verbose = 0
# these were the original lines
shots=np.loadtxt('pyfusion/acquisition/LHD/lhd_clk4.txt',dtype=type(1))
fileformat = '/data/datamining/cache/fircall@{0}.dat.bz2'
# 2015 update -
shots=[105396]
fileformat = '/data/datamining/cache/wp/wp@{0}.dat.bz2'
separate=0
import pyfusion.utils
exec(pf.utils.process_cmd_line_args())
missing_shots = []
good_shots =[]
for shot in shots:
try:
dat=igetfile(fileformat,shot=shot)
if separate: pl.figure()
dat.plot(hold=1,ch=1)
good_shots.append(shot)
except IOError:
missing_shots.append(shot)
pl.show(block=0)
print("{0} missing shots out of {1}".format(len(missing_shots),(len(missing_shots)+len(good_shots))))
if verbose>0: print('missing shots are {0}'.format(missing_shots))
ndiags = None
for (i, diag) in enumerate(diag_names.split(",")):
data = dev.acq.getdata(shot, diag)
if i == 0:
if len(np.shape(data.channels)) == 0:
ndiags = 1
else:
ndisgs = len(data.channels)
if ndiags == 1:
(fig, ax1) = pl.subplots()
if offset is not None:
data.timebase += offset
data.plot_signals(labeleg="True", color="g") # ,downsamplefactor=10) not much diff
pl.ylim(-abs(max(pl.ylim())), abs(max(pl.ylim())))
if ndiags == 1:
ax2 = ax1.twinx()
else:
ax2 = pl.gca()
ax2.set_autoscaley_on(True)
for eg in egdiags.split(","):
egdat = igetfile("{d}@{s}.dat".format(s=shot, d=eg))
egdat.plot(1)
ax2.set_ylim(-abs(max(ax2.get_ylim())), abs(max(ax2.get_ylim())))
pl.show()
def get_basic_diagnostics(diags=None, shot=54196, times=None, delay=None, exception=False, debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
"""
global lhd_summary
# if no exception given and we are not debugging
# note - exception=None is a valid entry, meaning tolerate no exceptions
# so the "default" we use is False
if exception==False and debug==0: exception=Exception
if diags == None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if len(np.shape(diags)) == 0: diags = [diags]
if delay == None: delay = get_delay(shot)
if times == None:
times = np.linspace(0,4,4000)
times = np.array(times)
vals = {}
# create an extra time array to allow a cross check
vals.update({'check_tm':times})
vals.update({'check_shot':np.zeros(len(times),dtype=np.int)+shot})
for diag in diags:
if not(file_info.has_key(diag)):
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info['name']
subfolder = info['format'].split('@')[0]
filepath = os.path.sep.join([localigetfilepath,subfolder,info['format']])
if ':' in varname: (oper,varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test=lhd_summary.keys()
except:
print('reloading {0}'.format(info['format']))
lhd_summary = read_csv_data(acq_LHD+'/'+info['format'], header=3)
val = lhd_summary[varname][shot]
valarr = np.double(val)+(times*0)
else:
debug_(max(pyfusion.DEBUG, debug), level=4, key='find_data')
try:
dg = igetfile(filepath, shot=shot, debug=debug-1)
except IOError:
try:
dg = igetfile(filepath+'.bz2', shot=shot, debug=debug-1)
except IOError:
try:
dg = igetfile(filepath + '.gz', shot=shot, debug=debug-1)
except exception:
if debug>0: print('diag at {fp} not found'
.format(fp=filepath))
dg=None
#break # give up and try next diagnostic
if dg==None: # messy - break doesn't do what I want?
