{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Method development for geometric functions\n",
    "\n",
    "- 09/04/20 (post-debug)\n",
    "- 26/02/20 v1\n",
    "\n",
    "Aims:\n",
    "\n",
    "- Develop $\\beta_{L,M}$ formalism.\n",
    "- Develop corresponding numerical methods.\n",
    "- Speed things up (see [low-level benchmarking notebook](https://epsproc.readthedocs.io/en/dev/tests/Low_level_bench_tests_Wigner3j_Feb2020.html)).\n",
    "- Analyse geometric terms."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "* pyevtk not found, VTK export not available. \n"
     ]
    }
   ],
   "source": [
    "# Imports\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "from functools import lru_cache  # For function result caching\n",
    "\n",
    "# Special functions\n",
    "# from scipy.special import sph_harm\n",
    "import spherical_functions as sf\n",
    "import quaternion\n",
    "\n",
    "# Performance & benchmarking libraries\n",
    "# from joblib import Memory\n",
    "# import xyzpy as xyz\n",
    "import numba as nb\n",
    "\n",
    "# Timings with ttictoc\n",
    "# https://github.com/hector-sab/ttictoc\n",
    "# from ttictoc import TicToc\n",
    "\n",
    "# Package fns.\n",
    "# For module testing, include path to module here\n",
    "import sys\n",
    "import os\n",
    "modPath = r'D:\\code\\github\\ePSproc'  # Win test machine\n",
    "# modPath = r'/home/femtolab/github/ePSproc/'  # Linux test machine\n",
    "sys.path.append(modPath)\n",
    "import epsproc as ep\n",
    "# TODO: tidy this up!\n",
    "\n",
    "# Direct imports for dev functions\n",
    "from epsproc.util import matEleSelector\n",
    "from epsproc.geomFunc import geomCalc\n",
    "import epsproc._sns_matrixMod as snsMatMod  # Seaborn (SNS) code with modified clustermap function - see https://github.com/mwaskom/seaborn/pull/1393 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exploring Wigner 3js\n",
    "\n",
    "In photoionization calculations, there is a lot of angular momentum coupling to deal with. Typically, 4 to 6 Wigner 3j terms appear (depending on the formalism), and/or higher-order terms in cases where couplings are included.\n",
    "\n",
    "\\begin{equation}\n",
    "W = \\left(\\begin{array}{ccc}\n",
    "l & l' & L\\\\\n",
    "m & m' & M\n",
    "\\end{array}\\right)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Since this is, effectively, a 6D space, dimensions $(l_{max}, l_{max}, 2l_{max}, 2l_{max}+1, 2l_{max}+1, 4l_{max}+1)$ things can get large quickly. For small $l_{max}$ it's easy to look at some values directly...\n",
    "\n",
    "(For more details on [3j symbols, see Wikipedia](https://en.wikipedia.org/wiki/3-j_symbol) and [Wolfram Mathworld](https://mathworld.wolfram.com/Wigner3j-Symbol.html); for more on the numerics, see the [test notebook](https://epsproc.readthedocs.io/en/latest/tests/Spherical_function_testing_Aug_2019.html), and [benchmarks](https://epsproc.readthedocs.io/en/latest/tests/Low_level_bench_tests_Wigner3j_Feb2020.html).)\n",
    "\n",
    "TODO: test numerically some of the symmetry properties here, by summation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(25, 7)\n",
      "Max value: 1.0, min value: -0.5773502691896257\n",
      "\n",
      "[[ 0.          0.          0.          0.          0.          0.\n",
      "   1.        ]\n",
      " [ 0.          1.          1.          0.         -1.          1.\n",
      "   0.57735027]\n",
      " [ 0.          1.          1.          0.          0.          0.\n",
      "  -0.57735027]\n",
      " [ 0.          1.          1.          0.          1.         -1.\n",
      "   0.57735027]\n",
      " [ 1.          0.          1.         -1.          0.          1.\n",
      "   0.57735027]\n",
      " [ 1.          0.          1.          0.          0.          0.\n",
      "  -0.57735027]\n",
      " [ 1.          0.          1.          1.          0.         -1.\n",
      "   0.57735027]\n",
      " [ 1.          1.          2.         -1.         -1.          2.\n",
      "   0.4472136 ]\n",
      " [ 1.          1.          1.         -1.          0.          1.\n",
      "   0.40824829]\n",
      " [ 1.          1.          2.         -1.          0.          1.\n",
      "  -0.31622777]\n",
      " [ 1.          1.          0.         -1.          1.          0.\n",
      "   0.57735027]\n",
      " [ 1.          1.          1.         -1.          1.          0.\n",
      "  -0.40824829]\n",
      " [ 1.          1.          2.         -1.          1.          0.\n",
      "   0.18257419]\n",
      " [ 1.          1.          1.          0.         -1.          1.\n",
      "  -0.40824829]\n",
      " [ 1.          1.          2.          0.         -1.          1.\n",
      "  -0.31622777]\n",
      " [ 1.          1.          0.          0.          0.          0.\n",
      "  -0.57735027]\n",
      " [ 1.          1.          2.          0.          0.          0.\n",
      "   0.36514837]\n",
      " [ 1.          1.          1.          0.          1.         -1.\n",
      "   0.40824829]\n",
      " [ 1.          1.          2.          0.          1.         -1.\n",
      "  -0.31622777]\n",
      " [ 1.          1.          0.          1.         -1.          0.\n",
      "   0.57735027]\n",
      " [ 1.          1.          1.          1.         -1.          0.\n",
      "   0.40824829]\n",
      " [ 1.          1.          2.          1.         -1.          0.\n",
      "   0.18257419]\n",
      " [ 1.          1.          1.          1.          0.         -1.\n",
      "  -0.40824829]\n",
      " [ 1.          1.          2.          1.          0.         -1.\n",
      "  -0.31622777]\n",
      " [ 1.          1.          2.          1.          1.         -2.\n",
      "   0.4472136 ]]\n"
     ]
    }
   ],
   "source": [
    "# Calculate some values.\n",
    "# w3jTable will output all values up to l=lp=Lmax (hence L=2Lmax)\n",
    "lmax = 1\n",
    "w3jlist = geomCalc.w3jTable(Lmax = lmax, form = '2d', nonzeroFlag = True)  # For form = '2d', nonzeroFlag = True: the function will output only valid entries as a coordinate table\n",
    "\n",
    "print(w3jlist.shape)\n",
    "print(f'Max value: {w3jlist[:,-1].max()}, min value: {w3jlist[:,-1].min()}\\n')\n",
    "\n",
    "# Print part of the table - output format has rows (l, lp, L, m, mp, M, 3j)\n",
    "print(w3jlist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of valid (non-NaN) elements: <xarray.DataArray 'w3jStacked' ()>\n",
      "array(25)\n",
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Recalculate and set to Xarray output format, then plot with ep.lmPlot()\n",
    "\n",
    "w3j = geomCalc.w3jTable(Lmax = lmax, form = 'xdaLM', nonzeroFlag = True)\n",
    "\n",
    "# Check number of valid entries matches basic table above\n",
    "# print(f'Number of valid (non-NaN) elements: {w3j.count()}')\n",
    "print(f'Number of valid (non-NaN) elements: {w3j.notnull().sum()}')\n",
    "\n",
    "# Set parameters to restack the Xarray into (L,M) pairs\n",
    "xDim = {'LM':['L','M']}\n",
    "\n",
    "# Plot with ep.lmPlot(), real values\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(w3j, xDim=xDim, pType = 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e31f3e84e0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A complementary visulization is to call directly the sns.clustermap plot, use clustering and plot by category labels - see https://seaborn.pydata.org/index.html\n",
    "# (ep.lpPlot uses a modified version of this routine.)\n",
    "ep.basicPlotters.snsMatMod.clustermap(daPlotpd.fillna(0), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>L</th>\n",
       "      <th>0</th>\n",
       "      <th colspan=\"3\" halign=\"left\">1</th>\n",
       "      <th colspan=\"5\" halign=\"left\">2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>M</th>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>-2</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>l</th>\n",
       "      <th>lp</th>\n",
       "      <th>m</th>\n",
       "      <th>mp</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.577350</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.577350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">-1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.447214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.316228</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.57735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.182574</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.316228</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.57735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.365148</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.316228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.57735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.182574</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.316228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.447214</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "L                 0         1                             2            \\\n",
       "M                 0        -1         0         1        -2        -1   \n",
       "l lp m  mp                                                              \n",
       "0 0   0  0  1.00000       NaN       NaN       NaN       NaN       NaN   \n",
       "  1   0 -1      NaN       NaN       NaN  0.577350       NaN       NaN   \n",
       "         0      NaN       NaN -0.577350       NaN       NaN       NaN   \n",
       "         1      NaN  0.577350       NaN       NaN       NaN       NaN   \n",
       "1 0  -1  0      NaN       NaN       NaN  0.577350       NaN       NaN   \n",
       "      0  0      NaN       NaN -0.577350       NaN       NaN       NaN   \n",
       "      1  0      NaN  0.577350       NaN       NaN       NaN       NaN   \n",
       "  1  -1 -1      NaN       NaN       NaN       NaN       NaN       NaN   \n",
       "         0      NaN       NaN       NaN  0.408248       NaN       NaN   \n",
       "         1  0.57735       NaN -0.408248       NaN       NaN       NaN   \n",
       "      0 -1      NaN       NaN       NaN -0.408248       NaN       NaN   \n",
       "         0 -0.57735       NaN       NaN       NaN       NaN       NaN   \n",
       "         1      NaN  0.408248       NaN       NaN       NaN -0.316228   \n",
       "      1 -1  0.57735       NaN  0.408248       NaN       NaN       NaN   \n",
       "         0      NaN -0.408248       NaN       NaN       NaN -0.316228   \n",
       "         1      NaN       NaN       NaN       NaN  0.447214       NaN   \n",
       "\n",
       "L                                         \n",
       "M                  0         1         2  \n",
       "l lp m  mp                                \n",
       "0 0   0  0       NaN       NaN       NaN  \n",
       "  1   0 -1       NaN       NaN       NaN  \n",
       "         0       NaN       NaN       NaN  \n",
       "         1       NaN       NaN       NaN  \n",
       "1 0  -1  0       NaN       NaN       NaN  \n",
       "      0  0       NaN       NaN       NaN  \n",
       "      1  0       NaN       NaN       NaN  \n",
       "  1  -1 -1       NaN       NaN  0.447214  \n",
       "         0       NaN -0.316228       NaN  \n",
       "         1  0.182574       NaN       NaN  \n",
       "      0 -1       NaN -0.316228       NaN  \n",
       "         0  0.365148       NaN       NaN  \n",
       "         1       NaN       NaN       NaN  \n",
       "      1 -1  0.182574       NaN       NaN  \n",
       "         0       NaN       NaN       NaN  \n",
       "         1       NaN       NaN       NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Print out values by QNs (Pandas table)\n",
    "daPlotpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This ends up as a relatively sparse array, since many combinations are invalid (do not follow angular momentum selection rules), hence there are many NaN terms.\n",
    "\n",
    "The results can also be output as a 6D sparse array, using the [Sparse library](https://sparse.pydata.org/en/latest/index.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tbody><tr><th style=\"text-align: left\">Format</th><td style=\"text-align: left\">coo</td></tr><tr><th style=\"text-align: left\">Data Type</th><td style=\"text-align: left\">float64</td></tr><tr><th style=\"text-align: left\">Shape</th><td style=\"text-align: left\">(2, 2, 3, 2, 2, 3)</td></tr><tr><th style=\"text-align: left\">nnz</th><td style=\"text-align: left\">57</td></tr><tr><th style=\"text-align: left\">Density</th><td style=\"text-align: left\">0.3958333333333333</td></tr><tr><th style=\"text-align: left\">Read-only</th><td style=\"text-align: left\">True</td></tr><tr><th style=\"text-align: left\">Size</th><td style=\"text-align: left\">3.1K</td></tr><tr><th style=\"text-align: left\">Storage ratio</th><td style=\"text-align: left\">2.8</td></tr></tbody></table>"
      ],
      "text/plain": [
       "<COO: shape=(2, 2, 3, 2, 2, 3), dtype=float64, nnz=57, fill_value=0.0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculate and output in Sparse array format\n",
    "w3jSparse = geomCalc.w3jTable(Lmax = lmax, form = 'ndsparse')\n",
    "w3jSparse"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here `nnz` is the number of non-zero elements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of valid (non-NaN) elements: <xarray.DataArray 'w3jStacked' ()>\n",
      "array(7056)\n",
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Try a larger Lmax and plot only.\n",
    "lmax = 3\n",
    "w3j = geomCalc.w3jTable(Lmax = lmax, form = 'xdaLM')\n",
    "\n",
    "# Check number of valid entries matches basic table above\n",
    "print(f'Number of valid (non-NaN) elements: {w3j.count()}')\n",
    "\n",
    "# Set parameters to restack the Xarray into (L,M) pairs\n",
    "plotDimsRed = ['l', 'm', 'lp', 'mp']\n",
    "xDim = {'LM':['L','M']}\n",
    "\n",
    "# Plot with ep.lmPlot(), real values\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(w3j, plotDims=plotDimsRed, xDim=xDim, pType = 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Resort axis by (l,lp)\n",
