The Solar Cycle

This example shows the current and possible next solar cycle.

from __future__ import print_function, division

import datetime
import matplotlib.pyplot as plt

import sunpy.timeseries as ts

For this example we will use the SunPy sample data, if you want the current data, delete the argument to the create function. i.e. noaa = lc.NOAAIndicesLightCurve.create()

noaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')
noaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')

Next lets grab the data again to create a new data structure that we will shift by 12 years to simulate the next solar cycle. We will truncate the data to only plot what is necessary.

noaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices') =, freq=datetime.timedelta(days=365*12))
noaa2 = noaa2.truncate('2021/04/01', '2030/01/01')

Finally lets plot everything together with some arbitrary range for the strength of the next solar cycle.

plt.plot(,['sunspot RI'], label='Sunspot Number')
         color='grey', label='Near-term Prediction')
plt.fill_between(,['sunspot low'],
       ['sunspot high'], alpha=0.3, color='grey')

plt.fill_between(,['sunspot RI smooth']*0.4,
       ['sunspot RI smooth']*1.3, alpha=0.3, color='grey',
                 label='Next Cycle Predict')
plt.text('2011-01-01', 120, 'Cycle 24', fontsize=16)
plt.text('2024-01-01', 120, 'Cycle 25', fontsize=16)
plt.ylabel('Sunspot Number')
plt.legend(loc=2, framealpha=0.5)

Total running time of the script: ( 0 minutes 0.382 seconds)

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