| | |
- acorr(*args, **kwargs)
- call signature::
acorr(x, normed=False, detrend=mlab.detrend_none, usevlines=False,
maxlags=None, **kwargs)
Plot the autocorrelation of *x*. If *normed* = *True*,
normalize the data but 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:
- *lags* are a length 2*maxlags+1 lag vector
- *c* is the 2*maxlags+1 auto correlation vector
- *line* is a :class:`~matplotlib.lines.Line2D` instance
returned by :meth:`plot`
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 :func:`numpy.correlate` with
*mode* = 2.
If *usevlines* is *True*, :meth:`~matplotlib.axes.Axes.vlines`
rather than :meth:`~matplotlib.axes.Axes.plot` is used to draw
vertical lines from the origin to the acorr. Otherwise, the
plot style is determined by the kwargs, which are
:class:`~matplotlib.lines.Line2D` properties. The return
value is a tuple (*lags*, *c*, *linecol*, *b*) where
- *linecol* is the
:class:`~matplotlib.collections.LineCollection`
- *b* is the *x*-axis.
*maxlags* is a positive integer detailing the number of lags
to show. The default value of *None* will return all
``(2*len(x)-1)`` lags.
See the respective :meth:`~matplotlib.axes.Axes.plot` or
:meth:`~matplotlib.axes.Axes.vlines` functions for
documentation on valid kwargs.
**Example:**
:func:`~matplotlib.pyplot.xcorr` above, and
:func:`~matplotlib.pyplot.acorr` below.
**Example:**
.. plot:: ../mpl_examples/pylab_examples/xcorr_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- annotate(*args, **kwargs)
- 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 :class:`matplotlib.lines.Line2D`) for the arrow that connects
annotation to the point. Valid keys 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 :class:`matplotlib.patches.polygon`
========= ===========================================================
*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
animated [True | False]
axes an axes instance
backgroundcolor any matplotlib color
bbox rectangle prop dict plus key 'pad' which is a pad in points
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color any matplotlib color
contains unknown
family [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]
figure a :class:`matplotlib.figure.Figure` instance
fontproperties a matplotlib.font_manager.FontProperties instance
horizontalalignment or ha [ 'center' | 'right' | 'left' ]
label any string
linespacing float
lod [True | False]
multialignment ['left' | 'right' | 'center' ]
name or fontname string eg, ['Sans' | 'Courier' | 'Helvetica' ...]
picker [None|float|boolean|callable]
position (x,y)
rotation [ angle in degrees 'vertical' | 'horizontal'
size or fontsize [ size in points | relative size eg 'smaller', 'x-large' ]
style or fontstyle [ 'normal' | 'italic' | 'oblique']
text string or anything printable with '%s' conversion
transform unknown
variant [ 'normal' | 'small-caps' ]
verticalalignment or va [ 'center' | 'top' | 'bottom' | 'baseline' ]
visible [True | False]
weight or fontweight [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']
x float
y float
zorder any number
========================= =====================================================================
- arrow(*args, **kwargs)
- 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
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/arrow_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- autumn()
- Set the default colormap to *autumn* and apply to current image if any.
See :func:`colormaps` for more information.
- axes(*args, **kwargs)
- Add an axes at position rect specified by:
- ``axes()`` by itself creates a default full ``subplot(111)`` window axis.
- ``axes(rect, axisbg='w')`` where *rect* = [left, bottom, width,
height] in normalized (0, 1) units. *axisbg* is the background
color for the axis, default white.
- ``axes(h)`` where *h* is an axes instance makes *h* the current
axis. An :class:`~matplotlib.axes.Axes` instance is returned.
======= ============ ================================================
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:
* :file:`examples/pylab_examples/axes_demo.py` places custom axes.
* :file:`examples/pylab_examples/shared_axis_demo.py` uses
*sharex* and *sharey*.
- axhline(*args, **kwargs)
- 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
:meth:`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 :class:`~matplotlib.lines.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 :class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
See :meth:`axhspan` for example plot and source code
Additional kwargs: hold = [True|False] overrides default hold state
- axhspan(*args, **kwargs)
- 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 span the xrange, regardless of the xlim settings, even
if you change them, eg. with the :meth:`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 :class:`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 :class:`~matplotlib.patches.Polygon` properties:
=========== ===========================================================
Property Description
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/axhspan_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- axis(*v, **kwargs)
- 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. See :func:`xlim` and :func:`ylim` for more information
The xmin, xmax, ymin, ymax tuple is returned
- axvline(*args, **kwargs)
- 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
xlim settings, even if you change them, eg. with the
:meth:`set_xlim` 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 :class:`~matplotlib.lines.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 :class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
See :meth:`axhspan` for example plot and source code
Additional kwargs: hold = [True|False] overrides default hold state
- axvspan(*args, **kwargs)
- 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
span the yrange, regardless of the ylim settings, even if you
change them, eg. with the :meth:`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 :class:`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 :class:`~matplotlib.patches.Polygon`
properties:
=========== ===========================================================
Property Description
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
See :meth:`axhspan` for example plot and source code
Additional kwargs: hold = [True|False] overrides default hold state
- bar(*args, **kwargs)
- 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
:class:`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
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
**Example:** A stacked bar chart.
.. plot:: ../mpl_examples/pylab_examples/bar_stacked.py
Additional kwargs: hold = [True|False] overrides default hold state
- barbs(*args, **kwargs)
- 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 :func:`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 :class:`~matplotlib.collections.PolyCollection`
keyword arguments:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- barh(*args, **kwargs)
- 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
:class:`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
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
Additional kwargs: hold = [True|False] overrides default hold state
- bone()
- Set the default colormap to bone and apply to current image if any.
See :func:`colormaps` for more information.
- box(on=None)
- Turn the axes box on or off according to *on*.
If *on* is *None*, toggle state.
- boxplot(*args, **kwargs)
- 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.
- *notch* = 0 (default) produces a rectangular box plot.
- *notch* = 1 will produce a notched box plot
*sym* (default 'b+') is the default symbol for flier points.
Enter an empty string ('') if you don't want to show fliers.
- *vert* = 1 (default) makes the boxes vertical.
- *vert* = 0 makes horizontal boxes. This seems goofy, but
that's how Matlab did it.
*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 list of the :class:`matplotlib.lines.Line2D`
instances added.
**Example:**
.. plot:: boxplot_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- broken_barh(*args, **kwargs)
- 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
:class:`matplotlib.collections.BrokenBarHCollection`
properties:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform 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:**
.. plot:: ../mpl_examples/pylab_examples/broken_barh.py
Additional kwargs: hold = [True|False] overrides default hold state
- cla(*args, **kwargs)
- Clear the current axes
- clabel(*args, **kwargs)
- call signature::
clabel(cs, **kwargs)
adds labels to line contours in *cs*, where *cs* is a
:class:`~matplotlib.contour.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
.. TODO: Update this link to new fonts document
*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.
Additional kwargs: hold = [True|False] overrides default hold state
- clf()
- Clear the current figure
- clim(vmin=None, vmax=None)
- Set the color limits of the current image
To apply clim to all axes images do::
clim(0, 0.5)
If either *vmin* or *vmax* is None, the image min/max respectively
will be used for color scaling.
If you want to set the clim of multiple images,
use, for example::
for im in gca().get_images():
im.set_clim(0, 0.05)
- close(*args)
- Close a figure window
``close()`` by itself closes the current figure
``close(num)`` closes figure number *num*
``close(h)`` where *h* is a :class:`Figure` instance, closes that figure
``close('all')`` closes all the figure windows
- cohere(*args, **kwargs)
- call signature::
cohere(x, y, NFFT=256, Fs=2, Fc=0, detrend = mlab.detrend_none,
window = mlab.window_hanning, noverlap=0, **kwargs)
cohere the coherence between *x* and *y*. Coherence is the normalized
cross spectral density:
.. math::
C_{xy} = \frac{|P_{xy}|^2}{P_{xx}*P_{yy}}
The return value is a tuple (*Cxy*, *f*), where *f* are the
frequencies of the coherence vector.
See the :meth:`psd` for a description of the optional parameters.
kwargs are applied to the lines.
References:
* Bendat & Piersol -- Random Data: Analysis and Measurement
Procedures, John Wiley & Sons (1986)
kwargs control the :class:`~matplotlib.lines.Line2D`
properties of the coherence plot:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/cohere_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- colorbar(mappable=None, cax=None, ax=None, **kw)
- Add a colorbar to a plot.
Function signatures for the :mod:`~matplotlib.pyplot` interface; all
but the first are also method signatures for the
:meth:`matplotlib.Figure.colorbar` method::
colorbar(**kwargs)
colorbar(mappable, **kwargs)
colorbar(mappable, cax=cax, **kwargs)
colorbar(mappable, ax=ax, **kwargs)
arguments:
*mappable*
the image, :class:`~matplotlib.contours.ContourSet`, etc. to
which the colorbar applies; this argument is mandatory for the
:meth:`matplotlib.Figure.colorbar` method but optional for the
:func:`matplotlib.pyplot.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
========== ====================================================
*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
:class:`~matplotlib.ticker.ScalarFormatter` is used.
