def makePattern(pattern, oversample=2, col=None):
if pattern == "cross":
pattern = numpy.zeros((oversample, oversample, 4), numpy.float32)
pattern[oversample / 2:oversample / 2 + 1, :, 3] = 1
pattern[:, oversample / 2:oversample / 2 + 1, 3] = 1
if col == None:
col = (0, 1, 0)
pattern[oversample / 2:oversample / 2 + 1, :, :3] = col
pattern[:, oversample / 2:oversample / 2 + 1, :3] = col
elif pattern == "egg":
import tel
pattern = numpy.zeros((oversample, oversample, 4), numpy.float32)
pattern[:, :, 0] = tel.Pupil(oversample, oversample / 2, 0).fn
pattern[:, :, 1] = pattern[:, :, 0]
pattern[:, :, 2] = tel.Pupil(oversample, oversample / 4, 0).fn
#pattern[oversample*.25:oversample*.75,oversample*.25:oversample*.75,:3]=1
pattern[:, :, 3] = 0.4
elif pattern == "target":
import tel
pattern = numpy.zeros((oversample, oversample, 4), numpy.float32)
pattern[:, :, 1] = 1
pattern[:, :, 3] = tel.Pupil(oversample, oversample / 2,
oversample / 2 - 1).fn
else:
pattern = numpy.zeros((oversample, oversample, 4), numpy.float32)
pattern[:, :, 1::2] = 1
return pattern
def createZernikeOverlay(actmap, pupfn=None, nmodes=None):
#pupfn is same size as actmap
import zernike
if pupfn == None:
import tel
pupfn = tel.Pupil(actmap.shape[0], actmap.shape[0] / 2,
0).fn #(actmap!=0).astype(numpy.int32)
if nmodes == None:
nmodes = int((actmap.shape[0] + 1) * (actmap.shape[0] + 2) / 2.)
z = zernike.Zernike(pupfn, nmodes)
coeff = z.calcZernikeCoeff(actmap)
data = z.zernikeReconstruct(coeff, size=64)
return data
def zernikeReconstruct(self, coeff, out=None, size=None):
if out == None:
if size == None:
size = self.npup
out = numpy.zeros((size, size), numpy.float32)
if out.shape[0] != self.npup:
if self.zernExpand == None or self.zernExpand.shape[
1] != out.shape[0]:
import tel
print "Computing zernikes"
z = Zernike(
tel.Pupil(out.shape[0], out.shape[0] / 2, 0).fn,
coeff.shape[0])
self.zernExpand = z.zern
zern = self.zernExpand
else:
zern = self.zern
for i in range(1, coeff.shape[0]):
out += coeff[i] * zern[i]
return out
import numpy
ncam=6#1, 2, 3, 4. This is the number of physical cameras
nacts=220#97#54#+256
#ncam=(int(NCAMERAS)+1)/2
camPerGrab=numpy.ones((ncam,),"i")
ncamThreads=numpy.ones((ncam,),numpy.int32)*1
npxly=numpy.zeros((ncam,),numpy.int32)
npxly[:]=128
npxlx=npxly.copy()*camPerGrab
nsuby=npxlx.copy()
nsuby[:]=10#for config purposes only... not sent to rtc
nsubx=nsuby.copy()*camPerGrab#for config purposes - not sent to rtc
nsub=nsubx*nsuby#This is used by rtc.
nsubaps=nsub.sum()#(nsuby*nsubx).sum()
individualSubapFlag=tel.Pupil(10,10/2.,0.5,10,0.5).subflag.astype("i")
subapFlag=numpy.zeros((nsubaps,),"i")
for i in range(ncam):
tmp=subapFlag[nsub[:i].sum():nsub[:i+1].sum()]
tmp.shape=nsuby[i],nsubx[i]
for j in range(camPerGrab[i]):
tmp[:,j::camPerGrab[i]]=individualSubapFlag
#ncents=nsubaps*2
ncents=subapFlag.sum()*2
npxls=(npxly*npxlx).sum()
print "ncents %d"%ncents
fakeCCDImage=None#(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage=None#FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise=None#FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
#along with this program. If not, see <http://www.gnu.org/licenses/>.
