def decode(solution):
"""Convert solution into dict of hyperparameters."""
# Start with out stationary (locked) paramaters
hyperparameters = locked_values
# Obtain moving hyperparameters from binary solution
index = 0
for name, parameters in meta_parameters.items():
# Obtain binary for this hyperparameter
binary_size = parameters['binary_size']
binary = solution[index:index + binary_size]
index += binary_size # Just index to start of next hyperparameter
# Decode binary
if parameters['type'] == 'discrete':
i = helpers.binary_to_int(
binary, upper_bound=len(parameters['values']) - 1)
value = parameters['values'][i]
elif parameters['type'] == 'int':
value = helpers.binary_to_int(binary,
offset=parameters['min'],
upper_bound=parameters['max'])
elif parameters['type'] == 'float':
value = helpers.binary_to_float(binary,
minimum=parameters['min'],
maximum=parameters['max'])
else:
raise ValueError(
'Parameter type "{}" does not match known values'.format(
parameters['type']))
# Store value
hyperparameters[name] = value
return hyperparameters
def test_binary_to_float_neg_lower_bound():
assert helpers.binary_to_float([0], -1.0, 1.0) == -1.0
assert helpers.binary_to_float([1], -1.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0], -1.0, 1.0) == -1.0
assert _approx_equal(helpers.binary_to_float([0, 1], -1.0, 1.0), -0.3333333333)
assert _approx_equal(helpers.binary_to_float([1, 0], -1.0, 1.0), 0.3333333333)
assert helpers.binary_to_float([1, 1], -1.0, 1.0) == 1.0
def test_binary_to_float_neg_lower_and_upper_bound():
assert helpers.binary_to_float([0], -2.0, -1.0) == -2.0
assert helpers.binary_to_float([1], -2.0, -1.0) == -1.0
assert helpers.binary_to_float([0, 0], -2.0, -1.0) == -2.0
assert _approx_equal(helpers.binary_to_float([0, 1], -2.0, -1.0), -1.6666666666)
assert _approx_equal(helpers.binary_to_float([1, 0], -2.0, -1.0), -1.3333333333)
assert helpers.binary_to_float([1, 1], -2.0, -1.0) == -1.0
def test_binary_to_float_neg_lower_and_upper_bound():
assert helpers.binary_to_float([0], -2.0, -1.0) == -2.0
assert helpers.binary_to_float([1], -2.0, -1.0) == -1.0
assert helpers.binary_to_float([0, 0], -2.0, -1.0) == -2.0
assert _approx_equal(helpers.binary_to_float([0, 1], -2.0, -1.0),
-1.6666666666)
assert _approx_equal(helpers.binary_to_float([1, 0], -2.0, -1.0),
-1.3333333333)
assert helpers.binary_to_float([1, 1], -2.0, -1.0) == -1.0
def test_binary_to_float_neg_lower_bound():
assert helpers.binary_to_float([0], -1.0, 1.0) == -1.0
assert helpers.binary_to_float([1], -1.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0], -1.0, 1.0) == -1.0
assert _approx_equal(helpers.binary_to_float([0, 1], -1.0, 1.0),
-0.3333333333)
assert _approx_equal(helpers.binary_to_float([1, 0], -1.0, 1.0),
0.3333333333)
assert helpers.binary_to_float([1, 1], -1.0, 1.0) == 1.0
def decode(solution):
"""Convert solution into dict of hyperparameters."""
