matplotlib/lib/matplotlib/colorbar.py at master · flothesof/matplotlib · GitHub

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'''

Colorbar toolkit with two classes and a function:

: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`

the derived class for use with images or contour plots.

:func:`make_axes`

a function for resizing an axes and adding a second axes

suitable for a colorbar

The :meth:`~matplotlib.figure.Figure.colorbar` method uses :func:`make_axes`

and :class:`Colorbar`; the :func:`~matplotlib.pyplot.colorbar` function

is a thin wrapper over :meth:`~matplotlib.figure.Figure.colorbar`.

'''

from __future__ import (absolute_import, division, print_function,

unicode_literals)

from matplotlib.externals import six

from matplotlib.externals.six.moves import xrange, zip

import warnings

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 mtrans

from matplotlib import docstring

make_axes_kw_doc = '''

============= ====================================================

Property Description

============= ====================================================

*orientation* vertical or horizontal

*fraction* 0.15; fraction of original axes to use for colorbar

*pad* 0.05 if vertical, 0.15 if horizontal; fraction

of original axes between colorbar and new image axes

*shrink* 1.0; fraction by which to shrink the colorbar

*aspect* 20; ratio of long to short dimensions

*anchor* (0.0, 0.5) if vertical; (0.5, 1.0) if horizontal;

the anchor point of the colorbar axes

*panchor* (1.0, 0.5) if vertical; (0.5, 0.0) if horizontal;

the anchor point of the colorbar parent axes. If

False, the parent axes' anchor will be unchanged

============= ====================================================

'''

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* [ *False* | *True* ]

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 | list of ticks | Locator object ]

If None, ticks are determined automatically from the

input.

*format* [ None | format string | Formatter object ]

If None, the

:class:`~matplotlib.ticker.ScalarFormatter` is used.

If a format string is given, e.g., '%.3f', that is

used. An alternative

:class:`~matplotlib.ticker.Formatter` object may be

given instead.

*drawedges* [ False | True ] If true, draw lines at color

boundaries.

============ ====================================================

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

:meth:`~matplotlib.figure.Figure.colorbar` method::

colorbar(**kwargs)

colorbar(mappable, **kwargs)

colorbar(mappable, cax=cax, **kwargs)

colorbar(mappable, ax=ax, **kwargs)

arguments:

*mappable*

the :class:`~matplotlib.image.Image`,

:class:`~matplotlib.contour.ContourSet`, etc. to

which the colorbar applies; this argument is mandatory for the

:meth:`~matplotlib.figure.Figure.colorbar` method but optional for the

:func:`~matplotlib.pyplot.colorbar` function, which sets the

default to the current image.

keyword arguments:

*cax*

None | axes object into which the colorbar will be drawn

*ax*

None | parent axes object(s) 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*

False | 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

grid_spec module.

Additional keyword arguments are of two kinds:

axes properties:

colorbar properties:

If *mappable* is a :class:`~matplotlib.contours.ContourSet`, its *extend*

kwarg is included automatically.

Note that the *shrink* kwarg provides a simple way to keep a vertical

colorbar, for example, from being taller than the axes of the mappable

to which the colorbar is attached; but it is a manual method requiring

some trial and error. If the colorbar is too tall (or a horizontal

colorbar is too wide) use a smaller value of *shrink*.

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 viewer (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. Particularly

with semi transparent images (alpha < 1) and colorbar extensions and is not

enabled by default see (issue #1188).

returns:

:class:`~matplotlib.colorbar.Colorbar` instance; see also its base class,

:class:`~matplotlib.colorbar.ColorbarBase`. Call the

:meth:`~matplotlib.colorbar.ColorbarBase.set_label` method

to label the colorbar.

''' % (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 set_yticks by _patch_ax

warnings.warn("Use the colorbar set_ticks() method instead.")

class ColorbarBase(cm.ScalarMappable):

'''

Draw a colorbar in an existing axes.

This is a base class for the :class:`Colorbar` class, which is the

basis for the :func:`~matplotlib.pyplot.colorbar` function and the

:meth:`~matplotlib.figure.Figure.colorbar` method, which are the

usual ways of creating a colorbar.

It is also useful by itself for showing a colormap. 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::

colors.Normalize(clip=False)

To show the colors versus index instead of on the 0-1 scale,

use::

norm=colors.NoNorm.

