def _autolev(self, z, N):
'''
Select contour levels to span the data.
We need two more levels for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
three levels to provide boundaries for both regions.
'''
zmax = ma.maximum(z)
zmin = ma.minimum(z)
zmargin = (zmax - zmin) * 0.001 # so z < (zmax + zmargin)
if self.filled:
lev = linspace(zmin, zmax + zmargin, N+2)
else:
lev = linspace(zmin, zmax + zmargin, N+2)[1:-1]
return lev
def _autolev(self, z, N, filled):
'''
Select contour levels to span the data.
We need two more levels for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
three levels to provide boundaries for both regions.
'''
zmax = ma.maximum(z)
zmin = ma.minimum(z)
zmargin = (zmax - zmin) * 0.001 # so z < (zmax + zmargin)
if filled:
lev = linspace(zmin, zmax + zmargin, N+2)
else:
lev = linspace(zmin, zmax + zmargin, N+2)[1:-1]
return lev
def _autolev(self, z, N, filled, badmask):
'''
Select contour levels to span the data.
We need one more level for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
two levels. These are taken as the lower boundaries of
the regions.
'''
rz = ma.masked_array(z, badmask)
zmax = ma.maximum(rz) # was: zmax = amax(rz)
zmin = ma.minimum(rz)
if filled:
lev = linspace(zmin, zmax, N + 2)[:-1]
else:
lev = linspace(zmin, zmax, N + 2)[1:-1]
return lev
def _autolev(self, z, N, filled, badmask):
'''
Select contour levels to span the data.
We need one more level for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
a single contour boundary, say at z = 0, requires only
one contour line, but two filled regions, and therefore
two levels. These are taken as the lower boundaries of
the regions.
'''
rz = ma.masked_array(z, badmask)
zmax = ma.maximum(rz) # was: zmax = amax(rz)
zmin = ma.minimum(rz)
if filled:
lev = linspace(zmin, zmax, N+2)[:-1]
else:
lev = linspace(zmin, zmax, N+2)[1:-1]
return lev
def __init__(self, ax, labels, active=0, activecolor='blue'):
"""
Add radio buttons to axes.Axes instance ax
labels is a len(buttons) list of labels as strings
active is the index into labels for the button that is active
activecolor is the color of the button when clicked
"""
self.activecolor = activecolor
ax.set_xticks([])
ax.set_yticks([])
ax.set_navigate(False)
dy = 1. / (len(labels) + 1)
ys = linspace(1 - dy, dy, len(labels))
cnt = 0
axcolor = ax.get_axis_bgcolor()
self.labels = []
self.circles = []
for y, label in zip(ys, labels):
t = ax.text(0.25,
y,
label,
transform=ax.transAxes,
horizontalalignment='left',
verticalalignment='center')
if cnt == active:
facecolor = activecolor
else:
facecolor = axcolor
p = Circle(xy=(0.15, y),
radius=0.05,
facecolor=facecolor,
transform=ax.transAxes)
self.labels.append(t)
self.circles.append(p)
ax.add_patch(p)
cnt += 1
ax.figure.canvas.mpl_connect('button_press_event', self._clicked)
self.ax = ax
self.cnt = 0
self.observers = {}
def _initialize_x_y(self, z):
'''
Return X, Y arrays such that contour(Z) will match imshow(Z)
if origin is not None.
The center of pixel Z[i,j] depends on origin:
if origin is None, x = j, y = i;
if origin is 'lower', x = j + 0.5, y = i + 0.5;
if origin is 'upper', x = j + 0.5, y = Nrows - i - 0.5
If extent is not None, x and y will be scaled to match,
as in imshow.
If origin is None and extent is not None, then extent
will give the minimum and maximum values of x and y.
'''
if len(shape(z)) != 2:
raise TypeError("Input must be a 2D array.")
else:
Ny, Nx = shape(z)
if self.origin is None: # Not for image-matching.
if self.extent is None:
return meshgrid(arange(Nx), arange(Ny))
else:
x0,x1,y0,y1 = self.extent
x = linspace(x0, x1, Nx)
y = linspace(y0, y1, Ny)
return meshgrid(x, y)
# Match image behavior:
if self.extent is None:
x0,x1,y0,y1 = (0, Nx, 0, Ny)
else:
x0,x1,y0,y1 = self.extent
dx = float(x1 - x0)/Nx
dy = float(y1 - y0)/Ny
x = x0 + (arange(Nx) + 0.5) * dx
y = y0 + (arange(Ny) + 0.5) * dy
if self.origin == 'upper':
y = y[::-1]
return meshgrid(x,y)
def _initialize_x_y(self, z):
'''
Return X, Y arrays such that contour(Z) will match imshow(Z)
if origin is not None.