    "plotDimsRed = ['l', 'lp', 'm', 'mp']\n",
    "xDim = {'LM':['L','M']}\n",
    "\n",
    "# Plot with ep.lmPlot(), real values\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(w3j, plotDims=plotDimsRed, xDim=xDim, pType = 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e32129e2b0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A complementary visulization is to call directly the sns.clustermap plot, use clustering and plot by category labels - see https://seaborn.pydata.org/index.html\n",
    "# (ep.lpPlot uses a modified version of this routine.)\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This clearly shows that the valid terms become sparser at higher $l$, and the couplings become smaller.\n",
    "\n",
    "Structure can also be examined using other methods, e.g. correlation functions (see, for example, [Seaborn Discovering structure in heatmap data](https://seaborn.pydata.org/examples/structured_heatmap.html). The example here shows [Panda's standard Pearson correlation coefficient](https://pandas.pydata.org/pandas-docs/stable/user_guide/computation.html#correlation), which may (or may not) be particularly meaningful here... but does show structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e322ce36a0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0).T.corr(), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Test some other Seaborn methods... these likely won't scale well for large lmax!\n",
    "import seaborn as sns\n",
    "\n",
    "# Recalculate for small lmax\n",
    "lmax = 1\n",
    "w3j = geomCalc.w3jTable(Lmax = lmax, form = 'xdaLM')\n",
    "\n",
    "# Set parameters to restack the Xarray into (L,M) pairs\n",
    "plotDimsRed = ['l', 'm', 'lp', 'mp']\n",
    "xDim = {'LM':['L','M']}\n",
    "\n",
    "# Plot with ep.lmPlot(), real values\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(w3j, plotDims=plotDimsRed, xDim=xDim, pType = 'r')\n",
    "\n",
    "# Try sns pairplot\n",
    "# sns.pairplot(daPlotpd.fillna(0).T)  # Big grids!\n",
    "# sns.pairplot(daPlotpd.fillna(0))  # OK, not particularly informative\n",
    "# sns.pairplot(daPlotpd.fillna(0), hue = 'l')  # Doesn't work - multindex issue?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## $E_{P,R}$ tensor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The coupling of two 1-photon terms can be written as a tensor contraction:\n",
    "\n",
    "\\begin{equation}\n",
    "E_{PR}(\\hat{e})=[e\\otimes e^{*}]_{R}^{P}=[P]^{\\frac{1}{2}}\\sum_{p}(-1)^{R}\\left(\\begin{array}{ccc}\n",
    "1 & 1 & P\\\\\n",
    "p & R-p & -R\n",
    "\\end{array}\\right)e_{p}e_{R-p}^{*}\\label{eq:EPR-defn-1}\n",
    "\\end{equation}\n",
    "\n",
    "Where $e_{p}$ and $e_{R-p}$ define the field strengths for the polarizations $p$ and $R-p$, which are coupled into the spherical tensor $E_{PR}$.\n",
    "\n",
    "(To derive this result, one can start from, e.g., Eq. 5.40 in Zare\n",
    "\n",
    "\\begin{equation}\n",
    "[A^{(1)}\\otimes B^{(1)}]_{q}^{k}=\\sum_{m}\\langle1m,1q-m|kq\\rangle A(1,m)B(1,q-m)\n",
    "\\end{equation}\n",
    "\n",
    "Convert to $3j$ form:\n",
    "\n",
    "\\begin{equation}\n",
    "[A^{(1)}\\otimes B^{(1)}]_{q}^{k}=\\sum_{m}(-1)^{q}[k]^{1/2}\\left(\\begin{array}{ccc}\n",
    "1 & 1 & k\\\\\n",
    "m & q-m & -q\n",
    "\\end{array}\\right)A(1,m)B(1,q-m)\n",
    "\\end{equation}\n",
    "\n",
    "And substitute in appropriate terms.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 1.          1.          0.         -1.          1.          0.\n",
      "   0.57735027]\n",
      " [ 1.          1.          1.         -1.          0.          1.\n",
      "  -0.70710678]\n",
      " [ 1.          1.          1.         -1.          1.          0.\n",
      "  -0.70710678]\n",
      " [ 1.          1.          2.         -1.         -1.          2.\n",
      "   1.        ]\n",
      " [ 1.          1.          2.         -1.          0.          1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          2.         -1.          1.          0.\n",
      "   0.40824829]\n",
      " [ 1.          1.          0.          0.          0.          0.\n",
      "  -0.57735027]\n",
      " [ 1.          1.          1.          0.         -1.          1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          1.          0.          1.         -1.\n",
      "  -0.70710678]\n",
      " [ 1.          1.          2.          0.         -1.          1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          2.          0.          0.          0.\n",
      "   0.81649658]\n",
      " [ 1.          1.          2.          0.          1.         -1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          0.          1.         -1.          0.\n",
      "   0.57735027]\n",
      " [ 1.          1.          1.          1.         -1.          0.\n",
      "   0.70710678]\n",
      " [ 1.          1.          1.          1.          0.         -1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          2.          1.         -1.          0.\n",
      "   0.40824829]\n",
      " [ 1.          1.          2.          1.          0.         -1.\n",
      "   0.70710678]\n",
      " [ 1.          1.          2.          1.          1.         -2.\n",
      "   1.        ]]\n"
     ]
    }
   ],
   "source": [
    "# Calculate EPR terms, all QNs, with field strengths e = 1\n",
    "EPRtable = geomCalc.EPR(form = '2d')\n",
    "\n",
    "# Output values as list, [l, lp, P, p, R-p, R, EPR]\n",
    "print(EPRtable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As before, we can visualise these values..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n",
      "Set dataType (No dataType)\n",
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "EPRX = geomCalc.EPR(form = 'xarray')\n",
    "\n",
    "# Set parameters to restack the Xarray into (L,M) pairs\n",
    "# plotDimsRed = ['l', 'p', 'lp', 'R-p']\n",
    "plotDimsRed = ['p', 'R-p']\n",
    "xDim = {'PR':['P','R']}\n",
    "\n",
    "# Plot with ep.lmPlot(), real values\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(EPRX, plotDims=plotDimsRed, xDim=xDim, pType = 'r')\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(EPRX.unstack().sum(['l','lp','R-p']), xDim=xDim, pType = 'r')\n",
    "\n",
    "# Seem to have some all-NaN cols persisting here, not sure why..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>P</th>\n",
       "      <th>0</th>\n",
       "      <th colspan=\"3\" halign=\"left\">1</th>\n",
       "      <th colspan=\"5\" halign=\"left\">2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>R</th>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>-2</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-1</th>\n",
       "      <td>0.57735</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.707107</td>\n",
       "      <td>-0.707107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.57735</td>\n",
       "      <td>-0.707107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.816497</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.57735</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "P         0         1                        2                                \\\n",
       "R         0        -1         0         1   -2        -1         0         1   \n",
       "p                                                                              \n",
       "-1  0.57735       NaN -0.707107 -0.707107  NaN       NaN  0.408248  0.707107   \n",
       " 0 -0.57735 -0.707107       NaN  0.707107  NaN  0.707107  0.816497  0.707107   \n",
       " 1  0.57735  0.707107  0.707107       NaN  1.0  0.707107  0.408248       NaN   \n",
       "\n",
       "P        \n",
       "R     2  \n",
       "p        \n",
       "-1  1.0  \n",
       " 0  NaN  \n",
       " 1  NaN  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Tabulate\n",
    "daPlotpd.dropna(axis = 1, how = 'all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e324879748>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A complementary visulization is to call directly the sns.clustermap plot, use clustering and plot by category labels - see https://seaborn.pydata.org/index.html\n",
    "# (ep.lpPlot uses a modified version of this routine.)\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e3249a9668>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0).T.corr(), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## $B_{L,M}$ term\n",
    "\n",
    "The coupling of the partial wave pairs, $|l,m\\rangle$ and $|l',m'\\rangle$, into the observable set of $\\{L,M\\}$ is defined by a tensor contraction with two 3j terms.\n",
    "\n",
    "\\begin{equation}\n",
    "B_{L,M}=(-1)^{m}\\left(\\frac{(2l+1)(2l'+1)(2L+1)}{4\\pi}\\right)^{1/2}\\left(\\begin{array}{ccc}\n",
    "l & l' & L\\\\\n",
    "0 & 0 & 0\n",
    "\\end{array}\\right)\\left(\\begin{array}{ccc}\n",
    "l & l' & L\\\\\n",
    "-m & m' & M\n",
    "\\end{array}\\right)\n",
    "\\end{equation}\n",
    "\n",
    "(See notebook ePSproc_wigner3j_dataStructures_260220.ipynb on Bemo for additonal dev details)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that this term is equivalent, effectively, as the triple intergral over spherical harmonics (e.g. eqn. 3.119 in Zare):\n",
    "\n",
    "\\begin{equation}\n",
    "\\intop_{0}^{2\\pi}\\intop_{0}^{\\pi}Y_{J_{3}M_{3}}(\\theta,\\phi)Y_{J_{2}M_{2}}(\\theta,\\phi)Y_{J_{1}M_{1}}(\\theta,\\phi)\\sin\\theta d\\theta d\\phi=\\left(\\frac{(2J_{1}+1)(2J_{2}+1)(2J_{3}+1)}{4\\pi}\\right)^{1/2}\\left(\\begin{array}{ccc}\n",
    "J_{1} & J_{2} & J_{3}\\\\\n",
    "0 & 0 & 0\n",
    "\\end{array}\\right)\\left(\\begin{array}{ccc}\n",
    "J_{1} & J_{2} & J_{3}\\\\\n",
    "M_{1} & M_{2} & M_{3}\n",
    "\\end{array}\\right)\n",
    "\\end{equation}\n",
    "\n",
    "\n",
    "... or contraction over a pair of harmonics into a resultant harmonic (e.g. eqns. C.21, C.22 in Blum), and this is how the term arises in the derivation.\n",
    "\n",
    "\\begin{equation}\n",
    "Y_{J_{1}M_{1}}(\\theta,\\phi)Y_{J_{2}M_{2}}(\\theta,\\phi)=\\sum_{J_{3}M_{3}}\\left(\\frac{(2J_{1}+1)(2J_{2}+1)(2J_{3}+1)}{4\\pi}\\right)^{1/2}\\left(\\begin{array}{ccc}\n",
    "J_{1} & J_{2} & J_{3}\\\\\n",
    "0 & 0 & 0\n",
    "\\end{array}\\right)\\left(\\begin{array}{ccc}\n",
    "J_{1} & J_{2} & J_{3}\\\\\n",
    "M_{1} & M_{2} & M_{3}\n",
    "\\end{array}\\right)Y^*_{J_{3}M_{3}}(\\theta,\\phi)\n",
    "\\end{equation}\n",
    "\n",
    "(Again, for more details on [see Wikipedia](https://en.wikipedia.org/wiki/3-j_symbol) and [Wolfram Mathworld](https://mathworld.wolfram.com/Wigner3j-Symbol.html).)\n",
    "\n",
    "Note also some defns. use conjugate spherical harmonics, can convert as (Blum C.21):\n",
    "\n",
    "\\begin{equation}\n",
    "\\beta_{L,M}^{\\mu_{i},\\mu_{f}}Y_{LM}^{*}(\\theta_{\\hat{k}},\\phi_{\\hat{k}})=\\beta_{L,-M}^{\\mu_{i},\\mu_{f}}(-1)^{M}Y_{L,-M}(\\theta_{\\hat{k}},\\phi_{\\hat{k}})\\label{eq:sph-conj-conv}\n",
    "\\end{equation}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Lmax = 1\n",
    "BLMtable = geomCalc.betaTerm(Lmax = Lmax, form = 'xdaLM').stack({'lSet':['l','lp','L'],'mSet':['m','mp','M']}).dropna('mSet',how='all').dropna('lSet',how='all')  # Output as stacked Xarray & drop NaNs where possible"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray &#x27;w3jStacked&#x27; (lSet: 5, mSet: 9)&gt;\n",
       "array([[        nan,         nan,         nan,         nan,  0.28209479,\n",
       "                nan,         nan,         nan,         nan],\n",
       "       [        nan,         nan,         nan, -0.28209479,  0.28209479,\n",
       "        -0.28209479,         nan,         nan,         nan],\n",
       "       [        nan,  0.28209479,         nan,         nan,  0.28209479,\n",
       "                nan,         nan,  0.28209479,         nan],\n",
       "       [        nan,         nan,  0.28209479,         nan,  0.28209479,\n",
       "                nan,  0.28209479,         nan,         nan],\n",
       "       [-0.30901936,  0.21850969, -0.12615663, -0.21850969,  0.25231325,\n",
       "        -0.21850969, -0.12615663,  0.21850969, -0.30901936]])\n",
       "Coordinates:\n",
       "  * lSet     (lSet) MultiIndex\n",
       "  - l        (lSet) int64 0 0 1 1 1\n",
       "  - lp       (lSet) int64 0 1 0 1 1\n",
       "  - L        (lSet) int64 0 1 1 0 2\n",
       "  * mSet     (mSet) MultiIndex\n",
       "  - m        (mSet) int64 -1 -1 -1 0 0 0 1 1 1\n",
       "  - mp       (mSet) int64 -1 0 1 -1 0 1 -1 0 1\n",
       "  - M        (mSet) int64 2 1 0 1 0 -1 0 -1 -2\n",
       "Attributes:\n",
       "    dataType:   betaTerm\n",
       "    phaseCons:  {&#x27;phaseConvention&#x27;: &#x27;S&#x27;, &#x27;genMatEcons&#x27;: {&#x27;negm&#x27;: False}, &#x27;EPR...</pre>"
      ],
      "text/plain": [
       "<xarray.DataArray 'w3jStacked' (lSet: 5, mSet: 9)>\n",
       "array([[        nan,         nan,         nan,         nan,  0.28209479,\n",
       "                nan,         nan,         nan,         nan],\n",
       "       [        nan,         nan,         nan, -0.28209479,  0.28209479,\n",
       "        -0.28209479,         nan,         nan,         nan],\n",
       "       [        nan,  0.28209479,         nan,         nan,  0.28209479,\n",
       "                nan,         nan,  0.28209479,         nan],\n",
       "       [        nan,         nan,  0.28209479,         nan,  0.28209479,\n",
       "                nan,  0.28209479,         nan,         nan],\n",
       "       [-0.30901936,  0.21850969, -0.12615663, -0.21850969,  0.25231325,\n",
       "        -0.21850969, -0.12615663,  0.21850969, -0.30901936]])\n",
       "Coordinates:\n",
       "  * lSet     (lSet) MultiIndex\n",
       "  - l        (lSet) int64 0 0 1 1 1\n",
       "  - lp       (lSet) int64 0 1 0 1 1\n",
       "  - L        (lSet) int64 0 1 1 0 2\n",
       "  * mSet     (mSet) MultiIndex\n",
       "  - m        (mSet) int64 -1 -1 -1 0 0 0 1 1 1\n",
       "  - mp       (mSet) int64 -1 0 1 -1 0 1 -1 0 1\n",
       "  - M        (mSet) int64 2 1 0 1 0 -1 0 -1 -2\n",
       "Attributes:\n",
       "    dataType:   betaTerm\n",
       "    phaseCons:  {'phaseConvention': 'S', 'genMatEcons': {'negm': False}, 'EPR..."
