def arcturus_link():
arc_list =list()
for file in os.listdir('Arcturus'):
if 'ar' in file:
arc_list.append(file)
Arcturus = []
for line in arc_list:
arcspecfile = ('Arcturus/{}'.format(line) )
ArcSpec = np.genfromtxt(arcspecfile,dtype=float)
ArcSpec = np.array(ArcSpec,dtype=float)
Arcturus.append(ArcSpec)
Arc = np.vstack(Arcturus)
Arc[:,1] = Arc[:,1][np.argsort(Arc[:,0])]
Arc[:,2] = Arc[:,2][np.argsort(Arc[:,0])]
Arc[:,3] = Arc[:,3][np.argsort(Arc[:,0])]
Arc[:,0] = np.sort(Arc[:,0])
Arc[:,0] = pyasl.airtovac2(Arc[:,0])
np.savetxt('ArcturusSpectrum.txt',Arc)
Arc = Arc[(Arc[:,1] > 0.) & (Arc[:,3] > 0.)]
return Arc
def get_dispsol(wc_file,
ap_max,
show=False,
col='b',
is_wave_air=False,
label=None):
lines = open(wc_file, 'r').readlines()
shift, offset, slope = 0, 0, 1 #default values in case absent in ec* file
for i, l in enumerate(lines):
if '\tslope\t' in l:
slope = float(l.split()[1])
if '\toffset\t' in l:
offset = float(l.split()[1])
if '\tshift\t' in l:
shift = float(l.split()[1])
if '\tcoefficients\t' in l:
start = i
xpow = int(float(lines[start + 2].strip()))
opow = int(float(lines[start + 3].strip()))
xmin, xmax = float(lines[start + 5].strip()), float(lines[start +
6].strip())
omin, omax = float(lines[start + 7].strip()), float(lines[start +
8].strip())
c = np.reshape(
[float(lines[start + 9 + i].strip()) for i in range(opow * xpow)],
(opow, xpow))
ypix = np.arange(int(xmin), int(xmax) + 1)
wlist = []
for ap in range(1, ap_max + 1):
w = []
o = ap * slope + offset
for x in ypix:
w.append(
(wc(x, o, xpow, opow, xmin, xmax, omin, omax, c) + shift) / o)
if is_wave_air:
w = p.airtovac2(
w, mode='ciddor'
) #to convert to vacuum wavelengths if initially it is air wavelength
if show:
if ap > 1: label = None
plt.plot(ypix, w, c=col, label=label)
plt.axhline(w[-1], linestyle='dotted', c='k') #
wlist.append(w)
if show:
plt.xlabel('y-pixel')
plt.ylabel('Observed wavelength(A)')
plt.title('Dispersion solution')
plt.show(block=False)
return np.array(wlist)
#----------------------------------------------------------------
def load_linelist(linelist,directory=None):
if directory == None:
directory = '.'
Linelist = np.genfromtxt('{}/{}'.format(directory,linelist), dtype=([('element','a2'),
('ion' ,'a2'),
('wavelength' ,'f8'),
('potential' ,'f8'),
('oscillator' ,'f8')])
,skip_header = 1)
Linelist['element'] = Linelist['element'][np.argsort(Linelist['wavelength'])]
Linelist['ion'] = Linelist['ion'][np.argsort(Linelist['wavelength'])]
Linelist['potential'] = Linelist['potential'][np.argsort(Linelist['wavelength'])]
Linelist['oscillator'] = Linelist['oscillator'][np.argsort(Linelist['wavelength'])]
Linelist['wavelength'] = np.sort(Linelist['wavelength'])
Linelist['wavelength'] = pyasl.airtovac2(Linelist['wavelength'])
return Linelist
def mask_lines_bank(Data):
# The objects in the bank have a redshift of zero
z_obj = 0
#These lines are in rest frame
host_lines=np.array([
6564.61
,4862.69
,3726.09
,3729.88
,5008.24
,4960.30
,6549.84
,6585.23
,6718.32
,6732.71])
host_lines_air = (1+z_obj)*pyasl.airtovac2(host_lines)
host_range_air = np.column_stack([host_lines_air,host_lines_air])
z_disp = 4e2/3e5
host_range_air[:,0]=host_range_air[:,0]*(1-z_disp)
host_range_air[:,1]=host_range_air[:,1]*(1+z_disp)
func=lambda x,y: (x<y[1])&(x>y[0])
