diff --git a/docs/tutorial.ipynb b/docs/tutorial.ipynb
index e6c8a6d..81ccdf5 100644
--- a/docs/tutorial.ipynb
+++ b/docs/tutorial.ipynb
@@ -1,240 +1 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "2d7ffdfb-77cf-4059-b545-5a8aa6fec4b3",
-   "metadata": {},
-   "source": [
-    "## Setup and imports"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "4c44c92f-bf2a-4933-b03f-889a468ae0d6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import echosms"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b3e8f2d9-2500-41e7-adb2-f833bdee5f15",
-   "metadata": {},
-   "source": [
-    "## What reference models are available?"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "581abbb1-b682-4db6-a39b-0d1cf1048c6a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['fixed rigid sphere',\n",
-       " 'pressure release sphere',\n",
-       " 'gas filled sphere',\n",
-       " 'weakly scattering sphere',\n",
-       " 'spherical fluid shell with pressure release interior',\n",
-       " 'spherical fluid shell with gas interior',\n",
-       " 'spherical fluid shell with weakly scattering interior',\n",
-       " 'fixed rigid prolate spheroid',\n",
-       " 'pressure release prolate spheroid',\n",
-       " 'gas filled prolate spheroid',\n",
-       " 'weakly scattering prolate spheroid',\n",
-       " 'fixed rigid finite cylinder',\n",
-       " 'pressure release finite cylinder',\n",
-       " 'gas filled finite cylinder',\n",
-       " 'weakly scattering finite cylinder']"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "rm = echosms.ReferenceModels()\n",
-    "rm.names()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f2e4182d-8818-41bb-86e1-8b3e5d6fc06a",
-   "metadata": {},
-   "source": [
-    "## Get a pre-defined model"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "05b33291-41f7-4f22-b993-8b5a8e0136f6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'boundary_type': 'fluid filled',\n",
-       " 'a': 0.01,\n",
-       " 'medium_rho': 1026.8,\n",
-       " 'medium_c': 1477.4,\n",
-       " 'target_rho': 1028.9,\n",
-       " 'target_c': 1480.3}"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "p=rm.parameters('weakly scattering sphere')\n",
-    "p"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "163c05bf-e940-420d-90d7-6435c39a1ad1",
-   "metadata": {},
-   "source": [
-    "## Add run-specific parameters\n",
-    "The parameters from the reference models don't include the angle or the frequency, so add those in. Any item in p can be a single value or a 1-dimensional iterable."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "491abb07-ffc0-480b-887a-2760123e474a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'boundary_type': 'fluid filled',\n",
-       " 'a': 0.01,\n",
-       " 'medium_rho': 1026.8,\n",
-       " 'medium_c': 1477.4,\n",
-       " 'target_rho': 1028.9,\n",
-       " 'target_c': 1480.3,\n",
-       " 'theta': 90,\n",
-       " 'f': array([ 10000.,  11000.,  12000.,  13000.,  14000.,  15000.,  16000.,\n",
-       "         17000.,  18000.,  19000.,  20000.,  21000.,  22000.,  23000.,\n",
-       "         24000.,  25000.,  26000.,  27000.,  28000.,  29000.,  30000.,\n",
-       "         31000.,  32000.,  33000.,  34000.,  35000.,  36000.,  37000.,\n",
-       "         38000.,  39000.,  40000.,  41000.,  42000.,  43000.,  44000.,\n",
-       "         45000.,  46000.,  47000.,  48000.,  49000.,  50000.,  51000.,\n",
-       "         52000.,  53000.,  54000.,  55000.,  56000.,  57000.,  58000.,\n",
-       "         59000.,  60000.,  61000.,  62000.,  63000.,  64000.,  65000.,\n",
-       "         66000.,  67000.,  68000.,  69000.,  70000.,  71000.,  72000.,\n",
-       "         73000.,  74000.,  75000.,  76000.,  77000.,  78000.,  79000.,\n",
-       "         80000.,  81000.,  82000.,  83000.,  84000.,  85000.,  86000.,\n",
-       "         87000.,  88000.,  89000.,  90000.,  91000.,  92000.,  93000.,\n",
