Python pyplot.Axes方法代码示例

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def plot_data(data):
    t = np.arange(0, 29, 1)
    file_name_number = 0
    fig = plt.figure(frameon=False)
    for group in data:
        count = 30
        while count <= (len(group)-5):
            high = []
            low = []
            for item in group[count-30:count]:
                high.append(item[0])
                low.append(item[1])
            file_name = r'\fig_' + str(file_name_number)
            ax = plt.Axes(fig, [0., 0., 1., 1.])
            ax.set_axis_off()
            fig.add_axes(ax)
            ax.plot(t, high[0:-1], 'b', t, low[0:-1], 'g')
            fig.savefig(r'\figures' + file_name)
            fig.clf()
            file_name_number += 1
            count += 1
    print('Created %d files!' % file_name_number) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def plot_data(data):
    t = np.arange(0, 29, 1)
    file_name_number = 0
    fig = plt.figure(frameon=False, figsize=(width, height))
    for group in data:
        count = 30
        while count <= (len(group)-5):
            high = []
            low = []
            for item in group[count-30:count]:
                high.append(item[0])
                low.append(item[1])
            file_name = r'\fig_' + str(file_name_number)
            ax = plt.Axes(fig, [0., 0., 1., 1.])
            ax.set_axis_off()
            fig.add_axes(ax)
            ax.plot(t, high[0:-1], 'b', t, low[0:-1], 'g')
            fig.savefig(r'\figures_v2' + file_name, dpi=100)
            fig.clf()
            file_name_number += 1
            count += 1
    print('Created %d files!' % file_name_number) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def assert_is_valid_plot_return_object(objs):  # pragma: no cover
    import matplotlib.pyplot as plt

    if isinstance(objs, (pd.Series, np.ndarray)):
        for el in objs.ravel():
            msg = (
                "one of 'objs' is not a matplotlib Axes instance, "
                "type encountered {}".format(repr(type(el).__name__))
            )
            assert isinstance(el, (plt.Axes, dict)), msg
    else:
        msg = (
            "objs is neither an ndarray of Artist instances nor a single "
            "ArtistArtist instance, tuple, or dict, 'objs' is a {}".format(
                repr(type(objs).__name__))
        )
        assert isinstance(objs, (plt.Artist, tuple, dict)), msg 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def plot(self, **kwargs):
        """Plot current quadtree

        :param axes: Axes instance to plot in, defaults to None
        :type axes: [:py:class:`matplotlib.Axes`], optional
        :param figure: Figure instance to plot in, defaults to None
        :type figure: [:py:class:`matplotlib.Figure`], optional
        :param **kwargs: kwargs are passed into `plt.imshow`
        :type **kwargs: dict
        """
        self._initImagePlot(**kwargs)
        self.data = self._quadtree.leaf_matrix_means
        self.title = 'Quadtree Means'

        self._addInfoText()

        if self._show_plt:
            plt.show() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def _prepare_state_printing(self, ax: plt.Axes):
        ys = [self.TEXT_Y_POSN_INITIAL + i * self.TEXT_Y_INCREMENT
              for i in range(len(self.print_props))]

        for prop, y in zip(self.print_props, ys):
            label = str(prop.name)
            ax.text(self.TEXT_X_POSN_LABEL, y, label, transform=ax.transAxes, **(self.LABEL_TEXT_KWARGS))

        # print and store empty Text objects which we will rewrite each plot call
        value_texts = []
        dummy_msg = ''
        for y in ys:
            text = ax.text(self.TEXT_X_POSN_VALUE, y, dummy_msg, transform=ax.transAxes,
                           **(self.VALUE_TEXT_KWARGS))
            value_texts.append(text)
        self.value_texts = tuple(value_texts) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def axes_object(ax):
    """ Checks if a value if an Axes. If None, a new one is created.
    Both the figure and axes are returned (in that order).