The center of pixel Z[i,j] depends on origin:
if origin is None, x = j, y = i;
if origin is 'lower', x = j + 0.5, y = i + 0.5;
if origin is 'upper', x = j + 0.5, y = Nrows - i - 0.5
If extent is not None, x and y will be scaled to match,
as in imshow.
If origin is None and extent is not None, then extent
will give the minimum and maximum values of x and y.
'''
if len(shape(z)) != 2:
raise TypeError("Input must be a 2D array.")
else:
Ny, Nx = shape(z)
if self.origin is None: # Not for image-matching.
if self.extent is None:
return meshgrid(arange(Nx), arange(Ny))
else:
x0, x1, y0, y1 = self.extent
x = linspace(x0, x1, Nx)
y = linspace(y0, y1, Ny)
return meshgrid(x, y)
# Match image behavior:
if self.extent is None:
x0, x1, y0, y1 = (0, Nx, 0, Ny)
else:
x0, x1, y0, y1 = self.extent
dx = float(x1 - x0) / Nx
dy = float(y1 - y0) / Ny
x = x0 + (arange(Nx) + 0.5) * dx
y = y0 + (arange(Ny) + 0.5) * dy
if self.origin == 'upper':
y = y[::-1]
return meshgrid(x, y)
def __init__(self, ax, labels, active=0, activecolor='blue'):
"""
Add radio buttons to axes.Axes instance ax
labels is a len(buttons) list of labels as strings
active is the index into labels for the button that is active
activecolor is the color of the button when clicked
"""
self.activecolor = activecolor
ax.set_xticks([])
ax.set_yticks([])
ax.set_navigate(False)
dy = 1./(len(labels)+1)
ys = linspace(1-dy, dy, len(labels))
cnt = 0
axcolor = ax.get_axis_bgcolor()
self.labels = []
self.circles = []
for y, label in zip(ys, labels):
t = ax.text(0.25, y, label, transform=ax.transAxes,
horizontalalignment='left',
verticalalignment='center')
if cnt==active:
facecolor = activecolor
else:
facecolor = axcolor
p = Circle(xy=(0.15, y), radius=0.05, facecolor=facecolor,
transform=ax.transAxes)
self.labels.append(t)
self.circles.append(p)
ax.add_patch(p)
cnt += 1
ax.figure.canvas.mpl_connect('button_press_event', self._clicked)
self.ax = ax
self.cnt = 0
self.observers = {}
def __call__(self):
'Return the locations of the ticks'
self.verify_intervals()
vmin, vmax = self.viewInterval.get_bounds()
if vmax < vmin:
vmin, vmax = vmax, vmin
if self.presets.has_key((vmin, vmax)):
return self.presets[(vmin, vmax)]
if self.numticks is None:
self._set_numticks()
if self.numticks == 0: return []
ticklocs = linspace(vmin, vmax, self.numticks)
return ticklocs
def __call__(self):
'Return the locations of the ticks'
self.verify_intervals()
vmin, vmax = self.viewInterval.get_bounds()
if vmax<vmin:
vmin, vmax = vmax, vmin
if self.presets.has_key((vmin, vmax)):
return self.presets[(vmin, vmax)]
if self.numticks is None:
self._set_numticks()
if self.numticks==0: return []
ticklocs = linspace(vmin, vmax, self.numticks)
return ticklocs
def __init__(self, parent, handles, labels, loc, isaxes=True):
Artist.__init__(self)
if is_string_like(loc) and not self.codes.has_key(loc):
verbose.report_error(
'Unrecognized location %s. Falling back on upper right; valid locations are\n%s\t'
% (loc, '\n\t'.join(self.codes.keys())))
if is_string_like(loc): loc = self.codes.get(loc, 1)
if isaxes: # parent is an Axes
self.set_figure(parent.figure)
else: # parent is a Figure
self.set_figure(parent)
self.parent = parent
self.set_transform(get_bbox_transform(unit_bbox(), parent.bbox))
self._loc = loc
# make a trial box in the middle of the axes. relocate it
# based on it's bbox
left, upper = 0.5, 0.5
if self.NUMPOINTS == 1:
self._xdata = array([left + self.HANDLELEN * 0.5])
else:
self._xdata = linspace(left, left + self.HANDLELEN, self.NUMPOINTS)
textleft = left + self.HANDLELEN + self.HANDLETEXTSEP
self.texts = self._get_texts(labels, textleft, upper)
self.handles = self._get_handles(handles, self.texts)
left, top = self.texts[-1].get_position()
HEIGHT = self._approx_text_height()
bottom = top - HEIGHT
left -= self.HANDLELEN + self.HANDLETEXTSEP + self.PAD
self.legendPatch = Rectangle(
xy=(left, bottom),
width=0.5,
height=HEIGHT * len(self.texts),
facecolor='w',
edgecolor='k',
)
self._set_artist_props(self.legendPatch)
self._drawFrame = True
