def plot_new_lc(row,
mjds,
mag,
err,
period,
target_name,
phased=1,
smooth=0.1):
idx = np.argsort(mjds)
mjds = mjds[idx]
mag = mag[idx]
err = err[idx]
phase = (mjds / period) - np.floor(mjds / period)
phase = np.concatenate(
(phase, (phase + 1.0), (phase + 2.0), (phase + 3.0), (phase + 4.0)))
mag_long = np.concatenate((mag, mag, mag, mag, mag))
nir1 = len(mag)
err_long = np.concatenate((err, err, err, err, err))
#obs = np.arange(1, num_frames+1, 1)
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(
mag_long, err_long, phase, len(mag), smooth)
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(
ir11[200:300], 100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
sdevir1 = sdevir1 / factor
target_name_display = re.sub('_', ' ', target_name)
mp.close()
mp.clf()
mp.axis([1, 3.5, (np.average(mag) + 0.3), (np.average(mag) - 0.3)])
mp.plot(ir1x, ir11, 'k-')
mp.errorbar(phase, mag_long, yerr=err_long, ls='None', zorder=4)
mp.plot(phase, mag_long, 'ro', ls='None', zorder=4)
mp.axhline(aveir1, color='k', ls='--')
mp.xlabel("Phase")
mp.ylabel('[3.6]')
mp.title('Recal:' + target_name_display + ', P = ' +
str(np.around(period, decimals=4)) + ' d, [3.6] = ' +
str(np.around(aveir1, decimals=3)) + ' $\pm$ ' +
str(np.around(sdevir1, decimals=3)) + ' mag')
mp.show()
save_lc(target_name + '.rrl_lc_data', mjds, mag, err)
return (aveir1, sdevir1)
def plot_existing_lc(row, phased=1, smooth=0.1):
target_name = row.ix[0, 'target_name']
rrl_data = target_name + '_rrlyrae.data'
rrl_df = pd.read_csv(rrl_data,
delim_whitespace=True,
header=None,
names=('mjds', 'mag', 'err'))
period = row.ix[0, 'period']
idx = np.argsort(rrl_df.mjds)
mjds = rrl_df.mjds[idx]
mag = rrl_df.mag[idx]
err = rrl_df.err[idx]
phase = (mjds / period) - np.floor(mjds / period)
phase = np.concatenate(
(phase, (phase + 1.0), (phase + 2.0), (phase + 3.0), (phase + 4.0)))
mag_long = np.concatenate((mag, mag, mag, mag, mag))
nir1 = len(mag)
err_long = np.concatenate((err, err, err, err, err))
#obs = np.arange(1, num_frames+1, 1)
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(
mag_long, err_long, phase, len(mag), smooth)
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(
ir11[200:300], 100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
sdevir1 = sdevir1 / factor
target_name_display = re.sub('_', ' ', target_name)
mp.close()
mp.clf()
mp.axis([1, 3.5, (np.average(mag) + 0.3), (np.average(mag) - 0.3)])
mp.plot(ir1x, ir11, 'k-')
mp.errorbar(phase, mag_long, yerr=err_long, ls='None', zorder=4)
mp.plot(phase, mag_long, 'ro', ls='None', zorder=4)
mp.axhline(aveir1, color='k', ls='--')
mp.xlabel("Phase")
mp.ylabel('[3.6]')
mp.title('Existing:' + target_name_display + ', P = ' +
str(np.around(period, decimals=4)) + ' d, [3.6] = ' +
str(np.around(aveir1, decimals=3)) + ' $\pm$ ' +
str(np.around(sdevir1, decimals=3)) + ' mag')
mp.show()
return (0)
def plot_existing_lc(row, phased=1, smooth=0.1):
target_name = row.ix[0, 'target_name']
rrl_data = target_name + '_rrlyrae.data'
rrl_df = pd.read_csv(rrl_data, delim_whitespace=True, header=None, names=('mjds', 'mag', 'err'))
period = row.ix[0, 'period']
idx = np.argsort(rrl_df.mjds)
mjds = rrl_df.mjds[idx]
mag = rrl_df.mag[idx]
err = rrl_df.err[idx]
phase = (mjds / period) - np.floor(mjds / period)
phase = np.concatenate((phase,(phase+1.0),(phase+2.0),(phase+3.0),(phase+4.0)))
mag_long = np.concatenate((mag, mag, mag, mag, mag))
