doc/analyses_from_paper/required_sample_size.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Required sample sizes"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "How many samples are required to obatin stable CCA and PLS estimates?"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Setup"
   ]
  },
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       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
       "  \n",
       "\n",
       "\n",
       "</div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import scipy.linalg\n",
    "import scipy.stats\n",
    "from scipy.stats import pearsonr, zscore\n",
    "from scipy.spatial.distance import pdist, cdist, squareform\n",
    "\n",
    "from sklearn import clone\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import cross_validate, ShuffleSplit\n",
    "\n",
    "from gemmr.data import load_outcomes, print_ds_stats\n",
    "from gemmr.metrics import *\n",
    "from gemmr.sample_size.interpolation import *\n",
    "from gemmr.plot import heatmap_n_req\n",
    "from gemmr.util import nPerFtr2n, subset_ds\n",
    "\n",
    "import matplotlib\n",
    "import holoviews as hv\n",
    "from holoviews import opts\n",
    "hv.extension('matplotlib')\n",
    "hv.renderer('matplotlib').param.set_param(dpi=120)\n",
    "\n",
    "from my_config import *\n",
    "\n",
    "import warnings\n",
    "from matplotlib import MatplotlibDeprecationWarning\n",
    "warnings.simplefilter('ignore', MatplotlibDeprecationWarning)\n",
    "warnings.filterwarnings(\n",
    "    'ignore', 'aspect is not supported for Axes with xscale=log, yscale=linear', category=UserWarning\n",
    ")  # holoviews emits this for log-linear plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This will be populated below and then written to disk\n",
    "plotted_data = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# helper functions for figS layout, used below\n",
    "\n",
    "def figS_axpos(plot, elements):\n",
    "    # global ax\n",
    "    ax = plot.handles['axis']\n",
    "\n",
    "    pos = ax.get_position()\n",
    "    if pos.x0 < 0.1:\n",
    "        ax.set_position((pos.x0-.035, pos.y0, pos.width, pos.height))\n",
    "    elif pos.x0 < 0.4:\n",
    "        ax.set_position((pos.x0-.07, pos.y0, pos.width, pos.height))\n",
    "    elif pos.x0 < .6:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load pre-calculated outcomes of analyzed synthetic data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data from subfolder 'gemmr_latest'\n",
      "Loading data from subfolder 'gemmr_latest'\n"
     ]
    }
   ],
   "source": [
    "ds_cca = load_outcomes('sweep_cca_cca_random_sum+-2+-2')\n",
    "ds_pls = load_outcomes('sweep_pls_pls_random_sum+-2+-2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_cca = ds_cca.sel(px=ds_cca.px < 128)\n",
    "ds_pls = ds_pls.sel(px=ds_pls.px < 128)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_cca = subset_ds(ds_cca, n_keep=25)\n",
    "ds_pls = subset_ds(ds_pls, n_keep=25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What's in the outcome data files?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_modes\t\t 1\n",
      "n_rep\t\t 100\n",
      "n_per_ftr\t [   3    4    8   16   32   64  128  256  512 1024 2048 4096 8192]\n",
      "r\t\t [0.1 0.3 0.5 0.7]\n",
      "px\t\t [ 2  4  8 16 32 64]\n",
      "ax+ay range\t(-2.00, -2.00)\n",
      "py\t\t== px\n",
      "\n",
      "<xarray.DataArray 'n_Sigmas' (px: 6, r: 4)>\n",
      "array([[25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [ 0, 25, 25, 25]])\n",
      "Coordinates:\n",
      "  * r        (r) float64 0.1 0.3 0.5 0.7\n",
      "  * px       (px) int64 2 4 8 16 32 64\n",
      "\n",
      "power\t\tcalculated\n"
     ]
    }
   ],
   "source": [
    "print_ds_stats(ds_cca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "n_modes\t\t 1\n",
      "n_rep\t\t 100\n",
      "n_per_ftr\t [   3    4    8   16   32   64  128  256  512 1024 2048 4096 8192]\n",
      "r\t\t [0.1 0.3 0.5 0.7]\n",
      "px\t\t [ 2  4  8 16 32 64]\n",
      "ax+ay range\t(-2.00, -2.00)\n",
      "py\t\t== px\n",
      "\n",
      "<xarray.DataArray 'n_Sigmas' (px: 6, r: 4)>\n",