import FITS
import tel
import numpy
import os
#Set up some basic parameters
nacts = 1024
ncam = 1 # Number of WFSs
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 8 #Number of threads to use
npxly = numpy.ones((ncam, ), numpy.int32) * 128 #detector size
npxlx = npxly.copy()
nsuby = numpy.ones((ncam, ), numpy.int32) * 7 #number of sub-apertures
nsubx = nsuby.copy()
nsub = nsuby * nsubx
nsubtot = nsub.sum()
subapFlag = numpy.array([tel.Pupil(7 * 16, 7 * 8, 8, 7).subflag.astype("i")] *
ncam).ravel() #Generate an map of used sub-apertures
ncents = subapFlag.sum() * 2 #number of slope measurements (x and y)
npxls = (npxly * npxlx).sum()
#Calibration data
bgImage = numpy.ones(
128 * 128 * ncam) * 12 #None#FITS.Read("shimgb1stripped_bg.fits")[1]
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
nsubaps = nsuby * nsubx #cumulative subap
nsubapsCum = numpy.zeros((ncam + 1, ), numpy.int32)
ncentsCum = numpy.zeros((ncam + 1, ), numpy.int32)
for i in range(ncam):
import correlation,FITS
import tel
import numpy
nacts=52#97#54#+256
ncam=1
ncamThreads=numpy.ones((ncam,),numpy.int32)*8
npxly=numpy.zeros((ncam,),numpy.int32)
npxly[:]=128
npxlx=npxly.copy()
nsuby=npxly.copy()
nsuby[:]=7
#nsuby[4:]=16
nsubx=nsuby.copy()
nsub=nsubx*nsuby
nsubaps=(nsuby*nsubx).sum()
subapFlag=tel.Pupil(7*16,7*8,8,7).subflag.astype("i").ravel()#numpy.ones((nsubaps,),"i")
#ncents=nsubaps*2
ncents=subapFlag.sum()*2
npxls=(npxly*npxlx).sum()
fakeCCDImage=None#(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage=None#FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise=None#FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField=None#FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
#FITS.Write(camimg,"camImage.fits")#file used when reading from file,
subapLocation=numpy.zeros((nsubaps,6),"i")
nsubaps=nsuby*nsubx#cumulative subap
nacts = 54 #97#54#+256
ncam = (int(NCAMERAS) + 1) / 2
camPerGrab = numpy.ones((ncam, ), "i") * 2
if NCAMERAS % 2 == 1:
camPerGrab[-1] = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 128
npxlx = npxly.copy() * camPerGrab
nsuby = npxlx.copy()
nsuby[:] = 7 #for config purposes only... not sent to rtc
nsubx = nsuby.copy() * camPerGrab #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(7, 3.5, 1, 7).subflag.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
for j in range(camPerGrab[i]):
tmp[:, j::camPerGrab[i]] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
ncamThreads=numpy.ones((ncam,),numpy.int32)*8
nlots=[4]*ncam#number of blocks in which to do processing
noPrePostThread=0
threadPriority=numpy.ones((ncamThreads.sum()+1,),numpy.int32)*40
#threadPriority=numpy.arange(ncamThreads.sum()+1)+40
threadPriority[0]=39
threadAffinity=None#1<<(numpy.arange(1+ncamThreads.sum()))
nsub=84#should be 40 for sphere...
npxl=8
nact=nsub+1
nacts=tel.Pupil(nact,nact/2.,2).fn.astype("i").sum()
#if NCAMERAS%2==1:
# camPerGrab[-1]=1
npxly=numpy.zeros((ncam,),numpy.int32)
npxly[:]=nsub*npxl
npxlx=npxly.copy()*camPerGrab
nsuby=npxly.copy()
nsuby[:]=nsub
nsubx=nsuby.copy()*camPerGrab
nsubaps=(nsuby*nsubx).sum()
individualSubapFlag=tel.Pupil(nsub,nsub/2.,84/2./7.,nsub).subflag.astype("i")#42m, with 6m secondary
subapFlag=numpy.zeros(((nsuby*nsubx).sum(),),"i")
for i in range(ncam):
tmp=subapFlag[(nsuby[:i]*nsubx[:i]).sum():(nsuby[:i+1]*nsubx[:i+1]).sum()]
tmp.shape=nsuby[i],nsubx[i]
for j in range(camPerGrab[i]):
try:
ncam = int(prefix)
except:
ncam = 4
print "Using %d cameras" % ncam
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 488
npxlx = npxly.copy()
npxlx[:] = 488
nsuby = npxlx.copy()
nsuby[:] = 30 #for config purposes only... not sent to rtc
nsubx = nsuby.copy() #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(30, 15, 2, 30).subflag.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
tmp[:] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
mirrorParams[0] = 1000 #timeout/ms
mirrorParams[1] = 1 #port
mirrorParams[2] = 1 #thread affinity el size
mirrorParams[3] = 1 #thread prioirty
mirrorParams[4] = -1 #thread affinity
#Now describe the DM - this is for the GUI only, not the RTC.
