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Author: Duncan Macleod <duncan.macleod@astro.cf.ac.uk>
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PlotSegmentsPlot Horizontal bar segment plot. |
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ScatterPlot A simple scatter plot, taking x- and y-axis data. |
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ColorbarScatterPlot A scatter plot of x- versus y-data, coloured by z-data. |
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DetCharScatterPlot A 'DetChar' style scatter plot, whereby those triggers under a threshold on the colour column are plotted much smaller than others, allowing line features to be shown easily. |
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LineHistogram A simple line histogram plot. |
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VerticalBarHistogram | |||
DataPlot Time-series data plot. |
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ColorMap | |||
SkyPositionsPlot Plot of sky positions plotted onto mpl_toolkits basemap projection. |
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ColorbarSkyPositionsPlot |
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_display = getenv('DISPLAY', '')
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_backend_warn = """No display detected, moving to 'Agg' backen
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__date__ = git_version.date This module provides plotting routines for use in data quality investigations. |
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Format the x- and y-axis ticks to ensure minor ticks appear when needed and the x-axis is set for spaces of 4 rather than 5. Arguments: ax : matplotlib.axes.AxesSubplot Axes object to format |
Format the string columnName (e.g. xml table column) into latex format for an axis label. Examples: >>> display_name('snr') 'SNR' >>> display_name('bank_chisq_dof') 'Bank $\chi^2$ DOF' Arguments: columnName : string string to format |
Work out renormalisation for the time axis, makes the label more appropriate. Returns unit (in seconds) and string descriptor Example: >>> time_unit(100) (1, 'seconds') >>> time_unit(604800) (86400, 'days') Arguments: duration : float plot duration to normalise |
Returns the value of trig.col or trig.get_col() for the given string col, and the object trig. If col='time' is given, trig.get_peak() is returned for *Burst* objects, trig.get_end() for *Inspiral* objects and trig.get_start() for *Ringdown* objects. Raises KeyError if cannot execute. Arguments: trig : [ lsctables.SnglBurst | lscatbles.SnglInspiral | lsctables.SnglRingdown ] xml table entry from which to extract parameter col : string glue.ligolw.table column name to extract |
Plot the time series / spectrum of a given set (or given sets) of data. Arguments: data : list list of (ChannelName,x_data,y_data) tuples with channel name (or data source) and time/freq, amplitude arrays for each channel. Channels are plotted in the order given. outfile : str output plot path Keyword Arguments: x_format : [ 'time' | 'frequency' ] type of data for x_axis, allows formatting of axes zero : [ float | int | LIGOTimeGPS ] time around which to centre time series plot zeroindicator : [ False | True ] indicate zero time with veritcal dashed line, default: False Unnamed keyword arguments: logx : [ True | False ] boolean option to display x-axis in log scale. logy : [ True | False ] boolean option to display y-axis in log scale. xlim : tuple (xmin, xmax) limits for x-axis ylim : tuple (ymin, ymax) limits for y-axis xlabel : string label for x-axis ylabel : string label for y-axis title : string title for plot subtitle : string subtitle for plot All other given arguments will be passed to matplotlib.axes.Axes.plot. |
Wrapper for dqPlotUtils.LineHistogram to plot a histogram of the value in any column of the ligolw table triggers. If a glue.segments.segmentlist seglist is given, the histogram is presented before and after removal of triggers falling inside any segment in the list. Arguments: triggers : glue.ligolw.table.Table ligolw table containing triggers outfile : string string path for output plot Keyword arguments: column : string valid column of triggers table to plot as histrogram num_bins : int number of histogram bins to use seglist : glue.segments.segmentlist list of segments with which to veto triggers flag : string display name of segmentlist, normally the name of the DQ flag start : [ float | int | LIGOTimeGPS] GPS start time (exclude triggers and segments before this time) end : [ float | int | LIGOTimeGPS] GPS end time (exclude triggers and segments after this time) livetime : [ float | int | LIGOTimeGPS ] span of time from which triggers and