valarr=None
else:
nd=dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'
.format(dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [re.match(varname,nam)
!= None for nam in dg.vardict['ValName']]
w = np.where(np.array(matches) != False)[0]
# get the column(s) of the array corresponding to the name
if (oper in 'sum,average,rms,max,min'.split(',')):
if oper=='sum': op = np.sum
elif oper=='average': op = np.average
elif oper=='min': op = np.min
elif oper=='std': op = np.std
else: raise ValueError('operator {o} in {n} not known to get_basic_diagnostics'
.format(o=oper, n=info['name']))
valarr = op(dg.data[:,nd+w],1)
else:
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'
.format(varname, dg.filename))
if len(np.shape(dg.data))!=2:
raise LookupError(
'insufficient data for {0} in {1}'
.format(varname, dg.filename))
valarr = dg.data[:,nd+w[0]]
tim = dg.data[:,0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr)/(np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:])/2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr)/(np.average(np.diff(tim)))
ddw = np.diff(dw)/(np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
if (len(tim) < 10) or (np.std(tim)<0.1):
raise ValueError('Insufficient points or degenerate'
'timebase data in {0}, {1}'
.format(varname, dg.filename))
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
if valarr != None: vals.update({diag: valarr})
debug_(max(pyfusion.DEBUG, debug), level=5, key='interp')
return(vals)
def get_basic_params(diags=None, shot=54196, times=None, delay=None, debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
"""
global lhd_summary
if diags is None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if delay is None: delay = get_delay(shot)
if times is None:
times = np.linspace(0,4,4000)
times = np.array(times)
vals = {}
# create an extra time array to allow a cross check
vals.update({'check_tm':times})
vals.update({'check_shot':np.zeros(len(times),dtype=np.int)+shot})
for diag in diags:
if diag not in file_info:
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info['name']
if ':' in varname: (oper,varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test=lhd_summary.keys()
except:
print('reloading {0}'.format(info['format']))
lhd_summary = read_csv_data(acq_LHD+info['format'], header=3)
val = lhd_summary[varname][shot]
valarr = np.double(val)+(times*0)
else:
try:
dg = igetfile(local_dir + info['format'], shot=shot)
except IOError:
try:
dg = igetfile(local_dir + info['format']+'.bz2', shot=shot)
except IOError:
try:
dg = igetfile(local_dir + info['format']+'.gz', shot=shot)
except exception:
#debug_(1)
dg=None
#break # give up and try next diagnostic
if dg is None: # messy - break doesn't do what I want?
valarr=None
else:
nd=dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'
.format(dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [re.match(varname,nam)
!= None for nam in dg.vardict['ValName']]
w = np.where(np.array(matches) != False)[0]
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'.
format(varname, dg.filename))
# get the column of the array corresponding to the name
valarr = dg.data[:,nd+w[0]]
tim = dg.data[:,0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr)/(np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:])/2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr)/(np.average(np.diff(tim)))
ddw = np.diff(dw)/(np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
if valarr != None: vals.update({diag: valarr})
debug_(max(pyfusion.DEBUG, debug), level=5, key='interp')
return(vals)
def get_basic_params(diags=None, shot=54196, times=None, delay=None, debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
"""
global lhd_summary
if diags is None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if delay is None: delay = get_delay(shot)
if times is None:
times = np.linspace(0, 4, 4000)
times = np.array(times)
vals = {}
# create an extra time array to allow a cross check
vals.update({'check_tm': times})
vals.update({'check_shot': np.zeros(len(times), dtype=np.int) + shot})
for diag in diags:
if diag not in file_info:
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),
stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info['name']
if ':' in varname: (oper, varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test = lhd_summary.keys()
except:
print('reloading {0}'.format(info['format']))
lhd_summary = read_csv_data(acq_LHD + info['format'],
header=3)
val = lhd_summary[varname][shot]
valarr = np.double(val) + (times * 0)
else:
try:
dg = igetfile(local_dir + info['format'], shot=shot)
except IOError:
try:
dg = igetfile(local_dir + info['format'] + '.bz2',
shot=shot)
except IOError:
try:
dg = igetfile(local_dir + info['format'] + '.gz',
shot=shot)
except exception:
#debug_(1)
dg = None
#break # give up and try next diagnostic
if dg is None: # messy - break doesn't do what I want?