#The format is: ndms, N for each DM, actuator numbers...
#Where ndms is the number of DMs, N is the number of linear actuators for each, and the actuator numbers are then an array of size NxN with entries -1 for unused actuators, or the actuator number that will set this actuator in the DMC array.
dmDescription = numpy.zeros((8 * 8 + 1 + 1, ), numpy.int16)
dmDescription[0] = 1 #1 DM
dmDescription[1] = 8 #1st DM has nacts linear actuators
tmp = dmDescription[2:]
tmp[:] = -1
tmp.shape = 8, 8
dmflag = tel.Pupil(8, 4, 0).fn.ravel()
numpy.put(tmp, dmflag.nonzero()[0], numpy.arange(52))
control = {
"switchRequested":
0, #this is the only item in a currently active buffer that can be changed...
"pause": 0,
"go": 1,
#"DMgain":0.25,
#"staticTerm":None,
"maxClipped": nacts,
"refCentroids": None,
#"dmControlState":0,
#"gainReconmxT":None,#numpy.random.random((ncents,nacts)).astype("f"),#reconstructor with each row i multiplied by gain[i].
#"dmPause":0,
#"reconMode":"closedLoop",
import FITS
import tel
import numpy
nacts = 52 #97#54#+256
ncam = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 128
npxlx = npxly.copy()
nsuby = npxlx.copy()
nsuby[:] = 7 #for config purposes only... not sent to rtc
nsubx = nsuby.copy()
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
subapFlag = tel.Pupil(7, 3.5, 1, 7).subflag.astype("i").ravel()
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
subapLocation = numpy.zeros((nsubaps, 6), "i")
nsubapsCum = numpy.zeros((ncam + 1, ), numpy.int32)
ncentsCum = numpy.zeros((ncam + 1, ), numpy.int32)
nsubapsCum[1] = nsub[0]
ncentsCum[1] = subapFlag.sum() * 2
npxly[ncamSL:ncamSL+NLGSOCAM]=242
npxly[ncamSL+NLGSOCAM:ncamSL+NBOBCAT+NLGSOCAM]=140
npxlx=npxly.copy()#*camPerGrab
npxlx[ncamSL:ncamSL+NLGSOCAM]=264
nsuby=npxlx.copy()
nsuby[:]=7#for config purposes only... not sent to rtc
if ncamSL!=0:
nsuby[ncamSL-1]=14#truth
nsuby[ncamSL:ncamSL+NLGSOCAM]=7#The LGS
nsuby[ncamSL+NLGSOCAM:ncamSL+NLGSOCAM+NBOBCAT]=[7,14][:NBOBCAT]
nsubx=nsuby.copy()#*camPerGrab#for config purposes - not sent to rtc
#nsubx[1]=35#ngs3 + truth (14x14)
#nsubx[ncamSL:ncamSL+NLGSOCAM]=14*4#The LGS (4 WFS on 1 detector - in a row.)
nsub=nsubx*nsuby#This is used by rtc.
nsubaps=nsub.sum()#(nsuby*nsubx).sum()
individualSubapFlag=tel.Pupil(7,3.5,1,7).subflag.astype("i")
sf14=tel.Pupil(14,7.,2,14).subflag.astype("i")
sfNoObs=tel.Pupil(7,3.5,0,7).subflag.astype("i")
sf14NoObs=tel.Pupil(14,7.,0,14).subflag.astype("i")
#lgsSubapFlag=numpy.zeros((14,56),"i")
#For the ocam, I think we can simply interleave the top and bottom subap by subap.
