def get_archive_pv_value(
PV,
label,
start_time,
end_time,
scan_archives=True,
limit=100000,
interpolation='raw',
archiver=None,
):
'''get PV, PV-Label from archiver from start_time to end_time
Return:
pandas.DataFrame with keys as time-str, time-float, label-values
'''
import pandas as pd
import numpy as np
import time
if archiver is None:
from channelarchiver import Archiver
archiver = [
Archiver(
'http://xf11id-ca.nsls2.bnl.local/cgi-bin/ArchiveDataServer.cgi'
)
]
#if scan_archives:
#archiver.scan_archives()
if label[:3] == 'Acc': arch = archiver[1]
else: arch = archiver[0]
data = arch.get(PV,
start_time,
end_time,
scan_archives=scan_archives,
limit=limit,
interpolation=interpolation)
td = np.array(data.times)
v = np.array(data.values, dtype=float)
td = make_wave_data(td, dtype='x')
v = make_wave_data(v, dtype='y')
tf = trans_td_to_tf(td)
tv = np.array([td, tf, v]).T
index = np.arange(len(tv))
data = tv
df = pd.DataFrame(data, index=index, columns=['td', 'tf', label])
#
print('seraching %s from: %s---to: %s' % (label, start_time, end_time))
print('Found results: from: %s to :%s with %s points.' %
(df.td[0], df.td[len(df.td) - 1], len(df.td)))
return df
def get_archive_pvlist_values(PVs,
labels,
start_time,
end_time,
limit=100000,
interpolation='raw'):
'''get PV-list, PV-Label-list from archiver from start_time to end_time,
Return:
a dict { label:
pandas.DataFrame with keys as time-str, time-float, label-values
}
'''
from channelarchiver import Archiver
archiver = Archiver(
'http://xf11id-ca.nsls2.bnl.local/cgi-bin/ArchiveDataServer.cgi')
archiver_acc = Archiver(
'http://ca.cs.nsls2.local:8888/cgi-bin/ArchiveDataServer.cgi')
#archiver.scan_archives()
dict_tv = {}
N = len(PVs)
for i in range(N):
PV = PVs[i]
label = labels[i]
if i == 0: scan_archives = True
else: scan_archives = False
scan_archives = True
dict_tv[label] = get_archive_pv_value(
PV,
label,
start_time,
end_time,
scan_archives=scan_archives,
limit=limit,
interpolation=interpolation,
archiver=[archiver, archiver_acc])
return dict_tv
Based off of cafetch.py, written by Elena, with a few features removed to limit
dependencies.
Changelog:
2020-06-08 DG Ported to Python 3 and ObserverTools, takes a series of keys or
just one.
"""
from channelarchiver import Archiver
from argparse import ArgumentParser
from astropy.time import Time
import socket
try:
telemetry = Archiver('http://sdss-telemetry.apo.nmsu.edu/'
'telemetry/cgi/ArchiveDataServer.cgi')
telemetry.scan_archives()
except (socket.gaierror, ConnectionRefusedError):
try:
telemetry = Archiver('http://*****:*****@'
'sdss-gateway.apo.nmsu.edu')
__version__ = '3.1.1'
def setUp(self):
self.archiver = Archiver(
'https://xf23id-ca/cgi-bin/ArchiveDataServer.cgi')
self.archiver.archiver = MockArchiver()
#!/usr/bin/env python3
# bernie Tue. 26 June '18
# playing around
from channelarchiver import Archiver, codes, utils
ss = 'http://sdss-telemetry.apo.nmsu.edu/telemetry/cgi/ArchiveDataServer.cgi'
#ss='http://localhost:5080/telemetry/cgi/ArchiveDataServer.cgi'
archiver = Archiver(ss)
archiver.scan_archives()
start = '2018-06-25 10:00:00'
end = '2018-06-26 11:00:00'
archiver.scan_archives()
data1 = archiver.get('25m:boss:SP1B2LN2TempRead',
start,
end,
interpolation='raw',
scan_archives=False)
data2 = archiver.get('25m:boss:SP1R0LN2TempRead',
start,
end,
interpolation='raw',
scan_archives=False)
data3 = archiver.get('25m:boss:SP2B2LN2TempRead',
start,
end,
interpolation='raw',
scan_archives=False)
def setUp(self):
self.archiver = Archiver('http://fake')
self.archiver.archiver = MockArchiver()
def get_archived_pv(pv,
start_time,
end_time,
label=None,
limit=None,
make_wave=True,
interpolation='raw'):
'''Yugang May 15, 2017
Get a archived PV value
Input:
start time: str, e.g., '2017-04-11 09:00',
end time: str, e.g., '2017-04-12 11:00'
label: str, a meaningful label for the pv
limit: integer, the limit data point
make_wave: if True, make a 'square-wave like' data
interpolation: 'raw', gives the raw archived data
Return: a pandas.dataframe with column as
datetime, float time, and value
data
An example:
data = get_archived_pv('XF:11IDA-OP{Mono:DCM-Ax:Bragg}T-I', '2017-04-11 09:00', '2017-04-11 11:00')
'''
from channelarchiver import Archiver
archiver = Archiver(
'http://xf11id-ca.cs.nsls2.local/cgi-bin/ArchiveDataServer.cgi')
import numpy as np
import pandas as pd
if label is None:
label = pv
#if pv[0][:2] == 'SR':
# res = arget( pv,start=start_time,
# end=end_time,count=limit, conf = 'middle')
#else:
print('Seraching PV: %s from: %s---to: %s' % (label, start_time, end_time))
res = archiver.get(pv,
start_time,
end_time,
scan_archives=True,
limit=limit,
interpolation=interpolation)
#print res
key = pv
v = np.array(res[key][0], dtype=float)
k1 = res[key][1]
N = len(k1)
sec = np.array([k1[i][2] for i in range(N)])
nsec = np.array([k1[i][3] for i in range(N)])
tf = sec + nsec * 10**(-9)
if make_wave:
v = make_wave_data(v, dtype='y')
tf = make_wave_data(tf, dtype='x')
td = trans_tf_to_td(tf, dtype='array')
NN = len(td)
tv = np.array([td, tf.reshape(NN), v.reshape(NN)]).T
index = np.arange(len(tv))
data = tv
df = pd.DataFrame(data, index=index, columns=['td', 'tf', label[0]])
if make_wave: fnum = len(df.td) / 2
else: fnum = len(df.td)
return df
def archiver():
archiver = Archiver("http://fake")
archiver.archiver = MockArchiver()
return archiver
