"""

These are classes to support contour plotting and

labelling for the axes class

"""

from __future__ import (absolute_import, division, print_function,

unicode_literals)

import six

from six.moves import xrange

import warnings

import matplotlib as mpl

import numpy as np

from numpy import ma

import matplotlib._cntr as _cntr

import matplotlib.path as mpath

import matplotlib.ticker as ticker

import matplotlib.cm as cm

import matplotlib.colors as colors

import matplotlib.collections as mcoll

import matplotlib.font_manager as font_manager

import matplotlib.text as text

import matplotlib.cbook as cbook

import matplotlib.mlab as mlab

import matplotlib.mathtext as mathtext

import matplotlib.patches as mpatches

import matplotlib.texmanager as texmanager

import matplotlib.transforms as mtrans

# Import needed for adding manual selection capability to clabel

from matplotlib.blocking_input import BlockingContourLabeler

# 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 ClabelText(text.Text):

"""

Unlike the ordinary text, the get_rotation returns an updated

angle in the pixel coordinate assuming that the input rotation is

an angle in data coordinate (or whatever transform set).

"""

def get_rotation(self):

angle = text.Text.get_rotation(self)

trans = self.get_transform()

x, y = self.get_position()

new_angles = trans.transform_angles(np.array([angle]),

np.array([[x, y]]))

return new_angles[0]

class ContourLabeler:

"""Mixin to provide labelling capability to ContourSet"""

def clabel(self, *args, **kwargs):

"""

Label a contour plot.

Call signature::

clabel(cs, **kwargs)

Adds labels to line contours in *cs*, where *cs* is a

:class:`~matplotlib.contour.ContourSet` object returned by

contour.

::

clabel(cs, v, **kwargs)

only labels contours listed in *v*.

Optional keyword arguments:

*fontsize*:

size in points or relative size eg 'smaller', 'x-large'

*colors*:

- if *None*, the color of each label matches the color of

the corresponding contour

- if one string color, e.g., *colors* = 'r' or *colors* =

'red', all labels will be plotted in this color

- if a tuple of matplotlib color args (string, float, rgb, etc),

different labels will be plotted in different colors in the order

specified

*inline*:

controls whether the underlying contour is removed or

not. Default is *True*.

*inline_spacing*:

space in pixels to leave on each side of label when

placing inline. Defaults to 5. This spacing will be

exact for labels at locations where the contour is

straight, less so for labels on curved contours.

*fmt*:

a format string for the label. Default is '%1.3f'

Alternatively, this can be a dictionary matching contour

levels with arbitrary strings to use for each contour level

(i.e., fmt[level]=string), or it can be any callable, such

as a :class:`~matplotlib.ticker.Formatter` instance, that

returns a string when called with a numeric contour level.

*manual*:

if *True*, contour labels will be placed manually using

mouse clicks. Click the first button near a contour to

add a label, click the second button (or potentially both

mouse buttons at once) to finish adding labels. The third

button can be used to remove the last label added, but

only if labels are not inline. Alternatively, the keyboard

can be used to select label locations (enter to end label

placement, delete or backspace act like the third mouse button,

and any other key will select a label location).

*manual* can be an iterable object of x,y tuples. Contour labels

will be created as if mouse is clicked at each x,y positions.

*rightside_up*:

if *True* (default), label rotations will always be plus

or minus 90 degrees from level.

*use_clabeltext*:

if *True* (default is False), ClabelText class (instead of

matplotlib.Text) is used to create labels. ClabelText

recalculates rotation angles of texts during the drawing time,

therefore this can be used if aspect of the axes changes.

.. plot:: mpl_examples/pylab_examples/contour_demo.py

"""

"""

NOTES on how this all works:

clabel basically takes the input arguments and uses them to

add a list of "label specific" attributes to the ContourSet

object. These attributes are all of the form label* and names

should be fairly self explanatory.

Once these attributes are set, clabel passes control to the

labels method (case of automatic label placement) or

BlockingContourLabeler (case of manual label placement).

