call signature:
acorr(x, normed=True, detrend=mlab.detrend_none, usevlines=True,
maxlags=10, **kwargs)
Plot the autocorrelation of x. If normed = True, normalize the data by the autocorrelation at 0-th lag. x is detrended by the detrend callable (default no normalization).
Data are plotted as plot(lags, c, **kwargs)
Return value is a tuple (lags, c, line) where:
The default linestyle is None and the default marker is 'o', though these can be overridden with keyword args. The cross correlation is performed with numpy.correlate() with mode = 2.
If usevlines is True, vlines() rather than plot() is used to draw vertical lines from the origin to the acorr. Otherwise, the plot style is determined by the kwargs, which are Line2D properties.
maxlags is a positive integer detailing the number of lags
to show. The default value of None will return all
lags.
The return value is a tuple (lags, c, linecol, b) where
- linecol is the LineCollection
- b is the x-axis.
Example:
xcorr() above, and acorr() below.
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
annotate(s, xy, xytext=None, xycoords='data',
textcoords='data', arrowprops=None, **kwargs)
Keyword arguments:
Annotate the x, y point xy with text s at x, y location xytext. (If xytext = None, defaults to xy, and if textcoords = None, defaults to xycoords).
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 YAArow patch instance is created and drawn. Valid keys for YAArow 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. ie, 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.
| 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’ | 0,1 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. Eg:
# 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'
Additional kwargs are Text properties:
Property Description 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 any string linespacing float (multiple of font size) lod [True | False] multialignment [‘left’ | ‘right’ | ‘center’ ] 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’ ] 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 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
[source code, hires.png, pdf]
[source code, hires.png, pdf]
call signature:
arrow(x, y, dx, dy, **kwargs)
Draws arrow on specified axis from (x, y) to (x + dx, y + dy).
Optional kwargs control the arrow properties:
Property Description alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
Add an axes at position rect specified by:
| kwarg | Accepts | Desctiption |
|---|---|---|
| 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? |
Examples:
call signature:
axhline(y=0, xmin=0, xmax=1, **kwargs)
Axis Horizontal Line
Draw a horizontal line at y from xmin to xmax. With the default values of xmin = 0 and xmax = 1, this line will always span the horizontal extent of the axes, regardless of the xlim settings, even if you change them, eg. 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 the Line2D instance. kwargs are the same as kwargs to plot, and can be used to control the line properties. Eg.,
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 the middle half of the xrange
>>> axhline(y=.5, xmin=0.25, xmax=0.75)
Valid kwargs are Line2D properties:
Property Description 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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
call signature:
axhspan(ymin, ymax, xmin=0, xmax=1, **kwargs)
Axis Horizontal Span.
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, eg. 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 alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
Set/Get the axis properties:
>>> 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
call signature:
axvline(x=0, ymin=0, ymax=1, **kwargs)
Axis Vertical Line
Draw a vertical line at x from ymin to ymax. With the default values of ymin = 0 and ymax = 1, this line will always span the vertical extent of the axes, regardless of the ylim settings, even if you change them, eg. with the set_ylim() command. That is, the vertical extent is in axes coords: 0=bottom, 0.5=middle, 1.0=top but the x location is in data coordinates.
Return value is the Line2D instance. kwargs are the same as kwargs to plot, and can be used to control the line properties. Eg.,
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:
Property Description 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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
call signature:
axvspan(xmin, xmax, ymin=0, ymax=1, **kwargs)
Axis Vertical Span.
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, eg. 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 alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] 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
call signature:
bar(left, height, width=0.8, bottom=0,
color=None, edgecolor=None, linewidth=None,
yerr=None, xerr=None, ecolor=None, capsize=3,
align='edge', orientation='vertical', log=False)
Make a bar plot with rectangles bounded by:
- left, left + width, bottom, bottom + height
- (left, right, bottom and top edges)
left, height, width, and bottom can be either scalars or sequences
Return value is a list of matplotlib.patches.Rectangle instances.
