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)
Plot the autocorrelation of x.
| Parameters: | x : sequence of scalar hold : boolean, optional, default: True detrend : callable, optional, default: mlab.detrend_none
normed : boolean, optional, default: True
usevlines : boolean, optional, default: True
maxlags : integer, optional, default: 10
|
|---|---|
| Returns: | (lags, c, line, b) : where: |
| Other Parameters: | |
linestyle : Line2D prop, optional, default: None
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)
Additional kwargs: hold = [True|False] overrides default hold state
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.
- x: 1-D array or sequence
- Array or sequence containing the data
Keyword arguments:
- 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.
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).
Returns the tuple (spectrum, freqs, line):
- 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
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Create an annotation: a piece of text referring to a data point.
| Parameters: | s : string
xy : (x, y)
xytext : (x, y) , optional, default: None
xycoords : string, optional, default: “data”
textcoords : string, optional
arrowprops : matplotlib.lines.Line2D properties, optional
|
|---|---|
| Returns: | a : Annotation |
Notes
arrowprops, if not None, is a dictionary of line properties (see matplotlib.lines.Line2D) for the arrow that connects annotation to the point.
If the dictionary has a key arrowstyle, a FancyArrowPatch instance is created with the given dictionary and is drawn. Otherwise, a YAArrow patch instance is created and drawn. Valid keys for YAArrow are:
| Key | Description |
|---|---|
| width | the width of the arrow in points |
| frac | the fraction of the arrow length occupied by the head |
| headwidth | the width of the base of the arrow head in points |
| shrink | oftentimes it is convenient to have the arrowtip and base a bit away from the text and point being annotated. If d is the distance between the text and annotated point, shrink will shorten the arrow so the tip and base are shink percent of the distance d away from the endpoints. i.e., shrink=0.05 is 5% |
| ? | any key for matplotlib.patches.polygon |
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 |
xycoords and textcoords are strings that indicate the coordinates of xy and xytext, and may be one of the following values:
| Property | Description |
|---|---|
| ‘figure points’ | points from the lower left corner of the figure |
| ‘figure pixels’ | pixels from the lower left corner of the figure |
| ‘figure fraction’ | 0,0 is lower left of figure and 1,1 is upper right |
| ‘axes points’ | points from lower left corner of axes |
| ‘axes pixels’ | pixels from lower left corner of axes |
| ‘axes fraction’ | 0,0 is lower left of axes and 1,1 is upper right |
| ‘data’ | use the coordinate system of the object being annotated (default) |
| ‘offset points’ | Specify an offset (in points) from the xy value |
| ‘polar’ | you can specify theta, r for the annotation, even in cartesian plots. Note that if you are using a polar axes, you do not need to specify polar for the coordinate system since that is the native “data” coordinate system. |
If a ‘points’ or ‘pixels’ option is specified, values will be added to the bottom-left and if negative, values will be subtracted from the top-right. e.g.:
# 10 points to the right of the left border of the axes and
# 5 points below the top border
xy=(10,-5), xycoords='axes points'
You may use an instance of Transform or Artist. See Annotating Axes for more details.
The annotation_clip attribute 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”.
Additional kwargs are Text properties:
Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] axes an Axes instance backgroundcolor any matplotlib color bbox rectangle prop dict clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color any matplotlib color contains a callable function family or fontfamily or fontname or name [FONTNAME | ‘serif’ | ‘sans-serif’ | ‘cursive’ | ‘fantasy’ | ‘monospace’ ] figure a matplotlib.figure.Figure instance fontproperties or font_properties a matplotlib.font_manager.FontProperties instance gid an id string horizontalalignment or ha [ ‘center’ | ‘right’ | ‘left’ ] label string or anything printable with ‘%s’ conversion. linespacing float (multiple of font size) lod [True | False] multialignment [‘left’ | ‘right’ | ‘center’ ] path_effects unknown picker [None|float|boolean|callable] position (x,y) rasterized [True | False | None] rotation [ angle in degrees | ‘vertical’ | ‘horizontal’ ] rotation_mode unknown size or fontsize [size in points | ‘xx-small’ | ‘x-small’ | ‘small’ | ‘medium’ | ‘large’ | ‘x-large’ | ‘xx-large’ ] sketch_params unknown snap unknown stretch or fontstretch [a numeric value in range 0-1000 | ‘ultra-condensed’ | ‘extra-condensed’ | ‘condensed’ | ‘semi-condensed’ | ‘normal’ | ‘semi-expanded’ | ‘expanded’ | ‘extra-expanded’ | ‘ultra-expanded’ ] style or fontstyle [ ‘normal’ | ‘italic’ | ‘oblique’] text string or anything printable with ‘%s’ conversion. transform Transform instance url a url string usetex unknown variant or fontvariant [ ‘normal’ | ‘small-caps’ ] verticalalignment or va or ma [ ‘center’ | ‘top’ | ‘bottom’ | ‘baseline’ ] visible [True | False] weight or fontweight [a numeric value in range 0-1000 | ‘ultralight’ | ‘light’ | ‘normal’ | ‘regular’ | ‘book’ | ‘medium’ | ‘roman’ | ‘semibold’ | ‘demibold’ | ‘demi’ | ‘bold’ | ‘heavy’ | ‘extra bold’ | ‘black’ ] x float y float zorder any number
Examples
(png)
(png)
Add an arrow to the axes.
Call signature:
arrow(x, y, dx, dy, **kwargs)
Draws arrow on specified axis from (x, y) to (x + dx, y + dy). Uses FancyArrow patch to construct the arrow.
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="->"))
Optional kwargs control the arrow construction and properties:
Other valid kwargs (inherited from 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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
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.
Returns None.
set the default colormap to autumn and apply to current image if any. See help(colormaps) for more information
Add an axes to the figure.
The axes is added at position rect specified by:
| kwarg | Accepts | Description |
|---|---|---|
| axisbg | 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:
Add a horizontal line across the axis.
| Parameters: | y : scalar, optional, default: 0
xmin : scalar, optional, default: 0
xmax : scalar, optional, default: 1
|
|---|---|
| Returns: |
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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Add a horizontal span (rectangle) across the axis.
Call signature:
axhspan(ymin, ymax, xmin=0, xmax=1, **kwargs)
y coords are in data units and x coords are in axes (relative 0-1) units.
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.
Return value is a matplotlib.patches.Polygon instance.
Examples:
draw a gray rectangle from y = 0.25-0.75 that spans the horizontal extent of the axes:
>>> axhspan(0.25, 0.75, facecolor='0.5', alpha=0.5)
Valid kwargs are 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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
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.
The xmin, xmax, ymin, ymax tuple is returned
Add a vertical line across the axes.
| Parameters: | x : scalar, optional, default: 0
ymin : scalar, optional, default: 0
ymax : scalar, optional, default: 1
|
|---|---|
| Returns: |
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 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Add a vertical span (rectangle) across the axes.
Call signature:
axvspan(xmin, xmax, ymin=0, ymax=1, **kwargs)
x coords are in data units and y coords are in axes (relative 0-1) units.
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.
Return value is the matplotlib.patches.Polygon instance.
Examples:
draw a vertical green translucent rectangle from x=1.25 to 1.55 that spans the yrange of the axes:
>>> axvspan(1.25, 1.55, facecolor='g', alpha=0.5)
Valid kwargs are 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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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
Additional kwargs: hold = [True|False] overrides default hold state
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
height : sequence of scalars
width : scalar or array-like, optional, default: 0.8
bottom : scalar or array-like, optional, default: None
color : scalar or array-like, optional
edgecolor : scalar or array-like, optional
linewidth : scalar or array-like, optional, default: None
xerr : scalar or array-like, optional, default: None
yerr : scalar or array-like, optional, default: None
ecolor : scalar or array-like, optional, default: None
capsize : integer, optional, default: 3
error_kw :
align : [‘edge’ | ‘center’], optional, default: ‘edge’
orientation : ‘vertical’ | ‘horizontal’, optional, default: ‘vertical’
log : boolean, optional, default: False
|
|---|---|
| Returns: | matplotlib.patches.Rectangle instances. |
See also
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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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)
Additional kwargs: hold = [True|False] overrides default hold state
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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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:
(png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
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
width : scalar or array-like
height : sequence of scalars, optional, default: 0.8
left : sequence of scalars
|
|---|---|
| Returns: | matplotlib.patches.Rectangle instances. |
| Other Parameters: | |
color : scalar or array-like, optional
edgecolor : scalar or array-like, optional
linewidth : scalar or array-like, optional, default: None
xerr : scalar or array-like, optional, default: None
yerr : scalar or array-like, optional, default: None
ecolor : scalar or array-like, optional, default: None
capsize : integer, optional, default: 3
error_kw :
align : [‘edge’ | ‘center’], optional, default: ‘edge’
orientation : ‘vertical’ | ‘horizontal’, optional, default: ‘vertical’
log : boolean, optional, default: False
|
|
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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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
set the default colormap to bone and apply to current image if any. See help(colormaps) for more information
Turn the axes box on or off. on may be a boolean or a string, ‘on’ or ‘off’.
If on is None, toggle state.
Make a box and whisker plot.
Call signature:
boxplot(self, x, notch=False, sym='b+', vert=True, whis=1.5,
positions=None, widths=None, patch_artist=False,
bootstrap=None, usermedians=None, conf_intervals=None,
meanline=False, showmeans=False, showcaps=True,
showbox=True, showfliers=True, boxprops=None, labels=None,
flierprops=None, medianprops=None, meanprops=None,
capprops=None, whiskerprops=None, manage_xticks=True):
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.
|
|---|---|
| Returns: | result : dict
|
Examples
(Source code, png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
Plot horizontal bars.
Call signature:
broken_barh(self, xranges, yrange, **kwargs)
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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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)
Additional kwargs: hold = [True|False] overrides default hold state
Clear the current axes.
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.
(png)
(png)
(png)
(png)
(png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
Clear the current figure.
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)
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
Plot the coherence between x and y.
Call signature:
cohere(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, **kwargs)
Plot the coherence between x and y. Coherence is the normalized cross spectral density:
Keyword arguments:
- 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.
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().
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.
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)
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
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).
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, axisbg=(0.1843, 0.3098, 0.3098))
Here is an example that creates a pale turquoise title:
title('Is this the best color?', color='#afeeee')
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
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)
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 N automatically-chosen levels.
contour(Z,V)
contour(X,Y,Z,V)
draw contour lines at the values specified in sequence V
contourf(..., V)
fill the len(V)-1 regions between the values in V
contour(Z, **kwargs)
Use keyword args to control colors, linewidth, origin, cmap ... see below 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:
- 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; 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’].
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:
- nchunk: [ 0 | integer ]
- If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of roughly nchunk by nchunk points. This may never actually be advantageous, so this option may be removed. Chunking introduces artifacts at the chunk boundaries unless antialiased is False.
- 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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Additional kwargs: hold = [True|False] overrides default hold state
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 N automatically-chosen levels.
contour(Z,V)
contour(X,Y,Z,V)
draw contour lines at the values specified in sequence V
contourf(..., V)
fill the len(V)-1 regions between the values in V
contour(Z, **kwargs)
Use keyword args to control colors, linewidth, origin, cmap ... see below 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:
- 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; 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’].
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:
- nchunk: [ 0 | integer ]
- If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of roughly nchunk by nchunk points. This may never actually be advantageous, so this option may be removed. Chunking introduces artifacts at the chunk boundaries unless antialiased is False.
- 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:
(png)
(png)
(png)
(png)
(png)
(png)
(png)
(png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
set the default colormap to cool and apply to current image if any. See help(colormaps) for more information
set the default colormap to copper and apply to current image if any. See help(colormaps) for more information
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.
- x, y: 1-D arrays or sequences
- Arrays or sequences containing the data
Keyword arguments:
- 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.
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().
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.
If return_line is False, returns the tuple (Pxy, freqs). If return_line is True, returns the tuple (Pxy, freqs. line):
- 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 returend if return_line is True.
