def test_kcorr():
filters = ['u', 'B', 'V', 'r', 'i', 'Y', 'J', 'H']
wave0, flux0 = getSED(0, version="H3")
# redden the flux a bit
rflux = kcorr.redden(wave0, flux0, 0.1, 0.0, 0.0)
# generate artificial photometry at redshift 0.1:
mag0s = []
magzs = []
for f in filters:
mag0s.append(fset[f].synth_mag(wave0, rflux, z=0.))
magzs.append(fset[f].synth_mag(wave0, rflux, z=0.1) + 2.5 * log10(1.1))
mag0s = array([mag0s])
magzs = array([magzs])
masks = greater(magzs, 0)
k0s = array([kcorr.kcorr([0], f, f, 0.1)[0][0] for f in filters])
ks, mask, Rts, m_opts = kcorr.kcorr_mangle([0],
filters,
magzs,
masks,
filters,
0.1,
version='H3',
full_output=True,
gradient=True,
normfilter='H')
# difference in kcorrs with no mangling:
delta1 = absolute((magzs[0, :] - mag0s)[0] - k0s)
# difference in kcorrs with mangling:
delta2 = absolute((magzs[0, :] - mag0s)[0] - ks[0])
# The mangling should be better and precise
assert alltrue(delta2 < delta1) and alltrue(delta2 < 0.01)
def test_kcorr():
filters = ['u','B','V','r','i','Y','J','H']
wave0,flux0 = getSED(0, version="H3")
# redden the flux a bit
rflux = kcorr.redden(wave0,flux0, 0.1, 0.0, 0.0)
# generate artificial photometry at redshift 0.1:
mag0s = []
magzs = []
for f in filters:
mag0s.append(fset[f].synth_mag(wave0, rflux, z=0.))
magzs.append(fset[f].synth_mag(wave0, rflux, z=0.1)+2.5*log10(1.1))
mag0s = array([mag0s])
magzs = array([magzs])
masks = greater(magzs, 0)
k0s = array([kcorr.kcorr([0], f, f, 0.1)[0][0] for f in filters])
ks,mask,Rts,m_opts = kcorr.kcorr_mangle([0], filters, magzs, masks, filters,
0.1, version='H3', full_output=True, gradient=True, normfilter='H')
# difference in kcorrs with no mangling:
delta1 = absolute((magzs[0,:]-mag0s)[0] - k0s)
# difference in kcorrs with mangling:
delta2 = absolute((magzs[0,:]-mag0s)[0] - ks[0])
# The mangling should be better and precise
assert alltrue(delta2 < delta1) and alltrue(delta2 < 0.01)
def plot_kcorrs(self, device='13/XW', colors=None, symbols=None):
'''Plot the k-corrections, both mangled and un-mangled.'''
# See what filters we're going to use:
bands = self.ks.keys()
if len(bands) == 0:
return
if colors is None: colors = default_colors
if symbols is None: symbols = default_symbols
eff_wavs = []
for filter in bands:
eff_wavs.append(fset[filter].ave_wave)
eff_wavs = asarray(eff_wavs)
ids = argsort(eff_wavs)
bands = [bands[i] for i in ids]
minx = Inf
maxx = -Inf
for b in bands:
if b not in colors: colors[b] = 1
if b not in symbols: symbols[b] = 4
minx = min(minx, self.data[b].t.min())
maxx = max(maxx, self.data[b].t.max())
n_plots = len(bands)
cols = int(round(sqrt(n_plots)))
rows = (n_plots / cols)
if n_plots % cols: rows += 1
p = pygplot.Panel(1, n_plots, device=device, aspect=1.0/6*n_plots)
for b in bands:
x = self.data[b].MJD - self.Tmax
days = arange(int(x[0]), int(x[-1]), 1)
rest_days = days/(1+self.z)/self.ks_s
k,k_m = map(array, kcorr.kcorr(rest_days.tolist(), self.restbands[b], b,
self.z, self.EBVgal, 0.0, version=self.k_version))
k_m = equal(k_m, 1)
pp = pygplot.Plot(fsize=1, font=2, xlabel='Epoch (days)',
leftpad=0.1, rotylab=1, xrange=[minx,maxx])
pp.filter = b
pp.inst = self
p.add(pp)
pp.line(days[k_m],k[k_m], color=colors[b])
pp.point(x[self.ks_mask[b]], self.ks[b][self.ks_mask[b]],
symbol=symbols[b], color=colors[b], fillcolor=colors[b],
fsize=2)
pp.label(0.9, 0.9, b, just=1, vjust=1, reference='relative')
p.plots[n_plots/2].ylabel = 'K-correction'
p.plot()
p.interact(bindings={'A':plot_mangled_SED})
p.close()
return(p)
def plot_kcorrs(self, colors=None, symbols=None, outfile=None):
'''Plot the k-corrections, both mangled and un-mangled.'''
