Source code for spacepy.irbempy.irbempy

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
module wrapper for irbem_lib
Reference for this library
https://sourceforge.net/projects/irbem/
D. Boscher, S. Bourdarie, T. P. O'Brien, T. Guild, IRBEM library V4.3, 2004-2008


Authors
-------
Josef Koller, Steve Morley

Copyright 2010 Los Alamos National Security, LLC.
"""

import numbers
try:
    from collections.abc import Iterable
except ImportError:
    from collections import Iterable
import os
import sys
import warnings

import numpy as np

import spacepy
import spacepy.coordinates as spc
import spacepy.datamodel as dm
from . import irbempylib as oplib
import spacepy.toolbox as tb

# check whether TS07_DATA_PATH is set, if not then set to spacepy's installed data directory
if 'TS07_DATA_PATH' not in os.environ:
    import pkg_resources
    dataTS07D = os.path.join('data', 'TS07D')
    spdatapath = pkg_resources.resource_filename('spacepy', dataTS07D)
    os.environ['TS07_DATA_PATH'] = spdatapath  # set environment variable here


# -----------------------------------------------
def updateTS07Coeffs(path=None, force=False, verbose=False, **kwargs):
    '''Update coefficients for TS07 magnetic field model

    Parameters
    ----------
    path : str
        Base path for TS07 dynamic coefficients. If None (default)
        then the TS07_DATA_PATH environment variable is used.
    force : boolean
        If True (default is False) then missing paths will be created.
    verbose : boolean
        Print verbose output. Default is False.
    start : datetime.datetime or string
        Start time for archive retrieval. If start is a string then it should
        ISO8601 format (YYYY-MM-DDTHH:mm:SS). Defaults to 2007-01-01.
    end : datetime.datetime or string
        End time for archive retrieval. Required format same as start.
        Defaults to time of query (i.e. latest available).
    '''
    import glob
    import tarfile
    import spacepy.time as spt
    dt = spt.datetime
    if sys.version_info[0] < 3:
        import urllib as u
    else:
        import urllib.request as u

    if 'user_agent' in spacepy.config and spacepy.config['user_agent']:
        class AppURLopener(u.FancyURLopener):
            version = spacepy.config['user_agent']
        u._urlopener = AppURLopener()

    if not path:
        # test for TS07_DATA_PATH
        if 'TS07_DATA_PATH' in os.environ:
            path = os.environ['TS07_DATA_PATH']
        else:
            err_str = 'updateTS07Coeffs: Directory for TS07 data must be specified by \n' + \
                      'TS07_DATA_PATH environment variable or path keyword.'
            raise ValueError(err_str)

    # test that path exists, unless force keyword is set
    if not os.path.isdir(path):
        if force:
            os.makedirs(path, mode=0o777)
        else:
            errmsg = ' '.join(['updateTS07Coeffs:',
                               'Specified path for TS07 is not valid -',
                               'to force creation use "force" keyword'])
            raise IOError(errmsg)

    if 'start' not in kwargs:
        firstDate = dt.datetime(2007, 1, 1)
    else:
        firstDate = spt.Ticktock(kwargs['start']).UTC[0]  # make sure it's a datetime
    if 'end' not in kwargs:
        lastDate = dt.datetime.now()
    else:
        lastDate = spt.Ticktock(kwargs['end']).UTC[0]

    baseURL = 'http://rbspgway.jhuapl.edu/models/magneticfieldmodeling/ts07d/coeffs_v02/'

    # make inventory of current TS07 data
    current_days = sorted(glob.glob(os.path.join(path, 'Coeffs', '*')))
    current_days = [os.path.split(dd)[-1] for dd in current_days if 'tgz' not in dd]
    current_dates = []
    for vals in current_days:
        try:
            adddate = spt.doy2date(int(vals.split('_')[0]), int(vals.split('_')[1]), dtobj=True)
        except ValueError:  # not a valid date format
            continue
        current_dates.append(adddate)

    request_days = spt.tickrange(firstDate, lastDate, 1)
    timewant = set(request_days.UTC)
    timegot = set(current_dates)
    stillwant = sorted(list(timewant.difference(timegot)))

    print("Retrieving {2} requested files [{0} - {1}]".format(firstDate.date().isoformat(),
                                                              lastDate.date().isoformat(),
                                                              len(stillwant)))
    for day in stillwant:
        doy = spt.Ticktock(day).DOY[0]
        name = '{0}_{1:03d}'.format(day.year, doy)
        target = os.path.join(path, 'Coeffs', name)
        source = baseURL+'/{0}/'.format(day.year)+'{0}.tgz'.format(name)
        targetfile = os.path.join('{0}.tgz'.format(name))
        if verbose:
            print("\nFetching archive for {0}".format(day.date().isoformat()))
            tmp, report = u.urlretrieve(source, targetfile, reporthook=tb.progressbar)
        else:
            tmp, report = u.urlretrieve(source, targetfile)
        # if the file existed on the server then we won't get an HTML message back
        if 'html' not in report['content-type']:
            tar = tarfile.open(tmp, 'r:gz')
            tar.extractall(target)
            tar.close()
        # now remove tgz file
        os.unlink(tmp)


