diff --git a/examples/asc_test/master2.py b/examples/asc_test/master2.py
index 204c6d6b87dcdf0c78b9ef7def1003e6e30bff57..4af7eaa4acfca1511f1918c269e5983a7046379a 100644
--- a/examples/asc_test/master2.py
+++ b/examples/asc_test/master2.py
@@ -115,6 +115,8 @@ def main():
tmpfile.close()
+#-----------------------------------------------------------------------------------
+
def asc_signal(tmpkat):
kat = copy.deepcopy(tmpkat)
diff --git a/examples/asc_test/master3.py b/examples/asc_test/master3.py
index 44821c739df47156c37baa2704d50c6f28bf7cb9..12fb88d2b6ea638a6320e52fdf9ace3c0bef2083 100644
--- a/examples/asc_test/master3.py
+++ b/examples/asc_test/master3.py
@@ -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)
diff --git a/examples/asc_test/master3_plot.py b/examples/asc_test/master3_plot.py
index ff9e961af30f426881cad2348275f1bf43b26fdf..8b09d8037b6e44dd7e2d1e3306f0f6b7f4a8f824 100644
--- a/examples/asc_test/master3_plot.py
+++ b/examples/asc_test/master3_plot.py
@@ -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()
diff --git a/examples/asc_test/master4.py b/examples/asc_test/master4.py
new file mode 100644
index 0000000000000000000000000000000000000000..d49f8f0988ba4763526f9904102fbdb807907893
--- /dev/null
+++ b/examples/asc_test/master4.py
@@ -0,0 +1,144 @@
+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()
diff --git a/examples/asc_test/master4_plot.py b/examples/asc_test/master4_plot.py
new file mode 100644
index 0000000000000000000000000000000000000000..852a704d7fe68ea4c3d3a67998af3a049de3c6f6
--- /dev/null
+++ b/examples/asc_test/master4_plot.py
@@ -0,0 +1,115 @@
+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()