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "BLMtable  #.sel({'l':1,'lp':1,'M':0})  # Print subset of terms with l=lp=1, M=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotDimsRed = ['l', 'm', 'lp', 'mp']\n",
    "xDim = {'LM':['L','M']}\n",
    "# daPlot = BLMtable.unstack().stack({'LM':['L','M']})\n",
    "# ep.lmPlot(w3jXcombMult.unstack().stack({'LM':['l','m']}), plotDims=['lp', 'L', 'mp', 'M'], xDim='LM', SFflag = False)\n",
    "# daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMtable.unstack().stack(xDim), plotDims=plotDimsRed, xDim=xDim, SFflag = False, squeeze = False)\n",
    "# daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMtable, plotDims=plotDimsRed, xDim=xDim)\n",
    "# ep.lmPlot(w3jXcombMult.unstack(), plotDims=['lp', 'L', 'mp', 'M'], xDim='L', SFflag = False)\n",
    "\n",
    "# daPlotpd = daPlot.unstack().stack(plotDim = plotDimsRed).to_pandas().dropna(axis = 1).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMtable.unstack().stack(xDim), plotDims=plotDimsRed, xDim=xDim, pType = 'r')\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMtable, plotDims=plotDimsRed, xDim=xDim, pType = 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>L</th>\n",
       "      <th>0</th>\n",
       "      <th colspan=\"3\" halign=\"left\">1</th>\n",
       "      <th colspan=\"5\" halign=\"left\">2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>M</th>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>-2</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>l</th>\n",
       "      <th>m</th>\n",
       "      <th>lp</th>\n",
       "      <th>mp</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"12\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">-1</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.309019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.21851</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.126157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.21851</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.252313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.21851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.126157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.21851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.309019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "L                  0         1                             2           \\\n",
       "M                  0        -1         0         1        -2       -1   \n",
       "l m  lp mp                                                              \n",
       "0  0 0   0  0.282095       NaN       NaN       NaN       NaN      NaN   \n",
       "     1  -1       NaN       NaN       NaN -0.282095       NaN      NaN   \n",
       "         0       NaN       NaN  0.282095       NaN       NaN      NaN   \n",
       "         1       NaN -0.282095       NaN       NaN       NaN      NaN   \n",
       "1 -1 0   0       NaN       NaN       NaN  0.282095       NaN      NaN   \n",
       "     1  -1       NaN       NaN       NaN       NaN       NaN      NaN   \n",
       "         0       NaN       NaN       NaN       NaN       NaN      NaN   \n",
       "         1  0.282095       NaN       NaN       NaN       NaN      NaN   \n",
       "   0 0   0       NaN       NaN  0.282095       NaN       NaN      NaN   \n",
       "     1  -1       NaN       NaN       NaN       NaN       NaN      NaN   \n",
       "         0  0.282095       NaN       NaN       NaN       NaN      NaN   \n",
       "         1       NaN       NaN       NaN       NaN       NaN -0.21851   \n",
       "   1 0   0       NaN  0.282095       NaN       NaN       NaN      NaN   \n",
       "     1  -1  0.282095       NaN       NaN       NaN       NaN      NaN   \n",
       "         0       NaN       NaN       NaN       NaN       NaN  0.21851   \n",
       "         1       NaN       NaN       NaN       NaN -0.309019      NaN   \n",
       "\n",
       "L                                        \n",
       "M                  0        1         2  \n",
       "l m  lp mp                               \n",
       "0  0 0   0       NaN      NaN       NaN  \n",
       "     1  -1       NaN      NaN       NaN  \n",
       "         0       NaN      NaN       NaN  \n",
       "         1       NaN      NaN       NaN  \n",
       "1 -1 0   0       NaN      NaN       NaN  \n",
       "     1  -1       NaN      NaN -0.309019  \n",
       "         0       NaN  0.21851       NaN  \n",
       "         1 -0.126157      NaN       NaN  \n",
       "   0 0   0       NaN      NaN       NaN  \n",
       "     1  -1       NaN -0.21851       NaN  \n",
       "         0  0.252313      NaN       NaN  \n",
       "         1       NaN      NaN       NaN  \n",
       "   1 0   0       NaN      NaN       NaN  \n",
       "     1  -1 -0.126157      NaN       NaN  \n",
       "         0       NaN      NaN       NaN  \n",
       "         1       NaN      NaN       NaN  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daPlotpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e320212198>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A complementary visulization is to call directly the sns.clustermap plot, use clustering and plot by category labels - see https://seaborn.pydata.org/index.html\n",
    "# (ep.lpPlot uses a modified version of this routine.)\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0).T, center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e3201d3da0>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0).T.corr(), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e31e632da0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0).corr(), center=0, cmap=\"vlag\", row_cluster=True, col_cluster=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do we learn here...?  This is a nice way to visualize the selection rules into the observable: for instance, only terms $l=l'$ and $m=-m'$ contribute to the overall photoinoization cross-section term ($L=0, M=0$). However, since these terms are fairly simply followed algebraically in this case, via the rules inherent in the 3j product, this is not particularly insightful. These visualizations will become more useful when dealing with real sets of matrix elements, and specific polarization geometries, which will further modulate the $B_{L,M}$ terms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOT AS A FN. of dl, dm... should just need to recalc dims or add a separate label for this?\n",
    "# dl = BLMtable.l - BLMtable.lp\n",
    "# dm = BLMtable.m - BLMtable.mp\n",
    "\n",
    "BLMdeltas = BLMtable.unstack().stack({'LM':['L','M'], 'dl':['l','lp'], 'dm':['m','mp']})\n",
    "dl = BLMdeltas.l - BLMdeltas.lp\n",
    "dm = BLMdeltas.m - BLMdeltas.mp\n",
    "\n",
    "# Set new dims & plot\n",
    "BLMdeltas = BLMdeltas.assign_coords(dl=dl, dm=dm)  # This works, but not plotting correctly for some reason - maybe dim names?\n",
    "plotDimsRed = ['dl','dm']\n",
    "# BLMdeltas = BLMdeltas.assign_coords(dl=dl, dm=dm).rename({'dl':'l', 'dm':'m'})  # Hmm, same result - values present in daPlotpd not showing up here, or losing correlations...?\n",
    "# plotDimsRed = ['l','m']\n",
    "xDim = {'LM':['L','M']}\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMdeltas, plotDims=plotDimsRed, xDim=xDim, pType = 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>L</th>\n",
       "      <th>0</th>\n",
       "      <th colspan=\"3\" halign=\"left\">1</th>\n",
       "      <th colspan=\"5\" halign=\"left\">2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>M</th>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>-2</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dl</th>\n",
       "      <th>dm</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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">-1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.309019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.21851</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-2</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.126157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.21851</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.252313</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.21851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.282095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.126157</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.21851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.309019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "L             0         1                             2                     \\\n",
       "M             0        -1         0         1        -2       -1         0   \n",
       "dl dm                                                                        \n",
       " 0  0  0.282095       NaN       NaN       NaN       NaN      NaN       NaN   \n",
       "-1  1       NaN       NaN       NaN -0.282095       NaN      NaN       NaN   \n",
       "    0       NaN       NaN  0.282095       NaN       NaN      NaN       NaN   \n",
       "   -1       NaN -0.282095       NaN       NaN       NaN      NaN       NaN   \n",
