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Provides a MATLAB-like plotting framework.
:mod:`~matplotlib.pylab` combines pyplot with numpy into a single namespace.
This is convenient for interactive work, but for programming it
is recommended that the namespaces be kept separate, e.g.::
import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)
i����( t print_functionN( t _pylab_helperst interactive( t dedentt silent_listt is_string_liket
is_numlike( t docstring( t Figuret figaspect( t FigureCanvasBase( t imread( t imsave( t rcParamst rcParamsDefaultt get_backend( t interactive_bk( t getpt gett Artist( t setp( t Axest Subplott _string_to_bool( t PolarAxes( t mlab( t get_scale_docst get_scale_names( t cm( t get_cmapt
register_cmap( t Normalizet normalize( t Line2D( t Textt
Annotation( t Polygont Rectanglet Circlet Arrow( t SubplotToolt Buttont Slidert Widget( t
TickHelpert Formattert FixedFormattert
NullFormattert
FuncFormattert FormatStrFormattert ScalarFormattert LogFormattert LogFormatterExponentt LogFormatterMathtextt Locatort IndexLocatort FixedLocatort NullLocatort
LinearLocatort
LogLocatort AutoLocatort MultipleLocatort MaxNLocatorc C s� t d } t d s! | t k r% d St d j d � } d t j k r� | d k r� d d l } | j j � r�d d | t d <q�nd t j k r� | d
k r� d d l } | j j
� s�d t d <q�n� d t j k r| d
k rd d l } | j j j
� s�d t d <q�np d t j k rh| d k rhd d l
} | j � j � r�d d | t d <q�n d t j k r�| d k r�n d S( s� If rcParams['backend_fallback'] is true, check to see if the
current backend is compatible with the current running event
loop, and if not switches to a compatible one.
t backendt backend_fallbackNt Aggt wxt WXt WXAggi����t qtt QtAggt qtAggs PyQt4.QtCoret Qt4Aggt qt4Aggt gtkt GTKt GTKAggt GTKCairot Tkintert TkAgg( RC RD ( RK RL RM ( R
t _interactive_bkt endswitht syst modulesRB t Appt IsMainLoopRunningRE t qAppt
startingUpt PyQt4.QtGuit QtGuit gobjectt MainLoopt
is_running( R? t is_agg_backendRB RE t PyQt4RZ ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt _backend_selection; s0
( t pylab_setupc C s% | d k r t � } n | j | � S( N( t Nonet gcft findobj( t ot match( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyRc c s c C sL t d � t j | d t d t �d d l m } | � \ a a a a
d S( s�
Switch the default backend. 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.
t allt warnt forcei����( R` N( t closet
matplotlibt uset Falset Truet matplotlib.backendsR` t _backend_modt new_figure_managert draw_if_interactivet _show( t
newbackendR` ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt switch_backendj s
c O s t | | � d S( sM
Display a figure.
When running in ipython with its pylab mode, display all
figures and return to the ipython prompt.
In non-interactive mode, display all figures and block until
the figures have been closed; in interactive mode it has no
effect unless figures were created prior to a change from
non-interactive to interactive mode (not recommended). In
that case it displays the figures but does not block.
A single experimental keyword argument, *block*, may be
set to True or False to override the blocking behavior
described above.
N( Rr ( t argst kw( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt show} s c C s
t j � S( s,
Return status of interactive mode.
( Rj t is_interactive( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt
isinteractive� s c C s t j t � d S( s Turn interactive mode off.N( Rj R Rl ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt ioff� s c C s t j t � d S( s Turn interactive mode on.N( Rj R Rm ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt ion� s c C s� t d } | t k re t j j � } | d k re | j } | j � t d t � | j
| � d Sn d d l } | j | � d S( s�
Pause for *interval* seconds.
If there is an active figure it will be updated and displayed,
and the gui event loop will run during the pause.
If there is no active figure, or if a non-interactive backend
is in use, this executes time.sleep(interval).
This can be used for crude animation. For more complex
animation, see :mod:`matplotlib.animation`.
This function is experimental; its behavior may be changed
or extended in a future release.