#To be sure of ordering, have pxlCnt set to the end of the row, rather than subap.
nsublist=[]
print "nsub:",nsub
#for i in range(4):
# lgsSubapFlag[:,i::4]=sf14
subapFlag=numpy.zeros((nsubaps,),"i")
for i in range(NNGSCAM+NLGSOCAM+NBOBCAT):#ngs 1-3, truth, lgs, lofs, hofs
#You should have received a copy of the GNU Affero General Public License
#along with this program. If not, see <http://www.gnu.org/licenses/>.
#This is a configuration file for SPHERE.
#Aim to fill up the control dictionary with values to be used in the RTCS.
#import correlation
import FITS
import tel
import numpy
NCAMERAS = 1 #1, 2, 3, 4. This is the number of physical cameras
nsub = 48
npxl = 6
nact = nsub + 1
nacts = tel.Pupil(nact, nact / 2., 2).fn.astype("i").sum()
ncam = NCAMERAS #(int(NCAMERAS)+1)/2
camPerGrab = numpy.ones((ncam, ), "i")
#if NCAMERAS%2==1:
# camPerGrab[-1]=1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 4
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = nsub * npxl
npxlx = npxly.copy()
nsuby = npxly.copy()
nsuby[:] = nsub
nsubx = nsuby.copy()
nsubaps = (nsuby * nsubx).sum()
individualSubapFlag = tel.Pupil(nsub, nsub / 2., 2, nsub).subflag.astype("i")
subapFlag = numpy.zeros(((nsuby * nsubx).sum(), ), "i")
for i in range(ncam):
import tel
import numpy
import os
import time
#Set up some basic parameters
ndm=2
nacts=241*ndm
ncam=1 # Number of WFSs
ncamThreads=numpy.ones((ncam,),numpy.int32)*8 #Number of threads to use
npxly=numpy.ones((ncam,),numpy.int32)*128#detector size
npxlx=npxly.copy()
nsuby=numpy.ones((ncam,),numpy.int32)*7#number of sub-apertures
nsubx=nsuby.copy()
nsub=nsuby*nsubx
nsubtot=nsub.sum()
subapFlag=numpy.array([tel.Pupil(7*16,7*8,8,7).subflag.astype("i")]*ncam).ravel()#Generate an map of used sub-apertures
ncents=subapFlag.sum()*2#number of slope measurements (x and y)
npxls=(npxly*npxlx).sum()
#Calibration data
bgImage=numpy.ones(128*128*ncam)*12#None#FITS.Read("shimgb1stripped_bg.fits")[1]
darkNoise=None#FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField=None#FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
nsubaps=nsuby*nsubx#cumulative subap
nsubapsCum=numpy.zeros((ncam+1,),numpy.int32)
ncentsCum=numpy.zeros((ncam+1,),numpy.int32)
for i in range(ncam):
nsubapsCum[i+1]=nsubapsCum[i]+nsubaps[i]
ncentsCum[i+1]=ncentsCum[i]+subapFlag[nsubapsCum[i]:nsubapsCum[i+1]].sum()*2
nacts = 54 #97#54#+256
ncam = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 2
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 144 #300#480
npxlx = npxly.copy()
npxlx[:] = 144 #400#640
nsuby = npxly.copy()
nsuby[:] = 14 #15
#nsuby[4:]=16
nsubx = nsuby.copy()
nsubaps = (nsuby * nsubx).sum()
#subapFlag=tel.Pupil(15*16,15*8,8,15).subflag.astype("i").ravel()#numpy.ones((nsubaps,),"i")
subapFlag = tel.Pupil(
14 * 14, 14 * 7, 4 * 7,
14).subflag.astype("i").ravel() #numpy.ones((nsubaps,),"i")
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
subapLocation = numpy.zeros((nsubaps, 6), "i")
nsubaps = nsuby * nsubx #cumulative subap
except:
port = 8800
print port
import time
time.sleep(1)
#Set up some basic parameters
nacts = 52 #97#54#+256
ncam = 1 # Number of WFSs
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 8 #Number of threads to use
npxly = numpy.ones((ncam, ), numpy.int32) * 128 #detector size
npxlx = npxly.copy()
nsuby = numpy.ones((ncam, ), numpy.int32) * 7 #number of sub-apertures
nsubx = nsuby.copy()
nsub = nsuby * nsubx
nsubtot = nsub.sum()
subapFlag = numpy.array([tel.Pupil(7 * 16, 7 * 8, 8, 7).subflag.astype("i")] *
ncam).ravel() #Generate an map of used sub-apertures
ncents = subapFlag.sum() * 2 #number of slope measurements (x and y)
npxls = (npxly * npxlx).sum()
#Calibration data
bgImage = numpy.ones(
128 * 128 * ncam) * 12 #None#FITS.Read("shimgb1stripped_bg.fits")[1]
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
nsubaps = nsuby * nsubx #cumulative subap
nsubapsCum = numpy.zeros((ncam + 1, ), numpy.int32)
ncentsCum = numpy.zeros((ncam + 1, ), numpy.int32)
for i in range(ncam):
#You should have received a copy of the GNU Affero General Public License
#along with this program. If not, see <http://www.gnu.org/licenses/>.
