def char_cwsweep_trackdata():
ifluxbias = request.args.get('ifluxbias')
ixyfreq = request.args.get('ixyfreq')
ixypowa = request.args.get('ixypowa')
# list data position in file:
try:
data_location = {}
data_location['fluxbias'] = gotocdata([
session['c_cwsweep_structure'][0] - 1,
int(ifluxbias), 0, 0, 0, 0, 0, 0
], session['c_cwsweep_structure'])
data_location['xyfreq'] = gotocdata([
session['c_cwsweep_structure'][0] - 1,
session['c_cwsweep_structure'][1] - 1,
int(ixyfreq), 0, 0, 0, 0, 0
], session['c_cwsweep_structure'])
data_location['xypowa'] = gotocdata([
session['c_cwsweep_structure'][0] - 1,
session['c_cwsweep_structure'][1] - 1,
session['c_cwsweep_structure'][0] - 1,
int(ixypowa), 0, 0, 0, 0
], session['c_cwsweep_structure'])
except (ValueError):
print(Back.RED + Fore.WHITE + "All parameters must be FIXED!")
pass
return jsonify(data_location=data_location)
def assembler_xyfreq_fluxbias(args):
(y, x) = args
I, Q = 0, 0
for i_prepeat in range(powa_repeat):
r_powa = int(
ipowa
) * powa_repeat + i_prepeat # from the beginning position of repeating power
I += selectedata[gotocdata([
int(irepeat), x, y,
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa
], c_cwsweep_structure)]
Q += selectedata[gotocdata([
int(irepeat), x, y,
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa + 1
], c_cwsweep_structure)]
I /= powa_repeat
Q /= powa_repeat
Amp, P = IQAP(I, Q)
return I, Q, Amp, P
def f(args):
# (x,y) = args
I = A[gotocdata([args[0], 0, 0, 0, 2 * args[1]],
[10000, 1, 1, 1, 1000 * 2])]
Q = A[gotocdata([args[0], 0, 0, 0, 2 * args[1] + 1],
[10000, 1, 1, 1, 1000 * 2])]
Amp, P = IQAP(I, Q)
return I, Q, Amp, P
def assembler_freq_powa(args):
(y, x) = args
I = selectedata[gotocdata(
[int(ifluxbias), int(isparam),
int(iifb), x, 2 * y], c_fresp_structure)]
Q = selectedata[gotocdata(
[int(ifluxbias), int(isparam),
int(iifb), x, 2 * y + 1], c_fresp_structure)]
Amp, P = IQAP(I, Q)
return I, Q, Amp, P
def g(a):
A = list(range(200000000))
B = [
A[gotocdata([x, 0, 0, 0, a], [20000, 1, 1, 1, 10000])]
for x in range(20000)
]
return B
caddress = '[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,t]' #bare
# caddress = '[0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,t]' #dressed
# replacing x-variable:
caddress = caddress[:2 * CStructure.index(X[X_option]) +
1] + 'i' + caddress[2 * CStructure.index(X[X_option]) +
2:]
# replacing c-constant:
caddress = caddress[:2 * CStructure.index(C[C_option]) +
1] + C_index + caddress[2 *
CStructure.index(C[C_option]) +
2:]
print("C-Address: %s" % (caddress))
# Sweep first curve to decide:
IQdata = array([
alldata[gotocdata([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, x],
cstructure)] for x in timesweep
])
I, Q, Amp, Pha = IQAParray(IQdata)
A = [sqrt(i**2 + q**2) for (i, q) in zip(I, Q)] # slower iteration
# select which range you need from the curve:
curve(range(len(I)), I, 'Pick the start-end point:', '#', 'A(V)')
curve(range(len(Q)), Q, 'Pick the start-end point:', '#', 'A(V)')
curve(range(len(A)), A, 'Pick the start-end point:', '#', 'A(V)')
# assemble the analytics
startpoint = int(input("Reading the measured pulse from: "))
endpoint = int(input("Reading the measured pulse until: "))
firstpoint = int(input('Total %s points, plot from: ' % len(xdata)))
lastpoint = int(input('Total %s points, plot until: ' % len(xdata)))
# Start post-averaging:
def assembler(args):
(y,x) = args
selected_caddress = [s for s in cselect.values()]
# Sweep-command:
if k == 'repeat':
selected_sweep = cmd_repeat[session['user_name']]
else:
selected_sweep = M_sqepulse[session['user_name']].corder[k]
# Adjusting c-parameters range for data analysis based on progress:
parent_address = selected_caddress[:CParameters['SQE_Pulse'].index(k)] # address's part before x
