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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.lines — Matplotlib 3.0.0 documentation</title>

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<div id="unreleased-message"> You are reading an old version of the documentation (v3.0.0). For the latest version see <a href="/stable/">https://matplotlib.org/stable/</a> </div>

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

"""

This module contains all the 2D line class which can draw with a

variety of line styles, markers and colors.

"""

# TODO: expose cap and join style attrs

from numbers import Integral, Number, Real

import warnings

import numpy as np

from . import artist, cbook, colors as mcolors, docstring, rcParams

from .artist import Artist, allow_rasterization

from .cbook import (

_to_unmasked_float_array, iterable, ls_mapper, ls_mapper_r,

STEP_LOOKUP_MAP)

from .markers import MarkerStyle

from .path import Path

from .transforms import Bbox, TransformedPath, IdentityTransform

# Imported here for backward compatibility, even though they don't

# really belong.

from . import _path

from .markers import (

CARETLEFT, CARETRIGHT, CARETUP, CARETDOWN,

CARETLEFTBASE, CARETRIGHTBASE, CARETUPBASE, CARETDOWNBASE,

TICKLEFT, TICKRIGHT, TICKUP, TICKDOWN)

def _get_dash_pattern(style):

"""Convert linestyle -> dash pattern

"""

# go from short hand -> full strings

if isinstance(style, str):

style = ls_mapper.get(style, style)

# un-dashed styles

if style in ['solid', 'None']:

offset, dashes = None, None

# dashed styles

elif style in ['dashed', 'dashdot', 'dotted']:

offset = 0

dashes = tuple(rcParams['lines.{}_pattern'.format(style)])

#

elif isinstance(style, tuple):

offset, dashes = style

else:

raise ValueError('Unrecognized linestyle: %s' % str(style))

# normalize offset to be positive and shorter than the dash cycle

if dashes is not None and offset is not None:

dsum = sum(dashes)

if dsum:

offset %= dsum

return offset, dashes

def _scale_dashes(offset, dashes, lw):

if not rcParams['lines.scale_dashes']:

return offset, dashes

scaled_offset = scaled_dashes = None

if offset is not None:

scaled_offset = offset * lw

if dashes is not None:

scaled_dashes = [x * lw if x is not None else None

for x in dashes]

return scaled_offset, scaled_dashes

<div class="viewcode-block" id="segment_hits"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.segment_hits.html#matplotlib.lines.segment_hits">[docs]</a>def segment_hits(cx, cy, x, y, radius):

"""

Determine if any line segments are within radius of a

point. Returns the list of line segments that are within that

radius.

"""

# Process single points specially

if len(x) < 2:

res, = np.nonzero((cx - x) ** 2 + (cy - y) ** 2 <= radius ** 2)

return res

# We need to lop the last element off a lot.

xr, yr = x[:-1], y[:-1]

# Only look at line segments whose nearest point to C on the line

# lies within the segment.

dx, dy = x[1:] - xr, y[1:] - yr

Lnorm_sq = dx ** 2 + dy ** 2 # Possibly want to eliminate Lnorm==0

u = ((cx - xr) * dx + (cy - yr) * dy) / Lnorm_sq

candidates = (u >= 0) & (u <= 1)

# Note that there is a little area near one side of each point

# which will be near neither segment, and another which will

# be near both, depending on the angle of the lines. The

# following radius test eliminates these ambiguities.

point_hits = (cx - x) ** 2 + (cy - y) ** 2 <= radius ** 2

candidates = candidates & ~(point_hits[:-1] | point_hits[1:])

# For those candidates which remain, determine how far they lie away

# from the line.

px, py = xr + u * dx, yr + u * dy

line_hits = (cx - px) ** 2 + (cy - py) ** 2 <= radius ** 2

line_hits = line_hits & candidates

points, = point_hits.ravel().nonzero()

lines, = line_hits.ravel().nonzero()

return np.concatenate((points, lines))</div>

def _mark_every_path(markevery, tpath, affine, ax_transform):

"""

Helper function that sorts out how to deal the input

`markevery` and returns the points where markers should be drawn.

Takes in the `markevery` value and the line path and returns the

sub-sampled path.

