Supplementary files for the dingo Python library

<p>We&nbsp;compare the&nbsp;<a href="https://drops.dagstuhl.de/opus/frontdoor.php?source_opus=13820">Multiphase Monte Carlo&nbsp;flux Sampling (MMCS)</a> feature&nbsp;of the <a href="https://github.com/GeomScale/dingo">dingo</a> library&nbsp;against the combined method of <a href="https://gitlab.com/csb.ethz/PolyRound">PolyRound</a> (for rounding) followed by <a href="https://modsim.github.io/hopsy/">hopsy</a> (for sampling) on a set of 7 models with a ranging&nbsp;dimension&nbsp;(<em>ext_data.zip</em>).</p> <p>The&nbsp;<em>simpl_transf_polytopes.zip</em> contains the polytopes retrieved after the <em>simplify()</em> and <em>transform() </em>functions of the PolyRound library. <br>These polytopes were used as input for the dingo implementation of the MMCS algorithm asking for an ESS of 1000. <br>Under the&nbsp;<em>dingo_samples_on_simpl_transf_polytopes.zip</em>&nbsp;the resulting&nbsp;samples from <em>dingo</em> can be found using the MMCS algorithm.&nbsp;</p> <p>Similarly, <em>polyrounded_polytopes.zip&nbsp;contains&nbsp;</em>the polytopes retrieved after&nbsp;applying <em>simplify()</em>, <em>transform()</em> and&nbsp;<em>round()</em> functions of the PolyRound library. <br>These polytopes were used as input for the <a href="https://modsim.github.io/hopsy/">hopsy</a> library, again, asking for&nbsp;an ESS of 1000. <br>The <em>hopsy_samples.zip</em>&nbsp;folder contains the resulting&nbsp;samples from hopsy<em> </em>library, using&nbsp;a thinning of 100<em>d </em>;<em> </em>only in the case of Recon3D a thinning of 200<em>d </em>was used as suggested by the authors. Under the&nbsp;<em>hopsy_samples_ess_1000.zip&nbsp;</em>folder, we provide the&nbsp;<em>hopsy</em> samples with an ESS of 1000. <br>Last,&nbsp;the samples produced using the efficient Billiard Walk implementation of <em>dingo</em> can be found under the <em>BWRsamples.zip </em>file. <br>In this case, 20000 points were sampled for each model.</p> <p>Further, the <em>sars_samples.zip&nbsp;</em>file contains&nbsp;<em>dingo</em>&nbsp;samples from the solution space of the SARS-CoV-2&nbsp;integrated&nbsp;model of <a href="https://doi.org/10.1093/bioinformatics/btaa813">Renz et <em>al</em> (2020)</a>&nbsp;for the following cases:&nbsp;</p> <ul> <li>unbiased; where the zero vector has been used as the objective function of the model</li> <li>after maximising for the human biomass&nbsp;</li> <li>after maximising for the&nbsp;virus biomass objective function (VBOF)</li> </ul> <p>The following Python scripts to perform these experiments are included:</p> <ul> <li><em>polyround_preproces.py&nbsp;</em>: runs the <em>PolyRound&nbsp;</em>functions and builds the simplified and transformed polytopes that&nbsp;<em>dingo&nbsp;</em>will use as well as the simplified, transformed and rounded polytopes&nbsp;<em>hopsy</em>&nbsp;uses</li> <li><em>hopsy_on_polyrounded_polytopes.py&nbsp;</em>: performs&nbsp;sampling with <em>hopsy&nbsp;</em></li> <li><em>dingo_on_simpl_transf_polytopes.py&nbsp;</em>: performs sampling with&nbsp;<em>dingo&nbsp;</em></li> <li><em>run_bwr_exp.py</em> computes samples using the efficient Billiard Walk of <em>dingo</em></li> <li><em>binary_search.py</em>&nbsp;: a function to return the index in the chain where ESS becomes 1000</li> <li><em>compute_ess.py: </em>based on a model's&nbsp;<em>hopsy</em> samples (under the&nbsp;<em>hopsy_samples.zip </em>folder)&nbsp;it retrieves the samples&nbsp;with an ESS of 1000 and the corresponding&nbsp;required time for <em>hopsy&nbsp;</em>to build them. The script requires the total time of the&nbsp;<em>hopsy&nbsp;</em>experiment&nbsp;recorded in the model's corresponding <em>.txt&nbsp;</em>file (you can find this under the&nbsp;<em>hopsy_samples.zip)</em></li> <li><em>compute_ess_psrf_per_phase.py&nbsp;</em>computes ESS and PSRF in specific indices which correspond to those when MMCS switches from a phase a to next one</li> </ul> <p>A <a href="https://github.com/hariszaf/dingo/blob/vbof/tutorials/vbof.ipynb">notebook</a> is available for how the integrated model was sampled.&nbsp;</p> <p>&nbsp;</p>