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<h2>Statistics for NeuroImaging in Python</h2>
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<div class="section" id="id1">
<h1>0.5.0<a class="headerlink" href="#id1" title="Permalink to this headline">¶</a></h1>
<p><strong>Released November 2018</strong></p>
<div class="section" id="new">
<h2>NEW<a class="headerlink" href="#new" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p><a class="reference internal" href="../plotting/index.html#interactive-plotting"><span class="std std-ref">interactive plotting functions</span></a>, eg for use in a notebook.</p></li>
<li><p>New functions <a class="reference internal" href="../modules/generated/nilearn.plotting.view_surf.html#nilearn.plotting.view_surf" title="nilearn.plotting.view_surf"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_surf</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img_on_surf.html#nilearn.plotting.view_img_on_surf" title="nilearn.plotting.view_img_on_surf"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img_on_surf</span></code></a> for interactive visualization of maps on the cortical surface in a web browser.</p></li>
<li><p>New functions <a class="reference internal" href="../modules/generated/nilearn.plotting.view_connectome.html#nilearn.plotting.view_connectome" title="nilearn.plotting.view_connectome"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_connectome</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.plotting.view_markers.html#nilearn.plotting.view_markers" title="nilearn.plotting.view_markers"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_markers</span></code></a> for interactive visualization of connectomes and seed locations in 3D.</p></li>
<li><p>New function <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> for interactive visualization of volumes with 3 orthogonal cuts.</p></li>
</ul>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> was <code class="docutils literal notranslate"><span class="pre">nilearn.plotting.view_stat_map</span></code> in alpha and beta releases.</p>
</div>
<ul class="simple">
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.find_parcellation_cut_coords.html#nilearn.plotting.find_parcellation_cut_coords" title="nilearn.plotting.find_parcellation_cut_coords"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_parcellation_cut_coords</span></code></a> for extraction of coordinates on brain parcellations denoted as labels.</p></li>
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.find_probabilistic_atlas_cut_coords.html#nilearn.plotting.find_probabilistic_atlas_cut_coords" title="nilearn.plotting.find_probabilistic_atlas_cut_coords"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_probabilistic_atlas_cut_coords</span></code></a> for extraction of coordinates on brain probabilistic maps.</p></li>
</ul>
<dl class="simple">
<dt><strong>Minimum supported versions of packages have been bumped up.</strong></dt><dd><ul class="simple">
<li><p><code class="docutils literal notranslate"><span class="pre">scikit-learn</span> <span class="pre">--</span> <span class="pre">v0.18</span></code>.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">scipy</span> <span class="pre">--</span> <span class="pre">v0.17</span></code>.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pandas</span> <span class="pre">--</span> <span class="pre">v0.18</span></code>.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">numpy</span> <span class="pre">--</span> <span class="pre">v1.11</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">matplotlib</span> <span class="pre">--</span> <span class="pre">v1.5.1</span></code></p></li>
</ul>
</dd>
<dt><strong>Nilearn Python2 support is being removed in the near future.</strong></dt><dd><p>Users with a Python2 environment will be warned
at their first Nilearn import.</p>
</dd>
</dl>
<p><strong>Additional dataset downloaders for examples and tutorials.</strong></p>
<ul class="simple">
<li><p><a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_surf_fsaverage.html#nilearn.datasets.fetch_surf_fsaverage" title="nilearn.datasets.fetch_surf_fsaverage"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_surf_fsaverage</span></code></a>.</p></li>
<li><p><a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_atlas_pauli_2017.html#nilearn.datasets.fetch_atlas_pauli_2017" title="nilearn.datasets.fetch_atlas_pauli_2017"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_atlas_pauli_2017</span></code></a>.</p></li>
<li><p><a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_neurovault_auditory_computation_task.html#nilearn.datasets.fetch_neurovault_auditory_computation_task" title="nilearn.datasets.fetch_neurovault_auditory_computation_task"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_neurovault_auditory_computation_task</span></code></a>.</p></li>