"""

fontsize = kwargs.get('fontsize', None)

inline = kwargs.get('inline', 1)

inline_spacing = kwargs.get('inline_spacing', 5)

self.labelFmt = kwargs.get('fmt', '%1.3f')

_colors = kwargs.get('colors', None)

self._use_clabeltext = kwargs.get('use_clabeltext', False)

# Detect if manual selection is desired and remove from argument list

self.labelManual = kwargs.get('manual', False)

self.rightside_up = kwargs.get('rightside_up', True)

if len(args) == 0:

levels = self.levels

indices = list(xrange(len(self.cvalues)))

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.labelLevelList = levels

self.labelIndiceList = indices

self.labelFontProps = font_manager.FontProperties()

if fontsize is None:

font_size = int(self.labelFontProps.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.labelFontProps.get_size_in_points())

else:

self.labelFontProps.set_size(fontsize)

font_size = fontsize

self.labelFontSizeList = [font_size] * len(levels)

if _colors is None:

self.labelMappable = self

self.labelCValueList = np.take(self.cvalues, self.labelIndiceList)

else:

cmap = colors.ListedColormap(_colors, N=len(self.labelLevelList))

self.labelCValueList = list(xrange(len(self.labelLevelList)))

self.labelMappable = cm.ScalarMappable(cmap=cmap,

norm=colors.NoNorm())

#self.labelTexts = [] # Initialized in ContourSet.__init__

#self.labelCValues = [] # same

self.labelXYs = []

if cbook.iterable(self.labelManual):

for x, y in self.labelManual:

self.add_label_near(x, y, inline,

inline_spacing)

elif self.labelManual:

print('Select label locations manually using first mouse button.')

print('End manual selection with second mouse button.')

if not inline:

print('Remove last label by clicking third mouse button.')

blocking_contour_labeler = BlockingContourLabeler(self)

blocking_contour_labeler(inline, inline_spacing)

else:

self.labels(inline, inline_spacing)

# Hold on to some old attribute names. These are deprecated and will

# be removed in the near future (sometime after 2008-08-01), but

# keeping for now for backwards compatibility

self.cl = self.labelTexts

self.cl_xy = self.labelXYs

self.cl_cvalues = self.labelCValues

self.labelTextsList = cbook.silent_list('text.Text', self.labelTexts)

return self.labelTextsList

def print_label(self, linecontour, labelwidth):

"Return *False* if contours are too short for a label."

lcsize = len(linecontour)

if lcsize > 10 * labelwidth:

return True

xmax = np.amax(linecontour[:, 0])

xmin = np.amin(linecontour[:, 0])

ymax = np.amax(linecontour[:, 1])

ymin = np.amin(linecontour[:, 1])

lw = labelwidth

if (xmax - xmin) > 1.2 * lw or (ymax - ymin) > 1.2 * lw:

return True

else:

return False

def too_close(self, x, y, lw):

"Return *True* if a label is already near this location."

for loc in self.labelXYs:

d = np.sqrt((x - loc[0]) ** 2 + (y - loc[1]) ** 2)

if d < 1.2 * lw:

return True

return False

def get_label_coords(self, distances, XX, YY, ysize, lw):

"""

Return x, y, and the index of a label location.

Labels are plotted at a location with the smallest

deviation of the contour from a straight line

unless there is another label nearby, in which case

the next best place on the contour is picked up.

If all such candidates are rejected, the beginning

of the contour is chosen.

"""

hysize = int(ysize / 2)

adist = np.argsort(distances)

for ind in adist:

x, y = XX[ind][hysize], YY[ind][hysize]

if self.too_close(x, y, lw):

continue

return x, y, ind

ind = adist[0]

x, y = XX[ind][hysize], YY[ind][hysize]

return x, y, ind

def get_label_width(self, lev, fmt, fsize):

"""

Return the width of the label in points.

