diff --git a/notebooks/DFY_JEFF4_somenuclides.csv b/notebooks/DFY_JEFF4_somenuclides.csv
new file mode 100644
index 00000000..66a735e3
--- /dev/null
+++ b/notebooks/DFY_JEFF4_somenuclides.csv
@@ -0,0 +1,5 @@
+,Sr90,Cs137,Nd143,Nd144,Nd145,Nd146,Nd147,Nd148,Nd150
+C1,0.0014861,0.0016991,0.0013823,0.001276,0.00097696,0.00079095,0.00062539,0.00049911,0.00022425
+C2,0.0014864,0.0016995,0.0013826,0.0012764,0.00097723,0.00079116,0.00062556,0.00049925,0.00022432
+S1,0.0005934,0.00062325,0.00038788,0.00037033,0.00026744,0.00024771,0.00015465,0.00014863,8.92E-05
+S2,0.00059185,0.00069341,0.00049725,0.00047699,0.00041763,0.00038723,0.0001742,0.00020622,0.0001283
diff --git a/notebooks/FY_JEFF4_somenuclides.csv b/notebooks/FY_JEFF4_somenuclides.csv
new file mode 100644
index 00000000..660df898
--- /dev/null
+++ b/notebooks/FY_JEFF4_somenuclides.csv
@@ -0,0 +1,5 @@
+,Sr90,Cs137,Nd143,Nd144,Nd145,Nd146,Nd147,Nd148,Nd150
+C1,0.058063,0.062481,0.05942,0.054862,0.040262,0.029925,0.022534,0.016781,0.0065965
+C2,0.058076,0.062496,0.059434,0.054875,0.040272,0.029932,0.02254,0.016785,0.0065981
+S1,0.058572,0.061308,0.060302,0.055722,0.039164,0.029986,0.022025,0.016738,0.006543
+S2,0.058479,0.063435,0.060491,0.055845,0.041049,0.029843,0.021911,0.016644,0.0065125
diff --git a/notebooks/notebook_fy_check_jeff4.ipynb b/notebooks/notebook_fy_check_jeff4.ipynb
new file mode 100644
index 00000000..c111ac83
--- /dev/null
+++ b/notebooks/notebook_fy_check_jeff4.ipynb
@@ -0,0 +1,563 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "88c48db4",
+   "metadata": {},
+   "source": [
+    "# Checking FYs for JEFF-4.0"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "1e516fe1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sandy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "32b98f35",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "sns.set_style(\"ticks\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "id": "338794b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 67,
+   "id": "abb6e9ab",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_csv(\"FY_JEFF4_somenuclides.csv\", index_col=0)\n",
+    "dferr = pd.read_csv(\"DFY_JEFF4_somenuclides.csv\", index_col=0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 68,
+   "id": "f76bd98e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "nuclides = [380900, 551370, 601430, 601450, 601440,  601450,  601460,  601470,  601480,  601500]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "id": "84bf27f2",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fy = sandy.get_endf6_file(\"jeff_33\", \"nfpy\", 922350)\n",
+    "d = sandy.Fy.from_endf6(fy).data.query(\"MT==459 & E==2.53e-2\")\n",
+    "d_33 = d[d.ZAP.isin(nuclides)].assign(LIB=\"JEFF-3.3\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "id": "13e4d1c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fy = sandy.get_endf6_file(\"jeff_311\", \"nfpy\", 922350)\n",
+    "d = sandy.Fy.from_endf6(fy).data.query(\"MT==459 & E==2.53e-2\")\n",
+    "d_311 = d[d.ZAP.isin(nuclides)].assign(LIB=\"JEFF-3.1.1\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "id": "a7840782",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = pd.concat([\n",
+    "    d_311,\n",
+    "    d_33,\n",
+    "], ignore_index=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "id": "b037aec7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Sr90</th>\n",
+       "      <th>Cs137</th>\n",
+       "      <th>Nd143</th>\n",
+       "      <th>Nd144</th>\n",
+       "      <th>Nd145</th>\n",
+       "      <th>Nd146</th>\n",
+       "      <th>Nd147</th>\n",
+       "      <th>Nd148</th>\n",
+       "      <th>Nd150</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C1</th>\n",
+       "      <td>5.80630e-02</td>\n",
+       "      <td>6.24810e-02</td>\n",
+       "      <td>5.94200e-02</td>\n",
+       "      <td>5.48620e-02</td>\n",
+       "      <td>4.02620e-02</td>\n",
+       "      <td>2.99250e-02</td>\n",
+       "      <td>2.25340e-02</td>\n",
+       "      <td>1.67810e-02</td>\n",
+       "      <td>6.59650e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C2</th>\n",
+       "      <td>5.80760e-02</td>\n",
+       "      <td>6.24960e-02</td>\n",
+       "      <td>5.94340e-02</td>\n",
+       "      <td>5.48750e-02</td>\n",
+       "      <td>4.02720e-02</td>\n",
+       "      <td>2.99320e-02</td>\n",
+       "      <td>2.25400e-02</td>\n",
+       "      <td>1.67850e-02</td>\n",
+       "      <td>6.59810e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S1</th>\n",
+       "      <td>5.85720e-02</td>\n",
+       "      <td>6.13080e-02</td>\n",
+       "      <td>6.03020e-02</td>\n",
+       "      <td>5.57220e-02</td>\n",
+       "      <td>3.91640e-02</td>\n",
+       "      <td>2.99860e-02</td>\n",
+       "      <td>2.20250e-02</td>\n",
+       "      <td>1.67380e-02</td>\n",
+       "      <td>6.54300e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S2</th>\n",
+       "      <td>5.84790e-02</td>\n",
+       "      <td>6.34350e-02</td>\n",
+       "      <td>6.04910e-02</td>\n",
+       "      <td>5.58450e-02</td>\n",
+       "      <td>4.10490e-02</td>\n",
+       "      <td>2.98430e-02</td>\n",
+       "      <td>2.19110e-02</td>\n",
+       "      <td>1.66440e-02</td>\n",
+       "      <td>6.51250e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>JEFF-3.1.1</th>\n",
+       "      <td>5.72900e-02</td>\n",
+       "      <td>6.22080e-02</td>\n",
+       "      <td>5.95410e-02</td>\n",
+       "      <td>5.47450e-02</td>\n",
+       "      <td>3.94390e-02</td>\n",
+       "      <td>2.98660e-02</td>\n",
+       "      <td>2.23200e-02</td>\n",
+       "      <td>1.68080e-02</td>\n",
+       "      <td>6.50740e-03</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>JEFF-3.3</th>\n",
+       "      <td>5.67590e-02</td>\n",
+       "      <td>6.08970e-02</td>\n",
+       "      <td>5.95220e-02</td>\n",
+       "      <td>5.47810e-02</td>\n",
+       "      <td>3.95600e-02</td>\n",
+       "      <td>2.99690e-02</td>\n",
+       "      <td>2.24650e-02</td>\n",
+       "      <td>1.69270e-02</td>\n",
+       "      <td>6.53770e-03</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Sr90       Cs137       Nd143       Nd144       Nd145  \\\n",
+       "C1         5.80630e-02 6.24810e-02 5.94200e-02 5.48620e-02 4.02620e-02   \n",
+       "C2         5.80760e-02 6.24960e-02 5.94340e-02 5.48750e-02 4.02720e-02   \n",
+       "S1         5.85720e-02 6.13080e-02 6.03020e-02 5.57220e-02 3.91640e-02   \n",
+       "S2         5.84790e-02 6.34350e-02 6.04910e-02 5.58450e-02 4.10490e-02   \n",
+       "JEFF-3.1.1 5.72900e-02 6.22080e-02 5.95410e-02 5.47450e-02 3.94390e-02   \n",
+       "JEFF-3.3   5.67590e-02 6.08970e-02 5.95220e-02 5.47810e-02 3.95600e-02   \n",
+       "\n",
+       "                 Nd146       Nd147       Nd148       Nd150  \n",
