{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# include controllers to the path\n", "import sys, os\n", "sys.path.append(os.getcwd())\n", "sys.path.append(os.path.join(os.getcwd(), 'controllers'))\n", "\n", "# include pipeline repo to compute performance\n", "sys.path.append(os.path.join(os.getcwd(), '..'))\n", "sys.path.append(os.path.join(os.getcwd(), '..', 'pipeline'))\n", "sys.path.append(os.path.join(os.getcwd(), '..', 'pipeline', 'postprocessing'))\n", "\n", "import cv2\n", "import threading\n", "import math\n", "import time\n", "import random\n", "import json\n", "import datetime\n", "import os, shutil\n", "import numpy as np\n", "import multiprocess as mp\n", "\n", "# controllers\n", "import nbimporter\n", "from controllers.situtils import FPSTimes\n", "from controllers.camera import WebcamStream\n", "from controllers.video import VideoWriter\n", "from controllers.position import PositionTrackerSingle\n", "from controllers.sound import SoundControllerPR\n", "from controllers.serial import MCSArduino, FakeArduino\n", "from controllers.display import SITDisplay\n", "from controllers.island import IslandFactoryPR\n", "\n", "from pipeline.postprocessing.pack import pack\n", "from pipeline.postprocessing.performance import calculate_performance, dump_performance_to_H5" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Load experiment settings\n", "\n", "For every experimental cofiguration you can copy the original 'settings.json' file, build your own specific experimental preset, save it in this folder as e.g. 'settings_elena.json' and load it here instead of 'settings.json'." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "cfg_filename = os.path.join('profiles', 'valentin_PR_experiment.json')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "scrolled": false }, "outputs": [], "source": [ "with open(os.path.join('profiles', 'default.json')) as json_file:\n", " cfg = json.load(json_file)\n", "with open(cfg_filename) as json_file:\n", " cfg_local = json.load(json_file)\n", "\n", "for key in cfg.keys():\n", " cfg[key].update(cfg_local[key])\n", "cfg['experiment']['experiment_date'] = datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S')\n", "\n", "# print loaded settings\n", "#print(json.dumps(cfg, indent=4))" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# check if the sound interface is there\n", "import sounddevice as sd\n", "asio = [x for x in sd.query_devices() if x['name'].find('ASIO') > 0]\n", "#if len(asio) == 0:\n", "# raise SystemExit('The sound interface is not found. Please restart the computer')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Initialize session folder\n", "\n", "Run the upcoming cell, to create a session folder and to save the chosen experimetal parameters to a JSON-file (\"experiment_id_parameters.json\"). The session folder will be created here where this notebook is located." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# This session's protocols will be saved to this folder\n", "cfg_exp = cfg['experiment']\n", "experiment_id = \"%s_%s_%s\" % (cfg_exp['subject'], cfg_exp['experiment_type'], cfg_exp['experiment_date'])\n", "save_to = os.path.join('sessions', experiment_id)\n", " \n", "if not os.path.exists(save_to):\n", " os.makedirs(save_to)\n", "\n", "# update paths (assuming this paths are relative to this notebook)\n", "cfg['video']['file_path'] = os.path.join(save_to, cfg['video']['file_path'])\n", "cfg['position']['file_path'] = os.path.join(save_to, cfg['position']['file_path'])\n", "cfg['position']['contour_path'] = os.path.join(save_to, cfg['position']['contour_path'])\n", "cfg['experiment']['file_path'] = os.path.join(save_to, cfg['experiment']['file_path'])\n", "cfg['experiment']['islands_path'] = os.path.join(save_to, 