(config)
return (
        'exp_name:   ' + str(common['experiment_name'])              + '\n' +
        'alg_type:   ' + str(algorithm['type'].__name__)             + '\n' +
        'alg_dyn:    ' + alg_dyn + '\n' +
        'alg_cost:   ' + str(algorithm_cost_type)                    + '\n' +
        'iterations: ' + str(config['iterations'])                   + '\n' +
        'conditions: ' + str(algorithm['conditions'])                + '\n' +
        'samples:    ' + str(config['num_samples'])                  + '\n'
    )
Generate experiment info, to be displayed by GPS Trainig GUI.
    Assumes config is the config created in hyperparams.py
Generate experiment info, to be displayed by GPS Trainig GUI.
    Assumes config is the config created in hyperparams.py
Generate experiment info to be displayed by GPS Trainig GUI . Assumes config is the config created in hyperparams . py
def generate_experiment_info(config):
    """
    Generate experiment info, to be displayed by GPS Trainig GUI.
    Assumes config is the config created in hyperparams.py
    """
    common = config['common']
    algorithm = config['algorithm']

    if type(algorithm['cost']) == list:
        algorithm_cost_type = algorithm['cost'][0]['type'].__name__
        if (algorithm_cost_type) == 'CostSum':
            algorithm_cost_type += '(%s)' % ', '.join(
                    map(lambda cost: cost['type'].__name__,
                        algorithm['cost'][0]['costs']))
    else:
        algorithm_cost_type = algorithm['cost']['type'].__name__
        if (algorithm_cost_type) == 'CostSum':
            algorithm_cost_type += '(%s)' % ', '.join(
                    map(lambda cost: cost['type'].__name__,
                        algorithm['cost']['costs']))

    if 'dynamics' in algorithm:        
        alg_dyn = str(algorithm['dynamics']['type'].__name__)
    else:
        alg_dyn = 'None'       

    return (
        'exp_name:   ' + str(common['experiment_name'])              + '\n' +
        'alg_type:   ' + str(algorithm['type'].__name__)             + '\n' +
        'alg_dyn:    ' + alg_dyn + '\n' +
        'alg_cost:   ' + str(algorithm_cost_type)                    + '\n' +
        'iterations: ' + str(config['iterations'])                   + '\n' +
        'conditions: ' + str(algorithm['conditions'])                + '\n' +
        'samples:    ' + str(config['num_samples'])                  + '\n'
    )
def generate_experiment_info ( config ) : common = config [ 'common' ] algorithm = config [ 'algorithm' ] if type ( algorithm [ 'cost' ] ) == list : algorithm_cost_type = algorithm [ 'cost' ] [ 0 ] [ 'type' ] . __name__ if ( algorithm_cost_type ) == 'CostSum' : algorithm_cost_type += '(%s)' % ', ' . join ( map ( lambda cost : cost [ 'type' ] . __name__ , algorithm [ 'cost' ] [ 0 ] [ 'costs' ] ) ) else : algorithm_cost_type = algorithm [ 'cost' ] [ 'type' ] . __name__ if ( algorithm_cost_type ) == 'CostSum' : algorithm_cost_type += '(%s)' % ', ' . join ( map ( lambda cost : cost [ 'type' ] . __name__ , algorithm [ 'cost' ] [ 'costs' ] ) ) if 'dynamics' in algorithm : alg_dyn = str ( algorithm [ 'dynamics' ] [ 'type' ] . __name__ ) else : alg_dyn = 'None' return ( 'exp_name:   ' + str ( common [ 'experiment_name' ] ) + '\n' + 'alg_type:   ' + str ( algorithm [ 'type' ] . __name__ ) + '\n' + 'alg_dyn:    ' + alg_dyn + '\n' + 'alg_cost:   ' + str ( algorithm_cost_type ) + '\n' + 'iterations: ' + str ( config [ 'iterations' ] ) + '\n' + 'conditions: ' + str ( algorithm [ 'conditions' ] ) + '\n' + 'samples:    ' + str ( config [ 'num_samples' ] ) + '\n' )