def test_gcal2jd_with_astropy_erfa_cal2jd():
"""Compare gcal2jd with astropy._erfa.cal2jd."""
import random
import numpy as np
from astropy import _erfa
n = 1000
mday = [0, 31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
# sla_cldj needs year > -4699 i.e., 4700 BC.
year = [random.randint(-4699, 2200) for i in range(n)]
month = [random.randint(1, 12) for i in range(n)]
day = [random.randint(1, 31) for i in range(n)]
for i in range(n):
x = 0
if is_leap(year[i]) and month[i] == 2:
x = 1
if day[i] > mday[month[i]] + x:
day[i] = mday[month[i]]
jd_jdcal = np.array(
[gcal2jd(y, m, d) for y, m, d in zip(year, month, day)])
jd_erfa = np.array(_erfa.cal2jd(year, month, day)).T
assert np.allclose(jd_jdcal, jd_erfa)
def _test_erfa_conversion(leap, i_f):
i_i, f_i = i_f
assume(0 <= f_i < 1)
if leap:
assume(i_i in leap_sec_days)
else:
assume(i_i not in leap_sec_days)
jd1_in, jd2_in = day_frac(erfa.DJM0 + i_i, f_i)
y, mo, d, f = erfa.jd2cal(jd1_in, jd2_in)
assert 0 < y < 3000
assert 0 < mo <= 12
assert 0 <= d < 32
assert 0 <= f < 1
jd1_temp, jd2_temp = erfa.cal2jd(y, mo, d)
jd1_temp, jd2_temp = day_frac(jd1_temp, jd2_temp) # improve numerics
jd1_temp, jd2_temp = day_frac(jd1_temp, jd2_temp + f)
jd_change = abs((jd1_temp - jd1_in) + (jd2_temp - jd2_in)) * u.day
assert jd_change.to(u.ns) < 1 * u.ns
ft = 24 * f
h = safe_kind_conversion(np.floor(ft), dtype=int)
ft -= h
ft *= 60
m = safe_kind_conversion(np.floor(ft), dtype=int)
ft -= m
ft *= 60
s = ft
assert 0 <= h < 24
assert 0 <= m < 60
assert 0 <= s < 60
jd1, jd2 = erfa.dtf2d("UTC", y, mo, d, h, m, s)
y2, mo2, d2, f2 = erfa.jd2cal(jd1, jd2)
# assert (y, mo, d) == (y2, mo2, d2)
# assert (abs(f2-f)*u.day).to(u.s) < 1*u.ns
assert jd1 == np.floor(jd1) + 0.5
assert 0 <= jd2 < 1
jd1, jd2 = day_frac(jd1, jd2)
jd_change = abs((jd1 - jd1_in) + (jd2 - jd2_in)) * u.day
if leap:
assert jd_change.to(u.s) < 1 * u.s
else:
assert jd_change.to(u.ns) < 2 * u.ns
# assert jd_change.to(u.ns) < 1 * u.ns
return
i_o, f_o = day_frac(jd1 - erfa.DJM0, jd2)
mjd_change = abs((i_o - i_i) + (f_o - f_i)) * u.day
if leap:
assert mjd_change.to(u.s) < 1 * u.s
else:
assert mjd_change.to(u.ns) < 1 * u.ns
def value(self):
if self._scale == 'utc':
# Do the reverse of the above calculation
# Note this will return an incorrect value during
# leap seconds, so raise an exception in that
# case.
y, mo, d, hmsf = erfa.d2dtf('UTC',9,self.jd1,self.jd2)
if 60 in hmsf[...,2]:
raise ValueError('UTC times during a leap second cannot be represented in pulsar_mjd format')
j1, j2 = erfa.cal2jd(y,mo,d)
return (j1 - erfa.DJM0 + j2) + (hmsf[...,0]/24.0
+ hmsf[...,1]/1440.0
+ hmsf[...,2]/86400.0
+ hmsf[...,3]/86400.0e9)
else:
# As in TimeMJD
return (self.jd1 - erfa.DJM0) + self.jd2
def value(self):
if self._scale == 'utc':
# Do the reverse of the above calculation
# Note this will return an incorrect value during
# leap seconds, so raise an exception in that
# case.
y, mo, d, hmsf = erfa.d2dtf('UTC', 9, self.jd1, self.jd2)
if 60 in hmsf[..., 2]:
raise ValueError(
'UTC times during a leap second cannot be represented in pulsar_mjd format'
)
j1, j2 = erfa.cal2jd(y, mo, d)
return (j1 - erfa.DJM0 +
j2) + (hmsf[..., 0] / 24.0 + hmsf[..., 1] / 1440.0 +
hmsf[..., 2] / 86400.0 + hmsf[..., 3] / 86400.0e9)
else:
# As in TimeMJD
return (self.jd1 - erfa.DJM0) + self.jd2
def value(self):
if self._scale == 'utc':
