def test_aliases(self):
bo = band.band_by_name("BesU")
ba = band.band_by_name("U")
self.assertTrue(ba.is_chem_load, "The band should be loaded and with data")
self.assertItemsEqual(expected_seq=bo.wl, actual_seq=ba.wl, msg="The alias wl should be the same as original")
self.assertItemsEqual(expected_seq=bo.resp_wl, actual_seq=ba.resp_wl,
msg="The alias wl should be the same as original")
def test_spec_kcorr_zplot(self):
import matplotlib.pyplot as plt
nf, start, end = 100, 10., 1e5
wl = np.exp(np.linspace(np.log(end), np.log(start), nf))
freq = rf.val_to_hz(wl, inp="A")
Tcolor = 7.e3
sp = spectrum.SpectrumPlanck(freq, Tcolor, 'test')
bn_rest = 'B'
bn_obs = bn_rest
br = band_by_name(bn_rest)
bo = band_by_name(bn_obs)
z_arr = np.linspace(0, 0.3, 33)
kcoors = []
for z in z_arr:
k = kcorrection_spec(sp, z, br, bo)
kcoors.append(k)
fig, ax = plt.subplots(figsize=(4, 16))
ax.plot(z_arr, kcoors, marker='o', ls='', markersize=3)
# ax.set_ylim(-0., .3)
ax.grid()
ax.set_title("{} band, Tcol= {:.0f} K".format(bn_rest, Tcolor))
ax.set_xlabel('Redshift')
ax.set_ylabel('k-correction')
plt.show()
fig.savefig('k-correction.pdf')
def test_spec_kcorr_with_curve(self):
nf, start, end = 100, 10., 1e5
wl = np.exp(np.linspace(np.log(end), np.log(start), nf))
freq = rf.val_to_hz(wl, inp="A")
Tcolor = 7e3
sp = spectrum.SpectrumPlanck(freq, Tcolor, 'test')
z = 0.1
distance = 1e6 # phys.cosmology_D_by_z(z)
bn_rest = 'g'
# bn_obs = 'V'
bn_obs = bn_rest
br = band_by_name(bn_rest)
bo = band_by_name(bn_obs)
M_Q = sp.to_mag(br, z=0., d=phys.pc2cm(10.))
m_r = sp.to_mag(bo, z=z, d=phys.pc2cm(distance))
DM = phys.dist2MD(distance)
K_QR = m_r - M_Q - DM
kcorr = kcorrection_spec(sp, z, br, bo)
print("{}: z= {} K_QR= {:.5f} kcorr= {:.5f}".format(bn_rest, z, K_QR, kcorr))
self.assertAlmostEqual(K_QR, kcorr, 8, "{}: For z={} kcorr should be like K_QR. But kcorr={:.5f} K_QR= {:.5f}.".
format(bn_rest, z, kcorr, K_QR))
def test_aliases(self):
bo = band.band_by_name("BesU")
ba = band.band_by_name("U")
self.assertTrue(ba.is_load, "The band should be loaded and with data")
self.assertCountEqual(
bo.wl, ba.wl, msg="The alias wl should be the same as original")
self.assertCountEqual(
bo.resp_wl,
ba.resp_wl,
msg="The alias wl should be the same as original")
def read_curves_kurtenkov(path=sn_path):
jd = 2457000
lc_data = np.loadtxt(os.path.join(path, 'lrn_aa26564-15_p5.csv'), skiprows=2, usecols=(0, 1, 2, 3),
dtype=[('JD', '<f4'), ('b', 'S1'), ('mag', '<f4'), ('err', '<f4')])
# mshift = 24.43 # Distance Module to M31
curves = SetLightCurve('Red Nova')
bnames = np.unique(lc_data['b'])
for i, n in enumerate(bnames):
b = band.band_by_name(n)
d = lc_data[lc_data['b'] == n, ]
time = d['JD'] + jd
mags = d['mag']
errs = d['err']
