本文整理汇总了Python中gwpy.timeseries.TimeSeries.write方法的典型用法代码示例。如果您正苦于以下问题：Python TimeSeries.write方法的具体用法？Python TimeSeries.write怎么用？Python TimeSeries.write使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类gwpy.timeseries.TimeSeries的用法示例。
在下文中一共展示了TimeSeries.write方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: dump_calibrated_data
# 需要导入模块: from gwpy.timeseries import TimeSeries [as 别名]
# 或者: from gwpy.timeseries.TimeSeries import write [as 别名]
def dump_calibrated_data(fname):
data = numpy.load(fname)
# Figure out the times covered by the file from the filename
# I should start using HDF5 so I can store metadata
temp = fname.split('.')[0]
temp = temp.split('-')
ifo = temp[0]
st, dur = int(temp[-2]), int(temp[-1])
et = st + dur
maxidx = len(data)
width = 45
weights = 1. - ((numpy.arange(-width, width) / float(width))**2)
# The VCO frequencies are integers so we could dither them
# to avoid quantization error if we wanted to be fancy
# but it seems to make no differece
if False:
from numpy.random import triangular
data[:, 1] += triangular(-1., 0., 1., size=len(data))
# Just fit the whole thing at once, to get a single coefficient
a, b = numpy.polyfit(data[:, 0], data[:, 1], 1)
print "%.1f %u" % (a, b)
# Slide through the data fitting PSL to IMC for data around each sample
coeffs = []
for idx in xrange(maxidx):
idx1 = max(0, idx - width)
idx2 = min(idx + width, maxidx)
coeffs.append(numpy.polyfit(data[idx1:idx2, 0], data[idx1:idx2, 1], 1,
w=weights[idx1 - idx + width:idx2 - idx + width]))
coeffs = numpy.array(coeffs)
times = numpy.arange(len(coeffs)) + 0.5
connection = datafind.GWDataFindHTTPConnection()
cache = connection.find_frame_urls(
ifo[0], '%s_R' % ifo, st, et, urltype='file')
imc = TimeSeries.read(cache, "%s:IMC-F_OUT_DQ" % ifo, st, et)
imc = imc[::16384 / 256]
print imc
samp_times = numpy.arange(len(imc)) / 256.
coeffs0 = numpy.interp(samp_times, times, coeffs[:, 0])
coeffs1 = numpy.interp(samp_times, times, coeffs[:, 1]) - 7.6e7
vco_interp = coeffs0 * imc.data + coeffs1
chan = "%s:IMC-VCO_PREDICTION" % (ifo,)
vco_data = TimeSeries(vco_interp, epoch=st,
sample_rate=imc.sample_rate.value,
name=chan, channel=chan)
vco_data.write("%s-vcoprediction-%u-%u.hdf" % (ifo, st, dur), format='hdf')示例2: load
# 需要导入模块: from gwpy.timeseries import TimeSeries [as 别名]
# 或者: from gwpy.timeseries.TimeSeries import write [as 别名]
import sys
from numpy import *
from gwpy.timeseries import TimeSeries
from scipy.interpolate import interp1d
fname = sys.argv[1]
data = load(fname)
# Figure out the times covered by the file from the filename
# I should start using HDF5 so I can store metadata
temp = fname.split('.')[0]
temp = temp.split('-')
ifo = temp[0]
st, dur = int(temp[-2]), int(temp[-1])
et = st + dur
offset = 7.9e7
fvco = interp1d(arange(len(data)) + 0.5, data[:, 1] - offset, kind='cubic')
chan = "%s:IMC-VCO_INTERPOLATION" % (ifo,)
vco_data = TimeSeries(vco_interp, epoch=st, sample_rate=imc.sample_rate.value,
name=chan, channel=chan)
vco_data.write("%s-vcointerpolation-%u-%u.hdf" % (ifo, st, dur), format='hdf')
示例3: polyfit
# 需要导入模块: from gwpy.timeseries import TimeSeries [as 别名]
# 或者: from gwpy.timeseries.TimeSeries import write [as 别名]
a, b = polyfit(data[:, 0], data[:, 1], 1)
print "%.1f %u" % (a, b)
# Slide through the data fitting PSL to IMC for data around each sample
coeffs = []
for idx in xrange(maxidx):
idx1 = max(0, idx - width)
idx2 = min(idx + width, maxidx)
coeffs.append(polyfit(data[idx1:idx2, 0], data[idx1:idx2, 1], 1,
w=weights[idx1 - idx + width:idx2 - idx + width]))
coeffs = array(coeffs)
times = arange(len(coeffs)) + 0.5
connection = datafind.GWDataFindHTTPConnection()
cache = connection.find_frame_urls(
ifo[0], '%s_R' % ifo, st, et, urltype='file')
imc = TimeSeries.read(cache, "%s:IMC-F_OUT_DQ" % ifo, st, et)
imc = imc[::16384 / 256]
print imc
samp_times = arange(len(imc)) / 256.
coeffs0 = interp(samp_times, times, coeffs[:, 0])
coeffs1 = interp(samp_times, times, coeffs[:, 1]) - 7.6e7
vco_interp = coeffs0 * imc.data + coeffs1
chan = "%s:IMC-VCO_PREDICTION" % (ifo,)
vco_data = TimeSeries(vco_interp, epoch=st, sample_rate=imc.sample_rate.value,
name=chan, channel=chan)
vco_data.write("%s-vcoprediction-%u-%u.hdf" % (ifo, st, dur), format='hdf')