def test_tOverlap(self):
"""tOverlap should return a known value for known input"""
real_ans = ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39])
ans = tb.tOverlap(self.dt_a, self.dt_b)
self.assertEqual(real_ans, ans)
self.assertEqual( (None, None), tb.tOverlap(self.dt_a, self.dt_b2) )
def test_tOverlap(self):
"""tOverlap should return a known value for known input"""
real_ans = ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39])
ans = tb.tOverlap(self.dt_a, self.dt_b)
self.assertEqual(real_ans, ans)
self.assertEqual( (None, None), tb.tOverlap(self.dt_a, self.dt_b2) )
def test_tOverlapSorted(self):
"""Exploit the sorting for a fast tOverlap"""
real_ans = ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39])
ans = tb.tOverlap(self.dt_a, self.dt_b, presort=True)
numpy.testing.assert_array_equal(real_ans, ans)
def test_tOverlapSorted(self):
"""Exploit the sorting for a fast tOverlap"""
real_ans = ([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
11, 12, 13, 14, 15, 16, 17, 18, 19],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39])
ans = tb.tOverlap(self.dt_a, self.dt_b, presort=True)
numpy.testing.assert_array_equal(real_ans, ans)
def test_tOverlap_random(self):
"""Shuffle input before calling tOverlap"""
real_ans = ([1, 5, 6, 10, 15, 16, 18, 24, 29, 30, 43,
46, 47, 51, 53, 55, 56, 64, 67, 74],
[1, 2, 6, 7, 10, 12, 13, 14, 15, 17, 18,
19, 24, 27, 28, 30, 32, 35, 37, 38])
random.seed(0)
random.shuffle(self.dt_a, lambda:round(random.random(), 9))
random.shuffle(self.dt_b, lambda:round(random.random(), 9))
ans = tb.tOverlap(self.dt_a, self.dt_b)
numpy.testing.assert_array_equal(real_ans, ans)
def test_tOverlap_random(self):
"""Shuffle input before calling tOverlap"""
real_ans = ([1, 5, 6, 10, 15, 16, 18, 24, 29, 30, 43,
46, 47, 51, 53, 55, 56, 64, 67, 74],
[1, 2, 6, 7, 10, 12, 13, 14, 15, 17, 18,
19, 24, 27, 28, 30, 32, 35, 37, 38])
random.seed(0)
random.shuffle(self.dt_a, lambda:round(random.random(), 9))
random.shuffle(self.dt_b, lambda:round(random.random(), 9))
ans = tb.tOverlap(self.dt_a, self.dt_b)
numpy.testing.assert_array_equal(real_ans, ans)
"""Tests for the speed of tOverlap
Copyright ©2010 Los Alamos National Security, LLC.
"""
import datetime
import random
import timeit
from spacepy import toolbox
n_iter = 500
#Very simple call to make sure everything loaded/init before timing
dt_a = [datetime.datetime(2000, 1, 1), datetime.datetime(2000, 1, 2)]
dt_b = [datetime.datetime(1999, 12, 31), datetime.datetime(2000, 1, 1)]
toolbox.tOverlap(dt_a, dt_b, presort=False)
toolbox.tOverlap(dt_a, dt_b, presort=True)
dt1 = datetime.datetime(2000, 11, 12)
dt_a = [dt1 + datetime.timedelta(hours=offset) for offset in range(10000)]
dt_b = [
dt1 + datetime.timedelta(hours=offset) for offset in range(-5000, 5000)
]
timing = timeit.timeit('toolbox.tOverlap(dt_a, dt_b)',
'from __main__ import toolbox, dt_a, dt_b',
number=n_iter)
print('Sorted arrays took ' + str(timing) + ' seconds.')
timing = timeit.timeit('toolbox.tOverlap(dt_a, dt_b, presort=True)',
'from __main__ import toolbox, dt_a, dt_b',
number=n_iter)
def getPlasmaPause(ticks, model='M2002', LT='all', omnivals=None):
"""
Plasmapause location model(s)
CA1992 -- Carpenter, D. L., and R. R. Anderson, An ISEE/whistler
model of equatorial electron density in the magnetosphere,
J. Geophys. Res., 97, 1097, 1992.
M2002 -- Moldwin, M. B., L. Downward, H. K. Rassoul, R. Amin,
and R. R. Anderson, A new model of the location of the plasmapause:
CRRES results, J. Geophys. Res., 107(A11), 1339,
doi:10.1029/2001JA009211, 2002.