# -----------------------------------------------
[docs]def get_Bfield(ticks, loci, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None): """ call get_bfield in irbem lib and return a dictionary with the B-field vector and strenght. Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) Returns ======= - results (dictionary) : containing keys: Bvec, and Blocal Examples ======== >>> import spacepy.time as spt >>> import spacepy.coordinates as spc >>> import spacepy.irbempy as ib >>> t = spt.Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = spc.Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> ib.get_Bfield(t,y) {'Blocal': array([ 976.42565251, 3396.25991675]), 'Bvec': array([[ -5.01738885e-01, -1.65104338e+02, 9.62365503e+02], [ 3.33497974e+02, -5.42111173e+02, 3.33608693e+03]])} See Also ======== get_Lstar, find_Bmirror, find_magequator """ # prepare input values for irbem call d = prep_irbem(ticks, loci, alpha=[], extMag=extMag, options=options, omnivals=omnivals) nTAI = len(ticks) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] utsat = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] results = dm.SpaceData() results['Blocal'] = np.zeros(nTAI) results['Bvec'] = np.zeros((nTAI, 3)) for i in np.arange(nTAI): BxyzGEO, Blocal = oplib.get_field1(kext, options, sysaxes, iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], magin[:, i]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(Blocal, badval): Blocal = np.NaN BxyzGEO[np.where(np.isclose(BxyzGEO, badval))] = np.NaN results['Blocal'][i] = Blocal results['Bvec'][i, :] = BxyzGEO return results
# -----------------------------------------------
[docs]def find_Bmirror(ticks, loci, alpha, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None): """ call find_mirror_point from irbem library and return a dictionary with values for Blocal, Bmirr and the GEO (cartesian) coordinates of the mirror point Parameters ========== ticks : Ticktock class containing time information loci : Coords class containing spatial information alpha : array-like containing the pitch angles extMag : str optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] options : array-like (optional) length=5 : explained in Lstar omnivals : dict (optional) if not provided, will use lookup table (see get_Lstar documentation for further explanation) Returns ======= results : dictionary containing keys: Blocal, Bmirr, GEOcar Examples ======== >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> ib.find_Bmirror(t,y,[90,80,60,10]) {'Blocal': array([ 0., 0.]), 'Bmirr': array([ 0., 0.]), 'loci': Coords( [[ NaN NaN NaN] [ NaN NaN NaN]] ), dtype=GEO,car, units=['Re', 'Re', 'Re']} See Also ======== get_Lstar, get_Bfield, find_magequator """ # prepare input values for irbem call d = prep_irbem(ticks, loci, alpha, extMag=extMag, options=options, omnivals=omnivals) nTAI = len(ticks) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] # degalpha = d['degalpha'] # nalp_max = d['nalp_max'] # nalpha = d['nalpha'] results = dm.SpaceData() results['Blocal'] = np.zeros(nTAI) results['Bmirr'] = np.zeros(nTAI) results['loci'] = ['']*nTAI for i in np.arange(nTAI): blocal, bmirr, GEOcoord = oplib.find_mirror_point1(kext, options, sysaxes, iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], alpha, magin[:, i]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(blocal, badval): blocal = np.NaN if np.isclose(bmirr, badval): bmirr = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN results['Blocal'][i] = blocal results['Bmirr'][i] = bmirr results['loci'][i] = GEOcoord with warnings.catch_warnings(): warnings.filterwarnings('ignore', message=r'Use of IRBEM to perform', category=DeprecationWarning, module=r'spacepy.coordinates$') results['loci'] = spc.Coords(results['loci'], 'GEO', 'car', use_irbem=True) return results
# -----------------------------------------------
[docs]def find_magequator(ticks, loci, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None): """ call find_magequator from irbem library and return a dictionary with values for Bmin and the GEO (cartesian) coordinates of the magnetic equator Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) Returns ======= - results (dictionary) : containing keys: Bmin, Coords instance with GEO coordinates of the magnetic equator Examples ======== >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> op.find_magequator(t,y) {'Bmin': array([ 945.63652413, 3373.64496167]), 'loci': Coords( [[ 2.99938371 0.00534151 -0.03213603] [ 2.00298822 -0.0073077 0.04584859]] ), dtype=GEO,car, units=['Re', 'Re', 'Re']} See Also ======== get_Lstar, get_Bfield, find_Bmirr """ # prepare input values for irbem call d = prep_irbem(ticks, loci, alpha=[], extMag=extMag, options=options, omnivals=omnivals) nTAI = len(ticks) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] results = {} results['Bmin'] = np.zeros(nTAI) results['loci'] = ['']*nTAI for i in np.arange(nTAI): bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], magin[:, i]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN results['Bmin'][i] = bmin results['loci'][i] = GEOcoord with warnings.catch_warnings(): warnings.filterwarnings('ignore', message=r'Use of IRBEM to perform', category=DeprecationWarning, module=r'spacepy.coordinates$') results['loci'] = spc.Coords(results['loci'], 'GEO', 'car', use_irbem=True) return results
# ----------------------------------------------- def find_LCDS(ticks, alpha, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None, tol=0.05, bracket=[3, 12], mlt=0, **kwargs): """ Find the last closed drift shell (LCDS) for a given equatorial pitch angle. Uses the IRBEM library to determine L* and searches via bisection to find LCDS to a given tolerance in R (radial distance along GSM equator at local midnight). Parameters ========== - ticks (Ticktock class) : containing time information **for a single time** - alpha (numeric) : equatorial pitch angle for search - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) - tol (float) : tolerance for search in radial distance - bracket (list): X-GSM coordinates to bracket bisection search Returns ======= results (SpaceData, dictionary-like): contains keys LCDS, K, AlphaEq and UTC Examples ======== >>> t = spacepy.time.Ticktock(['2002-02-02T12:00:00'], 'ISO') >>> spacepy.irbempy.find_LCDS(t, 90, extMag='T89') See Also ======== get_Lstar, get_Bfield, find_Bmirr """ # prepare input values for irbem call nTAI = len(ticks) # First set inner bracket (default to R of 3) try: assert len(bracket) == 2 except: raise ValueError('Specified initial bracket is invalid') if not isinstance(alpha, Iterable): alpha = [alpha] results = dm.SpaceData() if len(alpha) != 1: results['LCDS'] = dm.dmfilled([nTAI, len(alpha)]) results['K'] = dm.dmfilled([nTAI, len(alpha)]) else: results['LCDS'] = dm.dmfilled([nTAI, ]) results['K'] = dm.dmfilled([nTAI, ]) results['LCDS'].attrs['DESCRIPTION'] = " ".join(["Last closed drift shell", "calculated with SpacePy's", "irbempy module"]) results['LCDS'].attrs['UNITS'] = "dimensionless" results['LCDS'].attrs['DEPEND_0'] = "UTC" results['LCDS'].attrs['DEPEND_1'] = "K" results['LCDS'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag) results['K'].attrs['DESCRIPTION'] = "Modified 2nd adiabatic invariant at LCDS" results['K'].attrs['UNITS'] = "R_E.G^{1/2}" results['K'].attrs['DEPEND_0'] = "UTC" results['K'].attrs['DEPEND_1'] = "AlphaEq" results['K'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag) results['UTC'] = ticks.UTC results['AlphaEq'] = dm.dmarray(alpha, attrs={'DESCRIPTION': ' '.join(['Equatorial pitch', 'angle for LCDS', 'calculation']), 'UNITS': 'degrees'}) mlt *= 15 # hours to degrees mlt = np.deg2rad(mlt) for