def plot(self, outfile, **params):
"""
Plot the spectrum of this NoiseTerm.
Arguments:
outfile : str
path to output file for this plot
"""
# labels
xlabel = params.pop("xlabel", "Frequency (Hz)")
ylabel = params.pop("ylabel", "Strain amplitude spectral density "
"$/\sqrt{\mbox{Hz}}$")
title = params.pop("title", "%s noise curve"\
% plotutils.display_name(self.name))
subtitle = params.pop("subtitle", "")
# extract params
bbox_inches = params.pop("bbox_inches", "tight")
hidden_colorbar = params.pop("hidden_colorbar", False)
logx = params.pop("logx", True)
logy = params.pop("logy", True)
# build limits
minx = self.deltaF
maxx = self.spectrum.size*self.deltaF + self.f0
xlim = params.pop("xlim", [minx, maxx])
ylim = params.pop("ylim", None)
# set plot object
plot = plotutils.DataPlot(xlabel, ylabel, title, subtitle)
f = numpy.arange(self.spectrum.size) * self.deltaF +\
self.f0
plot.add_content(f, self.spectrum,\
label=plotutils.display_name(self.name),\
color=self.color, **params)
if self.ref_spectrum is not None:
params["linestyle"] = "--"
params['linewidth'] = 0.3
f = numpy.arange(self.ref_spectrum.size) *\
self.ref_frequencyseries.deltaF + self.frequencyseries.f0
plot.add_content(f, self.ref_spectrum,\
label=plotutils.display_name(self.name),\
color=self.color, **params)
# finalize plot
plot.finalize(logx=logx, logy=logy, loc='upper right',\
hidden_colorbar=hidden_colorbar)
if xlim: plot.ax.set_xlim(xlim)
if ylim: plot.ax.set_ylim(ylim)
# save
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
def plottimeseries(series, outfile, t0=0, zeroline=False, **kwargs):
"""
Plot a REALXTimeSeries.
"""
# construct list of series
if hasattr(series, "__contains__"):
serieslist = series
else:
serieslist = [series]
# get limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
if xlim:
start, end = xlim
else:
start = min(float(s.epoch) for s in serieslist)
end = max(
float(s.epoch + s.data.length * s.deltaT) for s in serieslist)
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
# get legend loc
loc = kwargs.pop("loc", 0)
alpha = kwargs.pop("alpha", 0.8)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", None)
#
# get labels
#
xlabel = kwargs.pop("xlabel", None)
if xlabel:
unit = 1
if not xlabel:
unit, timestr = plotutils.time_axis_unit(end - start)
if not t0:
t0 = start
t0 = lal.LIGOTimeGPS(t0)
if int(t0.gpsNanoSeconds) == 0:
xlabel = datetime.datetime(*lal.GPSToUTC(int(t0))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)" % (timestr, xlabel, int(t0))
else:
xlabel = datetime.datetime(*lal.GPSToUTC(t0.gpsSeconds)[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)"\
% (timestr,
xlabel.replace(" UTC",".%.3s UTC" % t0.gpsNanoSeconds),\
t0)
t0 = float(t0)
ylabel = kwargs.pop("ylabel", "Amplitude (counts)")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
#
# set default line params
#
color = kwargs.pop("color", None)
if isinstance(color, str):
color = color.split(',')
if len(color) == 1:
color = [color[0]] * len(serieslist)
kwargs2 = dict()
kwargs2.update(kwargs)
if kwargs.has_key("marker"):
kwargs.setdefault("markersize", 5)
kwargs2.setdefault("markersize", 2)
else:
kwargs.setdefault("linestyle", "-")
kwargs.setdefault("linewidth", "1")
kwargs2.setdefault("linewidth", "0.1")
#
# make plot
#
allnames = [s.name for s in serieslist]
namedseries = [
s for s in serieslist if not re.search("(min|max)\Z", s.name)
]
plot = plotutils.SimplePlot(xlabel, ylabel, title, subtitle)
for i,(series,c) in enumerate(itertools.izip(namedseries,\
plotutils.default_colors())):
if color:
c = color[serieslist.index(series)]
x = numpy.arange(series.data.length) * series.deltaT +\
float(series.epoch) - float(t0)
x = x.astype(float)
x /= unit
d = series.data.data
if logy and ylim:
numpy.putmask(d, d == 0, ylim[0] - abs(ylim[0]) * 0.01)
plot.add_content(x, d, color=c,\
label=plotutils.display_name(series.name), **kwargs)
# find min/max and plot
for i, name in enumerate(allnames):
for ext in ["min", "max"]:
if re.match("%s[- _]%s" % (re.escape(series.name), ext), name):
if color:
c = color[i]
series2 = serieslist[i]
x2 = numpy.arange(series2.data.length) * series2.deltaT\
+ float(series2.epoch) - float(t0)
x2 /= unit
d2 = series2.data.data
if logy and ylim:
numpy.putmask(d2, d2 == 0,
ylim[0] - abs(ylim[0]) * 0.01)
plot.ax.plot(x2, d2, color=c, **kwargs2)
plot.ax.fill_between(x2, d, d2, alpha=0.1,\
color=c)
# finalize
plot.finalize(loc=loc, alpha=alpha)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# add zero line
axis_lims = plot.ax.get_ylim()
if zeroline:
plot.ax.plot([0, 0], [axis_lims[0], axis_lims[1]], 'r--', linewidth=2)
plot.ax.set_ylim([axis_lims[0], axis_lims[1]])
# set logscale
if logx:
plot.ax.xaxis.set_scale("log")
if logy:
plot.ax.yaxis.set_scale("log")
plot.ax._update_transScale()
# format axes
if xlim:
xlim = (numpy.asarray(xlim).astype(float) - t0) / unit
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax, x=False)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plotfrequencyseries(series, outfile, **kwargs):
"""
Plot a (swig)LAL FrequencySeries.