valarr = None
else:
nd = dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'.format(
dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [
re.match(varname, nam) != None
for nam in dg.vardict['ValName']
]
w = np.where(np.array(matches) != False)[0]
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'.
format(varname, dg.filename))
# get the column of the array corresponding to the name
valarr = dg.data[:, nd + w[0]]
tim = dg.data[:, 0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr) / (np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:]) / 2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr) / (np.average(np.diff(tim)))
ddw = np.diff(dw) / (np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
if valarr != None: vals.update({diag: valarr})
debug_(max(pyfusion.DEBUG, debug), level=5, key='interp')
return (vals)
def get_basic_diagnostics(diags=None, file_info=file_info, shot=54196, times=None, delay=None, exception=False, debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
Will access server if env('IGETFILE') points to an exe, else accesses cache
This is the first version to specifically allow for access through pyfusion.cfg
There are two types of access:
I/ single diag on its own timebase
II/ the original multi diag on a given timebase (i.e. that from flucstrcs)
Stage 1 puts the file_info into .cfg file just for I/ single diag access.
Ideally the file_info for II/ sho;d be in .cfg also.
For stage I/, we call it with a file_info dict constructed on the spot
as a dictionary with one just entry (for diags[0]).
"""
global lhd_summary
# if no exception given and we are not debugging
# note - exception=None is a valid entry, meaning tolerate no exceptions
# so the "default" we use is False
if exception==False and debug==0: exception=Exception
if diags is None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if len(np.shape(diags)) == 0: diags = [diags]
if delay is None: delay = get_delay(shot)
if times is None:
if len(diags)>1:
times = np.linspace(0,4,4000) # this is a crude guess.
# else leave it None
else:
# make sure it is an array
times = np.array(times)
vals = {}
for diag in diags:
if not(diag in file_info):
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info['name'] # refers to name for igetfile - can contain ':'
subfolder = info['format'].split('@')[0]
filepath = os.path.sep.join([localigetfilepath,subfolder,info['format']])
if ':' in varname: (oper,varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test=list(lhd_summary.keys())
except:
csvfilename = acq_LHD+'/'+info['format']
if pyfusion.DBG() > 1: print('looking for lhd summary in' + csvfilename)
if not os.path.exists(csvfilename):
csvfilename += ".bz2"
print('reloading {0}'.format(csvfilename))
lhd_summary = read_csv_data(csvfilename, header=3)
# should make this more formal - last shots
# from an 'extra' file, and finally, from shot info
if shot>117000: # fudge to get latest data
lhd_summary = np.load(acq_LHD+'/LHD_summary.npz')['LHD'].tolist()
print('loading newer shots from a separate file - fix-me')
# val = lhd_summary[varname][shot-70000] # not needed
# else:
val = lhd_summary[varname][shot]
valarr = np.double(val)+(times*0)
else:
try: # now igetfile checks for .gz etc
dg = igetfile(filepath, shot=shot, debug=debug-1)
except exception as details:
if debug>0: print('diag at {fp} not found'
.format(fp=filepath))
print(details,details.args)
dg=None
#break # give up and try next diagnostic
if dg is None: # messy - break doesn't do what I want?
