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Expand Up @@ -275,7 +275,7 @@ <h3>Plotting Periodic Topographies<a class="headerlink" href="#plotting-periodic
</div>
<img alt="plot mne example" class="sphx-glr-single-img" src="../../_images/sphx_glr_plot_mne_example_002.png" />
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>(&lt;matplotlib.image.AxesImage object at 0x7fc78f66b130&gt;, None)
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>(&lt;matplotlib.image.AxesImage object at 0x7f64454cc130&gt;, None)
</pre></div>
</div>
<p>And there we have it, our first topography of parameterized spectra, showing alpha power!</p>
Expand Down Expand Up @@ -352,7 +352,7 @@ <h3>Plotting Aperiodic Topographies<a class="headerlink" href="#plotting-aperiod
</div>
<img alt="plot mne example" class="sphx-glr-single-img" src="../../_images/sphx_glr_plot_mne_example_005.png" />
<p class="sphx-glr-script-out">Out:</p>
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>(&lt;matplotlib.image.AxesImage object at 0x7fc78f4225e0&gt;, None)
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>(&lt;matplotlib.image.AxesImage object at 0x7f64452825e0&gt;, None)
</pre></div>
</div>
<p>In the topography above, we can see that there is a fair amount of variation
Expand All @@ -375,7 +375,7 @@ <h3>Plotting Aperiodic Topographies<a class="headerlink" href="#plotting-aperiod
<h2>Conclusion<a class="headerlink" href="#conclusion" title="Permalink to this headline"></a></h2>
<p>In this example, we have seen how to apply power spectrum models to data that is
managed and processed with MNE.</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.761 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.796 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-analyses-plot-mne-example-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/208ddf4708879eabf6a6f4aae1ab846a/plot_mne_example.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_mne_example.py</span></code></a></p>
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Expand Up @@ -112,7 +112,7 @@

<div class="section" id="computation-times">
<span id="sphx-glr-auto-examples-analyses-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline"></a></h1>
<p><strong>00:01.761</strong> total execution time for <strong>auto_examples_analyses</strong> files:</p>
<p><strong>00:01.796</strong> total execution time for <strong>auto_examples_analyses</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 82%" />
Expand All @@ -121,7 +121,7 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_mne_example.html#sphx-glr-auto-examples-analyses-plot-mne-example-py"><span class="std std-ref">Topographical Analyses with MNE</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_mne_example.py</span></code>)</p></td>
<td><p>00:01.761</p></td>
<td><p>00:01.796</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
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Expand Up @@ -197,6 +197,7 @@ <h3>Inducing Model Fit Failures<a class="headerlink" href="#inducing-model-fit-f
Model fitting was unsuccessful.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
Model fitting was unsuccessful.
</pre></div>
</div>
<p>As we can see, there are now some model fit failures! Note that, as above, it will
Expand All @@ -207,8 +208,8 @@ <h3>Inducing Model Fit Failures<a class="headerlink" href="#inducing-model-fit-f
</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>Number of Null models : 6
Indices of Null models : [0, 2, 4, 5, 13, 16]
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Number of Null models : 7
Indices of Null models : [9, 13, 14, 20, 21, 23, 24]
</pre></div>
</div>
</div>
Expand Down Expand Up @@ -254,7 +255,7 @@ <h3>Debugging Model Fit Errors<a class="headerlink" href="#debugging-model-fit-e
<p>If you are unsure about why or how the model is failing to fit, consider
opening an <a class="reference external" href="https://github.com/fooof-tools/fooof/issues">issue</a> on the project
repository, and we will try to look into what seems to be happening.</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.335 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 3.805 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-manage-plot-failed-fits-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/db8de8edd3842461f54f58941cd05cc4/plot_failed_fits.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_failed_fits.py</span></code></a></p>
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Expand Up @@ -252,7 +252,7 @@ <h3>fit_fooof_3d<a class="headerlink" href="#fit-fooof-3d" title="Permalink to t
</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>[&lt;fooof.objs.group.FOOOFGroup object at 0x7fc799ced940&gt;, &lt;fooof.objs.group.FOOOFGroup object at 0x7fc799ced5e0&gt;, &lt;fooof.objs.group.FOOOFGroup object at 0x7fc799ced8b0&gt;]
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>[&lt;fooof.objs.group.FOOOFGroup object at 0x7f6451b65880&gt;, &lt;fooof.objs.group.FOOOFGroup object at 0x7f6451b65580&gt;, &lt;fooof.objs.group.FOOOFGroup object at 0x7f6451b658b0&gt;]
</pre></div>
</div>
<p>Note that the length of the returned list of objects should be equivalent to
Expand Down Expand Up @@ -287,9 +287,9 @@ <h3>Analyzing FOOOF Objects<a class="headerlink" href="#analyzing-fooof-objects"
</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>Aperiodic exponent for condition 0 is 1.3004
Aperiodic exponent for condition 1 is 1.4500
Aperiodic exponent for condition 2 is 1.6010
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Aperiodic exponent for condition 0 is 1.4508
Aperiodic exponent for condition 1 is 1.5513
Aperiodic exponent for condition 2 is 1.4500
</pre></div>
</div>
</div>
Expand Down Expand Up @@ -341,18 +341,18 @@ <h3>Managing FOOOF Objects<a class="headerlink" href="#managing-fooof-objects" t
Power spectra were fit without a knee.