idxt, tt in enumerate(ticks): if not omnivals: # prep_irbem will get omni if not specified, but to save on repeated calls, do it once here import spacepy.omni as omni omnivals = omni.get_omni(tt) for idxa, pa in enumerate(alpha): b1x = -1.0*bracket[0]*np.cos(mlt) b1y = -1.0*bracket[0]*np.sin(mlt) loci_brac1 = spc.Coords([b1x, b1y, 0], 'GSM', 'car') if 'verbose' in kwargs: print('Initial inner bracket: {0}'.format(loci_brac1)) d = prep_irbem(tt, loci_brac1, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] nTtoG = 1.0e-5 bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # Now get Lstar at this location... if GEOcoord[0] != np.NaN: pos1 = spc.Coords(GEOcoord, 'GEO', 'car') LS1 = get_Lstar(tt, pos1, pa, extMag=extMag, options=options, omnivals=omnivals) if np.isnan(LS1['Lstar']).any(): raise ValueError('Specified inner bracket ({0}) is on an open drift shell'.format(loci_brac1)) LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG) else: raise ValueError('Specified inner bracket ({0}) is on an open drift shell'.format(loci_brac1)) # print('L* at inner bracket: {0}'.format(LS1['Lstar'])) LCDS, LCDS_K = LS1['Lstar'][0], LS1['K'][0] # Set outer bracket (default to R of 12) b2x = -1.0*bracket[1]*np.cos(mlt) b2y = -1.0*bracket[1]*np.sin(mlt) loci_brac2 = spc.Coords([b2x, b2y, 0], 'GSM', 'car') if 'verbose' in kwargs: print('Initial outer bracket: {0}'.format(loci_brac2)) d2 = prep_irbem(tt, loci_brac2, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals) badval = d2['badval'] kext = d2['kext'] sysaxes = d2['sysaxes'] iyearsat = d2['iyearsat'] idoysat = d2['idoysat'] secs = d2['utsat'] xin1 = d2['xin1'] xin2 = d2['xin2'] xin3 = d2['xin3'] magin = d2['magin'] bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # Now get Lstar at this location... if GEOcoord[0] != np.NaN: pos2 = spc.Coords(GEOcoord, 'GEO', 'car') LS2 = get_Lstar(tt, pos2, pa, extMag=extMag, options=options, omnivals=omnivals) if not np.isnan(LS2['Lstar']).any(): raise ValueError('Specified outer bracket is on a closed drift shell') else: LS2 = {'Lstar': np.NaN} # print('L* at outer bracket: {0}; Xgsm = {1}'.format(LS2['Lstar'], loci_brac2.x)) # now search by bisection while (tb.hypot(loci_brac2.x, loci_brac2.y) - tb.hypot(loci_brac1.x, loci_brac1.y) > tol): newdist = (tb.hypot(loci_brac2.x, loci_brac2.y) + tb.hypot(loci_brac1.x, loci_brac1.y))/2.0 newx = -1.0*newdist*np.cos(mlt) newy = -1.0*newdist*np.sin(mlt) pos_test = spc.Coords([newx, newy, 0], 'GSM', 'car') dtest = prep_irbem(tt, pos_test, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals) badval = dtest['badval'] kext = dtest['kext'] sysaxes = dtest['sysaxes'] iyearsat = dtest['iyearsat'] idoysat = dtest['idoysat'] secs = dtest['utsat'] xin1 = dtest['xin1'] xin2 = dtest['xin2'] xin3 = dtest['xin3'] magin = dtest['magin'] bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # print('bmin, GEOcoord = {0},{1}'.format(bmin, GEOcoord)) if not (np.isnan(bmin)): # Now get Lstar at this location... postry = spc.Coords(GEOcoord, 'GEO', 'car') LStry = get_Lstar(tt, postry, pa, extMag=extMag, options=options, omnivals=omnivals) LStry['K'] = LStry['Xj']*np.sqrt(LStry['Bmirr']*nTtoG) else: LStry = {'Lstar': np.NaN, 'K': np.NaN} if 'verbose' in kwargs: print('L* at test point: {0}; Xgsm = {1}'.format(LStry['Lstar'], pos_test)) if np.isnan(LStry['Lstar']).any(): loci_brac2 = pos_test else: loci_brac1 = pos_test LCDS, LCDS_K = LStry['Lstar'][0], LStry['K'][0] try: results['LCDS'][idxt, idxa] = LCDS results['K'][idxt, idxa] = LCDS_K except IndexError: results['LCDS'][idxt] = LCDS results['K'][idxt] = LCDS_K results['LCDS'] = results['LCDS'] results['K'] = results['K'] return results # ----------------------------------------------- def find_LCDS_K(ticks, K, extMag='T01STORM', options=[1, 1, 3, 0, 0], omnivals=None, tol=0.05, bracket=[3, 12], mlt=0, **kwargs): """ Find the last closed drift shell (LCDS) for a given equatorial pitch angle. Uses the IRBEM library to determine L* and searches via bisection to find LCDS to a given tolerance in R (radial distance along GSM equator at local midnight). Parameters ========== - ticks (Ticktock class) : containing time information **for a single time** - alpha (numeric) : equatorial pitch angle for search - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) - tol (float) : tolerance for search in radial distance - bracket (list): X-GSM coordinates to bracket bisection search Returns ======= results (SpaceData, dictionary-like): contains keys LCDS, K, AlphaEq and UTC Examples ======== >>> t = spacepy.time.Ticktock(['2002-02-02T12:00:00'], 'ISO') >>> spacepy.irbempy.find_LCDS(t, 90, extMag='T89') See Also ======== get_Lstar, get_Bfield, find_Bmirr """ # prepare input values for irbem call nTAI = len(ticks) Aopt = [0] Aopt.extend(options[1:]) # First set inner bracket (default to R of 3) try: assert len(bracket) == 2 except: raise ValueError('Specified initial bracket is invalid') if not isinstance(K, Iterable): K = [K] results = dm.SpaceData() if len(K) != 1: results['LCDS'] = dm.dmfilled([nTAI, len(K)]) results['AlphaEq'] = dm.dmfilled([nTAI, len(K)]) results['Success'] = dm.dmfilled([nTAI, len(K)], fillval='Success', dtype='|S24') else: results['LCDS'] = dm.dmfilled([nTAI, ]) results['AlphaEq'] = dm.dmfilled([nTAI, ]) results['LCDS'].attrs['DESCRIPTION'] = "Last closed drift shell calculated with SpacePy's irbempy module" results['LCDS'].attrs['UNITS'] = "dimensionless" results['LCDS'].attrs['DEPEND_0'] = "UTC" results['LCDS'].attrs['DEPEND_1'] = "K" results['LCDS'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag) results['AlphaEq'].attrs['DESCRIPTION'] = "Modified 2nd adiabatic invariant at LCDS" results['AlphaEq'].attrs['UNITS'] = "R_E.G^{1/2}" results['AlphaEq'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag) results['UTC'] = ticks.UTC results['K'] = dm.dmarray(K, attrs={'DESCRIPTION': 'Equatorial pitch angle for LCDS calculation', 'UNITS': 'degrees'}) mlt *= 15 # hours to degrees mlt = np.deg2rad(mlt) for idxt, tt in enumerate(ticks): if not omnivals: # prep_irbem will get omni if not specified, but to save on repeated calls, do it once here import spacepy.omni as omni omnivals = omni.get_omni(tt) for idxk, k_i in enumerate(K): b1x = -1.0*bracket[0]*np.cos(mlt) b1y = -1.0*bracket[0]*np.sin(mlt) loci_brac1 = spc.Coords([b1x, b1y, 0], 'GSM', 'car') if 'verbose' in kwargs: print('Initial inner bracket: {0}'.format(loci_brac1)) d = prep_irbem(tt, loci_brac1, extMag=extMag, options=options, omnivals=omnivals) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] nTtoG = 1.0e-5 pa = np.NaN bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # Now get Lstar at this location... if np.isfinite(GEOcoord[0]): pos1 = spc.Coords(GEOcoord, 'GEO', 'car') pa = AlphaOfK(tt, pos1, k_i, extMag=extMag, options=Aopt, omnivals=omnivals) LS1 = get_Lstar(tt, pos1, pa, extMag=extMag, options=options, omnivals=omnivals) if np.isnan(LS1['Lstar']).any(): try: results['LCDS'][idxt, idxk] = np.NaN results['AlphaEq'][idxt, idxk] = pa results['Success'][idxt, idxk] = 'Invalid inner bracket' except IndexError: results['LCDS'][idxt] = np.NaN results['AlphaEq'][idxt] = pa results['Success'][idxt] = 'Invalid inner bracket' continue LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG) else: try: results['LCDS'][idxt, idxk] = np.NaN results['AlphaEq'][idxt, idxk] = pa results['Success'][idxt, idxk] = 'Invalid inner bracket' except IndexError: results['LCDS'][idxt] = np.NaN results['AlphaEq'][idxt] = pa results['Success'][idxt] = 'Invalid inner bracket' continue # print('L* at inner bracket: {0}'.format(LS1['Lstar'])) LCDS, LCDS_PA = LS1['Lstar'][0], pa # Set outer bracket (default to R of 12) b2x = -1.0*bracket[1]*np.cos(mlt) b2y = -1.0*bracket[1]*np.sin(mlt) loci_brac2 = spc.Coords([b2x, b2y, 0], 'GSM', 'car') if 'verbose' in kwargs: print('Initial outer bracket: {0}'.format(loci_brac2)) d2 = prep_irbem(tt, loci_brac2, extMag=extMag, options=options, omnivals=omnivals) badval = d2['badval'] kext = d2['kext'] sysaxes = d2['sysaxes'] iyearsat = d2['iyearsat'] idoysat = d2['idoysat'] secs = d2['utsat'] xin1 = d2['xin1'] xin2 = d2['xin2'] xin3 = d2['xin3'] magin = d2['magin'] bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # Now get Lstar at this location... if np.isfinite(GEOcoord[0]): pos2 = spc.Coords(GEOcoord, 'GEO', 'car') pa = AlphaOfK(tt, pos2, k_i, extMag=extMag, options=Aopt, omnivals=omnivals) LS2 = get_Lstar(tt, pos2, pa, extMag=extMag, options=options, omnivals=omnivals) if not np.isnan(LS2['Lstar']).any(): try: results['LCDS'][idxt, idxk] = np.NaN results['AlphaEq'][idxt, idxk] = pa results['Success'][idxt, idxk] = 'Invalid outer bracket' except IndexError: results['LCDS'][idxt] = np.NaN results['AlphaEq'][idxt] = pa results['Success'][idxt] = 'Invalid outer bracket' continue else: LS2 = {'Lstar': np.NaN} # print('L* at outer bracket: {0}; Xgsm = {1}'.format(LS2['Lstar'], loci_brac2.x)) # now search by bisection while (tb.hypot(loci_brac2.x, loci_brac2.y) - tb.hypot(loci_brac1.x, loci_brac1.y) > tol): newdist = (tb.hypot(loci_brac2.x, loci_brac2.y) + tb.hypot(loci_brac1.x, loci_brac1.y))/2.0 newx = -1.0*newdist*np.cos(mlt) newy = -1.0*newdist*np.sin(mlt) pos_test = spc.Coords([newx, newy, 0], 'GSM', 'car') dtest = prep_irbem(tt, pos_test, extMag=extMag, options=options, omnivals=omnivals) badval = dtest['badval'] kext = dtest['kext'] sysaxes = dtest['sysaxes'] iyearsat = dtest['iyearsat'] idoysat = dtest['idoysat'] secs = dtest['utsat'] xin1 = dtest['xin1'] xin2 = dtest['xin2'] xin3 = dtest['xin3'] magin = dtest['magin'] bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[0], idoysat[0], secs[0], xin1[0], xin2[0], xin3[0], magin[:, 0]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN # print('bmin, GEOcoord = {0},{1}'.format(bmin, GEOcoord)) if not (np.isnan(bmin)): # Now get Lstar at this location... postry = spc.Coords(GEOcoord, 'GEO', 'car') pa = AlphaOfK(tt, postry, k_i, extMag=extMag, options=Aopt, omnivals=omnivals) LStry = get_Lstar(tt, postry, pa, extMag=extMag, options=options, omnivals=omnivals) LStry['K'] = LStry['Xj']*np.sqrt(LStry['Bmirr']*nTtoG) else: LStry = {'Lstar': np.NaN, 'K': np.NaN} if 'verbose' in kwargs: print('L* at test point: {0}; Xgsm = {1}'.format(LStry['Lstar'], pos_test)) if np.isnan(LStry['Lstar']).any(): loci_brac2 = pos_test else: loci_brac1 = pos_test LCDS, LCDS_PA = LStry['Lstar'][0], pa try: results['LCDS'][idxt, idxk] = LCDS results['AlphaEq'][idxt, idxk] = LCDS_PA except IndexError: results['LCDS'][idxt] = LCDS results['AlphaEq'][idxt] = LCDS_PA results['LCDS'] = results['LCDS'] results['AlphaEq'] = results['AlphaEq'] return results # ----------------------------------------------- def AlphaOfK(ticks, loci, K, extMag='T01STORM', options=[0, 0, 3, 0, 0], omnivals=None): """ Find the equatorial pitch angle corresponding to a given second invariant K. Uses the IRBEM library to determine K and searches via bisection to find Alpha(K). Parameters ========== - ticks (Ticktock class) : containing time information **for a single time** - loci (Coords class) : containing position information **for a single point** - K (numeric) : value of second invariant (K) for search - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) - tol (float) : tolerance for search in radial distance - bracket (list): X-GSM coordinates to bracket bisection search Returns ======= AlphaEq : equatorial pitch angle corresponding to K Examples ======== >>> t = spacepy.time.Ticktock(['2002-09-01T04:00:00'], 'ISO') >>> loci = spacepy.coordinates.Coords([-4,0,0], 'GSM', 'car') >>> spacepy.irbempy.AlphaOfK(t, loci, 0.11, extMag='T89') 48.984375 See Also ======== get_Lstar, get_Bfield, find_Bmirr, find_LCDS """ # prepare input values for irbem call d = prep_irbem(ticks, loci, extMag=extMag, options=options, omnivals=omnivals) nTAI = len(ticks) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] nTtoG = 1.0e-5 outvals = np.zeros(nTAI) outvals.fill(np.NaN) for i in np.arange(nTAI): bmin, GEOcoord = oplib.find_magequator1(kext, options, sysaxes, iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], magin[:, i]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bmin, badval): bmin = np.NaN GEOcoord[np.where(np.isclose(GEOcoord, badval))] = np.NaN pa0 = 90 # start with equatorially mirroring # Now get K for initial alpha at this location... if np.isfinite(GEOcoord[0]): with warnings.catch_warnings(): warnings.filterwarnings('ignore', message=r'Use of IRBEM to perform', category=DeprecationWarning, module=r'spacepy.coordinates$') pos1 = spc.Coords(GEOcoord, 'GEO', 'car', use_irbem=True) LS1 = get_Lstar(ticks[i], pos1, pa0, extMag=extMag, options=options, omnivals=omnivals) if np.isnan(LS1['Xj']).any(): return np.NaN LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG) else: # print('i = {0}, skipping because of bad position'.format(i)) continue K0 = LS1['K'][0] if np.abs(K0-K) < 1e-3: outvals[i] = pa0 # print('i= {0}, found alpha = {1}'.format(i, pa0)) continue Done, count = False, 0 pa_upper, pa_lower, pa_test = pa0, 0, 30 while not Done: # print('Testing PA={0}'.format(pa_test)) # Now get K for initial alpha at this location... LS1 = get_Lstar(ticks[i], pos1, pa_test, extMag=extMag, options=options, omnivals=omnivals) if np.isnan(LS1['Xj']).any(): break LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG) # print('L* at inner bracket: {0}'.format(LS1['Lstar'])) K_test = LS1['K'][0] if np.abs(K_test-K) < 1e-3: # print('***Found K={0} (Req. {1}) at Alpha={2}'.format(K_test, K, pa_test)) outvals[i] = pa_test break # print('Not Done: Kfound = {0}, Kwant = {1}'.format(K_test, K)) if K_test > K: # K is too large, hence alpha is too small, increase. pa_lower = pa_test # print('Reset lower bound. U,L = {0},{1}'.format(pa_upper, pa_lower)) else: # K is too small, hence alpha is too large, reduce pa_upper = pa_test # print('Reset upper bound. U,L = {0},{1}'.format(pa_upper, pa_lower)) pa_test = pa_lower+np.abs((pa_upper-pa_lower))/2.0 # print('Change alpha to {0}'.format(pa_test)) count += 1 if count > 20: break return outvals # -----------------------------------------------
[docs]def find_footpoint(ticks, loci, extMag='T01STORM', options=[1, 0, 3, 0, 0], hemi='same', alt=100, omnivals=None): """ call find_foot_point1 from irbem library and return a dictionary with values for Bmin and the GEO (cartesian) coordinates of the magnetic equator Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained in Lstar - omni values as dictionary (optional) : if not provided, will use lookup table - (see Lstar documentation for further explanation) - hemi (string) : optional (valid cases are 'same', 'other', 'north' or 'south') will set the target hemisphere for tracing the footpoint - alt (numeric) : optional keyword to set stop height [km] of fieldline trace (default 100km) Returns ======= - results (spacepy.datamodel.SpaceData) : containing keys Bfoot - Magnitude of B-field at footpoint [nT] loci - Coords instance with GDZ coordinates of the magnetic footpoint [alt, lat, lon] Bfootvec - Components of B-field at footpoint in cartesian GEO coordinates [nT] Examples ======== >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = Coords([[3,0,0],[3,0,0]], 'GEO', 'car') >>> spacepy.irbempy.find_footpoint(t, y) {'Bfoot': array([ 47559.04643444, 47542.84688657]), 'Bfootvec': array([[-38428.07217246, 4497.31549786, -27657.19291928], [-38419.08514332, 4501.45390964, -27641.14866517]]), 'loci': Coords( [[ 99.31443778 55.71415787 -10.21888955] [ 99.99397026 55.70716296 -10.22797462]] ), dtype=GDZ,sph, units=['km', 'deg', 'deg']} See Also ======== get_Lstar, get_Bfield, find_Bmirr, find_magequator """ # prepare input values for irbem call d = prep_irbem(ticks, loci, extMag=extMag, options=options, omnivals=omnivals) nTAI = len(ticks) badval = d['badval'] kext = d['kext'] sysaxes = d['sysaxes'] iyearsat = d['iyearsat'] idoysat = d['idoysat'] secs = d['utsat'] xin1 = d['xin1'] xin2 = d['xin2'] xin3 = d['xin3'] magin = d['magin'] hemi_dict = {'same': 0, 'north': 1, 'south': -1, 'other': 2} if hemi.lower() in ['same', 'other', 'north', 'south']: hemi_flag = hemi_dict[hemi.lower()] else: raise ValueError('Option for hemisphere to trace to ({0}) is invalid.