R? t blockNi����(
R
RP R t Gcft
get_activeRa t canvast drawRw Rl t start_event_loopt timet sleep( t intervalR? t
figManagerR R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt pause� s
c O s t j | | � d S( N( Rj t rc( Ru t kwargs( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s c C s t j � t � d S( N( Rj t
rcdefaultsRq ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s
c C s
t � j � S( s�
Get the current colorable artist. Specifically, returns 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. The
current image is an attribute of the current axes, or the nearest
earlier axes in the current figure that contains an image.
( Rb t _gci( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt gci� s c C s t � j | � d S( s
Set the current image. This image will be the target of colormap
commands like :func:`~matplotlib.pyplot.jet`,
:func:`~matplotlib.pyplot.hot` or
:func:`~matplotlib.pyplot.clim`). The current image is an
attribute of the current axes.
N( t gcat _sci( t im( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt sci� s c O s t | | � } t � | S( N( t _setpRq ( Ru R� t ret( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR � s c s | d k r t d } n | d k r2 t d } n | d k rK t d } n | d k rd t d } n t � } | r� t | � d n d } d }
| d k r� | } nt t | � r | }
t � } |
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j j | � � � d k r�t
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| d | d | d | | �� |
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j j � � | � j j _ n t � � j j S( s�
Create a new figure.
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 a reference to it. If ``figure(num)`` does not exist
it will be created. Numbering starts at 1, MATLAB style::
figure(1)
The same applies if *num* is a string. In this case *num* will be used
as an explicit figure label::
figure("today")
and in windowed backends, the window title will be set to this figure
label.
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.
s figure.figsizes
figure.dpis figure.facecolors figure.edgecolori t Rf s( close('all') closes all existing figurest psiH t figsizet dpit facecolort edgecolort frameont FigureClassc s t j j � � d S( N( R R} t
set_active( t event( R� ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt make_active^ s t button_press_eventN( Ra R
t get_fignumst maxR t
get_figlabelst warningsRg t indext intR R} t get_fig_managerR t lowerRp t set_window_titleR t figuret set_labelt mpl_connectt _cidgcfR� t numberRq ( t numR� R� R� R� R� R� R� t allnumst next_numt figLabelt allLabelst inumR� t cid( ( R� s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � sX <
c C s0 t j j � } | d k r% | j j St � Sd S( s) Return a reference to the current figure.N( R R} R~ Ra R R� ( R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyRb k s
c C s t j j j � } | j � | S( s) Return a list of existing figure numbers.( R R} t figst keyst sort( t fignums( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� v s
c C sE t j j � } | j d d � � g | D] } | j j j � ^ q) S( s( Return a list of existing figure labels.t keyc S s | j S( N( R� ( t m( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt <lambda> s ( R R} t get_all_fig_managersR� R R� t get_label( t figManagersR� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� | s c C s8 t j j � } | d k r4 t � t j j � } n | S( N( R R} R~ Ra Rb ( R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt get_current_fig_manager� s
c C s t � j j | | � S( N( R� R R� ( t st func( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt connect� s c C s t � j j | � S( N( R� R t mpl_disconnect( R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt
disconnect� s c G s9 t | � d k rG t j j � } | d k r1 d St j j | j � n� t | � d k r)| d } | d k r t j j � q5t | t � r� t j j | � q5t
| � r� t � } | | k r&t � | j
| � } t j j | � q&q5t | t � rt j j | � q5t d t | � � � n t d � � d S( sS
Close a figure window.
``close()`` by itself closes the current figure
``close(h)`` where *h* is a :class:`Figure` instance, closes that figure
``close(num)`` closes figure number *num*
``close(name)`` where *name* is a string, closes figure with that label
``close('all')`` closes all the figure windows
i Ni Rf s& Unrecognized argument type %s to closes close takes 0 or 1 arguments( t lenR R} R~ Ra t destroyR� t destroy_allt
isinstanceR� R R� R� R� R t destroy_figt TypeErrort type( Ru R� t argR� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyRi � s(
c C s t � j � t � d S( s#
Clear the current figure.
N( Rb t clfRq ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s
c C s t � j j � d S( s�
Redraw the current figure.
This is used in interactive mode to update a figure that
has been altered using one or more plot object method calls;
it is not needed if figure modification is done entirely
with pyplot functions, if a sequence of modifications ends
with a pyplot function, or if matplotlib is in non-interactive
mode and the sequence of modifications ends with :func:`show` or
:func:`savefig`.
