Plotting uv-coverages (plotuv)
A simple way to plot uv-coverages is offered by the task plotuv:
# plotuv :: Plot the baseline distribution
vis = '' # Name of input visibility file (MS)
field = '' # Select field using ID(s) or name(s)
antenna = '' # Select data based on antenna/baseline
spw = '' # Select spectral window/channels
observation = '' # Select by observation ID(s)
array = '' # Select (sub)array(s) by array ID number
maxnpts = 100000 # Maximum number of points per plot.
colors = ['r', 'y', 'g', 'b'] # a list of matplotlib color codes
symb = ',' # A matplotlib plot symbol code
ncycles = 1 # How many times to cycle through colors per
# plot.
figfile = '' # Save the plotted figure(s) using this name
vis = '' # Name of input visibility file (MS)
field = '' # Select field using ID(s) or name(s)
antenna = '' # Select data based on antenna/baseline
spw = '' # Select spectral window/channels
observation = '' # Select by observation ID(s)
array = '' # Select (sub)array(s) by array ID number
maxnpts = 100000 # Maximum number of points per plot.
colors = ['r', 'y', 'g', 'b'] # a list of matplotlib color codes
symb = ',' # A matplotlib plot symbol code
ncycles = 1 # How many times to cycle through colors per
# plot.
figfile = '' # Save the plotted figure(s) using this name
plotuv provides basic selection of data as well as plotting style options. The difference to plotms is that plotuv is also plotting the Hermitian conjugates of the visibilities, which produces the familiar symmetric plots. This is a remedy to the restriction in plotms to allow flagging of data, which is achieved via a unambiguous link from a displayed data point to a visibility. Plotting Hermitian conjugates would break this rule in plotms, so plotuv is used instead to plot Hermitian conjugates.
| Type | Figure |
|---|---|
| ID | examination-fig-plotuv |
| Caption | UV-coverage plotted with plotuv. In this plot, the colors represent different wavelengths. |