Python matplotlib.interactive() Examples

def switch_backend(newbackend):
    """
    Switch the default backend.  This feature is **experimental**, and
    is only expected to work switching to an image backend.  e.g., if
    you have a bunch of PostScript scripts that you want to run from
    an interactive ipython session, you may want to switch to the PS
    backend before running them to avoid having a bunch of GUI windows
    popup.  If you try to interactively switch from one GUI backend to
    another, you will explode.

    Calling this command will close all open windows.
    """
    close('all')
    global _backend_mod, new_figure_manager, draw_if_interactive, _show
    matplotlib.use(newbackend, warn=False, force=True)
    from matplotlib.backends import pylab_setup
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup() 

def show(*args, **kw):
    """
    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.
    """
    global _show
    _show(*args, **kw) 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def plotdata(obsmode,spectrum,val,odict,sdict,
             instr,fieldname,outdir,outname):
    isetting=P.isinteractive()
    P.ioff()

    P.clf()
    P.plot(obsmode,val,'.')
    P.ylabel('(pysyn-syn)/syn')
    P.xlabel('obsmode')
    P.title("%s: %s"%(instr,fieldname))
    P.savefig(os.path.join(outdir,outname+'_obsmode.ps'))

    P.clf()
    P.plot(spectrum,val,'.')
    P.ylabel('(pysyn-syn)/syn')
    P.xlabel('spectrum')
    P.title("%s: %s"%(instr,fieldname))
    P.savefig(os.path.join(outdir,outname+'_spectrum.ps'))

    matplotlib.interactive(isetting) 

def exceptionDecorator(func):
    def wrapper(*args, **kwargs):
        try:
            isInteractive = plt.isinteractive()

            # switch to non-interactive mode
            #matplotlib.interactive(False)

            ret = func(*args, **kwargs)

            matplotlib.interactive(isInteractive)

            draw_if_interactive()
            return ret
        except Exception as exc:
            # switch back
            matplotlib.interactive(isInteractive)
            raise

    wrapper.__doc__ = func.__doc__

    return wrapper 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def draw():
    """
    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()


    """
    get_current_fig_manager().canvas.draw() 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def switch_backend(newbackend):
    """
    Switch the default backend.  This feature is **experimental**, and
    is only expected to work switching to an image backend.  e.g., if
    you have a bunch of PostScript scripts that you want to run from
    an interactive ipython session, you may want to switch to the PS
    backend before running them to avoid having a bunch of GUI windows
    popup.  If you try to interactively switch from one GUI backend to
    another, you will explode.

    Calling this command will close all open windows.
    """
    close('all')
    global _backend_mod, new_figure_manager, draw_if_interactive, _show
    matplotlib.use(newbackend, warn=False, force=True)
    from matplotlib.backends import pylab_setup
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup() 

def draw():
    """
    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()


    """
    get_current_fig_manager().canvas.draw() 

def draw():
    """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()
    """
    get_current_fig_manager().canvas.draw_idle() 

def switch_backend(newbackend):
    """
    Switch the default backend.  This feature is **experimental**, and
    is only expected to work switching to an image backend.  e.g., if
    you have a bunch of PostScript scripts that you want to run from
    an interactive ipython session, you may want to switch to the PS
    backend before running them to avoid having a bunch of GUI windows
    popup.  If you try to interactively switch from one GUI backend to
    another, you will explode.

    Calling this command will close all open windows.
    """
    close('all')
    global _backend_mod, new_figure_manager, draw_if_interactive, _show
    matplotlib.use(newbackend, warn=False, force=True)
    from matplotlib.backends import pylab_setup
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup() 

def draw():
    """
    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()


    """
    get_current_fig_manager().canvas.draw() 

def show(*args, **kw):
    """
    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.
    """
    global _show
    return _show(*args, **kw) 

def activate_matplotlib(backend):
    """Activate the given backend and set interactive to True."""

    import matplotlib
    matplotlib.interactive(True)
    
    # Matplotlib had a bug where even switch_backend could not force
    # the rcParam to update. This needs to be set *before* the module
    # magic of switch_backend().
    matplotlib.rcParams['backend'] = backend

    import matplotlib.pyplot
    matplotlib.pyplot.switch_backend(backend)

    # This must be imported last in the matplotlib series, after
    # backend/interactivity choices have been made
    import matplotlib.pylab as pylab

    pylab.show._needmain = False
    # We need to detect at runtime whether show() is called by the user.
    # For this, we wrap it into a decorator which adds a 'called' flag.
    pylab.draw_if_interactive = flag_calls(pylab.draw_if_interactive) 

def show(*args, **kw):
    """
    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.
    """
    global _show
    _show(*args, **kw) 

def switch_backend(newbackend):
    """
    Switch the default backend.  This feature is **experimental**, and
    is only expected to work switching to an image backend.  e.g., if
    you have a bunch of PostScript scripts that you want to run from
    an interactive ipython session, you may want to switch to the PS
    backend before running them to avoid having a bunch of GUI windows
    popup.  If you try to interactively switch from one GUI backend to
    another, you will explode.