def __init__(self, parent, handles, labels, loc, isaxes=True):
Artist.__init__(self)
if is_string_like(loc) and not self.codes.has_key(loc):
verbose.report_error(
"Unrecognized location %s. Falling back on upper right; valid locations are\n%s\t"
% (loc, "\n\t".join(self.codes.keys()))
)
if is_string_like(loc):
loc = self.codes.get(loc, 1)
if isaxes: # parent is an Axes
self.set_figure(parent.figure)
else: # parent is a Figure
self.set_figure(parent)
self.parent = parent
self.set_transform(get_bbox_transform(unit_bbox(), parent.bbox))
self._loc = loc
# make a trial box in the middle of the axes. relocate it
# based on it's bbox
left, upper = 0.5, 0.5
if self.NUMPOINTS == 1:
self._xdata = array([left + self.HANDLELEN * 0.5])
else:
self._xdata = linspace(left, left + self.HANDLELEN, self.NUMPOINTS)
textleft = left + self.HANDLELEN + self.HANDLETEXTSEP
self.texts = self._get_texts(labels, textleft, upper)
self.handles = self._get_handles(handles, self.texts)
left, top = self.texts[-1].get_position()
HEIGHT = self._approx_text_height()
bottom = top - HEIGHT
left -= self.HANDLELEN + self.HANDLETEXTSEP + self.PAD
self.legendPatch = Rectangle(
xy=(left, bottom), width=0.5, height=HEIGHT * len(self.texts), facecolor="w", edgecolor="k"
)
self._set_artist_props(self.legendPatch)
self._drawFrame = True
def colorbar_classic(self, mappable, cax=None,
orientation='vertical', tickfmt='%1.1f',
cspacing='proportional',
clabels=None, drawedges=False, edgewidth=0.5,
edgecolor='k'):
"""
Create a colorbar for mappable image
mappable is the cm.ScalarMappable instance that you want the
colorbar to apply to, e.g. an Image as returned by imshow or a
PatchCollection as returned by scatter or pcolor.
tickfmt is a format string to format the colorbar ticks
cax is a colorbar axes instance in which the colorbar will be
placed. If None, as default axesd will be created resizing the
current aqxes to make room for it. If not None, the supplied axes
will be used and the other axes positions will be unchanged.
orientation is the colorbar orientation: one of 'vertical' | 'horizontal'
cspacing controls how colors are distributed on the colorbar.
if cspacing == 'linear', each color occupies an equal area
on the colorbar, regardless of the contour spacing.
if cspacing == 'proportional' (Default), the area each color
occupies on the the colorbar is proportional to the contour interval.
Only relevant for a Contour image.
clabels can be a sequence containing the
contour levels to be labelled on the colorbar, or None (Default).
If clabels is None, labels for all contour intervals are
displayed. Only relevant for a Contour image.
if drawedges == True, lines are drawn at the edges between
each color on the colorbar. Default False.
edgecolor is the line color delimiting the edges of the colors
on the colorbar (if drawedges == True). Default black ('k')
edgewidth is the width of the lines delimiting the edges of
the colors on the colorbar (if drawedges == True). Default 0.5
return value is the colorbar axes instance
"""
if orientation not in ('horizontal', 'vertical'):
raise ValueError('Orientation must be horizontal or vertical')
if isinstance(mappable, FigureImage) and cax is None:
raise TypeError('Colorbars for figure images currently not supported unless you provide a colorbar axes in cax')
ax = self.gca()
cmap = mappable.cmap
if cax is None:
l,b,w,h = ax.get_position()
if orientation=='vertical':
neww = 0.8*w
ax.set_position((l,b,neww,h), 'both')
cax = self.add_axes([l + 0.9*w, b, 0.1*w, h])
else:
newh = 0.8*h
ax.set_position((l,b+0.2*h,w,newh), 'both')
cax = self.add_axes([l, b, w, 0.1*h])
else:
if not isinstance(cax, Axes):
raise TypeError('Expected an Axes instance for cax')
norm = mappable.norm
if norm.vmin is None or norm.vmax is None:
mappable.autoscale()
cmin = norm.vmin
cmax = norm.vmax
if isinstance(mappable, ContourSet):
# mappable image is from contour or contourf
clevs = mappable.levels
clevs = minimum(clevs, cmax)
clevs = maximum(clevs, cmin)
isContourSet = True
elif isinstance(mappable, ScalarMappable):