"""
# construct list of series
if hasattr(series, "__contains__"):
serieslist = series
else:
serieslist = [series]
# get limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
if not xlim:
fmin = min(float(s.f0) for s in serieslist)
fmax = max(float(s.f0 + s.data.length * s.deltaF) for s in serieslist)
xlim = [fmin, fmax]
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
# get legend loc
loc = kwargs.pop("loc", 0)
alpha = kwargs.pop("alpha", 0.8)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", None)
#
# get labels
#
xlabel = kwargs.pop("xlabel", "Frequency (Hz)")
ylabel = kwargs.pop("ylabel", "Amplitude")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
#
# set default line params
#
color = kwargs.pop("color", None)
if isinstance(color, str):
color = [color] * len(serieslist)
kwargs2 = dict()
kwargs2.update(kwargs)
if kwargs.has_key("marker"):
kwargs.setdefault("markersize", 5)
kwargs2.setdefault("markersize", 2)
else:
kwargs.setdefault("linestyle", "-")
kwargs.setdefault("linewidth", "1")
kwargs2.setdefault("linewidth", "0.1")
#
# make plot
#
allnames = [s.name for s in serieslist]
namedseries = [
s for s in serieslist if not re.search("(min|max)\Z", s.name)
]
plot = plotutils.SimplePlot(xlabel, ylabel, title, subtitle)
for i,(series,c) in enumerate(itertools.izip(namedseries,\
plotutils.default_colors())):
if color:
c = color[serieslist.index(series)]
if series.f_array is not None:
x = series.f_array
else:
x = numpy.arange(series.data.length) * series.deltaF + series.f0
x = x.astype(float)
plot.add_content(x,
series.data.data,
color=c,
label=plotutils.display_name(series.name),
**kwargs)
# find min/max and plot
for i, name in enumerate(allnames):
for ext in ["min", "max"]:
if re.match("%s[- _]%s" % (re.escape(series.name), ext), name):
if color:
c = color[i]
series2 = serieslist[i]
if series2.f_array is not None:
x2 = series2.f_array
else:
x2 = numpy.arange(series2.data.length) * series2.deltaF\
+ series2.f0
plot.ax.plot(x2, series2.data.data, color=c, **kwargs2)
# sanity check for malformed inputs
if series.data.data.shape == series2.data.data.shape:
plot.ax.fill_between(x2, series.data.data,\
series2.data.data, alpha=0.1,\
color=c)
# finalize
plot.finalize(loc=loc, alpha=alpha)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# set logscale
if logx:
plot.ax.xaxis.set_scale("log")
if logy:
plot.ax.yaxis.set_scale("log")
plot.ax._update_transScale()
# format axes
if xlim:
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
plot.ax.grid(True, which="both")
plotutils.set_minor_ticks(plot.ax)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plottimeseries(series, outfile, t0=0, zeroline=False, **kwargs):
"""
Plot a REALXTimeSeries.
"""
# construct list of series
if hasattr(series, "__contains__"):
serieslist = series
else:
serieslist = [series]
# get limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
if xlim:
start,end = xlim
else:
start = min(float(s.epoch) for s in serieslist)
end = max(float(s.epoch + s.data.length*s.deltaT) for s in serieslist)
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
# get legend loc
loc = kwargs.pop("loc", 0)
alpha = kwargs.pop("alpha", 0.8)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", None)
#
# get labels
#
xlabel = kwargs.pop("xlabel", None)
if xlabel:
unit = 1
if not xlabel:
unit, timestr = plotutils.time_axis_unit(end-start)
if not t0:
t0 = start
t0 = lal.LIGOTimeGPS(t0)
if int(t0.gpsNanoSeconds) == 0:
xlabel = datetime.datetime(*lal.GPSToUTC(int(t0))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)" % (timestr, xlabel, int(t0))
else:
xlabel = datetime.datetime(*lal.GPSToUTC(t0.gpsSeconds)[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)"\
% (timestr,
xlabel.replace(" UTC",".%.3s UTC" % t0.gpsNanoSeconds),\
t0)
t0 = float(t0)
ylabel = kwargs.pop("ylabel", "Amplitude (counts)")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
#
# set default line params
#
color = kwargs.pop("color", None)
if isinstance(color, str):
color = color.split(',')
if len(color) == 1:
color = [color[0]]*len(serieslist)
kwargs2 = dict()
kwargs2.update(kwargs)
if kwargs.has_key("marker"):
kwargs.setdefault("markersize", 5)
kwargs2.setdefault("markersize", 2)
else:
kwargs.setdefault("linestyle", "-")
kwargs.setdefault("linewidth", "1")
kwargs2.setdefault("linewidth", "0.1")
#
# make plot
#
allnames = [s.name for s in serieslist]
namedseries = [s for s in serieslist if not re.search("(min|max)\Z",s.name)]
plot = plotutils.SimplePlot(xlabel, ylabel, title, subtitle)
for i,(series,c) in enumerate(itertools.izip(namedseries,\
plotutils.default_colors())):
if color:
c = color[serieslist.index(series)]
x = numpy.arange(series.data.length) * series.deltaT +\
float(series.epoch) - float(t0)
x = x.astype(float)
x /= unit
d = series.data.data
if logy and ylim:
numpy.putmask(d, d==0, ylim[0]-abs(ylim[0])*0.01)
plot.add_content(x, d, color=c,\
label=plotutils.display_name(series.name), **kwargs)
# find min/max and plot
for i,name in enumerate(allnames):
for ext in ["min", "max"]:
if re.match("%s[- _]%s" % (re.escape(series.name), ext), name):
if color:
c = color[i]
series2 = serieslist[i]
x2 = numpy.arange(series2.data.length) * series2.deltaT\
+ float(series2.epoch) - float(t0)
x2 /= unit
d2 = series2.data.data
if logy and ylim:
numpy.putmask(d2, d2==0, ylim[0]-abs(ylim[0])*0.01)
plot.ax.plot(x2, d2, color=c, **kwargs2)
plot.ax.fill_between(x2, d, d2, alpha=0.1,\
color=c)
# finalize
plot.finalize(loc=loc, alpha=alpha)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# add zero line
axis_lims = plot.ax.get_ylim()
if zeroline:
plot.ax.plot([0, 0], [axis_lims[0], axis_lims[1]], 'r--', linewidth=2)
plot.ax.set_ylim([ axis_lims[0], axis_lims[1] ])
# set logscale
if logx:
plot.ax.xaxis.set_scale("log")
if logy:
plot.ax.yaxis.set_scale("log")
plot.ax._update_transScale()
# format axes
if xlim:
xlim = (numpy.asarray(xlim).astype(float)-t0)/unit
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax, x=False)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plotfrequencyseries(series, outfile, **kwargs):
"""
Plot a (swig)LAL FrequencySeries.
