"""
Colorbars are a visualization of the mapping from scalar values to colors.
In Matplotlib they are drawn into a dedicated `~.axes.Axes`.
.. note::
Colorbars are typically created through `.Figure.colorbar` or its pyplot
wrapper `.pyplot.colorbar`, which use `.make_axes` and `.Colorbar`
internally.
As an end-user, you most likely won't have to call the methods or
instantiate the classes in this module explicitly.
:class:`ColorbarBase`
The base class with full colorbar drawing functionality.
It can be used as-is to make a colorbar for a given colormap;
a mappable object (e.g., image) is not needed.
:class:`Colorbar`
On top of `.ColorbarBase` this connects the colorbar with a
`.ScalarMappable` such as an image or contour plot.
:class:`ColorbarPatch`
A specialized `.Colorbar` to support hatched contour plots.
:func:`make_axes`
Create an `~.axes.Axes` suitable for a colorbar. This functions can be
used with figures containing a single axes or with freely placed axes.
:func:`make_axes_gridspec`
Create a `~.SubplotBase` suitable for a colorbar. This function should
be used for adding a colorbar to a `.GridSpec`.
"""
import copy
import logging
import numpy as np
import matplotlib as mpl
import matplotlib.artist as martist
import matplotlib.cbook as cbook
import matplotlib.collections as collections
import matplotlib.colors as colors
import matplotlib.contour as contour
import matplotlib.cm as cm
import matplotlib.gridspec as gridspec
import matplotlib.patches as mpatches
import matplotlib.path as mpath
import matplotlib.ticker as ticker
import matplotlib.transforms as mtransforms
import matplotlib._layoutbox as layoutbox
import matplotlib._constrained_layout as constrained_layout
from matplotlib import docstring
_log = logging.getLogger(__name__)
_make_axes_param_doc = """
fraction : float, default: 0.15
Fraction of original axes to use for colorbar.
shrink : float, default: 1.0
Fraction by which to multiply the size of the colorbar.
aspect : float, default: 20
Ratio of long to short dimensions.
"""
_make_axes_other_param_doc = """
pad : float, default: 0.05 if vertical, 0.15 if horizontal
Fraction of original axes between colorbar and new image axes.
anchor : (float, float), optional
The anchor point of the colorbar axes.
Defaults to (0.0, 0.5) if vertical; (0.5, 1.0) if horizontal.
panchor : (float, float), or *False*, optional
The anchor point of the colorbar parent axes. If *False*, the parent
axes' anchor will be unchanged.
Defaults to (1.0, 0.5) if vertical; (0.5, 0.0) if horizontal.
"""
make_axes_kw_doc = _make_axes_param_doc + _make_axes_other_param_doc
colormap_kw_doc = """
============ ====================================================
Property Description
============ ====================================================
*extend* {'neither', 'both', 'min', 'max'}
If not 'neither', make pointed end(s) for out-of-
range values. These are set for a given colormap
using the colormap set_under and set_over methods.
*extendfrac* {*None*, 'auto', length, lengths}
If set to *None*, both the minimum and maximum
triangular colorbar extensions with have a length of
5% of the interior colorbar length (this is the
default setting). If set to 'auto', makes the
triangular colorbar extensions the same lengths as
the interior boxes (when *spacing* is set to
'uniform') or the same lengths as the respective
adjacent interior boxes (when *spacing* is set to
'proportional'). If a scalar, indicates the length
of both the minimum and maximum triangular colorbar
extensions as a fraction of the interior colorbar
length. A two-element sequence of fractions may also
be given, indicating the lengths of the minimum and
maximum colorbar extensions respectively as a
fraction of the interior colorbar length.
*extendrect* bool
If *False* the minimum and maximum colorbar extensions
will be triangular (the default). If *True* the
extensions will be rectangular.
*spacing* {'uniform', 'proportional'}
Uniform spacing gives each discrete color the same
space; proportional makes the space proportional to
the data interval.
*ticks* *None* or list of ticks or Locator
If None, ticks are determined automatically from the
input.
*format* None or str or Formatter
If None, `~.ticker.ScalarFormatter` is used.
If a format string is given, e.g., '%.3f', that is used.
An alternative `~.ticker.Formatter` may be given instead.
*drawedges* bool
Whether to draw lines at color boundaries.
*label* str
The label on the colorbar's long axis.
============ ====================================================
The following will probably be useful only in the context of
indexed colors (that is, when the mappable has norm=NoNorm()),
or other unusual circumstances.
============ ===================================================
Property Description
============ ===================================================
*boundaries* None or a sequence
*values* None or a sequence which must be of length 1 less
than the sequence of *boundaries*. For each region
delimited by adjacent entries in *boundaries*, the
color mapped to the corresponding value in values
will be used.
============ ===================================================
"""
colorbar_doc = """
Add a colorbar to a plot.
Function signatures for the :mod:`~matplotlib.pyplot` interface; all
but the first are also method signatures for the `~.Figure.colorbar` method::
colorbar(**kwargs)
colorbar(mappable, **kwargs)
colorbar(mappable, cax=cax, **kwargs)
colorbar(mappable, ax=ax, **kwargs)
Parameters
----------
mappable
The `matplotlib.cm.ScalarMappable` (i.e., `~matplotlib.image.AxesImage`,
`~matplotlib.contour.ContourSet`, etc.) described by this colorbar.
This argument is mandatory for the `.Figure.colorbar` method but optional
for the `.pyplot.colorbar` function, which sets the default to the current
image.
Note that one can create a `.ScalarMappable` "on-the-fly" to generate
colorbars not attached to a previously drawn artist, e.g. ::
fig.colorbar(cm.ScalarMappable(norm=norm, cmap=cmap), ax=ax)
cax : `~matplotlib.axes.Axes`, optional
Axes into which the colorbar will be drawn.
ax : `~matplotlib.axes.Axes`, list of Axes, optional
Parent axes from which space for a new colorbar axes will be stolen.
If a list of axes is given they will all be resized to make room for the
colorbar axes.
use_gridspec : bool, optional
If *cax* is ``None``, a new *cax* is created as an instance of Axes. If
*ax* is an instance of Subplot and *use_gridspec* is ``True``, *cax* is
created as an instance of Subplot using the :mod:`~.gridspec` module.
Returns
-------
colorbar : `~matplotlib.colorbar.Colorbar`
See also its base class, `~matplotlib.colorbar.ColorbarBase`.
Notes
-----
Additional keyword arguments are of two kinds:
axes properties:
%s
colorbar properties:
%s
If *mappable* is a `~.contour.ContourSet`, its *extend* kwarg is included
automatically.
The *shrink* kwarg provides a simple way to scale the colorbar with respect
to the axes. Note that if *cax* is specified, it determines the size of the
colorbar and *shrink* and *aspect* kwargs are ignored.
For more precise control, you can manually specify the positions of
the axes objects in which the mappable and the colorbar are drawn. In
this case, do not use any of the axes properties kwargs.
