def showme():
#! open HD19467B and read in the arrays for wavelength, flux, and uncertainty
file = open(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/HD19467NewSpect.txt'
)
W_obj, F_obj, U_obj = [], [], []
for line in file:
columns = line.split()
wav = float(columns[0])
flu = float(columns[1])
un = float(columns[2])
W_obj.append(wav)
F_obj.append(flu)
U_obj.append(un)
file.close()
W_obj_t = W_obj[4:30] #t = trimmed
F_obj_t = F_obj[4:30]
U_obj_t = U_obj[4:30]
myInt = 2.3630917239963894e-17
F_obj_tn = [x / myInt for x in F_obj_t] #n = normalized
U_obj_tn = [x / myInt for x in U_obj_t]
before = np.array([W_obj_t, F_obj_t, U_obj_t])
after = np.array([W_obj_t, F_obj_tn, U_obj_tn])
after = u.norm_spec(
after,
before) #to make sure all spaces in between points are the same length
after = [i.value for i in after]
# plt.errorbar(before[0],before[1],yerr=before[2])
# plt.errorbar(after[0],after[1],yerr=after[2])
plt.plot(before[0], before[1])
plt.show()
plt.clf()
plt.plot(after[0], after[1])
plt.show()
def showme():
#! open HD19467B and read in the arrays for wavelength, flux, and uncertainty
W, F, U = db.query.execute(
"select wavelength, flux, unc from spectra where id=15").fetchone()
binned_wl = 0
jump = 0.0267097 #defined by the wavelength points of HD19467B data
start = 1.1826776 - (jump / 2) #start half way before 1st flux point
W, F, U = u.scrub([W, F, U])
W = W.value
F = F.value
U = U.value
flux2 = 0
W_obj, F_obj, U_obj = [], [], []
unc2 = 0
w1 = start + (jump / 2) #first wl point is at start+the step/2
wavelength = 0
# W_temp, F_temp, U_temp=u.rebin_spec([W,F,U],wava)
#! loop through 21 iterations for the amount of wavelength ranges I have
for i in range(0, 21):
binned_wl = jump + start #range is half below and half above w1
flux2 = sum(F[np.where(np.logical_and(W > start,
W < binned_wl))]) #binning flux
unc2 = np.sqrt(
sum(U[np.where(np.logical_and(
W > start,
W < binned_wl))]**2)) #bin uncertainty in quadrature
start = binned_wl #set new range start
F_obj.append(flux2)
U_obj.append(unc2)
wavelength = w1 + (i * jump
) #this is where the flux point will go on plot
W_obj.append(wavelength)
object = np.array([
W_obj, F_obj, U_obj
]) #to make sure all spaces in between points are the same length
#! pick wavelength range between points on object plot #not necessary to this code
wavelength_points = [
1.1826776, 1.2093873000000002, 1.236097, 1.2628067, 1.2895164,
1.3162261000000002, 1.3429358, 1.3696455, 1.3963552,
1.4230649000000002, 1.4497746, 1.4764843, 1.503194, 1.5299037000000002,
1.5566134, 1.5833231, 1.6100328, 1.6367425, 1.6634522, 1.6901619,
1.7168716
]
#! get source_id for all T dwarfs from database, turn it into a list and use list to get spectra_id for each source's spex data
sources = db.query.execute(
"select distinct source_id from spectral_types where spectral_type>=20 and spectral_type<=30 and regime='IR'"
).fetchall()
sourcelist, ids, idlist = [], [], []
index = 0
while index < len(sources):
sourcelist.append(sources[index][0])
index = index + 1
for i in sourcelist:
id = db.query.execute(
"SELECT distinct id FROM spectra WHERE source_id='{}' AND instrument_id=6"
.format(i)).fetchone()
ids.append(id)
ids = filter(None, ids)
index = 0
while index < len(ids):
idlist.append(ids[index][0])
index = index + 1
print len(idlist)
#! loop through each object
chisquare, sptlist, chilist, namelist, specidlist = [], [], [], [], []
for j in idlist:
name, W, F, U = db.query.execute(
"SELECT source_id, wavelength, flux, unc from spectra where id='{}'"
.format(j)).fetchone()
binned_wl = 0
jump = 0.0267097 #defined by the wavelength points of HD19467B data
start = 1.1826776 - (jump / 2) #start half way before 1st flux point
W, F, U = u.scrub([W, F, U])
W = W.value
F = F.value
U = U.value
original = np.array([W, F, U])
