def shoot2(self, x, y, datum_point_x=7, datum_point_y=7, debug=False):
# calculate the rotate angles
quadrant = getQuadrant(x, y, datum_point_x, datum_point_y)
print 'quadrant : %d' % quadrant
xcoef = 1 if quadrant == 3 or quadrant == 4 else -1
ycoef = 1 if quadrant == 2 or quadrant == 4 else -1
base = abs(abs(x-datum_point_x) * self.gridLength - (xcoef * (self.gridLength / 2)))
height = abs(abs(y-datum_point_y) * self.gridLength - (ycoef * (self.gridLength / 2)))
laser2target = math.sqrt(pylab.square(base) + pylab.square(height) + pylab.square(self.laser2wall))
print "base : %f \t height : %f" % (base, height)
print laser2target
yaw = math.asin(base / laser2target)
pitch = math.asin(height / laser2target)
print "yaw : %f \t pitch : %f" % (yaw, pitch)
units2yaw = yaw / anglePerStep
units2pitch = pitch / anglePerStep
if quadrant == 1 or quadrant == 3:
units2yaw = -units2yaw
if quadrant == 3 or quadrant == 4:
units2pitch = -units2pitch
print 'steps to yaw %f \t steps to pitch %f' % (units2yaw, units2pitch)
self.move(units2yaw, units2pitch, 1, 3000)
time.sleep(5)
# return to the datum point
self.move(-units2yaw, -units2pitch, 1, 0)
def calc_a(x_point, y_point):
A = pylab.sum(pylab.square(x_point)) * 30
B = pylab.square(pylab.sum(x_point))
C = pylab.sum(x_point * y_point) * 30
D = pylab.sum(x_point) * pylab.sum(y_point)
a = (C - D) / (A - B)
print(a)
def r_squared(y, estimated):
"""
Calculate the R-squared error term.
Args:
y: 1-d pylab array with length N, representing the y-coordinates of the
N sample points
estimated: an 1-d pylab array of values estimated by the regression
model
Returns:
a float for the R-squared error term
"""
# TODO
# pass
mean = pylab.mean(y)
result = 1 - pylab.sum(pylab.square(y - estimated)) / pylab.sum(
pylab.square(y - mean))
return result
def rmse(y, estimated):
"""
Calculate the root mean square error term.
Args:
y: an 1-d pylab array with length N, representing the y-coordinates of
the N sample points
estimated: an 1-d pylab array of values estimated by the regression
model
Returns:
a float for the root mean square error term
"""
# TODO
return pylab.sqrt(pylab.sum(pylab.square(y - estimated)) / y.shape[0])
def hinton(W):
"""Draw a hinton diagram of the matrix W on the current pylab axis"""
M,N = W.shape
square_x,square_y = pylab.array([-.5,.5,.5,-.5]),pylab.array([-.5,-.5,.5,.5])
pylab.fill([-.5,N-.5,N-.5,-.5],[-.5,-.5,M-.5,M-.5],'grey')
Wmax = pylab.sqrt(pylab.square(W)).max() #pylab. has no abs!
for m,Wrow in enumerate(W):
for n,w in enumerate(Wrow):
c = pylab.signbit(w) and 'k' or 'w'#love python :)
pylab.fill(square_x*w/Wmax+n,square_y*w/Wmax+m,c,edgecolor=c)
pylab.axis('equal')
pylab.ylim(M-0.5,-0.5)
def qufromgain(caltable, badspw=[], paoffset=0.0):
mytb = taskinit.tbtool()
myme = taskinit.metool()
mytb.open(caltable + '/ANTENNA')
pos = mytb.getcol('POSITION')
meanpos = pl.mean(pos, 1)
frame = mytb.getcolkeyword('POSITION', 'MEASINFO')['Ref']
units = mytb.getcolkeyword('POSITION', 'QuantumUnits')
mpos = myme.position(frame,
str(meanpos[0]) + units[0],
str(meanpos[1]) + units[1],
str(meanpos[2]) + units[2])
myme.doframe(mpos)
# _geodetic_ latitude
latr = myme.measure(mpos, 'WGS84')['m1']['value']
print 'Latitude = ', latr * 180 / pi
mytb.open(caltable + '/FIELD')
nfld = mytb.nrows()
dirs = mytb.getcol('DELAY_DIR')[:, 0, :]
mytb.close()
print 'Found as many as ' + str(nfld) + ' fields.'
mytb.open(caltable + '/SPECTRAL_WINDOW')
nspw = mytb.nrows()
bandnames = [x.split('#')[0].split('_')[-1] for x in mytb.getcol('NAME')]
mytb.close()
print 'Found as many as ' + str(nspw) + ' spws.'