It is known that some vector graphics viewers (svg and pdf) renders white gaps
between segments of the colorbar. This is due to bugs in the viewers, not
Matplotlib. As a workaround, the colorbar can be rendered with overlapping
segments::
cbar = colorbar()
cbar.solids.set_edgecolor("face")
draw()
However this has negative consequences in other circumstances, e.g. with
semi-transparent images (alpha < 1) and colorbar extensions; therefore, this
workaround is not used by default (see issue #1188).
""" % (make_axes_kw_doc, colormap_kw_doc)
docstring.interpd.update(colorbar_doc=colorbar_doc)
def _set_ticks_on_axis_warn(*args, **kw):
# a top level function which gets put in at the axes'
# set_xticks and set_yticks by ColorbarBase.__init__.
cbook._warn_external("Use the colorbar set_ticks() method instead.")
class _ColorbarAutoLocator(ticker.MaxNLocator):
"""
AutoLocator for Colorbar
This locator is just a `.MaxNLocator` except the min and max are
clipped by the norm's min and max (i.e. vmin/vmax from the
image/pcolor/contour object). This is necessary so ticks don't
extrude into the "extend regions".
"""
def __init__(self, colorbar):
"""
This ticker needs to know the *colorbar* so that it can access
its *vmin* and *vmax*. Otherwise it is the same as
`~.ticker.AutoLocator`.
"""
self._colorbar = colorbar
nbins = 'auto'
steps = [1, 2, 2.5, 5, 10]
super().__init__(nbins=nbins, steps=steps)
def tick_values(self, vmin, vmax):
# flip if needed:
if vmin > vmax:
vmin, vmax = vmax, vmin
vmin = max(vmin, self._colorbar.norm.vmin)
vmax = min(vmax, self._colorbar.norm.vmax)
ticks = super().tick_values(vmin, vmax)
rtol = (vmax - vmin) * 1e-10
return ticks[(ticks >= vmin - rtol) & (ticks <= vmax + rtol)]
class _ColorbarAutoMinorLocator(ticker.AutoMinorLocator):
"""
AutoMinorLocator for Colorbar
This locator is just a `.AutoMinorLocator` except the min and max are
clipped by the norm's min and max (i.e. vmin/vmax from the
image/pcolor/contour object). This is necessary so that the minorticks
don't extrude into the "extend regions".
"""
def __init__(self, colorbar, n=None):
"""
This ticker needs to know the *colorbar* so that it can access
its *vmin* and *vmax*.
"""
self._colorbar = colorbar
self.ndivs = n
super().__init__(n=None)
def __call__(self):
vmin = self._colorbar.norm.vmin
vmax = self._colorbar.norm.vmax
ticks = super().__call__()
rtol = (vmax - vmin) * 1e-10
return ticks[(ticks >= vmin - rtol) & (ticks <= vmax + rtol)]
class _ColorbarLogLocator(ticker.LogLocator):
"""
LogLocator for Colorbarbar
This locator is just a `.LogLocator` except the min and max are
clipped by the norm's min and max (i.e. vmin/vmax from the
image/pcolor/contour object). This is necessary so ticks don't
extrude into the "extend regions".
"""
def __init__(self, colorbar, *args, **kwargs):
"""
This ticker needs to know the *colorbar* so that it can access
its *vmin* and *vmax*. Otherwise it is the same as
`~.ticker.LogLocator`. The ``*args`` and ``**kwargs`` are the
same as `~.ticker.LogLocator`.
"""
self._colorbar = colorbar
super().__init__(*args, **kwargs)
def tick_values(self, vmin, vmax):
if vmin > vmax:
vmin, vmax = vmax, vmin
vmin = max(vmin, self._colorbar.norm.vmin)
vmax = min(vmax, self._colorbar.norm.vmax)
ticks = super().tick_values(vmin, vmax)
rtol = (np.log10(vmax) - np.log10(vmin)) * 1e-10
ticks = ticks[(np.log10(ticks) >= np.log10(vmin) - rtol) &
(np.log10(ticks) <= np.log10(vmax) + rtol)]
return ticks
[docs]class ColorbarBase:
r"""
Draw a colorbar in an existing axes.
There are only some rare cases in which you would work directly with a
`.ColorbarBase` as an end-user. Typically, colorbars are used
with `.ScalarMappable`\s such as an `.AxesImage` generated via
`~.axes.Axes.imshow`. For these cases you will use `.Colorbar` and
likely create it via `.pyplot.colorbar` or `.Figure.colorbar`.
The main application of using a `.ColorbarBase` explicitly is drawing
colorbars that are not associated with other elements in the figure, e.g.
when showing a colormap by itself.
If the *cmap* kwarg is given but *boundaries* and *values* are left as
None, then the colormap will be displayed on a 0-1 scale. To show the
under- and over-value colors, specify the *norm* as::
norm=colors.Normalize(clip=False)
To show the colors versus index instead of on the 0-1 scale,
use::
norm=colors.NoNorm()
Useful public methods are :meth:`set_label` and :meth:`add_lines`.
Attributes
----------
ax : `~matplotlib.axes.Axes`
The `~.axes.Axes` instance in which the colorbar is drawn.
lines : list
A list of `.LineCollection` if lines were drawn, otherwise
an empty list.
dividers : `.LineCollection`
A LineCollection if *drawedges* is ``True``, otherwise ``None``.
Parameters
----------
ax : `~matplotlib.axes.Axes`
The `~.axes.Axes` instance in which the colorbar is drawn.
cmap : `~matplotlib.colors.Colormap`, default: :rc:`image.cmap`
The colormap to use.
norm : `~matplotlib.colors.Normalize`
alpha : float
The colorbar transparency between 0 (transparent) and 1 (opaque).
values
boundaries
orientation : {'vertical', 'horizontal'}
ticklocation : {'auto', 'left', 'right', 'top', 'bottom'}
extend : {'neither', 'both', 'min', 'max'}
spacing : {'uniform', 'proportional'}
ticks : `~matplotlib.ticker.Locator` or array-like of float
format : str or `~matplotlib.ticker.Formatter`
drawedges : bool
filled : bool
extendfrac
extendrec
label : str
"""
n_rasterize = 50 # rasterize solids if number of colors >= n_rasterize
@cbook._make_keyword_only("3.3", "cmap")
def __init__(self, ax, cmap=None,
norm=None,
alpha=None,
values=None,
boundaries=None,
orientation='vertical',
ticklocation='auto',
extend=None,
spacing='uniform', # uniform or proportional
ticks=None,
format=None,
drawedges=False,
filled=True,
extendfrac=None,
extendrect=False,
label='',
):
cbook._check_isinstance([colors.Colormap, None], cmap=cmap)
cbook._check_in_list(
['vertical', 'horizontal'], orientation=orientation)
cbook._check_in_list(
['auto', 'left', 'right', 'top', 'bottom'],
ticklocation=ticklocation)
cbook._check_in_list(
['uniform', 'proportional'], spacing=spacing)
