def hipeqgal():
"""Print summary of EQ-GAL comparison with SLALIB eqgal (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_eqgal.txt")
dummy = np.zeros((len(hip_tab['px']), ))
v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], dummy, dummy,
dummy, dummy, tpm.CJ)
v6o = convert.convertv6(v6l, s1=6, s2=4)
# The galactic coordinates are at epoch J2000. But SLALIB
# results are for B1950. So apply proper motion here.
v6o = convert.proper_motion(v6o, tpm.B1950, tpm.J2000)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB eqgal using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
def hipgaleq():
"""Print summary of GAL-EQ comparison with SLALIB galeq (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_galeq.txt")
dummy = np.zeros((len(hip_tab['px']), ))
v6l = convert.cat2v6(hip_tab['glon'], hip_tab['glat'], dummy, dummy, dummy,
dummy, tpm.CJ)
# The actual epoch of galactic data is J2000. But in SLALIB
# the input is taken to be B1950.0. So use tpm.B1950 as epoch
# in the conversion.
v6o = convert.convertv6(v6l, s1=4, s2=6, epoch=tpm.B1950)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB galeq using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
def hipecleq():
"""Print summary of ECL-EQ comparison with SLALIB ecleq (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_ecleq.txt")
dummy = np.zeros((len(hip_tab['px']), ))
v6l = convert.cat2v6(hip_tab['elon2'], hip_tab['elat2'], dummy, dummy,
dummy, dummy, tpm.CJ)
v6o = convert.convertv6(v6l, s1=3, s2=6)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB ecleq using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2], x[3]**0.5))
def hipfk524():
"""Print summary of FK5-FK4 comparison with SLALIB fk524 (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_fk524.txt")
rv = np.zeros((len(hip_tab['px'],)))
v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], hip_tab['pma'],
hip_tab['pmd'], hip_tab['px'], rv, tpm.CJ)
v6o = convert.convertv6(v6l, s1=6, s2=5, epoch=tpm.J2000)
v6o = convert.proper_motion(v6o, tpm.B1950, tpm.J2000)
cat = (tpm.v62cat(v, tpm.CB) for v in v6o)
d = cat2array(cat)
ra_diff = np.degrees(d['alpha']) - sla_tab[:, 0]
ra_diff *= 3600.0
dec_diff = np.degrees(d['delta']) - sla_tab[:, 1]
dec_diff *= 3600.0
px_diff = d['px'] * 1000.0 - sla_tab[:, 2]
pma_diff = d['pma'] * 1000.0 / 100.0 - sla_tab[:, 3]
pmd_diff = d['pmd'] * 1000.0 / 100.0 - sla_tab[:, 4]
rv_diff = d['rv'] - sla_tab[:, 5]
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = [stats.describe(np.abs(i)) for i in
[ra_diff, dec_diff, px_diff, pma_diff, pmd_diff, rv_diff]]
print("Comparison with SLALIB fk524 using HIPPARCOS data.")
for name, unit, s in zip(
["ra_diff", "dec_diff", "px_diff", "pma_diff", "pmd_diff",
"rv_diff"],
["arsec", "arcsec", "milliarcsec", "milli-arsec/trop. yr",
"milli-arcsec/trop. yr", "km/s"],
x):
print(fs.format(name, unit, s[1][0], s[1][1], s[2], s[3] ** 0.5))
def hipgaleq():
"""Print summary of GAL-EQ comparison with SLALIB galeq (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_galeq.txt")
dummy = np.zeros((len(hip_tab['px']),))
v6l = convert.cat2v6(hip_tab['glon'], hip_tab['glat'], dummy, dummy,
dummy, dummy, tpm.CJ)
# The actual epoch of galactic data is J2000. But in SLALIB
# the input is taken to be B1950.0. So use tpm.B1950 as epoch
# in the conversion.
v6o = convert.convertv6(v6l, s1=4, s2=6, epoch=tpm.B1950)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB galeq using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
def hipeqgal():
"""Print summary of EQ-GAL comparison with SLALIB eqgal (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_eqgal.txt")
dummy = np.zeros((len(hip_tab['px']),))
v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], dummy, dummy,
dummy, dummy, tpm.CJ)
v6o = convert.convertv6(v6l, s1=6, s2=4)
# The galactic coordinates are at epoch J2000. But SLALIB
# results are for B1950. So apply proper motion here.
v6o = convert.proper_motion(v6o, tpm.B1950, tpm.J2000)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB eqgal using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
def hipecleq():
"""Print summary of ECL-EQ comparison with SLALIB ecleq (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_ecleq.txt")
dummy = np.zeros((len(hip_tab['px']),))
v6l = convert.cat2v6(hip_tab['elon2'], hip_tab['elat2'], dummy, dummy,
dummy, dummy, tpm.CJ)
v6o = convert.convertv6(v6l, s1=3, s2=6)
cat = convert.v62cat(v6o, tpm.CJ)
cat = cat2array(cat)
ra_diff = np.degrees(cat['alpha']) - sla_tab[:, 0]
ra_diff = np.abs(ra_diff * 3600.0)
dec_diff = np.degrees(cat['delta']) - sla_tab[:, 1]
dec_diff = np.abs(dec_diff * 3600.0)
print("Comparison with SLALIB ecleq using HIPPARCOS data.")