Required arguments:
Argument Description left the x coordinates of the left sides of the bars height the heights of the bars
Optional keyword arguments:
Keyword Description width the widths of the bars bottom the y coordinates of the bottom edges of the bars color the colors of the bars edgecolor the colors of the bar edges linewidth width of bar edges; None means use default linewidth; 0 means don’t draw edges. xerr if not None, will be used to generate errorbars on the bar chart yerr if not None, will be used to generate errorbars on the bar chart ecolor specifies the color of any errorbar capsize (default 3) determines the length in points of the error bar caps align ‘edge’ (default) | ‘center’ orientation ‘vertical’ | ‘horizontal’ log [False|True] False (default) leaves the orientation axis as-is; True sets it to log scale
For vertical bars, align = ‘edge’ aligns bars by their left edges in left, while align = ‘center’ interprets these values as the x coordinates of the bar centers. For horizontal bars, align = ‘edge’ aligns bars by their bottom edges in bottom, while align = ‘center’ interprets these values as the y coordinates of the bar centers.
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.
Other optional kwargs:
Property Description alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Example: A stacked bar chart.
[source code, hires.png, pdf]
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 alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] snap unknown transform Transform instance url a url string urls unknown visible [True | False] zorder any number
Example:
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
barh(bottom, width, height=0.8, left=0, **kwargs)
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
Return value is a list of matplotlib.patches.Rectangle instances.
Required arguments:
Argument Description bottom the vertical positions of the bottom edges of the bars width the lengths of the bars
Optional keyword arguments:
Keyword Description height the heights (thicknesses) of the bars left the x coordinates of the left edges of the bars color the colors of the bars edgecolor the colors of the bar edges linewidth width of bar edges; None means use default linewidth; 0 means don’t draw edges. xerr if not None, will be used to generate errorbars on the bar chart yerr if not None, will be used to generate errorbars on the bar chart ecolor specifies the color of any errorbar capsize (default 3) determines the length in points of the error bar caps align ‘edge’ (default) | ‘center’ log [False|True] False (default) leaves the horizontal axis as-is; True sets it to log scale
Setting align = ‘edge’ aligns bars by their bottom edges in bottom, while align = ‘center’ interprets these values as the y coordinates of the bar centers.
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 barh as the basis for stacked bar charts, or candlestick plots.
other optional kwargs:
Property Description alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Additional kwargs: hold = [True|False] overrides default hold state
Turn the axes box on or off according to on.
If on is None, toggle state.
call signature:
boxplot(x, notch=0, sym='+', vert=1, whis=1.5,
positions=None, widths=None)
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.
sym (default ‘b+’) is the default symbol for flier points. Enter an empty string (‘’) if you don’t want to show fliers.
whis (default 1.5) defines the length of the whiskers as a function of the inner quartile range. They extend to the most extreme data point within ( whis*(75%-25%) ) data range.
positions (default 1,2,...,n) sets the horizontal positions of the boxes. The ticks and limits are automatically set to match the positions.
widths is either a scalar or a vector and sets the width of each box. The default is 0.5, or 0.15*(distance between extreme positions) if that is smaller.
x is an array or a sequence of vectors.
Returns a dictionary mapping each component of the boxplot to a list of the matplotlib.lines.Line2D instances created.
Example:
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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 alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] snap unknown transform Transform instance url a url string urls unknown visible [True | False] zorder any number
these can either be a single argument, ie:
facecolors = 'black'
or a sequence of arguments for the various bars, ie:
facecolors = ('black', 'red', 'green')
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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:
- See http://matplotlib.sf.net/fonts.html
- 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)
- 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).
- rightside_up:
- if True (default), label rotations will always be plus or minus 90 degrees from level.
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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(num) closes figure number num
close(h) where h is a Figure instance, closes that figure
close('all') closes all the figure windows
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)
cohere() the coherence between x and y. Coherence is the normalized cross spectral density:
Keyword arguments:
- NFFT: integer
- The number of data points used in each block for the FFT. Must be even; a power 2 is most efficient. The default value is 256.
