deploy: f184ccd

_sources/configuration.md.txt

@@ -90,7 +90,7 @@ Training hyperparameters are defined within the parent key: `training_hparams` s
 (metrics_config)=
 ## Metrics Configuration
 
-The [metrics_config.yaml](https://github.com/CosmoStat/wf-psf/blob/dummy_main/config/metrics_config.yaml) file stores the configuration parameters for the WaveDiff pipeline to carry out a set of computations of four metrics listed in the table below on a trained PSF model for the input training and test data sets, as applied in {cite:t}`Liaudat:23`.
+The [metrics_config.yaml](https://github.com/CosmoStat/wf-psf/blob/dummy_main/config/metrics_config.yaml) file stores the configuration parameters for the WaveDiff pipeline to carry out a set of computations for the four metrics listed in the table below on a trained PSF model for the input training and test data sets, as applied in {cite:t}`Liaudat:23`.
 
 | Metric type | Description |
 | --- | ----------- |

configuration.html

@@ -195,7 +195,7 @@ <h1>Configuration<a class="headerlink" href="#configuration" title="Link to this
 </section>
 <section id="metrics-configuration">
 <span id="metrics-config"></span><h2>Metrics Configuration<a class="headerlink" href="#metrics-configuration" title="Link to this heading"></a></h2>
-<p>The <a class="reference external" href="https://github.com/CosmoStat/wf-psf/blob/dummy_main/config/metrics_config.yaml">metrics_config.yaml</a> file stores the configuration parameters for the WaveDiff pipeline to carry out a set of computations of four metrics listed in the table below on a trained PSF model for the input training and test data sets, as applied in <span id="id1">Liaudat <em>et al.</em> [<a class="reference internal" href="z_ref.html#id6" title="Tobias Liaudat, Jean-Luc Starck, Martin Kilbinger, and Pierre-Antoine Frugier. Rethinking data-driven point spread function modeling with a differentiable optical model. Inverse Problems, 39(3):035008, feb 2023. URL: https://dx.doi.org/10.1088/1361-6420/acb664, doi:10.1088/1361-6420/acb664.">2023</a>]</span>.</p>
+<p>The <a class="reference external" href="https://github.com/CosmoStat/wf-psf/blob/dummy_main/config/metrics_config.yaml">metrics_config.yaml</a> file stores the configuration parameters for the WaveDiff pipeline to carry out a set of computations for the four metrics listed in the table below on a trained PSF model for the input training and test data sets, as applied in <span id="id1">Liaudat <em>et al.</em> [<a class="reference internal" href="z_ref.html#id6" title="Tobias Liaudat, Jean-Luc Starck, Martin Kilbinger, and Pierre-Antoine Frugier. Rethinking data-driven point spread function modeling with a differentiable optical model. Inverse Problems, 39(3):035008, feb 2023. URL: https://dx.doi.org/10.1088/1361-6420/acb664, doi:10.1088/1361-6420/acb664.">2023</a>]</span>.</p>
 <table class="docutils align-default">
 <thead>
 <tr class="row-odd"><th class="head"><p>Metric type</p></th>