def pre_setup(isotope, shift, reference_offset): spin_system = SpinSystem( sites=[Site(isotope=isotope, isotropic_chemical_shift=shift)]) method = Method.parse_dict_with_units( dict( channels=[isotope], spectral_dimensions=[{ "count": 2048, "spectral_width": "25 kHz", "reference_offset": f"{reference_offset} Hz", "events": [{ "magnetic_flux_density": "9.4 T" }], }], )) sim = Simulator() sim.spin_systems.append(spin_system) sim.methods += [method] sim.run() x, y = sim.methods[0].simulation.to_list() return x[np.argmax(y)], abs(x[1] - x[0])
def setup_simulator(): site = Site( isotope="23Na", isotropic_chemical_shift=32, shielding_symmetric={ "zeta": -120, "eta": 0.1 }, quadrupolar={ "Cq": 1e5, "eta": 0.31, "beta": 5.12 }, ) sys = SpinSystem(sites=[site], abundance=0.123) sim = Simulator() sim.spin_systems.append(sys) sim.methods.append( BlochDecayCTSpectrum(channels=["2H"], rotor_frequency=1e3)) sim.methods.append( BlochDecaySpectrum(channels=["2H"], rotor_frequency=12.5e3)) sim.methods.append(ThreeQ_VAS(channels=["27Al"])) sim.methods.append(SSB2D(channels=["17O"], rotor_frequency=35500)) return sim
# plot of the dataset. plt.figure(figsize=(4.25, 3.0)) ax = plt.subplot(projection="csdm") ax.plot(experiment, "k", alpha=0.5) ax.set_xlim(100, -100) plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # **Spin System** B11 = Site( isotope="11B", isotropic_chemical_shift=20.0, # in ppm quadrupolar=SymmetricTensor(Cq=2.3e6, eta=0.03), # Cq in Hz ) spin_systems = [SpinSystem(sites=[B11])] # %% # **Method** # Get the spectral dimension parameters from the experiment. spectral_dims = get_spectral_dimensions(experiment) MAS_CT = BlochDecayCTSpectrum( channels=["11B"], magnetic_flux_density=14.1, # in T rotor_frequency=12500, # in Hz spectral_dimensions=spectral_dims,
def SSB2D_setup(ist, vr, method_type): sites = [ Site( isotope=ist, isotropic_chemical_shift=29, shielding_symmetric={ "zeta": -70, "eta": 0.000 }, ), Site( isotope=ist, isotropic_chemical_shift=44, shielding_symmetric={ "zeta": -96, "eta": 0.166 }, ), Site( isotope=ist, isotropic_chemical_shift=57, shielding_symmetric={ "zeta": -120, "eta": 0.168 }, ), ] spin_systems = [SpinSystem(sites=[s]) for s in sites] B0 = 11.7 if method_type == "PASS": method = SSB2D( channels=[ist], magnetic_flux_density=B0, # in T rotor_frequency=vr, spectral_dimensions=[ { "count": 32, "spectral_width": 32 * vr, # in Hz "label": "Anisotropic dimension", }, # The last spectral dimension block is the direct-dimension { "count": 2048, "spectral_width": 2e4, # in Hz "reference_offset": 5e3, # in Hz "label": "Fast MAS dimension", }, ], ) else: method = Method2D( channels=[ist], magnetic_flux_density=B0, # in T spectral_dimensions=[ { "count": 64, "spectral_width": 8e4, # in Hz "label": "Anisotropic dimension", "events": [{ "rotor_angle": 90 * 3.14159 / 180 }], }, # The last spectral dimension block is the direct-dimension { "count": 2048, "spectral_width": 2e4, # in Hz "reference_offset": 5e3, # in Hz "label": "Fast MAS dimension", }, ], affine_matrix=[[1, -1], [0, 1]], ) sim = Simulator() sim.spin_systems = spin_systems # add spin systems sim.methods = [method] # add the method. sim.run() data_ssb = sim.methods[0].simulation dim_ssb = data_ssb.x[0].coordinates.value if method_type == "PASS": bloch = BlochDecaySpectrum( channels=[ist], magnetic_flux_density=B0, # in T rotor_frequency=vr, # in Hz spectral_dimensions=[ { "count": 32, "spectral_width": 32 * vr, # in Hz "reference_offset": 0, # in Hz "label": "MAS dimension", }, ], ) else: bloch = BlochDecaySpectrum( channels=[ist], magnetic_flux_density=B0, # in T rotor_frequency=vr, # in Hz rotor_angle=90 * 3.14159 / 180, spectral_dimensions=[ { "count": 64, "spectral_width": 8e4, # in Hz "reference_offset": 0, # in Hz "label": "MAS dimension", }, ], ) for i in range(3): iso = spin_systems[i].sites[0].isotropic_chemical_shift sys = spin_systems[i].copy() sys.sites[0].isotropic_chemical_shift = 0 sim2 = Simulator() sim2.spin_systems = [sys] # add spin systems sim2.methods = [bloch] # add the method. sim2.run() index = np.where(dim_ssb < iso)[0][-1] one_d_section = data_ssb.y[0].components[0][:, index] one_d_section /= one_d_section.max() one_d_sim = sim2.methods[0].simulation.y[0].components[0] one_d_sim /= one_d_sim.max() np.testing.assert_almost_equal(one_d_section, one_d_sim, decimal=6)
def test_MQMAS(): site = Site( isotope="87Rb", isotropic_chemical_shift=-9, shielding_symmetric={ "zeta": 100, "eta": 0 }, quadrupolar={ "Cq": 3.5e6, "eta": 0.36, "beta": 70 / 180 * np.pi }, ) spin_system = SpinSystem(sites=[site]) method = Method2D( channels=["87Rb"], magnetic_flux_density=9.4, spectral_dimensions=[ { "count": 128, "spectral_width": 20000, "events": [{ "transition_query": [{ "P": [-3], "D": [0] }] }], }, { "count": 128, "spectral_width": 20000, "events": [{ "transition_query": [{ "P": [-1], "D": [0] }] }], }, ], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.config.integration_volume = "hemisphere" sim.run() # process k = 21 / 27 # shear factor processor = sp.SignalProcessor(operations=[ sp.IFFT(dim_index=1), aft.Shear(factor=-k, dim_index=1, parallel=0), aft.Scale(factor=1 + k, dim_index=1), sp.FFT(dim_index=1), ]) processed_data = processor.apply_operations( data=sim.methods[0].simulation).real # Since there is a single site, after the shear and scaling transformations, there # should be a single perak along the isotropic dimension at index 70. # The isotropic coordinate of this peak is given by # w_iso = (17.8)*iso_shift + 1e6/8 * (vq/v0)^2 * (eta^2 / 3 + 1) # ref: D. Massiot et al. / Solid State Nuclear Magnetic Resonance 6 (1996) 73-83 iso_slice = processed_data[40, :] assert np.argmax(iso_slice.y[0].components[0]) == 70 # calculate the isotropic coordinate spin = method.channels[0].spin w0 = method.channels[0].gyromagnetic_ratio * 9.4 * 1e6 wq = 3 * 3.5e6 / (2 * spin * (2 * spin - 1)) w_iso = -9 * 17 / 8 + 1e6 / 8 * (wq / w0)**2 * ((0.36**2) / 3 + 1) # the coordinate from spectrum w_iso_spectrum = processed_data.x[1].coordinates[70].value np.testing.assert_almost_equal(w_iso, w_iso_spectrum, decimal=2) # The projection onto the MAS dimension should be the 1D block decay central # transition spectrum mas_slice = processed_data.sum(axis=1).y[0].components[0] # MAS spectrum method = BlochDecayCTSpectrum( channels=["87Rb"], magnetic_flux_density=9.4, rotor_frequency=1e9, spectral_dimensions=[{ "count": 128, "spectral_width": 20000 }], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.config.integration_volume = "hemisphere" sim.run() data = sim.methods[0].simulation.y[0].components[0] np.testing.assert_almost_equal(data / data.max(), mas_slice / mas_slice.max(), decimal=2, err_msg="not equal")