       " 1 -1       NaN       NaN       NaN  0.282095       NaN      NaN       NaN   \n",
       "    0       NaN       NaN  0.282095       NaN       NaN      NaN       NaN   \n",
       "    1       NaN  0.282095       NaN       NaN       NaN      NaN       NaN   \n",
       " 0  0       NaN       NaN       NaN       NaN       NaN      NaN       NaN   \n",
       "   -1       NaN       NaN       NaN       NaN       NaN      NaN       NaN   \n",
       "   -2  0.282095       NaN       NaN       NaN       NaN      NaN -0.126157   \n",
       "    1       NaN       NaN       NaN       NaN       NaN      NaN       NaN   \n",
       "    0  0.282095       NaN       NaN       NaN       NaN      NaN  0.252313   \n",
       "   -1       NaN       NaN       NaN       NaN       NaN -0.21851       NaN   \n",
       "    2  0.282095       NaN       NaN       NaN       NaN      NaN -0.126157   \n",
       "    1       NaN       NaN       NaN       NaN       NaN  0.21851       NaN   \n",
       "    0       NaN       NaN       NaN       NaN -0.309019      NaN       NaN   \n",
       "\n",
       "L                         \n",
       "M            1         2  \n",
       "dl dm                     \n",
       " 0  0      NaN       NaN  \n",
       "-1  1      NaN       NaN  \n",
       "    0      NaN       NaN  \n",
       "   -1      NaN       NaN  \n",
       " 1 -1      NaN       NaN  \n",
       "    0      NaN       NaN  \n",
       "    1      NaN       NaN  \n",
       " 0  0      NaN -0.309019  \n",
       "   -1  0.21851       NaN  \n",
       "   -2      NaN       NaN  \n",
       "    1 -0.21851       NaN  \n",
       "    0      NaN       NaN  \n",
       "   -1      NaN       NaN  \n",
       "    2      NaN       NaN  \n",
       "    1      NaN       NaN  \n",
       "    0      NaN       NaN  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daPlotpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e3250809b0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note correlation of terms, with final $L$ and $M$ odd or even terms grouped according to odd or even $\\Delta l$ and  $\\Delta m$ respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e32110f710>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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+ZXz7298uak4AAGDg6v2K0fFjxczRb5/61Kdi79698fDDD0fEH77gdc6cOfH//t//6/GaOXPmxKuvvhoPPvhgVFRUxDe/+c2oqamJp556Kt773veWKjoAADBADOqtdE8//XQ8/PDD8cQTT8QHPvCBiIi46667orq6Op555pl497vf3e11u3btinXr1sX73//+iIhYunRpNDQ0xI9+9CPFCAAAUqjXW+mOdbT3+2hra4uDBw92Otra2t5y+F27dsWIESNOlKKIiA9+8IMxYsSIaG5u7vG6yy67LO6777747W9/G8ePH49777032tra4q/+6q/eciYAAGDw6f0zRsfb+33U19efeAbojaO+vv4thy8UCvGud72ry/i73vWuKBQKPV533333xbFjx2LkyJGRzWZjwYIFsWXLlrjgggveciYAAGDw6cMzRkf7/SF1dXVRW1vbaSybzfZ4/vLly2PFihUnvefu3bsjIiKTyXSZ6+jo6Hb8DUuXLo1XXnklHnnkkaioqIjGxsb4xCc+EY8//nhccsklJ/1cAADg9FOSZ4yy2exJi9Cf+tznPhczZ8486TnnnXde/PSnP42XX365y9yvf/3ryOVy3V733HPPxR133BEtLS0xbty4iIgYP358PP7443HnnXf6bhkAAEih3n/B6/HSvXyhoqIiKioq3vS86urqePXVV+PJJ5888SKFH/7wh/Hqq6/GxIkTu73m8OHDERExZEjnXYRlZWVx/HhxXy0OAAAMTL1/+cLx9n4fxVJVVRUf+chH4rOf/Ww88cQT8cQTT8RnP/vZ+OhHP3rijXQvvfRSXHTRRfHkk09GRMRFF10UF154YSxYsCCefPLJeO655+IrX/lKNDU1xfTp04uWFQAAGLh6vWJ0pH1gfo/RN77xjfj85z8fU6dOjYiIj33sY3HHHXecmD969Gg888wzJ1aKysvL46GHHoqbb745rr766jh06FBceOGFcc8998R/+S//JZFfAwAAkKw+vHxh4H2PUUTEO9/5zvj617/e4/x5550XHR0dncb+43/8j/Gd73yn2NEAAIBBotfFqH2AFiMAAIC3KtPxp8spAAAAKdPrly8AAACcrnq9lY5T4+iB55OO0GvHnmhMOkKvHXv4kaQjnLYe+Kd3Jh2h1z584d6kI/TaI8/+RdIRTluD6fcBxTOY/hkbbL9n/WyLYzD9XCMiZv+q52f8BysrRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQFHt3r07Zs2aFWPHjo0zzzwzzjrrrBg7dmzMmjUrnnrqqaTjRUTEGUkHAAAATl+NjY0xY8aMuPLKK+PGG2+MXC4XHR0dsX///ti6dWtMmjQp7r///pg2bVqiORUjAACgT9ra2qKtra3TWDabjWw22+XcpUuXxsqVK+Pmm2/uMrdo0aK49dZb45ZbblGMTrV8Ph+tra1Jx+hi06ZNSUcAAIBTor6+PlasWNFpbNmyZbF8+fIu5z777LNx7bXX9niv6dOnx7Jly051xD477YpRa2urEgIAAEVUV1cXtbW1nca6Wy2KiLjggguisbExbrrppm7nH3jggTj//PNPeca+Ou2KEQAAUFw9bZvrzsqVK2PmzJmxffv2mDp1auRyuchkMlEoFKKpqSm2bt0a9957b5ETvznFCAAAKJrrrrsuHnvssbj99ttj9erVUSgUIiJi1KhRUV1dHdu3b4/q6uqEUypGAABAkVVXVw+I8nMyvscIAABIPcUIAABI1OTJk2PVqlVx+PDhxDIoRgAAQKLGjBkT27Zti6qqqsQyeMYIAABI1MaNGyMi4tChQ4llUIwAAICi2rt3b6xbty6am5ujUChEJpOJXC4XEydOjHw+H6NHj46IiGHDhiWW0VY6AACgaHbs2BFVVVWxZcuWGD9+fMydOzdmz54d48ePj8bGxhg3blzs3Lkz6ZhWjAAAgOJZvHhxzJ8/PxoaGnqcX7RoUezevbvEyTqzYgQAABRNS0tL5PP5HucXLFgQLS0tJUzUPcUIAAAomsrKymhubu5xfteuXVFZWVnCRN2zlQ4AACiaJUuWRD6fjz179sSUKVMil8tFJpOJQqEQTU1Ncffdd8eaNWuSjqkYAQAAxbNw4cIYOXJkNDQ0xIYNG6K9vT0iIsrKymLChAmxefPmmDFjRsIpFSMAAKDIampqoqamJo4ePRoHDhyIiIiKioooLy9PONkfKUYAAEBJlJeXD4jnibrj5QsAAEDqKUYAAEDqKUYAAEDqecaoxI490Zh0hF4744PTk47Qa2XvuSzpCKetEd/u/luqB6LWgwPnAc43M+J4e9IRTluD6fcBxTOY/hkbbL9n/WyLYzD9XE9XVowAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUO6O/F+bz+WhtbT2VWU6Jffv2JR0BAAAYZPpdjFpbW2PTpk2nMMqpMW/evKQjAAAAg4ytdAAAQOopRgAAQOopRgAAQFHt3r07Zs2aFWPHjo0zzzwzzjrrrBg7dmzMmjUrnnrqqaTjRcRbeMYIAABIp7a2tmhra+s0ls1mI5vNdjm3sbExZsyYEVdeeWXceOONkcvloqOjI/bv3x9bt26NSZMmxf333x/Tpk0rVfxuKUZ98FbexDcQX1QBAAD9UV9fHytWrOg0tmzZsli+fHmXc5cuXRorV66Mm2++ucvcokWL4tZbb41bbrlFMRpMBuqb+AAAoJTq6uqitra201h3q0UREc8++2xce+21Pd5r+vTpsWzZslOarz88YwQAAPRJNpuN4cOHdzp6KkYXXHBBNDY29nivBx54IM4///xiRe01K0YAAEDRrFy5MmbOnBnbt2+PqVOnRi6Xi0wmE4VCIZqammLr1q1x7733Jh1TMQIAAIrnuuuui8ceeyxuv/32WL16dRQKhYiIGDVqVFRXV8f27dujuro64ZSKEQAAUGTV1dUDovycjGeMAACA1FOMAACARE2ePDlWrVoVhw8fTiyDYgQAACRqzJgxsW3btqiqqkosg2eMAACARG3cuDEiIg4dOpRYBsUIAAAoqr1798a6deuiubk5CoVCZDKZyOVyMXHixMjn8zF69OiIiBg2bFhiGW2lAwAAimbHjh1RVVUVW7ZsifHjx8fcuXNj9uzZMX78+GhsbIxx48bFzp07k45pxQgAACiexYsXx/z586OhoaHH+UWLFsXu3btLnKwzK0YAAEDRtLS0RD6f73F+wYIF0dLSUsJE3VOMAACAoqmsrIzm5uYe53ft2hWVlZUlTNQ9W+kAAICiWbJkSeTz+dizZ09MmTIlcrlcZDKZKBQK0dTUFHfffXesWbMm6ZiKEQAAUDwLFy6MkSNHRkNDQ2zYsCHa29sjIqKsrCwmTJgQmzdvjhkzZiScUjECAACKrKamJmpqauLo0aNx4MCBiIioqKiI8vLyhJP9kWIEAACURHl5+YB4nqg7Xr4AAACknmIEAACknq10JXbs4UeSjtBrZe+5LOkIvZYZXpF0hNPW2zuOJR2h1w6/9rakI/TaYPq5DjaD6fcBxTOY/hkbbL9n/WyLYzD9XE9XVowAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUU4wAAIDUOyPpAKfa0KFDY968eUW59759+4pyXwAAIFmnXTFav3590e5drMIFAAAky1Y6AAAg9RQjAAAg9RQjAAAg9RQjAAAg9RQjAAAg9RQjAAAg9RQjAACgqH7/+9/Hjh074uc//3mXudbW1ti8eXMCqTpTjAAAgKL5xS9+EVVVVfGhD30oLrnkkvirv/qr2Ldv34n5V199Na6//voEE/6BYgQAAPRJW1tbHDx4sNPR1tbW7bl///d/H5dcckns378/nnnmmRg+fHhMmjQpXnzxxRKnPjnFCAAA6JP6+voYMWJEp6O+vr7bc5ubm+O///f/HhUVFXHhhRfGgw8+GFdddVVcfvnl8fzzz5c4ec/OSDoAAAAwuNTV1UVtbW2nsWw22+25v//97+OMMzrXjjvvvDOGDBkSV1xxRXzzm98sWs6+UIwAAIA+yWazPRahP3XRRRfFU089FVVVVZ3G/8//+T/R0dERH/vYx4oRsc9spQMAAIrmmmuuiW9961vdzt1xxx3xyU9+Mjo6OkqcqivFCAAAKJq6urp46KGHepxfu3ZtHD9+vISJuqcYAQAAJfWtb30rXn/99aRjdKIYAQAAJbVgwYJ4+eWXk47RiWIEAACU1EB4puhPKUYAAEDqKUYAAEBJffe7341zzjkn6Rid+B4jAACgpC677LKkI3RhxQgAAEjU5MmTY9WqVXH48OHEMihGAABAosaMGRPbtm2LqqqqxDLYSgcAACRq48aNERFx6NChxDIoRgAAQFHt3bs31q1bF83NzVEoFCKTyUQul4uJEydGPp+P0aNHR0TEsGHDEstoKx0AAFA0O3bsiKqqqtiyZUuMHz8+5s6dG7Nnz47x48dHY2NjjBs3Lnbu3Jl0TCtGAABA8SxevDjmz58fDQ0NPc4vWrQodu/eXeJknVkxAgAAiqalpSXy+XyP8wsWLIiWlpYSJuqeYgQAABRNZWVlNDc39zi/a9euqKysLGGi7tlKBwAAFM2SJUsin8/Hnj17YsqUKZHL5SKTyUShUIimpqa4++67Y82aNUnHVIwAAIDiWbhwYYwcOTIaGhpiw4YN0d7eHhERZWVlMWHChNi8eXPMmDEj4ZSKUZ8MHTo05s2b169rN23adEqzAADAYFFTUxM1NTVx9OjROHDgQEREVFRURHl5ecLJ/kgx6oP169cnHQEAAAat8vLyAfE8UXe8fAEAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAACiqffv2xde//vV46KGH4siRI53mXn/99Vi5cmVCyf7ojKQDAAAAg0tbW1u0tbV1Gstms5HNZrucu3v37pg6dWocP348jh49Gn/xF38RW7ZsiXHjxkVExKFDh2LFihXxD//wDyXJ3hMrRgAAQJ/U19fHiBEjOh319fXdnnvLLbfEtddeG6+88kq8/PLLMWXKlLjiiivixz/+cYlTn5wVIwAAoE/q6uqitra201h3q0UREXv27Ik777wzhgwZEm9/+9vjzjvvjDFjxsSVV14Z3/ve9+Lcc88tReQ3pRgBAAB90tO2uZ60trZ2+vubbrophgwZElOnTo2vfe1rpzpevyhGAABA0Vx88cXR3Nwcl156aafxJUuWREdHR3zyk59MKFlnnjECAACKZu7cubFz585u577whS/EypUrB8R2OsUIAAAomvnz58c//uM/9jh/0003xQsvvFDCRN1TjAAAgNRTjAAAgERNnjw5Vq1aFYcPH04sg2IEAAAkasyYMbFt27aoqqpKLIO30gEAAInauHFjREQcOnQosQyKEQAAUFR79+6NdevWRXNzcxQKhchkMpHL5WLixImRz+dj9OjRERExbNiwxDLaSgcAABTNjh07oqqqKrZs2RLjx4+PuXPnxuzZs2P8+PHR2NgY48aN6/F13qVkxQgAACiaxYsXx/z586OhoaHH+UWLFsXu3btLnKwzK0YAAEDRtLS0RD6f73F+wYIF0dLSUsJE3VOMAACAoqmsrIzm5uYe53ft2hWVlZUlTNQ9W+kAAICiWbJkSeTz+dizZ09MmTIlcrlcZDKZKBQK0dTUFHfffXesWbMm6ZiKEQAAUDwLFy6MkSNHRkNDQ2zYsCHa29sjIqKsrCwmTJgQmzdvjhkzZiScUjECAACKrKamJmpqauLo0aNx4MCBiIioqKiI8vLyhJP9keJ3CAsAACAASURBVGIEAACURHl5+YB4nqg7Xr4AAACknmIEAACknq10JfbAP70z6Qi9NuLb3X8J10D09o5jSUc4bU36l1uTjtBrL314QdIReu2114cnHeG0dd7bjyQdgQFgMP0zNth+zw6mn+2Hf/mTpCP02pZ3fijpCKlnxQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEg9xQgAAEjML3/5y/jMZz6TdAzFCAAA6Ju2trY4ePBgp6Otra1f9/rtb38b99xzzylO2HdnFPPm+Xw+Wltbi/kRg8amTZuSjgAAAKdEfX19rFixotPYsmXLYvny5V3OffDBB096r+eff/5URuu3ohaj1tZWhQAAAE4zdXV1UVtb22ksm812e+706dMjk8lER0dHj/fLZDKnNF9/2EoHAAD0STabjeHDh3c6eipGlZWV8Z3vfCeOHz/e7fGjH/2oxOm7pxgBAABFM2HChJOWnzdbTSqVom6lAwAA0u0LX/hCvP766z3OX3jhhfGDH/yghIm6pxgBAABFc/nll590/uyzz44rrriiRGl6ZisdAABQUt/61rdOuoqUBMUIAAAoqQULFsTLL7+cdIxOFCMAAKCkBsLLFv6UYgQAAKSeYgQAAJTUd7/73TjnnHOSjtGJt9IBAAAlddlllyUdoQsrRgAAQKImT54cq1atisOHDyeWQTECAAASNWbMmNi2bVtUVVUllsFWOgAAIFEbN26MiIhDhw4llkExAgAAimrv3r2xbt26aG5ujkKhEJlMJnK5XEycODHy+XyMHj06IiKGDRuWWEZb6QAAgKLZsWNHVFVVxZYtW2L8+PExd+7cmD17dowfPz4aGxtj3LhxsXPnzqRjWjECAACKZ/HixTF//vxoaGjocX7RokWxe/fuEifrzIoRAABQNC0tLZHP53ucX7BgQbS0tJQwUfcUIwAAoGgqKyujubm5x/ldu3ZFZWVlCRN1z1Y6AACgaJYsWRL5fD727NkTU6ZMiVwuF5lMJgqFQjQ1NcXdd98da9asSTpmcYpRPp+P1tbW2LdvXzFuP6h9+MK9SUfotdaD5UlH6LXDr70t6QinrZc+vCDpCL12ziMbko7Qe4Po5zrY/KxQkXQEBoBLRh1IOkKvDbbfs4PpZ7slPpR0hF675rePJR2hT4714dyFCxfGyJEjo6GhITZs2BDt7e0REVFWVhYTJkyIzZs3x4wZM4oTtA+KUoxaW1tj06ZNMW/evGLcHgAAGERqamqipqYmjh49GgcO/KFcV1RURHn5wPkf8bbSAQAAJVFeXj4gnifqjpcvAAAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAqacYAQAAifnlL38Zn/nMZ5KOoRgBAAB909bWFgcPHux0tLW19etev/3tb+Oee+45xQn77oxi3nzo0KExb968Yn7EoLFp06akIwAAwClRX18fK1as6DS2bNmyWL58eZdzH3zwwZPe6/nnnz+V0fqtqMVo/fr1xbw9AACQgLq6uqitre00ls1muz13+vTpkclkoqOjo8f7ZTKZU5qvP2ylAwAA+iSbzcbw4cM7HT0Vo8rKyvjOd74Tx48f7/b40Y9+VOL03VOMAACAopkwYcJJy8+brSaVSlG30gEAAOn2hS98IV5//fUe5y+88ML4wQ9+UMJE3VOMAACAorn88stPOn/22WfHFVdcUaI0PbOVDgAAKKlvfetbJ11FSoJiBAAAlNSCBQvi5ZdfTjpGJ4oRAABQUgPhZQt/SjECAABSTzECAABK6rvf/W6cc845ScfoxFvpAACAkrrsssuSjtCFFSMAACBRkydPjlWrVsXhw4cTy6AYAQAAiRozZkxs27YtqqqqEstgKx0AAJCojRs3RkTEoUOHEsugGAEAAEW1d+/eWLduXTQ3N0ehUIhMJhO5XC4mTpwY+Xw+Ro8eHRERw4YNSyyjrXQAAEDR7NixI6qqqmLLli0xfvz4mDt3bsyePTvGjx8fjY2NMW7cuNi5c2fSMa0YAQAAxbN48eKYP39+NDQ09Di/aNGi2L17d4mTdWbFCAAAKJqWlpbI5/M9zi9YsCBaWlpKmKh7ihEAAFA0lZWV0dzc3OP8rl27orKysoSJumcrHQAAUDRLliyJfD4fe/bsiSlTpkQul4tMJhOFQiGampri7rvvjjVr1iQdUzEqtUee/YukI/TaiOPtSUfotbd3HEs6wmnrtdeHJx2h9z68IOkEvXbOIxuSjnD6GkS/DyienxUqko7Qa5eMOpB0hD7xsy2OLfGhpCMUzcKFC2PkyJHR0NAQGzZsiPb2P/w3ZllZWUyYMCE2b94cM2bMSDilYgQAABRZTU1N1NTUxNGjR+PAgT8U1oqKiigvL0842R8pRgAAQEmUl5cPiOeJuuPlCwAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQNHs3r07Zs2aFWPHjo0zzzwzzjrrrBg7dmzMmjUrnnrqqaTjnXBG0gEAAIDBpa2tLdra2jqNZbPZyGazncYaGxtjxowZceWVV8aNN94YuVwuOjo6Yv/+/bF169aYNGlS3H///TFt2rRSxu+WYgQAAPRJfX19rFixotPYsmXLYvny5Z3Gli5dGitXroybb765yz0WLVoUt956a9xyyy0DohjZSgcAAPRJXV1dvPrqq52Ourq6Luc9++yzce211/Z4n+nTp8dzzz1XzKi9phgBAAB9ks1mY/jw4Z2OP91GFxFxwQUXRGNjY4/3eeCBB+L8888vZtRes5UOAAAoipUrV8bMmTNj+/btMXXq1MjlcpHJZKJQKERTU1Ns3bo17r333qRjRoRiBAAAFMl1110Xjz32WNx+++2xevXqKBQKERExatSoqK6uju3bt0d1dXXCKf9AMQIAAIqmurp6wJSfk/GMEQAAkHqKEQAAkJjJkyfHqlWr4vDhw4nmUIwAAIDEjBkzJrZt2xZVVVWJ5vCMEQAAkJiNGzdGRMShQ4cSzWHFCAAASNywYcMS/XzFCAAASMTLL78cK1euTDpGRChGAABAQgqFQqxYsSLpGBHhGSMAAKBIfvrTn550/plnnilRkjenGAEAAEXxn/7Tf4pMJhMdHR1d5t4Yz2QyCSTrSjECAACKYuTIkXHrrbfGlVde2e38v/zLv8TVV19d4lTdU4wAAICimDBhQvzqV7+KMWPGdDv/u9/9rtvVpCQoRgAAQFEsWLAgXn/99R7nzz333BPfY5Q0xQgAACiKa665psvYzp07433ve19ks9l4xzveEZ/+9KcTSNaV13UDAAAlc9VVV8VLL72UdIwuFCMAAKBkBsozRX8qsa10+Xw+Wltbk/r4ktu0aVPSEQAAgB4kVoxaW1uVBQAASJkNGzZELpdLOkYXXr4AAACUzKc+9amkI3TLM0YAAEDqKUYAAEDqKUYAAEDqKUYAAEDqKUYAAEDqKUYAAEDqKUYAAEDqKUYAAEDqveUveM3n89Ha2tppbN++fW/1tgAAACXzlotRa2trbNq0qdPYvHnz3uptAQAASsZWOgAAIPUUIwAAIPUUIwAAIPUUIwAAIPUUIwAAIPUUIwAAIPUUIwAAIPXe8vcYAQAA9EZ7e3scOHAgMplMjBw5MsrKypKOdIIVIwAAoE/a2tri4MGDnY62trYez9+yZUtMmjQpzjrrrPgP/+E/RGVlZZx11lkxadKkaGxsLGHynilGAABAn9TX18eIESM6HfX19d2eu2HDhpg5c2Zceumlcd9998WOHTvi8ccfj/vuuy8uvfTSmDlzZtx1110l/hV0ZSsdAADQJ3V1dVFbW9tpLJvNdnvubbfdFmvXro0bbrihy9z06dPjP//n/xxf/vKX47Of/WxRsvaWYgQAAPRJNpvtsQj9qZdeeikuu+yyHucnTpwYv/rVr05VtH6zlQ4AACiacePGxVe/+tUe5++6664YN25cCRN1z4oRAABQNF/5ylfib/7mb+Lhhx+OqVOnRi6Xi0wmE4VCIZqamuLf/u3f4qGHHko6pmIEAAAUzxVXXBEtLS2xbt26eOKJJ6JQKERExKhRo+KjH/1o5PP5OO+88/p839bW1vjpT38a+/fvj+PHj3ea+9jHPtbn+ylGAABAUZ133nlx6623nrL7PfzwwzF37tw4cOBAl7lMJhPt7e19vqdnjAAAgEHlc5/7XHziE5+Iffv2xfHjxzsd/SlFEYoRAACQsLFjx8YNN9wQL730Uq/O379/f9TW1kYulztlGRQjAAAgUZ/+9Kfj+PHj8aEPfahX53/84x+PRx999JRm8IwRAACQqOXLl/fp/DvuuCM+8YlPxOOPPx6XXHJJlJeXd5r//Oc/3+cMihEAAJCYX/7yl7Fs2bL42te+1utrvvnNb8b3vve9OPPMM+PRRx+NTCZzYi6TyfSrGNlKBwAAJOa3v/1t3HPPPX26ZunSpbFy5cp49dVX41//9V/jhRdeOHE8//zz/cphxQgAACiaBx988KTz/SkyR44ciZqamhgy5NSt8yhGAABA0UyfPj0ymUx0dHT0eM6/3wrXG5/+9Kfjvvvui1tuueWtxjtBMQIAAIqmsrIy7rzzzpg+fXq38z/5yU9iwoQJfbpne3t7/M//+T/je9/7Xlx66aVdXr6wevXqPudUjAAAgKKZMGFC/OhHP+qxGL3ZalJ3fvazn8V73/veiIhoaWnpcr/+UIwAAICi+cIXvhCvv/56j/MXXnhh/OAHP+jTPft6fm8oRgAAQNFcfvnlJ50/++yz44orrihRmp4pRgAAwIB37bXX9vrcf/qnf+rz/X2PEQAAMOCNGDHixDF8+PD4/ve/H0899dSJ+T179sT3v//9GDFiRL/ub8WoxD584d6kI/Ra68HyNz9pgDj82tuSjnDaOu/tR5KO0Gs/K1QkHaH3Prwg6QSnrXMe2ZB0hF57+OIvJh3htHXJqANJR+i1QfVnV/jZFstg+rkmZePGjSf++u///u9jxowZsX79+igrK4uIP7ypbuHChTF8+PB+3b9oxSifz0dra2uP8/v27SvWRwMAAKexr33ta7Fjx44TpSgioqysLGpra2PixIlx22239fmeRStGra2tsWnTph7n582bV6yPBgAATmPHjh2Lp59+Ot797nd3Gn/66afj+PHj/bqnrXQAAMCgcv3118dnPvOZePbZZ+ODH/xgREQ88cQT8T/+x/+I66+/vl/3VIwAAIBB5X/9r/8Vo0aNioaGhhOP6FRWVsZNN90Uf/d3f9eveypGAADAoDJkyJC46aab4qabboqDBw9GRPT7pQtvUIwAAIBB660Wojf4HiMAAOC0MXny5Fi1alUcPny4T9cpRgAAwGljzJgxsW3btqiqqurTdbbSAQAAp403vgj20KFDfbrOihEAAHDaGTZsWJ/Ot2IEAAAMeP/7f//vXp/7+c9/vs/3V4wAAIABr6GhoVfnZTIZxQgAADg9vfDCC0W9v2IEAAAMeLW1tb06L5PJxFe+8pU+318xAgAABrwf//jHnf5+z5490d7eHu9+97sjIuIXv/hFlJWVxYQJE/p1f8UIAAAY8H7wgx+c+OvVq1fH29/+9rjnnnviHe94R0REvPLKK3H99dfH5Zdf3q/7e103AAAwqHzlK1+J+vr6E6UoIuId73hH/Lf/9t/6tY0uQjECAAAGmYMHD8bLL7/cZXz//v3x2muv9eueihEAADCoXHPNNXH99dfHt7/97di7d2/s3bs3vv3tb8cNN9wQ1157bb/uqRgBAABFtXv37pg1a1aMHTs2zjzzzDjrrLNi7NixMWvWrHjqqaf6fL/169fH3/zN38Ts2bNjzJgxMWbMmJg1a1ZcddVVsXbt2n5l9PIFAACgT9ra2qKtra3TWDabjWw22+XcxsbGmDFjRlx55ZVx4403Ri6Xi46Ojti/f39s3bo1Jk2aFPfff39Mmzat159/1llnxdq1a+O2226L5557Ljo6OuLCCy+Ms88+u9+/pgFVjPL5fLS2tiYdoyg2bdqUdAQAADgl6uvrY8WKFZ3Gli1bFsuXL+9y7tKlS2PlypVx8803d5lbtGhR3HrrrXHLLbf0qRi94eyzz45LL720z9d1Z0AVo9bWVgUCAAAGuLq6ui5fuNrdalFExLPPPnvS536mT58ey5YtO6X5+sMzRgAAQJ9ks9kYPnx4p6OnYnTBBRdEY2Njj/d64IEH4vzzzy9W1F4bUCtGAADA6WXlypUxc+bM2L59e0ydOjVyuVxkMpkoFArR1NQUW7dujXvvvTfpmIoRAABQPNddd1089thjcfvtt8fq1aujUChERMSoUaOiuro6tm/fHtXV1QmnVIwAAIAiq66uHhDl52Q8YwQAAKSeYgQAACRq8uTJsWrVqjh8+HBiGRQjAAAgUWPGjIlt27ZFVVVVYhk8YwQAACRq48aNERFx6NChxDIoRgAAQFHt3bs31q1bF83NzVEoFCKTyUQul4uJEydGPp+P0aNHR0TEsGHDEstoKx0AAFA0O3bsiKqqqtiyZUuMHz8+5s6dG7Nnz47x48dHY2NjjBs3Lnbu3Jl0TCtGAABA8SxevDjmz58fDQ0NPc4vWrQodu/eXeJknVkxAgAAiqalpSXy+XyP8wsWLIiWlpYSJuqeYgQAABRNZWVlNDc39zi/a9euqKysLGGi7tlKBwAAFM2SJUsin8/Hnj17YsqUKZHL5SKTyUShUIimpqa4++67Y82aNUnHVIwAAIDiWbhwYYwcOTIaGhpiw4YN0d7eHhERZWVlMWHChNi8eXPMmDEj4ZSKEQAAUGQ1NTVRU1MTR48ejQMHDkREREVFRZSXlyec7I8UIwAAoCTKy8sHxPNE3fHyBQAAIPUUIwAAIPVspQPgtPLwxV9MOkKvfaTly0lH6JPB9LMF6KvEitHQoUNj3rx5ncb27duXTBgAACDVEitG69ev7zL2p0UJAACgFDxjBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAApJ5iBAAAFNXu3btj1qxZMXbs2DjzzDPjrLPOirFjx8asWbPiqaeeSjpeRESckXQAAABgcGlra4u2trZOY9lsNrLZbJdzGxsbY8aMGXHllVfGjTfeGLlcLjo6OmL//v2xdevWmDRpUtx///0xbdq0UsXvVlGK0dChQ+OFF17o13Xz5s079YEGgE2bNiUdAQAATon6+vpYsWJFp7Fly5bF8uXLu5y7dOnSWLlyZdx8881d5hYtWhS33npr3HLLLadnMVq/fn2/Cs769etPfRgAAOCUqquri9ra2k5j3a0WRUQ8++yzce211/Z4r+nTp8eyZctOab7+8IwRAADQJ9lsNoYPH97p6KkYXXDBBdHY2NjjvR544IE4//zzixW11zxjBAAAFM3KlStj5syZsX379pg6dWrkcrnIZDJRKBSiqakptm7dGvfee2/SMRUjAACgeK677rp47LHH4vbbb4/Vq1dHoVCIiIhRo0ZFdXV1bN++PaqrqxNOqRgBAABFVl1dPSDKz8l4xggAAEg9xQgAAEjU5MmTY9WqVXH48OHEMihGAABAosaMGRPbtm2LqqqqxDJ4xggAAEjUxo0bIyLi0KFDiWVQjAAAgKLau3dvrFu3Lpqbm6NQKEQmk4lcLhcTJ06MfD4fo0ePjoiIYcOGJZbRVjoAAKBoduzYEVVVVbFly5YYP358zJ07N2bPnh3jx4+PxsbGGDduXOzcuTPpmFaMAACA4lm8eHHMnz8/GhoaepxftGhR7N69u8TJOrNiBAAAFE1LS0vk8/ke5xcsWBAtLS0lTNQ9xQgAACiaysrKaG5u7nF+165dUVlZWcJE3bOVDgAAKJolS5ZEPp+PPXv2xJQpUyKXy0Umk4lCoRBNTU1x9913x5o1a5KOqRgBAADFs3Dhwhg5cmQ0NDTEhg0bor29PSIiysrKYsKECbF58+aYMWNGwikVIwAAoMhqamqipqYmjh49GgcOHIiIiIqKiigvL0842R8pRgAAQEmUl5cPiOeJuuPlCwAAQOopRgAAQOrZSgcACXn44i8mHaFPPtLy5aQj9NpLH16QdITT1oU//3nSEXptyzs/lHQEBhErRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRgAAQOopRsD/197dB1lV3/cD/1xh2bWCFKFdV6MrFkfZ1GB76UNsUIb4UDtjBidTaB2VrabDJo3NSiQTaqcsMCPQxECdtkIbC2QmYzoN4jjTSSc4PBgBm5SHGh/GtkgSJaAlVGXht4vA+f3x+2Gz7N1ld7nnnj2c12vmzsj3e+45b87ee3bengcAAApPMQIAADLx5ptvxv333591jIhQjAAAgEHq7u6O999/v8eru7t70Os5fPhwrFu3LoWEgzcyzZW3tbVFV1dXmpvIjbVr12YdAQAAqmLp0qWxaNGiHmMLFy6Mjo6OHmPPPvtsv+t54403qh1tyFItRl1dXQoBAACcZxYsWBDz5s3rMVZfX99ruZkzZ0apVIokSfpcV6lUqnq+oXApHQAAMCj19fVx8cUX93hVKkZNTU2xfv36OHXqVMXXrl27MkhfmWIEAACkolwu91t+znY2qZZSvZQOAAAorvnz58fRo0f7nJ80aVJs3ry5hon6NuRi1NDQEK2trXHgwIFq5gEAAM4T06ZN63f+oosuiptvvrlGafo35EvpVq1aFWvXro2mpqZq5gEAAM5jTz31VL9nkbLiHiMAAKBm5s6dG2+//XbWMXpRjAAAgJoZLg9bOJNiBAAAFJ5iBAAA1Mx3vvOduPzyy7OO0YvHdQMAADXziU98IusIFTljBAAAZGbGjBmxZMmSOHbsWKY5FCMAACAzzc3NsWnTppg8eXKmOVxKBwAAZGbNmjUREdHZ2ZlpDmeMAACAzI0ePTrT7StGAABAJt5+++1YvHhx1jEiQjECAAAycvDgwVi0aFHWMSLCPUYAAEBKXnrppX7nX3/99RolOTvFCAAASMUNN9wQpVIpkiTpNXd6vFQqZZCsN8UIAABIxfjx42P58uXxyU9+suL8K6+8EnfeeWeNU1WmGNXYc//1kawjDNjYUyezjjBgY5ITWUc4bx05enHWEQbs+ksPZR1hwH54cELWEc5befoc5M3+W+ZmHWHALn9uddYRBmzSZdOyjjAoGy65KesIA5an40Hefi9cNcDlyuVy/PSnP43m5uaK8++++27Fs0lZSK0YNTQ0xL59+9JaPQAAMMzNnTs3jh492uf8lVde+eG/Y5S11J5Kt2rVqmhqakpr9QAAwDB31113xT333NNjbNu2bdHd3R0REePGjYs5c+ZkEa0Xj+sGAABq5o477oj9+/dnHaMXxQgAAKiZ4XJP0ZkUIwAAoPAUIwAAoGZWr14djY2NWcfoxeO6AQCAmrn77ruzjlCRM0YAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAEDhKUYAAMCgdHd3x/vvv9/j1d3dPaR17d27N2bMmFHlhIM3Ms2VNzQ0RGtra5qbyI21a9dmHQEAAKpi6dKlsWjRoh5jCxcujI6OjkGvq7OzM7Zu3VqlZEOXajFatWpVmqsHAAAysGDBgpg3b16Psfr6+orLPv744/2ua//+/VXLdS5SLUYAAMD5p76+vs8idKb29vZoamqKUaNGVZw/fvx4NaMNmWIEAACkprm5OZYvXx6zZs2qOL9nz54ol8s1TtWbhy8AAACpKZfLsXPnzj7nS6VSJElSw0SVOWMEAACkZvHixXHs2LE+51taWmLfvn01TFSZYgQAAKSmpaWl3/m6urpobm6uUZq+uZQOAACoqWXLlsW7776bdYweFCMAAKCmHn300Th8+HDWMXpQjAAAgJoaDg9bOJNiBAAAFJ6HLwAAADX16quvxmWXXZZ1jB4UIwAAoKauuOKKrCP04lI6AAAgUxMnTowHHngg9u/fn1kGxQgAAMjUnDlz4tSpU3HTTTdllsGldAAAQKY6OjqyjuCMEQAAkJ0333wz7r///qxjKEYAAEB2Dh8+HOvWrcs6hkvpAACA9Dz77LP9zr/xxhs1StI/xQgAAEjNzJkzo1QqRZIkfS5TKpVqmKgyl9IBAACpaWpqivXr18epU6cqvnbt2pV1xIhwxqjmbpn0VtYRBqzr/bqsIwzYsSOjso5w3rpqzPGsIwzYDw9OyDrCgF1/6aGsI5y38vQ5ID2TLpuWdYQB+z8//V7WEQZl/y1zs44wYHk6HpzPvxfK5XLs2rUrZs6cWXH+bGeTakUxAgAAUjN//vw4evRon/OTJk2KzZs31zBRZYoRAACQmmnT+j+De9FFF8XNN99cozR9c48RAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQ0SnRvQAAGNRJREFUeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAABQeIoRAACQib1798aMGTOyjhERESOzDgAAAORLd3d3dHd39xirr6+P+vr6Qa2ns7Mztm7dWs1oQ5ZqMWpra4uurq40N5Eba9euzToCAABUxdKlS2PRokU9xhYuXBgdHR09xh5//PF+17N///5qRxuyVItRV1eXQgAAAOeZBQsWxLx583qMVTpb1N7eHk1NTTFq1KiK6zl+/Hgq+YbCpXQAAMCgDPSyuebm5li+fHnMmjWr4vyePXuiXC5XO96QePgCAACQinK5HDt37uxzvlQqRZIkNUzUN2eMAACAVCxevDiOHTvW53xLS0vs27evhon6phgBAACpaGlp6Xe+rq4umpuba5Smfy6lAwAACk8xAgAAMjNjxoxYsmRJv5fc1YJiBAAAZKa5uTk2bdoUkydPzjSHe4wAAIDMrFmzJiIiOjs7M83hjBEAAJC50aNHZ7p9xQgAAMjE22+/HYsXL846RkQoRgAAQEYOHjwYixYtyjpGRLjHCAAASMlLL73U7/zrr79eoyRnpxgBAACpuOGGG6JUKkWSJL3mTo+XSqUMkvWmGAEAAKkYP358LF++PD75yU9WnH/llVfizjvvrHGqyhQjAAAgFeVyOX76059Gc3Nzxfl333234tmkLChGAABAKubOnRtHjx7tc/7KK6/88N8xyppiBAAApOKuu+7qNbZt27aYOnVq1NfXx7hx42LOnDkZJOvN47oBAICaueOOO2L//v1Zx+hFMQIAAGpmuNxTdCaX0tXYc//1kawjDNjYUyezjjBgY5ITWUc4bx05enHWEQbs+ksPZR1hwH54cELWEc5befoc5M2kV1/NOsKAbbjkpqwjDNj+W+ZmHWFQLn9uddYRBi5H+zZvvxeuyjpACqpWjNra2qKrq6vH2IEDB6q1egAA4DywevXqaGxszDpGL1UrRl1dXbF27doeY62trdVaPQAAcB64++67s45QkXuMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAwlOMAACAQenu7o7333+/x6u7u3tI63rttdfi6quvrnLCwRuZ5sobGhqitbU1zU3kxtq1a7OOAAAAVbF06dJYtGhRj7GFCxdGR0fHoNd1/Pjx+PGPf1ylZEOXajFatWpVmqsHAAAysGDBgpg3b16Psfr6+orLnrncmf77v/+7arnORarFCAAAOP/U19f3WYTO9Fd/9Vdxww03xMUXX1xxvrOzs5rRhkwxAgAAUnPNNdfEQw89FPfcc0/F+T179kS5XK5xqt48fAEAAEhNuVyOnTt39jlfKpUiSZIaJqrMGSMAACA1jz32WL9PrJsyZUqcOnWqhokqU4wAAIDUXHrppVlHGBCX0gEAAIWnGAEAAJmaOHFiPPDAA7F///7MMihGAABApubMmROnTp2Km266KbMM7jECAAAy1dHRkXUEZ4wAAIDsvPnmm3H//fdnHUMxAgAAsnP48OFYt25d1jFcSgcAAKTn2Wef7Xf+jTfeqFGS/ilGAABAambOnBmlUimSJOlzmVKpVMNElbmUDgAASE1TU1OsX78+Tp06VfG1a9eurCNGhGIEAACkqFwu91t+znY2qVZcSgcAAKRm/vz5cfTo0T7nJ02aFJs3b65hosoUIwAAIDXTpk3rd/6iiy6Km2++uUZp+uZSOgAAoPAUIwAAoPBcSldjt0x6K+sIA9b1fl3WEQbs2JFRWUc4b93y5p6sIwzYhrgp6wgDdv2lh7KOcN764cEJWUc4b224xHcsDbn7zN4yN+sEA3b5c6uzjjBwOdqv56tzPmPU0NAQra2tceDAgWrkAQAAqLlzPmO0atWqiIhobW0911UBAABkwj1GAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABA4SlGAABAZvbu3RszZszIOkaMzDoAAACQL93d3dHd3d1jrL6+Purr6we9rs7Ozti6dWu1og1ZqsWora0turq60txEbqxduzbrCAAAUBVLly6NRYsW9RhbuHBhdHR09Fr28ccf73dd+/fvr2a0IUu1GHV1dSkEAABwnlmwYEHMmzevx1hfZ4va29ujqakpRo0aVXH++PHjVc83FC6lAwAABmUwl801NzfH8uXLY9asWRXn9+zZE+VyuZrxhsTDFwAAgNSUy+XYuXNnn/OlUimSJKlhosqcMQIAAFKzePHiOHbsWJ/zLS0tsW/fvhomqkwxAgAAUtPS0tLvfF1dXTQ3N9coTd9cSgcAABSeYgQAAGRqxowZsWTJkn4vuUubYgQAAGSqubk5Nm3aFJMnT84sg3uMAACATK1ZsyYiIjo7OzPLoBgBAACpeuutt+KJJ56I7du3x8GDB6NUKkVjY2PceOON0dbWFldccUVERIwePTqzjC6lAwAAUvPCCy/E5MmTY8OGDTFlypS477774p577okpU6bEM888Ex/96Edj27ZtWcd0xggAAEjPQw89FJ/5zGdixYoVfc63t7fHD37wgxon68kZIwAAIDUvv/xytLW19Tk/d+7cePnll2uYqDLFCAAASE1TU1Ns3769z/kdO3ZEU1NTDRNV5lI6AAAgNQ8//HC0tbXFzp0749Zbb43GxsYolUpx8ODB2LhxY3z961+PlStXZh1TMQIAANLzuc99LsaPHx8rVqyI1atXx8mTJyMiYsSIEVEul+Mb3/hGzJo1K+OUihEAAJCy2bNnx+zZs+ODDz6IQ4cORUTEhAkToq6uLuNk/0sxAgAAaqKurm5Y3E9UiYcvAAAAhacYAQAAhedSuhp77r8+knWEARt76mTWEQZsTHIi6wjnrQ2X3JR1hAG76/DzWUcYsA2Rn/2aN9dfeijrCAwDPzw4IesIA5a3z2ye9m3cMjfrBAN2+XOrs45QeFUrRg0NDdHa2tpj7MCBA9VaPQAAQGqqVoxWrVrVa+zMogQAADAcuccIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAAAoPMUIAADIzN69e2PGjBlZx4iRWQcAAADypbu7O7q7u3uM1dfXR319/aDX1dnZGVu3bq1WtCFLtRg1NDREa2trmpvIjbVr12YdAQAAqmLp0qWxaNGiHmMLFy6Mjo6OXss+/vjj/a5r//791Yw2ZKkWo1WrVqW5egAAIAMLFiyIefPm9Rjr62xRe3t7NDU1xahRoyrOHz9+vOr5hsKldAAAwKAM5rK55ubmWL58ecyaNavi/J49e6JcLlcz3pB4+AIAAJCacrkcO3fu7HO+VCpFkiQ1TFSZM0YAAEBqFi9eHMeOHetzvqWlJfbt21fDRJUpRgAAQGpaWlr6na+rq4vm5uYapembS+kAAIDCU4wAAIBMzZgxI5YsWdLvJXdpU4wAAIBMNTc3x6ZNm2Ly5MmZZXCPEQAAkKk1a9ZERERnZ2dmGRQjAAAgVW+99VY88cQTsX379jh48GCUSqVobGyMG2+8Mdra2uKKK66IiIjRo0dnltGldAAAQGpeeOGFmDx5cmzYsCGmTJkS9913X9xzzz0xZcqUeOaZZ+KjH/1obNu2LeuYzhgBAADpeeihh+Izn/lMrFixos/59vb2+MEPflDjZD05YwQAAKTm5Zdfjra2tj7n586dGy+//HINE1WmGAEAAKlpamqK7du39zm/Y8eOaGpqqmGiylxKBwAApObhhx+Otra22LlzZ9x6663R2NgYpVIpDh48GBs3boyvf/3rsXLlyqxjKkYAAEB6Pve5z8X48eNjxYoVsXr16jh58mRERIwYMSLK5XJ84xvfiFmzZmWcUjECAABSNnv27Jg9e3Z88MEHcejQoYiImDBhQtTV1WWc7H8pRgAAQE3U1dUNi/uJKvHwBQAAoPAUIwAAoPAUIwAAgITc6+rqShYuXJh0dXVlHeWsZE1PnvLKmp485ZU1PXnKK2s68pQ1SfKVV9bzVylJkiTrcsa5ef/992Ps2LHx3nvvxcUXX5x1nH7Jmp485ZU1PXnKK2t68pRX1nTkKWtEvvLKev5yKR0AAFB4ihEAAFB4ihEAAFB4Izo6OjqyDsG5GzFiREyfPj1Gjhz+/2avrOnJU15Z05OnvLKmJ095ZU1HnrJG5CuvrOcnD18AAAAKz6V0AABA4SlGAABA4SlGAABA4SlGAABA4SlGOfG3f/u3MXHixGhoaIhyuRzf+973+l1+/fr10dLSEvX19dHS0hIbNmyoUdJ8ZB1sxjMtXbo0fuM3fiPGjBkTv/zLvxwzZ86M119/PaW0/2swuf/+7/8+pk2bFuPGjYtx48bFLbfcEt///veHTb5Knn/++bjzzjvjsssui1KpFM8880xKSf+fvOU97emnn47bb789JkyYEKVSKfbs2TOg99XyuzaUfbN169Yol8vR0NAQV199daxatSq1fJXk4dh1Wl6yDvWzeqY0v2vVWPcrr7wSn/70p+Oqq66KUqkUK1eurFq+sxnKPq513sHu4wMHDsTdd98d1157bVxwwQXR3t6ear5KBvMdy/LnH5GvrMOdYpQD//iP/xjt7e3xyCOPxO7du2PatGlxxx13xE9+8pOKy+/YsSNmz54d9957b/z7v/973HvvvTFr1qz413/9V1mHkLGSrVu3xp/8yZ/Eiy++GBs3bowTJ07EbbfdFkePHh02ubds2RJ/+Id/GJs3b44dO3bElVdeGbfddlvs379/WOSr5OjRozFlypT467/+61Qy/ry85T1zu7/zO78Ty5YtG/B7av1dG+y+2bdvX/ze7/1eTJs2LXbv3h1/9md/Fn/6p38a69evTyXfmfJw7Mpj1qF8VvtaT1rftWqs+9ixY3H11VfHsmXL4tJLL61iurMbyj6udd7B7uPu7u74pV/6pXjkkUdiypQpKafrbbDfsSx//nnKmgsJw95v/uZvJm1tbT3GrrvuuuTLX/5yxeVnzZqV/O7v/m6Psdtvvz35gz/4g9QynpaHrIPNOBDvvPNOEhHJ1q1bzzVen84194kTJ5IxY8Yk69atSyNe1fdrRCQbNmyoRrSK8pa3kn379iURkezevfusy2Z5XBjIvvnSl76UXHfddT3G5s6dm/z2b/92mtE+lIdj12l5ynraYD6rZ5Pmd60a625ubk5WrFhRpUQDN9R9XOu8g93HN998c/KFL3whxUS9ncvvh1rvzzxlzQNnjIa548ePx86dO+O2227rMX7bbbfF9u3bK75nx44dvZa//fbb+1y+WvKQdSgZB+K9996LiIhLLrnknPL1pRq5jx07Fh988EEqGdPar2nJW95qyOq4MFB95fu3f/u3+OCDD1Lddh6OXaflKSvkUZ5+P+Qpa14oRsPcoUOH4uTJk9HY2NhjvLGxMQ4ePFjxPQcPHhzU8tWSh6xDyXg2SZLEvHnz4hOf+ET86q/+ajVi9lKN3F/+8pfj8ssvj1tuuWVY5qulvOWthqyOCwPVV74TJ07EoUOHUt12Ho5dp+UpK+RRnn4/5ClrXihGOVEqlXr8OUmSXmPnsnw15SHrQLf5ve99L0aPHv3h65vf/GavZT7/+c/HSy+9FE899VRqeU8b6r76y7/8y3jqqafi6aefjoaGhrTiVXW/1kIe8n7zm9/sse3BPiDi52V5XBiISvkqjddy+8Pt2DXUbdciazU+q8Pl2NCXn/zkJz3yPfroozXdfjWPB/RvuB8vf16esg53I7MOQP8mTJgQI0aM6NX833nnnV7/h+C0Sy+9dFDLV0sesg4249SpU3s84efMZR588MF49tln4/nnn4+PfOQjqWSOGNq+Pe2rX/1qPProo/Hcc8/Fxz72sWGR72z7NW15yvupT30qfuu3fuvDP19++eVDWk9Wx4WB6ivfyJEjY/z48aluOw/HrtOGc9ZqfFazPjaczWWXXdYjX1qXT/elWscD+nYuv29rLU9Z88IZo2Fu1KhRUS6XY+PGjT3GN27cGDfeeGPF93z84x/vtfx3v/vdPpevljxkHWzGCy+8MCZNmvTha8yYMRHx//5vzOc///l4+umnY9OmTTFx4sRU8g4192lf+cpXYsmSJfEv//IvMXXq1GGTr6/9Wit5yjtmzJge277wwguHtJ6sjgsD1Ve+qVOnRl1dXarbzsOx67ThnLUan9Wsjw1nM3LkyB75al2MqnU8oG9D/X2bhTxlzY1aP+2BwfvWt76V1NXVJU8++WTy6quvJu3t7clFF12U/OhHP6q4/LZt25IRI0Yky5YtS1577bVk2bJlyciRI5MXX3xR1iFkrOSzn/1sMnbs2GTLli3JgQMHPnwdO3Zs2ORevnx5MmrUqOTb3/52j4xHjhwZFvkqOXLkSLJ79+5k9+7dSUQkX/va15Ldu3cnP/7xjwuf9+f97Gc/S3bv3p388z//cxIRybe+9a1k9+7dyYEDB/p8T62/a4PdN2+88UbyC7/wC8lDDz2UvPrqq8mTTz6Z1NXVJd/+9rdTyXemPBy78ph1KJ/VStL8rlVj3d3d3R+uo6mpKXn44YeT3bt3J//5n/95zvnOZij7uNZ5h7KPTy9fLpeTu+++O9m9e3fyyiuvpJLvTIP9jmX5889T1jxQjHLib/7mb5Lm5uZk1KhRya//+q/3eCz0nDlzkptvvrnH8v/0T/+UXHvttUldXV1y3XXXJevXr5f1HDKeKSIqvtasWTNscjc3N1fMuHDhwmGRr5LNmzdXzDxnzhx5f86aNWvO+rPN+rt2tn2zcOHCpLm5ucd7tmzZkvzar/1aMmrUqOSqq65KnnjiidTyVZKHY1fesg71s3qmNL9rQ/msnun0o7LPfJ3t71UNQ9nHtc47lH1cafmz/RyqaTDfsSx//nnLOtyVkuT/391Kbk2fPj2mT58eHR0dWUc5qzxkzUPGSoZ77uGe70x5y3um4Z6/tbU1IiLWrl2baY6BGu778+flKWvE8M+bt89qJfZxdQ33/fnz8pR1OFCMcu7IkSPR0tISr732WowePTrrOP3KQ9Y8ZKxkuOce7vnOlLe8Z8pD/okTJ8bzzz8fV1xxRdZRzioP+/O0PGWNyEfePH1WK7GPqysP+/O0PGUdLhQjAACg8DyVDgAAKDzFCAAAKDzFCAAAKDzFCAAAKDzFCAAAKDzFCIBhbfr06dHe3h4REVdddVWsXLlyUO9vbW2NmTNnphENgPOIYgQAABSeYgQAABSeYgTAsHH06NG47777YvTo0dHU1BSPPfbYoN5/8uTJmDdvXvziL/5ijB8/Pr70pS/Fmf+O+fTp0+PBBx+M9vb2GDduXDQ2Nsbf/d3fxdGjR+OP/uiPYsyYMfErv/Ir8Z3vfKeafzUAhjnFCIBhY/78+bF58+bYsGFDfPe7340tW7bEzp07B/z+xx57LP7hH/4hnnzyyXjhhRfi8OHDsWHDhl7LrVu3LiZMmBDf//7348EHH4zPfvaz8fu///tx4403xq5du+L222+Pe++9N44dO1bNvx4Aw5hiBMCw0NnZGU8++WR89atfjVtvvTWuv/76WLduXZw8eXLA61i5cmUsWLAgPv3pT8fkyZNj1apVMXbs2F7LTZkyJf78z/88rrnmmliwYEFceOGFMWHChPjjP/7juOaaa+Iv/uIv4mc/+1m89NJL1fwrAjCMKUYADAt79+6N48ePx8c//vEPxy655JK49tprB/T+9957Lw4cONDj/SNHjoypU6f2WvZjH/vYh/89YsSIGD9+fFx//fUfjjU2NkZExDvvvDPovwcA+aQYATAsnHkvUJrq6up6/LlUKvUYK5VKERFx6tSpmmUCIFuKEQDDwqRJk6Kuri5efPHFD8f+53/+J/7jP/5jQO8fO3ZsNDU19Xj/iRMnBnWPEgDFNTLrAAAQETF69Oh44IEHYv78+TF+/PhobGyMRx55JC64YOD/D+8LX/hCLFu2LK655pqYPHlyfO1rX4t33303xdQAnC8UIwCGja985SvR2dkZn/rUp2LMmDHxxS9+Md57770+l29tbY0f/ehHsWXLloiI+OIXvxgHDhyI1tbWuOCCC+L++++Pu+66q991AEBERCmp5UXdAFBF06dPj+nTp0dHR0fWUQDIOcUIgFw6cuRItLS0xGuvvRajR4/OOg4AOacYAQAAheepdAAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOEpRgAAQOH9X3VDH36thOhUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "snsMatMod.clustermap(daPlotpd.fillna(0).T.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e321101358>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Test correlation fns.\n",
    "# This fails with NaNs present it seems\n",
    "# ep.snsMatMod.clustermap(daPlot.dropna(dim='plotDim', how='all').dropna(dim='LM',how='all').fillna(0).to_pandas().T.corr())\n",
    "# ep.snsMatMod.clustermap(daPlot.dropna(dim='plotDim', how='all').dropna(dim='LM',how='all').fillna(0).to_pandas().corr())\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0).T.corr())\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0).corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\femtolab\\.conda\\envs\\ePSdev\\lib\\site-packages\\xarray\\core\\nputils.py:215: RuntimeWarning:\n",