# from imshow or pcolor.
isContourSet = False
clevs = linspace(cmin, cmax, cmap.N+1) # boundaries, hence N+1
else:
raise TypeError("don't know how to handle type %s"%type(mappable))
N = len(clevs)
C = array([clevs, clevs])
if cspacing == 'linear':
X, Y = meshgrid(clevs, [0, 1])
elif cspacing == 'proportional':
X, Y = meshgrid(linspace(cmin, cmax, N), [0, 1])
else:
raise ValueError("cspacing must be 'linear' or 'proportional'")
if orientation=='vertical':
args = (transpose(Y), transpose(C), transpose(X), clevs)
else:
args = (C, Y, X, clevs)
#If colors were listed in the original mappable, then
# let contour handle them the same way.
colors = getattr(mappable, 'colors', None)
if colors is not None:
kw = {'colors': colors}
else:
kw = {'cmap':cmap, 'norm':norm}
if isContourSet and not mappable.filled:
CS = cax.contour(*args, **kw)
colls = mappable.collections
for ii in range(len(colls)):
CS.collections[ii].set_linewidth(colls[ii].get_linewidth())
else:
kw['antialiased'] = False
CS = cax.contourf(*args, **kw)
if drawedges:
for col in CS.collections:
col.set_edgecolor(edgecolor)
col.set_linewidth(edgewidth)
mappable.add_observer(CS)
mappable.set_colorbar(CS, cax)
if isContourSet:
if cspacing == 'linear':
ticks = linspace(cmin, cmax, N)
else:
ticks = clevs
if cmin == mappable.levels[0]:
ticklevs = clevs
else: # We are not showing the full ends of the range.
ticks = ticks[1:-1]
ticklevs = clevs[1:-1]
labs = [tickfmt % lev for lev in ticklevs]
if clabels is not None:
for i, lev in enumerate(ticklevs):
if lev not in clabels:
labs[i] = ''
if orientation=='vertical':
cax.set_xticks([])
cax.yaxis.tick_right()
cax.yaxis.set_label_position('right')
if isContourSet:
cax.set_yticks(ticks)
cax.set_yticklabels(labs)
else:
cax.yaxis.set_major_formatter(FormatStrFormatter(tickfmt))
else:
cax.set_yticks([])
if isContourSet:
cax.set_xticks(ticks)
cax.set_xticklabels(labs)
else:
cax.xaxis.set_major_formatter(FormatStrFormatter(tickfmt))
self.sca(ax)
return cax
def __init__(self, parent, handles, labels, loc,
isaxes=True,
numpoints = 4, # the number of points in the legend line
prop = FontProperties(size='smaller'),
pad = 0.2, # the fractional whitespace inside the legend border
markerscale = 0.6, # the relative size of legend markers vs. original
# the following dimensions are in axes coords
labelsep = 0.005, # the vertical space between the legend entries
handlelen = 0.05, # the length of the legend lines
handletextsep = 0.02, # the space between the legend line and legend text
axespad = 0.02, # the border between the axes and legend edge
shadow=False,
):
"""
parent # the artist that contains the legend
handles # a list of artists (lines, patches) to add to the legend
labels # a list of strings to label the legend
loc # a location code
isaxes=True # whether this is an axes legend
numpoints = 4 # the number of points in the legend line
fontprop = FontProperties('smaller') # the font property
pad = 0.2 # the fractional whitespace inside the legend border
markerscale = 0.6 # the relative size of legend markers vs. original
shadow # if True, draw a shadow behind legend
The following dimensions are in axes coords
labelsep = 0.005 # the vertical space between the legend entries
handlelen = 0.05 # the length of the legend lines
handletextsep = 0.02 # the space between the legend line and legend text
axespad = 0.02 # the border between the axes and legend edge
"""
Artist.__init__(self)
if is_string_like(loc) and not self.codes.has_key(loc):
verbose.report_error('Unrecognized location %s. Falling back on upper right; valid locations are\n%s\t' %(loc, '\n\t'.join(self.codes.keys())))
if is_string_like(loc): loc = self.codes.get(loc, 1)
self.numpoints = numpoints
self.prop = prop
self.fontsize = prop.get_size_in_points()
self.pad = pad
self.markerscale = markerscale
self.labelsep = labelsep
self.handlelen = handlelen
self.handletextsep = handletextsep