"""
# construct list of series
if hasattr(series, "__contains__"):
serieslist = series
else:
serieslist = [series]
# get limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
if not xlim:
fmin = min(float(s.f0) for s in serieslist)
fmax = max(float(s.f0 + s.data.length*s.deltaF) for s in serieslist)
xlim = [fmin, fmax]
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
# get legend loc
loc = kwargs.pop("loc", 0)
alpha = kwargs.pop("alpha", 0.8)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", None)
#
# get labels
#
xlabel = kwargs.pop("xlabel", "Frequency (Hz)")
ylabel = kwargs.pop("ylabel", "Amplitude")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
#
# set default line params
#
color = kwargs.pop("color", None)
if isinstance(color, str):
color = [color]*len(serieslist)
kwargs2 = dict()
kwargs2.update(kwargs)
if kwargs.has_key("marker"):
kwargs.setdefault("markersize", 5)
kwargs2.setdefault("markersize", 2)
else:
kwargs.setdefault("linestyle", "-")
kwargs.setdefault("linewidth", "1")
kwargs2.setdefault("linewidth", "0.1")
#
# make plot
#
allnames = [s.name for s in serieslist]
namedseries = [s for s in serieslist if not re.search("(min|max)\Z",s.name)]
plot = plotutils.SimplePlot(xlabel, ylabel, title, subtitle)
for i,(series,c) in enumerate(itertools.izip(namedseries,\
plotutils.default_colors())):
if color:
c = color[serieslist.index(series)]
if series.f_array is not None:
x = series.f_array
else:
x = numpy.arange(series.data.length) * series.deltaF + series.f0
x = x.astype(float)
plot.add_content(x, series.data.data, color=c,
label=plotutils.display_name(series.name), **kwargs)
# find min/max and plot
for i,name in enumerate(allnames):
for ext in ["min", "max"]:
if re.match("%s[- _]%s" % (re.escape(series.name), ext), name):
if color:
c = color[i]
series2 = serieslist[i]
if series2.f_array is not None:
x2 = series2.f_array
else:
x2 = numpy.arange(series2.data.length) * series2.deltaF\
+ series2.f0
plot.ax.plot(x2, series2.data.data, color=c, **kwargs2)
# sanity check for malformed inputs
if series.data.data.shape == series2.data.data.shape:
plot.ax.fill_between(x2, series.data.data,\
series2.data.data, alpha=0.1,\
color=c)
# finalize
plot.finalize(loc=loc, alpha=alpha)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# set logscale
if logx:
plot.ax.xaxis.set_scale("log")
if logy:
plot.ax.yaxis.set_scale("log")
plot.ax._update_transScale()
# format axes
if xlim:
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
plot.ax.grid(True, which="both")
plotutils.set_minor_ticks(plot.ax)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plottable(lsctable, outfile, xcolumn="time", ycolumn="snr",\
colorcolumn=None, rankcolumn=None, t0=None, **kwargs):
"""
Plot any column of a valid LigoLW table against any other, coloured by any
other, or plot all the same if you're that way inclined. Multiple tables
can be given for any non-coloured plot.
"time" as a column means the output of get_peak for Burst tables, get_end
for Inspiral tables, and get_start for ringdown tables
Arguments:
tables : [ dict | glue.ligolw.table.Table ]
dict of ("name", table) pairs, or single LigoLW tables
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).
"""
# work out dictionary or table
if isinstance(lsctable, table.Table):
tables = {"_": lsctable}
else:
tables = lsctable
tablenames = tables.keys()
tables = [tables[n] for n in tablenames]
# get axis limits
xlim = kwargs.pop('xlim', None)
ylim = kwargs.pop('ylim', None)
zlim = kwargs.pop('zlim', None)
colorlim = kwargs.pop('colorlim', None)
if zlim and not colorlim:
colorlim = zlim
# set up columns
columns = list(map(str.lower, [xcolumn, ycolumn]))
if colorcolumn:
columns.append(colorcolumn.lower())
if rankcolumn:
columns.append(rankcolumn.lower())
else:
columns.append(colorcolumn.lower())
# set up limits
limits = [xlim, ylim, zlim, None]
# get zero
if "time" in columns and not t0:
if xlim:
t0 = float(xlim[0])
else:
t0 = numpy.infty
for t in tables:
timedata = get_column(t, "time").astype(float)
if len(timedata):
t0 = min(t0, timedata.min())
if numpy.isinf(t0):
t0 = 0
t0 = int(t0)
#
# get data
#
# extract columns
data = list()
for i, name in enumerate(tablenames):
data.append(list())
for c in columns:
c = c.lower()
if ((c not in tables[i].columnnames and c != "time")
and not hasattr(tables[i], "get_%s" % c.lower())):
raise RuntimeError("Column '%s' not found in table '%s'."\
% (c,name))
data[-1].append(get_column(tables[i], c.lower()).astype(float))
if not len(data[-1][-1].shape)\
or data[-1][-1].shape[0] != len(tables[i]):
raise AttributeError("No data loaded for column \"%s\" and "\
"table \"%s\"" % (c, name))
# add our own limits
for i in range(len(columns)):
if not limits[i]:
mins = [data[j][i].min() for j in range(len(tablenames))\
if len(data[j][i].shape) and data[j][i].shape[0] != 0]
if len(mins):
lmin = min(mins)
lmax = max(data[j][i].max() for j in range(len(tablenames))\
if len(data[j][i]))
limits[i] = [lmin, lmax]
# get time unit
if "time" in columns:
idx = columns.index("time")
if limits[idx]:
unit, timestr = plotutils.time_axis_unit(limits[idx][1]\
- limits[idx][0])
else:
unit, timestr = plotutils.time_axis_unit(1)
# format data
for i, name in enumerate(tablenames):
for j, column in enumerate(columns):
if column == "time":
data[i][j] = (data[i][j] - t0) / unit
if i == 0 and limits[j]:
limits[j] = [float(limits[j][0] - t0) / unit,\
float(limits[j][1] - t0) / unit]
# format a condition to reject triggers outside the plot range
plotted = True
for j, column in enumerate(columns):
if limits[j]:
plotted = plotted & (limits[j][0] <= data[i][j])\
& (limits[j][1] >= data[i][j])
# apply the limits
if not isinstance(plotted, bool):
for j, d in enumerate(data[i]):
data[i][j] = d[plotted]
#
# find loudest event
#
loudest = None
