def test_nolerp_basic(self):
f = Gimenez(npol=500, nthr=1, lerp=False)(self.z, self.k, self.u[0])
npt.assert_array_almost_equal(f, self.f_ref[:, 0])
for i in range(2, 4):
f = Gimenez(npol=500, nthr=1, lerp=False)(self.z, self.k,
self.u[0:i])
npt.assert_array_almost_equal(f, self.f_ref[:, 0:i])
def test_lerp_npol(self):
f = Gimenez(npol=100, nthr=1, lerp=True)(self.z, self.k, self.u[0])
npt.assert_array_almost_equal(f, self.f_ref[:, 0], decimal=4)
for i in range(2, 4):
f = Gimenez(npol=100, nthr=1, lerp=True)(self.z, self.k,
self.u[0:i])
npt.assert_array_almost_equal(f, self.f_ref[:, 0:i], decimal=4)
def test_lerp_threading(self):
for nthr in range(16):
f = Gimenez(npol=500, nthr=nthr, lerp=True)(self.z, self.k,
self.u[0])
npt.assert_array_almost_equal(f, self.f_ref[:, 0], decimal=4)
for i in range(2, 4):
f = Gimenez(npol=500, nthr=nthr, lerp=True)(self.z, self.k,
self.u[0:i])
npt.assert_array_almost_equal(f, self.f_ref[:, 0:i], decimal=4)
def test_noip_threading(self):
for nthr in range(16):
tm = Gimenez(npol=500, nthr=nthr, interpolate=False)
f = tm(self.z, self.k, self.u[0])
npt.assert_array_almost_equal(f, self.f_ref[:, 0])
for i in range(2, 4):
f = tm(self.z, self.k, self.u[0:i])
npt.assert_array_almost_equal(f, self.f_ref[:, 0:i])
import numpy as np
import matplotlib.pyplot as pl
from pytransit import Gimenez, MandelAgol, z_circular
m_mad = MandelAgol()
m_mal = MandelAgol(interpolate=True)
m_gmd = Gimenez(interpolate=False)
m_gml = Gimenez(interpolate=True)
u = np.array([[0.1, 0.1], [0.2, 0.2], [0.6, 0.3]])
t = np.linspace(-0.2, 0.2, 500)
pl.plot(t, m_mad.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi), 'b-', alpha=0.5)
pl.plot(t, m_mal.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi), 'r-', alpha=0.5)
pl.plot(t,
m_gmd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi),
'k--',
alpha=1.0)
pl.show()
import numpy as np
import matplotlib.pyplot as pl
from pytransit import Gimenez, MandelAgol
k, t0, p, a, i, e, w = 0.1, 1., 4., 8., 0.5*np.pi, 0.01, 0.5*np.pi
t = np.linspace(0.9,1.1,20)
#u = np.array([[0.04*iu, 0.025*iu, 0.01*iu] for iu in range(21)])
u = np.array([[0.04*iu, 0.025*iu] for iu in range(4)])
c = np.linspace(0,0.9,u.shape[0])*0
m = Gimenez(lerp=True, npol=100, nldc=2)
m = MandelAgol(lerp=True, nthr=4)
f = m.evaluate(t, k, u, t0, p, a, i, e, w, c=c)
fig,ax = pl.subplots(1,1,figsize=(7,7))
ax.plot(t,f + np.arange(u.shape[0])*0.00, 'k');
pl.setp(ax, ylim=(0.9875,1.011), yticks=[], xlabel='Time [d]', ylabel='Normalised flux',
title='Light curve for a set of multiple limb darkening coefficients');
fig.tight_layout()
pl.show()
import numpy as np import matplotlib.pyplot as pl from pytransit import Gimenez, MandelAgol, MandelAgolCL, z_circular mgfd = Gimenez() mgfl = Gimenez(lerp=True) macl = MandelAgolCL() mafl = MandelAgol(lerp=True) mafd = MandelAgol(lerp=False) u = [[0.1,0.0], [0.2,0.05], [0.5,0.4]] u1 = [0.5,0.4] t = np.linspace(-0.2, 0.2, 500) pl.plot(t, mafd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), ls='-', c='0.5', lw=1, alpha=0.5) #, drawstyle='steps-mid') pl.plot(t, macl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), 'b-', alpha=0.5) #, drawstyle='steps-mid') pl.plot(t, mgfd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi)+1e-4, 'b-', alpha=0.5) #, drawstyle='steps-mid') pl.plot(t, mgfl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi)+2e-4, 'b-', alpha=0.5) #, drawstyle='steps-mid') #pl.plot(t, mafl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), ls='--', c='0.5', lw=3, alpha=0.5) #, drawstyle='steps-mid') #pl.plot(t, mafl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), 'k-', alpha=0.5) #, drawstyle='steps-mid') #pl.plot(t, macl.evaluate(t, 0.1, u1, 0.0, 5, 5, 0.47*np.pi), 'b--', alpha=0.5) #, drawstyle='steps-mid') pl.ylim(0.98,1.005) pl.xlim(-0.2,0.2) pl.show()