If a format string is given, e.g. '%.3f', that is
used. An alternative
:class:`~matplotlib.ticker.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 :class:`~matplotlib.contours.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.
- colormaps()
- matplotlib provides the following colormaps.
* autumn
* bone
* cool
* copper
* flag
* gray
* hot
* hsv
* jet
* pink
* prism
* spring
* summer
* winter
* spectral
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.
- colors()
- This is a do nothing function to provide you with help on how
matplotlib handles colors.
Commands which take color arguments can use several formats to
specify the colors. For the basic 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(s, func)
- Connect event with string *s* to *func*. The signature of *func* is::
def func(event)
where event is a :class:`matplotlib.backend_bases.Event`. The
following events are recognized
- 'button_press_event'
- 'button_release_event'
- 'draw_event'
- 'key_press_event'
- 'key_release_event'
- 'motion_notify_event'
- 'pick_event'
- 'resize_event'
- 'scroll_event'
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 :class:`~matplotlib.axes.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
:class:`~matplotlib.backend_bases.KeyEvent` and
:class:`~matplotlib.backend_bases.MouseEvent` for more info.
Return value is a connection id that can be used with
:meth:`~matplotlib.backend_bases.Event.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(*args, **kwargs)
- :func:`~matplotlib.pyplot.contour` and
:func:`~matplotlib.pyplot.contourf` draw contour lines and
filled contours, respectively. Except as noted, function
signatures and return values are the same for both versions.
:func:`~matplotlib.pyplot.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 :func:`~matplotlib.pyplot.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
:class:`~matplotlib.contour.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 :class:`~matplotlib.cm.Colormap` instance or
*None*. If *cmap* is *None* and *colors* is *None*, a
default Colormap is used.
*norm*: [ None | Normalize ]
A :class:`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 :func:`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
:class:`~matplotlib.ticker.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
:meth:`matplotlib.cm.Colormap.set_under` and
:meth:`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
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:**
.. plot:: contour_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- contourf(*args, **kwargs)
- :func:`~matplotlib.pyplot.contour` and
:func:`~matplotlib.pyplot.contourf` draw contour lines and
filled contours, respectively. Except as noted, function
signatures and return values are the same for both versions.
:func:`~matplotlib.pyplot.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 :func:`~matplotlib.pyplot.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
:class:`~matplotlib.contour.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 :class:`~matplotlib.cm.Colormap` instance or
*None*. If *cmap* is *None* and *colors* is *None*, a
default Colormap is used.
*norm*: [ None | Normalize ]
A :class:`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 :func:`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
:class:`~matplotlib.ticker.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
:meth:`matplotlib.cm.Colormap.set_under` and
:meth:`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
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:**
.. plot:: contour_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- cool()
- Set the default colormap to cool and apply to current image if any.
See :func:`colormaps` for more information.
- copper()
- Set the default colormap to copper and apply to current image if any.
See :func:`colormaps` for more information.
- csd(*args, **kwargs)
- call signature::
csd(x, y, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
window=window_hanning, noverlap=0, **kwargs)
The cross spectral density :math:`P_{xy}` by Welches 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 :math:`P_{xy}`, with a scaling to correct for power
loss due to windowing.
See :meth:`psd` for a description of the optional parameters.
Returns the tuple (*Pxy*, *freqs*). *P* is the cross spectrum
(complex valued), and :math:`10\log_{10}|P_{xy}|` is
plotted.
References:
Bendat & Piersol -- Random Data: Analysis and Measurement
Procedures, John Wiley & Sons (1986)
kwargs control the Line2D properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/csd_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- delaxes(*args)
- ``delaxes(ax)``: remove *ax* from the current figure. If *ax*
doesn't exist, an error will be raised.
``delaxes()``: delete the current axes
- disconnect(cid)
- disconnect callback id cid
Example usage::
cid = canvas.mpl_connect('button_press_event', on_press)
#...later
canvas.mpl_disconnect(cid)
- draw()
- redraw the current figure
- errorbar(*args, **kwargs)
- 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, Nx2 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, Nx2 Numpy array, errorbars are drawn at -column1 and
+column2
*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
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
Return value is a length 3 tuple. The first element is the
:class:`~matplotlib.lines.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
:class:`~matplotlib.collections.LineCollection` instances for
the horizontal and vertical error ranges.
**Example:**
.. plot:: errorbar_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- figimage(*args, **kwargs)
- 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:
* If *X* is MxN, assume luminance (grayscale)
* If *X* is MxNx3, assume RGB
* If *X* is MxNx4, assume RGBA
Optional keyword arguments:
========= ==========================================================
Keyword Description
========= ==========================================================
xo or yo An integer, the *x* and *y* image offset in pixels
cmap a :class:`matplotlib.cm.ColorMap` instance, eg cm.jet.
If None, default to the rc ``image.cmap`` value
norm a :class:`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
(:meth:`~matplotlib.axes.Axes.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
:class:`~matplotlib.axes.Axes` with size [0,1,0,1].
An :class:`matplotlib.image.FigureImage` instance is returned.
.. plot:: ../mpl_examples/pylab_examples/figimage_demo.py
Addition kwargs: hold = [True|False] overrides default hold state
- figlegend(handles, labels, loc, **kwargs)
- Place a legend in the figure.
*labels*
a sequence of strings
*handles*
a sequence of :class:`~matplotlib.lines.Line2D` or
:class:`~matplotlib.patches.Patch` instances
*loc*
can be a string or an integer specifying the legend
location
Example::
figlegend( (line1, line2, line3),
('label1', 'label2', 'label3'),
'upper right' )
See :func:`~matplotlib.pyplot.legend` for information about the
location codes
A :class:`matplotlib.legend.Legend` instance is returned.
- figtext(*args, **kwargs)
- Call signature::
figtext(x, y, s, fontdict=None, **kwargs)
Add text to figure at location *x*, *y* (relative 0-1
coords). See :func:`~matplotlib.pyplot.text` for the meaning
of the other arguments.
kwargs control the :class:`~matplotlib.text.Text` properties:
========================= =====================================================================
Property Description
========================= =====================================================================
alpha float
animated [True | False]
axes an axes instance
backgroundcolor any matplotlib color
bbox rectangle prop dict plus key 'pad' which is a pad in points
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color any matplotlib color
contains unknown
family [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]
figure a :class:`matplotlib.figure.Figure` instance
fontproperties a matplotlib.font_manager.FontProperties instance
horizontalalignment or ha [ 'center' | 'right' | 'left' ]
label any string
linespacing float
lod [True | False]
multialignment ['left' | 'right' | 'center' ]
name or fontname string eg, ['Sans' | 'Courier' | 'Helvetica' ...]
picker [None|float|boolean|callable]
position (x,y)
rotation [ angle in degrees 'vertical' | 'horizontal'
size or fontsize [ size in points | relative size eg 'smaller', 'x-large' ]
style or fontstyle [ 'normal' | 'italic' | 'oblique']
text string or anything printable with '%s' conversion
transform unknown
variant [ 'normal' | 'small-caps' ]
verticalalignment or va [ 'center' | 'top' | 'bottom' | 'baseline' ]
visible [True | False]
weight or fontweight [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']
x float
y float
zorder any number
========================= =====================================================================
- figure(num=None, figsize=None, dpi=None, facecolor=None, edgecolor=None, frameon=True, FigureClass=<class 'matplotlib.figure.Figure'>, **kwargs)
- call signature::
figure(num = None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')
Create a new figure and return a :class:`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 the handle 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 :class:`~matplotlib.figure.Figure` or derived
class that will be passed on to :meth:`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.
- fill(*args, **kwargs)
- 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 :func:`~matplotlib.pyplot.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 :class:`~matplotlib.patches.Patch`
instances that were added.
The same color strings that :func:`~matplotlib.pyplot.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
:func:`~matplotlib.pylab.poly_between`, eg.::
xs, ys = poly_between(x, 0, y)
axes.fill(xs, ys, facecolor='red', alpha=0.5)
See :file:`examples/pylab_examples/fill_between.py` for more examples.
The *closed* kwarg will close the polygon when *True* (default).
kwargs control the Polygon properties:
=========== ===========================================================
Property Description
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/fill_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- findobj(o=None, match=None)
- pyplot signature:
findobj(o=gcf(), match=None)
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
.. plot:: ../mpl_examples/pylab_examples/findobj_demo.py
- flag()
- Set the default colormap to flag and apply to current image if any.
See :func:`colormaps` for more information.
- gca(**kwargs)
- Return the current axis instance. This can be used to control
axis properties either using set or the
:class:`~matplotlib.axes.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])
- gcf()
- Return a handle to the current figure.
