def pulse2op(pulse_obj, gyratio, pname, spin_system, obs_iso, offset=0.0):
"""
A Vespa-Simulation pulse object is passed in via pulse_obj input. The
gyratio input is a float gyromagnetic ratio, pname is a string name for
the pulse waveform creates, obs_iso is a string indicating the isotope
being affected (e.g. '1H') and offset is a float value in Hz for how
far the complex Vespa pulse object waveform should be shifted from its
resonance value at 0.0 ppm/Hz. For example, we would need to shift a
pulse by 4.7ppm (converted to Hz) in order to center an RF pulse on water
for a typical simulation.
PulWaveform expects Hz amplitude and angle in degrees, while
Simulation gives us mT amplitude and angle in radians.
We need to use the appropriate gyromagnetic ratio to do the
conversion. This depends on our observe_isotope, since the pulse
is not isotope specific, but the spins we expect it to affect,
is. (e.g. we use 42576.0 for 1H to covert mT and RAD2DEG for phase)
"""
step = float(pulse_obj['dwell_time']) * 1e-6 # in usec
wave = pulse_obj['waveform']
wave = np.array(wave)
ampl = np.abs(wave) * gyratio
phas = np.angle(wave) * 180.0 / np.pi # in radians
pulse = pg.row_vector(len(wave))
ptime = pg.row_vector(len(wave))
for j, val in enumerate(zip(ampl, phas)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(step, 0), j)
plength = pulse.size() * step # total pulse duration
if offset != 0.0:
# typically offset should be 0.0 or negative
pulse = pg.pulseshift(pulse, ptime, offset)
pwave = pg.PulWaveform(pulse, ptime, pname)
pcomp = pg.PulComposite(pwave, spin_system, obs_iso)
pulse_op = pcomp.GetUsum(-1)
return pulse_op, plength
t1 = 0.025
t2 = 0.025
pulsestep = 0.00001
sys.read(insysfile)
specfreq = sys.Omega()
# read_pulse replaces ReadPulse() and is a static member of row_vector
pulse = pg.row_vector.read_pulse(inpulse180file, pg.row_vector.ASCII_MT_DEG)
ptime = pg.row_vector(pulse.size())
#need to use pg.complex() so it can find correct function to call.
for j in range(pulse.size()):
ptime.put(pg.complex(pulsestep, 0), j)
pwf = pg.PulWaveform(pulse, ptime, "TestPulse")
pulc = pg.PulComposite(pwf, sys, "1H")
H = pg.Hcs(sys) + pg.HJ(sys)
D = pg.Fm(sys)
Udelay1 = pg.prop(H, t1)
Udelay2 = pg.prop(H, t2)
# Neet to effectively typecast D as a gen_op.
ac = pg.acquire1D(pg.gen_op(D), H, 0.001)
ACQ = ac
t1 = 0.025
t2 = 0.025
pulsestep = 0.00001
sys.read(insysfile)
specfreq = sys.Omega()
# read_pulse replaces ReadPulse() and is a static member of row_vector
pulse = pg.row_vector.read_pulse(inpulse180file, pg.row_vector.ASCII_MT_DEG)
ptime = pg.row_vector(pulse.size())
#need to use pg.complex() so it can find correct function to call.
for j in range(pulse.size()):
ptime.put(pg.complex(pulsestep, 0), j)
pwf = pg.PulWaveform(pulse, ptime, "TestPulse")
pulc = pg.PulComposite(pwf, sys, "1H")
H = pg.Hcs(sys) + pg.HJ(sys);
D = pg.Fm(sys);
Udelay1 = pg.prop(H, t1);
Udelay2 = pg.prop(H, t2);
