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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>matplotlib.contour — Matplotlib 3.1.0 documentation</title>

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<h1>Source code for matplotlib.contour</h1><div class="highlight"><pre>

"""

These are classes to support contour plotting and labelling for the Axes class.

"""

from numbers import Integral

import numpy as np

from numpy import ma

import matplotlib as mpl

import matplotlib.path as mpath

import matplotlib.ticker as ticker

import matplotlib.cm as cm

import matplotlib.colors as mcolors

import matplotlib.collections as mcoll

import matplotlib.font_manager as font_manager

import matplotlib.text as text

import matplotlib.cbook as cbook

import matplotlib.mathtext as mathtext

import matplotlib.patches as mpatches

import matplotlib.texmanager as texmanager

import matplotlib.transforms as mtransforms

# 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.

<div class="viewcode-block" id="ClabelText"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ClabelText">[docs]</a>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).

"""

<div class="viewcode-block" id="ClabelText.get_rotation"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ClabelText.get_rotation">[docs]</a> 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]</div></div>

<div class="viewcode-block" id="ContourLabeler"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler">[docs]</a>class ContourLabeler(object):

"""Mixin to provide labelling capability to `.ContourSet`."""

<div class="viewcode-block" id="ContourLabeler.clabel"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.clabel">[docs]</a> def clabel(self, *args,

fontsize=None, inline=True, inline_spacing=5, fmt='%1.3f',

colors=None, use_clabeltext=False, manual=False,

rightside_up=True):

"""

Label a contour plot.

Call signature::

clabel(cs, [levels,] **kwargs)

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

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

``contour()``.

Parameters

----------

cs : `.ContourSet`

The ContourSet to label.

levels : array-like, optional

A list of level values, that should be labeled. The list must be

a subset of ``cs.levels``. If not given, all levels are labeled.

fontsize : string or float, optional

Size in points or relative size e.g., 'smaller', 'x-large'.

See `.Text.set_size` for accepted string values.

colors : color-spec, optional

The label 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 : bool, optional

If ``True`` the underlying contour is removed where the label is

placed. Default is ``True``.

inline_spacing : float, optional

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 : string or dict, optional

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 : bool or iterable, optional

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 also 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 : bool, optional

If ``True``, label rotations will always be plus

or minus 90 degrees from level. Default is ``True``.

use_clabeltext : bool, optional

If ``True``, `.ClabelText` class (instead of `.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. Default is ``False``.

Returns

-------

labels

A list of `.Text` instances for the labels.

"""

"""

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).

"""

self.labelFmt = fmt

self._use_clabeltext = use_clabeltext

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

self.labelManual = manual

self.rightside_up = rightside_up

if len(args) == 0:

levels = self.levels

indices = list(range(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):

raise ValueError("Specified levels {} don't match available "

"levels {}".format(levlabs, self.levels))

else:

raise TypeError("Illegal arguments to clabel, see help(clabel)")

self.labelLevelList = levels

self.labelIndiceList = indices

self.labelFontProps = font_manager.FontProperties()

self.labelFontProps.set_size(fontsize)

font_size_pts = self.labelFontProps.get_size_in_points()

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

if colors is None:

self.labelMappable = self

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

else:

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

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

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

norm=mcolors.NoNorm())

self.labelXYs = []

if np.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)

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

return self.labelTextsList</div>

cl = cbook.deprecated("3.0", alternative="labelTexts")(property(

lambda self: self.labelTexts))

cl_xy = cbook.deprecated("3.0", alternative="labelXYs")(property(

lambda self: self.labelXYs))

cl_cvalues = cbook.deprecated("3.0", alternative="labelCValues")(property(

lambda self: self.labelCValues))

<div class="viewcode-block" id="ContourLabeler.print_label"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.print_label">[docs]</a> def print_label(self, linecontour, labelwidth):

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

return (len(linecontour) > 10 * labelwidth

or (np.ptp(linecontour, axis=0) > 1.2 * labelwidth).any())</div>

<div class="viewcode-block" id="ContourLabeler.too_close"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.too_close">[docs]</a> def too_close(self, x, y, lw):

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

thresh = (1.2 * lw) ** 2

return any((x - loc[0]) ** 2 + (y - loc[1]) ** 2 < thresh

for loc in self.labelXYs)</div>

<div class="viewcode-block" id="ContourLabeler.get_label_coords"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.get_label_coords">[docs]</a> 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]

return x, y, ind</div>

<div class="viewcode-block" id="ContourLabeler.get_label_width"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.get_label_width">[docs]</a> def get_label_width(self, lev, fmt, fsize):

"""

Return the width of the label in points.

"""

if not isinstance(lev, str):

lev = self.get_text(lev, fmt)

lev, ismath = text.Text()._preprocess_math(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:

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</div>

<div class="viewcode-block" id="ContourLabeler.set_label_props"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.set_label_props">[docs]</a> 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)</div>

<div class="viewcode-block" id="ContourLabeler.get_text"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.get_text">[docs]</a> def get_text(self, lev, fmt):

"""Get the text of the label."""

if isinstance(lev, str):

return lev

else:

if isinstance(fmt, dict):

return fmt.get(lev, '%1.3f')

elif callable(fmt):

return fmt(lev)

else:

return fmt % lev</div>

<div class="viewcode-block" id="ContourLabeler.locate_label"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.locate_label">[docs]</a> def locate_label(self, linecontour, labelwidth):

"""

Find good place to draw a label (relatively flat part of the contour).

"""

# Number of contour points

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[:, :1]

ylast = YY[:, -1:]

xfirst = XX[:, :1]

xlast = XX[:, -1:]

s = (yfirst - YY) * (xlast - xfirst) - (xfirst - XX) * (ylast - yfirst)

L = np.hypot(xlast - xfirst, ylast - yfirst)

# Ignore warning that divide by zero throws, as this is a valid option

with np.errstate(divide='ignore', invalid='ignore'):

dist = np.sum(np.abs(s) / L, axis=-1)

x, y, ind = self.get_label_coords(dist, XX, YY, ysize, labelwidth)

# There must be a more efficient way...

lc = [tuple(l) for l in linecontour]

dind = lc.index((x, y))

return x, y, dind</div>

<div class="viewcode-block" id="ContourLabeler.calc_label_rot_and_inline"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.calc_label_rot_and_inline">[docs]</a> 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 calculating path lengths

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 = _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

# Calculate path lengths

pl = np.zeros(slc.shape[0], dtype=float)

dx = np.diff(slc, axis=0)

pl[1:] = np.cumsum(np.hypot(dx[:, 0], dx[:, 1]))

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)

# Get angle of vector between the two ends of the label - must be

# calculated in pixel space for text rotation to work correctly.

(dx,), (dy,) = (np.diff(np.interp(dp + xi, pl, slc_col))

for slc_col in slc.T)

rotation = np.rad2deg(np.arctan2(dy, dx))

if self.rightside_up:

# Fix angle so text is never upside-down

rotation = (rotation + 90) % 180 - 90

# Break contour if desired

nlc = []

if len(lc):

# Expand range by spacing

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

# Get (integer) indices near points of interest; use -1 as marker

# for out of bounds.

I = np.interp(xi, pl, np.arange(len(pl)), left=-1, right=-1)

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

if I[0] != -1:

xy1 = [np.interp(xi[0], pl, lc_col) for lc_col in lc.T]

if I[1] != -1:

xy2 = [np.interp(xi[1], pl, lc_col) for lc_col in lc.T]

# Actually break contours

if closed:

# This will remove contour if shorter than label

if all(i != -1 for i in I):

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

else:

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

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

# 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</div>

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 rotation 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]),

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)

<div class="viewcode-block" id="ContourLabeler.add_label"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.add_label">[docs]</a> 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)</div>

<div class="viewcode-block" id="ContourLabeler.add_label_clabeltext"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.add_label_clabeltext">[docs]</a> 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 rotation of the clabel is along the

# contour line always.

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

<div class="viewcode-block" id="ContourLabeler.add_label_near"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.add_label_near">[docs]</a> 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.

Parameters

----------

x, y : float

The approximate location of the label.

inline : bool, optional, default: True

If *True* remove the segment of the contour beneath the label.

inline_spacing : int, optional, default: 5

Space in pixels to leave on each side of label when placing

inline. 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 its vertices

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

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])

# lw is in points.

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

# now lw in pixels

# 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))</div>

<div class="viewcode-block" id="ContourLabeler.pop_label"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.pop_label">[docs]</a> 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()</div>

<div class="viewcode-block" id="ContourLabeler.labels"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourLabeler.labels">[docs]</a> 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)

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 _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):

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

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)</div></div>

def _find_closest_point_on_leg(p1, p2, p0):

"""Find the 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 _is_closed_polygon(X):

"""

Return whether first and last object in a sequence are the same. These are

presumably coordinates on a polygonal curve, in which case this function

tests if that curve is closed.

"""

return np.all(X[0] == X[-1])

def _find_closest_point_on_path(lc, point):

"""

Parameters

----------

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 = _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)

<div class="viewcode-block" id="ContourSet"><a class="viewcode-back" href="../../api/contour_api.html#matplotlib.contour.ContourSet">[docs]</a>class ContourSet(cm.ScalarMappable, ContourLabeler):

"""

Store a set of contour lines or filled regions.

User-callable method: `~.axes.Axes.clabel`

Parameters

----------

ax : `~.axes.Axes`

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``. The lists

should look like::

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)``. The lists

should look like::

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]``.

**kwargs

Keyword arguments are as described in the docstring of

`~.axes.Axes.contour`.

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,

levels=None, filled=False, linewidths=None, linestyles=None,

alpha=None, origin=None, extent=None,

cmap=None, colors=None, norm=None, vmin=None, vmax=None,

extend='neither', antialiased=None,

**kwargs):

"""

Draw contour lines or filled regions, depending on

whether keyword arg *filled* is ``False`` (default) or ``True``.

Call signature::

ContourSet(ax, levels, allsegs, [allkinds], **kwargs)

Parameters

----------

ax : `~.axes.Axes`

The `~.axes.Axes` object to draw on.

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``. The lists

should look like::

level0segs = [polygon0, polygon1, ...]

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

allkinds : [level0kinds, level1kinds, ...], optional

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)``. The lists

should look like::

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]``.

**kwargs

Keyword arguments are as described in the docstring of

`~axes.Axes.contour`.

"""

self.ax = ax

self.levels = levels

self.filled = filled

self.linewidths = linewidths

self.linestyles = linestyles

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

self.alpha = alpha

self.origin = origin

self.extent = extent

self.colors = colors

self.extend = extend

self.antialiased = antialiased

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 :rc:`lines.antialiased`.

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

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

if (isinstance(norm, mcolors.LogNorm)

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

self.logscale = True

if norm is None:

norm = mcolors.LogNorm()

else:

self.logscale = False

cbook._check_in_list([None, 'lower', 'upper', 'image'], origin=origin)

if self.extent is not None and len(self.extent) != 4:

raise ValueError("If given, *extent* must be '[ *None* |"

" (x0,x1,y0,y1) ]'")

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.pop('transform', None)

kwargs = self._process_args(*args, **kwargs)

self._process_levels()

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 (extend_min or extend_max):

use_set_under_over = True

if extend_min:

i0 = 1

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

if use_set_under_over:

if extend_min:

cmap.set_under(self.colors[0])

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