A more object-oriented alternative, given any
:class:`~matplotlib.figure.Figure` instance, :attr:`fig`, that
was created using a :mod:`~matplotlib.pyplot` function, is::
fig.canvas.draw()
N( R� R R� ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s c O s t � } | j | | � S( N( Rb t savefig( Ru R� t fig( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s c O s t � j | | � S( s�
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.
( Rb t ginput( Ru R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s
c O s t � j | | � S( s
Blocking call to interact with the figure.
This will wait for *n* key or mouse clicks from the user and
return a list containing True's for keyboard clicks and False's
for mouse clicks.
If *timeout* is negative, does not timeout.
( Rb t waitforbuttonpress( Ru R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s c O s t � j | | � } t � | S( N( Rb t textRq ( Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt figtext� s c O s t � j | | � } t � | S( N( Rb t suptitleRq ( Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� � s sA Addition kwargs: hold = [True|False] overrides default hold states
c O s t � j | | � } t � | S( N( Rb t figimageRq ( Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� s c K s& t � j | | | | � } t � | S( s&
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
A :class:`matplotlib.legend.Legend` instance is returned.
Example::
figlegend( (line1, line2, line3),
('label1', 'label2', 'label3'),
'upper right' )
.. seealso::
:func:`~matplotlib.pyplot.legend`
( Rb t legendRq ( t handlest labelst locR� t l( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt figlegend s c C sO t � } | j � } | j | � | j | � | j � } t d d | �d S( s�
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.
t axest holdN( Rb R� R� t isholdR� ( t bR� t ax( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� 0 s
c C s
t � j � S( s5
Return the hold status of the current axes.
( R� R� ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR� K s c O s. t � } t t � | | | � t | � d S( s�
Call a function with hold(True).
Calls::
func(*args, **kwargs)
with ``hold(True)`` and then restores the hold state.
N( R� R� Rm ( R� Ru R� t h( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt overQ s
c O s� t | � } t | � d k r+ t d | � S| d k rF t d � � n | d } t | t � rt t � j | � } n | } t � j | | � } t � | S( s�
Add an axes to the figure.
The axes is added at position *rect* specified by:
- ``axes()`` by itself creates a default full ``subplot(111)`` window axis.
- ``axes(rect, 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*.
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Remove an axes from the current figure. If *ax*
doesn't exist, an error will be raised.
``delaxes()``: delete the current axes
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Set the current Axes instance to *ax*.
The current Figure is updated to the parent of *ax*.
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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])
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| � qi qi Wx | D] } t | � q� Wt � | S( s�
Create a new axes (subplot).
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.
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(212, axisbg='y') # creates 2nd subplot with yellow background
Keyword arguments:
*axisbg*:
The background color of the subplot, which can be any valid
color specifier. See :mod:`matplotlib.colors` for more
information.
*polar*:
A boolean flag indicating whether the subplot plot should be
a polar projection. Defaults to *False*.
*projection*:
A string giving the name of a custom projection to be used
for the subplot. This projection must have been previously
registered. See :mod:`matplotlib.projections`.
.. seealso::
:func:`~matplotlib.pyplot.axes`
For additional information on :func:`axes` and
:func:`subplot` keyword arguments.
:file:`examples/pylab_examples/polar_scatter.py`
For an example
**Example:**
.. plot:: mpl_examples/pylab_examples/subplot_demo.py
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Create a figure with a set of subplots already made.
This utility wrapper makes it convenient to create common layouts of
subplots, including the enclosing figure object, in a single call.
Keyword arguments:
*nrows* : int
Number of rows of the subplot grid. Defaults to 1.
*ncols* : int
Number of columns of the subplot grid. Defaults to 1.
*sharex* : string or bool
If *True*, the X axis will be shared amongst all subplots. If
*True* and you have multiple rows, the x tick labels on all but
the last row of plots will have visible set to *False*
If a string must be one of "row", "col", "all", or "none".
"all" has the same effect as *True*, "none" has the same effect
as *False*.
If "row", each subplot row will share a X axis.
If "col", each subplot column will share a X axis and the x tick
labels on all but the last row will have visible set to *False*.
*sharey* : string or bool
If *True*, the Y axis will be shared amongst all subplots. If
*True* and you have multiple columns, the y tick labels on all but
the first column of plots will have visible set to *False*
If a string must be one of "row", "col", "all", or "none".
