def Closed_Field(*args, **kwargs):
"""
Function to see if a field line is closed
Either MagEphem or pos and date must be specified
Parameters
----------
MagEphem : Lgm_MagEphemInfo, optional
If a populated Lgm_MagEphemInfo class is passed in the data is pulled
from it
pos : list, optional
3-element list of the position in system coord_system
date : datetime, optional
date and time of the calculation
height : float, optional
height above the earth to consider a particle lost [km], default=100
tol1 : float, optional
TODO what do I set? default=0.01
tol2 : float, optional
TODO what do I set? default=1e-7
bfield : str, optional
The magnetic field model to use, default=Lgm_B_T89
Kp : int, optional
Kp index for the calculation, default=2
coord_system : str
the coordinate system of the input position, default=GSM
extended_out : bool
switch on extended vs regular output, see examples for details,
default=False
Returns
-------
out : str
a string with the open of closed value for the input
- LGM_OPEN_IMF
- LGM_CLOSED
- LGM_OPEN_N_LOBE
- LGM_OPEN_S_LOBE
- LGM_INSIDE_EARTH
- LGM_TARGET_HEIGHT_UNREACHABLE
Examples
--------
>>> from lgmpy import Closed_Field
>>> import datetime
>>> Closed_Field([3,1,0], datetime.datetime(2000, 12, 3))
'LGM_CLOSED'
>>> Closed_Field([6,1,12], datetime.datetime(2000, 12, 3))
'LGM_OPEN_IMF'
>>> Closed_Field([-16,1,5], datetime.datetime(2000, 12, 3))
'LGM_OPEN_N_LOBE'
"""
defaults = {
'height': 100,
'tol1': 0.01,
'tol2': 1e-7,
'bfield': 'Lgm_B_T89',
'Kp': 2,
'coord_system': 'GSM',
'extended_out': False
}
#replace missing kwargs with defaults
for dkey in defaults:
if dkey not in kwargs:
kwargs[dkey] = defaults[dkey]
northern = Lgm_Vector.Lgm_Vector()
southern = Lgm_Vector.Lgm_Vector()
minB = Lgm_Vector.Lgm_Vector()
#check for call w/ Lgm_MagModelInfo
if len(args) == 1:
MagEphemInfo = args[0]
try:
mmi = MagEphemInfo.LstarInfo.contents.mInfo.contents
except AttributeError:
raise (RuntimeError('Incorrect arguments specified'))
dum = [MagEphemInfo.P.x, MagEphemInfo.P.y, MagEphemInfo.P.z]
position = Lgm_Vector.Lgm_Vector(*dum)
elif len(args) == 2:
# input checking
if kwargs['coord_system'] != 'GSM':
# raise(NotImplementedError('Different coord systems are not yet ready to use') )
pos = magcoords.coordTrans(args[0], args[1],
kwargs['coord_system'], 'GSM')
else:
pos = args[0]
# could consider a Lgm_MagModelInfo param to use an existing one
mmi = Lgm_MagModelInfo.Lgm_MagModelInfo()
mmi.Kp = kwargs['Kp']
try:
Bfield_dict[kwargs['bfield']](pointer(mmi))
except KeyError:
raise (NotImplementedError("Only Bfield=%s currently supported" %
Bfield_dict.keys()))
datelong = Lgm_CTrans.dateToDateLong(args[1])
utc = Lgm_CTrans.dateToFPHours(args[1])
Lgm_Set_Coord_Transforms(datelong, utc,
mmi.c) # dont need pointer as it is one
try:
position = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise (TypeError('position must be an iterable'))
else:
raise (RuntimeError('Incorrect number of arguments specified'))
ans = Lgm_Trace(pointer(position), pointer(southern), pointer(northern),
pointer(minB), kwargs['height'], kwargs['tol1'],
kwargs['tol2'], pointer(mmi))
L = numpy.nan #default to this is field not closed
if ans == LGM_OPEN_IMF:
retstr = 'LGM_OPEN_IMF'
elif ans == LGM_CLOSED:
retstr = 'LGM_CLOSED'
L = _simpleL(northern, mmi)
elif ans == LGM_OPEN_N_LOBE:
retstr = 'LGM_OPEN_N_LOBE'
elif ans == LGM_OPEN_S_LOBE:
retstr = 'LGM_OPEN_S_LOBE'
elif ans == LGM_INSIDE_EARTH:
retstr = 'LGM_INSIDE_EARTH'
elif ans == LGM_TARGET_HEIGHT_UNREACHABLE:
retstr = 'LGM_TARGET_HEIGHT_UNREACHABLE'
elif ans == LGM_BAD_TRACE:
retstr = 'LGM_BAD_TRACE'
if kwargs['extended_out']:
return retstr, northern.tolist(), southern.tolist(), minB.tolist(), L
else:
return retstr
def get_Lstar(pos, date, alpha = 90.,
Kp = 2, coord_system='GSM',
Bfield = 'Lgm_B_OP77',
LstarThresh = 10.0, # beyond this Lsimple don't compute Lstar
extended_out = False,
LstarQuality = 3):
"""
This method does all the work for the calculation of Lstar.
There are many options to set and a lot of output. We have tried to describe
it well here but certainly have missed something, if you can't understand something
please contact the authors.
Parameters
==========
pos : list or array
The position that Lstar should be calculated for
date : datetime
The date and time that Lstar should be calculated for
alpha : float, optional
Local pitch angle at ``pos`` to calculate Lstar, default (90)
Kp : int, optional
The Kp index to pass to the magnetic field model, used in T89, ignored
in OP77, default (2)
coord_system : str, optional
The coordinate system of the input position, default (GSM)
Bfield : str, optional
The Magnetic field model to use for the calculation, default (Lgm_B_T89)
LstarThresh : float, optional
The calculation computes a simple L value and does not calculation Lstar
if simple L is beyond this, default (10)
extended_out : bool, optional
Keyword that enables the output of significantly more information into
the Lstar_Data output, default (False). The extra information allows
the points along the Lstar trace to be used since Lstar is the same at
each point along the trace.
LstarQuality : int
The quality flag for the integrators in the calculation, this can have
serious impact on run speed and Lstar value
Returns
=======
out : Lstar_Data
Returns a datamodel object that contains all the information for the run.
See examples for the contents of this object for extended_out=False and True
Examples
========
>>> from lgmpy import Lstar
>>> import datetime
>>> dat = Lstar.get_Lstar([1,2,0], datetime.datetime(2000, 1, 2), extended_out=False)
>>> print(dat)
+
|____90.0 (spacepy.datamodel.SpaceData [8])
|____Bmin (spacepy.datamodel.dmarray ())
:|____units (str [2])
|____Bmirror (spacepy.datamodel.dmarray ())
:|____coord_system (str [3])
:|____units (str [2])
|____I (spacepy.datamodel.dmarray ())
|____LHilton (float)
|____LMcIlwain (float)
|____Lsimple (spacepy.datamodel.dmarray (1,))
|____Lstar (spacepy.datamodel.dmarray (1,))
:|____info (str [4])
|____Pmin (spacepy.datamodel.dmarray (3,))
:|____coord_system (str [3])
:|____units (str [3])
|____Bcalc (spacepy.datamodel.dmarray (3,))
:|____Kp (int)
:|____coord_system (str [3])
:|____model (str [10])
:|____units (str [2])
|____Epoch (spacepy.datamodel.dmarray (1,))
|____Kp (spacepy.datamodel.dmarray (1,))
|____MLT (spacepy.datamodel.dmarray ())
:|____coord_system (str [5])
|____position (dict [1])
|____GSM (spacepy.datamodel.dmarray (3,))
:|____units (str [2])
...