if len(columns) == 4 and len(tablenames) == 1 and len(data[0][0]) > 0:
idx = data[0][3].argmax()
loudest = [data[0][j][idx] for j in range(len(columns))]
#
# get or set the labels
#
label = {}
for i,(label,column) in enumerate(zip(["xlabel", "ylabel", "colorlabel"],\
columns)):
# get given label
l = kwargs.pop(label, None)
if l is None:
# format time string
if column == "time" and limits[i]:
zerostr = datetime.datetime(\
*date.XLALGPSToUTC(LIGOTimeGPS(t0))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
l = "Time (%s) since %s (%s)" % (timestr, zerostr, t0)
# format any other column
else:
l = plotutils.display_name(column)
if label == "xlabel":
xlabel = l
elif label == "ylabel":
ylabel = l
else:
colorlabel = l
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", None)
if subtitle is None and loudest:
subtitle = "Loudest event by %s:" % plotutils.display_name(columns[-1])
for j, c in enumerate(columns):
if j != 0 and c == columns[j - 1]: continue
lstr = loudest[j]
if c == "time":
lstr = lstr * unit + t0
subtitle += " %s=%.2f" % (plotutils.display_name(c), lstr)
else:
loudest = None
#
# get parameters
#
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
logcolor = kwargs.pop("logcolor", False)
# get legend loc
loc = kwargs.pop("loc", 0)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", "tight")
# get detchar plot params
dqstyle = (kwargs.pop("detchar", False)
or kwargs.pop('detchar_style', False))
dqthresh = (kwargs.pop('dcthreshold', False)
or kwargs.pop('detchar_style_threshold', 10))
# get greyscale param
greyscale = kwargs.pop("greyscale", False)
if greyscale and not kwargs.has_key("cmap"):
kwargs["cmap"] =\
pylab.matplotlib.colors.LinearSegmentedColormap("clrs",\
pylab.matplotlib.cm.hot_r._segmentdata)
elif not kwargs.has_key("cmap"):
kwargs["cmap"] = jet
#
# make the plot
#
tablenames = map(plotutils.display_name, tablenames)
if len(columns) == 2:
plot = plotutils.ScatterPlot(xlabel, ylabel, title, subtitle)
for i in range(len(tablenames)):
plot.add_content(data[i][0], data[i][1], label=tablenames[i],\
**kwargs)
plot.finalize(loc=loc)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
else:
if dqstyle:
plot = plotutils.DQScatterPlot(xlabel, ylabel, colorlabel,\
title, subtitle)
else:
plot = plotutils.ColorbarScatterPlot(xlabel, ylabel, colorlabel,\
title, subtitle)
plot.add_content(data[0][0], data[0][1], data[0][2],\
label=tablenames[0], **kwargs)
kwargs.pop("cmap", None)
if dqstyle:
plot.finalize(logcolor=logcolor, clim=colorlim, loc=loc,\
threshold=dqthresh)
else:
plot.finalize(logcolor=logcolor, clim=colorlim, loc=loc)
# plot loudest
if loudest:
plot.ax.plot([loudest[0]], [loudest[1]], marker="*", color="gold",\
markersize=15)
# set axes
if logx:
plot.ax.set_xscale("log")
if logy:
plot.ax.set_yscale("log")
plot.ax.autoscale_view(tight=True, scalex=True, scaley=True)
if limits[0]:
plot.ax.set_xlim(limits[0])
if limits[1]:
plot.ax.set_ylim(limits[1])
plot.ax.grid(True, which="both")
if xcolumn == "time":
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax)
# save and close
if greyscale:
plot.ax.patch.set_facecolor("#E8E8E8")
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plothistogram(lsctable, outfile, column="snr", numbins=100,\
colorcolumn=None, colorbins=10, normalize=None,\
cumulative=None, bar=False, **kwargs):
"""
Plot any column of a valid LigoLW table against any other, coloured by any
other, or plot all the same if you're that way inclined. Multiple tables
can be given for any non-coloured plot.
"time" as a column means the output of get_peak for Burst tables, get_end
for Inspiral tables, and get_start for ringdown tables
Arguments:
table : [ dict | glue.ligolw.table.Table ]
dict of ("name", table) pairs, or single LigoLW table
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).
"""
# work out dictionary or table
if isinstance(lsctable, table.Table):
tables = {"_": lsctable}
else:
tables = lsctable
tablenames = sorted(tables.keys())
tables = [tables[n] for n in tablenames]
# get axis limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
zlim = kwargs.pop("zlim", None)
clim = kwargs.pop("clim", zlim)
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
logcolor = kwargs.pop("logcolor", False)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", "tight")
# get fill
fill = kwargs.pop("fill", False)
# get extras
rate = kwargs.pop("rate", False)
if normalize:
rate = True
if not hasattr(normalize, "__iter__"):
normalize = [normalize] * len(tablenames)
else:
normalize = [1] * len(tablenames)
loc = kwargs.pop("loc", 0)
# set labels
xlabel = kwargs.pop("xlabel", plotutils.display_name(column))
if rate and cumulative:
ylabel = kwargs.pop("ylabel", "Cumulative rate (Hz)")
elif rate:
ylabel = kwargs.pop("ylabel", "Rate (Hz)")
elif not rate and cumulative:
ylabel = kwargs.pop("ylabel", "Cumulative number")
else:
ylabel = kwargs.pop("ylabel", "Number")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
colorlabel = kwargs.pop("colorlabel", colorcolumn\
and plotutils.display_name(colorcolumn) or "")
#
# get column data
#
if colorcolumn:
colordata = get_column(tables[0], colorcolumn).astype(float)
if not clim and colordata.size != 0:
clim = [colordata.min(), colordata.max()]
elif not clim:
clim = [1, 10]
if isinstance(colorbins, int):
numcolorbins = colorbins
if logcolor:
colorbins = numpy.logspace(*numpy.log10(clim),
num=numcolorbins)
else:
colorbins = numpy.linspace(*clim, num=numcolorbins)
else:
numcolorbins = len(colorbins)
data = list()
for i, lsctable in enumerate(tables):
d = get_column(lsctable, column).astype(float)
if i == 0 and colorcolumn:
data.append(list())
for j in range(numcolorbins):
data[i].append(d[d >= colorbins[j]])
else:
data.append(d)
#
# generate plot and make
#
if colorcolumn:
raise NotImplementedError("This has not been implemented in "+\
"plotutils yet, here's your chance!")
