Files
MARTe2-isttok/Analysis/SdasImport2File.py
2024-12-09 15:33:14 +00:00

165 lines
5.6 KiB
Python

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Python3 App to Import data from ISTTOK SDAS to MDSPlus
author: B. Carvalho / IPFN-IST
email: bernardo.carvalho@tecnico.ulisboa.pt
Install sdas:
http://metis.ipfn.tecnico.ulisboa.pt/CODAC/IPFN_Software/SDAS/Access/Python
"""
import numpy as np
import argparse
# import matplotlib.pyplot as plt
from MdsImportSdas import StartSdas, LoadSdasData
ISTTOK_RT_PERIOD = 0.0001
def build_import_table_magnetic():
SDAS_NODEFMT = 'MARTE_NODE_IVO3.DataCollection.Channel_{}'
MAGNETIC_OFF = 166
NUM_PROBES = 12
table = []
for n in range(NUM_PROBES):
sdas_str = SDAS_NODEFMT.format(str(MAGNETIC_OFF + n).zfill(3))
nd = {'sdas': sdas_str,
'name': f'Mirnov coil no. {n+1}'}
table.append(nd)
return table
def build_import_table_langmuir():
SDAS_NODEFMT = 'MARTE_NODE_IVO3.DataCollection.Channel_{}'
LANGMUIR_OFF = 24
NUM_PROBES = 4
"""
ADC_electric_top_near: MARTE_NODE_IVO3.DataCollection.Channel_024
ADC_electric_outer_near: MARTE_NODE_IVO3.DataCollection.Channel_025
ADC_electric_bottom_near: MARTE_NODE_IVO3.DataCollection.Channel_026
ADC_electric_inner_near: MARTE_NODE_IVO3.DataCollection.Channel_027
"""
table = []
for n in range(NUM_PROBES):
sdas_str = SDAS_NODEFMT.format(str(LANGMUIR_OFF + n).zfill(3))
nd = {'sdas': sdas_str, 'name': f'Langmuir Probe no. {n+1}'}
table.append(nd)
return table
"""
def plot_signals(pulse, nodeTable):
try:
tree = Tree(MDSTREENAME, pulse)
except mdsExceptions.TreeNOPATH:
print(f'Failed opening {MDSTREENAME}')
except mdsExceptions.TreeFOPENR:
print(f'Failed opening {MDSTREENAME} for pulse number {pulse:d}')
exit()
NoOfColors = len(nodeTable)
cm = plt.get_cmap('jet')
fig = plt.figure(figsize=(5, 7), tight_layout=True)
ax = fig.add_subplot(111)
ax.set_prop_cycle(color=[cm(1.*i/NoOfColors) for i in range(NoOfColors)])
plt.title(f'#{pulse}: Mirnov coil signals')
for nd in nodeTable:
nd_mds = tree.getNode(nd['mds'])
mdsData = nd_mds.getData()
signal = mdsData.data()
if len(signal) > 0:
times = mdsData.dims[0]
plt.plot(times, signal, label=nd['name'])
plt.xlabel('Time / s ')
plt.legend()
plt.grid(True)
plt.show()
"""
def get_arguments():
parser = argparse.ArgumentParser(
description='Import SDAS ISTTOK to csv File ')
parser.add_argument('-p', '--pulse',
help='pulse (shot) number', default='46241', type=int)
# parser.add_argument('-s', '--shot',
# type=int, help='Mds+ pulse Number ([1, ...])',
# default=100)
parser.add_argument('-f', '--file', type=str,
help='filename device to save', default='SdasData')
parser.add_argument('-e', '--exportData',
action='store_true', help='Export to MDSPlus')
parser.add_argument('-m', '--mirnov',
action='store_true', help='Import Mirnov')
parser.add_argument('-l', '--langmuir',
action='store_true', help='Import Langmuir')
parser.add_argument('-t', '--trigger', type=int,
help='Trigger sample', default='0')
parser.add_argument('-n', '--names',
action='store_true', help='Print Node Table')
parser.add_argument('-z', '--zeros', type=int,
help='Insert zeros rows', default='0')
return parser.parse_args()
if (__name__ == "__main__"):
args = get_arguments()
pulseNo = args.pulse
client = StartSdas()
nodeTable = build_import_table_langmuir()
langmuirData = []
for nd in nodeTable:
print(nd['sdas'])
data, tzero_us, period = LoadSdasData(client, nd['sdas'], pulseNo)
langmuirData.append(data)
time = np.arange(len(data), dtype='uint32') * int(period)
trigger = np.zeros(len(data), dtype='uint32')
if args.trigger > 0:
trigger[args.trigger:] = 1
langmuirNp = np.array(langmuirData).T
nodeTable = build_import_table_magnetic()
magneticData = []
for nd in nodeTable:
print(nd['sdas'])
data, tzero_us, period = LoadSdasData(client, nd['sdas'], pulseNo)
magneticData.append(data)
magneticNp = np.array(magneticData).T
data2file = np.insert(langmuirNp, 0, trigger, axis=1)
data2file = np.append(data2file, magneticNp, axis=1)
data2file = np.insert(data2file, 0, time, axis=1)
if args.zeros > 0:
nCol = data2file.shape[1]
zerRows = np.zeros([args.zeros, nCol])
data2file = np.insert(data2file, 0, zerRows, axis=0)
fname = f"{args.file:s}_{pulseNo}"
filename = f"{fname}.csv"
# head = ('#Time (uint32)[1],Langmuir0 (float32)[1],Langmuir1 (float32)[1],'
# 'Langmuir2 (float32)[1],Langmuir3 (float32)[1]')
# formt = '%d,%.6f,%.6f,%.6f,%.6f'
# formt = '%d,%d,{%.6f,%.6f,%.6f,%.6f}'
# head = '#TimeSdas (uint32)[1],Trigger (uint32)[1],LangmuirSignals (float32)[4]'
formt = ('%d,%d,{%.6f,%.6f,%.6f,%.6f},'
'{%.6g,%.6g,%.6g,%.6g,%.6g,%.6g,'
'%.6g,%.6g,%.6g,%.6g,%.6g,%.6g}')
# head = '#TimeSdas (uint32)[1],Trigger (uint32)[1],LangmuirSignals (float32)[4]'
head = ('#TimeSdas (uint32)[1],Trigger (uint32)[1],'
'LangmuirSignals (float32)[4],'
'MagneticSignals (float32)[12]')
np.savetxt(filename, data2file, fmt=formt,
header=head, comments='')
# , delimiter=',')
np.save(fname, data2file)
# plot_signals(46241, table)
# formt = ['%d', '%.6f', '%.6f', '%.6f', '%.6f']