00001 '''
Colorbar toolkit with two classes and a function:
ColorbarBase is 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.
Colorbar is the derived class for use with images or contour plots.
make_axes is a function for resizing an axes and adding a second axes
suitable for a colorbar
The Figure.colorbar() method uses make_axes and Colorbar; the pylab.colorbar()
function is a thin wrapper over Figure.colorbar().
'''
import matplotlib.numerix as nx
from matplotlib.mlab import meshgrid, linspace
from matplotlib.numerix.mlab import amin, amax
from matplotlib import colors, cm, ticker
from matplotlib.cbook import iterable, is_string_like
from matplotlib.transforms import Interval, Value, PBox
from matplotlib.lines import Line2D
from matplotlib.patches import Polygon
from matplotlib import rcParams
from matplotlib.collections import LineCollection
from matplotlib.contour import ContourSet
from matplotlib.axes import Axes
make_axes_kw_doc = '''
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
'''
colormap_kw_doc = '''
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.
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 ScalarFormatter is used.
If a format string is given, e.g. '%.3f', that is used.
An alternative 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.
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:
colorbar(**kwargs)
colorbar(mappable, **kwargs)
colorbar(mappable, cax, **kwargs)
The optional arguments mappable and cax may be included in the kwargs;
they are image, ContourSet, etc. to which the colorbar applies, and
the axes object in which the colorbar will be drawn. Defaults are
the current image and a new axes object created next to that image
after resizing the image.
kwargs are in two groups:
axes properties:
%s
colorbar properties:
%s
If mappable is a 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.
''' % (make_axes_kw_doc, colormap_kw_doc)
00111 class ColorbarBase(cm.ScalarMappable):
'''
'''
_slice_dict = {'neither': slice(0,1000000),
'both': slice(1,-1),
'min': slice(1,1000000),
'max': slice(0,-1)}
def __init__(self, ax, cmap=None,
norm=None,
alpha=1.0,
values=None,
boundaries=None,
orientation='vertical',
extend='neither',
spacing='uniform',
ticks=None,
format=None,
drawedges=False,
00130 filled=True,
):
self.ax = 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.solids = None
self.lines = None
if iterable(ticks):
self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
else:
self.locator = ticks
if format is None:
if isinstance(self.norm, colors.LogNorm):
self.formatter = ticker.LogFormatter()
else:
self.formatter = ticker.ScalarFormatter()
elif is_string_like(format):
self.formatter = ticker.FormatStrFormatter(format)
else:
self.formatter = format
self.draw_all()
00163 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[:,nx.NewAxis]
self._config_axes(X, Y)
if self.filled:
self._add_solids(X, Y, C)
00176 def _config_axes(self, X, Y):
'''
Make an axes patch and outline.
'''
ax = self.ax
ax.set_frame_on(False)
ax.set_navigate(False)
x, y = self._outline(X, Y)
ax.set_xlim(amin(x), amax(x))
ax.set_ylim(amin(y), amax(y))
ax.update_datalim_numerix(x, y)
self.outline = Line2D(x, y, color=rcParams['axes.edgecolor'],
linewidth=rcParams['axes.linewidth'])
ax.add_artist(self.outline)
c = rcParams['axes.facecolor']
self.patch = Polygon(zip(x,y), edgecolor=c,
facecolor=c,
linewidth=0.01,
zorder=-1)
ax.add_artist(self.patch)
ticks, ticklabels, offset_string = self._ticker()
if self.orientation == 'vertical':
ax.set_xticks([])
ax.yaxis.set_label_position('right')
ax.yaxis.set_ticks_position('right')
ax.set_yticks(ticks)
ax.set_yticklabels(ticklabels)
ax.yaxis.get_major_formatter().set_offset_string(offset_string)
else:
ax.set_yticks([])
ax.xaxis.set_label_position('bottom')
ax.set_xticks(ticks)
ax.set_xticklabels(ticklabels)
ax.xaxis.get_major_formatter().set_offset_string(offset_string)
def set_label(self, label, **kw):
if self.orientation == 'vertical':
self.ax.set_ylabel(label, **kw)
else:
self.ax.set_xlabel(label, **kw)
00218 def _outline(self, X, Y):
'''
Return x, y arrays of colorbar bounding polygon,
taking orientation into account.
'''
N = nx.shape(X)[0]
ii = [0, 1, N-2, N-1, 2*N-1, 2*N-2, N+1, N, 0]
x = nx.take(nx.ravel(nx.transpose(X)), ii)
y = nx.take(nx.ravel(nx.transpose(Y)), ii)
if self.orientation == 'horizontal':
return y,x
return x,y
00231 def _edges(self, X, Y):
'''
Return the separator line segments; helper for _add_solids.