nir1 = len(mag)
err_long = np.concatenate((err, err, err, err, err))
#obs = np.arange(1, num_frames+1, 1)
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(mag_long,err_long, phase,len(mag),smooth)
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(ir11[200:300],100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
sdevir1 = sdevir1/factor
target_name_display = re.sub('_', ' ', target_name)
mp.close()
mp.clf()
mp.axis([1,3.5,(np.average(mag) + 0.3),(np.average(mag) - 0.3)])
mp.plot(ir1x,ir11,'k-')
mp.errorbar(phase, mag_long, yerr=err_long, ls='None', zorder=4)
mp.plot(phase, mag_long, 'ro', ls='None', zorder=4)
mp.axhline(aveir1, color='k',ls='--')
mp.xlabel("Phase")
mp.ylabel('[3.6]')
mp.title('Existing:' + target_name_display + ', P = ' + str(np.around(period, decimals=4)) +' d, [3.6] = ' + str(np.around(aveir1, decimals=3)) + ' $\pm$ ' + str(np.around(sdevir1, decimals=3)) + ' mag')
mp.show()
return(0)
def plot_new_lc(row, mjds, mag, err, period, target_name, phased=1, smooth=0.1):
idx = np.argsort(mjds)
mjds = mjds[idx]
mag = mag[idx]
err = err[idx]
phase = (mjds / period) - np.floor(mjds / period)
phase = np.concatenate((phase,(phase+1.0),(phase+2.0),(phase+3.0),(phase+4.0)))
mag_long = np.concatenate((mag, mag, mag, mag, mag))
nir1 = len(mag)
err_long = np.concatenate((err, err, err, err, err))
#obs = np.arange(1, num_frames+1, 1)
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(mag_long,err_long, phase,len(mag),smooth)
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(ir11[200:300],100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
sdevir1 = sdevir1/factor
target_name_display = re.sub('_', ' ', target_name)
mp.close()
mp.clf()
mp.axis([1,3.5,(np.average(mag) + 0.3),(np.average(mag) - 0.3)])
mp.plot(ir1x,ir11,'k-')
mp.errorbar(phase, mag_long, yerr=err_long, ls='None', zorder=4)
mp.plot(phase, mag_long, 'ro', ls='None', zorder=4)
mp.axhline(aveir1, color='k',ls='--')
mp.xlabel("Phase")
mp.ylabel('[3.6]')
mp.title('Recal:' + target_name_display + ', P = ' + str(np.around(period, decimals=4)) +' d, [3.6] = ' + str(np.around(aveir1, decimals=3)) + ' $\pm$ ' + str(np.around(sdevir1, decimals=3)) + ' mag')
mp.show()
save_lc(target_name + '.rrl_lc_data', mjds, mag, err)
return(aveir1, sdevir1)
ax1 = plt.subplot(121)
ax1.axis([1,3.5,(maxlim),(minlim)])
titlestring = cepname2 + ', P = ' + str(period) + ' days'
#print titlestring
mp.title(titlestring, fontsize=20)
ax1.set_ylabel('Magnitude')
ax1.set_xlabel('Phase $\phi$')
## Fitting and plotting for each band
print nu, nb, nv, nr, ni, nj, nh, nk, nir1, nir2, nir3, nir4
if nu > 0:
u1, ux, yu, yeu, xphaseu = gf.fit_one_band(u,eu,phase,nu,xu)
ax1.plot(ux,u1+3.,'k-')
ax1.plot(xphaseu,yu+3.,color='Violet',marker='o',ls='None', label='$U+3$')
aveu, adevu, sdevu, varu, skewu, kurtosisu, ampu = gf.moment(u1[200:300],100)
erru = sdevu / sqrt(nu)
if nu > 1:
print '<U> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveu, sdevu/sqrt(nu), ampu)
print >> avsout, '<U> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveu, sdevu/sqrt(nu), ampu)
if nu == 1:
print 'U = {0:.3f} --- single point'.format(aveu)
print >> avsout, 'U = {0:.3f} --- single point'.format(aveu)
if nu == 0:
aveu = 99.99
erru = 9.999
mp.close()
mp.clf()
mp.axis([1,3.5,(maxlim),(minlim)])
ax1 = subplot(111)
#mp.xlabel('Phase $\phi$')
mp.ylabel('[3.6]')