#This is a configuration file for CANARY.
#Aim to fill up the control dictionary with values to be used in the RTCS.
#import correlation
import FITS
import tel
import numpy
NCAMERAS = 7 #1, 2, 3, 4. This is the number of physical cameras
nsub = 16
npxl = 12
nact = nsub + 1
nacts = tel.Pupil(17, 8.5, 1).fn.astype("i").sum()
ncam = NCAMERAS #(int(NCAMERAS)+1)/2
camPerGrab = numpy.ones((ncam, ), "i")
#if NCAMERAS%2==1:
# camPerGrab[-1]=1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = nsub * npxl
npxlx = npxly.copy()
nsuby = npxly.copy()
nsuby[:] = 16
nsubx = nsuby.copy()
nsub = nsubx * nsuby
nsubaps = (nsuby * nsubx).sum()
individualSubapFlag = tel.Pupil(nsubx[0], nsubx[0] / 2., 1,
nsubx[0]).subflag.astype("i")
#along with this program. If not, see <http://www.gnu.org/licenses/>.
import FITS
import tel
import numpy
import os
#Set up some basic parameters
nacts=52#97#54#+256
ncam=1 # Number of WFSs
ncamThreads=numpy.ones((ncam,),numpy.int32)*8 #Number of threads to use
npxly=numpy.ones((ncam,),numpy.int32)*20#detector size
npxlx=npxly.copy()
nsuby=numpy.ones((ncam,),numpy.int32)*10#number of sub-apertures
nsubx=nsuby.copy()
nsub=nsuby*nsubx
nsubtot=nsub.sum()
subapFlag=tel.Pupil(10,5,0).fn.astype("i")
ncents=subapFlag.sum()*2#number of slope measurements (x and y)
npxls=(npxly*npxlx).sum()
#Calibration data
bgImage=None
darkNoise=None
flatField=None
nsubaps=nsuby*nsubx#cumulative subap
nsubapsCum=numpy.zeros((ncam+1,),numpy.int32)
ncentsCum=numpy.zeros((ncam+1,),numpy.int32)
for i in range(ncam):
nsubapsCum[i+1]=nsubapsCum[i]+nsubaps[i]
ncentsCum[i+1]=ncentsCum[i]+subapFlag[nsubapsCum[i]:nsubapsCum[i+1]].sum()*2
camAffin[1 - (mcpu - nthreads - 1) / 32] = 0
print "cam affinity", [bin(i) for i in camAffin]
# print out threadAfinity in binary form for verification
for i in range(nthreads + 1):
print i, [
bin(j)
for j in threadAffinity[i * threadAffElSize:(i + 1) * threadAffElSize]
]
npxl = 6 # for square subaps
xnpxl = 12 # width for rectangular subaps
ynpxl = 3 #height for rectangular subaps
nact = (nsub + 1)
#print "nact = ", nact
nacts = tel.Pupil(nact, nact / 2., 2).fn.astype("i").sum()
print "nacts1", nacts
nacts = 16 * ((nacts + 15) / 16)
#nacts=10000
print "nacts2", nacts
camPerGrab = numpy.ones((ncam, ), "i")
#if NCAMERAS%2==1:
# camPerGrab[-1]=1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = nsub * npxl #square subaps
npxly[:] = nsub * ynpxl #rectangular subaps
npxly[:] = 260 #manually set for 10G camera
npxlx = npxly.copy() #square subaps
npxlx[:] = nsub * xnpxl #rectangular subaps
import numpy
NCAMERAS=1#1, 2, 3, 4. This is the number of physical cameras
ncam=NCAMERAS#(int(NCAMERAS)+1)/2
nn=8
nlots=[nn*3]*ncam#number of chunks to divide up into.
