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e522a09084 ... bbceab82a7

Author SHA1 Message Date
Stephan I. Böttcher
bbceab82a7 DORN/RC: bgo calib 
Remove pulser calib for slice 1
Intercalibtrate the BGO signals using 2025-07-24-seth-9
Raise HETB threshold to 15
 2025-07-25 13:23:54 +02:00
Stephan I. Böttcher
9a125cd357 dorn_hk: read from stdin, default --what=pretty 2025-07-25 13:23:24 +02:00
Stephan I. Böttcher
c2b723e3f6 seth_hist, bgo fits 2025-07-25 13:22:07 +02:00
Stephan I. Böttcher
f04b5ef9c5 ahepam: make %.Itime 2025-07-18 12:25:33 +02:00
8 changed files with 603 additions and 42 deletions
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60
ahepam/2025-07-24-seth-9-fit.gpt Normal file
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@ -0,0 +1,60 @@
#!/usr/local/bin/gnuplot
fn = "2025-07-24-seth-9"
set tit fn
set samples 10000
set xrange [ 10.6473 : 72.0818 ] noreverse writeback
set yrange [ 0.0824143 : 319.883 ] noreverse writeback
set logscale y
set fit logfile fn.".fitlog" brief errorvariables
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
Itime = 1
array a[13] = [,,,,,,, \
859.092052918976, 836.661498376021, 774.308992188805, \
868.7682895186, 886.040923070115, 839.914159064545 ]
array e[13] = [,,,,,,, \
23.1129960324349, 23.7449670595066, 24.6546072882361, \
21.9335751062165, 21.1775893511824, 22.8589648291739 ]
array s[13] = [,,,,,,, \
2.93026673210812, 3.02173616155514, 3.36397159128985, \
2.83639020739353, 2.83826477232856, 3.01391842919058 ]
a_8__err = 17.0887311070516
e_8__err = 0.0889472501153327
s_8__err = 0.0935171552631583
a_9__err = 17.4032436542983
e_9__err = 0.097488036256732
s_9__err = 0.106290500933751
a_10__err = 15.7027910610272
e_10__err = 0.105569403248042
s_10__err = 0.114612006466013
a_11__err = 20.7697327629865
e_11__err = 0.100670852522929
s_11__err = 0.102334658647667
a_12__err = 16.5452708067998
e_12__err = 0.0803181922085788
s_12__err = 0.0845228040571695
a_13__err = 18.1355609385629
e_13__err = 0.105214047154568
s_13__err = 0.118194681270004
plot for [c=8:13] "seth/".fn.".seth_hist" \
u 1:(column(2+c)/Itime) \
t "".c." ".columnhead(2+c) \
w histeps, \
for [c=8:13] mips(c,x)+0.1 not w l lt c-7
do for [c=8:13] {
fit [] [a[c]/10.:*] \
mips(c,x) \
"seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) \
zerror \
via a[c],e[c],s[c]
replot
}