      "\n",
      "All-NaN slice encountered\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=r, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Switch plotting dims\n",
    "plotDimsRed = ['L','M']\n",
    "xDim = {'llpmmp':['l', 'm', 'lp', 'mp']}\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(BLMtable, plotDims=plotDimsRed, xDim=xDim, mMax = 2, pType = 'r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## $\\Lambda$ Term\n",
    "\n",
    "Define MF projection term, $\\Lambda_{R',R}(R_{\\hat{n}})$:\n",
    "\n",
    "\\begin{equation}\n",
    "\\Lambda_{R',R}(R_{\\hat{n}})=(-1)^{(R')}\\left(\\begin{array}{ccc}\n",
    "1 & 1 & P\\\\\n",
    "\\mu & -\\mu' & R'\n",
    "\\end{array}\\right)D_{-R',-R}^{P}(R_{\\hat{n}})\n",
    "\\end{equation}\n",
    "\n",
    "This is similar to the $E_{PR}$ term, and essentially rotates it into the MF by a set of rotations (Euler angles) defined by $R_{\\hat{n}}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate MF projection terms, all QNs, for Euler angles corresponding to (z,x,y) cases\n",
    "lambdaTerm, lambdaTable, lambdaD, QNs = geomCalc.MFproj(form = '2d')\n",
    "\n",
    "# Output values as list, ['l', 'lp', 'P', 'mu', 'mup', 'Rp', 'R']\n",
    "# print(lambdaTerm.shape)  \n",
    "# print(np.c_[QNs[0:10,:], lambdaTerm[0:10,:]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Xarray form\n",
    "lambdaTerm, lambdaTable, lambdaD, QNs = geomCalc.MFproj(form = 'xarray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check values Xarray vs. 2d case for consistency\n",
    "# TO DO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('Rp', 'l', 'lp', 'P', 'mu', 'mup', 'R', 'Labels')"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# In this case the QNs are left unstacked to facilitate multiplication across different terms - this fails for stacked (multindex) cases here.\n",
    "lambdaTerm.dims"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting data (No filename), pType=a, thres=0.01, with Seaborn\n",
      "Plotting data (No filename), pType=phase, thres=0.01, with Seaborn\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1200 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot all QNs vs. Euler angles (by label)\n",
    "xDim = 'Labels'\n",
    "daPlot, daPlotpd, legendList, gFig = ep.lmPlot(lambdaTerm, xDim=xDim, pType = 'a')   # Plot abs values\n",
    "daPlotPhase, daPlotpdPhase, legendList, gFig = ep.lmPlot(lambdaTerm, xDim=xDim, pType = 'phase')   # Plot phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Labels</th>\n",
       "      <th>z</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P</th>\n",
       "      <th>R</th>\n",
       "      <th>Rp</th>\n",
       "      <th>l</th>\n",
       "      <th>lp</th>\n",
       "      <th>mu</th>\n",
       "      <th>mup</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "      <td>0.577350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"18\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"6\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.288675</td>\n",
       "      <td>0.288675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.408248</td>\n",
       "      <td>0.204124</td>\n",
       "      <td>0.204124</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"35\" valign=\"top\">2</th>\n",
       "      <th rowspan=\"9\" valign=\"top\">-2</th>\n",
       "      <th>-2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>0.447214</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">-1</th>\n",
       "      <th>-2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">0</th>\n",
       "      <th>-2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.273861</td>\n",
       "      <td>0.273861</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
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       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>0.182574</td>\n",
       "      <td>0.091287</td>\n",
       "      <td>0.091287</td>\n",
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       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>0.365148</td>\n",
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       "      <td>0.182574</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.182574</td>\n",
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       "      <td>0.091287</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
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       "      <th>1</th>\n",
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       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.273861</td>\n",
       "      <td>0.273861</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">1</th>\n",
       "      <th>-2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
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       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.316228</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">2</th>\n",
       "      <th>-2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">-1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">0</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"3\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.223607</td>\n",
       "      <td>0.223607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th rowspan=\"2\" valign=\"top\">1</th>\n",
       "      <th>-1</th>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>-1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.158114</td>\n",
       "      <td>0.158114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>1</th>\n",
       "      <th>1</th>\n",
       "      <th>-1</th>\n",
       "      <th>-1</th>\n",
       "      <td>0.447214</td>\n",
       "      <td>0.111803</td>\n",
       "      <td>0.111803</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Labels                      z         x         y\n",
       "P R  Rp l lp mu mup                              \n",
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       "              0  0   0.577350  0.577350  0.577350\n",
       "              1 -1   0.577350  0.577350  0.577350\n",
       "1 -1 -1 1 1   0  1   0.408248  0.204124  0.204124\n",
       "              1  0   0.408248  0.204124  0.204124\n",
       "      0 1 1  -1  1        NaN  0.288675  0.288675\n",
       "              1 -1        NaN  0.288675  0.288675\n",
       "      1 1 1  -1  0        NaN  0.204124  0.204124\n",
       "              0 -1        NaN  0.204124  0.204124\n",
       "   0 -1 1 1   0  1        NaN  0.288675  0.288675\n",
       "              1  0        NaN  0.288675  0.288675\n",
       "      0 1 1  -1  1   0.408248       NaN       NaN\n",
       "              1 -1   0.408248       NaN       NaN\n",
       "      1 1 1  -1  0        NaN  0.288675  0.288675\n",
       "              0 -1        NaN  0.288675  0.288675\n",
       "   1 -1 1 1   0  1        NaN  0.204124  0.204124\n",
       "              1  0        NaN  0.204124  0.204124\n",
       "      0 1 1  -1  1        NaN  0.288675  0.288675\n",
       "              1 -1        NaN  0.288675  0.288675\n",
       "      1 1 1  -1  0   0.408248  0.204124  0.204124\n",
       "              0 -1   0.408248  0.204124  0.204124\n",
       "2 -2 -2 1 1   1  1   0.447214  0.111803  0.111803\n",
       "     -1 1 1   0  1        NaN  0.158114  0.158114\n",
       "              1  0        NaN  0.158114  0.158114\n",
       "      0 1 1  -1  1        NaN  0.111803  0.111803\n",
       "              0  0        NaN  0.223607  0.223607\n",
       "              1 -1        NaN  0.111803  0.111803\n",
       "      1 1 1  -1  0        NaN  0.158114  0.158114\n",
       "              0 -1        NaN  0.158114  0.158114\n",
       "      2 1 1  -1 -1        NaN  0.111803  0.111803\n",
       "  -1 -2 1 1   1  1        NaN  0.223607  0.223607\n",
       "     -1 1 1   0  1   0.316228  0.158114  0.158114\n",
       "              1  0   0.316228  0.158114  0.158114\n",
       "      1 1 1  -1  0        NaN  0.158114  0.158114\n",
       "              0 -1        NaN  0.158114  0.158114\n",
       "      2 1 1  -1 -1        NaN  0.223607  0.223607\n",
       "   0 -2 1 1   1  1        NaN  0.273861  0.273861\n",
       "      0 1 1  -1  1   0.182574  0.091287  0.091287\n",
       "              0  0   0.365148  0.182574  0.182574\n",
       "              1 -1   0.182574  0.091287  0.091287\n",
       "      2 1 1  -1 -1        NaN  0.273861  0.273861\n",
       "   1 -2 1 1   1  1        NaN  0.223607  0.223607\n",
       "     -1 1 1   0  1        NaN  0.158114  0.158114\n",
       "              1  0        NaN  0.158114  0.158114\n",
       "      1 1 1  -1  0   0.316228  0.158114  0.158114\n",
       "              0 -1   0.316228  0.158114  0.158114\n",
       "      2 1 1  -1 -1        NaN  0.223607  0.223607\n",
       "   2 -2 1 1   1  1        NaN  0.111803  0.111803\n",
       "     -1 1 1   0  1        NaN  0.158114  0.158114\n",
       "              1  0        NaN  0.158114  0.158114\n",
       "      0 1 1  -1  1        NaN  0.111803  0.111803\n",
