Python pyplot.ioff方法代碼示例

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def plot_convergence(self, filename=None):
        yy = self.iter_values
        xx = range(len(yy))
        import matplotlib.pyplot as plt
        # Plot
        plt.ioff()
        fig = plt.figure()
        fig.set_size_inches(18.5, 10.5)
        font = {'size': 28}
        plt.title('Value over # evaluations')
        plt.xlabel('X', fontdict=font)
        plt.ylabel('Y', fontdict=font)
        plt.plot(xx, yy)
        plt.axes().set_yscale('log')
        if filename is None:
            filename = 'plots/iter.png'
        plt.savefig(filename, bbox_inches='tight')
        plt.close(fig)
        print('plotting convergence OK.. ' + filename) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def generate_png_chess_dp_vertex(self):
    """Produces pictures of the dominant product vertex a chessboard convention"""
    import matplotlib.pylab as plt
    plt.ioff()
    dab2v = self.get_dp_vertex_doubly_sparse()
    for i, ab in enumerate(dab2v): 
        fname = "chess-v-{:06d}.png".format(i)
        print('Matrix No.#{}, Size: {}, Type: {}'.format(i+1, ab.shape, type(ab)), fname)
        if type(ab) != 'numpy.ndarray': ab = ab.toarray()
        fig = plt.figure()
        ax = fig.add_subplot(1,1,1)
        ax.set_aspect('equal')
        plt.imshow(ab, interpolation='nearest', cmap=plt.cm.ocean)
        plt.colorbar()
        plt.savefig(fname)
        plt.close(fig) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def __init__(self, interactive, ticks=False, figsize=None, limits=None):
        """Construct a new SimpleVectorPlotter.

        interactive - boolean flag denoting interactive mode
        ticks       - boolean flag denoting whether to show axis tickmarks
        figsize     - optional figure size
        limits      - optional geographic limits (x_min, x_max, y_min, y_max)
        """
        # if figsize:
        #     plt.figure(num=1, figsize=figsize)
        plt.figure(num=1, figsize=figsize)
        self.interactive = interactive
        self.ticks = ticks
        if interactive:
            plt.ion()
        else:
            plt.ioff()
        if limits is not None:
            self.set_limits(*limits)
        if not ticks:
            self.no_ticks()
        plt.axis('equal')
        self._graphics = {}
        self._init_colors() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def render_figure_to_tensor(figure):
    import matplotlib

    matplotlib.use("Agg")
    import matplotlib.pyplot as plt

    plt.ioff()

    figure.canvas.draw()

    image = np.array(figure.canvas.renderer._renderer)
    plt.close(figure)
    del figure

    image = tensor_from_rgb_image(image)
    return image 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def __init__(self, fig=None, axis=None, **params):
        self._create_fig = True
        super(MPLPlot, self).__init__(**params)
        # List of handles to matplotlib objects for animation update
        self.fig_scale = self.fig_size/100.
        if isinstance(self.fig_inches, (tuple, list)):
            self.fig_inches = [None if i is None else i*self.fig_scale
                               for i in self.fig_inches]
        else:
            self.fig_inches *= self.fig_scale
        if self.fig_latex:
            self.fig_rcparams['text.usetex'] = True

        if self.renderer.interactive:
            plt.ion()
            self._close_figures = False
        elif not self.renderer.notebook_context:
            plt.ioff()

        fig, axis = self._init_axis(fig, axis)

        self.handles['fig'] = fig
        self.handles['axis'] = axis
        self.handles['bbox_extra_artists'] = [] 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def update_plot(self):
            plt.ioff()
            col = self.picker.currentText()

            plt.figure()

            arr = self.df[col].dropna()
            if self.df[col].dtype.name in ['object', 'bool', 'category']:
                ax = sns.countplot(y=arr, color='grey', order=arr.value_counts().iloc[:10].index)

            else:
                ax = sns.distplot(arr, color='black', hist_kws=dict(color='grey', alpha=1))

            self.figure_viewer.setFigure(ax.figure)