468
ahepam/2025-07-24-seth-9.fitlog Normal file
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@ -0,0 +1,468 @@
*******************************************************************************
Fri Jul 25 13:03:18 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [85.9092 : *]
#datapoints = 48
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[8] e[8] s[8]
0 6.4318474790e+01 0.00e+00 2.93e+01 8.590921e+02 2.311300e+01 2.930267e+00
1 6.4318474759e+01 -4.89e-05 2.93e+00 8.590923e+02 2.311300e+01 2.930265e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 64.3185
rel. change during last iteration : -4.88767e-10
degrees of freedom (FIT_NDF) : 45
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.19553
variance of residuals (reduced chisquare) = WSSR/ndf : 1.4293
p-value of the Chisq distribution (FIT_P) : 0.0307724
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[8] = 859.092 +/- 17.09 (1.989%)
e[8] = 23.113 +/- 0.08895 (0.3848%)
s[8] = 2.93027 +/- 0.09352 (3.191%)
correlation matrix of the fit parameters:
a[8] e[8] s[8]
a[8] 1.000
e[8] -0.251 1.000
s[8] -0.719 0.383 1.000
*******************************************************************************
Fri Jul 25 13:03:18 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [83.6661 : *]
#datapoints = 48
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[9] e[9] s[9]
0 6.8507114449e+01 0.00e+00 2.75e+01 8.366615e+02 2.374497e+01 3.021736e+00
1 6.8507114449e+01 -2.07e-11 2.75e+04 8.366615e+02 2.374497e+01 3.021736e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 68.5071
rel. change during last iteration : -2.07436e-16
degrees of freedom (FIT_NDF) : 45
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.23385
variance of residuals (reduced chisquare) = WSSR/ndf : 1.52238
p-value of the Chisq distribution (FIT_P) : 0.0135097
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[9] = 836.661 +/- 17.4 (2.08%)
e[9] = 23.745 +/- 0.09749 (0.4106%)
s[9] = 3.02174 +/- 0.1063 (3.518%)
correlation matrix of the fit parameters:
a[9] e[9] s[9]
a[9] 1.000
e[9] -0.211 1.000
s[9] -0.725 0.297 1.000
*******************************************************************************
Fri Jul 25 13:03:19 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [77.4309 : *]
#datapoints = 54
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[10] e[10] s[10]
0 7.6078685857e+01 0.00e+00 2.44e+01 7.743090e+02 2.465461e+01 3.363972e+00
1 7.6078685837e+01 -2.66e-05 2.44e+00 7.743093e+02 2.465461e+01 3.363969e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 76.0787
rel. change during last iteration : -2.66022e-10
degrees of freedom (FIT_NDF) : 51
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.22137
variance of residuals (reduced chisquare) = WSSR/ndf : 1.49174
p-value of the Chisq distribution (FIT_P) : 0.0129596
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[10] = 774.309 +/- 15.7 (2.028%)
e[10] = 24.6546 +/- 0.1056 (0.4282%)
s[10] = 3.36397 +/- 0.1146 (3.407%)
correlation matrix of the fit parameters:
a[10] e[10] s[10]
a[10] 1.000
e[10] -0.179 1.000
s[10] -0.726 0.235 1.000
*******************************************************************************
Fri Jul 25 13:03:19 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [86.8768 : *]
#datapoints = 49
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[11] e[11] s[11]
0 9.5016426174e+01 0.00e+00 2.83e+01 8.687683e+02 2.193358e+01 2.836390e+00
1 9.5016426174e+01 -1.50e-11 2.83e+06 8.687683e+02 2.193358e+01 2.836390e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 95.0164
rel. change during last iteration : -1.49562e-16
degrees of freedom (FIT_NDF) : 46
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.43721
variance of residuals (reduced chisquare) = WSSR/ndf : 2.06557
p-value of the Chisq distribution (FIT_P) : 2.90326e-05
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[11] = 868.768 +/- 20.77 (2.391%)
e[11] = 21.9336 +/- 0.1007 (0.459%)
s[11] = 2.83639 +/- 0.1023 (3.608%)
correlation matrix of the fit parameters:
a[11] e[11] s[11]
a[11] 1.000
e[11] -0.203 1.000
s[11] -0.722 0.280 1.000
*******************************************************************************
Fri Jul 25 13:03:19 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [88.6041 : *]
#datapoints = 47
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[12] e[12] s[12]
0 5.5243080524e+01 0.00e+00 2.81e+01 8.860409e+02 2.117759e+01 2.838265e+00
1 5.5243080524e+01 -1.73e-08 2.81e+02 8.860409e+02 2.117759e+01 2.838265e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 55.2431
rel. change during last iteration : -1.72738e-13
degrees of freedom (FIT_NDF) : 44
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.1205
variance of residuals (reduced chisquare) = WSSR/ndf : 1.25552
p-value of the Chisq distribution (FIT_P) : 0.119174
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[12] = 886.041 +/- 16.55 (1.867%)
e[12] = 21.1776 +/- 0.08032 (0.3793%)
s[12] = 2.83826 +/- 0.08452 (2.978%)
correlation matrix of the fit parameters:
a[12] e[12] s[12]
a[12] 1.000
e[12] -0.245 1.000
s[12] -0.723 0.358 1.000
*******************************************************************************
Fri Jul 25 13:03:19 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [83.9914 : *]
#datapoints = 46
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[13] e[13] s[13]
0 6.7709403756e+01 0.00e+00 2.49e+01 8.399142e+02 2.285896e+01 3.013918e+00
1 6.7709403750e+01 -9.61e-06 2.49e+01 8.399142e+02 2.285897e+01 3.013919e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 67.7094
rel. change during last iteration : -9.60902e-11
degrees of freedom (FIT_NDF) : 43
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.25485
variance of residuals (reduced chisquare) = WSSR/ndf : 1.57464
p-value of the Chisq distribution (FIT_P) : 0.00947836
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[13] = 839.914 +/- 18.14 (2.159%)