valarr=None
else:
nd=dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'
.format(dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [re.match(varname,nam)
!= None for nam in dg.vardict['ValName']]
w = np.where(np.array(matches) != False)[0]
# get the column(s) of the array corresponding to the name
if (oper in 'sum,average,rms,max,min'.split(',')):
if oper=='sum': op = np.sum
elif oper=='average': op = np.average
elif oper=='min': op = np.min
elif oper=='std': op = np.std
else: raise ValueError('operator {o} in {n} not known to get_basic_diagnostics'
.format(o=oper, n=info['name']))
valarr = op(dg.data[:,nd+w],1)
else:
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'
.format(varname, dg.filename))
if len(np.shape(dg.data))!=2:
raise LookupError(
'insufficient data for {0} in {1}'
.format(varname, dg.filename))
valarr = dg.data[:,nd+w[0]]
tim = dg.data[:,0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr)/(np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:])/2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr)/(np.average(np.diff(tim)))
ddw = np.diff(dw)/(np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
if (len(tim) < 10) or (np.std(tim)<0.1):
raise ValueError('Insufficient points or degenerate'
'timebase data in {0}, {1}'
.format(varname, dg.filename))
if times is not None:
debug_(max(pyfusion.DEBUG, debug), level=5, key='interp')
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
else:
times = tim
if valarr is not None: vals.update({diag: valarr})
# create an extra time array to allow a cross check
vals.update({'check_tm':times})
vals.update({'check_shot':np.zeros(len(times),dtype=np.int)+shot})
return(vals)
# trivial example to illustrate the igetfile class import pylab as pl import os import traceback from pyfusion.acquisition.LHD.read_igetfile import igetfile testfile = os.path.join(os.path.dirname(__file__),'[email protected]') try: dat=igetfile(testfile,plot=1) pl.figure() dat.plot() except Exception as reason: print('unable to read EG data from examples - maybe no files there "{r}"'.format(r=reason)) pl.figure() try: # nice if we could always have it in this place (may be a soft link( dat=igetfile(os.getenv('HOME')+'/data/datamining/cache/wp/[email protected]',plot=1) except Exception as reason: print('unable to read file - maybe no files there "{r}"'.format(r=reason)) traceback.print_exc() # plot the lot pl.figure() dat.plot() pl.show(block=0)
def get_basic_diagnostics(diags=None,
file_info=file_info,
shot=54196,
times=None,
delay=None,
exception=False,
debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
Will access server if env('IGETFILE') points to an exe, else accesses cache
This is the first version to specifically allow for access through pyfusion.cfg
There are two types of access:
I/ single diag on its own timebase
II/ the original multi diag on a given timebase (i.e. that from flucstrcs)
Stage 1 puts the file_info into .cfg file just for I/ single diag access.
Ideally the file_info for II/ sho;d be in .cfg also.
For stage I/, we call it with a file_info dict constructed on the spot
as a dictionary with one just entry (for diags[0]).
"""
global lhd_summary
# if no exception given and we are not debugging
# note - exception=None is a valid entry, meaning tolerate no exceptions
# so the "default" we use is False
if exception == False and debug == 0: exception = Exception
if diags is None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if len(np.shape(diags)) == 0: diags = [diags]
if delay is None: delay = get_delay(shot)
if times is None:
if len(diags) > 1:
times = np.linspace(0, 4, 4000) # this is a crude guess.
# else leave it None
else:
# make sure it is an array
times = np.array(times)
vals = {}
for diag in diags:
if not (diag in file_info):
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),
stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info[
'name'] # refers to name for igetfile - can contain ':'
subfolder = info['format'].split('@')[0]
filepath = os.path.sep.join(
[localigetfilepath, subfolder, info['format']])
if ':' in varname: (oper, varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test = list(lhd_summary.keys())
except:
csvfilename = acq_LHD + '/' + info['format']
if pyfusion.DBG() > 1:
print('looking for lhd summary in' + csvfilename)
if not os.path.exists(csvfilename):
csvfilename += ".bz2"
print('reloading {0}'.format(csvfilename))
lhd_summary = read_csv_data(csvfilename, header=3)
# should make this more formal - last shots
# from an 'extra' file, and finally, from shot info
if shot > 117000: # fudge to get latest data
lhd_summary = np.load(acq_LHD +
'/LHD_summary.npz')['LHD'].tolist()
print('loading newer shots from a separate file - fix-me')
# val = lhd_summary[varname][shot-70000] # not needed
# else:
val = lhd_summary[varname][shot]
valarr = np.double(val) + (times * 0)
else:
try: # now igetfile checks for .gz etc
dg = igetfile(filepath, shot=shot, debug=debug - 1)
except exception as details:
if debug > 0:
print('diag at {fp} not found'.format(fp=filepath))
print(details, details.args)
dg = None
#break # give up and try next diagnostic
if dg is None: # messy - break doesn't do what I want?