Useful attributes:

:attr:`ax`

the Axes instance in which the colorbar is drawn

:attr:`lines`

a list of LineCollection if lines were drawn, otherwise

an empty list

:attr:`dividers`

a LineCollection if *drawedges* is True, otherwise None

Useful public methods are :meth:`set_label` and :meth:`add_lines`.

'''

_slice_dict = {'neither': slice(0, None),

'both': slice(1, -1),

'min': slice(1, None),

'max': slice(0, -1)}

n_rasterize = 50 # rasterize solids if number of colors >= n_rasterize

def __init__(self, ax, cmap=None,

norm=None,

alpha=None,

values=None,

boundaries=None,

orientation='vertical',

ticklocation='auto',

extend='neither',

spacing='uniform', # uniform or proportional

ticks=None,

format=None,

drawedges=False,

filled=True,

extendfrac=None,

extendrect=False,

label='',

#: The axes that this colorbar lives in.

self.ax = ax

self._patch_ax()

if cmap is None:

cmap = cm.get_cmap()

if norm is None:

norm = colors.Normalize()

self.alpha = alpha

cm.ScalarMappable.__init__(self, cmap=cmap, norm=norm)

self.values = values

self.boundaries = boundaries

self.extend = extend

self._inside = self._slice_dict[extend]

self.spacing = spacing

self.orientation = orientation

self.drawedges = drawedges

self.filled = filled

self.extendfrac = extendfrac

self.extendrect = extendrect

self.solids = None

self.lines = list()

self.outline = None

self.patch = None

self.dividers = None

if ticklocation == 'auto':

ticklocation = 'bottom' if orientation == 'horizontal' else 'right'

self.ticklocation = ticklocation

self.set_label(label)

if cbook.iterable(ticks):

self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))

else:

self.locator = ticks # Handle default in _ticker()

if format is None:

if isinstance(self.norm, colors.LogNorm):

self.formatter = ticker.LogFormatterMathtext()

else:

self.formatter = ticker.ScalarFormatter()

elif cbook.is_string_like(format):

self.formatter = ticker.FormatStrFormatter(format)

else:

self.formatter = format # Assume it is a Formatter

# The rest is in a method so we can recalculate when clim changes.

self.config_axis()

self.draw_all()

def _extend_lower(self):

"""Returns whether the lower limit is open ended."""

return self.extend in ('both', 'min')

def _extend_upper(self):

"""Returns whether the uper limit is open ended."""

return self.extend in ('both', 'max')

def _patch_ax(self):

# bind some methods to the axes to warn users

# against using those methods.

self.ax.set_xticks = _set_ticks_on_axis_warn

self.ax.set_yticks = _set_ticks_on_axis_warn

def draw_all(self):

'''

Calculate any free parameters based on the current cmap and norm,

and do all the drawing.

'''

self._process_values()

self._find_range()

X, Y = self._mesh()

C = self._values[:, np.newaxis]

self._config_axes(X, Y)

if self.filled:

self._add_solids(X, Y, C)

def config_axis(self):

ax = self.ax

if self.orientation == 'vertical':

ax.xaxis.set_ticks([])

# location is either one of 'bottom' or 'top'

ax.yaxis.set_label_position(self.ticklocation)

ax.yaxis.set_ticks_position(self.ticklocation)

else:

ax.yaxis.set_ticks([])

# location is either one of 'left' or 'right'

ax.xaxis.set_label_position(self.ticklocation)

ax.xaxis.set_ticks_position(self.ticklocation)

self._set_label()

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

ticks, ticklabels, offset_string = self._ticker()

if self.orientation == 'vertical':

ax.yaxis.set_ticks(ticks)

ax.set_yticklabels(ticklabels)

ax.yaxis.get_major_formatter().set_offset_string(offset_string)

else:

ax.xaxis.set_ticks(ticks)

ax.set_xticklabels(ticklabels)

ax.xaxis.get_major_formatter().set_offset_string(offset_string)

def set_ticks(self, ticks, update_ticks=True):

"""

set tick locations. Tick locations are updated immediately unless

update_ticks is *False*. To manually update the ticks, call

*update_ticks* method explicitly.

"""

if cbook.iterable(ticks):

self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))

else:

self.locator = ticks

if update_ticks:

self.update_ticks()

self.stale = True

def set_ticklabels(self, ticklabels, update_ticks=True):

"""

set tick labels. Tick labels are updated immediately unless

update_ticks is *False*. To manually update the ticks, call

*update_ticks* method explicitly.