self.ax = ax
# Bind some methods to the axes to warn users against using them.
ax.set_xticks = ax.set_yticks = _set_ticks_on_axis_warn
ax.set(frame_on=False, navigate=False)
if cmap is None:
cmap = cm.get_cmap()
if norm is None:
norm = colors.Normalize()
if extend is None:
if hasattr(norm, 'extend'):
extend = norm.extend
else:
extend = 'neither'
self.alpha = alpha
self.cmap = cmap
self.norm = norm
self.values = values
self.boundaries = boundaries
self.extend = extend
self._inside = cbook._check_getitem(
{'neither': slice(0, None), 'both': slice(1, -1),
'min': slice(1, None), 'max': slice(0, -1)},
extend=extend)
self.spacing = spacing
self.orientation = orientation
self.drawedges = drawedges
self.filled = filled
self.extendfrac = extendfrac
self.extendrect = extendrect
self.solids = None
self.lines = []
self.outline = mpatches.Polygon(
np.empty((0, 2)),
edgecolor=mpl.rcParams['axes.edgecolor'], facecolor='none',
linewidth=mpl.rcParams['axes.linewidth'], closed=True, zorder=2)
ax.add_artist(self.outline)
self.outline.set(clip_box=None, clip_path=None)
self.patch = mpatches.Polygon(
np.empty((0, 2)),
color=mpl.rcParams['axes.facecolor'], linewidth=0.01, zorder=-1)
ax.add_artist(self.patch)
self.dividers = None
self.locator = None
self.formatter = None
self._manual_tick_data_values = None
self.__scale = None # linear, log10 for now. Hopefully more?
if ticklocation == 'auto':
ticklocation = 'bottom' if orientation == 'horizontal' else 'right'
self.ticklocation = ticklocation
self.set_label(label)
self._reset_locator_formatter_scale()
if np.iterable(ticks):
self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
else:
self.locator = ticks # Handle default in _ticker()
if isinstance(format, str):
self.formatter = ticker.FormatStrFormatter(format)
else:
self.formatter = format # Assume it is a Formatter or None
self.draw_all()
def _extend_lower(self):
"""Return whether the lower limit is open ended."""
return self.extend in ('both', 'min')
def _extend_upper(self):
"""Return whether the upper limit is open ended."""
return self.extend in ('both', 'max')
[docs] def draw_all(self):
"""
Calculate any free parameters based on the current cmap and norm,
and do all the drawing.
"""
# sets self._boundaries and self._values in real data units.
# takes into account extend values:
self._process_values()
# sets self.vmin and vmax in data units, but just for the part of the
# colorbar that is not part of the extend patch:
self._find_range()
# returns the X and Y mesh, *but* this was/is in normalized units:
X, Y = self._mesh()
C = self._values[:, np.newaxis]
self._config_axis() # Inline it after deprecation elapses.
# Configure axes limits, patch, and outline.
xy = self._outline(X, Y)
xmin, ymin = xy.min(axis=0)
xmax, ymax = xy.max(axis=0)
self.ax.set(xlim=(xmin, xmax), ylim=(ymin, ymax))
self.outline.set_xy(xy)
self.patch.set_xy(xy)
self.update_ticks()
if self.filled:
self._add_solids(X, Y, C)
[docs] @cbook.deprecated("3.3")
def config_axis(self):
self._config_axis()
def _config_axis(self):
"""Set up long and short axis."""
ax = self.ax
if self.orientation == 'vertical':
long_axis, short_axis = ax.yaxis, ax.xaxis
if mpl.rcParams['ytick.minor.visible']:
self.minorticks_on()
else:
long_axis, short_axis = ax.xaxis, ax.yaxis
if mpl.rcParams['xtick.minor.visible']:
self.minorticks_on()
long_axis.set(label_position=self.ticklocation,
ticks_position=self.ticklocation)
short_axis.set_ticks([])
short_axis.set_ticks([], minor=True)
self._set_label()
def _get_ticker_locator_formatter(self):
"""
Return the ``locator`` and ``formatter`` of the colorbar.
If they have not been defined (i.e. are *None*), suitable formatter
and locator instances will be created, attached to the respective
attributes and returned.
"""
locator = self.locator
formatter = self.formatter
if locator is None:
if self.boundaries is None:
if isinstance(self.norm, colors.NoNorm):
nv = len(self._values)
base = 1 + int(nv / 10)
locator = ticker.IndexLocator(base=base, offset=0)
elif isinstance(self.norm, colors.BoundaryNorm):
b = self.norm.boundaries
locator = ticker.FixedLocator(b, nbins=10)
elif isinstance(self.norm, colors.LogNorm):
locator = _ColorbarLogLocator(self)
elif isinstance(self.norm, colors.SymLogNorm):
# The subs setting here should be replaced
# by logic in the locator.
locator = ticker.SymmetricalLogLocator(
subs=np.arange(1, 10),
linthresh=self.norm.linthresh,
base=10)
else:
if mpl.rcParams['_internal.classic_mode']:
locator = ticker.MaxNLocator()
else:
locator = _ColorbarAutoLocator(self)
else:
b = self._boundaries[self._inside]
locator = ticker.FixedLocator(b, nbins=10)
if formatter is None:
if isinstance(self.norm, colors.LogNorm):
formatter = ticker.LogFormatterSciNotation()
elif isinstance(self.norm, colors.SymLogNorm):
formatter = ticker.LogFormatterSciNotation(
linthresh=self.norm.linthresh)
else:
formatter = ticker.ScalarFormatter()
else:
formatter = self.formatter
self.locator = locator
self.formatter = formatter
_log.debug('locator: %r', locator)
return locator, formatter
def _use_auto_colorbar_locator(self):
"""
Return if we should use an adjustable tick locator or a fixed
one. (check is used twice so factored out here...)
"""
contouring = self.boundaries is not None and self.spacing == 'uniform'
return (type(self.norm) in [colors.Normalize, colors.LogNorm] and
not contouring)
def _reset_locator_formatter_scale(self):
"""
Reset the locator et al to defaults. Any user-hardcoded changes
need to be re-entered if this gets called (either at init, or when
the mappable normal gets changed: Colorbar.update_normal)
"""
self.locator = None
self.formatter = None
if isinstance(self.norm, colors.LogNorm):
# *both* axes are made log so that determining the
# mid point is easier.
self.ax.set_xscale('log')
self.ax.set_yscale('log')
self.minorticks_on()
self.__scale = 'log'
else:
self.ax.set_xscale('linear')
self.ax.set_yscale('linear')
if type(self.norm) is colors.Normalize:
self.__scale = 'linear'
else:
self.__scale = 'manual'
[docs] def update_ticks(self):
"""
Force the update of the ticks and ticklabels. This must be
called whenever the tick locator and/or tick formatter changes.
"""
ax = self.ax
# Get the locator and formatter; defaults to self.locator if not None.
locator, formatter = self._get_ticker_locator_formatter()
long_axis = ax.yaxis if self.orientation == 'vertical' else ax.xaxis
if self._use_auto_colorbar_locator():
_log.debug('Using auto colorbar locator %r on colorbar', locator)
long_axis.set_major_locator(locator)
long_axis.set_major_formatter(formatter)
else:
_log.debug('Using fixed locator on colorbar')
ticks, ticklabels, offset_string = self._ticker(locator, formatter)
long_axis.set_ticks(ticks)
long_axis.set_ticklabels(ticklabels)
long_axis.get_major_formatter().set_offset_string(offset_string)
[docs] def set_ticks(self, ticks, update_ticks=True):
"""
Set tick locations.
