gwsumm.plot.segments module

Definitions for the standard plots

class gwsumm.plot.segments.DutyDataPlot(flags, start, end, state=None, outdir='.', bins=None, **kwargs)

Bases: SegmentDataPlot

DataPlot of the duty-factor for a SegmentList

calculate_duty_factor(segments, bins=None, cumulative=False, normalized=None)

data = 'segments'

defaults = {'alpha': 0.8, 'animation.convert_args': ['-layers', 'OptimizePlus'], 'axes.axisbelow': False, 'axes.edgecolor': 'gray', 'axes.formatter.limits': [-3, 4], 'axes.formatter.use_mathtext': True, 'axes.grid': True, 'axes.labelpad': 5.0, 'axes.labelsize': 18.0, 'axes.titlesize': 22.0, 'contour.algorithm': 'mpl2014', 'cumulative': False, 'figure.figsize': [12.0, 6.0], 'figure.labelsize': 'large', 'figure.labelweight': 'normal', 'font.sans-serif': ['Roboto'], 'grid.alpha': 0.5, 'grid.linewidth': 0.5, 'legend.edgecolor': 'inherit', 'legend.fancybox': False, 'legend.fontsize': 10.0, 'legend.handlelength': 1.0, 'legend.numpoints': 2, 'mathtext.bf': 'Roboto', 'mathtext.cal': 'Calligraffiti', 'mathtext.fontset': 'custom', 'mathtext.it': 'Roboto:italic', 'mathtext.rm': 'Roboto', 'mathtext.sf': 'Roboto', 'mathtext.tt': 'Roboto Slab', 'normalized': None, 'savefig.transparent': True, 'sep': False, 'side_by_side': False, 'stacked': False, 'svg.fonttype': 'none', 'text.parse_math': True, 'xscale': 'auto-gps', 'xtick.labelsize': 14.0, 'ylabel': 'Duty factor [%]', 'ylim': (0, 100), 'yscale': 'linear', 'ytick.labelsize': 14.0}

dict of default plotting kwargs

draw(outputfile=None)

Read in all necessary data, and generate the figure.

get_bins()

Work out the correct histogram binning for this DutyDataPlot

parse_plot_kwargs(*args, **kwargs)

Pop keyword arguments for Axes.plot from the pargs for this Plot

property pid

File pid for this DataPlot.

type = 'duty'

name for DataPlot subclass

class gwsumm.plot.segments.NetworkDutyBarPlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: SegmentBarPlot

Special case of the SegmentPiePlot for network duty factors.

NETWORK_COLOR = {'G1': '#222222', 'H1': '#ee0000', 'I1': '#b0dd8b', 'K1': '#ffb200', 'L1': '#4ba6ff', 'V1': '#9b59b6'}

NETWORK_NAME = {0: 'no', 1: 'single', 2: 'double', 3: 'triple', 4: 'quadruple', 5: 'quintuple', 6: 'sextuple'}

defaults = {'alpha': 0.6, 'scale': 'percent', 'title': 'Network duty factor', 'ylabel': 'Duty factor [%]'}

dict of default plotting kwargs

draw()

Process all data and generate the output file for this SummaryPlot.

This function should be provided by all sub-classes, and should take no arguments.

type = 'network-duty-segment-bar'

name for DataPlot subclass

class gwsumm.plot.segments.NetworkDutyPiePlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: SegmentPiePlot

Special case of the SegmentPiePlot for network duty factors

NETWORK_COLOR = {'G1': '#222222', 'H1': '#ee0000', 'I1': '#b0dd8b', 'K1': '#ffb200', 'L1': '#4ba6ff', 'V1': '#9b59b6', 'double': (0.0, 0.4, 1.0), 'no': 'black', 'quadruple': (1.0, 0.4, 0.0), 'single': (1.0, 0.7, 0.0), 'triple': 'pink'}

NETWORK_NAME = {0: 'no', 1: 'single', 2: 'double', 3: 'triple', 4: 'quadruple', 5: 'quintuple', 6: 'sextuple'}

defaults = {'legend-bbox_to_anchor': (0.8, 0.5), 'legend-fontsize': 24, 'legend-frameon': False, 'legend-loc': 'center left', 'wedge-edgecolor': 'white', 'wedge-width': 0.55}

dict of default plotting kwargs

draw()

Process all data and generate the output file for this SummaryPlot.

