.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/2D_simulation(crystalline)/plot_3_SAS_Rb2CrO4.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_2D_simulation(crystalline)_plot_3_SAS_Rb2CrO4.py: Rb₂CrO₄, ⁸⁷Rb (I=3/2) SAS ^^^^^^^^^^^^^^^^^^^^^^^^^ ⁸⁷Rb (I=3/2) Switched-angle spinning (SAS) simulation. .. GENERATED FROM PYTHON SOURCE LINES 9-14 The following is a Switched-Angle Spinning (SAS) simulation of :math:`\text{Rb}_2\text{CrO}_4`. While :math:`\text{Rb}_2\text{CrO}_4` has two rubidium sites, the site with the smaller quadrupolar interaction was selectively observed and reported by Shore `et al.` [#f1]_. The following is the simulation based on the published tensor parameters. .. GENERATED FROM PYTHON SOURCE LINES 14-23 .. code-block:: Python import numpy as np import matplotlib.pyplot as plt from mrsimulator import Simulator, SpinSystem, Site from mrsimulator.method import Method, SpectralDimension, SpectralEvent from mrsimulator import signal_processor as sp from mrsimulator.spin_system.tensors import SymmetricTensor .. GENERATED FROM PYTHON SOURCE LINES 25-26 Generate the site and spin system objects. .. GENERATED FROM PYTHON SOURCE LINES 26-40 .. code-block:: Python site = Site( isotope="87Rb", isotropic_chemical_shift=-7, # in ppm shielding_symmetric=SymmetricTensor(zeta=110, eta=0), quadrupolar=SymmetricTensor( Cq=3.5e6, # in Hz eta=0.3, alpha=0, # in rads beta=70 * 3.14159 / 180, # in rads gamma=0, # in rads ), ) spin_system = SpinSystem(sites=[site]) .. GENERATED FROM PYTHON SOURCE LINES 41-43 Use the generic `Method` class to simulate a 2D SAS spectrum by customizing the method parameters, as shown below. .. GENERATED FROM PYTHON SOURCE LINES 43-75 .. code-block:: Python sas = Method( channels=["87Rb"], magnetic_flux_density=4.2, # in T rotor_frequency=np.inf, spectral_dimensions=[ SpectralDimension( count=256, spectral_width=1.5e4, # in Hz reference_offset=-5e3, # in Hz label="70.12 dimension", events=[ SpectralEvent( rotor_angle=70.12 * np.pi / 180, # in radians transition_queries=[{"ch1": {"P": [-1], "D": [0]}}], ) ], ), SpectralDimension( count=512, spectral_width=15e3, # in Hz reference_offset=-7e3, # in Hz label="MAS dimension", events=[ SpectralEvent( rotor_angle=54.74 * np.pi / 180, # in radians transition_queries=[{"ch1": {"P": [-1], "D": [0]}}], ) ], ), ], ) .. GENERATED FROM PYTHON SOURCE LINES 76-78 Create the Simulator object, add the method and spin system objects, and run the simulation. .. GENERATED FROM PYTHON SOURCE LINES 78-85 .. code-block:: Python sim = Simulator(spin_systems=[spin_system], methods=[sas]) # Configure the simulator object. For non-coincidental tensors, set the value of the # `integration_volume` attribute to `hemisphere`. sim.config.integration_volume = "hemisphere" sim.run() .. GENERATED FROM PYTHON SOURCE LINES 86-87 The plot of the simulation. .. GENERATED FROM PYTHON SOURCE LINES 87-97 .. code-block:: Python dataset = sim.methods[0].simulation plt.figure(figsize=(4.25, 3.0)) ax = plt.subplot(projection="csdm") cb = ax.imshow(dataset.real / dataset.real.max(), aspect="auto", cmap="gist_ncar_r") plt.colorbar(cb) ax.invert_xaxis() plt.tight_layout() plt.show() .. image-sg:: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_3_SAS_Rb2CrO4_001.png :alt: plot 3 SAS Rb2CrO4 :srcset: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_3_SAS_Rb2CrO4_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 98-99 Add post-simulation signal processing. .. GENERATED FROM PYTHON SOURCE LINES 99-111 .. code-block:: Python processor = sp.SignalProcessor( operations=[ # Gaussian convolution along both dimensions. sp.IFFT(dim_index=(0, 1)), sp.apodization.Gaussian(FWHM="0.2 kHz", dim_index=0), sp.apodization.Gaussian(FWHM="0.2 kHz", dim_index=1), sp.FFT(dim_index=(0, 1)), ] ) processed_dataset = processor.apply_operations(dataset=dataset) processed_dataset /= processed_dataset.max() .. GENERATED FROM PYTHON SOURCE LINES 112-113 The plot of the simulation after signal processing. .. GENERATED FROM PYTHON SOURCE LINES 113-121 .. code-block:: Python plt.figure(figsize=(4.25, 3.0)) ax = plt.subplot(projection="csdm") cb = ax.imshow(processed_dataset.real, cmap="gist_ncar_r", aspect="auto") plt.colorbar(cb) ax.invert_xaxis() plt.tight_layout() plt.show() .. image-sg:: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_3_SAS_Rb2CrO4_002.png :alt: plot 3 SAS Rb2CrO4 :srcset: /examples/2D_simulation(crystalline)/images/sphx_glr_plot_3_SAS_Rb2CrO4_002.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 122-126 .. [#f1] Shore, J.S., Wang, S.H., Taylor, R.E., Bell, A.T., Pines, A. Determination of quadrupolar and chemical shielding tensors using solid-state two-dimensional NMR spectroscopy, J. Chem. Phys. (1996) **105** *21*, 9412. `DOI: 10.1063/1.472776 `_ .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.913 seconds) .. _sphx_glr_download_examples_2D_simulation(crystalline)_plot_3_SAS_Rb2CrO4.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_3_SAS_Rb2CrO4.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_3_SAS_Rb2CrO4.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_