- gci()
- Get the current :class:`~matplotlib.cm.ScalarMappable` instance
(image or patch collection), or *None* if no images or patch
collections have been defined. The commands
:func:`~matplotlib.pyplot.imshow` and
:func:`~matplotlib.pyplot.figimage` create
:class:`~matplotlib.image.Image` instances, and the commands
:func:`~matplotlib.pyplot.pcolor` and
:func:`~matplotlib.pyplot.scatter` create
:class:`~matplotlib.collections.Collection` instances.
- get_current_fig_manager()
- get_plot_commands()
- ginput(*args, **kwargs)
- call signature::
ginput(self, n=1, timeout=30, show_clicks=True)
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 negative, does not timeout.
If *n* is negative, accumulate clicks until a middle click
terminates the input.
Right clicking cancels last input.
- gray()
- Set the default colormap to gray and apply to current image if any.
See :func:`colormaps` for more information.
- grid(*args, **kwargs)
- 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 :class:`~matplotlib.lines.Line2D` kwargs are
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
- hexbin(*args, **kwargs)
- 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,
**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, :math:`log_{10}(i+1)` 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.
Other keyword arguments controlling color mapping and normalization
arguments:
*cmap*: [ None | Colormap ]
a :class:`matplotlib.cm.Colormap` instance. If *None*,
defaults to rc ``image.cmap``.
*norm*: [ None | Normalize ]
:class:`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
:class:`~matplotlib.collections.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
:class:`~matplotlib.collections.Collection` kwargs:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
The return value is a
:class:`~matplotlib.collections.PolyCollection` instance; use
:meth:`~matplotlib.collection.PolyCollection.get_array` on
this :class:`~matplotlib.collections.PolyCollection` to get
the counts in each hexagon.
**Example:**
.. plot:: ../mpl_examples/pylab_examples/hexbin_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- hist(*args, **kwargs)
- 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 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 or a
2D array with multiple data in its columns. Note, if *bins*
is an integer input argument=numbins, *bins* + 1 bin edges
will be returned, compatible with the semantics of
:func:`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.
*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))
*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 one. 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
- '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 this 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', :func:`~matplotlib.pyplot.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'.
*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
:class:`~matplotlib.patches.Rectangle` instances:
=========== ===========================================================
Property Description
=========== ===========================================================
aa [True | False] or None for default
alpha float
animated [True | False]
antialiased [True | False] or None for default
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
ec mpl color spec, or None for default, or 'none' for no color
edgecolor mpl color spec, or None for default, or 'none' for no color
facecolor mpl color spec, or None for default, or 'none' for no color
fc mpl color spec, or None for default, or 'none' for no color
figure a :class:`matplotlib.figure.Figure` instance
fill [True | False]
hatch unknown
label any string
linestyle ['solid' | 'dashed' | 'dashdot' | 'dotted']
linewidth float or None for default
lod [True | False]
ls ['solid' | 'dashed' | 'dashdot' | 'dotted']
lw float or None for default
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
=========== ===========================================================
You can use labels for your histogram, and only the first
:class:`~matplotlib.patches.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()
**Example:**
.. plot:: ../mpl_examples/pylab_examples/histogram_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- hlines(*args, **kwargs)
- call signature::
hlines(y, xmin, xmax, colors='k', linestyle='solid', **kwargs)
Plot horizontal lines at each *y* from *xmin* to *xmax*.
Returns the :class:`~matplotlib.collections.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
*linestyle*:
[ 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
**Example:**
.. plot:: ../mpl_examples/pylab_examples/hline_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- hold(b=None)
- 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.
- hot()
- Set the default colormap to hot and apply to current image if any.
See :func:`colormaps` for more information.
- hsv()
- Set the default colormap to hsv and apply to current image if any.
See :func:`colormaps` for more information.
- imread(*args, **kwargs)
- Return image file in *fname* as :class:`numpy.array`.
Return value is a :class:`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
<http://www.pythonware.com/products/pil/>`_ is installed, it will
use it to load the image and return an array (if possible) which
can be used with :func:`~matplotlib.pyplot.imshow`.
TODO: support RGB and grayscale return values in _image.readpng
- imshow(*args, **kwargs)
- 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:
* MxN -- luminance (grayscale, float array only)
* MxNx3 -- RGB (float or uint8 array)
* MxNx4 -- RGBA (float or uint8 array)
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 :class:`matplotlib.image.AxesImage` instance is returned.
Keyword arguments:
*cmap*: [ None | Colormap ]
A :class:`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', 'blackman'
If *interpolation* is *None*, default to rc
``image.interpolation``. See also the *filternorm* and
*filterrad* parameters
*norm*: [ None | Normalize ]
An :class:`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) ]
Eata values of 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 :class:`~matplotlib.artist.Artist` properties:
========= ===============================================
Property Description
========= ===============================================
alpha float
animated [True | False]
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
figure a :class:`matplotlib.figure.Figure` instance
label any string
lod [True | False]
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
========= ===============================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/image_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- ioff()
- Turn interactive mode off.
- ion()
- Turn interactive mode on.
- ishold()
- Return the hold status of the current axes
- isinteractive()
- Return the interactive status
- jet()
- Set the default colormap to jet and apply to current image if any.
See :func:`colormaps` for more information.
- legend(*args, **kwargs)
- 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()
:meth:`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
=============== =============
If none of these are locations are suitable, loc can be a 2-tuple
giving x,y in axes coords, ie::
loc = 0, 1 # left top
loc = 0.5, 0.5 # center
Keyword arguments:
*isaxes*: [ True | False ]
Indicates that this is an axes legend
*numpoints*: integer
The number of points in the legend line, default is 4
*prop*: [ None | FontProperties ]
A :class:`matplotlib.font_manager.FontProperties`
instance, or *None* to use rc settings.
*pad*: [ None | scalar ]
The fractional whitespace inside the legend border, between 0 and 1.
If *None*, use rc settings.
*markerscale*: [ None | scalar ]
The relative size of legend markers vs. original. If *None*, use rc
settings.
*shadow*: [ None | False | True ]
If *True*, draw a shadow behind legend. If *None*, use rc settings.
*labelsep*: [ None | scalar ]
The vertical space between the legend entries. If *None*, use rc
settings.
*handlelen*: [ None | scalar ]
The length of the legend lines. If *None*, use rc settings.
*handletextsep*: [ None | scalar ]
The space between the legend line and legend text. If *None*, use rc
settings.
*axespad*: [ None | scalar ]
The border between the axes and legend edge. If *None*, use rc
settings.
**Example:**
.. plot:: ../mpl_examples/api/legend_demo.py
- loglog(*args, **kwargs)
- call signature::
loglog(*args, **kwargs)
Make a plot with log scaling on the *x* and *y* axis.
:func:`~matplotlib.pyplot.loglog` supports all the keyword
arguments of :func:`~matplotlib.pyplot.plot` and
:meth:`matplotlib.axes.Axes.set_xscale`/:meth:`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
:meth:`matplotlib.axes.Axes.set_xscale`/:meth:`matplotlib.axes.Axes.set_yscale`
for details
The remaining valid kwargs are
:class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
**Example:**
.. plot:: ../mpl_examples/pylab_examples/log_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- matshow(A, fignum=None, **kw)
- 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
:func:`~matplotlib.pyplot.imshow`.
*fignum*: [ None | integer | False ]
By default, :func:`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
:func:`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.
- over(func, *args, **kwargs)
- over calls::
func(*args, **kwargs)
with ``hold(True)`` and then restores the hold state.
- pcolor(*args, **kwargs)
- 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 :ref:`Grid Orientation
<axes-pcolor-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 :class:`matplotlib.cm.Colormap` instance. If *None*, use
rc settings.
norm: [ None | Normalize ]
An :class:`matplotlib.colors.Normalize` instance is used
to scale luminance data to 0,1. If *None*, defaults to
:func:`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 :class:`matplotlib.collection.Collection`
instance.
.. _axes-pcolor-grid-orientation:
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 :func:`~matplotlib.pyplot.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 :func:`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
:class:`~matplotlib.collection.PolyCollection` properties:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- pcolormesh(*args, **kwargs)
- 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, :func:`~matplotlib.pyplot.pcolor` simply does not
draw quadrilaterals with masked colors or vertices.
Keyword arguments:
*cmap*: [ None | Colormap ]
A :class:`matplotlib.cm.Colormap` instance. If None, use
rc settings.
*norm*: [ None | Normalize ]
A :class:`matplotlib.colors.Normalize` instance is used to
scale luminance data to 0,1. If None, defaults to
:func:`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 :class:`matplotlib.collection.QuadMesh`
object.
See :func:`~matplotlib.pyplot.pcolor` for an explanation of
the grid orientation and the expansion of 1-D *X* and/or *Y*
to 2-D arrays.
kwargs can be used to control the
:class:`matplotlib.collections.QuadMesh`
properties:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- pie(*args, **kwargs)
- 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])
Return value:
If *autopct* is None, return the tuple (*patches*, *texts*):
- *patches* is a sequence of
:class:`matplotlib.patches.Wedge` instances
- *texts* is a list of the label
:class:`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
:class:`~matplotlib.text.Text` instances for the numeric
labels.