segments are valid, used to display histogram counts in terms of rate (Hz) for easy comparisons etg : string display name of trigger generator, defaults based on triggers tableName Unnamed keyword arguments: cumulative : [ True | False ] plot cumulative histogram rate : [ True | False ] plot rate histogram (normalises with given or calculated livetime) fill : [ True | False ] fill below the histogram curves, default colors: red (vetoed), green (not vetoed). logx : [ True | False ] boolean option to display x-axis in log scale. logy : [ True | False ] boolean option to display y-axis in log scale. xlim : tuple (xmin, xmax) limits for x-axis ylim : tuple (ymin, ymax) limits for y-axis xlabel : string label for x-axis ylabel : string label for y-axis title : string title for plot subtitle : string subtitle for plot greyscale : [ True | False ] use (non-greyscale) colour scheme suitable for greyscale plots All other given arguments will be passed to matplotlib.axes.Axes.plot and matplotlib.axes.Axes.fill_between. |
Plots ycolumn against xcolumn for columns in given Sngl{Burst,Inspiral}Table object triggers, coloured by the zcolumn highlighting those entries falling inside one of the entries in the glue.segments.segmentlist object segments, if given. 'time' given as a column name is a special case, since s and ns times are stored separately in the SnglTable structures. In this case the trigger.get_xxxx() function is called. Arguments: triggers : glue.ligolw.table.Table ligolw table containing triggers outfile : string string path for output plot Keyword arguments: xcolumn : string valid column of triggers table to plot on x-axis ycolumn : string valid column of triggers table to plot on y-axis zcolumn : string valid column of triggers table to use for colorbar (optional). rankcolumn : string valid column of triggers table to use for ranking events (optional). etg : string display name of trigger generator, defaults based on triggers tableName start : [ float | int | LIGOTimeGPS ] GPS start time of plot end : [ float | int | LIGOTimeGPS ] GPS end time of plot zero : [ float | int | LIGOTimeGPS ] time around which to centre plot seglist : glue.segments.segmentlist list of segments with which to veto triggers flag : string display name of segmentlist, normally the name of the DQ flag Unnamed keyword arguments: detchar : [ True | False ] use 'DetChar' style for scatter plot with colorbar, triggers below given dcthreshold are small with no edges, whilst other triggers are normal dcthreshold : float threshold below which scatter points are small with no edges when using DetChar plotting style logx : [ True | False ] boolean option to display x-axis in log scale. logy : [ True | False ] boolean option to display y-axis in log scale. logz : [ True | False ] boolean option to display z-axis in log scale. xlim : tuple (xmin, xmax) limits for x-axis. Triggers outside range are removed. ylim : tuple (ymin, ymax) limits for y-axis. Triggers outside range are removed. zlim : tuple (zmin, zmax) limits for z-axis. Triggers outside range are removed. clim : tuple (cmin, cmax) limits for color scale. Triggers outside range are moved onto boundary. xlabel : string label for x-axis ylabel : string label for y-axis zlabel : string label for z-axis title : string title for plot subtitle : string subtitle for plot greyscale : [ True | False ] use (non-greyscale) colour scheme suitable for greyscale plots All other given arguments will be passed to matplotlib.axes.Axes.scatter. |
segments. Plots a histogram of segment duration for the glue.segments.segmentlist Arguments: segs : [ glue.segments.segmentlist | glue.segments.segmentlistdict ] list of segments with which to veto triggers, use dict for multiple datasets outfile : string string path for output plot Keyword arguments: flag : string display name for segments, normally the name of the DQ flag logx : [ True | False ] boolean option to display x-axis in log scale. logy : [ True | False ] boolean option to display y-axis in log scale. |
Plot rate versus time for the given ligolw table triggers, binned by the given bincolumn using the bins list. Arguments: triggers : glue.ligolw.table LIGOLW table containing a list of triggers outfile : string string path for output plot Keyword arguments: average : float Length (seconds) of rate segment start : [ float | int | LIGOTimeGPS ] GPS start time end : [ float | int | LIGOTimeGPS ] GPS end time zero : [ float | int | LIGOTimeGPS ] GPS time to use for 0 on time axis bincolumn : string valid column of the trigger table to use for binning bins : list list of tuples defining the rate bins etg : string display name of trigger generator logy : [ True | False ] boolean option to display y-axis in log scale ylim : tuple (ymin, ymax) limits for rate axis |