"all" has the same effect as *True*, "none" has the same effect
as *False*.
If "row", each subplot row will share a Y axis.
If "col", each subplot column will share a Y axis and the y tick
labels on all but the last row will have visible set to *False*.
*squeeze* : bool
If *True*, extra dimensions are squeezed out from the
returned axis object:
- if only one subplot is constructed (nrows=ncols=1), the
resulting single Axis object is returned as a scalar.
- for Nx1 or 1xN subplots, the returned object is a 1-d numpy
object array of Axis objects are returned as numpy 1-d
arrays.
- for NxM subplots with N>1 and M>1 are returned as a 2d
array.
If *False*, no squeezing at all is done: the returned axis
object is always a 2-d array contaning Axis instances, even if it
ends up being 1x1.
*subplot_kw* : dict
Dict with keywords passed to the
:meth:`~matplotlib.figure.Figure.add_subplot` call used to
create each subplots.
*fig_kw* : dict
Dict with keywords passed to the :func:`figure` call. Note that all
keywords not recognized above will be automatically included here.
Returns:
fig, ax : tuple
- *fig* is the :class:`matplotlib.figure.Figure` object
- *ax* can be either a single axis object or an array of axis
objects if more than one subplot was created. The dimensions
of the resulting array can be controlled with the squeeze
keyword, see above.
Examples::
x = np.linspace(0, 2*np.pi, 400)
y = np.sin(x**2)
# Just a figure and one subplot
f, ax = plt.subplots()
ax.plot(x, y)
ax.set_title('Simple plot')
# Two subplots, unpack the output array immediately
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)
ax1.plot(x, y)
ax1.set_title('Sharing Y axis')
ax2.scatter(x, y)
# Four polar axes
plt.subplots(2, 2, subplot_kw=dict(polar=True))
# Share a X axis with each column of subplots
plt.subplots(2, 2, sharex='col')
# Share a Y axis with each row of subplots
plt.subplots(2, 2, sharey='row')
# Share a X and Y axis with all subplots
plt.subplots(2, 2, sharex='all', sharey='all')
# same as
plt.subplots(2, 2, sharex=True, sharey=True)
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Create a subplot in a grid. The grid is specified by *shape*, at
location of *loc*, spanning *rowspan*, *colspan* cells in each
direction. The index for loc is 0-based. ::
subplot2grid(shape, loc, rowspan=1, colspan=1)
is identical to ::
gridspec=GridSpec(shape[0], shape[2])
subplotspec=gridspec.new_subplotspec(loc, rowspan, colspan)
subplot(subplotspec)
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c C s/ | d k r t � } n | j � } t � | S( s@
Make a second axes that shares the *x*-axis. The new axes will
overlay *ax* (or the current axes if *ax* is *None*). The ticks
for *ax2* will be placed on the right, and the *ax2* instance is
returned.
.. seealso::
:file:`examples/api_examples/two_scales.py`
For an example
N( Ra R� t twinxRq ( R� t ax1( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR s
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Make a second axes that shares the *y*-axis. The new axis will
overlay *ax* (or the current axes if *ax* is *None*). The ticks
for *ax2* will be placed on the top, and the *ax2* instance is
returned.
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c O s$ t � } | j | | � t � d S( s�
Tune the subplot layout.
call signature::
subplots_adjust(left=None, bottom=None, right=None, top=None,
wspace=None, hspace=None)
The parameter meanings (and suggested defaults) are::
left = 0.125 # the left side of the subplots of the figure
right = 0.9 # the right side of the subplots of the figure
bottom = 0.1 # the bottom of the subplots of the figure
top = 0.9 # the top of the subplots of the figure
wspace = 0.2 # the amount of width reserved for blank space between subplots
hspace = 0.2 # the amount of height reserved for white space between subplots
The actual defaults are controlled by the rc file
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Launch a subplot tool window for a figure.
A :class:`matplotlib.widgets.SubplotTool` instance is returned.
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Automatically adjust subplot parameters to give specified padding.
Parameters:
pad : float
padding between the figure edge and the edges of subplots, as a fraction of the font-size.
h_pad, w_pad : float
padding (height/width) between edges of adjacent subplots.