"""

if not cbook.is_string_like(lev):

lev = self.get_text(lev, fmt)

lev, ismath = text.Text.is_math_text(lev)

if ismath == 'TeX':

if not hasattr(self, '_TeX_manager'):

self._TeX_manager = texmanager.TexManager()

lw, _, _ = self._TeX_manager.get_text_width_height_descent(lev,

fsize)

elif ismath:

if not hasattr(self, '_mathtext_parser'):

self._mathtext_parser = mathtext.MathTextParser('bitmap')

img, _ = self._mathtext_parser.parse(lev, dpi=72,

prop=self.labelFontProps)

lw = img.get_width() # at dpi=72, the units are PostScript points

else:

# width is much less than "font size"

lw = (len(lev)) * fsize * 0.6

return lw

def get_real_label_width(self, lev, fmt, fsize):

"""

This computes actual onscreen label width.

This uses some black magic to determine onscreen extent of non-drawn

label. This magic may not be very robust.

This method is not being used, and may be modified or removed.

"""

# Find middle of axes

xx = np.mean(np.asarray(self.ax.axis()).reshape(2, 2), axis=1)

# Temporarily create text object

t = text.Text(xx[0], xx[1])

self.set_label_props(t, self.get_text(lev, fmt), 'k')

# Some black magic to get onscreen extent

# NOTE: This will only work for already drawn figures, as the canvas

# does not have a renderer otherwise. This is the reason this function

# can't be integrated into the rest of the code.

bbox = t.get_window_extent(renderer=self.ax.figure.canvas.renderer)

# difference in pixel extent of image

lw = np.diff(bbox.corners()[0::2, 0])[0]

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.labelFontProps)

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:

if isinstance(fmt, dict):

return fmt[lev]

elif six.callable(fmt):

return fmt(lev)

else:

return fmt % lev

def locate_label(self, linecontour, labelwidth):

"""

Find a good place to plot a label (relatively flat

part of the contour).

"""

nsize = len(linecontour)

if labelwidth > 1:

xsize = int(np.ceil(nsize / labelwidth))

else:

xsize = 1

if xsize == 1:

ysize = nsize

else:

ysize = int(labelwidth)

XX = np.resize(linecontour[:, 0], (xsize, ysize))

YY = np.resize(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 = np.sqrt((xlast - xfirst) ** 2 + (ylast - yfirst) ** 2).ravel()

dist = np.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

# 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, dind

def calc_label_rot_and_inline(self, slc, ind, lw, lc=None, spacing=5):

"""

This function calculates the appropriate label rotation given

the linecontour coordinates in screen units, the index of the

label location and the label width.

It will also break contour and calculate inlining if *lc* is

not empty (lc defaults to the empty list if None). *spacing*

is the space around the label in pixels to leave empty.

Do both of these tasks at once to avoid calling mlab.path_length

multiple times, which is relatively costly.

The method used here involves calculating the path length

along the contour in pixel coordinates and then looking

approximately label width / 2 away from central point to

determine rotation and then to break contour if desired.

"""

if lc is None:

lc = []

# Half the label width

hlw = lw / 2.0

# Check if closed and, if so, rotate contour so label is at edge

closed = mlab.is_closed_polygon(slc)

if closed:

slc = np.r_[slc[ind:-1], slc[:ind + 1]]

if len(lc): # Rotate lc also if not empty

lc = np.r_[lc[ind:-1], lc[:ind + 1]]

ind = 0

# Path length in pixel space

pl = mlab.path_length(slc)

pl = pl - pl[ind]

# Use linear interpolation to get points around label

xi = np.array([-hlw, hlw])

if closed: # Look at end also for closed contours

dp = np.array([pl[-1], 0])

else:

dp = np.zeros_like(xi)

ll = mlab.less_simple_linear_interpolation(pl, slc, dp + xi,

extrap=True)

# get vector in pixel space coordinates from one point to other

dd = np.diff(ll, axis=0).ravel()

# Get angle of vector - must be calculated in pixel space for

# text rotation to work correctly

if np.all(dd == 0): # Must deal with case of zero length label

rotation = 0.0

else:

rotation = np.arctan2(dd[1], dd[0]) * 180.0 / np.pi

if self.rightside_up:

