for testing and deploying your application
for finding and fixing issues
for empowering human code reviews
"""
Hyperactive is very versatile, because of it can handle not just numerical or
string variables in the search space, but also functions. This enables many
possibilities for more complex optimization applications. Neural architecture search,
feature engineering, ensemble optimization and many other applications are
only possible or much easier, if you can put functions in the search space.
from hyperactive import Hyperactive
def function_0():
pass
def function_1():
def function_2():
def list1():
return [1, 0, 0]
def list2():
return [0, 1, 0]
def list3():
return [0, 0, 1]
# Hyperactive can handle python objects in the search space
search_space = {
"int": list(range(1, 10)),
"float": [0.1, 0.01, 0.001],
"string": ["string1", "string2"],
"function": [function_0, function_1, function_2],
"list": [list1, list2, list3],
}
def objective_function(para):
# score must be a single number
score = 1
return score
hyper = Hyperactive()
hyper.add_search(objective_function, search_space, n_iter=20)
hyper.run()
search_data = hyper.results(objective_function)
print("\n Search Data: \n", search_data)
SimonBlanke /
Hyperactive