Parameters
----------
ticks : array-like or `~matplotlib.ticker.Locator` or None
The tick positions can be hard-coded by an array of values; or
they can be defined by a `.Locator`. Setting to *None* reverts
to using a default locator.
update_ticks : bool, default: True
If True, tick locations are updated immediately. If False, the
user has to call `update_ticks` later to update the ticks.
"""
if np.iterable(ticks):
self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
else:
self.locator = ticks
if update_ticks:
self.update_ticks()
self.stale = True
[docs] def get_ticks(self, minor=False):
"""Return the x ticks as a list of locations."""
if self._manual_tick_data_values is None:
ax = self.ax
long_axis = (
ax.yaxis if self.orientation == 'vertical' else ax.xaxis)
return long_axis.get_majorticklocs()
else:
# We made the axes manually, the old way, and the ylim is 0-1,
# so the majorticklocs are in those units, not data units.
return self._manual_tick_data_values
[docs] def set_ticklabels(self, ticklabels, update_ticks=True):
"""
Set tick labels.
Tick labels are updated immediately unless *update_ticks* is *False*,
in which case one should call `.update_ticks` explicitly.
"""
if isinstance(self.locator, ticker.FixedLocator):
self.formatter = ticker.FixedFormatter(ticklabels)
if update_ticks:
self.update_ticks()
else:
cbook._warn_external("set_ticks() must have been called.")
self.stale = True
[docs] def minorticks_on(self):
"""
Turn the minor ticks of the colorbar on without extruding
into the "extend regions".
"""
ax = self.ax
long_axis = ax.yaxis if self.orientation == 'vertical' else ax.xaxis
if long_axis.get_scale() == 'log':
long_axis.set_minor_locator(_ColorbarLogLocator(self, base=10.,
subs='auto'))
long_axis.set_minor_formatter(ticker.LogFormatterSciNotation())
else:
long_axis.set_minor_locator(_ColorbarAutoMinorLocator(self))
[docs] def minorticks_off(self):
"""Turn the minor ticks of the colorbar off."""
ax = self.ax
long_axis = ax.yaxis if self.orientation == 'vertical' else ax.xaxis
long_axis.set_minor_locator(ticker.NullLocator())
def _set_label(self):
if self.orientation == 'vertical':
self.ax.set_ylabel(self._label, **self._labelkw)
else:
self.ax.set_xlabel(self._label, **self._labelkw)
self.stale = True
[docs] def set_label(self, label, *, loc=None, **kwargs):
"""Add a label to the long axis of the colorbar."""
_pos_xy = 'y' if self.orientation == 'vertical' else 'x'
_protected_kw = [_pos_xy, 'horizontalalignment', 'ha']
if any([k in kwargs for k in _protected_kw]):
if loc is not None:
raise TypeError(f'Specifying *loc* is disallowed when any of '
f'its corresponding low level keyword '
f'arguments {_protected_kw} are also supplied')
loc = 'center'
else:
if loc is None:
loc = mpl.rcParams['%saxis.labellocation' % _pos_xy]
if self.orientation == 'vertical':
cbook._check_in_list(('bottom', 'center', 'top'), loc=loc)
else:
cbook._check_in_list(('left', 'center', 'right'), loc=loc)
if loc in ['right', 'top']:
kwargs[_pos_xy] = 1.
kwargs['horizontalalignment'] = 'right'
elif loc in ['left', 'bottom']:
kwargs[_pos_xy] = 0.
kwargs['horizontalalignment'] = 'left'
self._label = label
self._labelkw = kwargs
self._set_label()
def _outline(self, X, Y):
"""
Return *x*, *y* arrays of colorbar bounding polygon,
taking orientation into account.
"""
N = X.shape[0]
ii = [0, 1, N - 2, N - 1, 2 * N - 1, 2 * N - 2, N + 1, N, 0]
x = X.T.reshape(-1)[ii]
y = Y.T.reshape(-1)[ii]
return (np.column_stack([y, x])
if self.orientation == 'horizontal' else
np.column_stack([x, y]))
def _edges(self, X, Y):
"""Return the separator line segments; helper for _add_solids."""
N = X.shape[0]
# Using the non-array form of these line segments is much
# simpler than making them into arrays.
if self.orientation == 'vertical':
return [list(zip(X[i], Y[i])) for i in range(1, N - 1)]
else:
return [list(zip(Y[i], X[i])) for i in range(1, N - 1)]
def _add_solids(self, X, Y, C):
"""
Draw the colors using `~.axes.Axes.pcolormesh`;
optionally add separators.
"""
if C.shape[0] == Y.shape[0]:
# trim the last one to be compatible with old behavior.
C = C[:-1]
if self.orientation == 'vertical':
args = (X, Y, C)
else:
args = (np.transpose(Y), np.transpose(X), np.transpose(C))
kw = dict(cmap=self.cmap,
norm=self.norm,
alpha=self.alpha,
edgecolors='None')
_log.debug('Setting pcolormesh')
col = self.ax.pcolormesh(*args, **kw, shading='flat')
# self.add_observer(col) # We should observe, not be observed...
if self.solids is not None:
self.solids.remove()
self.solids = col
if self.dividers is not None:
self.dividers.remove()
self.dividers = None
if self.drawedges:
linewidths = (0.5 * mpl.rcParams['axes.linewidth'],)
self.dividers = collections.LineCollection(
self._edges(X, Y),
colors=(mpl.rcParams['axes.edgecolor'],),
linewidths=linewidths)
self.ax.add_collection(self.dividers)
elif len(self._y) >= self.n_rasterize:
self.solids.set_rasterized(True)
[docs] def add_lines(self, levels, colors, linewidths, erase=True):
"""
Draw lines on the colorbar.
The lines are appended to the list :attr:`lines`.
Parameters
----------
levels : array-like
The positions of the lines.
colors : color or list of colors
Either a single color applying to all lines or one color value for
each line.
linewidths : float or array-like
Either a single linewidth applying to all lines or one linewidth
for each line.
erase : bool, default: True
Whether to remove any previously added lines.
"""
y = self._locate(levels)
rtol = (self._y[-1] - self._y[0]) * 1e-10
igood = (y < self._y[-1] + rtol) & (y > self._y[0] - rtol)
y = y[igood]
if np.iterable(colors):
colors = np.asarray(colors)[igood]
if np.iterable(linewidths):
linewidths = np.asarray(linewidths)[igood]
X, Y = np.meshgrid([self._y[0], self._y[-1]], y)
if self.orientation == 'vertical':
xy = np.stack([X, Y], axis=-1)
else:
xy = np.stack([Y, X], axis=-1)
col = collections.LineCollection(xy, linewidths=linewidths)
if erase and self.lines:
for lc in self.lines:
lc.remove()
self.lines = []
self.lines.append(col)
col.set_color(colors)
self.ax.add_collection(col)
self.stale = True
def _ticker(self, locator, formatter):
"""
Return the sequence of ticks (colorbar data locations),
ticklabels (strings), and the corresponding offset string.