For plotting, the power is plotted as
for decibels, though P_{xy} itself
is returned.
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Remove an axes from the current figure. If ax doesn’t exist, an error will be raised.
delaxes(): delete the current axes
Disconnect callback id cid
Example usage:
cid = canvas.mpl_connect('button_press_event', on_press)
#...later
canvas.mpl_disconnect(cid)
Redraw the current figure.
This is used in interactive mode to update a figure that has been altered using one or more plot object method calls; it is not needed if figure modification is done entirely with pyplot functions, if a sequence of modifications ends with a pyplot function, or if matplotlib is in non-interactive mode and the sequence of modifications ends with show() or savefig().
A more object-oriented alternative, given any Figure instance, fig, that was created using a pyplot function, is:
fig.canvas.draw()
Plot an errorbar graph.
Call signature:
errorbar(x, y, yerr=None, xerr=None,
fmt='', ecolor=None, elinewidth=None, capsize=3,
barsabove=False, lolims=False, uplims=False,
xlolims=False, xuplims=False, errorevery=1,
capthick=None)
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.
Optional keyword arguments:
- xerr/yerr: [ scalar | N, Nx1, or 2xN array-like ]
If a scalar number, len(N) array-like object, or an Nx1 array-like object, errorbars are drawn at +/-value relative to the data.
If a sequence of shape 2xN, errorbars are drawn at -row1 and +row2 relative to the data.
- fmt: [ ‘’ | ‘none’ | plot format string ]
- 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: [ None | mpl color ]
- A matplotlib color arg which gives the color the errorbar lines; if None, use the color of the line connecting the markers.
- elinewidth: scalar
- The linewidth of the errorbar lines. If None, use the linewidth.
- capsize: scalar
- The length of the error bar caps in points
- capthick: scalar
- 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: [ True | False ]
- if True, will plot the errorbars above the plot symbols. Default is below.
- lolims / uplims / xlolims / xuplims: [ False | True ]
- 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
- subsamples the errorbars. e.g., if everyerror=5, errorbars for every 5-th datapoint will be plotted. The data plot itself still shows all data points.
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 markeredgewith.
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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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 (plotline, caplines, barlinecols):
- plotline: Line2D instance
- x, y plot markers and/or line
- caplines: list of error bar cap
- Line2D instances
- barlinecols: list of
- LineCollection instances for the horizontal and vertical error ranges.
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Plot identical parallel lines at specific positions.
Call signature:
eventplot(positions, orientation='horizontal', lineoffsets=0,
linelengths=1, linewidths=None, color =None,
linestyles='solid'
Plot parallel lines at the given positions. positions should be a 1D or 2D array-like object, with each row corresponding to a row or column of lines.
This type of plot is commonly used in neuroscience for representing neural events, where it is commonly called a spike raster, dot raster, or raster plot.
However, it is useful in any situation where you wish to show the timing or position of multiple sets of discrete events, such as the arrival times of people to a business on each day of the month or the date of hurricanes each year of the last century.
For linelengths, linewidths, colors, and linestyles, if only a single value is given, that value is applied to all lines. If an array-like is given, it must have the same length as positions, and each value will be applied to the corresponding row or column in positions.
Returns a list of matplotlib.collections.EventCollection objects that were added.
kwargs are LineCollection 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] norm unknown offset_position unknown offsets float or sequence of floats path_effects unknown paths unknown picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] segments unknown sketch_params unknown snap unknown transform Transform instance url a url string urls unknown verts unknown visible [True | False] zorder any number
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Adds a non-resampled image to the figure.
call signatures:
figimage(X, **kwargs)
adds a non-resampled array X to the figure.
figimage(X, xo, yo)
with pixel offsets xo, yo,
X must be a float array:
Optional keyword arguments:
Keyword Description xo or yo An integer, the x and y image offset in pixels cmap a matplotlib.colors.Colormap instance, e.g., cm.jet. If None, default to the rc image.cmap value norm a matplotlib.colors.Normalize instance. The default is normalization(). This scales luminance -> 0-1 vmin|vmax are used to scale a luminance image to 0-1. If either is None, the min and max of the luminance values will be used. Note if you pass a norm instance, the settings for vmin and vmax will be ignored. alpha the alpha blending value, default is None origin [ ‘upper’ | ‘lower’ ] Indicates where the [0,0] index of the array is in the upper left or lower left corner of the axes. Defaults to the rc image.origin value
figimage complements the axes image (imshow()) which will be resampled to fit the current axes. If you want a resampled image to fill the entire figure, you can define an Axes with size [0,1,0,1].
An matplotlib.image.FigureImage instance is returned.
(Source code, png)
Additional kwargs are Artist kwargs passed on to FigureImage Addition kwargs: hold = [True|False] overrides default hold state
Place a legend in the figure.
A matplotlib.legend.Legend instance is returned.
Example:
figlegend( (line1, line2, line3),
('label1', 'label2', 'label3'),
'upper right' )
See also
Add text to figure.
Call signature:
text(x, y, s, fontdict=None, **kwargs)
Add text to figure at location x, y (relative 0-1 coords). See text() for the meaning of the other arguments.
kwargs control the Text properties:
Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] axes an Axes instance backgroundcolor any matplotlib color bbox rectangle prop dict clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color any matplotlib color contains a callable function family or fontfamily or fontname or name [FONTNAME | ‘serif’ | ‘sans-serif’ | ‘cursive’ | ‘fantasy’ | ‘monospace’ ] figure a matplotlib.figure.Figure instance fontproperties or font_properties a matplotlib.font_manager.FontProperties instance gid an id string horizontalalignment or ha [ ‘center’ | ‘right’ | ‘left’ ] label string or anything printable with ‘%s’ conversion. linespacing float (multiple of font size) lod [True | False] multialignment [‘left’ | ‘right’ | ‘center’ ] path_effects unknown picker [None|float|boolean|callable] position (x,y) rasterized [True | False | None] rotation [ angle in degrees | ‘vertical’ | ‘horizontal’ ] rotation_mode unknown size or fontsize [size in points | ‘xx-small’ | ‘x-small’ | ‘small’ | ‘medium’ | ‘large’ | ‘x-large’ | ‘xx-large’ ] sketch_params unknown snap unknown stretch or fontstretch [a numeric value in range 0-1000 | ‘ultra-condensed’ | ‘extra-condensed’ | ‘condensed’ | ‘semi-condensed’ | ‘normal’ | ‘semi-expanded’ | ‘expanded’ | ‘extra-expanded’ | ‘ultra-expanded’ ] style or fontstyle [ ‘normal’ | ‘italic’ | ‘oblique’] text string or anything printable with ‘%s’ conversion. transform Transform instance url a url string usetex unknown variant or fontvariant [ ‘normal’ | ‘small-caps’ ] verticalalignment or va or ma [ ‘center’ | ‘top’ | ‘bottom’ | ‘baseline’ ] visible [True | False] weight or fontweight [a numeric value in range 0-1000 | ‘ultralight’ | ‘light’ | ‘normal’ | ‘regular’ | ‘book’ | ‘medium’ | ‘roman’ | ‘semibold’ | ‘demibold’ | ‘demi’ | ‘bold’ | ‘heavy’ | ‘extra bold’ | ‘black’ ] x float y float zorder any number
Creates a new figure.
| Parameters: | num : integer or string, optional, default: none
figsize : tuple of integers, optional, default: None
dpi : integer, optional, default: None
facecolor :
edgecolor :
|
|---|---|
| Returns: | figure : Figure
|
Notes
If you are creating many figures, make sure you explicitly call “close” on the figures you are not using, because this will enable pylab to properly clean up the memory.
rcParams defines the default values, which can be modified in the matplotlibrc file
Plot filled polygons.
Call signature:
fill(*args, **kwargs)
args is a variable length argument, allowing for multiple x, y pairs with an optional color format string; see plot() for details on the argument parsing. For example, to plot a polygon with vertices at x, y in blue.:
ax.fill(x,y, 'b' )
An arbitrary number of x, y, color groups can be specified:
ax.fill(x1, y1, 'g', x2, y2, 'r')
Return value is a list of Patch instances that were added.
The same color strings that plot() supports are supported by the fill format string.
If you would like to fill below a curve, e.g., shade a region between 0 and y along x, use fill_between()
The closed kwarg will close the polygon when True (default).
kwargs control the 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, or None for default, or ‘none’ for no color 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’] linewidth or lw float or None for default lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Make filled polygons between two curves.
Call signature:
fill_between(x, y1, y2=0, where=None, **kwargs)
Create a PolyCollection filling the regions between y1 and y2 where where==True
- x :
- An N-length array of the x data
- y1 :
- An N-length array (or scalar) of the y data
- y2 :
- An N-length array (or scalar) of the y data
- where :
- If None, default to fill between everywhere. If not None, it is an N-length numpy boolean array and the fill will only happen over the regions where where==True.
- interpolate :
- If True, interpolate between the two lines to find the precise point of intersection. Otherwise, the start and end points of the filled region will only occur on explicit values in the x array.
- kwargs :
- Keyword args passed on to the PolyCollection.
kwargs control the Polygon 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
(png)
(png)
(png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Make filled polygons between two horizontal curves.
Call signature:
fill_betweenx(y, x1, x2=0, where=None, **kwargs)
Create a PolyCollection filling the regions between x1 and x2 where where==True
- y :
- An N-length array of the y data
- x1 :
- An N-length array (or scalar) of the x data
- x2 :
- An N-length array (or scalar) of the x data
- where :
- If None, default to fill between everywhere. If not None, it is a N length numpy boolean array and the fill will only happen over the regions where where==True
- kwargs :
- keyword args passed on to the PolyCollection
kwargs control the Polygon 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
(png)
(png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Find artist objects.
Recursively find all Artist instances contained in self.
match can be
- None: return all objects contained in artist.
- function with signature boolean = match(artist) used to filter matches
- class instance: e.g., Line2D. Only return artists of class type.
If include_self is True (default), include self in the list to be checked for a match.
set the default colormap to flag and apply to current image if any. See help(colormaps) for more information
Get the current Axes instance on the current figure matching the given keyword args, or create one.
See also
Examples
To get the current polar axes on the current figure:
plt.gca(projection='polar')
If the current axes doesn’t exist, or isn’t a polar one, the appropriate axes will be created and then returned.
Get a reference to the current figure.
Get the current colorable artist. Specifically, returns the current ScalarMappable instance (image or patch collection), or None if no images or patch collections have been defined. The commands imshow() and figimage() create Image instances, and the commands pcolor() and scatter() create Collection instances. The current image is an attribute of the current axes, or the nearest earlier axes in the current figure that contains an image.
Return a list of existing figure labels.
Return a list of existing figure numbers.
Get a sorted list of all of the plotting commands.
Call signature:
ginput(self, n=1, timeout=30, show_clicks=True,
mouse_add=1, mouse_pop=3, mouse_stop=2)
Blocking call to interact with the figure.
This will wait for n clicks from the user and return a list of the coordinates of each click.
If timeout is zero or negative, does not timeout.
If n is zero or negative, accumulate clicks until a middle click (or potentially both mouse buttons at once) terminates the input.
Right clicking cancels last input.
The buttons used for the various actions (adding points, removing points, terminating the inputs) can be overriden via the arguments mouse_add, mouse_pop and mouse_stop, that give the associated mouse button: 1 for left, 2 for middle, 3 for right.
The keyboard can also be used to select points in case your mouse does not have one or more of the buttons. The delete and backspace keys act like right clicking (i.e., remove last point), the enter key terminates input and any other key (not already used by the window manager) selects a point.
set the default colormap to gray and apply to current image if any. See help(colormaps) for more information
Turn the axes grids on or off.
Call signature:
grid(self, b=None, which='major', axis='both', **kwargs)
Set the axes grids on or off; b is a boolean. (For MATLAB compatibility, b may also be a string, ‘on’ or ‘off’.)