- 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.
- detrend: 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.
- 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.
- noverlap: integer
- The number of points of overlap between blocks. The default value is 0 (no overlap).
- pad_to: integer
- The number of points to which the data segment is padded when performing the FFT. This can be different from NFFT, which specifies the number of data points used. While not increasing the actual resolution of the psd (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to NFFT
- sides: [ ‘default’ | ‘onesided’ | ‘twosided’ ]
- Specifies which sides of the PSD 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 PSD, while ‘twosided’ forces two-sided.
- scale_by_freq: boolean
- 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.
- Fc: integer
- The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband.
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 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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, hires.png, pdf]
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 from which space for a new colorbar axes will be stolen
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 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. 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.
matplotlib provides the following colormaps.
You can set the colormap for an image, pcolor, scatter, etc, either as a keyword argument:
imshow(X, cmap=cm.hot)
or post-hoc using the corresponding pylab interface function:
imshow(X)
hot()
jet()
In interactive mode, this will update the colormap allowing you to see which one works best for your data.
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 builtin 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 turqoise 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)
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 (TM) version in that it does not draw the polygon edges, because the contouring engine yields simply connected regions with branch cuts. To draw the 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, Y, and Z must be arrays with the same dimensions.
Z may be a masked array, but filled contouring may not handle internal masked regions correctly.
C = contour(...) returns a ContourSet 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.
- 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.cm.Colormap.set_under() and matplotlib.cm.Colormap.set_over() methods.
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 ‘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.
contourf-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.
Example:
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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 (TM) version in that it does not draw the polygon edges, because the contouring engine yields simply connected regions with branch cuts. To draw the 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, Y, and Z must be arrays with the same dimensions.
Z may be a masked array, but filled contouring may not handle internal masked regions correctly.
C = contour(...) returns a ContourSet 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.
- 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.cm.Colormap.set_under() and matplotlib.cm.Colormap.set_over() methods.
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 ‘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.
contourf-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.
Example:
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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, **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. 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.
Returns the tuple (Pxy, freqs). P is the cross spectrum
(complex valued), and 
is
plotted.
Keyword arguments:
- NFFT: integer
- The number of data points used in each block for the FFT. Must be even; a power 2 is most efficient. The default value is 256.
- 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.
- detrend: 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.
- 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.
- noverlap: integer
- The number of points of overlap between blocks. The default value is 0 (no overlap).
- pad_to: integer
- The number of points to which the data segment is padded when performing the FFT. This can be different from NFFT, which specifies the number of data points used. While not increasing the actual resolution of the psd (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to NFFT
- sides: [ ‘default’ | ‘onesided’ | ‘twosided’ ]
- Specifies which sides of the PSD 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 PSD, while ‘twosided’ forces two-sided.
- scale_by_freq: boolean
- 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.
- Fc: integer
- The center frequency of x (defaults to 0), which offsets the x extents of the plot to reflect the frequency range used when a signal is acquired and then filtered and downsampled to baseband.
kwargs control the Line2D properties:
Property Description 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
delaxes(ax): remove ax 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)
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)
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 +/- value.
If a rank-1, 2xN numpy array, errorbars are drawn at -row1 and +row2
- fmt: ‘-‘
- The plot format symbol for y. If fmt is None, just plot the errorbars with no line symbols. This can be useful for creating a bar plot with errorbars.
- ecolor: [ None | mpl color ]
- a matplotlib color arg which gives the color the errorbar lines; if None, use the marker color.
- elinewidth: scalar
- the linewidth of the errorbar lines. If None, use the linewidth.
- capsize: scalar
- the size of the error bar caps in points
- 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.
All other keyword arguments are passed on to the plot command for the markers, so you can add additional key=value pairs to control the errorbar 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 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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
Return value is a length 3 tuple. The first element is the Line2D instance for the y symbol lines. The second element is a list of error bar cap lines, the third element is a list of LineCollection instances for the horizontal and vertical error ranges.
