doc/analyses_from_paper/empirical_data_how_many_pcs.ipynb

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   "source": [
    "# How many PCs are really necessary?"
   ]
  },
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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 os\n",
    "\n",
    "import xarray as xr\n",
    "\n",
    "from gemmr.data.loaders import load_other_outcomes\n",
    "\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": "markdown",
   "metadata": {},
   "source": [
    "## Prepare data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following takes a while to run:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "import os\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from tqdm import trange\n",
    "from gemmr.estimators import SVDCCA\n",
    "from gemmr.estimators.helpers import pearson_transform_scorer\n",
    "\n",
    "_ds = xr.open_dataset(\n",
    "    os.path.expanduser('~/gemmr_data/empirical/ukb_fmri_smithpreproc_pcs.nc')\n",
    ")\n",
    "ukbb_fMRI_X, ukbb_fMRI_Y = _ds['X_pcs'].values, _ds['Y_pcs'].values\n",
    "\n",
    "cca_rs = np.nan * np.empty((100, 100))\n",
    "cca_rs_cv = np.nan * np.empty((100, 100))\n",
    "cca = SVDCCA()\n",
    "for i in trange(1, 100):\n",
    "    for j in trange(1, 100, leave=False):\n",
    "        cca_rs[i,j] = cca.fit(ukbb_fMRI_X[:, :i], ukbb_fMRI_Y[:, :j]).assocs_[0]\n",
    "        cca_rs_cv[i, j] = cross_val_score(\n",
    "            cca, ukbb_fMRI_X[:, :i], ukbb_fMRI_Y[:, :j], cv=5, \n",
    "            scoring=pearson_transform_scorer, n_jobs=None\n",
    "        ).mean()\n",
    "\n",
    "ds = xr.Dataset(dict(\n",
    "    cca_rs=xr.DataArray(cca_rs, dims=('n_X_pcs', 'n_Y_pcs')),\n",
    "    cca_rs_cv=xr.DataArray(cca_rs_cv, dims=('n_X_pcs', 'n_Y_pcs'))\n",
    "))\n",
    "ds.to_netcdf('ukb_how_many_pcs_cca_inSampleCV.nc')\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "import os\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from tqdm import trange\n",
    "from gemmr.estimators import SVDPLS\n",
    "from gemmr.estimators.helpers import cov_transform_scorer\n",
    "\n",
    "_ds = xr.open_dataset(\n",
    "    os.path.expanduser('~/gemmr_data/empirical/ukb_fmri_smithpreproc_pcs.nc')\n",
    ")\n",
    "ukbb_fMRI_X, ukbb_fMRI_Y = _ds['X_pcs'].values, _ds['Y_pcs'].values\n",
    "\n",
    "pls_covs = np.nan * np.empty((100, 100))\n",
    "pls_covs_cv = np.nan * np.empty((100, 100))\n",
    "pls = SVDPLS()\n",
    "for i in trange(1, 100):\n",
    "    for j in trange(1, 100, leave=False):\n",
    "        pls_covs[i,j] = pls.fit(ukbb_fMRI_X[:, :i], ukbb_fMRI_Y[:, :j]).assocs_[0]\n",
    "        pls_covs_cv[i, j] = cross_val_score(\n",
    "            pls, ukbb_fMRI_X[:, :i], ukbb_fMRI_Y[:, :j], cv=5, \n",
    "            scoring=cov_transform_scorer, n_jobs=None\n",
    "        ).mean()\n",
    "\n",
    "ds = xr.Dataset(dict(\n",
    "    pls_covs=xr.DataArray(pls_covs, dims=('n_X_pcs', 'n_Y_pcs')),\n",
    "    pls_covs_cv=xr.DataArray(pls_covs_cv, dims=('n_X_pcs', 'n_Y_pcs'))\n",
    "))\n",
    "ds.to_netcdf('ukb_how_many_pcs_pls_inSampleCV.nc')\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The previous code segments store their outputs in files for later usage. Now load these previously generated data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_cca = xr.load_dataset('ukb_how_many_pcs_cca_inSampleCV.nc')\n",
    "ds_pls = xr.load_dataset('ukb_how_many_pcs_pls_inSampleCV.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-05-15T13:29:21.845314Z",
     "iopub.status.busy": "2021-05-15T13:29:21.844734Z",
     "iopub.status.idle": "2021-05-15T13:29:21.919853Z",
     "shell.execute_reply": "2021-05-15T13:29:21.920215Z"
    }
   },
   "outputs": [],
   "source": [
    "cca_rs, cca_rs_cv = ds_cca.cca_rs.values, ds_cca.cca_rs_cv.values\n",
    "pls_covs, pls_covs_cv = ds_pls.pls_covs.values, ds_pls.pls_covs_cv.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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' style='max-width:100%; margin: auto; display: block; '/>"
      ],
      "text/plain": [
       ":Layout\n",
       "   .Raster.CCA                                                                 :Raster   [# top behav. PCs retained,# top neuroim. PCs retained]   (z)\n",
       "   .Raster.CCA_left_parenthesis_cross_hyphen_minus_validated_right_parenthesis :Raster   [# top behav. PCs retained,# top neuroim. PCs retained]   (z)\n",
       "   .Raster.PLS                                                                 :Raster   [# top behav. PCs retained,# top neuroim. PCs retained]   (z)\n",
       "   .Raster.PLS_left_parenthesis_cross_hyphen_minus_validated_right_parenthesis :Raster   [# top behav. PCs retained,# top neuroim. PCs retained]   (z)"
      ]
     },
     "execution_count": 8,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {}
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = (\n",
    "    hv.Raster(cca_rs[1:, 1:]).relabel('CCA').opts(clabel='Canonical correlation', xlabel='')\n",
    "    + hv.Raster(cca_rs_cv[1:, 1:]).relabel('CCA (cross-validated)').opts(clabel='Canonical correlation', xlabel='', ylabel='')\n",
    "    + hv.Raster(pls_covs[1:, 1:] / 3500).relabel('PLS').opts(clabel='PLS covariance / a.u.')\n",
    "    + hv.Raster(pls_covs_cv[1:, 1:] / 3500).relabel('PLS (cross-validated)').opts(clabel='PLS covariance / a.u.', ylabel='')\n",
    ").redim(\n",
    "    x='# top behav. PCs retained',\n",
    "    y='# top neuroim. PCs retained'\n",
    ").cols(\n",
    "    2\n",
    ").opts(*fig_opts).opts(\n",
    "    opts.Raster(colorbar=True, cmap='viridis', xticks=[0, 20, 40, 60, 80], invert_yaxis=True),\n",
    "    opts.Layout(hspace=.6, vspace=.45, sublabel_position=(-.28, .95))\n",
    ")\n",
    "\n",
    "hv.save(fig, \"fig/figS_cca_pls_assocStrength_dependingOnNRetainedPCs.pdf\")\n",
    "\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "gemmr",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}