# Neet to effectively typecast D as a gen_op.
ac = pg.acquire1D(pg.gen_op(D), H, 0.001)
ACQ = ac;
def simulate(self):
self.postToConsole.emit(' | Simulating ... ' + self.insysfile)
print(' | Simulating ...' + self.insysfile)
metab_name = self.insysfile.replace('.sys', '')
if self.sim_experiment.b0 == 123.3:
self.insysfile = 'pints/metabolites/3T_' + self.insysfile
elif self.sim_experiment.b0 == 297.2:
self.insysfile = 'pints/metabolites/7T_' + self.insysfile
elif self.sim_experiment.b0 == 400.2:
self.insysfile = 'pints/metabolites/9.4T_' + self.insysfile
if self.sim_experiment.name == "semi-LASER (Bruker)":
spin_system = pg.spin_system()
spin_system.read(self.insysfile)
for i in range(spin_system.spins()):
spin_system.PPM(
i,
spin_system.PPM(i) - self.sim_experiment.RF_OFFSET)
TE = self.sim_experiment.TE * 1E-3
TE1 = self.sim_experiment.TE1 * 1E-3
TE2 = self.sim_experiment.TE2 * 1E-3
# build 90 degree pulse
inpulse90file = self.sim_experiment.inpulse90file
A_90 = self.sim_experiment.A_90
PULSE_90_LENGTH = self.sim_experiment.PULSE_90_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse90 = Pulse(inpulse90file, PULSE_90_LENGTH, 'bruker')
n_old = np.linspace(0, PULSE_90_LENGTH, sp.size(pulse90.waveform))
n_new = np.linspace(0, PULSE_90_LENGTH,
sp.size(pulse90.waveform) + 1)
waveform_real = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.real(pulse90.waveform) * A_90)(n_new)
waveform_imag = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.imag(pulse90.waveform) * A_90)(n_new)
pulse90.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse90.waveform)
phas_arr = np.unwrap(np.angle(pulse90.waveform)) * 180.0 / math.pi
pulse = pg.row_vector(len(pulse90.waveform))
ptime = pg.row_vector(len(pulse90.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(pulse90.pulsestep, 0), j)
pulse_dur_90 = pulse.size() * pulse90.pulsestep
pwf_90 = pg.PulWaveform(pulse, ptime, "90excite")
pulc_90 = pg.PulComposite(pwf_90, spin_system,
self.sim_experiment.obs_iso)
Ureal90 = pulc_90.GetUsum(-1)
# build 180 degree pulse
inpulse180file = self.sim_experiment.inpulse180file
A_180 = self.sim_experiment.A_180
PULSE_180_LENGTH = self.sim_experiment.PULSE_180_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse180 = Pulse(inpulse180file, PULSE_180_LENGTH, 'bruker')
n_old = np.linspace(0, PULSE_180_LENGTH,
sp.size(pulse180.waveform))
n_new = np.linspace(0, PULSE_180_LENGTH,
sp.size(pulse180.waveform) + 1)
waveform_real = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.real(pulse180.waveform) * A_180)(n_new)
waveform_imag = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.imag(pulse180.waveform) * A_180)(n_new)
pulse180.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse180.waveform)
phas_arr = np.unwrap(np.angle(pulse180.waveform)) * 180.0 / math.pi
freq_arr = np.gradient(phas_arr)
pulse = pg.row_vector(len(pulse180.waveform))
ptime = pg.row_vector(len(pulse180.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(n_new[1], 0), j)
pulse_dur_180 = pulse.size() * pulse180.pulsestep
pwf_180 = pg.PulWaveform(pulse, ptime, "180afp")
pulc_180 = pg.PulComposite(pwf_180, spin_system,
self.sim_experiment.obs_iso)
Ureal180 = pulc_180.GetUsum(-1)
H = pg.Hcs(spin_system) + pg.HJ(spin_system)
D = pg.Fm(spin_system, self.sim_experiment.obs_iso)
ac = pg.acquire1D(pg.gen_op(D), H, self.sim_experiment.dwell_time)
ACQ = ac
delay1 = TE1 / 2.0 - pulse_dur_90 / 2.0 - pulse_dur_180 / 2.0
delay2 = TE1 / 2.0 + TE2 / 2.0 - pulse_dur_180
delay3 = TE2 - pulse_dur_180
delay4 = delay2
