Ring Current Proton Artifician Neural Network Model
Project description
RCPANN - Ring Current Proton ANN Model
The Ring Current Proton Artificial Neural Network (RCPANN) model specifies the ring current proton distribution using artificial neural network (multi-layer perceptron).
This model is based on RBSP/RBSPICE measurements from 2013-2018. The RBSPICE measures proton flux at 14 energy channels from 45 keV to 598 keV, and this model provides proton spin-averaged flux in those 14 energy channels. The data for the training and modeling are available at https://doi.org/10.5281/zenodo.7651736. The training program are available ar https://github.com/jinxingli87/RCPANN.
How to use the RCPANN model
First, pip install the 'rcpann' package. Tensorflow and Pytorch packages are required.
pip3 install rcpann
✨ Example 1: Predict proton flux at a specific moment
Input: iek, coord in shape of either (4,) or (1,4), and tstr in form of 'yyyy-mm-dd hh:mm:ss' The iek should be a number between 0 and 13, and the corresponding energy is listed below.
iek | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Energy (keV) | 45 | 55 | 67 | 82 | 99 | 121 | 148 | 181 | 220 | 269 | 328 | 400 | 489 | 598 |
from rcpann import *
iek=1
coord=np.array([3.5, 0.0, 1.0, 0.0]) # L=3.5, cos(theta)=0, sin(theta)=1.0, Lat=0.0, which means MLT = 6h
print(pflux(iek,coord,tstr = '2017-03-01 22:42:00'))
✨ Example 2. Model the global distribution of proton flux
from rcpann import *
iek=1
tstr1='2017-03-01 22:42:00'
tstr2='2017-03-04 23:59:00'
rcpann_global_dist(iek,tstr1,tstr2)
Please contact jinxing.li.87@gmail.com for support.
License
MIT
Free Software, Hell Yeah!
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