"""
These are classes to support contour plotting and
labelling for the axes class
"""
from __future__ import division
import warnings
import matplotlib as mpl
import numpy as npy
import matplotlib.numerix.npyma as ma
import matplotlib._cntr as _cntr
import matplotlib.path as path
import matplotlib.ticker as ticker
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.collections as collections
import matplotlib.font_manager as font_manager
import matplotlib.text as text
import matplotlib.cbook as cbook
# We can't use a single line collection for contour because a line
# collection can have only a single line style, and we want to be able to have
# dashed negative contours, for example, and solid positive contours.
# We could use a single polygon collection for filled contours, but it
# seems better to keep line and filled contours similar, with one collection
# per level.
class ContourLabeler:
'''Mixin to provide labelling capability to ContourSet'''
def clabel(self, *args, **kwargs):
"""
clabel(CS, **kwargs) - add labels to line contours in CS,
where CS is a ContourSet object returned by contour.
clabel(CS, V, **kwargs) - only label contours listed in V
keyword arguments:
* fontsize = None: as described in http://matplotlib.sf.net/fonts.html
* colors = None:
- a tuple of matplotlib color args (string, float, rgb, etc),
different labels will be plotted in different colors in the order
specified
- one string color, e.g. colors = 'r' or colors = 'red', all labels
will be plotted in this color
- if colors == None, the color of each label matches the color
of the corresponding contour
* inline = True: controls whether the underlying contour is removed
(inline = True) or not (False)
* fmt = '%1.3f': a format string for the label
"""
fontsize = kwargs.get('fontsize', None)
inline = kwargs.get('inline', 1)
self.fmt = kwargs.get('fmt', '%1.3f')
_colors = kwargs.get('colors', None)
if len(args) == 0:
levels = self.levels
indices = range(len(self.levels))
elif len(args) == 1:
levlabs = list(args[0])
indices, levels = [], []
for i, lev in enumerate(self.levels):
if lev in levlabs:
indices.append(i)
levels.append(lev)
if len(levels) < len(levlabs):
msg = "Specified levels " + str(levlabs)
msg += "\n don't match available levels "
msg += str(self.levels)
raise ValueError(msg)
else:
raise TypeError("Illegal arguments to clabel, see help(clabel)")
self.label_levels = levels
self.label_indices = indices
self.fp = font_manager.FontProperties()
if fontsize == None:
font_size = int(self.fp.get_size_in_points())
else:
if type(fontsize) not in [int, float, str]:
raise TypeError("Font size must be an integer number.")
# Can't it be floating point, as indicated in line above?
else:
if type(fontsize) == str:
font_size = int(self.fp.get_size_in_points())
else:
self.fp.set_size(fontsize)
font_size = fontsize
self.fslist = [font_size] * len(levels)
if _colors == None:
self.label_mappable = self
self.label_cvalues = npy.take(self.cvalues, self.label_indices)
else:
cmap = colors.ListedColormap(_colors, N=len(self.label_levels))
self.label_cvalues = range(len(self.label_levels))
self.label_mappable = cm.ScalarMappable(cmap = cmap,
norm = colors.NoNorm())
#self.cl = [] # Initialized in ContourSet.__init__
#self.cl_cvalues = [] # same
self.cl_xy = []
self.labels(inline)
for label in self.cl:
self.ax.add_artist(label)
self.label_list = cbook.silent_list('text.Text', self.cl)
return self.label_list
def print_label(self, linecontour,labelwidth):
"if contours are too short, don't plot a label"
lcsize = len(linecontour)
if lcsize > 10 * labelwidth:
return 1
