""" ================ Axes Zoom Effect ================ """ 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): """ Connect *ax1* and *ax2*. The *xmin*-to-*xmax* range in both axes will be marked. Parameters ---------- ax1 The main axes. ax2 The zoomed axes. xmin, xmax The limits of the colored area in both plot axes. **kwargs Arguments passed to the patch constructor. """ 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(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()