diff --git a/notebooks/Modes.ipynb b/notebooks/Modes.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9274cf02",
+   "metadata": {},
+   "source": [
+    "## MODE FITS - TEST DIFFERENT FITS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "d56bc498",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from itertools import product"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "b8d925f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from specparam import SpectralModel\n",
+    "from specparam.sim import gen_freqs, sim_power_spectrum\n",
+    "from specparam.plts import plot_spectra\n",
+    "from specparam.sim.utils import set_random_seed\n",
+    "from specparam.modes.definitions import *"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "b8ec5622",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "set_random_seed(191)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "670f8085",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define simulation settings\n",
+    "AP_PARAMS = {\n",
+    "    'fixed' : [1, 0.75],\n",
+    "    'knee' : [0, 1000, 1.5],\n",
+    "    'doublexp' : [0, 0.15, 900, 1.25],\n",
+    "}\n",
+    "\n",
+    "PE_PARAMS = {\n",
+    "    'gaussian' : [10, 0.25, 1, 20, 0.15, 2],\n",
+    "    'cauchy' : [10, 0.25, 1, 20, 0.15, 2],\n",
+    "    'skewed_gaussian' : [10, 0.25, 1, 5, 20, 0.15, 2, 7.5],\n",
+    "    'triangle' : [10, 0.25, 2, 25, 0.15, 4],\n",
+    "    #'gamma' : [X, X, X, X],\n",
+    "}\n",
+    "\n",
+    "nlv = 0.001"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "11d3afbf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define algorithm settings\n",
+    "model_settings = {'min_peak_height' : 0.1, 'max_n_peaks' : 6, 'peak_width_limits' : [0.5, 12]}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "6768acdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Generate combinations of all modes\n",
+    "mode_samples = product(*[list(AP_MODES.keys()), list(PE_MODES.keys())])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "7b4d5ada",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SIMULATED - AP: fixed, PE: triangle\n",
+      "==================================================================================================\n",
+      "                                                                                                  \n",
+      "                                       POWER SPECTRUM MODEL                                       \n",
+      "                                                                                                  \n",
+      "                       The model was fit with the 'spectral_fit' algorithm                        \n",
+      "              Model was fit to the 1-175 Hz frequency range with 0.50 Hz resolution               \n",
+      "                                                                                                  \n",
+      "                               Aperiodic Parameters ('fixed' mode)                                \n",
+      "                                        (offset, exponent)                                        \n",
+      "                                          1.0156, 0.7574                                          \n",
+      "                                                                                                  \n",
+      "                         Peak Parameters ('triangle' mode) 3 peaks found                          \n",
+      "                                CF:   9.00, PW:   0.13, BW:   0.85                                \n",
+      "                                CF:  10.00, PW:   0.29, BW:   1.70                                \n",
+      "                                CF:  25.00, PW:   0.18, BW:   4.25                                \n",
+      "                                                                                                  \n",
+      "                                          Model metrics:                                          \n",
+      "                                     error (mae) is 0.0048                                        \n",
+      "                                  gof (rsquared) is 0.9985                                        \n",
+      "                                                                                                  \n",
+      "==================================================================================================\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 850x650 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "c_ap_mode, c_pe_mode = next(mode_samples)\n",
+    "print('SIMULATED - AP: {}, PE: {}'.format(c_ap_mode, c_pe_mode))\n",
+    "freqs, powers = sim_power_spectrum(\\\n",
+    "    [1, 175], {c_ap_mode : AP_PARAMS[c_ap_mode]}, {c_pe_mode : PE_PARAMS[c_pe_mode]}, nlv)\n",
+    "fm = SpectralModel(aperiodic_mode=c_ap_mode, periodic_mode=c_pe_mode, \n",
+    "                   **model_settings, verbose=False)\n",
+    "fm.report(freqs, powers, plt_log=False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e9a5e913",
+   "metadata": {},
+   "source": [
+    "## SIMS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c02a744d",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# for ap_mode in AP_MODES:\n",
+    "#     for pe_mode in PE_MODES:\n",
+    "        \n",
+    "#         freqs, powers = sim_power_spectrum(\\\n",
+    "#             [1, 150], {ap_mode : AP_PARAMS[ap_mode]}, {pe_mode : PE_PARAMS[pe_mode]}, nlv)\n",
+    "#         plot_spectra(freqs, powers, log_freqs=True, log_powers=True,\n",
+    "#                      title='AP: {} - PE: {}'.format(ap_mode, pe_mode))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "14d65d9b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "51cd94df",
+   "metadata": {},
+   "source": [
+    "## MODELS"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b2b6105c",
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "# for ap_mode in AP_MODES:\n",
+    "#     for pe_mode in PE_MODES:\n",
+    "        \n",
+    "#         freqs, powers = sim_power_spectrum(\\\n",
+    "#             [3, 50], {ap_mode : AP_PARAMS[ap_mode]}, {pe_mode : PE_PARAMS[pe_mode]}, nlv)\n",
+    "        \n",
+    "#         fm = SpectralModel(aperiodic_mode=ap_mode, periodic_mode=pe_mode, verbose=False)\n",
+    "#         fm.report(freqs, powers, plt_log=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "cdf9635e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}