Example:
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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.cm.ColorMap instance, eg 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 1.0 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, hires.png, pdf]
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
Call signature:
figtext(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 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 any string linespacing float (multiple of font size) lod [True | False] multialignment [‘left’ | ‘right’ | ‘center’ ] 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’ ] 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 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
call signature:
figure(num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')
Create a new figure and return a matplotlib.figure.Figure instance. If num = None, the figure number will be incremented and a new figure will be created. The returned figure objects have a number attribute holding this number.
If num is an integer, and figure(num) already exists, make it active and return a reference to it. If figure(num) does not exist it will be created. Numbering starts at 1, matlab style:
figure(1)
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.
Optional keyword arguments:
Keyword Description figsize width x height in inches; defaults to rc figure.figsize dpi resolution; defaults to rc figure.dpi facecolor the background color; defaults to rc figure.facecolor edgecolor the border color; defaults to rc figure.edgecolor
rcParams defines the default values, which can be modified in the matplotlibrc file
FigureClass is a Figure or derived class that will be passed on to new_figure_manager() in the backends which allows you to hook custom Figure classes into the pylab interface. Additional kwargs will be passed on to your figure init function.
call signature:
fill(*args, **kwargs)
Plot filled polygons. 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, eg. 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 alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
fill_between(x, y1, y2=0, where=None, **kwargs)
Create a PolyCollection filling the regions between y1 and y2 where where==True
kwargs control the Polygon properties:
Property Description alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] snap unknown transform Transform instance url a url string urls unknown visible [True | False] zorder any number
[source code, hires.png, pdf]
[source code, hires.png, pdf]
[source code, hires.png, pdf]
See also
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
fill_between(y, x1, x2=0, where=None, **kwargs)
Create a PolyCollection filling the regions between x1 and x2 where where==True
kwargs control the Polygon properties:
%(PolyCollection)s
[source code, hires.png, pdf]
[source code, hires.png, pdf]
See also
Additional kwargs: hold = [True|False] overrides default hold state
Recursively find all :class:matplotlib.artist.Artist instances contained in self.
match can be
- None: return all objects contained in artist (including artist)
- function with signature boolean = match(artist) used to filter matches
- class instance: eg Line2D. Only return artists of class type
[source code, hires.png, pdf]
Return the current axis instance. This can be used to control axis properties either using set or the Axes methods, for example, setting the xaxis range:
plot(t,s)
set(gca(), 'xlim', [0,10])
or:
plot(t,s)
a = gca()
a.set_xlim([0,10])
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.
call signature:
grid(self, b=None, **kwargs)
Set the axes grids on or off; b is a boolean
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
kawrgs are used to set the grid line properties, eg:
ax.grid(color='r', linestyle='-', linewidth=2)
Valid Line2D kwargs are
Property Description 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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
call signature:
hexbin(x, y, C = None, gridsize = 100, bins = None,
xscale = 'linear', yscale = 'linear',
cmap=None, norm=None, vmin=None, vmax=None,
alpha=1.0, 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:
- gridsize: [ 100 | integer ]
- The number of hexagons in the x-direction, default is 100. The corresponding number of hexagons in the y-direction is chosen such that the hexagons are approximately regular. Alternatively, gridsize can be a tuple with two elements specifying the number of hexagons in the x-direction and the y-direction.
- bins: [ None | ‘log’ | integer | sequence ]
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.
- xscale: [ ‘linear’ | ‘log’ ]
- Use a linear or log10 scale on the horizontal axis.
- scale: [ ‘linear’ | ‘log’ ]
- Use a linear or log10 scale on the vertical axis.
- mincnt: None | a positive integer
- If not None, only display cells with more than mincnt number of points in the cell
- marginals: True|False
- if marginals is True, plot the marginal density as colormapped rectagles along the bottom of the x-axis and left of the y-axis
- extent: [ None | scalars (left, right, bottom, top) ]
- The limits of the bins. The default assigns the limits based on gridsize, x, y, xscale and yscale.
