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# This file was automatically generated by SWIG (http://www.swig.org). # Version 2.0.4 # # Do not make changes to this file unless you know what you are doing--modify # the SWIG interface file instead.
from sys import version_info if version_info >= (2,6,0): def swig_import_helper(): from os.path import dirname import imp fp = None try: fp, pathname, description = imp.find_module('_tableplot', [dirname(__file__)]) except ImportError: import _tableplot return _tableplot if fp is not None: try: _mod = imp.load_module('_tableplot', fp, pathname, description) finally: fp.close() return _mod _tableplot = swig_import_helper() del swig_import_helper else: import _tableplot del version_info try: _swig_property = property except NameError: pass # Python < 2.2 doesn't have 'property'. def _swig_setattr_nondynamic(self,class_type,name,value,static=1): if (name == "thisown"): return self.this.own(value) if (name == "this"): if type(value).__name__ == 'SwigPyObject': self.__dict__[name] = value return method = class_type.__swig_setmethods__.get(name,None) if method: return method(self,value) if (not static): self.__dict__[name] = value else: raise AttributeError("You cannot add attributes to %s" % self)
def _swig_setattr(self,class_type,name,value): return _swig_setattr_nondynamic(self,class_type,name,value,0)
def _swig_getattr(self,class_type,name): if (name == "thisown"): return self.this.own() method = class_type.__swig_getmethods__.get(name,None) if method: return method(self) raise AttributeError(name)
def _swig_repr(self): try: strthis = "proxy of " + self.this.__repr__() except: strthis = "" return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,)
try: _object = object _newclass = 1 except AttributeError: class _object : pass _newclass = 0
class tableplot(_object): """Proxy of C++ casac::tableplot class""" __swig_setmethods__ = {} __setattr__ = lambda self, name, value: _swig_setattr(self, tableplot, name, value) __swig_getmethods__ = {} __getattr__ = lambda self, name: _swig_getattr(self, tableplot, name) __repr__ = _swig_repr def __init__(self): """__init__(self) -> tableplot""" this = _tableplot.new_tableplot() try: self.this.append(this) except: self.this = this __swig_destroy__ = _tableplot.delete_tableplot __del__ = lambda self : None; def open(self, *args, **kwargs): """ open(self, tabnames = std::vector< string >(1, "")) -> bool
Summary Specify list of tables to operate on.
Description
Specify a list of table names to open for plotting. All plots will operate on these tables until open is called again to change the list of tables. Returns true if tables are valid, false otherwise.
Input Parameters: tabnames List of strings identifying Table names
Example:
# set the list of tables to plot from. tp.open(tabnames=['3c273.ms','3c48.ms'])
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""" return _tableplot.tableplot_open(self, *args, **kwargs)
def setgui(self, gui = False): """ setgui(self, gui = False) -> bool
Summary
Set the GUI on or off. Can be done only once !!
Description
Set the GUI on or off. Can be done only once !!
Input Parameters: gui gui=False to turn off gui false
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""" return _tableplot.tableplot_setgui(self, gui)
def savefig(self, *args, **kwargs): """ savefig(self, filename = string(""), dpi = -1, orientation = string(""), papertype = string(""), facecolor = string(""), edgecolor = string("")) -> bool
Summary
Save the currently plotted image.
Description
Store the contents of the plot window in a file. The file format (type) is based on the file name, ie. the file extension given determines the format the file is saved as. The accepted formats are eps, ps, png, pdf, and svg.
Internally, this function uses the matplotlib pl.savefig function.
Note that if a full path is not given that the files will be saved in the current working directory.
Input Parameters: filename Name the plot image is to be saved to. dpi Number of dots per inch (resolution) to save the image at. -1 orientation Either landscape or portrait. Supported by the postscript format only. papertype Valid values are: letter, legal, exective, ledger, a0-a10 and b0-b10. This option is supported byt the postscript format only. facecolor Color of space between the plot and the edge of the square. Valid values are the same as those accepted by the plotcolour option of tp.plotdata(). edgecolor Color of the outer edge. Valid values are the same as those accepted by the plotcolour option of tp.plotdata().