cum_mask=np.array([True]*len(Data[:,0]))
for i in range(len(host_lines_air)):
mask=np.array(list(map(lambda x: ~func(x,host_range_air[i]),Data[:,0])))
cum_mask = cum_mask & mask
Data_masked = Data[cum_mask]
#plt.figure()
#plt.plot(Data[:,0],Data[:,1],'r')
#plt.plot(Data_masked[:,0],Data_masked[:,1],'.b')
#plt.show()
return Data_masked
Linelist = np.genfromtxt('SpecConvolve/NLTEin.txt', dtype=([('element' ,'a2'),
('ion' ,'a2'),
('wavelength' ,'f8'),
('potential' ,'f8'),
('oscillator' ,'f8')])
,skip_header = 1)
Linelist['element'] = Linelist['element'][np.argsort(Linelist['wavelength'])]
Linelist['ion'] = Linelist['ion'][np.argsort(Linelist['wavelength'])]
Linelist['potential'] = Linelist['potential'][np.argsort(Linelist['wavelength'])]
Linelist['oscillator'] = Linelist['oscillator'][np.argsort(Linelist['wavelength'])]
Linelist['wavelength'] = np.sort(Linelist['wavelength'])
#print min(Linelist['wavelength']), max(Linelist['wavelength'])
#### Converting wavelengths in air to wavelengths in vacuum. ####
Linelist['wavelength'] = pyasl.airtovac2(Linelist['wavelength'])
allelementslist = []
for l in range(0,len(Linelist)):
if Linelist['element'][l] not in allelementslist:
allelementslist.append(Linelist['element'][l])
print 'Elements to choose from:'
print allelementslist
while True:
try:
element = raw_input('Type an element to analyze, or type All for all elements: ')
if element != 'All':
dtype=([('element', 'a2'), ('ion', 'a2'),
('wavelength', 'f8'), ('potential', 'f8'),
('oscillator', 'f8')]),
skip_header=1)
Linelist['element'] = Linelist['element'][np.argsort(Linelist['wavelength'])]
Linelist['ion'] = Linelist['ion'][np.argsort(Linelist['wavelength'])]
Linelist['potential'] = Linelist['potential'][np.argsort(
Linelist['wavelength'])]
Linelist['oscillator'] = Linelist['oscillator'][np.argsort(
Linelist['wavelength'])]
Linelist['wavelength'] = np.sort(Linelist['wavelength'])
#print min(Linelist['wavelength']), max(Linelist['wavelength'])
#### Converting wavelengths in air to wavelengths in vacuum. ####
Linelist['wavelength'] = pyasl.airtovac2(Linelist['wavelength'])
allelementslist = []
for l in range(0, len(Linelist)):
if Linelist['element'][l] not in allelementslist:
allelementslist.append(Linelist['element'][l])
print 'Elements to choose from:'
print allelementslist
while True:
try:
element = raw_input(
'Type an element to analyze, or type All for all elements: ')
if element != 'All':
import matplotlib.pyplot as plt
Data=np.genfromtxt('/home/idoi/Dropbox/superfit/ZTF20aawbzlo_20200527_P200_v2.ascii')
z_obj=0.034
host_lines=np.array([
6564.61
,4862.69
,3726.09
,3729.88
,5008.24
,4960.30
,6549.84
,6585.23
,6718.32
,6732.71])
host_lines_air=(1+z_obj)*pyasl.airtovac2(host_lines)
host_range_air=np.column_stack([host_lines_air,host_lines_air])
z_disp=4e2/3e5
host_range_air[:,0]=host_range_air[:,0]*(1-z_disp)
host_range_air[:,1]=host_range_air[:,1]*(1+z_disp)
func=lambda x,y: (x<y[1])&(x>y[0])
cum_mask=np.array([True]*len(Data[:,0]))
for i in range(len(host_lines_air)):
mask=np.array(list(map(lambda x: ~func(x,host_range_air[i]),Data[:,0])))
cum_mask=cum_mask & mask
Data_masked = Data[cum_mask]
np.savetxt('/home/idoi/Dropbox/superfit/ZTF20aawbzlo_20200527_P200_v2_host_line_masked.ascii',Data_masked)