source, spectype = db.query.execute(
"SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id='{}'"
.format(j)).fetchone()
print name, source
flux2 = 0
W_temp, F_temp, U_temp = [], [], []
unc2 = 0
w1 = start + (jump / 2) #first wl point is at start+the step/2
wavelength = 0
# W_temp, F_temp, U_temp=u.rebin_spec([W,F,U],wava)
#! loop through 21 iterations for the amount of wavelength ranges I have
for i in range(0, 21):
binned_wl = jump + start #range is half below and half above w1
flux2 = sum(F[np.where(np.logical_and(
W > start, W < binned_wl))]) #binning flux
unc2 = np.sqrt(
sum(U[np.where(np.logical_and(
W > start,
W < binned_wl))]**2)) #bin uncertainty in quadrature
start = binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength = w1 + (i * jump
) #this is where the flux point will go on plot
W_temp.append(wavelength)
template = np.array([W_temp, F_temp,
U_temp]) #create arrays for ease of use
template = u.norm_spec(
template, original) #Joe's code to normalize plots to each other
template = [i.value for i in template]
#! plot template over template's original flux
plt.plot(template[0], template[1])
plt.plot(original[0], original[1])
plt.savefig(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/SanityCheckplots/binned_flux_with_original/'
+ '{}'.format(name) + '.pdf')
plt.clf()
template = np.array([W_temp, F_temp, U_temp])
template = u.norm_spec(
template, object) #Joe's code to normalize plots to each other
template = [i.value for i in template]
#! plot template over object
plt.errorbar(template[0], template[1], yerr=template[2], marker="o")
plt.errorbar(object[0], object[1], yerr=object[2], marker="o")
plt.savefig(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/SanityCheckplots/template_over_object/'
+ '{}'.format(name) + '_HD19467.pdf')
plt.clf()
#-----------------------------------------------------------------------------------------
try:
chi = sum(((template[1] - object[1])**2) /
((template[2]**2) +
(object[2]**2))) #both data sets have uncertainties
namelist.append(source)
sptlist.append(spectype)
chilist.append(chi)
specidlist.append(j)
# output=np.array([name,spectype,chi])
except ValueError:
pass
output = np.array([namelist, specidlist, sptlist, chilist])
print len(sptlist), chilist
#! plotting the best fits, or minimum chi squared values over the object
min_vals = np.where(output[3] < 400)
for i in min_vals:
print "min_vals = {0}".format(i)
print output[0][i], output[1][i], output[2][i], output[3][i]
for k in output[1][i]:
name, W, F, U = db.query.execute(
"SELECT source_id, wavelength, flux, unc from spectra where id='{}'"
.format(k)).fetchone()
binned_wl = 0
jump = 0.0267097 #defined by the wavelength points of HD19467B data
start = 1.1826776 - (jump / 2
) #start half way before 1st flux point
source, spectype = db.query.execute(
"SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id='{}'"
.format(k)).fetchone()
print source, spectype
flux2 = 0
W_temp, F_temp, U_temp, = [], [], []
unc2 = 0
w1 = start + (jump / 2) #first wl point is at start+the step/2
wavelength = 0
#! loop through 21 iterations for the amount of wavelength ranges I have
for i in range(0, 21):
binned_wl = jump + start #range is half below and half above w1
flux2 = sum(F[np.where(np.logical_and(
W > start, W < binned_wl))]) #binning flux
unc2 = np.sqrt(
sum(U[np.where(np.logical_and(
W > start,
W < binned_wl))]**2)) #bin uncertainty in quadrature
start = binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength = w1 + (
i * jump) #this is where the flux point will go on plot
W_temp.append(wavelength)
template = np.array([W_temp, F_temp, U_temp])
template = u.norm_spec(template, object)
plt.errorbar(template[0],
template[1],
yerr=template[2],
marker="o",
label=str(spectype))
plt.legend(loc='upper right')
plt.errorbar(object[0],