valarr = None
else:
nd = dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'.format(
dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [
re.match(varname, nam) != None
for nam in dg.vardict['ValName']
]
w = np.where(np.array(matches) != False)[0]
# get the column(s) of the array corresponding to the name
if (oper in 'sum,average,rms,max,min'.split(',')):
if oper == 'sum': op = np.sum
elif oper == 'average': op = np.average
elif oper == 'min': op = np.min
elif oper == 'std': op = np.std
else:
raise ValueError(
'operator {o} in {n} not known to get_basic_diagnostics'
.format(o=oper, n=info['name']))
valarr = op(dg.data[:, nd + w], 1)
else:
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'
.format(varname, dg.filename))
if len(np.shape(dg.data)) != 2:
raise LookupError(
'insufficient data for {0} in {1}'.format(
varname, dg.filename))
valarr = dg.data[:, nd + w[0]]
tim = dg.data[:, 0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr) / (np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:]) / 2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr) / (np.average(np.diff(tim)))
ddw = np.diff(dw) / (np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
if (len(tim) < 10) or (np.std(tim) < 0.1):
raise ValueError('Insufficient points or degenerate'
'timebase data in {0}, {1}'.format(
varname, dg.filename))
if times is not None:
debug_(max(pyfusion.DEBUG, debug),
level=5,
key='interp')
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
else:
times = tim
if valarr is not None: vals.update({diag: valarr})
# create an extra time array to allow a cross check
vals.update({'check_tm': times})
vals.update({'check_shot': np.zeros(len(times), dtype=np.int) + shot})
return (vals)
def get_basic_diagnostics(diags=None,
shot=54196,
times=None,
delay=None,
exception=False,
debug=0):
""" return a list of np.arrays of normally numeric values for the
times given, for the given shot.
"""
global lhd_summary
# if no exception given and we are not debugging
# note - exception=None is a valid entry, meaning tolerate no exceptions
# so the "default" we use is False
if exception == False and debug == 0: exception = Exception
if diags == None: diags = "<n_e19>,b_0,i_p,w_p,dw_pdt,dw_pdt2".split(',')
if len(np.shape(diags)) == 0: diags = [diags]
if delay == None: delay = get_delay(shot)
if times == None:
times = np.linspace(0, 4, 4000)
times = np.array(times)
vals = {}
# create an extra time array to allow a cross check
vals.update({'check_tm': times})
vals.update({'check_shot': np.zeros(len(times), dtype=np.int) + shot})
for diag in diags:
if not (file_info.has_key(diag)):
warn('diagnostic {0} not found in shot {1}'.format(diag, shot),
stacklevel=2)
vals.update({diag: np.nan + times})
else:
info = file_info[diag]
varname = info['name']
subfolder = info['format'].split('@')[0]
filepath = os.path.sep.join(
[localigetfilepath, subfolder, info['format']])
if ':' in varname: (oper, varname) = varname.split(':')
else: oper = None
if info['format'].find('.csv') > 0:
try:
test = lhd_summary.keys()
except:
print('reloading {0}'.format(info['format']))
lhd_summary = read_csv_data(acq_LHD + '/' + info['format'],
header=3)
val = lhd_summary[varname][shot]
valarr = np.double(val) + (times * 0)
else:
debug_(max(pyfusion.DEBUG, debug), level=4, key='find_data')
try:
dg = igetfile(filepath, shot=shot, debug=debug - 1)
except IOError:
try:
dg = igetfile(filepath + '.bz2',
shot=shot,
debug=debug - 1)
except IOError:
try:
dg = igetfile(filepath + '.gz',
shot=shot,
debug=debug - 1)
except exception:
if debug > 0:
print('diag at {fp} not found'.format(
fp=filepath))
dg = None
#break # give up and try next diagnostic
if dg == None: # messy - break doesn't do what I want?