If b is None and len(kwargs)==0, toggle the grid state. If kwargs are supplied, it is assumed that you want a grid and b is thus set to True.
which can be ‘major’ (default), ‘minor’, or ‘both’ to control whether major tick grids, minor tick grids, or both are affected.
axis can be ‘both’ (default), ‘x’, or ‘y’ to control which set of gridlines are drawn.
kwargs are used to set the grid line properties, e.g.,:
ax.grid(color='r', linestyle='-', linewidth=2)
Valid Line2D kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Make a hexagonal binning plot.
Call signature:
hexbin(x, y, C = None, gridsize = 100, bins = None,
xscale = 'linear', yscale = 'linear',
cmap=None, norm=None, vmin=None, vmax=None,
alpha=None, linewidths=None, edgecolors='none'
reduce_C_function = np.mean, mincnt=None, marginals=True
**kwargs)
Make a hexagonal binning plot of x versus y, where x, y are 1-D sequences of the same length, N. If C is None (the default), this is a histogram of the number of occurences of the observations at (x[i],y[i]).
If C is specified, it specifies values at the coordinate (x[i],y[i]). These values are accumulated for each hexagonal bin and then reduced according to reduce_C_function, which defaults to numpy’s mean function (np.mean). (If C is specified, it must also be a 1-D sequence of the same length as x and y.)
x, y and/or C may be masked arrays, in which case only unmasked points will be plotted.
Optional keyword arguments:
If None, no binning is applied; the color of each hexagon directly corresponds to its count value.
If ‘log’, use a logarithmic scale for the color
map. Internally, 
is used to
determine the hexagon color.
If an integer, divide the counts in the specified number of bins, and color the hexagons accordingly.
If a sequence of values, the values of the lower bound of the bins to be used.
Other keyword arguments controlling color mapping and normalization arguments:
Other keyword arguments controlling the Collection properties:
If 'none', draws the edges in the same color as the fill color. This is the default, as it avoids unsightly unpainted pixels between the hexagons.
If None, draws the outlines in the default color.
If a matplotlib color arg or sequence of rgba tuples, draws the outlines in the specified color.
Here are the standard descriptions of all the Collection kwargs:
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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
The return value is a PolyCollection instance; use get_array() on this PolyCollection to get the counts in each hexagon. If marginals is True, horizontal bar and vertical bar (both PolyCollections) will be attached to the return collection as attributes hbar and vbar.
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Plot a histogram.
Compute and draw the histogram of x. The return value is a tuple (n, bins, patches) or ([n0, n1, ...], bins, [patches0, patches1,...]) if the input contains multiple data.
Multiple data can be provided via x as a list of datasets of potentially different length ([x0, x1, ...]), or as a 2-D ndarray in which each column is a dataset. Note that the ndarray form is transposed relative to the list form.
Masked arrays are not supported at present.
| Parameters: | x : (n,) array or sequence of (n,) arrays
bins : integer or array_like, optional
range : tuple or None, optional
normed : boolean, optional
weights : (n, ) array_like or None, optional
cumulative : boolean, optional
bottom : array_like, scalar, or None
histtype : {‘bar’, ‘barstacked’, ‘step’, ‘stepfilled’}, optional
align : {‘left’, ‘mid’, ‘right’}, optional
orientation : {‘horizontal’, ‘vertical’}, optional
rwidth : scalar or None, optional
log : boolean, optional
color : color or array_like of colors or None, optional
label : string or None, optional
stacked : boolean, optional
|
|---|---|
| Returns: | n : array or list of arrays
bins : array
patches : list or list of lists
|
| Other Parameters: | |
kwargs : Patch properties |
|
See also
Notes
Until numpy release 1.5, the underlying numpy histogram function was incorrect with normed`=`True if bin sizes were unequal. MPL inherited that error. It is now corrected within MPL when using earlier numpy versions.
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Make a 2D histogram plot.
| Parameters: | x, y: array_like, shape (n, )
bins: [None | int | [int, int] | array_like | [array, array]]
range : array_like shape(2, 2), optional, default: None
normed : boolean, optional, default: False
weights : array_like, shape (n, ), optional, default: None
cmin : scalar, optional, default: None
cmax : scalar, optional, default: None
|
|---|---|
| Returns: | The return value is (counts, xedges, yedges, Image). |
| Other Parameters: | |
kwargs : pcolorfast() properties. |
|
See also
Notes
Rendering the histogram with a logarithmic color scale is accomplished by passing a colors.LogNorm instance to the norm keyword argument. Likewise, power-law normalization (similar in effect to gamma correction) can be accomplished with colors.PowerNorm.
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Plot horizontal lines at each y from xmin to xmax.
| Parameters: | y : scalar or sequence of scalar
xmin, xmax : scalar or 1D array_like
colors : array_like of colors, optional, default: ‘k’ linestyles : [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’], optional label : string, optional, default: ‘’ |
|---|---|
| Returns: | lines : LineCollection |
| Other Parameters: | |
kwargs : LineCollection properties. |
|
See also
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Set the hold state. If b is None (default), toggle the hold state, else set the hold state to boolean value b:
hold() # toggle hold
hold(True) # hold is on
hold(False) # hold is off
When hold is True, subsequent plot commands will be added to the current axes. When hold is False, the current axes and figure will be cleared on the next plot command.
set the default colormap to hot and apply to current image if any. See help(colormaps) for more information
set the default colormap to hsv and apply to current image if any. See help(colormaps) for more information
Read an image from a file into an array.
fname may be a string path or a Python file-like object. If using a file object, it must be opened in binary mode.
If format is provided, will try to read file of that type, otherwise the format is deduced from the filename. If nothing can be deduced, PNG is tried.
Return value is a numpy.array. For grayscale images, the return array is MxN. For RGB images, the return value is MxNx3. For RGBA images the return value is MxNx4.
matplotlib can only read PNGs natively, but if PIL is installed, it will use it to load the image and return an array (if possible) which can be used with imshow().
Save an array as in image file.
The output formats available depend on the backend being used.
Display an image on the axes.
| Parameters: | X : array_like, shape (n, m) or (n, m, 3) or (n, m, 4)
cmap : Colormap, optional, default: None
aspect : [‘auto’ | ‘equal’ | scalar], optional, default: None
interpolation : string, optional, default: None
norm : Normalize, optional, default: None
vmin, vmax : scalar, optional, default: None
alpha : scalar, optional, default: None
origin : [‘upper’ | ‘lower’], optional, default: None
extent : scalars (left, right, bottom, top), optional, default: None
shape : scalars (columns, rows), optional, default: None
filternorm : scalar, optional, default: 1
filterrad : scalar, optional, default: 4.0
|
|---|---|
| Returns: | image : AxesImage |
| Other Parameters: | |
kwargs : Artist properties. |
|
See also
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Turn interactive mode off.
Turn interactive mode on.
Return the hold status of the current axes.
Return status of interactive mode.
set the default colormap to jet and apply to current image if any. See help(colormaps) for more information
Places a legend on the axes.
To make a legend for lines which already exist on the axes (via plot for instance), simply call this function with an iterable of strings, one for each legend item. For example:
ax.plot([1, 2, 3])
ax.legend(['A simple line'])
However, in order to keep the “label” and the legend element instance together, it is preferable to specify the label either at artist creation, or by calling the set_label() method on the artist:
line, = ax.plot([1, 2, 3], label='Inline label')
# Overwrite the label by calling the method.
line.set_label('Label via method')
ax.legend()
Specific lines can be excluded from the automatic legend element selection by defining a label starting with an underscore. This is default for all artists, so calling legend() without any arguments and without setting the labels manually will result in no legend being drawn.
For full control of which artists have a legend entry, it is possible to pass an iterable of legend artists followed by an iterable of legend labels respectively:
legend((line1, line2, line3), ('label1', 'label2', 'label3'))
| Parameters: | loc : int or string or pair of floats, default: 0
bbox_to_anchor : matplotlib.transforms.BboxBase instance or tuple of floats
ncol : integer
prop : None or matplotlib.font_manager.FontProperties or dict
fontsize : int or float or {‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’}
numpoints : None or int
scatterpoints : None or int
scatteryoffsets : iterable of floats
markerscale : None or int or float
*markerfirst*: [ *True* | *False* ]
frameon : None or bool
fancybox : None or bool
shadow : None or bool
framealpha : None or float
mode : {“expand”, None}
bbox_transform : None or matplotlib.transforms.Transform
title : str or None
borderpad : float or None
labelspacing : float or None
handlelength : float or None
handletextpad : float or None
borderaxespad : float or None
columnspacing : float or None
handler_map : dict or None
|
|---|
Notes
Not all kinds of artist are supported by the legend command. See Legend guide for details.
Examples
(Source code, png)
Control behavior of tick locators.
Keyword arguments:
Remaining keyword arguments are passed to directly to the set_params() method.
Typically one might want to reduce the maximum number of ticks and use tight bounds when plotting small subplots, for example:
ax.locator_params(tight=True, nbins=4)
Because the locator is involved in autoscaling, autoscale_view() is called automatically after the parameters are changed.
This presently works only for the MaxNLocator used by default on linear axes, but it may be generalized.
Make a plot with log scaling on both the x and y axis.
Call signature:
loglog(*args, **kwargs)
loglog() supports all the keyword arguments of plot() and matplotlib.axes.Axes.set_xscale() / matplotlib.axes.Axes.set_yscale().
Notable keyword arguments:
- basex/basey: scalar > 1
- Base of the x/y logarithm
- subsx/subsy: [ None | sequence ]
- The location of the minor x/y ticks; None defaults to autosubs, which depend on the number of decades in the plot; see matplotlib.axes.Axes.set_xscale() / matplotlib.axes.Axes.set_yscale() for details
- nonposx/nonposy: [‘mask’ | ‘clip’ ]
- Non-positive values in x or y can be masked as invalid, or clipped to a very small positive number
The remaining valid kwargs are 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Plot the magnitude spectrum.
Call signature:
magnitude_spectrum(x, Fs=2, Fc=0, window=mlab.window_hanning,
pad_to=None, sides='default', **kwargs)
Compute the magnitude spectrum of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.
- x: 1-D array or sequence
- Array or sequence containing the data
Keyword arguments:
- 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.
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).
Returns the tuple (spectrum, freqs, line):
- spectrum: 1-D array
- The values for the magnitude spectrum before scaling (real valued)
- freqs: 1-D array
- The frequencies corresponding to the elements in spectrum
- line: a Line2D instance
- The line created by this function
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Set or retrieve autoscaling margins.
signatures:
margins()
returns xmargin, ymargin
margins(margin)
margins(xmargin, ymargin)
margins(x=xmargin, y=ymargin)
margins(..., tight=False)
All three forms above set the xmargin and ymargin parameters. All keyword parameters are optional. A single argument specifies both xmargin and ymargin. The tight parameter is passed to autoscale_view(), which is executed after a margin is changed; the default here is True, on the assumption that when margins are specified, no additional padding to match tick marks is usually desired. Setting tight to None will preserve the previous setting.
Specifying any margin changes only the autoscaling; for example, if xmargin is not None, then xmargin times the X data interval will be added to each end of that interval before it is used in autoscaling.
Display an array as a matrix in a new figure window.
The origin is set at the upper left hand corner and rows (first dimension of the array) are displayed horizontally. The aspect ratio of the figure window is that of the array, unless this would make an excessively short or narrow figure.
Tick labels for the xaxis are placed on top.
With the exception of fignum, keyword arguments are passed to imshow(). You may set the origin kwarg to “lower” if you want the first row in the array to be at the bottom instead of the top.
By default, matshow() creates a new figure window with automatic numbering. If fignum is given as an integer, the created figure will use this figure number. Because of how matshow() tries to set the figure aspect ratio to be the one of the array, if you provide the number of an already existing figure, strange things may happen.
If fignum is False or 0, a new figure window will NOT be created.
Remove minor ticks from the current plot.
Display minor ticks on the current plot.
Displaying minor ticks reduces performance; turn them off using minorticks_off() if drawing speed is a problem.
Call a function with hold(True).