object[1],
yerr=object[2],
marker="o",
label='HD19467B')
plt.savefig(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/SanityCheckplots/bestfits_w_object.pdf'
)
plt.clf()
chisquare = [sptlist, chilist]
#! plot spectral type vs chi square
plt.scatter(chisquare[0], chisquare[1])
chisquare = zip(*sorted(zip(*chisquare)))
pfit = np.polyfit(chisquare[0], chisquare[1],
3) # Fit a 2nd order polynomial to (x, y) data
yfit = np.polyval(pfit, chisquare[0]) # Evaluate the polynomial at x
plt.plot(chisquare[0], yfit)
plt.savefig(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/SanityCheckplots/chisquare_distribution.pdf'
)
plt.clf()
def showme(ax):
file=open('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/HD19467B.txt')
W_obj,F_obj,U_obj=[],[],[]
for line in file:
columns=line.split()
wav=float(columns[0])
flu=float(columns[1])
un=float(columns[2])
W_obj.append(wav) ; F_obj.append(flu) ; U_obj.append(un)
file.close()
object=np.array([W_obj,F_obj,U_obj])
lamb=np.gradient(W_obj)
xer=lamb/2
# T6
original, template6=m.bin_down(7982,0.0267097,1.1826776,21)
source,spectype=db.query.execute("SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id=7982").fetchone()
spectype=a.specType(spectype)
template_plot26=u.norm_spec(template6,object) #Joe's code to normalize plots to each other
template_plot26=[i.value for i in template_plot26]
ax.plot(template_plot26[0],template_plot26[1],'c:',linewidth=2,label=str(spectype))
# T7
original, template7=m.bin_down(3121,0.0267097,1.1826776,21)
source,spectype=db.query.execute("SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id=3121").fetchone()
spectype=a.specType(spectype)
template_plot27=u.norm_spec(template7,object) #Joe's code to normalize plots to each other
template_plot27=[i.value for i in template_plot27]
ax.plot(template_plot27[0],template_plot27[1],'g-.',linewidth=2,label=str(spectype))
# T7.5
original, template=m.bin_down(5308,0.0267097,1.1826776,21)
source,spectype=db.query.execute("SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id=5308").fetchone()
spectype=a.specType(spectype)
template_plot2=u.norm_spec(template,object) #Joe's code to normalize plots to each other
template_plot2=[i.value for i in template_plot2]
ax.plot(template_plot2[0],template_plot2[1],'r--',linewidth=2,label=str(spectype))
# T8
with open('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/LateTdata/WISEJ050003.04-122343.2_SpeX.txt') as f:
lines_after_17 = f.readlines()[7:]
Wtxt,Ftxt,Utxt=[],[],[]
for line in lines_after_17:
columns=line.split()
wavx=float(columns[0])
flux=float(columns[1])
unx=float(columns[2])
Wtxt.append(wavx) ; Ftxt.append(flux) ; Utxt.append(unx)
f.close()
spectype=28
spectype=a.specType(spectype)
binned_wl=0 #defined by the wavelength points of HD19467B data
start=1.1826776-(0.0267097/2) #start half way before 1st flux point
W,F,U=u.scrub([Wtxt,Ftxt,Utxt])
W=W.value
F=F.value
U=U.value
original=np.array([Wtxt,Ftxt,Utxt])
flux2=0
W_temp, F_temp, U_temp=[],[],[]
unc2=0 #first wl point is at start+the step/2
wavelength=0
for i in range(21):
binned_wl=0.0267097 + start #range is half below and half above w1
flux2=sum(F[np.where(np.logical_and(W>start,W<binned_wl))]) #binning flux
unc2=np.sqrt(sum(U[np.where(np.logical_and(W>start,W<binned_wl))]**2)) #bin uncertainty in quadrature
start=binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength=1.1826776+(i*0.0267097) #this is where the flux point will go on plot
W_temp.append(wavelength)
template28=np.array([W_temp, F_temp, U_temp])
template_plot28=u.norm_spec(template28,object) #Joe's code to normalize plots to each other
template_plot28=[i.value for i in template_plot28]
ax.plot(template_plot28[0],template_plot28[1],'b',linewidth=3,label=str(spectype))