self.axespad = axespad
self.shadow = shadow
if isaxes: # parent is an Axes
self.set_figure(parent.figure)
else: # parent is a Figure
self.set_figure(parent)
self.parent = parent
self.set_transform( get_bbox_transform( unit_bbox(), parent.bbox) )
self._loc = loc
# make a trial box in the middle of the axes. relocate it
# based on it's bbox
left, upper = 0.5, 0.5
if self.numpoints == 1:
self._xdata = array([left + self.handlelen*0.5])
else:
self._xdata = linspace(left, left + self.handlelen, self.numpoints)
textleft = left+ self.handlelen+self.handletextsep
self.texts = self._get_texts(labels, textleft, upper)
self.handles = self._get_handles(handles, self.texts)
left, top = self.texts[-1].get_position()
HEIGHT = self._approx_text_height()
bottom = top-HEIGHT
left -= self.handlelen + self.handletextsep + self.pad
self.legendPatch = Rectangle(
xy=(left, bottom), width=0.5, height=HEIGHT*len(self.texts),
facecolor='w', edgecolor='k',
)
self._set_artist_props(self.legendPatch)
self._drawFrame = True
def __init__(self, ax, labels, actives):
"""
Add check buttons to axes.Axes instance ax
labels is a len(buttons) list of labels as strings
actives is a len(buttons) list of booleans indicating whether
the button is active
"""
ax.set_xticks([])
ax.set_yticks([])
ax.set_navigate(False)
if len(labels)>1:
dy = 1./(len(labels)+1)
ys = linspace(1-dy, dy, len(labels))
else:
dy = 0.25
ys = [0.5]
cnt = 0
axcolor = ax.get_axis_bgcolor()
self.labels = []
self.lines = []
self.rectangles = []
lineparams = {'color':'k', 'linewidth':1.25, 'transform':ax.transAxes,
'solid_capstyle':'butt'}
for y, label in zip(ys, labels):
t = ax.text(0.25, y, label, transform=ax.transAxes,
horizontalalignment='left',
verticalalignment='center')
w, h = dy/2., dy/2.
x, y = 0.05, y-h/2.
p = Rectangle(xy=(x,y), width=w, height=h,
facecolor=axcolor,
transform=ax.transAxes)
l1 = Line2D([x, x+w], [y+h, y], **lineparams)
l2 = Line2D([x, x+w], [y, y+h], **lineparams)
l1.set_visible(actives[cnt])
l2.set_visible(actives[cnt])
self.labels.append(t)
self.rectangles.append(p)
self.lines.append((l1,l2))
ax.add_patch(p)
ax.add_line(l1)
ax.add_line(l2)
cnt += 1
ax.figure.canvas.mpl_connect('button_press_event', self._clicked)
self.ax = ax
self.cnt = 0
self.observers = {}
def __init__(self, parent, handles, labels, loc,
isaxes= None,
numpoints = None, # the number of points in the legend line
prop = None,
pad = None, # the fractional whitespace inside the legend border
markerscale = None, # the relative size of legend markers vs. original
# the following dimensions are in axes coords
labelsep = None, # the vertical space between the legend entries
handlelen = None, # the length of the legend lines
handletextsep = None, # the space between the legend line and legend text
axespad = None, # the border between the axes and legend edge
shadow= None,
):
"""
parent # the artist that contains the legend
handles # a list of artists (lines, patches) to add to the legend
labels # a list of strings to label the legend
loc # a location code
isaxes=True # whether this is an axes legend
numpoints = 4 # the number of points in the legend line
fontprop = FontProperties(size='smaller') # the font property
pad = 0.2 # the fractional whitespace inside the legend border
markerscale = 0.6 # the relative size of legend markers vs. original
shadow # if True, draw a shadow behind legend
The following dimensions are in axes coords
labelsep = 0.005 # the vertical space between the legend entries
handlelen = 0.05 # the length of the legend lines
handletextsep = 0.02 # the space between the legend line and legend text
axespad = 0.02 # the border between the axes and legend edge
"""
Artist.__init__(self)
if is_string_like(loc) and not self.codes.has_key(loc):
warnings.warn('Unrecognized location %s. Falling back on upper right; valid locations are\n%s\t' %(loc, '\n\t'.join(self.codes.keys())))
