simulator

class simulator[source]

Tool for simulation

simulator provides a unified interface for simulation of telescope processing. It can create a MeasurementSet from scratch or read in an existing MeasurementSet, it can predict synthesis data onto the (u,v) coordinates or single dish data onto (ra,dec) points, and it can corrupt this data through Gaussian errors, an atmospheric model, or through specific errors residing in (anti-) calibration tables.

In the observing phase, simulator creates a MeasurementSet and calculates uvw values. You first make a simulator tool, with the name of the MeasurementSet that you wish to construct. Next you use the various set methods to set up the observing (antenna locations, sources, spectral windows, etc.). Then you call the observe method for each observing scan you wish to make, or observemany to create several scans. You specify the source name, spectral window name, and observing times. After this, you have a MeasurementSet that is complete but visibilities=0.

In the prediction phase, you fill a MeasurementSet (either one newly created or a pre-existing one, perhaps from a real telescope) with data from a model or componentlist, and then corrupt the measurements (if desired).

NOTE: sm.predict assumes model image units are Jy/pixel, and in fact will overwrite the brightness units of the image itself!

The ft function of the imager tool can also be used to calculate the model visibility for a model image or componentmodels.

To apply errors, first set up the various effects using the relevant set methods, and then call corrupt.

Some important details: - One call to observe generates one scan (all rows have the same SCAN_NUMBER). - The start and stop times specified to observe need not be contiguous and so one can simulate antenna drive times or other gaps. - Currently there is only a rudimentary method to calculate patterns of observing (mosaicing), since it is easy to do this via sequences of calls of observe, or simutil::calcpointings, or the simobserve task - The heavy duty columns (DATA, FLAG, IMAGING_WEIGHT, etc. are tiled. New tiles are generated for each scan. Thus the TSM files will not get very large. - predict(incremental=False) calculates new visibilities and replaces the DATA column, - predict(incremental=True) calculates new visibilities, adds them to the DATA column - predict for any value of incremental then sets CORRECTED_DATA equal to DATA, and MODEL_DATA to 1

Methods Summary

`close`	Close tools and write data to disk.
`corrupt`	Add errors specified by the set functions (such as noise, gains, polarization leakage, bandpass, etc) to the visibility data.
`done`	Close tools and write data to disk.
`name`	Returns the name of the attached MeasurementSet.
`observe`	Observe a given source with a given spectral window for the specified times, including start, stop, integration, and gap times.
`observemany`	Observe given sources with a given spectral window for the specified times, including start, stop, integration, and gap times.
`oldsetnoise`	Set various system parameters from which the thermal (ie, random
`open`	A simulator tool can either operate on an existing MeasurementSet, predicting and/or corrupting data on the existing uvw coordinates
`openfromms`	A simulator tool can either operate on an existing MeasurementSet, predicting and/or corrupting data on the existing uvw coordinates - to do that open the MS with sm.openfromms(msname) or it can be used to create a new MeasurementSet from descriptions of the array configuration and the observational parameters.
`predict`	Predict astronomical data from an image.
`reset`	Reset the visibility corruption terms: this means that corrupt introduces no errors.
`setapply`	Arrange for corruption by existing cal tables, in a manner exactly analogous to calibrater.setapply.
`setauto`	Set autocorrelation weight
`setbandpass`	Set the level of bandpass errors.
`setconfig`	Set the positions of the antennas.
`setdata`	This setup tool function selects which data are to be used subsequently.
`setfeed`	Specify feed parameters.
`setfield`	Set one or more observed fields, including name and coordinates.
`setgain`	Set the level of gain errors.
`setleakage`	Set the level of polarization leakage between feeds.
`setlimits`	Data are flagged for two conditions:
`setmosaicfield`	Set mosaic fields by internally invoking setfield multiple times.
`setnoise`	Set various system parameters from which the thermal (ie, random
`setoptions`	Set options for predict.
`setpa`	Corrupt phase by the parallactic angle
`setpointingerror`	Set the pointing error from a calpointing table
`setseed`	Set the seed for the random number generator
`setspwindow`	Set one or more spectral windows for the observations, including starting frequency, number of channels, channel increment and resolution, and stokes parameters observed.
`settimes`	This method sets values to be used in sm.observe.
`settrop`	Set up for corruption by the atmosphere - attenuation and increase in noise.
`setvp`	Set the voltage pattern model (and hence, the primary beam) used for a Telecope.
`simulator`	Create a simulator tool.
`summary`	Writes a summary of the currently set properties to the default logger.
`type`	This function returns the string ‘Simulator’.

close()[source]: Close tools and write data to disk. This is a synonym for done.

corrupt()[source]

Add errors specified by the set functions (such as noise, gains, polarization leakage, bandpass, etc) to the visibility data. The errors are applied to the DATA and CORRECTED_DATA columns.

Note that corrupt handles only visibility-plane effects, not image-plane effects such as pointing errors and voltage patterns, which get applied in predict. Note, the function applies errors to both cross- and auto-correlation data; The auto-correlation data are corrupted properly only for the thermalnoise set by setnoise.

done()[source]: Close tools and write data to disk. This is a synonym for done.

name()[source]: Returns the name of the attached MeasurementSet.

observe(sourcename='', spwname='', starttime='0s', stoptime='3600s', add_observation=False, state_sig=True, state_ref=False, state_cal=0.0, state_load=0.0, state_sub_scan=0, state_obs_mode='OBSERVE_TARGET.ON_SOURCE', observer='CASA simulator', project='CASA simulation')[source]

Observe a given source with a given spectral window for the specified times, including start, stop, integration, and gap times.

If usehourangle=False (set with settimes), the start and stop times are referenced to referencetime.

If userhourangle=True, starttime/stoptime are interpreted as startha/stopha, the start and stop times are calculated such that the start time is later than the reference time, but less than one day later, and the hour angles refer to the first source observed.

setconfig, setspwindow, setfeed, and setfield must be run before observe can be run.

See also sm.observe

Parameters

sourcenames (stringVec='') - Name of sources
spwname (string='') - Unique user-supplied name for this spectral window
starttimes (stringVec=['0s']) - Start times referenced to referencetime, or start hour angle
stoptimes (stringVec=['3600s']) - Stop time referenced to referencetime, or stop hour angle
directions (stringVec=[''])
add_observation (bool=False) - Add a new line to the OBSERVATION subtable for this call
state_sig (bool=True) - a new line will be added to STATE if the following don’t match
state_ref (bool=False)
state_cal (double=0.0)
state_load (double=0.0)
state_sub_scan (int=0)
state_obs_mode (string='OBSERVE\_TARGET#ON\_SOURCE')
observer (string='CASA simulator')
project (string='CASA simulation')

Returns

bool

oldsetnoise(mode='calculate', table='', simplenoise='0.0Jy', antefficiency=0.8, correfficiency=0.85, spillefficiency=0.85, tau=0.1, trx=50, tatmos=230.0, tcmb=2.7)[source]

Set various system parameters from which the thermal (ie, random additive) noise level will be calculated.

For mode=simplenoise, one specifies the standard deviation for the noise to be added to real and imaginary parts of the visibility.

For mode=calculate, the noise will vary with dish diameter, antenna efficiency, system temperature, opacity, sky temperature, etc. The noise will increase with the airmass if tau is greater than zero. The noise is calculated according to the Brown Equation (ie, R.L. Brown’s calculation of MMA sensitivity, 3Oct95):

dS = 4*sqrt(2) *( T_rx*exp(-tau_atm) + T_atm*( exp(tau_atm) - epsilon_l + T_cmb) ) *epsilon_q *epsilon_a *pi *D^2 *sqrt(dnu*dt)

Parameters

mode (string='calculate') - Mode of operation. String: ‘simplenoise’|’calculate’
table (string='') - Name of noise table - not currently implemented
simplenoise (variant='0.0Jy') - Level of noise (if mode=simplenoise)
antefficiency (double=0.8) - antenna efficiency
correfficiency (double=0.85) - Correlation efficiency
spillefficiency (double=0.85) - Forward spillover efficiency
tau (double=0.1) - Atmospheric Opacity
trx (double=50) - Receiver temp (ie, all non-atmospheric Tsys contributions) [K]
tatmos (double=230.0) - (Physical, not Brightness) Temperature of atmosphere [K]
tcmb (double=2.7) - Temperature of cosmic microwave background [K]

Returns

bool

open(ms='')[source]

A simulator tool can either operate on an existing MeasurementSet, predicting and/or corrupting data on the existing uvw coordinates

– to do that open the MS with sm.openfromms(msname).

or it can be used to create a new MeasurementSet from descriptions of the array configuration and the observational parameters

– to create a new MS, use this method sm.open(msname).

You will also need to run setconfig, setfield, setspw, setspwindow, setfeed, and settimes.

Creating the actual (empty) MS is accomplished with sm.observe. Data can be subsequently sm.predict-ed and sm.corrupt-ed.

NOTE: sm.predict assumes the model image units are Jy/pixel, and in fact will overwrite the brightness units of the image itself!

Parameters

ms (string='') - MeasurementSet to be created

Returns

bool

Examples

In this example, we read in the antenna coordinates from an ASCII file, 
and simulate a single-pointing VLA observation with a calibrator. 
Note that no primary beam attenuation will be applied (see sm.setvp).

tabname = 'VLAC.LOCAL.TAB'
asciifile = 'VLAC.LOCAL.STN'
mytab=table.create()
mytab.fromascii(tabname, asciifile);
xx=[]; yy:=[]; zz:=[]; diam:=[];
xx = mytab.getcol('X');  
yy = mytab.getcol('Y');
zz = mytab.getcol('Z');
diam = mytab.getcol('DIAM');
#
sm.open('NEW1.ms')
# do configuration
posvla = me.observatory('vla');  #  me.observatory('ALMA') also works!
sm.setconfig(telescopename='VLA', x=xx, y=yy, z=zz, dishdiameter=diam, 
          mount='alt-az', antname='VLA',
             coordsystem='local', referencelocation=posvla);

# Initialize the spectral windows    
sm.setspwindow(spwname='CBand', freq='5GHz',
            deltafreq='50MHz',
            freqresolution='50MHz',
            nchannels=1,
            stokes='RR RL LR LL');
sm.setspwindow(spwname='LBand', freq='1.420GHz',
            deltafreq='3.2MHz',
            freqresolution='3.2MHz',
            nchannels=32,
            stokes='RR LL');

# Initialize the source and calibrater
sm.setfield(sourcename='My cal',
         sourcedirection=['J2000','00h0m0.0','+45.0.0.000'],
         calcode='A');
sm.setfield(sourcename='My source',
         sourcedirection=['J2000','01h0m0.0','+47.0.0.000']);

sm.setlimits(shadowlimit=0.001, elevationlimit='8.0deg');
sm.setauto(autocorrwt=0.0);

sm.settimes(integrationtime='10s', usehourangle=F, 
            referencetime=me.epoch('utc', 'today'));

sm.observe('My cal', 'LBand', starttime='0s', stoptime='300s');
sm.observe('My source', 'LBand', starttime='310s', stoptime='720s');
sm.observe('My cal', 'CBand', starttime='720s', stoptime='1020s');
sm.observe('My source', 'CBand', starttime='1030s', stoptime='1500s');

sm.setdata(spwid=1, fieldid=1);
sm.predict(imagename='M31.MOD');
sm.setdata(spwid=2, fieldid=2);
sm.predict(imagename='BigLBand.MOD');
sm.close();    

openfromms(ms='')[source]

A simulator tool can either operate on an existing MeasurementSet, predicting and/or corrupting data on the existing uvw coordinates - to do that open the MS with sm.openfromms(msname) or it can be used to create a new MeasurementSet from descriptions of the array configuration and the observational parameters. - to create a new MS, use sm.open(msname).

NOTE: sm.predict assumes the model image units are Jy/pixel, and in fact will overwrite the brightness units of the image itself!

Parameters

ms (string='') - MeasurementSet to be processed

Returns

bool

Examples

sm.openfromms('3C273XC1.MS');
sm.predict('3C273XC1.imagename');
sm.setnoise(simplenoise='10mJy');
sm.setgain(interval='100s', amplitude=0.01);
sm.corrupt();
sm.close();

predict(imagename='', complist='', incremental=False)[source]

Predict astronomical data from an image. The (u,v) coordinates already exist, either from a MeasurementSet we have read in or by generating the MeasurementSet coordinates and empty data through smobserve. This method calculates visibilities for those coordinates.

predict(incremental=False) calculates new visibilities and replaces the DATA column, - predict(incremental=True) calculates new visibilities, adds them to the DATA column - predict for any value of incremental then sets CORRECTED_DATA equal to DATA, and MODEL_DATA to 1 - predict assumes model image units are Jy/pixel, and in fact will overwrite the brightness units of the image itself! - treatment of primary beam depends critically on parameters set in sm.setvp() and sm.setoptions(ftmachine) - see help sm.setvp for details. For componentlists, if sm.setvp() is run prior to predict, then the spectral variation of each component in the componentlist will include the multiplicative term of the beam value for each channel frequency. So a flat spectrum component will show the frequency variation of the beam in the predicted visibilities.

Parameters

imagename (stringVec='') - Name of image from which to predict visibilities
complist (string='') - Name of component list
incremental (bool=False) - Add this model to the existing Data Visibilities?

Returns

bool

reset()[source]: Reset the visibility corruption terms: this means that corrupt introduces no errors.

setapply(table='', type='B', t=0.0, field='', interp='aipslin', calwt=False, spwmap=[-1], opacity=0.0)[source]

Arrange for corruption by existing cal tables, in a manner exactly analogous to calibrater.setapply.

Parameters

table (string='') - Calibration table name
type (string='B') - Component type
t (double=0.0) - Interpolation interval (seconds)
field (variant='') - Select on field
interp (string='aipslin') - Interpolation type (in time)
calwt (bool=False) - Calibrate weights?
spwmap (intVec=[-1]) - Spectral windows to apply
opacity (double=0.0) - Array-wide zenith opacity (for type=’TOPAC’)

Returns

bool

setauto(autocorrwt=0.0)[source]

Set autocorrelation weight

Parameters

autocorrwt (double=0.0) - Weight to assign autocorrelations (0=none)

Returns

bool

setbandpass(mode='calculate', table='', interval='3600s', amplitude=[0.0])[source]

Set the level of bandpass errors. The error distributions are normal, mean zero, with the variances as specified. (Not yet implemented).