'islands.csv')\n", "cfg['sound']['file_path'] = os.path.join(save_to, cfg['sound']['file_path'])\n", "cfg['position']['background_light'] = os.path.join('assets', cfg['position']['background_light'])\n", "cfg['position']['background_dark'] = os.path.join('assets', cfg['position']['background_dark'])\n", "if 'continuous' in cfg['sound']:\n", " cfg['sound']['continuous']['wav_file'] = os.path.join('assets', cfg['sound']['continuous']['wav_file'])\n", " \n", "# Saves all parameters to a JSON file with the user-defined \"Experiment ID\" as filename\n", "with open(os.path.join(save_to, experiment_id + '.json'), 'w') as f:\n", " json.dump(cfg, f, indent=4)\n", " \n", "with open(cfg['experiment']['file_path'], 'w') as f:\n", " # state: 0 - trial start, 1 - trial success, 2 - trial fail\n", " f.write('time, target_x, target_y, target_r, trial, state\\n')\n", "\n", "with open(cfg['experiment']['islands_path'], 'w') as f:\n", " f.write('tgt_x, tgt_y, tgt_r, d1_x, d1_y, d1_r, d2_x, d2_y, d2_r, d3_x, d3_y, d3_r\\n')" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "def timeout(t_start):\n", " return time.time() - t_start > cfg_exp['session_duration'] if t_start is not None else False" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "def log_event(*args): # log start / end of a trial\n", " with open(cfg_exp['file_path'], 'a') as f:\n", " f.write(\",\".join([str(x) for x in args]) + \"\\n\")" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "def log_islands(islands): # log position of the islands\n", " sorted_islands = sorted(islands, key=lambda x: x.sound_id, reverse=False)\n", " args = [(i.x, i.y, i.r) for i in sorted_islands]\n", " to_dump = [x for xs in args for x in xs]\n", " \n", " with open(cfg_exp['islands_path'], 'a') as f: \n", " f.write(\",\".join([str(round(x, 4)) for x in to_dump]) + \"\\n\")" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "def switch_light(pt, board):\n", " pt.switch_background()\n", " board.switch_light()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Start the experiment\n", "\n", "This cell contains code for animal tracking. We hope that the comments provided in the code suffice to understand the individual steps and to adjust them to your own setup and needs, if necessary.\n", "\n", "- press 's' to start recording\n", "- press 's' again to stop recording\n", "- press 'q' to quit\n", "\n", "The experiment will stop automatically if the pre-defined session duration is reached." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Webcam stream 1024.0:768.0 at 30.00 FPS started\n", "Position tracker stopped\n", "Video writer stopped\n", "Camera released\n" ] } ], "source": [ "# experiment status: 1 - idle, 2 - running (recording, logging), 0 - stopped\n", "status = mp.Value('i', 1)\n", "\n", "# init the sync with the acquisition system and feeder via Arduino\n", "if cfg['experiment']['MCSArduinoPort'] == 'fake':\n", " board = FakeArduino()\n", "else:\n", " board = MCSArduino(cfg['experiment']['MCSArduinoPort'])\n", "\n", "# start the camera stream\n", "vs = WebcamStream(cfg['camera'])\n", "vs.start()\n", "\n", "# init video recorder\n", "vw = VideoWriter(status, vs, cfg['video'])\n", "vw.start()\n", "\n", "# start position tracking\n", "pt = PositionTrackerSingle(status, vs, cfg['position']) #if cfg['position']['single_agent'] else PositionTrackerDouble(status, vs, cfg['position'])\n", "pt.start()\n", "\n", "# init frame renderer\n", "dc = SITDisplay(pt, cfg['video'])\n", "\n", "# init sound controller\n", "sc = SoundControllerPR(status, cfg['sound'])\n", "\n", "cfg_pos = cfg['position']\n", "isl_factory = IslandFactoryPR(cfg_pos['floor_r_in_meters'], cfg['experiment'])\n", "\n", "timers = []\n", "fps = FPSTimes()\n", "names = ['camera', 'video', 'position', 'main']\n", "trial = 0\n", "rewards = 0\n", "t_start = None\n", "target_since = None # holds either time in target or time in the middle point\n", "phase_start = time.time() # holds start of the phase\n", "phase = 0 # 0 - idle, 1 - foraging, 2 - inter-trial interval, 3 - reward / punishment\n", "cfg_exp = cfg['experiment']\n", "cfg_pos = cfg['position']\n", "islands = []\n", "iti_distance = 0.0\n", "last_x, last_y = None, None\n", "\n", "\n", "try:\n", " while trial <= cfg_exp['trial_number'] and not timeout(t_start):\n", " \n", " # ---------- rendering logic -----------\n", " \n", " frame = vs.read()\n", " if frame is None:\n", " time.sleep(0.1)\n", " continue # wait for the stream\n", " \n", " c_time = time.time()\n", " fps.count()\n", " angles, text_infos = [], []\n", " \n", " for i, ctrl in enumerate([vs, vw, pt, fps]): # FPS indicators\n", " text_infos.append('%s: %.2f FPS' % (names[i], ctrl.get_avg_fps()))\n", " \n", " if len(islands) > 0: # target island X, Y\n", " target = [i for i in islands if not i.is_distractor][0]\n", " text_infos.append('Target: %.3f %.3f' % (target.x, target.y))\n", "\n", " text_infos.append('Time: %.2f' % float(c_time - t_start) if t_start is not None else 'Time: Idle') # stopwatch\n", " text_infos.append('Trial: %.2f' % float(cfg_exp['trial_duration'] - (c_time - phase_start)) if phase == 1 else 'Trial: not started')\n", " text_infos.append('Trial: %s' % trial)\n", " text_infos.append('Rewards: %s' % rewards) # rewards\n", " text_infos.append('In target: %.2f' % float(c_time - target_since) if target_since is not None else 'In target: --')\n", " text_infos.append('ITI distance: %.2f' % iti_distance if iti_distance > 0 else 'ITI distance: --')\n", "\n", " frame, frame_to_save = dc.render(frame, status, islands=islands, angles=angles, text_infos=text_infos)\n", " \n", " # assign the frame back to the video stream for other controllers\n", " vs.frame_with_infos = frame_to_save\n", " \n", " cv2.imshow('Press (s)-to start/stop, (q)-to end', frame)\n", "\n", " # -------- experiment logic ---------------\n", " \n", " # animal is either foraging==trial (phase == 1) or in the inter-trial-interval (phase == 2) \n", " # or in reward / punishment (phase == 3)\n", " \n", " if pt.positions_in_m is not None:\n", " if phase == 1: # foraging\n", " tgt = [i for i in islands if not i.is_distractor][0]\n", "\n", " if pt.is_inside(tgt.x, tgt.y, tgt.r): # check if animal in the island and for how long\n", " if target_since is None: # just entered target\n", " target_since = c_time\n", "\n", " elif c_time - target_since > cfg_exp['target_duration']: # successful trial\n", " log_event(c_time, round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4), trial, 1) # log trial success\n", " board.feed()\n", " phase_start = c_time # start of the reward phase\n", " islands = [] # reset islands\n", " phase = 3 \n", " rewards += 1\n", " target_since = None\n", "\n", " elif c_time - phase_start > cfg_exp['trial_duration']: # trial failed and animal is not in the target\n", " log_event(c_time, round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4), trial, 2) # log trial failed\n", " phase_start = c_time\n", " sc.play_non_blocking('noise', pt.hds) # punishment noise\n", " islands = [] # reset islands\n", " phase = 3\n", " target_since = None # take care of the case in which animal was in target at trial end but exited before target_duration\n", "\n", " else:\n", " target_since = None\n", "\n", " elif phase == 2: # inter-trial-interval\n", " if last_x is None: # count distance between trials\n", " last_x, last_y = pt.positions_in_m[0]\n", " else:\n", " x, y = pt.positions_in_m[0]\n", " iti_distance += np.sqrt((x - last_x)**2 + (y - last_y)**2)\n", " last_x, last_y = x, y\n", "\n", " startpoint = [i for i in islands if not i.is_distractor][0]\n", " if pt.is_inside(startpoint.x, startpoint.y, startpoint.r): # inside starting point\n", "\n", " if target_since is None: # just entered middle point\n", " target_since = c_time\n", "\n", " elif c_time - target_since > cfg_exp['trial_init_time']: # successful start of the trial\n", "\n", " if cfg_exp['training_mode']: # if training for starting point, reward immediately\n", " tgt = [i for i in islands if not i.is_distractor][0]\n", " log_event(c_time, round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4), trial, 1) # log trial success\n", " board.feed()\n", " phase_start = c_time # start of the reward phase\n", " islands = [] # reset islands\n", " phase = 3 \n", " rewards += 1\n", " target_since = None\n", " \n", " else: # init_new_trial\n", " sc.play_non_blocking('target', pt.hds) # play sound from the correct speaker\n", " islands = isl_factory.generate_target(pt.hds) # island near the speaker\n", " log_islands(islands) # log island(s) positions\n", " tgt = [i for i in islands if not i.is_distractor][0]\n", " phase = 1 # trial phase\n", " trial += 1\n", " log_event(c_time, round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4), trial, 0)\n", " iti_distance = 0\n", " phase_start = c_time\n", " target_since = None\n", "\n", " # fail ITI with punishment\n", " elif c_time - phase_start > cfg_exp['iti_duration']:\n", " phase = 3\n", " phase_start = c_time\n", " islands = []\n", " sc.play_non_blocking('noise', pt.hds)\n", "\n", " else:\n", " target_since = None\n", "\n", " elif phase == 3:\n", " if c_time - phase_start > cfg_exp['punishment_or_reward_duration']:\n", " phase = 2\n", " phase_start = c_time\n", " islands = isl_factory.generate_startpoint()\n", " \n", " \n", " # -------- key press events ---------------\n", " \n", " k = cv2.waitKey(33)\n", " \n", " # light on/off\n", " if k == ord('l'):\n", " switch_light(pt, board)\n", " \n", " # feeding\n", " if k == ord('f'):\n", " tf = threading.Timer(0, board.feed, args=[])\n", " tf.start()\n", "\n", " if k == ord('c'):\n", " f_name = cfg_pos['background_light'] if pt.is_light else cfg_pos['background_dark']\n", " cv2.imwrite(f_name, dc.masked_frame)\n", " tf = threading.Timer(0.2, pt.reload_background, args=[])\n", " tf.start() \n", "\n", " # quit the session\n", " if k == ord('q'):\n", " break\n", "\n", " # start the experiment\n", " if k == ord('s'):\n", " board.start_or_stop() # start/stop data acquisition\n", " c_time = time.time() # more accurate time\n", " \n", " if status.value == 1: # start the session\n", " if t_start is None:\n", " t_start = c_time\n", " phase_start = c_time\n", " status.value = 2\n", " islands = isl_factory.generate_startpoint()\n", " phase = 2\n", " \n", " # init light events\n", " timers = []\n", " for event_t in cfg_exp['light_events']:\n", " timers.append(threading.Timer(event_t, switch_light, args=(pt, board)))\n", " \n", " for t in timers:\n", " t.start()\n", " \n", " elif status.value == 2: # pause the session\n", " if len(islands) > 0:\n", " tgt = [i for i in islands if not i.is_distractor][0]\n", " x, y, r = round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4)\n", " else:\n", " x, y, r = 0, 0, 0\n", " log_event(c_time, x, y, r, trial, -1) # log experiment break\n", " \n", " status.value = 1\n", " phase = 0\n", " islands = []\n", " for t in timers:\n", " t.cancel()\n", "\n", "finally:\n", " if status.value == 2: # stop data acquisition, in case exited via timeout\n", " board.start_or_stop()\n", " if len(islands) > 0:\n", " tgt = [i for i in islands if not i.is_distractor][0]\n", " x, y, r = round(tgt.x, 4), round(tgt.y, 4), round(tgt.r, 4)\n", " else: \n", " x, y, r = 0, 0, 0\n", " log_event(c_time, x, y, r, trial, -1) # log experiment end\n", " \n", " status.value = 0\n", " time.sleep(0.01)\n", " for t in timers:\n", " t.cancel()\n", " \n", " if board.is_light_off:\n", " board.switch_light() # turn light back on\n", " time.sleep(0.1)\n", " board.exit()\n", " \n", " cv2.destroyAllWindows()\n", " #sc.join()\n", " for ctrl in [pt, vw, vs]:\n", " ctrl.stop()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Merge data in HDF5 file" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "session_path = save_to\n", "#session_path = os.path.join('sessions', '2021-07-30_09-24-14') # some particular session\n", "#session_path = 'Y:\\\\Michael\\\\FreeBehaving\\\\SIT_sessions\\\\50_aSIT_2021-10-25_10-32-19'" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "ename": "IndexError", "evalue": "too many indices for array: array is 1-dimensional, but 2 were indexed", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mIndexError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;31m# do pack data to HDF5\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[0mh5name\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpack\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msession_path\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 6\u001b[0m \u001b[0mtrial\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32mD:\\runSIT\\..\\pipeline\\postprocessing\\pack.py\u001b[0m in \u001b[0;36mpack\u001b[1;34m(session_path)\u001b[0m\n\u001b[0;32m 77\u001b[0m \u001b[0mevents\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mevents\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0ms_start\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 78\u001b[0m \u001b[0msounds\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0marray\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'raw'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'sounds'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 79\u001b[1;33m \u001b[0msounds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0msounds\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0ms_start\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 80\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 81\u001b[0m \u001b[1;31m# squeeze - if session was interrupted, adjust times\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;31mIndexError\u001b[0m: too many indices for array: array is 1-dimensional, but 2 were indexed" ] } ], "source": [ "if not trial > 0:\n", " raise SystemExit('Nothing recorded. No sense to continue.')\n", "\n", "# do pack data to HDF5\n", "h5name = pack(session_path)\n", "trial = 0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plot sessions stats" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import h5py\n", "import numpy as np\n", "from scipy import signal" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "arena_r = 0.4 # in meters\n", "\n", "with h5py.File(h5name, 'r') as f:\n", " tl = np.array(f['processed']['timeline'])\n", " trial_idxs = np.array(f['processed']['trial_idxs'])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": false }, "outputs": [], "source": [ "fig = plt.figure(figsize=(12, 12))\n", "\n", "# trajectory and islands\n", "ax = fig.add_subplot(221)\n", "ax.scatter(tl[:, 1], tl[:, 2], s=1, alpha=0.1) # positions\n", "scat = ax.scatter(trial_idxs[:, 2], trial_idxs[:, 3], s=1000, facecolors='none', edgecolors='r') # islands, radius approx.