matplotlib.pyplot¶

Provides a MATLAB-like plotting framework.

pylab combines pyplot with numpy into a single namespace. This is convenient for interactive work, but for programming it is recommended that the namespaces be kept separate, e.g.:

import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)

matplotlib.pyplot.acorr(x, hold=None, data=None, **kwargs)¶

Plot the autocorrelation of x.

Parameters:	x : sequence of scalar hold : boolean, optional, deprecated, default: True detrend : callable, optional, default: mlab.detrend_none x is detrended by the detrend callable. Default is no normalization. normed : boolean, optional, default: True if True, input vectors are normalised to unit length. usevlines : boolean, optional, default: True if True, Axes.vlines is used to plot the vertical lines from the origin to the acorr. Otherwise, Axes.plot is used. maxlags : integer, optional, default: 10 number of lags to show. If None, will return all 2 * len(x) - 1 lags.
Returns:	(lags, c, line, b) : where: lags are a length 2`maxlags+1 lag vector. c is the 2`maxlags+1 auto correlation vectorI line is a Line2D instance returned by plot. b is the x-axis.
Other Parameters:
	linestyle : Line2D prop, optional, default: None Only used if usevlines is False. marker : string, optional, default: ‘o’

Notes

The cross correlation is performed with numpy.correlate() with mode = 2.

Examples

xcorr is top graph, and acorr is bottom graph.

(Source code, png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All arguments with the following names: ‘x’.

matplotlib.pyplot.angle_spectrum(x, Fs=None, Fc=None, window=None, pad_to=None, sides=None, hold=None, data=None, **kwargs)¶

Plot the angle spectrum.

Call signature:

angle_spectrum(x, Fs=2, Fc=0,  window=mlab.window_hanning,
               pad_to=None, sides='default', **kwargs)

Compute the angle spectrum (wrapped phase spectrum) of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.

Parameters:

x : 1-D array or sequence Array or sequence containing the data Fs : scalar The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit. The default value is 2. window : callable or ndarray A function or a vector of length NFFT. To create window vectors see window_hanning(), window_none(), numpy.blackman(), numpy.hamming(), numpy.bartlett(), scipy.signal(), scipy.signal.get_window(), etc. The default is window_hanning(). If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment. sides : [ ‘default’ | ‘onesided’ | ‘twosided’ ] Specifies which sides of the spectrum to return. Default gives the default behavior, which returns one-sided for real data and both for complex data. ‘onesided’ forces the return of a one-sided spectrum, while ‘twosided’ forces two-sided. pad_to : integer The number of points to which the data segment is padded when performing the FFT. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to the length of the input signal (i.e. no padding). Fc : integer The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband. **kwargs : Keyword arguments control the Line2D properties: Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color or c any matplotlib color contains a callable function dash_capstyle [‘butt’ | ‘round’ | ‘projecting’] dash_joinstyle [‘miter’ | ‘round’ | ‘bevel’] dashes sequence of on/off ink in points drawstyle [‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’] gid an id string label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points marker A valid marker style markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markerfacecoloralt or mfcalt any matplotlib color markersize or ms float markevery [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float] path_effects unknown picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] sketch_params unknown snap unknown solid_capstyle [‘butt’ | ‘round’ | ‘projecting’] solid_joinstyle [‘miter’ | ‘round’ | ‘bevel’] transform a matplotlib.transforms.Transform instance url a url string visible [True | False] xdata 1D array ydata 1D array zorder any number

Returns:

spectrum : 1-D array The values for the angle spectrum in radians (real valued) freqs : 1-D array The frequencies corresponding to the elements in spectrum line : a Line2D instance The line created by this function

See also

magnitude_spectrum()

angle_spectrum() plots the magnitudes of the corresponding frequencies.

phase_spectrum()

phase_spectrum() plots the unwrapped version of this function.

specgram()

specgram() can plot the angle spectrum of segments within the signal in a colormap.

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]: * All arguments with the following names: ‘x’.

Examples

(Source code, png, pdf)

matplotlib.pyplot.annotate(*args, **kwargs)¶

Annotate the point xy with text s.

Additional kwargs are passed to Text.

Parameters:

s : str The text of the annotation xy : iterable Length 2 sequence specifying the (x,y) point to annotate xytext : iterable, optional Length 2 sequence specifying the (x,y) to place the text at. If None, defaults to xy. xycoords : str, Artist, Transform, callable or tuple, optional The coordinate system that xy is given in. For a str the allowed values are: Property Description ‘figure points’ points from the lower left of the figure ‘figure pixels’ pixels from the lower left of the figure ‘figure fraction’ fraction of figure from lower left ‘axes points’ points from lower left corner of axes ‘axes pixels’ pixels from lower left corner of axes ‘axes fraction’ fraction of axes from lower left ‘data’ use the coordinate system of the object being annotated (default) ‘polar’ (theta,r) if not native ‘data’ coordinates If a Artist object is passed in the units are fraction if it’s bounding box. If a Transform object is passed in use that to transform xy to screen coordinates If a callable it must take a RendererBase object as input and return a Transform or Bbox object If a tuple must be length 2 tuple of str, Artist, Transform or callable objects. The first transform is used for the x coordinate and the second for y. See Advanced Annotation for more details. Defaults to 'data' textcoords : str, Artist, Transform, callable or tuple, optional The coordinate system that xytext is given, which may be different than the coordinate system used for xy. All xycoords values are valid as well as the following strings: Property Description ‘offset points’ offset (in points) from the xy value ‘offset pixels’ offset (in pixels) from the xy value defaults to the input of xycoords arrowprops : dict, optional If not None, properties used to draw a FancyArrowPatch arrow between xy and xytext. If arrowprops does not contain the key 'arrowstyle' the allowed keys are: Key Description width the width of the arrow in points headwidth the width of the base of the arrow head in points headlength the length of the arrow head in points shrink fraction of total length to ‘shrink’ from both ends ? any key to matplotlib.patches.FancyArrowPatch If the arrowprops contains the key 'arrowstyle' the above keys are forbidden. The allowed values of 'arrowstyle' are: Name Attrs '-' None '->' head_length=0.4,head_width=0.2 '-[' widthB=1.0,lengthB=0.2,angleB=None '|-|' widthA=1.0,widthB=1.0 '-|>' head_length=0.4,head_width=0.2 '<-' head_length=0.4,head_width=0.2 '<->' head_length=0.4,head_width=0.2 '<|-' head_length=0.4,head_width=0.2 '<|-|>' head_length=0.4,head_width=0.2 'fancy' head_length=0.4,head_width=0.4,tail_width=0.4 'simple' head_length=0.5,head_width=0.5,tail_width=0.2 'wedge' tail_width=0.3,shrink_factor=0.5 Valid keys for FancyArrowPatch are: Key Description arrowstyle the arrow style connectionstyle the connection style relpos default is (0.5, 0.5) patchA default is bounding box of the text patchB default is None shrinkA default is 2 points shrinkB default is 2 points mutation_scale default is text size (in points) mutation_aspect default is 1. ? any key for matplotlib.patches.PathPatch Defaults to None annotation_clip : bool, optional Controls the visibility of the annotation when it goes outside the axes area. If True, the annotation will only be drawn when the xy is inside the axes. If False, the annotation will always be drawn regardless of its position. The default is None, which behave as True only if xycoords is “data”.

Returns:

Annotation

matplotlib.pyplot.arrow(x, y, dx, dy, hold=None, **kwargs)¶

Add an arrow to the axes.

Draws arrow on specified axis from (x, y) to (x + dx, y + dy). Uses FancyArrow patch to construct the arrow.

