Commit 7ec0e7db authored by Andreas Freise's avatar Andreas Freise
Browse files

finishe large alignment ASC signals. Only one plot missing. :)

parent a9f61348
......@@ -115,6 +115,8 @@ def main():
tmpfile.close()
#-----------------------------------------------------------------------------------
def asc_signal(tmpkat):
kat = copy.deepcopy(tmpkat)
......
......@@ -40,9 +40,8 @@ def main():
# %reset -f
# making these global during testing and debugging
global kat
global out
global result
#global kat
#global out
kat = finesse.kat(tempdir=".",tempname="test")
kat.verbose = False
......@@ -57,12 +56,8 @@ def main():
tmpfile.close()
except: raise Exception("Could not open temprary results file {0}".format(tmpresultfile))
# overwriting some variables
kat.maxtem=3
Lambda=1064.0e-9
print "--------------------------------------------------------"
print " 9. ASC signals for large misalignments"
print " 9. ASC signals for large misalignments (ITM)"
asc_large(kat)
......
......@@ -60,7 +60,7 @@ def main():
except: raise Exception("Could not open temprary results file {0}".format(tmpresultfile))
print "--------------------------------------------------------"
print " 9. ASC signals for large misalignments"
print " 9. Plotting ASC signals for large misalignments"
asc_large()
......
from pykat import finesse
from pykat.commands import *
import pylab as pl
import numpy as np
import shelve
import copy
import sys
import shutil
from itertools import cycle
import matplotlib
from matplotlib import rc
import matplotlib.pyplot as plt
formatter = matplotlib.ticker.EngFormatter(unit='', places=0)
formatter.ENG_PREFIXES[-6] = 'u'
def main():
print """
--------------------------------------------------------------
Example file for using PyKat to automate Finesse simulations
Finesse: http://www.gwoptics.org/finesse
PyKat: https://pypi.python.org/pypi/PyKat/
The file runs through the various pykat files which are used
to generate the Finesse results reported in the document:
`Comparing Finesse simulations, analytical solutions and OSCAR
simulations of Fabry-Perot alignment signals', LIGO-T1300345
Run this file to create the data and master4_plot.py to plot
the results. Results are saved after each step and plots can
be created at any time.
Andreas Freise 06.12.2013
--------------------------------------------------------------
"""
# shall we clear the workspace?
# %reset -f
# making these global during testing and debugging
#global kat
#global out
kat = finesse.kat(tempdir=".",tempname="test")
kat.verbose = False
tmpresultfile = 'myshelf2.dat'
# loading data saved by master.py
kat.loadKatFile('asc_base3.kat')
try:
tmpfile = shelve.open(tmpresultfile)
result=tmpfile['result']
tmpfile.close()
except: raise Exception("Could not open temprary results file {0}".format(tmpresultfile))
print "--------------------------------------------------------"
print " 10. ASC signals for large misalignments (ETM)"
asc_large(kat)
def asc_large(tmpkat):
kat = copy.deepcopy(tmpkat)
code_lock = """
set err PDrefl_p re
lock z $err 900 1p
put* ETM phi $z
noplot z
"""
kat.parseKatCode(code_lock)
kat.parseKatCode('yaxis abs')
kat.parseKatCode('xaxis ETM ybeta lin 0 1u 100')
maxtems = [1, 3, 7, 20]
#kat.verbose=1
xscale = 1e6
yscale = 1e6
global out
tmpfilename = "datashelf2.dat"
backupname = "datashelf2.dat.bck"
out={}
done_maxtems = []
for tem in maxtems:
done_maxtems.append(tem)
print " Calculating maxtem = %d " % tem
kat.maxtem = tem
out[str(tem)] = kat.run(printout=0,printerr=1)
import os.path
if os.path.isfile(tmpfilename):
shutil.copyfile(tmpfilename, backupname)
print " current results saved in: {0}".format(tmpfilename)
tmpfile = shelve.open(tmpfilename)
tmpfile['out']=out
tmpfile['maxtems']=done_maxtems
tmpfile.close()
def asc_signal(tmpkat):
kat = copy.deepcopy(tmpkat)
code_lock = """
set err PDrefl_p re
