/
tess_stars2px.py
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/
tess_stars2px.py
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"""
tess_stars2px.py - High precision TESS pointing tool.
Convert target coordinates given in Right Ascension and Declination to
TESS detector pixel coordinates for the prime mission TESS observing
sectors (Year 1 & 2), Extendend mission Years 3-5.
Can also query MAST to obtain detector
pixel coordinates for a star by TIC ID or common star name (must be online for this option).
USAGE to display command line arguments:
python tess_stars2px.py -h
AUTHORS: Original programming in C and focal plane geometry solutions
by Alan Levine (MIT)
This python translation by Christopher J. Burke (MIT)
Testing and focal plane geometry refinements by Michael Fausnaugh &
Roland Vanderspek (MIT)
Testing by Thomas Barclay (NASA Goddard) &
Jessica Roberts (Univ. of Colorado)
Sesame queries by Brett Morris (UW)
Proxy Support added by Dishendra Mishra
Deprecation warnings correctsion by Ethan Kruse
Updates by Tyler Pritchard, Christina Hedges
VERSION: 0.8.1
WHAT'S NEW:
-Year 7 pointings for Sectors 84-96 now available.
-Year 6 pointings (Sectors 70-83) now available
-Deprecation Warning Corrections
-Year 5 pointings (Sectors 56-69) now available
-Added Sector Pointing override file input
Supports mission planning as well as enabling the user
to speed up the calculation by only searching a subset of all sectors
-Bug correction for aberration. Only impacts if you were using
aberration flag (-a) WITHOUT the single sector flag (-s). In other words,
does not affect users that did not use --aberrate or -aberrate with -s
NOTES:
-Pointing table is for TESS Year 1 - 5 (Sectors 1-69)
-Pointing table is unofficial, and the pointings may change.
-See https://tess.mit.edu/observations/ for latest TESS pointing table
-Pointing prediction algorithm is similar to internally at MIT for
target management. However, hard coded focal plane geometry is not
up to date and may contain inaccurate results.
-Testing shows pointing with this tool should be accurate to better than
a pixel, but without including aberration effects, ones algorithm
adopted for centroiding highly assymmetric point-spread function
at edge of
camera, and by-eye source location, a 2 pixel accuracy estimate is
warranted. There is an approximate aberration option now available
-The output pixel coordinates assume the ds9 convention with
1,1 being the middle of the lower left corner pixel.
-No corrections for velocity aberration are calculated by default.
Potentially more accurate
results can be obtained if the target RA and Declination coordinates
have aberration effects applied. An aberration approximation is available
by using the -a flag. The aberration approximation assumes Earth motion without
taking into account the TESS spacecraft motion around Earth.
-For proposals to the TESS science office or directors discretionary time,
please consult the TESS prediction webtool available at
https://heasarc.gsfc.nasa.gov/cgi-bin/tess/webtess/wtv.py
for official identification of 'observable' targets. However,
if your proposal depends on a single or few targets, then this tool is
helpful to further refine the likelihood of the target being available
on the detectors.
-The calibrated FFI fits file release at MAST and calibrated by
NASA Ames SPOC will have WCS information available to
supplant this code. The WCS generation is independent of the
focal plane geometry model employed in this code and will give
different results at the pixel level. However, the WCS information
is not available until the FFI files are released, whereas
this code can predict positions in advance of data release.
-Hard coded focal plane geometry parameters from rfpg5_c1kb.txt
TODOS:
-Time dependent Focal plane geometry
DEPENDENCIES:
python 3+
astropy
numpy
SPECIAL THANKS TO:
Includes code from the python MAST query examples
https://mast.stsci.edu/api/v0/pyex.html
IMPLEMENTATION DETAILS:
In summary, the code begins with a space craft bore site pointing in RA,
Dec, and roll angle. A series of Euler angle translation matrices
are calculated based upon the space craft bore site. Next the target
coordinates in RA and Dec are translated to the space craft bore site
frame. Next, the target coordinates are translated to each of the four
TESS camera frames. Once target coordinates are translated to the
camera frame the radial position of the target relative to the camera
center is checked to see if it is potentially in the camera field of view.
If so, the focal plane position is calculated using a radial polynomial
model with a constant term and terms the even powers (2nd ,4th , and 8th).
Rotations are applied to convert the on sky positions to the detector
readout directions.
