You are reading documentation for the unreleased version of Matplotlib. Try searching for the released version of this page instead?
Applications are open for the 2018 John Hunter Matplotlib Summer Fellowship. Apply now!
Version 2.2.2.post1768+g23420a4c1
matplotlib
Fork me on GitHub

Related Topics

Axes Zoom EffectΒΆ

../../_images/sphx_glr_axes_zoom_effect_001.png
from matplotlib.transforms import (
    Bbox, TransformedBbox, blended_transform_factory)

from mpl_toolkits.axes_grid1.inset_locator import (
    BboxPatch, BboxConnector, BboxConnectorPatch)


def connect_bbox(bbox1, bbox2,
                 loc1a, loc2a, loc1b, loc2b,
                 prop_lines, prop_patches=None):
    if prop_patches is None:
        prop_patches = {
            **prop_lines,
            "alpha": prop_lines.get("alpha", 1) * 0.2,
        }

    c1 = BboxConnector(bbox1, bbox2, loc1=loc1a, loc2=loc2a, **prop_lines)
    c1.set_clip_on(False)
    c2 = BboxConnector(bbox1, bbox2, loc1=loc1b, loc2=loc2b, **prop_lines)
    c2.set_clip_on(False)

    bbox_patch1 = BboxPatch(bbox1, **prop_patches)
    bbox_patch2 = BboxPatch(bbox2, **prop_patches)

    p = BboxConnectorPatch(bbox1, bbox2,
                           # loc1a=3, loc2a=2, loc1b=4, loc2b=1,
                           loc1a=loc1a, loc2a=loc2a, loc1b=loc1b, loc2b=loc2b,
                           **prop_patches)
    p.set_clip_on(False)

    return c1, c2, bbox_patch1, bbox_patch2, p


def zoom_effect01(ax1, ax2, xmin, xmax, **kwargs):
    """
    ax1 : the main axes
    ax1 : the zoomed axes
    (xmin,xmax) : the limits of the colored area in both plot axes.

    connect ax1 & ax2. The x-range of (xmin, xmax) in both axes will
    be marked.  The keywords parameters will be used ti create
    patches.

    """

    trans1 = blended_transform_factory(ax1.transData, ax1.transAxes)
    trans2 = blended_transform_factory(ax2.transData, ax2.transAxes)

    bbox = Bbox.from_extents(xmin, 0, xmax, 1)

    mybbox1 = TransformedBbox(bbox, trans1)
    mybbox2 = TransformedBbox(bbox, trans2)

    prop_patches = {**kwargs, "ec": "none", "alpha": 0.2}

    c1, c2, bbox_patch1, bbox_patch2, p = connect_bbox(
        mybbox1, mybbox2,
        loc1a=3, loc2a=2, loc1b=4, loc2b=1,
        prop_lines=kwargs, prop_patches=prop_patches)

    ax1.add_patch(bbox_patch1)
    ax2.add_patch(bbox_patch2)
    ax2.add_patch(c1)
    ax2.add_patch(c2)
    ax2.add_patch(p)

    return c1, c2, bbox_patch1, bbox_patch2, p


def zoom_effect02(ax1, ax2, **kwargs):
    """
    ax1 : the main axes
    ax1 : the zoomed axes

    Similar to zoom_effect01.  The xmin & xmax will be taken from the
    ax1.viewLim.
    """

    tt = ax1.transScale + (ax1.transLimits + ax2.transAxes)
    trans = blended_transform_factory(ax2.transData, tt)

    mybbox1 = ax1.bbox
    mybbox2 = TransformedBbox(ax1.viewLim, trans)

    prop_patches = {**kwargs, "ec": "none", "alpha": 0.2}

    c1, c2, bbox_patch1, bbox_patch2, p = connect_bbox(
        mybbox1, mybbox2,
        loc1a=3, loc2a=2, loc1b=4, loc2b=1,
        prop_lines=kwargs, prop_patches=prop_patches)

    ax1.add_patch(bbox_patch1)
    ax2.add_patch(bbox_patch2)
    ax2.add_patch(c1)
    ax2.add_patch(c2)
    ax2.add_patch(p)

    return c1, c2, bbox_patch1, bbox_patch2, p


import matplotlib.pyplot as plt

plt.figure(1, figsize=(5, 5))
ax1 = plt.subplot(221)
ax2 = plt.subplot(212)
ax2.set_xlim(0, 1)
ax2.set_xlim(0, 5)
zoom_effect01(ax1, ax2, 0.2, 0.8)


ax1 = plt.subplot(222)
ax1.set_xlim(2, 3)
ax2.set_xlim(0, 5)
zoom_effect02(ax1, ax2)

plt.show()

Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery