|
3 | 3 | Interactive Adjustment of Colormap Range |
4 | 4 | ======================================== |
5 | 5 |
|
6 | | -Demonstration of using colorbar, picker, and event functionality to make an |
7 | | -interactively adjustable colorbar widget. |
| 6 | +Demonstration of how a colorbar can be used to interactively adjust the |
| 7 | +range of colormapping on an image. To use the interactive feature, you must |
| 8 | +be in either zoom or pan mode and click inside the colorbar. |
8 | 9 |
|
9 | | -Left clicks and drags inside the colorbar axes adjust the high range of the |
10 | | -color scheme. Likewise, right clicks and drags adjust the low range. The |
11 | | -connected AxesImage immediately updates to reflect the change. |
| 10 | +When zooming, the bbox of the zoom region defines the new vmin and vmax of |
| 11 | +the norm. Right clicking while in zoom mode will expand the |
| 12 | +vmin and vmax proportionally to the selected region, in the same manner that |
| 13 | +one can zoom out of an axis. When panning, the vmin and vmax of the norm are |
| 14 | +both adjusted according to the direction of movement. |
| 15 | +
|
| 16 | +The title on the axes show what happens if a zoom or pan occurs on the |
| 17 | +colorbar. All of the colorbars in the figure have interactivity enabled and |
| 18 | +only update the image that the colorbar is associated with. |
12 | 19 |
|
13 | 20 | .. redirect-from:: /gallery/userdemo/colormap_interactive_adjustment |
14 | 21 | """ |
15 | | - |
16 | | -import numpy as np |
17 | 22 | import matplotlib.pyplot as plt |
18 | | -from matplotlib.backend_bases import MouseButton |
19 | | - |
20 | | -############################################################################### |
21 | | -# Callback definitions |
22 | | - |
23 | | - |
24 | | -def on_pick(event): |
25 | | - adjust_colorbar(event.mouseevent) |
26 | | - |
27 | | - |
28 | | -def on_move(mouseevent): |
29 | | - if mouseevent.inaxes is colorbar.ax: |
30 | | - adjust_colorbar(mouseevent) |
31 | | - |
| 23 | +import numpy as np |
32 | 24 |
|
33 | | -def adjust_colorbar(mouseevent): |
34 | | - if mouseevent.button == MouseButton.LEFT: |
35 | | - colorbar.norm.vmax = max(mouseevent.ydata, colorbar.norm.vmin) |
36 | | - elif mouseevent.button == MouseButton.RIGHT: |
37 | | - colorbar.norm.vmin = min(mouseevent.ydata, colorbar.norm.vmax) |
| 25 | +start = 0 |
| 26 | +stop = 2 * np.pi |
| 27 | +N = 1024 |
| 28 | +t = np.linspace(start, stop, N) |
| 29 | +data1d = np.sin(t) |
| 30 | + |
| 31 | +data2d = np.sin(t[:, np.newaxis]) * np.cos(t[np.newaxis, :]) |
| 32 | + |
| 33 | +zoom_axes = ["2d", "color zoom in", "color zoom out"] |
| 34 | +pan_axes = ["2d", "color pan up", "color pan down"] |
| 35 | + |
| 36 | +fig, ax_dict = plt.subplot_mosaic( |
| 37 | + [ |
| 38 | + zoom_axes, |
| 39 | + pan_axes |
| 40 | + ], |
| 41 | + constrained_layout=True, |
| 42 | +) |
| 43 | + |
| 44 | +for name in zoom_axes: |
| 45 | + ax = ax_dict[name] |
| 46 | + im = ax.imshow( |
| 47 | + data2d, |
| 48 | + extent=[start - (stop - start) / (2 * N), |
| 49 | + stop + (stop - start) / (2 * N)] * 2, |
| 50 | + ) |
| 51 | + ax.set_title(name) |
| 52 | + fig.colorbar(im, ax=ax, aspect=7) |
| 53 | + if name == "color zoom in": |
| 54 | + im.set_clim(-0.1, 0.1) |
| 55 | + elif name == "color zoom out": |
| 56 | + im.set_clim(-10, 10) |
38 | 57 | else: |
39 | | - # discard all others |
40 | | - return |
41 | | - |
42 | | - canvas.draw_idle() |
43 | | - |
44 | | - |
45 | | -############################################################################### |
46 | | -# Generate figure with Axesimage and Colorbar |
47 | | - |
48 | | -fig, ax = plt.subplots() |
49 | | -canvas = fig.canvas |
50 | | - |
51 | | -delta = 0.1 |
52 | | -x = np.arange(-3.0, 4.001, delta) |
53 | | -y = np.arange(-4.0, 3.001, delta) |
54 | | -X, Y = np.meshgrid(x, y) |
55 | | -Z1 = np.exp(-X**2 - Y**2) |
56 | | -Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2) |
57 | | -Z = (0.9*Z1 - 0.5*Z2) * 2 |
58 | | - |
59 | | -cmap = plt.colormaps['viridis'].with_extremes( |
60 | | - over='xkcd:orange', under='xkcd:dark red') |
61 | | -axesimage = plt.imshow(Z, cmap=cmap) |
62 | | -colorbar = plt.colorbar(axesimage, ax=ax, use_gridspec=True) |
63 | | - |
64 | | -############################################################################### |
65 | | -# Note that axesimage and colorbar share a Normalize object |
66 | | -# so they will stay in sync |
67 | | - |
68 | | -assert colorbar.norm is axesimage.norm |
69 | | -colorbar.norm.vmax = 1.5 |
70 | | -axesimage.norm.vmin = -0.75 |
71 | | - |
72 | | -############################################################################### |
73 | | -# Hook Colorbar up to canvas events |
74 | | - |
75 | | -# `set_navigate` helps you see what value you are about to set the range |
76 | | -# to, and enables zoom and pan in the colorbar which can be helpful for |
77 | | -# narrow or wide data ranges |
78 | | -colorbar.ax.set_navigate(True) |
79 | | - |
80 | | -# React to all motion with left or right mouse buttons held |
81 | | -canvas.mpl_connect("motion_notify_event", on_move) |
82 | | - |
83 | | -# React only to left and right clicks |
84 | | -colorbar.ax.set_picker(True) |
85 | | -canvas.mpl_connect("pick_event", on_pick) |
86 | | - |
87 | | -############################################################################### |
88 | | -# Display |
89 | | -# |
90 | | -# The colormap will now respond to left and right clicks in the Colorbar axes |
| 58 | + im.set_clim(-1, 1) |
| 59 | + |
| 60 | +for name in pan_axes: |
| 61 | + ax = ax_dict[name] |
| 62 | + if name == "2d": |
| 63 | + # Don't make this axes twice |
| 64 | + continue |
| 65 | + im = ax.imshow( |
| 66 | + data2d, |
| 67 | + extent=[start - (stop - start) / (2 * N), |
| 68 | + stop + (stop - start) / (2 * N)] * 2, |
| 69 | + ) |
| 70 | + ax.set_title(name) |
| 71 | + fig.colorbar(im, ax=ax, aspect=7) |
| 72 | + if name == "color pan up": |
| 73 | + im.set_clim(0, 2) |
| 74 | + elif name == "color pan down": |
| 75 | + im.set_clim(-2, 0) |
| 76 | + else: |
| 77 | + im.set_clim(-1, 1) |
91 | 78 |
|
92 | 79 | plt.show() |
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