Additional kwargs: hold = [True|False] overrides default hold state
- pink()
- Set the default colormap to pink and apply to current image if any.
See :func:`colormaps` for more information.
- plot(*args, **kwargs)
- Plot lines and/or markers to the
:class:`~matplotlib.axes.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 the 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 line styles are supported::
- # solid line
-- # dashed line
-. # dash-dot line
: # dotted line
. # points
, # pixels
o # circle symbols
^ # triangle up symbols
v # triangle down symbols
< # triangle left symbols
> # triangle right symbols
s # square symbols
+ # plus symbols
x # cross symbols
D # diamond symbols
d # thin diamond symbols
1 # tripod down symbols
2 # tripod up symbols
3 # tripod left symbols
4 # tripod right symbols
h # hexagon symbols
H # rotated hexagon symbols
p # pentagon symbols
| # vertical line symbols
_ # horizontal line symbols
steps # use gnuplot style 'steps' # kwarg only
The following color abbreviations are supported::
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.
The kwargs are :class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
kwargs *scalex* and *scaley*, if defined, are passed on to
:meth:`~matplotlib.axes.Axes.autoscale_view` to determine
whether the *x* and *y* axes are autoscaled; the default is
*True*.
Additional kwargs: hold = [True|False] overrides default hold state
- plot_date(*args, **kwargs)
- call signature::
plot_date(x, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs)
Similar to the :func:`~matplotlib.pyplot.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.
See :mod:`~matplotlib.dates` for helper functions
:func:`~matplotlib.dates.date2num`,
:func:`~matplotlib.dates.num2date` and
:func:`~matplotlib.dates.drange` for help on creating the
required floating point dates.
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 :meth:`plot_date` since :meth:`plot_date` will set the
default tick locator to
:class:`matplotlib.ticker.AutoDateLocator` (if the tick
locator is not already set to a
:class:`matplotlib.ticker.DateLocator` instance) and the
default tick formatter to
:class:`matplotlib.ticker.AutoDateFormatter` (if the tick
formatter is not already set to a
:class:`matplotlib.ticker.DateFormatter` instance).
Valid kwargs are :class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- plotfile(fname, cols=(0,), plotfuncs=None, comments='#', skiprows=0, checkrows=5, delimiter=',', **kwargs)
- Plot the data in *fname*
*cols* is a sequence of column identifiers to plot. An identifier
is either an int or a string. If it is an int, it indicates the
column number. If it is a string, it indicates the column header.
matplotlib will make column headers lower case, replace spaces with
underscores, and remove all illegal characters; so ``'Adj Close*'``
will have name ``'adj_close'``.
- If len(*cols*) == 1, only that column will be plotted on the *y* axis.
- If len(*cols*) > 1, the first element will be an identifier for
data for the *x* axis and the remaining elements will be the
column indexes for multiple subplots
*plotfuncs*, if not *None*, is a dictionary mapping identifier to
an :class:`~matplotlib.axes.Axes` plotting function as a string.
Default is 'plot', other choices are 'semilogy', 'fill', 'bar',
etc. You must use the same type of identifier in the *cols*
vector as you use in the *plotfuncs* dictionary, eg., integer
column numbers in both or column names in both.
*comments*, *skiprows*, *checkrows*, and *delimiter* are all passed on to
:func:`matplotlib.pylab.csv2rec` to load the data into a record array.
kwargs are passed on to plotting functions.
Example usage::
# plot the 2nd and 4th column against the 1st in two subplots
plotfile(fname, (0,1,3))
# plot using column names; specify an alternate plot type for volume
plotfile(fname, ('date', 'volume', 'adj_close'), plotfuncs={'volume': 'semilogy'})
- plotting()
- Plotting commands
========= =================================================
Command Description
========= =================================================
axes Create a new axes
axis Set or return the current axis limits
bar make a bar chart
boxplot make a box and whiskers chart
cla clear current axes
clabel label a contour plot
clf clear a figure window
close close a figure window
colorbar add a colorbar to the current figure
cohere make a plot of coherence
contour make a contour plot
contourf make a filled contour plot
csd make a plot of cross spectral density
draw force a redraw of the current figure
errorbar make an errorbar graph
figlegend add a legend to the figure
figimage add an image to the figure, w/o resampling
figtext add text in figure coords
figure create or change active figure
fill make filled polygons
gca return the current axes
gcf return the current figure
gci get the current image, or None
getp get a handle graphics property
hist make a histogram
hold set the hold state on current axes
legend add a legend to the axes
loglog a log log plot
imread load image file into array
imshow plot image data
matshow display a matrix in a new figure preserving aspect
pcolor make a pseudocolor plot
plot make a line plot
plotfile plot data from a flat file
psd make a plot of power spectral density
quiver make a direction field (arrows) plot
rc control the default params
savefig save the current figure
scatter make a scatter plot
setp set a handle graphics property
semilogx log x axis
semilogy log y axis
show show the figures
specgram a spectrogram plot
stem make a stem plot
subplot make a subplot (numrows, numcols, axesnum)
table add a table to the axes
text add some text at location x,y to the current axes
title add a title to the current axes
xlabel add an xlabel to the current axes
ylabel add a ylabel to the current axes
========= =================================================
The following commands will set the default colormap accordingly:
* autumn
* bone
* cool
* copper
* flag
* gray
* hot
* hsv
* jet
* pink
* prism
* spring
* summer
* winter
* spectral
- polar(*args, **kwargs)
- call signature::
polar(theta, r, **kwargs)
Make a polar plot. Multiple *theta*, *r* arguments are supported,
with format strings, as in :func:`~matplotlib.pyplot.plot`.
- prism()
- Set the default colormap to prism and apply to current image if any.
See :func:`colormaps` for more information.
- psd(*args, **kwargs)
- call signature::
psd(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
window=mlab.window_hanning, noverlap=0, **kwargs)
The power spectral density by Welches average periodogram
method. The vector *x* is divided into *NFFT* length
segments. Each segment is detrended by function *detrend* and
windowed by function *window*. *noperlap* gives the length of
the overlap between segments. The :math:`|\mathrm{fft}(i)|^2`
of each segment :math:`i` are averaged to compute *Pxx*, with a
scaling to correct for power loss due to windowing. *Fs* is the
sampling frequency.
Keyword arguments:
*NFFT*: integer
The length of the fft segment, must be a power of 2
*Fs*: integer
The sampling frequency.
*Fc*: integer
The center frequency of *x* (defaults to 0), which offsets
the yextents of the image to reflect the frequency range used
when a signal is acquired and then filtered and downsampled to
baseband.
*detrend*:
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 :mod:`~matplotlib.pylab`
module defines :func:`~matplotlib.pylab.detrend_none`,
:func:`~matplotlib.pylab.detrend_mean`, and
:func:`~matplotlib.pylab.detrend_linear`, but you can use
a custom function as well.
*window*:
The function used to window the segments. *window* is a
function, unlike in matlab where it is a vector.
:mod:`~matplotlib.pylab` defines
:func:`~matplotlib.pylab.window_none`, and
:func:`~matplotlib.pylab.window_hanning`, but you can use
a custom function as well.
*noverlap*: integer
Gives the length of the overlap between segments.
Returns the tuple (*Pxx*, *freqs*).
For plotting, the power is plotted as
:math:`10\log_{10}(P_{xx})` for decibels, though *Pxx* itself
is returned.
References:
Bendat & Piersol -- Random Data: Analysis and Measurement
Procedures, John Wiley & Sons (1986)
kwargs control the :class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- quiver(*args, **kwargs)
- Plot a 2-D field of arrows.
call signatures::
quiver(U, V, **kw)
quiver(U, V, C, **kw)
quiver(X, Y, U, V, **kw)
quiver(X, Y, U, V, C, **kw)
Arguments:
*X*, *Y*:
The x and y coordinates of the arrow locations
(default is tail of arrow; see *pivot* kwarg)
*U*, *V*:
give the *x* and *y* components of the arrow vectors
*C*:
an optional array used to map colors to the arrows
All arguments may be 1-D or 2-D arrays or sequences. If *X* and *Y*
are absent, they will be generated as a uniform grid. If *U* and *V*
are 2-D arrays but *X* and *Y* are 1-D, and if len(*X*) and len(*Y*)
match the column and row dimensions of *U*, then *X* and *Y* will be
expanded with :func:`numpy.meshgrid`.
*U*, *V*, *C* may be masked arrays, but masked *X*, ** are not
supported at present.
Keyword arguments:
*units*: ['width' | 'height' | 'dots' | 'inches' | 'x' | 'y' ]
arrow units; the arrow dimensions *except for length* are
in multiples of this unit.