"""

# pull out the two bits of data we want from the path

codes, verts = tpath.codes, tpath.vertices

def _slice_or_none(in_v, slc):

'''

Helper function to cope with `codes` being an

ndarray or `None`

'''

if in_v is None:

return None

return in_v[slc]

# if just an int, assume starting at 0 and make a tuple

if isinstance(markevery, Integral):

markevery = (0, markevery)

# if just a float, assume starting at 0.0 and make a tuple

elif isinstance(markevery, Real):

markevery = (0.0, markevery)

if isinstance(markevery, tuple):

if len(markevery) != 2:

raise ValueError('`markevery` is a tuple but its len is not 2; '

'markevery={}'.format(markevery))

start, step = markevery

# if step is an int, old behavior

if isinstance(step, Integral):

# tuple of 2 int is for backwards compatibility,

if not isinstance(start, Integral):

raise ValueError(

'`markevery` is a tuple with len 2 and second element is '

'an int, but the first element is not an int; markevery={}'

.format(markevery))

# just return, we are done here

return Path(verts[slice(start, None, step)],

_slice_or_none(codes, slice(start, None, step)))

elif isinstance(step, Real):

raise ValueError(

'`markevery` is a tuple with len 2 and second element is '

'a float, but the first element is not a float or an int; '

# calc cumulative distance along path (in display coords):

disp_coords = affine.transform(tpath.vertices)

delta = np.empty((len(disp_coords), 2))

delta[0, :] = 0

delta[1:, :] = disp_coords[1:, :] - disp_coords[:-1, :]

delta = np.sum(delta**2, axis=1)

delta = np.sqrt(delta)

delta = np.cumsum(delta)

# calc distance between markers along path based on the axes

# bounding box diagonal being a distance of unity:

scale = ax_transform.transform(np.array([[0, 0], [1, 1]]))

scale = np.diff(scale, axis=0)

scale = np.sum(scale**2)

scale = np.sqrt(scale)

marker_delta = np.arange(start * scale, delta[-1], step * scale)

# find closest actual data point that is closest to

# the theoretical distance along the path:

inds = np.abs(delta[np.newaxis, :] - marker_delta[:, np.newaxis])

inds = inds.argmin(axis=1)

inds = np.unique(inds)

# return, we are done here

return Path(verts[inds],

_slice_or_none(codes, inds))

else:

raise ValueError(

'`markevery` is a tuple with len 2, but its second element is '

'not an int or a float; markevery=%s' % (markevery,))

elif isinstance(markevery, slice):

# mazol tov, it's already a slice, just return

return Path(verts[markevery], _slice_or_none(codes, markevery))

elif iterable(markevery):

#fancy indexing

try:

except (ValueError, IndexError):

raise ValueError('`markevery` is iterable but '

'not a valid form of numpy fancy indexing; '

'markevery=%s' % (markevery,))

else:

raise ValueError('Value of `markevery` is not '

'recognized; '

'markevery=%s' % (markevery,))

<div class="viewcode-block" id="Line2D"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D">[docs]</a>@cbook._define_aliases({

"antialiased": ["aa"],

"color": ["c"],

"linestyle": ["ls"],

"linewidth": ["lw"],

"markeredgecolor": ["mec"],

"markeredgewidth": ["mew"],

"markerfacecolor": ["mfc"],

"markerfacecoloralt": ["mfcalt"],

"markersize": ["ms"],

})

class Line2D(Artist):

"""

A line - the line can have both a solid linestyle connecting all

the vertices, and a marker at each vertex. Additionally, the

drawing of the solid line is influenced by the drawstyle, e.g., one

can create "stepped" lines in various styles.

"""

lineStyles = _lineStyles = { # hidden names deprecated

'-': '_draw_solid',

'--': '_draw_dashed',

'-.': '_draw_dash_dot',

':': '_draw_dotted',

'None': '_draw_nothing',

' ': '_draw_nothing',

'': '_draw_nothing',

}

_drawStyles_l = {

'default': '_draw_lines',

'steps-mid': '_draw_steps_mid',

'steps-pre': '_draw_steps_pre',

'steps-post': '_draw_steps_post',

}

_drawStyles_s = {

'steps': '_draw_steps_pre',

}

# drawStyles should now be deprecated.

drawStyles = {**_drawStyles_l, **_drawStyles_s}

# Need a list ordered with long names first:

drawStyleKeys = [*_drawStyles_l, *_drawStyles_s]