    Calling this command will close all open windows.
    """
    close('all')
    global _backend_mod, new_figure_manager, draw_if_interactive, _show
    matplotlib.use(newbackend, warn=False, force=True)
    from matplotlib.backends import pylab_setup
    _backend_mod, new_figure_manager, draw_if_interactive, _show = pylab_setup() 

def plot_sphere_func(f, grid='Clenshaw-Curtis', beta=None, alpha=None, colormap='jet', fignum=0, normalize=True):

    #TODO: All grids except Clenshaw-Curtis have holes at the poles
    # TODO: update this function now that we changed the order of axes in f

    import matplotlib
    matplotlib.use('WxAgg')
    matplotlib.interactive(True)
    from mayavi import mlab

    if normalize:
        f = (f - np.min(f)) / (np.max(f) - np.min(f))

    if grid == 'Driscoll-Healy':
        b = f.shape[0] / 2
    elif grid == 'Clenshaw-Curtis':
        b = (f.shape[0] - 2) / 2
    elif grid == 'SOFT':
        b = f.shape[0] / 2
    elif grid == 'Gauss-Legendre':
        b = (f.shape[0] - 2) / 2

    if beta is None or alpha is None:
        beta, alpha = meshgrid(b=b, grid_type=grid)

    alpha = np.r_[alpha, alpha[0, :][None, :]]
    beta = np.r_[beta, beta[0, :][None, :]]
    f = np.r_[f, f[0, :][None, :]]

    x = np.sin(beta) * np.cos(alpha)
    y = np.sin(beta) * np.sin(alpha)
    z = np.cos(beta)

    mlab.figure(fignum, bgcolor=(1, 1, 1), fgcolor=(0, 0, 0), size=(600, 400))
    mlab.clf()
    mlab.mesh(x, y, z, scalars=f, colormap=colormap)

    #mlab.view(90, 70, 6.2, (-1.3, -2.9, 0.25))
    mlab.show() 

def test_plot():
    from ..util.audio import AudioDataLoader, NonSplitDataLoader
    train_dataset = AsrDataset(mode="test")
    loader = AudioDataLoader(train_dataset, batch_size=10, num_workers=4, shuffle=True)
    print(f"num_workers={loader.num_workers}")

    for i, data in enumerate(loader):
        tensors, targets = data
        #for tensors, targets in data:
        print("f{tensors}, {targets}")
        if False:
            import matplotlib
            matplotlib.use('TkAgg')
            matplotlib.interactive(True)
            import matplotlib.pyplot as plt

            for tensor, target in zip(tensors, targets):
                tensor = tensor.view(-1, params.CHANNEL, params.WIDTH, params.HEIGHT)
                t = np.arange(0, tensor.size(3)) / 8000
                f = np.linspace(0, 4000, tensor.size(2))

                fig = plt.figure(1)
                p = plt.pcolormesh(t, f, np.log10(10 ** tensor[0][0] - 1), cmap='plasma')
                plt.colorbar(p)
                plt.show(block=True)
        if i == 2:
            break
    #plt.close('all') 

def plot(array):
    mpl.interactive(True)
    fig = plt.figure(figsize=(30, 5))
    ax = fig.add_subplot(111)
    ax.xaxis.label.set_color('grey')
    ax.yaxis.label.set_color('grey')
    ax.xaxis.label.set_fontsize(23)
    ax.yaxis.label.set_fontsize(23)
    ax.tick_params(axis='x', colors='grey', labelsize=23)
    ax.tick_params(axis='y', colors='grey', labelsize=23)
    plt.plot(array)
    mpl.interactive(False) 

def plot_spec(M):
    mpl.interactive(True)
    M = np.flip(M, axis=0)
    plt.figure(figsize=(18,4))
    plt.imshow(M, interpolation='nearest', aspect='auto')
    plt.show()
    mpl.interactive(False) 

def ion():
    """Turn interactive mode on."""
    matplotlib.interactive(True)
    install_repl_displayhook() 

def ion():
    """Turn the interactive mode on."""
    matplotlib.interactive(True)
    install_repl_displayhook() 

def cli_run():
    """Main entry point."""

    wf = make_workflow_from_user_options()

    if wf.vis_type is not None:
        # matplotlib.interactive(True)
        wf.run()
    else:
        raise ValueError('Invalid state for visualQC!\n'
                         '\t Ensure proper combination of arguments is used.')

    return 

def ioff():
    """Turn interactive mode off."""
    matplotlib.interactive(False)
    uninstall_repl_displayhook() 

def isinteractive():
    """
    Return status of interactive mode.
    """
    return matplotlib.is_interactive() 

def isinteractive():
    """Return the status of interactive mode."""
    return matplotlib.is_interactive() 

def ioff():
    """Turn the interactive mode off."""
    matplotlib.interactive(False)
    uninstall_repl_displayhook()