Parameters

mode (string='calculate') - Mode of operation. String: ‘calculate’|’table’
table (string='') - Name of table
interval (variant='3600s') - Coherence interval e.g. ‘1h’
amplitude (doubleVec=[0.0]) - Variances errors in amplitude and phase

Returns

bool

setconfig(telescopename='VLA', x=[0], y=[0], z=[0], dishdiameter=[0], offset=[0], mount=['ALT-AZ'], antname=['A'], padname=['P'], coordsystem='global', referencelocation='ALMA')[source]

Set the positions of the antennas. - The name of the telescope will control which voltage pattern is applied to the data (see sm.setvp for details). - The diameter(s) will be written to the antenna subtable but ONLY affect the calculated visibilities in sm.predict if telescope=ALMA,ACA,OVRO, *and* ftmachine=mosaic (see sm.setvp for details). - simutil::readantenna can be used to read an antenna config. file which includes many existing observatories. see help for the simobserve task, or the example below

Parameters

telescopename (string='VLA') - Name of the telescope we are simulating (determines VP)
x (doubleVec=[0]) - Vector of x values of all antennas [m]
y (doubleVec=[0]) - Vector of y values of all antennas [m]
z (doubleVec=[0]) - Vector of z values of all antennas [m]
dishdiameter (doubleVec=[0]) - Vector of diameters of all antennas [m]
offset (doubleVec=[0]) - Vector of offset of all antennas [m]
mount (stringVec=['ALT-AZ']) - Vector of mount types of all antennas (recognized mounts are ‘ALT-AZ’, ‘EQUATORIAL’, ‘X-Y’, ‘ORBITING’, ‘BIZARRE’
antname (stringVec=['A']) - Vector of names of all antennas
padname (stringVec=['P']) - Vector of names of pads or stations
coordsystem (string='global') - Coordinate system of antenna positions [x,y,z], possibilities are ‘global’, ‘local’ , ‘longlat’
referencelocation (variant='ALMA') - Reference location [required for local coords] Position Measure of Coordinates of array location. E.g me.position(‘ITRF’, ‘30.5deg’, -20.2deg’, 6000km’) or me.observatory(‘ALMA’)

Returns

bool

Examples

# known antenna configurations are stored in the data repository, 
# for historical reasons under "alma" even though this includes all
# known observatories:
configdir=casa.values()[0]['data']+"/alma/simmos/"

# please look in that directory if your observatory is present.
# if so, simutil can be used to read the file:
from simutil import simutil
# a simutil must be instantiated to use most methods
u=simutil()
x,y,z,d,padnames,telescope,posobs = u.readantenna(configdir+"vla.a.cfg")

# note that readantenna converts the positions to earth-centered 
# global, from whatever format is in the configuration file, so 
# coordsystem="global" should be used in setconfig
sm.setconfig(telescopename=telescope, x=x, y=y, z=z, 
             dishdiameter=d.tolist(), 
             mount=['alt-az'], antname=padnames,
             coordsystem='global', referencelocation=pospbs);

setdata(spwid=[0], fieldid=[0], msselect='')[source]

This setup tool function selects which data are to be used subsequently. After invocation of setdata, only the selected data are operated on.

Parameters

spwid (intVec=[0]) - Spectral Window Ids (0 relative) to select
fieldid (intVec=[0]) - Field Ids (0 relative) to select
msselect (string='') - TAQL select string applied as a logical “and” with the other selections

Returns

bool

setfeed(mode='', x=[0], y=[0], pol=['R'])[source]

Specify feed parameters. At this moment, you only have the choice between ’perfect R L’ and ’perfect X Y’ (i.e., you cannot invent your own corrupted feeds yet). Doesn’t need to be run if you want perfect R and L feeds.

Parameters

mode (string='') - Mode for specifying feed parameters (currently, perfect only)
x (doubleVec=[0]) - Some very secretive feed array parameter x
y (doubleVec=[0]) - Some more very secretive feed array parameter y
pol (stringVec=['R'])

Returns

bool

setfield(sourcename='SOURCE', sourcedirection='', calcode='', distance='0m')[source]

Set one or more observed fields, including name and coordinates. Can be invoked multiple times for a complex observation. Must be invoked at least once before sm.observe.

If the distance to the object is set then the phase term includes a curvature for the near-field effect at the center of the image.