xmax = npy.amax(npy.array(linecontour)[:,0])
xmin = npy.amin(npy.array(linecontour)[:,0])
ymax = npy.amax(npy.array(linecontour)[:,1])
ymin = npy.amin(npy.array(linecontour)[:,1])
lw = labelwidth
if (xmax - xmin) > 1.2* lw or (ymax - ymin) > 1.2 * lw:
return 1
else:
return 0
def too_close(self, x,y, lw):
"if there's a label already nearby, find a better place"
if self.cl_xy != []:
dist = [npy.sqrt((x-loc[0]) ** 2 + (y-loc[1]) ** 2)
for loc in self.cl_xy]
for d in dist:
if d < 1.2*lw:
return 1
else: return 0
else: return 0
def get_label_coords(self, distances, XX, YY, ysize, lw):
""" labels are ploted at a location with the smallest
dispersion of the contour from a straight line
unless there's another label nearby, in which case
the second best place on the contour is picked up
if there's no good place a label isplotted at the
beginning of the contour
"""
hysize = int(ysize/2)
adist = npy.argsort(distances)
for ind in adist:
x, y = XX[ind][hysize], YY[ind][hysize]
if self.too_close(x,y, lw):
continue
else:
self.cl_xy.append((x,y))
return x,y, ind
ind = adist[0]
x, y = XX[ind][hysize], YY[ind][hysize]
self.cl_xy.append((x,y))
return x,y, ind
def get_label_width(self, lev, fmt, fsize):
"get the width of the label in points"
if cbook.is_string_like(lev):
lw = (len(lev)) * fsize
else:
lw = (len(fmt%lev)) * fsize
return lw
def set_label_props(self, label, text, color):
"set the label properties - color, fontsize, text"
label.set_text(text)
label.set_color(color)
label.set_fontproperties(self.fp)
label.set_clip_box(self.ax.bbox)
def get_text(self, lev, fmt):
"get the text of the label"
if cbook.is_string_like(lev):
return lev
else:
return fmt%lev
def break_linecontour(self, linecontour, rot, labelwidth, ind):
"break a contour in two contours at the location of the label"
lcsize = len(linecontour)
hlw = int(labelwidth/2)
#length of label in screen coords
ylabel = abs(hlw * npy.sin(rot*npy.pi/180))
xlabel = abs(hlw * npy.cos(rot*npy.pi/180))
trans = self.ax.transData
slc = trans.transform(linecontour)
x,y = slc[ind]
xx= npy.asarray(slc)[:,0].copy()
yy=npy.asarray(slc)[:,1].copy()
#indices which are under the label
inds, = npy.nonzero(((xx < x+xlabel) & (xx > x-xlabel)) &
((yy < y+ylabel) & (yy > y-ylabel)))
if len(inds) >0:
#if the label happens to be over the beginning of the
#contour, the entire contour is removed, i.e.
#indices to be removed are
#inds= [0,1,2,3,305,306,307]
#should rewrite this in a better way
linds, = npy.nonzero(inds[1:]- inds[:-1] != 1)
if inds[0] == 0 and len(linds) != 0:
ii = inds[linds[0]]
lc1 =linecontour[ii+1:inds[ii+1]]
lc2 = []
else:
lc1=linecontour[:inds[0]]
lc2= linecontour[inds[-1]+1:]
else:
lc1=linecontour[:ind]
lc2 = linecontour[ind+1:]
if rot <0:
new_x1, new_y1 = x-xlabel, y+ylabel
new_x2, new_y2 = x+xlabel, y-ylabel
else:
new_x1, new_y1 = x-xlabel, y-ylabel
new_x2, new_y2 = x+xlabel, y+ylabel
inverse = trans.inverted()
new_x1d, new_y1d = inverse.transform_point((new_x1, new_y1))
new_x2d, new_y2d = inverse.transform_point((new_x2, new_y2))
new_xy1 = npy.array(((new_x1d, new_y1d),))
new_xy2 = npy.array(((new_x2d, new_y2d),))
if rot > 0:
if (len(lc1) > 0 and (lc1[-1][0] <= new_x1d)
and (lc1[-1][1] <= new_y1d)):
lc1 = npy.concatenate((lc1, new_xy1))
#lc1.append((new_x1d, new_y1d))
if (len(lc2) > 0 and (lc2[0][0] >= new_x2d)
and (lc2[0][1] >= new_y2d)):
lc2 = npy.concatenate((new_xy2, lc2))
#lc2.insert(0, (new_x2d, new_y2d))
else:
if (len(lc1) > 0 and ((lc1[-1][0] <= new_x1d)
and (lc1[-1][1] >= new_y1d))):
lc1 = npy.concatenate((lc1, new_xy1))
#lc1.append((new_x1d, new_y1d))