if [int(s) for s in parent_address] < session['c_sqepulse_progress'][0:len(parent_address)]:
print(Fore.YELLOW + "selection is well within progress")
sweepables = session['c_sqepulse_structure'][CParameters['SQE_Pulse'].index(k)]
else: sweepables = session['c_sqepulse_progress'][CParameters['SQE_Pulse'].index(k)]+1
# Special treatment on the last 'buffer' parameter to factor out the data-density first:
if CParameters['SQE_Pulse'].index(k) == len(CParameters['SQE_Pulse'])-1 :
isweep = range(sweepables//M_sqepulse[session['user_name']].datadensity)
else:
isweep = range(sweepables) # flexible access until progress resume-point
print(Back.WHITE + Fore.BLACK + "Sweeping %s points" %len(isweep))
Idata = zeros(len(isweep))
Qdata = zeros(len(isweep))
for i in isweep:
selected_caddress[CParameters['SQE_Pulse'].index(k)] = i # register x-th position
if [c for c in cselect.values()][-1] == "s": # sampling mode currently limited to time-range (last 'basic' parameter) only
srange = request.args.get('srange').split("-") # sample range
if [int(srange[1]) , int(srange[0])] > [session['c_sqepulse_structure'][-1]//M_sqepulse[session['user_name']].datadensity] * 2:
print(Back.WHITE + Fore.RED + "Out of range")
else:
# FASTEST PARALLEL VECTORIZATION OF BIG DATA BY NUMPY:
slength = int(srange[1]) - int(srange[0]) + 1
# Assemble stacks of selected c-address for this sample range:
selected_caddress_I = array([[int(s) for s in selected_caddress[:-1]] + [0]] * slength)
selected_caddress_Q = array([[int(s) for s in selected_caddress[:-1]] + [0]] * slength)
# sort-out interleaved IQ:
selected_caddress_I[:,-1] = 2 * array(range(int(srange[0]),int(srange[1])+1))
selected_caddress_Q[:,-1] = 2 * array(range(int(srange[0]),int(srange[1])+1)) + ones(slength)
# Compressing I & Q of this sample range:
selectedata = array(selectedata)
Idata[i] = mean(selectedata[gotocdata(selected_caddress_I, session['c_sqepulse_structure'])]-0)
Qdata[i] = mean(selectedata[gotocdata(selected_caddress_Q, session['c_sqepulse_structure'])]-0)
else:
# Ground level Pulse shape response:
selected_caddress = [int(s) for s in selected_caddress]
Basic = selected_caddress[-1]
# Extracting I & Q:
Idata[i] = selectedata[gotocdata(selected_caddress[:-1]+[2*Basic], session['c_sqepulse_structure'])]
Qdata[i] = selectedata[gotocdata(selected_caddress[:-1]+[2*Basic+1], session['c_sqepulse_structure'])]
I, Q = 0, 0
for i_prepeat in range(powa_repeat):
r_powa = int(ipowa) * powa_repeat + i_prepeat # from the beginning position of repeating power
I += selectedata[gotocdata([x,y,int(ixyfreq),int(ixypowa),int(isparam),int(iifb),int(ifreq),2*r_powa],c_cwsweep_structure)]
Q += selectedata[gotocdata([x,y,int(ixyfreq),int(ixypowa),int(isparam),int(iifb),int(ifreq),2*r_powa+1],c_cwsweep_structure)]
I /= powa_repeat
Q /= powa_repeat
Amp,P = IQAP(I,Q)
return I, Q, Amp, P
def char_cwsweep_1ddata():
print(Fore.GREEN + "User %s is plotting 1D-Data" % session['user_name'])
M_cwsweep[session['user_name']].loadata()
selectedata = M_cwsweep[session['user_name']].selectedata
# load parameter indexes from json call:
irepeat = request.args.get('irepeat')
ifluxbias = request.args.get('ifluxbias')
ixyfreq = request.args.get('ixyfreq')
ixypowa = request.args.get('ixypowa')
isparam = request.args.get('isparam')
iifb = request.args.get('iifb')
ifreq = request.args.get('ifreq')
ipowa = request.args.get('ipowa')
# pre-transform ipowa:
xpowa = waveform(M_cwsweep[session['user_name']].corder['Power'])
ipowa_repeat = xpowa.inner_repeat
# selecting data:
if "x" in ifluxbias:
xtitle = "<b>Flux-Bias(V/A)</b>"
selected_sweep = M_cwsweep[session['user_name']].corder['Flux-Bias']