Parameters

sourcename (string='SOURCE') - Name of source or field (must be specified)
sourcedirection (variant='') - Direction Measure of Coordinates of source to be observed. E.g me.direction(‘J2000’, ‘30.5deg’,’-20.2deg’).
calcode (string='') - Calibration code
distance (variant='0m') - Distance to the object

Returns

bool

Examples

sm.setconfig(telescopename=telescope, x=x, y=y, z=z, 
             dishdiameter=d.tolist(), 
             mount=['alt-az'], antname=padnames,
             coordsystem='global', referencelocation=pospbs);

sm.setspwindow(spwname='XBAND', freq='8GHz', deltafreq='50MHz',
               freqresolution='50MHz', nchannels=1, stokes='RR
               LL');
dir0 = me.direction('B1950',  '16h00m0.0', '50d0m0.000')
sm.setfield(sourcename='SIMU1', sourcedirection=dir0);
sm.settimes(integrationtime="10s", usehourangle=True, 
            referencetime=me.epoch('TAI', "2012/01/01/00:00:00"))
sm.observe(sourcename='SIMU1', spwname='XBAND',
           starttime='0s', stoptime='3600s')

setgain(mode='fbm', table='', interval='10s', amplitude=[0.01])[source]

Set the level of gain errors. Gain drift is implemented as fractional brownian motion with rms amplitude as specified. Interval is not currently used.

Parameters

mode (string='fbm') - Mode of operation. String: ‘fbm’
table (string='') - Optional name of table to write
interval (variant='10s') - timescale for gain variations NOT USED
amplitude (doubleVec=[0.01]) - amplitude scale (RMS) for gain variations [real,imag] or scalar

Returns

bool

setleakage(mode='constant', table='', amplitude=[0.01], offset=[0.0])[source]

Set the level of polarization leakage between feeds. Currently, no time dependence is available.

Parameters

mode (string='constant') - Mode of operation. String: ‘constant’
table (string='') - Optional name of table to write
amplitude (doubleVec=[0.01]) - Magnitude of pol leakage [real,imag]
offset (doubleVec=[0.]) - Meam of pol leakage [real,imag]

Returns

bool

setlimits(shadowlimit=1e-06, elevationlimit='10deg')[source]

Data are flagged for two conditions:

Below elevation limit: If either of the antennas point below the specified elevation limit then the data are flagged. The elevation is calculated correctly for antennas at different locations (such as occurs in VLBI).
Shadowing: If one antenna shadows another such that the fractional (geometric) blockage is greater than the specified limit then the data are flagged. No correction for blockage is made for shadowed but non-flagged points.

Parameters

shadowlimit (double=1e-6) - Maximum fraction of geometrically shadowed area before flagging occurs
elevationlimit (variant='10deg') - Minimum elevation angle before flagging occurs

Returns

bool

setmosaicfield(sourcename='SOURCE', calcode='', fieldcenter='', xmosp=1, ymosp=1, mosspacing='1arcsec', distance='0m')[source]

Set mosaic fields by internally invoking setfield multiple times. Currently only handle a rectangular mosaicing pattern. Either setfield or setmosaicfield must be invoked at least once before observe.

If the distance to the object is set then the phase term includes a curvature for the near-field effect at the center of the image.

Parameters

sourcename (string='SOURCE') - Name of source or field (must be specified).
calcode (string='') - Calibration code
fieldcenter (variant='') - Coordinates of mosaic field center
xmosp (int=1) - Number of mosaic pointing in horizontal direction
ymosp (int=1) - Number of mosaic pointing in vertical direction
mosspacing (variant='1arcsec') - Spacing between mosaic pointings
distance (variant='0m') - Distance to the object

Returns

bool

Examples

sm.setconfig(telescopename='VLA', x=xx, y=yy, z=zz, dishdiameter=diam,
             mount='alt-az', antname='VLA',
             coordsystem='local', referencelocation=dm.observatory('vla'));

sm.setspwindow(spwname='XBAND', freq='8GHz', deltafreq='50MHz',
               freqresolution='50MHz', nchannels=1, stokes='RR
               LL');
dir0 = me.direction('B1950',  '16h00m0.0', '50d0m0.000')
sm.setmosaicfield(sourcename='SIMU1', fieldcenter=dir0,
                  xmosp=2, ymosp=2, mosspacing='154.5arcsec');
sm.settimes(integrationtime='10s');
sm.observe('SIMU1_1', 'XBAND', starttime='0s', stoptime='100s');
sm.observe('SIMU1_2', 'XBAND', starttime='110s', stoptime='210s');
sm.observe('SIMU1_3', 'XBAND', starttime='220s', stoptime='320s');
sm.observe('SIMU1_4', 'XBAND', starttime='330s', stoptime='430s');

setnoise(mode='simplenoise', table='', simplenoise='0.1Jy', pground='560mbar', relhum=20.0, altitude='5000m', waterheight='200m', pwv='1mm', tatmos=250.0, tau=0.1, antefficiency=0.8, spillefficiency=0.85, correfficiency=0.88, trx=50, tground=270.0, tcmb=2.73, OTF=True, senscoeff=0.0, rxtype=0)[source]

Set various system parameters from which the thermal (ie, random additive) noise level will be calculated.