MIT License
Copyright (c) 2018 Christopher J Burke
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
"""
import numpy as np
import os
import argparse
from astropy.coordinates import SkyCoord
import astropy.units as u
from astropy.time import Time
import sys
import datetime
import json
try: # Python 3.x
from urllib.parse import quote as urlencode
from urllib.request import urlretrieve
from urllib.parse import urlparse
except ImportError: # Python 2.x
from urllib import pathname2url as urlencode
from urllib import urlretrieve
from urlparse import urlparse
try: # Python 3.x
import http.client as httplib
except ImportError: # Python 2.x
import httplib
import scipy.optimize as opt
import base64
class Levine_FPG():
"""Al Levine Focal Plane Geometry Methods
Translated from starspx6.c
INPUT:
sc_ra_dec_roll = numpy array of the SpaceCraft boresite (sc Z-axis)
ra, dec, and roll [deg]
The roll angle is in RA, Dec space clockwise relative to the celestial
pole. roll angle = 0 [deg] implies space craft X-axis points N celestial (increasing dec)
roll angle = 90 [deg] implies sc X-axis points towards increasing/decreasing (?) RA
*** In practice there is a separate fpg file for each of the four cameras ***
rmat1[3,3] = is the rotation matrix from ra&dec to spacecraft boresite coords
rmat4[NCAM,3,3] - is the rotation matrix from ra&dec to NCAM coords
"""
parm_dict_list = [{}, {}, {}, {}]
NCAM = 4 # Number of Cameras
NCCD = 4 # Number of CCDs per Camera
def __init__(self, sc_ra_dec_roll=None, fpg_file_list=None):
self.eulcam = np.zeros((self.NCAM,3), dtype=np.double)
self.optcon = np.zeros((self.NCAM,6), dtype=np.double)
self.ccdxy0 = np.zeros((self.NCAM, self.NCCD, 2), dtype=np.double)
self.pixsz = np.zeros((self.NCAM, self.NCCD, 2), dtype=np.double)
self.ccdang = np.zeros((self.NCAM, self.NCCD), dtype=np.double)
self.ccdtilt = np.zeros((self.NCAM, self.NCCD, 2), dtype=np.double)
self.asymang = np.zeros((self.NCAM,), dtype=np.double)
self.asymfac = np.zeros((self.NCAM,), dtype=np.double)
self.rmat1 = np.zeros((3,3), dtype=np.double)
self.rmat4 = np.zeros((self.NCAM,3,3), dtype=np.double)
self.havePointing = False
# Read in the fpg parameter files
self.read_all_levine_fpg_files(fpg_file_list)
# Generate rotation matrices if ra dec and roll values given
if not sc_ra_dec_roll is None:
# go from sky to spacecraft
self.sky_to_sc_mat(sc_ra_dec_roll)
# Go from spacecraft to each camera's coords
for icam in range(self.NCAM):
cureul = self.eulcam[icam,:]
rmat2 = self.sc_to_cam_mat(cureul)
self.rmat4[icam] = np.matmul(rmat2, self.rmat1)
self.havePointing = True
def read_all_levine_fpg_files(self, fpg_file_list=None):
default_fpg_file_list = ['fpg_pars.txt-', \
'fpg_pars.txt-', \
'fpg_pars.txt-', \
'fpg_pars.txt-']
# For each camera read in the separate fpg parameter file
for icam in range(self.NCAM):
if fpg_file_list == None:
fpg_file = default_fpg_file_list[icam]
else:
fpg_file = fpg_file_list[icam]
self.read_levine_fpg_file(icam, fpg_file)
# We now have parameters for all 4 cameras in the parm_dict_list
# parse the dictionary values into the working numpy arrays
for icam in range(self.NCAM):
pd = self.parm_dict_list[icam]
self.eulcam[icam][0] = pd['ang1_cam1']
self.eulcam[icam][1] = pd['ang2_cam1']
self.eulcam[icam][2] = pd['ang3_cam1']
self.optcon[icam][0] = pd['fl_cam1']
self.optcon[icam][1] = pd['opt_coef1_cam1']
self.optcon[icam][2] = pd['opt_coef2_cam1']
self.optcon[icam][3] = pd['opt_coef3_cam1']
self.optcon[icam][4] = pd['opt_coef4_cam1']
self.optcon[icam][5] = pd['opt_coef5_cam1']
self.asymang[icam] = pd['asymang_cam1']
self.asymfac[icam] = pd['asymfac_cam1']
for iccd in range(self.NCCD):
self.ccdxy0[icam][iccd][0] = pd['x0_ccd{0:1d}_cam1'.format(iccd+1)]
self.ccdxy0[icam][iccd][1] = pd['y0_ccd{0:1d}_cam1'.format(iccd+1)]
self.pixsz[icam][iccd][0] = pd['pix_x_ccd{0:1d}_cam1'.format(iccd+1)]
self.pixsz[icam][iccd][1] = pd['pix_y_ccd{0:1d}_cam1'.format(iccd+1)]
self.ccdang[icam][iccd] = pd['ang_ccd{0:1d}_cam1'.format(iccd+1)]