      "array([[25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [25, 25, 25, 25],\n",
      "       [ 0, 25, 25, 25],\n",
      "       [ 0, 25, 25, 25],\n",
      "       [ 0,  0,  0, 10]])\n",
      "Coordinates:\n",
      "  * r        (r) float64 0.1 0.3 0.5 0.7\n",
      "  * px       (px) int64 2 4 8 16 32 64\n",
      "\n",
      "power\t\tcalculated\n"
     ]
    }
   ],
   "source": [
    "print_ds_stats(ds_pls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Required sample sizes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's calculate the required sample size. This is implemented in ``ccapwr.required_sample_size``. The function ``calc_n_required_all_metrics`` produces sample size estimates based on 5 metrics (power, relative error of between-set association strength, weight error, loading error, score error), as well as a combination of these 5 metrics (i.e. the maximum across all 5 metrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "cca_n_req_per_ftr = calc_n_required_all_metrics(ds_cca.sel(mode=0), search_dim='n_per_ftr')\n",
    "pls_n_req_per_ftr = calc_n_required_all_metrics(ds_pls.sel(mode=0), search_dim='n_per_ftr')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Illustration of the required sample size based on the combined criterion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Layout\n",
       "   .QuadMesh.I  :QuadMesh   [Number of features,$r_\\mathrm{true}$]   (Required sample size)\n",
       "   .QuadMesh.II :QuadMesh   [Number of features,$r_\\mathrm{true}$]   (Required sample size)"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metric = 'combined'\n",
    "fig_required_sample_size_heatmap = (\n",
    "    heatmap_n_req(nPerFtr2n(cca_n_req_per_ftr[metric], ds_cca.py)).opts(hooks=[figS_axpos, suptitle_cca])\n",
    "    + heatmap_n_req(nPerFtr2n(pls_n_req_per_ftr[metric], ds_pls.py)).opts(colorbar=True, hooks=[figS_axpos, suptitle_pls])\n",
    ").cols(\n",
    "    2\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.QuadMesh(logx=True, logz=True, #xlim=(2, 256+64), ylim=(0, 1),\n",
    "                clim=(1e1, 1e5), cmap='inferno',\n",
    "                sublabel_position=(-.45, .95),\n",
    "                fontsize=dict(labels=8, ticks=7, legend=7, title=8),\n",
    "                ),\n",
    "    opts.Layout(fig_inches=(3.42, None))\n",
    ")\n",
    "\n",
    "fig_required_sample_size_heatmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's somewhat hard to read off the numbers, therefore we replot this for individual values of $r_\\mathrm{true}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def plot_n_req(n_req, qs=(.025, .975), color=None, label='mean', plotted_data=None, panel_label=None):\n",
    "    \n",
    "    n_req_q = n_req.dropna('ptot', how='all').quantile(qs, 'Sigma_id')\n",
    "    \n",
    "    if plotted_data is not None:\n",
    "        _plotted_data = pd.concat(\n",
    "            [\n",
    "                n_req.mean('Sigma_id').to_pandas().rename('mean'),\n",
    "                n_req_q.sel(quantile=qs[0]).to_pandas().rename(f'{100*qs[0]:.1f}%'),\n",
    "                n_req_q.sel(quantile=qs[-1]).to_pandas().rename(f'{100*qs[-1]:.1f}%'),\n",
    "            ],\n",
    "            axis=1\n",
    "        )\n",
    "        plotted_data[panel_label] = _plotted_data\n",
    "    \n",
    "    return (\n",
    "        hv.Curve(\n",
    "           (n_req.ptot, n_req.mean('Sigma_id')),\n",
    "            label=label\n",
    "        )\n",
    "        * hv.Area(\n",
    "            (n_req_q.ptot, n_req_q.sel(quantile=qs[0]), n_req_q.sel(quantile=qs[-1])),\n",
    "            vdims=['y', 'y2']\n",
    "        )\n",
    "    ).redim(\n",
    "        x='Number of features',\n",
    "        y='Required sample size'\n",
    "    ).opts(\n",
    "        opts.Curve(color=color),\n",
    "        opts.Area(alpha=.25, color=color),\n",
    "        opts.Overlay(logx=True, logy=True)\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":NdLayout   [r_true]\n",
       "   :Overlay\n",
       "      .Curve.CCA :Curve   [Number of features]   (Required sample size)\n",
       "      .Area.I    :Area   [Number of features]   (Required sample size,y2)\n",
