Python inset_locator.inset_axes方法代码示例

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def test_plain_axes(self):

        # supplied ax itself is a SubplotAxes, but figure contains also
        # a plain Axes object (GH11556)
        fig, ax = self.plt.subplots()
        fig.add_axes([0.2, 0.2, 0.2, 0.2])
        Series(rand(10)).plot(ax=ax)

        # suppliad ax itself is a plain Axes, but because the cmap keyword
        # a new ax is created for the colorbar -> also multiples axes (GH11520)
        df = DataFrame({'a': randn(8), 'b': randn(8)})
        fig = self.plt.figure()
        ax = fig.add_axes((0, 0, 1, 1))
        df.plot(kind='scatter', ax=ax, x='a', y='b', c='a', cmap='hsv')

        # other examples
        fig, ax = self.plt.subplots()
        from mpl_toolkits.axes_grid1 import make_axes_locatable
        divider = make_axes_locatable(ax)
        cax = divider.append_axes("right", size="5%", pad=0.05)
        Series(rand(10)).plot(ax=ax)
        Series(rand(10)).plot(ax=cax)

        fig, ax = self.plt.subplots()
        from mpl_toolkits.axes_grid1.inset_locator import inset_axes
        iax = inset_axes(ax, width="30%", height=1., loc=3)
        Series(rand(10)).plot(ax=ax)
        Series(rand(10)).plot(ax=iax) 

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def set_colorbar(smp, ax, orientation="vertical", labelsize=None):
    cax = inset_axes(ax, width="2%", height="30%", loc=4, borderpad=0)
    cb = pl.colorbar(smp, orientation=orientation, cax=cax)
    cb.set_alpha(1)
    cb.ax.tick_params(labelsize=labelsize)
    cb.draw_all()
    cb.locator = MaxNLocator(nbins=3, integer=True)
    cb.update_ticks() 

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def set_colorbar(ax):
    """https://matplotlib.org/3.1.0/gallery/axes_grid1/demo_colorbar_with_inset_locator.html"""
    from mpl_toolkits.axes_grid1.inset_locator import inset_axes

    axins = inset_axes(ax,
                       width="2.5%",  # width = 5% of parent_bbox width
                       height="20%",  # height : 50%
                       # loc='lower left',
                       # bbox_to_anchor=(1.05, 0., 1, 1),
                       # bbox_transform=ax.transAxes,
                       # borderpad=0,
                       )
    return axins 

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def add_colorbar(powers_ax, im, cb_ticks=[], cb_ticks_font_size=12):
    from mpl_toolkits.axes_grid1.inset_locator import inset_axes
    axins = inset_axes(powers_ax, width="5%", height="100%", loc=5,
                       bbox_to_anchor=(1.15, 0, 1, 1), bbox_transform=powers_ax.transAxes)
    cb = plt.colorbar(im, cax=axins)
    if cb_ticks != []:
        cb.set_ticks(cb_ticks)
    cb.ax.tick_params(labelsize=cb_ticks_font_size)
    cb.ax.set_ylabel('dBHZ Z-Score', color='black', fontsize=cb_ticks_font_size) 

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def mcolorbar(imgh, ax, location="horizontal", width="5%", height="100%", offset="-15%", vticks=[], ticksize=10, label_offset="5", label="", labelsize=10):
  """
  Add a multiple colormap colorbar to a plot.

  Parameters
  ----------
  imgh         : list of image hangle returned from contour or img funtions
  ax           : current Axes instance, usually ax = plt.gca()
  location     : horizontal or vertical
  width        : in percentage
  height       : in percentage
  offset       : offset from the main plot in percentage
  ticksize     : tick size
  vticks       : tick value labels
  labelsize    : label size
  label        : colorbar label
  label_offset : offset from the main plot in percentage
  """