if (len(lc2) > 0 and ((lc2[0][0] >= new_x2d)
and (lc2[0][1] <= new_y2d))):
lc2 = npy.concatenate((new_xy2, lc2))
#lc2.insert(0, (new_x2d, new_y2d))
return [lc1,lc2]
def locate_label(self, linecontour, labelwidth):
"""find a good place to plot a label (relatively flat
part of the contour) and the angle of rotation for the
text object
"""
nsize= len(linecontour)
if labelwidth > 1:
xsize = int(npy.ceil(nsize/labelwidth))
else:
xsize = 1
if xsize == 1:
ysize = nsize
else:
ysize = labelwidth
XX = npy.resize(npy.asarray(linecontour)[:,0],(xsize, ysize))
YY = npy.resize(npy.asarray(linecontour)[:,1],(xsize, ysize))
#I might have fouled up the following:
yfirst = YY[:,0].reshape(xsize, 1)
ylast = YY[:,-1].reshape(xsize, 1)
xfirst = XX[:,0].reshape(xsize, 1)
xlast = XX[:,-1].reshape(xsize, 1)
s = (yfirst-YY) * (xlast-xfirst) - (xfirst-XX) * (ylast-yfirst)
L = npy.sqrt((xlast-xfirst)**2+(ylast-yfirst)**2).ravel()
dist = npy.add.reduce(([(abs(s)[i]/L[i]) for i in range(xsize)]),-1)
x,y,ind = self.get_label_coords(dist, XX, YY, ysize, labelwidth)
#print 'ind, x, y', ind, x, y
angle = npy.arctan2(ylast - yfirst, xlast - xfirst).ravel()
rotation = angle[ind]*180/npy.pi
if rotation > 90:
rotation = rotation -180
if rotation < -90:
rotation = 180 + rotation
# There must be a more efficient way...
lc = [tuple(l) for l in linecontour]
dind = lc.index((x,y))
#print 'dind', dind
#dind = list(linecontour).index((x,y))
return x,y, rotation, dind
def labels(self, inline):
levels = self.label_levels
fslist = self.fslist
trans = self.ax.transData
_colors = self.label_mappable.to_rgba(self.label_cvalues)
fmt = self.fmt
for icon, lev, color, cvalue, fsize in zip(self.label_indices,
self.label_levels,
_colors,
self.label_cvalues, fslist):
con = self.collections[icon]
lw = self.get_label_width(lev, fmt, fsize)
additions = []
paths = con.get_paths()
for segNum, linepath in enumerate(paths):
linecontour = linepath.vertices
# for closed contours add one more point to
# avoid division by zero
if npy.all(linecontour[0] == linecontour[-1]):
linecontour = npy.concatenate((linecontour,
linecontour[1][npy.newaxis,:]))
#linecontour.append(linecontour[1])
# transfer all data points to screen coordinates
slc = trans.transform(linecontour)
if self.print_label(slc,lw):
x,y, rotation, ind = self.locate_label(slc, lw)
# transfer the location of the label back to
# data coordinates
dx,dy = trans.inverted().transform_point((x,y))
t = text.Text(dx, dy, rotation = rotation,
horizontalalignment='center',
verticalalignment='center')
_text = self.get_text(lev,fmt)
self.set_label_props(t, _text, color)
self.cl.append(t)
self.cl_cvalues.append(cvalue)
if inline:
new = self.break_linecontour(linecontour, rotation, lw, ind)
if len(new[0]):
paths[segNum] = path.Path(new[0], closed=False)
if len(new[1]):
additions.append(path.Path(new[1], closed=False))
paths.extend(additions)
class ContourSet(cm.ScalarMappable, ContourLabeler):
"""
Create and store a set of contour lines or filled regions.
User-callable method: clabel
Useful attributes:
ax - the axes object in which the contours are drawn
collections - a silent_list of LineCollections or PolyCollections
levels - contour levels
layers - same as levels for line contours; half-way between
levels for filled contours. See _process_colors method.
"""
def __init__(self, ax, *args, **kwargs):
"""
Draw contour lines or filled regions, depending on
whether keyword arg 'filled' is False (default) or True.
The first argument of the initializer must be an axes
object. The remaining arguments and keyword arguments
are described in ContourSet.contour_doc.