Aperiodic Fit Values:
Exponents - Min: 0.998, Max: 2.004, Mean: 1.450
Exponents - Min: 0.999, Max: 2.004, Mean: 1.484

In total 28 peaks were extracted from the group
In total 27 peaks were extracted from the group

Goodness of fit metrics:
R2s - Min: 1.000, Max: 1.000, Mean: 1.000
Errors - Min: 0.004, Max: 0.004, Mean: 0.004
Errors - Min: 0.003, Max: 0.004, Mean: 0.004

==================================================================================================
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.258 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.260 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-manage-plot-fit-fooof-3d-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/ce373e0838d5783353a4548ff47106a9/plot_fit_fooof_3d.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_fit_fooof_3d.py</span></code></a></p>
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Expand Up @@ -221,8 +221,8 @@ <h3>Checking the Error Across Groups of Model Fits<a class="headerlink" href="#c
</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>Frequency with highest mean error: 47.5
Frequency with highest standard deviation of error: 7.5
<div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Frequency with highest mean error: 3.0
Frequency with highest standard deviation of error: 3.0
</pre></div>
</div>
<p>In the plot and checks above, we again see that the error is on average low, and
Expand Down Expand Up @@ -259,7 +259,7 @@ <h3>Frequency-by-Frequency Errors When There is a Problem<a class="headerlink" h
<p>If you see high errors, especially bunched up around particular frequencies,
this is a sign that something might be going wrong, and it might be worth
looking more into the how the model fits are going.</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.127 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.620 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-manage-plot-freq-by-freq-error-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/16d9586d4d5bb0e93cc846c336cef657/plot_freq_by_freq_error.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_freq_by_freq_error.py</span></code></a></p>
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Expand Up @@ -313,7 +313,7 @@ <h2>Averaging Across Model Fits<a class="headerlink" href="#averaging-across-mod
out = np.array([np.insert(getattr(data, name), 3, index, axis=1)
</pre></div>
</div>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.123 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.116 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-manage-plot-manipulating-fooofs-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/df69e7186299ce3b317510052e083eba/plot_manipulating_fooofs.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_manipulating_fooofs.py</span></code></a></p>
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Expand Up @@ -112,7 +112,7 @@

