Code for analyzing 2-photon imaging data with TTL event data

There are two ways to set everything up:

$ make create
docker-compose -f docker-compose.yaml up --no-start
Creating network "monkey_frog_default" with the default driver
Building app

Once your image is built you can run your data directly with a make command:

$ make run file=myparams.json

Or if you want something interactive you can use make bash or make ipython:

$ make bash
docker-compose -f docker-compose.yaml run --entrypoint /bin/bash app
Creating monkey_frog_app_run ... done
root@65a51952baad:/app# 

When you are finished you can remove all the old containers:

$ make down

To setup your virtual environment, have miniconda installed for python3.8x, then run

$ conda env create -f environment.yaml

Before running any code, make sure to enter your virtual environment

$ conda activate monkey_frog

When finished for the day

$ conda deactivate

will get you out of your virtual environment

If you want to run process_data.py from the command line, do the following:

$ python3 process_data.py

By default, it will read parameters from params.json, but you can make your own file and read it in with the -f flag.

$ python3 process_data.py -f my_parameters.json

[1]: !python3 process_data.py -f params.json

You can also use the python shell commands below

With no separate parameter file:

>>> exec(open("./process_data.py").read())

If you want to examine the output

>>> from process_data import process_data
>>> trials, segment_list = process_data('my_parameters.json')

If you do have your own parameter file, you can us the os or subprocess modules:

>>> import os
>>> os.system("python3 process_data.py -f my_parameters.json")

>>> import subprocess
>>> subprocess.Popen(["python3", "process_data.py", "-f", "params.json"])