\n'.format(hemi) + 'Valid options are: same, other, north and south') results = dm.SpaceData() results['Bfoot'] = np.zeros(nTAI) results['Bfootvec'] = np.zeros([nTAI, 3]) results['loci'] = ['']*nTAI for i in np.arange(nTAI): xfoot, bfoot, bfootmag = oplib.find_foot_point1(kext, options, sysaxes, iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], alt, hemi_flag, magin[:, i]) # take out all the odd 'bad values' and turn them into NaN if np.isclose(bfootmag, badval): bmin = np.NaN xfoot[np.where(np.isclose(xfoot, badval))] = np.NaN bfoot[np.where(np.isclose(bfoot, badval))] = np.NaN results['Bfoot'][i] = bfootmag results['loci'][i] = xfoot results['Bfootvec'][i] = bfoot with warnings.catch_warnings(): warnings.filterwarnings('ignore', message=r'Use of IRBEM to perform', category=DeprecationWarning, module=r'spacepy.coordinates$') results['loci'] = spc.Coords(results['loci'], 'GDZ', 'sph', use_irbem=True) results.attrs return results
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[docs]def coord_trans(loci, returntype, returncarsph): """ thin layer to call coor_trans1 from irbem lib this will convert between systems GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL Parameters ========== - loci (Coords instance) : containing coordinate information, can contain n points - returntype (str) : describing system as GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL - returncarsph (str) : cartesian or spherical units 'car', 'sph' Returns ======= - xout (ndarray) : values after transformation in (n,3) dimensions Examples ======== >>> c = Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> c.ticks = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> coord_trans(c, 'GSM', 'car') array([[ 2.8639301 , -0.01848784, 0.89306361], [ 1.9124434 , 0.07209424, 0.58082929]]) See Also ======== sph2car, car2sph """ sysaxesin = spc.SYSAXES_TYPES[loci.dtype][loci.carsph] sysaxesout = spc.SYSAXES_TYPES[returntype][returncarsph] # swap carsph if sysaxesout is None if (sysaxesout is None) and (returncarsph == 'sph'): sysaxesout = spc.SYSAXES_TYPES[returntype]['car'] aflag = True elif (sysaxesout is None) and (returncarsph == 'car'): sysaxesout = spc.SYSAXES_TYPES[returntype]['sph'] aflag = True else: aflag = False xout = np.zeros(np.shape(loci.data)) for i in np.arange(len(loci)): iyear = loci.ticks.UTC[i].year idoy = loci.ticks.DOY[i] secs = loci.ticks.UTC[i].hour*3600. + loci.ticks.UTC[i].minute*60. + \ loci.ticks.UTC[i].second xout[i, :] = oplib.coord_trans1(sysaxesin, sysaxesout, iyear, idoy, secs, loci.data[i]) # add sph to car or v/v convertion if initial sysaxesout was None if aflag: if returncarsph == 'sph': xout = spc.car2sph(xout) else: # 'car' needs to be returned xout = spc.sph2car(xout) return xout
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[docs]@spacepy.deprecated( '0.2.3', 'moved to spacepy.coordinates', 'use :func:`spacepy.coordinates.car2sph`') def car2sph(CARin): """ coordinate transformation from cartesian to spherical Parameters ========== - CARin (list or ndarray) : coordinate points in (n,3) shape with n coordinate points in units of [Re, Re, Re] = [x,y,z] Returns ======= - results (ndarray) : values after conversion to spherical coordinates in radius, latitude, longitude in units of [Re, deg, deg] Examples ======== >>> sph2car([1,45,0]) array([ 0.70710678, 0. , 0.70710678]) See Also ======== sph2car """ return spc.car2sph(CARin)
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[docs]@spacepy.deprecated( '0.2.3', 'moved to spacepy.coordinates', 'use :func:`spacepy.coordinates.sph2car`') def sph2car(SPHin): """ coordinate transformation from spherical to cartesian Parameters ========== - SPHin (list or ndarray) : coordinate points in (n,3) shape with n coordinate points in units of [Re, deg, deg] = [r, latitude, longitude] Returns ======= - results (ndarray) : values after conversion to cartesian coordinates x,y,z Examples ======== >>> sph2car([1,45,45]) array([ 0.5 , 0.5 , 0.70710678]) See Also ======== car2sph """ if isinstance(SPHin[0], numbers.Number): SPH = np.array([SPHin]) else: SPH = np.asanyarray(SPHin) res = np.zeros(np.shape(SPH)) for i in np.arange(len(SPH)): r, lati, longi = SPH[i, 0], SPH[i, 1], SPH[i, 2] colat = np.pi/2. - lati*np.pi/180. x = r*np.sin(colat)*np.cos(longi*np.pi/180.) y = r*np.sin(colat)*np.sin(longi*np.pi/180.) z = r*np.cos(colat) res[i, :] = [x, y, z] if isinstance(SPHin[0], numbers.Number): return res[0] else: return res
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[docs]@spacepy.deprecated( '0.2.3', 'get_sysaxes marked for removal', 'use `spacepy.coordinates.SYSAXES_TYPES`' ) def get_sysaxes(dtype, carsph): """ will return the sysaxes according to the irbem library Parameters ========== - dtype (str) : coordinate system, possible values: GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL - carsph (str) : cartesian or spherical, possible values: 'sph', 'car' Returns ======= - sysaxes (int) : value after oner_desp library from 0-8 (or None if not available) Examples ======== >>> get_sysaxes('GSM', 'car') 2 See Also ======== get_dtype """ sysaxes = spc.SYSAXES_TYPES[dtype][carsph] return sysaxes
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[docs]def get_dtype(sysaxes): """ will return the coordinate system type as string Parameters ========== - sysaxes (int) : number according to the irbem, possible values: 0-8 Returns ======= - dtype (str) : coordinate system GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL - carsph (str) : cartesian or spherical 'car', 'sph' Examples ======== >>> get_dtype(3) ('GSE', 'car') See Also ======== get_sysaxes """ for key in spc.SYSAXES_TYPES: for subkey in spc.SYSAXES_TYPES[key]: if spc.SYSAXES_TYPES[key][subkey] == sysaxes: dtype = key carsph = subkey return dtype, carsph