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = stats.describe(ra_diff)
print(fs.format("ra_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
x = stats.describe(dec_diff)
print(fs.format("dec_diff", "arcsec", x[1][0], x[1][1], x[2],
x[3] ** 0.5))
def hipfk524():
"""Print summary of FK5-FK4 comparison with SLALIB fk524 (HIP)."""
hip_tab = get_hipdata()
sla_tab = get_sla("slalib_hip_fk524.txt")
rv = np.zeros((len(hip_tab['px'], )))
v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], hip_tab['pma'],
hip_tab['pmd'], hip_tab['px'], rv, tpm.CJ)
v6o = convert.convertv6(v6l, s1=6, s2=5, epoch=tpm.J2000)
v6o = convert.proper_motion(v6o, tpm.B1950, tpm.J2000)
cat = (tpm.v62cat(v, tpm.CB) for v in v6o)
d = cat2array(cat)
ra_diff = np.degrees(d['alpha']) - sla_tab[:, 0]
ra_diff *= 3600.0
dec_diff = np.degrees(d['delta']) - sla_tab[:, 1]
dec_diff *= 3600.0
px_diff = d['px'] * 1000.0 - sla_tab[:, 2]
pma_diff = d['pma'] * 1000.0 / 100.0 - sla_tab[:, 3]
pmd_diff = d['pmd'] * 1000.0 / 100.0 - sla_tab[:, 4]
rv_diff = d['rv'] - sla_tab[:, 5]
fs = "{0} {1}\n" + \
"Min: {2:.4f} Max: {3:.4f} \nMean: {4:.4f} Std: {5:.4f}\n"
x = [
stats.describe(np.abs(i))
for i in [ra_diff, dec_diff, px_diff, pma_diff, pmd_diff, rv_diff]
]
print("Comparison with SLALIB fk524 using HIPPARCOS data.")
for name, unit, s in zip(
["ra_diff", "dec_diff", "px_diff", "pma_diff", "pmd_diff", "rv_diff"],
[
"arsec", "arcsec", "milliarcsec", "milli-arsec/trop. yr",
"milli-arcsec/trop. yr", "km/s"
], x):
print(fs.format(name, unit, s[1][0], s[1][1], s[2], s[3]**0.5))
# Convert HIPPARCOS data using SLALIB. The output files can then be # used to compare with PyTPM. import math from pyslalib import slalib import read_data from read_data import get_hipdata import numpy as np tab = get_hipdata() # sla_fk524. # Convert HIP FK5 J2000 coordinates as given by Vizier to B1950 # coordinates using SLALIB function fk524, which takes proper motion # as well. This is NOT a transformation to HIPPARCOS frame. I just use # the coordinates given by Vizier to compare proper motion conversions # using PyTPM and SLALIB. #raj = [math.radians(i) for i in tab['raj2']] #decj = [math.radians(i) for i in tab["decj2"]] ## Milli-arcsec/Jul. year *cos(dec) into rad/Jul year. #pmaj = [math.radians(i / 1000.0 / math.cos(j) / 3600.0) # for i, j in zip(tab['pma'], decj)] #pmdj = [math.radians(i / 1000.0 / 3600.0) # for i in tab['pmd']] #pxj = [i / 1000.0 for i in tab['px']] # milli-arcsec to arc-sec. #rvj = list(0.0 for i in range(len(pxj))) # #rab = [] #decb = [] #pmab = [] #pmdb = [] #pxb = []
from __future__ import print_function
from __future__ import absolute_import
import sys
from scipy import stats
import numpy as np
import os
from read_data import testdatadir
from read_data import get_hipdata
from read_data import cat2array
# I want to run these without having to install PyTPM.
sys.path.append("..")
from pytpm import tpm, convert
# Load HIPPAROCS data and output from running SLALIB map.
hip_tab = get_hipdata()
tab = np.loadtxt(os.path.join(testdatadir, "slalib_hip_map.txt"))
rv = np.zeros_like(hip_tab['px'])
# Create V6C array from catalog data.
v6l = convert.cat2v6(hip_tab['raj2'], hip_tab['decj2'], hip_tab['pma'],
hip_tab['pmd'], hip_tab['px'], rv, tpm.CJ)
# UTC and TDB for mid-night of 2010/1/1.
utc = tpm.gcal2j(2010, 1, 1) - 0.5 # midnight
tt = tpm.utc2tdb(utc)
# Apply proper motion from J2000 to date.
v6o = convert.proper_motion(v6l, tt, tpm.J2000)
# Convert from mean equinox J2000 to true equinox and epoch of date.