# The 2D QMAT spectrum is a correlation of finite speed MAS to an infinite speed MAS # spectrum. The parameters for the simulation are obtained from Walder `et al.` [#f1]_. import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import SSB2D from mrsimulator.spin_system.tensors import SymmetricTensor # sphinx_gallery_thumbnail_number = 2 # %% # Generate the site and spin system objects. sites = [ Site( isotope="87Rb", isotropic_chemical_shift=16, # in ppm quadrupolar=SymmetricTensor(Cq=5.3e6, eta=0.1), # Cq in Hz ), Site( isotope="87Rb", isotropic_chemical_shift=40, # in ppm quadrupolar=SymmetricTensor(Cq=2.6e6, eta=1.0), # Cq in Hz ), ] spin_systems = [SpinSystem(sites=[s]) for s in sites] # %% # Use the ``SSB2D`` method to simulate a PASS, MAT, QPASS, QMAT, or any equivalent # sideband separation spectrum. Here, we use the method to generate a QMAT spectrum. # The QMAT method is created from the ``SSB2D`` method in the same as a PASS or MAT # method. The difference is that the observed channel is a half-integer quadrupolar
def test_2D(): site_Ni = Site( isotope="2H", isotropic_chemical_shift=-97, # in ppm shielding_symmetric=dict( zeta=-551, eta=0.12, alpha=62 * np.pi / 180, beta=114 * np.pi / 180, gamma=171 * np.pi / 180, ), quadrupolar=dict(Cq=77.2e3, eta=0.9), # Cq in Hz ) spin_system = SpinSystem(sites=[site_Ni]) data = [] for angle, n_gamma in zip([0, np.pi / 4], [1, 500]): shifting_d = Method( name="Shifting-d", channels=["2H"], magnetic_flux_density=9.395, # in T rotor_frequency=0, # in Hz rotor_angle=angle, # in Hz spectral_dimensions=[ SpectralDimension( count=512, spectral_width=2.5e5, # in Hz label="Quadrupolar frequency", events=[ SpectralEvent( transition_queries=[{ "ch1": { "P": [-1] } }], freq_contrib=["Quad1_2"], ), MixingEvent(query="NoMixing"), ], ), SpectralDimension( count=256, spectral_width=2e5, # in Hz reference_offset=2e4, # in Hz label="Paramagnetic shift", events=[ SpectralEvent( transition_queries=[{ "ch1": { "P": [-1] } }], freq_contrib=["Shielding1_0", "Shielding1_2"], ) ], ), ], ) sim = Simulator(spin_systems=[spin_system], methods=[shifting_d]) sim.config.integration_volume = "hemisphere" sim.config.number_of_gamma_angles = n_gamma sim.run(auto_switch=False) res = sim.methods[0].simulation.y[0].components[0] data.append(res / res.max()) # _, ax = plt.subplots(1, 2) # ax[0].imshow(data[0].real) # ax[1].imshow(data[1].real) # plt.show() np.testing.assert_almost_equal(data[0], data[1], decimal=1.8)
# broadening is applied to the spectrum as a post-simulation step. import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.method.lib import ThreeQ_VAS from mrsimulator import signal_processor as sp from mrsimulator.spin_system.tensors import SymmetricTensor from mrsimulator.method import SpectralDimension # sphinx_gallery_thumbnail_number = 3 # %% # Generate the site and spin system objects. Rb87_1 = Site( isotope="87Rb", isotropic_chemical_shift=-27.4, # in ppm quadrupolar=SymmetricTensor(Cq=1.68e6, eta=0.2), # Cq is in Hz ) Rb87_2 = Site( isotope="87Rb", isotropic_chemical_shift=-28.5, # in ppm quadrupolar=SymmetricTensor(Cq=1.94e6, eta=1.0), # Cq is in Hz ) Rb87_3 = Site( isotope="87Rb", isotropic_chemical_shift=-31.3, # in ppm quadrupolar=SymmetricTensor(Cq=1.72e6, eta=0.5), # Cq is in Hz ) sites = [Rb87_1, Rb87_2, Rb87_3] # all sites spin_systems = [SpinSystem(sites=[s]) for s in sites]
import numpy as np from mrsimulator import Simulator, SpinSystem, Site, Coupling from mrsimulator.methods import Method1D from mrsimulator.method import SpectralDimension, SpectralEvent, MixingEvent from mrsimulator.spin_system.tensors import SymmetricTensor # sphinx_gallery_thumbnail_number = 2 # %% # For demonstration, we will create two spin systems, one with a single site and other # with two spin 1/2 sites. S1 = Site( isotope="1H", isotropic_chemical_shift=10, # in ppm shielding_symmetric=SymmetricTensor(zeta=-80, eta=0.25), # zeta in ppm ) S2 = Site(isotope="1H", isotropic_chemical_shift=-10) S12 = Coupling(site_index=[0, 1], isotropic_j=100, dipolar=SymmetricTensor(D=2000, eta=0, alpha=0)) spin_system_1 = SpinSystem(sites=[S1], label="Uncoupled system") spin_system_2 = SpinSystem(sites=[S1, S2], couplings=[S12], label="Coupled system") # %% # **Create a custom method** #
plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # **Guess model** # # Create a guess list of spin systems. For fitting the sideband profile at an isotropic # chemical shift cross-section from PASS/MAT datasets, set the isotropic_chemical_shift # parameter of the site object as zero. site = Site( isotope="13C", isotropic_chemical_shift=0, # shielding_symmetric={ "zeta": -70, "eta": 0.8 }, ) spin_systems = [SpinSystem(sites=[site])] # %% # **Method** # # For the sideband-only cross-section, use the BlochDecaySpectrum method. # Get the dimension information from the experiment. spectral_dims = get_spectral_dimensions(pass_cross_section) PASS = BlochDecaySpectrum( channels=["13C"],
# :math:`^{29}\text{Si}` sites. The :math:`^{29}\text{Si}` tensor parameters # were obtained from Hansen `et al.` [#f1]_ import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator import signal_processing as sp from mrsimulator.methods import BlochDecaySpectrum from mrsimulator.spin_system.tensors import SymmetricTensor # sphinx_gallery_thumbnail_number = 3 # %% # **Step 1:** Create the sites. Si29_1 = Site( isotope="29Si", isotropic_chemical_shift=-89.0, # in ppm shielding_symmetric=SymmetricTensor(zeta=59.8, eta=0.62), # zeta in ppm ) Si29_2 = Site( isotope="29Si", isotropic_chemical_shift=-89.5, # in ppm shielding_symmetric=SymmetricTensor(zeta=52.1, eta=0.68), # zeta in ppm ) Si29_3 = Site( isotope="29Si", isotropic_chemical_shift=-87.8, # in ppm shielding_symmetric=SymmetricTensor(zeta=69.4, eta=0.60), # zeta in ppm ) # %% # **Step 2:** Create the spin systems from these sites. Again, we create three
import matplotlib as mpl import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import Method1D # global plot configuration mpl.rcParams["figure.figsize"] = [4.5, 3.0] # sphinx_gallery_thumbnail_number = 1 # %% # Create a single-site arbitrary spin system. site = Site( name="27Al", isotope="27Al", isotropic_chemical_shift=35.7, # in ppm quadrupolar={ "Cq": 2.959e6, "eta": 0.98 }, # Cq is in Hz ) spin_system = SpinSystem(sites=[site]) # %% # Selecting the triple-quantum transition # --------------------------------------- # # For spin-site spin-5/2 spin system, there are three triple-quantum transition # # - :math:`|1/2\rangle\rightarrow|-5/2\rangle` (:math:`P=-3, D=6`) # - :math:`|3/2\rangle\rightarrow|-3/2\rangle` (:math:`P=-3, D=0`) # - :math:`|5/2\rangle\rightarrow|-1/2\rangle` (:math:`P=-3, D=-6`)
plt.show() # %% # Create a fitting model # ---------------------- # **Guess model** # # Create a guess list of spin systems. site = Site( isotope="2H", isotropic_chemical_shift=200, # in ppm shielding_symmetric={ "zeta": -1300, # in ppm "eta": 0.2, "alpha": np.pi, # in rads "beta": np.pi / 2, # in rads "gamma": np.pi / 2, # in rads }, quadrupolar={ "Cq": 110e3, "eta": 0.83 }, # Cq in Hz ) spin_systems = [SpinSystem(sites=[site])] # %% # **Method** # # Use the generic 2D method, `Method2D`, to generate a shifting-d echo method.