# Examples 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def _plot_image(self, axis: plt.Axes=None, title: str=''):
        plt.ioff()
        if axis is None:
            fig, axis = plt.subplots()
        axis.imshow(self.image.array, cmap=get_dicom_cmap())
        # show vertical/axial profiles
        left_profile = self.positions['vertical left']
        right_profile = self.positions['vertical right']
        axis.axvline(left_profile, color='b')
        axis.axvline(right_profile, color='b')
        # show horizontal/transverse profiles
        bottom_profile = self.positions['horizontal bottom']
        top_profile = self.positions['horizontal top']
        axis.axhline(bottom_profile, color='b')
        axis.axhline(top_profile, color='b')
        _remove_ticklabels(axis)
        axis.set_title(title) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def _plot_symmetry(self, direction: str, axis: plt.Axes=None):
        plt.ioff()
        if axis is None:
            fig, axis = plt.subplots()
        data = self.symmetry[direction.lower()]
        axis.set_title(direction.capitalize() + " Symmetry")
        axis.plot(data['profile'].values)
        # plot lines
        cax_idx = data['profile'].fwxm_center()
        axis.axvline(data['profile left'], color='g', linestyle='-.')
        axis.axvline(data['profile right'], color='g', linestyle='-.')
        axis.axvline(cax_idx, color='m', linestyle='-.')
        # plot symmetry array
        if not data['array'] == 0:
            twin_axis = axis.twinx()
            twin_axis.plot(range(cax_idx, data['profile right']), data['array'][int(round(len(data['array'])/2)):])
            twin_axis.set_ylabel("Symmetry (%)")
        _remove_ticklabels(axis)
        # plot profile mirror
        central_idx = int(round(data['profile'].values.size / 2))
        offset = cax_idx - central_idx
        mirror_vals = data['profile'].values[::-1]
        axis.plot(data['profile']._indices + 2 * offset, mirror_vals) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def render_figure_to_tensor(figure):
    """@TODO: Docs. Contribution is welcome."""
    import matplotlib

    matplotlib.use("Agg")
    import matplotlib.pyplot as plt

    plt.ioff()

    figure.canvas.draw()

    image = np.array(figure.canvas.renderer._renderer)  # noqa: WPS437
    plt.close(figure)
    del figure

    image = tensor_from_rgb_image(image)
    return image 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def plotBy(self,by,variable,df, gridLines = False):

        if not isinstance(df,PowerCurve):
            kind = 'scatter'
        else:
            kind = 'line'
            df=df.data_frame[df.data_frame[self.analysis.baseline.wind_speed_column] <= self.analysis.allMeasuredPowerCurve.cut_out_wind_speed]
        try:
            from matplotlib import pyplot as plt
            plt.ioff()
            ax = df.plot(kind=kind,x=by ,y=variable,title=variable+" By " +by,alpha=0.6,legend=None)
            ax.set_xlim([df[by].min()-1,df[by].max()+1])
            ax.set_xlabel(by)
            ax.set_ylabel(variable)
            if gridLines:
                ax.grid(True)
            file_out = self.path + "/"+variable.replace(" ","_")+"_By_"+by.replace(" ","_")+".png"
            chckMake(self.path)
            plt.savefig(file_out)
            plt.close()
            return file_out
        except:
            Status.add("Tried to make a " + variable.replace(" ","_") + "_By_"+by.replace(" ","_")+" chart. Couldn't.", verbosity=2) 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def plot_multiple(self, windSpeedCol, powerCol, meanPowerCurveObj):