# Fix angle so text is never upside-down

if rotation > 90:

rotation = rotation - 180.0

if rotation < -90:

rotation = 180.0 + rotation

# Break contour if desired

nlc = []

if len(lc):

# Expand range by spacing

xi = dp + xi + np.array([-spacing, spacing])

# Get indices near points of interest

I = mlab.less_simple_linear_interpolation(

pl, np.arange(len(pl)), xi, extrap=False)

# If those indices aren't beyond contour edge, find x,y

if (not np.isnan(I[0])) and int(I[0]) != I[0]:

xy1 = mlab.less_simple_linear_interpolation(

pl, lc, [xi[0]])

if (not np.isnan(I[1])) and int(I[1]) != I[1]:

xy2 = mlab.less_simple_linear_interpolation(

pl, lc, [xi[1]])

# Round to integer values but keep as float

# To allow check against nan below

I = [np.floor(I[0]), np.ceil(I[1])]

# Actually break contours

if closed:

# This will remove contour if shorter than label

if np.all(~np.isnan(I)):

nlc.append(np.r_[xy2, lc[int(I[1]):int(I[0]) + 1], xy1])

else:

# These will remove pieces of contour if they have length zero

if not np.isnan(I[0]):

nlc.append(np.r_[lc[:int(I[0]) + 1], xy1])

if not np.isnan(I[1]):

nlc.append(np.r_[xy2, lc[int(I[1]):]])

# The current implementation removes contours completely

# covered by labels. Uncomment line below to keep

# original contour if this is the preferred behavior.

#if not len(nlc): nlc = [ lc ]

return rotation, nlc

def _get_label_text(self, x, y, rotation):

dx, dy = self.ax.transData.inverted().transform_point((x, y))

t = text.Text(dx, dy, rotation=rotation,

horizontalalignment='center',

verticalalignment='center')

return t

def _get_label_clabeltext(self, x, y, rotation):

# x, y, rotation is given in pixel coordinate. Convert them to

# the data coordinate and create a label using ClabelText

# class. This way, the roation of the clabel is along the

# contour line always.

transDataInv = self.ax.transData.inverted()

dx, dy = transDataInv.transform_point((x, y))

drotation = transDataInv.transform_angles(np.array([rotation]),

np.array([[x, y]]))

t = ClabelText(dx, dy, rotation=drotation[0],

horizontalalignment='center',

verticalalignment='center')

return t

def _add_label(self, t, x, y, lev, cvalue):

color = self.labelMappable.to_rgba(cvalue, alpha=self.alpha)

_text = self.get_text(lev, self.labelFmt)

self.set_label_props(t, _text, color)

self.labelTexts.append(t)

self.labelCValues.append(cvalue)

self.labelXYs.append((x, y))

# Add label to plot here - useful for manual mode label selection

self.ax.add_artist(t)

def add_label(self, x, y, rotation, lev, cvalue):

"""

Add contour label using :class:`~matplotlib.text.Text` class.

"""

t = self._get_label_text(x, y, rotation)

self._add_label(t, x, y, lev, cvalue)

def add_label_clabeltext(self, x, y, rotation, lev, cvalue):

"""

Add contour label using :class:`ClabelText` class.

"""

# x, y, rotation is given in pixel coordinate. Convert them to

# the data coordinate and create a label using ClabelText

# class. This way, the roation of the clabel is along the

# contour line always.

t = self._get_label_clabeltext(x, y, rotation)

self._add_label(t, x, y, lev, cvalue)

def add_label_near(self, x, y, inline=True, inline_spacing=5,

transform=None):

"""

Add a label near the point (x, y). If transform is None

(default), (x, y) is in data coordinates; if transform is

False, (x, y) is in display coordinates; otherwise, the

specified transform will be used to translate (x, y) into

display coordinates.

*inline*:

controls whether the underlying contour is removed or

not. Default is *True*.

