Thanks to visit codestin.com
Credit goes to github.com

Skip to content

[Doc] Revise histogram features example (Closes #26604) #26606

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 4 commits into from
Aug 26, 2023
Merged

[Doc] Revise histogram features example (Closes #26604) #26606

Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
fa87746
[Doc] Revise histogram features example (Addresses Issue #26604)
jsdodge Aug 26, 2023
e5e1504
Update histogram_features.py
jsdodge Aug 26, 2023
d9b4d5b
Fix trailing whitespace
jsdodge Aug 26, 2023
2819f55
Restore RNG seed to 19680801
jsdodge Aug 26, 2023
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
15 changes: 8 additions & 7 deletions galleries/examples/statistics/histogram_features.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,14 +20,14 @@
import matplotlib.pyplot as plt
import numpy as np

np.random.seed(19680801)
rng = np.random.default_rng(19680801)

# example data
mu = 100 # mean of distribution
sigma = 15 # standard deviation of distribution
x = mu + sigma * np.random.randn(437)
mu = 106 # mean of distribution
sigma = 17 # standard deviation of distribution
x = rng.normal(loc=mu, scale=sigma, size=420)

num_bins = 50
num_bins = 42

fig, ax = plt.subplots()

Expand All @@ -38,9 +38,10 @@
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_xlabel('Value')
ax.set_ylabel('Probability density')
ax.set_title(r'Histogram of IQ: $\mu=100$, $\sigma=15$')
ax.set_title('Histogram of normal distribution sample: '
fr'$\mu={mu:.0f}$, $\sigma={sigma:.0f}$')

# Tweak spacing to prevent clipping of ylabel
fig.tight_layout()
Expand Down