Calls:
func(*args, **kwargs)
with hold(True) and then restores the hold state.
Pause for interval seconds.
If there is an active figure it will be updated and displayed, and the GUI event loop will run during the pause.
If there is no active figure, or if a non-interactive backend is in use, this executes time.sleep(interval).
This can be used for crude animation. For more complex animation, see matplotlib.animation.
This function is experimental; its behavior may be changed or extended in a future release.
Create a pseudocolor plot of a 2-D array.
Note
pcolor can be very slow for large arrays; consider using the similar but much faster pcolormesh() instead.
Call signatures:
pcolor(C, **kwargs)
pcolor(X, Y, C, **kwargs)
C is the array of color values.
X and Y, if given, specify the (x, y) coordinates of the colored quadrilaterals; the quadrilateral for C[i,j] has corners at:
(X[i, j], Y[i, j]),
(X[i, j+1], Y[i, j+1]),
(X[i+1, j], Y[i+1, j]),
(X[i+1, j+1], Y[i+1, j+1]).
Ideally the dimensions of X and Y should be one greater than those of C; if the dimensions are the same, then the last row and column of C will be ignored.
Note that the the column index corresponds to the x-coordinate, and the row index corresponds to y; for details, see the Grid Orientation section below.
If either or both of X and Y are 1-D arrays or column vectors, they will be expanded as needed into the appropriate 2-D arrays, making a rectangular grid.
X, Y and C may be masked arrays. If either C[i, j], or one of the vertices surrounding C[i,j] (X or Y at [i, j], [i+1, j], [i, j+1],[i+1, j+1]) is masked, nothing is plotted.
Keyword arguments:
- cmap: [ None | Colormap ]
- A matplotlib.colors.Colormap instance. If None, use rc settings.
- norm: [ None | Normalize ]
- An matplotlib.colors.Normalize instance is used to scale luminance data to 0,1. If None, defaults to normalize().
- vmin/vmax: [ None | scalar ]
- vmin and vmax are used in conjunction with norm to normalize luminance data. If either is None, it is autoscaled to the respective min or max of the color array C. If not None, vmin or vmax passed in here override any pre-existing values supplied in the norm instance.
- shading: [ ‘flat’ | ‘faceted’ ]
If ‘faceted’, a black grid is drawn around each rectangle; if ‘flat’, edges are not drawn. Default is ‘flat’, contrary to MATLAB.
- This kwarg is deprecated; please use ‘edgecolors’ instead:
- shading=’flat’ – edgecolors=’none’
- shading=’faceted – edgecolors=’k’
- edgecolors: [ None | 'none' | color | color sequence]
If None, the rc setting is used by default.
If 'none', edges will not be visible.
An mpl color or sequence of colors will set the edge color
- alpha: 0 <= scalar <= 1 or None
- the alpha blending value
- snap: bool
- Whether to snap the mesh to pixel boundaries.
Return value is a matplotlib.collections.Collection instance.
The grid orientation follows the MATLAB convention: an array C with shape (nrows, ncolumns) is plotted with the column number as X and the row number as Y, increasing up; hence it is plotted the way the array would be printed, except that the Y axis is reversed. That is, C is taken as C*(*y, x).
Similarly for meshgrid():
x = np.arange(5)
y = np.arange(3)
X, Y = np.meshgrid(x, y)
is equivalent to:
X = array([[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4],
[0, 1, 2, 3, 4]])
Y = array([[0, 0, 0, 0, 0],
[1, 1, 1, 1, 1],
[2, 2, 2, 2, 2]])
so if you have:
C = rand(len(x), len(y))
then you need to transpose C:
pcolor(X, Y, C.T)
or:
pcolor(C.T)
MATLAB pcolor() always discards the last row and column of C, but matplotlib displays the last row and column if X and Y are not specified, or if X and Y have one more row and column than C.
kwargs can be used to control the PolyCollection 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
Note
The default antialiaseds is False if the default edgecolors*=”none” is used. This eliminates artificial lines at patch boundaries, and works regardless of the value of alpha. If *edgecolors is not “none”, then the default antialiaseds is taken from rcParams[‘patch.antialiased’], which defaults to True. Stroking the edges may be preferred if alpha is 1, but will cause artifacts otherwise.
See also
Additional kwargs: hold = [True|False] overrides default hold state
Plot a quadrilateral mesh.
Call signatures:
pcolormesh(C)
pcolormesh(X, Y, C)
pcolormesh(C, **kwargs)
Create a pseudocolor plot of a 2-D array.
pcolormesh is similar to pcolor(), but uses a different mechanism and returns a different object; pcolor returns a PolyCollection but pcolormesh returns a QuadMesh. It is much faster, so it is almost always preferred for large arrays.
C may be a masked array, but X and Y may not. Masked array support is implemented via cmap and norm; in contrast, pcolor() simply does not draw quadrilaterals with masked colors or vertices.
Keyword arguments:
- cmap: [ None | Colormap ]
- A matplotlib.colors.Colormap instance. If None, use rc settings.
- norm: [ None | Normalize ]
- A matplotlib.colors.Normalize instance is used to scale luminance data to 0,1. If None, defaults to normalize().
- vmin/vmax: [ None | scalar ]
- vmin and vmax are used in conjunction with norm to normalize luminance data. If either is None, it is autoscaled to the respective min or max of the color array C. If not None, vmin or vmax passed in here override any pre-existing values supplied in the norm instance.
- shading: [ ‘flat’ | ‘gouraud’ ]
- ‘flat’ indicates a solid color for each quad. When ‘gouraud’, each quad will be Gouraud shaded. When gouraud shading, edgecolors is ignored.
- edgecolors: [None | 'None' | 'face' | color |
If None, the rc setting is used by default.
If 'None', edges will not be visible.
If 'face', edges will have the same color as the faces.
An mpl color or sequence of colors will set the edge color
- alpha: 0 <= scalar <= 1 or None
- the alpha blending value
Return value is a matplotlib.collections.QuadMesh object.
kwargs can be used to control the matplotlib.collections.QuadMesh 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
See also
Additional kwargs: hold = [True|False] overrides default hold state
Plot the phase spectrum.
Call signature:
phase_spectrum(x, Fs=2, Fc=0, window=mlab.window_hanning,
pad_to=None, sides='default', **kwargs)
Compute the phase spectrum (unwrapped angle spectrum) of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.
- x: 1-D array or sequence
- Array or sequence containing the data
Keyword arguments:
- 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.
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).
Returns the tuple (spectrum, freqs, line):
- spectrum: 1-D array
- The values for the phase 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
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Plot a pie chart.
Call signature:
pie(x, explode=None, labels=None,
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),
autopct=None, pctdistance=0.6, shadow=False,
labeldistance=1.1, startangle=None, radius=None,
counterclock=True, wedgeprops=None, textprops=None,
center = (0, 0), frame = False )
Make a pie chart of array x. The fractional area of each wedge is given by x/sum(x). If sum(x) <= 1, then the values of x give the fractional area directly and the array will not be normalized. The wedges are plotted counterclockwise, by default starting from the x-axis.
Keyword arguments:
- explode: [ None | len(x) sequence ]
- If not None, is a len(x) array which specifies the fraction of the radius with which to offset each wedge.
- colors: [ None | color sequence ]
- A sequence of matplotlib color args through which the pie chart will cycle.
- labels: [ None | len(x) sequence of strings ]
- A sequence of strings providing the labels for each wedge
- autopct: [ None | format string | format function ]
- If not None, is a string or function used to label the wedges with their numeric value. The label will be placed inside the wedge. If it is a format string, the label will be fmt%pct. If it is a function, it will be called.
- pctdistance: scalar
- The ratio between the center of each pie slice and the start of the text generated by autopct. Ignored if autopct is None; default is 0.6.
- labeldistance: scalar
- The radial distance at which the pie labels are drawn
- shadow: [ False | True ]
- Draw a shadow beneath the pie.
- startangle: [ None | Offset angle ]
- If not None, rotates the start of the pie chart by angle degrees counterclockwise from the x-axis.
radius: [ None | scalar ] The radius of the pie, if radius is None it will be set to 1.
- counterclock: [ False | True ]
- Specify fractions direction, clockwise or counterclockwise.
- wedgeprops: [ None | dict of key value pairs ]
- Dict of arguments passed to the wedge objects making the pie. For example, you can pass in wedgeprops = { ‘linewidth’ : 3 } to set the width of the wedge border lines equal to 3. For more details, look at the doc/arguments of the wedge object. By default clip_on=False.
- textprops: [ None | dict of key value pairs ]
- Dict of arguments to pass to the text objects.
center: [ (0,0) | sequence of 2 scalars ] Center position of the chart.
- frame: [ False | True ]
- Plot axes frame with the chart.
The pie chart will probably look best if the figure and axes are square, or the Axes aspect is equal. e.g.:
figure(figsize=(8,8))
ax = axes([0.1, 0.1, 0.8, 0.8])
or:
axes(aspect=1)
If autopct is None, return the tuple (patches, texts):
- patches is a sequence of matplotlib.patches.Wedge instances
- texts is a list of the label matplotlib.text.Text instances.
If autopct is not None, return the tuple (patches, texts, autotexts), where patches and texts are as above, and autotexts is a list of Text instances for the numeric labels.
Additional kwargs: hold = [True|False] overrides default hold state
set the default colormap to pink and apply to current image if any. See help(colormaps) for more information
Plot lines and/or markers to the Axes. args is a variable length argument, allowing for multiple x, y pairs with an optional format string. For example, each of the following is legal:
plot(x, y) # plot x and y using default line style and color
plot(x, y, 'bo') # plot x and y using blue circle markers
plot(y) # plot y using x as index array 0..N-1
plot(y, 'r+') # ditto, but with red plusses
If x and/or y is 2-dimensional, then the corresponding columns will be plotted.
An arbitrary number of x, y, fmt groups can be specified, as in:
a.plot(x1, y1, 'g^', x2, y2, 'g-')
Return value is a list of lines that were added.
By default, each line is assigned a different color specified by a ‘color cycle’. To change this behavior, you can edit the axes.color_cycle rcParam.
The following format string characters are accepted to control the line style or marker:
| character | description |
|---|---|
| '-' | solid line style |
| '--' | dashed line style |
| '-.' | dash-dot line style |
| ':' | dotted line style |
| '.' | point marker |
| ',' | pixel marker |
| 'o' | circle marker |
| 'v' | triangle_down marker |
| '^' | triangle_up marker |
| '<' | triangle_left marker |
| '>' | triangle_right marker |
| '1' | tri_down marker |
| '2' | tri_up marker |
| '3' | tri_left marker |
| '4' | tri_right marker |
| 's' | square marker |
| 'p' | pentagon marker |
| '*' | star marker |
| 'h' | hexagon1 marker |
| 'H' | hexagon2 marker |
| '+' | plus marker |
| 'x' | x marker |
| 'D' | diamond marker |
| 'd' | thin_diamond marker |
| '|' | vline marker |
| '_' | hline marker |
The following color abbreviations are supported:
| character | color |
|---|---|
| ‘b’ | blue |
| ‘g’ | green |
| ‘r’ | red |
| ‘c’ | cyan |
| ‘m’ | magenta |
| ‘y’ | yellow |
| ‘k’ | black |
| ‘w’ | white |
In addition, you can specify colors in many weird and wonderful ways, including full names ('green'), hex strings ('#008000'), RGB or RGBA tuples ((0,1,0,1)) or grayscale intensities as a string ('0.8'). Of these, the string specifications can be used in place of a fmt group, but the tuple forms can be used only as kwargs.
Line styles and colors are combined in a single format string, as in 'bo' for blue circles.
The kwargs can be used to set line properties (any property that has a set_* method). You can use this to set a line label (for auto legends), linewidth, anitialising, marker face color, etc. Here is an example:
plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)
plot([1,2,3], [1,4,9], 'rs', label='line 2')
axis([0, 4, 0, 10])
legend()
If you make multiple lines with one plot command, the kwargs apply to all those lines, e.g.:
plot(x1, y1, x2, y2, antialised=False)
Neither line will be antialiased.