Defaults to `pad_inches`.
rect : if rect is given, it is interpreted as a rectangle
(left, bottom, right, top) in the normalized figure
coordinate that the whole subplots area (including
labels) will fit into. Default is (0, 0, 1, 1).
t padt h_padt w_padR� N( Rb t tight_layoutRq ( R- R. R/ R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR0 e s "c C sI t � } t | � } | d k r1 | j � } n | j | � t � d S( s�
Turn the axes box on or off. *on* may be a boolean or a string,
'on' or 'off'.
If *on* is *None*, toggle state.
N( R� R Ra t get_frame_ont set_frame_onRq ( t onR� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt box| s
c O s# t � j | | | � } t � | S( s\
Set the title of the current axis.
Default font override is::
override = {'fontsize': 'medium',
'verticalalignment': 'baseline',
'horizontalalignment': 'center'}
.. seealso::
:func:`~matplotlib.pyplot.text`
for information on how override and the optional args work.
( R� t set_titleRq ( R� Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt title� s c O s& t � } | j | | � } t � | S( s�
Set or get the axis properties.::
>>> axis()
returns the current axes limits ``[xmin, xmax, ymin, ymax]``.::
>>> axis(v)
sets the min and max of the x and y axes, with
``v = [xmin, xmax, ymin, ymax]``.::
>>> axis('off')
turns off the axis lines and labels.::
>>> axis('equal')
changes limits of *x* or *y* axis so that equal increments of *x*
and *y* have the same length; a circle is circular.::
>>> axis('scaled')
achieves the same result by changing the dimensions of the plot box instead
of the axis data limits.::
>>> axis('tight')
changes *x* and *y* axis limits such that all data is shown. If
all data is already shown, it will move it to the center of the
figure without modifying (*xmax* - *xmin*) or (*ymax* -
*ymin*). Note this is slightly different than in MATLAB.::
>>> axis('image')
is 'scaled' with the axis limits equal to the data limits.::
>>> axis('auto')
and::
>>> axis('normal')
are deprecated. They restore default behavior; axis limits are automatically
scaled to make the data fit comfortably within the plot box.
if ``len(*v)==0``, you can pass in *xmin*, *xmax*, *ymin*, *ymax*
as kwargs selectively to alter just those limits without changing
the others.
The xmin, xmax, ymin, ymax tuple is returned
.. seealso::
:func:`xlim`, :func:`ylim`
For setting the x- and y-limits individually.
( R� t axisRq ( t vR� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR7 � s : c O s# t � j | | | � } t � | S( sq
Set the *x* axis label of the current axis.
Default override is::
override = {
'fontsize' : 'small',
'verticalalignment' : 'top',
'horizontalalignment' : 'center'
}
.. seealso::
:func:`~matplotlib.pyplot.text`
For information on how override and the optional args work
( R� t
set_xlabelRq ( R� Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt xlabel� s c O s# t � j | | | � } t � | S( s�
Set the *y* axis label of the current axis.
Defaults override is::
override = {
'fontsize' : 'small',
'verticalalignment' : 'center',
'horizontalalignment' : 'right',
'rotation'='vertical' : }
.. seealso::
:func:`~matplotlib.pyplot.text`
For information on how override and the optional args
work.
( R� t
set_ylabelRq ( R� Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt ylabel� s c O s> t � } | r! | r! | j � S| j | | � } t � | S( s)
Get or set the *x* limits of the current axes.
::
xmin, xmax = xlim() # return the current xlim
xlim( (xmin, xmax) ) # set the xlim to xmin, xmax
xlim( xmin, xmax ) # set the xlim to xmin, xmax
If you do not specify args, you can pass the xmin and xmax as
kwargs, eg.::
xlim(xmax=3) # adjust the max leaving min unchanged
xlim(xmin=1) # adjust the min leaving max unchanged
Setting limits turns autoscaling off for the x-axis.
The new axis limits are returned as a length 2 tuple.
( R� t get_xlimt set_xlimRq ( Ru R� R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt xlim s
c O s> t � } | r! | r! | j � S| j | | � } t � | S( s,
Get or set the *y*-limits of the current axes.
