gh_version
gh_xte
ghats_all
gh_info
gh_licu,'file',time,rate
gh_plot_licu,time,rate,0,500
ghx,'event.pds',nu,pow,pow_e
gh_plot_power,nu,pow,pow_e
ghx,'event.pds',nu,pow,pow_e,/poisson
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0
gh_reb,nu,pow,pow_e,2,x,y,ye -> rebin
gh_reb,nu,pow,pow_e,-100,x,y,ye -> logarithmic rebinnin
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0,time=[0,1000] -> time selection
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0,rate=[0,1000] -> rate selection
gh_oplot,... -> oplot
gh_plot_hk,'event.pds'
gh_cross,....... -> for time lags. requires two fft files..etc look up manual
for burst :
tvscl,congrid(dyna[655:680,150:220],512,512)<5
a small dot - > burst oscillation
gh_dyn,dd,time,rate,nu,dyna,frebin=10
tvscl,congrid(dyna,512,512)
tvscl,congrid(dyna(*,1200:1537),512,512)
tvscl,congrid(dyna,512,512)< 5
zmore ****.gz -> preview gz file
gzip -d * -> zip everything
->untar data file->pca->gzip->ghats->gh_xte
p=pow/c
p_real=pow/(c-b)^2
plot, nu vs nu*p or nu vs nu*nu*p in power density spectra. this enhances the power in higher frequencies
plot nu vs pow to see peak. increase frequency resolution to increase accuracy
ghats to xpsec
gh_xspec,x,y,ye,'powspec' -> produces powspec.pha and powspec.rmf
xspec fit :
data powspec.pha -> load data
cpd /xw -> open GUI
plot data
setplot energy
XSPEC12>plot data
XSPEC12>plot ldata -> plot logarithmic
XSPEC12>ig 150.-** -> ignore data channel (to remove poisson noise part)
XSPEC12>notice 0.-160. -> include channel
XSPEC12>model loren -> choose model
6.5 0.05( 0.065) 0 0 1e+06 1e+06
1:lorentz:LineE>0 -1.0 0 0 0 0
0.1 0.05( 0.001) 0 0 10 20
2:lorentz:Width>0.5
1 0.01( 0.01) 0 0 1e+24 1e+24
3:lorentz:norm>50
--> negative width means fix variable
XSPEC12>pl -> plot
XSPEC12>renorm -> renormalise data
XSPEC12>addcomp 2 loren -> add another component and use it as secondary fitting component
newp 3 -> change value of parameter 3
del 4 -> delete component
fit -> fit result
err 1 1-12 -> fit with 1 sigma for parameters 1-12
show -> show parameters
save all model -> save model parameters
to see error :
err 1. # -> model number
to load model :
@model.xcm
fit
err 1 #-#
gh_xte
ghats_all
gh_info
gh_licu,'file',time,rate
gh_plot_licu,time,rate,0,500
ghx,'event.pds',nu,pow,pow_e
gh_plot_power,nu,pow,pow_e
ghx,'event.pds',nu,pow,pow_e,/poisson
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0
gh_reb,nu,pow,pow_e,2,x,y,ye -> rebin
gh_reb,nu,pow,pow_e,-100,x,y,ye -> logarithmic rebinnin
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0,time=[0,1000] -> time selection
ghx,'event.pds',nu,pow,pow_e,/poisson,rms=20.0,rate=[0,1000] -> rate selection
gh_oplot,... -> oplot
gh_plot_hk,'event.pds'
gh_cross,....... -> for time lags. requires two fft files..etc look up manual
for burst :
tvscl,congrid(dyna[655:680,150:220],512,512)<5
a small dot - > burst oscillation
gh_dyn,dd,time,rate,nu,dyna,frebin=10
tvscl,congrid(dyna,512,512)
tvscl,congrid(dyna(*,1200:1537),512,512)
tvscl,congrid(dyna,512,512)< 5
zmore ****.gz -> preview gz file
gzip -d * -> zip everything
->untar data file->pca->gzip->ghats->gh_xte
p=pow/c
p_real=pow/(c-b)^2
plot, nu vs nu*p or nu vs nu*nu*p in power density spectra. this enhances the power in higher frequencies
plot nu vs pow to see peak. increase frequency resolution to increase accuracy
ghats to xpsec
gh_xspec,x,y,ye,'powspec' -> produces powspec.pha and powspec.rmf
xspec fit :
data powspec.pha -> load data
cpd /xw -> open GUI
plot data
setplot energy
XSPEC12>plot data
XSPEC12>plot ldata -> plot logarithmic
XSPEC12>ig 150.-** -> ignore data channel (to remove poisson noise part)
XSPEC12>notice 0.-160. -> include channel
XSPEC12>model loren -> choose model
6.5 0.05( 0.065) 0 0 1e+06 1e+06
1:lorentz:LineE>0 -1.0 0 0 0 0
0.1 0.05( 0.001) 0 0 10 20
2:lorentz:Width>0.5
1 0.01( 0.01) 0 0 1e+24 1e+24
3:lorentz:norm>50
--> negative width means fix variable
XSPEC12>pl -> plot
XSPEC12>renorm -> renormalise data
XSPEC12>addcomp 2 loren -> add another component and use it as secondary fitting component
newp 3 -> change value of parameter 3
del 4 -> delete component
fit -> fit result
err 1 1-12 -> fit with 1 sigma for parameters 1-12
show -> show parameters
save all model -> save model parameters
to see error :
err 1. # -> model number
to load model :
@model.xcm
fit
err 1 #-#