e[13] = 22.859 +/- 0.1052 (0.4603%)
s[13] = 3.01392 +/- 0.1182 (3.922%)
correlation matrix of the fit parameters:
a[13] e[13] s[13]
a[13] 1.000
e[13] -0.137 1.000
s[13] -0.728 0.143 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [85.9092 : *]
#datapoints = 48
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[8] e[8] s[8]
0 6.4318474790e+01 0.00e+00 2.93e+01 8.590921e+02 2.311300e+01 2.930267e+00
1 6.4318474759e+01 -4.89e-05 2.93e+00 8.590923e+02 2.311300e+01 2.930265e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 64.3185
rel. change during last iteration : -4.88767e-10
degrees of freedom (FIT_NDF) : 45
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.19553
variance of residuals (reduced chisquare) = WSSR/ndf : 1.4293
p-value of the Chisq distribution (FIT_P) : 0.0307724
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[8] = 859.092 +/- 17.09 (1.989%)
e[8] = 23.113 +/- 0.08895 (0.3848%)
s[8] = 2.93027 +/- 0.09352 (3.191%)
correlation matrix of the fit parameters:
a[8] e[8] s[8]
a[8] 1.000
e[8] -0.251 1.000
s[8] -0.719 0.383 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [83.6661 : *]
#datapoints = 48
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[9] e[9] s[9]
0 6.8507114449e+01 0.00e+00 2.75e+01 8.366615e+02 2.374497e+01 3.021736e+00
1 6.8507114449e+01 -2.07e-11 2.75e+04 8.366615e+02 2.374497e+01 3.021736e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 68.5071
rel. change during last iteration : -2.07436e-16
degrees of freedom (FIT_NDF) : 45
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.23385
variance of residuals (reduced chisquare) = WSSR/ndf : 1.52238
p-value of the Chisq distribution (FIT_P) : 0.0135097
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[9] = 836.661 +/- 17.4 (2.08%)
e[9] = 23.745 +/- 0.09749 (0.4106%)
s[9] = 3.02174 +/- 0.1063 (3.518%)
correlation matrix of the fit parameters:
a[9] e[9] s[9]
a[9] 1.000
e[9] -0.211 1.000
s[9] -0.725 0.297 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [77.4309 : *]
#datapoints = 54
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[10] e[10] s[10]
0 7.6078685857e+01 0.00e+00 2.44e+01 7.743090e+02 2.465461e+01 3.363972e+00
1 7.6078685837e+01 -2.66e-05 2.44e+00 7.743093e+02 2.465461e+01 3.363969e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 76.0787
rel. change during last iteration : -2.66022e-10
degrees of freedom (FIT_NDF) : 51
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.22137
variance of residuals (reduced chisquare) = WSSR/ndf : 1.49174
p-value of the Chisq distribution (FIT_P) : 0.0129596
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[10] = 774.309 +/- 15.7 (2.028%)
e[10] = 24.6546 +/- 0.1056 (0.4282%)
s[10] = 3.36397 +/- 0.1146 (3.407%)
correlation matrix of the fit parameters:
a[10] e[10] s[10]
a[10] 1.000
e[10] -0.179 1.000
s[10] -0.726 0.235 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [86.8768 : *]
#datapoints = 49
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[11] e[11] s[11]
0 9.5016426174e+01 0.00e+00 2.83e+01 8.687683e+02 2.193358e+01 2.836390e+00
1 9.5016426174e+01 -1.50e-11 2.83e+06 8.687683e+02 2.193358e+01 2.836390e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 95.0164
rel. change during last iteration : -1.49562e-16
degrees of freedom (FIT_NDF) : 46
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.43721
variance of residuals (reduced chisquare) = WSSR/ndf : 2.06557
p-value of the Chisq distribution (FIT_P) : 2.90326e-05
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[11] = 868.768 +/- 20.77 (2.391%)
e[11] = 21.9336 +/- 0.1007 (0.459%)
s[11] = 2.83639 +/- 0.1023 (3.608%)
correlation matrix of the fit parameters:
a[11] e[11] s[11]
a[11] 1.000
e[11] -0.203 1.000
s[11] -0.722 0.280 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [88.6041 : *]
#datapoints = 47
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[12] e[12] s[12]
0 5.5243080524e+01 0.00e+00 2.81e+01 8.860409e+02 2.117759e+01 2.838265e+00
1 5.5243080524e+01 -1.73e-08 2.81e+02 8.860409e+02 2.117759e+01 2.838265e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 55.2431
rel. change during last iteration : -1.72738e-13
degrees of freedom (FIT_NDF) : 44
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.1205
variance of residuals (reduced chisquare) = WSSR/ndf : 1.25552
p-value of the Chisq distribution (FIT_P) : 0.119174
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[12] = 886.041 +/- 16.55 (1.867%)
e[12] = 21.1776 +/- 0.08032 (0.3793%)
s[12] = 2.83826 +/- 0.08452 (2.978%)
correlation matrix of the fit parameters:
a[12] e[12] s[12]
a[12] 1.000
e[12] -0.245 1.000
s[12] -0.723 0.358 1.000
*******************************************************************************
Fri Jul 25 13:04:41 2025
FIT: data read from "seth/".fn.".seth_hist" u 1:2+c:(sqrt(column(2+c)+1)) zerror
format = x:z:s
function range restricted to [83.9914 : *]
#datapoints = 46
function used for fitting: mips(c,x)
mips(i, x)=a[i]*landau((x-e[i])/s[i])
landau(l)=sqrt(exp(-l-exp(-l))/2/pi)
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a[13] e[13] s[13]
0 6.7709403756e+01 0.00e+00 2.49e+01 8.399142e+02 2.285896e+01 3.013918e+00
1 6.7709403750e+01 -9.61e-06 2.49e+01 8.399142e+02 2.285897e+01 3.013919e+00
After 1 iterations the fit converged.
final sum of squares of residuals : 67.7094
rel. change during last iteration : -9.60902e-11
degrees of freedom (FIT_NDF) : 43
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1.25485
variance of residuals (reduced chisquare) = WSSR/ndf : 1.57464
p-value of the Chisq distribution (FIT_P) : 0.00947836
Final set of parameters Asymptotic Standard Error
======================= ==========================
a[13] = 839.914 +/- 18.14 (2.159%)
e[13] = 22.859 +/- 0.1052 (0.4603%)
s[13] = 3.01392 +/- 0.1182 (3.922%)
correlation matrix of the fit parameters:
a[13] e[13] s[13]
a[13] 1.000
e[13] -0.137 1.000
s[13] -0.728 0.143 1.000