Other keyword arguments controlling color mapping and normalization arguments:
- cmap: [ None | Colormap ]
- a matplotlib.cm.Colormap instance. If None, defaults to rc image.cmap.
- norm: [ None | Normalize ]
- matplotlib.colors.Normalize instance is used to scale luminance data to 0,1.
- vmin/vmax: scalar
- vmin and vmax are used in conjunction with norm to normalize luminance data. If either are None, the min and max of the color array C is used. Note if you pass a norm instance, your settings for vmin and vmax will be ignored.
- alpha: scalar
- the alpha value for the patches
- linewidths: [ None | scalar ]
- If None, defaults to rc lines.linewidth. Note that this is a tuple, and if you set the linewidths argument you must set it as a sequence of floats, as required by RegularPolyCollection.
Other keyword arguments controlling the Collection properties:
- edgecolors: [ None | mpl color | color sequence ]
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 alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] 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, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
hist(x, bins=10, range=None, normed=False, cumulative=False,
bottom=None, histtype='bar', align='mid',
orientation='vertical', rwidth=None, log=False, **kwargs)
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.
Keyword arguments:
- bins:
- Either an integer number of bins or a sequence giving the bins. x are the data to be binned. x can be an array, a 2D array with multiple data in its columns, or a list of arrays with data of different length. Note, if bins is an integer input argument=numbins, bins + 1 bin edges will be returned, compatible with the semantics of numpy.histogram() with the new = True argument. Unequally spaced bins are supported if bins is a sequence.
- range:
The lower and upper range of the bins. Lower and upper outliers are ignored. If not provided, range is (x.min(), x.max()). Range has no effect if bins is a sequence.
If bins is a sequence or range is specified, autoscaling is set off (autoscale_on is set to False) and the xaxis limits are set to encompass the full specified bin range.
- normed:
If True, the first element of the return tuple will be the counts normalized to form a probability density, i.e., n/(len(x)*dbin). In a probability density, the integral of the histogram should be 1; you can verify that with a trapezoidal integration of the probability density function:
pdf, bins, patches = ax.hist(...) print np.sum(pdf * np.diff(bins))- weights
- An array of weights, of the same shape as x. Each value in x only contributes its associated weight towards the bin count (instead of 1). If normed is True, the weights are normalized, so that the integral of the density over the range remains 1.
- cumulative:
- If True, then a histogram is computed where each bin gives the counts in that bin plus all bins for smaller values. The last bin gives the total number of datapoints. If normed is also True then the histogram is normalized such that the last bin equals 1. If cumulative evaluates to less than 0 (e.g. -1), the direction of accumulation is reversed. In this case, if normed is also True, then the histogram is normalized such that the first bin equals 1.
- histtype: [ ‘bar’ | ‘barstacked’ | ‘step’ | ‘stepfilled’ ]
The type of histogram to draw.
- ‘bar’ is a traditional bar-type histogram. If multiple data are given the bars are aranged side by side.
- ‘barstacked’ is a bar-type histogram where multiple data are stacked on top of each other.
- ‘step’ generates a lineplot that is by default unfilled.
- ‘stepfilled’ generates a lineplot that is by default filled.
- align: [‘left’ | ‘mid’ | ‘right’ ]
Controls how the histogram is plotted.
- ‘left’: bars are centered on the left bin edges.
- ‘mid’: bars are centered between the bin edges.
- ‘right’: bars are centered on the right bin edges.
- orientation: [ ‘horizontal’ | ‘vertical’ ]
- If ‘horizontal’, barh() will be used for bar-type histograms and the bottom kwarg will be the left edges.
- rwidth:
- The relative width of the bars as a fraction of the bin width. If None, automatically compute the width. Ignored if histtype = ‘step’ or ‘stepfilled’.
