def plot_session_from_file(session_df_filepath):
'''
Method to plot session from its session_df file
@example
from slm_lab.experiment import analysis
filepath = 'data/reinforce_cartpole_2018_01_22_211751/reinforce_cartpole_t0_s0_session_df.csv'
analysis.plot_session_from_file(filepath)
'''
from slm_lab.experiment.monitor import InfoSpace
spec_name = util.prepath_to_spec_name(session_df_filepath)
session_spec = {'name': spec_name}
session_df = util.read(session_df_filepath,
header=[0, 1, 2, 3],
index_col=0,
dtype=np.float32)
session_data = util.session_df_to_data(session_df)
tn, sn = session_df_filepath.replace('_session_df.csv', '').split('_')[-2:]
info_space = InfoSpace()
info_space.set('experiment', 0)
info_space.set('trial', int(tn[1:]))
info_space.set('session', int(sn[1:]))
session_fig = plot_session(session_spec, info_space, session_data)
viz.save_image(
session_fig,
session_df_filepath.replace('_session_df.csv', '_session_graph.png'))
def save_experiment_data(spec, info_space, experiment_df, experiment_fig):
'''Save the experiment data: best_spec, experiment_df, experiment_graph.'''
prepath = util.get_prepath(spec, info_space, unit='experiment')
logger.info(f'Saving experiment data to {prepath}')
util.write(experiment_df, f'{prepath}_experiment_df.csv')
viz.save_image(experiment_fig, f'{prepath}_experiment_graph.png')
# TODO tmp hack
plot_best_sessions(experiment_df, prepath)
def save_experiment_data(spec, info_space, experiment_df, experiment_fig):
'''Save the experiment data: best_spec, experiment_df, experiment_graph.'''
prepath = util.get_prepath(spec, info_space, unit='experiment')
logger.info(f'Saving experiment data to {prepath}')
util.write(experiment_df, f'{prepath}_experiment_df.csv')
viz.save_image(experiment_fig, f'{prepath}_experiment_graph.png')
# zip for ease of upload
predir, _, _, _, _, _ = util.prepath_split(prepath)
shutil.make_archive(predir, 'zip', predir)
logger.info(f'All experiment data zipped to {predir}.zip')
def save_experiment_data(info_space, best_spec, experiment_df, experiment_fig):
'''Save the experiment data: best_spec, experiment_df, experiment_graph.'''
spec_name = best_spec['name']
predir = f'data/{spec_name}_{info_space.experiment_ts}'
prename = f'{spec_name}'
logger.info(f'Saving experiment data to {predir}')
util.write(best_spec, f'{predir}/{prename}_best_spec.json')
util.write(experiment_df, f'{predir}/{prename}_experiment_df.csv')
viz.save_image(experiment_fig, f'{predir}/{prename}_experiment_graph.png')
plot_best_sessions(experiment_df, predir, prename)
def save_trial_data(spec, info_space, trial_fitness_df, trial_fig):
'''Save the trial data: spec, trial_fitness_df.'''
prepath = util.get_prepath(spec, info_space, unit='trial')
logger.info(f'Saving trial data to {prepath}')
util.write(trial_fitness_df, f'{prepath}_trial_fitness_df.csv')
viz.save_image(trial_fig, f'{prepath}_trial_graph.png')
if util.get_lab_mode() == ('train', 'eval'):
predir, _, _, _, _, _ = util.prepath_split(prepath)
shutil.make_archive(predir, 'zip', predir)
logger.info(f'All trial data zipped to {predir}.zip')
def save_session_data(session_spec, session_df, session_fig):
'''
Save the session data: df, plot.
session_df is multi-indexed with (a,e,b), 3 extra levels
to read, use:
session_df = util.read(filepath, header=[0, 1, 2, 3])
session_data = util.session_df_to_data(session_df)
'''
# TODO generalize to use experiment timestamp, id, sesison coor in info space, to replace timestamp
spec_name = session_spec['name']
prepath = f'data/{spec_name}/{spec_name}_{util.get_timestamp()}'
logger.info(f'Saving session data to {prepath}_*')
util.write(session_df, f'{prepath}_session_df.csv')
viz.save_image(session_fig, f'{prepath}_session_graph.png')
def save_session_data(spec, info_space, session_data, session_fitness_df, session_fig):
'''
Save the session data: session_df, session_fitness_df, session_graph.
