# Get the spectral dimension parameters from the experiment.
spectral_dims = get_spectral_dimensions(experiment)
static1D = BlochDecaySpectrum(
channels=["31P"],
magnetic_flux_density=9.395, # in T
rotor_frequency=0, # in Hz
rotor_angle=0, # in rads
spectral_dimensions=spectral_dims,
experiment=experiment, # experimental dataset
)
# Optimize the script by pre-setting the transition pathways for each spin system from
# the method.
for sys in spin_systems:
sys.transition_pathways = static1D.get_transition_pathways(sys)
# %%
# **Guess Model Spectrum**
# Simulation
# ----------
sim = Simulator(spin_systems=spin_systems, methods=[static1D])
sim.run()
# Post Simulation Processing
# --------------------------
processor = sp.SignalProcessor(operations=[
sp.IFFT(),
sp.apodization.Gaussian(FWHM="3000 Hz"),
sp.FFT(),
MAS = BlochDecaySpectrum(
channels=["31P"],
magnetic_flux_density=9.395, # in T
rotor_frequency=6000, # in Hz
spectral_dimensions=spectral_dims,
experiment=experiment, # experimental dataset
)
# A method object queries every spin system for a list of transition pathways that are
# relevant to the given method. Since the method and the number of spin systems remains
# unchanged during the least-squares analysis, a one-time query is sufficient. To avoid
# querying for the transition pathways at every iteration in a least-squares fitting,
# evaluate the transition pathways once and store it as follows
for sys in spin_systems:
sys.transition_pathways = MAS.get_transition_pathways(sys)
# %%
# **Step 3:** Create the Simulator object and add the method and spin system objects.
sim = Simulator(spin_systems=spin_systems, methods=[MAS])
sim.run()
# %%
# **Step 4:** Create a SignalProcessor class object and apply the post-simulation
# signal processing operations.
processor = sp.SignalProcessor(operations=[
sp.IFFT(),
sp.apodization.Exponential(FWHM="0.3 kHz"),
sp.FFT(),
sp.Scale(factor=300),
sp.baseline.ConstantOffset(offset=-2),
# Get the dimension information from the experiment.
spectral_dims = get_spectral_dimensions(pass_cross_section)
PASS = BlochDecaySpectrum(
channels=["13C"],
magnetic_flux_density=9.395, # in T
rotor_frequency=1500, # in Hz
spectral_dimensions=spectral_dims,
experiment=pass_cross_section, # also add the measurement to the method.
)
# Optimize the script by pre-setting the transition pathways for each spin system from
# the method.
for sys in spin_systems:
sys.transition_pathways = PASS.get_transition_pathways(sys)
# %%
# **Guess Spectrum**
# Simulation
# ----------
sim = Simulator(spin_systems=spin_systems, methods=[PASS])
sim.run()
# Post Simulation Processing
# --------------------------
processor = sp.SignalProcessor(operations=[sp.Scale(factor=2000)])
processed_dataset = processor.apply_operations(
dataset=sim.methods[0].simulation).real