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""" return _tableplot.tableplot_savefig(self, *args, **kwargs)
def selectdata(self, *args, **kwargs): """ selectdata(self, taqlstring = string("")) -> bool
Summary
Perform a TaQL based subtable selection for subsequent plots.
Description
Specify a TaQL select string. A subtable will be generated, and passed to the plotter.
Input Parameters: taqlstring TaQL string for selection
Example:
# set the list of tables to plot from. tp.open(tabnames=['3c273.ms','3c48.ms']) tp.selectdata(taqlstring='ANTENNA1==5')
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""" return _tableplot.tableplot_selectdata(self, *args, **kwargs)
def plotdata(self, *args, **kwargs): """ plotdata(self, poption = initialize_record("1 1 6 0.8 1.0"), labels = std::vector< string >(1, ""), datastr = std::vector< string >(1, "")) -> bool
Summary
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. egin{enumerate} \item 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. \item 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). \item If multiple tables are specified in tp.open(), then the TaQL expressions are applied to all tables and overlay plots are generated. \item Plots can be made to separate panels whose locations on the plot window are user specified as a 3-tuple [nrows, ncolumns, panelnumber]. \item Multiple plots can be stacked upon each other on a panel (overplot mode). \item Plotter options can be specifed to control appearance, plot-style, labels, etc. nd{enumerate}
Valid TaQL strings must satisfy the following conditions. egin{enumerate} \item Each TaQL string must result in a Double scalar or array.\ { t 'AMPLITUDE(DATA[1,1])'} results in a Double scalar (valid). \ { t 'AMPLITUDE(DATA[1:2,1])'} results in a Double array (valid).\ { t 'MEAN(AMPLITUDE(DATA[1:2,1]))'} results in a Double scalar (valid).\ { t 'DATA[1,1]'} results in a Complex scalar (NOT valid).\ { t 'AMPLITUDE(DATA[1,1])\<10'} results in a Bool scalar (NOT valid). \item 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. \item 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.) \item 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. nd{enumerate}
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.
Input Parameters: poption Record of plot options 1 1 6 0.8 1.0 labels List of strings : Title,Xlabel,Ylabel datastr List of TaQL strings : X,Y
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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""" return _tableplot.tableplot_plotdata(self, *args, **kwargs)
def iterplotstart(self, *args, **kwargs): """ iterplotstart(self, poption = initialize_record("1 1 6 0.8 1.0"), labels = std::vector< string >(1, ""), datastr = std::vector< string >(1, ""), iteraxes = std::vector< string >(1, "")) -> bool
Summary Initialize plotting with an iteration axis
Description
Begin a series of plots using subtables constructed via an iteration axes. In addition to plotdata parameters, set a list of iteration axes (Table column names) and use iterplotnext() to step through. Only forward step through is allowed.
Input Parameters: poption Record of plot options default is nxpanels=1, nypanels=1, windowsize=6, aspectratio=0.8, fontsize=1.0 1 1 6 0.8 1.0 labels List of strings : Title,Xlabel,Ylabel datastr List of TaQL strings : X,Y iteraxes List of strings : Iteration axes
Example:
# Open a list of MS tables to plot from, # and initialize a plot of Amplitude vs UV distance for # channel 1 and stokes 1, iterating over Antenna1 tp.open(tabnames=['3c273.ms','3c48.ms']) pop = { 'nrows':3, 'ncols':1,'panel':1, 'plotcolour':1, 'aspectratio':1.6} iteraxes = ['ANTENNA1'] labels = ['Amplitude vs UVdist','uvdist','amplitude'] xystr = ['SQRT(SUMSQUARE(UVW[1:2]))','AMPLITUDE(DATA[1,1:2])'] tp.iterplotstart(poption=pop, labels=labels, datastr=xystr, iteraxes=iteraxes) tp.iterplotnext()
Example:
To iterate over baseline and plot Amplitude vs time, for stokes 1, channel 1.
pop = { 'nrows':4, 'ncols':1 } labels = ['Amplitude vs UVdist (iterating over Baseline)', 'uvdist','amplitude'] xystr = ['SQRT(SUMSQUARE(UVW[1:2]))','AMPLITUDE(DATA[1,1])'] iteraxes = ['ANTENNA1','ANTENNA2'] tp.iterplotstart(poption=plotopts,labels=labels, datastr=xystr,iteraxes=iteraxes)
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""" return _tableplot.tableplot_iterplotstart(self, *args, **kwargs)
def replot(self): """ replot(self) -> bool
Summary
Replot all existing panels and layers.