# Referenced here to maintain API. These are defined in

# MarkerStyle

markers = MarkerStyle.markers

filled_markers = MarkerStyle.filled_markers

fillStyles = MarkerStyle.fillstyles

zorder = 2

validCap = ('butt', 'round', 'projecting')

validJoin = ('miter', 'round', 'bevel')

def __str__(self):

if self._label != "":

return "Line2D(%s)" % (self._label)

elif self._x is None:

return "Line2D()"

elif len(self._x) > 3:

return "Line2D((%g,%g),(%g,%g),...,(%g,%g))"\

% (self._x[0], self._y[0], self._x[0],

self._y[0], self._x[-1], self._y[-1])

else:

return "Line2D(%s)"\

% (",".join(["(%g,%g)" % (x, y) for x, y

in zip(self._x, self._y)]))

def __init__(self, xdata, ydata,

linewidth=None, # all Nones default to rc

linestyle=None,

color=None,

marker=None,

markersize=None,

markeredgewidth=None,

markeredgecolor=None,

markerfacecolor=None,

markerfacecoloralt='none',

fillstyle=None,

antialiased=None,

dash_capstyle=None,

solid_capstyle=None,

dash_joinstyle=None,

solid_joinstyle=None,

pickradius=5,

drawstyle=None,

markevery=None,

**kwargs

):

"""

Create a :class:`~matplotlib.lines.Line2D` instance with *x*

and *y* data in sequences *xdata*, *ydata*.

The kwargs are :class:`~matplotlib.lines.Line2D` properties:

%(Line2D)s

See :meth:`set_linestyle` for a description of the line styles,

:meth:`set_marker` for a description of the markers, and

:meth:`set_drawstyle` for a description of the draw styles.

"""

Artist.__init__(self)

#convert sequences to numpy arrays

if not iterable(xdata):

raise RuntimeError('xdata must be a sequence')

if not iterable(ydata):

raise RuntimeError('ydata must be a sequence')

if linewidth is None:

linewidth = rcParams['lines.linewidth']

if linestyle is None:

linestyle = rcParams['lines.linestyle']

if marker is None:

marker = rcParams['lines.marker']

if markerfacecolor is None:

markerfacecolor = rcParams['lines.markerfacecolor']

if markeredgecolor is None:

markeredgecolor = rcParams['lines.markeredgecolor']

if color is None:

color = rcParams['lines.color']

if markersize is None:

markersize = rcParams['lines.markersize']

if antialiased is None:

antialiased = rcParams['lines.antialiased']

if dash_capstyle is None:

dash_capstyle = rcParams['lines.dash_capstyle']

if dash_joinstyle is None:

dash_joinstyle = rcParams['lines.dash_joinstyle']

if solid_capstyle is None:

solid_capstyle = rcParams['lines.solid_capstyle']

if solid_joinstyle is None:

solid_joinstyle = rcParams['lines.solid_joinstyle']

if isinstance(linestyle, str):

ds, ls = self._split_drawstyle_linestyle(linestyle)

if ds is not None and drawstyle is not None and ds != drawstyle:

raise ValueError("Inconsistent drawstyle ({!r}) and linestyle "

"({!r})".format(drawstyle, linestyle))

linestyle = ls

if ds is not None:

drawstyle = ds

if drawstyle is None:

drawstyle = 'default'

self._dashcapstyle = None

self._dashjoinstyle = None

self._solidjoinstyle = None

self._solidcapstyle = None

self.set_dash_capstyle(dash_capstyle)

self.set_dash_joinstyle(dash_joinstyle)

self.set_solid_capstyle(solid_capstyle)

self.set_solid_joinstyle(solid_joinstyle)

self._linestyles = None

self._drawstyle = None

self._linewidth = linewidth

# scaled dash + offset

self._dashSeq = None

self._dashOffset = 0

# unscaled dash + offset

# this is needed scaling the dash pattern by linewidth

self._us_dashSeq = None

self._us_dashOffset = 0

self.set_linewidth(linewidth)

self.set_linestyle(linestyle)

self.set_drawstyle(drawstyle)

self._color = None

self.set_color(color)

self._marker = MarkerStyle(marker, fillstyle)