if int(irepeat
) < session['c_cwsweep_address'][0]: # address's part before x
# print("Well within Progress!")
xsweep = range(
session['c_cwsweep_structure'][1]
) # can access full-range if selection is well within progress resume-point
else:
xsweep = range(session['c_cwsweep_address'][1] +
1) # can only access until progress resume-point
selected_Ir, selected_Qr = [], []
for i_prepeat in range(ipowa_repeat):
r_powa = int(
ipowa
) * ipowa_repeat + i_prepeat # from the beginning position of repeating power
selected_Ir += [
selectedata[gotocdata([
int(irepeat), x,
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa
], session['c_cwsweep_structure'])] for x in xsweep
]
selected_Qr += [
selectedata[gotocdata([
int(irepeat), x,
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa + 1
], session['c_cwsweep_structure'])] for x in xsweep
]
# AVERAGE up those power repeats:
selected_I = list(
mean(array(selected_Ir).reshape(ipowa_repeat, len(xsweep)),
axis=0))
selected_Q = list(
mean(array(selected_Qr).reshape(ipowa_repeat, len(xsweep)),
axis=0))
elif "x" in ixyfreq:
xtitle = "<b>XY-Frequency(GHz)</b>"
selected_sweep = M_cwsweep[session['user_name']].corder['XY-Frequency']
if [int(irepeat), int(ifluxbias)
] < session['c_cwsweep_address'][0:2]: # address's part before x
xsweep = range(
session['c_cwsweep_structure'][2]
) # can access full-range if selection is well within progress resume-point
else:
xsweep = range(session['c_cwsweep_address'][2] +
1) # can only access until progress resume-point
selected_Ir, selected_Qr = [], []
for i_prepeat in range(ipowa_repeat):
r_powa = int(
ipowa
) * ipowa_repeat + i_prepeat # from the beginning position of repeating power
selected_Ir += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias), x,
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa
], session['c_cwsweep_structure'])] for x in xsweep
]
selected_Qr += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias), x,
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa + 1
], session['c_cwsweep_structure'])] for x in xsweep
]
# AVERAGE up those power repeats:
selected_I = list(
mean(array(selected_Ir).reshape(ipowa_repeat, len(xsweep)),
axis=0))
selected_Q = list(
mean(array(selected_Qr).reshape(ipowa_repeat, len(xsweep)),
axis=0))
elif "x" in ixypowa:
xtitle = "<b>XY-Power(dBm)</b>"
selected_sweep = M_cwsweep[session['user_name']].corder['XY-Power']
if [int(irepeat), int(ifluxbias),
int(ixyfreq)
] < session['c_cwsweep_address'][0:3]: # address's part before x
xsweep = range(
session['c_cwsweep_structure'][3]
) # can access full-range if selection is well within progress resume-point
else:
xsweep = range(session['c_cwsweep_address'][3] +
1) # can only access until progress resume-point
selected_Ir, selected_Qr = [], []
for i_prepeat in range(ipowa_repeat):
r_powa = int(
ipowa
) * ipowa_repeat + i_prepeat # from the beginning position of repeating power
selected_Ir += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq), x,
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa
], session['c_cwsweep_structure'])] for x in xsweep
]
selected_Qr += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq), x,
int(isparam),
int(iifb),
int(ifreq), 2 * r_powa + 1
], session['c_cwsweep_structure'])] for x in xsweep
]
# AVERAGE up those power repeats:
selected_I = list(
mean(array(selected_Ir).reshape(ipowa_repeat, len(xsweep)),
axis=0))
selected_Q = list(
