<div dir="rtl"><div dir="ltr">CODE:<br clear="all"></div><div dir="ltr"><div style="color:rgb(212,212,212);background-color:rgb(30,30,30);font-family:Consolas,"Courier New",monospace;font-size:14px;line-height:19px;white-space:pre"><br><div><span style="color:rgb(197,134,192)">for</span> <span style="color:rgb(156,220,254)">nii</span> <span style="color:rgb(197,134,192)">in</span> <span style="color:rgb(78,201,176)">os</span>.<span style="color:rgb(220,220,170)">listdir</span>(<span style="color:rgb(206,145,120)">"c:/users/administrator/desktop/nii"</span>):</div><br><div>    <span style="color:rgb(197,134,192)">from</span> <span style="color:rgb(78,201,176)">nilearn</span> <span style="color:rgb(197,134,192)">import</span> <span style="color:rgb(78,201,176)">plotting</span></div><div>    <span style="color:rgb(197,134,192)">from</span> <span style="color:rgb(78,201,176)">nilearn</span> <span style="color:rgb(197,134,192)">import</span> <span style="color:rgb(78,201,176)">datasets</span></div><div>    <span style="color:rgb(156,220,254)">atlas</span> = <span style="color:rgb(78,201,176)">datasets</span>.<span style="color:rgb(220,220,170)">fetch_atlas_msdl</span>()</div><div>    <span style="color:rgb(106,153,85)"># Loading atlas image stored in 'maps'</span></div><div>    <span style="color:rgb(156,220,254)">atlas_filename</span> = <span style="color:rgb(206,145,120)">"C:/Users/Administrator/Desktop/64/64/2mm/maps.nii.gz"</span></div><div>    <span style="color:rgb(106,153,85)"># Loading atlas data stored in 'labels'</span></div><div>    <span style="color:rgb(156,220,254)">labels</span> = <span style="color:rgb(78,201,176)">pd</span>.<span style="color:rgb(220,220,170)">read_csv</span>(<span style="color:rgb(206,145,120)">"C:/Users/Administrator/Desktop/64/64/labels_64_dictionary.csv"</span>)</div><div>    <span style="color:rgb(156,220,254)">a</span>=<span style="color:rgb(156,220,254)">labels</span>.<span style="color:rgb(220,220,170)">to_dict</span>()</div><div>    <span style="color:rgb(156,220,254)">b</span>=<span style="color:rgb(156,220,254)">a</span>[<span style="color:rgb(206,145,120)">"Difumo_names"</span>]</div><div>    <span style="color:rgb(197,134,192)">from</span> <span style="color:rgb(78,201,176)">nilearn</span>.<span style="color:rgb(78,201,176)">maskers</span> <span style="color:rgb(197,134,192)">import</span> <span style="color:rgb(78,201,176)">NiftiMapsMasker</span></div><div>    <span style="color:rgb(156,220,254)">masker</span> = <span style="color:rgb(78,201,176)">NiftiMapsMasker</span>(<span style="color:rgb(156,220,254)">maps_img</span>=<span style="color:rgb(156,220,254)">atlas_filename</span>, <span style="color:rgb(156,220,254)">standardize</span>=<span style="color:rgb(86,156,214)">True</span>,</div><div>                            <span style="color:rgb(156,220,254)">memory</span>=<span style="color:rgb(206,145,120)">'nilearn_cache'</span>, <span style="color:rgb(156,220,254)">verbose</span>=<span style="color:rgb(181,206,168)">5</span>)</div><br><div>    <span style="color:rgb(156,220,254)">time_series</span> = <span style="color:rgb(156,220,254)">masker</span>.<span style="color:rgb(220,220,170)">fit_transform</span>(<span style="color:rgb(206,145,120)">"c:/users/administrator/desktop/nii/"</span>+<span style="color:rgb(156,220,254)">nii</span>)</div><div>    <span style="color:rgb(197,134,192)">try</span>:</div><div>        <span style="color:rgb(197,134,192)">from</span> <span style="color:rgb(78,201,176)">sklearn</span>.<span style="color:rgb(78,201,176)">covariance</span> <span style="color:rgb(197,134,192)">import</span> <span style="color:rgb(78,201,176)">GraphicalLassoCV</span></div><div>    <span style="color:rgb(197,134,192)">except</span> <span style="color:rgb(78,201,176)">ImportError</span>:</div><div>        <span style="color:rgb(106,153,85)"># for Scitkit-Learn < v0.20.0</span></div><div>        <span style="color:rgb(197,134,192)">from</span> <span style="color:rgb(78,201,176)">sklearn</span>.<span style="color:rgb(78,201,176)">covariance</span> <span style="color:rgb(197,134,192)">import</span> GraphLassoCV <span style="color:rgb(197,134,192)">as</span> <span style="color:rgb(78,201,176)">GraphicalLassoCV</span></div><br><div>    <span style="color:rgb(156,220,254)">estimator</span> = <span style="color:rgb(78,201,176)">GraphicalLassoCV</span>()</div><div>    <span style="color:rgb(156,220,254)">estimator</span>.