* 'width' or 'height': the width or height of the axes
* 'dots' or 'inches': pixels or inches, based on the figure dpi
* 'x' or 'y': *X* or *Y* data units
In all cases the arrow aspect ratio is 1, so that if *U*==*V* the
angle of the arrow on the plot is 45 degrees CCW from the *x*-axis.
The arrows scale differently depending on the units, however.
For 'x' or 'y', the arrows get larger as one zooms in; for other
units, the arrow size is independent of the zoom state. For
'width or 'height', the arrow size increases with the width and
height of the axes, respectively, when the the window is resized;
for 'dots' or 'inches', resizing does not change the arrows.
*scale*: [ None | float ]
data units per arrow unit, e.g. m/s per plot width;
a smaller scale parameter makes the arrow longer.
If *None*, a simple autoscaling algorithm is used, based
on the average vector length and the number of vectors.
*width*:
shaft width in arrow units; default depends on choice of units,
above, and number of vectors; a typical starting value is about
0.005 times the width of the plot.
*headwidth*: scalar
head width as multiple of shaft width, default is 3
*headlength*: scalar
head length as multiple of shaft width, default is 5
*headaxislength*: scalar
head length at shaft intersection, default is 4.5
*minshaft*: scalar
length below which arrow scales, in units of head length. Do not
set this to less than 1, or small arrows will look terrible!
Default is 1
*minlength*: scalar
minimum length as a multiple of shaft width; if an arrow length
is less than this, plot a dot (hexagon) of this diameter instead.
Default is 1.
*pivot*: [ 'tail' | 'middle' | 'tip' ]
The part of the arrow that is at the grid point; the arrow
rotates about this point, hence the name *pivot*.
*color*: [ color | color sequence ]
This is a synonym for the
:class:`~matplotlib.collections.PolyCollection` facecolor kwarg.
If *C* has been set, *color* has no effect.
The defaults give a slightly swept-back arrow; to make the head a
triangle, make *headaxislength* the same as *headlength*. To make the
arrow more pointed, reduce *headwidth* or increase *headlength* and
*headaxislength*. To make the head smaller relative to the shaft,
scale down all the head parameters. You will probably do best to leave
minshaft alone.
linewidths and edgecolors can be used to customize the arrow
outlines. Additional :class:`~matplotlib.collections.PolyCollection`
keyword arguments:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- quiverkey(*args, **kwargs)
- Add a key to a quiver plot.
call signature::
quiverkey(Q, X, Y, U, label, **kw)
Arguments:
*Q*:
The Quiver instance returned by a call to quiver.
*X*, *Y*:
The location of the key; additional explanation follows.
*U*:
The length of the key
*label*:
a string with the length and units of the key
Keyword arguments:
*coordinates* = [ 'axes' | 'figure' | 'data' | 'inches' ]
Coordinate system and units for *X*, *Y*: 'axes' and 'figure'
are normalized coordinate systems with 0,0 in the lower
left and 1,1 in the upper right; 'data' are the axes
data coordinates (used for the locations of the vectors
in the quiver plot itself); 'inches' is position in the
figure in inches, with 0,0 at the lower left corner.
*color*:
overrides face and edge colors from *Q*.
*labelpos* = [ 'N' | 'S' | 'E' | 'W' ]
Position the label above, below, to the right, to the left
of the arrow, respectively.
*labelsep*:
Distance in inches between the arrow and the label.
Default is 0.1
*labelcolor*:
defaults to default :class:`~matplotlib.text.Text` color.
*fontproperties*:
A dictionary with keyword arguments accepted by the
:class:`~matplotlib.font_manager.FontProperties` initializer:
*family*, *style*, *variant*, *size*, *weight*
Any additional keyword arguments are used to override vector
properties taken from *Q*.
The positioning of the key depends on *X*, *Y*, *coordinates*, and
*labelpos*. If *labelpos* is 'N' or 'S', *X*, *Y* give the position
of the middle of the key arrow. If *labelpos* is 'E', *X*, *Y*
positions the head, and if *labelpos* is 'W', *X*, *Y* positions the
tail; in either of these two cases, *X*, *Y* is somewhere in the
middle of the arrow+label key object.
Additional kwargs: hold = [True|False] overrides default hold state
- rc(*args, **kwargs)
- Set the current rc params. Group is the grouping for the rc, eg.
for ``lines.linewidth`` the group is ``lines``, for
``axes.facecolor``, the group is ``axes``, and so on. Group may
also be a list or tuple of group names, eg. (*xtick*, *ytick*).
*kwargs* is a dictionary attribute name/value pairs, eg::
rc('lines', linewidth=2, color='r')
sets the current rc params and is equivalent to::
rcParams['lines.linewidth'] = 2
rcParams['lines.color'] = 'r'
The following aliases are available to save typing for interactive
users:
===== =================
Alias Property
===== =================
'lw' 'linewidth'
'ls' 'linestyle'
'c' 'color'
'fc' 'facecolor'
'ec' 'edgecolor'
'mew' 'markeredgewidth'
'aa' 'antialiased'
===== =================
Thus you could abbreviate the above rc command as::
rc('lines', lw=2, c='r')
Note you can use python's kwargs dictionary facility to store
dictionaries of default parameters. Eg, you can customize the
font rc as follows::
font = {'family' : 'monospace',
'weight' : 'bold',
'size' : 'larger'}
rc('font', **font) # pass in the font dict as kwargs
This enables you to easily switch between several configurations.
Use :func:`~matplotlib.pyplot.rcdefaults` to restore the default
rc params after changes.
- rcdefaults()
- Restore the default rc params - the ones that were created at
matplotlib load time.
- rgrids(*args, **kwargs)
- Set/Get the radial locations of the gridlines and ticklabels on a
polar plot.
call signatures::
lines, labels = rgrids()
lines, labels = rgrids(radii, labels=None, angle=22.5, **kwargs)
When called with no arguments, :func:`rgrid` simply returns the
tuple (*lines*, *labels*), where *lines* is an array of radial
gridlines (:class:`~matplotlib.lines.Line2D` instances) and
*labels* is an array of tick labels
(:class:`~matplotlib.text.Text` instances). When called with
arguments, the labels will appear at the specified radial
distances and angles.
*labels*, if not *None*, is a len(*radii*) list of strings of the
labels to use at each angle.
If *labels* is None, the rformatter will be used
Examples::
# set the locations of the radial gridlines and labels
lines, labels = rgrids( (0.25, 0.5, 1.0) )
# set the locations and labels of the radial gridlines and labels
lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )
- savefig(*args, **kwargs)
- call signature::
savefig(fname, dpi=None, facecolor='w', edgecolor='w',
orientation='portrait', papertype=None, format=None,
transparent=False):
Save the current figure.
The output formats available depend on the backend being used.
Arguments:
*fname*:
A string containing a path to a filename, or a Python file-like object.
If *format* is *None* and *fname* is a string, the output
format is deduced from the extension of the filename.
Keyword arguments:
*dpi*: [ None | scalar > 0 ]
The resolution in dots per inch. If *None* it will default to
the value ``savefig.dpi`` in the matplotlibrc file.
*facecolor*, *edgecolor*:
the colors of the figure rectangle
*orientation*: [ 'landscape' | 'portrait' ]
not supported on all backends; currently only on postscript output
*papertype*:
One of 'letter', 'legal', 'executive', 'ledger', 'a0' through
'a10', 'b0' through 'b10'. Only supported for postscript
output.
*format*:
One of the file extensions supported by the active
backend. Most backends support png, pdf, ps, eps and svg.
*transparent*:
If *True*, the figure patch and axes patches will all be
transparent. This is useful, for example, for displaying
a plot on top of a colored background on a web page. The
transparency of these patches will be restored to their
original values upon exit of this function.
- scatter(*args, **kwargs)
- call signatures::
scatter(x, y, s=20, c='b', marker='o', cmap=None, norm=None,
vmin=None, vmax=None, alpha=1.0, linewidths=None,
verts=None, **kwargs)
Make a scatter plot of *x* versus *y*, where *x*, *y* are 1-D
sequences of the same length, *N*.
Keyword arguments:
*s*:
size in points^2. It is a scalar or an array of the same
length as *x* and *y*.
*c*:
a color. *c* can be a single color format string, or a
sequence of color specifications of length *N*, or a
sequence of *N* numbers to be mapped to colors using the
*cmap* and *norm* specified via kwargs (see below). Note
that *c* should not be a single numeric RGB or RGBA
sequence because that is indistinguishable from an array
of values to be colormapped. *c* can be a 2-D array in
which the rows are RGB or RGBA, however.
*marker*:
can be one of:
===== ==============
Value Description
===== ==============
's' square
'o' circle
'^' triangle up
'>' triangle right
'v' triangle down
'<' triangle left
'd' diamond
'p' pentagram
'h' hexagon
'8' octagon
'+' plus
'x' cross
===== ==============
The marker can also be a tuple (*numsides*, *style*,
*angle*), which will create a custom, regular symbol.
