axy.set_major_formatter(
plt.FuncFormatter(
lambda s, a: r'$%i^\circ$' % np.round(s * 180 / np.pi)))
ax.set_xlim(-np.pi, np.pi)
ax.set_ylim(-np.pi / 2, np.pi / 2)
return ax
plt.figure()
ax = mercator_axes()
ax.grid(True)
plot_tissot_ellipse(circ_long[:, None],
circ_lat,
radius,
ax=ax,
fc='k',
alpha=0.3,
lw=0)
ax.set_title('Mercator projection')
#------------------------------------------------------------
# Other projections can be done more automatically
plt.figure(figsize=(10, 8))
plt.subplots_adjust(hspace=0,
wspace=0.1,
left=0.05,
right=0.95,
bottom=0.05,
top=1.0)
# For more information, see http://astroML.github.com
import numpy as np
from matplotlib import pyplot as plt
from astroML.plotting import plot_tissot_ellipse
# ------------------------------------------------------------
# generate a latitude/longitude grid
circ_long = np.linspace(-np.pi, np.pi, 13)[1:-1]
circ_lat = np.linspace(-np.pi / 2, np.pi / 2, 7)[1:-1]
radius = 10 * np.pi / 180.0
# ------------------------------------------------------------
# Plot the built-in projections
plt.figure(figsize=(10, 8))
plt.subplots_adjust(hspace=0, wspace=0.1, left=0.05, right=0.95, bottom=0.05, top=1.0)
for (i, projection) in enumerate(["Hammer", "Aitoff", "Mollweide", "Lambert"]):
ax = plt.subplot(221 + i, projection=projection.lower())
ax.xaxis.set_major_locator(plt.FixedLocator(np.pi / 3 * np.linspace(-2, 2, 5)))
ax.xaxis.set_minor_locator(plt.FixedLocator(np.pi / 6 * np.linspace(-5, 5, 11)))
ax.yaxis.set_major_locator(plt.FixedLocator(np.pi / 6 * np.linspace(-2, 2, 5)))
ax.yaxis.set_minor_locator(plt.FixedLocator(np.pi / 12 * np.linspace(-5, 5, 11)))
ax.grid(True, which="minor")
plot_tissot_ellipse(circ_long[:, None], circ_lat, radius, ax=ax, fc="k", alpha=0.3, linewidth=0)
ax.set_title("%s projection" % projection)
plt.show()
#------------------------------------------------------------
# generate a latitude/longitude grid
circ_long = np.linspace(-np.pi, np.pi, 13)[1:-1]
circ_lat = np.linspace(-np.pi / 2, np.pi / 2, 7)[1:-1]
radius = 10 * np.pi / 180.
#------------------------------------------------------------
# plot Mercator projection: we need to set this up manually
def mercator_axes():
ax = plt.axes(aspect=1.0)
ax.set_xticks(np.pi / 6 * np.linspace(-5, 5, 11))
ax.set_yticks(np.pi / 12 * np.linspace(-5, 5, 11))
for axy in (ax.xaxis, ax.yaxis):
axy.set_major_formatter(plt.FuncFormatter(lambda s, a: r'$%i^\circ$'
% np.round(s * 180 / np.pi)))
ax.set_xlim(-np.pi, np.pi)
ax.set_ylim(-np.pi / 2, np.pi / 2)
return ax
plt.figure()
ax = mercator_axes()
ax.grid(True)
plot_tissot_ellipse(circ_long[:, None], circ_lat, radius,
ax=ax, fc='k', alpha=0.3, lw=0)
ax.set_title('Mercator projection')
plt.show()
def plot_star_projected(self):
# projections: ['Hammer', 'Aitoff', 'Mollweide', 'Lambert']
projection = 'Hammer'
# Plot the built-in projections
plt.figure(figsize=(10, 10))
ax = plt.subplot(211, projection=projection.lower())
ax2 = plt.subplot(212)
# plot latitude/longitude grid
ax.xaxis.set_major_locator(plt.FixedLocator(np.pi / 3
* np.linspace(-2, 2, 5)))
ax.xaxis.set_minor_locator(plt.FixedLocator(np.pi / 6
* np.linspace(-5, 5, 11)))
ax.yaxis.set_major_locator(plt.FixedLocator(np.pi / 6
* np.linspace(-2, 2, 5)))
ax.yaxis.set_minor_locator(plt.FixedLocator(np.pi / 12
* np.linspace(-5, 5, 11)))
ax.grid(True, which='minor', color='gray', ls=':')
ax.set_title(self.index)
# plot transit path
in_transit_times = self.lc.mask_out_of_transit(self.transit_params, oot_duration_fraction=0)['times'].jd
# transit_chord_X, transit_chord_Y, transit_chord_Z = planet_position_cartesian(in_transit_times, self.transit_params)
# transit_chord_x, transit_chord_y, transit_chord_z = project_planet_to_stellar_surface(transit_chord_X, transit_chord_Y)
# transit_chord_x_s, transit_chord_y_s, transit_chord_z_s = observer_view_to_stellar_view(transit_chord_x,
# transit_chord_y,
# transit_chord_z,
# self.transit_params,
# in_transit_times)
# transit_chord_r, transit_chord_theta, transit_chord_phi = cartesian_to_spherical(transit_chord_x_s,
# transit_chord_y_s,
# transit_chord_z_s)
latitude, longitude = times_to_occulted_lat_lon(in_transit_times, self.transit_params)
ax.scatter(longitude, latitude, color='k', s=0.7, alpha=0.5)
# plot tissot ellipses for samples from the gaussian spots
skip_every = 20000 # plots 50 ellipses per spot
times = self.chains[::skip_every, 1::3].T
amplitudes = self.chains[::skip_every, 0::3].T
n_spots = times.shape[0]
colors = ['b', 'g', 'r']
while n_spots > len(colors):
colors.extend(colors)
for i, time, amplitude in zip(range(len(times)), times, amplitudes):
X, Y, Z = planet_position_cartesian(time, self.transit_params)
spot_x, spot_y, spot_z = project_planet_to_stellar_surface(X, Y)
spot_x_s, spot_y_s, spot_z_s = observer_view_to_stellar_view(spot_x, spot_y, spot_z, self.transit_params, time)
spot_r, spot_theta, spot_phi = cartesian_to_spherical(spot_x_s, spot_y_s, spot_z_s)
longitude = spot_theta
latitude = np.pi/2 - spot_phi
alpha = np.median(amplitude)/self.transit_params.rp**2/25
radius = 2*self.transit_params.rp # from s=r*theta
plot_tissot_ellipse(longitude, latitude, radius, ax=ax, linewidth=0,
fc=colors[i], alpha=alpha)
# plot transit+spots model
model = spotted_transit_model(self.best_params, self.lc.times.jd,
self.transit_params)
individual_models = spotted_transit_model_individuals(self.best_params,
self.lc.times.jd,
self.transit_params)
errorbar_props = dict(fmt='.', color='k', capsize=0, ecolor='gray')
min_jd_int = int(self.lc.times.jd.min())
ax2.errorbar(self.lc.times.jd - min_jd_int, self.lc.fluxes,
self.lc.errors, **errorbar_props)
ax2.plot(self.lc.times.jd - min_jd_int, model, 'r', lw='3')
for individual_model in individual_models:
ax2.plot(self.lc.times.jd - min_jd_int, individual_model, 'b')
ax2.set_xlabel('JD - {0}'.format(min_jd_int))
ax2.set_ylabel('Flux')