plot = plotutils.ColorbarLineHistogram(xlabel, ylabel, colorlabel,\
title, subtitle)
for dataset, colorbin in zip(data[0], colorbins):
plot.add_content(dataset, normalize=normalize[0],\
colorvalue=colorbin, label=tablenames[0], **kwargs)
for i, name in enumerate(tablenames[1:]):
plot.add_content(data[i+1], normalize=normalize[i+1],\
label=name, **kwargs)
plot.finalize(logcolor=logcolor, colorlabel=colorlabel, loc=loc)
else:
color = kwargs.pop("color", None)
if isinstance(color, str):
color = color.split(',')
if len(color) == 1:
color = [color[0]] * len(serieslist)
plot = plotutils.LineHistogram(xlabel, ylabel, title, subtitle)
for i, name in enumerate(tablenames):
if color:
kwargs["color"] = color[i]
plot.add_content(data[i], normalize=normalize[i], label=name,\
**kwargs)
plot.finalize(loc=loc, logx=logx, logy=logy, bar=bar, num_bins=numbins,\
cumulative=cumulative)
plot.ax.autoscale_view(tight=True, scalex=True, scaley=True)
if xlim:
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plotdutycycle(segdict, outfile, binlength=3600, keys=None, t0=None,\
showmean=False, **kwargs):
"""
Plot the percentage duty cycle each flag in the given
glue.segments.segmentlistdict, binned over the given duration.
"""
# get time limits
xlim = kwargs.pop("xlim", None)
if xlim is None:
try:
extents = [seg.extent() for seg in segdict.values()]
start = min(s[0] for s in extents)
end = max(s[1] for s in extents)
except ValueError:
start = 0
end = 1
xlim = start, end
else:
start, end = xlim
# get unit for plot
unit, timestr = plotutils.time_axis_unit(end - start)
# set xlabel and renomalize time
xlabel = kwargs.pop("xlabel", None)
if not xlabel:
if not t0:
t0 = start
unit, timestr = plotutils.time_axis_unit(end - start)
t0 = LIGOTimeGPS(float(t0))
if t0.nanoseconds == 0:
xlabel = datetime.datetime(*date.XLALGPSToUTC(t0)[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)" % (timestr, xlabel, int(t0))
else:
xlabel = datetime.datetime(*date.XLALGPSToUTC(\
LIGOTimeGPS(t0.seconds))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)"\
% (timestr,
xlabel.replace(" UTC", ".%.3s UTC" % t0.nanoseconds),\
t0)
t0 = float(t0)
xlim[0] = (start - t0) / unit
xlim[1] = (end - t0) / unit
ylabel = kwargs.pop("ylabel", "")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
# get other parameters
loc = kwargs.pop("loc", 0)
legalpha = kwargs.pop("alpha", 0.8)
labels_inset = kwargs.pop("labels_inset", False)
bbox_inches = kwargs.pop("bbox_inches", "tight")
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# escape underscores for latex text
if not keys:
keys = segdict.keys()
if pylab.rcParams["text.usetex"]:
newdict = segments.segmentlistdict()
for i, key in enumerate(keys):
newkey = re.sub('(?<!\\\\)_', '\_', key)
keys[i] = newkey
newdict[newkey] = segdict[key]
segdict = newdict
#
# generate duty cycle info
#
# generate bins
binlength = float(binlength)
if int(end - start) % binlength == 0:
numbins = int(end - start) / binlength
else:
numbins = float(end - start) // binlength + 1
bins = numpy.arange(float(start), float(end), binlength) + binlength / 2
duty = dict((key, numpy.zeros(numbins)) for key in keys)
bs = float(start)
for i in range(numbins):
be = float(bs + binlength)
seg = segments.segmentlist([segments.segment(bs, be)])
for key in keys:
duty[key][i] = float(abs(segdict[key] & seg)) / abs(seg) * 100
bs += binlength
if showmean:
mean = dict((key, numpy.zeros(numbins)) for key in keys)
for key in keys:
mean[key] = [duty[key][:i + 1].mean() for i in range(numbins)]
#
# generate plot
#
bins = (bins - t0) / unit
plot = plotutils.BarPlot(xlabel, ylabel, title, subtitle)
for i, key in enumerate(keys):
if showmean:
thislabel = plotutils.display_name(
key) + ' (%.2f\%%)' % (mean[key][-1])
else:
thislabel = plotutils.display_name(key)
plot.add_content(bins, duty[key], label=thislabel,\
alpha=0.8, width=binlength/unit)
plot.finalize(loc=loc, alpha=legalpha)
# add running mean
if showmean:
for i, key in enumerate(keys):
print i, key
plot.ax.plot(bins, mean[key], linestyle='--')
plot.ax.get_legend().get_frame().set_alpha(0.5)
# add colorbar
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# set limits
plot.ax.autoscale_view(tight=True, scalex=True)
if xlim:
plot.ax.set_xlim(map(float, xlim))
plot.ax.set_ylim(0, 100)
# set grid
plot.ax.grid(True, which="both")
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax, x=False)
# save figure
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
def plotdutycycle(segdict, outfile, binlength=3600, keys=None, t0=None,\
showmean=False, **kwargs):
"""
Plot the percentage duty cycle each flag in the given
glue.segments.segmentlistdict, binned over the given duration.