"""
if isinstance(self.norm, colors.NoNorm) and self.boundaries is None:
intv = self._values[0], self._values[-1]
else:
intv = self.vmin, self.vmax
locator.create_dummy_axis(minpos=intv[0])
formatter.create_dummy_axis(minpos=intv[0])
locator.set_view_interval(*intv)
locator.set_data_interval(*intv)
formatter.set_view_interval(*intv)
formatter.set_data_interval(*intv)
b = np.array(locator())
if isinstance(locator, ticker.LogLocator):
eps = 1e-10
b = b[(b <= intv[1] * (1 + eps)) & (b >= intv[0] * (1 - eps))]
else:
eps = (intv[1] - intv[0]) * 1e-10
b = b[(b <= intv[1] + eps) & (b >= intv[0] - eps)]
self._manual_tick_data_values = b
ticks = self._locate(b)
ticklabels = formatter.format_ticks(b)
offset_string = formatter.get_offset()
return ticks, ticklabels, offset_string
def _process_values(self, b=None):
"""
Set the :attr:`_boundaries` and :attr:`_values` attributes
based on the input boundaries and values. Input boundaries
can be *self.boundaries* or the argument *b*.
"""
if b is None:
b = self.boundaries
if b is not None:
self._boundaries = np.asarray(b, dtype=float)
if self.values is None:
self._values = 0.5 * (self._boundaries[:-1]
+ self._boundaries[1:])
if isinstance(self.norm, colors.NoNorm):
self._values = (self._values + 0.00001).astype(np.int16)
else:
self._values = np.array(self.values)
return
if self.values is not None:
self._values = np.array(self.values)
if self.boundaries is None:
b = np.zeros(len(self.values) + 1)
b[1:-1] = 0.5 * (self._values[:-1] + self._values[1:])
b[0] = 2.0 * b[1] - b[2]
b[-1] = 2.0 * b[-2] - b[-3]
self._boundaries = b
return
self._boundaries = np.array(self.boundaries)
return
# Neither boundaries nor values are specified;
# make reasonable ones based on cmap and norm.
if isinstance(self.norm, colors.NoNorm):
b = self._uniform_y(self.cmap.N + 1) * self.cmap.N - 0.5
v = np.zeros(len(b) - 1, dtype=np.int16)
v[self._inside] = np.arange(self.cmap.N, dtype=np.int16)
if self._extend_lower():
v[0] = -1
if self._extend_upper():
v[-1] = self.cmap.N
self._boundaries = b
self._values = v
return
elif isinstance(self.norm, colors.BoundaryNorm):
b = list(self.norm.boundaries)
if self._extend_lower():
b = [b[0] - 1] + b
if self._extend_upper():
b = b + [b[-1] + 1]
b = np.array(b)
v = np.zeros(len(b) - 1)
bi = self.norm.boundaries
v[self._inside] = 0.5 * (bi[:-1] + bi[1:])
if self._extend_lower():
v[0] = b[0] - 1
if self._extend_upper():
v[-1] = b[-1] + 1
self._boundaries = b
self._values = v
return
else:
if not self.norm.scaled():
self.norm.vmin = 0
self.norm.vmax = 1
self.norm.vmin, self.norm.vmax = mtransforms.nonsingular(
self.norm.vmin,
self.norm.vmax,
expander=0.1)
b = self.norm.inverse(self._uniform_y(self.cmap.N + 1))
if isinstance(self.norm, (colors.PowerNorm, colors.LogNorm)):
# If using a lognorm or powernorm, ensure extensions don't
# go negative
if self._extend_lower():
b[0] = 0.9 * b[0]
if self._extend_upper():
b[-1] = 1.1 * b[-1]
else:
if self._extend_lower():
b[0] = b[0] - 1
if self._extend_upper():
b[-1] = b[-1] + 1
self._process_values(b)
def _find_range(self):
"""
Set :attr:`vmin` and :attr:`vmax` attributes to the first and
last boundary excluding extended end boundaries.
"""
b = self._boundaries[self._inside]
self.vmin = b[0]
self.vmax = b[-1]
def _central_N(self):
"""Return the number of boundaries excluding end extensions."""
nb = len(self._boundaries)
if self.extend == 'both':
nb -= 2
elif self.extend in ('min', 'max'):
nb -= 1
return nb
def _extended_N(self):
"""
Based on the colormap and extend variable, return the
number of boundaries.
"""
N = self.cmap.N + 1
if self.extend == 'both':
N += 2
elif self.extend in ('min', 'max'):
N += 1
return N
def _get_extension_lengths(self, frac, automin, automax, default=0.05):
"""
Return the lengths of colorbar extensions.
This is a helper method for _uniform_y and _proportional_y.
"""
# Set the default value.
extendlength = np.array([default, default])
if isinstance(frac, str):
cbook._check_in_list(['auto'], extendfrac=frac.lower())
# Use the provided values when 'auto' is required.
extendlength[:] = [automin, automax]
elif frac is not None:
try:
# Try to set min and max extension fractions directly.
extendlength[:] = frac
# If frac is a sequence containing None then NaN may
# be encountered. This is an error.
if np.isnan(extendlength).any():
raise ValueError()
except (TypeError, ValueError) as err:
# Raise an error on encountering an invalid value for frac.
raise ValueError('invalid value for extendfrac') from err
return extendlength
def _uniform_y(self, N):
"""
Return colorbar data coordinates for *N* uniformly
spaced boundaries, plus ends if required.
"""
if self.extend == 'neither':
y = np.linspace(0, 1, N)
else:
automin = automax = 1. / (N - 1.)
extendlength = self._get_extension_lengths(self.extendfrac,
automin, automax,
default=0.05)
if self.extend == 'both':
y = np.zeros(N + 2, 'd')
y[0] = 0. - extendlength[0]
y[-1] = 1. + extendlength[1]
elif self.extend == 'min':
y = np.zeros(N + 1, 'd')
y[0] = 0. - extendlength[0]
else:
y = np.zeros(N + 1, 'd')
y[-1] = 1. + extendlength[1]
y[self._inside] = np.linspace(0, 1, N)
return y
def _proportional_y(self):
"""
Return colorbar data coordinates for the boundaries of
a proportional colorbar.
"""
if isinstance(self.norm, colors.BoundaryNorm):
y = (self._boundaries - self._boundaries[0])
y = y / (self._boundaries[-1] - self._boundaries[0])
else:
y = self.norm(self._boundaries.copy())
y = np.ma.filled(y, np.nan)
if self.extend == 'min':
# Exclude leftmost interval of y.
clen = y[-1] - y[1]
automin = (y[2] - y[1]) / clen
automax = (y[-1] - y[-2]) / clen
elif self.extend == 'max':
# Exclude rightmost interval in y.
clen = y[-2] - y[0]
automin = (y[1] - y[0]) / clen
automax = (y[-2] - y[-3]) / clen
elif self.extend == 'both':
# Exclude leftmost and rightmost intervals in y.
clen = y[-2] - y[1]
automin = (y[2] - y[1]) / clen
automax = (y[-2] - y[-3]) / clen
if self.extend in ('both', 'min', 'max'):
extendlength = self._get_extension_lengths(self.extendfrac,
automin, automax,
default=0.05)
if self.extend in ('both', 'min'):
y[0] = 0. - extendlength[0]
if self.extend in ('both', 'max'):
y[-1] = 1. + extendlength[1]
yi = y[self._inside]
norm = colors.Normalize(yi[0], yi[-1])
y[self._inside] = np.ma.filled(norm(yi), np.nan)
return y
def _mesh(self):
"""
Return ``(X, Y)``, the coordinate arrays for the colorbar pcolormesh.