- log:
- If True, the histogram axis will be set to a log scale. If log is True and x is a 1D array, empty bins will be filtered out and only the non-empty (n, bins, patches) will be returned.
kwargs are used to update the properties of the hist Rectangle instances:
Property Description alpha float (0.0 transparent through 1.0 opaque) animated [True | False] antialiased or aa [True | False] or None for default axes an Axes instance clip_box a matplotlib.transforms.Bbox instance clip_on [True | False] clip_path [ (Path, Transform) | Patch | None ] color matplotlib color arg or sequence of rgba tuples 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’ | ‘.’ | ‘*’ ] label any string linestyle or ls [‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’] linewidth or lw float or None for default lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
You can use labels for your histogram, and only the first Rectangle gets the label (the others get the magic string ‘_nolegend_’. This will make the histograms work in the intuitive way for bar charts:
ax.hist(10+2*np.random.randn(1000), label='men')
ax.hist(12+3*np.random.randn(1000), label='women', alpha=0.5)
ax.legend()
label can also be a sequence of strings. If multiple data is provided in x, the labels are asigned sequentially to the histograms.
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
hlines(y, xmin, xmax, colors='k', linestyles='solid', **kwargs)
Plot horizontal lines at each y from xmin to xmax.
Returns the LineCollection that was added.
Required arguments:
- y:
- a 1-D numpy array or iterable.
- xmin and xmax:
- can be scalars or len(x) numpy arrays. If they are scalars, then the respective values are constant, else the widths of the lines are determined by xmin and xmax.
Optional keyword arguments:
- colors:
- a line collections color argument, either a single color or a len(y) list of colors
- linestyles:
- [ ‘solid’ | ‘dashed’ | ‘dashdot’ | ‘dotted’ ]
Example:
[source code, hires.png, pdf]
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.
Return image file in fname as numpy.array.
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().
Saves a 2D numpy.array as an image with one pixel per element. The output formats available depend on the backend being used.
call signature:
imshow(X, cmap=None, norm=None, aspect=None, interpolation=None,
alpha=1.0, vmin=None, vmax=None, origin=None, extent=None,
**kwargs)
Display the image in X to current axes. X may be a float array, a uint8 array or a PIL image. If X is an array, X can have the following shapes:
The value for each component of MxNx3 and MxNx4 float arrays should be in the range 0.0 to 1.0; MxN float arrays may be normalised.
An matplotlib.image.AxesImage instance is returned.
Keyword arguments:
- cmap: [ None | Colormap ]
A matplotlib.cm.Colormap instance, eg. cm.jet. If None, default to rc image.cmap value.
cmap is ignored when X has RGB(A) information
- aspect: [ None | ‘auto’ | ‘equal’ | scalar ]
If ‘auto’, changes the image aspect ratio to match that of the axes
If ‘equal’, and extent is None, changes the axes aspect ratio to match that of the image. If extent is not None, the axes aspect ratio is changed to match that of the extent.
If None, default to rc image.aspect value.
interpolation:
- Acceptable values are None, ‘nearest’, ‘bilinear’,
- ‘bicubic’, ‘spline16’, ‘spline36’, ‘hanning’, ‘hamming’, ‘hermite’, ‘kaiser’, ‘quadric’, ‘catrom’, ‘gaussian’, ‘bessel’, ‘mitchell’, ‘sinc’, ‘lanczos’,
If interpolation is None, default to rc image.interpolation. See also the filternorm and filterrad parameters
- norm: [ None | Normalize ]
An matplotlib.colors.Normalize instance; if None, default is normalization(). This scales luminance -> 0-1
norm is only used for an MxN float array.
- vmin/vmax: [ None | scalar ]
- 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 norm is not None, the settings for vmin and vmax will be ignored.
- alpha: scalar
- The alpha blending value, between 0 (transparent) and 1 (opaque)
- origin: [ None | ‘upper’ | ‘lower’ ]
- Place the [0,0] index of the array in the upper left or lower left corner of the axes. If None, default to rc image.origin.