The data object is a dictionary with keys:
- 90.0 : this is the pitch angle specified (multiple can be specified)
- Bmin : the minimum B for that pitch angle and position
- BMirror : the position of the mirror point for that position
- I : the I value for that position
- LHilton : L value calculated with the Hilton approximation
- LMcIlwain: L values calculated with the McIlwain formula
- Lsimple : a simple L value
- Lstar : the value of Lstar for that position and pitch angle
- Pmin : TODO what is Pmin?
- Bcalc : information about the magnetic field model
- Epoch : the time of the calculation
- Kp : Kp used for the calculation
- MLT : MLT value for the position and coord_system
- position : the position of the calculation
- GSM : the value in this system, if conversions are done they all appear here
>>> from lgmpy import Lstar
>>> import datetime
>>> dat = Lstar.get_Lstar([1,2,0], datetime.datetime(2000, 1, 2), extended_out=True)
>>> print(dat)
+
|____90.0 (spacepy.datamodel.SpaceData [21])
:|____Calc_Time (float)
|____Bmag (numpy.ndarray (100, 1000))
|____Bmin (spacepy.datamodel.dmarray ())
:|____units (str [2])
|____Bmirror (spacepy.datamodel.dmarray ())
:|____coord_system (str [3])
:|____units (str [2])
|____I (spacepy.datamodel.dmarray ())
|____LHilton (float)
|____LMcIlwain (float)
|____Lsimple (spacepy.datamodel.dmarray (1,))
|____Lstar (spacepy.datamodel.dmarray (1,))
:|____info (str [4])
|____Pmin (spacepy.datamodel.dmarray (3,))
:|____coord_system (str [3])
:|____units (str [3])
|____ShellEllipsoidFootprint_Pn (numpy.ndarray (100,))
|____ShellEllipsoidFootprint_Ps (numpy.ndarray (100,))
|____ShellI (spacepy.datamodel.dmarray (100,))
|____ShellMirror_Pn (numpy.ndarray (100,))
|____ShellMirror_Ps (numpy.ndarray (100,))
|____ShellMirror_Sn (float)
|____ShellMirror_Ss (float)
|____nFieldPnts (numpy.ndarray (100,))
|____s_gsm (numpy.ndarray (100, 1000))
|____x_gsm (numpy.ndarray (100, 1000))
|____y_gsm (numpy.ndarray (100, 1000))
|____z_gsm (numpy.ndarray (100, 1000))
|____Bcalc (spacepy.datamodel.dmarray (3,))
:|____Kp (int)
:|____coord_system (str [3])
:|____model (str [10])
:|____units (str [2])
|____Epoch (spacepy.datamodel.dmarray (1,))
|____Kp (spacepy.datamodel.dmarray (1,))
|____MLT (spacepy.datamodel.dmarray ())
:|____coord_system (str [5])
|____position (dict [1])
|____GSM (spacepy.datamodel.dmarray (3,))
:|____units (str [2])
...
The data object is a dictionary with keys:
- 90.0 : this is the pitch angle specified (multiple can be specified)
- Calc_Time : the clock time that the calculation took to run
- Bmag : the magnitude of B along the Lstar trace
- Bmin : the minimum B for that pitch angle and position
- BMirror : the position of the mirror point for that position
- I : the I value for that position
- LHilton : L value calculated with the Hilton approximation
- LMcIlwain: L values calculated with the McIlwain formula
- Lsimple : a simple L value
- Lstar : the value of Lstar for that position and pitch angle
- Pmin : TODO what am I?
- ShellEllipsoidFootprint_Pn : TODO what am I?
- ShellEllipsoidFootprint_Ps : TODO what am I?
- ShellI : TODO what am I?
- ShellMirror_Pn : TODO what am I?
- ShellMirror_Ps : TODO what am I?
- ShellMirror_Sn : TODO what am I?
- ShellMirror_Ss : TODO what am I?
- nFieldPnts : TODO what am I?
- s_gsm : TODO what am I?
- x_gsm : TODO what am I?
- y_gsm : TODO what am I?
- z_gsm : TODO what am I?
- Bcalc : information about the magnetic field model
- Epoch : the time of the calculation
- Kp : Kp used for the calculation
- MLT : MLT value for the position and coord_system
- position : the position of the calculation
- GSM : the value in this system, if conversions are done they all appear here
"""
# setup a datamodel object to hold the answer
ans = Lstar_Data()
# change datetime to Lgm Datelong and UTC
try:
datelong = Lgm_CTrans.dateToDateLong(date)
utc = Lgm_CTrans.dateToFPHours(date)
except AttributeError:
raise(TypeError("Date must be a datetime object"))
else:
ans['Epoch'] = datamodel.dmarray([date])
# pitch angles to calculate
try:
Alpha = list(alpha)
except TypeError:
Alpha = [alpha]
# required setup
MagEphemInfo = Lgm_MagEphemInfo.Lgm_MagEphemInfo(len(Alpha), 0)
# setup a shortcut to MagModelInfo
mmi = MagEphemInfo.LstarInfo.contents.mInfo.contents
Lgm_Set_Coord_Transforms( datelong, utc, mmi.c) # dont need pointer as it is one
# convert to **GSM**
if coord_system == 'GSM':
try:
Pgsm = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise(TypeError("Position must be listlike" ) )
ans['position']['GSM'] = datamodel.dmarray(pos, attrs={'units':'Re'})
elif coord_system == 'SM':
try:
Psm = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise(TypeError("Position must be listlike" ) )
Pgsm = Lgm_Vector.Lgm_Vector()
Lgm_Convert_Coords( pointer(Psm), pointer(Pgsm), SM_TO_GSM, mmi.c )
ans['position']['SM'] = datamodel.dmarray(pos, attrs={'units':'Re'})
ans['position']['GSM'] = datamodel.dmarray(Pgsm.tolist(), attrs={'units':'Re'})
else:
raise(NotImplementedError("Only GSM or SM input currently supported"))
Pwgs = Lgm_Vector.Lgm_Vector()
Pmlt = Lgm_Vector.Lgm_Vector()
Lgm_Convert_Coords( pointer(Pgsm), pointer(Pwgs), GSM_TO_WGS84, mmi.c )
Lgm_Convert_Coords( pointer(Pwgs), pointer(Pmlt), WGS84_TO_EDMAG, mmi.c )
R, MLat, MLon, MLT = c_double(), c_double(), c_double(), c_double(),
Lgm_EDMAG_to_R_MLAT_MLON_MLT( pointer(Pmlt), pointer(R), pointer(MLat), pointer(MLon),
pointer(MLT), mmi.c)
ans['MLT'] = datamodel.dmarray(MLT.value, attrs={'coord_system': 'EDMAG'})
# save Kp
# TODO maybe add some Kp checking
ans['Kp'] = datamodel.dmarray([Kp])
# Set the LstarQuality, TODO add a comment here on what each does
MagEphemInfo.LstarQuality = LstarQuality
# L* in one place is L* in lots of places (for GPS set to False)
MagEphemInfo.SaveShellLines = extended_out
# TODO maybe not hardcoded, but for now its fine
MagEphemInfo.LstarInfo.contents.VerbosityLevel = 0
MagEphemInfo.LstarInfo.contents.mInfo.contents.VerbosityLevel = 0
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_T89;
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_cdip;
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_OP77;
#MagEphemInfo->LstarInfo->mInfo->InternalModel = LGM_CDIP;
## decide which field model to use, this is a keyword
try:
Bfield_dict[Bfield](MagEphemInfo.LstarInfo.contents.mInfo)
except KeyError:
raise(NotImplementedError("Only Bfield=%s currently supported" % Bfield_dict.keys()))