"""
self.ax = ax
self.levels = kwargs.get('levels', None)
self.filled = kwargs.get('filled', False)
self.linewidths = kwargs.get('linewidths', None)
self.alpha = kwargs.get('alpha', 1.0)
self.origin = kwargs.get('origin', None)
self.extent = kwargs.get('extent', None)
cmap = kwargs.get('cmap', None)
self.colors = kwargs.get('colors', None)
norm = kwargs.get('norm', None)
self.extend = kwargs.get('extend', 'neither')
self.antialiased = kwargs.get('antialiased', True)
self.nchunk = kwargs.get('nchunk', 0)
self.locator = kwargs.get('locator', None)
if self.origin is not None: assert(self.origin in
['lower', 'upper', 'image'])
if self.extent is not None: assert(len(self.extent) == 4)
if cmap is not None: assert(isinstance(cmap, colors.Colormap))
if self.colors is not None and cmap is not None:
raise ValueError('Either colors or cmap must be None')
if self.origin == 'image': self.origin = mpl.rcParams['image.origin']
x, y, z = self._contour_args(*args) # also sets self.levels,
# self.layers
if self.colors is not None:
cmap = colors.ListedColormap(self.colors, N=len(self.layers))
if self.filled:
self.collections = cbook.silent_list('collections.PolyCollection')
else:
self.collections = cbook.silent_list('collections.LineCollection')
# label lists must be initialized here
self.cl = []
self.cl_cvalues = []
kw = {'cmap': cmap}
if norm is not None:
kw['norm'] = norm
cm.ScalarMappable.__init__(self, **kw) # sets self.cmap;
self._process_colors()
_mask = ma.getmask(z)
if _mask is ma.nomask:
_mask = None
if self.filled:
if self.linewidths is not None:
warnings.warn('linewidths is ignored by contourf')
C = _cntr.Cntr(x, y, z.filled(), _mask)
lowers = self._levels[:-1]
uppers = self._levels[1:]
for level, level_upper in zip(lowers, uppers):
nlist = C.trace(level, level_upper, points = 0,
nchunk = self.nchunk)
col = collections.PolyCollection(nlist,
antialiaseds = (self.antialiased,),
edgecolors= 'None')
self.ax.add_collection(col)
self.collections.append(col)
else:
tlinewidths = self._process_linewidths()
self.tlinewidths = tlinewidths
C = _cntr.Cntr(x, y, z.filled(), _mask)
for level, width in zip(self.levels, tlinewidths):
nlist = C.trace(level, points = 0)
col = collections.LineCollection(nlist,
linewidths = width)
if level < 0.0 and self.monochrome:
ls = mpl.rcParams['contour.negative_linestyle']
col.set_linestyle(ls)
col.set_label('_nolegend_')
self.ax.add_collection(col, False)
self.collections.append(col)
self.changed() # set the colors
x0 = ma.minimum(x)
x1 = ma.maximum(x)
y0 = ma.minimum(y)
y1 = ma.maximum(y)
self.ax.update_datalim([(x0,y0), (x1,y1)])
self.ax.set_xlim((x0, x1))
self.ax.set_ylim((y0, y1))
def changed(self):
tcolors = [ (tuple(rgba),) for rgba in
self.to_rgba(self.cvalues, alpha=self.alpha)]
self.tcolors = tcolors
for color, collection in zip(tcolors, self.collections):
collection.set_color(color)
for label, cv in zip(self.cl, self.cl_cvalues):
label.set_color(self.label_mappable.to_rgba(cv))
# add label colors
cm.ScalarMappable.changed(self)
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.
'''
if self.locator is None:
self.locator = ticker.MaxNLocator(N+1)
self.locator.create_dummy_axis()
locator = self.locator
zmax = self.zmax
zmin = self.zmin
locator.set_bounds(zmin, zmax)
lev = locator()
zmargin = (zmax - zmin) * 0.000001 # so z < (zmax + zmargin)
if zmax >= lev[-1]:
lev[-1] += zmargin
if zmin <= lev[0]:
lev[0] -= zmargin
self._auto = True
if self.filled:
return lev
return lev[1:-1]
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 z.ndim != 2:
raise TypeError("Input must be a 2D array.")
else:
Ny, Nx = z.shape
if self.origin is None: # Not for image-matching.
if self.extent is None:
return npy.meshgrid(npy.arange(Nx), npy.arange(Ny))
else:
x0,x1,y0,y1 = self.extent
x = npy.linspace(x0, x1, Nx)
y = npy.linspace(y0, y1, Ny)
return npy.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 + (npy.arange(Nx) + 0.5) * dx
y = y0 + (npy.arange(Ny) + 0.5) * dy
if self.origin == 'upper':
y = y[::-1]
return npy.meshgrid(x,y)
def _check_xyz(self, args):
'''
For functions like contour, check that the dimensions
of the input arrays match; if x and y are 1D, convert
them to 2D using meshgrid.