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[docs]def get_AEP8(energy, loci, model='min', fluxtype='diff', particles='e'): """ will return the flux from the AE8-AP8 model Parameters ========== - energy (float) : center energy in MeV; if fluxtype=RANGE, then needs to be a list [Emin, Emax] - loci (Coords) : a Coords instance with the location inside the magnetosphere optional instead of a Coords instance, one can also provide a list with [BBo, L] combination - model (str) : MIN or MAX for solar cycle dependence - fluxtype (str) : DIFF, RANGE, INT are possible types - particles (str): e or p or electrons or protons Returns ======= - float : flux from AE8/AP8 model Examples ======== >>> spacepy.irbempy.get_aep8() >>> import spacepy.time as spt >>> import spacepy.coordinates as spc >>> import spacepy.irbempy as ib >>> t = spt.Ticktock(['2017-02-02T12:00:00'], 'ISO') >>> y = spc.Coords([3,0,0], 'GEO', 'car') >>> y.ticks = t >>> energy = 1.0 #MeV >>> ib.get_AEP8(energy, y, model='max') 1932209.4427359989 """ # find bad values and dimensions if particles.lower() == 'e': # then choose electron model if model.upper() == 'MIN': whichm = 1 elif model.upper() == 'MAX': whichm = 2 else: print('Warning: model=' + model + ' is not implemented: Choose MIN or MAX') elif particles.lower() == 'p': # then choose proton model if model.upper() == 'MIN': whichm = 3 elif model.upper() == 'MAX': whichm = 4 else: print('Warning: model='+model+' is not implemented: Choose MIN or MAX') else: print('Warning: particles='+particles+' is not available: choose e or p') if fluxtype.upper() == 'DIFF': whatf = 1 elif fluxtype.upper() == 'RANGE': whatf = 2 elif fluxtype.upper() == 'INT': whatf = 3 else: print('Warning: fluxtype='+fluxtype+' is not implemented: Choose DIFF, INT or RANGE') # need range if whatf=2 Nene = 1 if whatf == 2: assert len(energy) == 2, 'Need energy range with this choice of fluxtype=RANGE' ntmax = 1 # build dummy OMNI dictionary for prep_irbem (AE/AP8 doesn't need these inputs) dum_omni = dict() magkeys = ['Kp', 'Dst', 'dens', 'velo', 'Pdyn', 'ByIMF', 'BzIMF', 'G1', 'G2', 'G3', 'W1', 'W2', 'W3', 'W4', 'W5', 'W6'] for key in magkeys: dum_omni[key] = [0]*len(loci) if isinstance(loci, spc.Coords): assert loci.ticks, 'Coords require time information with a Ticktock object' d = prep_irbem(ticks=loci.ticks, loci=loci, omnivals=dum_omni) E_array = np.zeros((2, d['nalp_max'])) E_array[:, 0] = energy # now get the flux flux = oplib.fly_in_nasa_aeap1(ntmax, d['sysaxes'], whichm, whatf, Nene, E_array, d['iyearsat'], d['idoysat'], d['utsat'], d['xin1'], d['xin2'], d['xin3']) elif isinstance(loci, (list, np.ndarray)): BBo, L = loci d = prep_irbem(omnivals=dum_omni) E_array = np.zeros((2, d['nalp_max'])) E_array[:, 0] = energy B_array = np.zeros(d['ntime_max']) B_array[0] = BBo L_array = np.zeros(d['ntime_max']) L_array[0] = L # now get the flux flux = oplib.get_ae8_ap8_flux(ntmax, whichm, whatf, Nene, E_array, B_array, L_array) else: print('Warning: coords need to be either a spacepy.coordinates.Coords instance or a list of [BBo, L]') flux[np.where(np.isclose(flux, d['badval']))] = np.NaN return flux[0, 0]
# ----------------------------------------------- def _get_Lstar(ticks, loci, alpha, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None, landi2lstar=False): """ This will call make_lstar1 or make_lstar_shell_splitting_1 from the irbem library and will lookup omni values for given time if not provided (optional). If pitch angles are provided, drift shell splitting will be calculated and "Bmirr" will be returned. If they are not provided, then no drift shell splitting is calculated and "Blocal" is returned. Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - alpha (list or ndarray) : pitch angles in degrees; if provided will calculate shell splitting; max 25 values - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained below - omni values as dictionary (optional) : if not provided, will use lookup table - landi2lstar : if True, will use the faster landi2lstar routine if possible. This routine can only be used with OPQUIET+IGRF magnetic field models. Returns ======= - results (dictionary) : containing keys: Lm, Lstar, Bmin, Blocal (or Bmirr), Xj (I - the 2nd invariant), MLT if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr" is returned if not provided, then "Blocal" at spacecraft is returned. Examples ======== >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> spacepy.irbempy.Lstar(t,y) {'Blocal': array([ 1020.40493286, 3446.08845227]), 'Bmin': array([ 1019.98404311, 3437.63865243]), 'Lm': array([ 3.08948304, 2.06022102]), 'Lstar': array([ 2.97684043, 1.97868577]), 'MLT': array([ 23.5728333 , 23.57287944]), 'Xj': array([ 0.00112884, 0.00286955])} Notes ===== External Field - 0 : no external field - MEAD : Mead & Fairfield [1975] (uses 0<=Kp<=9 - Valid for rGEO<=17. Re) - T87SHORT: Tsyganenko short [1987] (uses 0<=Kp<=9 - Valid for rGEO<=30. Re) - T87LONG : Tsyganenko long [1987] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re) - T89 : Tsyganenko [1989] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re) - OPQUIET : Olson & Pfitzer quiet [1977] (default - Valid for rGEO<=15. Re) - OPDYN : Olson & Pfitzer dynamic [1988] (uses 5.<=dens<=50., 300.<=velo<=500., -100.<=Dst<=20. - Valid for rGEO<=60. Re) - T96 : Tsyganenko [1996] (uses -100.<=Dst (nT)<=20., 0.5<=Pdyn (nPa)<10., |ByIMF| (nT)<1=0., |BzIMF| (nT)<=10. - Valid for rGEO<=40. Re) - OSTA : Ostapenko & Maltsev [1997] (uses dst,Pdyn,BzIMF, Kp) T01QUIET: Tsyganenko [2002a,b] (uses -50.<Dst (nT)<20., 0.5<Pdyn (nPa)<=5., |ByIMF| (nT)<=5., |BzIMF| (nT)<=5., 0.<=G1<=10., 0.<=G2<=10. - Valid for xGSM>=-15. Re) - T01STORM: Tsyganenko, Singer & Kasper [2003] storm (uses Dst, Pdyn, ByIMF, BzIMF, G2, G3 - there is no upper or lower limit for those inputs - Valid for xGSM>=-15. Re) - T05 : Tsyganenko & Sitnov [2005] storm (uses Dst, Pdyn, ByIMF, BzIMF, W1, W2, W3, W4, W5, W6 - no upper or lower limit for inputs - Valid for xGSM>=-15. Re) - TS07 : Tsyganenko and Sitnov [2007] model. Uses specially calculated coefficient files. OMNI contents - Kp: value of Kp as in OMNI2 files but has to be double instead of integer type - Dst: Dst index (nT) - dens: Solar Wind density (cm-3) - velo: Solar Wind velocity (km/s) - Pdyn: Solar Wind dynamic pressure (nPa) - ByIMF: GSM y component of IMF mag. field (nT) - BzIMF: GSM z component of IMF mag. field (nT) - G1: G1=< Vsw*(Bperp/40)2/(1+Bperp/40)*sin3(theta/2) > where the <> mean an average over the previous 1 hour, Vsw is the solar wind speed, Bperp is the transverse IMF component (GSM) and theta it's clock angle. - G2: G2=< a*Vsw*Bs > where the <> mean an average over the previous 1 hour, Vsw is solar wind speed, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0, a=0.005. - G3: G3=< Vsw*Dsw*Bs /2000.> where the <> mean an average over the previous 1 hour, Vsw is the solar wind speed, Dsw is the solar wind density, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0. - W1 - W6: see definition in (JGR-A, v.110(A3), 2005.) (PDF 1.2MB) - AL: the auroral index Options - 1st element: 0 - don't compute L* or phi ; 1 - compute L*; 2- compute phi - 2nd element: 0 - initialize IGRF field once per year (year.5); n - n is the frequency (in days) starting on January 1st of each year (i.e. if options(2nd element)=15 then IGRF will be updated on the following days of the year: 1, 15, 30, 45 ...) - 3rd element: resolution to compute L* (0 to 9) where 0 is the recomended value to ensure a good ratio precision/computation time (i.e. an error of ~2% at L=6). The higher the value the better will be the precision, the longer will be the computing time. Generally there is not much improvement for values larger than 4. Note that this parameter defines the integration step (theta) along the field line such as dtheta=(2pi)/(720*[options(3rd element)+1]) - 4th element: resolution to compute L* (0 to 9). The higher the value the better will be the precision, the longer will be the computing time. It is recommended to use 0 (usually sufficient) unless L* is not computed on a LEO orbit. For LEO orbit higher values are recommended. Note that this parameter defines the integration step (phi) along the drift shell such as dphi=(2pi)/(25*[options(4th element)+1]) - 5th element: allows to select an internal magnetic field model (default is set to IGRF) - 0 = IGRF - 1 = Eccentric tilted dipole - 2 = Jensen&Cain 1960 - 3 = GSFC 12/66 updated to 1970 - 4 = User-defined model (Default: Centred dipole + uniform [Dungey open model] ) - 5 = Centred dipole """ nTAI = len(ticks) d = prep_irbem(ticks, loci, alpha, extMag, options, omnivals) nalpha = d['nalpha'] if d['kext'] != 5 or d['options'][4] != 0: landi2lstar = False