# Save Date, UTC to MagEphemInfo structure ** is this needed?
MagEphemInfo.Date = datelong
MagEphemInfo.UTC = utc
MagEphemInfo.LstarInfo.contents.mInfo.contents.Kp = Kp
# Save nAlpha, and Alpha array to MagEphemInfo structure
MagEphemInfo.nAlpha = len(Alpha)
for i in range(len(Alpha)):
MagEphemInfo.Alpha[i] = Alpha[i]
# Set Tolerances
Lgm_SetLstarTolerances(LstarQuality, 24, MagEphemInfo.LstarInfo )
# * Blocal at sat location
MagEphemInfo.P = Pgsm
Bvec = Lgm_Vector.Lgm_Vector()
# Get B at the point in question
MagEphemInfo.LstarInfo.contents.mInfo.contents.Bfield(pointer(Pgsm), pointer(Bvec),
MagEphemInfo.LstarInfo.contents.mInfo)
ans['Bcalc'] = datamodel.dmarray(Bvec.tolist(), attrs={'units':'nT'})
ans['Bcalc'].attrs['model'] = Bfield
ans['Bcalc'].attrs['Kp'] = Kp
ans['Bcalc'].attrs['coord_system'] = 'GSM'
# save its magnitude in the structure
MagEphemInfo.B = Bvec.magnitude()
# check and see if the field line is closed before doing much work
trace, northern, southern, minB, Lsimple = Closed_Field.Closed_Field(MagEphemInfo, extended_out=True)
# presetup the ans[Angle] so that it can be filled correctly
for pa in Alpha:
ans[pa] = datamodel.SpaceData()
ans[pa]['Lsimple'] = datamodel.dmarray([Lsimple])
#sets up nans in case of Lstar failure
ans[pa]['I'] = datamodel.dmarray([numpy.nan])
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':trace})
ans[pa]['LMcIlwain'] = datamodel.dmarray([numpy.nan])
ans[pa]['LHilton'] = datamodel.dmarray([numpy.nan])
ans[pa]['Bmin'] = datamodel.dmarray([numpy.nan], attrs={'units':'nT'})
ans[pa]['Bmirror'] = datamodel.dmarray([numpy.nan], attrs={'units':'nT'})
if trace != 'LGM_CLOSED':
return ans
# if this is not LGM_CLOSED then don't both with any pitch angle? true?
# Save field-related quantities for each Pitch Angle.
MagEphemInfo.Pmin = Lgm_Vector.Lgm_Vector(*minB)
MagEphemInfo.Bmin = MagEphemInfo.LstarInfo.contents.mInfo.contents.Bmin
ans[pa]['Pmin'] = datamodel.dmarray(minB, attrs={'units':'R_E'})
ans[pa]['Pmin'].attrs['coord_system'] = 'GSM'
ans[pa]['Bmin'] = datamodel.dmarray(MagEphemInfo.Bmin, attrs={'units':'nT'})
# LOOP OVER PITCH ANGLES
for i, pa in enumerate(Alpha):
tnow = datetime.datetime.now()
PreStr = MagEphemInfo.LstarInfo.contents.PreStr
PostStr = MagEphemInfo.LstarInfo.contents.PostStr
# ***********************************************
# *** not sure I fully understand this chunk, B at the mirror point*****
# Set Pitch Angle, sin, sin^2, and Bmirror
sa = math.sin( pa*RadPerDeg )
sa2 = sa*sa
# print("{0}Computing L* for Pitch Angle: Alpha[{1}] = {2} Date: {3} UTC: {4} Lsimple = {5:4.3}{6}\n").format(PreStr, i, MagEphemInfo.Alpha[i], date, utc, Lsimple, PostStr )
if sa2!=0: #non-zero pitch angle
MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm = MagEphemInfo.B/sa2
else:
continue
ans[pa]['Bmirror'] = datamodel.dmarray(MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm, attrs={'units':'nT'})
ans[pa]['Bmirror'].attrs['coord_system'] = 'GSM'
# ***********************************************
# I tink this is already done
# Lgm_Set_Coord_Transforms( Date, UTC, MagEphemInfo.LstarInfo.contents.mInfo.contents.c )
MagEphemInfo.LstarInfo.contents.PitchAngle = pa
MagEphemInfo.Bm[i] = MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm
# Compute L*
if Lsimple < LstarThresh:
Ls_vec = Lgm_Vector.Lgm_Vector(*minB)
LS_Flag = Lgm_Lstar( pointer(Ls_vec), MagEphemInfo.LstarInfo)
lstarinf = MagEphemInfo.LstarInfo.contents #shortcut
MagEphemInfo.LHilton.contents.value = LFromIBmM_Hilton(c_double(lstarinf.I[0]),
c_double(MagEphemInfo.Bm[i]),
c_double(lstarinf.mInfo.contents.c.contents.M_cd))
ans[pa]['LHilton'] = MagEphemInfo.LHilton.contents.value
MagEphemInfo.LMcIlwain.contents.value = LFromIBmM_McIlwain(c_double(lstarinf.I[0]),
c_double(MagEphemInfo.Bm[i]),
c_double(lstarinf.mInfo.contents.c.contents.M_cd))
ans[pa]['LMcIlwain'] = MagEphemInfo.LMcIlwain.contents.value
if LS_Flag == -2: # mirror below southern hemisphere mirror alt
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':'S_LOSS'})
elif LS_Flag == -1: # mirror below northern hemisphere mirror alt
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':'N_LOSS'})
elif LS_Flag >= 0: # valid calc
ans[pa]['Lstar'] = datamodel.dmarray([lstarinf.LS], attrs={'info':'GOOD'}) # want better word?