# Start with out stationary (locked) paramaters
hyperparameters = copy.deepcopy(locked_values)
# Obtain moving hyperparameters from binary solution
index = 0
for name, parameters in meta_parameters.iteritems():
# Obtain binary for this hyperparameter
binary_size = parameters['binary_size']
binary = solution[index:index + binary_size]
index += binary_size # Just index to start of next hyperparameter
# Decode binary
if parameters['type'] == 'discrete':
i = helpers.binary_to_int(
binary, upper_bound=len(parameters['values']) - 1)
value = parameters['values'][i]
elif parameters['type'] == 'int':
value = helpers.binary_to_int(
binary,
lower_bound=parameters['min'],
upper_bound=parameters['max'])
elif parameters['type'] == 'float':
value = helpers.binary_to_float(
binary,
lower_bound=parameters['min'],
upper_bound=parameters['max'])
else:
raise ValueError(
'Parameter type "{}" does not match known values'.format(
parameters['type']))
# Store value
hyperparameters[name] = value
return hyperparameters
def decode_binary(binary, min_, max_):
# Helpful functions from helpers are used to convert binary to floats
x1 = helpers.binary_to_float(binary[0:16], min_, max_)
x2 = helpers.binary_to_float(binary[16:32], min_, max_)
return x1, x2
def decode_ackley(binary):
# Helpful functions from helpers are used to convert binary to float
# x1 and x2 range from -5.0 to 5.0
x1 = helpers.binary_to_float(binary[0:16], -5.0, 5.0)
x2 = helpers.binary_to_float(binary[16:32], -5.0, 5.0)
return x1, x2
def decode_param(binary):
learning_rate = helpers.binary_to_float(binary[0:16], 0.4, 1.0)
neuron = helpers.binary_to_int(binary[16:32], 10, 15)
return learning_rate, neuron
def test_binary_to_float_zero_one_bounds():
assert helpers.binary_to_float([0], 0.0, 1.0) == 0.0
assert helpers.binary_to_float([1], 0.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0], 0.0, 1.0) == 0.0
assert _approx_equal(helpers.binary_to_float([0, 1], 0.0, 1.0),
0.3333333333)
assert _approx_equal(helpers.binary_to_float([1, 0], 0.0, 1.0),
0.6666666666)
assert helpers.binary_to_float([1, 1], 0.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0, 0], 0.0, 1.0) == 0.0
assert _approx_equal(helpers.binary_to_float([0, 0, 1], 0.0, 1.0),
0.14285714285714285)
assert _approx_equal(helpers.binary_to_float([0, 1, 0], 0.0, 1.0),
0.2857142857142857)
assert _approx_equal(helpers.binary_to_float([0, 1, 1], 0.0, 1.0),
0.42857142857142855)
assert _approx_equal(helpers.binary_to_float([1, 0, 0], 0.0, 1.0),
0.5714285714285714)
assert _approx_equal(helpers.binary_to_float([1, 0, 1], 0.0, 1.0),
0.7142857142857142)
assert _approx_equal(helpers.binary_to_float([1, 1, 0], 0.0, 1.0),
0.8571428571428571)
assert helpers.binary_to_float([1, 1, 1], 0.0, 1.0) == 1.0
def test_binary_to_float_empty_binary_list():
"""An empty list can represent one value, and defaults to lower_bound."""
assert helpers.binary_to_float([], 0.0, 1.0) == 0.0
def test_binary_to_float_zero_one_bounds():
assert helpers.binary_to_float([0], 0.0, 1.0) == 0.0
assert helpers.binary_to_float([1], 0.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0], 0.0, 1.0) == 0.0
assert _approx_equal(
helpers.binary_to_float([0, 1], 0.0, 1.0), 0.3333333333)
assert _approx_equal(
helpers.binary_to_float([1, 0], 0.0, 1.0), 0.6666666666)
assert helpers.binary_to_float([1, 1], 0.0, 1.0) == 1.0
assert helpers.binary_to_float([0, 0, 0], 0.0, 1.0) == 0.0
assert _approx_equal(
helpers.binary_to_float([0, 0, 1], 0.0, 1.0), 0.14285714285714285)
assert _approx_equal(
helpers.binary_to_float([0, 1, 0], 0.0, 1.0), 0.2857142857142857)
assert _approx_equal(
helpers.binary_to_float([0, 1, 1], 0.0, 1.0), 0.42857142857142855)
assert _approx_equal(
helpers.binary_to_float([1, 0, 0], 0.0, 1.0), 0.5714285714285714)
assert _approx_equal(
helpers.binary_to_float([1, 0, 1], 0.0, 1.0), 0.7142857142857142)
assert _approx_equal(
helpers.binary_to_float([1, 1, 0], 0.0, 1.0), 0.8571428571428571)
assert helpers.binary_to_float([1, 1, 1], 0.0, 1.0) == 1.0
def test_binary_to_float_empty_binary_list():
"""An empty list can represent one value, and defaults to lower_bound."""
assert helpers.binary_to_float([], 0.0, 1.0) == 0.0
def decode_anfisga_search_space(binary):
sigma_lb = helpers.binary_to_float(binary[0:16], 0.25, 5)
sigma_ub = helpers.binary_to_float(binary[16:32], 5, 10)
return sigma_lb, sigma_ub
def decode_svmga_search_space(binary):
c = helpers.binary_to_float(binary[0:16], 1, 20.0)
epsilon = helpers.binary_to_float(binary[16:32], 0.001, 0.01)
return c, epsilon
def decode_small_binary(binary, min_, max_):
x1 = helpers.binary_to_float(binary[0:6], min_, max_)
x2 = helpers.binary_to_float(binary[6:12], min_, max_)
return x1, x2