ncamThreads=numpy.ones((ncam,),numpy.int32)*nn
noPrePostThread=0
threadPriority=numpy.ones((ncamThreads.sum()+1,),numpy.int32)*40
#threadPriority=numpy.arange(ncamThreads.sum()+1)+40
threadPriority[0]=39
threadAffinity=1<<(numpy.arange(1+ncamThreads.sum()))
#threadAffinity=None
nsub=31
npxl=4
nact=nsub+1
nacts=tel.Pupil(nact,nact/2.,2).fn.astype("i").sum()
camPerGrab=numpy.ones((ncam,),"i")
#if NCAMERAS%2==1:
# camPerGrab[-1]=1
npxly=numpy.zeros((ncam,),numpy.int32)
npxly[:]=128#nsub*npxl
npxlx=npxly.copy()
nsuby=npxly.copy()
nsuby[:]=nsub
nsubx=nsuby.copy()
nsubaps=(nsuby*nsubx).sum()
individualSubapFlag=tel.Pupil(nsub,nsub/2.,2.7,nsub).subflag.astype("i")#gives 1240 used subaps
subapFlag=numpy.zeros(((nsuby*nsubx).sum(),),"i")
for i in range(ncam):
tmp=subapFlag[(nsuby[:i]*nsubx[:i]).sum():(nsuby[:i+1]*nsubx[:i+1]).sum()]
tmp.shape=nsuby[i],nsubx[i]
nacts = 140 #97#54#+256
ncam = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 480
npxlx = npxly.copy()
npxlx[:] = 640
nsuby = npxly.copy()
nsuby[:] = 11
#nsuby[4:]=16
nsubx = nsuby.copy()
nsub = nsubx * nsuby
nsubaps = (nsuby * nsubx).sum()
#subapFlag=numpy.ones((nsubaps,),"i")
subapFlag = tel.Pupil(
11, 11 / 2., 1,
11).subflag.astype("i").ravel() #numpy.ones((nsubaps,),"i")
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
#indx=0
#nx=npxlx/nsubx
#ny=npxly/nsuby
try:
ncam = int(prefix)
except:
ncam = 4
print "Using %d cameras" % ncam
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 140 #488
npxlx = npxly.copy()
npxlx[:] = 140 #648
nsuby = npxlx.copy()
nsuby[:] = 15 #for config purposes only... not sent to rtc
nsubx = nsuby.copy() #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(15, 7.5, 1, 15).subflag.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
tmp[:] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
import FITS
import tel
import numpy
import os
#Set up some basic parameters
nacts=5318#97#54#+256
ncam=1 # Number of WFSs
ncamThreads=numpy.ones((ncam,),numpy.int32)*2 #Number of threads to use
npxly=numpy.ones((ncam,),numpy.int32)*800#detector size
npxlx=npxly.copy()
nsuby=numpy.ones((ncam,),numpy.int32)*74#number of sub-apertures
nsubx=nsuby.copy()
nsub=nsuby*nsubx
nsubtot=nsub.sum()
subapFlag=numpy.array([tel.Pupil(74,40,7).fn.astype("i")]*ncam).ravel()
ncents=subapFlag.sum()*2#number of slope measurements (x and y)
npxls=(npxly*npxlx).sum()
#Calibration data
bgImage=numpy.random.normal(0,0.1,(npxlx*npxly).sum()).astype("f")#None#FITS.Read("shimgb1stripped_bg.fits")[1]
darkNoise=None#FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField=numpy.random.normal(1,0.1,(npxlx*npxly).sum()).astype("f")#FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
nsubaps=nsuby*nsubx#cumulative subap
nsubapsCum=numpy.zeros((ncam+1,),numpy.int32)
ncentsCum=numpy.zeros((ncam+1,),numpy.int32)
for i in range(ncam):
nsubapsCum[i+1]=nsubapsCum[i]+nsubaps[i]
ncentsCum[i+1]=ncentsCum[i]+subapFlag[nsubapsCum[i]:nsubapsCum[i+1]].sum()*2
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = nsub * npxl #square subaps
npxly[:] = nsub * ynpxl #rectangular subaps