# filter bad values
# is_good = mags < 30.
# t = time[is_good]
# mags = mags[is_good]
# errs = errs[is_good]
# add
lc = LightCurve(b, time, mags, errs=errs)
# lc.tshift = -tshift
# lc.mshift = -mshift
curves.add(lc)
return curves
def read_curves_kurtenkov(path=sn_path):
jd = 2457000
lc_data = np.loadtxt(os.path.join(path, 'lrn_aa26564-15_p5.csv'), skiprows=2, usecols=(0, 1, 2, 3),
dtype=[('JD', '<f4'), ('b', '|S1'), ('mag', '<f4'), ('err', '<f4')])
# mshift = 24.43 # Distance Module to M31
curves = SetLightCurve('Red Nova')
bnames = np.unique(lc_data['b'])
for i, n in enumerate(bnames):
b = band.band_by_name(n.decode("utf-8"))
d = lc_data[lc_data['b'] == n, ]
time = d['JD'] + jd
mags = d['mag']
errs = d['err']
# filter bad values
# is_good = mags < 30.
# t = time[is_good]
# mags = mags[is_good]
# errs = errs[is_good]
# add
lc = LightCurve(b, time, mags, errs=errs)
# lc.tshift = -tshift
# lc.mshift = -mshift
curves.add(lc)
return curves
def test_wl_eff(self):
# wl_eff = {'U': 3650, 'B': 4450, 'V': 5510, 'R': 6580, 'I': 8060}
wl_eff = {
'u': 3560,
'g': 4830,
'r': 6260,
'i': 7670,
'z': 8890,
'U': 3600,
'B': 4380,
'V': 5450,
'R': 6410,
'I': 7980,
'J': 12200,
'H': 16300,
'K': 21900
}
for bname, wl in wl_eff.items():
b = band.band_by_name(bname)
res = b.wl_eff_angs
print('{} {:.0f} VS {:.0f}'.format(bname, res, wl))
self.assertAlmostEqual(
res,
wl,
delta=wl * 0.03,
msg="The effective wavelength of band %s equals %f. "
"Should be %f" % (b.Name, res, wl))
def flux_to_curves(self, bands, z=0., d=phys.pc2cm(10.), magnification=1.):
"""
:param bands:
:param z:
:param d:
:param magnification:
:return:
"""
from pystella.rf.lc import SetLightCurve
from pystella.rf import band
curves = SetLightCurve(self.Name)
for bname in bands:
if isinstance(bname, str):
b = band.band_by_name(bname)
else:
b = bname
try:
lc = self.flux_to_curve(b, z=z, d=d, magnification=magnification)
curves.add(lc)
except ValueError as ex:
logger.error("Could not compute light curve {} for band {} due to {}.".
format(self.Name, bname, ex))
return curves
def mags_bands(self, bands, z=0., d=rf.pc_to_cm(10.), magnification=1.):
mags = dict((k, None) for k in bands)
for n in bands:
b = band.band_by_name(n)
mags[n] = self.flux_to_mags(b, z=z, d=d, magnification=magnification)
mags['time'] = self.Time * (1. + z)
return mags
def test_zero_point(self):
zp = 0.748 # See filters.ini
b = band.band_by_name('U')
self.assertAlmostEqual(
b.zp,
zp,
msg="Zero points of band %s equals %f. Should be %f" %
(b.Name, b.zp, zp))
def test_available_bands(self):
bands = ['U', 'B', 'V', 'R', "I"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % b)
bands = ['g', 'i', 'r', 'u', "z"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % b)
bands4 = dict(UVM2="photonUVM2.dat", UVW1="photonUVW1.dat", UVW2="photonUVW2.dat",
SwiftU="photonU_Swift.dat", SwiftB="photonB_Swift.dat", SwiftV="photonV_Swift.dat")
bands = ['SwiftU', 'SwiftB', 'SwiftV', 'UVM2', "UVW1", "UVW2"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % n)
def test_spec_kcorr_positive(self):
nf = 300
start, end = 100., 1e5
wl = np.exp(np.linspace(np.log(end), np.log(start), nf))
freq = rf.val_to_hz(wl, inp="A")
Tcolor = 7e3
sp = spectrum.SpectrumPlanck(freq, Tcolor, 'test')
z = 0.1
for bn_rest in ['U', 'B', 'V', 'R', 'u', 'g', 'r']:
bn_obs = bn_rest
br = band_by_name(bn_rest)
bo = band_by_name(bn_obs)
kcorr = kcorrection_spec(sp, z, br, bo)
print('{}: z= {} kcorr= {}'.format(bn_rest, z, kcorr))
self.assertGreater(kcorr, 0., "{}: For z={} kcorr should be > 0. But kcorr={:.5f}.".
