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<div class="sphx-glr-example-title section" id="basic-nilearn-example-manipulating-and-looking-at-data">
<span id="sphx-glr-auto-examples-plot-nilearn-101-py"></span><h1><span class="section-number">9.1.2. </span>Basic nilearn example: manipulating and looking at data<a class="headerlink" href="#basic-nilearn-example-manipulating-and-looking-at-data" title="Permalink to this headline">¶</a></h1>
<p>A simple example showing how to load an existing Nifti file and use
basic nilearn functionalities.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="c1"># Let us use a Nifti file that is shipped with nilearn</span>
<span class="kn">from</span> <span class="nn">nilearn.datasets</span> <span class="kn">import</span> <a href="https://docs.python.org/3.8/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">MNI152_FILE_PATH</span></a>
<span class="c1"># Note that the variable MNI152_FILE_PATH is just a path to a Nifti file</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">'Path to MNI152 template: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <a href="https://docs.python.org/3.8/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">MNI152_FILE_PATH</span></a><span class="p">)</span>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Path to MNI152 template: '/home/nicolas/GitRepos/nilearn-fork/nilearn/datasets/data/mni_icbm152_t1_tal_nlin_sym_09a_converted.nii.gz'
</pre></div>
</div>
<div class="section" id="a-first-step-looking-at-our-data">
<h2><span class="section-number">9.1.2.1. </span>A first step: looking at our data<a class="headerlink" href="#a-first-step-looking-at-our-data" title="Permalink to this headline">¶</a></h2>
<p>Let’s quickly plot this file:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">nilearn</span> <span class="kn">import</span> <span class="n">plotting</span>
<a href="../modules/generated/nilearn.plotting.plot_img.html#nilearn.plotting.plot_img" title="nilearn.plotting.plot_img" class="sphx-glr-backref-module-nilearn-plotting sphx-glr-backref-type-py-function"><span class="n">plotting</span><span class="o">.</span><span class="n">plot_img</span></a><span class="p">(</span><a href="https://docs.python.org/3.8/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">MNI152_FILE_PATH</span></a><span class="p">)</span>
</pre></div>
</div>
<img src="../_images/sphx_glr_plot_nilearn_101_001.png" srcset="../_images/sphx_glr_plot_nilearn_101_001.png" alt="plot nilearn 101" class = "sphx-glr-single-img"/><p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f9e050bbee0>
</pre></div>
</div>
<p>This is not a very pretty plot. We just used the simplest possible
code. There is a whole <a class="reference internal" href="../plotting/index.html#plotting"><span class="std std-ref">section of the documentation</span></a>
on making prettier code.</p>
<p><strong>Exercise</strong>: Try plotting one of your own files. In the above,
MNI152_FILE_PATH is nothing more than a string with a path pointing to
a nifti image. You can replace it with a string pointing to a file on
your disk. Note that it should be a 3D volume, and not a 4D volume.</p>
</div>
<div class="section" id="simple-image-manipulation-smoothing">
<h2><span class="section-number">9.1.2.2. </span>Simple image manipulation: smoothing<a class="headerlink" href="#simple-image-manipulation-smoothing" title="Permalink to this headline">¶</a></h2>
<p>Let’s use an image-smoothing function from nilearn:
<a class="reference internal" href="../modules/generated/nilearn.image.smooth_img.html#nilearn.image.smooth_img" title="nilearn.image.smooth_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">nilearn.image.smooth_img</span></code></a></p>
<p>Functions containing ‘img’ can take either a filename or an image as input.</p>
<p>Here we give as inputs the image filename and the smoothing value in mm</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">nilearn</span> <span class="kn">import</span> <span class="n">image</span>
<a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">smooth_anat_img</span></a> <span class="o">=</span> <a href="../modules/generated/nilearn.image.smooth_img.html#nilearn.image.smooth_img" title="nilearn.image.smooth_img" class="sphx-glr-backref-module-nilearn-image sphx-glr-backref-type-py-function"><span class="n">image</span><span class="o">.</span><span class="n">smooth_img</span></a><span class="p">(</span><a href="https://docs.python.org/3.8/library/stdtypes.html#str" title="builtins.str" class="sphx-glr-backref-module-builtins sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">MNI152_FILE_PATH</span></a><span class="p">,</span> <span class="n">fwhm</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<span class="c1"># While we are giving a file name as input, the function returns</span>
<span class="c1"># an in-memory object:</span>
<a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">smooth_anat_img</span></a>
</pre></div>
</div>
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><nibabel.nifti1.Nifti1Image object at 0x7f9e0528ad30>
</pre></div>
</div>
<p>This is an in-memory object. We can pass it to nilearn function, for
