OwlCyberSecurity - MANAGER
Edit File: pyplot.cpython-38.pyc
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It provides a MATLAB-like way of plotting. pyplot is mainly intended for interactive plots and simple cases of programmatic plot generation:: import numpy as np import matplotlib.pyplot as plt x = np.arange(0, 5, 0.1) y = np.sin(x) plt.plot(x, y) The object-oriented API is recommended for more complex plots. � N)�Number)�cycler)�rcsetup�style)�_pylab_helpers� interactive)�cbook)�dedent� deprecated� silent_list�warn_deprecated)� docstring)�FigureCanvasBase)�Figure� figaspect)�GridSpec)�rcParams�rcParamsDefault� get_backend� rcParamsOrig)� rc_context)�interactive_bk)�getp�get�Artist)�setp)�Axes�Subplot)� PolarAxes)�mlab)�get_scale_docs�get_scale_names)�cm)�get_cmap� register_cmap)� Normalize)�Line2D)�Text� Annotation)�Polygon� Rectangle�Circle�Arrow)� SubplotTool�Button�Slider�Widget� )� TickHelper� Formatter�FixedFormatter� NullFormatter� FuncFormatter�FormatStrFormatter�ScalarFormatter� LogFormatter�LogFormatterExponent�LogFormatterMathtext�Locator� IndexLocator� FixedLocator� NullLocator� LinearLocator� LogLocator� AutoLocator�MultipleLocator� MaxNLocator)� pylab_setup�"_get_running_interactive_frameworkFc C s� G dd� dt �} z�dtjkr�ddlm} |� }|dkr<| � �trFW dS dd� }z|j�d |� W n tk r~ |� |� Y nX |ad a dd l m } |� t� �}|r�|�|� nd a W n t| fk r� d a Y nX dS ) z� Install a repl display hook so that any stale figure are automatically redrawn when control is returned to the repl. This works both with IPython and with vanilla python shells. c @ s e Zd ZdS )z-install_repl_displayhook.<locals>._NotIPythonN)�__name__� __module__� __qualname__� rJ rJ �3/usr/lib/python3/dist-packages/matplotlib/pyplot.py� _NotIPython\ s rL �IPythonr �� get_ipythonNc S s t �� rt� d S �N)� matplotlib�is_interactive�draw_allrJ rJ rJ rK � post_executek s z.install_repl_displayhook.<locals>.post_executerT F)� backend2guiT)� Exception�sys�modulesrM rO �_IP_REGISTERED�events�register�AttributeErrorZregister_post_execute�_INSTALL_FIG_OBSERVERZIPython.core.pylabtoolsrU r r Z enable_gui� ImportError)rL rO �iprT rU Zipython_gui_namerJ rJ rK �install_repl_displayhookR s. r` c C sV t rJddlm} | � }z|j�dt � W n tk rD td��Y nX da trRdadS )a� Uninstall the matplotlib display hook. .. warning Need IPython >= 2 for this to work. For IPython < 2 will raise a ``NotImplementedError`` .. warning If you are using vanilla python and have installed another display hook this will reset ``sys.displayhook`` to what ever function was there when matplotlib installed it's displayhook, possibly discarding your changes. r rN rT z*Can not unregister events in IPython < 2.0NF)rY rM rO rZ Z unregisterr\ �NotImplementedErrorr] )rO r_ rJ rJ rK �uninstall_repl_displayhook� s rb c O s t j| |�S rP )rQ � set_loglevel��args�kwargsrJ rJ rK rc � s rc Tc C s | d krt � } | j||d�S )N)� include_self)�gcf�findobj)�o�matchrg rJ rJ rK ri � s ri c C s$ t d� | tjkrddD ]8}z t|� W n tk r> Y qY qX |td< dS qtd� dtd< dS | �d�rz| dd� n d�| �� �}t � |�}t d t j jft|��}t�d | |j� |j}|dk r�t j �� }|r�|r�||kr�td �| ||���| td< td< |a|ja|ja|ja| t j _ dS ) a� Close all open figures and set the Matplotlib backend. The argument is case-insensitive. Switching to an interactive backend is possible only if no event loop for another interactive backend has started. Switching to and from non-interactive backends is always possible. Parameters ---------- newbackend : str The name of the backend to use. �all)ZmacosxZqt5aggZqt4aggZgtk3aggZtkaggZwxagg�backendNZaggz module://� z matplotlib.backends.backend_{}�Backendz Loaded backend %s version %s.zdCannot load backend {!r} which requires the {!r} interactive framework, as {!r} is currently running) �closer �_auto_backend_sentinel�switch_backendr^ r � startswith�format�lower� importlib� import_module�typerQ ZbackendsZ_Backend�vars�_log�debugZbackend_versionZ required_interactive_frameworkrF r r Z _backend_mod�new_figure_manager�draw_if_interactive�show�_showrm )Z newbackend� candidateZ backend_nameZ backend_modro Zrequired_frameworkZcurrent_frameworkrJ rJ rK rr � sZ � � ��� ��rr c O s t | |�S )aM 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. )r )re �kwrJ rJ rK r~ � s r~ c C s t �� S )z&Return the status of interactive mode.)rQ rR rJ rJ rJ rK � isinteractive s r� c C s t �d� t� dS )z Turn the interactive mode off.FN)rQ r rb rJ rJ rJ rK �ioff s r� c C s t �d� t� dS )z Turn the interactive mode on.TN)rQ r r` rJ rJ rJ rK �ion s r� c C sL t j�� }|dk r>|j}|jjr(|�� tdd� |�| � n t � | � dS )a� Pause for *interval* seconds. If there is an active figure, it will be updated and displayed before the pause, and the GUI event loop (if any) will run during the pause. This can be used for crude animation. For more complex animation, see :mod:`matplotlib.animation`. Notes ----- This function is experimental; its behavior may be changed or extended in a future release. NF)�block) r �Gcf� get_active�canvas�figureZstale� draw_idler~ Zstart_event_loop�time�sleep)Zinterval�managerr� rJ rJ rK �pause! s r� c K s t j| f|� d S rP )rQ �rc)�grouprf rJ rJ rK r� ; s r� c C s t �| |�S rP )rQ r )r� �fnamerJ rJ rK r @ s r c C s t �� t �� rt� d S rP )rQ � rcdefaultsrR rS rJ rJ rJ rK r� E s r� c C s t � �� S )a& 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. Notes ----- Historically, the only colorable artists were images; hence the name ``gci`` (get current image). )rh Z_gcirJ rJ rJ rK �gciO s r� c O s t | f|�|�S rP )�_setp)�objre rf rJ rJ rK r i s r �d � c C s` t d rtd��ddlm} tddddd gd | ||f|jd d d �gdddddddddddd��S )a� Turn on `xkcd <https://xkcd.com/>`_ sketch-style drawing mode. This will only have effect on things drawn after this function is called. For best results, the "Humor Sans" font should be installed: it is not included with matplotlib. Parameters ---------- scale : float, optional The amplitude of the wiggle perpendicular to the source line. length : float, optional The length of the wiggle along the line. randomness : float, optional The scale factor by which the length is shrunken or expanded. Notes ----- This function works by a number of rcParams, so it will probably override others you have set before. If you want the effects of this function to be temporary, it can be used as a context manager, for example:: with plt.xkcd(): # This figure will be in XKCD-style fig1 = plt.figure() # ... # This figure will be in regular style fig2 = plt.figure() z text.usetexz3xkcd mode is not compatible with text.usetex = Truer )� patheffects�xkcdz xkcd Scriptz Humor Sansz Comic Sans MSZStayPuftg ,@� �w)� linewidthZ foregroundg �?g @Zwhiteg FZblack� � )z font.familyz font.sizez path.sketchz path.effectszaxes.linewidthzlines.linewidth�figure.facecolorzgrid.linewidthz axes.gridzaxes.unicode_minuszaxes.edgecolorzxtick.major.sizezxtick.major.widthzytick.major.sizezytick.major.width)r � RuntimeErrorrQ r� r Z withStroke)�scaleZlengthZ randomnessr� rJ rJ rK r� n s, "� �r� c s� |dkrt d }|dkr t d }|dkr0t d }|dkr@t d }t� } | rVt| �d nd} d} | dkrl| } nPt| t�r�| } t� } | | kr�| dkr�t�d � | } q�| �| �} | | } nt | �} t j � | �� � dk�r�t d }t | �| kr�dk�rn nt�d | t� t� �� d k�r d }t| f||||||d�|��� | �rX� �| � � jj�| � � fdd�}� j�d|�}|� _t j �� � � jj}| |_t�� �r�t � t �r�t |_ |�r�� jj� � � jjS )a8 Create a new figure. Parameters ---------- num : integer or string, optional, default: None If not provided, a new figure will be created, and the figure number will be incremented. The figure objects holds this number in a `number` attribute. If num is provided, and a figure with this id already exists, make it active, and returns a reference to it. If this figure does not exists, create it and returns it. If num is a string, the window title will be set to this figure's `num`. figsize : (float, float), optional, default: None width, height in inches. If not provided, defaults to :rc:`figure.figsize` = ``[6.4, 4.8]``. dpi : integer, optional, default: None resolution of the figure. If not provided, defaults to :rc:`figure.dpi` = ``100``. facecolor : color spec the background color. If not provided, defaults to :rc:`figure.facecolor` = ``'w'``. edgecolor : color spec the border color. If not provided, defaults to :rc:`figure.edgecolor` = ``'w'``. frameon : bool, optional, default: True If False, suppress drawing the figure frame. FigureClass : subclass of `~matplotlib.figure.Figure` Optionally use a custom `.Figure` instance. clear : bool, optional, default: False If True and the figure already exists, then it is cleared. Returns ------- figure : `~matplotlib.figure.Figure` The `.Figure` instance returned will also be passed to new_figure_manager in the backends, which allows to hook custom `.Figure` classes into the pyplot interface. Additional kwargs will be passed to the `.Figure` init function. Notes ----- If you are creating many figures, make sure you explicitly call :func:`.pyplot.close` on the figures you are not using, because this will enable pyplot to properly clean up the memory. `~matplotlib.rcParams` defines the default values, which can be modified in the matplotlibrc file. Nzfigure.figsizez figure.dpir� zfigure.edgecolorr1 � rl z(close('all') closes all existing figureszfigure.max_open_warningz�More than %d figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).Zps�H )�figsize�dpi� facecolor� edgecolor�frameon� FigureClassc s t j�� � d S rP )r r� � set_active)Zevent�� figManagerrJ rK � make_active( s zfigure.<locals>.make_activeZbutton_press_event)!r � get_fignums�max� isinstance�str� get_figlabelsr �_warn_external�index�intr r� Zget_fig_manager�len�RuntimeWarningr ru r| Zset_window_titler� r� Z set_label� mpl_connectZ_cidgcfr� ZnumberrQ rR r} r] �_auto_draw_if_interactiveZstale_callback�clear)�numr� r� r� r� r� r� r� rf ZallnumsZnext_numZfigLabel� allLabelsZinumZmax_open_warningr� �cid�figrJ r� rK r� � s| D � �� �� r� c C s$ |r t �� r | j�� s | j�� dS )z� This is an internal helper function for making sure that auto-redrawing works as intended in the plain python repl. Parameters ---------- fig : Figure A figure object which is assumed to be associated with a canvas N)rQ rR r� Z is_savingr� )r� �valrJ rJ rK r� B s r� c C s$ t j�� } | dk r| jjS t� S dS )zw Get the current figure. If no current figure exists, a new one is created using `~.pyplot.figure()`. N)r r� r� r� r� r� rJ rJ rK rh P s rh c C s t j�| �p| t� kS )z3Return whether the figure with the given id exists.)r r� Z has_fignumr� �r� rJ rJ rK � fignum_exists^ s r� c C s t tjj�S )z)Return a list of existing figure numbers.)