    """

    if ax is None:
        ax = pyplot.gca()
        fig = ax.figure
    elif isinstance(ax, pyplot.Axes):
        fig = ax.figure
    else:
        msg = "`ax` must be a matplotlib Axes instance or None"
        raise ValueError(msg)

    return fig, ax 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def show(plot_to_show):
    """Display a plot, either interactive or static.

    Parameters
    ----------
    plot_to_show: Output of a plotting command (matplotlib axis or bokeh figure)
        The plot to show

    Returns
    -------
    None
    """
    if isinstance(plot_to_show, plt.Axes):
        show_static()
    elif isinstance(plot_to_show, bpl.Figure):
        show_interactive(plot_to_show)
    else:
        raise ValueError(
            "The type of ``plot_to_show`` was not valid, or not understood."
        ) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def _write_annotations(self, mesh: mpl_collections.Collection,
                           ax: plt.Axes) -> None:
        """Writes annotations to the center of cells. Internal."""
        for path, facecolor in zip(mesh.get_paths(), mesh.get_facecolors()):
            # Calculate the center of the cell, assuming that it is a square
            # centered at (x=col, y=row).
            vertices = path.vertices[:4]
            row = int(round(np.mean([v[1] for v in vertices])))
            col = int(round(np.mean([v[0] for v in vertices])))
            annotation = self.annot_map.get((row, col), '')
            if not annotation:
                continue
            face_luminance = relative_luminance(facecolor)
            text_color = 'black' if face_luminance > 0.4 else 'white'
            text_kwargs = dict(color=text_color, ha="center", va="center")
            text_kwargs.update(self.annot_kwargs)
            ax.text(col, row, annotation, **text_kwargs) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def plot(self, ax: Optional[plt.Axes] = None,
             **plot_kwargs: Any) -> plt.Axes:
        """Plots the average XEB fidelity vs the number of cycles.

        Args:
            ax: the plt.Axes to plot on. If not given, a new figure is created,
                plotted on, and shown.
            **plot_kwargs: Arguments to be passed to 'plt.Axes.plot'.
        Returns:
            The plt.Axes containing the plot.
        """
        show_plot = not ax
        if not ax:
            fig, ax = plt.subplots(1, 1, figsize=(8, 8))
        num_cycles = [d.num_cycle for d in self.data]
        fidelities = [d.xeb_fidelity for d in self.data]
        ax.set_ylim([0, 1.1])
        ax.plot(num_cycles, fidelities, 'ro-', **plot_kwargs)
        ax.set_xlabel('Number of Cycles')
        ax.set_ylabel('XEB Fidelity')
        if show_plot:
            fig.show()
        return ax 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def plot(self, ax: Optional[plt.Axes] = None,
             **plot_kwargs: Any) -> plt.Axes:
        """Plots the average ground state probability vs the number of
        Cliffords in the RB study.