*numsides*:
the number of sides
*style*:
the style of the regular symbol:
===== =============================================
Value Description
===== =============================================
0 a regular polygon
1 a star-like symbol
2 an asterisk
3 a circle (*numsides* and *angle* is ignored)
===== =============================================
*angle*:
the angle of rotation of the symbol
Finally, *marker* can be (*verts*, 0): *verts* is a
sequence of (*x*, *y*) vertices for a custom scatter
symbol. Alternatively, use the kwarg combination
*marker* = *None*, *verts* = *verts*.
Any or all of *x*, *y*, *s*, and *c* may be masked arrays, in
which case all masks will be combined and only unmasked points
will be plotted.
Other keyword arguments: the color mapping and normalization
arguments will be used only if *c* is an array of floats.
*cmap*: [ None | Colormap ]
A :class:`matplotlib.colors.Colormap` instance. If *None*,
defaults to rc ``image.cmap``. *cmap* is only used if *c*
is an array of floats.
*norm*: [ None | Normalize ]
A :class:`matplotlib.colors.Normalize` instance is used to
scale luminance data to 0, 1. If *None*, use the default
:func:`normalize`. *norm* is only used if *c* is an array
of floats.
*vmin*/*vmax*:
*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*: 0 <= scalar <= 1
The alpha value for the patches
*linewidths*: [ None | scalar | sequence ]
If *None*, defaults to (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
:class:`~matplotlib.collections.RegularPolyCollection`.
Optional kwargs control the
:class:`~matplotlib.collections.Collection` properties; in
particular:
*edgecolors*:
'none' to plot faces with no outlines
*facecolors*:
'none' to plot unfilled outlines
Here are the standard descriptions of all the
:class:`~matplotlib.collections.Collection` kwargs:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
transform unknown
visible [True | False]
zorder any number
============ ======================================================================
A :class:`~matplotlib.collections.Collection` instance is
returned.
Additional kwargs: hold = [True|False] overrides default hold state
- sci(im)
- Set the current image (target of colormap commands like
:func:`~matplotlib.pyplot.jet`, :func:`~matplotlib.pyplot.hot` or
:func:`~matplotlib.pyplot.clim`).
- semilogx(*args, **kwargs)
- call signature::
semilogx(*args, **kwargs)
Make a plot with log scaling on the *x* axis.
:func:`semilogx` supports all the keyword arguments of
:func:`~matplotlib.pyplot.plot` and
:meth:`matplotlib.axes.Axes.set_xscale`.
Notable keyword arguments:
*basex*: scalar > 1
base of the *x* logarithm
*subsx*: [ None | sequence ]
The location of the minor xticks; *None* defaults to
autosubs, which depend on the number of decades in the
plot; see :meth:`~matplotlib.axes.Axes.set_xscale` for
details.
The remaining valid kwargs are
:class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
See :meth:`loglog` for example code and figure
Additional kwargs: hold = [True|False] overrides default hold state
- semilogy(*args, **kwargs)
- call signature::
semilogy(*args, **kwargs)
Make a plot with log scaling on the *y* axis.
:func:`semilogy` supports all the keyword arguments of
:func:`~matplotlib.pylab.plot` and
:meth:`matplotlib.axes.Axes.set_yscale`.
Notable keyword arguments:
*basey*: scalar > 1
Base of the *y* logarithm
*subsy*: [ None | sequence ]
The location of the minor yticks; *None* defaults to
autosubs, which depend on the number of decades in the
plot; see :meth:`~matplotlib.axes.Axes.set_yscale` for
details.
The remaining valid kwargs are
:class:`~matplotlib.lines.Line2D` properties:
====================== ====================================================================================================
Property Description
====================== ====================================================================================================
alpha float
animated [True | False]
antialiased or aa [True | False]
axes unknown
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color or c any matplotlib color
contains unknown
dash_capstyle ['butt' | 'round' | 'projecting']
dash_joinstyle ['miter' | 'round' | 'bevel']
dashes sequence of on/off ink in points
data (np.array xdata, np.array ydata)
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle or ls [ '-' | '--' | '-.' | ':' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post' | 'None' | ' ' | '' ]
linewidth or lw float value in points
lod [True | False]
marker [ '+' | ',' | '.' | '1' | '2' | '3' | '4'
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
picker unknown
pickradius unknown
solid_capstyle ['butt' | 'round' | 'projecting']
solid_joinstyle ['miter' | 'round' | 'bevel']
transform a matplotlib.transforms.Transform instance
visible [True | False]
xdata np.array
ydata np.array
zorder any number
====================== ====================================================================================================
See :meth:`loglog` for example code and figure
Additional kwargs: hold = [True|False] overrides default hold state
- setp(*args, **kwargs)
- matplotlib supports the use of :func:`setp` ("set property") and
:func:`getp` to set and get object properties, as well as to do
introspection on the object. For example, to set the linestyle of a
line to be dashed, you can do::
>>> line, = plot([1,2,3])
>>> setp(line, linestyle='--')
If you want to know the valid types of arguments, you can provide the
name of the property you want to set without a value::
>>> setp(line, 'linestyle')
linestyle: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' ]
If you want to see all the properties that can be set, and their
possible values, you can do::
>>> setp(line)
... long output listing omitted
:func:`setp` operates on a single instance or a list of instances.
If you are in query mode introspecting the possible values, only
the first instance in the sequence is used. When actually setting
values, all the instances will be set. E.g., suppose you have a
list of two lines, the following will make both lines thicker and
red::
>>> x = arange(0,1.0,0.01)
>>> y1 = sin(2*pi*x)
>>> y2 = sin(4*pi*x)
>>> lines = plot(x, y1, x, y2)
>>> setp(lines, linewidth=2, color='r')
:func:`setp` works with the matlab(TM) style string/value pairs or
with python kwargs. For example, the following are equivalent
>>> setp(lines, 'linewidth', 2, 'color', r') # matlab style
>>> setp(lines, linewidth=2, color='r') # python style
- specgram(*args, **kwargs)
- call signature::
specgram(x, NFFT=256, Fs=2, Fc=0, detrend=mlab.detrend_none,
window = mlab.window_hanning, noverlap=128,
cmap=None, xextent=None)
Compute a spectrogram of data in *x*. Data are split into
*NFFT* length segments and the PSD of each section is
computed. The windowing function *window* is applied to each
segment, and the amount of overlap of each segment is
specified with *noverlap*.
Keyword arguments:
*cmap*:
A :class:`matplotlib.cm.Colormap` instance; if *None* use
default determined by rc
*xextent*:
The image extent in the xaxes xextent=xmin, xmax
default 0, max(bins), 0, max(freqs) where bins is the return
value from mlab.specgram
See :meth:`~matplotlib.axes.Axes.psd` for information on the
other keyword arguments.
Return value is (*Pxx*, *freqs*, *bins*, *im*):
- *bins* are the time points the spectrogram is calculated over
- *freqs* is an array of frequencies
- *Pxx* is a len(times) x len(freqs) array of power
- *im* is a :class:`matplotlib.image.AxesImage` instance
Note: If *x* is real (i.e. non-complex), only the positive
spectrum is shown. If *x* is complex, both positive and
negative parts of the spectrum are shown.
Additional kwargs: hold = [True|False] overrides default hold state
- spectral()
- Set the default colormap to spectral and apply to current image if any.
See :func:`colormaps` for more information.
- spring()
- Set the default colormap to spring and apply to current image if any.
See :func:`colormaps` for more information.
- spy(*args, **kwargs)
- call signature::
spy(Z, precision=None, marker=None, markersize=None,
aspect='equal', **kwargs)
``spy(Z)`` plots the sparsity pattern of the 2-D array *Z*.
If *precision* is *None*, any non-zero value will be plotted;
else, values of :math:`|Z| > precision` will be plotted.
The array will be plotted as it would be printed, with
the first index (row) increasing down and the second
index (column) increasing to the right.
By default aspect is 'equal', so that each array element
occupies a square space; set the aspect kwarg to 'auto'
to allow the plot to fill the plot box, or to any scalar
number to specify the aspect ratio of an array element
directly.
Two plotting styles are available: image or marker. Both
are available for full arrays, but only the marker style
works for :class:`scipy.sparse.spmatrix` instances.
If *marker* and *markersize* are *None*, an image will be
returned and any remaining kwargs are passed to
:func:`~matplotlib.pyplot.imshow`; else, a
:class:`~matplotlib.lines.Line2D` object will be returned with
the value of marker determining the marker type, and any
remaining kwargs passed to the
:meth:`~matplotlib.axes.Axes.plot` method.
If *marker* and *markersize* are *None*, useful kwargs include:
* *cmap*
* *alpha*
See documentation for :func:`~matplotlib.pyplot.imshow` for details.
For controlling colors, e.g. cyan background and red marks,
use::
cmap = mcolors.ListedColormap(['c','r'])
If *marker* or *markersize* is not *None*, useful kwargs include:
* *marker*
* *markersize*
* *color*
See documentation for :func:`~matplotlib.pyplot.plot` for details.
