def bin_shift_and_tilt_spline(self, order, singlebin, binSize, multiple, shift, sigma, slope, offset, minuit, **kwargs):
"""trying to smooth, interpolate, and integrate the fit."""
mask = self.Orders[order]['mask']
ok = reduce(np.logical_and, [self.Orders[order][binSize][singlebin]['ok'], mask])
iok = self.Orders[order][binSize][singlebin]['iok']
iow = self.Orders[order]['iow'][iok]
iof = self.Orders[order]['iof'][iok]
wav = self.Orders[order]['wav'][ok]
flx = self.Orders[order]['flx'][ok]
err = self.Orders[order]['err'][ok]
con = self.Orders[order]['con'][ok]
pix = self.Orders[order]['pix'][ok]
overflx = multiple * slope_to_array(slope,
wav + shift,
interp.interp_spline(wav + shift,
iow,
convolve.convolve_constant_dv(iow,
iof,
vfwhm=sigma)
)
) + offset
chi_square = np.sum((overflx - flx/con)**2 / (err/con)**2)
if minuit == 0:
return chi_square
else:
return chi_square, wav, flx/con, err/con, pix, overflx
def bin_shift_and_tilt_spline(self, order, singlebin, binSize, multiple,
shift, sigma, slope, offset, minuit,
**kwargs):
"""trying to smooth, interpolate, and integrate the fit."""
mask = self.Orders[order]['mask']
ok = reduce(np.logical_and,
[self.Orders[order][binSize][singlebin]['ok'], mask])
iok = self.Orders[order][binSize][singlebin]['iok']
iow = self.Orders[order]['iow'][iok]
iof = self.Orders[order]['iof'][iok]
wav = self.Orders[order]['wav'][ok]
flx = self.Orders[order]['flx'][ok]
err = self.Orders[order]['err'][ok]
con = self.Orders[order]['con'][ok]
pix = self.Orders[order]['pix'][ok]
overflx = multiple * slope_to_array(
slope,
interp.interp_spline(
wav + shift, iow,
convolve.convolve_constant_dv(iow, iof, vfwhm=sigma))) + offset
chi_square = np.sum((overflx - flx / con)**2 / (err / con)**2)
if minuit == 0:
return chi_square
else:
return chi_square, wav, flx / con, err / con, pix, overflx
def readLSF(grating, dw_new=None):
""" Read the COS line spread function, optionally interpolated to
a new pixel width.
Parameters
----------
grating : str, {'G130M', 'G160M', 'NUV'}
Either 'NUV' for all near UV gratings, or the name of the far UV
COS grating.
dw_new : float
The new pixel width in Angstroms. Default is `None`, which
returns the original LSF.
Returns
-------
LSF, wa : ndarrays of shape (N,)
The new LSF and the wavelength offsets from the line centre.
"""
# see if we've already calculated it
try:
#print grating, dw, 'cached!'
return cacheLSF[grating, dw_new]
except KeyError:
pass
oldLSF = readtxt(datapath + '/LSF/%s.txt' % grating, readnames=1)
dw_orig = dict(G130M=0.00997, G160M=0.01223, NUV=0.390)
wa0 = oldLSF.relpix * dw_orig[grating]
if dw_new is None:
return oldLSF, wa0
t = np.arange(0, wa0[-1], dw_new)
wa1 = np.concatenate([-t[::-1][:-1], t])
wavs = oldLSF.dtype.names[1:]
newLSF = []
for w in wavs:
newLSF.append(interp_spline(wa1, wa0, oldLSF[w]))
t = np.arange(len(wa1) // 2 + 1)
newpix = np.concatenate([-t[::-1][:-1], t])
#import pdb; pdb.set_trace()
newLSF = np.rec.fromarrays([newpix] + newLSF, names=oldLSF.dtype.names)
cacheLSF[grating, dw_new] = newLSF, wa1
return newLSF, wa1
def readLSF(grating, dw_new=None):
""" Read the COS line spread function, optionally interpolated to
a new pixel width.
Parameters
----------
grating : str, {'G130M', 'G160M', 'NUV'}
Either 'NUV' for all near UV gratings, or the name of the far UV
COS grating.
dw_new : float
The new pixel width in Angstroms. Default is `None`, which
returns the original LSF.
Returns
-------
LSF, wa : ndarrays of shape (N,)
The new LSF and the wavelength offsets from the line centre.