::
ymin, ymax = ylim() # return the current ylim
ylim( (ymin, ymax) ) # set the ylim to ymin, ymax
ylim( ymin, ymax ) # set the ylim to ymin, ymax
If you do not specify args, you can pass the *ymin* and *ymax* as
kwargs, eg.::
ylim(ymax=3) # adjust the max leaving min unchanged
ylim(ymin=1) # adjust the min leaving max unchanged
Setting limits turns autoscaling off for the y-axis.
The new axis limits are returned as a length 2 tuple.
( R� t get_ylimt set_ylimRq ( Ru R� R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt ylim- s
c O s$ t � } | j | | � t � d S( s�
Set the scaling of the *x*-axis.
call signature::
xscale(scale, **kwargs)
The available scales are: %(scale)s
Different keywords may be accepted, depending on the scale:
%(scale_docs)s
N( R� t
set_xscaleRq ( Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt xscaleI s c O s$ t � } | j | | � t � d S( s�
Set the scaling of the *y*-axis.
call signature::
yscale(scale, **kwargs)
The available scales are: %(scale)s
Different keywords may be accepted, depending on the scale:
%(scale_docs)s
N( R� t
set_yscaleRq ( Ru R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt yscale\ s c O s� t � } t | � d k r6 | j � } | j � } n~ t | � d k rj | j | d � } | j � } nJ t | � d k r� | j | d � } | j | d | � } n t d � � t | � r� x | D] } | j | � q� Wn t � | t d | � f S( s^
Get or set the *x*-limits of the current tick locations and labels.
::
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = xticks()
# set the locations of the xticks
xticks( arange(6) )
# set the locations and labels of the xticks
xticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are :class:`~matplotlib.text.Text`
properties. For example, to rotate long labels::
xticks( arange(12), calendar.month_name[1:13], rotation=17 )
i i i s% Illegal number of arguments to xtickss Text xticklabel(
R� R� t
get_xticksR t
set_xtickst set_xticklabelsR� t updateRq R ( Ru R� R� t locsR� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt xtickso s
c O s� t � } t | � d k r6 | j � } | j � } n~ t | � d k rj | j | d � } | j � } nJ t | � d k r� | j | d � } | j | d | � } n t d � � t | � r� x | D] } | j | � q� Wn t � | t d | � f S( s^
Get or set the *y*-limits of the current tick locations and labels.
::
# return locs, labels where locs is an array of tick locations and
# labels is an array of tick labels.
locs, labels = yticks()
# set the locations of the yticks
yticks( arange(6) )
# set the locations and labels of the yticks
yticks( arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue') )
The keyword args, if any, are :class:`~matplotlib.text.Text`
properties. For example, to rotate long labels::
yticks( arange(12), calendar.month_name[1:13], rotation=45 )
i i i s% Illegal number of arguments to ytickss Text yticklabel(
R� R� t
get_yticksR t
set_ytickst set_yticklabelsR� RJ Rq R ( Ru R� R� RK R� R� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt yticks� s"
c C s t � j � t � d S( s�
Display minor ticks on the current plot.
Displaying minor ticks reduces performance; turn them off using
minorticks_off() if drawing speed is a problem.
N( R� t
minorticks_onRq ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyRQ � s
c C s t � j � t � d S( s3
Remove minor ticks from the current plot.
N( R� t minorticks_offRq ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyRR � s
c O s� t � } t | t � s' t d � � n t | � d k rZ | j j � } | j j � } n | j | | � \ } } t � t
d | � t
d | � f S( s�
Get or set the radial gridlines on a polar plot.
call signatures::
lines, labels = rgrids()
lines, labels = rgrids(radii, labels=None, angle=22.5, **kwargs)
When called with no arguments, :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' )
s" rgrids only defined for polar axesi s Line2D rgridlines Text rgridlabel( R� R� R R' R� R t
get_gridlinest get_ticklabelst
set_rgridsRq R ( Ru R� R� t linesR� ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyt rgrids� s c O s� t � } t | t � s' t d � � n t | � d k rZ | j j � } | j j � } n | j | | � \ } } t � t
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Get or set the theta locations of the gridlines in a polar plot.
If no arguments are passed, return a tuple (*lines*, *labels*)
where *lines* is an array of radial gridlines
(: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') )
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Get a sorted list of all of the plotting commands.