'''
N = nx.shape(X)[0]
if self.orientation == 'vertical':
return [zip(X[i], Y[i]) for i in range(1, N-1)]
else:
return [zip(Y[i], X[i]) for i in range(1, N-1)]
00243 def _add_solids(self, X, Y, C):
'''
Draw the colors using pcolor; optionally add separators.
'''
if self.orientation == 'vertical':
args = (X, Y, C)
else:
args = (nx.transpose(Y), nx.transpose(X), nx.transpose(C))
kw = {'cmap':self.cmap, 'norm':self.norm,
'shading':'flat', 'alpha':self.alpha}
col = self.ax.pcolor(*args, **kw)
self.solids = col
if self.drawedges:
self.dividers = LineCollection(self._edges(X,Y),
colors=(rcParams['axes.edgecolor'],),
linewidths=(0.5*rcParams['axes.linewidth'],)
)
self.ax.add_collection(self.dividers)
00265 def add_lines(self, levels, colors, linewidths):
'''
Draw lines on the colorbar.
'''
N = len(levels)
dummy, y = self._locate(levels)
if len(y) <> N:
raise ValueError("levels are outside colorbar range")
x = nx.array([0.0, 1.0])
X, Y = meshgrid(x,y)
if self.orientation == 'vertical':
xy = [zip(X[i], Y[i]) for i in range(N)]
else:
xy = [zip(Y[i], X[i]) for i in range(N)]
col = LineCollection(xy, linewidths=linewidths)
self.lines = col
col.set_color(colors)
self.ax.add_collection(col)
00285 def _ticker(self):
'''
Return two sequences: ticks (colorbar data locations)
and ticklabels (strings).
'''
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.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 = Interval(Value(self._values[0]), Value(self._values[-1]))
else:
intv = Interval(Value(self.vmin), Value(self.vmax))
locator.set_view_interval(intv)
locator.set_data_interval(intv)
formatter.set_view_interval(intv)
formatter.set_data_interval(intv)
b = nx.array(locator())
b, ticks = self._locate(b)
formatter.set_locs(b)
ticklabels = [formatter(t) for t in b]
offset_string = formatter.get_offset()
return ticks, ticklabels, offset_string
00320 def _process_values(self, b=None):
'''
Set the _boundaries and _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 = nx.array(b)
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(nx.Int16)
return
self._values = nx.array(self.values)
return
if self.values is not None:
self._values = nx.array(self.values)
if self.boundaries is None:
b = nx.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 = nx.array(self.boundaries)
return
if isinstance(self.norm, colors.NoNorm):
b = nx.arange(self.norm.vmin, self.norm.vmax + 2) - 0.5
else:
b = self.norm.inverse(self._uniform_y(self.cmap.N+1))
self._process_values(b)
00355 def _find_range(self):
'''
Set vmin and 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]
00364 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
00373 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
00385 def _uniform_y(self, N):
'''
Return colorbar data coordinates for N uniformly
spaced boundaries, plus ends if required.
'''
if self.extend == 'neither':
y = linspace(0, 1, N)
else:
if self.extend == 'both':
y = nx.zeros(N + 2, 'd')
y[0] = -0.05
y[-1] = 1.05
elif self.extend == 'min':
y = nx.zeros(N + 1, 'd')
y[0] = -0.05
else:
y = nx.zeros(N + 1, 'd')
y[-1] = 1.05
y[self._inside] = linspace(0, 1, N)
return y
00406 def _proportional_y(self):
'''
Return colorbar data coordinates for the boundaries of
a proportional colorbar.
'''
y = self.norm(self._boundaries.copy())
if self.extend in ('both', 'min'):
y[0] = -0.05
if self.extend in ('both', 'max'):
y[-1] = 1.05
yi = y[self._inside]
norm = colors.Normalize(yi[0], yi[-1])
y[self._inside] = norm(yi)
return y
00421 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 = nx.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 = meshgrid(x,y)
if self.extend in ('min', 'both'):
X[0,:] = 0.5
if self.extend in ('max', 'both'):
X[-1,:] = 0.5
return X, Y
00441 def _locate(self, x):
'''
Given a possible set of color data values, return the ones
within range, together with their corresponding colorbar
data coordinates.