You do not need to use format strings, which are just abbreviations. All of the line properties can be controlled by keyword arguments. For example, you can set the color, marker, linestyle, and markercolor with:
plot(x, y, color='green', linestyle='dashed', marker='o',
markerfacecolor='blue', markersize=12).
See Line2D for details.
The kwargs are 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
kwargs scalex and scaley, if defined, are passed on to autoscale_view() to determine whether the x and y axes are autoscaled; the default is True.
Additional kwargs: hold = [True|False] overrides default hold state
Plot with data with dates.
Call signature:
plot_date(x, y, fmt='bo', tz=None, xdate=True,
ydate=False, **kwargs)
Similar to the plot() command, except the x or y (or both) data is considered to be dates, and the axis is labeled accordingly.
x and/or y can be a sequence of dates represented as float days since 0001-01-01 UTC.
Keyword arguments:
- fmt: string
- The plot format string.
- tz: [ None | timezone string | tzinfo instance]
- The time zone to use in labeling dates. If None, defaults to rc value.
- xdate: [ True | False ]
- If True, the x-axis will be labeled with dates.
- ydate: [ False | True ]
- If True, the y-axis will be labeled with dates.
Note if you are using custom date tickers and formatters, it may be necessary to set the formatters/locators after the call to plot_date() since plot_date() will set the default tick locator to matplotlib.dates.AutoDateLocator (if the tick locator is not already set to a matplotlib.dates.DateLocator instance) and the default tick formatter to matplotlib.dates.AutoDateFormatter (if the tick formatter is not already set to a matplotlib.dates.DateFormatter instance).
Valid kwargs are 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
See also
dates for helper functions
date2num(), num2date() and drange() for help on creating the required floating point dates.
Additional kwargs: hold = [True|False] overrides default hold state
Plot the data in in a file.
cols is a sequence of column identifiers to plot. An identifier is either an int or a string. If it is an int, it indicates the column number. If it is a string, it indicates the column header. matplotlib will make column headers lower case, replace spaces with underscores, and remove all illegal characters; so 'Adj Close*' will have name 'adj_close'.
plotfuncs, if not None, is a dictionary mapping identifier to an Axes plotting function as a string. Default is ‘plot’, other choices are ‘semilogy’, ‘fill’, ‘bar’, etc. You must use the same type of identifier in the cols vector as you use in the plotfuncs dictionary, e.g., integer column numbers in both or column names in both. If subplots is False, then including any function such as ‘semilogy’ that changes the axis scaling will set the scaling for all columns.
comments, skiprows, checkrows, delimiter, and names are all passed on to matplotlib.pylab.csv2rec() to load the data into a record array.
If newfig is True, the plot always will be made in a new figure; if False, it will be made in the current figure if one exists, else in a new figure.
kwargs are passed on to plotting functions.
Example usage:
# plot the 2nd and 4th column against the 1st in two subplots
plotfile(fname, (0,1,3))
# plot using column names; specify an alternate plot type for volume
plotfile(fname, ('date', 'volume', 'adj_close'),
plotfuncs={'volume': 'semilogy'})
Note: plotfile is intended as a convenience for quickly plotting data from flat files; it is not intended as an alternative interface to general plotting with pyplot or matplotlib.
Make a polar plot.
call signature:
polar(theta, r, **kwargs)
Multiple theta, r arguments are supported, with format strings, as in plot().
set the default colormap to prism and apply to current image if any. See help(colormaps) for more information
Plot the power spectral density.
Call signature:
psd(x, 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 power spectral density 
by Welch’s average
periodogram method. The vector x is 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 
of each segment 
are averaged to compute ,
with a scaling to correct for power loss due to windowing.
If len(x) < NFFT, it will be zero padded to NFFT.
- x: 1-D array or sequence
- Array or sequence containing the data
Keyword arguments:
- 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.
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().
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.
If return_line is False, returns the tuple (Pxx, freqs). If return_line is True, returns the tuple (Pxx, freqs. line):
- Pxx: 1-D array
- The values for the power spectrum P_{xx} before scaling (real valued)
- freqs: 1-D array
- The frequencies corresponding to the elements in Pxx
- line: a Line2D instance
- The line created by this function. Only returend if return_line is True.
For plotting, the power is plotted as
for decibels, though Pxx itself
is returned.
kwargs 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
Example:
(Source code, png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
Plot a 2-D field of arrows.
call signatures:
quiver(U, V, **kw)
quiver(U, V, C, **kw)
quiver(X, Y, U, V, **kw)
quiver(X, Y, U, V, C, **kw)
Arguments:
- X, Y:
- The x and y coordinates of the arrow locations (default is tail of arrow; see pivot kwarg)
- U, V:
- Give the x and y components of the arrow vectors
- C:
- An optional array used to map colors to the arrows
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:
- units: [ ‘width’ | ‘height’ | ‘dots’ | ‘inches’ | ‘x’ | ‘y’ | ‘xy’ ]
Arrow units; the arrow dimensions except for length are in multiples of this unit.
- ‘width’ or ‘height’: the width or height of the axes
- ‘dots’ or ‘inches’: pixels or inches, based on the figure dpi
- ‘x’, ‘y’, or ‘xy’: X, Y, or sqrt(X^2+Y^2) data units
The arrows scale differently depending on the units. For ‘x’ or ‘y’, the arrows get larger as one zooms in; for other units, the arrow size is independent of the zoom state. For ‘width or ‘height’, the arrow size increases with the width and height of the axes, respectively, when the the window is resized; for ‘dots’ or ‘inches’, resizing does not change the arrows.
- angles: [ ‘uv’ | ‘xy’ | array ]
- With the default ‘uv’, the arrow aspect ratio is 1, so that if U*==*V the angle of the arrow on the plot is 45 degrees CCW from the x-axis. With ‘xy’, the arrow points from (x,y) to (x+u, y+v). Alternatively, arbitrary angles may be specified as an array of values in degrees, CCW from the x-axis.
- scale: [ None | float ]
- Data units per arrow length unit, e.g., m/s per plot width; a smaller scale parameter makes the arrow longer. If None, a simple autoscaling algorithm is used, based on the average vector length and the number of vectors. The arrow length unit is given by the scale_units parameter
- scale_units: None, or any of the units options.
For example, if scale_units is ‘inches’, scale is 2.0, and (u,v) = (1,0), then the vector will be 0.5 inches long. If scale_units is ‘width’, then the vector will be half the width of the axes.
If scale_units is ‘x’ then the vector will be 0.5 x-axis units. To plot vectors in the x-y plane, with u and v having the same units as x and y, use “angles=’xy’, scale_units=’xy’, scale=1”.
- width:
- Shaft width in arrow units; default depends on choice of units, above, and number of vectors; a typical starting value is about 0.005 times the width of the plot.
- headwidth: scalar
- Head width as multiple of shaft width, default is 3
- headlength: scalar
- Head length as multiple of shaft width, default is 5
- headaxislength: scalar
- Head length at shaft intersection, default is 4.5
- minshaft: scalar
- Length below which arrow scales, in units of head length. Do not set this to less than 1, or small arrows will look terrible! Default is 1
- minlength: scalar
- Minimum length as a multiple of shaft width; if an arrow length is less than this, plot a dot (hexagon) of this diameter instead. Default is 1.
- pivot: [ ‘tail’ | ‘mid’ | ‘middle’ | ‘tip’ ]
- The part of the arrow that is at the grid point; the arrow rotates about this point, hence the name pivot.
- color: [ color | color sequence ]
- This is a synonym for the PolyCollection facecolor kwarg. If C has been set, color has no effect.
The defaults give a slightly swept-back arrow; to make the head a triangle, make headaxislength the same as headlength. To make the arrow more pointed, reduce headwidth or increase headlength and headaxislength. To make the head smaller relative to the shaft, scale down all the head parameters. You will probably do best to leave minshaft alone.
linewidths and edgecolors can be used to customize the arrow outlines. 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 arg or sequence of rgba tuples facecolor or facecolors matplotlib color arg or sequence of rgba tuples figure a matplotlib.figure.Figure instance gid an id string hatch [ ‘/’ | ‘\’ | ‘|’ | ‘-‘ | ‘+’ | ‘x’ | ‘o’ | ‘O’ | ‘.’ | ‘*’ ] label string or anything printable with ‘%s’ conversion. linestyle or linestyles or dashes [‘solid’ | ‘dashed’, ‘dashdot’, ‘dotted’ | (offset, on-off-dash-seq) ] linewidth or lw or linewidths float or sequence of floats lod [True | False] 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
Additional kwargs: hold = [True|False] overrides default hold state
Add a key to a quiver plot.
Call signature:
quiverkey(Q, X, Y, U, label, **kw)
Arguments:
- Q:
- The Quiver instance returned by a call to quiver.
- X, Y:
- The location of the key; additional explanation follows.
- U:
- The length of the key
- label:
- A string with the length and units of the key
Keyword arguments:
- coordinates = [ ‘axes’ | ‘figure’ | ‘data’ | ‘inches’ ]
- Coordinate system and units for X, Y: ‘axes’ and ‘figure’ are normalized coordinate systems with 0,0 in the lower left and 1,1 in the upper right; ‘data’ are the axes data coordinates (used for the locations of the vectors in the quiver plot itself); ‘inches’ is position in the figure in inches, with 0,0 at the lower left corner.
- color:
- overrides face and edge colors from Q.
- labelpos = [ ‘N’ | ‘S’ | ‘E’ | ‘W’ ]
- Position the label above, below, to the right, to the left of the arrow, respectively.
- labelsep:
- Distance in inches between the arrow and the label. Default is 0.1
- labelcolor:
- defaults to default Text color.
- fontproperties:
- A dictionary with keyword arguments accepted by the FontProperties initializer: family, style, variant, size, weight
Any additional keyword arguments are used to override vector properties taken from Q.
The positioning of the key depends on X, Y, coordinates, and labelpos. If labelpos is ‘N’ or ‘S’, X, Y give the position of the middle of the key arrow. If labelpos is ‘E’, X, Y positions the head, and if labelpos is ‘W’, X, Y positions the tail; in either of these two cases, X, Y is somewhere in the middle of the arrow+label key object.
Additional kwargs: hold = [True|False] overrides default hold state
Set the current rc params. Group is the grouping for the rc, e.g., for lines.linewidth the group is lines, for axes.facecolor, the group is axes, and so on. Group may also be a list or tuple of group names, e.g., (xtick, ytick). kwargs is a dictionary attribute name/value pairs, e.g.,:
rc('lines', linewidth=2, color='r')
sets the current rc params and is equivalent to:
rcParams['lines.linewidth'] = 2
rcParams['lines.color'] = 'r'
The following aliases are available to save typing for interactive users:
| Alias | Property |
|---|---|
| ‘lw’ | ‘linewidth’ |
| ‘ls’ | ‘linestyle’ |
| ‘c’ | ‘color’ |
| ‘fc’ | ‘facecolor’ |
| ‘ec’ | ‘edgecolor’ |
| ‘mew’ | ‘markeredgewidth’ |
| ‘aa’ | ‘antialiased’ |
Thus you could abbreviate the above rc command as:
rc('lines', lw=2, c='r')
Note you can use python’s kwargs dictionary facility to store dictionaries of default parameters. e.g., you can customize the font rc as follows:
font = {'family' : 'monospace',
'weight' : 'bold',
'size' : 'larger'}
rc('font', **font) # pass in the font dict as kwargs
This enables you to easily switch between several configurations. Use rcdefaults() to restore the default rc params after changes.
Return a context manager for managing rc settings.
This allows one to do:
with mpl.rc_context(fname='screen.rc'):
plt.plot(x, a)
with mpl.rc_context(fname='print.rc'):
plt.plot(x, b)
plt.plot(x, c)
The ‘a’ vs ‘x’ and ‘c’ vs ‘x’ plots would have settings from ‘screen.rc’, while the ‘b’ vs ‘x’ plot would have settings from ‘print.rc’.
