.. _rebuild_scm:

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Rebuild an existing single hippocampal cell model
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This Use Case allows a user to configure the BluePyOpt to re-run an 
optimization with his/her own choices for the parameters range. The current 
version allows to select models obtained in previous optimizations.

Selecting this Use Case, three Jupyter Notebooks are cloned in a private 
existing/new Collab. The cloned Notebooks are:

*********************************
Rebuild Single HippoCell - Config
*********************************
   
It allows the user to:

1. Visualize the electrophysiological features for the chosen model, that will 
   be used as reference by the optimization process (“Features” tab); they 
   cannot be changed:

.. container:: bsp-container-center

   .. image:: images/visualize_feat.png
       :width: 700px
       :align: right

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2. Visualize and change parameters of an existing optimization (“Parameters” 
   tab). Values can be changed and saved by the option “Save new parameters”.
    
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3. Configure the BluePyOpt optimization algorithm, by defining the offspring 
   size and the max number of generations; they are set by default to 10 and 2 
   respectively.
    
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4. Generate a zip file needed to run the new optimization by the option 
   “Create zip file”:

.. container:: bsp-container-center

    .. image:: images/visualize_params.png
        :width: 700px
        :align: right

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5. Login to the NSG (Neuroscience Gateway) by inserting a username and password 
   and clicking on the “Login NSG” button:

.. container:: bsp-container-center

    .. image:: images/login.png
        :width: 400px
        :align: right

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6. Configure the parameters of the optimization job: number of nodes, number of 
   cores and runtime. They are set by default to 2, 10 and 0.5 respectively. 
   The maximum number of nodes available per job is 72. If you would require 
   more than 72 nodes, please contact nsghelp@sdsc.edu. The maximum number of cores 
   required per node is 24.
    
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7. Run the optimization by clicking on the “Run NSG simulation”.

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8. The job has been submitted when you see:
    
.. container:: bsp-container-center

    .. image:: images/ job_submitted.png
        :width: 400px
        :align: right

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You can check the job status by clicking on the “Check NSG simulation”. The 
status may be: QUEUE, COMMANDRENDERING, INPUTSTAGING, SUBMITTED, LOAD_RESULTS 
or COMPLETED; Once the job is COMPLETED, results are saved in the Collab 
storage, under the BluePyOptOne/resultsNSG/username/foldername (foldername is 
the name of the old optimization, where date and time are updated with the 
current date and time).

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9. If you are interested in the code, click on the “Click here to toggle on/off 
   the source code” button:
    
.. container:: bsp-container-center

    .. image:: images/toggle_button.png
        :width: 300px
        :align: right

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*******************************************
BuildOwn Single HippoCell - NSG Job Manager
*******************************************

.. include:: ../nsg_job_manager/nsg_job_manager.rst
   
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BuildOwn Single HippoCell - Analysis
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.. include:: ../analyze_run/analyze_run.rst