# T8.5
with open('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/LateTdata/WISEJ004945.61+215120.0_SpeX.txt') as f:
lines_after_17 = f.readlines()[7:]
Wtxt,Ftxt,Utxt=[],[],[]
for line in lines_after_17:
columns=line.split()
wavx=float(columns[0])
flux=float(columns[1])
unx=float(columns[2])
Wtxt.append(wavx) ; Ftxt.append(flux) ; Utxt.append(unx)
f.close()
spectype=28.5
spectype=a.specType(spectype)
binned_wl=0 #defined by the wavelength points of HD19467B data
start=1.1826776-(0.0267097/2) #start half way before 1st flux point
W,F,U=u.scrub([Wtxt,Ftxt,Utxt])
W=W.value
F=F.value
U=U.value
original=np.array([Wtxt,Ftxt,Utxt])
flux2=0
W_temp, F_temp, U_temp=[],[],[]
unc2=0 #first wl point is at start+the step/2
wavelength=0
for i in range(21):
binned_wl=0.0267097 + start #range is half below and half above w1
flux2=sum(F[np.where(np.logical_and(W>start,W<binned_wl))]) #binning flux
unc2=np.sqrt(sum(U[np.where(np.logical_and(W>start,W<binned_wl))]**2)) #bin uncertainty in quadrature
start=binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength=1.1826776+(i*0.0267097) #this is where the flux point will go on plot
W_temp.append(wavelength)
template29=np.array([W_temp, F_temp, U_temp])
template_plot29=u.norm_spec(template29,object) #Joe's code to normalize plots to each other
template_plot29=[i.value for i in template_plot29]
ax.plot(template_plot29[0],template_plot29[1],'m--',linewidth=2,label=str(spectype))
# T9
with open('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/LateTdata/T9_UGPS0722-0540_STD.txt') as f:
lines_after_17 = f.readlines()[7:]
Wtxt,Ftxt,Utxt=[],[],[]
for line in lines_after_17:
columns=line.split()
wavx=float(columns[0])
flux=float(columns[1])
unx=float(columns[2])
Wtxt.append(wavx) ; Ftxt.append(flux) ; Utxt.append(unx)
f.close()
spectype=29
spectype=a.specType(spectype)
binned_wl=0 #defined by the wavelength points of HD19467B data
start=1.1826776-(0.0267097/2) #start half way before 1st flux point
W,F,U=u.scrub([Wtxt,Ftxt,Utxt])
W=W.value
F=F.value
U=U.value
original=np.array([Wtxt,Ftxt,Utxt])
flux2=0
W_temp, F_temp, U_temp=[],[],[]
unc2=0 #first wl point is at start+the step/2
wavelength=0
for i in range(21):
binned_wl=0.0267097 + start #range is half below and half above w1
flux2=sum(F[np.where(np.logical_and(W>start,W<binned_wl))]) #binning flux
unc2=np.sqrt(sum(U[np.where(np.logical_and(W>start,W<binned_wl))]**2)) #bin uncertainty in quadrature
start=binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength=1.1826776+(i*0.0267097) #this is where the flux point will go on plot
W_temp.append(wavelength)
template29=np.array([W_temp, F_temp, U_temp])
template_plot29=u.norm_spec(template29,object) #Joe's code to normalize plots to each other
template_plot29=[i.value for i in template_plot29]
ax.plot(template_plot29[0],template_plot29[1],'g-.',linewidth=2,label=str(spectype))
ax.errorbar(object[0],object[1],xerr=xer,yerr=object[2],fmt=None,ecolor='k',marker='o',label='HD19467B')
ax.set_ylim(0.001,1.1)
ax.set_xlim(1.15,1.75)
ax.legend( loc='upper right',fontsize=10,prop={'size':15}, ncol=2, numpoints=1)
ax.set_xlabel(r'Wavelength ($\mu$m)', fontsize="x-large")
ax.set_ylabel('Normalized Flux', fontsize="x-large")
ax.tick_params(labelsize="large")
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/figure.pdf')
# plt.clf()
# return p2
def showme():
file = open(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/HD19467B.txt'
)
wava = []
flua = []
una = []
for line in file:
columns = line.split()
wav = float(columns[0])
flu = float(columns[1])
un = float(columns[2])
wava.append(wav)
flua.append(flu)
una.append(un)
file.close()
# pick wavelength range between points on object plot
wavelength_points = [
1.1826776, 1.2093873000000002, 1.236097, 1.2628067, 1.2895164,
1.3162261000000002, 1.3429358, 1.3696455, 1.3963552,