self._markevery = None

self._markersize = None

self._antialiased = None

self.set_markevery(markevery)

self.set_antialiased(antialiased)

self.set_markersize(markersize)

self._markeredgecolor = None

self._markeredgewidth = None

self._markerfacecolor = None

self._markerfacecoloralt = None

self.set_markerfacecolor(markerfacecolor)

self.set_markerfacecoloralt(markerfacecoloralt)

self.set_markeredgecolor(markeredgecolor)

self.set_markeredgewidth(markeredgewidth)

self.verticalOffset = None

# update kwargs before updating data to give the caller a

# chance to init axes (and hence unit support)

self.update(kwargs)

self.pickradius = pickradius

self.ind_offset = 0

if isinstance(self._picker, Number):

self.pickradius = self._picker

self._xorig = np.asarray([])

self._yorig = np.asarray([])

self._invalidx = True

self._invalidy = True

self._x = None

self._y = None

self._xy = None

self._path = None

self._transformed_path = None

self._subslice = False

self._x_filled = None # used in subslicing; only x is needed

self.set_data(xdata, ydata)

<div class="viewcode-block" id="Line2D.contains"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.contains">[docs]</a> def contains(self, mouseevent):

"""

Test whether the mouse event occurred on the line. The pick

radius determines the precision of the location test (usually

within five points of the value). Use

:meth:`~matplotlib.lines.Line2D.get_pickradius` or

:meth:`~matplotlib.lines.Line2D.set_pickradius` to view or

modify it.

Returns *True* if any values are within the radius along with

``{'ind': pointlist}``, where *pointlist* is the set of points

within the radius.

TODO: sort returned indices by distance

"""

if callable(self._contains):

return self._contains(self, mouseevent)

if not isinstance(self.pickradius, Number):

raise ValueError("pick radius should be a distance")

# Make sure we have data to plot

if self._invalidy or self._invalidx:

self.recache()

if len(self._xy) == 0:

return False, {}

# Convert points to pixels

transformed_path = self._get_transformed_path()

path, affine = transformed_path.get_transformed_path_and_affine()

path = affine.transform_path(path)

xy = path.vertices

xt = xy[:, 0]

yt = xy[:, 1]

# Convert pick radius from points to pixels

if self.figure is None:

warnings.warn('no figure set when check if mouse is on line')

pixels = self.pickradius

else:

pixels = self.figure.dpi / 72. * self.pickradius

# the math involved in checking for containment (here and inside of

# segment_hits) assumes that it is OK to overflow. In case the

# application has set the error flags such that an exception is raised

# on overflow, we temporarily set the appropriate error flags here and

# set them back when we are finished.

with np.errstate(all='ignore'):

# Check for collision

if self._linestyle in ['None', None]:

# If no line, return the nearby point(s)

d = (xt - mouseevent.x) ** 2 + (yt - mouseevent.y) ** 2

ind, = np.nonzero(np.less_equal(d, pixels ** 2))

else:

# If line, return the nearby segment(s)

ind = segment_hits(mouseevent.x, mouseevent.y, xt, yt, pixels)

if self._drawstyle.startswith("steps"):

ind //= 2

ind += self.ind_offset

# Return the point(s) within radius

return len(ind) > 0, dict(ind=ind)</div>

<div class="viewcode-block" id="Line2D.get_pickradius"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_pickradius">[docs]</a> def get_pickradius(self):

"""return the pick radius used for containment tests"""

return self.pickradius</div>

<div class="viewcode-block" id="Line2D.set_pickradius"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_pickradius">[docs]</a> def set_pickradius(self, d):

"""Set the pick radius used for containment tests.

Parameters

----------

d : float

Pick radius, in points.

"""

self.pickradius = d</div>

<div class="viewcode-block" id="Line2D.get_fillstyle"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_fillstyle">[docs]</a> def get_fillstyle(self):

"""

return the marker fillstyle

"""

return self._marker.get_fillstyle()</div>

<div class="viewcode-block" id="Line2D.set_fillstyle"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_fillstyle">[docs]</a> def set_fillstyle(self, fs):

"""

Set the marker fill style; 'full' means fill the whole marker.

'none' means no filling; other options are for half-filled markers.

