| """ | |
| ==================================== | |
| Automatically setting tick positions | |
| ==================================== | |
| Setting the behavior of tick auto-placement. | |
| By default, Matplotlib will choose the number of ticks and tick positions so | |
| that there is a reasonable number of ticks on the axis and they are located | |
| at "round" numbers. | |
| As a result, there may be no ticks on the edges of the plot. | |
| """ | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| np.random.seed(19680801) | |
| fig, ax = plt.subplots() | |
| dots = np.linspace(0.3, 1.2, 10) | |
| X, Y = np.meshgrid(dots, dots) | |
| x, y = X.ravel(), Y.ravel() | |
| ax.scatter(x, y, c=x+y) | |
| plt.show() | |
| # %% | |
| # If you want to keep ticks at round numbers, and also have ticks at the edges | |
| # you can switch :rc:`axes.autolimit_mode` to 'round_numbers'. This expands the | |
| # axis limits to the next round number. | |
| plt.rcParams['axes.autolimit_mode'] = 'round_numbers' | |
| # Note: The limits are calculated at draw-time. Therefore, when using | |
| # :rc:`axes.autolimit_mode` in a context manager, it is important that | |
| # the ``show()`` command is within the context. | |
| fig, ax = plt.subplots() | |
| ax.scatter(x, y, c=x+y) | |
| plt.show() | |
| # %% | |
| # The round numbers autolimit_mode is still respected if you set an additional | |
| # margin around the data using `.Axes.set_xmargin` / `.Axes.set_ymargin`: | |
| fig, ax = plt.subplots() | |
| ax.scatter(x, y, c=x+y) | |
| ax.set_xmargin(0.8) | |
| plt.show() | |