  bmargin=(1.0-float(height.strip('%'))/100.0)*0.5
  fheight = 1.0/len(imgh)
  cheight_float = (1.0-2.0*bmargin)*fheight
  cheight = "%.2f%%" % (cheight_float*100.0)
  offset=float(offset.strip('%'))/100.0
  label_offset=float(label_offset.strip('%'))/100.0
  for i in range(0,len(imgh)):
    if location == "horizontal":
       axins = inset_axes(ax, cheight, width, loc=3,
                   bbox_to_anchor=(bmargin+cheight_float*i, offset, 1, 1),
                   bbox_transform=ax.transAxes,
                   borderpad=0,
                   )
       cb = plt.colorbar(imgh[i], cax=axins, orientation="horizontal")
    elif location == "vertical":
       axins = inset_axes(ax, width, cheight, loc=3,
                   bbox_to_anchor=(1.0+offset, bmargin+cheight_float*i, 1, 1),
                   bbox_transform=ax.transAxes,
                   borderpad=0,
                   )
       cb = plt.colorbar(imgh[i], cax=axins)
    cb.ax.tick_params(labelsize=ticksize)
    # Customize colorbar tick labels
    cb.set_ticks(vticks)

  if location == "horizontal":
    plt.text(bmargin+cheight_float*len(imgh)*0.5, offset+label_offset, label,
       horizontalalignment='center',
       verticalalignment='center',
       fontsize=labelsize,
       transform = ax.transAxes)
  else:
    plt.text(1.0+offset+label_offset, bmargin+cheight_float*len(imgh)*0.5, label,
       horizontalalignment='center',
       verticalalignment='center',
       rotation=90,
       fontsize=labelsize,
       transform = ax.transAxes) 

# 需要导入模块: from mpl_toolkits.axes_grid1 import inset_locator [as 别名]
# 或者: from mpl_toolkits.axes_grid1.inset_locator import inset_axes [as 别名]
def plot_reldiag(reldiag, ax=None):
    """Plot a reliability diagram.

    Parameters
    ----------
    reldiag : dict
        A reldiag object created by probscores.reldiag_init.
    ax : axis handle, optional
        Axis handle for the figure. If set to None, the handle is taken from
        the current figure (matplotlib.pylab.gca()).

    """
    if ax is None:
        ax = plt.gca()

    # Plot the reliability diagram.
    f = 1.0 * reldiag["Y_sum"] / reldiag["num_idx"]
    r = 1.0 * reldiag["X_sum"] / reldiag["num_idx"]

    mask = np.logical_and(np.isfinite(r), np.isfinite(f))

    ax.plot(r[mask], f[mask], "kD-")
    ax.plot([0, 1], [0, 1], "k--")

    ax.set_xlim(0, 1)
    ax.set_ylim(0, 1)

    ax.grid(True, ls=":")

    ax.set_xlabel("Forecast probability")
    ax.set_ylabel("Observed relative frequency")

    # Plot sharpness diagram into an inset figure.
    iax = inset_axes(ax, width="35%", height="20%", loc=4, borderpad=3.5)
    bw = reldiag["bin_edges"][2] - reldiag["bin_edges"][1]
    iax.bar(
        reldiag["bin_edges"][:-1],
        reldiag["sample_size"],
        width=bw,
        align="edge",
        color="gray",
        edgecolor="black",
    )
    iax.set_yscale("log", basey=10)
    iax.set_xticks(reldiag["bin_edges"])
    iax.set_xticklabels(["%.1f" % max(v, 1e-6) for v in reldiag["bin_edges"]])
    yt_min = int(max(np.floor(np.log10(min(reldiag["sample_size"][:-1]))), 1))
    yt_max = int(np.ceil(np.log10(max(reldiag["sample_size"][:-1]))))
    t = [pow(10.0, k) for k in range(yt_min, yt_max)]

    iax.set_yticks([int(t_) for t_ in t])
    iax.set_xlim(0.0, 1.0)
    iax.set_ylim(t[0], 5 * t[-1])
    iax.set_ylabel("log10(samples)")
    iax.yaxis.tick_right()
    iax.yaxis.set_label_position("right")
    iax.tick_params(axis="both", which="major", labelsize=6)