delay5 = TE1 / 2.0 - pulse_dur_180 + self.sim_experiment.DigShift
Udelay1 = pg.prop(H, delay1)
Udelay2 = pg.prop(H, delay2)
Udelay3 = pg.prop(H, delay3)
Udelay4 = pg.prop(H, delay4)
Udelay5 = pg.prop(H, delay5)
sigma0 = pg.sigma_eq(spin_system) # init
sigma1 = Ureal90.evolve(sigma0) # apply 90-degree pulse
sigma0 = pg.evolve(sigma1, Udelay1)
sigma1 = Ureal180.evolve(sigma0) # apply AFP1
sigma0 = pg.evolve(sigma1, Udelay2)
sigma1 = Ureal180.evolve(sigma0) # apply AFP2
sigma0 = pg.evolve(sigma1, Udelay3)
sigma1 = Ureal180.evolve(sigma0) # apply AFP3
sigma0 = pg.evolve(sigma1, Udelay4)
sigma1 = Ureal180.evolve(sigma0) # apply AFP4
sigma0 = pg.evolve(sigma1, Udelay5)
elif self.sim_experiment.name == "semi-LASER":
spin_system = pg.spin_system()
spin_system.read(self.insysfile)
for i in range(spin_system.spins()):
spin_system.PPM(
i,
spin_system.PPM(i) - self.sim_experiment.RF_OFFSET)
TE = self.sim_experiment.TE
TE1 = float((TE * 0.31) / 1000.0)
TE3 = float((TE * 0.31) / 1000.0)
TE2 = float(TE / 1000.0 - TE1 - TE3)
TE_fill = TE / 1000.0 - TE1 - TE2 - TE3
# build 90 degree pulse
inpulse90file = self.sim_experiment.inpulse90file
A_90 = self.sim_experiment.A_90
PULSE_90_LENGTH = self.sim_experiment.PULSE_90_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse90 = Pulse(inpulse90file, PULSE_90_LENGTH)
n_old = np.linspace(0, PULSE_90_LENGTH, sp.size(pulse90.waveform))
n_new = np.linspace(0, PULSE_90_LENGTH,
sp.size(pulse90.waveform) + 1)
waveform_real = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.real(pulse90.waveform) * A_90)(n_new)
waveform_imag = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.imag(pulse90.waveform) * A_90)(n_new)
pulse90.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse90.waveform) * gyratio
phas_arr = np.unwrap(np.angle(pulse90.waveform)) * 180.0 / math.pi
pulse = pg.row_vector(len(pulse90.waveform))
ptime = pg.row_vector(len(pulse90.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(pulse90.pulsestep, 0), j)
pulse_dur_90 = pulse.size() * pulse90.pulsestep
peak_to_end_90 = pulse_dur_90 - (
209 + self.sim_experiment.fudge_factor) * pulse90.pulsestep
pwf_90 = pg.PulWaveform(pulse, ptime, "90excite")
pulc_90 = pg.PulComposite(pwf_90, spin_system,
self.sim_experiment.obs_iso)
Ureal90 = pulc_90.GetUsum(-1)
# build 180 degree pulse
inpulse180file = self.sim_experiment.inpulse180file
A_180 = self.sim_experiment.A_180
PULSE_180_LENGTH = self.sim_experiment.PULSE_180_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse180 = Pulse(inpulse180file, PULSE_180_LENGTH)
n_old = np.linspace(0, PULSE_180_LENGTH,
sp.size(pulse180.waveform))
n_new = np.linspace(0, PULSE_180_LENGTH,
sp.size(pulse180.waveform) + 1)
waveform_real = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.real(pulse180.waveform) * A_180)(n_new)
waveform_imag = sp.interpolate.InterpolatedUnivariateSpline(
n_old,
np.imag(pulse180.waveform) * A_180)(n_new)
pulse180.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse180.waveform) * gyratio
phas_arr = np.unwrap(np.angle(pulse180.waveform)) * 180.0 / math.pi
freq_arr = np.gradient(phas_arr)
pulse = pg.row_vector(len(pulse180.waveform))
ptime = pg.row_vector(len(pulse180.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(n_new[1], 0), j)
pulse_dur_180 = pulse.size() * pulse180.pulsestep
pwf_180 = pg.PulWaveform(pulse, ptime, "180afp")
pulc_180 = pg.PulComposite(pwf_180, spin_system,
self.sim_experiment.obs_iso)
Ureal180 = pulc_180.GetUsum(-1)
H = pg.Hcs(spin_system) + pg.HJ(spin_system)
D = pg.Fm(spin_system, self.sim_experiment.obs_iso)
