Solar wind in situ data suitable for machine learning (python numpy arrays): STEREO-A/B, Wind, Parker Solar Probe, Ulysses, Venus Express, MESSENGER

Name: Solar wind in situ data suitable for machine learning (python numpy arrays): STEREO-A/B, Wind, Parker Solar Probe, Ulysses, Venus Express, MESSENGER
Creator: figshare
Published: 2020-08-25 18:48:17
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DataCite Commons2020-08-25 更新2024-07-28 收录

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https://figshare.com/articles/Solar_wind_in_situ_data_suitable_for_machine_learning_python_numpy_arrays_STEREO-A_B_Wind_Parker_Solar_Probe_Ulysses_Venus_Express_MESSENGER/12058065/1

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资源简介：

**work in progress** don't use yet! These are solar wind in situ data arrays in python pickle suitable for machine learning, i.e. the arrays consist only of numbers, no strings, no datetime objects. Made with https://github.com/cmoestl/heliocats Load in python with e.g.: > import pickle> filepsp='psp_2018_2019_numpy.p'> [psp,hpsp]=pickle.load(open(filepsp, "rb" ) ) plot time vs total field> import matplotlib.pyplot as plt> plt.plot(psp[:,0],psp[:,1]) Times psp[:,0 ]are in matplotlib format. Variable 'hpsp' contains a header with the variable names for each column.

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figshare

创建时间：

2020-04-01