For mode=simplenoise, one specifies the standard deviation “sigma” for the noise to be added to real and imaginary parts of the visibility. The noise in amplitude per visibility is approximately “sigma” although it is not Gaussian (see Thompson, Moran, and Swenson fig. 6.9) and the point source noise in a Stokes I image will approximately be sigma/sqrt(n_pol * n_baselines * n_integrations * n_chan), where n_pol are the number of polarizations in the MS (typically 2), and n_integrations are the number of correlator integration times in the MS (~ track time / int. time)

For mode=tsys-atm or tsys-manual, the noise will vary with dish diameter, antenna efficiency, system temperature, opacity, sky temperature, etc. The noise will increase with the airmass if tau is greater than zero. The noise is calculated according to the Brown Equation (ie, R.L. Brown’s calculation of MMA sensitivity, 3Oct95):

dS = 4*sqrt(2) *( T_rx*exp(-tau_atm) + T_atm*( exp(tau_atm) - epsilon_l + T_cmb) ) *epsilon_q *epsilon_a *pi *D^2 *sqrt(dnu*dt)

For mode=tsys-atm, the sky brightness temperature is calculated using an atmospheric model created for the user-input PWV. For mode=tsys-manual, the user specifies the sky brightness temperature manually.

Parameters

mode (string='simplenoise') - Mode of operation.
table (string='') - Name of optional cal table to write (if OTF=False)
simplenoise (variant='0.1Jy') - Level of noise if not calculated by amt
pground (variant='560mbar') - Ground pressure for ATM model (if tsys-atm)
relhum (double=20.0) - ground relative humidity for ATM model (if tsys-atm)
altitude (variant='5000m') - site altitude for ATM model (if tsys-atm)
waterheight (variant='200m') - Height of water layer for ATM model (if tsys-atm)
pwv (variant='1mm') - Precipitable Water Vapor ATM model (if tsys-atm)
tatmos (double=250.0) - Temperature of atmosphere [K] (if tsys-manual)
tau (double=0.1) - Zenith Atmospheric Opacity (if tsys-manual)
antefficiency (double=0.8) - Antenna efficiency
spillefficiency (double=0.85) - Forward spillover efficiency
correfficiency (double=0.88) - Correlation efficiency
trx (double=50) - Receiver temp (ie, all non-atmospheric Tsys contributions) [K]
tground (double=270.0) - Temperature of ground/spill [K]
tcmb (double=2.73) - Temperature of cosmic microwave background [K]
OTF (bool=True) - calculate noise on-the-fly (WARNING: only experts with high-RAM machines should use False)
senscoeff (double=0.) - sensitivity constant (1./sqrt(2) for interferometer [default]; 1. for total power)
rxtype (int=0) - Receiver type; 0=2SB, 1=DSB e.g. ALMA B9

Returns

bool

setoptions(ftmachine='ft', cache=0, tile=16, gridfunction='SF', location='ALMA', padding=1.3, facets=1, maxdata=2000.0, wprojplanes=1)[source]

Set options for predict. See also imager help.

To simulate single dish data, use gridft=SD and gridfunction=PB.

To invoke primary beam convolution in the uv domain, use ftmachine=”mosaic”. This is the only option that allows heterogeneous array simulation - see the example below and help sm.setvp for more details.

Parameters

ftmachine (string='ft') - Fourier transform machine. Possibilities are ‘ft’, ‘sd’, ‘mosaic’
cache (int=0) - Size of gridding cache in complex pixels
tile (int=16) - Size of a gridding tile in pixels (in 1 dimension)
gridfunction (string='SF') - Gridding function. String: ‘SF’|’BOX’|’PB’
location (variant='ALMA') - Location used in phase rotations. Position Measure of Coordinates of array location. E.g me.position(‘ITRF’, ‘30.5deg’, ‘-20.2deg’, ‘6000km’) or me.observatory(‘ALMA’)
padding (double=1.3) - Padding factor in image plane (>=1.0)
facets (int=1) - Number of facets
maxdata (double=2000.0) - Maximum data to write to a single TSM file (MB)
wprojplanes (int=1) - Number of projection planes when using wproject as the ft-machine