mean(array(selected_Qr).reshape(ipowa_repeat, len(xsweep)),
axis=0))
elif "x" in isparam:
pass
elif "x" in iifb:
pass
elif "x" in ifreq:
xtitle = "<b>frequency(GHz)</b>"
selected_sweep = M_cwsweep[session['user_name']].corder['Frequency']
if [
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb)
] < session['c_cwsweep_address'][0:6]: # address's part before x
xsweep = range(
session['c_cwsweep_structure'][6]
) # can access full-range if selection is well within progress resume-point
else:
xsweep = range(session['c_cwsweep_address'][6] +
1) # can only access until progress resume-point
selected_Ir, selected_Qr = [], []
for i_prepeat in range(ipowa_repeat):
r_powa = int(
ipowa
) * ipowa_repeat + i_prepeat # from the beginning position of repeating power
selected_Ir += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb), x, 2 * r_powa
], session['c_cwsweep_structure'])] for x in xsweep
]
selected_Qr += [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb), x, 2 * r_powa + 1
], session['c_cwsweep_structure'])] for x in xsweep
]
# AVERAGE up those power repeats:
selected_I = list(
mean(array(selected_Ir).reshape(ipowa_repeat, len(xsweep)),
axis=0))
selected_Q = list(
mean(array(selected_Qr).reshape(ipowa_repeat, len(xsweep)),
axis=0))
elif "x" in ipowa:
xtitle = "<b>Power(dBm)</b>"
xpowa_repeat = ipowa_repeat
if [
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq)
] < session['c_cwsweep_address'][0:7]: # address's part before x
xsweep = range(
session['c_cwsweep_structure'][7] // 2
) # can access full-range if selection is well within progress resume-point
else:
xsweep = range((session['c_cwsweep_address'][7] + 1) //
2) # can only access until progress resume-point
selected_Ir = [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * x
], session['c_cwsweep_structure'])] for x in xsweep
]
selected_Qr = [
selectedata[gotocdata([
int(irepeat),
int(ifluxbias),
int(ixyfreq),
int(ixypowa),
int(isparam),
int(iifb),
int(ifreq), 2 * x + 1
], session['c_cwsweep_structure'])] for x in xsweep
]
# AVERAGE up those repeated IQ-pairs:
selected_I = list(
mean(array(selected_Ir).reshape(
len(xsweep) // xpowa_repeat, xpowa_repeat),
axis=1)) #-->
selected_Q = list(
mean(array(selected_Qr).reshape(
len(xsweep) // xpowa_repeat, xpowa_repeat),
axis=1)) #-->
# preparing data:
# assembly amplitude & phase:
MagPha = [IQAP(x[0], x[1]) for x in zip(selected_I, selected_Q)]
Amp, Pha = [], []
for i, j in MagPha:
Amp.append(i)
Pha.append(j)
# x-range:
if "x" in ipowa:
selected_progress = xpowa.data[0:(len(xsweep) // xpowa_repeat)]
else:
selected_progress = waveform(selected_sweep).data[0:len(xsweep)]
# to avoid exception when encountering recursive parameters:
if "c" in ixyfreq + ixypowa + ifluxbias + isparam + iifb + ifreq + ipowa:
selected_progress = list(range(len(selected_progress)))
x1, y1, yup, yp = selected_progress, Amp, list(
UnwraPhase(selected_progress, Pha)), Pha #list(unwrap(Pha))
global data_dict
data_dict = {
xtitle: x1,
'Amplitude': y1,
'UPhase': yup,
'I': selected_I,
'Q': selected_Q,
"exported by": session['user_name']
}
return jsonify(x1=x1, y1=y1, yup=yup, yp=yp, x1title=xtitle)
def char_fresp_1ddata():
print(Fore.GREEN + "User %s is plotting 1D-Data" % session['user_name'])
M_fresp[session['user_name']].loadata()
selectedata = M_fresp[session['user_name']].selectedata
ifluxbias = request.args.get('ifluxbias')