This function should be provided by all sub-classes, and should take no arguments.

type = 'network-duty-pie'

name for DataPlot subclass

class gwsumm.plot.segments.ODCDataPlot(*args, **kwargs)

Bases: SegmentLabelSvgMixin, StateVectorDataPlot

Custom StateVectorDataPlot for ODCs with bitmasks

data = 'odc'

defaults = {'animation.convert_args': ['-layers', 'OptimizePlus'], 'axes.axisbelow': False, 'axes.edgecolor': 'gray', 'axes.formatter.limits': [-3, 4], 'axes.formatter.use_mathtext': True, 'axes.grid': True, 'axes.labelpad': 5.0, 'axes.labelsize': 18.0, 'axes.titlesize': 22.0, 'color': None, 'contour.algorithm': 'mpl2014', 'figure.figsize': [12.0, 6.0], 'figure.labelsize': 'large', 'figure.labelweight': 'normal', 'font.sans-serif': ['Roboto'], 'grid.alpha': 0.5, 'grid.linewidth': 0.5, 'in_mask_color': (0.0, 0.4, 1.0), 'insetlabels': 'inset', 'legend-bbox_to_anchor': (1.01, 1), 'legend-borderaxespad': 0.0, 'legend-fontsize': 10, 'legend-frameon': False, 'legend-handletextpad': 0.5, 'legend-loc': 'upper left', 'legend.edgecolor': 'inherit', 'legend.fancybox': False, 'legend.fontsize': 10.0, 'legend.handlelength': 1.0, 'legend.numpoints': 2, 'mask': None, 'masked_off_color': 'red', 'mathtext.bf': 'Roboto', 'mathtext.cal': 'Calligraffiti', 'mathtext.fontset': 'custom', 'mathtext.it': 'Roboto:italic', 'mathtext.rm': 'Roboto', 'mathtext.sf': 'Roboto', 'mathtext.tt': 'Roboto Slab', 'no_summary_bit': False, 'on-is-bad': False, 'savefig.transparent': True, 'svg.fonttype': 'none', 'text.parse_math': True, 'unmasked_off_color': (1.0, 0.7, 0.0), 'xscale': 'auto-gps', 'xtick.labelsize': 14.0, 'yscale': 'linear', 'ytick.labelsize': 14.0}

dict of default plotting kwargs

draw()

Read in all necessary data, and generate the figure.

get_bitmask_channels()

property pid

type = 'odc'

name for DataPlot subclass

class gwsumm.plot.segments.SegmentBarPlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: BarPlot, SegmentDataPlot

SCALE_UNIT = {'percent': '%', 1: 'seconds', 3600: 'hours', 60: 'minutes', None: 'seconds'}

defaults = {'alpha': 0.6, 'color': '#33cc33', 'edgecolor': 'green', 'scale': 'percent'}

dict of default plotting kwargs

draw(outputfile=None)

Process all data and generate the output file for this SummaryPlot.

This function should be provided by all sub-classes, and should take no arguments.

type = 'segment-bar'

name for DataPlot subclass

class gwsumm.plot.segments.SegmentDataPlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: SegmentLabelSvgMixin, TimeSeriesDataPlot

Segment plot of one or more DataQualityFlags <DataQualityFlag>.