self.ccdtilt[icam][iccd][0] = pd['tilt_x_ccd{0:1d}_cam1'.format(iccd+1)]
self.ccdtilt[icam][iccd][1] = pd['tilt_y_ccd{0:1d}_cam1'.format(iccd+1)]
def read_levine_fpg_file(self, icam, fpg_file):
gotParm = False
parm_dict = {}
if os.path.isfile(fpg_file):
try:
fpin = open(fpg_file, 'r')
# Read in parameters
dtypeseq = ['U20','i4','f16']
dataBlock = np.genfromtxt(fpin, dtype=dtypeseq)
parm_keys = dataBlock['f0']
parm_fitted_flags = dataBlock['f1']
parm_values = dataBlock['f2']
# Now build dictionary of the parameters
for i in range(len(parm_keys)):
parm_dict[parm_keys[i]] = parm_values[i]
self.parm_dict_list[icam] = parm_dict
gotParm = True
print('Successful Focal Plane Geometry Read From {0}'.format(fpg_file))
except:
print('Could not open {0}! Using Hard-coded Focal Plane Geometry from Levine_FPG read_levine_fpg_file()'.format(fpg_file))
# If anything goes wrong with reading in parameters revert to hard coded version
# or file was never given and default_fpg_file does not exist
if not gotParm:
#print('Using Hard-coded Focal Plane Geometry from Levine_FPG read_levine_fpg_file')
# *** For now this hard code is just a filler need to actually fill in values for all cameras separately
# to prepare parameters for dictionary
# awk -v q="'" -v d=":" '{print q $1 q d $3 ",\"}' rfpg5_c1kb.txt
if icam == 0:
parm_dict = {'ang1_cam1' : 0.101588, \
'ang2_cam1' : -36.022035, \
'ang3_cam1' : 90.048315, \
'fl_cam1' : 145.948116, \
'opt_coef1_cam1' : 1.00000140, \
'opt_coef2_cam1' : 0.24779006, \
'opt_coef3_cam1' : -0.22681254, \
'opt_coef4_cam1' : 10.78243356, \
'opt_coef5_cam1' : -34.97817276, \
'asymang_cam1' : 0.00000000, \
'asymfac_cam1' : 1.00000000, \
'x0_ccd1_cam1' : 31.573417, \
'y0_ccd1_cam1' : 31.551637, \
'pix_x_ccd1_cam1' : 0.015000, \
'pix_y_ccd1_cam1' : 0.015000, \
'ang_ccd1_cam1' : 179.980833, \
'tilt_x_ccd1_cam1' : 0.000000, \
'tilt_y_ccd1_cam1' : 0.000000, \
'x0_ccd2_cam1' : -0.906060, \
'y0_ccd2_cam1' : 31.536148, \
'pix_x_ccd2_cam1' : 0.015000, \
'pix_y_ccd2_cam1' : 0.015000, \
'ang_ccd2_cam1' : 180.000000, \
'tilt_x_ccd2_cam1' : 0.000000, \
'tilt_y_ccd2_cam1' : 0.000000, \
'x0_ccd3_cam1' : -31.652818, \
'y0_ccd3_cam1' : -31.438350, \
'pix_x_ccd3_cam1' : 0.015000, \
'pix_y_ccd3_cam1' : 0.015000, \
'ang_ccd3_cam1' : -0.024851, \
'tilt_x_ccd3_cam1' : 0.000000, \
'tilt_y_ccd3_cam1' : 0.000000, \
'x0_ccd4_cam1' : 0.833161, \
'y0_ccd4_cam1' : -31.458180, \
'pix_x_ccd4_cam1' : 0.015000, \
'pix_y_ccd4_cam1' : 0.015000, \
'ang_ccd4_cam1' : 0.001488, \
'tilt_x_ccd4_cam1' : 0.000000, \
'tilt_y_ccd4_cam1' : 0.000000}
if icam == 1:
parm_dict = {'ang1_cam1':-0.179412,\
'ang2_cam1':-12.017260,\
'ang3_cam1':90.046500,\
'fl_cam1':145.989933,\
'opt_coef1_cam1':1.00000140,\
'opt_coef2_cam1':0.24069345,\
'opt_coef3_cam1':0.15391120,\
'opt_coef4_cam1':4.05433503,\
'opt_coef5_cam1':3.43136895,\
'asymang_cam1':0.00000000,\
'asymfac_cam1':1.00000000,\
'x0_ccd1_cam1':31.653635,\
'y0_ccd1_cam1':31.470291,\
'pix_x_ccd1_cam1':0.015000,\
'pix_y_ccd1_cam1':0.015000,\
'ang_ccd1_cam1':180.010890,\
'tilt_x_ccd1_cam1':0.000000,\
'tilt_y_ccd1_cam1':0.000000,\
'x0_ccd2_cam1':-0.827405,\
'y0_ccd2_cam1':31.491388,\
'pix_x_ccd2_cam1':0.015000,\
'pix_y_ccd2_cam1':0.015000,\
'ang_ccd2_cam1':180.000000,\
'tilt_x_ccd2_cam1':0.000000,\
'tilt_y_ccd2_cam1':0.000000,\
'x0_ccd3_cam1':-31.543794,\
'y0_ccd3_cam1':-31.550699,\
'pix_x_ccd3_cam1':0.015000,\
'pix_y_ccd3_cam1':0.015000,\
'ang_ccd3_cam1':-0.006624,\
'tilt_x_ccd3_cam1':0.000000,\
'tilt_y_ccd3_cam1':0.000000,\
'x0_ccd4_cam1':0.922834,\
'y0_ccd4_cam1':-31.557268,\
'pix_x_ccd4_cam1':0.015000,\
'pix_y_ccd4_cam1':0.015000,\
'ang_ccd4_cam1':-0.015464,\
'tilt_x_ccd4_cam1':0.000000,\
'tilt_y_ccd4_cam1':0.000000}
if icam == 2:
parm_dict = {'ang1_cam1':0.066596,\
'ang2_cam1':12.007750,\
'ang3_cam1':-89.889085,\
'fl_cam1':146.006602,\
'opt_coef1_cam1':1.00000140,\
'opt_coef2_cam1':0.23452229,\
'opt_coef3_cam1':0.33552009,\
'opt_coef4_cam1':1.92009863,\
'opt_coef5_cam1':12.48880182,\
'asymang_cam1':0.00000000,\