<li><p><a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_neurovault_motor_task.html#nilearn.datasets.fetch_neurovault_motor_task" title="nilearn.datasets.fetch_neurovault_motor_task"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_neurovault_motor_task</span></code></a>.</p></li>
</ul>
</div>
<div class="section" id="enhancements">
<h2>ENHANCEMENTS<a class="headerlink" href="#enhancements" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> now accepts a mask to restrict the cleaning of the image, reducing memory load and computation time.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">NiftiMaskers</span></code> now have a <code class="docutils literal notranslate"><span class="pre">dtype</span></code> parameter, by default keeping the same data type as the input data.</p></li>
<li><p>Displays by plotting functions can now add a scale bar (see <a class="reference internal" href="../plotting/index.html#plotting"><span class="std std-ref">Plotting brain images</span></a>).</p></li>
<li><p>Lots of other fixes in documentation and examples.</p></li>
<li><p>A cleaner layout and improved navigation for the website, with a better introduction.</p></li>
<li><p>Dataset fetchers are now more reliable, less verbose.</p></li>
<li><p>The <a class="reference internal" href="../modules/generated/nilearn.decoding.SearchLight.html#nilearn.decoding.SearchLight.fit" title="nilearn.decoding.SearchLight.fit"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit</span></code></a> method now accepts 4D niimgs.</p></li>
<li><p>Anaconda link in the installation documentation updated.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">Scipy</span></code> is listed as a dependency for Nilearn installation.</p></li>
</ul>
</div>
<div class="section" id="changes">
<h2>Changes<a class="headerlink" href="#changes" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Default value of <code class="docutils literal notranslate"><span class="pre">t_r</span></code> in functions <a class="reference internal" href="../modules/generated/nilearn.signal.clean.html#nilearn.signal.clean" title="nilearn.signal.clean"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> is <code class="docutils literal notranslate"><span class="pre">None</span></code> and cannot be <code class="docutils literal notranslate"><span class="pre">None</span></code> if <code class="docutils literal notranslate"><span class="pre">low_pass</span></code> or <code class="docutils literal notranslate"><span class="pre">high_pass</span></code> is specified.</p></li>
</ul>
<p>Lots of changes and improvements. Detailed change list for each release follows.</p>
</div>
</div>
<div class="section" id="rc">
<h1>0.5.0 rc<a class="headerlink" href="#rc" title="Permalink to this headline">¶</a></h1>
<div class="section" id="highlights">
<h2>Highlights<a class="headerlink" href="#highlights" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> (formerly <code class="docutils literal notranslate"><span class="pre">nilearn.plotting.view_stat_map</span></code> in Nilearn <code class="docutils literal notranslate"><span class="pre">0.5.0</span></code> pre-release versions) generates significantly smaller notebooks and HTML pages while getting a more consistent look and feel with Nilearn’s plotting functions. Huge shout out to <a class="reference external" href="https://github.com/pbellec">Pierre Bellec</a> (pbellec) for making a great feature awesome and for sportingly accommodating all our feedback.</p></li>
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> now accepts a mask to restrict the cleaning of the image. This approach can help to reduce the memory load and computation time. Big thanks to <a class="reference external" href="https://github.com/miykael">Michael Notter</a> (miykael).</p></li>
</ul>
</div>
<div class="section" id="id2">
<h2>Enhancements<a class="headerlink" href="#id2" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> is now using the <code class="docutils literal notranslate"><span class="pre">brainsprite.js</span></code> library, which results in much smaller notebooks or html pages. The interactive viewer also looks more similar to the plots generated by function <a class="reference internal" href="../modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map" title="nilearn.plotting.plot_stat_map"><code class="xref py py-func docutils literal notranslate"><span class="pre">plot_stat_map</span></code></a>, and most parameters found in <a class="reference internal" href="../modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map" title="nilearn.plotting.plot_stat_map"><code class="xref py py-func docutils literal notranslate"><span class="pre">plot_stat_map</span></code></a> are now supported in <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a>.</p></li>
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> now accepts a mask to restrict the cleaning of the image. This approach can help to reduce the memory load and computation time.</p></li>
<li><p>Method <a class="reference internal" href="../modules/generated/nilearn.decoding.SpaceNetRegressor.html#nilearn.decoding.SpaceNetRegressor.fit" title="nilearn.decoding.SpaceNetRegressor.fit"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit</span></code></a> raises a meaningful error in regression tasks if the target Y contains all 1s.</p></li>
</ul>
</div>
<div class="section" id="id3">
<h2>Changes<a class="headerlink" href="#id3" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Default value of <code class="docutils literal notranslate"><span class="pre">t_r</span></code> in functions <a class="reference internal" href="../modules/generated/nilearn.signal.clean.html#nilearn.signal.clean" title="nilearn.signal.clean"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> is changed from 2.5 to <code class="docutils literal notranslate"><span class="pre">None</span></code>. If <code class="docutils literal notranslate"><span class="pre">low_pass</span></code> or <code class="docutils literal notranslate"><span class="pre">high_pass</span></code> is specified, then <code class="docutils literal notranslate"><span class="pre">t_r</span></code> needs to be specified as well otherwise it will raise an error.</p></li>
<li><p>Order of filters in functions <a class="reference internal" href="../modules/generated/nilearn.signal.clean.html#nilearn.signal.clean" title="nilearn.signal.clean"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> has changed to detrend, low- and high-pass filter, remove confounds and standardize. To ensure orthogonality between temporal filter and confound removal, an additional temporal filter will be applied on the confounds before removing them. This is according to Lindquist et al. (2018).</p></li>
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.image.clean_img.html#nilearn.image.clean_img" title="nilearn.image.clean_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">clean_img</span></code></a> now accepts a mask to restrict the cleaning of the image. This approach can help to reduce the memory load and computation time.</p></li>
<li><p>Function <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> is now using the <code class="docutils literal notranslate"><span class="pre">brainsprite.js</span></code> library, which results in much smaller notebooks or html pages. The interactive viewer also looks more similar to the plots generated by <a class="reference internal" href="../modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map" title="nilearn.plotting.plot_stat_map"><code class="xref py py-func docutils literal notranslate"><span class="pre">plot_stat_map</span></code></a>, and most parameters found in <a class="reference internal" href="../modules/generated/nilearn.plotting.plot_stat_map.html#nilearn.plotting.plot_stat_map" title="nilearn.plotting.plot_stat_map"><code class="xref py py-func docutils literal notranslate"><span class="pre">plot_stat_map</span></code></a> are now supported in <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a>.</p></li>
</ul>
</div>
<div class="section" id="contributors">
<h2>Contributors<a class="headerlink" href="#contributors" title="Permalink to this headline">¶</a></h2>
<p>The following people contributed to this release:</p>
<blockquote>
<div><ul class="simple">
<li><p><a class="reference external" href="http://gael-varoquaux.info/">Gael Varoquaux</a> (15)</p></li>
<li><p><a class="reference external" href="https://github.com/pbellec">Pierre Bellec</a> (114)</p></li>
<li><p><a class="reference external" href="https://github.com/miykael">Michael Notter</a> (30)</p></li>
<li><p><a class="reference external" href="https://github.com/kchawla-pi">Kshitij Chawla</a> (28)</p></li>
<li><p><a class="reference external" href="https://github.com/KamalakerDadi">Kamalakar Reddy Daddy</a> (4)</p></li>
<li><p>himanshupathak21061998 (4)</p></li>
<li><p><a class="reference external" href="http://chymera.eu/">Christian Horea</a> (1)</p></li>
<li><p><a class="reference external" href="https://jeromedockes.github.io/">Jerome Dockes</a> (7)</p></li>
</ul>
</div></blockquote>
</div>
</div>
<div class="section" id="beta">
<h1>0.5.0 beta<a class="headerlink" href="#beta" title="Permalink to this headline">¶</a></h1>
<p><strong>Released October 2018</strong></p>
<div class="section" id="id4">
<h2>Highlights<a class="headerlink" href="#id4" title="Permalink to this headline">¶</a></h2>
<p><strong>Nilearn Python2 support is being removed in the near future.