R = pl.zeros((nspw, nfld))
Q = pl.zeros((nspw, nfld))
U = pl.zeros((nspw, nfld))
mask = pl.ones((nspw, nfld), dtype=bool)
if (len(badspw) > 0):
mask[badspw, :] = False
QU = {}
mytb.open(caltable)
for ifld in range(nfld):
for ispw in range(nspw):
st = mytb.query('FIELD_ID==' + str(ifld) +
' && SPECTRAL_WINDOW_ID==' + str(ispw))
nrows = st.nrows()
if nrows > 0:
rah = dirs[0, ifld] * 12.0 / pi
decr = dirs[1, ifld]
times = st.getcol('TIME')
gains = st.getcol('CPARAM')
ants = st.getcol('ANTENNA1')
nants = ants.max() + 1
# times
time0 = 86400.0 * floor(times[0] / 86400.0)
rtimes = times - time0
# amplitude ratio
amps = pl.absolute(gains)
amps[amps == 0.0] = 1.0
ratio = amps[0, 0, :] / amps[1, 0, :]
ratio.resize(nrows / nants, nants)
# parang
parang = pl.zeros(len(times))
for itim in range(len(times)):
tm = myme.epoch('UTC', str(times[itim]) + 's')
last = myme.measure(tm, 'LAST')['m0']['value']
last -= floor(last) # days
last *= 24.0 # hours
ha = last - rah # hours
har = ha * 2.0 * pi / 24.0
parang[itim] = atan2((cos(latr) * sin(har)),
(sin(latr) * cos(decr) -
cos(latr) * sin(decr) * cos(har)))
parang.resize(nrows / nants, nants)
parang += bandpa(bandnames[ispw]) # feed pos ang offset
parang += (paoffset * pi / 180.) # manual feed pa offset
parangd = parang * (180.0 / pi)
A = pl.ones((nrows / nants, 3))
A[:, 1] = pl.cos(2 * parang[:, 0])
A[:, 2] = pl.sin(2 * parang[:, 0])
fit = pl.lstsq(A, pl.square(ratio))
ants0 = range(nants)
rsum = pl.sum(ratio[:, ants0], 1)
rsum /= len(ants0)
fit = pl.lstsq(A, pl.square(rsum))
R[ispw, ifld] = fit[0][0]
Q[ispw, ifld] = fit[0][1] / R[ispw, ifld] / 2.0
U[ispw, ifld] = fit[0][2] / R[ispw, ifld] / 2.0
P = sqrt(Q[ispw, ifld]**2 + U[ispw, ifld]**2)
X = 0.5 * atan2(U[ispw, ifld], Q[ispw, ifld]) * 180 / pi
print 'Fld=', ifld, 'Spw=', ispw, '(B=' + str(
bandnames[ispw]) + ', PA offset=' + str(
bandpa(bandnames[ispw]) * 180. /
pi) + 'deg)', 'Gx/Gy=', R[ispw, ifld], 'Q=', Q[
ispw, ifld], 'U=', U[ispw, ifld], 'P=', P, 'X=', X
else:
mask[ispw, ifld] = False
st.close()
if sum(mask[:, ifld]) > 0:
print 'For field id = ', ifld, ' there are ', sum(
mask[:, ifld]), 'good spws.'
Qm = pl.mean(Q[mask[:, ifld], ifld])
Um = pl.mean(U[mask[:, ifld], ifld])
QU[ifld] = (Qm, Um)
Qe = pl.std(Q[mask[:, ifld], ifld])
Ue = pl.std(U[mask[:, ifld], ifld])
Pm = sqrt(Qm**2 + Um**2)
Xm = 0.5 * atan2(Um, Qm) * 180 / pi
print 'Spw mean: Fld=', ifld, 'Q=', Qm, 'U=', Um, '(rms=', Qe, Ue, ')', 'P=', Pm, 'X=', Xm
mytb.close()
return QU
def qufromgain(caltable,badspw=[],paoffset=0.0):
mytb=taskinit.tbtool()
myme=taskinit.metool()
mytb.open(caltable+'/ANTENNA')
pos=mytb.getcol('POSITION')
meanpos=pl.mean(pos,1)
frame=mytb.getcolkeyword('POSITION','MEASINFO')['Ref']
units=mytb.getcolkeyword('POSITION','QuantumUnits')
mpos=myme.position(frame,
str(meanpos[0])+units[0],
str(meanpos[1])+units[1],
str(meanpos[2])+units[2])
myme.doframe(mpos)
# _geodetic_ latitude
latr=myme.measure(mpos,'WGS84')['m1']['value']
print 'Latitude = ',latr*180/pi
mytb.open(caltable+'/FIELD')
nfld=mytb.nrows()
dirs=mytb.getcol('DELAY_DIR')[:,0,:]
mytb.close()
print 'Found as many as '+str(nfld)+' fields.'
mytb.open(caltable+'/SPECTRAL_WINDOW')
nspw=mytb.nrows()
bandnames=[x.split('#')[0].split('_')[-1] for x in mytb.getcol('NAME')]
mytb.close()
print 'Found as many as '+str(nspw)+' spws.'