format(bn_rest, z, kcorr))
def test_band_zp_vs_Jy(self):
bands = band.band_load_names()
for bname in bands:
b = band.band_by_name(bname)
if b.is_zp and b.is_Jy:
m_ab = Flux2MagAB(b.Jy * phys.jy_to_erg)
self.assertAlmostEqual(m_ab, b.zp, msg="Band [%s] zp and Jy should be coincide each other. "
"zp=%f, m_zp(Jy) = %f, Jy = %f"
% (b.name, b.zp, m_ab, b.Jy),
delta=0.01)
def test_spec_kcorr_z0(self):
nf, start, end = 100, 10., 1e5
wl = np.exp(np.linspace(np.log(end), np.log(start), nf))
freq = rf.val_to_hz(wl, inp="A")
Tcolor = 7e3
sp = spectrum.SpectrumPlanck(freq, Tcolor, 'test')
z = 0.
bn_rest = 'V'
# bn_obs = 'V'
for bn_rest in ['U', 'B', 'V', 'R', 'g']:
bn_obs = bn_rest
br = band_by_name(bn_rest)
bo = band_by_name(bn_obs)
kcorr = kcorrection_spec(sp, z, br, bo)
self.assertAlmostEqual(kcorr, 0., 8, "{}: For z={} kcorr should be 0. But kcorr={:.5f}.".
format(bn_rest, z, kcorr))
def plot_UBVRI():
plt.title("UBVRI filter response")
bands = dict(U="b", B="c", V="g", R="r", I="p")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_JHK():
plt.title("JHK filter response")
bands = dict(J="b", H="c", K="r")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_Misc():
plt.title('The filter responses of the different sources')
bands = dict(AtlasC="cyan", AtlasO="orange")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_SWIFT():
plt.title("SWIFT filter response")
bands = dict(UVM2="m", UVW1="r", UVW2="b", SwiftU="k", SwiftB="c", SwiftV="g")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def read_curves_tt(self):
block = self.read()
header = 'Mbol MU MB MV MI MR'.split()
curves = SetLightCurve(self.name)
time = block['time']
for col in header:
b = band.band_by_name(col.replace('M', ''))
mag = block[col]
lc = LightCurve(b, time, mag)
curves.add(lc)
return curves
def mags_bands(self, bands, z=0., d=phys.pc2cm(10.), magnification=1.):
from pystella.rf import band
mags = dict((k, None) for k in bands)
for bn in bands:
b = band.band_by_name(bn)
times, m = self.to_mags(b, z=z, d=d, magnification=magnification)
mags[bn] = m
mags['time'] = self.Time * (1. + z)
return mags
def read_curves(self):
block = self.load()
header = 'Mbol MU MB MV MI MR'.split()
curves = SetLightCurve(self.name)
time = block['time']
for col in header:
b = band.band_by_name(col.replace('M', ''))
mag = block[col]
lc = LightCurve(b, time, mag)
curves.add(lc)
return curves
def plot_JHK():
plt.title('JHK filter response')
bands = dict(J='b', H='c', K='r')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_UBVRI():
plt.title('UBVRI filter response')
bands = dict(U='b', B='c', V='g', R='r', I='p')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_Kepler():
plt.title("The Kepler Space Telescope filter responses")
bands = dict(Kepler="magenta")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_HSC():
plt.title('The Hyper Suprime-Cam(HSC) Photometric filter responses')
bands = dict(HSCg='m', HSCr='b', HSCi='r', HSCz='y', HSCY='g')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_PS1():
plt.title('The Pan-STARRS1 Photometric filter responses')
bands = dict(PS1g='m', PS1i='r', PS1r='b', PS1z='y', PS1y='g', PS1w='p')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_HSC():
plt.title("The Hyper Suprime-Cam(HSC) Photometric filter responses")
bands = dict(HSCg="m", HSCr="b", HSCi="r", HSCz="y", HSCY="g")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_griuz():