def test_site_quad_set_to_None(): a = Site(isotope="27Al", quadrupolar=None) assert a.isotope.symbol == "27Al" assert a.quadrupolar is None
# plot of the dataset. plt.figure(figsize=(4.25, 3.0)) ax = plt.subplot(projection="csdm") ax.plot(experiment, color="black", linewidth=0.5, label="Experiment") ax.set_xlim(600, -700) plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # **Spin System** H_2 = Site( isotope="2H", isotropic_chemical_shift=-57.12, # in ppm, quadrupolar=SymmetricTensor(Cq=3e4, eta=0.0), # Cq in Hz ) spin_systems = [SpinSystem(sites=[H_2])] # %% # **Method** # Get the spectral dimension parameters from the experiment. spectral_dims = get_spectral_dimensions(experiment) MAS = BlochDecaySpectrum( channels=["2H"], magnetic_flux_density=9.395, # in T rotor_frequency=4517.1, # in Hz
import mrsimulator.signal_processing as sp import mrsimulator.signal_processing.apodization as apo from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import Method2D # global plot configuration mpl.rcParams["figure.figsize"] = [4.5, 3.0] # sphinx_gallery_thumbnail_number = 1 # %% # Create the sites and spin systems sites = [ Site( isotope="29Si", isotropic_chemical_shift=-89.0, # in ppm shielding_symmetric={ "zeta": 59.8, "eta": 0.62 }, # zeta in ppm ), Site( isotope="29Si", isotropic_chemical_shift=-89.5, # in ppm shielding_symmetric={ "zeta": 52.1, "eta": 0.68 }, # zeta in ppm ), Site( isotope="29Si", isotropic_chemical_shift=-87.8, # in ppm shielding_symmetric={
# The following is an example of the STMAS simulation of :math:`\text{RbNO}_3`. The # :math:`^{87}\text{Rb}` tensor parameters were obtained from Massiot `et al.` [#f1]_. import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import ST1_VAS from mrsimulator import signal_processing as sp # sphinx_gallery_thumbnail_number = 2 # %% # Generate the site and spin system objects. Rb87_1 = Site( isotope="87Rb", isotropic_chemical_shift=-27.4, # in ppm quadrupolar={ "Cq": 1.68e6, "eta": 0.2 }, # Cq is in Hz ) Rb87_2 = Site( isotope="87Rb", isotropic_chemical_shift=-28.5, # in ppm quadrupolar={ "Cq": 1.94e6, "eta": 1.0 }, # Cq is in Hz ) Rb87_3 = Site( isotope="87Rb", isotropic_chemical_shift=-31.3, # in ppm quadrupolar={
# plot of the dataset. plt.figure(figsize=(4.25, 3.0)) ax = plt.subplot(projection="csdm") ax.plot(experiment, color="black", linewidth=0.5, label="Experiment") ax.set_xlim(200, -200) plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # **Spin System** P_31 = Site( isotope="31P", isotropic_chemical_shift=5.0, # in ppm, shielding_symmetric=SymmetricTensor(zeta=-80, eta=0.5), # zeta in Hz ) spin_systems = [SpinSystem(sites=[P_31])] # %% # **Method** # 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
def test_csa_01(): site = Site(isotope="13C", shielding_symmetric={"zeta": 50, "eta": 0.5}) spin_system = SpinSystem(sites=[site]) setup_test(spin_system, volume="octant", sw=2.5e4)
ax.plot(experiment, color="black", linewidth=0.5, label="Experiment") ax.set_xlim(100, -50) plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # # A fitting model is a composite of ``Simulator`` and ``SignalProcessor`` objects. # # **Step 1:** Create initial guess sites and spin systems O1 = Site( isotope="17O", isotropic_chemical_shift=60.0, # in ppm, quadrupolar=SymmetricTensor(Cq=4.2e6, eta=0.5), # Cq in Hz ) O2 = Site( isotope="17O", isotropic_chemical_shift=40.0, # in ppm, quadrupolar=SymmetricTensor(Cq=2.4e6, eta=0.0), # Cq in Hz ) spin_systems = [ SpinSystem(sites=[O1], abundance=50, name="O1"), SpinSystem(sites=[O2], abundance=50, name="O2"), ] # %%
import mrsimulator.signal_processing as sp import mrsimulator.signal_processing.apodization as apo from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import BlochDecayCentralTransitionSpectrum # global plot configuration mpl.rcParams["figure.figsize"] = [4.5, 3.0] # sphinx_gallery_thumbnail_number = 2 # %% # **Step 1:** Create the sites. # default unit of isotropic_chemical_shift is ppm and Cq is Hz. O17_1 = Site(isotope="17O", isotropic_chemical_shift=29, quadrupolar={ "Cq": 6.05e6, "eta": 0.000 }) O17_2 = Site(isotope="17O", isotropic_chemical_shift=41, quadrupolar={ "Cq": 5.43e6, "eta": 0.166 }) O17_3 = Site(isotope="17O", isotropic_chemical_shift=57, quadrupolar={ "Cq": 5.45e6, "eta": 0.168 }) O17_4 = Site(isotope="17O",