titlestring = cepname + ', P = ' + str(period) + ' days'
#print titlestring
mp.title(titlestring)
## Fitting and plotting for each band
if nir1 > 0:
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(ir1,eir1,phase,nir1,xir1)
# ax1.plot(ir1x,ir11-0.9,'k-')
# ax1.plot(xphaseir1,yir1-0.9,color='MediumVioletRed',marker='o',ls='None', label='[3.6]-0.9')
## for RRLyrae WISE plots:
#mag1string = '<[3.6]> = ' + str(aveir1) + ' $\pm$ ' + str(sdevir1)
ax1.plot(ir1x,ir11,'k-')
ax1.errorbar(xphaseir1, yir1, yeir1, color='k', ls='None')
ax1.plot(xphaseir1,yir1,color='Turquoise',marker='o',ls='None', label='[3.6]')
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(ir11[200:300],100)
if phased == 1:
factor = sqrt(nir1)
if phased == 0:
factor = 1
if nir1 > 1:
print >> avsout, '<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f} N ir1 = {3}'.format(aveir1, sdevir1/factor, ampir1,nir1)
print '<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveir1, sdevir1/factor, ampir1)
def runGloess(mag_ch1, err_ch1, mag_ch2, err_ch2, LC_time, period, starname, xir1, xir2, wantcolour):
## Converting the gloess fourtran/pgplot code to python/matplotlib
## June 15 2012
## Version 1.0
## last edit - June 19 2012
## Next thing to add:
##Print fits to an output text file
## Open the input data file and read the info
#input = sys.argv[1]
#input = 'c:/Users/Jake/MPhys-code/MPhys-RRL/test_photometry/gloess-master/RRLyr.gloess_in'
#input = 'c:/Users/Jake/MPhys-code/MPhys-RRL/test_photometry/gloess-master/UVOct.gloess_in'
#counter = 0
## Want to know whether the IRAC data is phased or not.
## If it is phased, must reduce the uncertainty by another factor of sqrt(N)
#nir1 = sum(ir1<50)
#nir2= sum(ir2<50)
phased = 0 # our data is NOT phased
ir1 = np.array(mag_ch1)
#nir1 = len(ir1)
nir1 = sum(ir1<50)
eir1 = np.array(err_ch1)
#xir1 = 0.10
ir2 = np.array(mag_ch2)
#nir2 = len(ir2)
nir2 = sum(ir2<50)
eir2 = np.array(err_ch2)
#xir2 = 0.10
mjd = np.array(LC_time)
# Phases don't need to be done individually by band - only depends on P
phase = (mjd / period) - np.floor(mjd / period)
#phase = np.concatenate((phase,(phase+1.0),(phase+2.0),(phase+3.0),(phase+4.0)))
# Usage: fit_one_band(data,err,phases,n,smooth):
maxvals = []
minvals = []
if nir1 > 0:
maxvals.append(np.amax(ir1[ir1<50])-1.4)
minvals.append(np.amin(ir1[ir1<50])-1.4)
if nir2 > 0:
maxvals.append(np.amax(ir2[ir2<50])-1.8)
minvals.append(np.amin(ir2[ir2<50])-1.8)
maxvals = np.array(maxvals)
minvals = np.array(minvals)
max = np.max(maxvals)
min = np.min(minvals)
print(starname, '---- Period =', period, 'days')
print('------------------------------------------------------')
# Set up names for output files
#fitname = starname + '.glo_fits'
#avname = str(starname) + '.glo_avs'
#avsout = open(avname,'w')
#fitout = open(fitname,'w')
maxlim = max + 0.5
minlim = min - 0.5
plt.clf()
#fig = plt.figure()
#ax1 = fig.add_subplot(111)
#plt.figure(figsize=(16.0,10.0))
gs = gridspec.GridSpec(3, 4)
ax1 = plt.subplot(gs[:, 0:2])
ax2 = plt.subplot(gs[0, 2:4])
ax3 = plt.subplot(gs[1, 2:4])
ax4 = plt.subplot(gs[2, 2:4])
ax1.axis([1,3.5,(maxlim),(minlim)])
titlestring = str(starname) + ', P = ' + str(period) + ' days'
#print titlestring
plt.suptitle(titlestring, fontsize=20)
ax1.set_ylabel('Magnitude')
ax1.set_xlabel('Phase $\phi$')
## Fitting and plotting for each band
print(nir1, nir2)
if nir1 > 0:
