00001 """ These are classes to support contour plotting and labelling for the axes class """ from __future__ import division from matplotlib import rcParams import numerix.ma as ma from ticker import MaxNLocator from transforms import Interval, Value from numerix import absolute, arange, array, asarray, ones, divide,\ transpose, log, log10, Float, Float32, ravel, zeros, Int16,\ Int32, Int, Float64, ceil, indices, shape, which, where, sqrt,\ asum, resize, reshape, add, argmin, arctan2, pi, argsort, sin,\ cos, nonzero, take, concatenate, all, newaxis from mlab import linspace, meshgrid import _contour from cm import ScalarMappable from cbook import iterable, is_string_like, flatten, enumerate, \ allequal, dict_delall, strip_math, popall, silent_list from colors import colorConverter, Normalize, Colormap, ListedColormap, NoNorm from collections import PolyCollection, LineCollection from font_manager import FontProperties from numerix.mlab import amin, amax from text import Text import warnings # 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. 00037 class ContourLabeler: '''Mixin to provide labelling capability to ContourSet''' 00040 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 = 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 = take(self.cvalues, self.label_indices) else: cmap = ListedColormap(colors, N=len(self.label_levels)) self.label_cvalues = range(len(self.label_levels)) self.label_mappable = ScalarMappable(cmap = cmap, norm = 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 = silent_list('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 = amax(array(linecontour)[:,0]) xmin = amin(array(linecontour)[:,0]) ymax = amax(array(linecontour)[:,1]) ymin = amin(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 = [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 00161 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 = 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 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 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 * sin(rot*pi/180)) xlabel = abs(hlw * cos(rot*pi/180)) trans = self.ax.transData slc = trans.seq_xy_tups(linecontour) x,y = slc[ind] xx= asarray(slc)[:,0].copy() yy=asarray(slc)[:,1].copy() #indices which are under the label inds=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 = 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 new_x1d, new_y1d = trans.inverse_xy_tup((new_x1, new_y1)) new_x2d, new_y2d = trans.inverse_xy_tup((new_x2, new_y2)) new_xy1 = array(((new_x1d, new_y1d),)) new_xy2 = 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 = 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 = 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 = 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 = concatenate((new_xy2, lc2)) #lc2.insert(0, (new_x2d, new_y2d)) return [lc1,lc2] 00289 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(ceil(nsize/labelwidth)) else: xsize = 1 if xsize == 1: ysize = nsize else: ysize = labelwidth XX = resize(asarray(linecontour)[:,0],(xsize, ysize)) YY = resize(asarray(linecontour)[:,1],(xsize,ysize)) yfirst = YY[:,0] ylast = YY[:,-1] xfirst = XX[:,0] xlast = XX[:,-1] s = ( (reshape(yfirst, (xsize,1))-YY) * (reshape(xlast,(xsize,1)) - reshape(xfirst,(xsize,1))) - (reshape(xfirst,(xsize,1))-XX) * (reshape(ylast,(xsize,1)) - reshape(yfirst,(xsize,1))) ) L=sqrt((xlast-xfirst)**2+(ylast-yfirst)**2) dist = 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 = arctan2(ylast - yfirst, xlast - xfirst) rotation = angle[ind]*180/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 = [] for segNum, linecontour in enumerate(con._segments): # for closed contours add one more point to # avoid division by zero if all(linecontour[0] == linecontour[-1]): linecontour = concatenate((linecontour, linecontour[1][newaxis,:])) #linecontour.append(linecontour[1]) # transfer all data points to screen coordinates slc = trans.seq_xy_tups(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.inverse_xy_tup((x,y)) t = 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) con._segments[segNum] = new[0] additions.append(new[1]) con._segments.extend(additions) 00376 class ContourSet(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. """ 00391 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.clip_ends = kwargs.get('clip_ends', None) ######## self.extend = kwargs.get('extend', 'neither') if self.clip_ends is not None: warnings.warn("'clip_ends' has been replaced by 'extend'") self.levels = self.levels[1:-1] # discard specified end levels self.extend = 'both' # regenerate end levels 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, 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 = rcParams['image.origin'] x, y, z = self._contour_args(*args) # also sets self.levels, # self.layers if self.colors is not None: cmap = ListedColormap(self.colors, N=len(self.layers)) if self.filled: self.collections = silent_list('PolyCollection') else: self.collections = silent_list('LineCollection') # label lists must be initialized here self.cl = [] self.cl_cvalues = [] kw = {'cmap': cmap} if norm is not None: kw['norm'] = norm ScalarMappable.