no_shell_splitting = (nalpha == 0) or (nalpha == 1 and alpha[0] == 90) # Arguments that are common to all flavors of L* functions args = [nTAI, d['kext'], d['options'], d['sysaxes'], d['iyearsat'], d['idoysat'], d['utsat'], d['xin1'], d['xin2'], d['xin3'], d['magin']] if no_shell_splitting: # no drift shell splitting func = oplib.landi2lstar1 if landi2lstar else oplib.make_lstar1 else: # with drift shell splitting # Drift shell splitting requires pitch angle positional args args.insert(1, nalpha) args.insert(-1, d['degalpha']) func = oplib.landi2lstar_shell_splitting1 if landi2lstar \ else oplib.make_lstar_shell_splitting1 # For a locally 90-degree particle, bmirr is blocal lm, lstar, bmirr, bmin, xj, mlt = func(*args) # take out all the odd 'bad values' and turn them into NaN lm[np.where(np.isclose(lm, d['badval']))] = np.NaN lstar[np.where(np.isclose(lstar, d['badval']))] = np.NaN bmin[np.where(np.isclose(bmin, d['badval']))] = np.NaN xj[np.where(np.isclose(xj, d['badval']))] = np.NaN mlt[np.where(np.isclose(mlt, d['badval']))] = np.NaN results = {} if no_shell_splitting: results['Lm'] = lm[0:nTAI][:, None] results['Lstar'] = lstar[0:nTAI][:, None] bmirr[np.where(np.isclose(bmirr, d['badval']))] = np.NaN results['Blocal'] = bmirr[0:nTAI] results['Bmirr'] = results['Blocal'][:, None] results['Bmin'] = bmin[0:nTAI] results['Xj'] = xj[0:nTAI][:, None] results['MLT'] = mlt[0:nTAI] else: results['Lm'] = lm[0:nTAI, 0:nalpha] results['Lstar'] = lstar[0:nTAI, 0:nalpha] bmirr[np.where(np.isclose(bmirr, d['badval']))] = np.NaN results['Bmirr'] = bmirr[0:nTAI, 0:nalpha] results['Bmin'] = bmin[0:nTAI] results['Xj'] = xj[0:nTAI, 0:nalpha] results['MLT'] = mlt[0:nTAI] return results # -----------------------------------------------
[docs]def get_Lm(ticks, loci, alpha, extMag='T01STORM', intMag='IGRF', IGRFset=0, omnivals=None): """ Return the MacIlwain L value for a given location, time and model Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - alpha (list or ndarray) : pitch angles in degrees - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - intMag (string) : optional: select the internal field model possible values ['IGRF','EDIP','JC','GSFC','DUN','CDIP'] For full details see get_Lstar - omni values as dictionary (optional) : if not provided, will use lookup table Returns ======= - results (dictionary) : containing keys: Lm, Bmin, Blocal (or Bmirr), Xj, MLT if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr" is returned if not provided, then "Blocal" at spacecraft is returned. A negative value for Lm indicates the field line is closed but particles are lost to the atmosphere; the absolute value indicates the L value. Examples ======== Notes ===== """ intMaglookup = {'IGRF': 0, 'EDIP': 1, 'JC': 2, 'GSFC': 3, 'DUN': 4, 'CDIP': 5} if intMag not in intMaglookup: raise ValueError('Invalid value of intMag: valid values are: {0}'.format(intMaglookup.keys())) if IGRFset != 0: try: assert IGRFset > 0 # TODO: test for numeric type except AssertionError: raise ValueError('IGRFset must be positive-valued and numeric') opts = [0, IGRFset, 0, 0, intMaglookup[intMag]] results = get_Lstar(ticks, loci, alpha, extMag=extMag, options=opts, omnivals=omnivals) dum = results.pop('Lstar') return results
# -----------------------------------------------
[docs]def get_Lstar(ticks, loci, alpha=90, extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None, landi2lstar=False): """ This will call make_lstar1 or make_lstar_shell_splitting_1 from the irbem library and will lookup omni values for given time if not provided (optional). If pitch angles are provided, drift shell splitting will be calculated and "Bmirr" will be returned. If they are not provided, then no drift shell splitting is calculated and "Blocal" is returned. Parameters ========== - ticks (Ticktock class) : containing time information - loci (Coords class) : containing spatial information - alpha (list or ndarray) : optional pitch angles in degrees (default is 90); if provided will calculate shell splitting; max 25 values - extMag (string) : optional; will choose the external magnetic field model possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] - options (optional list or array of integers length=5) : explained below - omni values as dictionary (optional) : if not provided, will use lookup table - landi2lstar : if True, will use the faster landi2lstar routine if possible. This routine can only be used with OPQUIET+IGRF magnetic field models. Returns ======= - results (dictionary) : containing keys: Lm, Lstar, Bmin, Blocal (or Bmirr), Xj, MLT if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr" is returned if not provided, then "Blocal" at spacecraft is returned. A negative value for Lm indicates the field line is closed but particles are lost to the atmosphere; the absolute value indicates the L value. A negative value for Lstar indicates the field line is closed but particles are lost to the atmosphere before completing a drift orbit; the absolute value indicates the drift shell. Examples ======== >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO') >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car') >>> spacepy.irbempy.Lstar(t,y) {'Blocal': array([ 1020.40493286, 3446.08845227]), 'Bmin': array([ 1019.98404311, 3437.63865243]), 'Lm': array([ 3.08948304, 2.06022102]), 'Lstar': array([ 2.97684043, 1.97868577]), 'MLT': array([ 23.5728333 , 23.57287944]), 'Xj': array([ 0.00112884, 0.00286955])} Notes ===== External Field - 0 : no external field - MEAD : Mead & Fairfield [1975] (uses 0<=Kp<=9 - Valid for rGEO<=17. Re) - T87SHORT: Tsyganenko short [1987] (uses 0<=Kp<=9 - Valid for rGEO<=30. Re) - T87LONG : Tsyganenko long [1987] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re) - T89 : Tsyganenko [1989] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re) - OPQUIET : Olson & Pfitzer quiet [1977] (default - Valid for rGEO<=15. Re) - OPDYN : Olson & Pfitzer dynamic [1988] (uses 5.<=dens<=50., 300.<=velo<=500., -100.<=Dst<=20. - Valid for rGEO<=60. Re) - T96 : Tsyganenko [1996] (uses -100.<=Dst (nT)<=20., 0.5<=Pdyn (nPa)<10., abs(ByIMF) (nT)<1=0., abs(BzIMF) (nT)<=10. - Valid for rGEO<=40. Re) - OSTA : Ostapenko & Maltsev [1997] (uses dst,Pdyn,BzIMF, Kp) T01QUIET: Tsyganenko [2002a,b] (uses -50.<Dst (nT)<20., 0.5<Pdyn (nPa)<=5., abs(ByIMF) (nT)<=5., abs(BzIMF) (nT)<=5., 0.<=G1<=10., 0.<=G2<=10. - Valid for xGSM>=-15. Re) - T01STORM: Tsyganenko, Singer & Kasper [2003] storm (uses Dst, Pdyn, ByIMF, BzIMF, G2, G3 - there is no upper or lower limit for those inputs - Valid for xGSM>=-15. Re) - T05 : Tsyganenko & Sitnov [2005] storm (uses Dst, Pdyn, ByIMF, BzIMF, W1, W2, W3, W4, W5, W6 - no upper or lower limit for inputs - Valid for xGSM>=-15. Re) OMNI contents - Kp: value of Kp as in OMNI2 files but has to be double instead of integer type - Dst: Dst index (nT) - dens: Solar Wind density (cm-3) - velo: Solar Wind velocity (km/s) - Pdyn: Solar Wind dynamic pressure (nPa) - ByIMF: GSM y component of IMF mag. field (nT) - BzIMF: GSM z component of IMF mag. field (nT) - G1: G1=< Vsw*(Bperp/40)2/(1+Bperp/40)*sin3(theta/2) > where the <> mean an average over the previous 1 hour, Vsw is the solar wind speed, Bperp is the transverse IMF component (GSM) and theta it's clock angle. - G2: G2=< a*Vsw*Bs > where the <> mean an average over the previous 1 hour, Vsw is solar wind speed, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0, a=0.005. - G3: G3=< Vsw*Dsw*Bs /2000.