session_data is saved as session_df; multi-indexed with (a,e,b), 3 extra levels
to read, use:
session_df = util.read(filepath, header=[0, 1, 2, 3])
session_data = util.session_df_to_data(session_df)
'''
prepath = util.get_prepath(spec, info_space, unit='session')
logger.info(f'Saving session data to {prepath}')
if 'retro_analyze' not in os.environ['PREPATH']:
session_df = pd.concat(session_data, axis=1)
util.write(session_df, f'{prepath}_session_df.csv')
util.write(session_fitness_df, f'{prepath}_session_fitness_df.csv')
viz.save_image(session_fig, f'{prepath}_session_graph.png')
def save_session_data(spec, info_space, session_data, session_fitness_df, session_fig, body_df_kind='eval'):
'''
Save the session data: session_df, session_fitness_df, session_graph.
session_data is saved as session_df; multi-indexed with (a,e,b), 3 extra levels
to read, use:
session_df = util.read(filepath, header=[0, 1, 2, 3], index_col=0)
session_data = util.session_df_to_data(session_df)
'''
prepath = util.get_prepath(spec, info_space, unit='session')
logger.info(f'Saving session data to {prepath}')
prefix = 'train' if body_df_kind == 'train' else ''
if 'retro_analyze' not in os.environ['PREPATH']:
save_session_df(session_data, f'{prepath}_{prefix}session_df.csv', info_space)
util.write(session_fitness_df, f'{prepath}_{prefix}session_fitness_df.csv')
viz.save_image(session_fig, f'{prepath}_{prefix}session_graph.png')
def plot_experiment_from_file(experiment_df_filepath):
'''
Method to plot experiment from its experiment_df file
@example
from slm_lab.experiment import analysis
filepath = 'data/reinforce_cartpole_2018_01_22_190720/reinforce_cartpole_experiment_df.csv'
analysis.plot_experiment_from_file(filepath)
'''
spec_name = '_'.join(experiment_df_filepath.split('/')[1].split('_')[:-4])
experiment_spec = {'name': spec_name}
experiment_df = util.read(experiment_df_filepath)
experiment_fig = plot_experiment(experiment_spec, experiment_df)
viz.save_image(
experiment_fig,
experiment_df_filepath.replace('_experiment_df.csv',
'_experiment_graph.png'))
def plot_session_from_file(session_df_filepath):
'''
Method to plot session from its session_df file
@example
from slm_lab.experiment import analysis
filepath = 'data/reinforce_cartpole_2018_01_22_211751/reinforce_cartpole_t0_s0_session_df.csv'
analysis.plot_session_from_file(filepath)
'''
spec_name = '_'.join(session_df_filepath.split('/')[1].split('_')[:-4])
session_spec = {'name': spec_name}
session_df = util.read(session_df_filepath, header=[0, 1, 2, 3])
session_data = util.session_df_to_data(session_df)
session_fig = plot_session(session_spec, session_data)
viz.save_image(
session_fig,
session_df_filepath.replace('_session_df.csv', '_session_graph.png'))
def save_session_data(spec, info_space, session_mdp_data, session_data, session_fitness_df, session_fig):
'''
Save the session data: session_mdp_df, session_df, session_fitness_df, session_graph.
