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tableplot.plotdata - Function

3.2.2 Plot the result of a general TaQL expression.
Description

This function evaluates the specified TaQL expressions for the X and Y axes of a two-dimensional plot,extracts the resulting columns, and plots them.

  1. TaQL expressions resulting in scalars are plotted as a single X-Y plot. Expressions involving Array-Columns can result in arrays which are then plotted as overlays.
  2. The default mode of operation is to plot one expression against another. In the case of Array-Columns (ex. DATA column of a measurement set with each row containing an array of shape NColumns x NPolarzations), a Cross-plot mode allows plots with the x-axis representing one axes of the Array-Column. (ex. X-axis is channel number or polarization number).
  3. If multiple tables are specified in tp.open(), then the TaQL expressions are applied to all tables and overlay plots are generated.
  4. Plots can be made to separate panels whose locations on the plot window are user specified as a 3-tuple [nrows, ncolumns, panelnumber].
  5. Multiple plots can be stacked upon each other on a panel (overplot mode).
  6. Plotter options can be specifed to control appearance, plot-style, labels, etc.

Valid TaQL strings must satisfy the following conditions.

  1. Each TaQL string must result in a Double scalar or array.
    ’AMPLITUDE(DATA[1,1])’ results in a Double scalar (valid).
    ’AMPLITUDE(DATA[1:2,1])’ results in a Double array (valid).
    ’MEAN(AMPLITUDE(DATA[1:2,1]))’ results in a Double scalar (valid).
    ’DATA[1,1]’ results in a Complex scalar (NOT valid).
    ’AMPLITUDE(DATA[1,1])<10’ results in a Bool scalar (NOT valid).
  2. All TaQL functions resulting in Double Scalars/Arrays are allowed, except for those involving an explicit collapse axis (means,sums,etc..). Note that these functions are different from mean,sum,etc.. which are supported.
  3. TaQL strings must be provided as pairs of strings, with the X-TaQL first, followed by the Y-TaQL. There are 3 cases.
    X-TaQL - Scalar, Y-TaQL - Scalar (one-to-one single plot)
    X-TaQL - Scalar, Y-TaQL - Array (one-to-many overlay plot)
    X-TaQL - Array, Y-TaQL - Array (if the shapes are the same, then a one-to-one mapping is done, otherwise only the first X-TaQL result is used for a one-to-many mapping with the Y-TaQL Array.)
  4. For cross plots (for example amplitude vs channel plots in an MS), the X-TaQL must be a string containing ’CROSS’. The Y-TaQL is used to read out the data from the table, and the x-values are the column indices (channel numbers) chosen by the Y-TaQL.

Plotting options (’poption’ entries) are listed below.