ac = pg.acquire1D(pg.gen_op(D), H, self.sim_experiment.dwell_time)
ACQ = ac
delay1 = TE1 / 2.0 + TE_fill / 8.0 - pulse_dur_180 / 2.0 - peak_to_end_90
delay2 = TE1 / 2.0 + TE_fill / 8.0 + TE2 / 4.0 + TE_fill / 8.0 - pulse_dur_180
delay3 = TE2 / 4.0 + TE_fill / 8.0 + TE2 / 4.0 + TE_fill / 8.0 - pulse_dur_180
delay4 = TE2 / 4.0 + TE_fill / 8.0 + TE3 / 2.0 + TE_fill / 8.0 - pulse_dur_180
delay5 = TE3 / 2.0 + TE_fill / 8.0 - pulse_dur_180 / 2.0
Udelay1 = pg.prop(H, delay1)
Udelay2 = pg.prop(H, delay2)
Udelay3 = pg.prop(H, delay3)
Udelay4 = pg.prop(H, delay4)
Udelay5 = pg.prop(H, delay5)
sigma0 = pg.sigma_eq(spin_system) # init
sigma1 = Ureal90.evolve(sigma0) # apply 90-degree pulse
sigma0 = pg.evolve(sigma1, Udelay1)
sigma1 = Ureal180.evolve(sigma0) # apply AFP1
sigma0 = pg.evolve(sigma1, Udelay2)
sigma1 = Ureal180.evolve(sigma0) # apply AFP2
sigma0 = pg.evolve(sigma1, Udelay3)
sigma1 = Ureal180.evolve(sigma0) # apply AFP3
sigma0 = pg.evolve(sigma1, Udelay4)
sigma1 = Ureal180.evolve(sigma0) # apply AFP4
sigma0 = pg.evolve(sigma1, Udelay5)
elif self.sim_experiment.name == "LASER":
spin_system = pg.spin_system()
spin_system.read(self.insysfile)
for i in range(spin_system.spins()):
spin_system.PPM(
i,
spin_system.PPM(i) - self.sim_experiment.RF_OFFSET)
# build 90 degree AHP pulse
inpulse90file = self.sim_experiment.inpulse90file
A_90 = self.sim_experiment.A_90
PULSE_90_LENGTH = self.sim_experiment.PULSE_90_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse90 = Pulse(inpulse90file, PULSE_90_LENGTH, 'varian')
n_new = np.linspace(0, PULSE_90_LENGTH, 256)
waveform_real = np.real(pulse90.waveform) * A_90
waveform_imag = np.imag(pulse90.waveform) * A_90
pulse90.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse90.waveform) * gyratio
phas_arr = np.unwrap(np.angle(pulse90.waveform)) * 180.0 / math.pi
pulse = pg.row_vector(len(pulse90.waveform))
ptime = pg.row_vector(len(pulse90.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(pulse90.pulsestep, 0), j)
pulse_dur_90 = pulse.size() * pulse90.pulsestep
pwf_90 = pg.PulWaveform(pulse, ptime, "90excite")
pulc_90 = pg.PulComposite(pwf_90, spin_system,
self.sim_experiment.obs_iso)
Ureal90 = pulc_90.GetUsum(-1)
# build 180 degree pulse
inpulse180file = self.sim_experiment.inpulse180file
A_180 = self.sim_experiment.A_180
PULSE_180_LENGTH = self.sim_experiment.PULSE_180_LENGTH
gyratio = self.sim_experiment.getGyratio()
pulse180 = Pulse(inpulse180file, PULSE_180_LENGTH, 'varian')
n_new = np.linspace(0, PULSE_180_LENGTH, 512)
waveform_real = np.real(pulse180.waveform) * A_180
waveform_imag = np.imag(pulse180.waveform) * A_180
pulse180.waveform = waveform_real + 1j * (waveform_imag)
ampl_arr = np.abs(pulse180.waveform) * gyratio
phas_arr = np.unwrap(np.angle(pulse180.waveform)) * 180.0 / math.pi
freq_arr = np.gradient(phas_arr)
pulse = pg.row_vector(len(pulse180.waveform))
ptime = pg.row_vector(len(pulse180.waveform))
for j, val in enumerate(zip(ampl_arr, phas_arr)):
pulse.put(pg.complex(val[0], val[1]), j)
ptime.put(pg.complex(n_new[1], 0), j)
pulse_dur_180 = pulse.size() * pulse180.pulsestep
pwf_180 = pg.PulWaveform(pulse, ptime, "180afp")
pulc_180 = pg.PulComposite(pwf_180, spin_system,
self.sim_experiment.obs_iso)
Ureal180 = pulc_180.GetUsum(-1)
# calculate pulse timings
ROF1 = 100E-6 #sec
ROF2 = 10E-6 #sec
TCRUSH1 = 0.0008 #sec
TCRUSH2 = 0.0008 #sec
ss_grad_rfDelayFront = 0 #TCRUSH1 - ROF1
ss_grad_rfDelayBack = 0 #TCRUSH2 - ROF2
ro_grad_atDelayFront = 0
ro_grad_atDelayBack = 0
TE = self.sim_experiment.TE / 1000.