Plot RMS versus time for the given ligolw table triggers, binned by the given bincolumn using the bins list. Arguments: triggers : glue.ligolw.table LIGOLW table containing a list of triggers outfile : string string path for output plot Keyword arguments: average : float Length (seconds) of RMS segment start : [ float | int | LIGOTimeGPS ] GPS start time end : [ float | int | LIGOTimeGPS ] GPS end time zero : [ float | int | LIGOTimeGPS ] GPS time to use for 0 on time axis rmscolumn : string valid column of the trigger table to RMS over bincolumn : string valid column of the trigger table to use for binning bins : list list of tuples defining the rate bins etg : string display name of trigger generator logy : [ True | False ] boolean option to display y-axis in log scale ylim : tuple (ymin, ymax) limits for rate axis |
Plot the segments contained within the glue.segments.segmentlistdict segdict to the given path string outfile. The list keys can be given to guarantee the order of the segments on the y-axis. x-axis limits can be controlled using start, end and zero. The glue.segments.segmentlist object highlight_segments can be given to highlight a number of segments. Arguments: segdict : glue.segments.segmentlistdict |
Parse ConfigParser.ConfigParser section for plot parameters. Sections should be name '[plot xcolumn-ycolumn-zcolumn]' e.g. '[plot time-peak_frequency-snr]'. Returns a pair of dicts with the following keys: columns: xcolumn : [ string | None ] column string to plot on x-axis ycolumn : [ string | None ] column string to plot on y-axis zcolumn : [ string | None ] column string to plot on z-axis params: xlim : list [xmin, xmax] pair for x-axis limits ylim : list [ymin, ymax] pair for y-axis limits zlim : list [zmin, zmax] pair for z-axis limits clim : list [cmin, cmax] pair for colorbar limits logx : bool True / False to plot log scale on x-axis logy : bool True / False to plot log scale on y-axis logz : bool True / False to plot log scale on z-axis |
Plot latitude against longitude for the given ligolw table skyTable into the given outfile. Uses the mpl_toolkits basemap module to plot the sky sphere in a variety of projections, or simply a scatter plot if projection=None. Can plot lines and detector positions on top if given. Arguments: skyTable : glue.ligolw.table.Table ligolw table containing triggers or SkyPosition objects outfile : string string path for output plot Keyword arguments: zcolumn : string valid column of ligolw table to use for colorbar (optional). format : [ 'radians' | 'degrees' ] str identifying format of longtiude/ra, latitude/dec colums in table. Plot is always drawn in degrees. projection : str type of spherical projection to use, if any. See matplotlib Basemap documentation for details, recommended: 'ortho', 'hammer'. centre : tuple (longitude, latitude) pair on which to centre plot. Latitude centring only works for certain projections. detectors : list list of detector prefixes to plot, e.g. ['H1', 'L1']. lines : dict dict of name:table pairs from which to plot lines (+ marker) on top of points range : tuple ((xmin, ymin), (xmax, ymax)) tuples for lower left and upper right corners, in range 0-1, e.g. (0,0) is full lower left, (1,1) full upper right corners for full spherical projection. Only works with certain projections. Unnamed keyword arguments: logx : [ True | False ] boolean option to display x-axis in log scale. Not applicable when using projection. logy : [ True | False ] boolean option to display y-axis in log scale. Not applicable when using projection. logz : [ True | False ] boolean option to display z-axis in log scale. xlim : tuple (xmin, xmax) limits for x-axis (longitude). Triggers outside range are removed. ylim : tuple (ymin, ymax) limits for y-axis (latitude). Triggers outside range are removed. zlim : tuple (zmin, zmax) limits for z-axis. Triggers outside range are removed. clim : tuple (cmin, cmax) limits for color scale. Triggers outside range are moved onto boundary. xlabel : string label for x-axis ylabel : string label for y-axis zlabel : string label for z-axis title : string title for plot subtitle : string subtitle for plot All other given arguments will be passed to matplotlib.axes.Axes.scatter. |
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_backend_warn
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__date__This module provides plotting routines for use in data quality investigations. All routines are written to work in as general a way as possible with ligolw tables and lsctables compatible columns, and to plot in a similar pythonic way to pylal.plotutils.
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