Users with a Python2 environment will be warned at their first Nilearn import.</strong></p>
</div>
<div class="section" id="id5">
<h2>Enhancements<a class="headerlink" href="#id5" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Displays created by plotting functions can now add a scale bar to indicate the size in mm or cm (see <a class="reference internal" href="../plotting/index.html#plotting"><span class="std std-ref">Plotting brain images</span></a>) (by <a class="reference external" href="https://github.com/oesteban">Oscar Esteban</a>).</p></li>
<li><p>Colorbars in plotting functions now have a middle gray background suitable for use with custom colormaps with a non-unity alpha channel (by <a class="reference external" href="https://larsoner.com/">Eric Larson</a>).</p></li>
</ul>
<p>Loads of fixes and quality of life improvements</p>
<ul class="simple">
<li><p>A cleaner layout and improved navigation for the website, with a better introduction.</p></li>
<li><p>Less warnings and verbosity while using certain functions and during dataset downloads.</p></li>
<li><p>Improved backend for the dataset fetchers means more reliable dataset downloads.</p></li>
<li><p>Some datasets, such as the ICBM, are now compressed to take up less disk space.</p></li>
</ul>
</div>
<div class="section" id="fixes">
<h2>Fixes<a class="headerlink" href="#fixes" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Method <a class="reference internal" href="../modules/generated/nilearn.decoding.SearchLight.html#nilearn.decoding.SearchLight.fit" title="nilearn.decoding.SearchLight.fit"><code class="xref py py-meth docutils literal notranslate"><span class="pre">decoding.SearchLight.fit</span></code></a> now accepts 4D niimgs (by <a class="reference external" href="https://danjgale.github.io/">Dan Gale</a>).</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">plotting.view_markers.open_in_browser()</span></code> in <code class="docutils literal notranslate"><span class="pre">js_plotting_utils</span></code> fixed.</p></li>
<li><p>Brainomics dataset has been replaced in several examples.</p></li>
<li><p>Lots of other fixes in documentation and examples.</p></li>
</ul>
</div>
<div class="section" id="id6">
<h2>Changes<a class="headerlink" href="#id6" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>In function <a class="reference internal" href="../modules/generated/nilearn.regions.img_to_signals_labels.html#nilearn.regions.img_to_signals_labels" title="nilearn.regions.img_to_signals_labels"><code class="xref py py-func docutils literal notranslate"><span class="pre">img_to_signals_labels</span></code></a>, the <code class="docutils literal notranslate"><span class="pre">See</span> <span class="pre">Also</span></code> section in documentation now also points to <a class="reference internal" href="../modules/generated/nilearn.maskers.NiftiLabelsMasker.html#nilearn.maskers.NiftiLabelsMasker" title="nilearn.maskers.NiftiLabelsMasker"><code class="xref py py-class docutils literal notranslate"><span class="pre">NiftiLabelsMasker</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.maskers.NiftiMapsMasker.html#nilearn.maskers.NiftiMapsMasker" title="nilearn.maskers.NiftiMapsMasker"><code class="xref py py-class docutils literal notranslate"><span class="pre">NiftiMapsMasker</span></code></a>.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">Scipy</span></code> is listed as a dependency for Nilearn installation.</p></li>
<li><p>Anaconda link in the installation documentation updated.</p></li>
</ul>
</div>
<div class="section" id="id7">
<h2>Contributors<a class="headerlink" href="#id7" title="Permalink to this headline">¶</a></h2>
<p>The following people contributed to this release:</p>
<blockquote>
<div><ul class="simple">
<li><p><a class="reference external" href="http://gael-varoquaux.info/">Gael Varoquaux</a> (58)</p></li>
<li><p><a class="reference external" href="https://github.com/kchawla-pi">Kshitij Chawla</a> (115)</p></li>
<li><p><a class="reference external" href="https://jeromedockes.github.io/">Jerome Dockes</a> (15)</p></li>
<li><p><a class="reference external" href="https://github.com/oesteban">Oscar Esteban</a> (14)</p></li>
<li><p><a class="reference external" href="https://larsoner.com/">Eric Larson</a> (10)</p></li>
<li><p><a class="reference external" href="https://github.com/KamalakerDadi">Kamalakar Reddy Daddy</a> (6)</p></li>