DRAW_PARAMS = ['imshow', 'origin', 'vmin', 'vmax', 'alpha', 'color', 'normed', 'log', 'weights', 'orientation', 'marker', 'density', 'bottom', 'label', 'interpolation', 'rwidth', 'aspect', 'cmap', 'range', 'histtype', 'zorder', 'norm', 's', 'linestyle', 'cumulative', 'linewidth', 'stacked', 'extent', 'bins', 'rasterized', 'logbins', 'align', 'known', 'height', 'y', 'facecolor', 'edgecolor']

list of parameters parsed for plot() calls

add_flag(f)

add_legend(ax, colors, **kwargs)

property allflags

data = 'segments'

defaults = {'animation.convert_args': ['-layers', 'OptimizePlus'], 'axes.axisbelow': False, 'axes.edgecolor': 'gray', 'axes.formatter.limits': [-3, 4], 'axes.formatter.use_mathtext': True, 'axes.grid': True, 'axes.labelpad': 5.0, 'axes.labelsize': 18.0, 'axes.titlesize': 22.0, 'color': None, 'contour.algorithm': 'mpl2014', 'figure.figsize': [12.0, 6.0], 'figure.labelsize': 'large', 'figure.labelweight': 'normal', 'font.sans-serif': ['Roboto'], 'grid.alpha': 0.5, 'grid.linewidth': 0.5, 'insetlabels': 'inset', 'legend-bbox_to_anchor': (1.0, 1.0), 'legend-borderaxespad': 0, 'legend-fontsize': 12, 'legend-frameon': False, 'legend-handletextpad': 0.5, 'legend-loc': 'upper left', 'legend.edgecolor': 'inherit', 'legend.fancybox': False, 'legend.fontsize': 10.0, 'legend.handlelength': 1.0, 'legend.numpoints': 2, 'mask': None, 'mathtext.bf': 'Roboto', 'mathtext.cal': 'Calligraffiti', 'mathtext.fontset': 'custom', 'mathtext.it': 'Roboto:italic', 'mathtext.rm': 'Roboto', 'mathtext.sf': 'Roboto', 'mathtext.tt': 'Roboto Slab', 'on-is-bad': False, 'savefig.transparent': True, 'svg.fonttype': 'none', 'text.parse_math': True, 'xscale': 'auto-gps', 'xtick.labelsize': 14.0, 'yscale': 'linear', 'ytick.labelsize': 14.0}

dict of default plotting kwargs

draw()

Read in all necessary data, and generate the figure.

property flags

classmethod from_ini(config, section, start, end, flags=None, state='all', **kwargs)

Define a new DataPlot.

get_channel_groups(*args, **kwargs)

Find and group (mean, min, max) sets of channels for plotting.

Returns:

groupslist of tuple

list of (channelname, channellist) tuples giving core channel name and an ordered list of channels. Ordering in preference of ‘rms’, ‘mean’, ‘min’, ‘max’.

Notes

This method used to return an OrderedDict, but was changed to return a list of tuple to enable plotting a channel multiple times on a plot, for whatever reason.

get_segment_color()

Parse the configured pargs and determine the colors for active and valid segments.

property ifos

Interferometer set for this SegmentDataPlot

init_plot(projection='segments', **kwargs)

Initialise the Figure and Axes objects for this TimeSeriesDataPlot.

property padding

parse_plot_kwargs(*args, **kwargs)

Pop keyword arguments for Axes.plot from the pargs for this Plot

property pid

File pid for this DataPlot.

type = 'segments'

name for DataPlot subclass

class gwsumm.plot.segments.SegmentHistogramPlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: TimeSeriesHistogramPlot, SegmentDataPlot

Histogram of segment duration

data = 'segments'

defaults = {'bottom': 0, 'histtype': 'stepfilled', 'log': False, 'rwidth': 1, 'ylabel': 'Number of segments'}

dict of default plotting kwargs

draw(outputfile=None)

Get data and generate the figure.

parse_plot_kwargs(**defaults)

Pop keyword arguments for Axes.plot from the pargs for this Plot

type = 'segment-histogram'

name for DataPlot subclass

class gwsumm.plot.segments.SegmentPiePlot(flags, start, end, state=None, outdir='.', **kwargs)

Bases: PiePlot, SegmentDataPlot

defaults = {'legend-bbox_to_anchor': (0.8, 0.5), 'legend-fontsize': 14, 'legend-frameon': False, 'legend-loc': 'center left', 'wedge-edgecolor': 'white', 'wedge-width': 0.55}

dict of default plotting kwargs

draw(outputfile=None)

Process all data and generate the output file for this SummaryPlot.