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(ir1,eir1,phase,nir1,xir1)
ax1.plot(ir1x,ir11-1.4,'k-')
ax1.plot(xphaseir1,yir1-1.4,color='MediumVioletRed',marker='o',ls='None', label='$[3.6]-1.4$')
## for RRLyrae WISE plots:
# ax1.plot(ir1x,ir11+1.,'k-')
# ax1.plot(xphaseir1,yir1+1.,color='Turquoise',marker='o',ls='None', label='W1+1.0')
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(ir11[200:300],100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
sdevir1 = sdevir1 / factor # this way, the value spat out at the end should include this factor
if nir1 > 1:
#print('<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f} N ir1 = {3}'.format(aveir1, sdevir1, ampir1,nir1), file = avsout)
print('<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveir1, sdevir1, ampir1))
if nir1 == 1:
#print('[3.6] = {0:.3f} --- single point'.format(aveir1), file=avsout)
print('[3.6] = {0:.3f} --- single point'.format(aveir1))
ax2.axis([1,3.5,(np.average(ir11[200:300]) + 0.4),(np.average(ir11[200:300]) - 0.4)])
ax2.yaxis.tick_right()
ax2.plot(ir1x,ir11,'k-')
ax2.plot(xphaseir1,yir1,color='MediumVioletRed',marker='o',ls='None', label='$[3.6]$')
ax2.annotate('$[3.6]$', xy=(0.04, 0.8375), xycoords='axes fraction', fontsize=16)
else:
aveir1 = float("NaN")
ampir1 = float("NaN")
sdevir1 = float("NaN")
if nir2 > 0:
ir21, ir2x, yir2, yeir2, xphaseir2 = gf.fit_one_band(ir2,eir2,phase,nir2,xir2)
ax1.plot(ir2x,ir21-1.8,'k-')
ax1.plot(xphaseir2,yir2-1.8,color='DeepPink',marker='o',ls='None', label='$[4.5]-1.8$')
## For RRLyrae WISE plots:
# ax1.plot(ir2x,ir21,'k-')
# ax1.plot(xphaseir2,yir2,color='Gold',marker='o',ls='None', label='W2')
aveir2, adevir2, sdevir2, varir2, skewir2, kurtosisir2, ampir2= gf.moment(ir21[200:300],100)
if phased == 1:
factor = np.sqrt(nir2)
if phased == 0:
factor = 1
sdevir2 = sdevir2 / factor
if nir2 > 1:
#print('<[4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f} N IR2 = {3}'.format(aveir2, sdevir2, ampir2,nir2), file = avsout)
print('<[4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveir2, sdevir2, ampir2))
if nir2 == 1:
#print('[4.5] = {0:.3f} --- single point'.format(aveir2), file = avsout)
print('[4.5] = {0:.3f} --- single point'.format(aveir2))
ax3.axis([1,3.5,(np.average(ir21[200:300]) + 0.4),(np.average(ir21[200:300]) - 0.4)])
ax3.yaxis.tick_right()
ax3.plot(ir2x,ir21,'k-')
ax3.plot(xphaseir2,yir2,color='DeepPink',marker='o',ls='None', label='$[3.6]$')
ax3.annotate('$[4.5]$', xy=(0.04, 0.8375), xycoords='axes fraction',fontsize=16)
else:
aveir2 = float("NaN")
ampir2 = float("NaN")
sdevir2 = float("NaN")
handles, labels = ax1.get_legend_handles_labels()
#ax1.legend(handles[::-1],labels[::-1],bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0., numpoints=1)
ax1.legend(handles[::-1],labels[::-1],loc=4, numpoints=1,prop={'size':10})
#plt.setp(ax1.get_xticklabels(),visible=False)
if (wantcolour == 'yes' or wantcolour == True):
if nir1 == nir2:
### Define the colour curve
colour_curve = ir11 - ir21
## Define the colour points
ch1_points = yir1[yir1<99]
ch2_points = yir2[yir2<99]
colour_points = ch1_points - ch2_points
colour_phases = xphaseir1[yir1<99]
colour_points = np.concatenate((colour_points,colour_points,colour_points,colour_points,colour_points))
colour_phases = np.concatenate((colour_phases,(colour_phases+1.),(colour_phases+2.),(colour_phases+3.),(colour_phases+4.)))