# you will first need to create a fitting model. We will use the ``mrsimulator`` objects # as tools in creating a model for the least-squares fitting. # # **Step 1:** Create initial guess sites and spin systems. # # The initial guess is often based on some prior knowledge about the system under # investigation. For the current example, we know that Cuspidine is a crystalline silica # polymorph with one crystallographic Si site. Therefore, our initial guess model is a # single :math:`^{29}\text{Si}` site spin system. For non-linear fitting algorithms, as # a general recommendation, the initial guess model parameters should be a good starting # point for the algorithms to converge. # the guess model comprising of a single site spin system site = Site( isotope="29Si", isotropic_chemical_shift=-82.0, # in ppm, shielding_symmetric=SymmetricTensor(zeta=-63, eta=0.4), # zeta in ppm ) spin_system = SpinSystem( name="Si Site", description="A 29Si site in cuspidine", sites=[site], # from the above code abundance=100, ) # %% # **Step 2:** Create the method object. # # The method should be the same as the one used # in the measurement. In this example, we use the `BlochDecaySpectrum` method. Note,
def test_ThreeQ_VAS_spin_3halves(): site = Site( isotope="87Rb", isotropic_chemical_shift=-9, shielding_symmetric={ "zeta": 100, "eta": 0 }, quadrupolar={ "Cq": 3.5e6, "eta": 0.36, "beta": 70 / 180 * np.pi }, ) spin_system = SpinSystem(sites=[site]) method = ThreeQ_VAS( channels=["87Rb"], magnetic_flux_density=9.4, spectral_dimensions=[ { "count": 1024, "spectral_width": 20000 }, { "count": 512, "spectral_width": 20000 }, ], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.config.integration_volume = "hemisphere" sim.run() data = sim.methods[0].simulation dat = data.y[0].components[0] index = np.where(dat == dat.max())[0] # The isotropic coordinate of this peak is given by # v_iso = (17/8)*iso_shift + 1e6/8 * (vq/v0)^2 * (eta^2 / 3 + 1) # ref: D. Massiot et al. / Solid State Nuclear Magnetic Resonance 6 (1996) 73-83 spin = method.channels[0].spin v0 = method.channels[0].gyromagnetic_ratio * 9.4 * 1e6 vq = (3 * 3.5e6) / (2 * spin * (2 * spin - 1)) v_iso = -9 * 17 / 8 + 1e6 / 8 * ((vq / v0)**2) * ((0.36**2) / 3 + 1) # the coordinate from spectrum along the iso dimension must be equal to v_iso v_iso_spectrum = data.x[1].coordinates[index[0]].value np.testing.assert_almost_equal(v_iso, v_iso_spectrum, decimal=2) # The projection onto the MAS dimension should be the 1D block decay central # transition spectrum mas_slice = data.sum(axis=1).y[0].components[0] # MAS spectrum method = BlochDecayCTSpectrum( channels=["87Rb"], magnetic_flux_density=9.4, rotor_frequency=1e9, spectral_dimensions=[{ "count": 512, "spectral_width": 20000 }], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.config.integration_volume = "hemisphere" sim.run() data = sim.methods[0].simulation.y[0].components[0] assert np.allclose(data / data.max(), mas_slice / mas_slice.max())
from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.methods import Method2D from mrsimulator import signal_processing as sp from mrsimulator.spin_system.tensors import SymmetricTensor from mrsimulator.method import SpectralDimension, SpectralEvent # sphinx_gallery_thumbnail_number = 3 # %% # Generate the site and spin system objects. site = Site( isotope="87Rb", isotropic_chemical_shift=-9, # in ppm shielding_symmetric=SymmetricTensor(zeta=110, eta=0), quadrupolar=SymmetricTensor( Cq=3.5e6, # in Hz eta=0.36, alpha=0, # in rads beta=70 * 3.14159 / 180, # in rads gamma=0, # in rads ), ) spin_system = SpinSystem(sites=[site]) # %% # Use the generic 2D method, `Method2D`, to simulate a COASTER spectrum by customizing # the method parameters, as shown below. Note, the Method2D method simulates an infinite # spinning speed spectrum. coaster = Method2D( name="COASTER", channels=["87Rb"], magnetic_flux_density=9.4, # in T