<li><p><a class="reference external" href="https://pages.saclay.inria.fr/bertrand.thirion/">Bertrand Thirion</a> (3)</p></li>
<li><p><a class="reference external" href="https://github.com/aabadie">Alexandre Abadie</a> (5)</p></li>
<li><p><a class="reference external" href="https://github.com/souravsingh">Sourav Singh</a> (4)</p></li>
<li><p><a class="reference external" href="https://github.com/cancan101">Alex Rothberg</a> (3)</p></li>
<li><p>AnaLu (3)</p></li>
<li><p><a class="reference external" href="https://github.com/demianw">Demian Wassermann</a> (3)</p></li>
<li><p><a class="reference external" href="http://chymera.eu/">Christian Horea</a> (3)</p></li>
<li><p><a class="reference external" href="http://jgors.com/">Jason Gors</a> (3)</p></li>
<li><p>Jean Remi King (3)</p></li>
<li><p>MADHYASTHA Meghana (3)</p></li>
<li><p><a class="reference external" href="https://github.com/SRSteinkamp">Simon Steinkamp</a> (3)</p></li>
<li><p><a class="reference external" href="https://github.com/ja-che">Jerome-Alexis Chevalier</a> (3)</p></li>
<li><p><a class="reference external" href="https://github.com/salma1601">Salma Bougacha</a> (3)</p></li>
<li><p>sfvnMAC (3)</p></li>
<li><p>Akshay (2)</p></li>
<li><p><a class="reference external" href="https://github.com/dangom">Daniel Gomez</a> (2)</p></li>
<li><p><a class="reference external" href="https://glemaitre.github.io/">Guillaume Lemaitre</a> (2)</p></li>
<li><p><a class="reference external" href="https://github.com/pbellec">Pierre Bellec</a> (2)</p></li>
<li><p><a class="reference external" href="http://arokem.org/">Ariel Rokem</a> (2)</p></li>
<li><p>erramuzpe (2)</p></li>
<li><p>foucault (2)</p></li>
<li><p>jehane (2)</p></li>
<li><p>Sylvain LANNUZEL (1)</p></li>
<li><p>Aki Nikolaidis (1)</p></li>
<li><p>Christophe Bedetti (1)</p></li>
<li><p><a class="reference external" href="https://danjgale.github.io/">Dan Gale</a> (1)</p></li>
<li><p>Dillon Plunkett (1)</p></li>
<li><p><a class="reference external" href="https://github.com/DimitriPapadopoulos">Dimitri Papadopoulos Orfanos</a> (1)</p></li>
<li><p>Greg Operto (1)</p></li>
<li><p>Ivan Gonzalez (1)</p></li>
<li><p>Yaroslav Halchenko (1)</p></li>
<li><p>dtyulman (1)</p></li>
</ul>
</div></blockquote>
</div>
</div>
<div class="section" id="alpha">
<h1>0.5.0 alpha<a class="headerlink" href="#alpha" title="Permalink to this headline">¶</a></h1>
<p><strong>Released August 2018</strong></p>
<p>This is an alpha release: to download it, you need to explicitly ask for
the version number:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="n">nilearn</span><span class="o">==</span><span class="mf">0.5</span><span class="o">.</span><span class="mi">0</span><span class="n">a0</span>
</pre></div>
</div>
<div class="section" id="id8">
<h2>Highlights<a class="headerlink" href="#id8" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><dl class="simple">
<dt><strong>Minimum supported versions of packages have been bumped up.</strong></dt><dd><ul>
<li><p><code class="docutils literal notranslate"><span class="pre">scikit-learn</span> <span class="pre">--</span> <span class="pre">v0.18</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">scipy</span> <span class="pre">--</span> <span class="pre">v0.17</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">pandas</span> <span class="pre">--</span> <span class="pre">v0.18</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">numpy</span> <span class="pre">--</span> <span class="pre">v1.11</span></code></p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">matplotlib</span> <span class="pre">--</span> <span class="pre">v1.5.1</span></code></p></li>
</ul>
</dd>
</dl>
</li>
<li><p>New <a class="reference internal" href="../plotting/index.html#interactive-plotting"><span class="std std-ref">interactive plotting functions</span></a>, eg for use in a notebook.</p></li>
</ul>
</div>
<div class="section" id="id9">
<h2>Enhancements<a class="headerlink" href="#id9" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>All <code class="docutils literal notranslate"><span class="pre">NiftiMaskers</span></code> now have a <code class="docutils literal notranslate"><span class="pre">dtype</span></code> argument. For now the default behaviour is to keep the same data type as the input data.</p></li>
<li><p>Displays created by plotting functions can now add a scale bar to indicate the size in mm or cm (see <a class="reference internal" href="../plotting/index.html#plotting"><span class="std std-ref">Plotting brain images</span></a>) (by <a class="reference external" href="https://github.com/oesteban">Oscar Esteban</a>).</p></li>