"""

if isinstance(self.locator, ticker.FixedLocator):

self.formatter = ticker.FixedFormatter(ticklabels)

if update_ticks:

self.update_ticks()

else:

warnings.warn("set_ticks() must have been called.")

self.stale = True

def _config_axes(self, X, Y):

'''

Make an axes patch and outline.

'''

ax = self.ax

ax.set_frame_on(False)

ax.set_navigate(False)

xy = self._outline(X, Y)

ax.update_datalim(xy)

ax.set_xlim(*ax.dataLim.intervalx)

ax.set_ylim(*ax.dataLim.intervaly)

if self.outline is not None:

self.outline.remove()

self.outline = mpatches.Polygon(

xy, 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)

self.outline.set_clip_path(None)

c = mpl.rcParams['axes.facecolor']

if self.patch is not None:

self.patch.remove()

self.patch = mpatches.Polygon(xy, edgecolor=c,

facecolor=c,

linewidth=0.01,

zorder=-1)

ax.add_artist(self.patch)

self.update_ticks()

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

def set_label(self, label, **kw):

'''

Label the long axis of the colorbar

'''

self._label = '%s' % (label, )

self._labelkw = kw

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 = np.take(np.ravel(np.transpose(X)), ii)

y = np.take(np.ravel(np.transpose(Y)), ii)

x = x.reshape((len(x), 1))

y = y.reshape((len(y), 1))

if self.orientation == 'horizontal':

return np.hstack((y, x))

return np.hstack((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 xrange(1, N - 1)]

else:

return [list(zip(Y[i], X[i])) for i in xrange(1, N - 1)]

def _add_solids(self, X, Y, C):

'''

Draw the colors using :meth:`~matplotlib.axes.Axes.pcolormesh`;

optionally add separators.

'''

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')

# Save, set, and restore hold state to keep pcolor from

# clearing the axes. Ordinarily this will not be needed,

# since the axes object should already have hold set.

_hold = self.ax.ishold()

self.ax.hold(True)

col = self.ax.pcolormesh(*args, **kw)

self.ax.hold(_hold)

#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)

def add_lines(self, levels, colors, linewidths, erase=True):

'''

Draw lines on the colorbar.

*colors* and *linewidths* must be scalars or

sequences the same length as *levels*.

Set *erase* to False to add lines without first

removing any previously added lines.

'''

y = self._locate(levels)

igood = (y < 1.001) & (y > -0.001)

y = y[igood]

if cbook.iterable(colors):

colors = np.asarray(colors)[igood]

if cbook.iterable(linewidths):

linewidths = np.asarray(linewidths)[igood]

N = len(y)

x = np.array([0.0, 1.0])

X, Y = np.meshgrid(x, y)

if self.orientation == 'vertical':

xy = [list(zip(X[i], Y[i])) for i in xrange(N)]

else:

xy = [list(zip(Y[i], X[i])) for i in xrange(N)]

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):

'''

Return the sequence of ticks (colorbar data locations),

ticklabels (strings), and the corresponding offset string.

'''

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 = ticker.LogLocator()

else:

locator = ticker.MaxNLocator()

else:

b = self._boundaries[self._inside]

locator = ticker.FixedLocator(b, nbins=10)

if isinstance(self.norm, colors.NoNorm):

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)]

ticks = self._locate(b)

formatter.set_locs(b)

ticklabels = [formatter(t, i) for i, t in enumerate(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)

return

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, 'd')

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,), dtype=float)

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 = mtrans.nonsingular(self.norm.vmin,

self.norm.vmax,

expander=0.1)

b = self.norm.inverse(self._uniform_y(self.cmap.N + 1))

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):

'''number of boundaries **before** extension of ends'''

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):

'''

Get the lengths of colorbar extensions.

A helper method for _uniform_y and _proportional_y.

'''

# Set the default value.

extendlength = np.array([default, default])

if isinstance(frac, six.string_types):

if frac.lower() == 'auto':

# Use the provided values when 'auto' is required.

extendlength[0] = automin

extendlength[1] = automax

else:

# Any other string is invalid.

raise ValueError('invalid value for extendfrac')

elif frac is not None:

try:

# Try to set min and max extension fractions directly.

extendlength[:] = frac

# If frac is a sequence contaning None then NaN may

# be encountered. This is an error.

if np.isnan(extendlength).any():

raise ValueError()

except (TypeError, ValueError):

# Raise an error on encountering an invalid value for frac.

raise ValueError('invalid value for extendfrac')

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())

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

else:

# Exclude leftmost and rightmost intervals in y.

clen = y[-2] - y[1]

automin = (y[2] - y[1]) / clen

automax = (y[-2] - y[-3]) / clen

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] = norm(yi)

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.