Possible change: I think we should make and use an ArgumentError
Exception class (here and elsewhere).
'''
x = npy.asarray(args[0], dtype=npy.float64)
y = npy.asarray(args[1], dtype=npy.float64)
z = ma.asarray(args[2], dtype=npy.float64)
if z.ndim != 2:
raise TypeError("Input z must be a 2D array.")
else: Ny, Nx = z.shape
if x.shape == z.shape and y.shape == z.shape:
return x,y,z
if x.ndim != 1 or y.ndim != 1:
raise TypeError("Inputs x and y must be 1D or 2D.")
nx, = x.shape
ny, = y.shape
if nx != Nx or ny != Ny:
raise TypeError("Length of x must be number of columns in z,\n" +
"and length of y must be number of rows.")
x,y = npy.meshgrid(x,y)
return x,y,z
def _contour_args(self, *args):
if self.filled: fn = 'contourf'
else: fn = 'contour'
Nargs = len(args)
if Nargs <= 2:
z = ma.asarray(args[0], dtype=npy.float64)
x, y = self._initialize_x_y(z)
elif Nargs <=4:
x,y,z = self._check_xyz(args[:3])
else:
raise TypeError("Too many arguments to %s; see help(%s)" % (fn,fn))
self.zmax = ma.maximum(z)
self.zmin = ma.minimum(z)
self._auto = False
if self.levels is None:
if Nargs == 1 or Nargs == 3:
lev = self._autolev(z, 7)
else: # 2 or 4 args
level_arg = args[-1]
try:
if type(level_arg) == int:
lev = self._autolev(z, level_arg)
else:
lev = npy.asarray(level_arg).astype(npy.float64)
except:
raise TypeError(
"Last %s arg must give levels; see help(%s)" % (fn,fn))
if self.filled and len(lev) < 2:
raise ValueError("Filled contours require at least 2 levels.")
# Workaround for cntr.c bug wrt masked interior regions:
#if filled:
# z = ma.masked_array(z.filled(-1e38))
# It's not clear this is any better than the original bug.
self.levels = lev
#if self._auto and self.extend in ('both', 'min', 'max'):
# raise TypeError("Auto level selection is inconsistent "
# + "with use of 'extend' kwarg")
self._levels = list(self.levels)
if self.extend in ('both', 'min'):
self._levels.insert(0, min(self.levels[0],self.zmin) - 1)
if self.extend in ('both', 'max'):
self._levels.append(max(self.levels[-1],self.zmax) + 1)
self._levels = npy.asarray(self._levels)
self.vmin = npy.amin(self.levels) # alternative would be self.layers
self.vmax = npy.amax(self.levels)
if self.extend in ('both', 'min'):
self.vmin = 2 * self.levels[0] - self.levels[1]
if self.extend in ('both', 'max'):
self.vmax = 2 * self.levels[-1] - self.levels[-2]
self.layers = self._levels # contour: a line is a thin layer
if self.filled:
self.layers = 0.5 * (self._levels[:-1] + self._levels[1:])
if self.extend in ('both', 'min'):
self.layers[0] = 0.5 * (self.vmin + self._levels[1])
if self.extend in ('both', 'max'):
self.layers[-1] = 0.5 * (self.vmax + self._levels[-2])
return (x, y, z)
def _process_colors(self):
"""
Color argument processing for contouring.
Note that we base the color mapping on the contour levels,
not on the actual range of the Z values. This means we
don't have to worry about bad values in Z, and we always have
the full dynamic range available for the selected levels.
The color is based on the midpoint of the layer, except for
an extended end layers.