    Default values are indicated within [ ] when present.  
    nrows [ 1 ] :            Number of rows of panels  
    ncols [ 1 ] :            Number of columns of panels  
    panel [ 1 ] :            Panel index. Must be in [1,nrows x ncols]  
    plotcolour [ 1 ] :       Plot colour. Codes for matplotlib are  
                             [0:black, 1:red, 2:green, 3:blue, 4:cyan, 5:yellow]  
                             [magenta is reserved for plotting flagged  
                                 values if showflags = 1 , and cannot be set  
                               by the user as a plot colour]  
                             If the plotcolour field is left out from ’poption’,  
                             colours are chosen automatically.  
    multicolour [ False ] :  True -> Each channel,pol appears in a different colour.  
                             False -> Data from all pols and channels appear  
                             in the same colour. Different colours  
                             appear for different layers (overplot).  
                             or data from different tables.  
    timeplot [ False ] :     True -> Turn on date/time formatting for the x-axis.  
    overplot [ False ] :     True -> Overlay on an existing plot. All layers will  
                             remain active for data editing via flagging. Labels  
                             will be those of the top-most layer.  
                             False -> Replace an existing plot with a new one.  
                             In the case of an existing stack of plots, the  
                             top-most layer is replaced. For example, this can be  
                             used to modify the colour of the top-most layer  
                             without creating an additional layer.  
    py_plotsymbol [ , ] :    Plot markers. Options for matplotlib are  
                             [[,]:pixel, [.]:point, [o]:circle, [x]:cross,  
                             [+]:plus, [^]:triangle up, [v]:triangle down,  
                             [<]:triangle left, [>]:triangle right,  
                             [-]:solid line, [--]:dashed line, [-.]:dash-dot line,  
                             [:]:dotted line, [s]:square, [D]:diamond,  
                             [d]:thin diamond, [1]:tripod down, [2]:tripod up,  
                             [3]:tripod left, [4]:tripod right, [h]:hexagon,  
                             [H]:rotated hexagon, [p]:pentagon,  
                             [|]:vertical line symbol, [_]:horizontal line symbol.  
    markersize [ 10.0 ] :    The size (in pixels) of the markers being plotted.  
                             Markers are specified by the py_plotsymbol option.  
                             For example, ’+’, ’o’, and ’d’  
    linewidth [ 2.0 ]        The width of the lines that are drawn, lines are  
                             if the py_plotsymbol chosen is a line.  For example,  
                             ’-’, ’--’, and ’:’.  
    plotrange [ ]  :         Only data within this specific range of values  
                             [xmin,xmax,ymin,ymax] will be plotted.  
                             Default is the data range.  
    showflags [ 0 ] :        True -> Plot only unflagged data.  
                             False -> Plot only flagged data.  
    crossdirection [ False ] : Applies only with CROSS-plots on table ArrayColumns.  
                             False -> use column number as the x-axis (ex. channel no.).  
                             True -> use row number as the x-axis (ex. polarization no.).  
    pointlabels [ ] :        Data points can be annotated by supplying a  
                             list of labels. If N labels are supplied, the  
                             first N data points plotted will be annotated.  
                             (Note that if data is edited via flagging,the  
                             points are relabeled to label the first N points.)  
    windowsize [ 8.0 ] :     horizontal size of plot window (inches)  
    aspectratio [ 0.8 ] :    aspect-ratio of the plot window (dx/dy)  
    fontsize [ 12.0 ] :      Font size of title text.  
                             Font size of x,y labels are 80% of this.  

Returns true if plotting is successful, false otherwise.

Arguments

Inputs

poption

Record of plot options

allowed:

any

Default:

record 1 1 6 0.8 1.0

labels

List of strings : Title,Xlabel,Ylabel

allowed:

stringArray

Default:

datastr

List of TaQL strings : X,Y

allowed:

stringArray

Default:

Returns
bool

Example

Plot data amplitude vs uv-distance for two Measurement set tables as a single panel plot. Operate on channel 1 for Stokes 1 and 2 using the DATA column.

 tp.open(tabnames=[’3c273.ms’,’3c48.ms’])  
 pop = { ’nrows’:1, ’ncols’:1,’panel’:1}  
 labels = [’Amplitude vs UVdist’,’uvdist’,’amplitude’]  
 xystr = [’SQRT(SUMSQUARE(UVW[1:2]))’,’AMPLITUDE(DATA[1,1:2])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

TaQL strings for the above example can also be written as follows.

  xystr = [’SQRT(UVW[1]*UVW[1]+UVW[2]*UVW[2])’,’AMPLITUDE(DATA[1,1:2])’]

Example

Multi-panel plotting

 # uvdist for pol 1 and chan 1,2 on panel 211  
 pop = { ’nrows’:2, ’ncols’:1,’panel’:1}  
 labels = [’Amplitude vs UVdist’,’uvdist’,’amplitude’]  
 xystr = [’SQRT(SUMSQUARE(UVW[1:2]))’,’AMPLITUDE(DATA[1,1:2])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)  
 
