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test_exposure.py
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test_exposure.py
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# -*- coding: utf-8 -*-
import exoplanet as exo
import starry
import numpy as np
import pytest
def moving_average(a, n):
"""
Compute a moving average over a window
of `n` points. Based on
https://stackoverflow.com/a/14314054
"""
if n % 2 != 0:
n += 1
ret = np.cumsum(a, dtype=float)
ret[n:] = ret[n:] - ret[:-n]
result = ret[n - 1:] / n
return np.concatenate([np.ones(n // 2) * result[0],
result,
np.ones(n // 2 - 1) * result[-1]])
def test_ld():
texp = 0.05
map = starry.Map(udeg=2)
map[1:] = [0.4, 0.26]
orbit = exo.orbits.KeplerianOrbit(period=1.0, m_star=1.0, r_star=1.0)
t = np.linspace(-0.2, 0.2, 10000)
flux = map.flux(t=t, orbit=orbit, ro=0.1).eval()
fluence_mavg = moving_average(flux, int(texp / (t[1] - t[0])))
fluence_starry = map.flux(t=t, orbit=orbit, ro=0.1,
texp=texp, oversample=30).eval()
fluence_starry_vec = map.flux(t=t, orbit=orbit, ro=0.1,
texp=np.ones_like(t) * texp, oversample=30).eval()
assert np.allclose(fluence_mavg, fluence_starry, fluence_starry_vec)
def test_ylm_occ():
texp = 0.05
map = starry.Map(ydeg=2)
np.random.seed(11)
map[1:, :] = 0.1 * np.random.randn(8)
orbit = exo.orbits.KeplerianOrbit(period=1.0, m_star=1.0, r_star=1.0)
t = np.linspace(-0.2, 0.2, 10000)
flux = map.flux(t=t, orbit=orbit, ro=0.1).eval()
xo = orbit.get_relative_position(t)[0].eval()
yo = orbit.get_relative_position(t)[1].eval()
flux = map.flux(xo=xo, yo=yo, ro=0.1)
fluence_mavg = moving_average(flux, int(texp / (t[1] - t[0])))
fluence_starry = map.flux(t=t, orbit=orbit, ro=0.1,
texp=texp, oversample=30).eval()
fluence_starry_vec = map.flux(t=t, orbit=orbit, ro=0.1,
texp=np.ones_like(t) * texp, oversample=30).eval()
assert np.allclose(fluence_mavg, fluence_starry, fluence_starry_vec)
def test_ylm_phase():
texp = 0.05
map = starry.Map(ydeg=2)
np.random.seed(11)
map[1:, :] = 0.1 * np.random.randn(8)
theta = np.linspace(0, 360, 10000)
t = np.linspace(-0.2, 0.2, 10000)
orbit = exo.orbits.KeplerianOrbit(period=1.0)
flux = map.flux(theta=theta)
window = int(texp / (t[1] - t[0]))
fluence_mavg = moving_average(flux, window)
fluence_starry = map.flux(t=t, orbit=orbit, theta=theta,
texp=texp, oversample=50).eval()
# The error is primarily coming from our moving average
# integrator, so let's be lenient
f1 = fluence_mavg[window:-window]
f2 = fluence_starry[window:-window]
assert np.allclose(f1, f2, atol=1e-4, rtol=1e-4)
if __name__ == "__main__":
test_ylm_phase()