Returns

bool

Examples

# set some options
sm.setoptions(cache=10000000, tile=32, gridfunction='BOX', me.location('vla'))


# set ftmachine to invoke uv-domain primary beam convolution, and use that 
# to simulate a heterogeneous ALMA 7m+12m array.
from simutil import simutil
u=simutil()
configdir=casa.values()[0]['data']+"/alma/simmos/"
x,y,z,d,padnames,telescope,posobs = u.readantenna(configdir+"alma.cycle5.1.cfg")
x2,y2,z2,d2,padnames2,telescope2,posobs2 = u.readantenna(configdir+"aca.cycle5.cfg")

sm.open("new.het.alma.ms")
sm.setconfig(telescopename="ALMA",
  x=np.append(x,x2),y=np.append(y,y2),z=np.append(z,z2),
  dishdiameter=np.append(d,d2),
  mount=['alt-az'], padname=np.append(padnames,padnames2).tolist(),
  coordsystem='global', referencelocation=posobs)
sm.setspwindow(spwname="band1", freq="330GHz",
  deltafreq="1GHz",freqresolution="1GHz",nchannels=1,stokes='XX YY')
sm.setfeed(mode='perfect X Y',pol=[''])
sm.setlimits(shadowlimit=0.01, elevationlimit='10deg')
sm.setauto(0.0)
sm.setfield(sourcename="src1", 
  sourcedirection="ICRS 10:00:00.00 -23.01.22",
  calcode="OBJ", distance='0m')
sm.setfield(sourcename="src2", 
  sourcedirection="ICRS 10:00:00.00 -23.01.32",
  calcode="OBJ", distance='0m')
sm.settimes(integrationtime="10s", usehourangle=True, 
  referencetime=me.epoch('TAI', "2012/01/01/00:00:00"))
etime="600s"
sm.observe(sourcename="src1", spwname="band1",
  starttime=qa.mul(-1,qa.quantity(etime)),
  stoptime=qa.quantity(0,"s"));
sm.observe(sourcename="src2", spwname="band1",
  starttime=qa.quantity(0,"s"),
  stoptime=qa.quantity(etime));
sm.setoptions(ftmachine="mosaic")
sm.predict(imagename="point.ra10.image")
sm.done()

setpa(mode='calculate', table='', interval='10s')[source]

Corrupt phase by the parallactic angle

Parameters

mode (string='calculate') - Mode of operation. String: ‘calculate’|’table’
table (string='') - Name of table
interval (variant='10s') - Interval for parallactic angle application, e.g. ’10s’

Returns

bool

setpointingerror(epjtablename='', applypointingoffsets=False, dopbcorrection=False)[source]

Set the pointing error from a calpointing table

Parameters

epjtablename (string='') - Name of a table that has E-Jones errors for Pointing
applypointingoffsets (bool=False) - Apply pointing offsets
dopbcorrection (bool=False) - apply primary beam correction

Returns

bool

setseed(seed=185349251)[source]

Set the seed for the random number generator

Parameters

seed (int=185349251) - Seed

Returns

bool

setspwindow(spwname='XBAND', freq='8.0e9Hz', deltafreq='50e6Hz', freqresolution='50.e6Hz', refcode='TOPO', nchannels=1, stokes='RR LL')[source]

Set one or more spectral windows for the observations, including starting frequency, number of channels, channel increment and resolution, and stokes parameters observed. Can be invoked multiple times for a complex observation. Must be invoked at least once before observe.

Parameters

spwname (string='XBAND') - Unique user-supplied name for this spectral window
freq (variant='8.0e9Hz') - Starting frequency
deltafreq (variant='50e6Hz') - Frequency increment per channel
freqresolution (variant='50.e6Hz') - Frequency resolution per channel
refcode (string='TOPO') - Spectral reference code e.g. LSRK, TOPO, BARY
nchannels (int=1) - Number of channels
stokes (string='RR LL') - Stokes types to simulate

Returns

bool

Examples

To simulate a two spectral window (or two IF's in VLA jargon) data
set, use setpwid as follows (here we are simulating 16 channels, 50MHz
wide channel for each spectral window)


sm.setspwindow(spwname='CBAND', freq='2GHz', deltafreq='50MHz',
                   freqresolution='50MHz', nchannels=16, stokes='RR LL');

sm.setspwindow(spwname='SBAND', freq='5GHz', deltafreq='50MHz',
                   freqresolution='50MHz', nchannels=16, stokes='RR LL');


Note that the spwname is used in observe to determine which spectral window
to use.

settimes(integrationtime='10s', usehourangle=True, referencetime='50000.0d')[source]

This method sets values to be used in sm.observe.

If usehourangle=False, the start and stop times in sm.observe are referenced to referencetime.

If usehourangle=True, then in sm.observe, starttime/stoptime will be interpreted as startha/stopha. In that case, the start and stop times are calculated such that the start time is later than the reference time, but less than one day later. The hour angles refer to the first source observed.

Parameters

integrationtime (variant='10s') - Integration time
usehourangle (bool=True) - Use starttime/stoptime as hour angles - else they are referenced to referencetime
referencetime (variant='50000.0d') - Reference time for starttime and stoptime. Epoch Measure . E.g me.epoch(‘UTC’, ‘50000.0d’)

Returns

bool

settrop(mode='screen', table='', pwv=3.0, deltapwv=0.15, beta=1.1, windspeed=7.0, simint=-1.0)[source]

Set up for corruption by the atmosphere - attenuation and increase in noise.