<div class="section" id="computation-times">
<span id="sphx-glr-auto-examples-manage-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this headline"></a></h1>
<p><strong>00:04.844</strong> total execution time for <strong>auto_examples_manage</strong> files:</p>
<p><strong>00:04.800</strong> total execution time for <strong>auto_examples_manage</strong> files:</p>
<table class="docutils align-default">
<colgroup>
<col style="width: 84%" />
Expand All @@ -121,19 +121,19 @@
</colgroup>
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_failed_fits.html#sphx-glr-auto-examples-manage-plot-failed-fits-py"><span class="std std-ref">Failed Model Fits</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_failed_fits.py</span></code>)</p></td>
<td><p>00:03.335</p></td>
<td><p>00:03.805</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_freq_by_freq_error.html#sphx-glr-auto-examples-manage-plot-freq-by-freq-error-py"><span class="std std-ref">Frequency-by-Frequency Errors</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_freq_by_freq_error.py</span></code>)</p></td>
<td><p>00:01.127</p></td>
<td><p>00:00.620</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="plot_fit_fooof_3d.html#sphx-glr-auto-examples-manage-plot-fit-fooof-3d-py"><span class="std std-ref">Fitting Power Spectrum Models Across 3D Arrays</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_fit_fooof_3d.py</span></code>)</p></td>
<td><p>00:00.258</p></td>
<td><p>00:00.260</p></td>
<td><p>0.0 MB</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="plot_manipulating_fooofs.html#sphx-glr-auto-examples-manage-plot-manipulating-fooofs-py"><span class="std std-ref">Manipulating FOOOF Objects</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_manipulating_fooofs.py</span></code>)</p></td>
<td><p>00:00.123</p></td>
<td><p>00:00.116</p></td>
<td><p>0.0 MB</p></td>
</tr>
</tbody>
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Expand Up @@ -243,7 +243,7 @@ <h2>Other Plotting Options<a class="headerlink" href="#other-plotting-options" t
</pre></div>
</div>
<img alt="plot fooof models" class="sphx-glr-single-img" src="../../_images/sphx_glr_plot_fooof_models_007.png" />
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.080 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 1.070 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plots-plot-fooof-models-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/e20a5bfa6c526d2378b76bd42b8330a7/plot_fooof_models.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_fooof_models.py</span></code></a></p>
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Expand Up @@ -213,6 +213,11 @@ <h2>Periodic Components<a class="headerlink" href="#periodic-components" title="
<span class="n">g2_alphas</span> <span class="o">=</span> <a href="../../generated/fooof.analysis.get_band_peak_fg.html#fooof.analysis.get_band_peak_fg" title="fooof.analysis.get_band_peak_fg" class="sphx-glr-backref-module-fooof-analysis sphx-glr-backref-type-py-function"><span class="n">get_band_peak_fg</span></a><span class="p">(</span><a href="../../generated/fooof.FOOOFGroup.html#fooof.FOOOFGroup" title="fooof.FOOOFGroup" class="sphx-glr-backref-module-fooof sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">fg2</span></a><span class="p">,</span> <a href="../../generated/fooof.Bands.html#fooof.Bands" title="fooof.Bands" class="sphx-glr-backref-module-fooof sphx-glr-backref-type-py-class sphx-glr-backref-instance"><span class="n">bands</span></a><span class="o">.</span><span class="n">alpha</span><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>/home/rph/Projects/fooof/.env/lib/python3.8/site-packages/fooof/objs/group.py:378: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify &#39;dtype=object&#39; when creating the ndarray
out = np.array([np.insert(getattr(data, name), 3, index, axis=1)
</pre></div>
</div>
<div class="section" id="plotting-peak-parameters">
<h3>Plotting Peak Parameters<a class="headerlink" href="#plotting-peak-parameters" title="Permalink to this headline"></a></h3>
<p>The <a class="reference internal" href="../../generated/fooof.plts.periodic.plot_peak_params.html#fooof.plts.periodic.plot_peak_params" title="fooof.plts.periodic.plot_peak_params"><code class="xref py py-func docutils literal notranslate"><span class="pre">plot_peak_params()</span></code></a> function takes in peak parameters,
Expand Down Expand Up @@ -317,7 +322,7 @@ <h2>Conclusions<a class="headerlink" href="#conclusions" title="Permalink to thi
would suggest there may be interesting differences between these groups. Follow up
analyses in such a case could investigate whether there are statistically significant
differences between these groups.</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.710 seconds)</p>
<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.781 seconds)</p>
<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plots-plot-model-components-py">
<div class="sphx-glr-download sphx-glr-download-python docutils container">
<p><a class="reference download internal" download="" href="../../_downloads/47009921621730270815c103aed0f359/plot_model_components.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_model_components.py</span></code></a></p>
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Expand Up @@ -243,7 +243,7 @@ <h2>Put it all together<a class="headerlink" href="#put-it-all-together" title="
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 0.382 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plots-plot-power-spectra-py">
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<p><a class="reference download internal" download="" href="../../_downloads/4c23cdca0dc3598148c67ed23a512c59/plot_power_spectra.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_power_spectra.py</span></code></a></p>
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