Parameters:	x : float X-coordinate of the arrow base y : float Y-coordinate of the arrow base dx : float Length of arrow along x-coordinate dy : float Length of arrow along y-coordinate
Returns:	a : FancyArrow patches.FancyArrow object
Other Parameters:
	Optional kwargs (inherited from FancyArrow patch) control the arrow construction and properties: Constructor arguments width: float (default: 0.001) width of full arrow tail length_includes_head: [True | False] (default: False) True if head is to be counted in calculating the length. head_width: float or None (default: 3*width) total width of the full arrow head head_length: float or None (default: 1.5 * head_width) length of arrow head shape: [‘full’, ‘left’, ‘right’] (default: ‘full’) draw the left-half, right-half, or full arrow overhang: float (default: 0) fraction that the arrow is swept back (0 overhang means triangular shape). Can be negative or greater than one. head_starts_at_zero: [True | False] (default: False) if True, the head starts being drawn at coordinate 0 instead of ending at coordinate 0. Other valid kwargs (inherited from :class:`Patch`) are: Property Description agg_filter unknown alpha float or None animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance capstyle [‘butt’ | ‘round’ | ‘projecting’] clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color spec contains a callable function edgecolor or ec mpl color spec, None, ‘none’, or ‘auto’ facecolor or fc mpl color spec, or None for default, or ‘none’ for no color figure a matplotlib.figure.Figure instance fill [True | False] gid an id string hatch [‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’] joinstyle [‘miter’ | ‘round’ | ‘bevel’] label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float or None for default path_effects unknown picker [None|float|boolean|callable] rasterized [True | False | None] sketch_params unknown snap unknown transform Transform instance url a url string visible [True | False] zorder any number

Notes

The resulting arrow is affected by the axes aspect ratio and limits. This may produce an arrow whose head is not square with its stem. To create an arrow whose head is square with its stem, use annotate() for example:

ax.annotate("", xy=(0.5, 0.5), xytext=(0, 0),
    arrowprops=dict(arrowstyle="->"))

Examples

(Source code, png, pdf)

matplotlib.pyplot.autoscale(enable=True, axis='both', tight=None)¶

Autoscale the axis view to the data (toggle).

Convenience method for simple axis view autoscaling. It turns autoscaling on or off, and then, if autoscaling for either axis is on, it performs the autoscaling on the specified axis or axes.

enable: [True | False | None]

True (default) turns autoscaling on, False turns it off. None leaves the autoscaling state unchanged.

axis: [‘x’ | ‘y’ | ‘both’]

which axis to operate on; default is ‘both’

tight: [True | False | None]

If True, set view limits to data limits; if False, let the locator and margins expand the view limits; if None, use tight scaling if the only artist is an image, otherwise treat tight as False. The tight setting is retained for future autoscaling until it is explicitly changed.

Returns None.

matplotlib.pyplot.autumn()¶

set the default colormap to autumn and apply to current image if any. See help(colormaps) for more information

matplotlib.pyplot.axes(*args, **kwargs)¶

Add an axes to the figure.

The axes is added at position rect specified by:

• axes() by itself creates a default full subplot(111) window axis.
• axes(rect, facecolor='w') where rect = [left, bottom, width, height] in normalized (0, 1) units. facecolor is the background color for the axis, default white.
• axes(h) where h is an axes instance makes h the current axis. An Axes instance is returned.

kwarg	Accepts	Description
facecolor	color	the axes background color
frameon	[True|False]	display the frame?
sharex	otherax	current axes shares xaxis attribute with otherax
sharey	otherax	current axes shares yaxis attribute with otherax
polar	[True|False]	use a polar axes?
aspect	[str | num]	[‘equal’, ‘auto’] or a number. If a number the ratio of x-unit/y-unit in screen-space. Also see set_aspect().

Examples:

• examples/pylab_examples/axes_demo.py places custom axes.
• examples/pylab_examples/shared_axis_demo.py uses sharex and sharey.

matplotlib.pyplot.axhline(y=0, xmin=0, xmax=1, hold=None, **kwargs)¶

Add a horizontal line across the axis.

Parameters:	y : scalar, optional, default: 0 y position in data coordinates of the horizontal line. xmin : scalar, optional, default: 0 Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot. xmax : scalar, optional, default: 1 Should be between 0 and 1, 0 being the far left of the plot, 1 the far right of the plot.
Returns:	Line2D

See also

axhspan

for example plot and source code

Notes

kwargs are passed to Line2D and can be used to control the line properties.

Examples

• draw a thick red hline at ‘y’ = 0 that spans the xrange:

  >>> axhline(linewidth=4, color='r')
  

• draw a default hline at ‘y’ = 1 that spans the xrange:

  >>> axhline(y=1)
  

• draw a default hline at ‘y’ = .5 that spans the middle half of the xrange:

  >>> axhline(y=.5, xmin=0.25, xmax=0.75)
  

Valid kwargs are Line2D properties, with the exception of ‘transform’:

Property	Description
agg_filter	unknown
alpha	float (0.0 transparent through 1.0 opaque)
animated	[True | False]
antialiased or aa	[True | False]
axes	an Axes instance
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
color or c	any matplotlib color
contains	a callable function
dash_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
dash_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
dashes	sequence of on/off ink in points
drawstyle	[‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’]
figure	a matplotlib.figure.Figure instance
fillstyle	[‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’]
gid	an id string
label	string or anything printable with ‘%s’ conversion.
linestyle or ls	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or lw	float value in points
marker	A valid marker style
markeredgecolor or mec	any matplotlib color
markeredgewidth or mew	float value in points
markerfacecolor or mfc	any matplotlib color
markerfacecoloralt or mfcalt	any matplotlib color
markersize or ms	float
markevery	[None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]
path_effects	unknown
picker	float distance in points or callable pick function fn(artist, event)
pickradius	float distance in points
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
solid_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
solid_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
transform	a matplotlib.transforms.Transform instance
url	a url string
visible	[True | False]
xdata	1D array
ydata	1D array
zorder	any number

matplotlib.pyplot.axhspan(ymin, ymax, xmin=0, xmax=1, hold=None, **kwargs)¶

Add a horizontal span (rectangle) across the axis.

Draw a horizontal span (rectangle) from ymin to ymax. With the default values of xmin = 0 and xmax = 1, this always spans the xrange, regardless of the xlim settings, even if you change them, e.g., with the set_xlim() command. That is, the horizontal extent is in axes coords: 0=left, 0.5=middle, 1.0=right but the y location is in data coordinates.

Parameters:	ymin : float Lower limit of the horizontal span in data units. ymax : float Upper limit of the horizontal span in data units. xmin : float, optional, default: 0 Lower limit of the vertical span in axes (relative 0-1) units. xmax : float, optional, default: 1 Upper limit of the vertical span in axes (relative 0-1) units.
Returns:	Polygon : Polygon
Other Parameters:
	kwargs : Polygon properties. Property Description agg_filter unknown alpha float or None animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance capstyle [‘butt’ | ‘round’ | ‘projecting’] clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color spec contains a callable function edgecolor or ec mpl color spec, None, ‘none’, or ‘auto’ facecolor or fc mpl color spec, or None for default, or ‘none’ for no color figure a matplotlib.figure.Figure instance fill [True | False] gid an id string hatch [‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’] joinstyle [‘miter’ | ‘round’ | ‘bevel’] label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float or None for default path_effects unknown picker [None|float|boolean|callable] rasterized [True | False | None] sketch_params unknown snap unknown transform Transform instance url a url string visible [True | False] zorder any number

See also

axvspan

Add a vertical span (rectangle) across the axes.

Examples

(Source code, png, pdf)

matplotlib.pyplot.axis(*v, **kwargs)¶

Convenience method to get or set axis properties.

Calling with no arguments:

>>> axis()

returns the current axes limits [xmin, xmax, ymin, ymax].:

>>> axis(v)

sets the min and max of the x and y axes, with v = [xmin, xmax, ymin, ymax].:

>>> axis('off')

turns off the axis lines and labels.:

>>> axis('equal')

changes limits of x or y axis so that equal increments of x and y have the same length; a circle is circular.:

>>> axis('scaled')

achieves the same result by changing the dimensions of the plot box instead of the axis data limits.:

>>> axis('tight')

changes x and y axis limits such that all data is shown. If all data is already shown, it will move it to the center of the figure without modifying (xmax - xmin) or (ymax - ymin). Note this is slightly different than in MATLAB.:

>>> axis('image')

is ‘scaled’ with the axis limits equal to the data limits.:

>>> axis('auto')

and:

>>> axis('normal')

are deprecated. They restore default behavior; axis limits are automatically scaled to make the data fit comfortably within the plot box.

if len(*v)==0, you can pass in xmin, xmax, ymin, ymax as kwargs selectively to alter just those limits without changing the others.

>>> axis('square')

changes the limit ranges (xmax-xmin) and (ymax-ymin) of the x and y axes to be the same, and have the same scaling, resulting in a square plot.

The xmin, xmax, ymin, ymax tuple is returned

See also

xlim(), ylim()

For setting the x- and y-limits individually.

matplotlib.pyplot.axvline(x=0, ymin=0, ymax=1, hold=None, **kwargs)¶

Add a vertical line across the axes.