       "      .Curve.PLS :Curve   [Number of features]   (Required sample size)\n",
       "      .Area.II   :Area   [Number of features]   (Required sample size,y2)"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "panels_req_sample_size = {}\n",
    "for r in [.1, .3, .5, .7,]:\n",
    "    panels_req_sample_size[r] = (\n",
    "        plot_n_req(nPerFtr2n(cca_n_req_per_ftr['combined'], ds_cca.py).sel(r=r), color=clr_cca, label='CCA', plotted_data=plotted_data, panel_label=f'CCA_r{r:.1f}_req_n')\n",
    "        * plot_n_req(nPerFtr2n(pls_n_req_per_ftr['combined'], ds_pls.py).sel(r=r), color=clr_pls, label='PLS', plotted_data=plotted_data, panel_label=f'PLS_r{r:.1f}_req_n')\n",
    "    ).opts(\n",
    "        opts.Overlay(logx=True, logy=True, show_legend=True, hooks=[legend_frame_off])\n",
    "    )\n",
    "\n",
    "    \n",
    "hv.NdLayout(\n",
    "    panels_req_sample_size, \n",
    "    kdims=hv.Dimension('r_true', label=r'$r_\\mathrm{true}$')\n",
    ").cols(\n",
    "    5\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Required sample sizes depending on used metric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Layout\n",
       "   .Overlay.I  :Overlay\n",
       "      .Curve.Power        :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.BetweenAssoc :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.WeightError  :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.LoadingError :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.ScoreError   :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.Combined     :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "   .Overlay.II :Overlay\n",
       "      .Curve.Power        :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.I             :Text   [x,y]\n",
       "      .Curve.BetweenAssoc :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.II            :Text   [x,y]\n",
       "      .Curve.WeightError  :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.III           :Text   [x,y]\n",
       "      .Curve.LoadingError :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.IV            :Text   [x,y]\n",
       "      .Curve.ScoreError   :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.V             :Text   [x,y]\n",
       "      .Curve.Combined     :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.VI            :Text   [x,y]"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = 0.3\n",
    "\n",
    "panels = dict(cca=hv.Overlay(), pls=hv.Overlay())\n",
    "\n",
    "metric_labels = dict(\n",
    "    power='power',\n",
    "    betweenAssoc='assoc. strength error',\n",
    "    weightError='weight error',\n",
    "    scoreError='score error',\n",
    "    loadingError='loading error',\n",
    "    combined='combined'\n",
    ")\n",
    "metric_clrs = hv.Palette('Dark2', samples=len(metric_labels)).values\n",
    "\n",
    "for model, ds_, n_req_per_ftr in [\n",
    "    ('cca', ds_cca, cca_n_req_per_ftr),\n",
    "    ('pls', ds_pls, pls_n_req_per_ftr),\n",
    "]:\n",
    "    for metric_i, metric in enumerate(n_req_per_ftr):\n",
    "        if metric == 'combined':\n",
    "            linestyle = '--'\n",
    "        else:\n",
    "            linestyle = '-'\n",
    "        n_req = nPerFtr2n(n_req_per_ftr[metric], ds_.py).sel(r=r)\n",
    "        panels[model] *= hv.Curve(n_req.mean('Sigma_id').dropna('ptot'), label=metric).opts(linestyle=linestyle, color=metric_clrs[metric_i])\n",
    "        \n",
    "        if model == 'pls':\n",
    "            panels[model] *= hv.Text(256, 3 * (2.25)**metric_i, metric_labels[metric], fontsize=7, halign='right', valign='bottom').opts(color=metric_clrs[metric_i])\n",
    "        \n",
    "fig_req_sample_size_by_metric = (\n",
    "    panels['cca'].opts(hooks=[figS_axpos, suptitle_cca])\n",
    "    + panels['pls'].opts(ylabel='', hooks=[figS_axpos, suptitle_pls])\n",
    ").redim(\n",
    "    ptot='Number of features',\n",
    "    n_required='Req. sample size to obtain\\n' + r'$\\geq$ 90% power & $\\leq$ 10%' + '\\nerror in other metrics'\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.Curve(linewidth=1),\n",
    "    opts.Overlay(logx=True, logy=True, show_legend=False)\n",
    ")\n",