-       "         94000.,  95000.,  96000.,  97000.,  98000.,  99000., 100000.,\n",
-       "        101000., 102000., 103000., 104000., 105000., 106000., 107000.,\n",
-       "        108000., 109000., 110000., 111000., 112000., 113000., 114000.,\n",
-       "        115000., 116000., 117000., 118000., 119000., 120000., 121000.,\n",
-       "        122000., 123000., 124000., 125000., 126000., 127000., 128000.,\n",
-       "        129000., 130000., 131000., 132000., 133000., 134000., 135000.,\n",
-       "        136000., 137000., 138000., 139000., 140000., 141000., 142000.,\n",
-       "        143000., 144000., 145000., 146000., 147000., 148000., 149000.,\n",
-       "        150000., 151000., 152000., 153000., 154000., 155000., 156000.,\n",
-       "        157000., 158000., 159000., 160000., 161000., 162000., 163000.,\n",
-       "        164000., 165000., 166000., 167000., 168000., 169000., 170000.,\n",
-       "        171000., 172000., 173000., 174000., 175000., 176000., 177000.,\n",
-       "        178000., 179000., 180000., 181000., 182000., 183000., 184000.,\n",
-       "        185000., 186000., 187000., 188000., 189000., 190000., 191000.,\n",
-       "        192000., 193000., 194000., 195000., 196000., 197000., 198000.,\n",
-       "        199000.])}"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "p['theta']=90\n",
-    "p['f']=np.arange(10,200,1)*1e3\n",
-    "p"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "00bfc9bd-7096-4c96-8931-f3d524941e77",
-   "metadata": {},
-   "source": [
-    "## Choose and run the model\n",
-    "We'll now run the modal series solution model using these parameters. The model takes care of getting all the possible combinations of the parameters in p. "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "a4bd1426-735c-4bd1-902e-bdf10ee333e9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x1309a8a8e10>]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1800x1200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "mss = echosms.MSSModel()\n",
-    "ts = mss.calculate_ts(p)\n",
-    "plt.plot(p['f']/1000,  ts)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "175f57d0-cfeb-4654-b7c5-691ff24e45c7",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (Spyder)",
-   "language": "python3",
-   "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": "3.11.9"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
+{"cells":[{"cell_type":"markdown","metadata":{},"source":["## Tutorial \n","\n","This notebook provides an introductory tutorial for echoSMs."]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"collapsed":true,"executionInfo":{"elapsed":10231,"status":"ok","timestamp":1724374592133,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"vvvd0_LuowDN","outputId":"6ebbda45-32d1-4c4b-9ea2-85dbf1326efd"},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting echosms\n","  Downloading echosms-0.1.2-py3-none-any.whl.metadata (10 kB)\n","Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (from echosms) (3.7.1)\n","Collecting mkdocstrings[python] (from echosms)\n","  Downloading mkdocstrings-0.25.2-py3-none-any.whl.metadata (7.6 kB)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from echosms) (1.26.4)\n","Requirement 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echosms"]},{"cell_type":"markdown","metadata":{"id":"K9izbBdpuj30"},"source":["## Imports\n","\n","We import the modal series solution model from echoSMs and the benchmark data and reference models."]