if is_string_like(loc): loc = self.codes.get(loc, 1)
proplist=[numpoints, pad, markerscale, labelsep, handlelen, handletextsep, axespad, shadow, isaxes]
propnames=['numpoints', 'pad', 'markerscale', 'labelsep', 'handlelen', 'handletextsep', 'axespad', 'shadow', 'isaxes']
for name, value in zip(propnames,proplist):
if value is None:
value=rcParams["legend."+name]
setattr(self,name,value)
if prop is None:
self.prop=FontProperties(size=rcParams["legend.fontsize"])
else:
self.prop=prop
self.fontsize = self.prop.get_size_in_points()
if self.isaxes: # parent is an Axes
self.set_figure(parent.figure)
else: # parent is a Figure
self.set_figure(parent)
self.parent = parent
self.set_transform( get_bbox_transform( unit_bbox(), parent.bbox) )
self._loc = loc
# make a trial box in the middle of the axes. relocate it
# based on it's bbox
left, top = 0.5, 0.5
if self.numpoints == 1:
self._xdata = array([left + self.handlelen*0.5])
else:
self._xdata = linspace(left, left + self.handlelen, self.numpoints)
textleft = left+ self.handlelen+self.handletextsep
self.texts = self._get_texts(labels, textleft, top)
self.legendHandles = self._get_handles(handles, self.texts)
if len(self.texts):
left, top = self.texts[-1].get_position()
HEIGHT = self._approx_text_height()*len(self.texts)
else:
HEIGHT = 0.2
bottom = top-HEIGHT
left -= self.handlelen + self.handletextsep + self.pad
self.legendPatch = Rectangle(
xy=(left, bottom), width=0.5, height=HEIGHT,
facecolor='w', edgecolor='k',
)
self._set_artist_props(self.legendPatch)
self._drawFrame = True
def __init__(self, ax, labels, actives):
"""
Add check buttons to axes.Axes instance ax
labels is a len(buttons) list of labels as strings
actives is a len(buttons) list of booleans indicating whether
the button is active
"""
ax.set_xticks([])
ax.set_yticks([])
ax.set_navigate(False)
if len(labels) > 1:
dy = 1. / (len(labels) + 1)
ys = linspace(1 - dy, dy, len(labels))
else:
dy = 0.25
ys = [0.5]
cnt = 0
axcolor = ax.get_axis_bgcolor()
self.labels = []
self.lines = []
self.rectangles = []
lineparams = {
'color': 'k',
'linewidth': 1.25,
'transform': ax.transAxes,
'solid_capstyle': 'butt'
}
for y, label in zip(ys, labels):
t = ax.text(0.25,
y,
label,
transform=ax.transAxes,
horizontalalignment='left',
verticalalignment='center')
w, h = dy / 2., dy / 2.
x, y = 0.05, y - h / 2.
p = Rectangle(xy=(x, y),
width=w,
height=h,
facecolor=axcolor,
transform=ax.transAxes)
l1 = Line2D([x, x + w], [y + h, y], **lineparams)
l2 = Line2D([x, x + w], [y, y + h], **lineparams)
l1.set_visible(actives[cnt])
l2.set_visible(actives[cnt])
self.labels.append(t)
self.rectangles.append(p)
self.lines.append((l1, l2))
ax.add_patch(p)
ax.add_line(l1)
ax.add_line(l2)
cnt += 1
ax.figure.canvas.mpl_connect('button_press_event', self._clicked)
self.ax = ax
self.cnt = 0
self.observers = {}
def colorbar_classic(self,
mappable,
cax=None,
orientation='vertical',
tickfmt='%1.1f',
cspacing='proportional',
clabels=None,
drawedges=False,
edgewidth=0.5,
edgecolor='k'):
"""
Create a colorbar for mappable image
mappable is the cm.ScalarMappable instance that you want the
colorbar to apply to, e.g. an Image as returned by imshow or a
PatchCollection as returned by scatter or pcolor.
tickfmt is a format string to format the colorbar ticks
cax is a colorbar axes instance in which the colorbar will be
placed. If None, as default axesd will be created resizing the
current aqxes to make room for it. If not None, the supplied axes
will be used and the other axes positions will be unchanged.
orientation is the colorbar orientation: one of 'vertical' | 'horizontal'
cspacing controls how colors are distributed on the colorbar.
if cspacing == 'linear', each color occupies an equal area
on the colorbar, regardless of the contour spacing.
if cspacing == 'proportional' (Default), the area each color
occupies on the the colorbar is proportional to the contour interval.