A dictionary can also be passed to the context manager:
with mpl.rc_context(rc={'text.usetex': True}, fname='screen.rc'):
plt.plot(x, a)
The ‘rc’ dictionary takes precedence over the settings loaded from ‘fname’. Passing a dictionary only is also valid.
Restore the default rc params. These are not the params loaded by the rc file, but mpl’s internal params. See rc_file_defaults for reloading the default params from the rc file
Get or set the radial gridlines on a polar plot.
call signatures:
lines, labels = rgrids()
lines, labels = rgrids(radii, labels=None, angle=22.5, **kwargs)
When called with no arguments, rgrid() simply returns the tuple (lines, labels), where lines is an array of radial gridlines (Line2D instances) and labels is an array of tick labels (Text instances). When called with arguments, the labels will appear at the specified radial distances and angles.
labels, if not None, is a len(radii) list of strings of the labels to use at each angle.
If labels is None, the rformatter will be used
Examples:
# set the locations of the radial gridlines and labels
lines, labels = rgrids( (0.25, 0.5, 1.0) )
# set the locations and labels of the radial gridlines and labels
lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )
Save the current figure.
Call signature:
savefig(fname, dpi=None, facecolor='w', edgecolor='w',
orientation='portrait', papertype=None, format=None,
transparent=False, bbox_inches=None, pad_inches=0.1,
frameon=None)
The output formats available depend on the backend being used.
Arguments:
- fname:
A string containing a path to a filename, or a Python file-like object, or possibly some backend-dependent object such as PdfPages.
If format is None and fname is a string, the output format is deduced from the extension of the filename. If the filename has no extension, the value of the rc parameter savefig.format is used.
If fname is not a string, remember to specify format to ensure that the correct backend is used.
Keyword arguments:
- dpi: [ None | scalar > 0 ]
- The resolution in dots per inch. If None it will default to the value savefig.dpi in the matplotlibrc file.
- facecolor, edgecolor:
- the colors of the figure rectangle
- orientation: [ ‘landscape’ | ‘portrait’ ]
- not supported on all backends; currently only on postscript output
- papertype:
- One of ‘letter’, ‘legal’, ‘executive’, ‘ledger’, ‘a0’ through ‘a10’, ‘b0’ through ‘b10’. Only supported for postscript output.
- format:
- One of the file extensions supported by the active backend. Most backends support png, pdf, ps, eps and svg.
- transparent:
- If True, the axes patches will all be transparent; the figure patch will also be transparent unless facecolor and/or edgecolor are specified via kwargs. This is useful, for example, for displaying a plot on top of a colored background on a web page. The transparency of these patches will be restored to their original values upon exit of this function.
- frameon:
- If True, the figure patch will be colored, if False, the figure background will be transparent. If not provided, the rcParam ‘savefig.frameon’ will be used.
- bbox_inches:
- Bbox in inches. Only the given portion of the figure is saved. If ‘tight’, try to figure out the tight bbox of the figure.
- pad_inches:
- Amount of padding around the figure when bbox_inches is ‘tight’.
- bbox_extra_artists:
- A list of extra artists that will be considered when the tight bbox is calculated.
Set the current Axes instance to ax.
The current Figure is updated to the parent of ax.
Make a scatter plot of x vs y, where x and y are sequence like objects of the same lengths.
| Parameters: | x, y : array_like, shape (n, )
s : scalar or array_like, shape (n, ), optional, default: 20
c : color or sequence of color, optional, default
marker : MarkerStyle, optional, default: ‘o’
cmap : Colormap, optional, default: None
norm : Normalize, optional, default: None
vmin, vmax : scalar, optional, default: None
alpha : scalar, optional, default: None
linewidths : scalar or array_like, optional, default: None
|
|---|---|
| Returns: | paths : PathCollection |
| Other Parameters: | |
kwargs : Collection properties |
|
Notes
Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Set the current image. This image will be the target of colormap commands like jet(), hot() or clim()). The current image is an attribute of the current axes.
Make a plot with log scaling on the x axis.
Call signature:
semilogx(*args, **kwargs)
semilogx() supports all the keyword arguments of plot() and matplotlib.axes.Axes.set_xscale().
Notable keyword arguments:
- basex: scalar > 1
- Base of the x logarithm
- subsx: [ None | sequence ]
- The location of the minor xticks; None defaults to autosubs, which depend on the number of decades in the plot; see set_xscale() for details.
- nonposx: [ ‘mask’ | ‘clip’ ]
- Non-positive values in x can be masked as invalid, or clipped to a very small positive number
The remaining valid kwargs are 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
See also
Additional kwargs: hold = [True|False] overrides default hold state
Make a plot with log scaling on the y axis.
call signature:
semilogy(*args, **kwargs)
semilogy() supports all the keyword arguments of plot() and matplotlib.axes.Axes.set_yscale().
Notable keyword arguments:
- basey: scalar > 1
- Base of the y logarithm
- subsy: [ None | sequence ]
- The location of the minor yticks; None defaults to autosubs, which depend on the number of decades in the plot; see set_yscale() for details.
- nonposy: [ ‘mask’ | ‘clip’ ]
- Non-positive values in y can be masked as invalid, or clipped to a very small positive number
The remaining valid kwargs are 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 ['-' | '--' | '-.' | ':' | 'None' | ' ' | ''] linewidth or lw float value in points lod [True | False] 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
See also
Additional kwargs: hold = [True|False] overrides default hold state
Set the default colormap. Applies to the current image if any. See help(colormaps) for more information.
cmap must be a Colormap instance, or the name of a registered colormap.
See matplotlib.cm.register_cmap() and matplotlib.cm.get_cmap().
Set a property on an artist object.
matplotlib supports the use of setp() (“set property”) and getp() to set and get object properties, as well as to do introspection on the object. For example, to set the linestyle of a line to be dashed, you can do:
>>> line, = plot([1,2,3])
>>> setp(line, linestyle='--')
If you want to know the valid types of arguments, you can provide the name of the property you want to set without a value:
>>> setp(line, 'linestyle')
linestyle: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' ]
If you want to see all the properties that can be set, and their possible values, you can do:
>>> setp(line)
... long output listing omitted
setp() operates on a single instance or a list of instances. If you are in query mode introspecting the possible values, only the first instance in the sequence is used. When actually setting values, all the instances will be set. e.g., suppose you have a list of two lines, the following will make both lines thicker and red:
>>> x = arange(0,1.0,0.01)
>>> y1 = sin(2*pi*x)
>>> y2 = sin(4*pi*x)
>>> lines = plot(x, y1, x, y2)
>>> setp(lines, linewidth=2, color='r')
setp() works with the MATLAB style string/value pairs or with python kwargs. For example, the following are equivalent:
>>> setp(lines, 'linewidth', 2, 'color', 'r') # MATLAB style
>>> setp(lines, linewidth=2, color='r') # python style
Display a figure. When running in ipython with its pylab mode, display all figures and return to the ipython prompt.
In non-interactive mode, display all figures and block until the figures have been closed; in interactive mode it has no effect unless figures were created prior to a change from non-interactive to interactive mode (not recommended). In that case it displays the figures but does not block.
A single experimental keyword argument, block, may be set to True or False to override the blocking behavior described above.
Plot a spectrogram.
Call signature:
specgram(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
window=mlab.window_hanning, noverlap=128,
cmap=None, xextent=None, pad_to=None, sides='default',
scale_by_freq=None, mode='default', scale='default',
**kwargs)
Compute and plot a spectrogram of data in x. Data are split into NFFT length segments and the spectrum of each section is computed. The windowing function window is applied to each segment, and the amount of overlap of each segment is specified with noverlap. The spectrogram is plotted as a colormap (using imshow).
Keyword arguments:
- 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.
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().
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.
Note
detrend and scale_by_freq only apply when mode is set to ‘psd’
Returns the tuple (spectrum, freqs, t, im):
- spectrum: 2-D array
- columns are the periodograms of successive segments
- freqs: 1-D array
- The frequencies corresponding to the rows in spectrum
- t: 1-D array
- The times corresponding to midpoints of segments (i.e the columns in spectrum)
- im: instance of class AxesImage
- The image created by imshow containing the spectrogram
Example:
(Source code, png)
See also
Additional kwargs: hold = [True|False] overrides default hold state
set the default colormap to spectral and apply to current image if any. See help(colormaps) for more information
set the default colormap to spring and apply to current image if any. See help(colormaps) for more information
Plot the sparsity pattern on a 2-D array.
spy(Z) plots the sparsity pattern of the 2-D array Z.
| Parameters: | Z : sparse array (n, m)
precision : float, optional, default: 0
origin : [“upper”, “lower”], optional, default: “upper”
aspect : [‘auto’ | ‘equal’ | scalar], optional, default: “equal”
Two plotting styles are available: image or marker. Both are available for full arrays, but only the marker style works for :class:`scipy.sparse.spmatrix` instances. If *marker* and *markersize* are *None*, an image will be returned and any remaining kwargs are passed to :func:`~matplotlib.pyplot.imshow`; else, a :class:`~matplotlib.lines.Line2D` object will be returned with the value of marker determining the marker type, and any remaining kwargs passed to the :meth:`~matplotlib.axes.Axes.plot` method. If *marker* and *markersize* are *None*, useful kwargs include: * *cmap* * *alpha* |
|---|
Draws a stacked area plot.
x : 1d array of dimension N
- y : 2d array of dimension MxN, OR any number 1d arrays each of dimension
1xN. The data is assumed to be unstacked. Each of the following calls is legal:
stackplot(x, y) # where y is MxN stackplot(x, y1, y2, y3, y4) # where y1, y2, y3, y4, are all 1xNmKeyword arguments:
- baseline : [‘zero’, ‘sym’, ‘wiggle’, ‘weighted_wiggle’]
- Method used to calculate the baseline. ‘zero’ is just a simple stacked plot. ‘sym’ is symmetric around zero and is sometimes called ThemeRiver. ‘wiggle’ minimizes the sum of the squared slopes. ‘weighted_wiggle’ does the same but weights to account for size of each layer. It is also called Streamgraph-layout. More details can be found at http://www.leebyron.com/else/streamgraph/.
labels : A list or tuple of labels to assign to each data series.
- colors : A list or tuple of colors. These will be cycled through and
- used to colour the stacked areas. All other keyword arguments are passed to fill_between()
Returns r : A list of PolyCollection, one for each element in the stacked area plot.
Additional kwargs: hold = [True|False] overrides default hold state
Create a stem plot.
Call signatures:
will be plotted.stem(y, linefmt='b-', markerfmt='bo', basefmt='r-')
stem(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')
A stem plot plots vertical lines (using linefmt) at each x location from the baseline to y, and places a marker there using markerfmt. A horizontal line at 0 is is plotted using basefmt.
If no x values are provided, the default is (0, 1, ..., len(y) - 1)
Return value is a tuple (markerline, stemlines, baseline).
See also
This document for details.
Example:
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Make a step plot.
Call signature:
step(x, y, *args, **kwargs)
Additional keyword args to step() are the same as those for plot().
x and y must be 1-D sequences, and it is assumed, but not checked, that x is uniformly increasing.
Keyword arguments:
If ‘pre’, the interval from x[i] to x[i+1] has level y[i+1]
If ‘post’, that interval has level y[i]
If ‘mid’, the jumps in y occur half-way between the x-values.
Additional kwargs: hold = [True|False] overrides default hold state
Draws streamlines of a vector flow.
- x, y : 1d arrays
- an evenly spaced grid.
- u, v : 2d arrays
- x and y-velocities. Number of rows should match length of y, and the number of columns should match x.
- density : float or 2-tuple
- Controls the closeness of streamlines. When density = 1, the domain is divided into a 30x30 grid—density linearly scales this grid. Each cell in the grid can have, at most, one traversing streamline. For different densities in each direction, use [density_x, density_y].
