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 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 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()
