plotdm.xml

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darc, the Durham Adaptive optics Real-time Controller.
Copyright (C) 2010 Alastair Basden.

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<displayset date="09/09/18 22:56:09/18/09">
<plot pos="(0, 0)" size="(493, 400)" show="0" tbVal="(0,0,0,0,0,0)"><mangle>debug=1
tbNames=["Coeffs","Zernike","Spline","1D actuators","Text","Acts as Volts"]
if data.shape not in [(375,)]:
 print "Error - expecting 375 actuators got %s"%str(data.shape)
nmodes=45
asdac=0
tt=data[-2],data[-1]
if not store.has_key("z"):#do the setup...
 print "Setting up..."
 import tel
 import zernike
 store["pupfn"]=tel.Pupil(21,11,0).fn.astype(numpy.int32)
 store["actmap"]=numpy.zeros((21,21),numpy.float32)
 store["z"]=zernike.Zernike(store["pupfn"],nmodes)
 size=21*8
 store["out"]=numpy.zeros((size,size),numpy.float32)
 store["bigpfn"]=tel.Pupil(size,size/2,0).fn.astype(numpy.int32)
 store["ztt"]=zernike.Zernike(tel.Pupil(int(size*0.18),int(size*0.18)/2,0).fn.astype(numpy.int32),3)
 store["ttscale"]=numpy.max(store["ztt"].zern[1]+store["ztt"].zern[2])
z=store["z"]
ttscale=store["ttscale"]
bigpfn=store["bigpfn"]
ztt=store["ztt"]
actmap=store["actmap"]
pupfn=store["pupfn"]
out=store["out"]
import overlayMaker
if tbVal[0]:#plot the zernike coeffiecients
 numpy.put(actmap,numpy.nonzero(pupfn.ravel())[0],data[:373]-data[:373].sum()/373.)
 data=z.calcZernikeCoeff(actmap)
 title="Zernike coefficients"
 tbVal[1]=0
 tbVal[2]=0
elif tbVal[1]:#plot a reconstructed zernike
 tbVal[0]=0
 tbVal[2]=0
 numpy.put(actmap,numpy.nonzero(pupfn.ravel())[0],data[:373]-data[:373].sum()/373.)
 coeff=z.calcZernikeCoeff(actmap)
 ttdata=ztt.zern[1]*tt[0]+ztt.zern[2]*tt[1]
 rnge=numpy.max(data[:373])-numpy.min(data[:373])#:52 added June 2014.
 out[:]=0
 data=z.zernikeReconstruct(coeff,out)
 maxi=numpy.max(data)
 if maxi!=0:
  data/=maxi
 title="Zernike reconstruction"
 #now inset the tip-tilt...
 data[-ttdata.shape[0]:,-ttdata.shape[1]:]+=ttdata*rnge/ttscale/10.
elif tbVal[2]:#plot a cubic spline fit.
 tbVal[0]=0
 tbVal[1]=0
 numpy.put(actmap,numpy.nonzero(pupfn.ravel())[0],data[:373]-data[:373].sum()/373.)
 data=overlayMaker.createSplineOverlay(actmap,out)*bigpfn
 #now inset the tip-tilt...
 title="Cubic spline interpolation"
 ttdata=ztt.zern[1]*tt[0]+ztt.zern[2]*tt[1]
 rnge=numpy.max(data)-numpy.min(data)
 data[-ttdata.shape[0]:,-ttdata.shape[1]:]+=ttdata*rnge/ttscale
elif tbVal[3]:
 pass
elif tbVal[4]:
 txt=""
 numpy.put(actmap,numpy.nonzero(pupfn.ravel())[0],data[:373])#don't subtract average
 if asdac==0:
  for i in range(21):
   for j in range(21):
    txt+="%8.2f "%actmap[i,j]
   txt+="\n"
  if data.size>373:
   txt+="\n%8.2f %8.2f\n"%(data[373],data[374])
 else:
  for i in range(21):
   for j in range(21):
    txt+="%5d "%actmap[i,j]
   txt+="\n"
  if data.size>373:
   txt+="\n%5d %5d\n"%(data[373],data[374])
 data=txt
 fount="Mono 9"
else:
 numpy.put(actmap,numpy.nonzero(pupfn.ravel())[0],data[:373]-data[:373].sum()/373.)
 data=actmap
 title="Reconstructed phase map"
if type(data)!=type("") and len(data.shape)==2:
 arrows=[]
 if data.shape[0]==21:
  xpos=7
  ypos=0
 else:
  xpos=60
  ypos=4
 if tt[0]!=0:
  w=tt[0]*.3*data.shape[0]/16.
  arrows.append([xpos,ypos,tt[0]*data.shape[0]/16.,0,{"head_width":w,"head_length":w,"length_includes_head":True,"fc":"red","ec":"red"}])
 if tt[1]!=0:
  w=tt[1]*.3*data.shape[0]/16.
  arrows.append([xpos,ypos,0,tt[1]*data.shape[0]/16.,{"head_width":w,"head_length":w,"length_includes_head":True,"fc":"red","ec":"red"}])
</mangle>
<sub>[('rtcMirrorBuf',1,1)]</sub>
</plot>
</displayset>