nrn-modeldb-ci

Installation

In your virtual environment, install in editable mode:

pip install -e .

NOTE: You have to install NEURON by yourself (wheel, CMake install).

Usage

The following commands are now available:

• getmodels -> retrieve all or specified models from ModelDB.

  getmodels -h
  

• runmodels -> run nrn-modeldb-ci for all or specified models.

  runmodels -h
  

  Note that models have to be downloaded beforehand with getmodels. You can specify --virtual so that NEURON GUI is run in headless mode. It requires a backend (n.r. Xvfb). Re-running in the same --workdir can mangle results. Please use --clean if you wish to re-run in the same --workdir.

• report2html -> create an interactive HTML report for a given json report (obtained with runmodels)

  report2html -h
  

  Note that the generated HTML file is self-contained.

• diffgout -> launch nrngui and display the two gout files in different colors.

  diffgout -h
  

  This can come in handy when comparing/investigating results from binary incompatible neuron versions.

• diffreports2html -> create an interactive NEURONv1-vs-NEURONv2 HTML report

  diffreports2html -h
  

  The differences that are taken into account:

  • nrn_run and moderr from the json reports -> outputs side-by-side diffs
  • gout -> outputs git-like diffs; NOTE: this walks gout paths from json report run_info, make sure they are present.

  Note that the generated HTML file is self-contained.

• modeldb-config -> list configuration for nrn-modeldb-ci:

    modeldb-config
  

  Config	Details
  ROOT_DIR	location of nrn-modeldb-ci installation
  MODELDB_ROOT_DIR	path to modeldb package inside nrn-modeldb-ci
  MODELDB_RUN_FILE	yaml file containing run instructions for models (required for runmodels)
  MODELDB_METADATA_FILE	yaml file containing model info for those downloaded with getmodels
  MODELS_ZIP_DIR	location of cache folder for models populated via getmodels
  MDB_NEURON_MODELS_URL	url template used to get NEURON model IDs and last-updated timestamps (needed for getmodels)
  MDB_MODEL_METADATA_URL	url template used to get metadata about a single NEURON model (needed for getmodels)
  MDB_MODEL_DOWNLOAD_URL	url template used for model downloading (cf {model_id})

Model Run

MODELDB_RUN_FILE

This is where the "black magic" lives, instructions on how to run models from ModelDB. Default handling is available in case there are no entries for a given model id.

All entries are optional:

(*) verify_graph_() saves all lines of all graphs to the gout file in the model working directory.

TODO: Model Run Activity Diagram

Report

The generated report following runmodels contains te following info:

• gout - (optional) graph data from the neuron execution (must be run with runmodels --gout)
• logs - logs regarding model setup, nrnivmodl, ...
• nrn_run - command used to run the model and its output
• run_info - model run information
• run_time - model run time

For example, by running:

runmodels --gout --workdir=test3682 3682

we will generate report test3782.json :

