#!/urs/bin/env python
#
# Copyright (C) 2019, the ixpeobssim team.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
"""Spacecraft-related facilities.
"""
from __future__ import print_function, division
import numpy
from ixpeobssim.core.spline import xInterpolatedUnivariateSpline
[docs]
def period_to_omega(period):
"""Convert a characteristic period (in s) into the corresponding omega
(in rad/s).
"""
assert period > 0
return 2. * numpy.pi / period
[docs]
def dithering_pattern(amplitude=1.6, period_a=907., period_x=101., period_y=449.):
"""Implementation of the full dithering pattern as per the report by
Allyn Tennant and Kurt Dietz linked in the issue page:
https://bitbucket.org/ixpesw/ixpeobssim/issues/193
Note this returns an anonymous function that can be evaluated into a generic
array of time values, the basic usage being:
>>> t = numpy.linspace(0., 10000., 10001)
>>> dithering = dithering_pattern()
>>> x, y = dithering(t)
Arguments
---------
amplitude : float
The dithering amplitude in arcminutes.
period_a : float
The main dither period.
period_x : float
The x dithering period.
period_y : float
The y dithering period.
"""
omega_a = period_to_omega(period_a)
omega_x = period_to_omega(period_x)
omega_y = period_to_omega(period_y)
x = lambda t: amplitude * numpy.cos(omega_a * t) * numpy.cos(omega_x * t)
y = lambda t: amplitude * numpy.sin(omega_a * t) * numpy.sin(omega_y * t)
return lambda t: (x(t), y(t))
[docs]
def triangular_wave(x, amplitude, period):
"""Basic description of a (symmetric) triangular wave with a given period
and amplitude.
The basic expression is taken from
https://en.wikipedia.org/wiki/Triangular_distribution
and, in this form, the function evaluates to 0 for x = 0.
"""
half_period = 0.5 * period
# Take the input x array modulo the period.
x = numpy.mod(x, period)
# Use the wikipedia formula.
return amplitude * (half_period - numpy.abs(half_period - x)) / half_period
[docs]
def pow_triangular_wave(x, amplitude, period, exponent=0.5):
"""Modified triangual wave, where the relative values are raised to a
generic exponent, in such a way that the values of the maxima and minima are
preserved.
"""
return amplitude * (triangular_wave(x, amplitude, period) / amplitude) ** exponent
[docs]
def spiral_dithering_pattern(amplitude=1.6, period_theta=100., period_r=970.,
exponent=0.5):
"""Alternative, spiral-like dithering pattern.
"""
omega = period_to_omega(period_theta)
r = lambda t: pow_triangular_wave(t, amplitude, period_r, exponent)
x = lambda t: r(t) * numpy.cos(omega * t)
y = lambda t: r(t) * numpy.sin(omega * t)
return lambda t: (x(t), y(t))
[docs]
def pointing_splines(sc_data):
"""Build a pair of R.A. and Dec dithering splines starting from as set
of spacecraft data.
This can be used to recover the actual pointing as a function of time, given
a SC_DATA binary table.
"""
met = sc_data['MET']
ra = sc_data['RA_PNT']
dec = sc_data['DEC_PNT']
ra_spline = xInterpolatedUnivariateSpline(met, ra, xlabel='MET [s]', ylabel='Ditehring R.A.')
dec_spline = xInterpolatedUnivariateSpline(met, dec, xlabel='MET [s]', ylabel='Ditehring Dec')
return ra_spline, dec_spline
[docs]
def pointing_direction(sc_data, met):
"""Return the pointing direction at a given array of MET.
"""
ra_spline, dec_spline = pointing_splines(sc_data)
return ra_spline(met), dec_spline(met)