RT1970 -- Rycroft, M. J., and J. O. Thomas, The magnetospheric
plasmapause and the electron density trough at the alouette i
orbit, Planetary and Space Science, 18(1), 65-80, 1970
Parameters
==========
ticks : spacepy.time.Ticktock
TickTock object of desired times
Lpp_model : string, optional
'CA1992' or 'M2002' (default)
CA1992 returns the Carpenter and Anderson model,
M2002 returns the Moldwin et al. model
LT : int, float
requested local time sector, 'all' is valid option
omnivals : spacepy.datamodel.SpaceData, dict
dict-like containing UTC (datetimes) and Kp keys
Returns
=======
out : float
Plasmapause radius in Earth radii
Examples
========
>>> import spacepy.time as spt
>>> import spacepy.empiricals as emp
>>> ticks = spt.tickrange('2002-01-01T12:00:00','2002-01-04T00:00:00',.25)
>>> emp.getPlasmaPause(ticks)
array([ 6.42140002, 6.42140002, 6.42140002, 6.42140002, 6.42140002,
6.42140002, 6.42140002, 6.26859998, 5.772 , 5.6574 ,
5.6574 ])
"""
def calcLpp(Kpmax, A, B, power=1):
currLpp = A - B * Kpmax**power
return currLpp
model_list = ['CA1992', 'M2002', 'RT1970']
if model == 'CA1992':
if LT != 'all':
print('No LT dependence currently supported for this model')
if model not in model_list:
raise ValueError("Please specify a valid model:\n{0}".format(
' or '.join(model_list)))
if LT == 'all':
parA = {'CA1992': 5.6, 'M2002': 5.39, 'RT1970': 5.64}
parB = {'CA1992': 0.46, 'M2002': 0.382, 'RT1970': 0.78}
priorvals = {
'CA1992': datetime.timedelta(hours=24),
'M2002': datetime.timedelta(hours=12),
'RT1970': datetime.timedelta(0)
}
A, B = parA[model], parB[model]
prior = priorvals[model]
else:
try:
float(LT)
except (ValueError, TypeError):
raise ValueError(
"Please specify a valid LT:\n'all' or a numeric type")
parA = {
'CA1992': [5.6] * 24,
'M2002':
[5.7] * 3 + [6.05] * 6 + [5.2] * 6 + [4.45] * 6 + [5.7] * 3,
'RT1970': [5.64] * 24
}
parB = {
'CA1992': [0.46] * 24,
'M2002':
[0.42] * 3 + [0.573] * 6 + [0.425] * 6 + [0.167] * 6 + [0.42] * 3,
'RT1970': [0.78] * 24
}
priorvals = {
'CA1992': [datetime.timedelta(hours=24)] * 24,
'M2002': [datetime.timedelta(hours=12)] * 24,
'RT1970': [datetime.timedelta(0)] * 24
}
try:
LThr = long(LT)
except NameError:
LThr = int(LT)
prior = priorvals[model][LThr]
A, B = parA[model][LThr], parB[model][LThr]
st, en = ticks.UTC[0] - prior, ticks.UTC[-1]
if omnivals is None:
omdat = om.get_omni(spt.tickrange(st, en, 1.0 / 24.0),
dbase='QDhourly')
else:
#now test for sanity of input
try:
assert isinstance(omnivals, dict)
except:
raise TypeError(
'Not a valid input type for omnivals, expected spacepy.datamodel.SpaceData'
)
try:
assert 'UTC' in omnivals
assert 'Kp' in omnivals
except:
raise KeyError(
'Required data not found in input dict-like (omnivals)')
omdat = omnivals
einds, oinds = tb.tOverlap([st, en], omdat['UTC'])
utc = np.array(omdat['UTC'])[oinds]
Kp = np.array(omdat['Kp'])[oinds]
Lpp = np.zeros(len(ticks))
if model == 'RT1970':
power = 0.5
else:
power = 1
for i, t1 in enumerate(ticks.UTC):
t0 = t1 - prior
iprevday, dum = tb.tOverlap(utc, [t0, t1])
if iprevday:
Kpmax = max(Kp[iprevday])
Lpp[i] = calcLpp(Kpmax, A, B, power=power)
else:
Lpp[i] = np.nan
return Lpp
def getPlasmaPause(ticks, model='M2002', LT='all', omnivals=None):
"""
Plasmapause location model(s)
