Change 'autoformat' from Figure kwarg to rc setting

Author: lukelbd

proplot/axes/plot.py

@@ -66,8 +66,7 @@
     Whether *x* axis labels, *y* axis labels, axis formatters, axes titles,
     colorbar labels, and legend labels are automatically configured when
     a `~pandas.Series`, `~pandas.DataFrame` or `~xarray.DataArray` is passed
-    to the plotting command. Default is the figure-wide
-    `proplot.figure.Figure.autoformat` setting.
+    to the plotting command. Default is :rc:`autoformat`.
 """
 
 docstring.snippets['axes.cmap_changer'] = """
@@ -458,7 +457,6 @@ def standardize_1d(self, func, *args, autoformat=None, **kwargs):
     # Sanitize input
     # TODO: Add exceptions for methods other than 'hist'?
     name = func.__name__
-    autoformat = _not_none(autoformat, self.figure._auto_format)
     _load_objects()
     if not args:
         return func(self, *args, **kwargs)
@@ -554,7 +552,8 @@ def standardize_1d(self, func, *args, autoformat=None, **kwargs):
 
     # WARNING: For some functions, e.g. boxplot and violinplot, we *require*
     # cycle_changer is also applied so it can strip 'x' input.
-    with _state_context(self, _auto_format=autoformat):
+    autoformat = _not_none(autoformat, rc['autoformat'])
+    with rc.context(autoformat=autoformat):
         return func(self, x, *ys, *args, **kwargs)
 
 
@@ -679,7 +678,6 @@ def standardize_2d(
     """
     # Sanitize input
     name = func.__name__
-    autoformat = _not_none(autoformat, self.figure._auto_format)
     _load_objects()
     if not args:
         return func(self, *args, **kwargs)
@@ -933,7 +931,8 @@ def standardize_2d(
         kwargs['latlon'] = False
 
     # Finally return result
-    with _state_context(self, _auto_format=autoformat):
+    autoformat = _not_none(autoformat, rc['autoformat'])
+    with rc.context(autoformat=autoformat):
         return func(self, x, y, *Zs, **kwargs)
 
 
@@ -1100,20 +1099,22 @@ def indicate_error(
         calculated automatically).
     boxstds, boxpctiles, boxdata : optional
         As with `barstds`, `barpctiles`, and `bardata`, but for *thicker error bars*
-        representing a smaller interval than thick error bars. If `boxstds` is
+        representing a smaller interval than the thin error bars. If `boxstds` is
         ``True``, the default standard deviation multiples ``(-1, 1)`` are used.
         If `boxpctiles` is ``True``, the default percentile multiples ``(25, 75)``
-        (i.e. the interquartile range) are used. When boxes and bars are combined, this
+        are used (i.e. the interquartile range). When boxes and bars are combined, this
         has the effect of drawing miniature box-and-whisker plots.
     shadestds, shadepctiles, shadedata : optional
         As with `barstds`, `barpctiles`, and `bardata`, but using *shading* to indicate
         the error range. If `shadestds` is ``True``, the default standard deviation
         multiples ``(-2, 2)`` are used. If `shadepctiles` is ``True``, the default
-        percentile multiples ``(5, 95)`` are used. Shading is generally useful for
+        percentile multiples ``(10, 90)`` are used. Shading is generally useful for
         `~matplotlib.axes.Axes.plot` plots and not `~matplotlib.axes.Axes.bar` plots.
     fadestds, fadepctiles, fadedata : optional
         As with `shadestds`, `shadepctiles`, and `shadedata`, but for an additional,
-        more faded, *secondary* shaded region.
+        more faded, *secondary* shaded region. If `fadestds` is ``True``, the default
+        standard deviation multiples ``(-3, 3)`` are used. If `fadepctiles` is ``True``,
+        the default percentile multiples ``(0, 100)`` are used.
     barcolor, boxcolor, shadecolor, fadecolor : color-spec, optional
         Colors for the different error indicators. For error bars, the default is
         ``'k'``. For shading, the default behavior is to inherit color from the
@@ -2255,7 +2256,7 @@ def cycle_changer(
     # NOTE: Requires standardize_1d wrapper before reaching this. Also note
     # that the 'x' coordinates are sometimes ignored below.
     name = func.__name__
-    autoformat = self._auto_format  # possibly manipulated by standardize_[12]d
+    autoformat = rc['autoformat']  # possibly manipulated by standardize_[12]d
     if not args:
         return func(self, *args, **kwargs)
     x, y, *args = args
@@ -2846,7 +2847,7 @@ def cmap_changer(
     of the color selections.
     """
     name = func.__name__
-    autoformat = self._auto_format  # possibly manipulated by standardize_[12]d
+    autoformat = rc['autoformat']  # possibly manipulated by standardize_[12]d
     if not args:
         return func(self, *args, **kwargs)
 