plt.title('griuz filter response')
bands = dict(g='g', i='r+', r='r', u='o', z='*')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_HST():
plt.title("The Hubble Space Telescope filter responses")
bands = dict(F105W="blue", F125W="g", F435W="skyblue", F140W="orange", F160W="r", F606W="cyan", F814W="magenta")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_Kepler():
plt.title('The Kepler Space Telescope filter responses')
bands = dict(Kepler="magenta")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_PS1():
plt.title("The Pan-STARRS1 Photometric filter responses")
bands = dict(PS1g="m", PS1i="r", PS1r="b", PS1z="y", PS1y="g", PS1w="p")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def plot_griuz():
plt.title("griuz filter response")
bands = dict(g="g", i="r+", r="r", u="o", z="*")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel("Amplitude Response")
plt.xlabel("Wave [A]")
plt.grid()
plt.show()
def test_available_bands(self):
bands = ['U', 'B', 'V', 'R', "I"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % b)
bands = ['g', 'i', 'r', 'u', "z"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % b)
bands4 = dict(UVM2="photonUVM2.dat",
UVW1="photonUVW1.dat",
UVW2="photonUVW2.dat",
SwiftU="photonU_Swift.dat",
SwiftB="photonB_Swift.dat",
SwiftV="photonV_Swift.dat")
bands = ['SwiftU', 'SwiftB', 'SwiftV', 'UVM2', "UVW1", "UVW2"]
for n in bands:
b = band.band_by_name(n)
self.assertTrue(b is not None, "Band %s does not exist." % n)
def __init__(self, b, time, mags, errs=None, tshift=0., mshift=0.):
"""Creates a Light Curve instance. Required parameters: b (band), time, mags."""
if isinstance(b, str): # convert band-name to band instance
if band.is_exist(b):
self._b = band.band_by_name(b)
else:
raise ValueError("No such band: {}".format(b))
else:
self._b = b
super().__init__(self._b.Name, time, mags, errs, tshift=tshift)
self._mshift = mshift
self._attrs = {}
def test_band_zp_vs_Jy(self):
bands = band.band_load_names()
for bname in bands:
b = band.band_by_name(bname)
if b.is_zp and b.is_Jy:
m_ab = Flux2MagAB(b.Jy * phys.jy_to_erg)
self.assertAlmostEqual(
m_ab,
b.zp,
msg="Band [%s] zp and Jy should be coincide each other. "
"zp=%f, m_zp(Jy) = %f, Jy = %f" %
(b.Name, b.zp, m_ab, b.Jy),
delta=0.01)
def table2curves(name, tbl, bands=None):
time = tbl['time']
curves = SetLightCurve(name)
if bands is None:
bands = [n for n in tbl.dtype.names if band.band_is_exist(n)]
for bname in bands:
b = band.band_by_name(bname)
mag = tbl[bname]
lc = LightCurve(b, time, mag)
curves.add(lc)
return curves
def test_band_ubvri(self):
import pylab as plt
b = band.band_by_name(band.Band.NameUBVRI)
plt.plot(b.wl * phys.cm_to_angs,
b.resp_wl,
band.colors(b.Name),
label=b.Name,
linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def read_curves(path=sn_path):
fs = {'U': 'pav_U.csv', 'B': 'pav_B.csv', 'V': 'pav_V.csv', 'R': 'pav_R.csv', 'I': 'pav_I.csv'}
fs = dict((k, os.path.join(path, v)) for k, v in fs.items())
curves = SetLightCurve('Sn87A')
for n, fname in fs.items():
data = np.loadtxt(fname, comments='#', skiprows=1, delimiter="\t", usecols=(0, 1))
b = band.band_by_name(n)
t = data[:, 0]
mags = data[:, 1]
lc = LightCurve(b, t, mags)
curves.add(lc)
return curves
def read_curves_gri(self):
block = self.read(ext='gri', line_header=1)
# header = 'L_bol Mu MB Mg Mr Mi'.split()
# header = 'MB MV'.split()
header = 'L_bol Mu MB MV Mg Mr Mi J H K '.split()