�sortedr r� ZfigsrJ rJ rJ rK r� c s r� c C s( t j�� } | jdd� d� dd� | D �S )z(Return a list of existing figure labels.c S s | j S rP r� )�mrJ rJ rK �<lambda>k � z get_figlabels.<locals>.<lambda>)�keyc S s g | ]}|j j�� �qS rJ )r� r� Z get_label)�.0r� rJ rJ rK � <listcomp>l s z!get_figlabels.<locals>.<listcomp>)r r� �get_all_fig_managers�sort)Z figManagersrJ rJ rK r� h s r� c C s& t j�� } | dkr"t� t j�� } | S )as Return the figure manager of the current figure. The figure manager is a container for the actual backend-depended window that displays the figure on screen. If if no current figure exists, a new one is created an its figure manager is returned. Returns ------- manager : `.FigureManagerBase` or backend-dependent subclass thereof N)r r� r� rh r� rJ rJ rK �get_current_fig_managero s r� c C s t � j�| |�S rP )r� r� r� )�s�funcrJ rJ rK �connect� s r� c C s t � j�| �S rP )r� r� �mpl_disconnect)r� rJ rJ rK � disconnect� s r� c C s� | dkr.t j�� }|dkr dS t j�|j� n�| dkrBt j�� n�t| t�rZt j�| � npt| d�rtt j�| j� nVt| t �r�t � }| |kr�t � |� | � }t j�|� n t| t �r�t j�| � ntd��dS )al Close a figure window. Parameters ---------- fig : None or int or str or `.Figure` The figure to close. There are a number of ways to specify this: - *None*: the current figure - `.Figure`: the given `.Figure` instance - ``int``: a figure number - ``str``: a figure name - 'all': all figures Nrl r� zFclose() argument must be a Figure, an int, a string, or None, not '%s')r r� r� Zdestroyr� Z destroy_allr� r� �hasattrr� r� r� r� r Z destroy_fig� TypeError)r� r� r� r� rJ rJ rK rp � s& rp c C s t � �� dS )zClear the current figure.N)rh �clfrJ rJ rJ rK r� � s r� c C s t � j�� dS )a+ Redraw the current figure. This is used to update a figure that has been altered, but not automatically re-drawn. If interactive mode is on (:func:`.ion()`), this should be only rarely needed, but there may be ways to modify the state of a figure without marking it as `stale`. Please report these cases as bugs. A more object-oriented alternative, given any :class:`~matplotlib.figure.Figure` instance, :attr:`fig`, that was created using a :mod:`~matplotlib.pyplot` function, is:: fig.canvas.draw_idle() N)r� r� r� rJ rJ rJ rK �draw� s r� c O s t � }|j| |�}|j�� |S rP )rh �savefigr� r� )re rf r� �resrJ rJ rK r� � s r� c O s t � j| |�S )z� 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. )rh �ginputrd rJ rJ rK r� � s r� c O s t � j| |�S )a 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. )rh �waitforbuttonpressrd rJ rJ rK r� � s r� c O s t � j| ||f|�|�S rP )rh �text)�x�yr� re rf rJ rJ rK �figtext� s r� c K s t � j| f|�S rP )rh �suptitle)�trf rJ rJ rK r� � s r� c O s t � j| |�S rP )rh �figimagerd rJ rJ rK r� � s r� c O s t � j| |�S rP )rh �legendrd rJ rJ rK � figlegend s r� zlegend(z figlegend(c K s& | dkrt d|�S t� j| f|�S dS )a9 Add an axes to the current figure and make it the current axes. Call signatures:: plt.axes() plt.axes(rect, projection=None, polar=False, **kwargs) plt.axes(ax) Parameters ---------- arg : None or 4-tuple The exact behavior of this function depends on the type: - *None*: A new full window axes is added using ``subplot(111, **kwargs)`` - 4-tuple of floats *rect* = ``[left, bottom, width, height]``. A new axes is added with dimensions *rect* in normalized (0, 1) units using `~.Figure.add_axes` on the current figure. projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', 'polar', 'rectilinear', str}, optional The projection type of the `~.axes.Axes`. *str* is the name of a custom projection, see `~matplotlib.projections`. The default None results in a 'rectilinear' projection. polar : boolean, optional If True, equivalent to projection='polar'. sharex, sharey : `~.axes.Axes`, optional Share the x or y `~matplotlib.axis` with sharex and/or sharey. The axis will have the same limits, ticks, and scale as the axis of the shared axes. label : str A label for the returned axes. Other Parameters ---------------- **kwargs This method also takes the keyword arguments for the returned axes class. The keyword arguments for the rectilinear axes class `~.axes.Axes` can be found in the following table but there might also be other keyword arguments if another projection is used, see the actual axes class. %(Axes)s Returns ------- axes : `~.axes.Axes` (or a subclass of `~.axes.Axes`) The returned axes class depends on the projection used. It is `~.axes.Axes` if rectilinear projection are used and `.projections.polar.PolarAxes` if polar projection are used. Notes ----- If the figure already has a axes with key (*args*, *kwargs*) then it will simply make that axes current and return it. This behavior is deprecated. Meanwhile, if you do not want this behavior (i.e., you want to force the creation of a new axes), you must use a unique set of args and kwargs. The axes *label* attribute has been exposed for this purpose: if you want two axes that are otherwise identical to be added to the figure, make sure you give them unique labels. See Also -------- .Figure.add_axes .pyplot.subplot .Figure.add_subplot .Figure.subplots .pyplot.subplots Examples -------- :: # Creating a new full window axes plt.axes() # Creating a new axes with specified dimensions and some kwargs plt.axes((left, bottom, width, height), facecolor='w') N�o )r� )�subplotrh �add_axes)�argrf rJ rJ rK �axes s Y r� c C s | dkrt � } | j�| � dS )z� Remove the `Axes` *ax* (defaulting to the current axes) from its figure. A KeyError is raised if the axes doesn't exist. N)�gcar� �delaxes)�axrJ rJ rK r� k s r� c C sN t j�� }|D ]2}| |jjjkrt j�|� |jj�| � dS qtd��dS )zj Set the current Axes instance to *ax*. The current Figure is updated to the parent of *ax*. Nz0Axes instance argument was not found in a figure) r r� r� r� r� r� r� �sca� ValueError)r� Zmanagersr� rJ rJ rK r� v s r� c K s t � jf | �S )a� Get the current :class:`~matplotlib.axes.Axes` instance on the current figure matching the given keyword args, or create one. Examples -------- To get the current polar axes on the current figure:: plt.gca(projection='polar') If the current axes doesn't exist, or isn't a polar one, the appropriate axes will be created and then returned. See Also -------- matplotlib.figure.Figure.gca : The figure's gca method. )rh r� )rf rJ rJ rK r� � s r� c O s� t | �dkrd} t | �dkr4t| d t�r4t�d� t� }|j| |�}|j}g }|jD ]$}||krdqV|� |j�rV|� |� qV|D ] }t |� q�|S )an Add a subplot to the current figure. Wrapper of `.Figure.add_subplot` with a difference in behavior explained in the notes section. Call signatures:: subplot(nrows, ncols, index, **kwargs) subplot(pos, **kwargs) subplot(ax) Parameters ---------- *args Either a 3-digit integer or three separate integers describing the position of the subplot. If the three integers are *nrows*, *ncols*, and *index* in order, the subplot will take the *index* position on a grid with *nrows* rows and *ncols* columns. *index* starts at 1 in the upper left corner and increases to the right. *pos* is a three digit integer, where the first digit is the number of rows, the second the number of columns, and the third the index of the subplot. i.e. fig.add_subplot(235) is the same as fig.add_subplot(2, 3, 5). Note that all integers must be less than 10 for this form to work. projection : {None, 'aitoff', 'hammer', 'lambert', 'mollweide', 'polar', 'rectilinear', str}, optional The projection type of the subplot (`~.axes.Axes`). *str* is the name of a custom projection, see `~matplotlib.projections`. The default None results in a 'rectilinear' projection. polar : boolean, optional If True, equivalent to projection='polar'. sharex, sharey : `~.axes.Axes`, optional Share the x or y `~matplotlib.axis` with sharex and/or sharey. The axis will have the same limits, ticks, and scale as the axis of the shared axes. label : str A label for the returned axes. Other Parameters ---------------- **kwargs This method also takes the keyword arguments for the returned axes base class. The keyword arguments for the rectilinear base class `~.axes.Axes` can be found in the following table but there might also be other keyword arguments if another projection is used. %(Axes)s Returns ------- axes : an `.axes.SubplotBase` subclass of `~.axes.Axes` (or a subclass of `~.axes.Axes`) The axes of the subplot. The returned axes base class depends on the projection used. It is `~.axes.Axes` if rectilinear projection are used and `.projections.polar.PolarAxes` if polar projection are used. The returned axes is then a subplot subclass of the base class. Notes ----- Creating a subplot will delete any pre-existing subplot that overlaps with it beyond sharing a boundary:: import matplotlib.pyplot as plt # plot a line, implicitly creating a subplot(111) plt.plot([1,2,3]) # now create a subplot which represents the top plot of a grid # with 2 rows and 1 column. Since this subplot will overlap the # first, the plot (and its axes) previously created, will be removed plt.subplot(211) If you do not want this behavior, use the `.Figure.add_subplot` method or the `.pyplot.axes` function instead. If the figure already has a subplot with key (*args*, *kwargs*) then it will simply make that subplot current and return it. This behavior is deprecated. Meanwhile, if you do not want this behavior (i.e., you want to force the creation of a new subplot), you must use a unique set of args and kwargs. The axes *label* attribute has been exposed for this purpose: if you want two subplots that are otherwise identical to be added to the figure, make sure you give them unique labels. In rare circumstances, `.add_subplot` may be called with a single argument, a subplot axes instance already created in the present figure but not in the figure's list of axes. See Also -------- .Figure.add_subplot .pyplot.subplots .pyplot.axes .Figure.subplots Examples -------- :: plt.subplot(221) # equivalent but more general ax1=plt.subplot(2, 2, 1) # add a subplot with no frame ax2=plt.subplot(222, frameon=False) # add a polar subplot plt.subplot(223, projection='polar') # add a red subplot that shares the x-axis with ax1 plt.subplot(224, sharex=ax1, facecolor='red') # delete ax2 from the figure plt.delaxes(ax2) # add ax2 to the figure again plt.subplot(ax2) r )r1 r1 r1 r� r� zbThe subplot index argument to subplot() appears to be a boolean. Did you intend to use subplots()?) r� r� �boolr r� rh � add_subplot�bboxr� �fully_overlaps�appendr� )re rf r� �ar� �byebye�otherr� rJ rJ rK r� � s" r� c K s* t f |�}|j| ||||||d�} || fS )a6 Create a figure and a set of subplots. This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call. Parameters ---------- nrows, ncols : int, optional, default: 1 Number of rows/columns of the