Parameters:	x : scalar, optional, default: 0 x position in data coordinates of the vertical line. ymin : scalar, optional, default: 0 Should be between 0 and 1, 0 being the bottom of the plot, 1 the top of the plot. ymax : scalar, optional, default: 1 Should be between 0 and 1, 0 being the bottom of the plot, 1 the top of the plot.
Returns:	Line2D

See also

axhspan

for example plot and source code

Examples

• draw a thick red vline at x = 0 that spans the yrange:

  >>> axvline(linewidth=4, color='r')
  

• draw a default vline at x = 1 that spans the yrange:

  >>> axvline(x=1)
  

• draw a default vline at x = .5 that spans the middle half of the yrange:

  >>> axvline(x=.5, ymin=0.25, ymax=0.75)
  

Valid kwargs are Line2D properties, with the exception of ‘transform’:

Property	Description
agg_filter	unknown
alpha	float (0.0 transparent through 1.0 opaque)
animated	[True | False]
antialiased or aa	[True | False]
axes	an Axes instance
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
color or c	any matplotlib color
contains	a callable function
dash_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
dash_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
dashes	sequence of on/off ink in points
drawstyle	[‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’]
figure	a matplotlib.figure.Figure instance
fillstyle	[‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’]
gid	an id string
label	string or anything printable with ‘%s’ conversion.
linestyle or ls	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or lw	float value in points
marker	A valid marker style
markeredgecolor or mec	any matplotlib color
markeredgewidth or mew	float value in points
markerfacecolor or mfc	any matplotlib color
markerfacecoloralt or mfcalt	any matplotlib color
markersize or ms	float
markevery	[None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]
path_effects	unknown
picker	float distance in points or callable pick function fn(artist, event)
pickradius	float distance in points
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
solid_capstyle	[‘butt’ | ‘round’ | ‘projecting’]
solid_joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
transform	a matplotlib.transforms.Transform instance
url	a url string
visible	[True | False]
xdata	1D array
ydata	1D array
zorder	any number

matplotlib.pyplot.axvspan(xmin, xmax, ymin=0, ymax=1, hold=None, **kwargs)¶

Add a vertical span (rectangle) across the axes.

Draw a vertical span (rectangle) from xmin to xmax. With the default values of ymin = 0 and ymax = 1. This always spans the yrange, regardless of the ylim settings, even if you change them, e.g., with the set_ylim() command. That is, the vertical extent is in axes coords: 0=bottom, 0.5=middle, 1.0=top but the y location is in data coordinates.

Parameters:	xmin : scalar Number indicating the first X-axis coordinate of the vertical span rectangle in data units. xmax : scalar Number indicating the second X-axis coordinate of the vertical span rectangle in data units. ymin : scalar, optional Number indicating the first Y-axis coordinate of the vertical span rectangle in relative Y-axis units (0-1). Default to 0. ymax : scalar, optional Number indicating the second Y-axis coordinate of the vertical span rectangle in relative Y-axis units (0-1). Default to 1.
Returns:	rectangle : matplotlib.patches.Polygon Vertical span (rectangle) from (xmin, ymin) to (xmax, ymax).
Other Parameters:
	**kwargs Optional parameters are properties of the class matplotlib.patches.Polygon.

See also

axhspan

Examples

Draw a vertical, green, translucent rectangle from x = 1.25 to x = 1.55 that spans the yrange of the axes.

>>> axvspan(1.25, 1.55, facecolor='g', alpha=0.5)

matplotlib.pyplot.bar(left, height, width=0.8, bottom=None, hold=None, data=None, **kwargs)¶

Make a bar plot.

Make a bar plot with rectangles bounded by:

left, left + width, bottom, bottom + height

(left, right, bottom and top edges)

Parameters:

left : sequence of scalars the x coordinates of the left sides of the bars height : sequence of scalars the heights of the bars width : scalar or array-like, optional the width(s) of the bars default: 0.8 bottom : scalar or array-like, optional the y coordinate(s) of the bars default: None color : scalar or array-like, optional the colors of the bar faces edgecolor : scalar or array-like, optional the colors of the bar edges linewidth : scalar or array-like, optional width of bar edge(s). If None, use default linewidth; If 0, don’t draw edges. default: None tick_label : string or array-like, optional the tick labels of the bars default: None xerr : scalar or array-like, optional if not None, will be used to generate errorbar(s) on the bar chart default: None yerr : scalar or array-like, optional if not None, will be used to generate errorbar(s) on the bar chart default: None ecolor : scalar or array-like, optional specifies the color of errorbar(s) default: None capsize : scalar, optional determines the length in points of the error bar caps default: None, which will take the value from the errorbar.capsize rcParam. error_kw : dict, optional dictionary of kwargs to be passed to errorbar method. ecolor and capsize may be specified here rather than as independent kwargs. align : {‘center’, ‘edge’}, optional If ‘edge’, aligns bars by their left edges (for vertical bars) and by their bottom edges (for horizontal bars). If ‘center’, interpret the left argument as the coordinates of the centers of the bars. To align on the align bars on the right edge pass a negative width. orientation : {‘vertical’, ‘horizontal’}, optional The orientation of the bars. log : boolean, optional If true, sets the axis to be log scale. default: False

Returns:

bars : matplotlib.container.BarContainer Container with all of the bars + errorbars

See also

barh

Plot a horizontal bar plot.

Notes

The optional arguments color, edgecolor, linewidth, xerr, and yerr can be either scalars or sequences of length equal to the number of bars. This enables you to use bar as the basis for stacked bar charts, or candlestick plots. Detail: xerr and yerr are passed directly to errorbar(), so they can also have shape 2xN for independent specification of lower and upper errors.

Other optional kwargs:

Property	Description
agg_filter	unknown
alpha	float or None
animated	[True | False]
antialiased or aa	[True | False] or None for default
axes	an Axes instance
capstyle	[‘butt’ | ‘round’ | ‘projecting’]
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
color	matplotlib color spec
contains	a callable function
edgecolor or ec	mpl color spec, None, ‘none’, or ‘auto’
facecolor or fc	mpl color spec, or None for default, or ‘none’ for no color
figure	a matplotlib.figure.Figure instance
fill	[True | False]
gid	an id string
hatch	[‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’]
joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
label	string or anything printable with ‘%s’ conversion.
linestyle or ls	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or lw	float or None for default
path_effects	unknown
picker	[None|float|boolean|callable]
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
transform	Transform instance
url	a url string
visible	[True | False]
zorder	any number

Examples

Example: A stacked bar chart.

(Source code, png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All arguments with the following names: ‘bottom’, ‘color’, ‘ecolor’, ‘edgecolor’, ‘height’, ‘left’, ‘linewidth’, ‘tick_label’, ‘width’, ‘xerr’, ‘yerr’.

matplotlib.pyplot.barbs(*args, **kw)¶

Plot a 2-D field of barbs.

Call signatures:

barb(U, V, **kw)
barb(U, V, C, **kw)
barb(X, Y, U, V, **kw)
barb(X, Y, U, V, C, **kw)

Arguments:

X, Y:

The x and y coordinates of the barb locations (default is head of barb; see pivot kwarg)

U, V:

Give the x and y components of the barb shaft

C:

An optional array used to map colors to the barbs

All arguments may be 1-D or 2-D arrays or sequences. If X and Y are absent, they will be generated as a uniform grid. If U and V are 2-D arrays but X and Y are 1-D, and if len(X) and len(Y) match the column and row dimensions of U, then X and Y will be expanded with numpy.meshgrid().

U, V, C may be masked arrays, but masked X, Y are not supported at present.

Keyword arguments:

length:

Length of the barb in points; the other parts of the barb are scaled against this. Default is 9

pivot: [ ‘tip’ | ‘middle’ ]

The part of the arrow that is at the grid point; the arrow rotates about this point, hence the name pivot. Default is ‘tip’

barbcolor: [ color | color sequence ]

Specifies the color all parts of the barb except any flags. This parameter is analagous to the edgecolor parameter for polygons, which can be used instead. However this parameter will override facecolor.

flagcolor: [ color | color sequence ]

Specifies the color of any flags on the barb. This parameter is analagous to the facecolor parameter for polygons, which can be used instead. However this parameter will override facecolor. If this is not set (and C has not either) then flagcolor will be set to match barbcolor so that the barb has a uniform color. If C has been set, flagcolor has no effect.

sizes:

A dictionary of coefficients specifying the ratio of a given feature to the length of the barb. Only those values one wishes to override need to be included. These features include:

• ‘spacing’ - space between features (flags, full/half barbs)
• ‘height’ - height (distance from shaft to top) of a flag or full barb
• ‘width’ - width of a flag, twice the width of a full barb
• ‘emptybarb’ - radius of the circle used for low magnitudes

fill_empty:

A flag on whether the empty barbs (circles) that are drawn should be filled with the flag color. If they are not filled, they will be drawn such that no color is applied to the center. Default is False

rounding:

A flag to indicate whether the vector magnitude should be rounded when allocating barb components. If True, the magnitude is rounded to the nearest multiple of the half-barb increment. If False, the magnitude is simply truncated to the next lowest multiple. Default is True

barb_increments:

A dictionary of increments specifying values to associate with different parts of the barb. Only those values one wishes to override need to be included.