__init__(self, **kw) # sets self.cmap; self._process_colors() if self.filled: if self.linewidths is None: self.linewidths = 0.05 # Good default for Postscript. if iterable(self.linewidths): self.linewidths = self.linewidths[0] C = _contour.Cntr(x, y, z.filled(), ma.getmaskorNone(z)) 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 = PolyCollection(nlist, linewidths = (self.linewidths,), antialiaseds = (self.antialiased,), edgecolors= 'None') self.ax.add_collection(col) self.collections.append(col) else: tlinewidths = self._process_linewidths() self.tlinewidths = tlinewidths C = _contour.Cntr(x, y, z.filled(), ma.getmaskorNone(z)) for level, width in zip(self.levels, tlinewidths): nlist = C.trace(level, points = 0) col = LineCollection(nlist, linewidths = width) if level < 0.0 and self.monochrome: col.set_linestyle((0, rcParams['contour.negative_linestyle'])) col.set_label('_nolegend_') self.ax.add_collection(col) 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 ScalarMappable.changed(self) 00500 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 = self.zmax zmin = self.zmin zmargin = (zmax - zmin) * 0.001 # so z < (zmax + zmargin) zmax = zmax + zmargin intv = Interval(Value(zmin), Value(zmax)) if self.locator is None: self.locator = MaxNLocator(N+1) self.locator.set_view_interval(intv) self.locator.set_data_interval(intv) lev = self.locator() self._auto = True if self.filled: return lev return lev[1:-1] 00526 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) 00564 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). Add checking for everything being the same numerix flavor? ''' x,y,z = args if len(shape(z)) != 2: raise TypeError("Input z must be a 2D array.") else: Ny, Nx = shape(z) if shape(x) == shape(z) and shape(y) == shape(z): return x,y,z if len(shape(x)) != 1 or len(shape(y)) != 1: raise TypeError("Inputs x and y must be 1D or 2D.") nx, = shape(x) ny, = shape(y) 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 = 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 = args[0] 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)) z = ma.asarray(z) # Convert to native masked array format if necessary. 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] if type(level_arg) == int: lev = self._autolev(z, level_arg) elif iterable(level_arg) and len(shape(level_arg)) == 1: lev = array([float(fl) for fl in level_arg]) else: 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 = asarray(self._levels) self.vmin = amin(self.levels) # alternative would be self.layers self.vmax = amax(self.levels) if self.extend in ('both', 'min') or self.clip_ends: self.vmin = 2 * self.levels[0] - self.levels[1] if self.extend in ('both', 'max') or self.clip_ends: 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') or self.clip_ends: self.layers[0] = 0.5 * (self.vmin + self._levels[1]) if self.extend in ('both', 'max') or self.clip_ends: self.layers[-1] = 0.5 * (self.vmax + self._levels[-2]) return (x, y, z) 00651 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(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 = [(rcParams['lines.linewidth'],)] *Nlev else: if iterable(linewidths) and len(linewidths) < Nlev: linewidths = list(linewidths) * int(ceil(Nlev/len(linewidths))) elif not iterable(linewidths) and type(linewidths) in [int, float]: linewidths = [linewidths] * Nlev tlinewidths = [(w,) for w in linewidths] return tlinewidths 00694 def get_alpha(self): '''For compatibility with artists, return self.alpha''' return self.alpha 00698 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. ***** New: ***** * 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. To replace clip_ends=True and V = [-100, 2, 1, 0, 1, 2, 100], use extend='both' and V = [2, 1, 0, 1, 2]. **************** 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: ***** Obsolete: **** * clip_ends = True If False, the limits for color scaling are set to the minimum and maximum contour levels. True (default) clips the scaling limits. Example: if the contour boundaries are V = [-100, 2, 1, 0, 1, 2, 100], then the scaling limits will be [-100, 100] if clip_ends is False, and [-3, 3] if clip_ends is True. * linewidths = None or a number; default of 0.05 works for Postscript; a value of about 0.5 seems better for Agg. * antialiased = True (default) or False; if False, there is no need to increase the linewidths for Agg, but True gives nicer color boundaries. If antialiased is True and linewidths is too small, then there may be light-colored lines at the color boundaries caused by the antialiasing. * 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, or linewidths is set to a large enough value for the particular renderer and resolution. """