Parameters

----------

fs : {'full', 'left', 'right', 'bottom', 'top', 'none'}

"""

self._marker.set_fillstyle(fs)

self.stale = True</div>

<div class="viewcode-block" id="Line2D.set_markevery"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_markevery">[docs]</a> def set_markevery(self, every):

"""Set the markevery property to subsample the plot when using markers.

e.g., if `every=5`, every 5-th marker will be plotted.

Parameters

----------

every: None or int or (int, int) or slice or List[int] or float or \

(float, float)

Which markers to plot.

- every=None, every point will be plotted.

- every=N, every N-th marker will be plotted starting with

marker 0.

- every=(start, N), every N-th marker, starting at point

start, will be plotted.

- every=slice(start, end, N), every N-th marker, starting at

point start, up to but not including point end, will be plotted.

- every=[i, j, m, n], only markers at points i, j, m, and n

will be plotted.

- every=0.1, (i.e. a float) then markers will be spaced at

approximately equal distances along the line; the distance

along the line between markers is determined by multiplying the

display-coordinate distance of the axes bounding-box diagonal

by the value of every.

- every=(0.5, 0.1) (i.e. a length-2 tuple of float), the

same functionality as every=0.1 is exhibited but the first

marker will be 0.5 multiplied by the

display-cordinate-diagonal-distance along the line.

Notes

-----

Setting the markevery property will only show markers at actual data

points. When using float arguments to set the markevery property

on irregularly spaced data, the markers will likely not appear evenly

spaced because the actual data points do not coincide with the

theoretical spacing between markers.

When using a start offset to specify the first marker, the offset will

be from the first data point which may be different from the first

the visible data point if the plot is zoomed in.

If zooming in on a plot when using float arguments then the actual

data points that have markers will change because the distance between

markers is always determined from the display-coordinates

axes-bounding-box-diagonal regardless of the actual axes data limits.

"""

if self._markevery != every:

self.stale = True

self._markevery = every</div>

<div class="viewcode-block" id="Line2D.get_markevery"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_markevery">[docs]</a> def get_markevery(self):

"""return the markevery setting"""

return self._markevery</div>

<div class="viewcode-block" id="Line2D.set_picker"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_picker">[docs]</a> def set_picker(self, p):

"""Sets the event picker details for the line.

Parameters

----------

p : float or callable[[Artist, Event], Tuple[bool, dict]]

If a float, it is used as the pick radius in points.

"""

if callable(p):

self._contains = p

else:

self.pickradius = p

self._picker = p</div>

<div class="viewcode-block" id="Line2D.get_window_extent"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_window_extent">[docs]</a> def get_window_extent(self, renderer):

bbox = Bbox([[0, 0], [0, 0]])

trans_data_to_xy = self.get_transform().transform

bbox.update_from_data_xy(trans_data_to_xy(self.get_xydata()),

ignore=True)

# correct for marker size, if any

if self._marker:

ms = (self._markersize / 72.0 * self.figure.dpi) * 0.5

bbox = bbox.padded(ms)

return bbox</div>

@Artist.axes.setter

def axes(self, ax):

# call the set method from the base-class property

Artist.axes.fset(self, ax)

if ax is not None:

# connect unit-related callbacks

if ax.xaxis is not None:

self._xcid = ax.xaxis.callbacks.connect('units',

self.recache_always)

if ax.yaxis is not None:

self._ycid = ax.yaxis.callbacks.connect('units',

self.recache_always)

<div class="viewcode-block" id="Line2D.set_data"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_data">[docs]</a> def set_data(self, *args):

"""

Set the x and y data

ACCEPTS: 2D array (rows are x, y) or two 1D arrays

"""

if len(args) == 1:

x, y = args[0]

else:

x, y = args

self.set_xdata(x)

self.set_ydata(y)</div>

<div class="viewcode-block" id="Line2D.recache_always"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.recache_always">[docs]</a> def recache_always(self):

self.recache(always=True)</div>

<div class="viewcode-block" id="Line2D.recache"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.recache">[docs]</a> def recache(self, always=False):

if always or self._invalidx:

xconv = self.convert_xunits(self._xorig)

x = _to_unmasked_float_array(xconv).ravel()

else:

x = self._x

if always or self._invalidy:

yconv = self.convert_yunits(self._yorig)

