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solo-loader

Data loader for SolO/EPD EPT and HET level 2 (L2) and low latency (ll) data provided by CDF files from http://soar.esac.esa.int/soar.

Example 1 - low latency data

Example code that loads low latency (ll) electron and proton (+alphas) fluxes (and errors) for EPT NORTH telescope from Apr 15 2021 to Apr 16 2021 into two Pandas dataframes (one for protons & alphas, one for electrons). In general available are 'sun', 'asun', 'north', and 'south' viewing directions for 'ept' and 'het' telescopes of SolO/EPD.

from epd_loader import *

df_protons, df_electrons, energies = \
read_epd_cdf('ept', 'north', 'll', 20210415, 20210416, \
    path='/home/userxyz/uni/solo/data/low_latency/epd/LL02/')

# plot protons and alphas
ax = df_protons.plot(logy=True, subplots=True, figsize=(20,60))
plt.show()

# plot electrons
ax = df_electrons.plot(logy=True, subplots=True, figsize=(20,60))
plt.show()

Example 2 - level 2 data

Example code that loads level 2 (l2) electron and proton (+alphas) fluxes (and errors) for HET SUN telescope from Aug 20 2020 to Aug 20 2020 into two Pandas dataframes (one for protons & alphas, one for electrons).

from epd_loader import *

df_protons, df_electrons, energies = \
read_epd_cdf('het', 'sun', 'l2', 20200820, 20200821, \
    path='/home/userxyz/uni/solo/data/l2/epd/')

# plot protons and alphas
ax = df_protons.plot(logy=True, subplots=True, figsize=(20,60))
plt.show()

# plot electrons
ax = df_electrons.plot(logy=True, subplots=True, figsize=(20,60))
plt.show()

Data download within Python

Level 2 data can be downloaded from http://soar.esac.esa.int/soar using epd_l2_download(). Following example downloads EPT NORTH telescope data for Aug 20 2020 to the dir /home/userxyz/uni/solo/data/l2/epd/. Right now rudimentary working with one download (1 file/day) per call.

from epd_loader import *

epd_l2_download('ept', 'north', 20200820, '/home/userxyz/uni/solo/data/l2/epd/')

epd_ll_download() provides the same functionality for low latency data but doesn't work reliably at the moment.

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  • Python 100.0%