def test_ip_np100(self):
self.tae(Gimenez(npol=100, nthr=1, interpolate=True))
import numpy as np
import matplotlib.pyplot as pl
from pytransit import Gimenez, MandelAgol, z_circular
m_mad = MandelAgol()
m_mal = MandelAgol(lerp=True)
m_gmd = Gimenez()
t = np.linspace(0, 2, 100)
pl.plot(t, z_circular(t, 1, 1, 3, 0.5 * np.pi, nthreads=4))
pl.show()
u = [[0.1, 0.1], [0.2, 0.2], [0.6, 0.3]]
#u = [0.2,0.2]
t = np.linspace(-0.2, 0.2, 500)
pl.plot(t, m_mad.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi), 'b-', alpha=0.5)
pl.plot(t, m_mal.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi), 'r-', alpha=0.5)
pl.plot(t,
m_gmd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi),
'k--',
alpha=1.0)
pl.show()
def test_gmi_special_z(self):
"""Test the interpolated Gimenez model with z in [0,k,1-k,1,1+k]"""
tm = Gimenez(interpolate=True)
npt.assert_array_almost_equal(tm(self.z, self.k, self.u),
self.f,
decimal=3)
def test_gmi_multiband(self):
self.mbt(Gimenez(interpolate=True))
def test_gmi_singleband(self):
self.sbt(Gimenez(interpolate=True))
def test_gmd_multiband(self):
self.mbt(Gimenez(interpolate=False))
def test_gmd_singleband(self):
self.sbt(Gimenez(interpolate=False))
import numpy as np
import matplotlib.pyplot as pl
from pytransit import Gimenez, MandelAgol, MandelAgolCL, z_circular
mgfd = Gimenez()
mgfl = Gimenez(lerp=True)
macl = MandelAgolCL()
mafl = MandelAgol(lerp=True)
mafd = MandelAgol(lerp=False)
u = [[0.1, 0.0], [0.2, 0.05], [0.5, 0.4]]
u1 = [0.5, 0.4]
t = np.linspace(-0.2, 0.2, 500)
pl.plot(t,
mafd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi),
ls='-',
c='0.5',
lw=1,
alpha=0.5) #, drawstyle='steps-mid')
pl.plot(t, macl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi), 'b-',
alpha=0.5) #, drawstyle='steps-mid')
pl.plot(t,
mgfd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi) + 1e-4,
'b-',
alpha=0.5) #, drawstyle='steps-mid')
pl.plot(t,
mgfl.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47 * np.pi) + 2e-4,
'b-',
alpha=0.5) #, drawstyle='steps-mid')
import numpy as np
import matplotlib.pyplot as pl
from pytransit import Gimenez, MandelAgol
k, t0, p, a, i, e, w = 0.1, 1., 4., 8., 0.5 * np.pi, 0.01, 0.5 * np.pi
t = np.linspace(0.9, 1.1, 20)
#u = np.array([[0.04*iu, 0.025*iu, 0.01*iu] for iu in range(21)])
u = np.array([[0.04 * iu, 0.025 * iu] for iu in range(4)])
c = np.linspace(0, 0.9, u.shape[0]) * 0
m = Gimenez(lerp=True, npol=100, nldc=2)
m = MandelAgol(lerp=True, nthr=4)
f = m.evaluate(t, k, u, t0, p, a, i, e, w, c=c)
fig, ax = pl.subplots(1, 1, figsize=(7, 7))
ax.plot(t, f + np.arange(u.shape[0]) * 0.00, 'k')
pl.setp(ax,
ylim=(0.9875, 1.011),
yticks=[],
xlabel='Time [d]',
ylabel='Normalised flux',
title='Light curve for a set of multiple limb darkening coefficients')
fig.tight_layout()
pl.show()
import numpy as np import matplotlib.pyplot as pl from pytransit import Gimenez, MandelAgol, z_circular m_mad = MandelAgol() m_mal = MandelAgol(lerp=True) m_gmd = Gimenez(lerp=False) m_gml = Gimenez(lerp=True) u = np.array([[0.1,0.1],[0.2,0.2],[0.6,0.3]]) t = np.linspace(-0.2, 0.2, 500) pl.plot(t, m_mad.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), 'b-', alpha=0.5) pl.plot(t, m_mal.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), 'r-', alpha=0.5) pl.plot(t, m_gmd.evaluate(t, 0.1, u, 0.0, 5, 5, 0.47*np.pi), 'k--', alpha=1.0) pl.show()
def test_noip_np100(self):
self.tae(Gimenez(npol=100, nthr=1, interpolate=False))