+       "C1         2.99250e-02 2.25340e-02 1.67810e-02 6.59650e-03  \n",
+       "C2         2.99320e-02 2.25400e-02 1.67850e-02 6.59810e-03  \n",
+       "S1         2.99860e-02 2.20250e-02 1.67380e-02 6.54300e-03  \n",
+       "S2         2.98430e-02 2.19110e-02 1.66440e-02 6.51250e-03  \n",
+       "JEFF-3.1.1 2.98660e-02 2.23200e-02 1.68080e-02 6.50740e-03  \n",
+       "JEFF-3.3   2.99690e-02 2.24650e-02 1.69270e-02 6.53770e-03  "
+      ]
+     },
+     "execution_count": 72,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vals = data.query(\"ZAM==922350\").pivot_table(index=\"LIB\", columns=\"ZAP\", values=\"FY\")\n",
+    "vals.columns = pd.Index(map(sandy.zam.zam2nuclide, vals.columns), name=\"ZAP\")\n",
+    "vals = pd.concat([df, vals])\n",
+    "vals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "id": "1e563113",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Sr90</th>\n",
+       "      <th>Cs137</th>\n",
+       "      <th>Nd143</th>\n",
+       "      <th>Nd144</th>\n",
+       "      <th>Nd145</th>\n",
+       "      <th>Nd146</th>\n",
+       "      <th>Nd147</th>\n",
+       "      <th>Nd148</th>\n",
+       "      <th>Nd150</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>C1</th>\n",
+       "      <td>1.48610e-03</td>\n",
+       "      <td>1.69910e-03</td>\n",
+       "      <td>1.38230e-03</td>\n",
+       "      <td>1.27600e-03</td>\n",
+       "      <td>9.76960e-04</td>\n",
+       "      <td>7.90950e-04</td>\n",
+       "      <td>6.25390e-04</td>\n",
+       "      <td>4.99110e-04</td>\n",
+       "      <td>2.24250e-04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C2</th>\n",
+       "      <td>1.48640e-03</td>\n",
+       "      <td>1.69950e-03</td>\n",
+       "      <td>1.38260e-03</td>\n",
+       "      <td>1.27640e-03</td>\n",
+       "      <td>9.77230e-04</td>\n",
+       "      <td>7.91160e-04</td>\n",
+       "      <td>6.25560e-04</td>\n",
+       "      <td>4.99250e-04</td>\n",
+       "      <td>2.24320e-04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S1</th>\n",
+       "      <td>5.93400e-04</td>\n",
+       "      <td>6.23250e-04</td>\n",
+       "      <td>3.87880e-04</td>\n",
+       "      <td>3.70330e-04</td>\n",
+       "      <td>2.67440e-04</td>\n",
+       "      <td>2.47710e-04</td>\n",
+       "      <td>1.54650e-04</td>\n",
+       "      <td>1.48630e-04</td>\n",
+       "      <td>8.92000e-05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>S2</th>\n",
+       "      <td>5.91850e-04</td>\n",
+       "      <td>6.93410e-04</td>\n",
+       "      <td>4.97250e-04</td>\n",
+       "      <td>4.76990e-04</td>\n",
+       "      <td>4.17630e-04</td>\n",
+       "      <td>3.87230e-04</td>\n",
+       "      <td>1.74200e-04</td>\n",
+       "      <td>2.06220e-04</td>\n",
+       "      <td>1.28300e-04</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>JEFF-3.1.1</th>\n",
+       "      <td>1.31920e-03</td>\n",
+       "      <td>6.93580e-04</td>\n",
+       "      <td>8.33760e-04</td>\n",
+       "      <td>5.47200e-04</td>\n",
+       "      <td>4.34030e-04</td>\n",
+       "      <td>2.98670e-04</td>\n",
+       "      <td>4.01760e-04</td>\n",
+       "      <td>1.17600e-04</td>\n",
+       "      <td>6.50750e-05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>JEFF-3.3</th>\n",
+       "      <td>1.30680e-03</td>\n",
+       "      <td>6.32840e-04</td>\n",
+       "      <td>7.14390e-04</td>\n",
+       "      <td>4.92120e-04</td>\n",
+       "      <td>3.96460e-04</td>\n",
+       "      <td>2.99710e-04</td>\n",
+       "      <td>3.81910e-04</td>\n",
+       "      <td>1.18300e-04</td>\n",
+       "      <td>6.53910e-05</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  Sr90       Cs137       Nd143       Nd144       Nd145  \\\n",
+       "C1         1.48610e-03 1.69910e-03 1.38230e-03 1.27600e-03 9.76960e-04   \n",
+       "C2         1.48640e-03 1.69950e-03 1.38260e-03 1.27640e-03 9.77230e-04   \n",
+       "S1         5.93400e-04 6.23250e-04 3.87880e-04 3.70330e-04 2.67440e-04   \n",
+       "S2         5.91850e-04 6.93410e-04 4.97250e-04 4.76990e-04 4.17630e-04   \n",
+       "JEFF-3.1.1 1.31920e-03 6.93580e-04 8.33760e-04 5.47200e-04 4.34030e-04   \n",
+       "JEFF-3.3   1.30680e-03 6.32840e-04 7.14390e-04 4.92120e-04 3.96460e-04   \n",
+       "\n",
+       "                 Nd146       Nd147       Nd148       Nd150  \n",
+       "C1         7.90950e-04 6.25390e-04 4.99110e-04 2.24250e-04  \n",
+       "C2         7.91160e-04 6.25560e-04 4.99250e-04 2.24320e-04  \n",
+       "S1         2.47710e-04 1.54650e-04 1.48630e-04 8.92000e-05  \n",
+       "S2         3.87230e-04 1.74200e-04 2.06220e-04 1.28300e-04  \n",
+       "JEFF-3.1.1 2.98670e-04 4.01760e-04 1.17600e-04 6.50750e-05  \n",
+       "JEFF-3.3   2.99710e-04 3.81910e-04 1.18300e-04 6.53910e-05  "
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "err = data.query(\"ZAM==922350\").pivot_table(index=\"LIB\", columns=\"ZAP\", values=\"DFY\")\n",
+    "err.columns = pd.Index(map(sandy.zam.zam2nuclide, err.columns), name=\"ZAP\")\n",
+    "err = pd.concat([dferr, err])\n",
+    "err"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 118,
+   "id": "0180b4bf",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 3000x1440 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%capture --no-display\n",
+    "fig, ax = plt.subplots(figsize=(10, 4.8), dpi=300)\n",
+    "\n",
+    "vals2 = (vals/vals.iloc[-1] - 1)*100 \n",
+    "err2 = err/vals.iloc[-1]*100\n",
+    "err2 = err/vals*100\n",
+    "step = 1 / (vals2.T.columns.size + 1)\n",
+    "for i, LIB in enumerate(vals2.T.columns):\n",
+    "    x = np.arange(vals2.T[LIB].shape[0])\n",
+    "    ax.bar(data=vals2.T[LIB].reset_index(), x=x+i*step, height=LIB, yerr=err2.T[LIB], capsize=2, width=step)\n",
+    "ax.legend(labels=vals2.T.columns)\n",
+    "ticks = ax.get_xticks()\n",
+    "ax.set_xticklabels(vals2.columns.values)\n",
+    "ax.set_xticks(np.arange(len(vals2.columns)) + step)\n",
+    "ax.set(\n",
+    "    ylabel=\"CFY deviation from JEFF-3.3 $\\\\pm 1\\\\sigma$\",\n",
+    ")\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "id": "2cab4fd9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1000x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%capture --no-display\n",
+    "fig, ax = plt.subplots(figsize=(10, 4.8), dpi=100)\n",
+    "\n",
+    "vals2 = (vals/vals.iloc[-2] - 1)*100 \n",
+    "err2 = err/vals*100\n",
+    "step = 1 / (vals2.T.columns.size + 1)\n",
+    "for i, LIB in enumerate(vals2.T.columns):\n",
+    "    x = np.arange(vals2.T[LIB].shape[0])\n",
+    "    ax.bar(data=vals2.T[LIB].reset_index(), x=x+i*step, height=LIB, yerr=err2.T[LIB], capsize=2, width=step)\n",
+    "ax.legend(labels=vals2.T.columns)\n",
+    "ticks = ax.get_xticks()\n",