Only relevant for a Contour image.
clabels can be a sequence containing the
contour levels to be labelled on the colorbar, or None (Default).
If clabels is None, labels for all contour intervals are
displayed. Only relevant for a Contour image.
if drawedges == True, lines are drawn at the edges between
each color on the colorbar. Default False.
edgecolor is the line color delimiting the edges of the colors
on the colorbar (if drawedges == True). Default black ('k')
edgewidth is the width of the lines delimiting the edges of
the colors on the colorbar (if drawedges == True). Default 0.5
return value is the colorbar axes instance
"""
if orientation not in ('horizontal', 'vertical'):
raise ValueError('Orientation must be horizontal or vertical')
if isinstance(mappable, FigureImage) and cax is None:
raise TypeError(
'Colorbars for figure images currently not supported unless you provide a colorbar axes in cax'
)
ax = self.gca()
cmap = mappable.cmap
if cax is None:
l, b, w, h = ax.get_position()
if orientation == 'vertical':
neww = 0.8 * w
ax.set_position((l, b, neww, h), 'both')
cax = self.add_axes([l + 0.9 * w, b, 0.1 * w, h])
else:
newh = 0.8 * h
ax.set_position((l, b + 0.2 * h, w, newh), 'both')
cax = self.add_axes([l, b, w, 0.1 * h])
else:
if not isinstance(cax, Axes):
raise TypeError('Expected an Axes instance for cax')
norm = mappable.norm
if norm.vmin is None or norm.vmax is None:
mappable.autoscale()
cmin = norm.vmin
cmax = norm.vmax
if isinstance(mappable, ContourSet):
# mappable image is from contour or contourf
clevs = mappable.levels
clevs = minimum(clevs, cmax)
clevs = maximum(clevs, cmin)
isContourSet = True
elif isinstance(mappable, ScalarMappable):
# from imshow or pcolor.
isContourSet = False
clevs = linspace(cmin, cmax, cmap.N + 1) # boundaries, hence N+1
else:
raise TypeError("don't know how to handle type %s" %
type(mappable))
N = len(clevs)
C = array([clevs, clevs])
if cspacing == 'linear':
X, Y = meshgrid(clevs, [0, 1])
elif cspacing == 'proportional':
X, Y = meshgrid(linspace(cmin, cmax, N), [0, 1])
else:
raise ValueError("cspacing must be 'linear' or 'proportional'")
if orientation == 'vertical':
args = (transpose(Y), transpose(C), transpose(X), clevs)
else:
args = (C, Y, X, clevs)
#If colors were listed in the original mappable, then
# let contour handle them the same way.
colors = getattr(mappable, 'colors', None)
if colors is not None:
kw = {'colors': colors}
else:
kw = {'cmap': cmap, 'norm': norm}
if isContourSet and not mappable.filled:
CS = cax.contour(*args, **kw)
colls = mappable.collections
for ii in range(len(colls)):
CS.collections[ii].set_linewidth(colls[ii].get_linewidth())
else:
kw['antialiased'] = False
CS = cax.contourf(*args, **kw)
if drawedges:
for col in CS.collections:
col.set_edgecolor(edgecolor)
col.set_linewidth(edgewidth)
mappable.add_observer(CS)
mappable.set_colorbar(CS, cax)
if isContourSet:
if cspacing == 'linear':
ticks = linspace(cmin, cmax, N)
else:
ticks = clevs
if cmin == mappable.levels[0]:
ticklevs = clevs
else: # We are not showing the full ends of the range.
ticks = ticks[1:-1]
ticklevs = clevs[1:-1]
labs = [tickfmt % lev for lev in ticklevs]
if clabels is not None:
for i, lev in enumerate(ticklevs):
if lev not in clabels:
labs[i] = ''
if orientation == 'vertical':
cax.set_xticks([])
cax.yaxis.tick_right()
cax.yaxis.set_label_position('right')
if isContourSet:
cax.set_yticks(ticks)
cax.set_yticklabels(labs)
else:
cax.yaxis.set_major_formatter(FormatStrFormatter(tickfmt))
else:
cax.set_yticks([])
if isContourSet:
cax.set_xticks(ticks)
cax.set_xticklabels(labs)
else:
cax.xaxis.set_major_formatter(FormatStrFormatter(tickfmt))
self.sca(ax)
return cax
def colorbar(self,
mappable,
tickfmt='%1.1f',
cax=None,
orientation='vertical'):
"""
Create a colorbar for mappable image
tickfmt is a format string to format the colorbar ticks
cax is a colorbar axes instance in which the colorbar will be
placed. If None, as default axesd will be created resizing the
current aqxes to make room for it. If not None, the supplied axes
will be used and the other axes positions will be unchanged.