41
ahepam/AHEPAM.awk
View file

@ -346,6 +346,42 @@ function doHIST(Ch, x) {
}
}
function doSETHhist() {
if (NHCh != 14) {
NHCh = 14
name[ 0] = "iT0"
name[ 1] = "iT1"
name[ 2] = "T0"
name[ 3] = "T1"
name[ 4] = "HETB"
name[ 5] = "HETA"
name[ 6] = "BGO0"
name[ 7] = "BGO1"
name[ 8] = "BGO00"
name[ 9] = "BGO01"
name[10] = "BGO02"
name[11] = "BGO10"
name[12] = "BGO11"
name[13] = "BGO11"
}
if (EBGO0 > 48 && EBGO1 > 44) {
doHIST(0, 10*resV*iTRIG0)
doHIST(1, 10*resV*iTRIG1)
doHIST(2, ETRIG0)
doHIST(3, ETRIG1)
doHIST(4, EHETB)
doHIST(5, EHETA)
}
if (ETRIG0 > 12 && ETRIG1 > 12) {
doHIST(6, EBGO0)
doHIST(7, EBGO1)
for (i in cBGO) {
doHIST( 8 + cBGO[i], EE[i])
doHIST(11 + cBGO[i], EE[i+24])
}
}
}
BEGIN {
NDCh = 24
NCh = 48
@ -360,15 +396,16 @@ BEGIN {
}
function print_HIST(fn) {
if (!NHCh) NHCh = NCh
printf "mV" > fn
for (i=0; i<NCh; i++) {
for (i=0; i<NHCh; i++) {
printf " %s", name[i] > fn
}
print "" > fn
nx = int((maxV-minV)/resV)+1;
for (xx=0; xx<nx; xx++) {
printf "%g", (xx+0.5)*resV+minV > fn
for (i=0; i<NCh; i++) {
for (i=0; i<NHCh; i++) {
printf " %d", Hist[i,xx]+0 > fn
}
print "" > fn

6
ahepam/Makefile
View file

@ -6,6 +6,9 @@ include ../irena/libirena.make
%.AHA: %.dat ahepamfile
./ahepamfile $(CAT_BANANA) < $< > $@
%.Itime: %.AHA
../irena/Itime.awk $< > $@
ifneq ($(BANANA),)
CAT_BANANA := `cat $(BANANA)`
endif
@ -45,6 +48,9 @@ EE=E
%.SETH: %.AHA
./AHEPAM.awk 'isSETH(){doSETHBGO()}' $< > $@
%.seth_hist: %.AHA
./AHEPAM.awk 'isSETH(){doSETHhist()}' $< > $@
CUT=P
CUT_P=&&P>-0.398&&P<=-0.105
CUT_nP=&&(P<=-0.398||P>-0.105)