+    "ax.set_xticklabels(vals2.columns.values)\n",
+    "ax.set_xticks(np.arange(len(vals2.columns)) + step)\n",
+    "ax.set(\n",
+    "    ylabel=\"CFY deviation from JEFF-3.1.1 $\\\\pm 1\\\\sigma$\",\n",
+    ")\n",
+    "fig.tight_layout();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "id": "25fbcca7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 3000x1440 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%%capture --no-display\n",
+    "fig, axs = plt.subplots(1, 3, figsize=(10, 4.8), dpi=300, gridspec_kw={'width_ratios': [4, 1, 1]})\n",
+    "\n",
+    "ax = axs[0]\n",
+    "vals2 = vals.iloc[:, :4]\n",
+    "err2 = err.iloc[:, :4]\n",
+    "step = 1 / (vals2.T.columns.size + 1)\n",
+    "for i, LIB in enumerate(vals2.T.columns):\n",
+    "    x = np.arange(vals2.T[LIB].shape[0])\n",
+    "    ax.bar(data=vals2.T[LIB].reset_index(), x=x+i*step, height=LIB, yerr=err2.T[LIB], capsize=2, width=step)\n",
+    "ax.legend(labels=vals2.T.columns, ncol=2)\n",
+    "ticks = ax.get_xticks()\n",
+    "ax.set_xticklabels(vals2.columns.values)\n",
+    "ax.set_xticks(np.arange(len(vals2.columns)) + step)\n",
+    "ax.set(\n",
+    "    ylabel=\"cumulative fission yield $\\\\pm 1\\\\sigma$\",\n",
+    "    ylim=(.05, None),\n",
+    ")\n",
+    "\n",
+    "ax = axs[1]\n",
+    "vals2 = vals.iloc[:, 4:5]\n",
+    "err2 = err.iloc[:, 4:5]\n",
+    "step = 1 / (vals2.T.columns.size + 1)\n",
+    "for i, LIB in enumerate(vals2.T.columns):\n",
+    "    x = np.arange(vals2.T[LIB].shape[0])\n",
+    "    ax.bar(data=vals2.T[LIB].reset_index(), x=x+i*step, height=LIB, yerr=err2.T[LIB], capsize=2, width=step)\n",
+    "ax.legend(labels=vals2.T.columns)\n",
+    "ticks = ax.get_xticks()\n",
+    "ax.set_xticklabels(vals2.columns.values)\n",
+    "ax.set_xticks(np.arange(len(vals2.columns)) + step)\n",
+    "ax.get_legend().remove()\n",
+    "ax.set(\n",
+    "    ylabel=None,\n",
+    "    ylim=(.038, 0.042),\n",
+    ")\n",
+    "\n",
+    "ax = axs[2]\n",
+    "vals2 = vals.iloc[:, 7:8]\n",
+    "err2 = err.iloc[:, 7:8]\n",
+    "step = 1 / (vals2.T.columns.size + 1)\n",
+    "for i, LIB in enumerate(vals2.T.columns):\n",
+    "    x = np.arange(vals2.T[LIB].shape[0])\n",
+    "    ax.bar(data=vals2.T[LIB].reset_index(), x=x+i*step, height=LIB, yerr=err2.T[LIB], capsize=2, width=step)\n",
+    "ax.legend(labels=vals2.T.columns)\n",
+    "ticks = ax.get_xticks()\n",
+    "ax.set_xticklabels(vals2.columns.values)\n",
+    "ax.set_xticks(np.arange(len(vals2.columns)) + step)\n",
+    "ax.get_legend().remove()\n",
+    "ax.set(\n",
+    "    ylabel=None,\n",
+    "    ylim=(.016, 0.0175),\n",
+    ")\n",
+    "\n",
+    "fig.tight_layout();"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python3 (sandy-devel)",
+   "language": "python",
+   "name": "sandy-devel"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/notebook_lognormal.ipynb b/notebooks/notebook_lognormal.ipynb
new file mode 100644
index 00000000..5f9301a1
--- /dev/null
+++ b/notebooks/notebook_lognormal.ipynb
@@ -0,0 +1,1414 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "81d34803",
+   "metadata": {},
+   "source": [
+    "# Sampling from multivariate lognormal distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "67679dcf",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:03.246179Z",
+     "iopub.status.busy": "2022-11-20T15:54:03.245434Z",
+     "iopub.status.idle": "2022-11-20T15:54:04.932564Z",
+     "shell.execute_reply": "2022-11-20T15:54:04.931752Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import sandy"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "c894192e-f432-49e6-809a-0cca7427c780",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:04.936970Z",
+     "iopub.status.busy": "2022-11-20T15:54:04.936580Z",
+     "iopub.status.idle": "2022-11-20T15:54:04.942210Z",
+     "shell.execute_reply": "2022-11-20T15:54:04.941508Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "from scipy.stats import lognorm\n",
+    "\n",
+    "sns.set_style(\"ticks\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "abb2d548-c599-4d99-9fea-8b8483dbaeab",
+   "metadata": {},
+   "source": [
+    "Small simple covariance matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "4c059e41-f8db-4897-aff9-4fa701cd4109",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:04.946499Z",
+     "iopub.status.busy": "2022-11-20T15:54:04.945917Z",
+     "iopub.status.idle": "2022-11-20T15:54:04.954557Z",
+     "shell.execute_reply": "2022-11-20T15:54:04.953886Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "# 3 parameters with similar mean values (but not identical!)\n",
+    "parameters = ['A', 'B', 'C']\n",
+    "x1 = 4\n",
+    "x2 = 5\n",
+    "x3 = 6\n",
+    "mean = np.array([x1, x2, x3])\n",
+    "\n",
+    "# relative standard deviations\n",
+    "s1 = 10 / 100\n",
+    "s2 = 3 / 100    # small stdev\n",
+    "s3 = 60 / 100   # large stdev\n",
+    "\n",
+    "# correlations between parameters\n",
+    "c12 = 0.2\n",
+    "c13 = -0.4\n",
+    "c23 = 0.5\n",
+    "\n",
+    "# building covariance matrix\n",
+    "cov = sandy.CategoryCov(\n",
+    "    pd.DataFrame(\n",
+    "        [\n",
+    "            [s1 * x1 * s1 * x1,         s1 * x1 * s2 * x2 * c12,   s1 * x1 * s3 * x3 * c13],\n",
+    "            [s2 * x2 * s1 * x1 * c12,   s2 * x2 * s2 * x2,         s2 * x2 * s3 * x3 * c23],\n",
+    "            [s3 * x3 * s1 * x1 * c13,   s3 * x3 * s2 * x2 * c23,   s3 * x3 * s3 * x3],\n",
+    "        ], index=parameters, columns=parameters,\n",
+    "    )\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "7e771b73",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:04.957762Z",
+     "iopub.status.busy": "2022-11-20T15:54:04.957503Z",
+     "iopub.status.idle": "2022-11-20T15:54:05.147823Z",
+     "shell.execute_reply": "2022-11-20T15:54:05.147097Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 350x350 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(3.5, 3.5), dpi=100)\n",
+    "ax.set_aspect(\"equal\")\n",
+    "sns.heatmap(data=cov.get_corr().data, cmap='bwr', vmin=-1, vmax=1, ax=ax)\n",
+    "fig.tight_layout();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "46f30af3",
+   "metadata": {},
+   "source": [
+    "Let's convert mean vector and convariance matrix to relative terms."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a9861232",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:05.151492Z",
+     "iopub.status.busy": "2022-11-20T15:54:05.151222Z",
+     "iopub.status.idle": "2022-11-20T15:54:05.157720Z",
+     "shell.execute_reply": "2022-11-20T15:54:05.157111Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "A   1.00000e-01\n",
+       "B   3.00000e-02\n",
+       "C   6.00000e-01\n",
+       "Name: STD, dtype: float64"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cov_r = cov.corr2cov(1/mean)\n",