Description
Replot all existing panels and layers. To be used after a change of flag version, to get all visible plots to reflect the changed flags.
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""" return _tableplot.tableplot_replot(self)
def iterplotnext(self): """ iterplotnext(self) -> int
Summary
Start/Continue plotting
Description
Start/Continue plotting by stepping through the iteration axes. Call after tp.iterplotstart(). Returns 1 if additional iteration steps remain , 0 if last iteration has completed.
Example:
# iterate through the data
tp.open(tabnames=['3c273.ms','3c48.ms']) plotopts = {'aspectratio': 1.2, 'ncols': 2, 'nrows': 1} labels = ['Amplitude vs UVdist (iterating over Antenna1)', 'uvdist','amplitude'] xystr = ['SQRT(SUMSQUARE(UVW[1:2]))','AMPLITUDE(DATA[1,1])'] iteraxes = ['ANTENNA1'] tp.iterplotstart(poption=plotopts,labels=labels, datastr=xystr,iteraxes=iteraxes) ret = tp.iterplotnext() ret = tp.iterplotnext() ret = tp.iterplotnext() ...
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""" return _tableplot.tableplot_iterplotnext(self)
def iterplotstop(self, rmplotter = False): """ iterplotstop(self, rmplotter = False) -> bool
Summary Stop plot iterations.
Description
To be called at the end of the plot iterations, or in between if desired. Okay if ignored.
Input Parameters: rmplotter Indicates whether the plot window should be removed (true) from the display or left (false) false
Example:
# iterate through and stop after 5 iterations of 2 plots per page
tp.open(tabnames=['3c273.ms','3c48.ms']) plotopts = {'ncols': 2, 'nrows':1 } labels = ['Amplitude vs UVdist (iterating over Antenna1)', 'uvdist','amplitude'] xystr = ['SQRT(SUMSQUARE(UVW[1:2]))','AMPLITUDE(DATA[1,1])'] iteraxes = ['ANTENNA1'] tp.iterplotstart(poption=plotopts,labels=labels, datastr=xystr,iteraxes=iteraxes) ret = tp.iterplotnext() ret = tp.iterplotnext() ret = tp.iterplotnext() ret = tp.iterplotnext() ret = tp.iterplotnext() tp.iterplotstop()
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""" return _tableplot.tableplot_iterplotstop(self, rmplotter)
def markregions(self, *args, **kwargs): """ markregions(self, nrows = 0, ncols = 0, panel = 1, region = initialize_vector(1, (double)0.0)) -> bool
Summary Mark a rectangular region to flag
Description
Mark or specify a rectangular region to flag. Call without arguments to enable mouse based interactive region marking. Marked regions can be discarded via the 'Alt' key. Command-line region marking can be done by setting panel and region parameters. After marking flag regions, call tp.flagdata() or tp.unflagdata().
Input Parameters: nrows Number of rows of panels 0 ncols Number of columns of panels 0 panel Panel number 1 region [xmin,ymin,xmax,ymax] bounding box 0.0
Example:
tp.markregions(nrows=2,ncols=1,panel=1,region=[300.0,400.0,0.090,0.095])
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""" return _tableplot.tableplot_markregions(self, *args, **kwargs)
def flagdata(self): """ flagdata(self) -> bool
Summary
Flag Data for selected flag regions
Description
Set flags for all regions marked using { t tp.markregions()}. The plot is automatically redrawn after applying flags.
If reduction TaQL functions such as { t sum,mean} are used, flags corresponding to all accessed values will be modified. For example, with a measurement set table, flagging on the mean amplitude of stokes 1 and channels 1 to 5, given by 'MEAN(AMPLITUDE(DATA[1,1:5]))' results in flags being set for all 5 accessed channels.
For a measurement set, by default, flags are set only for accessed channels and stokes when the DATA column is used. However all channels/stokes can be flagged for the marked flag regions by setting the corresponding row flag.
--------------------------------------------------------------------------------
""" return _tableplot.tableplot_flagdata(self)
def unflagdata(self): """ unflagdata(self) -> bool
Summary
Unset flags for all regions marked using {tt tp.markregions()}.