# header = 'MB MV '.split()
# header = 'L_bol L_ubvgri Mu MB MV Mg Mr Mi'.split()
curves = SetLightCurve(self.name)
time = block['time']
for col in header:
b = band.band_by_name(col.replace('M', '').replace('L_', ''))
mag = block[col]
lc = LightCurve(b, time, mag)
curves.add(lc)
return curves
def read_curves_gri(self):
block = self.load(ext='gri', line_header=1)
# header = 'L_bol Mu MB Mg Mr Mi'.split()
# header = 'MB MV'.split()
header = 'L_bol Mu MB MV Mg Mr Mi J H K '.split()
# header = 'MB MV '.split()
# header = 'L_bol L_ubvgri Mu MB MV Mg Mr Mi'.split()
curves = SetLightCurve(self.name)
time = block['time']
for col in header:
b = band.band_by_name(col.replace('M', '').replace('L_', ''))
mag = block[col]
lc = LightCurve(b, time, mag)
curves.add(lc)
return curves
def read_curves_master(path=sn_path):
header = 'V I R'
bnames = map(str.strip, header.split())
curves = SetLightCurve('Red Nova')
for i, n in enumerate(bnames):
b = band.band_by_name(n)
d = np.loadtxt(os.path.join(path, n + '.txt'),
dtype=[('JD', '<f4'), ('mag', '<f4'), ('err', '<f4')])
time = d['JD']
mags = d['mag']
errs = d['err']
lc = LightCurve(b, time, mags, errs=errs)
curves.add(lc)
return curves
def read_curves_master(path=sn_path):
header = 'V I R'
bnames = map(str.strip, header.split())
curves = SetLightCurve('Red Nova')
for i, n in enumerate(bnames):
b = band.band_by_name(n)
d = np.loadtxt(os.path.join(path, n + '.txt'),
dtype=[('JD', '<f4'), ('mag', '<f4'), ('err', '<f4')])
time = d['JD']
mags = d['mag']
errs = d['err']
lc = LightCurve(b, time, mags, errs=errs)
curves.add(lc)
return curves
def plot_bands(bands, color_dic=None):
if color_dic is None:
color_dic = band.colors()
for bname in bands:
b = band.band_by_name(bname)
plt.plot(b.wl * phys.cm_to_angs,
b.resp_wl,
color_dic[bname],
label=bname,
linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def plot_SWIFT():
plt.title('SWIFT filter response')
bands = dict(UVM2='m',
UVW1='r',
UVW2='b',
SwiftU='k',
SwiftB='c',
SwiftV='g')
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k)
plt.legend()
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def flux_to_curves(self, bands, z=0., d=rf.pc_to_cm(10.), magnification=1.):
"""
:param bands:
:param z:
:param d:
:param magnification:
:return:
"""
curves = SetLightCurve(self.name)
for n in bands:
b = band.band_by_name(n)
lc = self.flux_to_curve(b, z=z, d=d, magnification=magnification)
curves.add(lc)
return curves
def plot_HST():
plt.title('The Hubble Space Telescope filter responses')
bands = dict(F105W="blue",
F125W="g",
F435W="skyblue",
F140W="orange",
F160W="r",
F606W="cyan",
F814W="magenta")
for k, v in bands.items():
b = band.band_by_name(k)
plt.plot(b.wl * phys.cm_to_angs, b.resp_wl, v, label=k, linewidth=2)
plt.legend(loc=4)
plt.ylabel('Amplitude Response')
plt.xlabel('Wave [A]')
plt.grid(linestyle=':')
plt.show()
def epsilon(theta, freq, mag, bands, radius, dist, z):
temp_color, zeta = theta
e = 0
if temp_color < 0 or zeta < 0:
for b in bands:
e += mag[b] ** 2
return e
# sp = spectrum.SpectrumDilutePlanck(freq, temp_color, W=zeta**2)
sp = spectrum.SpectrumDilutePlanck(freq, temp_color, W=zeta ** 2)
# sp.correct_zeta(zeta)
star = Star("bb", sp)
star.set_radius_ph(radius)
star.set_distance(dist)
star.set_redshift(z)
mag_bb = {b: star.magAB(band.band_by_name(b)) for b in bands}
