Python Axes.scatter方法代碼示例

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def test_move(ax, plotter):
    plotter(ax, [0, 1, 2], [0, 1, np.nan])
    cursor = mplcursors.cursor()
    # Nothing happens with no cursor.
    _process_event("key_press_event", ax, (.123, .456), "shift+left")
    assert len(cursor.selections) == 0
    # Now we move the cursor left or right.
    if plotter in [Axes.plot, Axes.errorbar]:
        _process_event("__mouse_click__", ax, (.5, .5), 1)
        assert tuple(cursor.selections[0].target) == approx((.5, .5))
        _process_event("key_press_event", ax, (.123, .456), "shift+up")
        _process_event("key_press_event", ax, (.123, .456), "shift+left")
    elif plotter is Axes.scatter:
        _process_event("__mouse_click__", ax, (0, 0), 1)
        _process_event("key_press_event", ax, (.123, .456), "shift+up")
    assert tuple(cursor.selections[0].target) == (0, 0)
    assert cursor.selections[0].target.index == 0
    _process_event("key_press_event", ax, (.123, .456), "shift+right")
    assert tuple(cursor.selections[0].target) == (1, 1)
    assert cursor.selections[0].target.index == 1
    # Skip through nan.
    _process_event("key_press_event", ax, (.123, .456), "shift+right")
    assert tuple(cursor.selections[0].target) == (0, 0)
    assert cursor.selections[0].target.index == 0 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def _register_scatter():
    """
    Patch `PathCollection` and `scatter` to register their return values.

    This registration allows us to distinguish `PathCollection`s created by
    `Axes.scatter`, which should use point-like picking, from others, which
    should use path-like picking.  The former is more common, so we store the
    latter instead; this also lets us guess the type better if this module is
    imported late.
    """

    @functools.wraps(PathCollection.__init__)
    def __init__(self, *args, **kwargs):
        _nonscatter_pathcollections.add(self)
        return __init__.__wrapped__(self, *args, **kwargs)
    PathCollection.__init__ = __init__

    @functools.wraps(Axes.scatter)
    def scatter(*args, **kwargs):
        paths = scatter.__wrapped__(*args, **kwargs)
        with suppress(KeyError):
            _nonscatter_pathcollections.remove(paths)
        return paths
    Axes.scatter = scatter 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def scatter(x, y, s=20, c='b', marker='o', cmap=None, norm=None, vmin=None,
            vmax=None, alpha=None, linewidths=None, verts=None, hold=None,
            **kwargs):
    ax = gca()
    # allow callers to override the hold state by passing hold=True|False
    washold = ax.ishold()

    if hold is not None:
        ax.hold(hold)
    try:
        ret = ax.scatter(x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
                         vmin=vmin, vmax=vmax, alpha=alpha,
                         linewidths=linewidths, verts=verts, **kwargs)
        draw_if_interactive()
    finally:
        ax.hold(washold)
    sci(ret)
    return ret

# This function was autogenerated by boilerplate.py.  Do not edit as
# changes will be lost 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def gci():
    """
    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.
    """
    return gcf()._gci()


## Any Artist ##


# (getp is simply imported) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def scatter(x, y, s=None, c=None, marker=None, cmap=None, norm=None, vmin=None,
            vmax=None, alpha=None, linewidths=None, verts=None, edgecolors=None,
            hold=None, data=None, **kwargs):
    ax = gca()
    # Deprecated: allow callers to override the hold state
    # by passing hold=True|False
    washold = ax._hold

    if hold is not None:
        ax._hold = hold
        from matplotlib.cbook import mplDeprecation
        warnings.warn("The 'hold' keyword argument is deprecated since 2.0.",
                      mplDeprecation)
    try:
        ret = ax.scatter(x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
                         vmin=vmin, vmax=vmax, alpha=alpha,
                         linewidths=linewidths, verts=verts,
                         edgecolors=edgecolors, data=data, **kwargs)
    finally:
        ax._hold = washold
    sci(ret)
    return ret

# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def test_scatter_text(ax):
    ax.scatter([0, 1], [0, 1], c=[2, 3])
    cursor = mplcursors.cursor()
    _process_event("__mouse_click__", ax, (0, 0), 1)
    assert _parse_annotation(
        cursor.selections[0], "x=(.*)\ny=(.*)\n\[(.*)\]") == (0, 0, 2) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def _(artist, event):
    offsets = artist.get_offsets()
    paths = artist.get_paths()
    if _is_scatter(artist):
        # Use the C implementation to prune the list of segments -- but only
        # for scatter plots as that implementation is inconsistent with Line2D
        # for segment-like collections (matplotlib/matplotlib#17279).
        contains, info = artist.contains(event)
        if not contains:
            return
        inds = info["ind"]
        offsets = artist.get_offsets()[inds]
        offsets_screen = artist.get_offset_transform().transform(offsets)
        ds = np.hypot(*(offsets_screen - [event.x, event.y]).T)
        argmin = ds.argmin()
        target = _with_attrs(
            _untransform(offsets[argmin], offsets_screen[argmin], artist.axes),
            index=inds[argmin])
        return Selection(artist, target, ds[argmin], None, None)
    else:
        # Note that this won't select implicitly closed paths.
        sels = [*filter(None, [
            _compute_projection_pick(
                artist,
                Affine2D().translate(*offsets[ind % len(offsets)])
                .transform_path(paths[ind % len(paths)]),
                (event.x, event.y))
            for ind in range(max(len(offsets), len(paths)))])]
        if not sels:
            return None
        idx = min(range(len(sels)), key=lambda idx: sels[idx].dist)
        sel = sels[idx]
        if sel.dist >= artist.get_pickradius():
            return None
        sel = sel._replace(artist=artist)
        sel.target.index = (idx, sel.target.index)
        return sel 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def gci():
    """
    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.
    """
    return gcf()._gci() 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def scatter(
        x, y, s=None, c=None, marker=None, cmap=None, norm=None,
        vmin=None, vmax=None, alpha=None, linewidths=None, verts=None,
        edgecolors=None, *, data=None, **kwargs):
    __ret = gca().scatter(
        x=x, y=y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
        vmin=vmin, vmax=vmax, alpha=alpha, linewidths=linewidths,
        verts=verts, edgecolors=edgecolors, data=data, **kwargs)
    sci(__ret)
    return __ret

# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def scatter(
        x, y, s=None, c=None, marker=None, cmap=None, norm=None,
        vmin=None, vmax=None, alpha=None, linewidths=None, verts=None,
        edgecolors=None, *, data=None, **kwargs):
    __ret = gca().scatter(
        x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
        vmin=vmin, vmax=vmax, alpha=alpha, linewidths=linewidths,
        verts=verts, edgecolors=edgecolors, **({"data": data} if data
        is not None else {}), **kwargs)
    sci(__ret)
    return __ret


# Autogenerated by boilerplate.py.  Do not edit as changes will be lost. 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def gci():
    """
    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).
    """
    return gcf()._gci()


## Any Artist ##


# (getp is simply imported) 

# 需要導入模塊: from matplotlib.axes import Axes [as 別名]
# 或者: from matplotlib.axes.Axes import scatter [as 別名]
def scatter(
        x, y, s=None, c=None, marker=None, cmap=None, norm=None,
        vmin=None, vmax=None, alpha=None, linewidths=None, verts=None,
        edgecolors=None, *, plotnonfinite=False, data=None, **kwargs):
    __ret = gca().scatter(
        x, y, s=s, c=c, marker=marker, cmap=cmap, norm=norm,
        vmin=vmin, vmax=vmax, alpha=alpha, linewidths=linewidths,
        verts=verts, edgecolors=edgecolors,
        plotnonfinite=plotnonfinite, **({"data": data} if data is not
        None else {}), **kwargs)
    sci(__ret)
    return __ret


# Autogenerated by boilerplate.py.  Do not edit as changes will be lost.