Source code for allensdk.internal.pipeline_modules.run_observatory_analysis

#!/usr/bin/python
# Copyright 2016 Allen Institute for Brain Science
# This file is part of Allen SDK.
#
# Allen SDK is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, version 3 of the License.
#
# Allen SDK is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Allen SDK.  If not, see <http://www.gnu.org/licenses/>.

import json, sys, traceback, logging
from allensdk.brain_observatory.session_analysis import run_session_analysis
import allensdk.brain_observatory.stimulus_info as si
import allensdk.core.json_utilities as json_util
from allensdk.internal.core.lims_pipeline_module import PipelineModule, run_module, SHARED_PYTHON
import allensdk.internal.core.lims_utilities as lu
from six import iteritems
import os
import logging


[docs]def get_experiment_nwb_file(experiment_id):
    res = lu.query("""
select * from well_known_files wkf 
join well_known_file_types wkft on wkft.id = wkf.well_known_file_type_id
where attachable_id = %d
and wkft.name = 'NWBOphys'
""" % experiment_id)
    return os.path.join(res[0]['storage_directory'], res[0]['filename'])



[docs]def get_experiment_session(experiment_id):
    return lu.query("""
select stimulus_name from ophys_sessions os
join ophys_experiments oe on oe.ophys_session_id = os.id
where oe.id = %d
""" % experiment_id)[0]['stimulus_name']



[docs]def debug(experiment_ids, local=False, 
                          OUTPUT_DIR = "/data/informatics/CAM/analysis/",
                          SDK_PATH = "/data/informatics/CAM/analysis/allensdk/",
                          walltime="10:00:00",
                          python=SHARED_PYTHON,
                          queue='braintv'):

    input_data = {}
    for eid in experiment_ids:
        exp_dir = os.path.join(OUTPUT_DIR, str(eid))
        input_data[eid] = dict(nwb_file=get_experiment_nwb_file(eid),
                               output_file=os.path.join(exp_dir, "%d_analysis.h5" % eid),
                               session_name=get_experiment_session(eid))

    run_module(os.path.abspath(__file__),
               input_data,
               exp_dir,
               python=python,
               sdk_path=SDK_PATH,
               pbs=dict(vmem=32,
                        job_name="bobanalysis_%d"% eid,
                        walltime=walltime,
                        queue=queue),
               local=local)



[docs]def main():
    mod = PipelineModule()
    jin = mod.input_data()

    results = {}

    for ident, experiment in iteritems(jin):
        nwb_file = experiment['nwb_file']
        output_file = experiment['output_file']

        if experiment["session_name"] not in si.SESSION_STIMULUS_MAP.keys():
            raise Exception("Could not run analysis for unknown session: %s" % experiment["session_name"])

        logging.info("Running %s analysis", experiment["session_name"])
        logging.info("NWB file %s", nwb_file)
        logging.info("Output file %s", output_file)

        results[ident] = run_session_analysis(nwb_file, output_file, 
                                              save_flag=True, plot_flag=False)

    logging.info("Generating output")

    jout = {}
    for session_name, data in results.items():
        # results for this session
        res = {}
        # metric fields
        names = {}
        roi_id = None
        for metric, values in data['cell'].items():
            if metric == "roi_id":
                roi_id = values
            else:
                # convert dict to array
                vals = []
                for i in range(len(values)):
                    vals.append(values[i])          # panda syntax
                names[metric] = vals
        # make an output record for each roi_id
        if roi_id is not None:
            for i in range(len(roi_id)):
                name = roi_id[i]
                roi = {}
                for field, values in names.items():
                    roi[field] = values[i]
                res[name] = roi

        jout[session_name] = {
            'cell': res,
            'experiment': data['experiment']
            }

    logging.info("Saving output")

    mod.write_output_data(jout)


if __name__ == "__main__": main()