*inline_spacing*:

space in pixels to leave on each side of label when

placing inline. Defaults to 5. This spacing will be

exact for labels at locations where the contour is

straight, less so for labels on curved contours.

"""

if transform is None:

transform = self.ax.transData

if transform:

x, y = transform.transform_point((x, y))

# find the nearest contour _in screen units_

conmin, segmin, imin, xmin, ymin = self.find_nearest_contour(

x, y, self.labelIndiceList)[:5]

# The calc_label_rot_and_inline routine requires that (xmin,ymin)

# be a vertex in the path. So, if it isn't, add a vertex here

# grab the paths from the collections

paths = self.collections[conmin].get_paths()

# grab the correct segment

active_path = paths[segmin]

# grab it's verticies

lc = active_path.vertices

# sort out where the new vertex should be added data-units

xcmin = self.ax.transData.inverted().transform_point([xmin, ymin])

# if there isn't a vertex close enough

if not np.allclose(xcmin, lc[imin]):

# insert new data into the vertex list

lc = np.r_[lc[:imin], np.array(xcmin)[None, :], lc[imin:]]

# replace the path with the new one

paths[segmin] = mpath.Path(lc)

# Get index of nearest level in subset of levels used for labeling

lmin = self.labelIndiceList.index(conmin)

# Coordinates of contour

paths = self.collections[conmin].get_paths()

lc = paths[segmin].vertices

# In pixel/screen space

slc = self.ax.transData.transform(lc)

# Get label width for rotating labels and breaking contours

lw = self.get_label_width(self.labelLevelList[lmin],

self.labelFmt, self.labelFontSizeList[lmin])

# Figure out label rotation.

if inline:

lcarg = lc

else:

lcarg = None

rotation, nlc = self.calc_label_rot_and_inline(

slc, imin, lw, lcarg,

inline_spacing)

self.add_label(xmin, ymin, rotation, self.labelLevelList[lmin],

self.labelCValueList[lmin])

if inline:

# Remove old, not looping over paths so we can do this up front

paths.pop(segmin)

# Add paths if not empty or single point

for n in nlc:

if len(n) > 1:

paths.append(mpath.Path(n))

def pop_label(self, index=-1):

"""Defaults to removing last label, but any index can be supplied"""

self.labelCValues.pop(index)

t = self.labelTexts.pop(index)

t.remove()

def labels(self, inline, inline_spacing):

if self._use_clabeltext:

add_label = self.add_label_clabeltext

else:

add_label = self.add_label

for icon, lev, fsize, cvalue in zip(

self.labelIndiceList, self.labelLevelList,

self.labelFontSizeList, self.labelCValueList):

con = self.collections[icon]

trans = con.get_transform()

lw = self.get_label_width(lev, self.labelFmt, fsize)

lw *= self.ax.figure.dpi / 72.0 # scale to screen coordinates

additions = []

paths = con.get_paths()

for segNum, linepath in enumerate(paths):

lc = linepath.vertices # Line contour

slc0 = trans.transform(lc) # Line contour in screen coords

# For closed polygons, add extra point to avoid division by

# zero in print_label and locate_label. Other than these

# functions, this is not necessary and should probably be

# eventually removed.

if mlab.is_closed_polygon(lc):

slc = np.r_[slc0, slc0[1:2, :]]

else:

slc = slc0

# Check if long enough for a label

if self.print_label(slc, lw):

x, y, ind = self.locate_label(slc, lw)

if inline:

lcarg = lc

else:

lcarg = None

rotation, new = self.calc_label_rot_and_inline(

slc0, ind, lw, lcarg,

inline_spacing)

# Actually add the label

add_label(x, y, rotation, lev, cvalue)

# If inline, add new contours

if inline:

for n in new:

# Add path if not empty or single point

if len(n) > 1:

additions.append(mpath.Path(n))

else: # If not adding label, keep old path

additions.append(linepath)