These are suitable for a vertical colorbar; swapping and transposition
for a horizontal colorbar are done outside this function.
These are scaled between vmin and vmax.
"""
# copy the norm and change the vmin and vmax to the vmin and
# vmax of the colorbar, not the norm. This allows the situation
# where the colormap has a narrower range than the colorbar, to
# accommodate extra contours:
norm = copy.copy(self.norm)
norm.vmin = self.vmin
norm.vmax = self.vmax
x = np.array([0.0, 1.0])
if self.spacing == 'uniform':
y = self._uniform_y(self._central_N())
else:
y = self._proportional_y()
xmid = np.array([0.5])
if self.__scale != 'manual':
y = norm.inverse(y)
x = norm.inverse(x)
xmid = norm.inverse(xmid)
else:
# if a norm doesn't have a named scale, or
# we are not using a norm
dv = self.vmax - self.vmin
x = x * dv + self.vmin
y = y * dv + self.vmin
xmid = xmid * dv + self.vmin
self._y = y
X, Y = np.meshgrid(x, y)
if self._extend_lower() and not self.extendrect:
X[0, :] = xmid
if self._extend_upper() and not self.extendrect:
X[-1, :] = xmid
return X, Y
def _locate(self, x):
"""
Given a set of color data values, return their
corresponding colorbar data coordinates.
"""
if isinstance(self.norm, (colors.NoNorm, colors.BoundaryNorm)):
b = self._boundaries
xn = x
else:
# Do calculations using normalized coordinates so
# as to make the interpolation more accurate.
b = self.norm(self._boundaries, clip=False).filled()
xn = self.norm(x, clip=False).filled()
bunique = b
yunique = self._y
# trim extra b values at beginning and end if they are
# not unique. These are here for extended colorbars, and are not
# wanted for the interpolation.
if b[0] == b[1]:
bunique = bunique[1:]
yunique = yunique[1:]
if b[-1] == b[-2]:
bunique = bunique[:-1]
yunique = yunique[:-1]
z = np.interp(xn, bunique, yunique)
return z
[docs] def set_alpha(self, alpha):
"""Set the transparency between 0 (transparent) and 1 (opaque)."""
self.alpha = alpha
[docs] def remove(self):
"""Remove this colorbar from the figure."""
self.ax.remove()
def _add_disjoint_kwargs(d, **kwargs):
"""
Update dict *d* with entries in *kwargs*, which must be absent from *d*.
"""
for k, v in kwargs.items():
if k in d:
cbook.warn_deprecated(
"3.3", message=f"The {k!r} parameter to Colorbar has no "
"effect because it is overridden by the mappable; it is "
"deprecated since %(since)s and will be removed %(removal)s.")
d[k] = v
[docs]class Colorbar(ColorbarBase):
"""
This class connects a `ColorbarBase` to a `~.cm.ScalarMappable`
such as an `~.image.AxesImage` generated via `~.axes.Axes.imshow`.
.. note::
This class is not intended to be instantiated directly; instead, use
`.Figure.colorbar` or `.pyplot.colorbar` to create a colorbar.
"""
def __init__(self, ax, mappable, **kwargs):
# Ensure the given mappable's norm has appropriate vmin and vmax set
# even if mappable.draw has not yet been called.
if mappable.get_array() is not None:
mappable.autoscale_None()
self.mappable = mappable
_add_disjoint_kwargs(kwargs, cmap=mappable.cmap, norm=mappable.norm)
if isinstance(mappable, contour.ContourSet):
cs = mappable
_add_disjoint_kwargs(
kwargs,
alpha=cs.get_alpha(),
boundaries=cs._levels,
values=cs.cvalues,
extend=cs.extend,
filled=cs.filled,
)
kwargs.setdefault(
'ticks', ticker.FixedLocator(cs.levels, nbins=10))
ColorbarBase.__init__(self, ax, **kwargs)
if not cs.filled:
self.add_lines(cs)
else:
if getattr(mappable.cmap, 'colorbar_extend', False) is not False:
kwargs.setdefault('extend', mappable.cmap.colorbar_extend)
if isinstance(mappable, martist.Artist):
_add_disjoint_kwargs(kwargs, alpha=mappable.get_alpha())
ColorbarBase.__init__(self, ax, **kwargs)
[docs] @cbook.deprecated("3.3", alternative="update_normal")
def on_mappable_changed(self, mappable):
"""
Update this colorbar to match the mappable's properties.
Typically this is automatically registered as an event handler
by :func:`colorbar_factory` and should not be called manually.
"""
_log.debug('colorbar mappable changed')
self.update_normal(mappable)
[docs] def add_lines(self, CS, erase=True):
"""
Add the lines from a non-filled `~.contour.ContourSet` to the colorbar.
Parameters
----------
CS : `~.contour.ContourSet`
The line positions are taken from the ContourSet levels. The
ContourSet must not be filled.
erase : bool, default: True
Whether to remove any previously added lines.
"""
if not isinstance(CS, contour.ContourSet) or CS.filled:
raise ValueError('add_lines is only for a ContourSet of lines')
tcolors = [c[0] for c in CS.tcolors]
tlinewidths = [t[0] for t in CS.tlinewidths]
# The following was an attempt to get the colorbar lines
# to follow subsequent changes in the contour lines,
# but more work is needed: specifically, a careful
# look at event sequences, and at how
# to make one object track another automatically.
#tcolors = [col.get_colors()[0] for col in CS.collections]
#tlinewidths = [col.get_linewidth()[0] for lw in CS.collections]
ColorbarBase.add_lines(self, CS.levels, tcolors, tlinewidths,
erase=erase)
[docs] def update_normal(self, mappable):
"""
Update solid patches, lines, etc.
This is meant to be called when the norm of the image or contour plot
to which this colorbar belongs changes.
If the norm on the mappable is different than before, this resets the
locator and formatter for the axis, so if these have been customized,
they will need to be customized again. However, if the norm only
changes values of *vmin*, *vmax* or *cmap* then the old formatter
and locator will be preserved.
"""
_log.debug('colorbar update normal %r %r', mappable.norm, self.norm)
self.mappable = mappable
self.set_alpha(mappable.get_alpha())
self.cmap = mappable.cmap
if mappable.norm != self.norm:
self.norm = mappable.norm
self._reset_locator_formatter_scale()
self.draw_all()
if isinstance(self.mappable, contour.ContourSet):
CS = self.mappable
if not CS.filled:
self.add_lines(CS)
self.stale = True
[docs] @cbook.deprecated("3.3", alternative="update_normal")
def update_bruteforce(self, mappable):
"""
Destroy and rebuild the colorbar. This is
intended to become obsolete, and will probably be
deprecated and then removed. It is not called when
the pyplot.colorbar function or the Figure.colorbar
method are used to create the colorbar.