MagEphemInfo.Lstar[i] = lstarinf.LS
# Save results to the MagEphemInfo structure.
MagEphemInfo.nShellPoints[i] = lstarinf.nPnts
## pull all this good extra info into numpy arrays
ans[pa]['I'] = datamodel.dmarray(lstarinf.I[0])
if extended_out:
ans[pa]['ShellI'] = \
datamodel.dmarray(numpy.ctypeslib.ndarray([len(lstarinf.I)],
dtype=c_double, buffer=lstarinf.I) ).copy()
ans[pa]['ShellEllipsoidFootprint_Pn'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Ellipsoid_Footprint_Pn),
dtype=c_double,
buffer=lstarinf.Ellipsoid_Footprint_Pn).copy()
ans[pa]['ShellEllipsoidFootprint_Ps'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Ellipsoid_Footprint_Ps),
dtype=c_double,
buffer=lstarinf.Ellipsoid_Footprint_Ps).copy()
ans[pa]['ShellMirror_Pn'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Mirror_Pn),
dtype=c_double,
buffer=lstarinf.Mirror_Pn).copy()
ans[pa]['ShellMirror_Ps'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Mirror_Ps),
dtype=c_double,
buffer=lstarinf.Mirror_Ps).copy()
ans[pa]['ShellMirror_Ss'] = lstarinf.mInfo.contents.Sm_South
ans[pa]['ShellMirror_Sn'] = lstarinf.mInfo.contents.Sm_North
ans[pa]['nFieldPnts'] = \
numpy.ctypeslib.ndarray(len(lstarinf.nFieldPnts),
dtype=c_int,
buffer=lstarinf.nFieldPnts).copy()
ans[pa]['s_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.s_gsm),
len(lstarinf.s_gsm[0])],
dtype=c_double,
buffer=lstarinf.s_gsm).copy()
ans[pa]['Bmag'] = \
numpy.ctypeslib.ndarray([len(lstarinf.Bmag),
len(lstarinf.Bmag[0])],
dtype=c_double,
buffer=lstarinf.Bmag).copy()
ans[pa]['x_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.x_gsm),
len(lstarinf.x_gsm[0])],
dtype=c_double,
buffer=lstarinf.x_gsm).copy()
ans[pa]['y_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.y_gsm),
len(lstarinf.y_gsm[0])],
dtype=c_double,
buffer=lstarinf.y_gsm).copy()
ans[pa]['z_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.z_gsm),
len(lstarinf.z_gsm[0])],
dtype=c_double,
buffer=lstarinf.z_gsm).copy()
delT = datetime.datetime.now() - tnow
ans[pa].attrs['Calc_Time'] = delT.seconds + delT.microseconds/1e6
Lgm_FreeMagEphemInfo_Children(pointer(MagEphemInfo))
return ans
def Lvalue(*args, **kwargs):
'''
Function to return the L-value of a position using either McIlwain or Hilton
approximation
Parameters
==========
pos : list
3-element position int he specified coord_system
time : datetime
date and time for the calculation
alpha : float, optional
the pitch angle for the L calculation, default=90
Bfield : str, optional
the magnetic field model to use, default=Lgm_B_T89
method : str, optional
the L-value formula to use, McIlwain or Hilton, default=Hilton
Kp : int
Kp index value for the calculation
coord_system : str
the input coordinate system, default=GSM
extended_out : bool
keyword specifying short or extended output, default=False
Returns
=======
out : dict
dictionary of the values, see examples for documentation of dictionary
Examples
========
>>> from lgmpy import magcoords
>>> import datetime
>>> magcoords.Lvalue([3, 0, 1], datetime.datetime(2000, 1, 1), extended_out=False)
{'I': 0.2434969602..., 'L': 3.195481841...}
The ``extended_out=False`` output is:
- I : I value at the given point
- L : L value at the given point
>>> from lgmpy import magcoords
>>> import datetime
>>> magcoords.Lvalue([3, 0, 1], datetime.datetime(2000, 1, 1), extended_out=True)
{'Blocal': 1024.1142193703838,
'Bmin': 921.8869150...,
'Bmirr': 1024.1142193...,
'I': 0.24349696021...,
'L': 3.1954818410...,
'M': 30119.614287...}
The ``extended_out=True`` output is:
- I : I value at the given point
- L : L value at the given point
- Bmin : minimum B at the input position (nT)
- Bmirror : mirror B at the input position (nT)
- M : TODO what exactly and I, magnetic moment?
'''
defaults = {'alpha': 90.,
'Bfield': 'Lgm_B_T89',
'method': 'Hilton',
'Kp': 2,
'coord_system': 'GSM',
'extended_out': False}
#replace missing kwargs with defaults
for dkey in defaults:
if dkey not in kwargs:
kwargs[dkey] = defaults[dkey]
method_dict = {'Hilton': 1, 'McIlwain': 0}
# change datetime to Lgm Datelong and UTC
mInfo = Lgm_MagModelInfo.Lgm_MagModelInfo()
mInfo.Kp = kwargs['Kp']
try:
Bfield_dict[kwargs['Bfield']](pointer(mInfo))
except KeyError:
raise(NotImplementedError("Only Bfield=%s currently supported" % Bfield_dict.keys()))
try:
datelong = Lgm_CTrans.dateToDateLong(args[1])
utc = Lgm_CTrans.dateToFPHours(args[1])
Lgm_Set_Coord_Transforms( datelong, utc, mInfo.c) # dont need pointer as it is one
except AttributeError:
raise(TypeError("Date must be a datetime object"))
#else:
#ans['Epoch'] = datamodel.dmarray([args[1]])
if kwargs['coord_system'] != 'GSM':
in_sys = kwargs['coord_system']
Pout = coordTrans(args[0], args[1], in_sys, 'GSM', de_eph=False)
Pgsm = Lgm_Vector.Lgm_Vector(*Pout)
else:
Pgsm = Lgm_Vector.Lgm_Vector(*args[0])
Iout = c_double()
Bm = c_double()
M = c_double()
ans = Lgm_McIlwain_L(datelong, utc, pointer(Pgsm), kwargs['alpha'],
method_dict[kwargs['method']],
pointer(Iout), pointer(Bm), pointer(M),
pointer(mInfo))
#TODO: decide on format for output -- perhaps use datamodel and have method as attribute?