# After looping over all segments on a contour, remove old

# paths and add new ones if inlining

if inline:

del paths[:]

paths.extend(additions)

def _find_closest_point_on_leg(p1, p2, p0):

"""find closest point to p0 on line segment connecting p1 and p2"""

# handle degenerate case

if np.all(p2 == p1):

d = np.sum((p0 - p1)**2)

return d, p1

d21 = p2 - p1

d01 = p0 - p1

# project on to line segment to find closest point

proj = np.dot(d01, d21) / np.dot(d21, d21)

if proj < 0:

proj = 0

if proj > 1:

proj = 1

pc = p1 + proj * d21

# find squared distance

d = np.sum((pc-p0)**2)

return d, pc

def _find_closest_point_on_path(lc, point):

"""

lc: coordinates of vertices

point: coordinates of test point

"""

# find index of closest vertex for this segment

ds = np.sum((lc - point[None, :])**2, 1)

imin = np.argmin(ds)

dmin = np.inf

xcmin = None

legmin = (None, None)

closed = mlab.is_closed_polygon(lc)

# build list of legs before and after this vertex

legs = []

if imin > 0 or closed:

legs.append(((imin-1) % len(lc), imin))

if imin < len(lc) - 1 or closed:

legs.append((imin, (imin+1) % len(lc)))

for leg in legs:

d, xc = _find_closest_point_on_leg(lc[leg[0]], lc[leg[1]], point)

if d < dmin:

dmin = d

xcmin = xc

legmin = leg

return (dmin, xcmin, legmin)

class ContourSet(cm.ScalarMappable, ContourLabeler):

"""

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 :meth:`_process_colors`.

"""

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 three arguments must be:

*ax*: axes object.

*levels*: [level0, level1, ..., leveln]

A list of floating point numbers indicating the contour

levels.

*allsegs*: [level0segs, level1segs, ...]

List of all the polygon segments for all the *levels*.

For contour lines ``len(allsegs) == len(levels)``, and for

filled contour regions ``len(allsegs) = len(levels)-1``.

level0segs = [polygon0, polygon1, ...]

polygon0 = array_like [[x0,y0], [x1,y1], ...]

*allkinds*: *None* or [level0kinds, level1kinds, ...]

Optional list of all the polygon vertex kinds (code types), as

described and used in Path. This is used to allow multiply-

connected paths such as holes within filled polygons.

If not *None*, len(allkinds) == len(allsegs).

level0kinds = [polygon0kinds, ...]

polygon0kinds = [vertexcode0, vertexcode1, ...]

If *allkinds* is not *None*, usually all polygons for a particular

contour level are grouped together so that

level0segs = [polygon0] and level0kinds = [polygon0kinds].

Keyword arguments are as described in

:class:`~matplotlib.contour.QuadContourSet` object.

**Examples:**

.. plot:: mpl_examples/misc/contour_manual.py

"""

self.ax = ax

self.levels = kwargs.get('levels', None)

self.filled = kwargs.get('filled', False)

self.linewidths = kwargs.get('linewidths', None)

self.linestyles = kwargs.get('linestyles', None)

self.hatches = kwargs.get('hatches', [None])

self.alpha = kwargs.get('alpha', None)

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)

vmin = kwargs.get('vmin', None)

vmax = kwargs.get('vmax', None)

self.extend = kwargs.get('extend', 'neither')

self.antialiased = kwargs.get('antialiased', None)

if self.antialiased is None and self.filled:

self.antialiased = False # eliminate artifacts; we are not

# stroking the boundaries.

# The default for line contours will be taken from

# the LineCollection default, which uses the

# rcParams['lines.antialiased']

self.nchunk = kwargs.get('nchunk', 0)

self.locator = kwargs.get('locator', None)

if (isinstance(norm, colors.LogNorm)

or isinstance(self.locator, ticker.LogLocator)):

self.logscale = True

if norm is None:

norm = colors.LogNorm()

if self.extend is not 'neither':

raise ValueError('extend kwarg does not work yet with log '