avecol, adevcol, sdevcol, varcol, skewcol, kurtosiscol, ampcol = gf.moment(colour_curve[200:300],100)
#print('<[3.6] - [4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(avecol, sdevcol/factor, ampcol), file = avsout)
print('<[3.6] - [4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(avecol, sdevcol/factor, ampcol))
print(np.average(ir11[200:300]) + 0.3)
print(np.average(ir11[200:300]) - 0.3)
#divider = make_axes_locatable(ax1)
#axcol = divider.append_axes("bottom",1.2,pad=0.1,sharex=ax1)
myaxis2 = [1,3.5,-0.2,0.2]
ax4.axis(myaxis2)
ax4.yaxis.tick_right()
ax4.yaxis.set_major_locator(plt.FixedLocator([-0.1,0,0.1]))
ax4.plot(ir1x,colour_curve,'k-')
ax4.plot(colour_phases,colour_points,color='Black',marker='o',ls='None', label='$[3.6]-[4.5]$')
ax4.set_xlabel('Phase $\phi$')
#ax4.annotate('$[3.6] - [4.5]$', xy=(1.1, 0.135), xycoords='data')
ax4.annotate('$[3.6] - [4.5]$', xy=(0.04, 0.8375), xycoords='axes fraction',fontsize=16)
ax4.hlines(0,1,3.5,'k','dashdot')
else:
print("Channels don't have the same number of measurements, so colour curve couldn't be plotted")
plt.setp(ax2.get_xticklabels(),visible=False)
plt.setp(ax3.get_xticklabels(),visible=False)
plotname = str(starname)+'.eps'
#plt.savefig(plotname, transparent='True')
plt.savefig(plotname)
#avsout.close()
plt.show()
#fitout.close()
return aveir1, ampir1, sdevir1, aveir2, ampir2, sdevir2
def runGloess(mag_ch1, err_ch1, LC_time):
#print(dummy)
#dummy += 1
#print(dummy)
du = []
db = []
dv = []
dr = []
di = []
dj = []
dh = []
dk = []
dir1 = []
dir2 = []
dir3 = []
dir4 = []
deu = []
deb = []
dev = []
der = []
dei = []
dej = []
deh = []
dek = []
deir1 = []
deir2 = []
deir3 = []
deir4 = []
dmjd = []
## Converting the gloess fourtran/pgplot code to python/matplotlib
## June 15 2012
## Version 1.0
## last edit - June 19 2012
## Next thing to add:
##Print fits to an output text file
## Open the input data file and read the info
#input = sys.argv[1]
#input = 'c:/Users/Jake/MPhys-code/MPhys-RRL/test_photometry/gloess-master/RRLyr.gloess_in'
input = 'c:/Users/Jake/MPhys-code/MPhys-RRL/test_photometry/gloess-master/UVOct.gloess_in'
counter = 0
## Want to know whether the IRAC data is phased or not.
## If it is phased, must reduce the uncertainty by another factor of sqrt(N)
## if phased == 1 then true. if phased == 0, false
print(input)
for line in open(input):
data = line.split()
if counter == 0:
cepname = data[0]
if counter == 1:
period = float(data[0])
if period > 0:
phased = 1
else:
phased = 0
if counter == 2:
nlines = float(data[0])
if counter == 3:
xu = float(data[0])
xb = float(data[1])
xv = float(data[2])
xr = float(data[3])
xi = float(data[4])
xj = float(data[5])
xh = float(data[6])
xk = float(data[7])
xir1 = float(data[8])
xir2 = float(data[9])
xir3 = float(data[10])
xir4 = float(data[11])
if counter > 3:
dmjd.append(float(data[0]))
du.append(float(data[1]))
deu.append(float(data[2]))
db.append(float(data[3]))
deb.append(float(data[4]))
dv.append(float(data[5]))
dev.append(float(data[6]))
dr.append(float(data[7]))
der.append(float(data[8]))
di.append(float(data[9]))
dei.append(float(data[10]))
dj.append(float(data[11]))
dej.append(float(data[12]))
dh.append(float(data[13]))
deh.append(float(data[14]))
dk.append(float(data[15]))
dek.append(float(data[16]))
dir1.append(float(data[17]))
deir1.append(float(data[18]))
dir2.append(float(data[19]))
deir2.append(float(data[20]))
dir3.append(float(data[21]))
deir3.append(float(data[22]))
dir4.append(float(data[23]))
deir4.append(float(data[24]))
