keep#

Hist1d.keep(lower, upper, squeeze=False, setval=0.0)[source]#

Keep every entry of the histogram in-between lower and upper

Parameters:

lowerfloat: Keep all data where the left edges are greater or equal to lower.
upperfloat: Keep all data where the right edges are lesser or equal to upper.
squeezebool, default False: Controls if the resulting Hist1d has the same number of bins as the original histogram.
setvalfloat, default 0.0: If squeeze is False, fill removed data with setval.

Returns:

histHist1d

See also

remove

Examples

Create a histogram:

>>> hist = ap.Hist1d([1, 2, 3, 4, 5], [0, 1, 2, 3, 4, 5])

Only keep values within the interval [1, 4]:

>>> hist.keep(1, 4).values
[0. 2. 3. 4. 0.]

Fill removed values with a numpy.nan

>>> hist.keep(1, 4, setval=np.nan).values
[nan 2. 3. 4. nan]

Squeeze length to only include kept values:

>>> hist.keep(1, 4, squeeze=True).edges
[1. 2. 3.]
>>> hist.keep(1, 4, squeeze=True).values
[2. 3]

Example plot:

import matplotlib.pyplot as plt
import numpy as np

import atompy as ap

plt.style.use("atom")

# create some histogram
bin_centers = np.linspace(-2, 2, 45)
hist = ap.Hist1d.from_centers(ap.gauss(bin_centers), bin_centers)

# plot it
ax = plt.subplot()
hist.plot_step(ax, lw=3.0, label="original")
hist.keep(-1, 1).plot_step(ax, lw=1.5, label="original")
ax.legend()

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