'asymfac_cam1':1.00000000,\
'x0_ccd1_cam1':31.615486,\
'y0_ccd1_cam1':31.413644,\
'pix_x_ccd1_cam1':0.015000,\
'pix_y_ccd1_cam1':0.015000,\
'ang_ccd1_cam1':179.993948,\
'tilt_x_ccd1_cam1':0.000000,\
'tilt_y_ccd1_cam1':0.000000,\
'x0_ccd2_cam1':-0.832993,\
'y0_ccd2_cam1':31.426621,\
'pix_x_ccd2_cam1':0.015000,\
'pix_y_ccd2_cam1':0.015000,\
'ang_ccd2_cam1':180.000000,\
'tilt_x_ccd2_cam1':0.000000,\
'tilt_y_ccd2_cam1':0.000000,\
'x0_ccd3_cam1':-31.548296,\
'y0_ccd3_cam1':-31.606976,\
'pix_x_ccd3_cam1':0.015000,\
'pix_y_ccd3_cam1':0.015000,\
'ang_ccd3_cam1':0.000298,\
'tilt_x_ccd3_cam1':0.000000,\
'tilt_y_ccd3_cam1':0.000000,\
'x0_ccd4_cam1':0.896018,\
'y0_ccd4_cam1':-31.569542,\
'pix_x_ccd4_cam1':0.015000,\
'pix_y_ccd4_cam1':0.015000,\
'ang_ccd4_cam1':-0.006464,\
'tilt_x_ccd4_cam1':0.000000,\
'tilt_y_ccd4_cam1':0.000000}
if icam == 3:
parm_dict = {'ang1_cam1':0.030756,\
'ang2_cam1':35.978116,\
'ang3_cam1':-89.976802,\
'fl_cam1':146.039793,\
'opt_coef1_cam1':1.00000140,\
'opt_coef2_cam1':0.23920416,\
'opt_coef3_cam1':0.13349450,\
'opt_coef4_cam1':4.77768896,\
'opt_coef5_cam1':-1.75114744,\
'asymang_cam1':0.00000000,\
'asymfac_cam1':1.00000000,\
'x0_ccd1_cam1':31.575820,\
'y0_ccd1_cam1':31.316510,\
'pix_x_ccd1_cam1':0.015000,\
'pix_y_ccd1_cam1':0.015000,\
'ang_ccd1_cam1':179.968217,\
'tilt_x_ccd1_cam1':0.000000,\
'tilt_y_ccd1_cam1':0.000000,\
'x0_ccd2_cam1':-0.890877,\
'y0_ccd2_cam1':31.363511,\
'pix_x_ccd2_cam1':0.015000,\
'pix_y_ccd2_cam1':0.015000,\
'ang_ccd2_cam1':180.000000,\
'tilt_x_ccd2_cam1':0.000000,\
'tilt_y_ccd2_cam1':0.000000,\
'x0_ccd3_cam1':-31.630470,\
'y0_ccd3_cam1':-31.716942,\
'pix_x_ccd3_cam1':0.015000,\
'pix_y_ccd3_cam1':0.015000,\
'ang_ccd3_cam1':-0.024359,\
'tilt_x_ccd3_cam1':0.000000,\
'tilt_y_ccd3_cam1':0.000000,\
'x0_ccd4_cam1':0.824159,\
'y0_ccd4_cam1':-31.728751,\
'pix_x_ccd4_cam1':0.015000,\
'pix_y_ccd4_cam1':0.015000,\
'ang_ccd4_cam1':-0.024280,\
'tilt_x_ccd4_cam1':0.000000,\
'tilt_y_ccd4_cam1':0.000000}
self.parm_dict_list[icam] = parm_dict
def sky_to_sc_mat(self, sc_ra_dec_roll):
"""Calculate the rotation matrix that will convert a vector in ra&dec
into the spacecraft boresite frame
"""
deg2rad = np.pi / 180.0
# Define the 3 euler angles of rotation
xeul = np.zeros((3,), dtype=np.double)
xeul[0] = deg2rad * sc_ra_dec_roll[0]
xeul[1] = np.pi/2.0 - deg2rad*sc_ra_dec_roll[1]
xeul[2] = deg2rad * sc_ra_dec_roll[2] + np.pi
# Generate the rotation matrix from the 3 euler angles
self.rmat1 = self.eulerm323(xeul)
def sc_to_cam_mat(self, eul):
"""Calculate the rotation matrix that will convert a vector in spacecraft
into the a camera's coords
"""
deg2rad = np.pi / 180.0
# Generate the rotation matrix from the 3 euler angles
xeul = deg2rad * eul
return self.eulerm323(xeul)
def eulerm323(self, eul):
mat1 = self.rotm1(2, eul[0])
mat2 = self.rotm1(1, eul[1])
mata = np.matmul(mat2, mat1)
mat1 = self.rotm1(2, eul[2])
rmat = np.matmul(mat1, mata)
return rmat
def rotm1(self, ax, ang):
mat = np.zeros((3,3), dtype=np.double)
n1 = ax
n2 = np.mod((n1+1), 3)
n3 = np.mod((n2+1), 3)
sinang = np.sin(ang)
cosang = np.cos(ang)
mat[n1][n1] = 1.0
mat[n2][n2] = cosang
mat[n3][n3] = cosang
mat[n2][n3] = sinang
mat[n3][n2] = -sinang
return mat
def sphereToCart(self, ras, decs):
""" Convert 3d spherical coordinates to cartesian
"""
deg2rad = np.pi / 180.0
rarads = deg2rad * ras
decrads = deg2rad * decs
sinras = np.sin(rarads)
cosras = np.cos(rarads)
sindecs = np.sin(decrads)
cosdecs = np.cos(decrads)
vec0s = cosras * cosdecs
vec1s = sinras * cosdecs
vec2s = sindecs
return vec0s, vec1s, vec2s
def cartToSphere(self, vec):
ra = 0.0
dec = 0.0
norm = np.sqrt(np.sum(vec*vec))
if (norm > 0.0):
dec = np.arcsin(vec[2] / norm)
if (not vec[0] == 0.0) or (not vec[1] == 0.0):
ra = np.arctan2(vec[1], vec[0])
ra = np.mod(ra, 2.0*np.pi)
return ra, dec
def star_in_fov(self, lng, lat):
deg2rad = np.pi / 180.0
inView = False
if lat > 70.0:
vec0, vec1, vec2 = self.sphereToCart(lng, lat)
vec = np.array([vec0, vec1, vec2], dtype=np.double)
norm = np.sqrt(np.sum(vec*vec))