"""
# get time limits
xlim = kwargs.pop("xlim", None)
if xlim is None:
try:
extents = [seg.extent() for seg in segdict.values()]
start = min(s[0] for s in extents)
end = max(s[1] for s in extents)
except ValueError:
start = 0
end = 1
xlim = start,end
else:
start,end = xlim
# get unit for plot
unit, timestr = plotutils.time_axis_unit(end-start)
# set xlabel and renomalize time
xlabel = kwargs.pop("xlabel", None)
if not xlabel:
if not t0:
t0 = start
unit, timestr = plotutils.time_axis_unit(end-start)
t0 = LIGOTimeGPS(float(t0))
if t0.nanoseconds==0:
xlabel = datetime.datetime(*date.XLALGPSToUTC(t0)[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)" % (timestr, xlabel, int(t0))
else:
xlabel = datetime.datetime(*date.XLALGPSToUTC(\
LIGOTimeGPS(t0.seconds))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
xlabel = "Time (%s) since %s (%s)"\
% (timestr,
xlabel.replace(" UTC", ".%.3s UTC" % t0.nanoseconds),\
t0)
t0 = float(t0)
xlim[0] = (start - t0)/unit
xlim[1] = (end - t0)/unit
ylabel = kwargs.pop("ylabel", "")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", "")
# get other parameters
loc = kwargs.pop("loc", 0)
legalpha = kwargs.pop("alpha", 0.8)
labels_inset = kwargs.pop("labels_inset", False)
bbox_inches = kwargs.pop("bbox_inches", "tight")
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# escape underscores for latex text
if not keys:
keys = segdict.keys()
if pylab.rcParams["text.usetex"]:
newdict = segments.segmentlistdict()
for i,key in enumerate(keys):
newkey = re.sub('(?<!\\\\)_', '\_', key)
keys[i] = newkey
newdict[newkey] = segdict[key]
segdict = newdict
#
# generate duty cycle info
#
# generate bins
binlength = float(binlength)
if int(end-start) % binlength == 0:
numbins = int(end-start)/binlength
else:
numbins = float(end-start)//binlength+1
bins = numpy.arange(float(start), float(end), binlength) + binlength/2
duty = dict((key, numpy.zeros(numbins)) for key in keys)
bs = float(start)
for i in range(numbins):
be = float(bs + binlength)
seg = segments.segmentlist([segments.segment(bs, be)])
for key in keys:
duty[key][i] = float(abs(segdict[key] & seg))/abs(seg) * 100
bs += binlength
if showmean:
mean = dict((key, numpy.zeros(numbins)) for key in keys)
for key in keys:
mean[key] = [duty[key][:i+1].mean() for i in range(numbins)]
#
# generate plot
#
bins = (bins-t0)/unit
plot = plotutils.BarPlot(xlabel, ylabel, title, subtitle)
for i,key in enumerate(keys):
if showmean:
thislabel = plotutils.display_name(key) + ' (%.2f\%%)' % (mean[key][-1])
else:
thislabel = plotutils.display_name(key)
plot.add_content(bins, duty[key], label=thislabel,\
alpha=0.8, width=binlength/unit)
plot.finalize(loc=loc, alpha=legalpha)
# add running mean
if showmean:
for i,key in enumerate(keys):
print i, key
plot.ax.plot(bins, mean[key], linestyle = '--')
plot.ax.get_legend().get_frame().set_alpha(0.5)
# add colorbar
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
# set limits
plot.ax.autoscale_view(tight=True, scalex=True)
if xlim:
plot.ax.set_xlim(map(float, xlim))
plot.ax.set_ylim(0, 100)
# set grid
plot.ax.grid(True, which="both")
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax, x=False)
# save figure
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
def plot(self, outfile, **params):
"""
Plot this NoiseBudget
"""
# extract params
bbox_inches = params.pop("bbox_inches", "tight")
hidden_colorbar = params.pop("hidden_colorbar", False)
logx = params.pop("logx", True)
logy = params.pop("logy", True)
plot_component_ref = params.pop("plot_component_ref", False)
if plot_component_ref == 'true':
plot_component_ref = True
# build limits
minx = min(t.deltaF for t in self)
maxx = max(t.spectrum.size*t.deltaF + t.f0 for t in self)
xlim = params.pop("xlim", [minx, maxx])
ylim = params.pop("ylim", None)
# labels
xlabel = params.pop("xlabel", "Frequency (Hz)")
ylabel = params.pop("ylabel", "Strain amplitude spectral density "
"$/\sqrt{\mbox{Hz}}$")
title = params.pop("title", plotutils.display_name(self.name))
subtitle = params.pop("subtitle", "")
# copy params for reference lines
refparams = copy.deepcopy(params)
refparams.setdefault('linestyle', '--')
refparams['linewidth'] = 0.3
# set plot object
plot = plotutils.DataPlot(xlabel, ylabel, title, subtitle)
reference_plotted = False
# plot target and noise sum
for term in ["target", "noise_sum"]:
if hasattr(self, term) and getattr(self, term) is not None:
term = getattr(self, term)
f = numpy.arange(term.data.size) *term.frequencyseries.deltaF +\
term.frequencyseries.f0
plot.add_content(f, term.data,\
label=plotutils.display_name(term.name),\
linecolor=term.color, **params)
# plot reference
if term.ref_spectrum is not None:
f = numpy.arange(term.ref_spectrum.size) *\
self.ref_frequencyseries.deltaF +\
self.ref_frequencyeries.f0
plot.add_content(f, term.ref_spectrum,\
label=plotutils.display_name(self.name),\
color=self.color, **refparams)
reference_plotted = True
# plot terms in the budget
for term in self:
f = numpy.arange(term.spectrum.size) * term.deltaF +\
term.f0
plot.add_content(f, term.spectrum,\
label=plotutils.display_name(term.name),\
color=term.color, **params)
if plot_component_ref and term.ref_spectrum is not None:
f = numpy.arange(term.ref_spectrum.size) *\
term.ref_frequencyseries.deltaF +\
term.ref_frequencyseries.f0
plot.add_content(f, term.ref_spectrum,\
label=None, color=term.color, **refparams)
reference_plotted = True
# finalize plot
plot.finalize(logx=logx, logy=logy, loc='upper right',\
hidden_colorbar=hidden_colorbar)
if xlim: plot.ax.set_xlim(xlim)
if ylim: plot.ax.set_ylim(ylim)
# add text box
if reference_plotted:
plot.ax.text(0.005, 0.99, 'Dashed line indicates reference',\
horizontalalignment='left', verticalalignment='top',\
transform=plot.ax.transAxes,\
backgroundcolor='white',\
bbox=dict(facecolor='white', alpha=0.6,\
edgecolor='black'))
# save
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
def plottable(lsctable, outfile, xcolumn="time", ycolumn="snr",\
colorcolumn=None, rankcolumn=None, t0=None, **kwargs):
"""
Plot any column of a valid LigoLW table against any other, coloured by any
other, or plot all the same if you're that way inclined. Multiple tables
can be given for any non-coloured plot.
