run_analysis.py

import sys
import os
from Analysis.Neural.MEI.estimate_mei_direct import produce_meis, produce_meis_extended
from Analysis.Video.behaviour_video_construction import draw_episode
from Analysis.load_data import load_data

try:
    run_config = sys.argv[1]
except IndexError:
    run_config = "1l"


if run_config == "extended_1l":
    produce_meis_extended("dqn_scaffold_26-2", "conv1l", True, 1000)
elif run_config == "extended_2l":
    produce_meis_extended("dqn_scaffold_26-2", "conv2l", True, 1000)
elif run_config == "extended_3l":
    produce_meis_extended("dqn_scaffold_26-2", "conv3l", True, 1000)
elif run_config == "extended_4l":
    produce_meis_extended("dqn_scaffold_26-2", "conv4l", True, 1000)
elif run_config == "1l":
    produce_meis("dqn_scaffold_26-2", "conv1l", True, 1000)
elif run_config == "2l":
    produce_meis("dqn_scaffold_26-2", "conv2l", True, 1000)
elif run_config == "3l":
    produce_meis("dqn_scaffold_26-2", "conv3l", True, 1000)
elif run_config == "4l":
    produce_meis("dqn_scaffold_26-2", "conv4l", True, 1000)
elif run_config == "dense":
    produce_meis("dqn_scaffold_26-2", "rnn_in", full_reafference=True, iterations=100, conv=False)
elif run_config == "draw_ep":
    model_name = "dqn_scaffold_26-2"
    data = load_data(model_name, "Behavioural-Data-Videos-A1", "Naturalistic-3")
    assay_config_name = "dqn_26_2_videos"
    draw_episode(data, assay_config_name, model_name, continuous_actions=False, show_energy_state=False,
                 trim_to_fish=True, showed_region_quad=750)
else:
    produce_meis_extended("dqn_scaffold_26-2", "conv1l", True, 1000)