All figure windows come with a navigation toolbar, which can be used to navigate through the data set. Here is a description of each of the buttons at the bottom of the toolbar
This button has two modes: pan and zoom. Click the toolbar button to activate panning and zooming, then put your mouse somewhere over an axes. Press the left mouse button and hold it to pan the figure, dragging it to a new position. When you release it, the data under the point where you pressed will be moved to the point where you released. If you press ‘x’ or ‘y’ while panning the motion will be constrained to the x or y axis, respectively. Press the right mouse button to zoom, dragging it to a new position. The x axis will be zoomed in proportionate to the rightward movement and zoomed out proportionate to the leftward movement. Ditto for the y axis and up/down motions. The point under your mouse when you begin the zoom remains stationary, allowing you to zoom to an arbitrary point in the figure. You can use the modifier keys ‘x’, ‘y’ or ‘CONTROL’ to constrain the zoom to the x axis, the y axis, or aspect ratio preserve, respectively.
With polar plots, the pan and zoom functionality behaves differently. The radius axis labels can be dragged using the left mouse button. The radius scale can be zoomed in and out using the right mouse button.
The following table holds all the default keys, which can be overwritten by use of your matplotlibrc (#keymap.*).
|Home/Reset||h or r or home|
|Back||c or left arrow or backspace|
|Forward||v or right arrow|
|Save||ctrl + s|
|Toggle fullscreen||ctrl + f|
|Close plot||ctrl + w|
|Constrain pan/zoom to x axis||hold x when panning/zooming with mouse|
|Constrain pan/zoom to y axis||hold y when panning/zooming with mouse|
|Preserve aspect ratio||hold CONTROL when panning/zooming with mouse|
|Toggle grid||g when mouse is over an axes|
|Toggle x axis scale (log/linear)||L or k when mouse is over an axes|
|Toggle y axis scale (log/linear)||l when mouse is over an axes|
If you are using matplotlib.pyplot the toolbar will be created automatically for every figure. If you are writing your own user interface code, you can add the toolbar as a widget. The exact syntax depends on your UI, but we have examples for every supported UI in the matplotlib/examples/user_interfaces directory. Here is some example code for GTK:
from matplotlib.figure import Figure from matplotlib.backends.backend_gtkagg import FigureCanvasGTKAgg as FigureCanvas from matplotlib.backends.backend_gtkagg import NavigationToolbar2GTKAgg as NavigationToolbar win = gtk.Window() win.connect("destroy", lambda x: gtk.main_quit()) win.set_default_size(400,300) win.set_title("Embedding in GTK") vbox = gtk.VBox() win.add(vbox) fig = Figure(figsize=(5,4), dpi=100) ax = fig.add_subplot(111) ax.plot([1,2,3]) canvas = FigureCanvas(fig) # a gtk.DrawingArea vbox.pack_start(canvas) toolbar = NavigationToolbar(canvas, win) vbox.pack_start(toolbar, False, False) win.show_all() gtk.main()