# 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