def plot_ubv(ax, path, jd_shift=0., mshift=0.):
colors = band.bands_colors()
curves = read_curves(path)
for lc in curves:
x = lc.Time + jd_shift
y = lc.Mag + mshift
bcolor = colors[lc.Band.Name]
ax.plot(x, y, label='%s SN 1987A' % lc.Band.Name,
ls="", color=bcolor, markersize=6, marker=".")
def plot_all(models_vels, models_dic, bands, call=None, xlim=None, ylim=None,
is_time_points=False, title='', fsave=None, bshift=None):
colors = band.bands_colors()
band_shift = dict((k, 0) for k, v in colors.items()) # no y-shift
if bshift is not None:
for k, v in bshift.items():
band_shift[k] = v
# band_shift['UVW1'] = 3
# band_shift['UVW2'] = 5
# band_shift['i'] = -1
is_vel = models_vels is not None
# setup figure
plt.matplotlib.rcParams.update({'font.size': 14})
fig = plt.figure(num=None, figsize=(12, 12), dpi=100, facecolor='w', edgecolor='k')
if is_vel:
gs1 = gridspec.GridSpec(4, 1)
axUbv = fig.add_subplot(gs1[:-1, 0])
axVel = fig.add_subplot(gs1[3, 0])
else:
gs1 = gridspec.GridSpec(1, 1)
axUbv = fig.add_subplot(gs1[0, 0])
axVel = None
gs1.update(wspace=0.3, hspace=0.3, left=0.1, right=0.95)
# plot the light curves
lcf.plot_ubv_models(axUbv, models_dic, bands, band_shift=band_shift, xlim=xlim, ylim=ylim,
is_time_points=is_time_points)
# plot callback
if call is not None:
call.plot(axUbv, {'ax2': axVel})
# finish plot
axUbv.set_ylabel('Magnitude')
axUbv.set_xlabel('Time [days]')
axUbv.legend(prop={'size': 8}, loc=4)
# ax.set_title(bset)
if title:
axUbv.set_title(title)
# plot velocities
if is_vel:
vel.plot_vels_models(axVel, models_vels, xlim=axUbv.get_xlim())
# vel.plot_vels_sn87a(axVel, z=1.49)
axVel.legend(prop={'size': 8}, loc=4)
plt.grid()
plt.show()
if fsave is not None:
print "Save plot to %s " % fsave
fig.savefig(fsave, bbox_inches='tight')
def test_fit_GP_SNRefsdal_all_lc(self):
# k = gptools.SquaredExponentialKernel(param_bounds=[(0, 1e3), (0, 100)])
# gp = gptools.GaussianProcess(k, mu=gptools.LinearMeanFunction())
# add data
dm = -29.38 # D = 7.5e6 pc
# dm = -30.4 # D = 12.e6 pc
image = "S1"
bands = ['F160W', 'F105W', 'F125W']
# bands = ('F160W','F140W','F105W', 'F125W')
curves = snrefsdal.read_curves(snrefsdal.path_data, image)
for bname in bands:
lc = curves.get(bname)
# lc.mshift = dm
t = lc.Time
y = lc.Mag
yerr = lc.MagErr
# Gaussian process
k = gptools.SquaredExponentialKernel(param_bounds=[(min(np.abs(y)), max(np.abs(y))),
(0, np.std(t))])
# k = gptools.SquaredExponentialKernel(param_bounds=[(min(np.abs(y)), max(np.abs(y))),
# (0, np.std(t))])
gp = gptools.GaussianProcess(k)
# gp = gptools.GaussianProcess(k, mu=gptools.LinearMeanFunction())
gp.add_data(t, y, err_y=yerr)
is_mcmc = True
if is_mcmc:
out = gp.predict(t, use_MCMC=True, full_MCMC=True, return_std=True,
num_proc=0, nsamp=100,
plot_posterior=True, plot_chains=False,
burn=10, thin=1)
else:
gp.optimize_hyperparameters()
out = gp.predict(t, use_MCMC=False)
y_star, err_y_star = out
# y_star, err_y_star = gp.predict(t)
fig = plt.figure()
ax = fig.add_axes((0.1, 0.3, 0.8, 0.65))
ax.invert_yaxis()
bcolor = band.bands_colors()[bname]
ax.plot(t, y, color=bcolor, label='L bol', lw=2.5)
ax.errorbar(t, y, yerr=yerr, fmt='o', color=bcolor, label='%s obs.')
#
# ax.plot(t, y_star, color='red', ls='--', lw=1.5, label='GP')
ax.plot(t, y_star, '-', color=bcolor)
ax.fill_between(t, y_star - 2 * err_y_star, y_star + 2 * err_y_star, color=bcolor, alpha=0.3)
plt.show()
def plot(ax, arg):
lw = 2.
band_shift = arg
colors = band.bands_colors()
fname = "~/Desktop/Downloads/2/100z0E60Ni_6.ph.hsc.2"
data = np.loadtxt(fname, comments='#')
fs = list('grizy')
x = data[:, 0]
for i in range(len(fs)):
y = data[:, i + 1]
bcolor = colors[fs[i]]
ax.plot(x, y, label='%s Tolstov' % lc.lbl(fs[i], band_shift),
color=bcolor, ls="-.", linewidth=lw)
def plot_ubv(ax, path, jd_shift=0., mshift=0.):
path = os.path.expanduser(path)
colors = band.bands_colors()
curves = read_curves_master(path)
for lc in curves:
x = lc.Time + jd_shift
y = lc.Mag # todo + mshift
bcolor = colors[lc.Band.Name]
ax.plot(x, y, label='%s Master' % lc.Band.Name,
ls=":", color=bcolor, markersize=7, marker="o")
ax.errorbar(x, y, yerr=lc.MagErr, color='gray', fmt='.', zorder=1)
print "jd_shift=%f mshift=%f " % (jd_shift, mshift)
curves = read_curves_kurtenkov(path)
for lc in curves:
x = lc.Time + jd_shift
y = lc.Mag + mshift
bcolor = colors[lc.Band.Name]
ax.plot(x, y, label='%s Kurtenkov' % lc.Band.Name,
ls=":", color=bcolor, markersize=7, marker="*")
ax.errorbar(x, y, yerr=lc.MagErr, color='gray', fmt='.', zorder=1)
import numpy as np
import os
import matplotlib.pyplot as plt
from matplotlib import gridspec
import pystella.rf.rad_func as rf
from pystella.model import sn_swd
from pystella.model.stella import Stella
from pystella.rf import band
from pystella.rf import extinction
from pystella.rf.lc import LightCurve
__author__ = 'bakl'
lc_colors = band.bands_colors()
lc_lntypes = dict(U="-", B="-", V="-", R="-", I="-",
UVM2="-.", UVW1="-.", UVW2="-.",
F125W="--", F160W="-.", F140W="--", F105W="-.", F435W="--", F606W="-.", F814W="--",
u="--", g="--", r="--", i="--", z="--",
bol='-')
markers = {u'D': u'diamond', 6: u'caretup', u's': u'square', u'x': u'x',
5: u'caretright', u'^': u'triangle_up', u'd': u'thin_diamond', u'h': u'hexagon1',
u'+': u'plus', u'*': u'star', u'o': u'circle', u'p': u'pentagon', u'3': u'tri_left',
u'H': u'hexagon2', u'v': u'triangle_down', u'8': u'octagon', u'<': u'triangle_left'}
markers = markers.keys()
def lbl(b, band_shift):
def test_band_colors_name(self):
bands = band.band_load_names()
for bname in bands:
self.assertTrue(bname in band.bands_colors(), "You have not color for band: %s" % bname)
