{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# This cell is added by sphinx-gallery\n\n%matplotlib inline\n\nimport mrsimulator\nprint(f'You are using mrsimulator v{mrsimulator.__version__}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n# RbNO3, 87Rb (I=3/2) STMAS\n\n87Rb (I=3/2) staellite-transition off magic-angle spinning simulation.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The following is an example of the STMAS simulation of $\\text{RbNO}_3$. The\n$^{87}\\text{Rb}$ tensor parameters were obtained from Massiot `et. al.` [#f1]_.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport mrsimulator.signal_processing as sp\nimport mrsimulator.signal_processing.apodization as apo\nfrom mrsimulator import Simulator, SpinSystem, Site\nfrom mrsimulator.methods import ST1_VAS\n\n# global plot configuration\nfont = {\"size\": 9}\nmpl.rc(\"font\", **font)\nmpl.rcParams[\"figure.figsize\"] = [4.25, 3.0]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generate the site and spin system objects.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "Rb87_1 = Site(\n isotope=\"87Rb\",\n isotropic_chemical_shift=-27.4, # in ppm\n quadrupolar={\"Cq\": 1.68e6, \"eta\": 0.2}, # Cq is in Hz\n)\nRb87_2 = Site(\n isotope=\"87Rb\",\n isotropic_chemical_shift=-28.5, # in ppm\n quadrupolar={\"Cq\": 1.94e6, \"eta\": 1.0}, # Cq is in Hz\n)\nRb87_3 = Site(\n isotope=\"87Rb\",\n isotropic_chemical_shift=-31.3, # in ppm\n quadrupolar={\"Cq\": 1.72e6, \"eta\": 0.5}, # Cq is in Hz\n)\n\nsites = [Rb87_1, Rb87_2, Rb87_3] # all sites\nspin_systems = [SpinSystem(sites=[s]) for s in sites]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Step 2:** Select a satellite-transition variable-angle spinning method. The\nfollowing `ST1_VAS` method correlates the frequencies from the two inner-satellite\ntransitions to the central transition. Note, STMAS measurements are highly suspectable\nto rotor angle mismatch. In the following, we show two methods, first set to\nmagic-angle and the second deliberately miss-sets by approximately 0.0059 degrees.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "angles = [54.7359, 54.73]\nmethod = []\nfor angle in angles:\n method.append(\n ST1_VAS(\n channels=[\"87Rb\"],\n magnetic_flux_density=7, # in T\n rotor_angle=angle * 3.14159 / 180, # in rad (magic angle)\n spectral_dimensions=[\n {\n \"count\": 256,\n \"spectral_width\": 3e3, # in Hz\n \"reference_offset\": -2.4e3, # in Hz\n \"label\": \"Isotropic dimension\",\n },\n {\n \"count\": 512,\n \"spectral_width\": 5e3, # in Hz\n \"reference_offset\": -4e3, # in Hz\n \"label\": \"MAS dimension\",\n },\n ],\n )\n )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create the Simulator object, add the method and spin system objects, and\nrun the simulation.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "sim = Simulator()\nsim.spin_systems = spin_systems # add the spin systems\nsim.methods = method # add the methods.\nsim.run()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The plot of the simulation.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "data = [sim.methods[0].simulation, sim.methods[1].simulation]\nfig, ax = plt.subplots(1, 2, figsize=(8.5, 3), subplot_kw={\"projection\": \"csdm\"})\n\ntitles = [\"STVAS @ magic-angle\", \"STVAS @ 0.0059 deg off magic-angle\"]\nfor i, item in enumerate(data):\n cb1 = ax[i].imshow(item / item.max(), aspect=\"auto\", cmap=\"gist_ncar_r\")\n ax[i].set_title(titles[i])\n plt.colorbar(cb1, ax=ax[i])\n ax[i].invert_xaxis()\n ax[i].invert_yaxis()\nplt.tight_layout()\nplt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Add post-simulation signal processing.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "processor = sp.SignalProcessor(\n operations=[\n # Gaussian convolution along both dimensions.\n sp.IFFT(dim_index=(0, 1)),\n apo.Gaussian(FWHM=\"50 Hz\", dim_index=0),\n apo.Gaussian(FWHM=\"50 Hz\", dim_index=1),\n sp.FFT(dim_index=(0, 1)),\n ]\n)\nprocessed_data = []\nfor item in data:\n processed_data.append(processor.apply_operations(data=item))\n processed_data[-1] /= processed_data[-1].max()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The plot of the simulation after signal processing.\n\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [ "ax = plt.subplot(projection=\"csdm\")\ncb = ax.imshow(processed_data[1].real, cmap=\"gist_ncar_r\", aspect=\"auto\")\nplt.colorbar(cb)\nax.invert_xaxis()\nax.invert_yaxis()\nplt.tight_layout()\nplt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ ".. [#f1] Massiot, D., Touzoa, B., Trumeaua, D., Coutures, J.P., Virlet, J., Florian,\n P., Grandinetti, P.J. Two-dimensional magic-angle spinning isotropic\n reconstruction sequences for quadrupolar nuclei, ssnmr, (1996), **6**, *1*,\n 73-83. `DOI: 10.1016/0926-2040(95)01210-9\n `_\n\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.5" } }, "nbformat": 4, "nbformat_minor": 0 }