#npxly[:]=320 #manually set for 10G camera
npxlx = npxly.copy() #square subaps
npxlx[:] = nsub * xnpxl #rectangular subaps
#npxlx[:]=320 #manually set for 10G camera
nsuby = npxly.copy()
nsuby[:] = nsub
nsubx = nsuby.copy()
nsubaps = (nsuby * nsubx).sum()
individualSubapFlag = tel.Pupil(nsub, nsub / 2., 2.8 * nsub / 20.,
nsub).subflag.astype(
"i") #gives 1240 used subaps
subapFlag = numpy.zeros(((nsuby * nsubx).sum(), ), "i")
for i in range(ncam):
tmp = subapFlag[(nsuby[:i] * nsubx[:i]).sum():(nsuby[:i + 1] *
nsubx[:i + 1]).sum()]
tmp.shape = nsuby[i], nsubx[i]
tmp[:] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
nvSubaps = subapFlag.sum() # number of valid subaps
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
ncam += 1 #Add the EVT.
print "Using %d cameras" % ncam
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 488
npxly[-1] = 1088 #EVT
npxlx = npxly.copy()
npxlx[:] = 648
npxlx[-1] = 2048 #EVT
nsuby = npxlx.copy()
nsuby[:] = 31 #for config purposes only... not sent to rtc
nsuby[-1] = 62 #the EVT
nsubx = nsuby.copy() #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(31, 15.5, 2, 31).subflag.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam - 1):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
tmp[:] = individualSubapFlag
#now the EVT
tmp = subapFlag[nsub[:-1].sum():nsub.sum()]
tmp.shape = nsuby[-1], nsubx[-1]
tmp[:31, :31] = individualSubapFlag
tmp[31:, :31] = individualSubapFlag
tmp[:31, 31:] = individualSubapFlag
tmp[31:, 31:] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
nacts = 54 #97#54#+256
ncam = 1
ncamSL240 = 0
print "Using %d cameras" % ncam
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 242 #121
npxlx = npxly.copy()
npxlx[:] = 264 #1056
nsuby = npxlx.copy()
nsuby[:] = 14 #for config purposes only... not sent to rtc
nsubx = nsuby.copy() #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(7, 3.5, 1).fn.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
for j in range(4):
tmp[(j // 2) * 7:(j // 2) * 7 + 7,
(j % 2) * 7:(j % 2) * 7 + 7] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
ncamThreads[2:] = 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 128
npxlx = npxly.copy()
npxlx[:] = 256
nsuby = npxly.copy()
nsuby[:2] = 15
nsuby[2:] = 7
#nsuby[4:]=16
nsubx = nsuby.copy()
nsubx[:2] = 30
nsubx[2:] = 14
nsub = nsubx * nsuby
nsubaps = (nsuby * nsubx).sum()
subapFlagNGS = tel.Pupil(7 * 16, 7 * 8, 8, 7).subflag.astype(
"i") #.ravel()#numpy.ones((nsubaps,),"i")
subapFlagLGS = tel.Pupil(15 * 8, 15 * 4, 8, 15).subflag.astype(
"i") #.ravel()#numpy.ones((nsubaps,),"i")
subapFlag = numpy.zeros((7 * 7 * 4 + 15 * 15 * 4, ), "i")
tmp = subapFlag[:15 * 30]
tmp.shape = 15, 30
tmp[:, ::2] = subapFlagLGS
tmp[:, 1::2] = subapFlagLGS
tmp = subapFlag[15 * 30:2 * 15 * 30]
tmp.shape = 15, 30
tmp[:, ::2] = subapFlagLGS
tmp[:, 1::2] = subapFlagLGS
tmp = subapFlag[2 * 15 * 30:2 * 15 * 30 + 7 * 14]
tmp.shape = 7, 14
tmp[:, ::2] = subapFlagNGS
tmp[:, 1::2] = subapFlagNGS
#along with this program. If not, see <http://www.gnu.org/licenses/>.