if norm > 0.0:
vec = vec / norm
xlen = np.abs(np.arctan(vec[0]/vec[2]))
ylen = np.abs(np.arctan(vec[1]/vec[2]))
if (xlen <= (12.5 * deg2rad)) and (ylen <= (12.5 * deg2rad)):
inView = True
return inView
def optics_fp(self, icam, lng_deg, lat_deg):
deg2rad = np.pi / 180.0
thetar = np.pi / 2.0 - (lat_deg * deg2rad)
tanth = np.tan(thetar)
cphi = np.cos(deg2rad*lng_deg)
sphi = np.sin(deg2rad*lng_deg)
rfp0 = self.optcon[icam][0]*tanth
noptcon = len(self.optcon[icam])
ii = np.arange(1, noptcon)
rfp = np.sum(self.optcon[icam][1:] * np.power(tanth, 2.0*(ii-1)))
xytmp = np.zeros((2,), dtype=np.double)
xytmp[0] = -cphi*rfp0*rfp
xytmp[1] = -sphi*rfp0*rfp
return self.make_az_asym(icam, xytmp)
def fp_optics(self, icam, xyfp):
deg2rad = np.pi/ 180.0
xy = self.rev_az_asym(icam, xyfp)
rfp_times_rfp0 = np.sqrt(xy[0]*xy[0] + xy[1]*xy[1])
phirad = np.arctan2(-xy[1], -xy[0])
phideg = phirad / deg2rad
if (phideg < 0.0):
phideg += 360.0
thetarad = self.tanth_of_r(icam, rfp_times_rfp0)
thetadeg = thetarad / deg2rad
lng_deg = phideg
lat_deg = 90.0 - thetadeg
return lng_deg, lat_deg
def r_of_tanth(self, icam, z):
tanth = np.tan(z)
rfp0 = self.optcon[icam][0]*tanth
noptcon = len(self.optcon[icam])
ii = np.arange(1, noptcon)
rfp = np.sum(self.optcon[icam][1:] * np.power(tanth, 2.0*(ii-1)))
return rfp0*rfp
def tanth_of_r(self, icam, rprp0):
if np.abs(rprp0) > 1.0e-10:
c0 = self.optcon[icam][0]
zi = np.arctan(np.sqrt(rprp0) / c0)
def minFunc(z, icam, rp):
rtmp = self.r_of_tanth(icam, z)
return (rtmp - rprp0)*(rtmp - rprp0)
optResult = opt.minimize(minFunc, [zi], \
args=(icam, rprp0), method='Nelder-Mead', \
tol=1.0e-10, \
options={'maxiter':500})
#print(optResult)
return optResult.x[0]
else:
return 0.0
def make_az_asym(self, icam, xy):
xyp = self.xyrotate(self.asymang[icam], xy)
xypa = np.zeros_like(xyp)
xypa[0] = self.asymfac[icam] * xyp[0]
xypa[1] = xyp[1]
xyout = self.xyrotate(-self.asymang[icam], xypa)
return xyout
def rev_az_asym(self, icam, xyin):
xyp = self.xyrotate(self.asymang[icam], xyin)
xypa = np.zeros_like(xyp)
xypa[0] = xyp[0] / self.asymfac[icam]
xypa[1] = xyp[1]
xyout = self.xyrotate(-self.asymang[icam], xypa)
return xyout
def xyrotate(self, angle_deg, xin):
deg2rad = np.pi / 180.0
ca = np.cos(deg2rad * angle_deg)
sa = np.sin(deg2rad * angle_deg)
xyout = np.zeros_like(xin)
xyout[0] = ca*xin[0] + sa*xin[1]
xyout[1] = -sa*xin[0] + ca*xin[1]
return xyout
def mm_to_pix(self, icam, xy):
"""Convert focal plane to pixel location also need to add in the
auxillary pixels added into FFIs
"""
CCDWD_T=2048
CCDHT_T=2058
ROWA=44
ROWB=44
COLDK_T=20
xya = np.copy(xy)
xyb = np.zeros_like(xya)
ccdpx = np.zeros_like(xya)
fitpx = np.zeros_like(xya)
if xya[0] >= 0.0:
if xya[1] >= 0.0:
iccd = 0
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = (CCDWD_T - ccdpx[0]) + CCDWD_T + 2*ROWA + ROWB - 1.0
fitpx[1] = (CCDHT_T - ccdpx[1]) + CCDHT_T + 2*COLDK_T - 1.0
else:
iccd = 3
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = ccdpx[0] + CCDWD_T + 2*ROWA + ROWB
fitpx[1] = ccdpx[1]
else:
if xya[1] >= 0.0:
iccd = 1
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = (CCDWD_T - ccdpx[0]) + ROWA - 1.0
fitpx[1] = (CCDHT_T - ccdpx[1]) + CCDHT_T + 2*COLDK_T - 1.0
else:
iccd = 2
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = ccdpx[0] + ROWA
fitpx[1] = ccdpx[1]
return iccd, ccdpx, fitpx
def mm_to_pix_single_ccd(self, icam, xy, iccd):
"""Convert focal plane to pixel location also need to add in the
auxillary pixels added into FFIs
"""
CCDWD_T=2048
CCDHT_T=2058
ROWA=44
ROWB=44
COLDK_T=20
xya = np.copy(xy)
xyb = np.zeros_like(xya)
ccdpx = np.zeros_like(xya)
fitpx = np.zeros_like(xya)
if iccd == 0:
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = (CCDWD_T - ccdpx[0]) + CCDWD_T + 2*ROWA + ROWB - 1.0
fitpx[1] = (CCDHT_T - ccdpx[1]) + CCDHT_T + 2*COLDK_T - 1.0
if iccd == 3:
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = ccdpx[0] + CCDWD_T + 2*ROWA + ROWB
fitpx[1] = ccdpx[1]
if iccd == 1:
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = (CCDWD_T - ccdpx[0]) + ROWA - 1.0
fitpx[1] = (CCDHT_T - ccdpx[1]) + CCDHT_T + 2*COLDK_T - 1.0
if iccd == 2:
xyb[0] = xya[0] - self.ccdxy0[icam][iccd][0]
xyb[1] = xya[1] - self.ccdxy0[icam][iccd][1]
xyccd = self.xyrotate(self.ccdang[icam][iccd], xyb)
ccdpx[0] = (xyccd[0] / self.pixsz[icam][iccd][0]) - 0.5
ccdpx[1] = (xyccd[1] / self.pixsz[icam][iccd][1]) - 0.5
fitpx[0] = ccdpx[0] + ROWA
fitpx[1] = ccdpx[1]
return ccdpx, fitpx
def pix_to_mm_single_ccd(self, icam, ccdpx, iccd):
"""convert pixel to mm focal plane position
"""
xyccd = np.zeros_like(ccdpx)
xyccd[0] = (ccdpx[0] + 0.5) * self.pixsz[icam][iccd][0]
xyccd[1] = (ccdpx[1] + 0.5) * self.pixsz[icam][iccd][1]
xyb = self.xyrotate(-self.ccdang[icam][iccd], xyccd)
xya = np.zeros_like(xyb)
xya[0] = xyb[0] + self.ccdxy0[icam][iccd][0]
xya[1] = xyb[1] + self.ccdxy0[icam][iccd][1]
return xya
def radec2pix(self, ras, decs):
""" After the rotation matrices are defined to the actual
ra and dec to pixel coords mapping
"""
nStar = len(ras)
inCamera = np.array([], dtype=int)
ccdNum = np.array([], dtype=int)
fitsxpos = np.array([], dtype=np.double)
fitsypos = np.array([], dtype=np.double)
ccdxpos = np.array([], dtype=np.double)
ccdypos = np.array([], dtype=np.double)
deg2rad = np.pi / 180.0
if self.havePointing == True:
# Convert ra and dec spherical coords to cartesian
vec0s, vec1s, vec2s = self.sphereToCart(ras, decs)
for i in range(nStar):
curVec = np.array([vec0s[i], vec1s[i], vec2s[i]], dtype=np.double)
# Find the new vector in all cameras
for j in range(self.NCAM):
# Do the rotation from ra dec coords to camera coords
camVec = np.matmul(self.rmat4[j], curVec)
# Get the longitude and latitude of camera coords position
lng, lat = self.cartToSphere(camVec)
lng = lng / deg2rad
lat = lat / deg2rad
if self.star_in_fov(lng, lat):
# Get the xy focal plane position in mm
xyfp = self.optics_fp(j, lng, lat)
# Convert mm to pixels
iccd, ccdpx, fitpx = self.mm_to_pix(j, xyfp)
inCamera = np.append(inCamera, j+1) # Als code is base 0 convert to base 1
ccdNum = np.append(ccdNum, iccd+1) # ""
fitsxpos = np.append(fitsxpos, fitpx[0])
fitsypos = np.append(fitsypos, fitpx[1])
ccdxpos = np.append(ccdxpos, ccdpx[0])
ccdypos = np.append(ccdypos, ccdpx[1])
else:
print('Spacecraft Pointing Not specified!')
return inCamera, ccdNum, fitsxpos, fitsypos, ccdxpos, ccdypos
def radec2pix_nocheck_single(self, ras, decs, cam, iccd):
"""
ra and dec to pixel coords mapping
With no checks and assuming a single target and detector
Supports minimizing for reverse mode
"""
deg2rad = np.pi / 180.0
# Convert ra and dec spherical coords to cartesian
vec0s, vec1s, vec2s = self.sphereToCart(ras, decs)
curVec = np.array([vec0s, vec1s, vec2s], dtype=np.double)
j = cam
# Do the rotation from ra dec coords to camera coords
camVec = np.matmul(self.rmat4[j], curVec)
# Get the longitude and latitude of camera coords position
lng, lat = self.cartToSphere(camVec)
lng = lng / deg2rad
lat = lat / deg2rad
# Get the xy focal plane position in mm
xyfp = self.optics_fp(j, lng, lat)
# Convert mm to pixels
ccdpx, fitpx = self.mm_to_pix_single_ccd(j, xyfp, iccd)
ccdNum = iccd+1
fitsxpos = fitpx[0]
fitsypos = fitpx[1]
ccdxpos = ccdpx[0]
ccdypos = ccdpx[1]
return ccdNum, fitsxpos, fitsypos, ccdxpos, ccdypos, lat
def pix2radec_nocheck_single(self, cam, iccd, ccdpx):
"""
Reverse the transform going from pixel coords to Ra & Dec
"""
deg2rad = np.pi / 180.0
# Convert pixels to mm
xyfp = self.pix_to_mm_single_ccd(cam, ccdpx, iccd)
lng_deg, lat_deg = self.fp_optics(cam, xyfp)
vcam0, vcam1, vcam2 = self.sphereToCart(lng_deg, lat_deg)
vcam = np.array([vcam0, vcam1, vcam2], dtype=np.double)
curVec = np.matmul(np.transpose(self.rmat4[cam]), vcam)
ra, dec = self.cartToSphere(curVec)
return ra/deg2rad, dec/deg2rad
class TESS_Spacecraft_Pointing_Data:
#Hard coded spacecraft pointings by Sector
# When adding sectors the arg2 needs to end +1 from sector
# due to the np.arange function ending at arg2-1
sectors = np.arange(1,97, dtype=int)
# Arrays are broken up into the following sectors:
# Line 1: Sectors 1-5 Start Year 1
# Line 2: Secotrs 6-9
# Line 3: Sectors 10-13 End Year 1
# Line 4: Sectors 14-17 Start Year 2
# Line 5: Sectors 18-22
# Line 6: Sectors 23-26 End Year 2
# Line 7: Sectors 27-30 Star Year 3
# Line 8: Sectors 31-34
# Line 9: Sectors 35-38
# Line 10: Sectors 39 End Year 3
# Line 11: Sectors 40-43 Star Year 4
# Line 12: S 44-47
# Line 13: S 48-51
# Line 14: S 52-55 END YEAR 4
# Line 15: S 56-59 START YEAR 5
# Line 16: S 60-63
# Line 17: S 64-67
# Line 18: S 68-69 END Year 5
# Line 19: S 70-72 START Year 6
# Line 20: S 73-76
# Line 21: S 77-80
# Line 22: S 81-83 END Year 6
# Line 23: S 84-87 START Year 7
# Line 24: S 88-90
# Line 25: S 91-93
# Line 26: S 94-96 END Year 7
### NOTE IF you add Sectors be sure to update the allowed range
### for sectors in argparse arguments!!!
ras = np.array([352.6844, 16.5571, 36.3138, 55.0070, 73.5382,\
92.0096,110.2559,128.1156,145.9071,\
165.0475,189.1247,229.5885,298.6671,\
276.7169,280.3985,282.4427,351.2381,\
16.1103, 60.2026,129.3867,171.7951,197.1008,\
217.2879,261.4516,265.6098,270.1381,\
326.8525,357.2944, 18.9190, 38.3564,\
57.6357, 77.1891, 96.5996,115.2951,\
133.2035,150.9497,170.2540,195.7176,\
242.1981,\
273.0766,277.6209, 13.0140, 49.5260,\
89.6066,130.2960,157.6997,143.3807,\
179.4254,202.6424,221.8575,239.4257,\
266.3618,270.8126,290.1210,307.8655,\
324.2778,344.2275, 9.3118, 52.9755,\
125.6742,118.0446,135.2412,153.0613,\
173.2653,201.6239,259.1702,326.7691,\
359.2829, 20.0449,\
24.0414, 77.3449, 133.7631, \
80.6709, 261.2194, 254.9290, 253.5335, \
255.8590, 260.4232, 266.0595, 275.6978, \
292.5709, 309.1299, 325.8933, \
343.8717, 5.8776, 42.6741, 97.9629, \
116.8315, 135.8409, 155.0705, \
227.0409, 311.9633, 260.5165, \
323.4700, 355.7011, 16.7112], dtype=float)
decs = np.array([-64.8531,-54.0160,-44.2590,-36.6420,-31.9349,\
-30.5839,-32.6344,-37.7370,-45.3044,\
-54.8165,-65.5369,-75.1256,-76.3281,\
62.4756, 64.0671, 66.1422, 57.8456,\
67.9575, 76.2343, 75.2520, 65.1924, 53.7434,\
43.8074, 63.1181, 61.9383, 61.5637,\
-72.4265,-63.0056,-52.8296,-43.3178,\
-35.7835,-31.3957,-30.7848,-33.7790,\
-39.6871,-47.7512,-57.3725,-67.8307,\
-76.3969,\
61.7450, 62.7640, 6.3337, 18.9737,\
24.1343, 19.0181, 10.0922, 73.1125,\
62.1038, 50.9532, 41.7577, 35.2333,\
61.8190, 61.5761, 32.6073, 37.6464,\
46.3448, 56.4121, 67.6524, 77.1746,\
77.3113,-36.0902,-42.2415,-50.6996,\
-60.8650,-71.5724,-78.7974,-74.2796,\
-64.2357,-54.2315,\
9.2629, 22.2220, 16.6536, \
78.8333, 72.3020, 69.9395, 66.8396, \
63.8557, 61.5745, 60.3042, 32.2323, \
34.6859, 39.7760, 47.1247, \
56.2316, 66.3525, 75.8930, -32.3927, \
-35.7542, -42.4981, -51.7243, \
-16.8742, -17.1415, -78.8295, \
-74.8966, -65.7252, -55.9356], dtype=float)
rolls = np.array([222.1532,220.4335,213.0384,202.8302,191.0517,\
178.6367,166.4476,155.3091,145.9163,\
139.1724,138.0761,153.9773,198.9378,\
32.2329, 55.4277, 79.4699, 41.9686,\
40.5453, 19.6463,334.5689,317.9495,319.6992,\
327.4246,317.2624,339.5293, 0.6038,\
214.5061,222.5216,219.7970,212.0441,\
201.2334,188.6263,175.5369,163.1916,\
152.4006,143.7306,138.1685,139.3519,\
161.5986,\
14.1539, 37.2224,292.8009,284.9617,\
270.1557,255.0927,248.4063,327.1020,\
317.4166,321.3516,329.7340,339.8650,\
343.1429, 3.6838, 13.4565, 24.5369,\
36.2524, 44.0100, 45.3615, 26.5121,\
337.3244, 162.2198,151.5884,142.7405,\
137.2810, 140.7443,173.9147,217.4678,\
226.0975, 222.7721,\
291.2985,274.9979,254.0304,\
8.0330,213.9191,247.4882,276.6424,\
302.3416,325.7085,347.5089,5.4938,\
17.1317,27.7999,37.0453, \
43.9159, 45.8046, 32.5811, 175.9167, \
163.0201, 151.2486, 141.9459, \
254.2704, 285.4229, 174.8522, \
215.8459, 225.9414, 223.7615], dtype=float)
midtimes = np.array([ 2458339.652778, 2458368.593750, 2458396.659722, 2458424.548611, 2458451.548611, \
2458478.104167, 2458504.697917, 2458530.256944, 2458556.722222, \
2458582.760417, 2458610.774306, 2458640.031250, 2458668.618056, \
