if ndarray is not DataArray and isinstance(data, DataArray):
         units = data.attrs.get('units', None)
@@ -1859,6 +1872,7 @@ def _redirect_or_standardize(self, *args, **kwargs):
                         kwargs[key] = _get_data(data, kwargs[key])
 
                 # Auto-setup matplotlib with the input unit registry
+                _load_objects()
                 for arg in args:
                     if ndarray is not DataArray and isinstance(arg, DataArray):
                         arg = arg.data
@@ -2939,10 +2953,9 @@ def _iter_columns(self, *args, label=None, labels=None, values=None, **kwargs):
         keyword arguments using the input label-list ``'labels'``.
         """
         # Handle cycle args and label lists
-        # WARNING: Must convert to ndarray or can get singleton DataArrays
-        # WARNING: We do not handle color cycling here because we want to allow
-        # iterating over columns of scatter() color arrays. Handle in _parse_cycle().
-        n = max(1 if a.ndim < 2 else a.shape[1] for a in args if isinstance(a, ndarray))
+        # NOTE: Arrays here should have had metadata stripped by _standardize_1d
+        # but could still be pint quantities that get processed by axis converter.
+        n = max(1 if not _is_array(a) or a.ndim < 2 else a.shape[-1] for a in args)
         labels = _not_none(label=label, values=values, labels=labels)
         if not np.iterable(labels) or isinstance(labels, str):
             labels = n * [labels]
@@ -2957,10 +2970,7 @@ def _iter_columns(self, *args, label=None, labels=None, values=None, **kwargs):
         for i in range(n):
             kw = kwargs.copy()
             kw['label'] = labels[i] or None
-            a = tuple(
-                a if not isinstance(a, ndarray) or a.ndim == 1 else a[:, i]
-                for a in args
-            )
+            a = tuple(a if not _is_array(a) or a.ndim < 2 else a[..., i] for a in args)
             yield (i, n, *a, kw)
 
     def _parse_cycle(