Data and metadata saving

Data saving classes in Stytra

All streaming data (tracking, stimulus state) is collected by subclasses of the Accumulator Accumulators collect named tuples of data and timing of data points. If the data format changes, the accumulator resets.

All other data (animal metadata, configuration information, GUI state etc. is collected inside the Experiment class via tha DataCollector

Configuring Stytra for updating external database:

In addition to the JSON file, the metadata can be saved to a database, such as MongoDB. For this, an appropriate database class has to be created and passed to the Stytra class. This example uses PyMongo


from stytra.utilities import Database, prepare_json
import pymongo

class PortuguesDatabase(Database):
    def __init__(self):
        # in the next line you have to put in the IP address and port of the
        # MongoDB instance
        self.client = pymongo.MongoClient("mongodb://192.???.???.???:????")
        # the database and collection are created in MongoDB before
        # the first use
        self.db = self.client.experiments
        self.collection = self.db["experiments"]

    def insert_experiment_data(self, exp_dict):
        """ Puts a record of the experiment in the default lab MongoDB database

        :param exp_dict: a dictionary from the experiment data collector
        :return: the database id of the inserted item

        # we use the prepare_json function to clean the dictionary
        # before inserting into the database

        db_id = self.collection.insert_one(
            prepare_json(exp_dict, eliminate_df=True)
        return str(db_id)