R=pl.zeros((nspw,nfld))
Q=pl.zeros((nspw,nfld))
U=pl.zeros((nspw,nfld))
mask=pl.ones((nspw,nfld),dtype=bool)
if (len(badspw)>0):
mask[badspw,:]=False
QU={}
mytb.open(caltable)
for ifld in range(nfld):
for ispw in range(nspw):
st=mytb.query('FIELD_ID=='+str(ifld)+' && SPECTRAL_WINDOW_ID=='+str(ispw))
nrows=st.nrows()
if nrows > 0:
rah=dirs[0,ifld]*12.0/pi
decr=dirs[1,ifld]
times=st.getcol('TIME')
gains=st.getcol('CPARAM')
ants=st.getcol('ANTENNA1')
nants=ants.max()+1
# times
time0=86400.0*floor(times[0]/86400.0)
rtimes=times-time0
# amplitude ratio
amps=pl.absolute(gains)
amps[amps==0.0]=1.0
ratio=amps[0,0,:]/amps[1,0,:]
ratio.resize(nrows/nants,nants)
# parang
parang=pl.zeros(len(times))
for itim in range(len(times)):
tm=myme.epoch('UTC',str(times[itim])+'s')
last=myme.measure(tm,'LAST')['m0']['value']
last-=floor(last) # days
last*=24.0 # hours
ha=last-rah # hours
har=ha*2.0*pi/24.0
parang[itim]=atan2( (cos(latr)*sin(har)),
(sin(latr)*cos(decr)-cos(latr)*sin(decr)*cos(har)) )
parang.resize(nrows/nants,nants)
parang+=bandpa(bandnames[ispw]) # feed pos ang offset
parang+=(paoffset*pi/180.) # manual feed pa offset
parangd=parang*(180.0/pi)
A=pl.ones((nrows/nants,3))
A[:,1]=pl.cos(2*parang[:,0])
A[:,2]=pl.sin(2*parang[:,0])
fit=pl.lstsq(A,pl.square(ratio))
ants0=range(nants)
rsum=pl.sum(ratio[:,ants0],1)
rsum/=len(ants0)
fit=pl.lstsq(A,pl.square(rsum))
R[ispw,ifld]=fit[0][0]
Q[ispw,ifld]=fit[0][1]/R[ispw,ifld]/2.0
U[ispw,ifld]=fit[0][2]/R[ispw,ifld]/2.0
P=sqrt(Q[ispw,ifld]**2+U[ispw,ifld]**2)
X=0.5*atan2(U[ispw,ifld],Q[ispw,ifld])*180/pi
print 'Fld=',ifld,'Spw=',ispw,'(B='+str(bandnames[ispw])+', PA offset='+str(bandpa(bandnames[ispw])*180./pi)+'deg)','Gx/Gy=',R[ispw,ifld],'Q=',Q[ispw,ifld],'U=',U[ispw,ifld],'P=',P,'X=',X
else:
mask[ispw,ifld]=False
st.close()
if sum(mask[:,ifld])>0:
print 'For field id = ',ifld,' there are ',sum(mask[:,ifld]),'good spws.'
Qm=pl.mean(Q[mask[:,ifld],ifld])
Um=pl.mean(U[mask[:,ifld],ifld])
QU[ifld]=(Qm,Um)
Qe=pl.std(Q[mask[:,ifld],ifld])
Ue=pl.std(U[mask[:,ifld],ifld])
Pm=sqrt(Qm**2+Um**2)
Xm=0.5*atan2(Um,Qm)*180/pi
print 'Spw mean: Fld=', ifld,'Q=',Qm,'U=',Um,'(rms=',Qe,Ue,')','P=',Pm,'X=',Xm
mytb.close()
return QU
def Fn(na=0.78, nc=1., D=13.5, Trx=20, L=1):
A = pl.pi*pl.square(D/2.);
numer = pl.sqrt(2)*k*Trx;
denom = na*nc*A*pl.sqrt(L)
dI = numer/denom;
return dI;
def sum_of_squares(self, parms):
model = mp.func(self.cut_xpsd, *parms)
return sum(p.square(model / self.cut_ypsd - self.cut_ypsd / model))
def qufromgain(caltable,badspw=[],badant=[],fieldids=[],paoffset=None):
mytb=taskinit.tbtool()
myme=taskinit.metool()
pos=myme.observatory('atca')
myme.doframe(pos)
# _geodetic_ latitude
latr=myme.measure(pos,'WGS84')['m1']['value']
#print 'latitude: ',latr*180/pi
mytb.open(caltable+'/FIELD')
nfld=mytb.nrows()
dirs=mytb.getcol('DELAY_DIR')[:,0,:]
mytb.close()
print 'Found '+str(nfld)+' fields.'
mytb.open(caltable+'/SPECTRAL_WINDOW')
freq=mytb.getcol('REF_FREQUENCY')
nspw=mytb.nrows()
mytb.close()
print 'Found '+str(nspw)+' spws.'