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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')
N( ( ( ( s7 /usr/lib64/python2.7/site-packages/matplotlib/pyplot.pyR] _ s .c C s t t j j � � S( s�'
Matplotlib provides a number of colormaps, and others can be added using
:func:`register_cmap`. This function documents the built-in colormaps,
and will also return a list of all registered colormaps if called.
You can set the colormap for an image, pcolor, scatter, etc,
using a keyword argument::
imshow(X, cmap=cm.hot)
or using the :func:`set_cmap` function::
imshow(X)
pyplot.set_cmap('hot')
pyplot.set_cmap('jet')
In interactive mode, :func:`set_cmap` will update the colormap post-hoc,
allowing you to see which one works best for your data.
All built-in colormaps can be reversed by appending ``_r``: For instance,
``gray_r`` is the reverse of ``gray``.
There are several common color schemes used in visualization:
Sequential schemes
for unipolar data that progresses from low to high
Diverging schemes
for bipolar data that emphasizes positive or negative deviations from a
central value
Cyclic schemes
meant for plotting values that wrap around at the
endpoints, such as phase angle, wind direction, or time of day
Qualitative schemes
for nominal data that has no inherent ordering, where color is used
only to distinguish categories
The base colormaps are (with the exception of `spectral`) derived from
those of the same name provided with Matlab:
========= =======================================================
Colormap Description
========= =======================================================
autumn sequential linearly-increasing shades of red-orange-yellow
bone sequential increasing black-white color map with
a tinge of blue, to emulate X-ray film
cool linearly-decreasing shades of cyan-magenta
copper sequential increasing shades of black-copper
flag repetitive red-white-blue-black pattern (not cyclic at
endpoints)
gray sequential linearly-increasing black-to-white
grayscale
hot sequential black-red-yellow-white, to emulate blackbody
radiation from an object at increasing temperatures
hsv cyclic red-yellow-green-cyan-blue-magenta-red, formed
by changing the hue component in the HSV color space
jet a spectral map with dark endpoints, blue-cyan-yellow-red;
based on a fluid-jet simulation by NCSA [#]_
pink sequential increasing pastel black-pink-white, meant
for sepia tone colorization of photographs
prism repetitive red-yellow-green-blue-purple-...-green pattern
(not cyclic at endpoints)
spring linearly-increasing shades of magenta-yellow
summer sequential linearly-increasing shades of green-yellow
winter linearly-increasing shades of blue-green
spectral black-purple-blue-green-yellow-red-white spectrum
========= =======================================================
For the above list only, you can also set the colormap using the
corresponding pylab shortcut interface function, similar to Matlab::
imshow(X)
hot()
jet()
The next set of palettes are from the `Yorick scientific visualisation
package <http://yorick.sourceforge.net/index.php>`_, an evolution of
the GIST package, both by David H. Munro:
============ =======================================================
Colormap Description
============ =======================================================
gist_earth mapmaker's colors from dark blue deep ocean to green
lowlands to brown highlands to white mountains
gist_heat sequential increasing black-red-orange-white, to emulate
blackbody radiation from an iron bar as it grows hotter
gist_ncar pseudo-spectral black-blue-green-yellow-red-purple-white
colormap from National Center for Atmospheric
Research [#]_
gist_rainbow runs through the colors in spectral order from red to
violet at full saturation (like *hsv* but not cyclic)
gist_stern "Stern special" color table from Interactive Data
Language software
============ =======================================================
The following colormaps are based on the `ColorBrewer
<http://colorbrewer.org>`_ color specifications and designs developed by
Cynthia Brewer:
ColorBrewer Diverging (luminance is highest at the midpoint, and
decreases towards differently-colored endpoints):
======== ===================================
Colormap Description
======== ===================================
BrBG brown, white, blue-green
PiYG pink, white, yellow-green
PRGn purple, white, green
PuOr orange, white, purple
RdBu red, white, blue
RdGy red, white, gray
RdYlBu red, yellow, blue
RdYlGn red, yellow, green
Spectral red, orange, yellow, green, blue
======== ===================================
ColorBrewer Sequential (luminance decreases monotonically):
======== ====================================
Colormap Description
======== ====================================
Blues white to dark blue
BuGn white, light blue, dark green
BuPu white, light blue, dark purple
GnBu white, light green, dark blue
Greens white to dark green
Greys white to black (not linear)
Oranges white, orange, dark brown
OrRd white, orange, dark red
PuBu white, light purple, dark blue
PuBuGn white, light purple, dark green
PuRd white, light purple, dark red
Purples white to dark purple
RdPu white, pink, dark purple
Reds white to dark red
YlGn light yellow, dark green
YlGnBu light yellow, light green, dark blue
YlOrBr light yellow, orange, dark brown
YlOrRd light yellow, orange, dark red
======== ====================================
ColorBrewer Qualitative:
(For plotting nominal data, :class:`ListedColormap` should be used,
not :class:`LinearSegmentedColormap`. Different sets of colors are
recommended for different numbers of categories. These continuous
versions of the qualitative schemes may be removed or converted in the
future.)