+    "cov_r.get_std()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "8d117988",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:05.161092Z",
+     "iopub.status.busy": "2022-11-20T15:54:05.160861Z",
+     "iopub.status.idle": "2022-11-20T15:54:05.165345Z",
+     "shell.execute_reply": "2022-11-20T15:54:05.164808Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([1., 1., 1.])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mean_r = mean / mean\n",
+    "mean_r"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a9526af",
+   "metadata": {},
+   "source": [
+    "For parameters with medium/large standard deviations the left tail with a Normal distribution spans in the negative range.\n",
+    "For many nuclear data types, negative values do not have a physical meaning."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "5a6b2ebe",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:05.208515Z",
+     "iopub.status.busy": "2022-11-20T15:54:05.208262Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.920743Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.920041Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 2700x900 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data = cov_r.sampling(nsmp).data.T\n",
+    "data.index.name = \"PARAM\"\n",
+    "data.columns.name = \"SMP\"\n",
+    "data = data.stack().rename(\"VAL\").reset_index()\n",
+    "g = sns.displot(data=data, x=\"VAL\", col=\"PARAM\",\n",
+    "                height=3, aspect=1, color=\"dodgerblue\", alpha=.6\n",
+    "               )\n",
+    "g.fig.set_dpi(300)\n",
+    "g.axes[0, 0].set_xlabel(None)\n",
+    "g.axes[0, 1].set_xlabel(None)\n",
+    "g.axes[0, 2].set_xlabel(None)\n",
+    "plt.xlim(-0.1, 2.1);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "666e616d",
+   "metadata": {},
+   "source": [
+    "This behavior can be avoided when sampling from a lognormal distribution. "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea5712ed",
+   "metadata": {},
+   "source": [
+    "## Retrieve mean and covariance matrix of underlying normal distribution"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a67fcf0f",
+   "metadata": {},
+   "source": [
+    "Two-step approach to sample log-normally distributed variables with mean vector $\\mathbf{\\mu}$ and covariance matrix $\\mathbf{\\Sigma}$:\n",
+    "\n",
+    "- draw normally-distributed samples with underlying mean vector $\\mathbf{\\mu_N}$ and covariance matrix $\\mathbf{\\Sigma}_N$;\n",
+    "- apply an exponential operator to the normally-distributed samples."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc772241",
+   "metadata": {},
+   "source": [
+    "$$\n",
+    "log\\mathcal{N} \\left( \\mathbf{\\mu}, \\mathbf{\\Sigma} \\right) = exp \\left( \\mathcal{N} \\left( \\mathbf{\\mu}_N, \\mathbf{\\Sigma}_N \\right) \\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0499076a",
+   "metadata": {},
+   "source": [
+    "The underlying mean vector $\\mathbf{\\mu}_N$ and covariance matrix $\\mathbf{\\Sigma}_N$ can be defined starting from $\\mathbf{\\mu}$ and $\\mathbf{\\Sigma}$ as defined in https://doi.org/10.1016/j.nima.2013.06.025"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ba89caaa",
+   "metadata": {},
+   "source": [
+    "$$\n",
+    "\\mu_{N_i} = ln \\left(\\mu_i\\right) - \\frac{\\sigma_i^2}{2}\n",
+    "$$\n",
+    "\n",
+    "$$\n",
+    "\\sigma_{N_i} = \\sqrt{ln\\left( 1 + \\frac{\\sigma_i^2}{\\mu_i^2}\\right)}\n",
+    "$$\n",
+    "\n",
+    "$$\n",
+    "\\Sigma_{N_{i,j}} = ln\\left( 1 + \\frac{\\Sigma_{i,j}^2}{\\mu_i\\mu_j}\\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b2ac296",
+   "metadata": {},
+   "source": [
+    "If the mean vector is $\\mathbf{\\mu}=\\mathbf{1}$, the equations above simplify to"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2ab090ae",
+   "metadata": {},
+   "source": [
+    "$$\n",
+    "\\mu_{N_i} =  - \\frac{\\sigma_i^2}{2}\n",
+    "$$\n",
+    "\n",
+    "$$\n",
+    "\\sigma_{N_i} = \\sqrt{ln\\left( 1 + \\sigma_i^2 \\right)}\n",
+    "$$\n",
+    "\n",
+    "$$\n",
+    "\\Sigma_{N_{i,j}} = ln\\left( 1 + \\Sigma_{i,j}\\right)\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "8a6c8970",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.925201Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.924950Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.928890Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.928156Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "mean_N = - np.diag(cov_r.data) / 2\n",
+    "cov_N = np.log(cov_r.data + 1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b72a6cde",
+   "metadata": {},
+   "source": [
+    "## Sampling from normal distribution"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "04014c31",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.932205Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.931984Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.936708Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.936000Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "nsmp = 10000\n",
+    "y = np.random.randn(3, nsmp)\n",
+    "L = np.linalg.cholesky(cov_N)\n",
+    "smp_N = L.dot(y) + mean_N.reshape(-1, 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "f159d810",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.939777Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.939543Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.942776Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.942084Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "smp_LogN = np.exp(smp_N)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "56d4bf19",
+   "metadata": {},
+   "source": [
+    "### Sample analysis"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "244a903f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.946035Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.945813Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.953886Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.953251Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "data = pd.DataFrame(smp_LogN, index=parameters)\n",
+    "data.index.name = \"PARAM\"\n",
+    "data.columns.name = \"SMP\"\n",
+    "data = data.stack().rename(\"VAL\").reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "4f6b0f17",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.956898Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.956667Z",
+     "iopub.status.idle": "2022-11-20T15:54:12.880390Z",
+     "shell.execute_reply": "2022-11-20T15:54:12.879668Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.displot(data=data, x=\"VAL\", col=\"PARAM\")\n",
+    "plt.xlim(0, 3);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c5438060",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:12.884329Z",
+     "iopub.status.busy": "2022-11-20T15:54:12.883942Z",