instance to look at it</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="../modules/generated/nilearn.plotting.plot_img.html#nilearn.plotting.plot_img" title="nilearn.plotting.plot_img" class="sphx-glr-backref-module-nilearn-plotting sphx-glr-backref-type-py-function"><span class="n">plotting</span><span class="o">.</span><span class="n">plot_img</span></a><span class="p">(</span><a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">smooth_anat_img</span></a><span class="p">)</span>
</pre></div>
</div>
<img src="../_images/sphx_glr_plot_nilearn_101_002.png" srcset="../_images/sphx_glr_plot_nilearn_101_002.png" alt="plot nilearn 101" class = "sphx-glr-single-img"/><p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f9e120f9640>
</pre></div>
</div>
<p>We could also pass it to the smoothing function</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">more_smooth_anat_img</span></a> <span class="o">=</span> <a href="../modules/generated/nilearn.image.smooth_img.html#nilearn.image.smooth_img" title="nilearn.image.smooth_img" class="sphx-glr-backref-module-nilearn-image sphx-glr-backref-type-py-function"><span class="n">image</span><span class="o">.</span><span class="n">smooth_img</span></a><span class="p">(</span><a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">smooth_anat_img</span></a><span class="p">,</span> <span class="n">fwhm</span><span class="o">=</span><span class="mi">3</span><span class="p">)</span>
<a href="../modules/generated/nilearn.plotting.plot_img.html#nilearn.plotting.plot_img" title="nilearn.plotting.plot_img" class="sphx-glr-backref-module-nilearn-plotting sphx-glr-backref-type-py-function"><span class="n">plotting</span><span class="o">.</span><span class="n">plot_img</span></a><span class="p">(</span><a href="https://nipy.org/nibabel/reference/nibabel.nifti1.html#nibabel.nifti1.Nifti1Image" title="nibabel.nifti1.Nifti1Image" class="sphx-glr-backref-module-nibabel-nifti1 sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">more_smooth_anat_img</span></a><span class="p">)</span>
</pre></div>
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<img src="../_images/sphx_glr_plot_nilearn_101_003.png" srcset="../_images/sphx_glr_plot_nilearn_101_003.png" alt="plot nilearn 101" class = "sphx-glr-single-img"/><p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span><nilearn.plotting.displays._slicers.OrthoSlicer object at 0x7f9e1206ea60>
</pre></div>
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<div class="section" id="saving-results-to-a-file">
<h2><span class="section-number">9.1.2.3. </span>Saving results to a file<a class="headerlink" href="#saving-results-to-a-file" title="Permalink to this headline">¶</a></h2>
<p>We can save any in-memory object as follows:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="https://nipy.org/nibabel/reference/nibabel.filebasedimages.html#nibabel.filebasedimages.FileBasedImage.to_filename" title="nibabel.filebasedimages.FileBasedImage.to_filename" class="sphx-glr-backref-module-nibabel-filebasedimages sphx-glr-backref-type-py-method"><span class="n">more_smooth_anat_img</span><span class="o">.</span><span class="n">to_filename</span></a><span class="p">(</span><span class="s1">'more_smooth_anat_img.nii.gz'</span><span class="p">)</span>
</pre></div>
</div>
<p>Finally, calling plotting.show() is necessary to display the figure
when running as a script outside IPython</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><a href="../modules/generated/nilearn.plotting.show.html#nilearn.plotting.show" title="nilearn.plotting.show" class="sphx-glr-backref-module-nilearn-plotting sphx-glr-backref-type-py-function"><span class="n">plotting</span><span class="o">.</span><span class="n">show</span></a><span class="p">()</span>
</pre></div>
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<div class="line"><br /></div>
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<hr class="docutils" />
<p>To recap, all the nilearn tools can take data as filenames or in-memory
objects, and return brain volumes as in-memory objects. These can be
passed on to other nilearn tools, or saved to disk.</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 5.474 seconds)</p>
<p><strong>Estimated memory usage:</strong> 228 MB</p>
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<p><a class="reference download internal" download="" href="../_downloads/515c7aae4e0178b0605ddd2599523d24/plot_nilearn_101.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">plot_nilearn_101.py</span></code></a></p>
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<p><a class="reference download internal" download="" href="../_downloads/503db59afd7f4fb53abc013ffd9f19a9/plot_nilearn_101.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">plot_nilearn_101.ipynb</span></code></a></p>
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<h4> Giving credit </h4>
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<li><p>Please consider <a href="../authors.html#citing">citing the
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<h3><a href="../index.html">Table of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">9.1.2. Basic nilearn example: manipulating and looking at data</a><ul>
<li><a class="reference internal" href="#a-first-step-looking-at-our-data">9.1.2.1. A first step: looking at our data</a></li>
<li><a class="reference internal" href="#simple-image-manipulation-smoothing">9.1.2.2. Simple image manipulation: smoothing</a></li>
<li><a class="reference internal" href="#saving-results-to-a-file">9.1.2.3. Saving results to a file</a></li>
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