1.4230649000000002, 1.4497746, 1.4764843, 1.503194, 1.5299037000000002,
1.5566134, 1.5833231, 1.6100328, 1.6367425, 1.6634522, 1.6901619,
1.7168716
]
sources = db.query.execute(
"select distinct source_id from spectral_types where spectral_type>=20 and spectral_type<=30 and regime='IR'"
).fetchall()
sourcelist = []
index = 0
while index < len(sources):
sourcelist.append(sources[index][0])
index = index + 1
ids = []
for i in sourcelist:
id = db.query.execute(
"SELECT distinct id FROM spectra WHERE source_id='{}' AND instrument_id=6"
.format(i)).fetchone()
ids.append(id)
ids = filter(None, ids)
idlist = []
index = 0
while index < len(ids):
idlist.append(ids[index][0])
index = index + 1
print len(idlist)
output = []
chisquare = []
sptlist = []
chilist = []
for j in idlist:
name, W, F, unc = db.query.execute(
"SELECT source_id, wavelength, flux, unc from spectra where id='{}'"
.format(j)).fetchone()
binned_wl = 0
jump = 0.0267097
start = 1.1826776 + (jump / 2) #start half way after 1st flux point
times = 21
end = 1.73022645
spectype = db.query.execute(
"SELECT spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectra.id='{}'"
.format(j)).fetchone()
# normalize the flux incase it's not already
NF = F * 1.27 / np.interp(1.27, W, F)
NU = unc * 1.27 / np.interp(1.27, W, unc)
flux2 = 0
newflux = []
unc2 = 0
newunc = []
w1 = start + (jump / 2) #first wl point is at start+the step/2
newwl = []
wavelength = 0
for i in range(0, 21):
binned_wl = jump + start #range is half below and half above w1
flux2 = sum(NF[np.where(np.logical_and(W > start, W < binned_wl))])
unc2 = np.sqrt(
sum(NU[np.where(np.logical_and(W > start, W < binned_wl))]**2))
start = binned_wl
newflux.append(flux2)
newunc.append(unc2)
wavelength = w1 + (i * jump)
newwl.append(wavelength)
#
# G,C=goodness([wava,flua,una],[newwl,newflux,newunc])
# newflux=C*np.array(newflux)
# newunc=C*np.array(newunc)
# plt.errorbar(newwl,newflux,yerr=newunc,marker="o")
# plt.errorbar(wava,flua,yerr=una,marker="o")
# calculate a chi squared
# wava*=q.um
# flua*=q.erg/q.s/q.cm**2/q.AA
# una*=q.erg/q.s/q.cm**2/q.AA
# #
template = np.array([newwl, newflux, newunc])
object = np.array([wava, flua, una])
template = u.norm_spec(template, object)
# plt.errorbar(template[0],template[1],yerr=template[2],marker="o")
# plt.errorbar(object[0],object[1],yerr=object[2],marker="o")
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/'+'{}'.format(name)+ '.pdf')
# plt.clf()
try:
chi, p = s.chisquare(
template[1], object[1]) #len of template and object dont match
output.append([chi, name, spectype])
sptlist.append(spectype)
chilist.append(chi)
except ValueError:
pass
chisquare = [sptlist, chilist]
plt.scatter(chisquare[0], chisquare[1])
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/chisquare_distribution.pdf')
# plt.clf()
plt.show()
def showme():
#! open HD19467B and read in the arrays for wavelength, flux, and uncertainty
file = open(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/HD19467B.txt'
)
W_obj, F_obj, U_obj = [], [], []
for line in file:
columns = line.split()
wav = float(columns[0])
flu = float(columns[1])
un = float(columns[2])
W_obj.append(wav)
F_obj.append(flu)
U_obj.append(un)
file.close()
object = np.array([W_obj, F_obj, U_obj])
print np.gradient(
W_obj) #to make sure all spaces in between points are the same length
#! get source_id for all T dwarfs from database, turn it into a list and use list to get spectra_id for each source's spex data
sources = db.query.execute(
"select distinct source_id from spectral_types where spectral_type>=20 and spectral_type<=30 and regime='IR'"
).fetchall()
sourcelist, ids, idlist = [], [], []
index = 0
while index < len(sources):
sourcelist.append(sources[index][0])
index = index + 1
for i in sourcelist:
id = db.query.execute(
"SELECT distinct id FROM spectra WHERE source_id='{}' AND instrument_id=6"