2458697.336806, 2458724.934028, 2458751.649306, 2458777.722222, \
2458803.440972, 2458828.958333, 2458856.388889, 2458884.916667, 2458913.565972, \
2458941.829861, 2458969.263889, 2458996.909722, 2459023.107639, \
2459049.145833, 2459075.166667, 2459102.319444, 2459130.201389, \
2459158.854167, 2459186.940972, 2459215.427083, 2459241.979167, \
2459268.579861, 2459295.301177, 2459322.577780, 2459349.854382, \
2459377.130985, \
2459404.407588, 2459431.684191, 2459458.960794, 2459486.237397, \
2459513.514000, 2459540.790602, 2459568.067205, 2459595.343808, \
2459622.620411, 2459649.897014, 2459677.173617, 2459704.450219, \
2459731.726822, 2459759.003425, 2459786.280028, 2459813.556631, \
2459840.833234, 2459868.109837, 2459895.386439, 2459922.663042, \
2459949.939645, 2459977.216248, 2460004.492851, 2460031.769454, \
2460059.046057, 2460086.322659, 2460113.599262, 2460140.875865, \
2460168.152468, 2460195.429071,\
2460220.5, 2460246.5, 2460272.5,\
2460299 , 2460326 , 2460353 , 2460381 ,\
2460409.5, 2460437.5, 2460465.5, 2460493 ,\
2460519.5, 2460545.5, 2460571.5, \
2460597. , 2460622.5, 2460649. , 2460676. , \
2460703.5, 2460732. , 2460760.5, \
2460788.5, 2460816. , 2460842.5, \
2460868.5, 2460894.5, 2460920.5], dtype=float)
camSeps = np.array([36.0, 12.0, 12.0, 36.0], dtype=float)
def __init__(self, trySector=None, fpgParmFileList=None, sectorOverrideFile=None):
# Convert S/C boresite pointings to ecliptic coords for each camera
# if sectorOverrideFile is set read in the sector pointing overrides
# This can be used for mission planning or for speed ups
# by allowing the user to put in a custom list of sectors that they want
# to run over
if not sectorOverrideFile is None:
try:
dataBlock = np.genfromtxt(sectorOverrideFile, dtype=['i4','f8','f8','f8'])
self.sectors = np.array(dataBlock['f0'])
self.ras = np.array(dataBlock['f1'])
self.decs = np.array(dataBlock['f2'])
self.rolls = np.array(dataBlock['f3'])
# just put something into midtimes at this point should never get used
# because aberration is not supported with sector override file
medmidtimes = np.median(self.midtimes)
self.midtimes = np.full_like(self.ras, medmidtimes)
except:
print('There was a problem reading the Sector Override File. Exiting!')
sys.exit(1)
# If trySector is set only keep the single requested sector
if not trySector is None:
idx = np.where(self.sectors == trySector)[0]
# Check for condition where the requested sector is not in list!
if len(idx) == 0:
print('Could not find requested sector: {0:d} in the available sector pointing data'.format(trySector))
sys.exit(1)
self.sectors = self.sectors[idx]
self.ras = self.ras[idx]
self.decs = self.decs[idx]
self.rolls = self.rolls[idx]
self.midtimes = self.midtimes[idx]
nPoints = len(self.sectors)
self.camRa = np.zeros((4, nPoints), dtype=float)
self.camDec = np.zeros((4, nPoints), dtype=float)
# Convert S/C boresite ra and dec to camera ra and dec
for iPnt in range(nPoints):
curra = self.ras[iPnt]
curdec = self.decs[iPnt]
curroll = self.rolls[iPnt]
camposangs = np.array([180.0-curroll, 180.0-curroll, \
360.0-curroll, 360.0-curroll])
camposangs = np.mod(camposangs, 360.0)
for iCam in range(4):
# Need to correct s/c roll to posang
pang = camposangs[iCam]
camra, camdec = get_radec_from_posangsep(curra, curdec, \
pang, self.camSeps[iCam])
self.camRa[iCam,iPnt] = camra
self.camDec[iCam,iPnt] = camdec
# Just for testing camera coords
# compare to published values
# print('{:d} {:d} {:f} {:f}'.format(self.sectors[iPnt],iCam+1,\
# self.camRa[iCam,iPnt], self.camDec[iCam,iPnt]))
# For every pointing make a Levine pointing class object
self.fpgObjs = []
fpg_file_list=None
if not fpgParmFileList is None:
fpg_file_list=fpgParmFileList
for iPnt in range(nPoints):
sc_ra_dec_roll = np.array([self.ras[iPnt], self.decs[iPnt], self.rolls[iPnt]])
self.fpgObjs.append(Levine_FPG(sc_ra_dec_roll, fpg_file_list=fpg_file_list))