        Args:
            ax: the plt.Axes to plot on. If not given, a new figure is created,
                plotted on, and shown.
            **plot_kwargs: Arguments to be passed to 'plt.Axes.plot'.
        Returns:
            The plt.Axes containing the plot.
        """
        show_plot = not ax
        if not ax:
            fig, ax = plt.subplots(1, 1, figsize=(8, 8))
        ax.set_ylim([0, 1])
        ax.plot(self._num_cfds_seq, self._gnd_state_probs, 'ro-', **plot_kwargs)
        ax.set_xlabel(r"Number of Cliffords")
        ax.set_ylabel('Ground State Probability')
        if show_plot:
            fig.show()
        return ax 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def save_pic(pic, path, exp):
    if len(pic.shape) == 4:
        pic = pic[0]
    height = pic.shape[0]
    width = pic.shape[1]
    fig = plt.figure(frameon=False, figsize=(width, height))#, dpi=1)
    ax = plt.Axes(fig, [0., 0., 1., 1.])
    ax.set_axis_off()
    fig.add_axes(ax)
    if exp.symmetrize:
        pic = (pic + 1.) / 2.
    if exp.dataset == 'mnist':
        pic = pic[:, :, 0]
        pic = 1. - pic
    if exp.dataset == 'mnist':
        ax.imshow(pic, cmap='Greys', interpolation='none')
    else:
        ax.imshow(pic, interpolation='none')
    fig.savefig(path, dpi=1, format='png')
    plt.close()
    # if exp.dataset == 'mnist':
    #     pic = pic[:, :, 0]
    #     pic = 1. - pic
    #     ax = plt.imshow(pic, cmap='Greys', interpolation='none')
    # else:
    #     ax = plt.imshow(pic, interpolation='none')
    # ax.axes.get_xaxis().set_ticks([])
    # ax.axes.get_yaxis().set_ticks([])
    # ax.axes.set_xlim([0, width])
    # ax.axes.set_ylim([height, 0])
    # ax.axes.set_aspect(1)
    # fig.savefig(path, format='png')
    # plt.close() 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def assert_is_valid_plot_return_object(objs):
    import matplotlib.pyplot as plt
    if isinstance(objs, (pd.Series, np.ndarray)):
        for el in objs.ravel():
            msg = ("one of 'objs' is not a matplotlib Axes instance, type "
                   "encountered {name!r}").format(name=el.__class__.__name__)
            assert isinstance(el, (plt.Axes, dict)), msg
    else:
        assert isinstance(objs, (plt.Artist, tuple, dict)), (
            'objs is neither an ndarray of Artist instances nor a '
            'single Artist instance, tuple, or dict, "objs" is a {name!r}'
            .format(name=objs.__class__.__name__)) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def __init__(self, image, title="Initial problem"):
        aspect_ratio = image.shape[0] / float(image.shape[1])

        width = 8
        height = width * aspect_ratio
        fig = plt.figure(figsize=(width, height), frameon=False)

        # Let image fill the figure
        ax = plt.Axes(fig, [0., 0., 1., .9])
        ax.set_axis_off()
        fig.add_axes(ax)

        self._current_image = ax.imshow(image, aspect="auto", animated=True)
        self.show_fittest(image, title) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def assert_is_valid_plot_return_object(objs):
    import matplotlib.pyplot as plt
    if isinstance(objs, (pd.Series, np.ndarray)):
        for el in objs.ravel():
            msg = ('one of \'objs\' is not a matplotlib Axes instance, type '
                   'encountered {name!r}').format(name=el.__class__.__name__)
            assert isinstance(el, (plt.Axes, dict)), msg
    else:
        assert isinstance(objs, (plt.Artist, tuple, dict)), \
            ('objs is neither an ndarray of Artist instances nor a '
             'single Artist instance, tuple, or dict, "objs" is a {name!r}'
             ).format(name=objs.__class__.__name__) 

# 需要导入模块: from matplotlib import pyplot [as 别名]
# 或者: from matplotlib.pyplot import Axes [as 别名]
def grouped_hist(data, column=None, by=None, ax=None, bins=50, figsize=None,
                 layout=None, sharex=False, sharey=False, rot=90, grid=True,
                 **kwargs):
    """
    Grouped histogram

    Parameters
    ----------
    data: Series/DataFrame
    column: object, optional
    by: object, optional
    ax: axes, optional
    bins: int, default 50
    figsize: tuple, optional
    layout: optional
    sharex: boolean, default False
    sharey: boolean, default False
    rot: int, default 90
    grid: bool, default True
    kwargs: dict, keyword arguments passed to matplotlib.Axes.hist

    Returns
    -------
    axes: collection of Matplotlib Axes
    """
    def plot_group(group, ax):
        ax.hist(group.dropna().values, bins=bins, **kwargs)

    fig, axes = _grouped_plot(plot_group, data, column=column,
                              by=by, sharex=sharex, sharey=sharey,
                              figsize=figsize, layout=layout, rot=rot)
    fig.subplots_adjust(bottom=0.15, top=0.9, left=0.1, right=0.9,
                        hspace=0.5, wspace=0.3)
    return axes