# Do the reverse of the above calculation
# Note this will return an incorrect value during
# leap seconds, so raise an exception in that
# case.
y, mo, d, hmsf = erfa.d2dtf('UTC',9,self.jd1,self.jd2)
# For ASTROPY_LT_3_1, convert to the new structured array dtype that
# is returned by the new erfa gufuncs.
if not hmsf.dtype.names:
hmsf = hmsf.view(self._new_ihmsfs_dtype)
if numpy.any(hmsf['s'] == 60):
raise ValueError('UTC times during a leap second cannot be represented in pulsar_mjd format')
j1, j2 = erfa.cal2jd(y,mo,d)
return (j1 - erfa.DJM0 + j2) + (hmsf['h']/24.0
+ hmsf['m']/1440.0
+ hmsf['s']/86400.0
+ hmsf['f']/86400.0e9)
else:
# As in TimeMJD
return (self.jd1 - erfa.DJM0) + self.jd2
def value(self):
if self._scale == 'utc':
# Do the reverse of the above calculation
# Note this will return an incorrect value during
# leap seconds, so raise an exception in that
# case.
y, mo, d, hmsf = erfa.d2dtf('UTC',9,self.jd1,self.jd2)
# For ASTROPY_LT_3_1, convert to the new structured array dtype that
# is returned by the new erfa gufuncs.
if not hmsf.dtype.names:
hmsf = hmsf.view(self._new_ihmsfs_dtype)
if numpy.any(hmsf['s'] == 60):
raise ValueError('UTC times during a leap second cannot be represented in pulsar_mjd format')
j1, j2 = erfa.cal2jd(y,mo,d)
return (j1 - erfa.DJM0 + j2) + (hmsf['h']/24.0
+ hmsf['m']/1440.0
+ hmsf['s']/86400.0
+ hmsf['f']/86400.0e9)
else:
# As in TimeMJD
return (self.jd1 - erfa.DJM0) + self.jd2
def jds_to_mjds_pulsar(jd1, jd2):
# Do the reverse of the above calculation
# Note this will return an incorrect value during
# leap seconds, so raise an exception in that
# case.
y, mo, d, hmsf = erfa.d2dtf("UTC", _digits, jd1, jd2)
# For ASTROPY_LT_3_1, convert to the new structured array dtype that
# is returned by the new erfa gufuncs.
if not hmsf.dtype.names:
hmsf = hmsf.view(_new_ihmsfs_dtype)[..., 0]
if np.any((hmsf["s"] == 60) & (hmsf["f"] != 0)):
# if f is exactly zero, this is probably fine to treat as the end of the day.
raise ValueError(
"UTC times during a leap second cannot be represented in pulsar_mjd format"
)
j1, j2 = erfa.cal2jd(y, mo, d)
return day_frac(
j1 - erfa.DJM0 + j2,
hmsf["h"] / 24.0
+ hmsf["m"] / 1440.0
+ hmsf["s"] / 86400.0
+ hmsf["f"] / 86400.0 / 10 ** _digits,
)
def test_gcal2jd_with_astropy_erfa_cal2jd():
"""Compare gcal2jd with astropy._erfa.cal2jd."""
import random
import numpy as np
from astropy import _erfa
n = 1000
mday = [0, 31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
# sla_cldj needs year > -4699 i.e., 4700 BC.
year = [random.randint(-4699, 2200) for i in range(n)]
month = [random.randint(1, 12) for i in range(n)]
day = [random.randint(1, 31) for i in range(n)]
for i in range(n):
x = 0
if is_leap(year[i]) and month[i] == 2:
x = 1
if day[i] > mday[month[i]] + x:
day[i] = mday[month[i]]
jd_jdcal = np.array([gcal2jd(y, m, d) for y, m, d in zip(year, month, day)])
jd_erfa = np.array(_erfa.cal2jd(year, month, day)).T
assert np.allclose(jd_jdcal, jd_erfa)
def utc2cel06a_parameters(t, eop, iau55=False):
"""
Purpose:
This function calculates the cartesian transformation matrix for transforming GCRS to ITRS or vice versa
:param eop:
eop is a dataframe containing the Earth Orientation Parameters as per IAU definitions
:param t:
t is a datetime object or a list of datetime objects with the UTC times for the transformation matrix to be
calculated for
:return:
jd is the julian date (always xxx.5 because it is based on a noon day break) in days
ttb is the leap second offset in fractions of a day
utb is the UT1 offset in fractions of a day
xp and yp are the coordinates (in radians) of the Celestial Intermediate Pole with respect to the International
Terrestrial Reference System (see IERS Conventions 2003), measured along the meridians to 0 and 90 deg west
respectively (as extrapolated from between the two published points before and after).