subplot grid. sharex, sharey : bool or {'none', 'all', 'row', 'col'}, default: False Controls sharing of properties among x (`sharex`) or y (`sharey`) axes: - True or 'all': x- or y-axis will be shared among all subplots. - False or 'none': each subplot x- or y-axis will be independent. - 'row': each subplot row will share an x- or y-axis. - 'col': each subplot column will share an x- or y-axis. When subplots have a shared x-axis along a column, only the x tick labels of the bottom subplot are created. Similarly, when subplots have a shared y-axis along a row, only the y tick labels of the first column subplot are created. To later turn other subplots' ticklabels on, use `~matplotlib.axes.Axes.tick_params`. squeeze : bool, optional, default: True - If True, extra dimensions are squeezed out from the returned array of `~matplotlib.axes.Axes`: - if only one subplot is constructed (nrows=ncols=1), the resulting single Axes object is returned as a scalar. - for Nx1 or 1xM subplots, the returned object is a 1D numpy object array of Axes objects. - 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 Axes object is always a 2D array containing Axes instances, even if it ends up being 1x1. num : integer or string, optional, default: None A `.pyplot.figure` keyword that sets the figure number or label. subplot_kw : dict, optional Dict with keywords passed to the `~matplotlib.figure.Figure.add_subplot` call used to create each subplot. gridspec_kw : dict, optional Dict with keywords passed to the `~matplotlib.gridspec.GridSpec` constructor used to create the grid the subplots are placed on. **fig_kw All additional keyword arguments are passed to the `.pyplot.figure` call. Returns ------- fig : `~.figure.Figure` ax : `.axes.Axes` object or array of Axes objects. *ax* can be either a single `~matplotlib.axes.Axes` object or an array of Axes objects if more than one subplot was created. The dimensions of the resulting array can be controlled with the squeeze keyword, see above. Examples -------- :: # First create some toy data: x = np.linspace(0, 2*np.pi, 400) y = np.sin(x**2) # Creates just a figure and only one subplot fig, ax = plt.subplots() ax.plot(x, y) ax.set_title('Simple plot') # Creates two subplots and unpacks 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) # Creates four polar axes, and accesses them through the returned array fig, axes = plt.subplots(2, 2, subplot_kw=dict(polar=True)) axes[0, 0].plot(x, y) axes[1, 1].scatter(x, y) # 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 both X and Y axes with all subplots plt.subplots(2, 2, sharex='all', sharey='all') # Note that this is the same as plt.subplots(2, 2, sharex=True, sharey=True) # Creates figure number 10 with a single subplot # and clears it if it already exists. fig, ax=plt.subplots(num=10, clear=True) See Also -------- .pyplot.figure .pyplot.subplot .pyplot.axes .Figure.subplots .Figure.add_subplot )�nrows�ncols�sharex�sharey�squeeze� subplot_kw� gridspec_kw)r� �subplots) r� r� r� r� r� r� r� Zfig_kwr� ZaxsrJ rJ rK r� ; s w �r� c K s� |dkrt � }| \}}t||�j|||d�}|j|f|�} | j} g } |jD ]$} | | krXqJ| �| j�rJ| �| � qJ| D ] } t| � qt| S )a� Create an axis at specific location inside a regular grid. Parameters ---------- shape : sequence of 2 ints Shape of grid in which to place axis. First entry is number of rows, second entry is number of columns. loc : sequence of 2 ints Location to place axis within grid. First entry is row number, second entry is column number. rowspan : int Number of rows for the axis to span to the right. colspan : int Number of columns for the axis to span downwards. fig : `Figure`, optional Figure to place axis in. Defaults to current figure. **kwargs Additional keyword arguments are handed to `add_subplot`. Notes ----- The following call :: subplot2grid(shape, loc, rowspan=1, colspan=1) is identical to :: gridspec=GridSpec(shape[0], shape[1]) subplotspec=gridspec.new_subplotspec(loc, rowspan, colspan) subplot(subplotspec) N)�rowspan�colspan) rh r Znew_subplotspecr� r� r� r� r� r� )�shape�locr� r� r� rf �s1�s2Z subplotspecr� r� r� r� r� rJ rJ rK � subplot2grid� s$ ( � r c C s | dkrt � } | �� }|S )a Make and return a second axes that shares the *x*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the right. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` N)r� �twinx�r� �ax1rJ rJ rK r � s r c C s | dkrt � } | �� }|S )a Make and return a second axes that shares the *y*-axis. The new axes will overlay *ax* (or the current axes if *ax* is *None*), and its ticks will be on the top. Examples -------- :doc:`/gallery/subplots_axes_and_figures/two_scales` N)r� �twinyr rJ rJ rK r s r c C s t � }|�| |||||� dS )a� Tune the subplot layout. 