Useful values for *marker* include:
* 's' square (default)
* 'o' circle
* '.' point
* ',' pixel
Additional kwargs: hold = [True|False] overrides default hold state
- stem(*args, **kwargs)
- call signature::
stem(x, y, linefmt='b-', markerfmt='bo', basefmt='r-')
A stem plot plots vertical lines (using *linefmt*) at each *x*
location from the baseline to *y*, and places a marker there
using *markerfmt*. A horizontal line at 0 is is plotted using
*basefmt*.
Return value is a tuple (*markerline*, *stemlines*,
*baseline*).
See `this document
<http://www.mathworks.com/access/helpdesk/help/techdoc/ref/stem.html>`_
for details and :file:`examples/pylab_examples/stem_plot.py` for a demo.
Additional kwargs: hold = [True|False] overrides default hold state
- step(*args, **kwargs)
- call signature::
step(x, y, *args, **kwargs)
Make a step plot. Additional keyword args to :func:`step` are the same
as those for :func:`~matplotlib.pyplot.plot`.
*x* and *y* must be 1-D sequences, and it is assumed, but not checked,
that *x* is uniformly increasing.
Keyword arguments:
*where*: [ 'pre' | 'post' | 'mid' ]
If 'pre', the interval from x[i] to x[i+1] has level y[i]
If 'post', that interval has level y[i+1]
If 'mid', the jumps in *y* occur half-way between the
*x*-values.
Additional kwargs: hold = [True|False] overrides default hold state
- subplot(*args, **kwargs)
- Create a subplot command, creating axes with::
subplot(numRows, numCols, plotNum)
where *plotNum* = 1 is the first plot number and increasing *plotNums*
fill rows first. max(*plotNum*) == *numRows* * *numCols*
You can leave out the commas if *numRows* <= *numCols* <=
*plotNum* < 10, as in::
subplot(211) # 2 rows, 1 column, first (upper) plot
``subplot(111)`` is the default axis.
The background color of the subplot can be specified via keyword
argument *axisbg*, which takes a color string as value, as in::
subplot(211, axisbg='y')
See :func:`~matplotlib.pyplot.axes` for additional information on
:func:`axes` and :func:`subplot` keyword arguments.
New subplots that overlap old will delete the old axes. If you do
not want this behavior, use
:meth:`matplotlib.figure.Figure.add_subplot` or the
:func:`~matplotlib.pyplot.axes` command. Eg.::
from pylab import *
plot([1,2,3]) # implicitly creates subplot(111)
subplot(211) # overlaps, subplot(111) is killed
plot(rand(12), rand(12))
- subplot_tool(targetfig=None)
- Launch a subplot tool window for *targetfig* (default gcf).
A :class:`matplotlib.widgets.SubplotTool` instance is returned.
- subplots_adjust(*args, **kwargs)
- call signature::
subplots_adjust(left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None)
Tune the subplot layout via the
:class:`matplotlib.figure.SubplotParams` mechanism. The parameter
meanings (and suggested defaults) are::
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.2 # the amount of height reserved for white space between subplots
The actual defaults are controlled by the rc file
- summer()
- Set the default colormap to summer and apply to current image if any.
See :func:`colormaps` for more information.
- suptitle(*args, **kwargs)
- Add a centered title to the figure.
kwargs are :class:`matplotlib.text.Text` properties. Using figure
coordinates, the defaults are::
*x* = 0.5
the x location of text in figure coords
*y* = 0.98
the y location of the text in figure coords
*horizontalalignment* = 'center'
the horizontal alignment of the text
*verticalalignment* = 'top'
the vertical alignment of the text
A :class:`matplotlib.text.Text` instance is returned.
Example::
fig.subtitle('this is the figure title', fontsize=12)
- switch_backend(newbackend)
- Switch the default backend to newbackend. This feature is
**experimental**, and is only expected to work switching to an
image backend. Eg, if you have a bunch of PostScript scripts that
you want to run from an interactive ipython session, you may want
to switch to the PS backend before running them to avoid having a
bunch of GUI windows popup. If you try to interactively switch
from one GUI backend to another, you will explode.
Calling this command will close all open windows.
- table(*args, **kwargs)
- call signature::
table(cellText=None, cellColours=None,
cellLoc='right', colWidths=None,
rowLabels=None, rowColours=None, rowLoc='left',
colLabels=None, colColours=None, colLoc='center',
loc='bottom', bbox=None):
Add a table to the current axes. Returns a
:class:`matplotlib.table.Table` instance. For finer grained
control over tables, use the :class:`~matplotlib.table.Table`
class and add it to the axes with
:meth:`~matplotlib.axes.Axes.add_table`.
Thanks to John Gill for providing the class and table.
kwargs control the :class:`~matplotlib.table.Table`
properties:
========= ===============================================
Property Description
========= ===============================================
alpha float
animated [True | False]
axes an axes instance
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
contains unknown
figure a :class:`matplotlib.figure.Figure` instance
fontsize a float in points
label any string
lod [True | False]
picker [None|float|boolean|callable]
transform unknown
visible [True | False]
zorder any number
========= ===============================================
- text(*args, **kwargs)
- call signature::
text(x, y, s, fontdict=None, **kwargs)
Add text in string *s* to axis at location *x*, *y*, data
coordinates.
Keyword arguments:
*fontdict*:
A dictionary to override the default text properties.
If *fontdict* is *None*, the defaults are determined by your rc
parameters.
*withdash*: [ False | True ]
Creates a :class:`~matplotlib.text.TextWithDash` instance
instead of a :class:`~matplotlib.text.Text` instance.
Individual keyword arguments can be used to override any given
parameter::
text(x, y, s, fontsize=12)
The default transform specifies that text is in data coords,
alternatively, you can specify text in axis coords (0,0 is
lower-left and 1,1 is upper-right). The example below places
text in the center of the axes::
text(0.5, 0.5,'matplotlib',
horizontalalignment='center',
verticalalignment='center',
transform = ax.transAxes)
You can put a rectangular box around the text instance (eg. to
set a background color) by using the keyword *bbox*. *bbox* is
a dictionary of :class:`matplotlib.patches.Rectangle`
properties. For example::
text(x, y, s, bbox=dict(facecolor='red', alpha=0.5))
Valid kwargs are :class:`matplotlib.text.Text` properties:
========================= =====================================================================
Property Description
========================= =====================================================================
alpha float
animated [True | False]
axes an axes instance
backgroundcolor any matplotlib color
bbox rectangle prop dict plus key 'pad' which is a pad in points
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
color any matplotlib color
contains unknown
family [ 'serif' | 'sans-serif' | 'cursive' | 'fantasy' | 'monospace' ]
figure a :class:`matplotlib.figure.Figure` instance
fontproperties a matplotlib.font_manager.FontProperties instance
horizontalalignment or ha [ 'center' | 'right' | 'left' ]
label any string
linespacing float
lod [True | False]
multialignment ['left' | 'right' | 'center' ]
name or fontname string eg, ['Sans' | 'Courier' | 'Helvetica' ...]
picker [None|float|boolean|callable]
position (x,y)
rotation [ angle in degrees 'vertical' | 'horizontal'
size or fontsize [ size in points | relative size eg 'smaller', 'x-large' ]
style or fontstyle [ 'normal' | 'italic' | 'oblique']
text string or anything printable with '%s' conversion
transform unknown
variant [ 'normal' | 'small-caps' ]
verticalalignment or va [ 'center' | 'top' | 'bottom' | 'baseline' ]
visible [True | False]
weight or fontweight [ 'normal' | 'bold' | 'heavy' | 'light' | 'ultrabold' | 'ultralight']
x float
y float
zorder any number
========================= =====================================================================
- thetagrids(*args, **kwargs)
- Set/Get the theta locations of the gridlines and ticklabels.
If no arguments are passed, return a tuple (*lines*, *labels*)
where *lines* is an array of radial gridlines
(:class:`~matplotlib.lines.Line2D` instances) and *labels* is an
array of tick labels (:class:`~matplotlib.text.Text` instances)::
lines, labels = thetagrids()
Otherwise the syntax is::
lines, labels = thetagrids(angles, labels=None, fmt='%d', frac = 1.1)
set the angles at which to place the theta grids (these gridlines
are equal along the theta dimension).
*angles* is in degrees.
*labels*, if not *None*, is a len(angles) list of strings of the
labels to use at each angle.
If *labels* is *None*, the labels will be ``fmt%angle``.
*frac* is the fraction of the polar axes radius at which to place
the label (1 is the edge). Eg. 1.05 is outside the axes and 0.95
is inside the axes.
Return value is a list of tuples (*lines*, *labels*):
- *lines* are :class:`~matplotlib.lines.Line2D` instances
- *labels* are :class:`~matplotlib.text.Text` instances.