+     "iopub.status.idle": "2022-11-20T15:54:12.905004Z",
+     "shell.execute_reply": "2022-11-20T15:54:12.904280Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PARAM</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>9.99768e-01</td>\n",
+       "      <td>9.89254e-02</td>\n",
+       "      <td>6.60579e-01</td>\n",
+       "      <td>9.30635e-01</td>\n",
+       "      <td>9.94885e-01</td>\n",
+       "      <td>1.06328e+00</td>\n",
+       "      <td>1.47582e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>B</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>1.00066e+00</td>\n",
+       "      <td>3.02411e-02</td>\n",
+       "      <td>8.71316e-01</td>\n",
+       "      <td>9.80449e-01</td>\n",
+       "      <td>1.00005e+00</td>\n",
+       "      <td>1.02074e+00</td>\n",
+       "      <td>1.13704e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>9.82209e-01</td>\n",
+       "      <td>5.87104e-01</td>\n",
+       "      <td>1.02501e-01</td>\n",
+       "      <td>5.85189e-01</td>\n",
+       "      <td>8.45324e-01</td>\n",
+       "      <td>1.21383e+00</td>\n",
+       "      <td>9.66212e+00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count        mean         std         min         25%         50%  \\\n",
+       "PARAM                                                                           \n",
+       "A     1.00000e+04 9.99768e-01 9.89254e-02 6.60579e-01 9.30635e-01 9.94885e-01   \n",
+       "B     1.00000e+04 1.00066e+00 3.02411e-02 8.71316e-01 9.80449e-01 1.00005e+00   \n",
+       "C     1.00000e+04 9.82209e-01 5.87104e-01 1.02501e-01 5.85189e-01 8.45324e-01   \n",
+       "\n",
+       "              75%         max  \n",
+       "PARAM                          \n",
+       "A     1.06328e+00 1.47582e+00  \n",
+       "B     1.02074e+00 1.13704e+00  \n",
+       "C     1.21383e+00 9.66212e+00  "
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.groupby(\"PARAM\").VAL.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb5c08c6",
+   "metadata": {},
+   "source": [
+    "The shape, mean and standard deviations of the lognormal samples look correct!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "83020e15",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:12.908308Z",
+     "iopub.status.busy": "2022-11-20T15:54:12.908077Z",
+     "iopub.status.idle": "2022-11-20T15:54:12.934420Z",
+     "shell.execute_reply": "2022-11-20T15:54:12.933737Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>PARAM</th>\n",
+       "      <th>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PARAM</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>1.00000e+00</td>\n",
+       "      <td>2.13442e-01</td>\n",
+       "      <td>-3.93749e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>B</th>\n",
+       "      <td>2.13442e-01</td>\n",
+       "      <td>1.00000e+00</td>\n",
+       "      <td>4.91663e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>-3.93749e-01</td>\n",
+       "      <td>4.91663e-01</td>\n",
+       "      <td>1.00000e+00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "PARAM            A           B            C\n",
+       "PARAM                                      \n",
+       "A      1.00000e+00 2.13442e-01 -3.93749e-01\n",
+       "B      2.13442e-01 1.00000e+00  4.91663e-01\n",
+       "C     -3.93749e-01 4.91663e-01  1.00000e+00"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.pivot_table(index=\"SMP\", columns=\"PARAM\", values=\"VAL\").corr()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9574fc52",
+   "metadata": {},
+   "source": [
+    "Also correlations converge to what was is expected."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e6789650",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:12.938102Z",
+     "iopub.status.busy": "2022-11-20T15:54:12.937466Z",
+     "iopub.status.idle": "2022-11-20T15:54:12.942670Z",
+     "shell.execute_reply": "2022-11-20T15:54:12.941923Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "False"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(data.VAL < 0).any()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "26b5c891",
+   "metadata": {},
+   "source": [
+    "...and all values the lognormal distribution are obviously positive!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "efd24441",
+   "metadata": {},
+   "source": [
+    "If we multiply the relative samples by the original mean we go back to absolute values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a0ae16c7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:12.946506Z",
+     "iopub.status.busy": "2022-11-20T15:54:12.945915Z",
+     "iopub.status.idle": "2022-11-20T15:54:13.744741Z",
+     "shell.execute_reply": "2022-11-20T15:54:13.743994Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "foo = lambda row: row.VAL * mean[0] if row.PARAM == \"A\" else row.VAL * mean[1] if row.PARAM == \"B\" else row.VAL * mean[2]\n",
+    "data[\"VAL_ABS\"]  = data.apply(foo, axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "c90b735b",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:13.750318Z",
+     "iopub.status.busy": "2022-11-20T15:54:13.748811Z",
+     "iopub.status.idle": "2022-11-20T15:54:17.903192Z",
+     "shell.execute_reply": "2022-11-20T15:54:17.902506Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1500x500 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.displot(data=data, x=\"VAL_ABS\", col=\"PARAM\")\n",
+    "plt.xlim(0, 15);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "4d8940f7",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:17.906289Z",
+     "iopub.status.busy": "2022-11-20T15:54:17.906049Z",
+     "iopub.status.idle": "2022-11-20T15:54:17.924364Z",
+     "shell.execute_reply": "2022-11-20T15:54:17.923652Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PARAM</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>3.99907e+00</td>\n",
+       "      <td>3.95701e-01</td>\n",
+       "      <td>2.64232e+00</td>\n",
+       "      <td>3.72254e+00</td>\n",
+       "      <td>3.97954e+00</td>\n",
+       "      <td>4.25314e+00</td>\n",
+       "      <td>5.90329e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>B</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>5.00328e+00</td>\n",
+       "      <td>1.51205e-01</td>\n",
+       "      <td>4.35658e+00</td>\n",
+       "      <td>4.90225e+00</td>\n",
+       "      <td>5.00025e+00</td>\n",
+       "      <td>5.10370e+00</td>\n",
+       "      <td>5.68518e+00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>1.00000e+04</td>\n",
+       "      <td>5.89325e+00</td>\n",
+       "      <td>3.52262e+00</td>\n",
+       "      <td>6.15008e-01</td>\n",
+       "      <td>3.51114e+00</td>\n",
+       "      <td>5.07194e+00</td>\n",
+       "      <td>7.28297e+00</td>\n",
