Fix issue with contours of 2d dataframes

Author: lukelbd

docs/2dplots.py

@@ -272,19 +272,20 @@
 
 # DataArray
 state = np.random.RandomState(51423)
-data = 50 * (
-    np.sin(np.linspace(0, 2 * np.pi, 20) + 0) ** 2
-    * np.cos(np.linspace(0, np.pi, 20) + np.pi / 2)[:, None] ** 2
+linspace = np.linspace(0, np.pi, 20)
+data = 50 * state.normal(1, 0.2, size=(20, 20)) * (
+    np.sin(linspace * 2) ** 2
+    * np.cos(linspace + np.pi / 2)[:, None] ** 2
 )
 lat = xr.DataArray(
     np.linspace(-90, 90, 20),
     dims=('lat',),
-    attrs={'units': 'degN'}
+    attrs={'units': 'deg_north'}
 )
 plev = xr.DataArray(
     np.linspace(1000, 0, 20),
     dims=('plev',),
-    attrs={'long_name': 'pressure', 'units': 'hPa'}
+    attrs={'long_name': 'pressure', 'units': 'mb'}
 )
 da = xr.DataArray(
     data,
@@ -295,14 +296,14 @@
 )
 
 # DataFrame
-data = state.rand(20, 20)
+data = state.rand(12, 20)
 df = pd.DataFrame(
-    data.cumsum(axis=0).cumsum(axis=1),
-    index=[*'JFMAMJJASONDJFMAMJJA']
+    (data - 0.4).cumsum(axis=0).cumsum(axis=1),
+    index=list('JFMAMJJASOND'),
 )
 df.name = 'temporal data'
-df.index.name = 'index'
-df.columns.name = 'time (days)'
+df.index.name = 'month'
+df.columns.name = 'variable (units)'
 
 # %%
 import proplot as plot
@@ -311,13 +312,13 @@
 
 # Plot DataArray
 axs[0].contourf(
-    da, cmap='RdPu', cmap_kw={'left': 0.05}, colorbar='l', lw=0.7, color='gray7'
+    da, cmap='RdPu', cmap_kw={'left': 0.05}, colorbar='l', lw=0.7, color='k'
 )
 axs[0].format(yreverse=True)
 
 # Plot DataFrame
 axs[1].contourf(
-    df, cmap='YlOrRd', colorbar='r', linewidth=0.7, color='gray7'
+    df, cmap='YlOrRd', colorbar='r', linewidth=0.7, color='k'
 )
 axs[1].format(xtickminor=False)
 

proplot/axes/plot.py

@@ -251,7 +251,7 @@ def _is_string(data):
     return len(data) and isinstance(_to_ndarray(data).flat[0], str)
 
 
-def _to_array(data):
+def _to_arraylike(data):
     """
     Convert list of lists to array-like type.
     """
@@ -434,7 +434,7 @@ def standardize_1d(self, func, *args, **kwargs):
         ys, args = (y, args[0]), args[1:]
     else:
         ys = (y,)
-    ys = [_to_array(y) for y in ys]
+    ys = [_to_arraylike(y) for y in ys]
 
     # Auto x coords
     y = ys[0]  # test the first y input
@@ -444,7 +444,7 @@ def standardize_1d(self, func, *args, **kwargs):
             or any(kwargs.get(s, None) for s in ('means', 'medians'))
         )
         x, _ = _axis_labels_title(y, axis=axis)
-    x = _to_array(x)
+    x = _to_arraylike(x)
     if x.ndim != 1:
         raise ValueError(
             f'x coordinates must be 1-dimensional, but got {x.ndim}.'
@@ -637,7 +637,7 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
     # Ensure DataArray, DataFrame or ndarray
     Zs = []
     for Z in args:
-        Z = _to_array(Z)
+        Z = _to_arraylike(Z)
         if Z.ndim != 2:
             raise ValueError(f'Z must be 2-dimensional, got shape {Z.shape}.')
         Zs.append(Z)
@@ -649,10 +649,12 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
     # Retrieve coordinates
     if x is None and y is None:
         Z = Zs[0]
-        if order == 'C':  # TODO: check order stuff works
+        if order == 'C':
             idx, idy = 1, 0
         else:
             idx, idy = 0, 1
+        # x = np.arange(Z.shape[idx])
+        # y = np.arange(Z.shape[idy])
         if isinstance(Z, ndarray):
             x = np.arange(Z.shape[idx])
             y = np.arange(Z.shape[idy])
@@ -667,8 +669,19 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
                 x = Z.index
                 y = Z.columns
 
+    # Optionally re-order
+    # TODO: Double check this
+    if order == 'F':
+        x, y = x.T, y.T  # in case they are 2-dimensional
+        Zs = tuple(Z.T for Z in Zs)
+    elif order != 'C':
+        raise ValueError(
+            f'Invalid order {order!r}. Choose from '
+            '"C" (row-major, default) and "F" (column-major).'
+        )
+
     # Check coordinates
-    x, y = _to_array(x), _to_array(y)
+    x, y = _to_arraylike(x), _to_arraylike(y)
     if x.ndim != y.ndim:
         raise ValueError(
             f'x coordinates are {x.ndim}-dimensional, '
@@ -691,7 +704,7 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
             kw['xlocator'] = mticker.FixedLocator(xi)
             kw['xformatter'] = mticker.IndexFormatter(x)
             kw['xminorlocator'] = mticker.NullLocator()
-        if _is_string(x):
+        if _is_string(y):
             yi = np.arange(len(y))
             kw['ylocator'] = mticker.FixedLocator(yi)
             kw['yformatter'] = mticker.IndexFormatter(y)
@@ -750,17 +763,6 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
                     f'Z borders {tuple(i+1 for i in Z.shape)}.'
                 )
 
-        # Optionally re-order
-        # TODO: Double check this
-        if order == 'F':
-            x, y = x.T, y.T  # in case they are 2-dimensional
-            Zs = (Z.T for Z in Zs)
-        elif order != 'C':
-            raise ValueError(
-                f'Invalid order {order!r}. Choose from '
-                '"C" (row-major, default) and "F" (column-major).'
-            )
-
     # Enforce centers
     else:
         # Get centers given edges. If 2d, don't raise error, let matplotlib
@@ -793,17 +795,6 @@ def standardize_2d(self, func, *args, order='C', globe=False, **kwargs):
                     f'or Z borders {tuple(i+1 for i in Z.shape)}.'
                 )
 
-        # Optionally re-order
-        # TODO: Double check this
-        if order == 'F':
-            x, y = x.T, y.T  # in case they are 2-dimensional
-            Zs = (Z.T for Z in Zs)
-        elif order != 'C':
-            raise ValueError(
-                f'Invalid order {order!r}. Choose from '
-                '"C" (row-major, default) and "F" (column-major).'
-            )
-
     # Cartopy projection axes
     if (
         getattr(self, 'name', '') == 'cartopy'