# See what filters we're going to use:
bands = self.ks.keys()
if len(bands) == 0:
return
if colors is None: colors = color_dict()
if symbols is None: symbols = symbol_dict()
eff_wavs = []
for filt in bands:
eff_wavs.append(fset[filt].ave_wave)
eff_wavs = asarray(eff_wavs)
ids = argsort(eff_wavs)
bands = [bands[i] for i in ids]
n_plots = len(bands)
p = myplotlib.PanelPlot(1, n_plots, num=112, figsize=(6,n_plots),
nymax=5, prunex=None)
p.title("Use 'm' to plot mangled SED for any point")
p.xlabel('Epoch (days)')
p.ylabel('K-corrections')
for i in range(len(bands)):
#p.axes[i].yaxis.set_major_locator(MaxNLocator(5))
b = bands[i]
x = self.data[b].MJD - self.Tmax
days = (arange(int(x[0]), int(x[-1]), 1)) #/(1+self.z)/self.ks_s
rest_days = days/(1+self.z)/self.ks_s
k,k_m = map(array, kcorr.kcorr(rest_days.tolist(), self.restbands[b],
b, self.z, self.EBVgal, 0.0, version=self.k_version))
k_m = equal(k_m, 1)
p.axes[i].filt = b
p.axes[i].inst = self
p.axes[i].plot(days[k_m],k[k_m], '-', color=colors[b])
p.axes[i].plot(x[self.ks_mask[b]], self.ks[b][self.ks_mask[b]],
symbols[b], color=colors[b])
p.axes[i].text(0.9, 0.9, b, transform=p.axes[i].transAxes,
verticalalignment='top', horizontalalignment='right')
p.set_limits(all_equal=0)
p.draw()
p.bc = ButtonClick(p.fig, bindings={'m':plot_mangled_SED})
p.bc.connect()
if outfile is not None:
p.fig.savefig(outfile)
return(p)
def plot_kcorrs(self, colors=None, symbols=None, outfile=None):
'''Plot the k-corrections, both mangled and un-mangled.'''
# See what filters we're going to use:
bands = list(self.ks.keys())
if len(bands) == 0:
return
if colors is None: colors = color_dict()
if symbols is None: symbols = symbol_dict()
eff_wavs = []
for filt in bands:
eff_wavs.append(fset[filt].ave_wave)
eff_wavs = asarray(eff_wavs)
ids = argsort(eff_wavs)
bands = [bands[i] for i in ids]
n_plots = len(bands)
p = myplotlib.PanelPlot(1, n_plots, num=112, figsize=(6,n_plots))
p.title("Use 'm' to plot mangled SED for any point")
p.xlabel('Epoch (days)')
p.ylabel('K-corrections')
for i in range(len(bands)):
#p.axes[i].yaxis.set_major_locator(MaxNLocator(5))
b = bands[i]
x = self.data[b].MJD - self.Tmax
days = (arange(int(x[0]), int(x[-1]), 1)) #/(1+self.z)/self.ks_s
rest_days = days/(1+self.z)/self.ks_s
k,k_m = list(map(array, kcorr.kcorr(rest_days.tolist(), self.restbands[b],
b, self.z, self.EBVgal, 0.0, version=self.k_version)))
k_m = equal(k_m, 1)
p.axes[i].filt = b
p.axes[i].inst = self
p.axes[i].plot(days[k_m],k[k_m], '-', color=colors[b])
p.axes[i].plot(x[self.ks_mask[b]], self.ks[b][self.ks_mask[b]],
symbols[b], color=colors[b])
p.axes[i].text(0.9, 0.9, b, transform=p.axes[i].transAxes,
verticalalignment='top', horizontalalignment='right')
p.set_limits(all_equal=0)
p.draw()
p.bc = ButtonClick(p.fig, bindings={'m':plot_mangled_SED})
p.bc.connect()
if outfile is not None:
p.fig.savefig(outfile)
return(p)
def plot_kcorrs(self, device='13/XW', colors=None, symbols=None):
'''Plot the k-corrections, both mangled and un-mangled.'''
# See what filters we're going to use:
bands = list(self.ks.keys())
if len(bands) == 0:
return
if colors is None: colors = default_colors
if symbols is None: symbols = default_symbols
eff_wavs = []
for filter in bands:
eff_wavs.append(fset[filter].ave_wave)
eff_wavs = asarray(eff_wavs)
ids = argsort(eff_wavs)
bands = [bands[i] for i in ids]
minx = Inf
maxx = -Inf
for b in bands:
if b not in colors: colors[b] = 1
if b not in symbols: symbols[b] = 4
minx = min(minx, self.data[b].t.min())
maxx = max(maxx, self.data[b].t.max())
n_plots = len(bands)
cols = int(round(sqrt(n_plots)))
rows = (n_plots / cols)
if n_plots % cols: rows += 1
p = pygplot.Panel(1, n_plots, device=device, aspect=1.0 / 6 * n_plots)
for b in bands:
x = self.data[b].MJD - self.Tmax
days = arange(int(x[0]), int(x[-1]), 1)
rest_days = days / (1 + self.z) / self.ks_s
k, k_m = list(
map(
array,
kcorr.kcorr(rest_days.tolist(),
self.restbands[b],
b,
self.z,
self.EBVgal,
0.0,
version=self.k_version)))
k_m = equal(k_m, 1)
pp = pygplot.Plot(fsize=1,
font=2,
xlabel='Epoch (days)',
leftpad=0.1,
rotylab=1,
xrange=[minx, maxx])
pp.filter = b
pp.inst = self
p.add(pp)
pp.line(days[k_m], k[k_m], color=colors[b])
pp.point(x[self.ks_mask[b]],
self.ks[b][self.ks_mask[b]],
symbol=symbols[b],
color=colors[b],
fillcolor=colors[b],
fsize=2)
pp.label(0.9, 0.9, b, just=1, vjust=1, reference='relative')
p.plots[n_plots / 2].ylabel = 'K-correction'
p.plot()
p.interact(bindings={'A': plot_mangled_SED})
p.close()
return (p)