<span style="color:rgb(220,220,170)">fit</span>(<span style="color:rgb(156,220,254)">time_series</span>)</div><div><span style="color:rgb(106,153,85)"># Display the covariancec</span></div><div>    <span style="color:rgb(156,220,254)">aas</span>={}</div><div>    <span style="color:rgb(156,220,254)">jsa</span>=<span style="color:rgb(181,206,168)">0</span></div><div>    <span style="color:rgb(197,134,192)">for</span> <span style="color:rgb(156,220,254)">i</span> <span style="color:rgb(197,134,192)">in</span> <span style="color:rgb(156,220,254)">estimator</span>.<span style="color:rgb(156,220,254)">covariance_</span>:</div><div>        <span style="color:rgb(156,220,254)">r</span>=<span style="color:rgb(78,201,176)">list</span>(<span style="color:rgb(156,220,254)">a</span>[<span style="color:rgb(206,145,120)">"Difumo_names"</span>].values())[<span style="color:rgb(156,220,254)">jsa</span>]</div><div>        <span style="color:rgb(156,220,254)">jsa</span>=<span style="color:rgb(156,220,254)">jsa</span>+<span style="color:rgb(181,206,168)">1</span></div><div>        <span style="color:rgb(156,220,254)">a</span>=<span style="color:rgb(78,201,176)">dict</span>()</div><br><br><div>        <span style="color:rgb(197,134,192)">for</span> <span style="color:rgb(156,220,254)">x</span> <span style="color:rgb(197,134,192)">in</span> <span style="color:rgb(78,201,176)">range</span>(<span style="color:rgb(181,206,168)">64</span>):</div><div>            <span style="color:rgb(156,220,254)">g</span>=<span style="color:rgb(78,201,176)">list</span>(<span style="color:rgb(156,220,254)">a</span>[<span style="color:rgb(206,145,120)">"Difumo_names"</span>].values())[<span style="color:rgb(156,220,254)">x</span>]</div><br><div>    <span style="color:rgb(220,220,170)">print</span>(<span style="color:rgb(156,220,254)">aas</span>)        </div><div>    <span style="color:rgb(156,220,254)">t</span>=   <span style="color:rgb(78,201,176)">nilearn</span>.plotting.plot_img(<span style="color:rgb(156,220,254)">estimator</span>.<span style="color:rgb(156,220,254)">covariance_</span>, <span style="color:rgb(156,220,254)">labels</span>=<span style="color:rgb(78,201,176)">list</span>(<span style="color:rgb(156,220,254)">a</span>[<span style="color:rgb(206,145,120)">"Difumo_names"</span>].values()),</div><div>                        <span style="color:rgb(156,220,254)">figure</span>=(<span style="color:rgb(181,206,168)">9</span>, <span style="color:rgb(181,206,168)">7</span>), <span style="color:rgb(156,220,254)">vmax</span>=<span style="color:rgb(181,206,168)">1</span>, <span style="color:rgb(156,220,254)">vmin</span>=-<span style="color:rgb(181,206,168)">1</span>,</div><div>                        <span style="color:rgb(156,220,254)">title</span>=<span style="color:rgb(206,145,120)">'Covariance'</span>)<span style="color:rgb(106,153,85)"># The covariance can be found at estimator.covariance_</span></div><br><div><span style="color:rgb(106,153,85)"># The covariance can be found at estimator.covariance_</span></div><div>    <span style="color:rgb(156,220,254)">t2</span>=  <span style="color:rgb(78,201,176)">nilearn</span>.plotting.plot_matrix(<span style="color:rgb(156,220,254)">estimator</span>.<span style="color:rgb(156,220,254)">covariance_</span>, <span style="color:rgb(156,220,254)">labels</span>=<span style="color:rgb(78,201,176)">list</span>(<span style="color:rgb(156,220,254)">a</span>[<span style="color:rgb(206,145,120)">"Difumo_names"</span>].values()),</div><div>                        <span style="color:rgb(156,220,254)">figure</span>=(<span style="color:rgb(181,206,168)">9</span>, <span style="color:rgb(181,206,168)">7</span>), <span style="color:rgb(156,220,254)">vmax</span>=<span style="color:rgb(181,206,168)">1</span>, <span style="color:rgb(156,220,254)">vmin</span>=-<span style="color:rgb(181,206,168)">1</span>,</div><div>                        <span style="color:rgb(156,220,254)">title</span>=<span style="color:rgb(206,145,120)">'Covariance'</span>)</div><br><br></div></div><div><br></div>-- <br><div dir="rtl" class="gmail_signature" data-smartmail="gmail_signature"><div dir="rtl"><a href="https://netanel.ml" target="_blank"><img width="200" height="51" src="https://ci3.googleusercontent.com/mail-sig/AIorK4ykFjL1iagUdlm0jcadJlaq1KyDf5c3YeE3nLFugFyn69aRMAcHd2OKO51XtKIvhzIdbuX81XE"></a></div></div></div>