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 space between subplots, # expressed as a fraction of the average axis width hspace = 0.2 # the amount of height reserved for space between subplots, # expressed as a fraction of the average axis height The actual defaults are controlled by the rc file N)rh �subplots_adjust)�left�bottom�right�topZwspaceZhspacer� rJ rJ rK r s r c C s� t d }dt d< | dkr(t� }|jj} n&tjjD ]}|jj| kr0 qNq0td��tdd�}|jdd� t | |�}|t d< tj� |� |S ) zy Launch a subplot tool window for a figure. A :class:`matplotlib.widgets.SubplotTool` instance is returned. Ztoolbar�NoneNz$Could not find manager for targetfig)� r� �r� g�������?)r ) r r� r� r� r r� Z _activeQuer� r r- r� )Z targetfigZtbarr� Ztoolfig�retrJ rJ rK � subplot_tool, s r �H�z�G�?c C s t � j| |||d� dS )ay 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, optional Padding (height/width) between edges of adjacent subplots, as a fraction of the font size. Defaults to *pad*. rect : tuple (left, bottom, right, top), optional 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). ��padZh_padZw_padZrectN)rh � tight_layoutr rJ rJ rK r G s r c C s& t � }| dkr|�� } |�| � dS )a@ Turn the axes box on or off on the current axes. Parameters ---------- on : bool or None The new `~matplotlib.axes.Axes` box state. If ``None``, toggle the state. See Also -------- :meth:`matplotlib.axes.Axes.set_frame_on` :meth:`matplotlib.axes.Axes.get_frame_on` N)r� Z get_frame_onZ set_frame_on)Zonr� rJ rJ rK �box[ s r c O s& t � }| s|s|�� S |j| |�}|S )a� Get or set the x limits of the current axes. Call signatures:: left, right = xlim() # return the current xlim xlim((left, right)) # set the xlim to left, right xlim(left, right) # set the xlim to left, right If you do not specify args, you can pass *left* or *right* as kwargs, i.e.:: xlim(right=3) # adjust the right leaving left unchanged xlim(left=1) # adjust the left leaving right unchanged Setting limits turns autoscaling off for the x-axis. Returns ------- left, right A tuple of the new x-axis limits. Notes ----- Calling this function with no arguments (e.g. ``xlim()``) is the pyplot equivalent of calling `~.Axes.get_xlim` on the current axes. Calling this function with arguments is the pyplot equivalent of calling `~.Axes.set_xlim` on the current axes. All arguments are passed though. )r� Zget_xlimZset_xlim�re rf r� r rJ rJ rK �xlimr s r c O s& t � }| s|s|�� S |j| |�}|S )a� Get or set the y-limits of the current axes. Call signatures:: bottom, top = ylim() # return the current ylim ylim((bottom, top)) # set the ylim to bottom, top ylim(bottom, top) # set the ylim to bottom, top If you do not specify args, you can alternatively pass *bottom* or *top* as kwargs, i.e.:: ylim(top=3) # adjust the top leaving bottom unchanged ylim(bottom=1) # adjust the bottom leaving top unchanged Setting limits turns autoscaling off for the y-axis. Returns ------- bottom, top A tuple of the new y-axis limits. Notes ----- Calling this function with no arguments (e.g. ``ylim()``) is the pyplot equivalent of calling `~.Axes.get_ylim` on the current axes. Calling this function with arguments is the pyplot equivalent of calling `~.Axes.set_ylim` on the current axes. All arguments are passed though. )r� Zget_ylimZset_ylimr rJ rJ rK �ylim� s r c K s~ t � }| dkr(|dkr(|�� }|�� }n4|dkrD|�| �}|�� }n|�| �}|j|f|�}|D ]}|�|� q`|td|�fS )a� Get or set the current tick locations and labels of the x-axis. Call signatures:: locs, labels = xticks() # Get locations and labels xticks(ticks, [labels], **kwargs) # Set locations and labels Parameters ---------- ticks : array_like A list of positions at which ticks should be placed. You can pass an empty list to disable xticks. labels : array_like, optional A list of explicit labels to place at the given *locs*. **kwargs :class:`.Text` properties can be used to control the appearance of the labels. Returns ------- locs An array of label locations. labels A list of `.Text` objects. Notes ----- Calling this function with no arguments (e.g. ``xticks()``) is the pyplot equivalent of calling `~.Axes.get_xticks` and `~.Axes.get_xticklabels` on the current axes. Calling this function with arguments is the pyplot equivalent of calling `~.Axes.set_xticks` and `~.Axes.set_xticklabels` on the current axes. Examples -------- Get the current locations and labels: >>> locs, labels = xticks() Set label locations: >>> xticks(np.arange(0, 1, step=0.2)) Set text labels: >>> xticks(np.arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue')) Set text labels and properties: >>> xticks(np.arange(12), calendar.month_name[1:13], rotation=20) Disable xticks: >>> xticks([]) NzText xticklabel)r� Z get_xticksZget_xticklabelsZ set_xticksZset_xticklabels�updater �Zticks�labelsrf r� Zlocs�lrJ rJ rK �xticks� s ; r c K s~ t � }| dkr(|dkr(|�� }|�� }n4|dkrD|�| �}|�� }n|�| �}|j|f|�}|D ]}|�|� q`|td|�fS )a� Get or set the current tick locations and labels of the y-axis. Call signatures:: locs, labels = yticks() # Get locations and labels yticks(ticks, [labels], **kwargs) # Set locations and labels Parameters ---------- ticks : array_like A list of positions at which ticks should be placed. You can pass an empty list to disable yticks. labels : array_like, optional A list of explicit labels to place at the given *locs*. **kwargs :class:`.Text` properties can be used to control the appearance of the labels. Returns ------- locs An array of label locations. labels A list of `.Text` objects. Notes ----- Calling this function with no arguments (e.g. ``yticks()``) is the pyplot equivalent of calling `~.Axes.get_yticks` and `~.Axes.get_yticklabels` on the current axes. Calling this function with arguments is the pyplot equivalent of calling `~.Axes.set_yticks` and `~.Axes.set_yticklabels` on the current axes. Examples -------- Get the current locations and labels: >>> locs, labels = yticks() Set