flowstab.scripts.run_clusterings
================================

.. py:module:: flowstab.scripts.run_clusterings

.. autoapi-nested-parse::

   Clusters the covariance integrals computed with `run_cov_integrals.py` (step 2).
   The clusterings are computed with the Louvain algorithm for each file containing the result of step 2 in {savedir}.
   The Louvain algorithm is repeated `num_repeat` times and the best partition (maximizing the flow stability) is selected.
   The ensemble of partitions is used to compute the variation of information.
   The computations for the different files is spread of `nproc_files` in parallel. It is also possible to parallelize the
   repeated clusterings using `nproc_clustering`. This requires nproc_files*nproc_clustering cores.

   A number of metadata (e.g. all the parameters used to run the code) is saved together with the results in a dictionary.

   The results of the clustering are saved with the following keys:
   - 'clust_counter' : All the different partitions found at each run of the Louvain algorithm togheter with the number of times they appeared.
   - 'stabilites' : All the values of the flow stability for each run.
   - 'seeds' : Random seeds for each run.
   - 'nvarinf' : Average normalized variation of information computed over the ensemble of partitions.
   - 'avg_stab': Average flow stability computed over the ensemble of partitions.
   - 'avg_nclust' : Average number of clusters computed over the ensemble of partitions.
   - 'best_cluster' : Best partition (the one with the max flow stability from the ensemble).
   - 'best_stab' : Flow stability value of the best partition.

   The results are saved in files named f'{savedir}/clusters_{netname}_tau_w{tau_w:.3e}_PT_{int_start:06d}_to_{int_stop:06d}.pickle'



Attributes
----------

.. autoapisummary::

   flowstab.scripts.run_clusterings.ap
   flowstab.scripts.run_clusterings.clust_verbose
   flowstab.scripts.run_clusterings.compute_clustering
   flowstab.scripts.run_clusterings.compute_nvarinf
   flowstab.scripts.run_clusterings.compute_static_clustering
   flowstab.scripts.run_clusterings.datadir
   flowstab.scripts.run_clusterings.direction
   flowstab.scripts.run_clusterings.files
   flowstab.scripts.run_clusterings.files
   flowstab.scripts.run_clusterings.inargs
   flowstab.scripts.run_clusterings.init_p1
   flowstab.scripts.run_clusterings.integral_rtol
   flowstab.scripts.run_clusterings.max_num_varinf_samples
   flowstab.scripts.run_clusterings.n_meta_iter_max
   flowstab.scripts.run_clusterings.n_sub_iter_max
   flowstab.scripts.run_clusterings.net_name
   flowstab.scripts.run_clusterings.normalize_cov_mat
   flowstab.scripts.run_clusterings.nproc_clustering
   flowstab.scripts.run_clusterings.nproc_files
   flowstab.scripts.run_clusterings.num_norm_iter
   flowstab.scripts.run_clusterings.num_repeat
   flowstab.scripts.run_clusterings.num_varinf_samples
   flowstab.scripts.run_clusterings.num_varinf_samples
   flowstab.scripts.run_clusterings.only_largest_comp
   flowstab.scripts.run_clusterings.optional
   flowstab.scripts.run_clusterings.print_num_loops
   flowstab.scripts.run_clusterings.required
   flowstab.scripts.run_clusterings.save_clustering_before_nvarinf
   flowstab.scripts.run_clusterings.savedir
   flowstab.scripts.run_clusterings.separate_comps
   flowstab.scripts.run_clusterings.var_dict
   flowstab.scripts.run_clusterings.verbose


Functions
---------

.. autoapisummary::

   flowstab.scripts.run_clusterings.compute_nvi_sample
   flowstab.scripts.run_clusterings.compute_static_clustering_fct
   flowstab.scripts.run_clusterings.load_autocov_int
   flowstab.scripts.run_clusterings.main
   flowstab.scripts.run_clusterings.n_random_seeds
   flowstab.scripts.run_clusterings.worker


Module Contents
---------------

.. py:function:: compute_nvi_sample(params)

.. py:function:: compute_static_clustering_fct(params)

.. py:function:: load_autocov_int(file, init_p1=False, direction=None)

.. py:function:: main()

.. py:function:: n_random_seeds(n)

.. py:function:: worker(file_args)

.. py:data:: ap

.. py:data:: clust_verbose

.. py:data:: compute_clustering

.. py:data:: compute_nvarinf

.. py:data:: compute_static_clustering

.. py:data:: datadir

.. py:data:: direction

.. py:data:: files

.. py:data:: files

.. py:data:: inargs

.. py:data:: init_p1

.. py:data:: integral_rtol

.. py:data:: max_num_varinf_samples

.. py:data:: n_meta_iter_max

.. py:data:: n_sub_iter_max

.. py:data:: net_name

.. py:data:: normalize_cov_mat

.. py:data:: nproc_clustering

.. py:data:: nproc_files

.. py:data:: num_norm_iter

.. py:data:: num_repeat

.. py:data:: num_varinf_samples

.. py:data:: num_varinf_samples

.. py:data:: only_largest_comp

.. py:data:: optional

.. py:data:: print_num_loops

.. py:data:: required

.. py:data:: save_clustering_before_nvarinf

.. py:data:: savedir

.. py:data:: separate_comps

.. py:data:: var_dict

.. py:data:: verbose