\n", "ax.add_patch(plt.Circle((0, 0), arena_r, color='r', fill=False))\n", "ax.set_aspect('equal')\n", "ax.set_xlabel('X, m', fontsize=14)\n", "ax.set_ylabel('Y, m', fontsize=14)\n", "ax.set_title('Running', fontsize=14)\n", "ax.grid()\n", "\n", "# occupancy\n", "sigma = 0.1\n", "lin_profile = np.linspace(-15, 15, 20) \n", "bump = np.exp(-sigma * lin_profile**2)\n", "bump /= np.trapz(bump) # normalize to 1\n", "kernel = bump[:, np.newaxis] * bump[np.newaxis, :]\n", "occupancy_map, _, _ = np.histogram2d(tl[:, 1], tl[:, 2], bins=[40, 40], range=np.array([[-0.5, 0.5], [-0.5, 0.5]]))\n", "occupancy_map = signal.convolve2d(occupancy_map, kernel, mode='same')\n", "\n", "ax = fig.add_subplot(222)\n", "ax.imshow(occupancy_map.T, origin='lower', extent=(-0.5, 0.5, -0.5, 0.5), cmap='Blues')\n", "ax.add_patch(plt.Circle((0, 0), arena_r, color='r', fill=False))\n", "ax.set_xlabel('X, m', fontsize=14)\n", "ax.set_title('Occupancy', fontsize=14)\n", "ax.grid()\n", "\n", "# trials\n", "durations = tl[trial_idxs[:, 1].astype(int)][:, 0] - tl[trial_idxs[:, 0].astype(int)][:, 0]\n", "colors = ['red' if x == 1 else 'grey' for x in trial_idxs[:, 5]]\n", "\n", "ax = fig.add_subplot(223)\n", "ax.barh(np.arange(len(trial_idxs)), durations, color=colors, align='center')\n", "ax.set_xlabel('Time, s', fontsize=14)\n", "ax.set_ylabel('Trial, #', fontsize=14)\n", "ax.set_title('Trials', fontsize=14)\n", "\n", "# speed\n", "ax = fig.add_subplot(224)\n", "ax.hist(tl[:, 3], bins=50, ec='black')\n", "ax.set_xlabel('Speed, m/s', fontsize=14)\n", "ax.set_title('Speed', fontsize=14)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Performance" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "h5name = os.path.join(session_path, experiment_id + '.h5')\n", "jsname = os.path.join(session_path, experiment_id + '.json')\n", "\n", "# loading position and trial data\n", "with h5py.File(h5name, 'r') as f:\n", " tl = np.array(f['processed']['timeline']) # time, X, Y, speed\n", " trial_idxs = np.array(f['processed']['trial_idxs']) # idx start, idx end, X, Y, R, trial result (idx to tl)\n", "\n", "# loading session configuration\n", "with open(jsname, 'r') as f:\n", " cfg = json.load(f)\n", "\n", "timepoints = cfg['experiment']['timepoints']\n", "s_duration = cfg['experiment']['session_duration']\n", "\n", "periods = [[0, s_duration], [0, timepoints[0]], [timepoints[1], timepoints[2]], [timepoints[3], s_duration]]\n", "\n", "# separate ALL, L, D, L'\n", "ds_names = ['performance_ALL', 'performance_L', 'performance_D', 'performance_Lp']\n", "ds_names = ['performance_ALL'] # only light\n", "\n", "for i, ds_name in enumerate(ds_names):\n", " t_start, t_end = periods[i]\n", " trial_starts = tl[trial_idxs[:, 0].astype(np.int32)][:, 0]\n", " trial_ends = tl[trial_idxs[:, 1].astype(np.int32)][:, 0]\n", " tr_idxs = trial_idxs[(trial_starts >= t_start) & (trial_ends <= t_end)]\n", "\n", " dataset = calculate_performance(tl, tr_idxs, cfg)\n", " dump_performance_to_H5(h5name, ds_name, dataset)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": true }, "outputs": [], "source": [ "fig = plt.figure(figsize=(4, 4))\n", "\n", "with h5py.File(h5name, 'r') as f:\n", " perf = np.array(f['analysis']['performance_ALL'])\n", " x = perf[:, 6]\n", "\n", "ax = fig.add_subplot(111)\n", "\n", "ax.plot(x, perf[:, 0]) # performance\n", "ax.plot(x, perf[:, 3]) # chance\n", "ax.fill_between(x, perf[:, 0] + perf[:, 1], perf[:, 0] + perf[:, 2], alpha=0.4)\n", "ax.fill_between(x, perf[:, 3] + perf[:, 4], perf[:, 3] + perf[:, 5], alpha=0.4)\n", "ax.set_ylim(0, 110)\n", "ax.set_xlim(0, 65)\n", "ax.grid()\n", "ax.set_title(experiment_id[-19:], fontsize=14)\n", "ax.set_xlabel('Time, s', fontsize=14)\n", "\n", "if i == 0:\n", " ax.set_ylabel('Successful trials, %', fontsize=14)\n", " \n", "fig.tight_layout()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.13" } }, "nbformat": 4, "nbformat_minor": 2 }