• ‘half’ - half barbs (Default is 5)
• ‘full’ - full barbs (Default is 10)
• ‘flag’ - flags (default is 50)

flip_barb:

Either a single boolean flag or an array of booleans. Single boolean indicates whether the lines and flags should point opposite to normal for all barbs. An array (which should be the same size as the other data arrays) indicates whether to flip for each individual barb. Normal behavior is for the barbs and lines to point right (comes from wind barbs having these features point towards low pressure in the Northern Hemisphere.) Default is False

Barbs are traditionally used in meteorology as a way to plot the speed and direction of wind observations, but can technically be used to plot any two dimensional vector quantity. As opposed to arrows, which give vector magnitude by the length of the arrow, the barbs give more quantitative information about the vector magnitude by putting slanted lines or a triangle for various increments in magnitude, as show schematically below:

:     /\    \
:    /  \    \
:   /    \    \    \
:  /      \    \    \
: ------------------------------

The largest increment is given by a triangle (or “flag”). After those come full lines (barbs). The smallest increment is a half line. There is only, of course, ever at most 1 half line. If the magnitude is small and only needs a single half-line and no full lines or triangles, the half-line is offset from the end of the barb so that it can be easily distinguished from barbs with a single full line. The magnitude for the barb shown above would nominally be 65, using the standard increments of 50, 10, and 5.

linewidths and edgecolors can be used to customize the barb. Additional PolyCollection keyword arguments:

Property	Description
agg_filter	unknown
alpha	float or None
animated	[True | False]
antialiased or antialiaseds	Boolean or sequence of booleans
array	unknown
axes	an Axes instance
clim	a length 2 sequence of floats
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
cmap	a colormap or registered colormap name
color	matplotlib color arg or sequence of rgba tuples
contains	a callable function
edgecolor or edgecolors	matplotlib color spec or sequence of specs
facecolor or facecolors	matplotlib color spec or sequence of specs
figure	a matplotlib.figure.Figure instance
gid	an id string
hatch	[ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ]
label	string or anything printable with ‘%s’ conversion.
linestyle or dashes or linestyles	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or linewidths or lw	float or sequence of floats
norm	unknown
offset_position	unknown
offsets	float or sequence of floats
path_effects	unknown
picker	[None|float|boolean|callable]
pickradius	unknown
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
transform	Transform instance
url	a url string
urls	unknown
visible	[True | False]
zorder	any number

Example:

(Source code)

(png, pdf)

(png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All positional and all keyword arguments.

matplotlib.pyplot.barh(bottom, width, height=0.8, left=None, hold=None, **kwargs)¶

Make a horizontal bar plot.

Make a horizontal bar plot with rectangles bounded by:

left, left + width, bottom, bottom + height

(left, right, bottom and top edges)

bottom, width, height, and left can be either scalars or sequences

Parameters:	bottom : scalar or array-like the y coordinate(s) of the bars width : scalar or array-like the width(s) of the bars height : sequence of scalars, optional, default: 0.8 the heights of the bars left : sequence of scalars the x coordinates of the left sides of the bars
Returns:	matplotlib.patches.Rectangle instances.
Other Parameters:
	color : scalar or array-like, optional the colors of the bars edgecolor : scalar or array-like, optional the colors of the bar edges linewidth : scalar or array-like, optional, default: None width of bar edge(s). If None, use default linewidth; If 0, don’t draw edges. tick_label : string or array-like, optional, default: None the tick labels of the bars xerr : scalar or array-like, optional, default: None if not None, will be used to generate errorbar(s) on the bar chart yerr : scalar or array-like, optional, default: None if not None, will be used to generate errorbar(s) on the bar chart ecolor : scalar or array-like, optional, default: None specifies the color of errorbar(s) capsize : scalar, optional determines the length in points of the error bar caps default: None, which will take the value from the errorbar.capsize rcParam. error_kw : dictionary of kwargs to be passed to errorbar method. ecolor and capsize may be specified here rather than as independent kwargs. align : {‘center’, ‘edge’}, optional If ‘edge’, aligns bars by their left edges (for vertical bars) and by their bottom edges (for horizontal bars). If ‘center’, interpret the bottom argument as the coordinates of the centers of the bars. To align on the align bars on the top edge pass a negative ‘height’. log : boolean, optional, default: False If true, sets the axis to be log scale

See also

bar

Plot a vertical bar plot.

Notes

The optional arguments color, edgecolor, linewidth, xerr, and yerr can be either scalars or sequences of length equal to the number of bars. This enables you to use bar as the basis for stacked bar charts, or candlestick plots. Detail: xerr and yerr are passed directly to errorbar(), so they can also have shape 2xN for independent specification of lower and upper errors.

Other optional kwargs:

Property	Description
agg_filter	unknown
alpha	float or None
animated	[True | False]
antialiased or aa	[True | False] or None for default
axes	an Axes instance
capstyle	[‘butt’ | ‘round’ | ‘projecting’]
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
color	matplotlib color spec
contains	a callable function
edgecolor or ec	mpl color spec, None, ‘none’, or ‘auto’
facecolor or fc	mpl color spec, or None for default, or ‘none’ for no color
figure	a matplotlib.figure.Figure instance
fill	[True | False]
gid	an id string
hatch	[‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’]
joinstyle	[‘miter’ | ‘round’ | ‘bevel’]
label	string or anything printable with ‘%s’ conversion.
linestyle or ls	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or lw	float or None for default
path_effects	unknown
picker	[None|float|boolean|callable]
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
transform	Transform instance
url	a url string
visible	[True | False]
zorder	any number

matplotlib.pyplot.bone()¶

set the default colormap to bone and apply to current image if any. See help(colormaps) for more information

matplotlib.pyplot.box(on=None)¶

Turn the axes box on or off. on may be a boolean or a string, ‘on’ or ‘off’.

If on is None, toggle state.

matplotlib.pyplot.boxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None, bootstrap=None, usermedians=None, conf_intervals=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None, manage_xticks=True, autorange=False, zorder=None, hold=None, data=None)¶

Make a box and whisker plot.

Make a box and whisker plot for each column of x or each vector in sequence x. The box extends from the lower to upper quartile values of the data, with a line at the median. The whiskers extend from the box to show the range of the data. Flier points are those past the end of the whiskers.

