Skip to content

interpolated plot #4557

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 5 commits into from
Mar 23, 2021
Merged

interpolated plot #4557

Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
5722fbd
interpolated plot
mjhajharia Mar 22, 2021
4fc408d
interpolated minor fixes
mjhajharia Mar 22, 2021
675f8c8
minor edits
mjhajharia Mar 22, 2021
e4f72a1
histogram fix
mjhajharia Mar 22, 2021
7bd94c7
relocate arviz style line position
mjhajharia Mar 23, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
22 changes: 22 additions & 0 deletions pymc3/distributions/continuous.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4223,6 +4223,28 @@ class Interpolated(BoundedContinuous):
Both parameters ``x_points`` and values ``pdf_points`` are not variables, but
plain array-like objects, so they are constant and cannot be sampled.

.. plot::

import matplotlib.pyplot as plt
import numpy as np
import pymc3 as pm
import arviz as az
from scipy.stats import gamma
plt.style.use('arviz-darkgrid')
rv = gamma(1.99)
x = np.linspace(rv.ppf(0.01),rv.ppf(0.99), 1000)
points = np.linspace(x[0], x[-1], 50)
pdf = rv.pdf(points)
interpolated = pm.Interpolated.dist(points, pdf)
fig, ax = plt.subplots(1, 1)
ax.plot(x, rv.pdf(x), 'C0', linestyle = '--', label='Original Gamma pdf',alpha=0.8,lw=2)
ax.plot(points, pdf, color='black', marker='o', label='Lattice Points',alpha=0.5,linestyle='')
ax.plot(x, np.exp(interpolated.logp(x).eval()),'C1',label='Interpolated pdf',alpha=0.8,lw=3)
r = interpolated.random(size=1000)
ax.hist(r, density=True, alpha=0.4,align ='mid',color='grey')
ax.legend(loc='best', frameon=False)
plt.show()

======== ===========================================
Support :math:`x \in [x\_points[0], x\_points[-1]]`
======== ===========================================
Expand Down