def test_MQMAS_spin_5halves(): spin_system = SpinSystem(sites=[ Site( isotope="27Al", isotropic_chemical_shift=64.5, # in ppm quadrupolar={ "Cq": 3.22e6, "eta": 0.66 }, # Cq is in Hz ) ]) method = ThreeQ_VAS( channels=["27Al"], magnetic_flux_density=7, spectral_dimensions=[ { "count": 1024, "spectral_width": 5000, "reference_offset": -3e3 }, { "count": 512, "spectral_width": 10000, "reference_offset": 4e3 }, ], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.run() data = sim.methods[0].simulation dat = data.y[0].components[0] index = np.where(dat == dat.max())[0] # The isotropic coordinate of this peak is given by # v_iso = -(17/31)*iso_shift + 8e6/93 * (vq/v0)^2 * (eta^2 / 3 + 1) # ref: D. Massiot et al. / Solid State Nuclear Magnetic Resonance 6 (1996) 73-83 spin = method.channels[0].spin v0 = method.channels[0].gyromagnetic_ratio * 7 * 1e6 vq = 3 * 3.22e6 / (2 * spin * (2 * spin - 1)) v_iso = -(17 / 31) * 64.5 - (8e6 / 93) * (vq / v0)**2 * ((0.66**2) / 3 + 1) # the coordinate from spectrum along the iso dimension must be equal to v_iso v_iso_spectrum = data.x[1].coordinates[index[0]].value np.testing.assert_almost_equal(v_iso, v_iso_spectrum, decimal=2) # The projection onto the MAS dimension should be the 1D block decay central # transition spectrum mas_slice = data.sum(axis=1).y[0].components[0] # MAS spectrum method = BlochDecayCTSpectrum( channels=["27Al"], magnetic_flux_density=7, rotor_frequency=1e9, spectral_dimensions=[{ "count": 512, "spectral_width": 10000, "reference_offset": 4e3 }], ) sim = Simulator() sim.spin_systems = [spin_system] sim.methods = [method] sim.config.integration_volume = "hemisphere" sim.run() data = sim.methods[0].simulation.y[0].components[0] assert np.allclose(data / data.max(), mas_slice / mas_slice.max())
def test_direct_init_spin_system(): # test-1 # empty spin system the_spin_system = SpinSystem(sites=[], abundance=10, transition_pathways=None) assert the_spin_system.sites == [] assert the_spin_system.abundance == 10.0 assert the_spin_system.transition_pathways is None assert the_spin_system.json() == {"abundance": "10.0 %"} assert the_spin_system.json(units=False) == { "abundance": 10.0, } # test-2 # site test_site = Site(isotope="29Si", isotropic_chemical_shift=10) assert test_site.isotope.symbol == "29Si" assert test_site.isotropic_chemical_shift == 10.0 assert test_site.property_units["isotropic_chemical_shift"] == "ppm" assert test_site.json() == { "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm", } assert test_site.json(units=False) == { "isotope": "29Si", "isotropic_chemical_shift": 10.0, } # test-3 # one site spin system the_spin_system = SpinSystem(sites=[test_site], abundance=10) assert isinstance(the_spin_system.sites[0], Site) assert the_spin_system.abundance == 10.0 assert the_spin_system.json() == { "sites": [{ "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm" }], "abundance": "10.0 %", } assert the_spin_system.json(units=False) == { "sites": [{ "isotope": "29Si", "isotropic_chemical_shift": 10.0 }], "abundance": 10, } # test-4 # two sites spin system the_spin_system = SpinSystem(sites=[test_site, test_site], abundance=10) assert isinstance(the_spin_system.sites[0], Site) assert isinstance(the_spin_system.sites[1], Site) assert id(the_spin_system.sites[0]) != id(the_spin_system.sites[1]) assert the_spin_system.abundance == 10.0 assert the_spin_system.json() == { "sites": [ { "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm" }, { "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm" }, ], "abundance": "10.0 %", } assert the_spin_system.json(units=False) == { "sites": [ { "isotope": "29Si", "isotropic_chemical_shift": 10.0 }, { "isotope": "29Si", "isotropic_chemical_shift": 10.0 }, ], "abundance": 10, } # test-5 # coupling test_coupling = Coupling(site_index=[0, 1], isotropic_j=10, dipolar={"D": 100}) assert test_coupling.site_index == [0, 1] assert test_coupling.isotropic_j == 10.0 assert test_coupling.property_units["isotropic_j"] == "Hz" assert test_coupling.dipolar.D == 100.0 assert