- linewidth : numeric or 2d array
- vary linewidth when given a 2d array with the same shape as velocities.
- color : matplotlib color code, or 2d array
- Streamline color. When given an array with the same shape as velocities, color values are converted to colors using cmap.
- cmap : Colormap
- Colormap used to plot streamlines and arrows. Only necessary when using an array input for color.
- norm : Normalize
- Normalize object used to scale luminance data to 0, 1. If None, stretch (min, max) to (0, 1). Only necessary when color is an array.
- arrowsize : float
- Factor scale arrow size.
- arrowstyle : str
- Arrow style specification. See FancyArrowPatch.
- minlength : float
- Minimum length of streamline in axes coordinates.
- zorder : int
- any number
Returns:
- stream_container : StreamplotSet
Container object with attributes
- lines: matplotlib.collections.LineCollection of streamlines
- arrows: collection of matplotlib.patches.FancyArrowPatch objects representing arrows half-way along stream lines.
This container will probably change in the future to allow changes to the colormap, alpha, etc. for both lines and arrows, but these changes should be backward compatible.
Additional kwargs: hold = [True|False] overrides default hold state
Return a subplot axes positioned by the given grid definition.
Typical call signature:
subplot(nrows, ncols, plot_number)
Where nrows and ncols are used to notionally split the figure into nrows * ncols sub-axes, and plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum of nrows * ncols.
In the case when nrows, ncols and plot_number are all less than 10, a convenience exists, such that the a 3 digit number can be given instead, where the hundreds represent nrows, the tens represent ncols and the units represent plot_number. For instance:
subplot(211)
produces a subaxes in a figure which represents the top plot (i.e. the first) in a 2 row by 1 column notional grid (no grid actually exists, but conceptually this is how the returned subplot has been positioned).
Note
Creating a new subplot with a position which is entirely inside a pre-existing axes will trigger the larger axes to be deleted:
import matplotlib.pyplot as plt
# plot a line, implicitly creating a subplot(111)
plt.plot([1,2,3])
# now create a subplot which represents the top plot of a grid
# with 2 rows and 1 column. Since this subplot will overlap the
# first, the plot (and its axes) previously created, will be removed
plt.subplot(211)
plt.plot(range(12))
plt.subplot(212, axisbg='y') # creates 2nd subplot with yellow background
If you do not want this behavior, use the add_subplot() method or the axes() function instead.
Keyword arguments:
- axisbg:
- The background color of the subplot, which can be any valid color specifier. See matplotlib.colors for more information.
- polar:
- A boolean flag indicating whether the subplot plot should be a polar projection. Defaults to False.
- projection:
- A string giving the name of a custom projection to be used for the subplot. This projection must have been previously registered. See matplotlib.projections.
See also
Example:
(Source code, png)
Create a subplot in a grid. The grid is specified by shape, at location of loc, spanning rowspan, colspan cells in each direction. The index for loc is 0-based.
subplot2grid(shape, loc, rowspan=1, colspan=1)
is identical to
gridspec=GridSpec(shape[0], shape[2])
subplotspec=gridspec.new_subplotspec(loc, rowspan, colspan)
subplot(subplotspec)
Launch a subplot tool window for a figure.
A matplotlib.widgets.SubplotTool instance is returned.
Create a figure with a set of subplots already made.
This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call.
Keyword arguments:
- nrows : int
- Number of rows of the subplot grid. Defaults to 1.
- ncols : int
- Number of columns of the subplot grid. Defaults to 1.
- sharex : string or bool
- If True, the X axis will be shared amongst all subplots. If True and you have multiple rows, the x tick labels on all but the last row of plots will have visible set to False If a string must be one of “row”, “col”, “all”, or “none”. “all” has the same effect as True, “none” has the same effect as False. If “row”, each subplot row will share a X axis. If “col”, each subplot column will share a X axis and the x tick labels on all but the last row will have visible set to False.
- sharey : string or bool
- If True, the Y axis will be shared amongst all subplots. If True and you have multiple columns, the y tick labels on all but the first column of plots will have visible set to False If a string must be one of “row”, “col”, “all”, or “none”. “all” has the same effect as True, “none” has the same effect as False. If “row”, each subplot row will share a Y axis and the y tick labels on all but the first column will have visible set to False. If “col”, each subplot column will share a Y axis.
- squeeze : bool
If True, extra dimensions are squeezed out from the returned axis object:
- if only one subplot is constructed (nrows=ncols=1), the resulting single Axis object is returned as a scalar.
- for Nx1 or 1xN subplots, the returned object is a 1-d numpy object array of Axis objects are returned as numpy 1-d arrays.
- for NxM subplots with N>1 and M>1 are returned as a 2d array.
If False, no squeezing at all is done: the returned axis object is always a 2-d array containing Axis instances, even if it ends up being 1x1.
- subplot_kw : dict
- Dict with keywords passed to the add_subplot() call used to create each subplots.
- gridspec_kw : dict
- Dict with keywords passed to the GridSpec constructor used to create the grid the subplots are placed on.
- fig_kw : dict
- Dict with keywords passed to the figure() call. Note that all keywords not recognized above will be automatically included here.
Returns:
fig, ax : tuple
- fig is the matplotlib.figure.Figure object
- ax can be either a single axis object or an array of axis objects if more than one subplot was created. The dimensions of the resulting array can be controlled with the squeeze keyword, see above.
Examples:
x = np.linspace(0, 2*np.pi, 400)
y = np.sin(x**2)
# Just a figure and one subplot
f, ax = plt.subplots()
ax.plot(x, y)
ax.set_title('Simple plot')
# Two subplots, unpack the output array immediately
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(x, y)
ax1.set_title('Sharing Y axis')
ax2.scatter(x, y)
# Four polar axes
plt.subplots(2, 2, subplot_kw=dict(polar=True))
# Share a X axis with each column of subplots
plt.subplots(2, 2, sharex='col')
# Share a Y axis with each row of subplots
plt.subplots(2, 2, sharey='row')
# Share a X and Y axis with all subplots
plt.subplots(2, 2, sharex='all', sharey='all')
# same as
plt.subplots(2, 2, sharex=True, sharey=True)
Tune the subplot layout.
call signature:
subplots_adjust(left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None)
The parameter meanings (and suggested defaults) are:
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.2 # the amount of height reserved for white space between subplots
The actual defaults are controlled by the rc file
set the default colormap to summer and apply to current image if any. See help(colormaps) for more information
Add a centered title to the figure.
kwargs are matplotlib.text.Text properties. Using figure coordinates, the defaults are:
- x : 0.5
- The x location of the text in figure coords
- y : 0.98
- The y location of the text in figure coords
- horizontalalignment : ‘center’
- The horizontal alignment of the text
- verticalalignment : ‘top’
- The vertical alignment of the text
A matplotlib.text.Text instance is returned.
Example:
fig.suptitle('this is the figure title', fontsize=12)
Switch the default backend. This feature is experimental, and is only expected to work switching to an image backend. e.g., if you have a bunch of PostScript scripts that you want to run from an interactive ipython session, you may want to switch to the PS backend before running them to avoid having a bunch of GUI windows popup. If you try to interactively switch from one GUI backend to another, you will explode.
Calling this command will close all open windows.
Add a table to the current axes.
Call signature:
table(cellText=None, cellColours=None,
cellLoc='right', colWidths=None,
rowLabels=None, rowColours=None, rowLoc='left',
colLabels=None, colColours=None, colLoc='center',
loc='bottom', bbox=None):
Returns a matplotlib.table.Table instance. For finer grained control over tables, use the Table class and add it to the axes with add_table().
Thanks to John Gill for providing the class and table.
kwargs control the Table properties:
Property Description agg_filter unknown alpha float (0.0 transparent through 1.0 opaque) animated [True | False] axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] contains a callable function figure a matplotlib.figure.Figure instance fontsize a float in points gid an id string label string or anything printable with ‘%s’ conversion. lod [True | False] 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
Add text to the axes.
Add text in string s to axis at location x, y, data coordinates.
| Parameters: | x, y : scalars
s : string
fontdict : dictionary, optional, default: None
withdash : boolean, optional, default: False
|
|---|---|
| Other Parameters: | |
kwargs : Text properties.
|
|
Examples
Individual keyword arguments can be used to override any given parameter:
>>> text(x, y, s, fontsize=12)
The default transform specifies that text is in data coords, alternatively, you can specify text in axis coords (0,0 is lower-left and 1,1 is upper-right). The example below places text in the center of the axes:
>>> text(0.5, 0.5,'matplotlib', horizontalalignment='center',
... verticalalignment='center',
... transform=ax.transAxes)
You can put a rectangular box around the text instance (e.g., to set a background color) by using the keyword bbox. bbox is a dictionary of Rectangle properties. For example:
>>> text(x, y, s, bbox=dict(facecolor='red', alpha=0.5))
Get or set the theta locations of the gridlines in a polar plot.
If no arguments are passed, return a tuple (lines, labels) where lines is an array of radial gridlines (Line2D instances) and labels is an array of tick labels (Text instances):
lines, labels = thetagrids()
Otherwise the syntax is:
lines, labels = thetagrids(angles, labels=None, fmt='%d', frac = 1.1)
set the angles at which to place the theta grids (these gridlines are equal along the theta dimension).
angles is in degrees.
labels, if not None, is a len(angles) list of strings of the labels to use at each angle.
If labels is None, the labels will be fmt%angle.
frac is the fraction of the polar axes radius at which to place the label (1 is the edge). e.g., 1.05 is outside the axes and 0.95 is inside the axes.
Return value is a list of tuples (lines, labels):
Note that on input, the labels argument is a list of strings, and on output it is a list of Text instances.
Examples:
# set the locations of the radial gridlines and labels
lines, labels = thetagrids( range(45,360,90) )
# set the locations and labels of the radial gridlines and labels
lines, labels = thetagrids( range(45,360,90), ('NE', 'NW', 'SW','SE') )
Change the appearance of ticks and tick labels.
Keyword arguments:
Example:
ax.tick_params(direction='out', length=6, width=2, colors='r')
This will make all major ticks be red, pointing out of the box, and with dimensions 6 points by 2 points. Tick labels will also be red.
Change the ScalarFormatter used by default for linear axes.
Optional keyword arguments:
Keyword Description style [ ‘sci’ (or ‘scientific’) | ‘plain’ ] plain turns off scientific notation scilimits (m, n), pair of integers; if style is ‘sci’, scientific notation will be used for numbers outside the range 10`m`:sup: to 10`n`:sup:. Use (0,0) to include all numbers. useOffset [True | False | offset]; if True, the offset will be calculated as needed; if False, no offset will be used; if a numeric offset is specified, it will be used. axis [ ‘x’ | ‘y’ | ‘both’ ] useLocale If True, format the number according to the current locale. This affects things such as the character used for the decimal separator. If False, use C-style (English) formatting. The default setting is controlled by the axes.formatter.use_locale rcparam.
Only the major ticks are affected. If the method is called when the ScalarFormatter is not the Formatter being used, an AttributeError will be raised.
Automatically adjust subplot parameters to give specified padding.
Parameters:
Set a title of the current axes.
Set one of the three available axes titles. The available titles are positioned above the axes in the center, flush with the left edge, and flush with the right edge.
See also
See text() for adding text to the current axes
| Parameters: | label : str
fontdict : dict
loc : {‘center’, ‘left’, ‘right’}, str, optional
|
|---|---|
| Returns: | text : Text
|
| Other Parameters: | |
kwargs : text properties
|
|
Draw contours on an unstructured triangular grid. tricontour() and tricontourf() draw contour lines and filled contours, respectively. Except as noted, function signatures and return values are the same for both versions.
The triangulation can be specified in one of two ways; either:
tricontour(triangulation, ...)
where triangulation is a matplotlib.tri.Triangulation object, or
tricontour(x, y, ...)
tricontour(x, y, triangles, ...)
tricontour(x, y, triangles=triangles, ...)
tricontour(x, y, mask=mask, ...)
tricontour(x, y, triangles, mask=mask, ...)
in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities.
