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)

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})

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