This function should be provided by all sub-classes, and should take no arguments.

parse_plot_kwargs(**defaults)

Pop keyword arguments for Axes.plot from the pargs for this Plot

parse_wedge_kwargs(defaults={})

type = 'segment-pie'

name for DataPlot subclass

class gwsumm.plot.segments.StateVectorDataPlot(*args, **kwargs)

Bases: TimeSeriesDataPlot

DataPlot of some StateVector data.

While technically a sub-class of the TimeSeriesDataPlot, for data access and processing reasons, the output shadows that of the SegmentDataPlot more closely.

DRAW_PARAMS = ['imshow', 'origin', 'vmin', 'vmax', 'alpha', 'color', 'normed', 'log', 'weights', 'orientation', 'marker', 'density', 'bottom', 'label', 'interpolation', 'rwidth', 'aspect', 'cmap', 'range', 'histtype', 'zorder', 'norm', 's', 'linestyle', 'cumulative', 'linewidth', 'stacked', 'extent', 'bins', 'rasterized', 'logbins', 'align', 'known', 'height', 'y', 'facecolor', 'edgecolor']

list of parameters parsed for plot() calls

data = 'statevector'

defaults = {'animation.convert_args': ['-layers', 'OptimizePlus'], 'axes.axisbelow': False, 'axes.edgecolor': 'gray', 'axes.formatter.limits': [-3, 4], 'axes.formatter.use_mathtext': True, 'axes.grid': True, 'axes.labelpad': 5.0, 'axes.labelsize': 18.0, 'axes.titlesize': 22.0, 'color': None, 'contour.algorithm': 'mpl2014', 'figure.figsize': [12.0, 6.0], 'figure.labelsize': 'large', 'figure.labelweight': 'normal', 'font.sans-serif': ['Roboto'], 'grid.alpha': 0.5, 'grid.linewidth': 0.5, 'insetlabels': 'inset', 'legend-bbox_to_anchor': (1.0, 1.0), 'legend-borderaxespad': 0, 'legend-fontsize': 12, 'legend-frameon': False, 'legend-handletextpad': 0.5, 'legend-loc': 'upper left', 'legend.edgecolor': 'inherit', 'legend.fancybox': False, 'legend.fontsize': 10.0, 'legend.handlelength': 1.0, 'legend.numpoints': 2, 'mask': None, 'mathtext.bf': 'Roboto', 'mathtext.cal': 'Calligraffiti', 'mathtext.fontset': 'custom', 'mathtext.it': 'Roboto:italic', 'mathtext.rm': 'Roboto', 'mathtext.sf': 'Roboto', 'mathtext.tt': 'Roboto Slab', 'on-is-bad': False, 'savefig.transparent': True, 'svg.fonttype': 'none', 'text.parse_math': True, 'xscale': 'auto-gps', 'xtick.labelsize': 14.0, 'yscale': 'linear', 'ytick.labelsize': 14.0}

dict of default plotting kwargs

draw()

Read in all necessary data, and generate the figure.

property flag

List of flags generated for this StateVectorDataPlot.

get_segment_color()

Parse the configured pargs and determine the colors for active and valid segments.

init_plot(*args, **kwargs)

Initialise the Figure and Axes objects for this TimeSeriesDataPlot.

parse_plot_kwargs(*args, **kwargs)

Pop keyword arguments for Axes.plot from the pargs for this Plot

property pid

type = 'statevector'

name for DataPlot subclass

gwsumm.plot.segments.common_limits(datasets, default_min=0, default_max=0)

Find the global maxima and minima of a list of datasets.

Parameters:

datasetsiterable

list (or any other iterable) of data arrays to analyse.

default_minfloat, optional

fall-back minimum value if datasets are all empty.

default_maxfloat, optional

fall-back maximum value if datasets are all empty.

Returns:

(min, max)float

2-tuple of common minimum and maximum over all datasets.

gwsumm.plot.segments.tint_hex(*args, **kwargs)