"""
# We are using an ugly brute-force method: clearing and
# redrawing the whole thing. The problem is that if any
# properties have been changed by methods other than the
# colorbar methods, those changes will be lost.
self.ax.cla()
self.locator = None
self.formatter = None
# clearing the axes will delete outline, patch, solids, and lines:
self.outline = mpatches.Polygon(
np.empty((0, 2)),
edgecolor=mpl.rcParams['axes.edgecolor'], facecolor='none',
linewidth=mpl.rcParams['axes.linewidth'], closed=True, zorder=2)
self.ax.add_artist(self.outline)
self.outline.set(clip_box=None, clip_path=None)
self.patch = mpatches.Polygon(
np.empty((0, 2)),
color=mpl.rcParams['axes.facecolor'], linewidth=0.01, zorder=-1)
self.ax.add_artist(self.patch)
self.solids = None
self.lines = []
self.dividers = None
self.update_normal(mappable)
self.draw_all()
if isinstance(self.mappable, contour.ContourSet):
CS = self.mappable
if not CS.filled:
self.add_lines(CS)
#if self.lines is not None:
# tcolors = [c[0] for c in CS.tcolors]
# self.lines.set_color(tcolors)
#Fixme? Recalculate boundaries, ticks if vmin, vmax have changed.
#Fixme: Some refactoring may be needed; we should not
# be recalculating everything if there was a simple alpha
# change.
[docs] def remove(self):
"""
Remove this colorbar from the figure.
If the colorbar was created with ``use_gridspec=True`` the previous
gridspec is restored.
"""
ColorbarBase.remove(self)
self.mappable.callbacksSM.disconnect(self.mappable.colorbar_cid)
self.mappable.colorbar = None
self.mappable.colorbar_cid = None
try:
ax = self.mappable.axes
except AttributeError:
return
try:
gs = ax.get_subplotspec().get_gridspec()
subplotspec = gs.get_topmost_subplotspec()
except AttributeError:
# use_gridspec was False
pos = ax.get_position(original=True)
ax._set_position(pos)
else:
# use_gridspec was True
ax.set_subplotspec(subplotspec)
[docs]@docstring.Substitution(_make_axes_param_doc, _make_axes_other_param_doc)
def make_axes(parents, location=None, orientation=None, fraction=0.15,
shrink=1.0, aspect=20, **kw):
"""
Create an `~.axes.Axes` suitable for a colorbar.
The axes is placed in the figure of the *parents* axes, by resizing and
repositioning *parents*.
Parameters
----------
parents : `~.axes.Axes` or list of `~.axes.Axes`
The Axes to use as parents for placing the colorbar.
location : None or {'left', 'right', 'top', 'bottom'}
The position, relative to *parents*, where the colorbar axes
should be created. If None, the value will either come from the
given ``orientation``, else it will default to 'right'.
orientation : None or {'vertical', 'horizontal'}
The orientation of the colorbar. Typically, this keyword shouldn't
be used, as it can be derived from the ``location`` keyword.
%s
Returns
-------
cax : `~.axes.Axes`
The child axes.
kw : dict
The reduced keyword dictionary to be passed when creating the colorbar
instance.
Other Parameters
----------------
%s
"""
locations = ["left", "right", "top", "bottom"]
if orientation is not None and location is not None:
raise TypeError('position and orientation are mutually exclusive. '
'Consider setting the position to any of {}'
.format(', '.join(locations)))
# provide a default location
if location is None and orientation is None:
location = 'right'
# allow the user to not specify the location by specifying the
# orientation instead
if location is None:
location = 'right' if orientation == 'vertical' else 'bottom'
cbook._check_in_list(locations, location=location)
default_location_settings = {'left': {'anchor': (1.0, 0.5),
'panchor': (0.0, 0.5),
'pad': 0.10,
'orientation': 'vertical'},
'right': {'anchor': (0.0, 0.5),
'panchor': (1.0, 0.5),
'pad': 0.05,
'orientation': 'vertical'},
'top': {'anchor': (0.5, 0.0),
'panchor': (0.5, 1.0),
'pad': 0.05,
'orientation': 'horizontal'},
'bottom': {'anchor': (0.5, 1.0),
'panchor': (0.5, 0.0),
'pad': 0.15, # backwards compat
'orientation': 'horizontal'},
}
loc_settings = default_location_settings[location]
# put appropriate values into the kw dict for passing back to
# the Colorbar class
kw['orientation'] = loc_settings['orientation']
kw['ticklocation'] = location
anchor = kw.pop('anchor', loc_settings['anchor'])
parent_anchor = kw.pop('panchor', loc_settings['panchor'])
parents_iterable = np.iterable(parents)
# turn parents into a list if it is not already. We do this w/ np
# because `plt.subplots` can return an ndarray and is natural to
# pass to `colorbar`.
parents = np.atleast_1d(parents).ravel()
# check if using constrained_layout:
try:
gs = parents[0].get_subplotspec().get_gridspec()
using_constrained_layout = (gs._layoutbox is not None)
except AttributeError:
using_constrained_layout = False
# defaults are not appropriate for constrained_layout:
pad0 = loc_settings['pad']
if using_constrained_layout:
pad0 = 0.02
pad = kw.pop('pad', pad0)
fig = parents[0].get_figure()
if not all(fig is ax.get_figure() for ax in parents):
raise ValueError('Unable to create a colorbar axes as not all '
'parents share the same figure.')
# take a bounding box around all of the given axes
parents_bbox = mtransforms.Bbox.union(
[ax.get_position(original=True).frozen() for ax in parents])
pb = parents_bbox
if location in ('left', 'right'):
if location == 'left':
pbcb, _, pb1 = pb.splitx(fraction, fraction + pad)
else:
pb1, _, pbcb = pb.splitx(1 - fraction - pad, 1 - fraction)
pbcb = pbcb.shrunk(1.0, shrink).anchored(anchor, pbcb)
else:
if location == 'bottom':
pbcb, _, pb1 = pb.splity(fraction, fraction + pad)
else:
pb1, _, pbcb = pb.splity(1 - fraction - pad, 1 - fraction)
pbcb = pbcb.shrunk(shrink, 1.0).anchored(anchor, pbcb)
# define the aspect ratio in terms of y's per x rather than x's per y
aspect = 1.0 / aspect
# define a transform which takes us from old axes coordinates to
# new axes coordinates
shrinking_trans = mtransforms.BboxTransform(parents_bbox, pb1)
# transform each of the axes in parents using the new transform
for ax in parents:
new_posn = shrinking_trans.transform(ax.get_position(original=True))
new_posn = mtransforms.Bbox(new_posn)
ax._set_position(new_posn)
if parent_anchor is not False:
ax.set_anchor(parent_anchor)
cax = fig.add_axes(pbcb, label="<colorbar>")
# OK, now make a layoutbox for the cb axis. Later, we will use this
# to make the colorbar fit nicely.
if not using_constrained_layout:
# no layout boxes:
lb = None
lbpos = None
# and we need to set the aspect ratio by hand...
cax.set_aspect(aspect, anchor=anchor, adjustable='box')
else:
if not parents_iterable:
# this is a single axis...
ax = parents[0]
lb, lbpos = constrained_layout.layoutcolorbarsingle(
ax, cax, shrink, aspect, location, pad=pad)
else: # there is more than one parent, so lets use gridspec
# the colorbar will be a sibling of this gridspec, so the
# parent is the same parent as the gridspec. Either the figure,
# or a subplotspec.
lb, lbpos = constrained_layout.layoutcolorbargridspec(
parents, cax, shrink, aspect, location, pad)
cax._layoutbox = lb
cax._poslayoutbox = lbpos
return cax, kw
[docs]@docstring.Substitution(_make_axes_param_doc, _make_axes_other_param_doc)
def make_axes_gridspec(parent, *, fraction=0.15, shrink=1.0, aspect=20, **kw):
"""
Create a `~.SubplotBase` suitable for a colorbar.