+       "      <td>5.79727e+01</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count        mean         std         min         25%         50%  \\\n",
+       "PARAM                                                                           \n",
+       "A     1.00000e+04 3.99907e+00 3.95701e-01 2.64232e+00 3.72254e+00 3.97954e+00   \n",
+       "B     1.00000e+04 5.00328e+00 1.51205e-01 4.35658e+00 4.90225e+00 5.00025e+00   \n",
+       "C     1.00000e+04 5.89325e+00 3.52262e+00 6.15008e-01 3.51114e+00 5.07194e+00   \n",
+       "\n",
+       "              75%         max  \n",
+       "PARAM                          \n",
+       "A     4.25314e+00 5.90329e+00  \n",
+       "B     5.10370e+00 5.68518e+00  \n",
+       "C     7.28297e+00 5.79727e+01  "
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.groupby(\"PARAM\").VAL_ABS.describe()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc9791c9",
+   "metadata": {},
+   "source": [
+    "Relative standard deviation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "ffb065f6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:17.927930Z",
+     "iopub.status.busy": "2022-11-20T15:54:17.927688Z",
+     "iopub.status.idle": "2022-11-20T15:54:17.969605Z",
+     "shell.execute_reply": "2022-11-20T15:54:17.968865Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PARAM\n",
+       "A   9.89483e-02\n",
+       "B   3.02212e-02\n",
+       "C   5.97738e-01\n",
+       "dtype: float64"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.pivot_table(index=\"SMP\", columns=\"PARAM\", values=\"VAL_ABS\").std() / data.pivot_table(index=\"SMP\", columns=\"PARAM\", values=\"VAL_ABS\").mean()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7e15fa1f",
+   "metadata": {},
+   "source": [
+    "Correlations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "7cdadc14",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:17.973110Z",
+     "iopub.status.busy": "2022-11-20T15:54:17.972872Z",
+     "iopub.status.idle": "2022-11-20T15:54:17.999243Z",
+     "shell.execute_reply": "2022-11-20T15:54:17.998512Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th>PARAM</th>\n",
+       "      <th>A</th>\n",
+       "      <th>B</th>\n",
+       "      <th>C</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>PARAM</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>A</th>\n",
+       "      <td>1.00000e+00</td>\n",
+       "      <td>2.13442e-01</td>\n",
+       "      <td>-3.93749e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>B</th>\n",
+       "      <td>2.13442e-01</td>\n",
+       "      <td>1.00000e+00</td>\n",
+       "      <td>4.91663e-01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>C</th>\n",
+       "      <td>-3.93749e-01</td>\n",
+       "      <td>4.91663e-01</td>\n",
+       "      <td>1.00000e+00</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "PARAM            A           B            C\n",
+       "PARAM                                      \n",
+       "A      1.00000e+00 2.13442e-01 -3.93749e-01\n",
+       "B      2.13442e-01 1.00000e+00  4.91663e-01\n",
+       "C     -3.93749e-01 4.91663e-01  1.00000e+00"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data.pivot_table(index=\"SMP\", columns=\"PARAM\", values=\"VAL_ABS\").corr()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d4ae8e79",
+   "metadata": {},
+   "source": [
+    "## Plot sample convergence"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8d467a14",
+   "metadata": {},
+   "source": [
+    "For these plots we use the functions and methods already implemented in `sandy`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "5dcbf027",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:18.002997Z",
+     "iopub.status.busy": "2022-11-20T15:54:18.002754Z",
+     "iopub.status.idle": "2022-11-20T15:54:18.006286Z",
+     "shell.execute_reply": "2022-11-20T15:54:18.005585Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "nsmp = list(range(10, 1000, 10)) + list(range(1000, 5001, 100))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "02a29190",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:18.009607Z",
+     "iopub.status.busy": "2022-11-20T15:54:18.009368Z",
+     "iopub.status.idle": "2022-11-20T15:54:20.984947Z",
+     "shell.execute_reply": "2022-11-20T15:54:20.984223Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "lognorm = {n: cov_r.sampling(n, pdf=\"lognormal\").data.std() for n in nsmp}\n",
+    "norm = {n: cov_r.sampling(n, pdf=\"normal\").data.std() for n in nsmp}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "d3f83e0f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:20.988550Z",
+     "iopub.status.busy": "2022-11-20T15:54:20.988291Z",
+     "iopub.status.idle": "2022-11-20T15:54:21.014551Z",
+     "shell.execute_reply": "2022-11-20T15:54:21.013861Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(norm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.name = \"PARAM\"\n",
+    "dfnorm = df.stack().rename(\"STD\").reset_index().assign(PDF=\"normal\")\n",
+    "\n",
+    "df = pd.DataFrame(lognorm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.name = \"PARAM\"\n",
+    "dflognorm = df.stack().rename(\"STD\").reset_index().assign(PDF=\"lognormal\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "4e1bb008",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:21.018079Z",
+     "iopub.status.busy": "2022-11-20T15:54:21.017831Z",
+     "iopub.status.idle": "2022-11-20T15:54:21.701060Z",
+     "shell.execute_reply": "2022-11-20T15:54:21.700289Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
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\n",
+      "text/plain": [
+       "<Figure size 1120x750 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = pd.concat([dflognorm, dfnorm], ignore_index=True)\n",
+    "\n",
+    "g = sns.relplot(\n",
+    "    data=df, x=\"NSMP\", y=\"STD\", row=\"PARAM\",\n",
+    "    hue=\"PDF\", kind=\"line\", palette=[\"b\", \"r\"],\n",
+    "    height=2.5, aspect=4,\n",
+    ")\n",
+    "g.figure.set_dpi(100)\n",
+    "plt.xlim(0, 5000)\n",
+    "plt.ylim(0, 0.8);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06ee9d9e",
+   "metadata": {},
+   "source": [
+    "## Plot mean convergence"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "a514862f",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:21.704480Z",
+     "iopub.status.busy": "2022-11-20T15:54:21.704229Z",
+     "iopub.status.idle": "2022-11-20T15:54:24.656368Z",
+     "shell.execute_reply": "2022-11-20T15:54:24.655638Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "lognorm = {n: cov_r.sampling(n, pdf=\"lognormal\").data.mean() for n in nsmp}\n",
+    "norm = {n: cov_r.sampling(n, pdf=\"normal\").data.mean() for n in nsmp}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "2bfc3399",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:24.660935Z",