y = _to_unmasked_float_array(yconv).ravel()

else:

y = self._y

self._xy = np.column_stack(np.broadcast_arrays(x, y)).astype(float)

self._x, self._y = self._xy.T # views

self._subslice = False

if (self.axes and len(x) > 1000 and self._is_sorted(x) and

self.axes.name == 'rectilinear' and

self.axes.get_xscale() == 'linear' and

self._markevery is None and

self.get_clip_on() is True):

self._subslice = True

nanmask = np.isnan(x)

if nanmask.any():

self._x_filled = self._x.copy()

indices = np.arange(len(x))

self._x_filled[nanmask] = np.interp(indices[nanmask],

indices[~nanmask], self._x[~nanmask])

else:

self._x_filled = self._x

if self._path is not None:

interpolation_steps = self._path._interpolation_steps

else:

interpolation_steps = 1

xy = STEP_LOOKUP_MAP[self._drawstyle](*self._xy.T)

self._path = Path(np.asarray(xy).T,

_interpolation_steps=interpolation_steps)

self._transformed_path = None

self._invalidx = False

self._invalidy = False</div>

def _transform_path(self, subslice=None):

"""

Puts a TransformedPath instance at self._transformed_path;

all invalidation of the transform is then handled by the

TransformedPath instance.

"""

# Masked arrays are now handled by the Path class itself

if subslice is not None:

xy = STEP_LOOKUP_MAP[self._drawstyle](*self._xy[subslice, :].T)

_path = Path(np.asarray(xy).T,

_interpolation_steps=self._path._interpolation_steps)

else:

_path = self._path

self._transformed_path = TransformedPath(_path, self.get_transform())

def _get_transformed_path(self):

"""

Return the :class:`~matplotlib.transforms.TransformedPath` instance

of this line.

"""

if self._transformed_path is None:

self._transform_path()

return self._transformed_path

<div class="viewcode-block" id="Line2D.set_transform"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.set_transform">[docs]</a> def set_transform(self, t):

"""

set the Transformation instance used by this artist

Parameters

----------

t : matplotlib.transforms.Transform

"""

Artist.set_transform(self, t)

self._invalidx = True

self._invalidy = True

self.stale = True</div>

def _is_sorted(self, x):

"""return True if x is sorted in ascending order"""

# We don't handle the monotonically decreasing case.

return _path.is_sorted(x)

<div class="viewcode-block" id="Line2D.draw"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.draw">[docs]</a> @allow_rasterization

def draw(self, renderer):

"""draw the Line with `renderer` unless visibility is False"""

if not self.get_visible():

return

self.recache()

self.ind_offset = 0 # Needed for contains() method.

if self._subslice and self.axes:

x0, x1 = self.axes.get_xbound()

i0, = self._x_filled.searchsorted([x0], 'left')

i1, = self._x_filled.searchsorted([x1], 'right')

subslice = slice(max(i0 - 1, 0), i1 + 1)

self.ind_offset = subslice.start

self._transform_path(subslice)

else:

subslice = None

if self.get_path_effects():

from matplotlib.patheffects import PathEffectRenderer

renderer = PathEffectRenderer(self.get_path_effects(), renderer)

renderer.open_group('line2d', self.get_gid())

if self._lineStyles[self._linestyle] != '_draw_nothing':

tpath, affine = (self._get_transformed_path()

.get_transformed_path_and_affine())

if len(tpath.vertices):

gc = renderer.new_gc()

self._set_gc_clip(gc)

lc_rgba = mcolors.to_rgba(self._color, self._alpha)

gc.set_foreground(lc_rgba, isRGBA=True)

gc.set_antialiased(self._antialiased)

gc.set_linewidth(self._linewidth)

if self.is_dashed():

cap = self._dashcapstyle

join = self._dashjoinstyle

else:

cap = self._solidcapstyle

join = self._solidjoinstyle

gc.set_joinstyle(join)

gc.set_capstyle(cap)

gc.set_snap(self.get_snap())

if self.get_sketch_params() is not None:

gc.set_sketch_params(*self.get_sketch_params())

gc.set_dashes(self._dashOffset, self._dashSeq)

renderer.draw_path(gc, tpath, affine.frozen())

gc.restore()

if self._marker and self._markersize > 0:

gc = renderer.new_gc()

self._set_gc_clip(gc)

ec_rgba = mcolors.to_rgba(

self.get_markeredgecolor(), self._alpha)

fc_rgba = mcolors.to_rgba(

self._get_markerfacecolor(), self._alpha)

fcalt_rgba = mcolors.to_rgba(

self._get_markerfacecolor(alt=True), self._alpha)