Parameters:	x : Array or a sequence of vectors. The input data. notch : bool, optional (False) If True, will produce a notched box plot. Otherwise, a rectangular boxplot is produced. The notches represent the confidence interval (CI) around the median. See the entry for the bootstrap parameter for information regarding how the locations of the notches are computed. Note In cases where the values of the CI are less than the lower quartile or greater than the upper quartile, the notches will extend beyond the box, giving it a distinctive “flipped” appearance. This is expected behavior and consistent with other statistical visualization packages. sym : str, optional The default symbol for flier points. Enter an empty string (‘’) if you don’t want to show fliers. If None, then the fliers default to ‘b+’ If you want more control use the flierprops kwarg. vert : bool, optional (True) If True (default), makes the boxes vertical. If False, everything is drawn horizontally. whis : float, sequence, or string (default = 1.5) As a float, determines the reach of the whiskers to the beyond the first and third quartiles. In other words, where IQR is the interquartile range (Q3-Q1), the upper whisker will extend to last datum less than Q3 + whis*IQR). Similarly, the lower whisker will extend to the first datum greater than Q1 - whis*IQR. Beyond the whiskers, data are considered outliers and are plotted as individual points. Set this to an unreasonably high value to force the whiskers to show the min and max values. Alternatively, set this to an ascending sequence of percentile (e.g., [5, 95]) to set the whiskers at specific percentiles of the data. Finally, whis can be the string 'range' to force the whiskers to the min and max of the data. bootstrap : int, optional Specifies whether to bootstrap the confidence intervals around the median for notched boxplots. If bootstrap is None, no bootstrapping is performed, and notches are calculated using a Gaussian-based asymptotic approximation (see McGill, R., Tukey, J.W., and Larsen, W.A., 1978, and Kendall and Stuart, 1967). Otherwise, bootstrap specifies the number of times to bootstrap the median to determine its 95% confidence intervals. Values between 1000 and 10000 are recommended. usermedians : array-like, optional An array or sequence whose first dimension (or length) is compatible with x. This overrides the medians computed by matplotlib for each element of usermedians that is not None. When an element of usermedians is None, the median will be computed by matplotlib as normal. conf_intervals : array-like, optional Array or sequence whose first dimension (or length) is compatible with x and whose second dimension is 2. When the an element of conf_intervals is not None, the notch locations computed by matplotlib are overridden (provided notch is True). When an element of conf_intervals is None, the notches are computed by the method specified by the other kwargs (e.g., bootstrap). positions : array-like, optional Sets the positions of the boxes. The ticks and limits are automatically set to match the positions. Defaults to range(1, N+1) where N is the number of boxes to be drawn. widths : scalar or array-like Sets the width of each box either with a scalar or a sequence. The default is 0.5, or 0.15*(distance between extreme positions), if that is smaller. patch_artist : bool, optional (False) If False produces boxes with the Line2D artist. Otherwise, boxes and drawn with Patch artists. labels : sequence, optional Labels for each dataset. Length must be compatible with dimensions of x. manage_xticks : bool, optional (True) If the function should adjust the xlim and xtick locations. autorange : bool, optional (False) When True and the data are distributed such that the 25th and 75th percentiles are equal, whis is set to 'range' such that the whisker ends are at the minimum and maximum of the data. meanline : bool, optional (False) If True (and showmeans is True), will try to render the mean as a line spanning the full width of the box according to meanprops (see below). Not recommended if shownotches is also True. Otherwise, means will be shown as points. zorder : scalar, optional (None) Sets the zorder of the boxplot.
Returns:	result : dict A dictionary mapping each component of the boxplot to a list of the matplotlib.lines.Line2D instances created. That dictionary has the following keys (assuming vertical boxplots): boxes: the main body of the boxplot showing the quartiles and the median’s confidence intervals if enabled. medians: horizontal lines at the median of each box. whiskers: the vertical lines extending to the most extreme, non-outlier data points. caps: the horizontal lines at the ends of the whiskers. fliers: points representing data that extend beyond the whiskers (fliers). means: points or lines representing the means.
Other Parameters:
	showcaps : bool, optional (True) Show the caps on the ends of whiskers. showbox : bool, optional (True) Show the central box. showfliers : bool, optional (True) Show the outliers beyond the caps. showmeans : bool, optional (False) Show the arithmetic means. capprops : dict, optional (None) Specifies the style of the caps. boxprops : dict, optional (None) Specifies the style of the box. whiskerprops : dict, optional (None) Specifies the style of the whiskers. flierprops : dict, optional (None) Specifies the style of the fliers. medianprops : dict, optional (None) Specifies the style of the median. meanprops : dict, optional (None) Specifies the style of the mean.

Examples

(Source code, png, pdf)

(png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All positional and all keyword arguments.

matplotlib.pyplot.broken_barh(xranges, yrange, hold=None, data=None, **kwargs)¶

Plot horizontal bars.

A collection of horizontal bars spanning yrange with a sequence of xranges.

Required arguments:

Argument	Description
xranges	sequence of (xmin, xwidth)
yrange	sequence of (ymin, ywidth)

kwargs are matplotlib.collections.BrokenBarHCollection properties:

Property	Description
agg_filter	unknown
alpha	float or None
animated	[True | False]
antialiased or antialiaseds	Boolean or sequence of booleans
array	unknown
axes	an Axes instance
clim	a length 2 sequence of floats
clip_box	a matplotlib.transforms.Bbox instance
clip_on	[True | False]
clip_path	[ (Path, Transform) | Patch | None ]
cmap	a colormap or registered colormap name
color	matplotlib color arg or sequence of rgba tuples
contains	a callable function
edgecolor or edgecolors	matplotlib color spec or sequence of specs
facecolor or facecolors	matplotlib color spec or sequence of specs
figure	a matplotlib.figure.Figure instance
gid	an id string
hatch	[ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ]
label	string or anything printable with ‘%s’ conversion.
linestyle or dashes or linestyles	[‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | '']
linewidth or linewidths or lw	float or sequence of floats
norm	unknown
offset_position	unknown
offsets	float or sequence of floats
path_effects	unknown
picker	[None|float|boolean|callable]
pickradius	unknown
rasterized	[True | False | None]
sketch_params	unknown
snap	unknown
transform	Transform instance
url	a url string
urls	unknown
visible	[True | False]
zorder	any number

these can either be a single argument, i.e.,:

facecolors = 'black'

or a sequence of arguments for the various bars, i.e.,:

facecolors = ('black', 'red', 'green')

Example:

(Source code, png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All positional and all keyword arguments.

matplotlib.pyplot.cla()¶

Clear the current axes.

matplotlib.pyplot.clabel(CS, *args, **kwargs)¶

Label a contour plot.

Call signature:

clabel(cs, **kwargs)

Adds labels to line contours in cs, where cs is a 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 e.g., ‘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 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.

(Source code)

(png, pdf)

(png, pdf)

(png, pdf)

(png, pdf)

(png, pdf)

(png, pdf)

matplotlib.pyplot.clf()¶

Clear the current figure.

matplotlib.pyplot.clim(vmin=None, vmax=None)¶

Set the color limits of the current image.

To apply clim to all axes images do:

clim(0, 0.5)

If either vmin or vmax is None, the image min/max respectively will be used for color scaling.

If you want to set the clim of multiple images, use, for example:

for im in gca().get_images():
    im.set_clim(0, 0.05)

matplotlib.pyplot.close(*args)¶

Close a figure window.

close() by itself closes the current figure

close(h) where h is a Figure instance, closes that figure

close(num) closes figure number num

close(name) where name is a string, closes figure with that label

close('all') closes all the figure windows

matplotlib.pyplot.cohere(x, y, NFFT=256, Fs=2, Fc=0, detrend=<function detrend_none>, window=<function window_hanning>, noverlap=0, pad_to=None, sides='default', scale_by_freq=None, hold=None, data=None, **kwargs)¶

Plot the coherence between x and y.

Plot the coherence between x and y. Coherence is the normalized cross spectral density:

Parameters:

Fs : scalar The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit. The default value is 2. window : callable or ndarray A function or a vector of length NFFT. To create window vectors see window_hanning(), window_none(), numpy.blackman(), numpy.hamming(), numpy.bartlett(), scipy.signal(), scipy.signal.get_window(), etc. The default is window_hanning(). If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment. sides : [ ‘default’ | ‘onesided’ | ‘twosided’ ] Specifies which sides of the spectrum to return. Default gives the default behavior, which returns one-sided for real data and both for complex data. ‘onesided’ forces the return of a one-sided spectrum, while ‘twosided’ forces two-sided. pad_to : integer The number of points to which the data segment is padded when performing the FFT. This can be different from NFFT, which specifies the number of data points used. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to NFFT NFFT : integer The number of data points used in each block for the FFT. A power 2 is most efficient. The default value is 256. This should NOT be used to get zero padding, or the scaling of the result will be incorrect. Use pad_to for this instead. detrend : {‘default’, ‘constant’, ‘mean’, ‘linear’, ‘none’} or callable The function applied to each segment before fft-ing, designed to remove the mean or linear trend. Unlike in MATLAB, where the detrend parameter is a vector, in matplotlib is it a function. The pylab module defines detrend_none(), detrend_mean(), and detrend_linear(), but you can use a custom function as well. You can also use a string to choose one of the functions. ‘default’, ‘constant’, and ‘mean’ call detrend_mean(). ‘linear’ calls detrend_linear(). ‘none’ calls detrend_none(). scale_by_freq : boolean, optional Specifies whether the resulting density values should be scaled by the scaling frequency, which gives density in units of Hz^-1. This allows for integration over the returned frequency values. The default is True for MATLAB compatibility. noverlap : integer The number of points of overlap between blocks. The default value is 0 (no overlap). Fc : integer The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband. **kwargs : Keyword arguments control the Line2D properties of the coherence plot: Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color or c any matplotlib color contains a callable function dash_capstyle [‘butt’ | ‘round’ | ‘projecting’] dash_joinstyle [‘miter’ | ‘round’ | ‘bevel’] dashes sequence of on/off ink in points drawstyle [‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’] gid an id string label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points marker A valid marker style markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markerfacecoloralt or mfcalt any matplotlib color markersize or ms float markevery [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float] path_effects unknown picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] sketch_params unknown snap unknown solid_capstyle [‘butt’ | ‘round’ | ‘projecting’] solid_joinstyle [‘miter’ | ‘round’ | ‘bevel’] transform a matplotlib.transforms.Transform instance url a url string visible [True | False] xdata 1D array ydata 1D array zorder any number

Returns:

The return value is a tuple (Cxy, f), where f are the frequencies of the coherence vector. kwargs are applied to the lines.