CA1992 -- Carpenter, D. L., and R. R. Anderson, An ISEE/whistler
model of equatorial electron density in the magnetosphere,
J. Geophys. Res., 97, 1097, 1992.
M2002 -- Moldwin, M. B., L. Downward, H. K. Rassoul, R. Amin,
and R. R. Anderson, A new model of the location of the plasmapause:
CRRES results, J. Geophys. Res., 107(A11), 1339,
doi:10.1029/2001JA009211, 2002.
RT1970 -- Rycroft, M. J., and J. O. Thomas, The magnetospheric
plasmapause and the electron density trough at the alouette i
orbit, Planetary and Space Science, 18(1), 65-80, 1970
Parameters
==========
ticks : spacepy.time.Ticktock
TickTock object of desired times
Lpp_model : string, optional
'CA1992' or 'M2002' (default)
CA1992 returns the Carpenter and Anderson model,
M2002 returns the Moldwin et al. model
LT : int, float
requested local time sector, 'all' is valid option
omnivals : spacepy.datamodel.SpaceData, dict
dict-like containing UTC (datetimes) and Kp keys
Returns
=======
out : float
Plasmapause radius in Earth radii
Examples
========
>>> import spacepy.time as spt
>>> import spacepy.empiricals as emp
>>> ticks = spt.tickrange('2002-01-01T12:00:00','2002-01-04T00:00:00',.25)
>>> emp.getPlasmaPause(ticks)
array([ 6.42140002, 6.42140002, 6.42140002, 6.42140002, 6.42140002,
6.42140002, 6.42140002, 6.26859998, 5.772 , 5.6574 ,
5.6574 ])
"""
def calcLpp(Kpmax, A, B, power=1):
currLpp = A - B*Kpmax**power
return currLpp
model_list = ['CA1992', 'M2002', 'RT1970']
if model == 'CA1992':
if LT!='all':
print('No LT dependence currently supported for this model')
if model not in model_list:
raise ValueError("Please specify a valid model:\n{0}".format(' or '.join(model_list)))
if LT=='all':
parA = {'CA1992': 5.6, 'M2002': 5.39, 'RT1970': 5.64}
parB = {'CA1992': 0.46, 'M2002': 0.382, 'RT1970': 0.78}
priorvals = {'CA1992': datetime.timedelta(hours=24),
'M2002': datetime.timedelta(hours=12),
'RT1970': datetime.timedelta(0)}
A, B = parA[model], parB[model]
prior = priorvals[model]
else:
try:
float(LT)
except (ValueError, TypeError):
raise ValueError("Please specify a valid LT:\n'all' or a numeric type")
parA = {'CA1992': [5.6]*24,
'M2002': [5.7]*3+[6.05]*6+[5.2]*6+[4.45]*6+[5.7]*3,
'RT1970': [5.64]*24}
parB = {'CA1992': [0.46]*24,
'M2002': [0.42]*3+[0.573]*6+[0.425]*6+[0.167]*6+[0.42]*3,
'RT1970': [0.78]*24}
priorvals = {'CA1992': [datetime.timedelta(hours=24)]*24,
'M2002': [datetime.timedelta(hours=12)]*24,
'RT1970': [datetime.timedelta(0)]*24}
try:
LThr = long(LT)
except NameError:
LThr = int(LT)
prior = priorvals[model][LThr]
A, B = parA[model][LThr], parB[model][LThr]