 # uvdist for pol 2 and chan 1,2 (overplot=1) on panel 211  
 pop = { ’nrows’:2, ’ncols’:1,’panel’:1, ’overplot’:True}  
 labels = [’Amplitude vs UVdist’,’uvdist’,’amplitude’]  
 xystr = [’SQRT(SUMSQUARE(UVW[1:2]))’,’AMPLITUDE(DATA[2,1:2])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)  
 
 # uv coverage on panel 223  
 pop = { ’nrows’:2, ’ncols’:2,’panel’:3, ’plotcolour’:4}  
 labels = [’UV Coverage’,’u’,’v’]  
 xystr = [’UVW[1]’,’UVW[2]’,’-UVW[1]’,’-UVW[2]’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)  
 
 # amp(data[1:2,1:10]) vs channel number on panel 224  
 pop = { ’nrows’:2, ’ncols’:2,’panel’:4, ’plotcolour’:1}  
 labels = [’Amplitude vs Baseline number’,’baseline number’,’amplitude’]  
 xystr = [’28*ANTENNA1+ANTENNA2-(ANTENNA1-1)*(ANTENNA1+2)/2’,  
           ’AMPLITUDE(DATA[1:2,1:10])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

Example

Plotting with time formatting

 # vistime for 10 chans (timeplot=1)  
 pop = { ’nrows’:1, ’ncols’:1,’panel’:1,’timeplot’:True}  
 labels = [’Timeplot’,’time’,’amplitude’]  
 xystr = [’TIME’,’AMPLITUDE(DATA[1:2,1:10])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

Example

Cross-plots - take in a single TaQL expression involving an ArrayColumn, and use the column numbers of each Array per row of the table as the x-axis. In a measurement set, the DATA ArrayColumn contains 2D Arrays, each with NCHAN columns and NPOL rows. Plotting with ’CROSS’ as the X-TaQL, uses channel numbers as the x-axis. The option ’crossdirection=True’ can be used to plot with polarization on the x-axis.

 
 pop = { ’nrows’:2, ’ncols’:1,’panel’:1, ’plotcolour’:2}  
 labels = [’Amplitude vs Channel number’,’chan’,’amplitude’]  
 xystr = [’CROSS’,’AMPLITUDE(DATA[1:2,1:10])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)  
 pop = { ’nrows’:2, ’ncols’:1,’panel’:1, ’plotcolour’:2, ’crossdirection’:True}  
 labels = [’Amplitude vs Polarization number’,’pol’,’amplitude’]  
 xystr = [’CROSS’,’AMPLITUDE(DATA[1:2,1:10])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

Example

Individual points can be annotated by specifying the ’pointlabels’ parameter. If N labels are specified, the first N data points to be plotted, are annotated.

 
 pop = {’nrows’:1,’ncols’:1, ’panel’:1, ’plotcolour’:1,’py_plotsymbol’:’o’,  
        ’pointlabels’:[’ A1’,’ A2’,’ A3’,’ A4’,’ A5’,’ A6’,’ A7’,’ A8’,  
                       ’ A9’,’ B1’,’ B2’,’ B3’,’ B4’,’ B5’,’ B6’,’ B7’,  
                       ’ B8’,’ B9’,’ C1’,’ C2’,’ C3’,’ C4’,’ C5’,’ C6’,  
                       ’ C7’,’ C8’,’ C9’,’ D1’,’ D2’,’ D3’,’ D4’]}  
 xystr = [’POSITION[1]’,’POSITION[2]’]  
 labels = [’Antenna positions’,’x’,’y’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

Example

To plot with multiple colours for each channel and polarization of an MS.

 #(multicolour=1, plotcolour > 5)  
 pop = { ’nrows’:1, ’ncols’:1,’panel’:1, ’plotcolour’:6,  
         ’showflags’:0, ’multicolour’:True}  
 labels = [’Amplitude vs UVdist’,’uvdist’,’amplitude’]  
 xystr = [’SQRT(SUMSQUARE(UVW[1:2]))’,’AMPLITUDE(DATA[1:2,1:2])’]  
 tp.plotdata(poption=pop,labels=labels,datastr=xystr)

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