> where the <> mean an average over the previous 1 hour, Vsw is the solar wind speed, Dsw is the solar wind density, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0. - W1 - W6: see definition in (JGR-A, v.110(A3), 2005.) (PDF 1.2MB) - AL: the auroral index Options - 1st element: 0 - don't compute L* or phi ; 1 - compute L*; 2- compute phi - 2nd element: 0 - initialize IGRF field once per year (year.5); n - n is the frequency (in days) starting on January 1st of each year (i.e. if options(2nd element)=15 then IGRF will be updated on the following days of the year: 1, 15, 30, 45 ...) - 3rd element: resolution to compute L* (0 to 9) where 0 is the recomended value to ensure a good ratio precision/computation time (i.e. an error of ~2% at L=6). The higher the value the better will be the precision, the longer will be the computing time. Generally there is not much improvement for values larger than 4. Note that this parameter defines the integration step (theta) along the field line such as dtheta=(2pi)/(720*[options(3rd element)+1]) - 4th element: resolution to compute L* (0 to 9). The higher the value the better will be the precision, the longer will be the computing time. It is recommended to use 0 (usually sufficient) unless L* is not computed on a LEO orbit. For LEO orbit higher values are recommended. Note that this parameter defines the integration step (phi) along the drift shell such as dphi=(2pi)/(25*[options(4th element)+1]) - 5th element: allows to select an internal magnetic field model (default is set to IGRF) - 0 = IGRF - 1 = Eccentric tilted dipole - 2 = Jensen&Cain 1960 - 3 = GSFC 12/66 updated to 1970 - 4 = User-defined model (Default: Centred dipole + uniform [Dungey open model] ) - 5 = Centred dipole """ def get_ov(fullov, stind, enind): '''Chop up omni data for multiprocessing''' out = dm.SpaceData() keylist = list(fullov.keys()) dum = keylist.pop(keylist.index('Qbits')) if 'Qbits' in keylist else None for key in keylist: out[key] = fullov[key][stind:enind] if 'Qbits' in fullov: out['Qbits'] = dm.SpaceData() for key in fullov['Qbits']: out['Qbits'][key] = fullov['Qbits'][key][stind:enind] return out def reassemble(result): '''Reassemble the results from the multiprocessing''' funcs = {'Bmin': np.hstack, 'Blocal': np.hstack, 'Bmirr': np.vstack, 'Lm': np.vstack, 'Lstar': np.vstack, 'MLT': np.hstack, 'Xj': np.vstack} out = dm.SpaceData() for el in result: for key in result[0]: if key in list(out.keys()): # not first chunk out[key] = funcs[key]([out[key], el[key]]) else: # first chunk out[key] = el[key].copy() return out if isinstance(alpha, numbers.Number): alpha = [alpha] ncpus = spacepy.config['ncpus'] ncalc = len(ticks) nalpha = len(alpha) if ncalc < ncpus * 2: # Don't multiprocess if not worth it ncpus = 1 if ncpus > 1: import __main__ as main if hasattr(main, '__file__'): try: from multiprocessing import Pool pool = Pool(ncpus) except (ImportError, OSError): ncpus = 1 # if pool setup fails, e.g. Wine, go single else: ncpus = 1 # won't multiprocess in interactive mode if ncpus > 1: nblocks = ncpus blocklen = np.floor_divide(ncalc, ncpus) tt, cc = [], [] if omnivals: ov = [] else: ov = [None] * nblocks for block in range(nblocks): startind = block*blocklen if block != nblocks-1: # not last block endind = block*blocklen + blocklen else: endind = ncalc # in last block, go to index of final time tt.append(ticks[startind:endind]) # chunk time tags cc.append(loci[startind:endind]) # chunk positions if omnivals: ov.append(get_ov(omnivals, startind, endind)) inputs = [[tch, cch, alpha, extMag, options, oval, landi2lstar] for tch, cch, oval in zip(tt, cc, ov)] result = pool.map(_multi_get_Lstar, inputs) pool.close() pool.join() DALL = reassemble(result) else: # single NCPU, no chunking DALL = _get_Lstar(ticks, loci, alpha, extMag, options, omnivals, landi2lstar) return DALL
def _multi_get_Lstar(inputs): ''' ''' ticks = inputs[0] loci = inputs[1] alpha = inputs[2] extMag = inputs[3] options = inputs[4] omnivals = inputs[5] landi2lstar = inputs[6] DALL = _get_Lstar(ticks, loci, alpha, extMag, options, omnivals, landi2lstar) return DALL # -----------------------------------------------
[docs]def prep_irbem(ticks=None, loci=None, alpha=[], extMag='T01STORM', options=[1, 0, 0, 0, 0], omnivals=None): """ Prepare inputs for direct IRBEM-LIB calls. Not expected to be called by the user. """ # setup dictionary to return input values for irbem d = {} d['badval'] = -1e31 d['nalp_max'] = 25 d['ntime_max'] = 100000 d['options'] = options badval = d['badval'] nalp_max = d['nalp_max'] ntime_max = d['ntime_max'] if ticks is None: return d UTC = ticks.UTC DOY = ticks.DOY eDOY = ticks.eDOY nTAI = len(ticks) # setup mag array and move omni values magin = np.zeros((nalp_max, ntime_max), float) magkeys = ['Kp', 'Dst', 'dens', 'velo', 'Pdyn', 'ByIMF', 'BzIMF', 'G1', 'G2', 'G3', 'W1', 'W2', 'W3', 'W4', 'W5', 'W6'] def fakeOMNI(npts, mk): fakeomni = {} for kk in magkeys: fakeomni[kk] = [1]*npts return fakeomni # get omni values if omnivals is None: # No OMNI values provided so look up (requires data files) if extMag.upper() not in ['0', 'OPQUIET', 'TS07']: import spacepy.omni as omni omnivals = omni.get_omni(ticks) # UNLESS we're asking for a static model... # then we spoof the input as the numbers are irrelevant # OR TS07, which uses special files elif extMag.upper() == 'TS07': # keep this separate, just in case TS07 params ever get passed in the usual way omnivals = fakeOMNI(len(ticks), magkeys) else: omnivals = fakeOMNI(len(ticks), magkeys) if 'G' in omnivals: for n in range(1, 4): dum = omnivals['G'][..., n-1] if dum.ndim == 0: dum = np.array([dum]) omnivals['G{0}'.format(n)] = dum del omnivals['G'] if 'W' in omnivals: for n in range(1, 7): dum = omnivals['W'][..., n-1] if dum.ndim == 0: dum = np.array([dum]) omnivals['W{0}'.format(n)] = dum del omnivals['W'] for iTAI in np.arange(nTAI): for ikey, key in enumerate(magkeys): magin[ikey, iTAI] = omnivals[key][iTAI] # multiply Kp*10 to look like omni database # this is what irbem lib is looking for magin[0, :] = magin[0, :]*10. d['magin'] = magin # setup time array iyearsat = np.zeros(ntime_max, dtype=int) idoysat = np.zeros(ntime_max, dtype=int) utsat = np.zeros(ntime_max, dtype=float) for i in np.arange(nTAI): iyearsat[i] = UTC[i].year idoysat[i] = int(DOY[i]) utsat[i] = (eDOY[i]-np.floor(eDOY[i]))*86400. d['iyearsat'] = iyearsat d['idoysat'] = idoysat d['utsat'] = utsat # copy coordinates into array # prepare coordinates if loci.sysaxes is None: # System type not supported by IRBEM # Convert car -> sph or vice versa as required newcarsph = [key for (key, val) in spc.SYSAXES_TYPES[loci.dtype].items() if val is not None][0] with warnings.catch_warnings(): warnings.filterwarnings('ignore', message=r'Use of IRBEM to perform', category=DeprecationWarning, module=r'spacepy.coordinates$') posi = loci.convert(loci.dtype, newcarsph) else: posi = loci d['sysaxes'] = posi.sysaxes xin1 = np.zeros(ntime_max, dtype=float) xin2 = np.zeros(ntime_max, dtype=float) xin3 = np.zeros(ntime_max, dtype=float) if posi.carsph == 'sph': xin1[0:nTAI] = posi.radi[:] xin2[0:nTAI] = posi.lati[:] xin3[0:nTAI] = posi.long[:] else: xin1[0:nTAI] = posi.x[:] xin2[0:nTAI] = posi.y[:] xin3[0:nTAI] = posi.z[:] d['xin1'] = xin1 d['xin2'] = xin2 d['xin3'] = xin3 # convert external magnetic field flag extkeys = ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07'] assert extMag in extkeys, 'extMag not available: {0}'.format(extMag) kext = extkeys.index(extMag.upper()) d['kext'] = kext # calc at given pitch angles 'alpha'? degalpha = np.zeros(nalp_max, dtype=float) if isinstance(alpha, numbers.Number): nalpha = 1 alpha = [alpha] nalpha = len(alpha) if nalpha > d['nalp_max']: raise ValueError('Too many pitch angles requested; {} is maximum.' .format(d['nalp_max'])) d['nalpha'] = nalpha if nalpha > 0: degalpha[0:nalpha] = alpha d['degalpha'] = degalpha return d