'''

x = np.array([0.0, 1.0])

if self.spacing == 'uniform':

y = self._uniform_y(self._central_N())

else:

y = self._proportional_y()

self._y = y

X, Y = np.meshgrid(x, y)

if self._extend_lower() and not self.extendrect:

X[0, :] = 0.5

if self._extend_upper() and not self.extendrect:

X[-1, :] = 0.5

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()

# The rest is linear interpolation with extrapolation at ends.

ii = np.searchsorted(b, xn)

i0 = ii - 1

itop = (ii == len(b))

ibot = (ii == 0)

i0[itop] -= 1

ii[itop] -= 1

i0[ibot] += 1

ii[ibot] += 1

db = np.take(b, ii) - np.take(b, i0)

y = self._y

dy = np.take(y, ii) - np.take(y, i0)

z = np.take(y, i0) + (xn - np.take(b, i0)) * dy / db

return z

def set_alpha(self, alpha):

self.alpha = alpha

def remove(self):

"""

Remove this colorbar from the figure

"""

fig = self.ax.figure

fig.delaxes(self.ax)

class Colorbar(ColorbarBase):

"""

This class connects a :class:`ColorbarBase` to a

:class:`~matplotlib.cm.ScalarMappable` such as a

:class:`~matplotlib.image.AxesImage` generated via

:meth:`~matplotlib.axes.Axes.imshow`.

It is not intended to be instantiated directly; instead,

use :meth:`~matplotlib.figure.Figure.colorbar` or

:func:`~matplotlib.pyplot.colorbar` to make your colorbar.

"""

def __init__(self, ax, mappable, **kw):

# Ensure the given mappable's norm has appropriate vmin and vmax set

# even if mappable.draw has not yet been called.

mappable.autoscale_None()

self.mappable = mappable

kw['cmap'] = cmap = mappable.cmap

kw['norm'] = norm = mappable.norm

if isinstance(mappable, contour.ContourSet):

CS = mappable

kw['alpha'] = mappable.get_alpha()

kw['boundaries'] = CS._levels

kw['values'] = CS.cvalues

kw['extend'] = CS.extend

#kw['ticks'] = CS._levels

kw.setdefault('ticks', ticker.FixedLocator(CS.levels, nbins=10))

kw['filled'] = CS.filled

ColorbarBase.__init__(self, ax, **kw)

if not CS.filled:

self.add_lines(CS)

else:

if getattr(cmap, 'colorbar_extend', False) is not False:

kw.setdefault('extend', cmap.colorbar_extend)

if isinstance(mappable, martist.Artist):

kw['alpha'] = mappable.get_alpha()

ColorbarBase.__init__(self, ax, **kw)

def on_mappable_changed(self, mappable):

"""

Updates 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.

"""

self.set_cmap(mappable.get_cmap())

self.set_clim(mappable.get_clim())

self.update_normal(mappable)

def add_lines(self, CS, erase=True):

'''

Add the lines from a non-filled

:class:`~matplotlib.contour.ContourSet` to the colorbar.

Set *erase* to False if these lines should be added to

any pre-existing 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]

#print 'tlinewidths:', tlinewidths

ColorbarBase.add_lines(self, CS.levels, tcolors, tlinewidths,

erase=erase)

def update_normal(self, mappable):

'''

update solid, lines, etc. Unlike update_bruteforce, it does

not clear the axes. This is meant to be called when the image

or contour plot to which this colorbar belongs is changed.

'''

self.draw_all()

if isinstance(self.mappable, contour.ContourSet):

CS = self.mappable

if not CS.filled:

self.add_lines(CS)

self.stale = True

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()

# clearing the axes will delete outline, patch, solids, and lines:

self.outline = None

self.patch = None

self.solids = None

self.lines = list()

self.dividers = None

self.set_alpha(mappable.get_alpha())

self.cmap = mappable.cmap

self.norm = mappable.norm

self.config_axis()

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.

def remove(self):

"""

Remove this colorbar from the figure. If the colorbar was created with

``use_gridspec=True`` then restore the gridspec to its previous value.

"""

ColorbarBase.remove(self)

self.mappable.callbacksSM.disconnect(self.mappable.colorbar_cid)

self.mappable.colorbar = None

View remainder of file in raw view

matplotlib/lib/matplotlib/colorbar.py at master · flothesof/matplotlib · GitHub

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