def rate_per_bin(table, stride, column, bins, start=None, end=None):
"""@returns a list of TimeSeries representing the rate of events
in each bin for the given LIGO_LW table
"""
# get time
tarray = triggers.get_time_column(table).astype(float)
tarray.sort()
# get limits
if not start:
start = tarray[0]
if not end:
end = tarray[-1]
start = float(start)
end = float(end)
duration = end - start
# contruct time bins
stride = float(stride)
duration = stride * round(duration/stride)
bins = numpy.linspace(start, start+duration, num = duration//stride)
# calculate rate per bin
carray = triggers.get_column(str(column))
out = []
for bin_l,bin_r in bins:
in_bin = (bin_l <= carray) & (carray < bin_r)
rate = CreateREAL8TimeSeries("Rate (Hz) [%s <= %s < %s]"
% (bin_l, column, bin_r),
LIGOTimeGPS(start), 0,
stride, lalHertzUnit, bins.size-1)
hist,_ = numpy.histogram(tarray, bins=bins)
rate.data.data = (hist / stride).astype(numpy.float64)
out.append(rate)
return out
def rate_per_bin(table, stride, column, bins, start=None, end=None):
"""@returns a list of TimeSeries representing the rate of events
in each bin for the given LIGO_LW table
"""
# get time
tarray = triggers.get_time_column(table).astype(float)
tarray.sort()
# get limits
if not start:
start = tarray[0]
if not end:
end = tarray[-1]
start = float(start)
end = float(end)
duration = end - start
# contruct time bins
stride = float(stride)
duration = stride * round(duration / stride)
bins = numpy.linspace(start, start + duration, num=duration // stride)
# calculate rate per bin
carray = triggers.get_column(str(column))
out = []
for bin_l, bin_r in bins:
in_bin = (bin_l <= carray) & (carray < bin_r)
rate = CreateREAL8TimeSeries(
"Rate (Hz) [%s <= %s < %s]" % (bin_l, column, bin_r),
LIGOTimeGPS(start), 0, stride, lalHertzUnit, bins.size - 1)
hist, _ = numpy.histogram(tarray, bins=bins)
rate.data.data = (hist / stride).astype(numpy.float64)
out.append(rate)
return out
def rate(table, stride, start=None, end=None):
"""@returns a TimeSeries of rate over time for all triggers in the
given LIGO_LW table.
"""
# get time
tarray = triggers.get_time_column(table).astype(float)
tarray.sort()
# get limits
if not start:
start = tarray[0]
if not end:
end = tarray[-1]
start = float(start)
end = float(end)
duration = end - start
# contruct time bins
stride = float(stride)
duration = stride * round(duration/stride)
bins = numpy.linspace(start, start+duration, num = duration//stride)
# calculate rate
rate = CreateREAL8TimeSeries("Rate (Hz)", LIGOTimeGPS(start), 0,
stride, lalHertzUnit, bins.size-1)
hist,_ = numpy.histogram(tarray, bins=bins)
rate.data.data = hist.astype(numpy.float64)/stride
return rate
def rate(table, stride, start=None, end=None):
"""@returns a TimeSeries of rate over time for all triggers in the
given LIGO_LW table.
"""
# get time
tarray = triggers.get_time_column(table).astype(float)
tarray.sort()
# get limits
if not start:
start = tarray[0]
if not end:
end = tarray[-1]
start = float(start)
end = float(end)
duration = end - start
# contruct time bins
stride = float(stride)
duration = stride * round(duration / stride)
bins = numpy.linspace(start, start + duration, num=duration // stride)
# calculate rate
rate = CreateREAL8TimeSeries("Rate (Hz)", LIGOTimeGPS(start), 0, stride,
lalHertzUnit, bins.size - 1)
hist, _ = numpy.histogram(tarray, bins=bins)
rate.data.data = hist.astype(numpy.float64) / stride
return rate