#maybe only return I for extended_out flag=True
if kwargs['extended_out']:
sunPos_GSM = coordTrans(mInfo.c.contents.Sun, args[1], 'MOD', kwargs['coord_system'])
SunMlon = np.rad2deg(np.arctan2( sunPos_GSM[1], sunPos_GSM[0]))
SunMlon += 180.0 # flip to midnight
MLON = np.rad2deg(np.arctan2( Pgsm.y, Pgsm.x))
if (MLON < 0.0):
MLON += 360.0
MLT = np.mod( (MLON-SunMlon)/15.0+24.0, 24.0 )
return {'L': ans, 'I': Iout.value, 'Bmin': mInfo.Bmin, 'Blocal': mInfo.Blocal,
'Bmirr': mInfo.Bm, 'M': M.value, 'MLon':MLON, 'MLT':MLT}
else:
return {'L': ans, 'I': Iout.value}
def Closed_Field(*args, **kwargs):
"""
Function to see if a field line is closed
Either MagEphem or pos and date must be specified
Parameters
----------
MagEphem : Lgm_MagEphemInfo, optional
If a populated Lgm_MagEphemInfo class is passed in the data is pulled
from it
pos : list, optional
3-element list of the position in system coord_system
date : datetime, optional
date and time of the calculation
height : float, optional
height above the earth to consider a particle lost [km], default=100
tol1 : float, optional
TODO what do I set? default=0.01
tol2 : float, optional
TODO what do I set? default=1e-7
bfield : str, optional
The magnetic field model to use, default=Lgm_B_T89
Kp : int, optional
Kp index for the calculation, default=2
coord_system : str
the coordinate system of the input position, default=GSM
extended_out : bool
switch on extended vs regular output, see examples for details,
default=False
Returns
-------
out : str
a string with the open of closed value for the input
- LGM_OPEN_IMF
- LGM_CLOSED
- LGM_OPEN_N_LOBE
- LGM_OPEN_S_LOBE
- LGM_INSIDE_EARTH
- LGM_TARGET_HEIGHT_UNREACHABLE
Examples
--------
>>> from lgmpy import Closed_Field
>>> import datetime
>>> Closed_Field([3,1,0], datetime.datetime(2000, 12, 3))
'LGM_CLOSED'
>>> Closed_Field([6,1,12], datetime.datetime(2000, 12, 3))
'LGM_OPEN_IMF'
>>> Closed_Field([-16,1,5], datetime.datetime(2000, 12, 3))
'LGM_OPEN_N_LOBE'
"""
defaults = {'height': 100,
'tol1': 0.01,
'tol2': 1e-7,
'bfield': 'Lgm_B_T89',
'Kp': 2,
'coord_system': 'GSM',
'extended_out': False}
#replace missing kwargs with defaults
for dkey in defaults:
if dkey not in kwargs:
kwargs[dkey] = defaults[dkey]
northern = Lgm_Vector.Lgm_Vector()
southern = Lgm_Vector.Lgm_Vector()
minB = Lgm_Vector.Lgm_Vector()
#check for call w/ Lgm_MagModelInfo
if len(args) == 1:
MagEphemInfo = args[0]
try:
mmi = MagEphemInfo.LstarInfo.contents.mInfo.contents
except AttributeError:
raise(RuntimeError('Incorrect arguments specified'))
dum = [MagEphemInfo.P.x, MagEphemInfo.P.y, MagEphemInfo.P.z]
position = Lgm_Vector.Lgm_Vector(*dum)
elif len(args) == 2:
# input checking
if kwargs['coord_system'] != 'GSM':
# raise(NotImplementedError('Different coord systems are not yet ready to use') )
pos = magcoords.coordTrans(args[0], args[1], kwargs['coord_system'],'GSM')
else:
pos = args[0]
# could consider a Lgm_MagModelInfo param to use an existing one
mmi = Lgm_MagModelInfo.Lgm_MagModelInfo()
mmi.Kp = kwargs['Kp']
try:
Bfield_dict[kwargs['bfield']](pointer(mmi))
except KeyError:
raise(NotImplementedError("Only Bfield=%s currently supported" % Bfield_dict.keys()))
datelong = Lgm_CTrans.dateToDateLong(args[1])
utc = Lgm_CTrans.dateToFPHours(args[1])
Lgm_Set_Coord_Transforms( datelong, utc, mmi.c) # dont need pointer as it is one
try:
position = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise(TypeError('position must be an iterable') )
else:
raise(RuntimeError('Incorrect number of arguments specified'))
ans = Lgm_Trace(pointer(position),
pointer(southern),
pointer(northern),
pointer(minB), kwargs['height'], kwargs['tol1'], kwargs['tol2'], pointer(mmi) )
L = numpy.nan #default to this is field not closed
if ans == LGM_OPEN_IMF:
retstr = 'LGM_OPEN_IMF'
elif ans == LGM_CLOSED:
retstr = 'LGM_CLOSED'
L = _simpleL(northern, mmi)
elif ans == LGM_OPEN_N_LOBE:
retstr = 'LGM_OPEN_N_LOBE'
elif ans == LGM_OPEN_S_LOBE:
retstr = 'LGM_OPEN_S_LOBE'
elif ans == LGM_INSIDE_EARTH:
retstr = 'LGM_INSIDE_EARTH'
elif ans == LGM_TARGET_HEIGHT_UNREACHABLE:
retstr = 'LGM_TARGET_HEIGHT_UNREACHABLE'
elif ans == LGM_BAD_TRACE:
retstr = 'LGM_BAD_TRACE'
if kwargs['extended_out']:
return retstr, northern.tolist(), southern.tolist(), minB.tolist(), L
else:
return retstr
def Lvalue(*args, **kwargs):
'''
Function to return the L-value of a position using either McIlwain or Hilton
approximation
Parameters
==========
pos : list
3-element position int he specified coord_system
time : datetime
date and time for the calculation
alpha : float, optional
the pitch angle for the L calculation, default=90
Bfield : str, optional
the magnetic field model to use, default=Lgm_B_T89
method : str, optional
the L-value formula to use, McIlwain or Hilton, default=Hilton
Kp : int
Kp index value for the calculation
coord_system : str
the input coordinate system, default=GSM
extended_out : bool
keyword specifying short or extended output, default=False
Returns
=======
out : dict
dictionary of the values, see examples for documentation of dictionary
Examples
========
>>> from lgmpy import magcoords
>>> import datetime
>>> magcoords.Lvalue([3, 0, 1], datetime.datetime(2000, 1, 1), extended_out=False)
{'I': 0.2434969602..., 'L': 3.195481841...}
The ``extended_out=False`` output is:
- I : I value at the given point
- L : L value at the given point
>>> from lgmpy import magcoords
>>> import datetime
>>> magcoords.Lvalue([3, 0, 1], datetime.datetime(2000, 1, 1), extended_out=True)
{'Blocal': 1024.1142193703838,
'Bmin': 921.8869150...,
'Bmirr': 1024.1142193...,
'I': 0.24349696021...,
'L': 3.1954818410...,
'M': 30119.614287...}
The ``extended_out=True`` output is:
- I : I value at the given point
- L : L value at the given point
- Bmin : minimum B at the input position (nT)
- Bmirror : mirror B at the input position (nT)
- M : TODO what exactly and I, magnetic moment?