counter = counter + 1
## Read in all the data from the file and filled the arrays. Need to convert these to numpy arrays.
number = counter - 4 # Number data lines in the file
#print number
u = np.array(du)
b = np.array(db)
v = np.array(dv)
r = np.array(dr)
i = np.array(di)
j = np.array(dj)
h = np.array(dh)
k = np.array(dk)
ir1 = np.array(dir1)
ir2 = np.array(dir2)
ir3 = np.array(dir3)
ir4 = np.array(dir4)
eu = np.array(deu)
eb = np.array(deb)
ev = np.array(dev)
er = np.array(der)
ei = np.array(dei)
ej = np.array(dej)
eh = np.array(deh)
ek = np.array(dek)
eir1 = np.array(deir1)
eir2 = np.array(deir2)
eir3 = np.array(deir3)
eir4 = np.array(deir4)
mjd = np.array(dmjd)
nu = sum(u < 50)
nb = sum(b < 50)
nv = sum(v < 50)
nr = sum(r < 50)
ni = sum(i < 50)
nj = sum(j < 50)
nh = sum(h < 50)
nk = sum(k < 50)
nir1 = sum(ir1 < 50)
nir2 = sum(ir2 < 50)
nir3 = sum(ir3 < 50)
nir4 = sum(ir4 < 50)
ir1 = np.array(mag_ch1)
nir1 = len(ir1)
eir1 = np.array(err_ch1)
xir1 = 0.10
mjd = np.array(LC_time)
# Phases don't need to be done individually by band - only depends on P
phase = (mjd / period) - np.floor(mjd / period)
#phase = np.concatenate((phase,(phase+1.0),(phase+2.0),(phase+3.0),(phase+4.0)))
# Usage: fit_one_band(data,err,phases,n,smooth):
maxvals = []
minvals = []
if nu > 0:
maxvals.append(np.amax(u[u < 50]) + 3.0)
minvals.append(np.amin(u[u < 50]) + 3.0)
if nb > 0:
maxvals.append(np.amax(b[b < 50]) + 1.5)
minvals.append(np.amin(b[b < 50]) + 1.5)
if nv > 0:
maxvals.append(np.amax(v[v < 50]) + 1.2)
minvals.append(np.amin(v[v < 50]) + 1.2)
if nr > 0:
maxvals.append(np.amax(r[r < 50]) + 0.7)
minvals.append(np.amin(r[r < 50]) + 0.7)
if ni > 0:
maxvals.append(np.amax(i[i < 50]) + 0.2)
minvals.append(np.amin(i[i < 50]) + 0.2)
if nj > 0:
maxvals.append(np.amax(j[j < 50]))
minvals.append(np.amin(j[j < 50]))
if nh > 0:
maxvals.append(np.amax(h[h < 50]) - 0.4)
minvals.append(np.amin(h[h < 50]) - 0.4)
if nk > 0:
maxvals.append(np.amax(k[k < 50]) - 0.8)
minvals.append(np.amin(k[k < 50]) - 0.8)
if nir1 > 0:
maxvals.append(np.amax(ir1[ir1 < 50]) - 1.4)
minvals.append(np.amin(ir1[ir1 < 50]) - 1.4)
if nir2 > 0:
maxvals.append(np.amax(ir2[ir2 < 50]) - 1.8)
minvals.append(np.amin(ir2[ir2 < 50]) - 1.8)
if nir3 > 0:
maxvals.append(np.amax(ir3[ir3 < 50]) - 2.2)
minvals.append(np.amin(ir3[ir3 < 50]) - 2.2)
if nir4 > 0:
maxvals.append(np.amax(ir4[ir4 < 50]) - 2.6)
minvals.append(np.amin(ir4[ir4 < 50]) - 2.6)
maxvals = np.array(maxvals)
minvals = np.array(minvals)
max = np.max(maxvals)
min = np.min(minvals)
print(cepname, ' ---- Period =', period, 'days')
print('------------------------------------------------------')
# Set up names for output files
#fitname = cepname + '.glo_fits'
avname = cepname + '.glo_avs'
avsout = open(avname, 'w')
#fitout = open(fitname,'w')
maxlim = max + 0.5
minlim = min - 0.5
plt.clf()
#fig = plt.figure()
#ax1 = fig.add_subplot(111)
#plt.figure(figsize=(16.0,10.0))
gs = gridspec.GridSpec(3, 4)
ax1 = plt.subplot(gs[:, 0:2])