lock z $err 900 1p
put* ETM phi $z
noplot z
"""
kat.parseKatCode(code_lock)
kat.parseKatCode('yaxis abs')
kat.noxaxis = True
kat.maxtem=1
signal=np.zeros((2, 2))
kat.ITM.ybeta=1e-10
kat.ETM.ybeta=0.0
out = kat.run(printout=0,printerr=0)
WFS1_idx=out.ylabels.index("WFS1_I")
WFS2_idx=out.ylabels.index("WFS2_I")
signal[0,0] = out.y[WFS1_idx]
signal[1,0] = out.y[WFS2_idx]
kat.ITM.ybeta=0.0
kat.ETM.ybeta=-1e-10
out = kat.run(printout=0,printerr=0)
signal[0,1] = out.y[WFS1_idx]
signal[1,1] = out.y[WFS2_idx]
signal = signal *1e10
sensors=('WFS1', 'WFS2')
mirrors=('ITM', 'ETM')
print " ASC Matrix:"
for i in range(2):
print " ", sensors[i], " ",
for j in range(2):
print "%12.10g" % signal[i,j],
print mirrors[i]
return signal
if __name__ == '__main__':
main()
from pykat import finesse
from pykat.commands import *
import pylab as pl
import numpy as np
import shelve
import copy
import sys
import shutil
from itertools import cycle
import matplotlib
from matplotlib import rc
import matplotlib.pyplot as plt
formatter = matplotlib.ticker.EngFormatter(unit='', places=0)
formatter.ENG_PREFIXES[-6] = 'u'
import matplotlib.backends.backend_pdf
def printPDF(self):
filename = 'test.pdf'
pdfp = matplotlib.backends.backend_pdf.PdfPages('large_ETM.pdf')
pdfp.savefig(self,dpi=300,bbox_inches='tight')
pdfp.close()
def main():
print """
--------------------------------------------------------------
Example file for using PyKat to automate Finesse simulations
Finesse: http://www.gwoptics.org/finesse
PyKat: https://pypi.python.org/pypi/PyKat/
The file runs through the various pykat files which are used
to generate the Finesse results reported in the document:
`Comparing Finesse simulations, analytical solutions and OSCAR
simulations of Fabry-Perot alignment signals', LIGO-T1300345
Run this file to plot the data generated with master4.py.
Andreas Freise 06.12.2013
--------------------------------------------------------------
"""
# shall we clear the workspace?
# %reset -f
# maybe close all plot windows?
# close('all')
# making these global during testing and debugging
#global kat
#global out
#global result
tmpresultfile = 'myshelf2.dat'
# loading data saved by master.py
try:
tmpfile = shelve.open(tmpresultfile)
result=tmpfile['result']
tmpfile.close()
except: raise Exception("Could not open temprary results file {0}".format(tmpresultfile))
print "--------------------------------------------------------"
print " 10. Plotting ASC signals for large misalignments (ETM)"
asc_large()
def asc_large():
xscale = 1e6
yscale = -1e6
tmpfilename = "datashelf2.dat"
backupname = "datashelf2.dat.bck"
try:
tmpfile = shelve.open(tmpfilename)
out=tmpfile['out']
maxtems=tmpfile['maxtems']
tmpfile.close()
except: raise Exception("Could not open temprary results file {0}".format(tmpfilename))
fig=pl.figure()
color_cycle=['b', 'c', 'r', 'k']
N=len(maxtems)
lw=np.ones(N)*3
lw[-2]=2
lw[-1]=1
for i, tem in zip(range(len(maxtems)), maxtems):
data=out[str(tem)]
WFS1_idx=data.ylabels.index("WFS1_I")
WFS2_idx=data.ylabels.index("WFS2_I")
pl.plot(xscale*data.x,yscale*data.y[:,WFS1_idx],'-', color= color_cycle[i], linewidth=lw[i], label='maxtem {0}'.format(tem))
line, = pl.plot(xscale*data.x,yscale*data.y[:,WFS2_idx],'-', color = color_cycle[i], linewidth=lw[i])
#line.set_dashes([12, 4])
osc1=np.loadtxt("OSCAR_large_tilt_ETM.txt",comments='%')
x=xscale*osc1[:,0]
y=-1.0*yscale*osc1[:,1]
pl.scatter(x,y,s=80,facecolors='none', edgecolors='k', label='OSCAR')
y=-1.0*yscale*osc1[:,2]
pl.scatter(x,y,s=80,facecolors='none', edgecolors='k')
pl.xlabel("ETM ybeta [urad]")
pl.ylabel("Alignment signal [uW]")
pl.annotate('WFS1',xy=[0.42,10])
pl.annotate('WFS2',xy=[0.62,-70])
pl.xlim([0,1])
pl.legend(loc=3)
pl.grid()
pl.draw()
pl.show(block=0)
printPDF(fig)
if __name__ == '__main__':
main()
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