"time" as a column means the output of get_peak for Burst tables, get_end
for Inspiral tables, and get_start for ringdown tables
Arguments:
tables : [ dict | glue.ligolw.table.Table ]
dict of ("name", table) pairs, or single LigoLW tables
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).
"""
# work out dictionary or table
if isinstance(lsctable, table.Table):
tables = {"_":lsctable}
else:
tables = lsctable
tablenames = tables.keys()
tables = [tables[n] for n in tablenames]
# get axis limits
xlim = kwargs.pop('xlim', None)
ylim = kwargs.pop('ylim', None)
zlim = kwargs.pop('zlim', None)
colorlim = kwargs.pop('colorlim', None)
if zlim and not colorlim:
colorlim = zlim
# set up columns
columns = list(map(str.lower, [xcolumn, ycolumn]))
if colorcolumn:
columns.append(colorcolumn.lower())
if rankcolumn:
columns.append(rankcolumn.lower())
else:
columns.append(colorcolumn.lower())
# set up limits
limits = [xlim, ylim, zlim, None]
# get zero
if "time" in columns and not t0:
if xlim:
t0 = float(xlim[0])
else:
t0 = numpy.infty
for t in tables:
timedata = get_column(t, "time").astype(float)
if len(timedata):
t0 = min(t0, timedata.min())
if numpy.isinf(t0):
t0 = 0
t0 = int(t0)
#
# get data
#
# extract columns
data = list()
for i,name in enumerate(tablenames):
data.append(list())
for c in columns:
c = c.lower()
if ((c not in tables[i].columnnames and c != "time") and not
hasattr(tables[i], "get_%s" % c.lower())):
raise RuntimeError("Column '%s' not found in table '%s'."\
% (c,name))
data[-1].append(get_column(tables[i], c.lower()).astype(float))
if not len(data[-1][-1].shape)\
or data[-1][-1].shape[0] != len(tables[i]):
raise AttributeError("No data loaded for column \"%s\" and "\
"table \"%s\"" % (c, name))
# add our own limits
for i in range(len(columns)):
if not limits[i]:
mins = [data[j][i].min() for j in range(len(tablenames))\
if len(data[j][i].shape) and data[j][i].shape[0] != 0]
if len(mins):
lmin = min(mins)
lmax = max(data[j][i].max() for j in range(len(tablenames))\
if len(data[j][i]))
limits[i] = [lmin, lmax]
# get time unit
if "time" in columns:
idx = columns.index("time")
if limits[idx]:
unit, timestr = plotutils.time_axis_unit(limits[idx][1]\
- limits[idx][0])
else:
unit, timestr = plotutils.time_axis_unit(1)
# format data
for i,name in enumerate(tablenames):
for j,column in enumerate(columns):
if column == "time":
data[i][j] = (data[i][j] - t0) / unit
if i==0 and limits[j]:
limits[j] = [float(limits[j][0] - t0) / unit,\
float(limits[j][1] - t0) / unit]
# format a condition to reject triggers outside the plot range
plotted = True
for j,column in enumerate(columns):
if limits[j]:
plotted = plotted & (limits[j][0] <= data[i][j])\
& (limits[j][1] >= data[i][j])
# apply the limits
if not isinstance(plotted, bool):
for j,d in enumerate(data[i]):
data[i][j] = d[plotted]
#
# find loudest event
#
loudest = None
if len(columns) == 4 and len(tablenames) == 1 and len(data[0][0]) > 0:
idx = data[0][3].argmax()
loudest = [data[0][j][idx] for j in range(len(columns))]
#
# get or set the labels
#
label = {}
for i,(label,column) in enumerate(zip(["xlabel", "ylabel", "colorlabel"],\
columns)):
# get given label
l = kwargs.pop(label, None)
if l is None:
# format time string
if column == "time" and limits[i]:
zerostr = datetime.datetime(\
*date.XLALGPSToUTC(LIGOTimeGPS(t0))[:6])\
.strftime("%B %d %Y, %H:%M:%S %ZUTC")
l = "Time (%s) since %s (%s)" % (timestr, zerostr, t0)
# format any other column
else:
l = plotutils.display_name(column)
if label == "xlabel":
xlabel = l
elif label == "ylabel":
ylabel = l
else:
colorlabel = l
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle", None)
if subtitle is None and loudest:
subtitle = "Loudest event by %s:" % plotutils.display_name(columns[-1])
for j,c in enumerate(columns):
if j!= 0 and c == columns[j-1]: continue
lstr = loudest[j]
if c == "time":
lstr = lstr * unit + t0
subtitle += " %s=%.2f" % (plotutils.display_name(c), lstr)
else:
loudest = None
#
# get parameters
#
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
logcolor = kwargs.pop("logcolor", False)
# get legend loc
loc = kwargs.pop("loc", 0)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", "tight")
# get detchar plot params
dqstyle = (kwargs.pop("detchar", False) or
kwargs.pop('detchar_style', False))
dqthresh = (kwargs.pop('dcthreshold', False) or
kwargs.pop('detchar_style_threshold', 10))
# get greyscale param
greyscale = kwargs.pop("greyscale", False)
if greyscale and not kwargs.has_key("cmap"):
kwargs["cmap"] =\
pylab.matplotlib.colors.LinearSegmentedColormap("clrs",\
pylab.matplotlib.cm.hot_r._segmentdata)
elif not kwargs.has_key("cmap"):
kwargs["cmap"] = jet
#
# make the plot
#
tablenames = map(plotutils.display_name, tablenames)
if len(columns) == 2:
plot = plotutils.ScatterPlot(xlabel, ylabel,title, subtitle)
for i in range(len(tablenames)):
plot.add_content(data[i][0], data[i][1], label=tablenames[i],\
**kwargs)
plot.finalize(loc=loc)
if hidden_colorbar:
plotutils.add_colorbar(plot.ax, visible=False)