        #plt.ioff()
        plotTitle = "Power Curve"

        meanPowerCurve = meanPowerCurveObj.data_frame[[windSpeedCol,powerCol,'Data Count']][meanPowerCurveObj.data_frame['Data Count'] > 0 ].reset_index().set_index(windSpeedCol)
        ax = meanPowerCurve[powerCol].plot(color='#00FF00',alpha=0.95,linestyle='--',label='Mean Power Curve')

        colourmap = plt.cm.gist_ncar
        colours = [colourmap(i) for i in np.linspace(0, 0.9, len(self.analysis.dataFrame[self.analysis.nameColumn].unique()))]

        for i,name in enumerate(self.analysis.dataFrame[self.analysis.nameColumn].unique()):
            ax = self.analysis.dataFrame[self.analysis.dataFrame[self.analysis.nameColumn] == name].plot(ax = ax, kind='scatter', x=windSpeedCol, y=powerCol, title=plotTitle, alpha=0.2, label=name, color = colours[i])

        ax.legend(loc=4, scatterpoints = 1)
        ax.set_xlim([min(self.analysis.dataFrame[windSpeedCol].min(),meanPowerCurve.index.min()), max(self.analysis.dataFrame[windSpeedCol].max(),meanPowerCurve.index.max()+2.0)])
        ax.set_xlabel(windSpeedCol + ' (m/s)')
        ax.set_ylabel(powerCol + ' (kW)') 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def grid_visual(data):
    """
    This function displays a grid of images to show full misclassification
    :param data: grid data of the form;
        [nb_classes : nb_classes : img_rows : img_cols : nb_channels]
    :return: if necessary, the matplot figure to reuse
    """
    import matplotlib.pyplot as plt

    # Ensure interactive mode is disabled and initialize our graph
    plt.ioff()
    figure = plt.figure()
    figure.canvas.set_window_title('Cleverhans: Grid Visualization')

    # Add the images to the plot
    num_cols = data.shape[0]
    num_rows = data.shape[1]
    num_channels = data.shape[4]
    current_row = 0
    for y in xrange(num_rows):
        for x in xrange(num_cols):
            figure.add_subplot(num_rows, num_cols, (x + 1) + (y * num_cols))
            plt.axis('off')

            if num_channels == 1:
                plt.imshow(data[x, y, :, :, 0], cmap='gray')
            else:
                plt.imshow(data[x, y, :, :, :])

    # Draw the plot and return
    plt.show()
    return figure 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def generate_png_spy_dp_vertex(self):
    """Produces pictures of the dominant product vertex in a common black-and-white way"""
    import matplotlib.pyplot as plt
    plt.ioff()
    dab2v = self.get_dp_vertex_doubly_sparse()
    for i,ab2v in enumerate(dab2v): 
      plt.spy(ab2v.toarray())
      fname = "spy-v-{:06d}.png".format(i)
      print(fname)
      plt.savefig(fname, bbox_inches='tight')
      plt.close()
    return 0 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def test_scatterplot_w_ioff(self):
        """Check if scatterplot generates"""

        plt.ioff()
        figs = plot.scatterplot(self.testInst, 'longitude', 'latitude',
                                'slt', [0.0, 24.0])

        axes = figs[0].get_axes()
        assert len(figs) == 1
        assert len(axes) == 3
        assert not mpl.is_interactive() 

# 需要導入模塊: from matplotlib import pyplot [as 別名]
# 或者: from matplotlib.pyplot import ioff [as 別名]
def __call__(self, **kwargs):
        """Figure realizer

        The Figure class only keeps track of a root panel.  It does
        not contain an actual matplotlib Figure instance.  Whenever a
        figure needs to be created, Figure creates a new matplotlib
        Figure in order to drew/rendered/realized the figure.

        Args:

            **kwargs (dict): Arbitrary Figure-specific keyworded
                arguments that are used to construct the matplotlib
                Figure.

        """
        kwprops = merge_dict(self.kwprops, kwargs)
        style   = kwprops.pop('style')

        with mpl.rc_context():
            mpl.rcdefaults()
            plt.style.use(style)

            imode = mpl.is_interactive()
            if imode:
                plt.ioff()

            fig = plt.figure(**kwprops)
            ax  = newaxes(fig)
            yield fig, ax

            if imode:
                plt.ion()