Plot#
Warning
This module is mainly intended for interactive usage, it is experimental and still in development. The API might change without warning and breaks code.
Utilities to plot PDFs and functions. These are simple helpers to plot models and their components, they are not meant to be a full-fledged plotting library but provide a quick way to visualize PDFs.
The plotting is based on matplotlib and integrates closely with it.
Quick Start#
The easiest way to plot a PDF is using the .plot attribute available on all PDFs:
# Plot a simple PDF
pdf.plot.plotpdf()
# Plot an extended PDF (scaled by yield)
pdf.plot.plotpdf(extended=True)
# Plot with custom styling
pdf.plot.plotpdf(linestyle='--', color='red', label='My PDF')
# For composite PDFs (like SumPDF), plot components
sumpdf.plot.comp.plotpdf()
Examples#
Basic plotting:
import zfit
import matplotlib.pyplot as plt
# Create a simple Gaussian
obs = zfit.Space("x", limits=(-5, 5))
gauss = zfit.pdf.Gauss(mu=0, sigma=1, obs=obs)
# Plot the PDF
gauss.plot.plotpdf()
plt.show()
Plotting extended PDFs with components:
# Create extended PDFs
gauss1 = zfit.pdf.Gauss(mu=-1, sigma=0.5, obs=obs).create_extended(100)
gauss2 = zfit.pdf.Gauss(mu=1, sigma=0.8, obs=obs).create_extended(150)
# Create a SumPDF (automatically extended)
sumpdf = zfit.pdf.SumPDF([gauss1, gauss2])
# Plot the sum and its components
sumpdf.plot.plotpdf(label='Sum')
sumpdf.plot.comp.plotpdf(linestyle='--')
plt.legend()
plt.show()
Custom plotting with data overlay:
# Generate and plot data
data = sumpdf.sample(1000)
plt.hist(data.value(), bins=50, density=True, alpha=0.5, label='Data')
# Overlay the PDF
sumpdf.plot.plotpdf(extended=False, label='PDF')
plt.legend()
plt.show()
Available Functions#
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Plot the 1 dimensional density of a model, possibly scaled by the yield if extended. |
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Plot the components of a sum pdf. |