#sort out pa offset to apply
paoff=pl.zeros(nspw)
if paoffset==None:
# use defaults for ATCA
# (should get these from Feed subtable, but cal table doesn't have one)
for ispw in range(nspw):
if freq[ispw]<30e9 or freq[ispw]>50e9:
paoff[ispw]=45.
else:
paoff[ispw]=135.
else:
paoff=paoffset
R=pl.zeros((nspw,nfld))
Q=pl.zeros((nspw,nfld))
U=pl.zeros((nspw,nfld))
mask=pl.ones((nspw,nfld),dtype=bool)
if (len(badspw)>0):
mask[badspw,:]=False
if (len(fieldids)==0):
fieldids=range(nfld)
QU={}
mytb.open(caltable)
for ifld in fieldids:
for ispw in range(nspw):
if not mask[ispw,ifld]:
continue
st=mytb.query('FIELD_ID=='+str(ifld)+' && SPECTRAL_WINDOW_ID=='+str(ispw))
nrows=st.nrows()
if nrows > 0:
rah=dirs[0,ifld]*12.0/pi
decr=dirs[1,ifld]
times=st.getcol('TIME')
gains=st.getcol('CPARAM')
ants=st.getcol('ANTENNA1')
ntimes=len(pl.unique(times))
nants=ants.max()+1
#print nrows, ntimes, nants
# times
time0=86400.0*floor(times[0]/86400.0)
rtimes=times-time0
# amplitude ratio
amps=pl.absolute(gains)
amps[amps==0.0]=1.0
ratio=amps[0,0,:]/amps[1,0,:]
# parang
parang=pl.zeros(len(times))
for itim in range(len(times)):
tm=myme.epoch('UTC',str(times[itim])+'s')
last=myme.measure(tm,'LAST')['m0']['value']
last-=floor(last) # days
last*=24.0 # hours
ha=last-rah # hours
har=ha*2.0*pi/24.0
parang[itim]=atan2( (cos(latr)*sin(har)),
(sin(latr)*cos(decr)-cos(latr)*sin(decr)*cos(har)) )
ratio.resize(nrows/nants,nants)
parang.resize(nrows/nants,nants)
parang+=paoff[ispw]*pi/180.
parangd=parang*(180.0/pi)
A=pl.ones((nrows/nants,3))
A[:,1]=pl.cos(2*parang[:,0])
A[:,2]=pl.sin(2*parang[:,0])
fit=pl.lstsq(A,pl.square(ratio))
amask=pl.ones(nants,dtype=bool)
if len(badant)>0:
amask[badant]=False
rsum=pl.sum(ratio[:,amask],1)
rsum/=pl.sum(amask)
fit=pl.lstsq(A,pl.square(rsum))
R[ispw,ifld]=fit[0][0]
Q[ispw,ifld]=fit[0][1]/R[ispw,ifld]/2.0
U[ispw,ifld]=fit[0][2]/R[ispw,ifld]/2.0
P=sqrt(Q[ispw,ifld]**2+U[ispw,ifld]**2)
X=0.5*atan2(U[ispw,ifld],Q[ispw,ifld])*180/pi
print 'Fld=%i, Spw=%i, PA Offset=%5.1f, Gx/Gy=%5.3f, Q=%5.3f, U=%5.3f, P=%5.3f, X=%5.1f' % (ifld,ispw,paoff[ispw],R[ispw,ifld],Q[ispw,ifld],U[ispw,ifld],P,X)
else:
mask[ispw,ifld]=False
st.close()
if (sum(mask[:,ifld]))>0:
print 'For field id = ',ifld,' there are ',sum(mask[:,ifld]),'good spws.'
Qm=pl.mean(Q[mask[:,ifld],ifld])
Um=pl.mean(U[mask[:,ifld],ifld])
QU[ifld]=(Qm,Um)
Qe=pl.std(Q[mask[:,ifld],ifld])
Ue=pl.std(U[mask[:,ifld],ifld])
Pm=sqrt(Qm**2+Um**2)
Xm=0.5*atan2(Um,Qm)*180/pi
print 'Spw mean: Fld=%i Fractional: Q=%5.3f, U=%5.3f, (rms= %5.3f,%5.3f), P=%5.3f, X=%5.1f' % (ifld,Qm,Um,Qe,Ue,Pm,Xm)
mytb.close()
return QU