References

Bendat & Piersol – Random Data: Analysis and Measurement Procedures, John Wiley & Sons (1986)

Examples

(Source code, png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All arguments with the following names: ‘x’, ‘y’.

matplotlib.pyplot.colorbar(mappable=None, cax=None, ax=None, **kw)¶

Add a colorbar to a plot.

Function signatures for the pyplot interface; all but the first are also method signatures for the colorbar() method:

colorbar(**kwargs)
colorbar(mappable, **kwargs)
colorbar(mappable, cax=cax, **kwargs)
colorbar(mappable, ax=ax, **kwargs)

arguments:

mappable

the Image, ContourSet, etc. to which the colorbar applies; this argument is mandatory for the colorbar() method but optional for the colorbar() function, which sets the default to the current image.

keyword arguments:

cax

None | axes object into which the colorbar will be drawn

ax

None | parent axes object(s) from which space for a new colorbar axes will be stolen. If a list of axes is given they will all be resized to make room for the colorbar axes.

use_gridspec

False | If cax is None, a new cax is created as an instance of Axes. If ax is an instance of Subplot and use_gridspec is True, cax is created as an instance of Subplot using the grid_spec module.

Additional keyword arguments are of two kinds:

axes properties:

Property	Description
orientation	vertical or horizontal
fraction	0.15; fraction of original axes to use for colorbar
pad	0.05 if vertical, 0.15 if horizontal; fraction of original axes between colorbar and new image axes
shrink	1.0; fraction by which to shrink the colorbar
aspect	20; ratio of long to short dimensions
anchor	(0.0, 0.5) if vertical; (0.5, 1.0) if horizontal; the anchor point of the colorbar axes
panchor	(1.0, 0.5) if vertical; (0.5, 0.0) if horizontal; the anchor point of the colorbar parent axes. If False, the parent axes’ anchor will be unchanged

colorbar properties:

Property	Description
extend	[ ‘neither’ | ‘both’ | ‘min’ | ‘max’ ] If not ‘neither’, make pointed end(s) for out-of- range values. These are set for a given colormap using the colormap set_under and set_over methods.
extendfrac	[ None | ‘auto’ | length | lengths ] If set to None, both the minimum and maximum triangular colorbar extensions with have a length of 5% of the interior colorbar length (this is the default setting). If set to ‘auto’, makes the triangular colorbar extensions the same lengths as the interior boxes (when spacing is set to ‘uniform’) or the same lengths as the respective adjacent interior boxes (when spacing is set to ‘proportional’). If a scalar, indicates the length of both the minimum and maximum triangular colorbar extensions as a fraction of the interior colorbar length. A two-element sequence of fractions may also be given, indicating the lengths of the minimum and maximum colorbar extensions respectively as a fraction of the interior colorbar length.
extendrect	[ False | True ] If False the minimum and maximum colorbar extensions will be triangular (the default). If True the extensions will be rectangular.
spacing	[ ‘uniform’ | ‘proportional’ ] Uniform spacing gives each discrete color the same space; proportional makes the space proportional to the data interval.
ticks	[ None | list of ticks | Locator object ] If None, ticks are determined automatically from the input.
format	[ None | format string | Formatter object ] If None, the ScalarFormatter is used. If a format string is given, e.g., ‘%.3f’, that is used. An alternative Formatter object may be given instead.
drawedges	[ False | True ] If true, draw lines at color boundaries.

The following will probably be useful only in the context of indexed colors (that is, when the mappable has norm=NoNorm()), or other unusual circumstances.

Property	Description
boundaries	None or a sequence
values	None or a sequence which must be of length 1 less than the sequence of boundaries. For each region delimited by adjacent entries in boundaries, the color mapped to the corresponding value in values will be used.

If mappable is a ContourSet, its extend kwarg is included automatically.

Note that the shrink kwarg provides a simple way to keep a vertical colorbar, for example, from being taller than the axes of the mappable to which the colorbar is attached; but it is a manual method requiring some trial and error. If the colorbar is too tall (or a horizontal colorbar is too wide) use a smaller value of shrink.

For more precise control, you can manually specify the positions of the axes objects in which the mappable and the colorbar are drawn. In this case, do not use any of the axes properties kwargs.

It is known that some vector graphics viewer (svg and pdf) renders white gaps between segments of the colorbar. This is due to bugs in the viewers not matplotlib. As a workaround the colorbar can be rendered with overlapping segments:

cbar = colorbar()
cbar.solids.set_edgecolor("face")
draw()

However this has negative consequences in other circumstances. Particularly with semi transparent images (alpha < 1) and colorbar extensions and is not enabled by default see (issue #1188).

returns:

Colorbar instance; see also its base class, ColorbarBase. Call the set_label() method to label the colorbar.

matplotlib.pyplot.colors()¶

This is a do-nothing function to provide you with help on how matplotlib handles colors.

Commands which take color arguments can use several formats to specify the colors. For the basic built-in colors, you can use a single letter

Alias	Color
‘b’	blue
‘g’	green
‘r’	red
‘c’	cyan
‘m’	magenta
‘y’	yellow
‘k’	black
‘w’	white

For a greater range of colors, you have two options. You can specify the color using an html hex string, as in:

color = '#eeefff'

or you can pass an R,G,B tuple, where each of R,G,B are in the range [0,1].

You can also use any legal html name for a color, for example:

color = 'red'
color = 'burlywood'
color = 'chartreuse'

The example below creates a subplot with a dark slate gray background:

subplot(111, facecolor=(0.1843, 0.3098, 0.3098))

Here is an example that creates a pale turquoise title:

title('Is this the best color?', color='#afeeee')

matplotlib.pyplot.connect(s, func)¶

Connect event with string s to func. The signature of func is:

def func(event)

where event is a matplotlib.backend_bases.Event. The following events are recognized

• ‘button_press_event’
• ‘button_release_event’
• ‘draw_event’
• ‘key_press_event’
• ‘key_release_event’
• ‘motion_notify_event’
• ‘pick_event’
• ‘resize_event’
• ‘scroll_event’
• ‘figure_enter_event’,
• ‘figure_leave_event’,
• ‘axes_enter_event’,
• ‘axes_leave_event’
• ‘close_event’

For the location events (button and key press/release), if the mouse is over the axes, the variable event.inaxes will be set to the Axes the event occurs is over, and additionally, the variables event.xdata and event.ydata will be defined. This is the mouse location in data coords. See KeyEvent and MouseEvent for more info.

Return value is a connection id that can be used with mpl_disconnect().

Example usage:

def on_press(event):
    print('you pressed', event.button, event.xdata, event.ydata)

cid = canvas.mpl_connect('button_press_event', on_press)

matplotlib.pyplot.contour(*args, **kwargs)¶

Plot contours.

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 version in that it does not draw the polygon edges. To draw edges, add line contours with calls to contour().

Call 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)
contour(X,Y,Z,N)

contour up to N automatically-chosen levels.

contour(Z,V)
contour(X,Y,Z,V)

draw contour lines at the values specified in sequence V, which must be in increasing order.

contourf(..., V)

fill the len(V)-1 regions between the values in V, which must be in increasing order.

contour(Z, **kwargs)

Use keyword args to control colors, linewidth, origin, cmap ... see below for more details.

X and Y must both be 2-D with the same shape as Z, or they must both be 1-D such that len(X) is the number of columns in Z and len(Y) is the number of rows in Z.

C = contour(...) returns a QuadContourSet object.

Optional keyword arguments:

corner_mask: [ True | False | ‘legacy’ ]

Enable/disable corner masking, which only has an effect if Z is a masked array. If False, any quad touching a masked point is masked out. If True, only the triangular corners of quads nearest those points are always masked out, other triangular corners comprising three unmasked points are contoured as usual. If ‘legacy’, the old contouring algorithm is used, which is equivalent to False and is deprecated, only remaining whilst the new algorithm is tested fully.

If not specified, the default is taken from rcParams[‘contour.corner_mask’], which is True unless it has been modified.

colors: [ None | string | (mpl_colors) ]

If None, the colormap specified by cmap will be used.

If a string, like ‘r’ or ‘red’, all levels will be plotted in this color.