'''
defaults = {
'alpha': 90.,
'Bfield': 'Lgm_B_T89',
'method': 'Hilton',
'Kp': 2,
'coord_system': 'GSM',
'extended_out': False
}
#replace missing kwargs with defaults
for dkey in defaults:
if dkey not in kwargs:
kwargs[dkey] = defaults[dkey]
method_dict = {'Hilton': 1, 'McIlwain': 0}
# change datetime to Lgm Datelong and UTC
mInfo = Lgm_MagModelInfo.Lgm_MagModelInfo()
mInfo.Kp = kwargs['Kp']
try:
Bfield_dict[kwargs['Bfield']](pointer(mInfo))
except KeyError:
raise (NotImplementedError("Only Bfield=%s currently supported" %
Bfield_dict.keys()))
try:
datelong = Lgm_CTrans.dateToDateLong(args[1])
utc = Lgm_CTrans.dateToFPHours(args[1])
Lgm_Set_Coord_Transforms(datelong, utc,
mInfo.c) # dont need pointer as it is one
except AttributeError:
raise (TypeError("Date must be a datetime object"))
#else:
#ans['Epoch'] = datamodel.dmarray([args[1]])
if kwargs['coord_system'] != 'GSM':
in_sys = kwargs['coord_system']
Pout = coordTrans(args[0], args[1], in_sys, 'GSM', de_eph=False)
Pgsm = Lgm_Vector.Lgm_Vector(*Pout)
else:
Pgsm = Lgm_Vector.Lgm_Vector(*args[0])
Iout = c_double()
Bm = c_double()
M = c_double()
ans = Lgm_McIlwain_L(datelong, utc, pointer(Pgsm), kwargs['alpha'],
method_dict[kwargs['method']], pointer(Iout),
pointer(Bm), pointer(M), pointer(mInfo))
#TODO: decide on format for output -- perhaps use datamodel and have method as attribute?
#maybe only return I for extended_out flag=True
if kwargs['extended_out']:
sunPos_GSM = coordTrans(mInfo.c.contents.Sun, args[1], 'MOD',
kwargs['coord_system'])
SunMlon = np.rad2deg(np.arctan2(sunPos_GSM[1], sunPos_GSM[0]))
SunMlon += 180.0 # flip to midnight
MLON = np.rad2deg(np.arctan2(Pgsm.y, Pgsm.x))
if (MLON < 0.0):
MLON += 360.0
MLT = np.mod((MLON - SunMlon) / 15.0 + 24.0, 24.0)
return {
'L': ans,
'I': Iout.value,
'Bmin': mInfo.Bmin,
'Blocal': mInfo.Blocal,
'Bmirr': mInfo.Bm,
'M': M.value,
'MLon': MLON,
'MLT': MLT
}
else:
return {'L': ans, 'I': Iout.value}
def get_Lstar(pos, date, alpha = 90.,
Kp = 2, coord_system='GSM',
Bfield = 'Lgm_B_OP77',
LstarThresh = 10.0, # beyond this Lsimple don't compute Lstar
extended_out = False,
LstarQuality = 3):
"""
This method does all the work for the calculation of Lstar.
There are many options to set and a lot of output. We have tried to describe
it well here but certainly have missed something, if you can't understand something
please contact the authors.
Parameters
==========
pos : list or array
The position that Lstar should be calculated for
date : datetime
The date and time that Lstar should be calculated for
alpha : float, optional
Local pitch angle at ``pos`` to calculate Lstar, default (90)
Kp : int, optional
The Kp index to pass to the magnetic field model, used in T89, ignored
in OP77, default (2)
coord_system : str, optional
The coordinate system of the input position, default (GSM)
Bfield : str, optional
The Magnetic field model to use for the calculation, default (Lgm_B_T89)
LstarThresh : float, optional
The calculation computes a simple L value and does not calculation Lstar
if simple L is beyond this, default (10)
extended_out : bool, optional
Keyword that enables the output of significantly more information into
the Lstar_Data output, default (False). The extra information allows
the points along the Lstar trace to be used since Lstar is the same at
each point along the trace.
LstarQuality : int
The quality flag for the integrators in the calculation, this can have
serious impact on run speed and Lstar value
Returns
=======
out : Lstar_Data
Returns a datamodel object that contains all the information for the run.
See examples for the contents of this object for extended_out=False and True
Examples
========
>>> from lgmpy import Lstar
>>> import datetime
>>> dat = Lstar.get_Lstar([1,2,0], datetime.datetime(2000, 1, 2), extended_out=False)
>>> print(dat)
+
|____90.0 (spacepy.datamodel.SpaceData [8])
|____Bmin (spacepy.datamodel.dmarray ())
:|____units (str [2])
|____Bmirror (spacepy.datamodel.dmarray ())
:|____coord_system (str [3])
:|____units (str [2])
|____I (spacepy.datamodel.dmarray ())
|____LHilton (float)
|____LMcIlwain (float)
|____Lsimple (spacepy.datamodel.dmarray (1,))
|____Lstar (spacepy.datamodel.dmarray (1,))
:|____info (str [4])
|____Pmin (spacepy.datamodel.dmarray (3,))
:|____coord_system (str [3])
:|____units (str [3])
|____Bcalc (spacepy.datamodel.dmarray (3,))
:|____Kp (int)
:|____coord_system (str [3])
:|____model (str [10])
:|____units (str [2])
|____Epoch (spacepy.datamodel.dmarray (1,))
|____Kp (spacepy.datamodel.dmarray (1,))
|____MLT (spacepy.datamodel.dmarray ())
:|____coord_system (str [5])
|____position (dict [1])
|____GSM (spacepy.datamodel.dmarray (3,))
:|____units (str [2])
...
The data object is a dictionary with keys:
- 90.0 : this is the pitch angle specified (multiple can be specified)
- Bmin : the minimum B for that pitch angle and position
- BMirror : the position of the mirror point for that position
- I : the I value for that position
- LHilton : L value calculated with the Hilton approximation
- LMcIlwain: L values calculated with the McIlwain formula
- Lsimple : a simple L value
- Lstar : the value of Lstar for that position and pitch angle
- Pmin : TODO what is Pmin?
- Bcalc : information about the magnetic field model
- Epoch : the time of the calculation
- Kp : Kp used for the calculation
- MLT : MLT value for the position and coord_system
- position : the position of the calculation
- GSM : the value in this system, if conversions are done they all appear here
>>> from lgmpy import Lstar
>>> import datetime
>>> dat = Lstar.get_Lstar([1,2,0], datetime.datetime(2000, 1, 2), extended_out=True)
>>> print(dat)
+
|____90.0 (spacepy.datamodel.SpaceData [21])
:|____Calc_Time (float)
|____Bmag (numpy.ndarray (100, 1000))
|____Bmin (spacepy.datamodel.dmarray ())
:|____units (str [2])
|____Bmirror (spacepy.datamodel.dmarray ())
:|____coord_system (str [3])
:|____units (str [2])
|____I (spacepy.datamodel.dmarray ())
|____LHilton (float)
|____LMcIlwain (float)
|____Lsimple (spacepy.datamodel.dmarray (1,))
|____Lstar (spacepy.datamodel.dmarray (1,))
:|____info (str [4])
|____Pmin (spacepy.datamodel.dmarray (3,))
:|____coord_system (str [3])
:|____units (str [3])
|____ShellEllipsoidFootprint_Pn (numpy.ndarray (100,))
|____ShellEllipsoidFootprint_Ps (numpy.ndarray (100,))
|____ShellI (spacepy.datamodel.dmarray (100,))
|____ShellMirror_Pn (numpy.ndarray (100,))
|____ShellMirror_Ps (numpy.ndarray (100,))
|____ShellMirror_Sn (float)
|____ShellMirror_Ss (float)
|____nFieldPnts (numpy.ndarray (100,))
|____s_gsm (numpy.ndarray (100, 1000))
|____x_gsm (numpy.ndarray (100, 1000))
|____y_gsm (numpy.ndarray (100, 1000))
|____z_gsm (numpy.ndarray (100, 1000))
|____Bcalc (spacepy.datamodel.dmarray (3,))
:|____Kp (int)
:|____coord_system (str [3])
:|____model (str [10])
:|____units (str [2])
|____Epoch (spacepy.datamodel.dmarray (1,))
|____Kp (spacepy.datamodel.dmarray (1,))
|____MLT (spacepy.datamodel.dmarray ())
:|____coord_system (str [5])
|____position (dict [1])
|____GSM (spacepy.datamodel.dmarray (3,))
:|____units (str [2])
...