},{"cell_type":"code","execution_count":4,"metadata":{"executionInfo":{"elapsed":2521,"status":"ok","timestamp":1724374603926,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"yzcGKsBuo2Hj"},"outputs":[],"source":["from echosms import MSSModel, BenchmarkData, ReferenceModels\n","import matplotlib.pyplot as plt\n","import numpy as np"]},{"cell_type":"markdown","metadata":{"id":"V1uNxsWfraXn"},"source":["## Reference models\n","The reference models in the Jech et al (2015) paper are available in the echoSMs package:"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2,"status":"ok","timestamp":1724374610285,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"o2J4jrvvo_OL","outputId":"1506a818-16c5-4892-ac2d-311bd4f69eb2"},"outputs":[{"name":"stdout","output_type":"stream","text":["Available reference models are:\n","\n","fixed rigid sphere\n","pressure release sphere\n","gas filled sphere\n","weakly scattering sphere\n","spherical fluid shell with pressure release interior\n","spherical fluid shell with gas interior\n","spherical fluid shell with weakly scattering interior\n","fixed rigid prolate spheroid\n","pressure release prolate spheroid\n","gas filled prolate spheroid\n","weakly scattering prolate spheroid\n","fixed rigid finite cylinder\n","pressure release finite cylinder\n","gas filled finite cylinder\n","weakly scattering finite cylinder\n","WC38.1 calibration sphere\n","Cu60 calibration sphere\n"]}],"source":["rm = ReferenceModels()\n","print('Available reference models are:\\n')\n","print('\\n'.join(rm.names()))"]},{"cell_type":"markdown","metadata":{"id":"uz4JhAIArmZA"},"source":["## Benchmark results\n","Likewise, the results from the benchmark model runs in the Jech et al (2015) paper are available in the echoSMs package."]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":444},"executionInfo":{"elapsed":6,"status":"ok","timestamp":1724374618002,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"HV8YqRUDpDfF","outputId":"4e851e6c-2280-4f4a-cc5a-41052994e26b"},"outputs":[{"data":{"application/vnd.google.colaboratory.intrinsic+json":{"summary":"{\n  \"name\": \"bmf\",\n  \"rows\": 195,\n  \"fields\": [\n    {\n      \"column\": \"Frequency_kHz\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 112,\n        \"min\": 12,\n        \"max\": 400,\n        \"num_unique_values\": 195,\n        \"samples\": [\n          288,\n     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<th>Cylinder_PressureRelease</th>\n","      <th>Cylinder_Gas</th>\n","      <th>Cylinder_WeaklyScattering</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>12</td>\n","      <td>-54.44</td>\n","      <td>-42.29</td>\n","      <td>-42.34</td>\n","      <td>-103.95</td>\n","      <td>-42.83</td>\n","      <td>-42.80</td>\n","      <td>-99.15</td>\n","      <td>-35.98</td>\n","      <td>-30.16</td>\n","      <td>NaN</td>\n","      <td>-87.05</td>\n","      <td>-38.75</td>\n","      <td>-35.29</td>\n","      <td>-35.30</td>\n","      <td>-89.79</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>14</td>\n","      <td>-52.20</td>\n","      <td>-42.92</td>\n","      <td>-42.93</td>\n","      <td>-101.62</td>\n","      <td>-43.40</td>\n","      <td>-43.44</td>\n","      <td>-96.79</td>\n","      <td>-33.83</td>\n","      <td>-30.02</td>\n","      <td>NaN</td>\n","      <td>-84.71</td>\n","      <td>-36.83</td>\n","      <td>-34.93</td>\n","      <td>-34.93</td>\n","      <td>-87.54</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>16</td>\n","      <td>-50.40</td>\n","      <td>-43.52</td>\n","      <td>-43.52</td>\n","      <td>-99.69</td>\n","      <td>-43.96</td>\n","      <td>-43.99</td>\n","      <td>-94.83</td>\n","      <td>-32.20</td>\n","      <td>-29.87</td>\n","      <td>NaN</td>\n","      <td>-82.78</td>\n","      <td>-35.45</td>\n","      <td>-34.56</td>\n","      <td>-34.56</td>\n","      <td>-85.73</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>18</td>\n","      <td>-48.96</td>\n","      <td>-44.02</td>\n","      <td>-44.03</td>\n","      <td>-98.10</td>\n","      <td>-44.49</td>\n","      <td>-44.51</td>\n","      <td>-93.20</td>\n","      <td>-30.97</td>\n","      <td>-29.70</td>\n","      <td>NaN</td>\n","      <td>-81.19</td>\n","      <td>-34.51</td>\n","      <td>-34.17</td>\n","      <td>-34.18</td>\n","      <td>-84.27</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>20</td>\n","      <td>-47.85</td>\n","      <td>-44.39</td>\n","      <td>-44.40</td>\n","      <td>-96.79</td>\n","      <td>-44.94</td>\n","      <td>-44.97</td>\n","      <td>-91.85</td>\n","      <td>-30.08</td>\n","      <td>-29.54</td>\n","      <td>NaN</td>\n","      <td>-79.87</td>\n","      <td>-33.95</td>\n","      <td>-33.80</td>\n","      <td>-33.81</td>\n","      <td>-83.12</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>190</th>\n","      <td>392</td>\n","      <td>-45.96</td>\n","      <td>-46.00</td>\n","      <td>-46.03</td>\n","      <td>-103.61</td>\n","      <td>-46.91</td>\n","      <td>-46.88</td>\n","      <td>-108.29</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>-86.94</td>\n","      <td>-21.74</td>\n","      <td>-21.86</td>\n","      <td>-21.92</td>\n","      <td>-70.78</td>\n","    </tr>\n","    <tr>\n","      <th>191</th>\n","      <td>394</td>\n","      <td>-45.86</td>\n","      <td>-46.00</td>\n","      <td>-45.96</td>\n","      <td>-100.25</td>\n","      <td>-46.91</td>\n","      <td>-46.78</td>\n","      <td>-107.19</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>-83.45</td>\n","      <td>-21.72</td>\n","      <td>-21.84</td>\n","      <td>-21.83</td>\n","      <td>-70.14</td>\n","    </tr>\n","    <tr>\n","      <th>192</th>\n","      <td>396</td>\n","      <td>-45.80</td>\n","      <td>-46.00</td>\n","      <td>-46.07</td>\n","      <td>-98.03</td>\n","      <td>-46.91</td>\n","      <td>-46.75</td>\n","      <td>-106.49</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>-81.16</td>\n","      <td>-21.70</td>\n","      <td>-21.82</td>\n","      <td>-21.82</td>\n","      <td>-69.78</td>\n","    </tr>\n","    <tr>\n","      <th>193</th>\n","      <td>398</td>\n","      <td>-45.80</td>\n","      <td>-46.00</td>\n","      <td>-45.96</td>\n","      <td>-96.47</td>\n","      <td>-46.91</td>\n","      <td>-46.99</td>\n","      <td>-106.14</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>-79.55</td>\n","      <td>-21.68</td>\n","      <td>-21.80</td>\n","      <td>-21.79</td>\n","      <td>-69.68</td>\n","    </tr>\n","    <tr>\n","      <th>194</th>\n","      <td>400</td>\n","      <td>-45.84</td>\n","      <td>-46.00</td>\n","      <td>-46.05</td>\n","      <td>-95.37</td>\n","      <td>-46.91</td>\n","      <td>-46.94</td>\n","      <td>-106.15</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>-78.41</td>\n","      <td>-21.65</td>\n","      <td>-21.77</td>\n","      <td>-21.79</td>\n","      <td>-69.83</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>195 rows × 16 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-15151d60-44b5-4b11-a92c-c9603c983b01')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      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         398        -45.80                  -46.00      -45.96   \n","194            400        -45.84                  -46.00      -46.05   \n","\n","     Sphere_WeaklyScattering  ShellSphere_PressureRelease  ShellSphere_Gas  \\\n","0                    -103.95                       -42.83           -42.80   \n","1                    -101.62                       -43.40           -43.44   \n","2                     -99.69                       -43.96           -43.99   \n","3                     -98.10                       -44.49           -44.51   \n","4                     -96.79                       -44.94           -44.97   \n","..                       ...                          ...              ...   \n","190                  -103.61                       -46.91           -46.88   \n","191                  -100.25                       -46.91           -46.78   \n","192                   -98.03                       -46.91           -46.75   \n","193                   -96.47                       -46.91           -46.99   \n","194                   -95.37                       -46.91           -46.94   \n","\n","     ShellSphere_WeaklyScattering  ProlateSpheroid_Rigid  \\\n","0                          -99.15                 -35.98   \n","1                          -96.79                 -33.83   \n","2                          -94.83                 -32.20   \n","3                          -93.20                 -30.97   \n","4                          -91.85                 -30.08   \n","..                            ...                    ...   \n","190                       -108.29                    NaN   \n","191                       -107.19                    NaN   \n","192                       -106.49                    NaN   \n","193                       -106.14                    NaN   \n","194                       -106.15                    NaN   \n","\n","     ProlateSpheroid_PressureRelease  ProlateSpheroid_Gas  \\\n","0                             -30.16                  NaN   \n","1                             -30.02                  NaN   \n","2                             -29.87                  NaN   \n","3                             -29.70                  NaN   \n","4                             -29.54                  NaN   \n","..                               ...                  ...   \n","190                              NaN                  NaN   \n","191                              NaN                  NaN   \n","192                              NaN                  NaN   \n","193                              NaN                  NaN   \n","194                              NaN                  NaN   \n","\n","     ProlateSpheroid_WeaklyScattering  Cylinder_Rigid  \\\n","0                              -87.05          -38.75   \n","1                              -84.71          -36.83   \n","2                              -82.78          -35.45   \n","3                              -81.19          -34.51   \n","4                              -79.87          -33.95   \n","..                                ...             ...   \n","190                            -86.94          -21.74   \n","191                            -83.45          -21.72   \n","192                            -81.16          -21.70   \n","193                            -79.55          -21.68   \n","194                            -78.41          -21.65   \n","\n","     Cylinder_PressureRelease  Cylinder_Gas  Cylinder_WeaklyScattering  \n","0                      -35.29        -35.30                     -89.79  \n","1                      -34.93        -34.93                     -87.54  \n","2                      -34.56        -34.56                     -85.73  \n","3                      -34.17        -34.18                     -84.27  \n","4                      -33.80        -33.81                     -83.12  \n","..                        ...           ...                        ...  \n","190                    -21.86        -21.92                     -70.78  \n","191                    -21.84        -21.83                     -70.14  \n","192                    -21.82        -21.82                     -69.78  \n","193                    -21.80        -21.79                     -69.68  \n","194                    -21.77        -21.79                     -69.83  \n","\n","[195 rows x 16 columns]"]},"execution_count":6,"metadata":{},"output_type":"execute_result"}],"source":["bm = BenchmarkData()\n","bmf = bm.freq_dataset  # this is a Pandas DataFrame\n","bmf"]},{"cell_type":"markdown","metadata":{"id":"SreX_FuOr9US"},"source":["## Creating the model parameters\n","\n","We can now get the model parameters and results for a given model in the Jech et al (2015) paper and run the same model using the echoSMs package and compare them. First step is to get the model parameters for a model - we choose the weakly scattering sphere for this example:"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":364,"status":"ok","timestamp":1724374636656,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"jynjQr3lpIBp","outputId":"c0307411-2e0c-48d0-bdb9-8b052e5e8239"},"outputs":[{"data":{"text/plain":["{'boundary_type': 'fluid filled',\n"," 'a': 0.01,\n"," 'medium_rho': 1026.8,\n"," 'medium_c': 1477.4,\n"," 'target_rho': 1028.9,\n"," 'target_c': 1480.3}"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["\n","m = rm.parameters('weakly scattering sphere')\n","m"]},{"cell_type":"markdown","metadata":{"id":"wUh0d2QTrUpq"},"source":["These parameters need to have an angle and frequency range added. We will use the frequencies from the Jech et al (2015) paper to make comparisons simplier."