proplot/figure.py

@@ -124,14 +124,17 @@ class Figure(mfigure.Figure):
     Figure dimensions may be automatically scaled to preserve subplot aspect
     ratios.
     """
+    # NOTE: If _rename_kwargs argument is an invalid identifier, it is
+    # simply used in the warning message.
+    @warnings._rename_kwargs('0.6.4', autoformat='plot.rc.autoformat = {}')
     def __init__(
         self, tight=None,
         ref=1, pad=None, axpad=None, panelpad=None, includepanels=False,
         span=None, spanx=None, spany=None,
         align=None, alignx=None, aligny=None,
         share=None, sharex=None, sharey=None,
-        autoformat=True, fallback_to_cm=None,
         gridspec_kw=None, subplots_kw=None, subplots_orig_kw=None,
+        fallback_to_cm=None,
         **kwargs
     ):
         """
@@ -189,11 +192,6 @@ def __init__(
 <https://matplotlib.org/3.1.1/gallery/subplots_axes_and_figures/align_labels_demo.html>`__
             for the *x* axis, *y* axis, or both axes. Only has an effect when `spanx`,
             `spany`, or `span` are ``False``. Default is :rc:`subplots.align`.
-        autoformat : bool, optional
-            Whether to automatically configure *x* axis labels, *y* axis labels,
-            axis formatters, axes titles, colorbar labels, and legend labels when
-            a `~pandas.Series`, `~pandas.DataFrame` or `~xarray.DataArray` with
-            relevant metadata is passed to a plotting command.
         fallback_to_cm : bool, optional
             Whether to replace unavailable glyphs with a glyph from Computer Modern
             or the "¤" dummy character. See `mathtext \
@@ -266,7 +264,6 @@ def __init__(
         self._pad = units(_not_none(pad, rc['subplots.pad']))
         self._axpad = units(_not_none(axpad, rc['subplots.axpad']))
         self._panelpad = units(_not_none(panelpad, rc['subplots.panelpad']))
-        self._auto_format = autoformat
         self._auto_tight = _not_none(tight, rc['subplots.tight'])
         self._include_panels = includepanels
         self._fallback_to_cm = fallback_to_cm
@@ -1402,9 +1399,9 @@ def _iter_axes(self, hidden=False, children=False):
     # Deprecations
     # NOTE: None of these even *worked* after drawing the figure. And not sure
     # what value (if any) they add even if we do get them to work.
-    get_alignx, set_alignx = warnings._read_only_property('0.6', 'alignx')
-    get_aligny, set_aligny = warnings._read_only_property('0.6', 'aligny')
-    get_sharex, set_sharex = warnings._read_only_property('0.6', 'sharex')
-    get_sharey, set_sharey = warnings._read_only_property('0.6', 'sharey')
-    get_spanx, set_spanx = warnings._read_only_property('0.6', 'spanx')
-    get_spany, set_spany = warnings._read_only_property('0.6', 'spany')
+    get_alignx, set_alignx = warnings._deprecate_getter_setter('0.6', 'alignx')
+    get_aligny, set_aligny = warnings._deprecate_getter_setter('0.6', 'aligny')
+    get_sharex, set_sharex = warnings._deprecate_getter_setter('0.6', 'sharex')
+    get_sharey, set_sharey = warnings._deprecate_getter_setter('0.6', 'sharey')
+    get_spanx, set_spanx = warnings._deprecate_getter_setter('0.6', 'spanx')
+    get_spany, set_spany = warnings._deprecate_getter_setter('0.6', 'spany')

proplot/internals/rcsetup.py

@@ -285,15 +285,21 @@
         'bold',
         'a-b-c label font weight.'
     ),
+    'autoformat': (
+        True,
+        'Whether to automatically apply labels from `pandas.Series`, '
+        '`pandas.DataFrame`, and `xarray.DataArray` objects passed to '
+        'plotting functions.'
+    ),
 
     # Axes additions
     'alpha': (
-        1,
+        1.0,
         'The opacity of the background axes patch.'
     ),
     'axes.alpha': (
         1.0,
-        'Opacity of the background axes patch.'
+        'The opacity of the background axes patch.'
     ),
     'formatter.timerotation': (
         90,

proplot/internals/warnings.py

@@ -27,7 +27,7 @@ def _warn_proplot(message):
         warnings.warn(message, stacklevel=2)
 
 
-def _read_only_property(version, property):
+def _deprecate_getter_setter(version, property):
     """
     Generate `set_name` and `get_name` methods for property setters and getters,
     and issue warnings when they are used.
@@ -80,15 +80,21 @@ def wrapper(*args, **kwargs):
 def _rename_kwargs(version, **kwargs_rename):
     """
     Emit a basic deprecation warning after removing or renaming function keyword
-    arguments. Each key should be an old keyword, and each arguments should be the
-    new keyword or a tuple of new keyword options.
+    arguments. Each key should be an old keyword, and each argument should be the
+    new keyword or *instructions* for what to use instead.
     """
     def decorator(func_orig):
         @functools.wraps(func_orig)
         def wrapper(*args, **kwargs):
             for key_old, key_new in kwargs_rename.items():
                 if key_old in kwargs:
-                    kwargs[key_new] = kwargs.pop(key_old)
+                    value = kwargs.pop(key_old)
+                    if key_new.isidentifier():
+                        # Rename argument
+                        kwargs[key_new] = value
+                    elif '{}' in key_new:
+                        # Nice warning message, but user's desired behavior fails
+                        key_new = key_new.format(value)
                     _warn_proplot(
                         f'Keyword arg {key_old!r} was deprecated in {version} and '
                         'will be removed in the next major release. '