st, en = ticks.UTC[0]-prior, ticks.UTC[-1]
if omnivals is None:
omdat = om.get_omni(spt.tickrange(st, en, 1.0/24.0), dbase='QDhourly')
else:
#now test for sanity of input
try:
assert isinstance(omnivals, dict)
except:
raise TypeError('Not a valid input type for omnivals, expected spacepy.datamodel.SpaceData')
try:
assert 'UTC' in omnivals
assert 'Kp' in omnivals
except:
raise KeyError('Required data not found in input dict-like (omnivals)')
omdat = omnivals
einds, oinds = tb.tOverlap([st, en], omdat['UTC'])
utc = np.array(omdat['UTC'])[oinds]
Kp = np.array(omdat['Kp'])[oinds]
Lpp = np.zeros(len(ticks))
if model == 'RT1970':
power = 0.5
else:
power = 1
for i, t1 in enumerate(ticks.UTC):
t0 = t1-prior
iprevday, dum = tb.tOverlap(utc, [t0, t1])
if iprevday:
Kpmax = max(Kp[iprevday])
Lpp[i] = calcLpp(Kpmax, A, B, power=power)
else:
Lpp[i] = np.nan
return Lpp
data=om.get_omni(ticks)
import spacepy.seapy as se
import spacepy.omni as om
import spacepy.toolbox as tb
import datetime as datetime
import numpy as np
epochs =se.readepochs('/Library/Python/2.7/site-packages/spacepy/data/SEA_epochs_OMNI.txt')
st = datetime.datetime(2005,1,1)
en = datetime.datetime(2009,1,1)
einds,oinds = tb.tOverlap([st,en],data['UTC'])
omni1hr = np.array(data['UTC'])[oinds]
delta = datetime.timedelta(hours=1)
window= datetime.timedelta(days=3)
sevx = se.Sea(data['velo'][oinds],omni1hr, epochs, window, delta)
# sevx = se.Sea(data['Pdyn'][oinds],omni1hr, epochs, window, delta)
sevx.sea()
sevx.plot(epochline=True,yquan='V$_{sw}$',xunits='days',yunits='Km s$^{-1}$')
"""Tests for the speed of tOverlap
Copyright ©2010 Los Alamos National Security, LLC.
"""
import datetime
import random
import timeit
from spacepy import toolbox
n_iter = 500
#Very simple call to make sure everything loaded/init before timing
dt_a = [datetime.datetime(2000, 1, 1), datetime.datetime(2000, 1, 2)]
dt_b = [datetime.datetime(1999, 12, 31), datetime.datetime(2000, 1, 1)]
toolbox.tOverlap(dt_a, dt_b, presort=False)
toolbox.tOverlap(dt_a, dt_b, presort=True)
dt1 = datetime.datetime(2000, 11, 12)
dt_a = [dt1 + datetime.timedelta(hours=offset) for offset in range(10000)]
dt_b = [dt1 + datetime.timedelta(hours=offset)
for offset in range(-5000, 5000)]
timing = timeit.timeit('toolbox.tOverlap(dt_a, dt_b)',
'from __main__ import toolbox, dt_a, dt_b',
number=n_iter)
print('Sorted arrays took ' + str(timing) + ' seconds.')
timing = timeit.timeit('toolbox.tOverlap(dt_a, dt_b, presort=True)',
'from __main__ import toolbox, dt_a, dt_b',
number=n_iter)
print('Sorted arrays, sorted algorithm took ' + str(timing) + ' seconds.')