ipd = (TE - pulse_dur_90 \
- 6*(ss_grad_rfDelayFront + pulse_dur_180 + ss_grad_rfDelayBack) \
- ro_grad_atDelayFront) / 12
delay1 = ipd + ss_grad_rfDelayFront
delay2 = ss_grad_rfDelayBack + 2 * ipd + ss_grad_rfDelayFront
delay3 = ss_grad_rfDelayBack + 2 * ipd + ss_grad_rfDelayFront
delay4 = ss_grad_rfDelayBack + 2 * ipd + ss_grad_rfDelayFront
delay5 = ss_grad_rfDelayBack + 2 * ipd + ss_grad_rfDelayFront
delay6 = ss_grad_rfDelayBack + 2 * ipd + ss_grad_rfDelayFront
delay7 = ss_grad_rfDelayBack + ipd + ro_grad_atDelayFront
# print A_90, A_180, pulse_dur_90, pulse_dur_180
# print TE, ipd, pulse_dur_90+6*pulse_dur_180, delay1+delay2+delay3+delay4+delay5+delay6+delay7, pulse_dur_90+6*pulse_dur_180+delay1+delay2+delay3+delay4+delay5+delay6+delay7
# print ''
# initialize acquisition
H = pg.Hcs(spin_system) + pg.HJ(spin_system)
D = pg.Fm(spin_system, self.sim_experiment.obs_iso)
ac = pg.acquire1D(pg.gen_op(D), H, self.sim_experiment.dwell_time)
ACQ = ac
Udelay1 = pg.prop(H, delay1)
Udelay2 = pg.prop(H, delay2)
Udelay3 = pg.prop(H, delay3)
Udelay4 = pg.prop(H, delay4)
Udelay5 = pg.prop(H, delay5)
Udelay6 = pg.prop(H, delay6)
Udelay7 = pg.prop(H, delay7)
sigma0 = pg.sigma_eq(spin_system) # init
sigma1 = Ureal90.evolve(sigma0) # apply 90-degree pulse
sigma0 = pg.evolve(sigma1, Udelay1)
sigma1 = Ureal180.evolve(sigma0) # apply AFP1
sigma0 = pg.evolve(sigma1, Udelay2)
sigma1 = Ureal180.evolve(sigma0) # apply AFP2
sigma0 = pg.evolve(sigma1, Udelay3)
sigma1 = Ureal180.evolve(sigma0) # apply AFP3
sigma0 = pg.evolve(sigma1, Udelay4)
sigma1 = Ureal180.evolve(sigma0) # apply AFP4
sigma0 = pg.evolve(sigma1, Udelay5)
sigma1 = Ureal180.evolve(sigma0) # apply AFP5
sigma0 = pg.evolve(sigma1, Udelay6)
sigma1 = Ureal180.evolve(sigma0) # apply AFP6
sigma0 = pg.evolve(sigma1, Udelay7)
# acquire
mx = pg.TTable1D(ACQ.table(sigma0))