The axes is placed in the figure of the *parent* axes, by resizing and
repositioning *parent*.
This function is similar to `.make_axes`. Primary differences are
- `.make_axes_gridspec` only handles the *orientation* keyword
and cannot handle the *location* keyword.
- `.make_axes_gridspec` should only be used with a `.SubplotBase` parent.
- `.make_axes` creates an `~.axes.Axes`; `.make_axes_gridspec` creates a
`.SubplotBase`.
- `.make_axes` updates the position of the parent. `.make_axes_gridspec`
replaces the ``grid_spec`` attribute of the parent with a new one.
While this function is meant to be compatible with `.make_axes`,
there could be some minor differences.
Parameters
----------
parent : `~.axes.Axes`
The Axes to use as parent for placing the colorbar.
%s
Returns
-------
cax : `~.axes.SubplotBase`
The child axes.
kw : dict
The reduced keyword dictionary to be passed when creating the colorbar
instance.
Other Parameters
----------------
orientation : {'vertical', 'horizontal'}, default: 'vertical'
The orientation of the colorbar.
%s
"""
orientation = kw.setdefault('orientation', 'vertical')
kw['ticklocation'] = 'auto'
x1 = 1 - fraction
# for shrinking
pad_s = (1 - shrink) * 0.5
wh_ratios = [pad_s, shrink, pad_s]
# we need to none the tree of layoutboxes because
# constrained_layout can't remove and replace the tree
# hierarchy w/o a seg fault.
gs = parent.get_subplotspec().get_gridspec()
layoutbox.nonetree(gs._layoutbox)
gs_from_subplotspec = gridspec.GridSpecFromSubplotSpec
if orientation == 'vertical':
pad = kw.pop('pad', 0.05)
wh_space = 2 * pad / (1 - pad)
gs = gs_from_subplotspec(1, 2,
subplot_spec=parent.get_subplotspec(),
wspace=wh_space,
width_ratios=[x1 - pad, fraction])
gs2 = gs_from_subplotspec(3, 1,
subplot_spec=gs[1],
hspace=0.,
height_ratios=wh_ratios)
anchor = (0.0, 0.5)
panchor = (1.0, 0.5)
else:
pad = kw.pop('pad', 0.15)
wh_space = 2 * pad / (1 - pad)
gs = gs_from_subplotspec(2, 1,
subplot_spec=parent.get_subplotspec(),
hspace=wh_space,
height_ratios=[x1 - pad, fraction])
gs2 = gs_from_subplotspec(1, 3,
subplot_spec=gs[1],
wspace=0.,
width_ratios=wh_ratios)
aspect = 1 / aspect
anchor = (0.5, 1.0)
panchor = (0.5, 0.0)
parent.set_subplotspec(gs[0])
parent.update_params()
parent._set_position(parent.figbox)
parent.set_anchor(panchor)
fig = parent.get_figure()
cax = fig.add_subplot(gs2[1], label="<colorbar>")
cax.set_aspect(aspect, anchor=anchor, adjustable='box')
return cax, kw
[docs]class ColorbarPatch(Colorbar):
"""
A Colorbar that uses a list of `~.patches.Patch` instances rather than the
default `~.collections.PatchCollection` created by `~.axes.Axes.pcolor`,
because the latter does not allow the hatch pattern to vary among the
members of the collection.
"""
def __init__(self, ax, mappable, **kw):
# we do not want to override the behaviour of solids
# so add a new attribute which will be a list of the
# colored patches in the colorbar
self.solids_patches = []
Colorbar.__init__(self, ax, mappable, **kw)
def _add_solids(self, X, Y, C):
"""
Draw the colors using `~matplotlib.patches.Patch`;
optionally add separators.
"""
n_segments = len(C)
# ensure there are sufficient hatches
hatches = self.mappable.hatches * n_segments
patches = []
for i in range(len(X) - 1):
val = C[i][0]
hatch = hatches[i]
xy = np.array([[X[i][0], Y[i][0]],
[X[i][1], Y[i][0]],
[X[i + 1][1], Y[i + 1][0]],
[X[i + 1][0], Y[i + 1][1]]])
if self.orientation == 'horizontal':
# if horizontal swap the xs and ys
xy = xy[..., ::-1]
patch = mpatches.PathPatch(mpath.Path(xy),
facecolor=self.cmap(self.norm(val)),
hatch=hatch, linewidth=0,
antialiased=False, alpha=self.alpha)
self.ax.add_patch(patch)
patches.append(patch)
if self.solids_patches:
for solid in self.solids_patches:
solid.remove()
self.solids_patches = patches
if self.dividers is not None:
self.dividers.remove()
self.dividers = None
if self.drawedges:
self.dividers = collections.LineCollection(
self._edges(X, Y),
colors=(mpl.rcParams['axes.edgecolor'],),
linewidths=(0.5 * mpl.rcParams['axes.linewidth'],))
self.ax.add_collection(self.dividers)
[docs]def colorbar_factory(cax, mappable, **kwargs):
"""
Create a colorbar on the given axes for the given mappable.
.. note::
This is a low-level function to turn an existing axes into a colorbar
axes. Typically, you'll want to use `~.Figure.colorbar` instead, which
automatically handles creation and placement of a suitable axes as
well.
Parameters
----------
cax : `~matplotlib.axes.Axes`
The `~.axes.Axes` to turn into a colorbar.
mappable : `~matplotlib.cm.ScalarMappable`
The mappable to be described by the colorbar.
**kwargs
Keyword arguments are passed to the respective colorbar class.
Returns
-------
`.Colorbar` or `.ColorbarPatch`
The created colorbar instance. `.ColorbarPatch` is only used if
*mappable* is a `.ContourSet` with hatches.
"""
# if the given mappable is a contourset with any hatching, use
# ColorbarPatch else use Colorbar
if (isinstance(mappable, contour.ContourSet)
and any(hatch is not None for hatch in mappable.hatches)):
cb = ColorbarPatch(cax, mappable, **kwargs)
else:
cb = Colorbar(cax, mappable, **kwargs)
cid = mappable.callbacksSM.connect('changed', cb.update_normal)
mappable.colorbar = cb
mappable.colorbar_cid = cid
return cb