else:
if dqstyle:
plot = plotutils.DQScatterPlot(xlabel, ylabel, colorlabel,\
title, subtitle)
else:
plot = plotutils.ColorbarScatterPlot(xlabel, ylabel, colorlabel,\
title, subtitle)
plot.add_content(data[0][0], data[0][1], data[0][2],\
label=tablenames[0], **kwargs)
kwargs.pop("cmap", None)
if dqstyle:
plot.finalize(logcolor=logcolor, clim=colorlim, loc=loc,\
threshold=dqthresh)
else:
plot.finalize(logcolor=logcolor, clim=colorlim, loc=loc)
# plot loudest
if loudest:
plot.ax.plot([loudest[0]], [loudest[1]], marker="*", color="gold",\
markersize=15)
# set axes
if logx:
plot.ax.set_xscale("log")
if logy:
plot.ax.set_yscale("log")
plot.ax.autoscale_view(tight=True, scalex=True, scaley=True)
if limits[0]:
plot.ax.set_xlim(limits[0])
if limits[1]:
plot.ax.set_ylim(limits[1])
plot.ax.grid(True, which="both")
if xcolumn == "time":
plotutils.set_time_ticks(plot.ax)
plotutils.set_minor_ticks(plot.ax)
# save and close
if greyscale:
plot.ax.patch.set_facecolor("#E8E8E8")
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
def plothistogram(lsctable, outfile, column="snr", numbins=100,\
colorcolumn=None, colorbins=10, normalize=None,\
cumulative=None, bar=False, **kwargs):
"""
Plot any column of a valid LigoLW table against any other, coloured by any
other, or plot all the same if you're that way inclined. Multiple tables
can be given for any non-coloured plot.
"time" as a column means the output of get_peak for Burst tables, get_end
for Inspiral tables, and get_start for ringdown tables
Arguments:
table : [ dict | glue.ligolw.table.Table ]
dict of ("name", table) pairs, or single LigoLW table
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).
"""
# work out dictionary or table
if isinstance(lsctable, table.Table):
tables = {"_":lsctable}
else:
tables = lsctable
tablenames = sorted(tables.keys())
tables = [tables[n] for n in tablenames]
# get axis limits
xlim = kwargs.pop("xlim", None)
ylim = kwargs.pop("ylim", None)
zlim = kwargs.pop("zlim", None)
clim = kwargs.pop("clim", zlim)
# get axis scales
logx = kwargs.pop("logx", False)
logy = kwargs.pop("logy", False)
logcolor = kwargs.pop("logcolor", False)
# get colorbar options
hidden_colorbar = kwargs.pop("hidden_colorbar", False)
# get savefig option
bbox_inches = kwargs.pop("bbox_inches", "tight")
# get fill
fill = kwargs.pop("fill", False)
# get extras
rate = kwargs.pop("rate", False)
if normalize:
rate = True
if not hasattr(normalize, "__iter__"):
normalize = [normalize]*len(tablenames)
else:
normalize = [1]*len(tablenames)
loc = kwargs.pop("loc", 0)
# set labels
xlabel = kwargs.pop("xlabel", plotutils.display_name(column))
if rate and cumulative:
ylabel = kwargs.pop("ylabel", "Cumulative rate (Hz)")
elif rate:
ylabel = kwargs.pop("ylabel", "Rate (Hz)")
elif not rate and cumulative:
ylabel = kwargs.pop("ylabel", "Cumulative number")
else:
ylabel = kwargs.pop("ylabel", "Number")
title = kwargs.pop("title", "")
subtitle = kwargs.pop("subtitle","")
colorlabel = kwargs.pop("colorlabel", colorcolumn\
and plotutils.display_name(colorcolumn) or "")
#
# get column data
#
if colorcolumn:
colordata = get_column(tables[0], colorcolumn).astype(float)
if not clim and colordata.size != 0:
clim = [colordata.min(), colordata.max()]
elif not clim:
clim = [1, 10]
if isinstance(colorbins, int):
numcolorbins = colorbins
if logcolor:
colorbins = numpy.logspace(*numpy.log10(clim), num=numcolorbins)
else:
colorbins = numpy.linspace(*clim, num=numcolorbins)
else:
numcolorbins = len(colorbins)
data = list()
for i,lsctable in enumerate(tables):
d = get_column(lsctable, column).astype(float)
if i==0 and colorcolumn:
data.append(list())
for j in range(numcolorbins):
data[i].append(d[d>=colorbins[j]])
else:
data.append(d)
#
# generate plot and make
#
if colorcolumn:
raise NotImplementedError("This has not been implemented in "+\
"plotutils yet, here's your chance!")
plot = plotutils.ColorbarLineHistogram(xlabel, ylabel, colorlabel,\
title, subtitle)
for dataset,colorbin in zip(data[0], colorbins):
plot.add_content(dataset, normalize=normalize[0],\
colorvalue=colorbin, label=tablenames[0], **kwargs)
for i,name in enumerate(tablenames[1:]):
plot.add_content(data[i+1], normalize=normalize[i+1],\
label=name, **kwargs)
plot.finalize(logcolor=logcolor, colorlabel=colorlabel, loc=loc)
else:
color = kwargs.pop("color", None)
if isinstance(color, str):
color = color.split(',')
if len(color) == 1:
color = [color[0]]*len(serieslist)
plot = plotutils.LineHistogram(xlabel, ylabel, title, subtitle)
for i,name in enumerate(tablenames):
if color:
kwargs["color"] = color[i]
plot.add_content(data[i], normalize=normalize[i], label=name,\
**kwargs)
plot.finalize(loc=loc, logx=logx, logy=logy, bar=bar, num_bins=numbins,\
cumulative=cumulative)
plot.ax.autoscale_view(tight=True, scalex=True, scaley=True)
if xlim:
plot.ax.set_xlim(xlim)
if ylim:
plot.ax.set_ylim(ylim)
# save and close
plot.savefig(outfile, bbox_inches=bbox_inches,\
bbox_extra_artists=plot.ax.texts)
plot.close()
