rcpann 0.0.7

Ring Current Proton Artifician Neural Network Model

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 [e-mail] for support.

License

MIT

Free Software, Hell Yeah!