+     "iopub.status.busy": "2022-11-20T15:54:24.660307Z",
+     "iopub.status.idle": "2022-11-20T15:54:24.687214Z",
+     "shell.execute_reply": "2022-11-20T15:54:24.686498Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(norm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.name = \"PARAM\"\n",
+    "dfnorm = df.stack().rename(\"MEAN\").reset_index().assign(PDF=\"normal\")\n",
+    "\n",
+    "df = pd.DataFrame(lognorm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.name = \"PARAM\"\n",
+    "dflognorm = df.stack().rename(\"MEAN\").reset_index().assign(PDF=\"lognormal\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "33556e4c",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:24.691047Z",
+     "iopub.status.busy": "2022-11-20T15:54:24.690438Z",
+     "iopub.status.idle": "2022-11-20T15:54:25.577188Z",
+     "shell.execute_reply": "2022-11-20T15:54:25.576372Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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749K1J7ax9sSkqzC2sUqcSTJlKDbKr7TAdjXybFFq6WYll25RYuFmxRduVWzBZkXt3CpH7mbZ3GWHvbymYUiJiTITkxRIbCB/fAPtsjnkat5KnqR0lSakqSQ+TUVxadobk6Y90enaY09WmcdWJfwIjrvdlUMRo0pIEly2b4Bi95QqXblVhjTtCI2nKl97lKhtaqJdUY3la9hYZuMmcrVsrLjWTZTaLk3NT7IrI8PquhxWWFhSIq1fL2PdOgVyfpR75ToZP65T1G/rZPcc/ue9MrNBg4pwt1EjmZXG1aiRzErjatTIenHV6QDWh72SzQUq+HmX9v5WoOJNu1S2bZe8ubtk5hdIu3fJuWeXoksKZPr9KrYnqtjeQEX2RBU7GqjE2cB6dCSqxNVApc4GKotqoFKX9ehxxcvutMluV/lgXe/8fkNer/VZu/IQnOf3l8/zmpLHI7vPLcNrPYbG/R5FOfyKclnXmiiXqSiXKZfTDI1bQ0Aul0LLgkNw2ukIaPf2zUp1OGXbu0e2or2yFxfKWVIoV0mhXGV7FOXeoxh3oWJ8exTnK1S8v1Au8+D/d/2yaY8jRUWuFBVHp6osJlnu+FR5ElLlb5AiMyVFRmqK7GkpsjdKUVTTVMU0T5UrOU478gxt3Spt3WpUCk6C86S9e+vy6dqUU15Fya0ouRWtMkXJrSbJZWqd4Var5mVq2ditFullat7IraYpbkUbbuvFGRx275a2b5dROTjJzZVRhy9mcpWmnWoomwJyGV5F2bxyyiuX4ZXD9MohnxymV/aAVzbV+mPfEROw2RVwVgQtRnSUbDHl0y5X9SDGMKz3HXv2SHv3yizcI7Nwj2xFe2TU/mNsNX7Z9LNaaY06aL29nXY0bK+iFu2lzDZKOylWLVpIGRlm+WPF21O/3y+Xq4YvvnHCq1OwEvTdd98pOztb8+fPV4sWLfTTTz/p9ddf1xlnnBF2QWoTrPTp00dDhgzRjTfeGJr3xRdf6IYbbtCKFSsUXYsuHMFgpSbbtzv1RP+9+krda95WNsWpWFudLZTizdNgzdQsDZFpGNoSc4qal/ysPFcTNfJsU67SlKFNuj71bT1b8Cc5TJ8+TL9apRP/ojOHD9JJ+k2FvztTP016XgsXpypj0/ca+vQVMg1DS1v2U9Nff1BTbdOuXr30y4QJ2rAhWv/4R3Od/vVrel63hcq0/uRzlbhhnRort0pZF+h8ddAaNdF2LdYfNCx9ngblTtWzuiO0znenDVOXFdlyyRuat8nWQhmBjRrreFC5voZ6TrdLkgqUrBTtUk7yWXrMfZ9ml1ygB8fl6uuvEzV7dkOlp3vkMHxavr2FGipf/4y9Q9eYUxVTWqgb9JJ2XzpIl1++Q02beuRymZo/P1kPPHCKoqP9+kvSyxq7/c/Vnu+vY8/T2SWf6rrrtmr9l2Was76z4lX1l3DcTZsqautW+WTXEM3UAOccXed9WcWK1f16Qhv6XaGOrQt023M9Q8/RA8ZYNbuhq/78Uj8VK1ZF9kSl+7fLL5vsCugyva2vmw1UVlahnNu2a9qiM6p8kChQsoqSGqvF7rVVyvJe5i1auy5eVzT4QCcVWuFHwLDJZgb0/oWP66tPojTBvKfaeW5Sc82JGqzrPC/KYXrlj4qW3V2mR/SwZjS5Ucv2tJGzuOo9YpYYZ+pMc0n15+z0EZrV63HZfW6l5/9PTXb8qKZ5a9Q0b62a7shRrLvme7Lsjm+srQ3ba0vDdtrSqIO2pmRqr5kgt9uQ22NXmduuMrdNHo9RPm6X221TaZmtynSZ266AbDJlvTExZCpDm9TZWKVusSvU2bZabbxrlFZW84dV0zDkbt5cpa1aqaxVK5WWD2UtW0o2m6I2blTsjz8q9scfFbd2rWLWrZOjhvvnBBwO7W15qvIy2mtzeidtSO6s9dEdtLMoXkVFdrlcpqKjAwccYmICinZ6FWcvVaxKFKNSOX1lsnvcspWVyeZ2y7TZZDocCjic8phOlfiiVOKLUrEnSsVel0q8UdrrjlKxJ1p73VEqcTtVXGxXaalNJSXWY3Gx9dz5PKaiyvYovrRAiZ58JbgLlOQrUJJ3p5L8+Urx56uh8tRQO0NDkmp/j51dStImZWijWtQ4bFVT+fdpxGiXT220Xp20Sp20Sp21Sp2NlTrJ/LXGY/gNu7Y3aKXtDdsqr3Eb7WreRiVmjAI79sjIL5R9925F792l2JJdSnAXKLX8PBopr8p1qC78smmXklWgFOUrtcbwpfJQpmi10s+h4KS9sVaZ5o9K0P7vw7Q7qpG2Jp2qHSmtVNColXaln6K9TU6S3xOQfWeBXLsKFLV7p2L35iuuaKcSSvOUVLZTyd4daujbofgD7Lsmbrm0Q2n7fPSteShQSpVgySW3OmulztJ3Okvf6UwtUVv9WO3NdECGctReS3SmvtNZWlIeQrvi7IqL88vttqmoyC6/f98PGaZiVVIldEnS7hrHk7VLDvnkl11+WdeG4HjlYX/zKy+Lkltp2qHG2q7G2q505aqR6nZfLLdc2q0kpSpfDtUuxMxTQ21Rc223N1Wuq6l2upoqP6aJCuPSZZgBxXn3KNa7R3HeQsX79ijeV6gEf6ES/LuVENijRLNQDQK71UC7FaPwAgOvHMpTI+1QWmjIVXq16SLFq6F27re2BMOTA9X12gjIUJ4aaZuaaJuaaHd0uooTGsqd0lCB9IayNUtW1EnJim/dQM7SIunHTYra8JviNm9QSu4varz7J6XXEOwFueXSerUpf4VawzY1UYxKFa8ixalY8Sra73iiUaREe5ESbNb8mECxYv1FcpjhBYIeV6xK4lNUWj6UxaeoLD5ZvjK/7Lv3yL53j6KKCxVbWqh4zy4l+HeHfT2rrYAM7VWCCtUgNBQrLvQh3yVP6MN+TeNHunyHw17Fh87NJ4eStUupylecwv8FTa8c8qvii6fge5WaxkMtHw1DhmFa07ZK4z6f7N7D++VLZX7ZtENp2qYm2qqmVR4rj+cqXT7VPt20yS+nvNUGh3xWGCOPYmS974lTceix8vj+HvcdDwZNUXIf0UDHJ7v2KLHKUGxPkDcmXoH4OKlBnBwpMYpOsCtu20Ylb/9ZTXetU7yv5l+cCMjQBp2sHLXXGnVQjtorR+21LbG1Epq41LixR59/nnTEzgfHr7CClaCioiJ9+OGHys7O1po1a9S5c2f16dNHI0eOrPO+jnawEmyxUpnHIzWJ3avdSq5xW0+LVora+JPe1R/1R2XrC52rHvpSZtu2Wv/SfzXu/E810zdA65SpJtqu91yXaYDnXdlk6k0N03WOaXrwcadm3bdEd7SYqcuW/tVqKl1xMlLDhvo0t4PuvnC1VqiLTKdLowZu0ZSZqQoEDC0weut88796U8N0hd4KbbpDjbQ68Wyd12CpfE8+rT4vDdXGz37WEp2pZO2Wr3cfuVetV1zuBpmndZGxYnlo28/UU/lK1R+VHZr35+4r9M9FnfRaw7/o6p3PSJLMdu0UWLRIDz+dpLFjberc2dSaNaryxvuviS9qwp6Km7asUkd11bLQB7aoKFMPPmjqnXcMrVxp6JFHAhoz2ivb6afLyCkPI+6/X8bf/y7D79cMDZVNAbXWT+qsVdqacZbytvp0mv8HSdIdnRao9//+qf5lFWUPyNAAfaBOo/vp8cdN7d0r3d94mv7puU7/0RW6StMVF2tqfUlzNdU2SZLPEaX3T7pdQ3+aoI3KUJa+1hY119O6U3fqGf2sU9RQOxWQTcOS5+vt9acpce7b2jDhXSWt+VorL3lAe6+7XQMH2pWRYeruK7folZf8Omf3bE3SrcpTw/IPGX4Frhou8883yWc4VTL0/5S8rSKg+Y+u0KKk/nph91Xapsb6TmdpoD5QjqOz9vhi9Ht9a53jpEkyJkyQsdFqLfWmfbiu8L+hEsXoJ7VWO62t8VtlrxzKUXut0GlaodO0XF20QqcpXw1rrPOHwuk0FRNj3Te4ausAKVGF6qA16qjVoaGTVu33g1LA4ZTpdMleWv0npj22KG2I76xVrtO1JHC6FpWcoe/LOsqjw3+vErvdDLV6jYmxrhlFRTWf49EQ73KriStfTZw7lW7fqSbGdjX1b1JT30Y19VmPTXwblRQ4eEsSv2zKczbTdlcLFTjS1Lhsg05xr1W0av6FsC1qqlXqpJXqXB67dNKPaiu3Dn4driw11VSTxqZOalik1kl5Oil+p5pH71QTpxW6JPvyFF+Wp7LNG9QgEJB27bJaJO0qkHEYf6LetNulVq2ktm1lZmZWPGZmVr1Oh6O4WL6tO1T6a65Kf90h7+Zc+bflStt3yLYzV66CHYouzFXM3lxFl9XthtQ+2bXTaKTtZrr8squTVtX4oSk/oaW2NT9T+aecqaL2Z8rXuaviGidU6bGSmFi1hbZpWl+olreuDrW0tr44NKq0vq4YjNA6hYXWN+Q1dd3ad9wwDr7OvuNOeZXs26Fk93Zr8OQqyZ2rpLJcNSjdrgZluUostcZj3burPB9+w65dUU20I6q5cu3NtNXWTJvNZvrN31wbPM30U1lzbQo0q3N9PpAolYU+BidpdyiEamTbqabOPDWx5Sq9PEJpGNihFN+OUAvOw82MjpbS0qX0NCk9XWZampSWVtG9as8eeX7bppJftsu3cZuM3O2KKtiuuOJc2c26t6yrSb5StFbt9KPaar2Rqe1JbbWrcTv5mp+ktCa2UHHS06W4OFMFBYZ27rRuJVFQIOXnG8rPV5WhehBYwSmPErQ3FOamaYcaKe+Aw6EEEG65tEsp2utMVnFUitxxKfIlJMlMSpGtYYpc6cmKapKsqDiHbHsLZewplK2oUPaivbIVFcpRVCh7caEcxXvkLC6Uo3SPnCWFsvsO/4d50+5QwBUlOV0yXS6ZNrtMGdZgqvzRUCA0r3zcNBQwtc+0NR4IGCqTU97YJHmiG8gT00De2ET54xrIn9BAZnyC1WemQQPZkxNkS24ge3KinA0bKKphgmLi7VVucVZUZF1Xina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\n",
+      "text/plain": [
+       "<Figure size 1120x750 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = pd.concat([dflognorm, dfnorm], ignore_index=True)\n",
+    "\n",
+    "g = sns.relplot(\n",
+    "    data=df, x=\"NSMP\", y=\"MEAN\", row=\"PARAM\",\n",
+    "    hue=\"PDF\", kind=\"line\", palette=[\"b\", \"r\"],\n",
+    "    height=2.5, aspect=4,\n",
+    ")\n",
+    "g.figure.set_dpi(100)\n",
+    "plt.xlim(0, 5000)\n",
+    "plt.ylim(0.8, 1.2);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "274e073e",
+   "metadata": {},
+   "source": [
+    "## Plot correlation convergence"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "e297ce85",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:25.581050Z",
+     "iopub.status.busy": "2022-11-20T15:54:25.580616Z",