orientation is the colorbar orientation: one of 'vertical' | 'horizontal'
return value is the colorbar axes instance
"""
if orientation not in ('horizontal', 'vertical'):
raise ValueError('Orientation must be horizontal or vertical')
if isinstance(mappable, FigureImage) and cax is None:
raise TypeError(
'Colorbars for figure images currently not supported unless you provide a colorbar axes in cax'
)
ax = self.gca()
cmap = mappable.cmap
norm = mappable.norm
if norm.vmin is None or norm.vmax is None:
mappable.autoscale()
cmin = norm.vmin
cmax = norm.vmax
if cax is None:
l, b, w, h = ax.get_position()
if orientation == 'vertical':
neww = 0.8 * w
ax.set_position((l, b, neww, h))
cax = self.add_axes([l + 0.9 * w, b, 0.1 * w, h])
else:
newh = 0.8 * h
ax.set_position((l, b + 0.2 * h, w, newh))
cax = self.add_axes([l, b, w, 0.1 * h])
else:
if not isinstance(cax, Axes):
raise TypeError('Expected an Axes instance for cax')
N = cmap.N
c = linspace(cmin, cmax, N)
C = array([c, c])
if orientation == 'vertical':
C = transpose(C)
if orientation == 'vertical':
extent = (0, 1, cmin, cmax)
else:
extent = (cmin, cmax, 0, 1)
coll = cax.imshow(C,
interpolation='nearest',
origin='lower',
cmap=cmap,
norm=norm,
extent=extent)
mappable.add_observer(coll)
mappable.set_colorbar(coll, cax)
if orientation == 'vertical':
cax.set_xticks([])
cax.yaxis.tick_right()
cax.yaxis.set_major_formatter(FormatStrFormatter(tickfmt))
else:
cax.set_yticks([])
cax.xaxis.set_major_formatter(FormatStrFormatter(tickfmt))
self.sca(ax)
return cax
def colorbar(self, mappable, tickfmt='%1.1f', cax=None, orientation='vertical'):
"""
Create a colorbar for mappable image
tickfmt is a format string to format the colorbar ticks
cax is a colorbar axes instance in which the colorbar will be
placed. If None, as default axesd will be created resizing the
current aqxes to make room for it. If not None, the supplied axes
will be used and the other axes positions will be unchanged.
orientation is the colorbar orientation: one of 'vertical' | 'horizontal'
return value is the colorbar axes instance
"""
if orientation not in ('horizontal', 'vertical'):
raise ValueError('Orientation must be horizontal or vertical')
if isinstance(mappable, FigureImage) and cax is None:
raise TypeError('Colorbars for figure images currently not supported unless you provide a colorbar axes in cax')
ax = self.gca()
cmap = mappable.cmap
norm = mappable.norm
if norm.vmin is None or norm.vmax is None:
mappable.autoscale()
cmin = norm.vmin
cmax = norm.vmax
if cax is None:
l,b,w,h = ax.get_position()
if orientation=='vertical':
neww = 0.8*w
ax.set_position((l,b,neww,h))
cax = self.add_axes([l + 0.9*w, b, 0.1*w, h])
else:
newh = 0.8*h
ax.set_position((l,b+0.2*h,w,newh))
cax = self.add_axes([l, b, w, 0.1*h])
else:
if not isinstance(cax, Axes):
raise TypeError('Expected an Axes instance for cax')
N = cmap.N
c = linspace(cmin, cmax, N)
C = array([c,c])
if orientation=='vertical':
C = transpose(C)
if orientation=='vertical':
extent=(0, 1, cmin, cmax)
else:
extent=(cmin, cmax, 0, 1)
coll = cax.imshow(C,
interpolation='nearest',
#interpolation='bilinear',
origin='lower',
cmap=cmap, norm=norm,
extent=extent)
mappable.add_observer(coll)
mappable.set_colorbar(coll, cax)
if orientation=='vertical':
cax.set_xticks([])
cax.yaxis.tick_right()
cax.yaxis.set_major_formatter(FormatStrFormatter(tickfmt))
else:
cax.set_yticks([])
cax.xaxis.set_major_formatter(FormatStrFormatter(tickfmt))
self.sca(ax)
return cax
