Note

This page was generated from an IPython notebook that can be downloaded here.

Getting startedΒΆ

The only user-facing function in the module is corner.corner and, in its simplest form, you use it like this:

import corner
import numpy as np

ndim, nsamples = 2, 10000
np.random.seed(42)
samples = np.random.randn(ndim * nsamples).reshape([nsamples, ndim])
figure = corner.corner(samples)
../_images/quickstart_2_0.png

The following snippet demonstrates a few more bells and whistles:

# Set up the parameters of the problem.
ndim, nsamples = 3, 50000

# Generate some fake data.
np.random.seed(42)
data1 = np.random.randn(ndim * 4 * nsamples // 5).reshape([4 * nsamples // 5, ndim])
data2 = (4*np.random.rand(ndim)[None, :] + np.random.randn(ndim * nsamples // 5).reshape([nsamples // 5, ndim]))
data = np.vstack([data1, data2])

# Plot it.
figure = corner.corner(data, labels=[r"$x$", r"$y$", r"$\log \alpha$", r"$\Gamma \, [\mathrm{parsec}]$"],
                       quantiles=[0.16, 0.5, 0.84],
                       show_titles=True, title_kwargs={"fontsize": 12})
../_images/quickstart_4_0.png

The API documentation gives more details about all the arguments available for customization.