for b in bands:
e += (mag[b] - mag_bb[b]) ** 2
return e
def table2curves(name,
tbl,
bands=None,
colt=('time', 'JD', 'MJD'),
is_filter_zero=True):
# time = None
for nm in colt:
if nm in tbl.dtype.names:
time = tbl[nm]
break
else:
raise ValueError(
"THe table should contain a column with name in [{0}]".format(
', '.join(colt)))
curves = SetLightCurve(name)
if bands is None:
bands = [n for n in tbl.dtype.names if band.is_exist(n)]
for bname in bands:
b = band.band_by_name(bname)
mag = tbl[bname]
mask = ~np.isnan(mag)
# filter
if is_filter_zero:
mask = np.logical_and(mask,
mag != 0) # filter out values not equal 0
mask = np.logical_and(mask, mag < 99)
t = time[mask]
m = mag[mask]
for err_name in (prefix + bname for prefix in err_prefix):
if err_name in tbl.dtype.names:
err = tbl[err_name]
e = err[mask]
lc = LightCurve(b, t, m, e)
break
else:
lc = LightCurve(b, t, m)
curves.add(lc)
return curves
def read_curves(path=sn_path):
header = 'U B V R I'
cols = map(str.strip, header.split())
lc_data = np.loadtxt(os.path.join(path, '1999emubvir.dat'), skiprows=1, usecols=range(1, 12))
time = lc_data[:, 0]
curves = SetLightCurve('Sn99em')
for i, n in enumerate(cols):
b = band.band_by_name(n)
mags = lc_data[:, 2*i+1]
errs = lc_data[:, 2*i+2]
# filter bad values
is_good = mags < 30.
t = time[is_good]
mags = mags[is_good]
errs = errs[is_good]
# add
lc = LightCurve(b, t, mags, errs=errs)
curves.add(lc)
return curves
def read_curves(path=sn_path):
header = 'U B V I R'
cols = map(str.strip, header.split())
lc_data = np.loadtxt(os.path.join(path, '1999emubvir.dat'), skiprows=1, usecols=range(1, 12))
time = lc_data[:, 0]
curves = SetLightCurve('Sn99em')
for i, n in enumerate(cols):
b = band.band_by_name(n)
mags = lc_data[:, 2*i+1]
errs = lc_data[:, 2*i+2]
# filter bad values
is_good = mags < 30.
t = time[is_good]
mags = mags[is_good]
errs = errs[is_good]
# add
lc = LightCurve(b, t, mags, errs=errs)
curves.add(lc)
return curves
def read_curves_master_abs_mag(path=sn_path):
jd = 2457036
header = 'V I R'
bnames = map(str.strip, header.split())
curves = SetLightCurve('Red Nova')
for i, n in enumerate(bnames):
b = band.band_by_name(n)
time = np.loadtxt(os.path.join(path, n + '_jd.txt')) + jd
mags = np.loadtxt(os.path.join(path, n + '_mag.txt'))
errs = np.loadtxt(os.path.join(path, n + '_err.txt'))
# filter bad values
# is_good = mags < 30.
# t = time[is_good]
# mags = mags[is_good]
# errs = errs[is_good]
# add
lc = LightCurve(b, time, mags, errs=errs)
curves.add(lc)
return curves
def read_curves_master_abs_mag(path=sn_path):
jd = 2457036
header = 'V I R'
bnames = map(str.strip, header.split())
curves = SetLightCurve('Red Nova')
for i, n in enumerate(bnames):
b = band.band_by_name(n)
time = np.loadtxt(os.path.join(path, n + '_jd.txt')) + jd
mags = np.loadtxt(os.path.join(path, n + '_mag.txt'))
errs = np.loadtxt(os.path.join(path, n + '_err.txt'))
# filter bad values
# is_good = mags < 30.
# t = time[is_good]
# mags = mags[is_good]
# errs = errs[is_good]
# add
lc = LightCurve(b, time, mags, errs=errs)
curves.add(lc)
return curves
def test_band_by_name(self):
b = band.band_by_name("BesU")
self.assertTrue(b.is_chem_load, "The band should be loaded and with data")
def test_zero_point(self):
zp = 0.748 # See filters.ini
b = band.band_by_name('U')
self.assertAlmostEqual(b.zp, zp, msg="Zero points of band %s equals %f. Should be %f" % (b.name, b.zp, zp))