<li><p>New functions <a class="reference internal" href="../modules/generated/nilearn.plotting.view_surf.html#nilearn.plotting.view_surf" title="nilearn.plotting.view_surf"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_surf</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.plotting.view_surf.html#nilearn.plotting.view_surf" title="nilearn.plotting.view_surf"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_surf</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img_on_surf.html#nilearn.plotting.view_img_on_surf" title="nilearn.plotting.view_img_on_surf"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img_on_surf</span></code></a> for interactive visualization of maps on the cortical surface in a web browser.</p></li>
<li><p>New functions <a class="reference internal" href="../modules/generated/nilearn.plotting.view_connectome.html#nilearn.plotting.view_connectome" title="nilearn.plotting.view_connectome"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_connectome</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.plotting.view_markers.html#nilearn.plotting.view_markers" title="nilearn.plotting.view_markers"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_markers</span></code></a> to visualize connectomes and seed locations in 3D</p></li>
<li><p>New function <code class="docutils literal notranslate"><span class="pre">nilearn.plotting.view_stat_map</span></code> (renamed to <a class="reference internal" href="../modules/generated/nilearn.plotting.view_img.html#nilearn.plotting.view_img" title="nilearn.plotting.view_img"><code class="xref py py-func docutils literal notranslate"><span class="pre">view_img</span></code></a> in stable release) for interactive visualization of volumes with 3 orthogonal cuts.</p></li>
<li><p>New function <a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_surf_fsaverage.html#nilearn.datasets.fetch_surf_fsaverage" title="nilearn.datasets.fetch_surf_fsaverage"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_surf_fsaverage</span></code></a> to download either <code class="docutils literal notranslate"><span class="pre">fsaverage</span></code> or <code class="docutils literal notranslate"><span class="pre">fsaverage5</span></code> (Freesurfer cortical meshes).</p></li>
<li><p>New function <a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_atlas_pauli_2017.html#nilearn.datasets.fetch_atlas_pauli_2017" title="nilearn.datasets.fetch_atlas_pauli_2017"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_atlas_pauli_2017</span></code></a> to download a recent subcortical neuroimaging atlas.</p></li>
<li><p>New function <a class="reference internal" href="../modules/generated/nilearn.plotting.find_parcellation_cut_coords.html#nilearn.plotting.find_parcellation_cut_coords" title="nilearn.plotting.find_parcellation_cut_coords"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_parcellation_cut_coords</span></code></a> for extraction of coordinates on brain parcellations denoted as labels.</p></li>
<li><p>New function <a class="reference internal" href="../modules/generated/nilearn.plotting.find_probabilistic_atlas_cut_coords.html#nilearn.plotting.find_probabilistic_atlas_cut_coords" title="nilearn.plotting.find_probabilistic_atlas_cut_coords"><code class="xref py py-func docutils literal notranslate"><span class="pre">find_probabilistic_atlas_cut_coords</span></code></a> for extraction of coordinates on brain probabilistic maps.</p></li>
<li><p>New functions <a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_neurovault_auditory_computation_task.html#nilearn.datasets.fetch_neurovault_auditory_computation_task" title="nilearn.datasets.fetch_neurovault_auditory_computation_task"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_neurovault_auditory_computation_task</span></code></a> and <a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_neurovault_motor_task.html#nilearn.datasets.fetch_neurovault_motor_task" title="nilearn.datasets.fetch_neurovault_motor_task"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_neurovault_motor_task</span></code></a> for simple example data.</p></li>
</ul>
</div>
<div class="section" id="id10">