test_coupling.dipolar.property_units["D"] == "Hz" assert test_coupling.json() == { "site_index": [0, 1], "isotropic_j": "10.0 Hz", "dipolar": { "D": "100.0 Hz" }, } assert test_coupling.json(units=False) == { "site_index": [0, 1], "isotropic_j": 10.0, "dipolar": { "D": 100.0 }, } # test-6 # two sites and one coupling spin system the_spin_system = SpinSystem(sites=[test_site, test_site], couplings=[test_coupling], abundance=10) assert isinstance(the_spin_system.sites[0], Site) assert isinstance(the_spin_system.sites[1], Site) assert isinstance(the_spin_system.couplings[0], Coupling) assert id(the_spin_system.sites[0]) != id(the_spin_system.sites[1]) assert the_spin_system.abundance == 10.0 assert the_spin_system.json() == { "sites": [ { "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm" }, { "isotope": "29Si", "isotropic_chemical_shift": "10.0 ppm" }, ], "couplings": [{ "site_index": [0, 1], "isotropic_j": "10.0 Hz", "dipolar": { "D": "100.0 Hz" }, }], "abundance": "10.0 %", } assert the_spin_system.json(units=False) == { "sites": [ { "isotope": "29Si", "isotropic_chemical_shift": 10.0 }, { "isotope": "29Si", "isotropic_chemical_shift": 10.0 }, ], "couplings": [{ "site_index": [0, 1], "isotropic_j": 10.0, "dipolar": { "D": 100.0 } }], "abundance": 10, } # test-5 the_spin_system = SpinSystem( name="Just a test", description="The same", sites=[ { "isotope": "1H", "isotropic_chemical_shift": 0 }, { "isotope": "17O", "isotropic_chemical_shift": -10, "quadrupolar": { "Cq": 5.1e6, "eta": 0.5 }, }, ], couplings=[{ "site_index": [0, 1], "isotropic_j": 34 }], abundance=4.23, ) assert the_spin_system.name == "Just a test" assert the_spin_system.description == "The same" assert the_spin_system.sites[0].isotope.symbol == "1H" assert the_spin_system.sites[0].isotropic_chemical_shift == 0 assert the_spin_system.sites[1].isotope.symbol == "17O" assert the_spin_system.sites[1].isotropic_chemical_shift == -10 assert the_spin_system.sites[1].quadrupolar.Cq == 5.1e6 assert the_spin_system.sites[1].quadrupolar.eta == 0.5 assert the_spin_system.couplings[0].site_index == [0, 1] assert the_spin_system.couplings[0].isotropic_j == 34.0 assert the_spin_system.abundance == 4.23 serialize = the_spin_system.json() assert serialize == { "name": "Just a test", "description": "The same", "sites": [ { "isotope": "1H", "isotropic_chemical_shift": "0.0 ppm" }, { "isotope": "17O", "isotropic_chemical_shift": "-10.0 ppm", "quadrupolar": { "Cq": "5100000.0 Hz", "eta": 0.5 }, }, ], "couplings": [{ "site_index": [0, 1], "isotropic_j": "34.0 Hz" }], "abundance": "4.23 %", } assert the_spin_system == SpinSystem.parse_dict_with_units(serialize) json_no_unit = the_spin_system.json(units=False) assert json_no_unit == { "name": "Just a test", "description": "The same", "sites": [ { "isotope": "1H", "isotropic_chemical_shift": 0 }, { "isotope": "17O", "isotropic_chemical_shift": -10.0, "quadrupolar": { "Cq": 5100000, "eta": 0.5 }, }, ], "couplings": [{ "site_index": [0, 1], "isotropic_j": 34.0 }], "abundance": 4.23, } assert the_spin_system == SpinSystem(**json_no_unit)
ax.set_xlim(100, -50) plt.grid() plt.tight_layout() plt.show() # %% # Create a fitting model # ---------------------- # # A fitting model is a composite of ``Simulator`` and ``SignalProcessor`` objects. # # **Step 1:** Create initial guess sites and spin systems O1 = Site( isotope="17O", isotropic_chemical_shift=60.0, # in ppm, quadrupolar={ "Cq": 4.2e6, "eta": 0.5 }, # Cq in Hz ) O2 = Site( isotope="17O", isotropic_chemical_shift=40.0, # in ppm, quadrupolar={ "Cq": 2.4e6, "eta": 0 }, # Cq in Hz ) spin_systems = [ SpinSystem(sites=[O1], abundance=50, name="O1"),
def get_spin_system_list(): isotopes = [ "19F", "31P", "2H", "6Li", "14N", "27Al", "25Mg", "45Sc", "87Sr" ] return SpinSystem(sites=[Site(isotope=item) for item in isotopes])
def test_warnings(): s = SpinSystem(sites=[Site(isotope="23Na")]) m = Method1D(channels=["1H"]) assert m.get_transition_pathways(s) == []
def test_bad_assignments(): error = "value is not a valid list" with pytest.raises(ValidationError, match=f".*{error}.*"): SpinSystem(sites=Site())