import FITS
import tel
import numpy
import os
#Set up some basic parameters
nacts=52#97#54#+256
ncam=1 # Number of WFSs
ncamThreads=numpy.ones((ncam,),numpy.int32)*8 #Number of threads to use
npxly=numpy.ones((ncam,),numpy.int32)*128#detector size
npxlx=npxly.copy()
nsuby=numpy.ones((ncam,),numpy.int32)*7#number of sub-apertures
nsubx=nsuby.copy()
nsub=nsuby*nsubx
nsubtot=nsub.sum()
subapFlag=numpy.array([tel.Pupil(7*16,7*8,8,7).subflag.astype("i")]*ncam).ravel()#Generate an map of used sub-apertures
ncents=subapFlag.sum()*2#number of slope measurements (x and y)
npxls=(npxly*npxlx).sum()
#Calibration data
bgImage=None#numpy.ones(128*128*ncam)*12#None#FITS.Read("shimgb1stripped_bg.fits")[1]
darkNoise=None#FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField=None#FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
nsubaps=nsuby*nsubx#cumulative subap
nsubapsCum=numpy.zeros((ncam+1,),numpy.int32)
ncentsCum=numpy.zeros((ncam+1,),numpy.int32)
for i in range(ncam):
nsubapsCum[i+1]=nsubapsCum[i]+nsubaps[i]
ncentsCum[i+1]=ncentsCum[i]+subapFlag[nsubapsCum[i]:nsubapsCum[i+1]].sum()*2
nacts = 54 #97#54#+256
ncam = (int(NCAMERAS) + 1) / 2
camPerGrab = numpy.ones((ncam, ), "i") * 2
if NCAMERAS % 2 == 1:
camPerGrab[-1] = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 1
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 128
npxlx = npxly.copy() * camPerGrab
nsuby = npxlx.copy()
nsuby[:] = 7 #for config purposes only... not sent to rtc
nsubx = nsuby.copy() * camPerGrab #for config purposes - not sent to rtc
nsub = nsubx * nsuby #This is used by rtc.
nsubaps = nsub.sum() #(nsuby*nsubx).sum()
individualSubapFlag = tel.Pupil(7, 3.5, 1, 7).subflag.astype("i")
subapFlag = numpy.zeros((nsubaps, ), "i")
for i in range(ncam):
tmp = subapFlag[nsub[:i].sum():nsub[:i + 1].sum()]
tmp.shape = nsuby[i], nsubx[i]
for j in range(camPerGrab[i]):
tmp[:, j::camPerGrab[i]] = individualSubapFlag
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
nacts = 54 #97#54#+256
ncam = 1
ncamThreads = numpy.ones((ncam, ), numpy.int32) * 2
npxly = numpy.zeros((ncam, ), numpy.int32)
npxly[:] = 144 #300#480
npxlx = npxly.copy()
npxlx[:] = 144 #400#640
nsuby = npxly.copy()
nsuby[:] = 12 #15
#nsuby[4:]=16
nsubx = nsuby.copy()
nsub = nsubx * nsuby
nsubaps = (nsuby * nsubx).sum()
#subapFlag=tel.Pupil(15*16,15*8,8,15).subflag.astype("i").ravel()#numpy.ones((nsubaps,),"i")
subapFlag = tel.Pupil(
12 * 12, 12 * 6, 6,
12).subflag.astype("i").ravel() #numpy.ones((nsubaps,),"i")
#ncents=nsubaps*2
ncents = subapFlag.sum() * 2
npxls = (npxly * npxlx).sum()
fakeCCDImage = None #(numpy.random.random((npxls,))*20).astype("i")
#camimg=(numpy.random.random((10,npxls))*20).astype(numpy.int16)
bgImage = None #FITS.Read("shimgb1stripped_bg.fits")[1].astype("f")#numpy.zeros((npxls,),"f")
darkNoise = None #FITS.Read("shimgb1stripped_dm.fits")[1].astype("f")
flatField = None #FITS.Read("shimgb1stripped_ff.fits")[1].astype("f")
subapLocation = numpy.zeros((nsubaps, 6), "i")
nsubaps = nsuby * nsubx #cumulative subap