    "\n",
    "fig_req_sample_size_by_metric"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Required sample size per variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way to condense the information shown in the heatmaps above, is to investigate the number of required samples per feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_n_per_ftr(n_req_per_ftr, color=None, label='', plotted_data=None, panel_label=None):\n",
    "    \n",
    "    px_exponent = 1 # error_bars['max'][2, 1]\n",
    "    n_per_ftr = n_req_per_ftr.mean('Sigma_id').rename('y')  # rename for redim below\n",
    "    n_per_ftr_stacked = n_per_ftr.stack(it=('r', 'px'))\n",
    "    \n",
    "    panel = hv.Curve(n_per_ftr.mean('px')).opts(\n",
    "        color='black', linestyle='--', linewidth=1\n",
    "    )\n",
    "\n",
    "    for r in n_per_ftr.r.values:\n",
    "        panel *= hv.Curve(\n",
    "            ([.85*r, 1.15*r], [float(n_per_ftr.sel(r=r).mean('px'))]*2),\n",
    "            kdims='r',\n",
    "            label=label,\n",
    "        ).opts(\n",
    "            color=color,\n",
    "            linewidth=1\n",
    "        )\n",
    "\n",
    "    panel *= hv.Scatter(\n",
    "        (n_per_ftr_stacked.r.values * np.random.uniform(.95, 1.05, size=n_per_ftr_stacked.r.shape), n_per_ftr_stacked),\n",
    "        kdims='r',\n",
    "    ).opts(marker='.', color=color)\n",
    "\n",
    "    if plotted_data is not None:\n",
    "        plotted_data[panel_label] = n_per_ftr_stacked.unstack().to_pandas()\n",
    "\n",
    "    panel = panel.redim(\n",
    "        r='$r_\\mathrm{true}$',\n",
    "        y='Req. samples per feature'\n",
    "    ).opts(\n",
    "        opts.Overlay(logx=True, logy=True)\n",
    "    )\n",
    "    return panel\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Overlay\n",
       "   .Curve.I       :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.PLS.I   :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.PLS.II  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.PLS.III :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.PLS.IV  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Scatter.I     :Scatter   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.II      :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.CCA.I   :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.CCA.II  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.CCA.III :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Curve.CCA.IV  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "   .Scatter.II    :Scatter   [$r_\\mathrm{true}$]   (Req. samples per feature)"
      ]
     },
     "execution_count": 15,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use only px, r for which both CCA and PLS data available!\n",
    "mask = np.isfinite(cca_n_req_per_ftr['combined'].mean('Sigma_id')) & np.isfinite(pls_n_req_per_ftr['combined'].mean('Sigma_id'))\n",
    "\n",
    "panels_req_n_per_variable = (\n",
    "    plot_n_per_ftr(pls_n_req_per_ftr['combined'].where(mask), color=clr_pls, label='PLS', plotted_data=plotted_data, panel_label='PLS_req_n_per_ftr').opts(yaxis='bare')#.relabel('PLS')\n",
    "    * plot_n_per_ftr(cca_n_req_per_ftr['combined'].where(mask), color=clr_cca, label='CCA', plotted_data=plotted_data, panel_label='CCA_req_n_per_ftr').opts(show_legend=False)#.relabel('CCA')\n",
    "    #* hv.Text(1, 2000, 'PLS', halign='right', valign='top', fontsize=8).opts(color=clr_pls)\n",
    "    #* hv.Text(1, 1000, 'CCA', halign='right', valign='top', fontsize=8).opts(color=clr_cca)\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.Scatter(s=15),\n",
    "    opts.Overlay(logx=True, logy=True, xlim=(None, 1.), padding=.02, show_legend=False, fig_inches=(1.7, None)),\n",
    ")\n",
    "\n",
    "panels_req_n_per_variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Layout\n",
       "   .Overlay.I  :Overlay\n",
       "      .Curve.CCA :Curve   [Number of features]   (Required sample size)\n",
       "      .Area.I    :Area   [Number of features]   (Required sample size,y2)\n",
       "      .Curve.PLS :Curve   [Number of features]   (Required sample size)\n",
