{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Design and simulate a set of gSlider excitation pulses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import sigpy as sp\n",
    "import sigpy.mri as mr\n",
    "import sigpy.plot as pl\n",
    "import sigpy.mri.rf as rf\n",
    "import scipy.signal as signal\n",
    "import matplotlib.pyplot as pyplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "N = 512\n",
    "G = 5\n",
    "exFlip = 90*np.pi/180\n",
    "tb = 12\n",
    "d1 = 0.01\n",
    "d2 = 0.01\n",
    "phi = np.pi\n",
    "dt = 1\n",
    "\n",
    "pulses = rf.slr.dz_gslider_rf(N, G, exFlip, phi, tb, d1, d2, cancel_alpha_phs = True)\n",
    "Mxy = np.zeros((np.size(np.arange(-2*tb, 2*tb, 0.01)), G), dtype = complex)\n",
    "\n",
    "for Gind in range(1, G+1):\n",
    "    \n",
    "    [a, b] = rf.sim.abrm(pulses[:, Gind-1], np.arange(-2*tb, 2*tb, 0.01), True)\n",
    "    Mxy[:, Gind-1] = 2*np.multiply(np.conj(a),b)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pl.LinePlot(Mxy.T)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pl.LinePlot(pulses.T)"
   ]
  }
 ],
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