+     "iopub.status.idle": "2022-11-20T15:54:28.625594Z",
+     "shell.execute_reply": "2022-11-20T15:54:28.624809Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "lognorm = {n: cov_r.sampling(n, pdf=\"lognormal\").data.corr().stack().loc[[(\"A\", \"B\"), (\"A\", \"C\"), (\"B\", \"C\")]] for n in nsmp}\n",
+    "norm = {n: cov_r.sampling(n, pdf=\"lognormal\").data.corr().stack().loc[[(\"A\", \"B\"), (\"A\", \"C\"), (\"B\", \"C\")]] for n in nsmp}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "a0697771",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:28.629818Z",
+     "iopub.status.busy": "2022-11-20T15:54:28.629513Z",
+     "iopub.status.idle": "2022-11-20T15:54:28.695755Z",
+     "shell.execute_reply": "2022-11-20T15:54:28.695037Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(norm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.names = (\"PARAM_1\", \"PARAM_2\")\n",
+    "dfnorm = df.unstack().rename(\"CORR\").reset_index().assign(PDF=\"normal\")\n",
+    "\n",
+    "df = pd.DataFrame(lognorm).T\n",
+    "df.index.name = \"NSMP\"\n",
+    "df.columns.names = (\"PARAM_1\", \"PARAM_2\")\n",
+    "dflognorm = df.unstack().rename(\"CORR\").reset_index().assign(PDF=\"lognormal\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "92881f39",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:28.700128Z",
+     "iopub.status.busy": "2022-11-20T15:54:28.699577Z",
+     "iopub.status.idle": "2022-11-20T15:54:29.460718Z",
+     "shell.execute_reply": "2022-11-20T15:54:29.460098Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1120x750 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "df = pd.concat([dflognorm, dfnorm], ignore_index=True)\n",
+    "df[\"PARAMS\"] = df.apply(lambda row: (row.PARAM_1, row.PARAM_2), axis=1)\n",
+    "\n",
+    "g = sns.relplot(\n",
+    "    data=df, x=\"NSMP\", y=\"CORR\", row=\"PARAMS\",\n",
+    "    hue=\"PDF\", kind=\"line\", palette=[\"b\", \"r\"],\n",
+    "    height=2.5, aspect=4,\n",
+    ")\n",
+    "g.figure.set_dpi(100)\n",
+    "plt.xlim(0, 2000);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b2cdc13",
+   "metadata": {},
+   "source": [
+    "## Putting it all together"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 97,
+   "id": "d8a21ceb",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-11-20T15:54:06.932205Z",
+     "iopub.status.busy": "2022-11-20T15:54:06.931984Z",
+     "iopub.status.idle": "2022-11-20T15:54:06.936708Z",
+     "shell.execute_reply": "2022-11-20T15:54:06.936000Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "nsmp = 10000\n",
+    "\n",
+    "data_n = cov_r.sampling(nsmp).data.T\n",
+    "data_n.index.name = \"PARAM\"\n",
+    "data_n.columns.name = \"SMP\"\n",
+    "data_n = data_n.stack().rename(\"VAL\").reset_index().assign(PDF=\"normal\")\n",
+    "\n",
+    "data_ln = cov_r.sampling(nsmp, pdf=\"lognormal\").data.T\n",
+    "data_ln.index.name = \"PARAM\"\n",
+    "data_ln.columns.name = \"SMP\"\n",
+    "data_ln = data_ln.stack().rename(\"VAL\").reset_index().assign(PDF=\"lognormal\")\n",
+    "\n",
+    "data_u = cov_r.sampling(nsmp, pdf=\"uniform\").data.T\n",
+    "data_u.index.name = \"PARAM\"\n",
+    "data_u.columns.name = \"SMP\"\n",
+    "data_u = data_u.stack().rename(\"VAL\").reset_index().assign(PDF=\"uniform\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 98,
+   "id": "18fac436",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 4046.53x1200 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "g = sns.displot(data=pd.concat([data_n, data_ln, data_u], ignore_index=True),\n",
+    "                x=\"VAL\", col=\"PARAM\", hue=\"PDF\",\n",
+    "                height=3, aspect=1, alpha=.8, palette=[\"dodgerblue\", \"tomato\", \"green\"],\n",
+    "               )\n",
+    "g.fig.set_dpi(400)\n",
+    "g.axes[0, 0].set_xlabel(None)\n",
+    "g.axes[0, 1].set_xlabel(None)\n",
+    "g.axes[0, 2].set_xlabel(None)\n",
+    "g.axes[0, 0].text(0, 600, \"$\\\\sigma=10 \\%$\\n$N=10k$\", size=10, va=\"top\",\n",
+    "         bbox=dict(boxstyle=\"square\",\n",
+    "                   ec=(1., 0.5, 0.5),\n",
+    "                   fc=(1., 0.8, 0.8),\n",
+    "                   )\n",
+    "         )\n",
+    "g.axes[0, 1].text(0, 600, \"$\\\\sigma=3 \\%$\\n$N=10k$\", size=10, va=\"top\",\n",
+    "         bbox=dict(boxstyle=\"square\",\n",
+    "                   ec=(1., 0.5, 0.5),\n",
+    "                   fc=(1., 0.8, 0.8),\n",
+    "                   )\n",
+    "         )\n",
+    "g.axes[0, 2].text(0, 600, \"$\\\\sigma=60 \\%$\\n$N=10k$\", size=10, va=\"top\",\n",
+    "         bbox=dict(boxstyle=\"square\",\n",
+    "                   ec=(1., 0.5, 0.5),\n",
+    "                   fc=(1., 0.8, 0.8),\n",
+    "                   )\n",
+    "         )\n",
+    "plt.xlim(-0.1, 2.1)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python3 (sandy-devel)",
+   "language": "python",
+   "name": "sandy-devel"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/notebook_truncate_eigenvalues.ipynb b/notebooks/notebook_truncate_eigenvalues.ipynb
index 52198599..cfa02e3c 100644
--- a/notebooks/notebook_truncate_eigenvalues.ipynb
+++ b/notebooks/notebook_truncate_eigenvalues.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "9e2c4eef",
    "metadata": {},
    "outputs": [],
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "c80f558f",
    "metadata": {},
    "outputs": [],
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "02407c34",
    "metadata": {},
    "outputs": [],
@@ -59,7 +59,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "843f4c88",
    "metadata": {},
    "outputs": [],
@@ -75,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "id": "b0089402",
    "metadata": {},
    "outputs": [],
@@ -98,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "16321359",
    "metadata": {},
    "outputs": [],
@@ -108,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "7cdc4ab5",
    "metadata": {},
    "outputs": [],
@@ -120,21 +120,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "7114c325",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, axs = plt.subplots(2, 1, figsize=(7, 4), sharex=True, dpi=100)\n",
     "\n",
@@ -193,7 +182,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "32a56dfd",
    "metadata": {},
    "outputs": [],
@@ -214,21 +203,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "03e8a2ee",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 1000x500 with 4 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, axs = plt.subplots(1, 2, figsize=(10, 5), sharex=True, sharey=True, dpi=100)\n",
     "\n",
@@ -259,21 +237,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "59aee805",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 700x400 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "fig, ax = plt.subplots(figsize=(7, 4), dpi=100)\n",
     "\n",