session_data is saved as session_df; multi-indexed with (a,e,b), 3 extra levels
to read, use:
session_df = util.read(filepath, header=[0, 1, 2, 3])
session_data = util.session_df_to_data(session_df)
Likewise for session_mdp_df
'''
prepath = util.get_prepath(spec, info_space, unit='session')
logger.info(f'Saving session data to {prepath}')
if session_mdp_data is not None: # not from retro analysis
session_mdp_df = pd.concat(session_mdp_data, axis=1)
session_df = pd.concat(session_data, axis=1)
# TODO reactivate saving when get to the transition matrix research
# util.write(session_mdp_df, f'{prepath}_session_mdp_df.csv')
util.write(session_df, f'{prepath}_session_df.csv')
util.write(session_fitness_df, f'{prepath}_session_fitness_df.csv')
viz.save_image(session_fig, f'{prepath}_session_graph.png')
def save_session_data(spec, info_space, session_mdp_data, session_data, session_fitness_df, session_fig):
'''
Save the session data: session_mdp_df, session_df, session_fitness_df, session_graph.
session_data is saved as session_df; multi-indexed with (a,e,b), 3 extra levels
to read, use:
session_df = util.read(filepath, header=[0, 1, 2, 3])
session_data = util.session_df_to_data(session_df)
Likewise for session_mdp_df
'''
prepath = util.get_prepath(spec, info_space, unit='session')
logger.info(f'Saving session data to {prepath}')
if session_mdp_data is not None: # not from retro analysis
session_mdp_df = pd.concat(session_mdp_data, axis=1)
session_df = pd.concat(session_data, axis=1)
# TODO reactivate saving when get to the transition matrix research
# util.write(session_mdp_df, f'{prepath}_session_mdp_df.csv')
util.write(session_df, f'{prepath}_session_df.csv')
util.write(session_fitness_df, f'{prepath}_session_fitness_df.csv')
# TODO replaced by plot_best_sessions until Feb 2018 https://github.com/plotly/plotly.py/issues/880
if os.environ.get('lab_mode') == 'train':
viz.save_image(session_fig, f'{prepath}_session_graph.png')
def plot_session_from_file(session_df_filepath):
'''
Method to plot session from its session_df file
@example
from slm_lab.experiment import analysis
filepath = 'data/reinforce_cartpole_2018_01_22_211751/reinforce_cartpole_t0_s0_session_df.csv'
analysis.plot_session_from_file(filepath)
'''
from slm_lab.experiment.monitor import InfoSpace
spec_name = util.prepath_to_spec_name(session_df_filepath)
session_spec = {'name': spec_name}
session_df = util.read(session_df_filepath, header=[0, 1, 2, 3], index_col=0, dtype=np.float32)
session_data = util.session_df_to_data(session_df)
tn, sn = session_df_filepath.replace('_session_df.csv', '').split('_')[-2:]
info_space = InfoSpace()
info_space.set('experiment', 0)
info_space.set('trial', int(tn[1:]))
info_space.set('session', int(sn[1:]))
session_fig = plot_session(session_spec, info_space, session_data)
viz.save_image(session_fig, session_df_filepath.replace('_session_df.csv', '_session_graph.png'))
def save_trial_data(spec, info_space, trial_fitness_df, trial_fig):
'''Save the trial data: spec, trial_fitness_df.'''
prepath = util.get_prepath(spec, info_space, unit='trial')
logger.info(f'Saving trial data to {prepath}')
util.write(trial_fitness_df, f'{prepath}_trial_fitness_df.csv')
viz.save_image(trial_fig, f'{prepath}_trial_graph.png')
def save_experiment_data(spec, info_space, experiment_df, experiment_fig):
'''Save the experiment data: best_spec, experiment_df, experiment_graph.'''
prepath = util.get_prepath(spec, info_space, unit='experiment')
logger.info(f'Saving experiment data to {prepath}')
util.write(experiment_df, f'{prepath}_experiment_df.csv')
viz.save_image(experiment_fig, f'{prepath}_experiment_graph.png')
def save_trial_data(spec, info_space, trial_fitness_df, trial_fig):
'''Save the trial data: spec, trial_fitness_df.'''
prepath = util.get_prepath(spec, info_space, unit='trial')
logger.info(f'Saving trial data to {prepath}')
util.write(trial_fitness_df, f'{prepath}_trial_fitness_df.csv')
viz.save_image(trial_fig, f'{prepath}_trial_graph.png')