36
dorn_hk.py
View file

@ -6,7 +6,7 @@ import sys, getopt
oo,ff = getopt.getopt(sys.argv[1:], "saw:n:c:",
["seth", "ahbgo", "what=", "slice=", "channels="])
what="print"
what="pretty"
sl = None
ch = list(range(8))
@ -22,17 +22,23 @@ for o,v in oo:
if o=="-c" or o=="--channels":
ch = list(map(int, v.split(",")))
T = 0
for fn in ff:
with open(fn) as f:
for l in f:
if l[:2] == "H ":
T = int(l.split()[1])
continue
if not T:
continue
h = dorn.hk(sl, what=what, data=l)
if not h:
continue
for c in ch:
print(T, c, h[c])
def hk_file(f):
T = 0
for l in f:
if l[:2] == "H ":
T = int(l.split()[1])
continue
if not T:
continue
h = dorn.hk(sl, what=what, data=l)
if not h:
continue
for c in ch:
print(T, c, h[c])
if not ff:
hk_file(sys.stdin)
else:
for fn in ff:
with open(fn) as f:
hk_file(f)

31
flash_NMAHEPAM/DORN.RC
View file

@ -1,29 +1,12 @@
@v/cache iter
@s/for 24: s/exe 'DORNCC.RC' 0, i, 0x10000
@s/exe 'DORNCC.RC' 1, 0, 0x0f385
@s/exe 'DORNCC.RC' 1, 1, 0x0f75d
@s/exe 'DORNCC.RC' 1, 2, 0x0f13b
@s/exe 'DORNCC.RC' 1, 3, 0x0f635
@s/exe 'DORNCC.RC' 1, 4, 0x0f914
@s/exe 'DORNCC.RC' 1, 5, 0x0f248
@s/exe 'DORNCC.RC' 1, 6, 0x10000
@s/exe 'DORNCC.RC' 1, 7, 0x0fd86
@s/exe 'DORNCC.RC' 1, 8, 0x0eb56
@s/exe 'DORNCC.RC' 1, 9, 0x0f4af
@s/exe 'DORNCC.RC' 1, 10, 0x0f984
@s/exe 'DORNCC.RC' 1, 11, 0x0fe83
@s/exe 'DORNCC.RC' 1, 12, 0x0f507
@s/exe 'DORNCC.RC' 1, 13, 0x0f58b
@s/exe 'DORNCC.RC' 1, 14, 0x0ed1f
@s/exe 'DORNCC.RC' 1, 15, 0x0f0d1
@s/exe 'DORNCC.RC' 1, 16, 0x0ecb2
@s/exe 'DORNCC.RC' 1, 17, 0x0f4b3
@s/exe 'DORNCC.RC' 1, 18, 0x0fa8b
@s/exe 'DORNCC.RC' 1, 19, 0x0f43d
@s/exe 'DORNCC.RC' 1, 20, 0x0f442
@s/exe 'DORNCC.RC' 1, 21, 0x0f380
@s/exe 'DORNCC.RC' 1, 22, 0x0fae5
@s/exe 'DORNCC.RC' 1, 23, 0x0fb39
@s/for 24: s/exe 'DORNCC.RC' 1, i, 0x10000
@s/exe 'DORNCC.RC' 0, 3, 0x0ea90
@s/exe 'DORNCC.RC' 0, 12, 0x0e451
@s/exe 'DORNCC.RC' 0, 20, 0x0dbe5
@s/exe 'DORNCC.RC' 1, 3, 0x0f72d
@s/exe 'DORNCC.RC' 1, 12, 0x10000
@s/exe 'DORNCC.RC' 1, 20, 0x0ed2b
@dorn/fifo/enable/inj 0xdb3
@s/for 2: dorn/enable[i]/samples/inj 0
@v $T = 0x101808

1
flash_NMAHEPAM/SN15.RC
View file

@ -4,3 +4,4 @@
pres/read/verify
@s/if errno >= 500: s/exit
@v F=5
@v Z[15]=15

2
irena/Itime.awk
View file

@ -2,7 +2,7 @@
END { print Itime }
/^H/ {
/^H / {
Time = $2
Diff = Time - Last
if (Diff>0 && Diff<=120) Itime += Diff