Joe,

OK, I got somewhere -- at first everything worked lousy,
but the system trained me enough so that it basically works OK.
(casapy didn't handle white space very well)

Notes in the Report.

 -Mark



Misc notes:


OK, blank space in the scripts gets you into MAJOR TROUBLE when
cutting and pasting.  spaces preceeding a value command result in
that command being invalid:

CASA [260]: i = 2

CASA [261]:  i = 2
------------------------------------------------------------
  File "<ipython console>", line 1
    i = 2
    ^
SyntaxError: invalid syntax

ALSO, tabs in your provided example script get misinterpreted
as "tell me more about this tool (ie, tb.<TAB>)


It seems that you can't have two tables open at the
same time?  Or images or MS?   BIG MISTAKE if true.

Hey, I got into a space where mp.close() (or mp.anything)
results in: File "<ipython console>", line 1
mp.array()


I solved for type='G' with cb ("crunchberry beast?"), and
LOW AND BEHOLD it found some good solutions in spite of only
having a single baseline!


Overall feeling is that this is a more
straightforward interface than the old AIPS++/glish,
although I am sort of hamstrung in that I don't know how to
do manipulative mathamatics in Python

Potentially major problem:
 tb.open('3C273_0506.ms')
 dat   = tb.getcol('DATA')
 t     = tb.getcol('TIME')
 i = 3
 t[i+1] - t[i]   # === ok, this works now, but it often DID NOT work.
##  and I can't figure out how to do vector operations on t, dat, which
##  seem to be lists???
 dt = t[1:64] - t [0:63]   ## how do I get a vector of dt?


Overall feeling is that this is a more
straightforward interface than the old AIPS++/glish,
although I am sort of hamstrung in that I don't know how to
do manipulative mathamatics in Python

On a number of occasions, casapy got into a bad state,
and things that should have worked did not -- restarting
casapy usually fixed things.


###############################################################################
## below, a script I was putting togther for the BIMA dataset
###############################################################################

ms.open('3C273_0506.ms')
ms.summary()                 # 1 channel, 65 rows, 14 minutes
ms.open('G1310_0506.ms')
ms.summary()                 # 1 channel??  315 rows,  7 hours
#
mp.open('3C273_0506.ms')
mp.plotoptions(plotsymbol='ro')
mp.array()
mp.uvcoverage()

mp.open('G1310_0506.ms')
mp.plotoptions(plotsymbol='ro')
mp.array()
mp.uvcoverage()
mp.vistime()            #  amp == 15

mp.uvdist(what='phase')
mp.vistime()    #  default = AMP    AMP == 1.??
mp.open('3C273_0506.ms')
mp.vistime()            #  amp == 15
mp.vistime(what='phase')    # phase dip
mp.markflags()           #  I don't see anything that I should flag

##
##
##    Hey, I got into a space where mp.close() (or mp.anything)
##    results in: File "<ipython console>", line 1
##    mp.array()

##
##  OK,  mp.elevation()  works
##       mp.elevation(what='phase')   works
##
##       how do we find out what the arguments are?
##        >>>>> pdoc
##
##       HOW DO I GET A PLOT OF THE MODEL DATA
##        AH:   mp.elevation(column='DATA', what='phase')



# calibrate data
cb.open('3C273_0506.ms')
cb.initcalset(); cb.reset()
cb.setsolve(type='M',t=60,table='3C273.M20')
cb.state()
cb.solve()
##
##  3s :=> 23 good solutions, 42 solutions with insufficient data
##  20s => 12 good, 21 failed
##  60s => 5 good    8 failed


cb.reset()
cb.setapply(type='M', table='3C273.M20')
cb.state()
cb.correct()
cb.close()


# Compare observed 'data' and 'corrected' data
mp.open('3C273_0506.ms')
mp.plotoptions(subplot=121)
mp.uvdist()
mp.plotoptions(subplot=121,overplot=true,plotsymbol='b+')
mp.uvdist('corrected')
mp.plotoptions(subplot=122)
mp.uvdist('data')
mp.plotoptions(subplot=122,overplot=true,plotsymbol='b+')
mp.setdata()
mp.uvdist('corrected')
pl.ylim(0.,1.5)
pl.savefig('3C273.M.corrected.60.png')



##   Do it again for 10s
cb.open('3C273_0506.ms')
cb.initcalset(); cb.reset()
cb.setsolve(type='M',t=10,table='3C273.M10')
cb.state()
cb.solve()
cb.setapply(type='M',table='3C273.M10')
cb.correct()
# Compare observed 'data' and 'corrected' data


mp.open('3C273_0506.ms')
mp.plotoptions(subplot=121)
mp.vistime()
mp.plotoptions(subplot=121,overplot=true,plotsymbol='b+')
mp.uvdist('corrected')
mp.plotoptions(subplot=122)
mp.uvdist('data', what='phase')
mp.plotoptions(subplot=122,overplot=true,plotsymbol='b+')
mp.setdata()
mp.vistime('corrected', what='phase')
pl.ylim(-1, 1)
pl.savefig('3C273.M.corrected.10.png')

##
mp.markflags()
mp.flagdata(true)


cb.open('3C273_0506.ms')
cb.initcalset(); cb.reset()
cb.setsolve(type='M',t=10,table='3C273.M10')
cb.state()
cb.solve()
cb.setapply(type='M',table='3C273.M10')
cb.correct()
# Compare observed 'data' and 'corrected' data


mp.open('3C273_0506.ms')
mp.plotoptions(subplot=121)
mp.vistime()
mp.plotoptions(subplot=121,overplot=true,plotsymbol='b+')
mp.uvdist('corrected')
mp.plotoptions(subplot=122)
mp.uvdist('data', what='phase')
mp.plotoptions(subplot=122,overplot=true,plotsymbol='b+')
mp.setdata()
mp.vistime('corrected', what='phase')
pl.ylim(-1, 1)
pl.savefig('3C273.M.corrected.10.png')



cb.open('3C273_0506.ms')
cb.initcalset(); cb.reset()
cb.setsolve(type='G',t=60,table='3C273.G')
cb.state()
cb.solve()
##
##   THIS SHOULD HAVE FAILED, but!
##   Found 4 good G Jones solutions.
##         1 solution intervals failed.
##         8 solution intervals had insufficient data.






cb.summary()

cb.setapply(type='M',table='3C273.M10')
cb.correct()
# Compare observed 'data' and 'corrected' data



##
##   Overall feeling is that this is a more
##   straightforward interface than the old AIPS++/glish,
##   although I am sort of hamstrung in that I don't know how to
##   do manipulative mathamatics in Python

##
##   Now, why are these so many M solutions that fail?
##

##
##   A lot of the system is not implemented yet!
##   tb.browse(), tb.summary(),


tb.open('3C273_0506.ms')
dat   = tb.getcol('DATA')
t     = tb.getcol('TIME')
flags = tb.getcol('FLAG')
wt    = tb.getcol('IMAGING_WEIGHT')
i = 0
dt = t
##   t[20] - t[19]   ==> this syntax doesn't work!
##
#while i < (len(t)-1) :
#    dt[i] = t[(i+1)] - t[i]
#
##
##   t, dat are stored as LISTS, which do not embrace Mathematical Operations ???
##
##



im.open('3C273_0506.ms')
im.advise()   ##  cell size: casac.Quantity --- how can I see this?
oo = im.advise()
qq = oo.get('cell')   ##  OK, we HAVE the quantity
qq.units
qq.value
## awkward, but OK
im.sensitivity().get('pointsource').value
im.sensitivity().get('pointsource').units