"""
# see if we've already calculated it
try:
#print grating, dw, 'cached!'
return cacheLSF[grating, dw_new]
except KeyError:
pass
oldLSF = readtxt(datapath + '/LSF/%s.txt' % grating, readnames=1)
dw_orig = dict(G130M=0.00997, G160M=0.01223, NUV=0.390)
wa0 = oldLSF.relpix * dw_orig[grating]
if dw_new is None:
return oldLSF, wa0
t = np.arange(0, wa0[-1], dw_new)
wa1 = np.concatenate([-t[::-1][:-1], t])
wavs = oldLSF.dtype.names[1:]
newLSF = []
for w in wavs:
newLSF.append(interp_spline(wa1, wa0, oldLSF[w]))
t = np.arange(len(wa1)//2 + 1)
newpix = np.concatenate([-t[::-1][:-1], t])
#import pdb; pdb.set_trace()
newLSF = np.rec.fromarrays([newpix] + newLSF, names=oldLSF.dtype.names)
cacheLSF[grating, dw_new] = newLSF, wa1
return newLSF, wa1
def order_shift_and_scale_spline(self, order, multiple, shift, sigma, slope, offset, minuit, **kwargs):
"""trying to smooth, interpolate, and integrate the fit."""
mask = self.Orders[order]['mask']
iow = self.Orders[order]['iow']
iof = self.Orders[order]['iof']
wav = self.Orders[order]['wav'][mask]
flx = self.Orders[order]['flx'][mask]
err = self.Orders[order]['err'][mask]
con = self.Orders[order]['con'][mask]
pix = self.Orders[order]['pix'][mask]
overflx = multiple * slope_to_array(slope, interp.interp_spline(wav + shift, iow, convolve.convolve_constant_dv(iow, iof, vfwhm=sigma))) + offset
chi_square = np.sum((overflx - flx/con)**2 / (err/con)**2)
if minuit == 0:
return chi_square
else:
return chi_square, wav, flx/con, err/con, pix, overflx
def order_shift_and_scale_spline(self, order, multiple, shift, sigma,
slope, offset, minuit, **kwargs):
"""trying to smooth, interpolate, and integrate the fit."""
mask = self.Orders[order]['mask']
iow = self.Orders[order]['iow']
iof = self.Orders[order]['iof']
wav = self.Orders[order]['wav'][mask]
flx = self.Orders[order]['flx'][mask]
err = self.Orders[order]['err'][mask]
con = self.Orders[order]['con'][mask]
pix = self.Orders[order]['pix'][mask]
overflx = multiple * slope_to_array(
slope,
interp.interp_spline(
wav + shift, iow,
convolve.convolve_constant_dv(iow, iof, vfwhm=sigma))) + offset
chi_square = np.sum((overflx - flx / con)**2 / (err / con)**2)
if minuit == 0:
return chi_square
else:
return chi_square, wav, flx / con, err / con, pix, overflx
# Faucher-Giguere 2009
gamma_HI = 0.861e-12
print 'gamma HeII'
for eta in 30, 100, 200:
print eta, "{:.3g}".format(0.43 * gamma_HI / eta)
prefix = "/Users/ncrighton/Projects/MPIA_QSO_LBG/Cloudy/J0004/comp1"
names = sorted(glob(prefix + "/uvb_k0?/*tilted*tbl"))
for n in names:
#if 'k00' not in n and 'k04' not in n and 'k06' not in n:
# continue
print n
T = Table.read(n, format='ascii')
# energy and log10jnu
if 0:
x = np.log10(T['energy'])
x1 = np.arange(x[0], x[-1], 0.1*(x[1]-x[0]))
from barak.interp import interp_spline
y1 = interp_spline(x1, x, T['log10jnu'])
jnu = 10**y1
gamHeII = find_gamma(10**x1, jnu, Z=2)
gamHI = find_gamma(10**x1, jnu, Z=1)
else:
jnu = 10**T['log10jnu']
gamHeII = find_gamma(T['energy'], jnu, Z=2)
gamHI = find_gamma(T['energy'], jnu, Z=1)
print 'HeII {:.3g}'.format(gamHeII*1e-12)
print 'HI {:.3g}'.format(gamHI*1e-12)
# Faucher-Giguere 2009
gamma_HI = 0.861e-12
print 'gamma HeII'
for eta in 30, 100, 200:
print eta, "{:.3g}".format(0.43 * gamma_HI / eta)
prefix = "/Users/ncrighton/Projects/MPIA_QSO_LBG/Cloudy/J0004/comp1"
names = sorted(glob(prefix + "/uvb_k0?/*tilted*tbl"))
for n in names:
#if 'k00' not in n and 'k04' not in n and 'k06' not in n:
# continue
print n
T = Table.read(n, format='ascii')
# energy and log10jnu
if 0:
x = np.log10(T['energy'])
x1 = np.arange(x[0], x[-1], 0.1 * (x[1] - x[0]))
from barak.interp import interp_spline
y1 = interp_spline(x1, x, T['log10jnu'])
jnu = 10**y1
gamHeII = find_gamma(10**x1, jnu, Z=2)
gamHI = find_gamma(10**x1, jnu, Z=1)
else:
jnu = 10**T['log10jnu']
gamHeII = find_gamma(T['energy'], jnu, Z=2)
gamHI = find_gamma(T['energy'], jnu, Z=1)
print 'HeII {:.3g}'.format(gamHeII * 1e-12)
print 'HI {:.3g}'.format(gamHI * 1e-12)