.format(i)).fetchone()
ids.append(id)
ids = filter(None, ids)
index = 0
while index < len(ids):
idlist.append(ids[index][0])
index = index + 1
print len(idlist)
#! loop through each object
chisquare, chilist, namelist, specidlist, sptlist = [], [], [], [], []
for j in idlist:
original, template = m.bin_down(j, 0.0267097, 1.1826776,
21) #create arrays for ease of use
source, spectype = db.query.execute(
"SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id='{}'"
.format(j)).fetchone()
template_plot1 = u.norm_spec(
template, original) #Joe's code to normalize plots to each other
template_plot1 = [i.value for i in template_plot1]
# #! plot template over template's original flux
# plt.plot(template_plot1[0],template_plot1[1])
# plt.plot(original[0],original[1])
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/binned_flux_with_original/'+'{}'.format(source)+ '.pdf')
# plt.clf()
template_plot2 = u.norm_spec(
template, object) #Joe's code to normalize plots to each other
template_plot2 = [i.value for i in template_plot2]
# #! plot template over object
# plt.errorbar(template_plot2[0],template_plot2[1],yerr=template_plot2[2],marker="o")
# plt.errorbar(object[0],object[1],yerr=object[2],marker="o")
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/template_over_object/'+'{}'.format(source)+ '_HD19467.pdf')
# plt.clf()
template = u.norm_spec(template, object)
template = [i.value for i in template]
chi = sum(((template[1] - object[1])**2) /
((template[2]**2) +
(object[2]**2))) #both data sets have uncertainties
namelist.append(source)
sptlist.append(spectype)
chilist.append(float(chi))
specidlist.append(j)
# filenamelist=['WISEJ225540.75-311842.0_SpeX','WISEJ222623.05+044004.0_SpeX','WISEJ171104.60+350036.8_SpeX','WISEJ165311.05+444422.8_SpeX','WISEJ132233.64-234016.8_SpeX','WISEJ062309.94-045624.6_SpeX','WISEJ045853.89+643452.5_SpeX','WISEJ050003.04-122343.2_SpeX','WISEJ025409.51+022358.6_SpeX','T9_UGPS0722-0540_STD','WISEJ004945.61+215120.0_SpeX','WISEJ024512.62-345047.8_SpeX']
# spectypelist=[28,28,28,28,28,28,28.5,28,28,29,28.5,28]
# for k in range(12):
# with open('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/LateTdata/'+'{}'.format(filenamelist[k])+'.txt') as f:
# lines_after_17 = f.readlines()[7:]
# Wtxt,Ftxt,Utxt=[],[],[]
# for line in lines_after_17:
# columns=line.split()
# wavx=float(columns[0])
# flux=float(columns[1])
# unx=float(columns[2])
# Wtxt.append(wavx) ; Ftxt.append(flux) ; Utxt.append(unx)
# f.close()
# spectype=spectypelist[k]
#
# binned_wl=0 #defined by the wavelength points of HD19467B data
# start=1.1826776-(0.0267097/2) #start half way before 1st flux point
# W,F,U=u.scrub([Wtxt,Ftxt,Utxt])
# W=W.value
# F=F.value
# U=U.value
# original=np.array([Wtxt,Ftxt,Utxt])
# flux2=0
# W_temp, F_temp, U_temp=[],[],[]
# unc2=0 #first wl point is at start+the step/2
# wavelength=0
#
# #! loop through 21 iterations for the amount of wavelength ranges I have
# for i in range(21):
# binned_wl=0.0267097 + start #range is half below and half above w1
#
# flux2=sum(F[np.where(np.logical_and(W>start,W<binned_wl))]) #binning flux
# unc2=np.sqrt(sum(U[np.where(np.logical_and(W>start,W<binned_wl))]**2)) #bin uncertainty in quadrature
#
# start=binned_wl #set new range start
#
# F_temp.append(flux2)
# U_temp.append(unc2)
# wavelength=1.1826776+(i*0.0267097) #this is where the flux point will go on plot
# W_temp.append(wavelength)
#
# template=np.array([W_temp, F_temp, U_temp])
#
# template_plot1=u.norm_spec(template,original) #Joe's code to normalize plots to each other
# template_plot1=[i.value for i in template_plot1]
# # #! plot template over template's original flux
# plt.plot(template_plot1[0],template_plot1[1])
# plt.plot(original[0],original[1])
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/binned_flux_with_original/'+'{}'.format(filenamelist[k])+ '.pdf')