Parameters

mode (string='screen') - Mode of operation - screen or individual antennas
table (string='') - Name of optional cal table to write
pwv (double=3.0) - total precipitable water vapour in mm
deltapwv (double=0.15) - RMS PWV fluctuations as a fraction of PWV parameter
beta (double=1.1) - exponent of fractional brownian motion
windspeed (double=7.) - wind speed for screen type corruption (m/s)
simint (double=-1.) - simulation time step interval (s)

Returns

bool

setvp(dovp=True, usedefaultvp=True, vptable='', dosquint=True, parangleinc='360deg', skyposthreshold='180deg', pblimit=0.01)[source]

Set the voltage pattern model (and hence, the primary beam) used for a Telecope. There are currently two ways to set the voltage pattern: by using the extensive list of defaults which the system knows about, or by creating a voltage pattern description with the vpmanager. If you are simulating a telescope which doesn’t yet exist, you will need to supply a model voltage pattern using the vpmanager.

sm.predict behavior depends critically on the parameters here, and the ftmachine parameter set in sm.setoptions

sm.predict will always query the vpmanager for a primary beam/VP pattern. if usedefaultvp==True, it will reset the vpmanager first, so that the PB obtained will be the default for the given telescope name if usedefaultvp==False, it will check whether vptable is set, and if so, load that table into the vpmanager and use the beams therein. if usedefaultvp==False and vptable is not set, it will use whatever is already set in the vpmanager (see example below for overriding a default telescope beam).

What sm.predict does with the obtained PB depends on the ftmachine and dovp parameters:

if ftmachine==”mosaic”: - a message “Performing Mosaic Gridding” indicates that one is using uv domain convolution for simulating from images. - if the primary beam returned by the vpmanager is ALMA, ACA, or OVRO, heterogeneous gridding will be invoked, and the dish diameter set in sm.setconfig, or already in the antenna subtable, will be used to convolve sky model images. for ALMA or ACA, dish diameter =12m will use a 10.7m Airy pattern, and dish diameter =7m will use a 6.25m Airy pattern. see help sm.setoptions for an example. - otherwise the PB returned by the vpmanager will be used. - heterogeneous simulation only works at present from a sky model image, NOT from sky model components. If you want to simulate a heterogeneous array, please add components to an image using ia.modify, and don’t specify a component list in sm.predict. Homogeneous array simulation from component lists works fine. - IF dovp=True, the primary beam returned by the vpmanager will be used to convolve sky model components. This is not automatically invoked by ftmachine=”mosaic”, but needs to be set explicitly with sm.setvp() if you are simulating from components in addition to or instead of sky model images.

if ftmachine==”ft” (the default): - a message “Synthesis Gridding” indicates that if requested with dovp==True, image domain PB convolution will be used. - if dovp==True, the primary beam returned by the vpmanager will be used to convolve sky model components and images.

Parameters

dovp (bool=True) - Multiply by the voltage pattern (ie, primary beam) when simulating
usedefaultvp (bool=True) - Look up the default VP for this telescope and frequency?
vptable (string='') - If usedefaultvp is False, provide a VP Table made with vpmanager
dosquint (bool=True) - Activate the beam squint in the VP model
parangleinc (variant='360deg') - Parallactice angle increment for squint application
skyposthreshold (variant='180deg') - Position threshold on the sky for feed arrays ??
pblimit (double=1.0e-2) - Primary beam limit to use in feed arrays ?

Returns

bool

Examples

# use the default primary beam in subsequent sm.predict (according to 
# whatever telescope name was set in sm.setconfig)
sm.setvp(dovp=True, usedefaultvp=True)
sm.predict(imagename="point.ra10.image",complist="point.cl")

# use an alternate VP table e.g. of the format created by vpmanager:
sm.setvp(dovp=True, usedefaultvp=False, vptable='MyAlternateVLAPBModel.TAB', dosquint=F);
sm.predict(imagename="point.ra10.image",complist="point.cl")

# set a VP and then use it overridding the default
# (if telescope="NGVLA" was used previously in setconfig, 
# or if an MS was loaded with observatory name = "NGVLA")
vp.setpbairy(telescope="NGVLA",dishdiam="10m",maxrad="5deg")
sm.setvp(dovp=True,usedefaultvp=False)
sm.predict(imagename="point.ra10.image",complist="point.cl")

simulator()[source]: Create a simulator tool.

summary()[source]: Writes a summary of the currently set properties to the default logger.

type()[source]: This function returns the string ‘Simulator’. It is used so that in a script, you can make sure this variable is a simulator tool.