"""
self.monochrome = self.cmap.monochrome
if self.colors is not None:
i0, i1 = 0, len(self.layers)
if self.extend in ('both', 'min'):
i0 = -1
if self.extend in ('both', 'max'):
i1 = i1 + 1
self.cvalues = range(i0, i1)
self.set_norm(colors.NoNorm())
else:
self.cvalues = self.layers
if not self.norm.scaled():
self.set_clim(self.vmin, self.vmax)
if self.extend in ('both', 'max', 'min'):
self.norm.clip = False
self.set_array(self.layers)
# self.tcolors are set by the "changed" method
def _process_linewidths(self):
linewidths = self.linewidths
Nlev = len(self.levels)
if linewidths is None:
tlinewidths = [(mpl.rcParams['lines.linewidth'],)] *Nlev
else:
if cbook.iterable(linewidths) and len(linewidths) < Nlev:
linewidths = list(linewidths) * int(npy.ceil(Nlev/len(linewidths)))
elif not cbook.iterable(linewidths) and type(linewidths) in [int, float]:
linewidths = [linewidths] * Nlev
tlinewidths = [(w,) for w in linewidths]
return tlinewidths
def get_alpha(self):
'''For compatibility with artists, return self.alpha'''
return self.alpha
def set_alpha(self, alpha):
'''For compatibility with artists, set self.alpha'''
self.alpha = alpha
self.changed()
contour_doc = """
contour and contourf draw contour lines and filled contours,
respectively. Except as noted, function signatures and return
values are the same for both versions.
contourf differs from the Matlab (TM) version in that it does not
draw the polygon edges, because the contouring engine yields
simply connected regions with branch cuts. To draw the edges,
add line contours with calls to contour.
Function signatures
contour(Z) - make a contour plot of an array Z. The level
values are chosen automatically.
contour(X,Y,Z) - X,Y specify the (x,y) coordinates of the surface
contour(Z,N) and contour(X,Y,Z,N) - contour N automatically-chosen
levels.
contour(Z,V) and contour(X,Y,Z,V) - draw len(V) contour lines,
at the values specified in sequence V
contourf(..., V) - fill the (len(V)-1) regions between the
values in V
contour(Z, **kwargs) - Use keyword args to control colors, linewidth,
origin, cmap ... see below
X, Y, and Z must be arrays with the same dimensions.
Z may be a masked array, but filled contouring may not handle
internal masked regions correctly.
C = contour(...) returns a ContourSet object.
Optional keyword args are shown with their defaults below (you must
use kwargs for these):
* colors = None; or one of the following:
- a tuple of matplotlib color args (string, float, rgb, etc),
different levels will be plotted in different colors in the order
specified
- one string color, e.g. colors = 'r' or colors = 'red', all levels
will be plotted in this color
- if colors == None, the colormap specified by cmap will be used
* alpha=1.0 : the alpha blending value
* cmap = None: a cm Colormap instance from matplotlib.cm.
- if cmap == None and colors == None, a default Colormap is used.
* norm = None: a matplotlib.colors.Normalize instance for
scaling data values to colors.
- if norm == None, and colors == None, the default
linear scaling is used.
* origin = None: 'upper'|'lower'|'image'|None.
If 'image', the rc value for image.origin will be used.
If None (default), the first value of Z will correspond
to the lower left corner, location (0,0).
This keyword is active only if contourf is called with
one or two arguments, that is, without explicitly
specifying X and Y.
* extent = None: (x0,x1,y0,y1); also active only if X and Y
are not specified. If origin is not None, then extent is
interpreted as in imshow: it gives the outer pixel boundaries.
In this case, the position of Z[0,0] is the center of the
pixel, not a corner.
If origin is None, then (x0,y0) is the position of Z[0,0],
and (x1,y1) is the position of Z[-1,-1].
* locator = None: an instance of a ticker.Locator subclass;
default is MaxNLocator. It is used to determine the
contour levels if they are not given explicitly via the
V argument.
* extend = 'neither', 'both', 'min', 'max'
Unless this is 'neither' (default), contour levels are
automatically added to one or both ends of the range so that
all data are included. These added ranges are then
mapped to the special colormap values which default to
the ends of the colormap range, but can be set via
Colormap.set_under() and Colormap.set_over() methods.
****************
contour only:
* linewidths = None: or one of these:
- a number - all levels will be plotted with this linewidth,
e.g. linewidths = 0.6
- a tuple of numbers, e.g. linewidths = (0.4, 0.8, 1.2) different
levels will be plotted with different linewidths in the order
specified
- if linewidths == None, the default width in lines.linewidth in
matplotlibrc is used
contourf only:
* antialiased = True (default) or False
* nchunk = 0 (default) for no subdivision of the domain;
specify a positive integer to divide the domain into
subdomains of roughly nchunk by nchunk points. This may
never actually be advantageous, so this option may be
removed. Chunking introduces artifacts at the chunk
boundaries unless antialiased = False
"""