'''
if isinstance(self.norm, colors.NoNorm):
b = self._boundaries
xn = x
xout = x
else:
b = self.norm(self._boundaries, clip=False).filled()
xn = self.norm(x, clip=False).filled()
in_cond = (xn > -0.001) & (xn < 1.001)
xn = nx.compress(in_cond, xn)
xout = nx.compress(in_cond, x)
y = self._y
N = len(b)
ii = nx.minimum(nx.searchsorted(b, xn), N-1)
i0 = nx.maximum(ii - 1, 0)
db = nx.take(b, ii) - nx.take(b, i0)
db = nx.where(i0==ii, 1.0, db)
dy = nx.take(y, ii) - nx.take(y, i0)
z = nx.take(y, i0) + (xn-nx.take(b,i0))*dy/db
return xout, z
def set_alpha(self, alpha):
self.alpha = alpha
class Colorbar(ColorbarBase):
def __init__(self, ax, mappable, **kw):
mappable.autoscale_None()
self.mappable = mappable
kw['cmap'] = mappable.cmap
kw['norm'] = mappable.norm
kw['alpha'] = mappable.get_alpha()
if isinstance(mappable, ContourSet):
CS = mappable
kw['boundaries'] = CS._levels
kw['values'] = CS.cvalues
kw['extend'] = CS.extend
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:
ColorbarBase.__init__(self, ax, **kw)
def add_lines(self, CS):
'''
Add the lines from a non-filled ContourSet to the colorbar.
'''
if not isinstance(CS, 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]
ColorbarBase.add_lines(self, CS.levels, tcolors, tlinewidths)
def notify(self, mappable):
'''Manually change any contour line colors. This is called
when the image or contour plot to which this colorbar belongs
is changed.
'''
cm.ScalarMappable.notify(self, mappable)
self.ax.cla()
self.draw_all()
if isinstance(self.mappable, ContourSet):
CS = self.mappable
if not CS.filled:
self.add_lines(CS)
def make_axes(parent, **kw):
orientation = kw.setdefault('orientation', 'vertical')
fraction = kw.pop('fraction', 0.15)
shrink = kw.pop('shrink', 1.0)
aspect = kw.pop('aspect', 20)
pb = PBox(parent.get_position(original=True))
if orientation == 'vertical':
pad = kw.pop('pad', 0.05)
x1 = 1.0-fraction
pb1, pbx, pbcb = pb.splitx(x1-pad, x1)
pbcb.shrink(1.0, shrink).anchor('C')
anchor = (0.0, 0.5)
panchor = (1.0, 0.5)
else:
pad = kw.pop('pad', 0.15)
pbcb, pbx, pb1 = pb.splity(fraction, fraction+pad)
pbcb.shrink(shrink, 1.0).anchor('C')
aspect = 1.0/aspect
anchor = (0.5, 1.0)
panchor = (0.5, 0.0)
parent.set_position(pb1)
parent.set_anchor(panchor)
fig = parent.get_figure()
cax = fig.add_axes(pbcb)
cax.set_aspect(aspect, anchor=anchor, adjustable='box')
return cax, kw
make_axes.__doc__ ='''
Resize and reposition a parent axes, and return a child
axes suitable for a colorbar.
cax, kw = make_axes(parent, **kw)
Keyword arguments may include the following (with defaults):
orientation = 'vertical' or 'horizontal'
%s
All but the first of these are stripped from the input kw set.
Returns (cax, kw), the child axes and the reduced kw dictionary.
''' % make_axes_kw_doc
'''
The following does not work correctly. The problem seems to be that
the transforms work right only when fig.add_axes(rect) is used to
generate the axes, not when the axes object is generated first and
then fig.add_axes(ax) is called. I don't understand this. - EF
class ColorbarAxes(Axes):
def __init__(self, parent, **kw):
orientation = kw.setdefault('orientation', 'vertical')
fraction = kw.pop('fraction', 0.15)
shrink = kw.pop('shrink', 1.0)
aspect = kw.pop('aspect', 20)
self.cbkw = kw
pb = PBox(parent.get_position())
if orientation == 'vertical':
pb1, pbcb = pb.splitx(1.0-fraction)
pbcb.shrink(1.0, shrink).anchor('C')
anchor = (0.3, 0.5)
panchor = (0.8, 0.5)
else:
pbcb, pb1 = pb.splity(fraction)
pbcb.shrink(shrink, 1.0).anchor('C')
aspect = 1.0/aspect
anchor = (0.5, 0.2)
panchor = (0.5, 0.8)
parent.set_position(pb1)
parent.set_anchor(panchor)
fig = parent.get_figure()
Axes.__init__(self, fig, pbcb)
fig.add_axes(self)
self.set_aspect(aspect, anchor=anchor, adjustable='box')
'''