The data object is a dictionary with keys:
- 90.0 : this is the pitch angle specified (multiple can be specified)
- Calc_Time : the clock time that the calculation took to run
- Bmag : the magnitude of B along the Lstar trace
- Bmin : the minimum B for that pitch angle and position
- BMirror : the position of the mirror point for that position
- I : the I value for that position
- LHilton : L value calculated with the Hilton approximation
- LMcIlwain: L values calculated with the McIlwain formula
- Lsimple : a simple L value
- Lstar : the value of Lstar for that position and pitch angle
- Pmin : TODO what am I?
- ShellEllipsoidFootprint_Pn : TODO what am I?
- ShellEllipsoidFootprint_Ps : TODO what am I?
- ShellI : TODO what am I?
- ShellMirror_Pn : TODO what am I?
- ShellMirror_Ps : TODO what am I?
- ShellMirror_Sn : TODO what am I?
- ShellMirror_Ss : TODO what am I?
- nFieldPnts : TODO what am I?
- s_gsm : TODO what am I?
- x_gsm : TODO what am I?
- y_gsm : TODO what am I?
- z_gsm : TODO what am I?
- Bcalc : information about the magnetic field model
- Epoch : the time of the calculation
- Kp : Kp used for the calculation
- MLT : MLT value for the position and coord_system
- position : the position of the calculation
- GSM : the value in this system, if conversions are done they all appear here
"""
# setup a datamodel object to hold the answer
ans = Lstar_Data()
# change datetime to Lgm Datelong and UTC
try:
datelong = Lgm_CTrans.dateToDateLong(date)
utc = Lgm_CTrans.dateToFPHours(date)
except AttributeError:
raise(TypeError("Date must be a datetime object"))
else:
ans['Epoch'] = datamodel.dmarray([date])
# pitch angles to calculate
try:
Alpha = list(alpha)
except TypeError:
Alpha = [alpha]
# required setup
MagEphemInfo = Lgm_MagEphemInfo.Lgm_MagEphemInfo(len(Alpha), 0)
# setup a shortcut to MagModelInfo
mmi = MagEphemInfo.LstarInfo.contents.mInfo.contents
Lgm_Set_Coord_Transforms( datelong, utc, mmi.c) # dont need pointer as it is one
# convert to **GSM**
if coord_system == 'GSM':
try:
Pgsm = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise(TypeError("Position must be listlike" ) )
ans['position']['GSM'] = datamodel.dmarray(pos, attrs={'units':'Re'})
elif coord_system == 'SM':
try:
Psm = Lgm_Vector.Lgm_Vector(*pos)
except TypeError:
raise(TypeError("Position must be listlike" ) )
Pgsm = Lgm_Vector.Lgm_Vector()
Lgm_Convert_Coords( pointer(Psm), pointer(Pgsm), SM_TO_GSM, mmi.c )
ans['position']['SM'] = datamodel.dmarray(pos, attrs={'units':'Re'})
ans['position']['GSM'] = datamodel.dmarray(Pgsm.tolist(), attrs={'units':'Re'})
else:
raise(NotImplementedError("Only GSM or SM input currently supported"))
Pwgs = Lgm_Vector.Lgm_Vector()
Pmlt = Lgm_Vector.Lgm_Vector()
Lgm_Convert_Coords( pointer(Pgsm), pointer(Pwgs), GSM_TO_WGS84, mmi.c )
Lgm_Convert_Coords( pointer(Pwgs), pointer(Pmlt), WGS84_TO_EDMAG, mmi.c )
R, MLat, MLon, MLT = c_double(), c_double(), c_double(), c_double(),
Lgm_EDMAG_to_R_MLAT_MLON_MLT( pointer(Pmlt), pointer(R), pointer(MLat), pointer(MLon),
pointer(MLT), mmi.c)
ans['MLT'] = datamodel.dmarray(MLT.value, attrs={'coord_system': 'EDMAG'})
# save Kp
# TODO maybe add some Kp checking
ans['Kp'] = datamodel.dmarray([Kp])
# Set the LstarQuality, TODO add a comment here on what each does
MagEphemInfo.LstarQuality = LstarQuality
# L* in one place is L* in lots of places (for GPS set to False)
MagEphemInfo.SaveShellLines = extended_out
# TODO maybe not hardcoded, but for now its fine
MagEphemInfo.LstarInfo.contents.VerbosityLevel = 0
MagEphemInfo.LstarInfo.contents.mInfo.contents.VerbosityLevel = 0
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_T89;
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_cdip;
#MagEphemInfo->LstarInfo->mInfo->Bfield = Lgm_B_OP77;
#MagEphemInfo->LstarInfo->mInfo->InternalModel = LGM_CDIP;
## decide which field model to use, this is a keyword
try:
Bfield_dict[Bfield](MagEphemInfo.LstarInfo.contents.mInfo)
except KeyError:
raise(NotImplementedError("Only Bfield=%s currently supported" % Bfield_dict.keys()))
# Save Date, UTC to MagEphemInfo structure ** is this needed?
MagEphemInfo.Date = datelong
MagEphemInfo.UTC = utc
MagEphemInfo.LstarInfo.contents.mInfo.contents.Kp = Kp
# Save nAlpha, and Alpha array to MagEphemInfo structure
MagEphemInfo.nAlpha = len(Alpha)
for i in range(len(Alpha)):
MagEphemInfo.Alpha[i] = Alpha[i]
# Set Tolerances
Lgm_SetLstarTolerances(LstarQuality, 24, MagEphemInfo.LstarInfo )
# * Blocal at sat location
MagEphemInfo.P = Pgsm
Bvec = Lgm_Vector.Lgm_Vector()
# Get B at the point in question
MagEphemInfo.LstarInfo.contents.mInfo.contents.Bfield(pointer(Pgsm), pointer(Bvec),
MagEphemInfo.LstarInfo.contents.mInfo)
ans['Bcalc'] = datamodel.dmarray(Bvec.tolist(), attrs={'units':'nT'})
ans['Bcalc'].attrs['model'] = Bfield
ans['Bcalc'].attrs['Kp'] = Kp
ans['Bcalc'].attrs['coord_system'] = 'GSM'
# save its magnitude in the structure
MagEphemInfo.B = Bvec.magnitude()
# check and see if the field line is closed before doing much work
trace, northern, southern, minB, Lsimple = Closed_Field.Closed_Field(MagEphemInfo, extended_out=True)
# presetup the ans[Angle] so that it can be filled correctly
for pa in Alpha:
ans[pa] = datamodel.SpaceData()
ans[pa]['Lsimple'] = datamodel.dmarray([Lsimple])
#sets up nans in case of Lstar failure
ans[pa]['I'] = datamodel.dmarray([numpy.nan])
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':trace})
ans[pa]['LMcIlwain'] = datamodel.dmarray([numpy.nan])
ans[pa]['LHilton'] = datamodel.dmarray([numpy.nan])
ans[pa]['Bmin'] = datamodel.dmarray([numpy.nan], attrs={'units':'nT'})
ans[pa]['Bmirror'] = datamodel.dmarray([numpy.nan], attrs={'units':'nT'})
if trace != 'LGM_CLOSED':