       "      .Area.II   :Area   [Number of features]   (Required sample size,y2)\n",
       "      .Text.I    :Text   [x,y]\n",
       "      .Text.II   :Text   [x,y]\n",
       "      .Text.III  :Text   [x,y]\n",
       "   .Overlay.II :Overlay\n",
       "      .Curve.I       :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.PLS.I   :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.PLS.II  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.PLS.III :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.PLS.IV  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Scatter.I     :Scatter   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.II      :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.CCA.I   :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.CCA.II  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.CCA.III :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Curve.CCA.IV  :Curve   [$r_\\mathrm{true}$]   (Req. samples per feature)\n",
       "      .Scatter.II    :Scatter   [$r_\\mathrm{true}$]   (Req. samples per feature)"
      ]
     },
     "execution_count": 16,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = (\n",
    "    (\n",
    "        panels_req_sample_size[0.3]\n",
    "        * hv.Text(256, 100, '$r_\\mathrm{true}=0.3$', halign='right', valign='bottom', fontsize=8)\n",
    "        * hv.Text(5, 5e4, 'PLS', halign='left', valign='top', fontsize=8).opts(color=clr_pls)\n",
    "        * hv.Text(5, 2.5e4, 'CCA', halign='left', valign='top', fontsize=8).opts(color=clr_cca)\n",
    "    ).opts(logx=True, logy=True, show_legend=False, ylabel='Req. sample size to obtain\\n' + r'$\\geq$ 90% power & $\\leq$ 10%' + '\\nerror in other metrics')\n",
    "    + panels_req_n_per_variable.opts(show_legend=False)\n",
    ").cols(\n",
    "    2\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.Layout(sublabel_position=(-.3, .95), hspace=.6)\n",
    ")\n",
    "\n",
    "hv.save(fig, 'fig/fig_required_sample_size.pdf')\n",
    "save_source_data(plotted_data, 'fig7')\n",
    "\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img 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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Layout\n",
       "   .QuadMesh.I  :QuadMesh   [Number of features,$r_\\mathrm{true}$]   (Required sample size)\n",
       "   .QuadMesh.II :QuadMesh   [Number of features,$r_\\mathrm{true}$]   (Required sample size)\n",
       "   .Overlay.I   :Overlay\n",
       "      .Curve.Power        :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.BetweenAssoc :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.WeightError  :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.LoadingError :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.ScoreError   :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Curve.Combined     :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "   .Overlay.II  :Overlay\n",
       "      .Curve.Power        :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.I             :Text   [x,y]\n",
       "      .Curve.BetweenAssoc :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.II            :Text   [x,y]\n",
       "      .Curve.WeightError  :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.III           :Text   [x,y]\n",
       "      .Curve.LoadingError :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.IV            :Text   [x,y]\n",
       "      .Curve.ScoreError   :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.V             :Text   [x,y]\n",
       "      .Curve.Combined     :Curve   [Number of features]   (Req. sample size to obtain\n",
       "$\\geq$ 90% power & $\\leq$ 10%\n",
       "error in other metrics)\n",
       "      .Text.VI            :Text   [x,y]"
      ]
     },
     "execution_count": 17,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "figS = (\n",
    "    fig_required_sample_size_heatmap\n",
    "    + fig_req_sample_size_by_metric\n",
    ").cols(\n",
    "    4\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.Layout(fig_inches=(7, .7), hspace=.75)\n",
    ")\n",
    "\n",
    "hv.save(figS, 'fig/figS_required_sample_size.pdf')\n",
    "\n",
    "figS"
   ]
  }
 ],
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