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":571,"status":"ok","timestamp":1724373610677,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"RTXejojmpQqC","outputId":"1130042a-0942-4d05-c3aa-80429019f1b6"},"outputs":[{"data":{"text/plain":["{'boundary_type': 'fluid filled',\n"," 'a': 0.01,\n"," 'medium_rho': 1026.8,\n"," 'medium_c': 1477.4,\n"," 'target_rho': 1028.9,\n"," 'target_c': 1480.3,\n"," 'f': 0       12000.0\n"," 1       14000.0\n"," 2       16000.0\n"," 3       18000.0\n"," 4       20000.0\n","          ...   \n"," 190    392000.0\n"," 191    394000.0\n"," 192    396000.0\n"," 193    398000.0\n"," 194    400000.0\n"," Name: Frequency_kHz, Length: 195, dtype: float64,\n"," 'theta': 90}"]},"execution_count":24,"metadata":{},"output_type":"execute_result"}],"source":["m['f'] = bm.freq_dataset['Frequency_kHz']*1e3\n","m['theta'] = 90\n","m"]},{"cell_type":"markdown","metadata":{"id":"FL-vhBY2qStT"},"source":["## Calculating target strength\n","\n","The reference model for a weakly scattering sphere was the model series solution, so we create an instance of that model in echoSMs and get it to calculate the target strength as per the parameters in ``m``.\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Di4CFovupSGx"},"outputs":[],"source":["mod = MSSModel()\n","ts = mod.calculate_ts(m)"]},{"cell_type":"markdown","metadata":{"id":"bZP9vgKAqqwI"},"source":["## Comparison to existing target strength\n","\n","These results can be compared to those from the Jech et al (2015) paper. We can also calculate the mean difference between the Jech values and those from the echoSMs calculations."]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":497},"executionInfo":{"elapsed":2206,"status":"ok","timestamp":1724374342091,"user":{"displayName":"Gavin Macaulay","userId":"15996873107556149664"},"user_tz":-720},"id":"cXTE9u-TpumE","outputId":"46e575e0-361a-4f1e-eebe-acc8f90dbbef"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 640x480 with 2 Axes>"]},"metadata":{},"output_type":"display_data"}],"source":["jech_index = np.mean(np.abs(ts - bmf['Sphere_WeaklyScattering']))\n","\n","fig, axs = plt.subplots(2, 1, sharex=True)\n","\n","axs[0].plot(m['f']/1e3, ts, label='echoSMs')\n","axs[0].plot(bmf['Frequency_kHz'], bmf['Sphere_WeaklyScattering'], label='Benchmark')\n","axs[0].set_ylabel('TS re 1 m$^2$ [dB]')\n","axs[0].legend(frameon=False, fontsize=6)\n","\n","axs[1].plot(m['f']*1e-3, ts-bmf['Sphere_WeaklyScattering'])\n","axs[1].set_xlabel('Frequency [kHz]')\n","axs[1].set_ylabel(r'$\\Delta$ TS [dB]')\n","axs[1].annotate(f'{jech_index:.2f} dB', (0.05, 0.80), xycoords='axes fraction',\n","                    backgroundcolor=[.8, .8, .8])\n","_ = plt.suptitle('Weakly scattering sphere')"]},{"cell_type":"markdown","metadata":{"id":"QOHyiEE-vkbr"},"source":["There is a 0.15 dB difference between the echoSMs results and those from the Jech et al (2015) paper. We don't know why (comparisons of other models and parameters give near identical results - it is just the weakly scattering models that don't agree)."]}],"metadata":{"colab":{"authorship_tag":"ABX9TyOLhNe1NqPbGufGbKTfWjEp","provenance":[{"file_id":"1EPUlnNihQmkFtk5OvXHN0B0MUKSTvMkX","timestamp":1724374399220}]},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}
diff --git a/pyproject.toml b/pyproject.toml
index d39a01c..9868ba2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,7 +7,7 @@ packages = ["src/echosms"]
 
 [project]
 name = 'echosms'
-version = '0.1.1'
+version = '0.1.2'
 license = {file = "LICENSE"}
 keywords = ["acoustic", "backscatter", "model"]
 authors = [