| TimeBeamIncoherent(timeseries_data[, ...]) | Usage: |
| makeAZELRDictGrid(AZ, EL, Distance[, nx, ...]) | Make a list containing direction dicts that represent a grid of nx * ny pointings around a central value specified by azimuth, elevation (in radians), and distance (in meter). |
A number of tools useful in calibrating radio data
Usage:
TimeBeamIncoherent(timeseries_data[nAntennas,blocklen],incoherent_sum=None) -> incoherent_sum.squareadd(timeseries_data)
returns incoherent_sum[blocklen]
Description:
Calculate the incoherent sum of the timeseries data of multiple antennas. Will square the E-Field and add all antennas into one time series, thus containing the ‘incoherent power’.
Example:
file = cr.open('/Users/falcke/LOFAR/usg/data/lofar/oneshot_level4_CS017_19okt_no-9.h5') #
file['BLOCKSIZE'] = 2**int(round(log(file['DATA_LENGTH'][0],2)))
file['SELECTED_DIPOLES']=[f for f in file['DIPOLE_NAMES'] if int(f)%2==1] # select uneven antenna IDs
timeseries_data = TimeBeamIncoherent(file['TIMESERIES_DATA'])
timeseries_data.plot()
Make a list containing direction dicts that represent a grid of nx * ny pointings around a central value specified by azimuth, elevation (in radians), and distance (in meter). offset is the offset between the pointings in radians (default: 5*deg).