* Accent
* Dark2
* Paired
* Pastel1
* Pastel2
* Set1
* Set2
* Set3
Other miscellaneous schemes:
========= =======================================================
Colormap Description
========= =======================================================
afmhot sequential black-orange-yellow-white blackbody
spectrum, commonly used in atomic force microscopy
brg blue-red-green
bwr diverging blue-white-red
coolwarm diverging blue-gray-red, meant to avoid issues with 3D
shading, color blindness, and ordering of colors [#]_
CMRmap "Default colormaps on color images often reproduce to
confusing grayscale images. The proposed colormap
maintains an aesthetically pleasing color image that
automatically reproduces to a monotonic grayscale with
discrete, quantifiable saturation levels." [#]_
cubehelix Unlike most other color schemes cubehelix was designed
by D.A. Green to be monotonically increasing in terms
of perceived brightness. Also, when printed on a black
and white postscript printer, the scheme results in a
greyscale with monotonically increasing brightness.
This color scheme is named cubehelix because the r,g,b
values produced can be visualised as a squashed helix
around the diagonal in the r,g,b color cube.
gnuplot gnuplot's traditional pm3d scheme
(black-blue-red-yellow)
gnuplot2 sequential color printable as gray
(black-blue-violet-yellow-white)
ocean green-blue-white
rainbow spectral purple-blue-green-yellow-orange-red colormap
with diverging luminance
seismic diverging blue-white-red
terrain mapmaker's colors, blue-green-yellow-brown-white,
originally from IGOR Pro
========= =======================================================
The following colormaps are redundant and may be removed in future
versions. It's recommended to use *gray* or *gray_r* instead, which
produce identical output:
========= =======================================================
Colormap Description
========= =======================================================
gist_gray identical to *gray*
gist_yarg identical to *gray_r*
binary identical to *gray_r*
========= =======================================================
.. rubric:: Footnotes
.. [#] Rainbow colormaps, ``jet`` in particular, are considered a poor
choice for scientific visualization by many researchers: `Rainbow Color
Map (Still) Considered Harmful
<http://www.jwave.vt.edu/%7Erkriz/Projects/create_color_table/color_07.pdf>`_
.. [#] Resembles "BkBlAqGrYeOrReViWh200" from NCAR Command
Language. See `Color Table Gallery
<http://www.ncl.ucar.edu/Document/Graphics/color_table_gallery.shtml>`_
.. [#] See `Diverging Color Maps for Scientific Visualization
<http://www.cs.unm.edu/~kmorel/documents/ColorMaps/>`_ by Kenneth
Moreland.
.. [#] See `A Color Map for Effective Black-and-White Rendering of
Color-Scale Images
<http://www.mathworks.com/matlabcentral/fileexchange/2662-cmrmap-m>`_
by Carey Rappaport
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Set the color limits of the current image.
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Set the default colormap. Applies to the current image if any.
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Display an array as a matrix in a new figure window.
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*fignum*: [ None | integer | False ]
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Make a polar plot.
call signature::
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Plot the data in in a file.
*cols* is a sequence of column identifiers to plot. An identifier
is either an int or a string. If it is an int, it indicates the
column number. If it is a string, it indicates the column header.
matplotlib will make column headers lower case, replace spaces with
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data for the *x* axis and the remaining elements will be the
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plotfile(fname, (0,1,3))
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plotfile(fname, ('date', 'volume', 'adj_close'),
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Note: plotfile is intended as a convenience for quickly plotting
data from flat files; it is not intended as an alternative
interface to general plotting with pyplot or matplotlib.
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See help(colormaps) for more information
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