Note that on input, the *labels* argument is a list of strings,
and on output it is a list of :class:`~matplotlib.text.Text`
instances.
Examples::
# set the locations of the radial gridlines and labels
lines, labels = thetagrids( range(45,360,90) )
# set the locations and labels of the radial gridlines and labels
lines, labels = thetagrids( range(45,360,90), ('NE', 'NW', 'SW','SE') )
- title(s, *args, **kwargs)
- Set the title of the current axis to *s*.
Default font override is::
override = {'fontsize': 'medium',
'verticalalignment': 'bottom',
'horizontalalignment': 'center'}
See the :func:`~matplotlib.pyplot.text` docstring for information
of how override and the optional args work.
- twinx(ax=None)
- Make a second axes overlay *ax* (or the current axes if *ax* is
*None*) sharing the xaxis. The ticks for *ax2* will be placed on
the right, and the *ax2* instance is returned.
See :file:`examples/pylab_examples/two_scales.py`
- twiny(ax=None)
- Make a second axes overlay *ax* (or the current axes if *ax* is
*None*) sharing the yaxis. The ticks for *ax2* will be placed on
the top, and the *ax2* instance is returned.
- vlines(*args, **kwargs)
- call signature::
vlines(x, ymin, ymax, color='k')
Plot vertical lines at each *x* from *ymin* to *ymax*. *ymin*
or *ymax* can be scalars or len(*x*) numpy arrays. If they are
scalars, then the respective values are constant, else the
heights of the lines are determined by *ymin* and *ymax*.
*colors* is a line collections color args, either a single color
or a len(*x*) list of colors
*linestyle* is one of [ 'solid' | 'dashed' | 'dashdot' | 'dotted' ]
Returns the :class:`matplotlib.collections.LineCollection`
that was added.
kwargs are :class:`~matplotlib.collections.LineCollection` properties:
============ ======================================================================
Property Description
============ ======================================================================
alpha float
animated [True | False]
antialiased Boolean or sequence of booleans
antialiaseds Boolean or sequence of booleans
array unknown
axes an axes instance
clim a length 2 sequence of floats
clip_box a :class:`matplotlib.transform.Bbox` instance
clip_on [True | False]
clip_path a :class:`~matplotlib.path.Path` instance and a
cmap a colormap
color matplotlib color arg or sequence of rgba tuples
colorbar unknown
contains unknown
dashes ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
edgecolor matplotlib color arg or sequence of rgba tuples
edgecolors matplotlib color arg or sequence of rgba tuples
facecolor matplotlib color arg or sequence of rgba tuples
facecolors matplotlib color arg or sequence of rgba tuples
figure a :class:`matplotlib.figure.Figure` instance
label any string
linestyle ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linestyles ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) ]
linewidth float or sequence of floats
linewidths float or sequence of floats
lod [True | False]
lw float or sequence of floats
norm unknown
offsets float or sequence of floats
picker [None|float|boolean|callable]
pickradius unknown
segments unknown
transform unknown
verts unknown
visible [True | False]
zorder any number
============ ======================================================================
Additional kwargs: hold = [True|False] overrides default hold state
- waitforbuttonpress(*args, **kwargs)
- call signature::
waitforbuttonpress(self, timeout=-1)
Blocking call to interact with the figure.
This will return True is a key was pressed, False if a mouse
button was pressed and None if *timeout* was reached without
either being pressed.
If *timeout* is negative, does not timeout.
- winter()
- Set the default colormap to winter and apply to current image if any.
See :func:`colormaps` for more information.
- xcorr(*args, **kwargs)
- call signature::
xcorr(x, y, normed=False, detrend=mlab.detrend_none,
usevlines=False, **kwargs):
Plot the cross correlation between *x* and *y*. If *normed* =
*True*, normalize the data but the cross correlation at 0-th
lag. *x* and y are detrended by the *detrend* callable
(default no normalization). *x* and *y* must be equal length.
Data are plotted as ``plot(lags, c, **kwargs)``
Return value is a tuple (*lags*, *c*, *line*) where:
- *lags* are a length ``2*maxlags+1`` lag vector
- *c* is the ``2*maxlags+1`` auto correlation vector
- *line* is a :class:`~matplotlib.lines.Line2D` instance
returned by :func:`~matplotlib.pyplot.plot`.
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 :func:`numpy.correlate`
with *mode* = 2.
If *usevlines* is *True*:
:func:`~matplotlib.pyplot.vlines`
rather than :func:`~matplotlib.pyplot.plot` is used to draw
vertical lines from the origin to the xcorr. Otherwise the
plotstyle is determined by the kwargs, which are
:class:`~matplotlib.lines.Line2D` properties.
The return value is a tuple (*lags*, *c*, *linecol*, *b*)
where *linecol* is the
:class:`matplotlib.collections.LineCollection` instance and
*b* is the *x*-axis.
*maxlags* is a positive integer detailing the number of lags to show.
The default value of *None* will return all ``(2*len(x)-1)`` lags.
**Example:**
:func:`~matplotlib.pyplot.xcorr` above, and
:func:`~matplotlib.pyplot.acorr` below.
**Example:**
.. plot:: ../mpl_examples/pylab_examples/xcorr_demo.py
Additional kwargs: hold = [True|False] overrides default hold state
- xlabel(s, *args, **kwargs)
- Set the *x* axis label of the current axis to *s*
Default override is::
override = {
'fontsize' : 'small',
'verticalalignment' : 'top',
'horizontalalignment' : 'center'
}
See :func:`~matplotlib.pyplot.text` for information of how
override and the optional args work
- xlim(*args, **kwargs)
- Set/Get the xlimits of the current axes::
xmin, xmax = xlim() # return the current xlim
xlim( (xmin, xmax) ) # set the xlim to xmin, xmax
xlim( xmin, xmax ) # set the xlim to xmin, xmax
If you do not specify args, you can pass the xmin and xmax as
kwargs, eg.::
xlim(xmax=3) # adjust the max leaving min unchanged
xlim(xmin=1) # adjust the min leaving max unchanged
The new axis limits are returned as a length 2 tuple.
- xscale(*args, **kwargs)
- call signature::
xscale(scale, **kwargs)
Set the scaling for the x-axis: 'linear' | 'log' | 'symlog'
Different keywords may be accepted, depending on the scale:
'linear'
'log'
*basex*/*basey*:
The base of the logarithm
*subsx*/*subsy*:
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]``
will place 10 logarithmically spaced minor ticks between
each major tick.
'symlog'
*basex*/*basey*:
The base of the logarithm
*linthreshx*/*linthreshy*:
The range (-*x*, *x*) within which the plot is linear (to
avoid having the plot go to infinity around zero).
*subsx*/*subsy*:
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]``
will place 10 logarithmically spaced minor ticks between
each major tick.
- xticks(*args, **kwargs)
- Set/Get the xlimits of the current ticklocs and labels::
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = xticks()
# set the locations of the xticks
xticks( arange(6) )
# set the locations and labels of the xticks
xticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are :class:`~matplotlib.text.Text`
properties.
- ylabel(s, *args, **kwargs)
- Set the *y* axis label of the current axis to *s*.
Defaults override is::
override = {
'fontsize' : 'small',
'verticalalignment' : 'center',
'horizontalalignment' : 'right',
'rotation'='vertical' : }
See :func:`~matplotlib.pyplot.text` for information on how
override and the optional args work.
- ylim(*args, **kwargs)
- Set/Get the ylimits of the current axes::
ymin, ymax = ylim() # return the current ylim
ylim( (ymin, ymax) ) # set the ylim to ymin, ymax
ylim( ymin, ymax ) # set the ylim to ymin, ymax
If you do not specify args, you can pass the *ymin* and *ymax* as
kwargs, eg.::
ylim(ymax=3) # adjust the max leaving min unchanged
ylim(ymin=1) # adjust the min leaving max unchanged
The new axis limits are returned as a length 2 tuple.
- yscale(*args, **kwargs)
- call signature::
xscale(scale, **kwargs)
Set the scaling for the y-axis: 'linear' | 'log' | 'symlog'
Different keywords may be accepted, depending on the scale:
'linear'
'log'
*basex*/*basey*:
The base of the logarithm
*subsx*/*subsy*:
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]``
will place 10 logarithmically spaced minor ticks between
each major tick.
'symlog'
*basex*/*basey*:
The base of the logarithm
*linthreshx*/*linthreshy*:
The range (-*x*, *x*) within which the plot is linear (to
avoid having the plot go to infinity around zero).
*subsx*/*subsy*:
Where to place the subticks between each major tick.
Should be a sequence of integers. For example, in a log10
scale: ``[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]``
will place 10 logarithmically spaced minor ticks between
each major tick.
- yticks(*args, **kwargs)
- Set/Get the ylimits of the current ticklocs and labels::
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = yticks()
# set the locations of the yticks
yticks( arange(6) )
# set the locations and labels of the yticks
yticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are :class:`~matplotlib.text.Text`
properties.
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