- extent: [ None | scalars (left, right, bottom, top) ]
- Data limits for the axes. The default assigns zero-based row, column indices to the x, y centers of the pixels.
- shape: [ None | scalars (columns, rows) ]
- For raw buffer images
- filternorm:
- A parameter for the antigrain image resize filter. From the antigrain documentation, if filternorm = 1, the filter normalizes integer values and corrects the rounding errors. It doesn’t do anything with the source floating point values, it corrects only integers according to the rule of 1.0 which means that any sum of pixel weights must be equal to 1.0. So, the filter function must produce a graph of the proper shape.
- filterrad:
- The filter radius for filters that have a radius parameter, i.e. when interpolation is one of: ‘sinc’, ‘lanczos’ or ‘blackman’
Additional kwargs are Artist properties:
Property Description 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 gid an id string label any string lod [True | False] picker [None|float|boolean|callable] rasterized [True | False | None] snap unknown transform Transform instance url a url string visible [True | False] zorder any number
Example:
[source code, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
call signature:
legend(*args, **kwargs)
Place a legend on the current axes at location loc. Labels are a sequence of strings and loc can be a string or an integer specifying the legend location.
To make a legend with existing lines:
legend()
legend() by itself will try and build a legend using the label property of the lines/patches/collections. You can set the label of a line by doing:
plot(x, y, label='my data')
or:
line.set_label('my data').
If label is set to ‘_nolegend_’, the item will not be shown in legend.
To automatically generate the legend from labels:
legend( ('label1', 'label2', 'label3') )
To make a legend for a list of lines and labels:
legend( (line1, line2, line3), ('label1', 'label2', 'label3') )
To make a legend at a given location, using a location argument:
legend( ('label1', 'label2', 'label3'), loc='upper left')
or:
legend( (line1, line2, line3), ('label1', 'label2', 'label3'), loc=2)
The location codes are
Location String Location Code ‘best’ 0 ‘upper right’ 1 ‘upper left’ 2 ‘lower left’ 3 ‘lower right’ 4 ‘right’ 5 ‘center left’ 6 ‘center right’ 7 ‘lower center’ 8 ‘upper center’ 9 ‘center’ 10
Users can specify any arbitrary location for the legend using the bbox_to_anchor keyword argument. bbox_to_anchor can be an instance of BboxBase(or its derivatives) or a tuple of 2 or 4 floats. For example,
loc = ‘upper right’, bbox_to_anchor = (0.5, 0.5)
will place the legend so that the upper right corner of the legend at the center of the axes.
The legend location can be specified in other coordinate, by using the bbox_transform keyword.
The loc itslef can be a 2-tuple giving x,y of the lower-left corner of the legend in axes coords (bbox_to_anchor is ignored).
Keyword arguments:
- prop: [ None | FontProperties | dict ]
- A matplotlib.font_manager.FontProperties instance. If prop is a dictionary, a new instance will be created with prop. If None, use rc settings.
- numpoints: integer
- The number of points in the legend for line
- scatterpoints: integer
- The number of points in the legend for scatter plot
- scatteroffsets: list of floats
- a list of yoffsets for scatter symbols in legend
- markerscale: [ None | scalar ]
- The relative size of legend markers vs. original. If None, use rc settings.
- fancybox: [ None | False | True ]
- if True, draw a frame with a round fancybox. If None, use rc
- shadow: [ None | False | True ]
- If True, draw a shadow behind legend. If None, use rc settings.
- ncol : integer
- number of columns. default is 1
- mode : [ “expand” | None ]
- if mode is “expand”, the legend will be horizontally expanded to fill the axes area (or bbox_to_anchor)
- bbox_to_anchor : an instance of BboxBase or a tuple of 2 or 4 floats
- the bbox that the legend will be anchored.
- bbox_transform : [ an instance of Transform | None ]
- the transform for the bbox. transAxes if None.