' scale')

else:

self.logscale = False

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 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']

self._transform = kwargs.get('transform', None)

self._process_args(*args, **kwargs)

self._process_levels()

if self.colors is not None:

ncolors = len(self.levels)

if self.filled:

ncolors -= 1

i0 = 0

# Handle the case where colors are given for the extended

# parts of the contour.

extend_min = self.extend in ['min', 'both']

extend_max = self.extend in ['max', 'both']

use_set_under_over = False

# if we are extending the lower end, and we've been given enough

# colors then skip the first color in the resulting cmap. For the

# extend_max case we don't need to worry about passing more colors

# than ncolors as ListedColormap will clip.

total_levels = ncolors + int(extend_min) + int(extend_max)

if (len(self.colors) == total_levels and

any([extend_min, extend_max])):

use_set_under_over = True

if extend_min:

i0 = 1

cmap = colors.ListedColormap(self.colors[i0:None], N=ncolors)

if use_set_under_over:

if extend_min:

cmap.set_under(self.colors[0])

if extend_max:

cmap.set_over(self.colors[-1])

if self.filled:

self.collections = cbook.silent_list('mcoll.PathCollection')

else:

self.collections = cbook.silent_list('mcoll.LineCollection')

# label lists must be initialized here

self.labelTexts = []

self.labelCValues = []

kw = {'cmap': cmap}

if norm is not None:

kw['norm'] = norm

# sets self.cmap, norm if needed;

cm.ScalarMappable.__init__(self, **kw)

if vmin is not None:

self.norm.vmin = vmin

if vmax is not None:

self.norm.vmax = vmax

self._process_colors()

self.allsegs, self.allkinds = self._get_allsegs_and_allkinds()

if self.filled:

if self.linewidths is not None:

warnings.warn('linewidths is ignored by contourf')

# Lower and upper contour levels.

lowers, uppers = self._get_lowers_and_uppers()

# Ensure allkinds can be zipped below.

if self.allkinds is None:

self.allkinds = [None] * len(self.allsegs)

for level, level_upper, segs, kinds in \

zip(lowers, uppers, self.allsegs, self.allkinds):

paths = self._make_paths(segs, kinds)

# Default zorder taken from Collection

zorder = kwargs.get('zorder', 1)

col = mcoll.PathCollection(

paths,

antialiaseds=(self.antialiased,),

edgecolors='none',

alpha=self.alpha,

transform=self.get_transform(),

zorder=zorder)

self.ax.add_collection(col, autolim=False)

self.collections.append(col)

else:

tlinewidths = self._process_linewidths()

self.tlinewidths = tlinewidths

tlinestyles = self._process_linestyles()

aa = self.antialiased

if aa is not None:

aa = (self.antialiased,)

for level, width, lstyle, segs in \

zip(self.levels, tlinewidths, tlinestyles, self.allsegs):

# Default zorder taken from LineCollection

zorder = kwargs.get('zorder', 2)

col = mcoll.LineCollection(

segs,

antialiaseds=aa,

linewidths=width,

linestyle=[lstyle],

alpha=self.alpha,

transform=self.get_transform(),

zorder=zorder)

col.set_label('_nolegend_')

self.ax.add_collection(col, autolim=False)

self.collections.append(col)

self.changed() # set the colors

def get_transform(self):

"""

Return the :class:`~matplotlib.transforms.Transform`

instance used by this ContourSet.

"""

if self._transform is None:

self._transform = self.ax.transData

elif (not isinstance(self._transform, mtrans.Transform)

and hasattr(self._transform, '_as_mpl_transform')):

self._transform = self._transform._as_mpl_transform(self.ax)

return self._transform

def __getstate__(self):

state = self.__dict__.copy()

# the C object Cntr cannot currently be pickled. This isn't a big issue

# as it is not actually used once the contour has been calculated

state['Cntr'] = None

return state

def legend_elements(self, variable_name='x', str_format=str):

"""

Return a list of artist and labels suitable for passing through

to :func:`plt.legend` which represent this ContourSet.