# plt.clf()
#
# template_plot2=u.norm_spec(template,object) #Joe's code to normalize plots to each other
# template_plot2=[i.value for i in template_plot2]
# # #! plot template over object
# plt.errorbar(template_plot2[0],template_plot2[1],yerr=template_plot2[2],marker="o")
# plt.errorbar(object[0],object[1],yerr=object[2],marker="o")
# plt.savefig('/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/template_over_object/'+'{}'.format(filenamelist[k])+ '_HD19467.pdf')
# plt.clf()
#
# template=u.norm_spec(template,object)
# template=[i.value for i in template]
# chi=sum(((template[1]-object[1])**2)/((template[2]**2)+(object[2]**2))) #both data sets have uncertainties
# # print filenamelist[k],type(chi), spectype
# namelist.append(filenamelist[k])
# sptlist.append(spectypelist[k])
# chilist.append(float(chi))
# specidlist.append('None')
#------------------------------
output = np.array([chilist, namelist, specidlist, sptlist])
chilistfloat = np.array([float(n) for n in output[0]])
print len(sptlist)
top5 = chilistfloat.argsort()[:10]
print top5
for i in top5:
print output[0][i], output[1][i], output[2][i], output[3][i]
if output[2][i] != 'None':
k = output[2][i]
original, template_min = m.bin_down(
k, 0.0267097, 1.1826776, 21) #create arrays for ease of use
source, spectype = db.query.execute(
"SELECT spectral_types.source_id, spectral_types.spectral_type from spectral_types join spectra on spectral_types.source_id=spectra.source_id where spectral_types.regime='IR' and spectral_types.spectral_type>=20 and spectral_types.spectral_type<=30 and spectra.id='{}'"
.format(k)).fetchone()
template_min = u.norm_spec(template_min, object)
template_min = [i.value for i in template_min]
plt.errorbar(template_min[0],
template_min[1],
yerr=template_min[2],
marker="o",
label=str(spectype))
else:
with open(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/LateTdata/'
+ '{}'.format(output[1][i]) + '.txt') as f:
lines_after_17 = f.readlines()[7:]
Wtxt, Ftxt, Utxt = [], [], []
for line in lines_after_17:
columns = line.split()
wavx = float(columns[0])
flux = float(columns[1])
unx = float(columns[2])
Wtxt.append(wavx)
Ftxt.append(flux)
Utxt.append(unx)
f.close()
spectype = output[3][i]
binned_wl = 0 #defined by the wavelength points of HD19467B data
start = 1.1826776 - (0.0267097 / 2
) #start half way before 1st flux point
W, F, U = u.scrub([Wtxt, Ftxt, Utxt])
W = W.value
F = F.value
U = U.value
original = np.array([Wtxt, Ftxt, Utxt])
flux2 = 0
W_temp, F_temp, U_temp = [], [], []
unc2 = 0 #first wl point is at start+the step/2
wavelength = 0
#! loop through 21 iterations for the amount of wavelength ranges I have
for i in range(21):
binned_wl = 0.0267097 + start #range is half below and half above w1
flux2 = sum(F[np.where(np.logical_and(
W > start, W < binned_wl))]) #binning flux
unc2 = np.sqrt(
sum(U[np.where(np.logical_and(
W > start,
W < binned_wl))]**2)) #bin uncertainty in quadrature
start = binned_wl #set new range start
F_temp.append(flux2)
U_temp.append(unc2)
wavelength = 1.1826776 + (
i * 0.0267097
) #this is where the flux point will go on plot
W_temp.append(wavelength)
template = np.array([W_temp, F_temp, U_temp])
template_min = u.norm_spec(template, object)
template_min = [i.value for i in template_min]
plt.errorbar(template_min[0],
template_min[1],
yerr=template_min[2],
marker="o",
label=str(spectype))
plt.legend(loc='upper right')
plt.xlim(1.15, 1.75)
plt.ylim(0.001, 1.2)
plt.errorbar(object[0],
object[1],
yerr=object[2],
marker="o",
label='HD19467B')
plt.savefig(
'/Users/paigegiorla/Code/Python/BDNYC/TDwarfplotting/HD19467B_project/plots/bestfits_w_object.pdf'
)
plt.clf()
return sptlist, chilist
chisquare = [sptlist, chilist]