return ans
# if this is not LGM_CLOSED then don't both with any pitch angle? true?
# Save field-related quantities for each Pitch Angle.
MagEphemInfo.Pmin = Lgm_Vector.Lgm_Vector(*minB)
MagEphemInfo.Bmin = MagEphemInfo.LstarInfo.contents.mInfo.contents.Bmin
ans[pa]['Pmin'] = datamodel.dmarray(minB, attrs={'units':'R_E'})
ans[pa]['Pmin'].attrs['coord_system'] = 'GSM'
ans[pa]['Bmin'] = datamodel.dmarray(MagEphemInfo.Bmin, attrs={'units':'nT'})
# LOOP OVER PITCH ANGLES
for i, pa in enumerate(Alpha):
tnow = datetime.datetime.now()
PreStr = MagEphemInfo.LstarInfo.contents.PreStr
PostStr = MagEphemInfo.LstarInfo.contents.PostStr
# ***********************************************
# *** not sure I fully understand this chunk, B at the mirror point*****
# Set Pitch Angle, sin, sin^2, and Bmirror
sa = math.sin( pa*RadPerDeg )
sa2 = sa*sa
# print("{0}Computing L* for Pitch Angle: Alpha[{1}] = {2} Date: {3} UTC: {4} Lsimple = {5:4.3}{6}\n").format(PreStr, i, MagEphemInfo.Alpha[i], date, utc, Lsimple, PostStr )
if sa2!=0: #non-zero pitch angle
MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm = MagEphemInfo.B/sa2
else:
continue
ans[pa]['Bmirror'] = datamodel.dmarray(MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm, attrs={'units':'nT'})
ans[pa]['Bmirror'].attrs['coord_system'] = 'GSM'
# ***********************************************
# I tink this is already done
# Lgm_Set_Coord_Transforms( Date, UTC, MagEphemInfo.LstarInfo.contents.mInfo.contents.c )
MagEphemInfo.LstarInfo.contents.PitchAngle = pa
MagEphemInfo.Bm[i] = MagEphemInfo.LstarInfo.contents.mInfo.contents.Bm
# Compute L*
if Lsimple < LstarThresh:
Ls_vec = Lgm_Vector.Lgm_Vector(*minB)
LS_Flag = Lgm_Lstar( pointer(Ls_vec), MagEphemInfo.LstarInfo)
lstarinf = MagEphemInfo.LstarInfo.contents #shortcut
MagEphemInfo.LHilton.contents.value = LFromIBmM_Hilton(c_double(lstarinf.I[0]),
c_double(MagEphemInfo.Bm[i]),
c_double(lstarinf.mInfo.contents.c.contents.M_cd))
ans[pa]['LHilton'] = MagEphemInfo.LHilton.contents.value
MagEphemInfo.LMcIlwain.contents.value = LFromIBmM_McIlwain(c_double(lstarinf.I[0]),
c_double(MagEphemInfo.Bm[i]),
c_double(lstarinf.mInfo.contents.c.contents.M_cd))
ans[pa]['LMcIlwain'] = MagEphemInfo.LMcIlwain.contents.value
if LS_Flag == -2: # mirror below southern hemisphere mirror alt
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':'S_LOSS'})
elif LS_Flag == -1: # mirror below northern hemisphere mirror alt
ans[pa]['Lstar'] = datamodel.dmarray([numpy.nan], attrs={'info':'N_LOSS'})
elif LS_Flag >= 0: # valid calc
ans[pa]['Lstar'] = datamodel.dmarray([lstarinf.LS], attrs={'info':'GOOD'}) # want better word?
MagEphemInfo.Lstar[i] = lstarinf.LS
# Save results to the MagEphemInfo structure.
MagEphemInfo.nShellPoints[i] = lstarinf.nPnts
## pull all this good extra info into numpy arrays
ans[pa]['I'] = datamodel.dmarray(lstarinf.I[0])
if extended_out:
ans[pa]['ShellI'] = \
datamodel.dmarray(numpy.ctypeslib.ndarray([len(lstarinf.I)],
dtype=c_double, buffer=lstarinf.I) ).copy()
ans[pa]['ShellEllipsoidFootprint_Pn'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Ellipsoid_Footprint_Pn),
dtype=c_double,
buffer=lstarinf.Ellipsoid_Footprint_Pn).copy()
ans[pa]['ShellEllipsoidFootprint_Ps'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Ellipsoid_Footprint_Ps),
dtype=c_double,
buffer=lstarinf.Ellipsoid_Footprint_Ps).copy()
ans[pa]['ShellMirror_Pn'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Mirror_Pn),
dtype=c_double,
buffer=lstarinf.Mirror_Pn).copy()
ans[pa]['ShellMirror_Ps'] = \
numpy.ctypeslib.ndarray(len(lstarinf.Mirror_Ps),
dtype=c_double,
buffer=lstarinf.Mirror_Ps).copy()
ans[pa]['ShellMirror_Ss'] = lstarinf.mInfo.contents.Sm_South
ans[pa]['ShellMirror_Sn'] = lstarinf.mInfo.contents.Sm_North
ans[pa]['nFieldPnts'] = \
numpy.ctypeslib.ndarray(len(lstarinf.nFieldPnts),
dtype=c_int,
buffer=lstarinf.nFieldPnts).copy()
ans[pa]['s_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.s_gsm),
len(lstarinf.s_gsm[0])],
dtype=c_double,
buffer=lstarinf.s_gsm).copy()
ans[pa]['Bmag'] = \
numpy.ctypeslib.ndarray([len(lstarinf.Bmag),
len(lstarinf.Bmag[0])],
dtype=c_double,
buffer=lstarinf.Bmag).copy()
ans[pa]['x_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.x_gsm),
len(lstarinf.x_gsm[0])],
dtype=c_double,
buffer=lstarinf.x_gsm).copy()
ans[pa]['y_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.y_gsm),
len(lstarinf.y_gsm[0])],
dtype=c_double,
buffer=lstarinf.y_gsm).copy()
ans[pa]['z_gsm'] = \
numpy.ctypeslib.ndarray([len(lstarinf.z_gsm),
len(lstarinf.z_gsm[0])],
dtype=c_double,
buffer=lstarinf.z_gsm).copy()
delT = datetime.datetime.now() - tnow
ans[pa].attrs['Calc_Time'] = delT.seconds + delT.microseconds/1e6
Lgm_FreeMagEphemInfo_Children(pointer(MagEphemInfo))
return ans
