from utils.experiment_utils import setup_experiments
from collections import OrderedDict

# when running an experiment override the parameter you're interested in
base_experiment = OrderedDict([
    ('id', 'exp'),
    ('epoch', 10000),  # nr epochs
    ('nr_points', 1000),  # nr test examples
    ('sensors', np.array([0, 0, 10, 0])),  # sensor locations [s1_x, s1_y, s2_x, s2_y .. ]
    ('sigma', 1),  # sigma for gaussian noise on output vector
    ('grid_width', 10),  # grid width
    ('grid_height', 10),  # grid height
    ('nh_1', 4),  # nr units in first hidden layer
    ('loss_function', 'categorical_crossentropy'),  # loss function
    ('hidden_activation', 'tanh'),  # activation for hidden layers
    ('output_activation', 'sigmoid'),  # final activation
    ('optimizer', 'adam')  # optimizer
])


# what experiments do we want to run
exp_settings = [
    {'param': 'nh_1', 'values': np.arange(1, 17)},                         # test nr hidden layers
    {'param': 'optimizer', 'values': ['sgd', 'adam']},                     # optimizing algorithms
    {'param': 'sigma', 'values': [0, 0.5, 1, 2]},                          # sigma
    {'param': 'hidden_activation', 'values': ['tanh', 'relu']},            # activation for hidden layer
    {'param': 'output_activation', 'values': ['sigmoid', 'softmax']},      # activation for output layer
    {'param': 'nr_points', 'values': [100, 500, 1000, 2500, 5000, 10000]}  # nr training examples
]

experiments = setup_experiments(exp_settings, base_experiment)