norm_diff#

Hist1d.norm_diff(other)[source]#

Return the normalized difference between two histograms.

Calculates (self - other) / (self + other).

Parameters:

otherHist1d

The other histogram.

Both histograms must have matching edges.

Returns:

norm_diffHist1d: A new histgram of the normalized difference.

Examples

import matplotlib.pyplot as plt

import atompy as ap

plt.style.use("atom")

edges = (0, 1, 2, 3)
hist0 = ap.Hist1d((1, 2, 3), edges, title="H1")
hist1 = ap.Hist1d((10, 20, 30), edges, title="H2")

plt.rcParams["figure.constrained_layout.use"] = True
plt.rcParams["figure.figsize"] = 9.0, 5.0

histos = (
    hist0,
    hist1,
    hist0 - hist1,
    hist0.norm_diff(hist1),
    hist0.norm_to_sum() - hist1.norm_to_sum(),
)
locs = (231, 232, 234, 235, 236)

for hist, loc in zip(histos, locs):
    hist.plot_step(plt.subplot(loc), start_at="auto")

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