Lstar and Lmax calculation using artificial neural network (ANN) technique.
This module requires the ffnet package.
Authors: Josef Koller, Yiqun Yu Institution: Los Alamos National Laboratory Contact: jkoller@lanl.gov, yiqun@lanl.gov
Copyright 2012 Los Alamos National Security, LLC.
LANLstar(inputdict, extMag) | Calculate Lstar |
LANLmax(inputdict, extMag) | Calculate last closed drift shell (Lmax) |
Calculate Lstar
Based on the L* artificial neural network (ANN) trained from different magnetospheric field models.
Parameters: | extMag : list of string(s)
inputdict : dictionary
|
---|---|
Returns: | out : dictionary
|
Examples
>>> import spacepy.LANLstar as LS
>>>
>>> inputdict = {}
>>> inputdict['Kp'] = [2.7 ] # Kp index
>>> inputdict['Dst'] = [7.7777 ] # Dst index (nT)
>>> inputdict['dens'] = [4.1011 ] # solar wind density (/cc)
>>> inputdict['velo'] = [400.1011 ] # solar wind velocity (km/s)
>>> inputdict['Pdyn'] = [4.1011 ] # solar wind dynamic pressure (nPa)
>>> inputdict['ByIMF'] = [3.7244 ] # GSM y component of IMF magnetic field (nT)
>>> inputdict['BzIMF'] = [-0.1266 ] # GSM z component of IMF magnetic field (nT)
>>> inputdict['G1'] = [1.029666 ] # as defined in Tsganenko 2003
>>> inputdict['G2'] = [0.549334 ]
>>> inputdict['G3'] = [0.813999 ]
>>> inputdict['W1'] = [0.122444 ] # as defined in Tsyganenko and Sitnov 2005
>>> inputdict['W2'] = [0.2514 ]
>>> inputdict['W3'] = [0.0892 ]
>>> inputdict['W4'] = [0.0478 ]
>>> inputdict['W5'] = [0.2258 ]
>>> inputdict['W6'] = [1.0461 ]
>>>
>>> inputdict['Year'] = [1996 ]
>>> inputdict['DOY'] = [6 ]
>>> inputdict['Hr'] = [1.2444 ]
>>>
>>> inputdict['Lm'] = [4.9360 ] # McIllwain L
>>> inputdict['Bmirr'] = [315.6202 ] # magnetic field strength at the mirror point
>>> inputdict['rGSM'] = [4.8341 ] # radial coordinate in GSM [Re]
>>> inputdict['lonGSM'] = [-40.2663 ] # longitude coodrinate in GSM [deg]
>>> inputdict['latGSM'] = [36.44696 ] # latitude coordiante in GSM [deg]
>>> inputdict['PA'] = [57.3874 ] # pitch angle [deg]
>>> inputdict['SMx'] = [3.9783 ]
>>> inputdict['SMy'] = [-2.51335 ]
>>> inputdict['SMz'] = [1.106617 ]
>>>
>>> LS.LANLstar(inputdict, ['OPDYN','OPQUIET','T01QUIET','T01STORM','T89','T96','T05','RAMSCB'])
{'OPDYN': array([4.7171]),
'OPQUIET': array([4.6673]),
'T01QUIET': array([4.8427]),
'T01STORM': array([4.8669]),
'T89': array([4.5187]),
'T96': array([4.6439]),
'TS05': array([4.7174]),
'RAMSCB','array([5.9609])}
Calculate last closed drift shell (Lmax)
Based on the L* artificial neural network (ANN) trained from different magnetospheric field models.
Parameters: | extMag : list of string(s)
inputdict : dictionary
|
---|---|
Returns: | out : dictionary
|
Examples
>>> import spacepy.LANLstar as LS
>>>
>>> inputdict = {}
>>> inputdict['Kp'] = [2.7 ] # Kp index
>>> inputdict['Dst'] = [7.7777 ] # Dst index (nT)
>>> inputdict['dens'] = [4.1011 ] # solar wind density (/cc)
>>> inputdict['velo'] = [400.1011 ] # solar wind velocity (km/s)
>>> inputdict['Pdyn'] = [4.1011 ] # solar wind dynamic pressure (nPa)
>>> inputdict['ByIMF'] = [3.7244 ] # GSM y component of IMF magnetic field (nT)
>>> inputdict['BzIMF'] = [-0.1266 ] # GSM z component of IMF magnetic field (nT)
>>> inputdict['G1'] = [1.029666 ] # as defined in Tsganenko 2003
>>> inputdict['G2'] = [0.549334 ]
>>> inputdict['G3'] = [0.813999 ]
>>> inputdict['W1'] = [0.122444 ] # as defined in Tsyganenko and Sitnov 2005
>>> inputdict['W2'] = [0.2514 ]
>>> inputdict['W3'] = [0.0892 ]
>>> inputdict['W4'] = [0.0478 ]
>>> inputdict['W5'] = [0.2258 ]
>>> inputdict['W6'] = [1.0461 ]
>>>
>>> inputdict['Year'] = [1996 ]
>>> inputdict['DOY'] = [6 ]
>>> inputdict['Hr'] = [1.2444 ]
>>>
>>> inputdict['PA'] = [57.3874 ] # pitch angle [deg]
>>>
>>> LS.LANLmax(inputdict, ['OPDYN','OPQUIET','T01QUIET','T01STORM','T89','T96','T05'])
{'OPDYN': array([10.6278]),
'OPQUIET': array([9.3352]),
'T01QUIET': array([10.0538]),
'T01STORM': array([9.9300]),
'T89': array([8.2888]),
'T96': array([9.2410]),
'T05': array([9.9295])}