# binning to remove degenerate peaks
# BINNING
# Note: Metabolite Peak Normalization and Blending
# The transition tables calculated by the GAMMA density matrix simulations frequently contain a
# large number of transitions caused by degenerate splittings and other processes. At the
# conclusion of each simulation run a routine is called to extract lines from the transition table.
# These lines are then normalized using a closed form calculation based on the number of spins.
# To reduce the number of lines required for display, multiple lines are blended by binning them
# together based on their PPM locations and phases. The following parameters are used to
# customize these procedures:
# Peak Search Range -- Low/High (PPM): the range in PPM that is searched for lines from the
# metabolite simulation.
# Peak Blending Tolerance (PPM and Degrees): the width of the bins (+/- in PPM and +/- in
# PhaseDegrees) that are used to blend the lines in the simulation. Lines that are included in the
# same bin are summed using complex addition based on Amplitude and Phase.
b0 = self.sim_experiment.b0
obs_iso = self.sim_experiment.obs_iso
tolppm = self.sim_experiment.tolppm
tolpha = self.sim_experiment.tolpha
ppmlo = self.sim_experiment.ppmlo
ppmhi = self.sim_experiment.ppmhi
rf_off = self.sim_experiment.RF_OFFSET
field = b0
nspins = spin_system.spins()
nlines = mx.size()
tmp = pg.Isotope(obs_iso)
obs_qn = tmp.qn()
qnscale = 1.0
for i in range(nspins):
qnscale *= 2 * spin_system.qn(i) + 1
qnscale = qnscale / (2.0 * (2.0 * obs_qn + 1))
freqs = []
outf = []
outa = []
outp = []
nbin = 0
found = False
PI = 3.14159265358979323846
RAD2DEG = 180.0 / PI
indx = mx.Sort(0, -1, 0)
for i in range(nlines):
freqs.append(-1 * mx.Fr(indx[i]) / (2.0 * PI * field))
for i in range(nlines):
freq = freqs[i]
if (freq > ppmlo) and (freq < ppmhi):
val = mx.I(indx[i])
tmpa = np.sqrt(val.real()**2 + val.imag()**2) / qnscale
tmpp = -RAD2DEG * np.angle(val.real() + 1j * val.imag())
if nbin == 0:
outf.append(freq)
outa.append(tmpa)
outp.append(tmpp)
nbin += 1
else:
for k in range(nbin):
if (freq >= outf[k] - tolppm) and (freq <=
outf[k] + tolppm):
if (tmpp >= outp[k] - tolpha) and (tmpp <=
outp[k] + tolpha):
ampsum = outa[k] + tmpa
outf[k] = (outa[k] * outf[k] +
tmpa * freq) / ampsum
outp[k] = (outa[k] * outp[k] +
tmpa * tmpp) / ampsum
outa[k] += tmpa
found = True
if not found:
outf.append(freq)
outa.append(tmpa)
outp.append(tmpp)
nbin += 1
found = False
for i, item in enumerate(outf):
outf[i] = item + rf_off
outp[i] = outp[i] - 90.0
metab = Metabolite()
metab.name = metab_name
metab.var = 0.0
for i in range(sp.size(outf)):
if outf[i] <= 5:
metab.ppm.append(outf[i])
metab.area.append(outa[i])
metab.phase.append(-1.0 * outp[i])
insysfile = self.insysfile.replace('pints/metabolites/3T_', '')
insysfile = self.insysfile.replace('pints/metabolites/7T_', '')
insysfile = self.insysfile.replace('pints/metabolites/9.4T_', '')
if insysfile == 'alanine.sys': #
metab.A_m = 0.078
metab.T2 = (87E-3)
elif insysfile == 'aspartate.sys':
metab.A_m = 0.117
metab.T2 = (87E-3)
elif insysfile == 'choline_1-CH2_2-CH2.sys': #
metab.A_m = 0.165
metab.T2 = (87E-3)
elif insysfile == 'choline_N(CH3)3_a.sys' or insysfile == 'choline_N(CH3)3_b.sys': #
metab.A_m = 0.165
metab.T2 = (121E-3)
elif insysfile == 'creatine_N(CH3).sys':
metab.A_m = 0.296
metab.T2 = (90E-3)
elif insysfile == 'creatine_X.sys':
metab.A_m = 0.296
metab.T2 = (81E-3)
elif insysfile == 'd-glucose-alpha.sys': #
metab.A_m = 0.049