# If the edgecolor is "auto", it is set according to the *line*

# color but inherits the alpha value of the *face* color, if any.

if (cbook._str_equal(self._markeredgecolor, "auto")

and not cbook._str_lower_equal(

self.get_markerfacecolor(), "none")):

ec_rgba = ec_rgba[:3] + (fc_rgba[3],)

gc.set_foreground(ec_rgba, isRGBA=True)

scale, length, randomness = self.get_sketch_params()

gc.set_sketch_params(scale/2, length/2, 2*randomness)

marker = self._marker

# Markers *must* be drawn ignoring the drawstyle (but don't pay the

# recaching if drawstyle is already "default").

if self.get_drawstyle() != "default":

with cbook._setattr_cm(

self, _drawstyle="default", _transformed_path=None):

self.recache()

self._transform_path(subslice)

.get_transformed_path_and_affine())

else:

.get_transformed_path_and_affine())

if len(tpath.vertices):

# subsample the markers if markevery is not None

markevery = self.get_markevery()

if markevery is not None:

subsampled = _mark_every_path(markevery, tpath,

affine, self.axes.transAxes)

else:

subsampled = tpath

snap = marker.get_snap_threshold()

if isinstance(snap, Real):

snap = renderer.points_to_pixels(self._markersize) >= snap

gc.set_snap(snap)

gc.set_joinstyle(marker.get_joinstyle())

gc.set_capstyle(marker.get_capstyle())

marker_path = marker.get_path()

marker_trans = marker.get_transform()

w = renderer.points_to_pixels(self._markersize)

if cbook._str_equal(marker.get_marker(), ","):

gc.set_linewidth(0)

else:

# Don't scale for pixels, and don't stroke them

marker_trans = marker_trans.scale(w)

renderer.draw_markers(gc, marker_path, marker_trans,

subsampled, affine.frozen(),

fc_rgba)

alt_marker_path = marker.get_alt_path()

if alt_marker_path:

alt_marker_trans = marker.get_alt_transform()

alt_marker_trans = alt_marker_trans.scale(w)

renderer.draw_markers(

gc, alt_marker_path, alt_marker_trans, subsampled,

affine.frozen(), fcalt_rgba)

gc.restore()

renderer.close_group('line2d')

self.stale = False</div>

<div class="viewcode-block" id="Line2D.get_antialiased"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_antialiased">[docs]</a> def get_antialiased(self):

return self._antialiased</div>

<div class="viewcode-block" id="Line2D.get_color"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_color">[docs]</a> def get_color(self):

return self._color</div>

<div class="viewcode-block" id="Line2D.get_drawstyle"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_drawstyle">[docs]</a> def get_drawstyle(self):

return self._drawstyle</div>

<div class="viewcode-block" id="Line2D.get_linestyle"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_linestyle">[docs]</a> def get_linestyle(self):

return self._linestyle</div>

<div class="viewcode-block" id="Line2D.get_linewidth"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_linewidth">[docs]</a> def get_linewidth(self):

return self._linewidth</div>

<div class="viewcode-block" id="Line2D.get_marker"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_marker">[docs]</a> def get_marker(self):

return self._marker.get_marker()</div>

<div class="viewcode-block" id="Line2D.get_markeredgecolor"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_markeredgecolor">[docs]</a> def get_markeredgecolor(self):

mec = self._markeredgecolor

if cbook._str_equal(mec, 'auto'):

if rcParams['_internal.classic_mode']:

if self._marker.get_marker() in ('.', ','):

return self._color

if self._marker.is_filled() and self.get_fillstyle() != 'none':

return 'k' # Bad hard-wired default...

return self._color

else:

return mec</div>

<div class="viewcode-block" id="Line2D.get_markeredgewidth"><a class="viewcode-back" href="../../api/_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D.get_markeredgewidth">[docs]</a> def get_markeredgewidth(self):

return self._markeredgewidth</div>

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