ax2 = plt.subplot(gs[0, 2:4])
ax3 = plt.subplot(gs[1, 2:4])
ax4 = plt.subplot(gs[2, 2:4])
ax1.axis([1, 3.5, (maxlim), (minlim)])
titlestring = cepname + ', P = ' + str(period) + ' days'
#print titlestring
plt.suptitle(titlestring, fontsize=20)
ax1.set_ylabel('Magnitude')
ax1.set_xlabel('Phase $\phi$')
## Fitting and plotting for each band
print(nu, nb, nv, nr, ni, nj, nh, nk, nir1, nir2, nir3, nir4)
if nir1 > 0:
ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(
ir1, eir1, phase, nir1, xir1)
ax1.plot(ir1x, ir11 - 1.4, 'k-')
ax1.plot(xphaseir1,
yir1 - 1.4,
color='MediumVioletRed',
marker='o',
ls='None',
label='$[3.6]-1.4$')
## for RRLyrae WISE plots:
# ax1.plot(ir1x,ir11+1.,'k-')
# ax1.plot(xphaseir1,yir1+1.,color='Turquoise',marker='o',ls='None', label='W1+1.0')
aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(
ir11[200:300], 100)
if phased == 1:
factor = np.sqrt(nir1)
if phased == 0:
factor = 1
if nir1 > 1:
print(
'<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f} N ir1 = {3}'
.format(aveir1, sdevir1 / factor, ampir1, nir1),
file=avsout)
print(
'<[3.6]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}'
.format(aveir1, sdevir1 / factor, ampir1))
if nir1 == 1:
print('[3.6] = {0:.3f} --- single point'.format(aveir1),
file=avsout)
print('[3.6] = {0:.3f} --- single point'.format(aveir1))
'''if nir2 > 0:
ir21, ir2x, yir2, yeir2, xphaseir2 = gf.fit_one_band(ir2,eir2,phase,nir2,xir2)
ax1.plot(ir2x,ir21-1.8,'k-')
ax1.plot(xphaseir2,yir2-1.8,color='DeepPink',marker='o',ls='None', label='$[4.5]-1.8$')
## For RRLyrae WISE plots:
# ax1.plot(ir2x,ir21,'k-')
# ax1.plot(xphaseir2,yir2,color='Gold',marker='o',ls='None', label='W2')
aveir2, adevir2, sdevir2, varir2, skewir2, kurtosisir2, ampir2= gf.moment(ir21[200:300],100)
if phased == 1:
factor = np.sqrt(nir2)
if phased == 0:
factor = 1
if nir2 > 1:
print('<[4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f} N IR2 = {3}'.format(aveir2, sdevir2/factor, ampir2,nir2), file = avsout)
print('<[4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(aveir2, sdevir2/factor, ampir2))
if nir2 == 1:
print('[4.5] = {0:.3f} --- single point'.format(aveir2), file = avsout)
print('[4.5] = {0:.3f} --- single point'.format(aveir2))'''
handles, labels = ax1.get_legend_handles_labels()
#ax1.legend(handles[::-1],labels[::-1],bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0., numpoints=1)
ax1.legend(handles[::-1],
labels[::-1],
loc=4,
numpoints=1,
prop={'size': 10})
#plt.setp(ax1.get_xticklabels(),visible=False)
'''### Define the colour curve
colour_curve = ir11 - ir21
## Define the colour points
ch1_points = yir1[yir1<99]
ch2_points = yir2[yir2<99]
colour_points = ch1_points - ch2_points
colour_phases = xphaseir1[yir1<99]
colour_points = np.concatenate((colour_points,colour_points,colour_points,colour_points,colour_points))
colour_phases = np.concatenate((colour_phases,(colour_phases+1.),(colour_phases+2.),(colour_phases+3.),(colour_phases+4.)))