       "              0  0        NaN  0.223607  0.223607\n",
       "              1 -1        NaN  0.111803  0.111803\n",
       "      1 1 1  -1  0        NaN  0.158114  0.158114\n",
       "              0 -1        NaN  0.158114  0.158114\n",
       "      2 1 1  -1 -1   0.447214  0.111803  0.111803"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "daPlotpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<epsproc._sns_matrixMod.ClusterGrid at 0x1e320acd0b8>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cGaNGjYqIiNbW1ujXr+jnRkT//v3jkUceieXLl8ezzz4bdXV1ccopp8SKFSti8ODBvfVrAAAAfUTxYbSbbqV7xezZs2P27Nk9/tm99977qq9dtmxZl58HDhwYd9999xs0GQAAsLcp4TNGHb05BwAAQMUUHUY7hBEAALCXKuFWOmEEAADsnfbIhy8AAADsTsWHUeeO3pwDAACgYop+5vX2QkfZRzmWLFkSo0ePjtra2mhoaIjVq1fv8trvfOc7MW7cuNhvv/1i3333jeOPPz5uvPHGLtcUCoVYsGBBHHLIITFw4MCYOHFi/OIXvyhrNgAAYO9SdBjtKHSUfZRqxYoVMXfu3Jg/f36sXbs2JkyYEJMnT47W1tYer99///1j/vz58ZOf/CT++7//O84+++w4++yzuzyi+7LLLotFixbFv/3bv8WDDz4YBx98cEyaNCmef/75kucDAAD2LsXvGHV2lH2UatGiRXHuuefGeeedF2PGjInFixfHyJEjY+nSpT1eP3HixDj99NNjzJgxccQRR8QFF1wQY8eOjfvuuy8i/rRbtHjx4pg/f35MnTo16uvr44YbboiXXnop/uM//qPk+QAAgL1LCWG0veyjra0tnnvuuS5HW1tbj+/T3t4eDz30UDQ2NnY539jYGA888MBrzlkoFOKHP/xhPPHEE/Ge97wnIiJ+85vfxKZNm7qsWVNTE+9973uLWhMAANi77ZbPGDU3N8fQoUO7HM3NzT2+z5YtW6KjoyOGDx/e5fzw4cNj06ZNu5zvj3/8YwwaNCiqq6vjAx/4QFx55ZUxadKkiIidryt1TQAAIIfiv+C1jFviXjFv3rxoamrqcq6mpuZVX1NVVdXl50Kh0O3cXxo8eHD8/Oc/jxdeeCF++MMfRlNTUxx++OExceLEstcEAABy2C1hVFNT85oh9Iphw4ZF//79u+3kbN68uduOz1/q169fHHnkkRERcfzxx8fjjz8ezc3NMXHixDj44IMj4k87R3V1dUWvCQAA5FD0rXTtHTvKPkpRXV0dDQ0N0dLS0uV8S0tLnHzyyUWvUygUdn6OafTo0XHwwQd3WbO9vT1+9KMflbQmAACwdyrhC17L3zEqVVNTU5x11lkxbty4OOmkk+Lqq6+O1tbWmDVrVkREzJgxI0aMGLHzc0rNzc0xbty4OOKII6K9vT1WrlwZy5cv3/kUu6qqqpg7d25ceumlcdRRR8VRRx0Vl156abzpTW+Kj3/847vt9wIAAPZMRYdRx24Mo2nTpsXWrVtj4cKFsXHjxqivr4+VK1fGqFGjIiKitbU1+vX782bXiy++GLNnz47f/e53MXDgwDjmmGPipptuimnTpu285qKLLoqXX345Zs+eHc8880yceOKJsWrVqhg8ePBu+70AAIA9U1WhUChUeggAAIBKKvozRgAAAHurom+l442xfctTlR4B6MHAQyZUegQA6DN2tG+o9AhvODtGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAA0KtOPfXUuPjii7udf+aZZ+LUU0+twETdVRUKhUKlh8hk+5anKj0C0IOBh0yo9AgA0GfsaN9Q0vX9+vWLAw44IMaPHx8333xz7LvvvhER8b//+79xyCGHREdHR2+MWRI7RgAAQK/7wQ9+EJs2bYp3vetdsW7dukqP040wAgAAStLW1hbPPfdcl6Otre1VX1NXVxc/+tGPYuzYsXHCCSfEvffeu3uGLdKAcl84a9as2LZt2xs5y15t2bJllR4BAADeEM3Nzd0+M/TlL385FixY0OP1VVVVERFRU1MTN998c1xyySXxvve9Lz772c/29qhFK/szRjNnzvQf+2XwGSPYM/mMEQAU78Xnn+q2Q1RTUxM1NTU9Xt+vX7/YtGlTHHTQQTvP3XrrrfGJT3wiXn755T3iM0Zl7xgBAAA5vVoE9eQ3v/lNHHjggV3OnXHGGXHMMcfEmjVr3ujxyiKMAACAXjVq1Kgezx977LFx7LHH7uZpeubhCwAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0BlR6gGwGHjKh0iMAPXj596srPQIAUEF2jAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAKQnjAAAgPSEEQAAkJ4wAgAA0hNGAABAesIIAABITxgBAADpCSMAACA9YQQAAOwVnn322bJfK4wAAIA+56tf/WqsWLFi588f+chH4oADDogRI0bEww8/XPJ6wggAAOhzrrrqqhg5cmRERLS0tERLS0t873vfi8mTJ8dnPvOZktcb8EYPCAAA0Ns2bty4M4zuvPPO+MhHPhKNjY1x2GGHxYknnljyenaMAACAPufNb35zrF+/PiIivv/978ff/M3fREREoVCIjo6OktezYwQAAPQ5U6dOjY9//ONx1FFHxdatW2Py5MkREfHzn/88jjzyyJLXE0YAAECfc/nll8dhhx0W69evj8suuywGDRoUEX+6xW727NklryeMAACAPmefffaJT3/6093Oz507t6z1hBEAANAn3H777UVf+3d/93clrS2MAACAPmHKlClFXVdVVVXyAxiEEQAA0Cd0dnb22toe1w0AAPRp27Zte91rCCMAAKDP6ejoiH/6p3+KESNGxKBBg+Kpp56KiIgvfvGLce2115a8njACAAD6nK985SuxbNmyuOyyy6K6unrn+be97W1xzTXXlLyeMAIAAPqc5cuXx9VXXx3Tp0+P/v377zw/duzY+OUvf1nyesIIAADoczZs2BBHHnlkt/OdnZ2xffv2ktcTRgAAQK/6wQ9+sMs/u+qqq8pa89hjj43Vq1d3O/+tb30r3v72t5e8nsd1AwAAveoDH/hAnH/++dHc3Lzz80B/+MMf4pxzzon7778//v7v/77kNb/85S/HWWedFRs2bIjOzs74zne+E0888UQsX7487rzzzpLXs2MEAAD0qh//+Mdxxx13xAknnBC/+MUv4q677or6+vp44YUX4uGHHy5rzQ9+8IOxYsWKWLlyZVRVVcWXvvSlePzxx+OOO+6ISZMmlbyeHSMAAKAkbW1t0dbW1uVcTU1N1NTU9Hj9iSeeGGvXro1Zs2ZFQ0NDdHZ2xiWXXBKf+cxnoqqqquw5TjvttDjttNPKfv1fsmMEAACUpLm5OYYOHdrlaG5uftXXPPHEE/Hggw/GX/3VX8WAAQPil7/8Zbz00kuve5Y1a9bEjTfeGDfddFM89NBDZa8jjAAAgJLMmzcv/vjHP3Y55s2bt8vr//mf/zlOOumkmDRpUjz66KPx4IMPxtq1a2Ps2LHxk5/8pKwZfve738WECRPine98Z1xwwQXxj//4j3HCCSfEu9/97li/fn3J6wkjAACgJDU1NTFkyJAux65uo4uIuOKKK+K2226LK6+8Mmpra+PYY4+Nn/3sZzF16tSYOHFiWTOcc845sX379nj88cfj6aefjqeffjoef/zxKBQKce6555a8ns8YAQAAveqRRx6JYcOGdTm3zz77xL/8y7/E3/7t35a15urVq+OBBx6It7zlLTvPveUtb4krr7wyxo8fX/J6dowAAIBe9X+j6C+9973vLWvNQw89tMcvct2xY0eMGDGi5PWEEQAA0Odcdtll8Q//8A+xZs2aKBQKEfGnBzFccMEF8a//+q8lr+dWOgAAoE9485vf3OXx3i+++GKceOKJMWDAn7Jmx44dMWDAgDjnnHNiypQpJa0tjAAAgD5h8eLFvba2MAIAAPqET3ziE722tjACAAD6tJdffrnbgxiGDBlS0hoevgAAAPQ5L774Ypx//vlx0EEHxaBBg+LNb35zl6NUwggAAOhzLrroorjnnntiyZIlUVNTE9dcc01cfPHFccghh8Ty5ctLXs+tdAAAQJ9zxx13xPLly2PixIlxzjnnxIQJE+LII4+MUaNGxc033xzTp3eq4QIAABFfSURBVE8vaT07RgAAQJ/z9NNPx+jRoyPiT58nevrppyMi4t3vfnf8+Mc/Lnk9YQQAAPQ5hx9+eKxbty4iIt761rfGN7/5zYj4007S0KFDS15PGAEAAH3O2WefHQ8//HBERMybN2/nZ40uvPDCuOiii0pez2eMAACAPufCCy/c+c+nnHJK/PKXv4w1a9bEgQceGNdff33J69kxAgAA+rxDDz00pk6dGkOGDIkbbrih5NcLIwAAID1hBAAApCeMAACA9Dx8AQAA6DOmTp36qn/+7LPPlrWuMAIAAPqM1/qOoqFDh8aMGTNKXlcYAQAAfUY5j+Iuhs8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgvQHlvrC2tjZmzpz5Bo6yd1u2bFmlRwAAAHahqlAoFCo9RCYDqkdUegSgBy//fnWlRwCAPmOfYYdXeoQ3nFvpAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAOkJIwAAID1hBAAApCeMAACA9IQRAACQnjACAADSE0YAAEB6wggAAEhPGAEAAL1q5syZ8eMf/7jSY7wqYQQAAPSq559/PhobG+Ooo46KSy+9NDZs2FDpkboRRgAAQK+69dZbY8OGDXH++efHt771rTjssMNi8uTJ8e1vfzu2b99e6fEiIqKqUCgUKj1EJgOqR1R6BKAHL/9+daVHAIA+o3PwiGhra+tyrqamJmpqaop6/dq1a+O6666La665JgYNGhRnnnlmzJ49O4466qjeGLcodowAAICSNDc3x9ChQ7sczc3NRb1248aNsWrVqli1alX0798/3v/+98cvfvGLeOtb3xqXX355L0++a3aMdjM7RrBnsmMEAMUrdcdo+/btcfvtt8f1118fq1atirFjx8Z5550X06dPj8GDB0dExC233BKf+tSn4plnnun1+XsyoCLvCgAA9Fml3DYXEVFXVxednZ3xsY99LH72s5/F8ccf3+2a0047Lfbbb783csyS2DHazewYwZ7JjhEAFG+fYYeXdP2NN94YH/7wh6O2traXJnr9hNFuJoxgzySMAKB4pYZRX+DhCwAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0hBEAAJCeMAIAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4wAAID0qgqFQqHSQ0Bf1NbWFs3NzTFv3ryoqamp9DjA/+fvJuyZ/N1kTyeMoEzPPfdcDB06NP74xz/GkCFDKj0O8P/5uwl7Jn832dO5lQ4AAEhPGAEAAOkJIwAAIL3+CxYsWFDpIaCv6t+/f0ycODEGDBhQ6VGAv+DvJuyZ/N1kT+bhCwAAQHpupQMAANITRgAAQHrCCAAASE8YAQAA6QkjAAAgPWEEAACkJ4ygROvWrYuqqqpux8SJEys9GqT1hz/8IQ4++OC49NJLd5776U9/GtXV1bFq1aoKTga5LV++PA444IBoa2vrcv6MM86IGTNmVGgq6JkwghKNHDkyNm7cuPNYu3ZtHHDAAfGe97yn0qNBWgceeGBcd911sWDBglizZk288MILceaZZ8bs2bOjsbGx0uNBWh/+8Iejo6Mjbr/99p3ntmzZEnfeeWecffbZFZwMuvMFr/A6bNu2LSZOnBgHHnhgfPe7341+/fy/BqikOXPmxA9+8IM44YQT4uGHH44HH3wwamtrKz0WpDZ79uxYt25drFy5MiIirrjiivj6178ev/71r6OqqqrC08GfCSN4HaZPnx4///nP4z//8z9j8ODBlR4H0nv55Zejvr4+1q9fH2vWrImxY8dWeiRIb+3atXHCCSfEb3/72xgxYkQcf/zxccYZZ8QXv/jFSo8GXfjf21CmSy65JL7//e/H7bffLopgD/HUU0/F73//++js7Izf/va3lR4HiIi3v/3tcdxxx8Xy5cvjv/7rv+KRRx6JmTNnVnos6MaOEZTh1ltvjY997GPxve99L/76r/+60uMAEdHe3h7vfOc74/jjj49jjjkmFi1aFI888kgMHz680qNBekuXLo3LL788Ghsb48knn4y777670iNBN8IISvToo4/GiSeeGE1NTTFnzpyd56urq2P//fev4GSQ22c+85n49re/HQ8//HAMGjQoTjnllBg8eHDceeedlR4N0nvuueeirq4uduzYEcuXL49p06ZVeiToxq10UKI1a9bESy+9FJdccknU1dXtPKZOnVrp0SCte++9NxYvXhw33nhjDBkyJPr16xc33nhj3HfffbF06dJKjwfpDRkyJM4444wYNGhQTJkypdLjQI/sGAEA0OsmTZoUY8aMia9//euVHgV6JIwAAOg1Tz/9dKxatSqmT58ejz32WLzlLW+p9EjQowGVHgAAgL3XO97xjnjmmWfiq1/9qihij2bHCAAASM/DFwAAgPSEEQAAkJ4wAgAA0hNGAABAesIIgD5r2bJlsd9++73udaqqquK22257AyYCoK8SRgBU1MyZM2PKlCmVHgOA5IQRAACQnjACYI+1aNGieNvb3hb77rtvjBw5MmbPnh0vvPBCt+tuu+22OProo6O2tjYmTZoU69ev7/Lnd9xxRzQ0NERtbW0cfvjhcfHFF8eOHTt6fM/29vY4//zzo66uLmpra+Owww6L5ubmXvn9ANhzCCMA9lj9+vWLr3/96/Hoo4/GDTfcEPfcc09cdNFFXa556aWX4itf+UrccMMNcf/998f/a+9uQuH74jiOf0ym0JCUIomFMsoCDcbGTh6iLIaRpLGwUMySbJSnhYVRI8VGFqM0k5SkPBQbRVETeZgssGGDhsLCxH+h35RY/BY/mf73/aqzuPeee8/5Lj/33M59fHxUS0tL9Pra2pra2trkdrt1cnKimZkZzc3NaXR09NsxvV6vlpeX5ff7FQqF5PP5lJub+5NlAgBiQNz7+/v7b08CAGBcLpdL4XD4rzY/CAQC6urq0u3traSPzRc6Ojq0u7ur8vJySdLZ2ZkKCgq0t7ensrIyVVZWqra2Vv39/dHn+Hw+9fb26vr6WtLH5gtLS0tqbGyU2+3W8fGxNjc3FRcX9wMVAwBiEStGAICYtbW1paqqKmVlZSk5OVnt7e26u7vT09NTtE98fLxsNlv02Gq1KjU1Vaenp5Kkg4MDDQ0NyWKxRFtnZ6dubm70/Pz8ZUyXy6VgMKj8/Hy53W6tr6//fKEAgF9HMAIAxKSrqyvV1dWpsLBQi4uLOjg40NTUlCTp9fX1U9/vVnb+nHt7e9Pg4KCCwWC0HR0d6fz8XAkJCV/uKykp0cXFhYaHh/Xy8qLm5mY5HI4fqBAAEEvif3sCAAB8Z39/X5FIROPj4zKZPt7j+f3+L/0ikYj29/dVVlYmSQqFQgqHw7JarZI+gk4oFFJeXt5fj52SkiKn0ymn0ymHw6Gamhrd398rLS3tH1QGAIhFBCMAwK97eHhQMBj8dC49PV2RSESTk5NqaGjQzs6Opqenv9xrNpvV09Mjr9crs9ms7u5u2e32aFAaGBhQfX29srOz1dTUJJPJpMPDQx0dHWlkZOTL8yYmJpSZmamioiKZTCYFAgFlZGT8kx/JAgBiF5/SAQB+3fb2toqLiz+12dlZeTwejY2NqbCwUPPz899um52UlKS+vj61traqoqJCiYmJWlhYiF6vrq7WysqKNjY2VFpaKrvdLo/Ho5ycnG/nYrFYNDY2JpvNptLSUl1eXmp1dTW6agUA+H9iVzoAAAAAhsfrLwAAAACGRzACAAAAYHgEIwAAAACGRzACAAAAYHgEIwAAAACGRzACAAAAYHgEIwAAAACGRzACAAAAYHgEIwAAAACGRzACAAAAYHgEIwAAAACGRzACAAAAYHj/AWJV+6eIgBZDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "# Test correlation fns.\n",
    "# ep.snsMatMod.clustermap(daPlotpd.fillna(0).T.corr())  # This currently failing with NaNs or inf?\n",
    "snsMatMod.clustermap(daPlotpd.fillna(0).corr())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here the separation of $z$ polarization, from the mixed $(x,y)$ case, in spherical functions, is clear."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## $\\beta_{L,M}^{MF}$ rewrite\n",
    "\n",
    "The various terms defined above can be used to redefine the full MF observables, expressed as a set of $\\beta_{L,M}$ coefficients.\n",
    "\n",
    "This is explored in pt 2..."
   ]
  }
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