<h2>Changes<a class="headerlink" href="#id10" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><p>Function <code class="docutils literal notranslate"><span class="pre">nilearn.datasets.fetch_surf_fsaverage5</span></code> is deprecated and will be removed in a future release. Use function <a class="reference internal" href="../modules/generated/nilearn.datasets.fetch_surf_fsaverage.html#nilearn.datasets.fetch_surf_fsaverage" title="nilearn.datasets.fetch_surf_fsaverage"><code class="xref py py-func docutils literal notranslate"><span class="pre">fetch_surf_fsaverage</span></code></a>, with the parameter <code class="docutils literal notranslate"><span class="pre">mesh="fsaverage5"</span></code> (the default) instead.</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">fsaverage5</span></code> surface data files are now shipped directly with Nilearn (see <a class="reference external" href="https://github.com/nilearn/nilearn/issues/1705">#1705</a> for discussion).</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">sklearn.cross_validation</span></code> and <code class="docutils literal notranslate"><span class="pre">sklearn.grid_search</span></code> have been replaced by <code class="docutils literal notranslate"><span class="pre">sklearn.model_selection</span></code> in all the examples.</p></li>
<li><p>Colorbars in plotting functions now have a middle gray background suitable for use with custom colormaps with a non-unity alpha channel.</p></li>
</ul>
</div>
<div class="section" id="id11">
<h2>Contributors<a class="headerlink" href="#id11" title="Permalink to this headline">¶</a></h2>
<p>The following people contributed to this release:</p>
<blockquote>
<div><ul class="simple">
<li><p><a class="reference external" href="http://gael-varoquaux.info/">Gael Varoquaux</a> (49)</p></li>
<li><p><a class="reference external" href="https://jeromedockes.github.io/">Jerome Dockes</a> (180)</p></li>
<li><p><a class="reference external" href="https://github.com/kchawla-pi">Kshitij Chawla</a> (57)</p></li>
<li><p><a class="reference external" href="https://github.com/SylvainLan">Sylvain Lan</a> (38)</p></li>
<li><p><a class="reference external" href="https://github.com/KamalakerDadi">Kamalakar Reddy Daddy</a> (36)</p></li>
<li><p><a class="reference external" href="https://github.com/Gilles86">Gilles de Hollander</a> (10)</p></li>
<li><p><a class="reference external" href="https://pages.saclay.inria.fr/bertrand.thirion/">Bertrand Thirion</a> (4)</p></li>
<li><p>MENUET Romuald (4)</p></li>
<li><p><a class="reference external" href="https://github.com/mjboos">Moritz Boos</a> (3)</p></li>
<li><p><a class="reference external" href="https://peerherholz.github.io/">Peer Herholz</a> (1)</p></li>
<li><p><a class="reference external" href="https://github.com/pbellec">Pierre Bellec</a> (1)</p></li>
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<h3><a href="../index.html">Table of Contents</a></h3>
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<li><a class="reference internal" href="#">0.5.0</a><ul>
<li><a class="reference internal" href="#new">NEW</a></li>
<li><a class="reference internal" href="#enhancements">ENHANCEMENTS</a></li>
<li><a class="reference internal" href="#changes">Changes</a></li>
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<li><a class="reference internal" href="#rc">0.5.0 rc</a><ul>
<li><a class="reference internal" href="#highlights">Highlights</a></li>
<li><a class="reference internal" href="#id2">Enhancements</a></li>
<li><a class="reference internal" href="#id3">Changes</a></li>
<li><a class="reference internal" href="#contributors">Contributors</a></li>
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<li><a class="reference internal" href="#beta">0.5.0 beta</a><ul>
<li><a class="reference internal" href="#id4">Highlights</a></li>
<li><a class="reference internal" href="#id5">Enhancements</a></li>
<li><a class="reference internal" href="#fixes">Fixes</a></li>
<li><a class="reference internal" href="#id6">Changes</a></li>
<li><a class="reference internal" href="#id7">Contributors</a></li>
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<li><a class="reference internal" href="#alpha">0.5.0 alpha</a><ul>
<li><a class="reference internal" href="#id8">Highlights</a></li>
<li><a class="reference internal" href="#id9">Enhancements</a></li>
<li><a class="reference internal" href="#id10">Changes</a></li>
<li><a class="reference internal" href="#id11">Contributors</a></li>
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