If a tuple of matplotlib color args (string, float, rgb, etc), different levels will be plotted in different colors in the order specified.

alpha: float

The alpha blending value

cmap: [ None | Colormap ]

A cm Colormap instance or None. If cmap is None and colors is None, a default Colormap is used.

norm: [ None | Normalize ]

A matplotlib.colors.Normalize instance for scaling data values to colors. If norm is None and colors is None, the default linear scaling is used.

vmin, vmax: [ None | scalar ]

If not None, either or both of these values will be supplied to the matplotlib.colors.Normalize instance, overriding the default color scaling based on levels.

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

A list of floating point numbers indicating the level curves to draw, in increasing order; e.g., to draw just the zero contour pass levels=[0]

origin: [ None | ‘upper’ | ‘lower’ | ‘image’ ]

If None, the first value of Z will correspond to the lower left corner, location (0,0). If ‘image’, the rc value for image.origin will be used.

This keyword is not active if X and Y are specified in the call to contour.

extent: [ None | (x0,x1,y0,y1) ]

If origin is not None, then extent is interpreted as in matplotlib.pyplot.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].

This keyword is not active if X and Y are specified in the call to contour.

locator: [ None | ticker.Locator subclass ]

If locator is None, the default MaxNLocator is used. The locator is used to determine the contour levels if they are not given explicitly via the V argument.

extend: [ ‘neither’ | ‘both’ | ‘min’ | ‘max’ ]

Unless this is ‘neither’, 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 matplotlib.colors.Colormap.set_under() and matplotlib.colors.Colormap.set_over() methods.

xunits, yunits: [ None | registered units ]

Override axis units by specifying an instance of a matplotlib.units.ConversionInterface.

antialiased: [ True | False ]

enable antialiasing, overriding the defaults. For filled contours, the default is True. For line contours, it is taken from rcParams[‘lines.antialiased’].

nchunk: [ 0 | integer ]

If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of nchunk by nchunk quads. Chunking reduces the maximum length of polygons generated by the contouring algorithm which reduces the rendering workload passed on to the backend and also requires slightly less RAM. It can however introduce rendering artifacts at chunk boundaries depending on the backend, the antialiased flag and value of alpha.

contour-only keyword arguments:

linewidths: [ None | number | tuple of numbers ]

If linewidths is None, the default width in lines.linewidth in matplotlibrc is used.

If a number, all levels will be plotted with this linewidth.

If a tuple, different levels will be plotted with different linewidths in the order specified.

linestyles: [ None | ‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’ ]

If linestyles is None, the default is ‘solid’ unless the lines are monochrome. In that case, negative contours will take their linestyle from the matplotlibrc contour.negative_linestyle setting.

linestyles can also be an iterable of the above strings specifying a set of linestyles to be used. If this iterable is shorter than the number of contour levels it will be repeated as necessary.

contourf-only keyword arguments:

hatches:

A list of cross hatch patterns to use on the filled areas. If None, no hatching will be added to the contour. Hatching is supported in the PostScript, PDF, SVG and Agg backends only.

Note: contourf fills intervals that are closed at the top; that is, for boundaries z1 and z2, the filled region is:

z1 < z <= z2

There is one exception: if the lowest boundary coincides with the minimum value of the z array, then that minimum value will be included in the lowest interval.

Examples:

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matplotlib.pyplot.contourf(*args, **kwargs)¶

Plot contours.

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 version in that it does not draw the polygon edges. To draw edges, add line contours with calls to contour().

Call 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)
contour(X,Y,Z,N)

contour up to N automatically-chosen levels.

contour(Z,V)
contour(X,Y,Z,V)

draw contour lines at the values specified in sequence V, which must be in increasing order.

contourf(..., V)

fill the len(V)-1 regions between the values in V, which must be in increasing order.

contour(Z, **kwargs)

Use keyword args to control colors, linewidth, origin, cmap ... see below for more details.

X and Y must both be 2-D with the same shape as Z, or they must both be 1-D such that len(X) is the number of columns in Z and len(Y) is the number of rows in Z.

C = contour(...) returns a QuadContourSet object.

Optional keyword arguments:

corner_mask: [ True | False | ‘legacy’ ]

Enable/disable corner masking, which only has an effect if Z is a masked array. If False, any quad touching a masked point is masked out. If True, only the triangular corners of quads nearest those points are always masked out, other triangular corners comprising three unmasked points are contoured as usual. If ‘legacy’, the old contouring algorithm is used, which is equivalent to False and is deprecated, only remaining whilst the new algorithm is tested fully.

If not specified, the default is taken from rcParams[‘contour.corner_mask’], which is True unless it has been modified.

colors: [ None | string | (mpl_colors) ]

If None, the colormap specified by cmap will be used.

If a string, like ‘r’ or ‘red’, all levels will be plotted in this color.

If a tuple of matplotlib color args (string, float, rgb, etc), different levels will be plotted in different colors in the order specified.

alpha: float

The alpha blending value

cmap: [ None | Colormap ]

A cm Colormap instance or None. If cmap is None and colors is None, a default Colormap is used.

norm: [ None | Normalize ]

A matplotlib.colors.Normalize instance for scaling data values to colors. If norm is None and colors is None, the default linear scaling is used.

vmin, vmax: [ None | scalar ]

If not None, either or both of these values will be supplied to the matplotlib.colors.Normalize instance, overriding the default color scaling based on levels.

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

A list of floating point numbers indicating the level curves to draw, in increasing order; e.g., to draw just the zero contour pass levels=[0]

origin: [ None | ‘upper’ | ‘lower’ | ‘image’ ]

If None, the first value of Z will correspond to the lower left corner, location (0,0). If ‘image’, the rc value for image.origin will be used.

This keyword is not active if X and Y are specified in the call to contour.

extent: [ None | (x0,x1,y0,y1) ]

If origin is not None, then extent is interpreted as in matplotlib.pyplot.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].

This keyword is not active if X and Y are specified in the call to contour.

locator: [ None | ticker.Locator subclass ]

If locator is None, the default MaxNLocator is used. The locator is used to determine the contour levels if they are not given explicitly via the V argument.

extend: [ ‘neither’ | ‘both’ | ‘min’ | ‘max’ ]

Unless this is ‘neither’, 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 matplotlib.colors.Colormap.set_under() and matplotlib.colors.Colormap.set_over() methods.

xunits, yunits: [ None | registered units ]

Override axis units by specifying an instance of a matplotlib.units.ConversionInterface.

antialiased: [ True | False ]

enable antialiasing, overriding the defaults. For filled contours, the default is True. For line contours, it is taken from rcParams[‘lines.antialiased’].

nchunk: [ 0 | integer ]

If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of nchunk by nchunk quads. Chunking reduces the maximum length of polygons generated by the contouring algorithm which reduces the rendering workload passed on to the backend and also requires slightly less RAM. It can however introduce rendering artifacts at chunk boundaries depending on the backend, the antialiased flag and value of alpha.

contour-only keyword arguments:

linewidths: [ None | number | tuple of numbers ]

If linewidths is None, the default width in lines.linewidth in matplotlibrc is used.

If a number, all levels will be plotted with this linewidth.

If a tuple, different levels will be plotted with different linewidths in the order specified.

linestyles: [ None | ‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’ ]

If linestyles is None, the default is ‘solid’ unless the lines are monochrome. In that case, negative contours will take their linestyle from the matplotlibrc contour.negative_linestyle setting.

linestyles can also be an iterable of the above strings specifying a set of linestyles to be used. If this iterable is shorter than the number of contour levels it will be repeated as necessary.

contourf-only keyword arguments:

hatches:

A list of cross hatch patterns to use on the filled areas. If None, no hatching will be added to the contour. Hatching is supported in the PostScript, PDF, SVG and Agg backends only.

Note: contourf fills intervals that are closed at the top; that is, for boundaries z1 and z2, the filled region is:

z1 < z <= z2

There is one exception: if the lowest boundary coincides with the minimum value of the z array, then that minimum value will be included in the lowest interval.

Examples:

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matplotlib.pyplot.cool()¶

set the default colormap to cool and apply to current image if any. See help(colormaps) for more information

matplotlib.pyplot.copper()¶

set the default colormap to copper and apply to current image if any. See help(colormaps) for more information

matplotlib.pyplot.csd(x, y, NFFT=None, Fs=None, Fc=None, detrend=None, window=None, noverlap=None, pad_to=None, sides=None, scale_by_freq=None, return_line=None, hold=None, data=None, **kwargs)¶

Plot the cross-spectral density.

