| """ | |
| ============================================== | |
| Some features of the histogram (hist) function | |
| ============================================== | |
| In addition to the basic histogram, this demo shows a few optional features: | |
| * Setting the number of data bins. | |
| * The *density* parameter, which normalizes bin heights so that the integral of | |
| the histogram is 1. The resulting histogram is an approximation of the | |
| probability density function. | |
| Selecting different bin counts and sizes can significantly affect the shape | |
| of a histogram. The Astropy docs have a great section_ on how to select these | |
| parameters. | |
| .. _section: http://docs.astropy.org/en/stable/visualization/histogram.html | |
| """ | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| np.random.seed(19680801) | |
| # example data | |
| mu = 100 # mean of distribution | |
| sigma = 15 # standard deviation of distribution | |
| x = mu + sigma * np.random.randn(437) | |
| num_bins = 50 | |
| fig, ax = plt.subplots() | |
| # the histogram of the data | |
| n, bins, patches = ax.hist(x, num_bins, density=True) | |
| # add a 'best fit' line | |
| y = ((1 / (np.sqrt(2 * np.pi) * sigma)) * | |
| np.exp(-0.5 * (1 / sigma * (bins - mu))**2)) | |
| ax.plot(bins, y, '--') | |
| ax.set_xlabel('Smarts') | |
| ax.set_ylabel('Probability density') | |
| ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$') | |
| # Tweak spacing to prevent clipping of ylabel | |
| fig.tight_layout() | |
| plt.show() | |
| # %% | |
| # | |
| # .. admonition:: References | |
| # | |
| # The use of the following functions, methods, classes and modules is shown | |
| # in this example: | |
| # | |
| # - `matplotlib.axes.Axes.hist` / `matplotlib.pyplot.hist` | |
| # - `matplotlib.axes.Axes.set_title` | |
| # - `matplotlib.axes.Axes.set_xlabel` | |
| # - `matplotlib.axes.Axes.set_ylabel` | |