label locations: >>> yticks(np.arange(0, 1, step=0.2)) Set text labels: >>> yticks(np.arange(5), ('Tom', 'Dick', 'Harry', 'Sally', 'Sue')) Set text labels and properties: >>> yticks(np.arange(12), calendar.month_name[1:13], rotation=45) Disable yticks: >>> yticks([]) NzText yticklabel)r� Z get_yticksZget_yticklabelsZ set_yticksZset_yticklabelsr r r rJ rJ rK �yticks s ; r c O s^ t � }t|t�std��t| �dkr:|j�� }|j�� }n|j| |�\}}t d|�t d|�fS )a Get or set the radial gridlines on the current polar plot. Call signatures:: lines, labels = rgrids() lines, labels = rgrids(radii, labels=None, angle=22.5, fmt=None, **kwargs) When called with no arguments, `.rgrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified radial distances and angle. Parameters ---------- radii : tuple with floats The radii for the radial gridlines labels : tuple with strings or None The labels to use at each radial gridline. The `matplotlib.ticker.ScalarFormatter` will be used if None. angle : float The angular position of the radius labels in degrees. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Returns ------- lines, labels : list of `.lines.Line2D`, list of `.text.Text` *lines* are the radial gridlines and *labels* are the tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `~.Text` properties for the labels. Examples -------- :: # set the locations of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0) ) # set the locations and labels of the radial gridlines lines, labels = rgrids( (0.25, 0.5, 1.0), ('Tom', 'Dick', 'Harry' )) See Also -------- .pyplot.thetagrids .projections.polar.PolarAxes.set_rgrids .Axis.get_gridlines .Axis.get_ticklabels z"rgrids only defined for polar axesr zLine2D rgridlinezText rgridlabel) r� r� r r� r� ZyaxisZ get_gridlines�get_ticklabelsZ set_rgridsr �re rf r� �linesr rJ rJ rK �rgridsT s 8 �r" c O s^ t � }t|t�std��t| �dkr:|j�� }|j�� }n|j| |�\}}t d|�t d|�fS )a� Get or set the theta gridlines on the current polar plot. Call signatures:: lines, labels = thetagrids() lines, labels = thetagrids(angles, labels=None, fmt=None, **kwargs) When called with no arguments, `.thetagrids` simply returns the tuple (*lines*, *labels*). When called with arguments, the labels will appear at the specified angles. Parameters ---------- angles : tuple with floats, degrees The angles of the theta gridlines. labels : tuple with strings or None The labels to use at each radial gridline. The `.projections.polar.ThetaFormatter` will be used if None. fmt : str or None Format string used in `matplotlib.ticker.FormatStrFormatter`. For example '%f'. Note that the angle in radians will be used. Returns ------- lines, labels : list of `.lines.Line2D`, list of `.text.Text` *lines* are the theta gridlines and *labels* are the tick labels. Other Parameters ---------------- **kwargs *kwargs* are optional `~.Text` properties for the labels. Examples -------- :: # set the locations of the angular gridlines lines, labels = thetagrids( range(45,360,90) ) # set the locations and labels of the angular gridlines lines, labels = thetagrids( range(45,360,90), ('NE', 'NW', 'SW','SE') ) See Also -------- .pyplot.rgrids .projections.polar.PolarAxes.set_thetagrids .Axis.get_gridlines .Axis.get_ticklabels z&thetagrids only defined for polar axesr zLine2D thetagridlinezText thetagridlabel) r� r� r r� r� ZxaxisZ get_ticklinesr Zset_thetagridsr r rJ rJ rK � thetagrids� s 5 �r# c C s d S rP rJ rJ rJ rJ rK �plotting� s r$ c sL ddddddddd h � � t t� �O � t�t��t� �fd d �t� �� D ��S ) z< Get a sorted list of all of the plotting commands. � colormaps�colorsr� r� �get_plot_commandsr� r� r$ r� c 3 s@ | ]8\}}|� d �s|� krt�|�rt�|��kr|V qdS )�_N)rs �inspectZ isfunction� getmodule)r� �namer� �ZexcludeZ this_modulerJ rK � <genexpr>� s �z$get_plot_commands.<locals>.<genexpr>)�setr% r) r* r' r� �globals�itemsrJ rJ r, rK r' � s � �r' c C s t tj�S )a�+ Matplotlib provides a number of colormaps, and others can be added using :func:`~matplotlib.cm.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 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 Matplotlib ships with 4 perceptually uniform color maps which are the recommended color maps for sequential data: ========= =================================================== Colormap Description ========= =================================================== inferno perceptually uniform shades of black-red-yellow magma perceptually uniform shades of black-red-white plasma perceptually uniform shades of blue-red-yellow viridis perceptually uniform shades of blue-green-yellow ========= =================================================== The following colormaps are based on the `ColorBrewer <http://colorbrewer2.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` is used, not :class:`LinearSegmentedColormap`. Different sets of colors are recommended for different numbers of categories.) * Accent * Dark2 * Paired * Pastel1 * Pastel2 * Set1 * Set2 * Set3 A set of colormaps derived from those of the same name provided with Matlab are also included: ========= ======================================================= 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 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 ========= ======================================================= A set of palettes from the `Yorick scientific visualisation package <https://dhmunro.github.io/yorick-doc/>`_, an evolution of the GIST package, both by David H. Munro are included: ============ ======================================================= 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 ============ ======================================================= A set of cyclic color maps: ================ ================================================= Colormap Description ================ ================================================= hsv red-yellow-green-cyan-blue-magenta-red, formed by changing the hue component in the HSV color space twilight perceptually uniform shades of white-blue-black-red-white twilight_shifted perceptually uniform shades of black-blue-white-red-black ================ ================================================= 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 nipy_spectral black-purple-blue-green-yellow-red-white spectrum, originally from the Neuroimaging in Python project 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 the names in the descriptions 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://ieeexplore.ieee.org/document/4118486/?arnumber=4118486>`_ .. [#] Resembles "BkBlAqGrYeOrReViWh200" from NCAR Command Language. See `Color Table Gallery <https://www.ncl.ucar.edu/Document/Graphics/color_table_gallery.shtml>`_ .. [#] See `Diverging Color Maps for Scientific Visualization <http://www.kennethmoreland.com/color-maps/>`_ by Kenneth Moreland. .. 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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. Parameters ---------- A : array-like(M, N) The matrix to be displayed. fignum : None or int or False If *None*, create a new figure window with automatic numbering. If a nonzero integer, draw into the figure with the given number (create it if it does not exist). If 0, use the current axes (or create one if it does not exist). .. note:: Because of how `.Axes.matshow` tries to set the figure aspect ratio to be the one of the array, strange things may happen if you reuse an existing figure. Returns ------- image : `~matplotlib.image.AxesImage` Other Parameters ---------------- **kwargs : `~matplotlib.axes.Axes.imshow` arguments r r g333333�?g ףp= �?g�������?)�npZ asanyarrayr� r� r r� �matshow�sci)�AZfignumrf r� r� rD rJ rJ rK rL X s ' rL c O s: t � �� r tt� t�s t�d� tdd�}|j| |�}|S )z� Make a polar plot. call signature:: polar(theta, r, **kwargs) Multiple *theta*, *r* arguments are supported, with format strings, as in :func:`~matplotlib.pyplot.plot`. zMTrying to create polar plot on an axis that does not have a polar projection.T)�polar)rh Zget_axesr� r� r r r� �plotr rJ rJ rK rO � s rO �r �#� �,c s� | r t � } nt� } t|�dk r&td��|dkr2i }t�� � tj| |||||d�� W 5 Q R X � fdd�} | |d �\} }g }t|�dkr�| �ddd�}|� |d d�}t ||�}||f| � |� | � n�t|�}t d|�D ]�}|�r |dk�r| �|d d|� }}n| j|d d||d �}n|dk�r6| �ddd�}| || �\}}|� |� |� || d�}t ||�}|||f| � |�r�|� |� |�� �r�|�| � q�|�d � q�|�s�|�|� | d k�r�| �� dS ) a Plot the data in a file. *cols* is a sequence of column identifiers to plot. 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scilimitsZ useOffsetZ useLocaleZ useMathTextc C s t � j| |||||d�S )Nr^ )r� �ticklabel_formatr^ rJ rJ rK r_ � s �r_ c O s$ t � j| |�}|jd k r t|� |S rP )r� � tricontourr� rM �re rf r� rJ rJ rK r` � s r` c O s$ t � j| |�}|jd k r t|� |S rP )r� � tricontourfr� rM ra rJ rJ rK rb � s rb g �?�r� r� rG rB rC r � facecolorsc O s. t � j|| ||||||d�|��} t| � | S )Nrc )r� � tripcolorrM ) r� r� rG rB rC r rd re rf r� rJ rJ rK re � s ��re c O s t � j| |�S rP )r� �triplotrd rJ rJ rK rf � s rf � �?c C s6 t � j| f||||||||d�| d k r.d| ini ��S )N)r� r� r� r� � showextrema� showmedians�points� bw_methodrf )r� � violinplot) Zdatasetr� r� r� r� rh ri rj rk rf rJ rJ rK rl � s � ��rl c K s2 t � j| ||f|||d�|d k r(d|ini |��S r� )r� �vlines)r� r} r~ r& r� r� rf rf rJ rJ rK rm � s � ��rm c K s2 t � j| |f||||d�|d k r(d|ini |��S )N)r� r� � usevlines�maxlagsrf )r� �xcorr)r� r� r� r� rn ro rf rf rJ rJ rK rp � s � � �rp c C s t � �| �S rP )r� �_sci)rD rJ rJ rK rM � s rM c K s t � j| f|||d�|��S )N)r[ r� r )r� � set_title)r� r[ r� r rf rJ rJ rK �title� s � ��rs c K s t � j| f||d�|��S �N)r[ �labelpad)r� ra )�xlabelr[ ru rf rJ rJ rK rv � s � ��rv c K s t � j| f||d�|��S rt )r� r_ )�ylabelr[ ru rf rJ rJ rK rw � s � ��rw c K s t � j| f|�S rP )r� � set_xscale��valuerf rJ rJ rK r� s r� c K s t � j| f|�S rP )r� � set_yscalery rJ rJ rK r� s r� c C s t d� dS )z� Set the colormap to "autumn". This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. �autumnN�rH rJ rJ rJ rK r| s r| c C s t d� dS )z� Set the colormap to "bone". This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. �boneNr} rJ rJ rJ rK r~ s r~ c C s t d� dS )z� Set the colormap to "cool". This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. �coolNr} rJ rJ rJ rK r $ s r c C s t d� dS )z� Set the colormap to "copper". This changes the default colormap as well as the colormap of the current image if there is one. See ``help(colormaps)`` for more information. �copperNr} rJ rJ rJ rK r� / s r� c C s t d� dS )z� Set the colormap to "flag". This changes the default colormap as well as the colormap of the current image if there is one. 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