avecol, adevcol, sdevcol, varcol, skewcol, kurtosiscol, ampcol = gf.moment(colour_curve[200:300],100)
print('<[3.6] - [4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(avecol, sdevcol/factor, ampcol), file = avsout)
print('<[3.6] - [4.5]> = {0:.3f} std dev = {1:.3f} amplitude = {2:.3f}' .format(avecol, sdevcol/factor, ampcol))'''
print(np.average(ir11[200:300]) + 0.3)
print(np.average(ir11[200:300]) - 0.3)
ax2.axis([
1, 3.5, (np.average(ir11[200:300]) + 0.4),
(np.average(ir11[200:300]) - 0.4)
])
ax2.yaxis.tick_right()
ax2.plot(ir1x, ir11, 'k-')
ax2.plot(xphaseir1,
yir1,
color='MediumVioletRed',
marker='o',
ls='None',
label='$[3.6]$')
ax2.annotate('$[3.6]$',
xy=(0.04, 0.8375),
xycoords='axes fraction',
fontsize=16)
'''ax3.axis([1,3.5,(np.average(ir21[200:300]) + 0.4),(np.average(ir21[200:300]) - 0.4)])
ax3.yaxis.tick_right()
ax3.plot(ir2x,ir21,'k-')
ax3.plot(xphaseir2,yir2,color='DeepPink',marker='o',ls='None', label='$[3.6]$')
ax3.annotate('$[4.5]$', xy=(0.04, 0.8375), xycoords='axes fraction',fontsize=16)'''
#divider = make_axes_locatable(ax1)
#axcol = divider.append_axes("bottom",1.2,pad=0.1,sharex=ax1)
myaxis2 = [1, 3.5, -0.2, 0.2]
ax4.axis(myaxis2)
ax4.yaxis.tick_right()
ax4.yaxis.set_major_locator(plt.FixedLocator([-0.1, 0, 0.1]))
#ax4.plot(ir1x,colour_curve,'k-')
#ax4.plot(colour_phases,colour_points,color='Black',marker='o',ls='None', label='$[3.6]-[4.5]$')
ax4.set_xlabel('Phase $\phi$')
#ax4.annotate('$[3.6] - [4.5]$', xy=(1.1, 0.135), xycoords='data')
ax4.annotate('$[3.6] - [4.5]$',
xy=(0.04, 0.8375),
xycoords='axes fraction',
fontsize=16)
ax4.hlines(0, 1, 3.5, 'k', 'dashdot')
plt.setp(ax2.get_xticklabels(), visible=False)
plt.setp(ax3.get_xticklabels(), visible=False)
plotname = cepname + '.eps'
#plt.savefig(plotname, transparent='True')
plt.savefig(plotname)
avsout.close()
plt.show()
#fitout.close()
#return dummy
min = np.min(minvals) print cepname, ' ---- Period =', period, 'days' print '------------------------------------------------------' # Set up names for output files #fitname = cepname + '.glo_fits' avname = cepname + '.glo_avs' avsout = open(avname,'w') #fitout = open(fitname,'w') ## gloess differential v1, vx, yv, yev, xphasev = gf.fit_one_band(v,ev,phase,nv,xv) ir11, ir1x, yir1, yeir1, xphaseir1 = gf.fit_one_band(ir1,eir1,phase,nir1,xir1) avev, adevv, sdevv, varv, skewv, kurtosisv, ampv = gf.moment(v1[200:300],100) aveir1, adevir1, sdevir1, varir1, skewir1, kurtosisir1, ampir1 = gf.moment(ir11[200:300],100) offset = avev - aveir1 off_ir11 = ir11 + offset off_yir1 = yir1 + offset dy1dp_max_light = 1000 dy1dp_min_light = 1000 dyvdp_max_light = 1000 dyvdp_min_light = 1000