Importing and setting libraries for data (pytimber) and plots (matplotlib)
%matplotlib notebook
import pytimber
import matplotlib.pyplot as pl
db=pytimber.LoggingDB()
Choose time window and variables
t1="2016-08-08 17:57:00"
t2="2016-08-08 17:58:00"
vn=['LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_H',
'LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_V',
'LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_H',
'LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_V']
Getting data
data=db.get(vn,t1,t2)
Align and flatten acquisitions
flatten={}
for name,(timestamps,values) in data.items():
print("%s %s"%(name,values.shape))
flatten[name]=pytimber.flattenoverlap(values)
print("%s %s"%(name,flatten[name].shape))
LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_H (375, 2048) Flatten: ... average overlap 248.72 samples LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_H (674977,) LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_V (375, 2048) Flatten: ... average overlap 248.72 samples LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_V (674978,) LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_H (375, 2048) Flatten: ... average overlap 248.72 samples LHC.BQBBQ.CONTINUOUS_HS.B2:ACQ_DATA_H (674978,) LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_V (375, 2048) Flatten: ... average overlap 248.72 samples LHC.BQBBQ.CONTINUOUS_HS.B1:ACQ_DATA_V (674977,)
Plot data
pl.figure(figsize=(13,6));ax=None
for iname,name in enumerate(vn):
ax=pl.subplot(221+iname,sharex=ax)
pl.specgram(flatten[name],Fs=1,NFFT=2048)
pl.title("Beam %s %s"%(name[25],name[-1]))
pl.xlabel('Turns')
pl.ylabel('Tune')
<matplotlib.text.Text at 0x7fa33cd9ef50>
Plot time domain detail
pl.figure()
name=vn[0]
pl.plot(flatten[name])
pl.title("Beam %s %s"%(name[25],name[-1]))
pl.xlim(293000,295000)
pl.xlabel('Turns')
pl.ylabel('Amplitude [a.u.]')
<matplotlib.text.Text at 0x7fa33cbabe50>