The remaining arguments may be:
tricontour(..., Z)
where Z is the array of values to contour, one per point in the triangulation. The level values are chosen automatically.
tricontour(..., Z, N)
contour N automatically-chosen levels.
tricontour(..., Z, V)
draw contour lines at the values specified in sequence V
tricontourf(..., Z, V)
fill the (len(V)-1) regions between the values in V
tricontour(Z, **kwargs)
Use keyword args to control colors, linewidth, origin, cmap ... see below for more details.
C = tricontour(...) returns a TriContourSet object.
Optional keyword arguments:
- 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.
- levels [level0, level1, ..., leveln]
- A list of floating point numbers indicating the level curves to draw; 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.
tricontour-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 ‘solid’ is used.
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.
If contour is using a monochrome colormap and the contour level is less than 0, then the linestyle specified in contour.negative_linestyle in matplotlibrc will be used.
tricontourf-only keyword arguments:
- antialiased: [ True | False ]
- enable antialiasing
- nchunk: [ 0 | integer ]
- If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of roughly nchunk by nchunk points. This may never actually be advantageous, so this option may be removed. Chunking introduces artifacts at the chunk boundaries unless antialiased is False.
Note: tricontourf 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:
(png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
Draw contours on an unstructured triangular grid. tricontour() and tricontourf() draw contour lines and filled contours, respectively. Except as noted, function signatures and return values are the same for both versions.
The triangulation can be specified in one of two ways; either:
tricontour(triangulation, ...)
where triangulation is a matplotlib.tri.Triangulation object, or
tricontour(x, y, ...)
tricontour(x, y, triangles, ...)
tricontour(x, y, triangles=triangles, ...)
tricontour(x, y, mask=mask, ...)
tricontour(x, y, triangles, mask=mask, ...)
in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities.
The remaining arguments may be:
tricontour(..., Z)
where Z is the array of values to contour, one per point in the triangulation. The level values are chosen automatically.
tricontour(..., Z, N)
contour N automatically-chosen levels.
tricontour(..., Z, V)
draw contour lines at the values specified in sequence V
tricontourf(..., Z, V)
fill the (len(V)-1) regions between the values in V
tricontour(Z, **kwargs)
Use keyword args to control colors, linewidth, origin, cmap ... see below for more details.
C = tricontour(...) returns a TriContourSet object.
Optional keyword arguments:
- 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.
- levels [level0, level1, ..., leveln]
- A list of floating point numbers indicating the level curves to draw; 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.
tricontour-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 ‘solid’ is used.
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.
If contour is using a monochrome colormap and the contour level is less than 0, then the linestyle specified in contour.negative_linestyle in matplotlibrc will be used.
tricontourf-only keyword arguments:
- antialiased: [ True | False ]
- enable antialiasing
- nchunk: [ 0 | integer ]
- If 0, no subdivision of the domain. Specify a positive integer to divide the domain into subdomains of roughly nchunk by nchunk points. This may never actually be advantageous, so this option may be removed. Chunking introduces artifacts at the chunk boundaries unless antialiased is False.
Note: tricontourf 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:
(png)
(png)
Additional kwargs: hold = [True|False] overrides default hold state
Create a pseudocolor plot of an unstructured triangular grid.
The triangulation can be specified in one of two ways; either:
tripcolor(triangulation, ...)
where triangulation is a matplotlib.tri.Triangulation object, or
tripcolor(x, y, ...)
tripcolor(x, y, triangles, ...)
tripcolor(x, y, triangles=triangles, ...)
tripcolor(x, y, mask=mask, ...)
tripcolor(x, y, triangles, mask=mask, ...)
in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities.
The next argument must be C, the array of color values, either one per point in the triangulation if color values are defined at points, or one per triangle in the triangulation if color values are defined at triangles. If there are the same number of points and triangles in the triangulation it is assumed that color values are defined at points; to force the use of color values at triangles use the kwarg facecolors*=C instead of just *C.
shading may be ‘flat’ (the default) or ‘gouraud’. If shading is ‘flat’ and C values are defined at points, the color values used for each triangle are from the mean C of the triangle’s three points. If shading is ‘gouraud’ then color values must be defined at points. shading of ‘faceted’ is deprecated; please use edgecolors instead.
The remaining kwargs are the same as for pcolor().
Example:
Additional kwargs: hold = [True|False] overrides default hold state
Draw a unstructured triangular grid as lines and/or markers.
The triangulation to plot can be specified in one of two ways; either:
triplot(triangulation, ...)
where triangulation is a matplotlib.tri.Triangulation object, or
triplot(x, y, ...)
triplot(x, y, triangles, ...)
triplot(x, y, triangles=triangles, ...)
triplot(x, y, mask=mask, ...)
triplot(x, y, triangles, mask=mask, ...)
in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities.
The remaining args and kwargs are the same as for plot().
Return a list of 2 Line2D containing respectively:
- the lines plotted for triangles edges
- the markers plotted for triangles nodes
Example:
Additional kwargs: hold = [True|False] overrides default hold state
Make a second axes that shares the x-axis. The new axes will overlay ax (or the current axes if ax is None). The ticks for ax2 will be placed on the right, and the ax2 instance is returned.
See also
Make a second axes that shares the y-axis. The new axis will overlay ax (or the current axes if ax is None). The ticks for ax2 will be placed on the top, and the ax2 instance is returned.
Make a violin plot.
Call signature:
violinplot(dataset, positions=None, vert=True, widths=0.5, showmeans=False, showextrema=True, showmedians=False, points=100, bw_method=None):Make a violin plot for each column of dataset or each vector in sequence dataset. Each filled area extends to represent the entire data range, with optional lines at the mean, the median, the minimum, and the maximum.
| Parameters: | dataset : Array or a sequence of vectors.
|
|---|---|
| Returns: | result : dict
Additional kwargs: hold = [True|False] overrides default hold state |
Plot vertical lines.
Plot vertical lines at each x from ymin to ymax.
| Parameters: | x : scalar or 1D array_like
ymin, ymax : scalar or 1D array_like
colors : array_like of colors, optional, default: ‘k’ linestyles : [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’], optional label : string, optional, default: ‘’ |
|---|---|
| Returns: | lines : LineCollection |
| Other Parameters: | |
kwargs : LineCollection properties. |
|
See also
Examples
(Source code, png)
Additional kwargs: hold = [True|False] overrides default hold state
Call signature:
waitforbuttonpress(self, timeout=-1)
Blocking call to interact with the figure.
This will return True is a key was pressed, False if a mouse button was pressed and None if timeout was reached without either being pressed.
If timeout is negative, does not timeout.
set the default colormap to winter and apply to current image if any. See help(colormaps) for more information
Plot the cross correlation between x and y.
| Parameters: | x : sequence of scalars of length n y : sequence of scalars of length n hold : boolean, optional, default: True detrend : callable, optional, default: mlab.detrend_none
normed : boolean, optional, default: True
usevlines : boolean, optional, default: True
maxlags : integer, optional, default: 10
|
|---|---|
| Returns: | (lags, c, line, b) : where: |
| Other Parameters: | |
linestyle : Line2D prop, optional, default: None
marker : string, optional, default: ‘o’ |
|
Notes
The cross correlation is performed with numpy.correlate() with mode = 2.
Additional kwargs: hold = [True|False] overrides default hold state
Turns on xkcd sketch-style drawing mode. This will only have effect on things drawn after this function is called.
For best results, the “Humor Sans” font should be installed: it is not included with matplotlib.
| Parameters: | scale : float, optional
length : float, optional
randomness : float, optional
|
|---|
Notes
This function works by a number of rcParams, so it will probably override others you have set before.
If you want the effects of this function to be temporary, it can be used as a context manager, for example:
with plt.xkcd():
# This figure will be in XKCD-style
fig1 = plt.figure()
# ...
# This figure will be in regular style
fig2 = plt.figure()
Set the x axis label of the current axis.
Default override is:
override = {
'fontsize' : 'small',
'verticalalignment' : 'top',
'horizontalalignment' : 'center'
}
See also
Get or set the x limits of the current axes.
xmin, xmax = xlim() # return the current xlim
xlim( (xmin, xmax) ) # set the xlim to xmin, xmax
xlim( xmin, xmax ) # set the xlim to xmin, xmax
If you do not specify args, you can pass the xmin and xmax as kwargs, e.g.:
xlim(xmax=3) # adjust the max leaving min unchanged
xlim(xmin=1) # adjust the min leaving max unchanged
Setting limits turns autoscaling off for the x-axis.
The new axis limits are returned as a length 2 tuple.
Set the scaling of the x-axis.
call signature:
xscale(scale, **kwargs)
The available scales are: u’linear’ | u’log’ | u’symlog’
Different keywords may be accepted, depending on the scale:
‘linear’
‘log’
- basex/basey:
- The base of the logarithm
- nonposx/nonposy: [‘mask’ | ‘clip’ ]
- non-positive values in x or y can be masked as invalid, or clipped to a very small positive number
- subsx/subsy:
Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
‘symlog’
- basex/basey:
- The base of the logarithm
- linthreshx/linthreshy:
- The range (-x, x) within which the plot is linear (to avoid having the plot go to infinity around zero).
- subsx/subsy:
Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
- linscalex/linscaley:
- This allows the linear range (-linthresh to linthresh) to be stretched relative to the logarithmic range. Its value is the number of decades to use for each half of the linear range. For example, when linscale == 1.0 (the default), the space used for the positive and negative halves of the linear range will be equal to one decade in the logarithmic range.
Get or set the x-limits of the current tick locations and labels.
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = xticks()
# set the locations of the xticks
xticks( arange(6) )
# set the locations and labels of the xticks
xticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are Text properties. For example, to rotate long labels:
xticks( arange(12), calendar.month_name[1:13], rotation=17 )
Set the y axis label of the current axis.
Defaults override is:
override = {
'fontsize' : 'small',
'verticalalignment' : 'center',
'horizontalalignment' : 'right',
'rotation'='vertical' : }
See also
Get or set the y-limits of the current axes.
ymin, ymax = ylim() # return the current ylim
ylim( (ymin, ymax) ) # set the ylim to ymin, ymax
ylim( ymin, ymax ) # set the ylim to ymin, ymax
If you do not specify args, you can pass the ymin and ymax as kwargs, e.g.:
ylim(ymax=3) # adjust the max leaving min unchanged
ylim(ymin=1) # adjust the min leaving max unchanged
Setting limits turns autoscaling off for the y-axis.
The new axis limits are returned as a length 2 tuple.
Set the scaling of the y-axis.
call signature:
yscale(scale, **kwargs)
The available scales are: u’linear’ | u’log’ | u’symlog’
Different keywords may be accepted, depending on the scale:
‘linear’
‘log’
- basex/basey:
- The base of the logarithm
- nonposx/nonposy: [‘mask’ | ‘clip’ ]
- non-positive values in x or y can be masked as invalid, or clipped to a very small positive number
- subsx/subsy:
Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
‘symlog’
- basex/basey:
- The base of the logarithm
- linthreshx/linthreshy:
- The range (-x, x) within which the plot is linear (to avoid having the plot go to infinity around zero).
- subsx/subsy:
Where to place the subticks between each major tick. Should be a sequence of integers. For example, in a log10 scale: [2, 3, 4, 5, 6, 7, 8, 9]
will place 8 logarithmically spaced minor ticks between each major tick.
- linscalex/linscaley:
- This allows the linear range (-linthresh to linthresh) to be stretched relative to the logarithmic range. Its value is the number of decades to use for each half of the linear range. For example, when linscale == 1.0 (the default), the space used for the positive and negative halves of the linear range will be equal to one decade in the logarithmic range.
Get or set the y-limits of the current tick locations and labels.
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = yticks()
# set the locations of the yticks
yticks( arange(6) )
# set the locations and labels of the yticks
yticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are Text properties. For example, to rotate long labels:
yticks( arange(12), calendar.month_name[1:13], rotation=45 )