metab.T2 = (87E-3)
elif insysfile == 'd-glucose-beta.sys': #
metab.A_m = 0.049
metab.T2 = (87E-3)
elif insysfile == 'eth.sys': #
metab.A_m = 0.320
metab.T2 = (87E-3)
elif insysfile == 'gaba.sys': #
metab.A_m = 0.155
metab.T2 = (82E-3)
elif insysfile == 'glutamate.sys':
metab.A_m = 0.898
metab.T2 = (88E-3)
elif insysfile == 'glutamine.sys':
metab.A_m = 0.427
metab.T2 = (87E-3)
elif insysfile == 'glutathione_cysteine.sys':
metab.A_m = 0.194
metab.T2 = (87E-3)
elif insysfile == 'glutathione_glutamate.sys':
metab.A_m = 0.194
metab.T2 = (87E-3)
elif insysfile == 'glutathione_glycine.sys':
metab.A_m = 0.194
metab.T2 = (87E-3)
elif insysfile == 'glycine.sys':
metab.A_m = 0.068
metab.T2 = (87E-3)
elif insysfile == 'gpc_7-CH2_8-CH2.sys': #
metab.A_m = 0.097
metab.T2 = (87E-3)
elif insysfile == 'gpc_glycerol.sys': #
metab.A_m = 0.097
metab.T2 = (87E-3)
elif insysfile == 'gpc_N(CH3)3_a.sys': #
metab.A_m = 0.097
metab.T2 = (121E-3)
elif insysfile == 'gpc_N(CH3)3_b.sys': #
metab.A_m = 0.097
metab.T2 = (121E-3)
elif insysfile == 'lactate.sys': #
metab.A_m = 0.039
metab.T2 = (87E-3)
elif insysfile == 'myoinositol.sys':
metab.A_m = 0.578
metab.T2 = (87E-3)
elif insysfile == 'naa_acetyl.sys':
metab.A_m = 1.000
metab.T2 = (130E-3)
elif insysfile == 'naa_aspartate.sys':
metab.A_m = 1.000
metab.T2 = (69E-3)
elif insysfile == 'naag_acetyl.sys':
metab.A_m = 0.160
metab.T2 = (130E-3)
elif insysfile == 'naag_aspartyl.sys':
metab.A_m = 0.160
metab.T2 = (87E-3)
elif insysfile == 'naag_glutamate.sys':
metab.A_m = 0.160
metab.T2 = (87E-3)
elif insysfile == 'pcho_N(CH3)3_a.sys': #
metab.A_m = 0.058
metab.T2 = (121E-3)
elif insysfile == 'pcho_N(CH3)3_b.sys': #
metab.A_m = 0.058
metab.T2 = (121E-3)
elif insysfile == 'pcho_X.sys': #
metab.A_m = 0.058
metab.T2 = (87E-3)
elif insysfile == 'pcr_N(CH3).sys':
metab.A_m = 0.422
metab.T2 = (90E-3)
elif insysfile == 'pcr_X.sys':
metab.A_m = 0.422
metab.T2 = (81E-3)
elif insysfile == 'peth.sys':
metab.A_m = 0.126
metab.T2 = (87E-3)
elif insysfile == 'scyllo-inositol.sys':
metab.A_m = 0.044
metab.T2 = (87E-3)
elif insysfile == 'taurine.sys':
metab.A_m = 0.117
metab.T2 = (85E-3)
elif insysfile == 'water.sys':
metab.A_m = 1.000
metab.T2 = (43.60E-3)
# Send save data signal
self.outputResults.emit(metab)
self.postToConsole.emit(' | Simulation completed for ... ' +
self.insysfile)
self.finished.emit(self.thread_num)
import pygamma
import numpy as np
if __name__ == "__main__":
cc = pygamma.complex(3, 2)
print(cc)
printsep(col*3, f)
# Matrix.row_vector
row = pg.row_vector()
printsep(row, f)
row = pg.row_vector(4)
printsep(row, f)
row[0] = 5
printsep(row, f)
row[1] = 9.2
row[3] = 11.6
printsep(row, f)
printsep(row+row, f)
printsep(row*3, f)
# Matrix.complex
val = pg.complex(0) # nb. empty complex() has randon numbers in it
printsep(val, f)
val = pg.complex(4, 3.2)
printsep(val, f)
val2 = pg.complex(val)
printsep(val2, f)
val3 = pg.complex(val+1)
printsep(val3, f)
header = (s1, s2) sys = pg.sys_dynamic() sys.read(infile) specfreq = sys.Omega() mx = pg.TTable1D() H = pg.Ho(sys) detect = pg.Fm(sys) sigma0 = pg.sigma_eq(sys) sigmap = pg.Iypuls(sys, sigma0, 90.) L = pg.Hsuper(H) L *= pg.complex(0,1) L += pg.Kex(sys, H.get_basis()); ACQ1 = pg.acquire1D(pg.gen_op(detect), L) mx = ACQ1.table(sigmap); #mx.dbwrite_old(outfile, "test_lines", -10, 10, specfreq, .1, 0, header) mx.dbwrite(outfile, runname, specfreq, sys.spins(), 0, header)
import pygamma
import numpy as np
if __name__ == "__main__":
cc = pygamma.complex(5,3)
print(cc, cc.__repr__())