Description
Unset flags for all regions marked using { t tp.markregions()}. This is similar to the tp.flagdata() function in all other respects.
Example:
# mark 2 flag regions on a multi-panel plot, one in panel 1 and one # in panel 2. Then apply the flags and write to disk. tp.markregions(panel=1) tp.markregions(panel=2) tp.unflagdata()
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""" return _tableplot.tableplot_unflagdata(self)
def locatedata(self, *args, **kwargs): """ locatedata(self, columnlist = std::vector< string >(1, "")) -> bool
Summary
Print info about data selected using tp.markregions().
Description
Print info about data selected using tp.markregions().
Input Parameters: columnlist List of strings : Column names (or TaQL expressions !)
--------------------------------------------------------------------------------
""" return _tableplot.tableplot_locatedata(self, *args, **kwargs)
def clearflags(self, roottable = False): """ clearflags(self, roottable = False) -> bool
Summary Clear all flags in the table.
Description
Clear all flags from the table. This may eventually be modified to allow for selective un-flagging of previously flagged regions (specified by indexing into a stored history of marked flag-regions).
Input Parameters: roottable false : clear flags for the current sub-selection; true : clear flags for root table false
Example:
# clear all flags from two measurement set tables
tp.open(tabnames=['3c273.ms','3c48.ms']) tp.clearflags() tp.done()
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""" return _tableplot.tableplot_clearflags(self, roottable)
def saveflagversion(self, *args, **kwargs): """ saveflagversion(self, versionname = string(""), comment = string(""), merge = string("")) -> bool
Summary Save current flags with a version name.
Description
Save current flags with a version name. This applies to the last opened Tables
Input Parameters: versionname Version name comment Comment for this flag table merge merge type
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""" return _tableplot.tableplot_saveflagversion(self, *args, **kwargs)
def restoreflagversion(self, *args, **kwargs): """ restoreflagversion(self, versionname = std::vector< string >(1, ""), merge = string("")) -> bool
Summary Restore flags from a saved flag_version.
Description Restore flags from a saved flag\_version. This applies to the last opened Tables
versionname : name of flag version to restore to main table merge : Type of operation to perform during restoration. merge = replace : replaces the main table flags. merge = and : logical AND with main table flags merge = or : logical OR with main table flags Default : replace.
Input Parameters: versionname Version name merge merge type
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""" return _tableplot.tableplot_restoreflagversion(self, *args, **kwargs)
def deleteflagversion(self, *args, **kwargs): """ deleteflagversion(self, versionname = std::vector< string >(1, "")) -> bool
Summary Delete a saved flag_version.
Description Delete a saved flag\_version. This applies to the last opened Tables
Input Parameters: versionname Version name
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""" return _tableplot.tableplot_deleteflagversion(self, *args, **kwargs)
def getflagversionlist(self): """ getflagversionlist(self) -> bool
Summary Print out a list of saved flag_versions.
Description
Print out a list of saved flag\_versions. This applies to the last opened Tables
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""" return _tableplot.tableplot_getflagversionlist(self)
def clearplot(self, nrows = 0, ncols = 0, panel = 0): """ clearplot(self, nrows = 0, ncols = 0, panel = 0) -> bool
Summary Clear a plot.
Description
Clear a plot. An empty argument list (i.e., clearplot()) or clearplot(0) clears all plots currently visible whereas clearplot(nrows,ncols,panel) clears a plot on a specified panel.
Input Parameters: nrows Number of rows of panels 0 ncols Number of columns of panels 0 panel Panel number (index) 0
Example:
# clear all flags from two measurement set tables
tp.open(tabnames=['3c273.ms','3c48.ms']) tp.clearflags() tp.done()
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""" return _tableplot.tableplot_clearplot(self, nrows, ncols, panel)
def done(self): """ done(self) -> bool
Summary Clean up the tableplot tool
Description Clean up the tableplot tool, and make it ready for tp.open() again.
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""" return _tableplot.tableplot_done(self)
tableplot_swigregister = _tableplot.tableplot_swigregister tableplot_swigregister(tableplot)
# This file is compatible with both classic and new-style classes.
|