dx06 and dy06 are the CIP offsets wrt IAU 2006/2000A (mas->radians) as extrapolated from between the two
published points before and after
"""
year, month, day, hour, minute, second = t.year, t.month, t.day, t.hour, t.minute, t.second
# TT (MJD). */
djmjd0, date = erfa.cal2jd(iy=year, im=month, id=day)
jd = djmjd0 + date
day_frac = (60.0 * (60 * hour + minute) + second) / DAYSEC
dat_s = erfa.dat(year, month, day, day_frac)
ttb = dat_s / DAYSEC + 32.184 / DAYSEC
# Polar motion (arcsec->radians)
xp_l = eop["x"][date]
yp_l = eop["y"][date]
xp_h = eop["x"][date + 1]
yp_h = eop["y"][date + 1]
xp = (xp_l * (1 - day_frac) + xp_h * day_frac) * DAS2R
yp = (yp_l * (1 - day_frac) + yp_h * day_frac) * DAS2R
# UT1-UTC (s). */
dut_l = eop["UT1-UTC"][date]
dut_h = eop["UT1-UTC"][date + 1]
dut1 = (dut_l * (1 - day_frac) + dut_h * day_frac)
# CIP offsets wrt IAU 2006/2000A (mas->radians). */
dx_l = eop["dX"][date]
dx_h = eop["dX"][date + 1]
dy_l = eop["dY"][date]
dy_h = eop["dY"][date + 1]
dx06 = (dx_l * (1 - day_frac) + dx_h * day_frac) * DAS2R
dy06 = (dy_l * (1 - day_frac) + dy_h * day_frac) * DAS2R
if iau55:
# CIP offsets wrt IAU 2006/2000A (mas->radians). */
dx06 = float64(0.1750 * DMAS2R, dtype="f64")
dy06 = float64(-0.2259 * DMAS2R, dtype="f64")
# UT1-UTC (s). */
dut1 = float64(-0.072073685, dtype="f64")
# Polar motion (arcsec->radians)
xp = float64(0.0349282 * DAS2R, dtype="f64")
yp = float64(0.4833163 * DAS2R, dtype="f64")
# UT1. */
utb = day_frac + dut1 / DAYSEC
return jd, ttb, utb, xp, dx06, yp, dy06
def gcrs2irts_matrix_b(t, eop):
"""
Ref: http://www.iausofa.org/sofa_pn_c.pdf
Purpose:
This function calculates the cartesian transformation matrix for transforming GCRS to ITRS or vice versa
:param eop:
eop is a dataframe containing the Earth Orientation Parameters as per IAU definitions
:param t:
t is a datetime object or a list of datetime objects with the UTC times for the transformation matrix to be
calculated for
:return:
matrix is a [3,3] numpy array or list of arrays used for transforming GCRS to ITRS or vice versa at the
specified times; ITRS = matrix @ GCRS
"""
if not (isinstance(t, Iterable)):
t = [t]
matrix = []
for ti in t:
year = ti.year
month = ti.month
day = ti.day
hour = ti.hour
minute = ti.minute
second = ti.second
# TT (MJD). */
djmjd0, date = erfa.cal2jd(iy=year, im=month, id=day)
# jd = djmjd0 + date
day_frac = (60.0 * (60.0 * hour + minute) + second) / DAYSEC
utc = date + day_frac
Dat = erfa.dat(year, month, day, day_frac)
tai = utc + Dat / DAYSEC
tt = tai + 32.184 / DAYSEC
# UT1. */
dut1 = eop["UT1-UTC"][date] * (
1 - day_frac) + eop["UT1-UTC"][date + 1] * day_frac
tut = day_frac + dut1 / DAYSEC
# ut1 = date + tut
# CIP and CIO, IAU 2006/2000A. */
x, y, s = erfa.xys06a(djmjd0, tt)
# X, Y offsets
dx06 = (eop["dX"][date] *
(1 - day_frac) + eop["dX"][date + 1] * day_frac) * DAS2R
dy06 = (eop["dY"][date] *
(1 - day_frac) + eop["dY"][date + 1] * day_frac) * DAS2R
# Add CIP corrections. */
x = x + dx06
y = y + dy06
# GCRS to CIRS matrix. */
rc2i = erfa.c2ixys(x, y, s)
# Earth rotation angle. */
era = erfa.era00(djmjd0 + date, tut)
# Form celestial-terrestrial matrix (no polar motion yet). */
rc2ti = erfa.cr(rc2i)
rc2ti = eraRZ(era, rc2ti)
#rc2ti = erfa.rz(era, rc2ti)
# Polar motion matrix (TIRS->ITRS, IERS 2003). */
xp = (eop["x"][date] *
(1 - day_frac) + eop["x"][date + 1] * day_frac) * DAS2R
yp = (eop["y"][date] *
(1 - day_frac) + eop["y"][date + 1] * day_frac) * DAS2R
rpom = erfa.pom00(xp, yp, erfa.sp00(djmjd0, tt))
# Form celestial-terrestrial matrix (including polar motion). */
rc2it = erfa.rxr(rpom, rc2ti)
matrix.append(rc2it)
if len(matrix) == 1:
matrix = matrix[0]
return matrix