Map Histogram

How to inspect the histogram of the data of a map.

from __future__ import print_function, division

import numpy as np
import matplotlib.pyplot as plt

import astropy.units as u

from astropy.coordinates import SkyCoord
from import AIA_171_IMAGE

We first create the Map using the sample data and we will create a submap of a quiet region.

aia =
bl = SkyCoord(-400 * u.arcsec, 0 * u.arcsec, frame=aia.coordinate_frame)
tr = SkyCoord(0 * u.arcsec, 400 * u.arcsec, frame=aia.coordinate_frame)
aia_smap = aia.submap(bl, tr)

We now create a histogram of the data in this region.

dmin = aia_smap.min()
dmax = aia_smap.max()
num_bins = 50
hist, bins = np.histogram(, bins=np.linspace(dmin, dmax, num_bins))
width = 0.7 * (bins[1] - bins[0])
x = (bins[:-1] + bins[1:]) / 2

Let’s plot the histogram as well as some standard values such as mean upper, and lower value and the one-sigma range.

plt.figure(), hist, align='center', width=width, label='Histogram')
plt.axvline(dmin, label='Data min={:.2f}'.format(dmin), color='black')
plt.axvline(dmax, label='Data max={:.2f}'.format(dmax), color='black')
            label='mean={:.2f}'.format(, color='green')
one_sigma = np.array([ -,
plt.axvspan(one_sigma[0], one_sigma[1], alpha=0.3, color='green',
            label='mean +/- std = [{0:.2f}, {1:.2f}]'.format(
            one_sigma[0], one_sigma[1]))
plt.axvline(one_sigma[0], color='green')
plt.axvline(one_sigma[1], color='red')

Finally let’s overplot what the one-sigma range means on the map

fig = plt.figure()
levels = one_sigma / dmax * u.percent * 100
aia_smap.draw_contours(levels=levels, colors=['red', 'green'])

Total running time of the script: ( 0 minutes 0.966 seconds)

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