# if ifluxbias == "o": ifluxbias = '0' # for backward compatibility
isparam = request.args.get('isparam')
iifb = request.args.get('iifb')
ipowa = request.args.get('ipowa')
ifreq = request.args.get('ifreq')
# selecting data
if ifluxbias == "x":
title = "<b>Flux-Bias(V)</b>"
selected_sweep = M_fresp[session['user_name']].corder['Flux-Bias']
selected_progress = waveform(
selected_sweep).data[0:session['c_fresp_address'][0] + 1]
selected_I = [
selectedata[gotocdata(
[x, int(isparam),
int(iifb),
int(ipowa), 2 * int(ifreq)], session['c_fresp_structure'])]
for x in range(session['c_fresp_address'][0] + 1)
]
selected_Q = [
selectedata[gotocdata(
[x, int(isparam),
int(iifb),
int(ipowa), 2 * int(ifreq) + 1],
session['c_fresp_structure'])]
for x in range(session['c_fresp_address'][0] + 1)
]
elif isparam == "x":
pass
elif iifb == "x":
pass
elif ipowa == "x":
title = "<b>Power(dBm)</b>"
selected_sweep = M_fresp[session['user_name']].corder['Power']
selected_progress = waveform(
selected_sweep).data[0:session['c_fresp_address'][3] + 1]
selected_I = [
selectedata[gotocdata(
[int(ifluxbias),
int(isparam),
int(iifb), x, 2 * int(ifreq)], session['c_fresp_structure'])]
for x in range(session['c_fresp_address'][3] + 1)
]
selected_Q = [
selectedata[gotocdata([
int(ifluxbias),
int(isparam),
int(iifb), x, 2 * int(ifreq) + 1
], session['c_fresp_structure'])]
for x in range(session['c_fresp_address'][3] + 1)
]
elif ifreq == "x":
title = "<b>frequency(GHz)</b>"
selected_sweep = M_fresp[session['user_name']].corder['Frequency']
selected_progress = waveform(selected_sweep).data # Full sweep
selected_I = [
selectedata[gotocdata(
[int(ifluxbias),
int(isparam),
int(iifb),
int(ipowa), 2 * x], session['c_fresp_structure'])]
for x in range(waveform(selected_sweep).count)
]
selected_Q = [
selectedata[gotocdata([
int(ifluxbias),
int(isparam),
int(iifb),
int(ipowa), 2 * x + 1
], session['c_fresp_structure'])]
for x in range(waveform(selected_sweep).count)
]
# Preparing data:
MagPha = [IQAP(x[0], x[1]) for x in zip(selected_I, selected_Q)]
Amp, Pha = [], []
for i, j in MagPha:
Amp.append(i)
Pha.append(j)
x1, y1, y2 = selected_progress, Amp, list(
UnwraPhase(selected_progress, Pha)) #list(unwrap(Pha))
global data_dict
data_dict = {
title: x1,
'Amplitude': y1,
'UPhase': y2,
'I': selected_I,
'Q': selected_Q,
"exported by": session['user_name']
}
return jsonify(x1=x1, y1=y1, y2=y2, title=title)
case.loadata()
selectedata = case.selectedata
X = cxyfreq.data
Y = cfluxbias.data[7:38]
AMP, PHA = [], []
for i_flux in range(7, 38):
print("retrieving Flux #%s/49" % (i_flux + 1))
# pre-transform ipowa:
ipowa_repeat = waveform(case.corder['Power']).inner_repeat
# print("repeating power at %s times" %ipowa_repeat)
selected_Ir, selected_Qr = [], []
for i_repeat in range(ipowa_repeat):
r_powa = 0 * ipowa_repeat + i_repeat # from the beginning position of repeating power
selected_Ir += [
selectedata[gotocdata([i_flux, x, 0, 0, 0, 0, 2 * r_powa],
c_cwsweep_structure)]
for x in range(cxyfreq.count)
]
selected_Qr += [
selectedata[gotocdata([i_flux, x, 0, 0, 0, 0, 2 * r_powa + 1],
c_cwsweep_structure)]
for x in range(cxyfreq.count)
]
# AVERAGE up those power repeats:
selected_I = list(
mean(array(selected_Ir).reshape(ipowa_repeat, cxyfreq.count), axis=0))
selected_Q = list(
mean(array(selected_Qr).reshape(ipowa_repeat, cxyfreq.count), axis=0))
# assembly amplitude & phase:
MagPha = [IQAP(x[0], x[1]) for x in zip(selected_I, selected_Q)]