valarr = None
else:
nd = dg.vardict['DimNo']
if nd != 1:
raise ValueError(
'Expecting a 1 D array in {0}, got {1}!'.format(
dg.filename, nd))
# pre re. w = np.where(np.array(dg.vardict['ValName'])==varname)[0]
matches = [
re.match(varname, nam) != None
for nam in dg.vardict['ValName']
]
w = np.where(np.array(matches) != False)[0]
# get the column(s) of the array corresponding to the name
if (oper in 'sum,average,rms,max,min'.split(',')):
if oper == 'sum': op = np.sum
elif oper == 'average': op = np.average
elif oper == 'min': op = np.min
elif oper == 'std': op = np.std
else:
raise ValueError(
'operator {o} in {n} not known to get_basic_diagnostics'
.format(o=oper, n=info['name']))
valarr = op(dg.data[:, nd + w], 1)
else:
if len(w) != 1:
raise LookupError(
'Need just one instance of variable {0} in {1}'
.format(varname, dg.filename))
if len(np.shape(dg.data)) != 2:
raise LookupError(
'insufficient data for {0} in {1}'.format(
varname, dg.filename))
valarr = dg.data[:, nd + w[0]]
tim = dg.data[:, 0] - delay
if oper == 'ddt': # derivative operator
valarr = np.diff(valarr) / (np.average(np.diff(tim)))
tim = (tim[0:-1] + tim[1:]) / 2.0
if oper == 'ddt2': # abd(ddw)*derivative operator
dw = np.diff(valarr) / (np.average(np.diff(tim)))
ddw = np.diff(dw) / (np.average(np.diff(tim)))
tim = tim[2:]
valarr = 4e-6 * dw[1:] * np.abs(ddw)
if (len(tim) < 10) or (np.std(tim) < 0.1):
raise ValueError('Insufficient points or degenerate'
'timebase data in {0}, {1}'.format(
varname, dg.filename))
valarr = (stineman_interp(times, tim, valarr))
w = np.where(times > max(tim))
valarr[w] = np.nan
if valarr != None: vals.update({diag: valarr})
debug_(max(pyfusion.DEBUG, debug), level=5, key='interp')
return (vals)
ndiags = None
for (i, diag) in enumerate(diag_names.split(',')):
data = dev.acq.getdata(shot, diag)
if (i == 0):
if len(np.shape(data.channels)) == 0:
ndiags = 1
else:
ndisgs = len(data.channels)
if ndiags == 1:
(fig, ax1) = pl.subplots()
if offset is not None:
data.timebase += offset
data.plot_signals(labeleg='True',
color='g') # ,downsamplefactor=10) not much diff
pl.ylim(-abs(max(pl.ylim())), abs(max(pl.ylim())))
if ndiags == 1: ax2 = ax1.twinx()
else: ax2 = pl.gca()
ax2.set_autoscaley_on(True)
for eg in egdiags.split(','):
egdat = igetfile('{d}@{s}.dat'.format(s=shot, d=eg))
egdat.plot(1)
ax2.set_ylim(-abs(max(ax2.get_ylim())), abs(max(ax2.get_ylim())))
pl.show()
# trivial example to illustrate the igetfile class # this does not use pyfusion, so the paths are hard coded. import pylab as pl import os import traceback from pyfusion.acquisition.LHD.read_igetfile import igetfile testfile = os.path.join(os.path.dirname(__file__), '[email protected]') try: dat = igetfile(testfile, plot=1) pl.figure() dat.plot() except Exception as reason: print('unable to read EG data from examples - maybe no files there "{r}"'. format(r=reason)) pl.figure() try: # nice if we could always have it in this place (may be a soft link( dat = igetfile(os.getenv('HOME') + '/data/datamining/cache/LHD/wp/[email protected]', plot=1) except Exception as reason: print('unable to read file - maybe no files there "{r}"'.format(r=reason)) traceback.print_exc() # plot the lot pl.figure() dat.plot()