{
    "0": {...} # runmodels stats, see next section
    "3682": {
        "gout": [
            "Graphs 1\n",
            "Graph[0]\n",
            "lines 1\n",
            "points 10001\n",
            "xvec1\n",
            "0\n",
            "0.025\n",
            ".....",            # truncated (can be HUGE)
            "-57.9912\n",
            "\n"
        ],
        "logs": [
            "",
            "",
            "/usr/bin/xcrun",
            "%model_dir%",
            "Mod files: \"%model_dir%/hh3.mod\" \"%model_dir%/rglu_score.mod\"",
            "",
            "Creating x86_64 directory for .o files.",
            "",
            "COBJS=''",
            " -> \u001b[32mNMODL\u001b[0m %model_dir%/hh3.mod",
            " -> \u001b[32mCompiling\u001b[0m mod_func.cpp",
            " -> \u001b[32mNMODL\u001b[0m %model_dir%/rglu_score.mod",
            "Translating hh3.mod into %model_dir%/x86_64/hh3.c",
            "Notice: VERBATIM blocks are not thread safe",
            "Translating rglu_score.mod into %model_dir%/x86_64/rglu_score.c",
            "Notice: This mechanism cannot be used with CVODE",
            "Notice: VERBATIM blocks are not thread safe",
            "Notice: Assignment to the GLOBAL variable, \"inf\", is not thread safe",
            "Notice: This mechanism cannot be used with CVODE",
            "Notice: Assignment to the GLOBAL variable, \"Rtau_AMPA\", is not thread safe",
            "Notice: Assignment to the GLOBAL variable, \"Rinf_AMPA\", is not thread safe",
            "Notice: Assignment to the GLOBAL variable, \"Rtau_NMDA\", is not thread safe",
            "Notice: Assignment to the GLOBAL variable, \"Rinf_NMDA\", is not thread safe",
            "Warning: Default 37 of PARAMETER celsius will be ignored and set by NEURON.",
            "Warning: Default -100 of PARAMETER ek will be ignored and set by NEURON.",
            "Warning: Default 40 of PARAMETER ena will be ignored and set by NEURON.",
            " -> \u001b[32mCompiling\u001b[0m hh3.c",
            " -> \u001b[32mCompiling\u001b[0m rglu_score.c",
            " => \u001b[32mLINKING\u001b[0m shared library ./libnrnmech.dylib",
            " => \u001b[32mLINKING\u001b[0m executable ./special LDFLAGS are:   ",
            "Successfully created x86_64/special",
            "INFO : Using neuron-nightly Package (Developer Version)",
            ""
        ],
        "nrn_run": [
            "RUNNING -> ./x86_64/special -nobanner %model_dir%/mosinit.hoc %model_dir%/driver.hoc",
            "\t0 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "\t1 ",
            "Spike at 40.5 ",
            "Spike at 81.15 ",
            "Spike at 108 ",
            "Spike at 133.65 ",
            "Spike at 180.775 ",
            "Spike at 201.3 ",
            "Total spikes: 6 ",
            "\t1 ",
            "\t1 ",
            ""
        ],
        "run_info": {
            "driver": "/Users/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap/driver.hoc",
            "init": "/Users/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap/mosinit.hoc",
            "model_dir": "/Users/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap",
            "script": [
                "echo 'use_mcell_ran4(1)' > temp",
                "cat mosinit.hoc >> temp",
                "mv temp  mosinit.hoc"
            ],
            "start_dir": "/Users/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap"
        },
        "run_time": "7.595794515"
    }
}

Every runmodels report will hold out run statistics in the "0" key:

    "0": {
        "NEURON version": "8.0a-743-g3871f82a",
        "Stats": {
            "Failed models": {
                "Accession numbers": [
                    20212,
                    97868,
                    144549,
                    186768,
                    244262
                ],
                "Count": 5
            },
            "Failed runs": {
                "Accession numbers": [
                    194897
                ],
                "Count": 1
            },
            "No. of models run": 659
        }
    },

For every model there is a <model.id>.yaml that is dumped in the model run directory. This is used in case the model is re-run in --inplace mode (also useful for debugging).

(venv) nrn-modeldb-ci$ cat test3682/synmap/3682.yaml

driver: /home/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap/driver.hoc
init: /home/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap/mosinit.hoc
model_dir: /home/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap
script:
- echo 'use_mcell_ran4(1)' > temp
- cat mosinit.hoc >> temp
- mv temp  mosinit.hoc
start_dir: /home/savulesc/Workspace/nrn-modeldb-ci/test3682/synmap
(venv) savulesc@bbd-cjngk03:~/Workspace/nrn-modeldb-ci$ 

Funding

nrn-modeldb-ci is developed in a joint collaboration between the Blue Brain Project and Yale University. This work is supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology, NIH grant number R01NS11613 (Yale University), the European Union Seventh Framework Program (FP7/20072013) under grant agreement n◦ 604102 (HBP) and the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreement n◦ 720270 (Human Brain Project SGA1), n◦ 785907 (Human Brain Project SGA2) and n◦ 945539 (Human Brain Project SGA3).

Copyright (c) 2022 Yale University & Blue Brain Project/EPFL