Call signature:

csd(x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
    window=mlab.window_hanning, noverlap=0, pad_to=None,
    sides='default', scale_by_freq=None, return_line=None, **kwargs)

The cross spectral density by Welch’s average periodogram method. The vectors x and y are divided into NFFT length segments. Each segment is detrended by function detrend and windowed by function window. noverlap gives the length of the overlap between segments. The product of the direct FFTs of x and y are averaged over each segment to compute , with a scaling to correct for power loss due to windowing.

If len(x) < NFFT or len(y) < NFFT, they will be zero padded to NFFT.

Parameters:

x, y : 1-D arrays or sequences Arrays or sequences containing the data Fs : scalar The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit. The default value is 2. window : callable or ndarray A function or a vector of length NFFT. To create window vectors see window_hanning(), window_none(), numpy.blackman(), numpy.hamming(), numpy.bartlett(), scipy.signal(), scipy.signal.get_window(), etc. The default is window_hanning(). If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment. sides : [ ‘default’ | ‘onesided’ | ‘twosided’ ] Specifies which sides of the spectrum to return. Default gives the default behavior, which returns one-sided for real data and both for complex data. ‘onesided’ forces the return of a one-sided spectrum, while ‘twosided’ forces two-sided. pad_to : integer The number of points to which the data segment is padded when performing the FFT. This can be different from NFFT, which specifies the number of data points used. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to NFFT NFFT : integer The number of data points used in each block for the FFT. A power 2 is most efficient. The default value is 256. This should NOT be used to get zero padding, or the scaling of the result will be incorrect. Use pad_to for this instead. detrend : {‘default’, ‘constant’, ‘mean’, ‘linear’, ‘none’} or callable The function applied to each segment before fft-ing, designed to remove the mean or linear trend. Unlike in MATLAB, where the detrend parameter is a vector, in matplotlib is it a function. The pylab module defines detrend_none(), detrend_mean(), and detrend_linear(), but you can use a custom function as well. You can also use a string to choose one of the functions. ‘default’, ‘constant’, and ‘mean’ call detrend_mean(). ‘linear’ calls detrend_linear(). ‘none’ calls detrend_none(). scale_by_freq : boolean, optional Specifies whether the resulting density values should be scaled by the scaling frequency, which gives density in units of Hz^-1. This allows for integration over the returned frequency values. The default is True for MATLAB compatibility. noverlap : integer The number of points of overlap between segments. The default value is 0 (no overlap). Fc : integer The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband. return_line : bool Whether to include the line object plotted in the returned values. Default is False. **kwargs : Keyword arguments control the Line2D properties: Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color or c any matplotlib color contains a callable function dash_capstyle [‘butt’ | ‘round’ | ‘projecting’] dash_joinstyle [‘miter’ | ‘round’ | ‘bevel’] dashes sequence of on/off ink in points drawstyle [‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’] gid an id string label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points marker A valid marker style markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markerfacecoloralt or mfcalt any matplotlib color markersize or ms float markevery [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float] path_effects unknown picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] sketch_params unknown snap unknown solid_capstyle [‘butt’ | ‘round’ | ‘projecting’] solid_joinstyle [‘miter’ | ‘round’ | ‘bevel’] transform a matplotlib.transforms.Transform instance url a url string visible [True | False] xdata 1D array ydata 1D array zorder any number

Returns:

Pxy : 1-D array The values for the cross spectrum P_{xy} before scaling (complex valued) freqs : 1-D array The frequencies corresponding to the elements in Pxy line : a Line2D instance The line created by this function. Only returned if return_line is True.

See also

psd()

psd() is the equivalent to setting y=x.

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]: * All arguments with the following names: ‘x’, ‘y’.

Notes

For plotting, the power is plotted as for decibels, though P_{xy} itself is returned.

References

Bendat & Piersol – Random Data: Analysis and Measurement Procedures, John Wiley & Sons (1986)

Examples

(Source code, png, pdf)

matplotlib.pyplot.delaxes(*args)¶

Remove an axes from the current figure. If ax doesn’t exist, an error will be raised.

delaxes(): delete the current axes

matplotlib.pyplot.disconnect(cid)¶

Disconnect callback id cid

Example usage:

cid = canvas.mpl_connect('button_press_event', on_press)
#...later
canvas.mpl_disconnect(cid)

matplotlib.pyplot.draw()¶

Redraw the current figure.

This is used to update a figure that has been altered, but not automatically re-drawn. If interactive mode is on (ion()), this should be only rarely needed, but there may be ways to modify the state of a figure without marking it as stale. Please report these cases as bugs.

A more object-oriented alternative, given any Figure instance, fig, that was created using a pyplot function, is:

fig.canvas.draw_idle()

matplotlib.pyplot.errorbar(x, y, yerr=None, xerr=None, fmt='', ecolor=None, elinewidth=None, capsize=None, barsabove=False, lolims=False, uplims=False, xlolims=False, xuplims=False, errorevery=1, capthick=None, hold=None, data=None, **kwargs)¶

Plot an errorbar graph.

Plot x versus y with error deltas in yerr and xerr. Vertical errorbars are plotted if yerr is not None. Horizontal errorbars are plotted if xerr is not None.

x, y, xerr, and yerr can all be scalars, which plots a single error bar at x, y.

Parameters:	x : scalar or array-like y : scalar or array-like xerr/yerr : scalar or array-like, shape(N,) or shape(2,N), optional If a scalar number, len(N) array-like object, or a N-element array-like object, errorbars are drawn at +/-value relative to the data. Default is None. If a sequence of shape 2xN, errorbars are drawn at -row1 and +row2 relative to the data. fmt : plot format string, optional, default: None The plot format symbol. If fmt is ‘none’ (case-insensitive), only the errorbars are plotted. This is used for adding errorbars to a bar plot, for example. Default is ‘’, an empty plot format string; properties are then identical to the defaults for plot(). ecolor : mpl color, optional, default: None A matplotlib color arg which gives the color the errorbar lines; if None, use the color of the line connecting the markers. elinewidth : scalar, optional, default: None The linewidth of the errorbar lines. If None, use the linewidth. capsize : scalar, optional, default: None The length of the error bar caps in points; if None, it will take the value from errorbar.capsize rcParam. capthick : scalar, optional, default: None An alias kwarg to markeredgewidth (a.k.a. - mew). This setting is a more sensible name for the property that controls the thickness of the error bar cap in points. For backwards compatibility, if mew or markeredgewidth are given, then they will over-ride capthick. This may change in future releases. barsabove : bool, optional, default: False if True , will plot the errorbars above the plot symbols. Default is below. lolims / uplims / xlolims / xuplims : bool, optional, default:None These arguments can be used to indicate that a value gives only upper/lower limits. In that case a caret symbol is used to indicate this. lims-arguments may be of the same type as xerr and yerr. To use limits with inverted axes, set_xlim() or set_ylim() must be called before errorbar(). errorevery : positive integer, optional, default:1 subsamples the errorbars. e.g., if errorevery=5, errorbars for every 5-th datapoint will be plotted. The data plot itself still shows all data points.
Returns:	plotline : Line2D instance x, y plot markers and/or line caplines : list of Line2D instances error bar cap barlinecols : list of LineCollection horizontal and vertical error ranges.
Other Parameters:
	kwargs : All other keyword arguments are passed on to the plot command for the markers. For example, this code makes big red squares with thick green edges: x,y,yerr = rand(3,10) errorbar(x, y, yerr, marker='s', mfc='red', mec='green', ms=20, mew=4) where mfc, mec, ms and mew are aliases for the longer property names, markerfacecolor, markeredgecolor, markersize and markeredgewidth. valid kwargs for the marker properties are Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color or c any matplotlib color contains a callable function dash_capstyle [‘butt’ | ‘round’ | ‘projecting’] dash_joinstyle [‘miter’ | ‘round’ | ‘bevel’] dashes sequence of on/off ink in points drawstyle [‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’ | ‘none’] gid an id string label string or anything printable with ‘%s’ conversion. linestyle or ls [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) | '-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points marker A valid marker style markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markerfacecoloralt or mfcalt any matplotlib color markersize or ms float markevery [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float] path_effects unknown picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] sketch_params unknown snap unknown solid_capstyle [‘butt’ | ‘round’ | ‘projecting’] solid_joinstyle [‘miter’ | ‘round’ | ‘bevel’] transform a matplotlib.transforms.Transform instance url a url string visible [True | False] xdata 1D array ydata 1D array zorder any number

Examples

(Source code, png, pdf)

Note

In addition to the above described arguments, this function can take a data keyword argument. If such a data argument is given, the following arguments are replaced by data[<arg>]:

• All arguments with the following names: ‘x’, ‘xerr’, ‘y’, ‘yerr’.