- title : string
- the legend title
Padding and spacing between various elements use following keywords parameters. The dimensions of these values are given as a fraction of the fontsize. Values from rcParams will be used if None.
| Keyword | Description |
|---|---|
| borderpad | the fractional whitespace inside the legend border |
| labelspacing | the vertical space between the legend entries |
| handlelength | the length of the legend handles |
| handletextpad | the pad between the legend handle and text |
| borderaxespad | the pad between the axes and legend border |
| columnspacing | the spacing between columns |
Example:
[source code, hires.png, pdf]
Also see Legend guide.
call signature:
loglog(*args, **kwargs)
Make a plot with log scaling on the x and y axis.
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 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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, hires.png, pdf]
Additional kwargs: hold = [True|False] overrides default hold state
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().
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.
Display minor ticks on the current plot.
Displaying minor ticks reduces performance; turn them off using minorticks_off() if drawing speed is a problem.
over calls:
func(*args, **kwargs)
with hold(True) and then restores the hold state.
call signatures:
pcolor(C, **kwargs)
pcolor(X, Y, C, **kwargs)
Create a pseudocolor plot of a 2-D array.
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.cm.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 are None, the min and max of the color array C is used. If you pass a norm instance, vmin and vmax will be ignored.
- 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(TM).
- 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
- the alpha blending value
Return value is a matplotlib.collection.Collection instance.
The grid orientation follows the Matlab(TM) 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 = 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:
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 alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] 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
call signatures:
pcolormesh(C)
pcolormesh(X, Y, C)
pcolormesh(C, **kwargs)
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.cm.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 are None, the min and max of the color array C is used. If you pass a norm instance, vmin and vmax will be ignored.
- 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(TM).
- 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
- the alpha blending value
Return value is a matplotlib.collection.QuadMesh object.
kwargs can be used to control the matplotlib.collections.QuadMesh properties:
Property Description alpha float 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 colorbar unknown 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 label any string 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 offsets float or sequence of floats picker [None|float|boolean|callable] pickradius unknown rasterized [True | False | None] 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
call signature:
pie(x, explode=None, labels=None,
colors=('b', 'g', 'r', 'c', 'm', 'y', 'k', 'w'),
autopct=None, pctdistance=0.6, labeldistance=1.1, shadow=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.
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.
The pie chart will probably look best if the figure and axes are square. Eg.:
figure(figsize=(8,8))
ax = axes([0.1, 0.1, 0.8, 0.8])
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
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.
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
:class:`~matplotlib.lines.Line2D` for details.
The kwargs are Line2D properties:
Property Description 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance fillstyle [‘full’ | ‘left’ | ‘right’ | ‘bottom’ | ‘top’] gid an id string label any string linestyle or ls [ ‘-‘ | ‘–’ | ‘-.’ | ‘:’ | ‘None’ | ‘ ‘ | ‘’ ] and any drawstyle in combination with a linestyle, e.g. ‘steps–’. linewidth or lw float value in points lod [True | False] marker [ ‘+’ | ‘*’ | ‘,’ | ‘.’ | ‘1’ | ‘2’ | ‘3’ | ‘4’ | ‘<’ | ‘>’ | ‘D’ | ‘H’ | ‘^’ | ‘_’ | ‘d’ | ‘h’ | ‘o’ | ‘p’ | ‘s’ | ‘v’ | ‘x’ | ‘|’ | TICKUP | TICKDOWN | TICKLEFT | TICKRIGHT | ‘None’ | ‘ ‘ | ‘’ ] markeredgecolor or mec any matplotlib color markeredgewidth or mew float value in points markerfacecolor or mfc any matplotlib color markersize or ms float markevery None | integer | (startind, stride) picker float distance in points or callable pick function fn(artist, event) pickradius float distance in points rasterized [True | False | None] 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
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 ]
- 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 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 data 2D array drawstyle [ ‘default’ | ‘steps’ | ‘steps-pre’ | ‘steps-mid’ | ‘steps-post’ ] figure a matplotlib.figure.Figure instance