#!/usr/bin/env python
# coding: utf-8

# # OPTaaS Quick Start
# 
# ### <span style="color:red">Note:</span> To run this notebook, you need an API Key. You can get one <a href="mailto:charles.brecque@mindfoundry.ai">here</a>.
# 
# More tutorials are [available here](./)

# ## Connect to OPTaaS using your API Key

# In[1]:


from mindfoundry.optaas.client.client import OPTaaSClient

client = OPTaaSClient('https://optaas.mindfoundry.ai', '<Your OPTaaS API key>')


# ## Define your parameters

# In[2]:


from mindfoundry.optaas.client.parameter import IntParameter, FloatParameter, CategoricalParameter, BoolParameter, \
    ChoiceParameter, GroupParameter

bool_param = BoolParameter('my_bool')
cat_param = CategoricalParameter('my_cat', values=['a', 'b', 'c'], default='c')

int_param = IntParameter('my_int', minimum=0, maximum=20)
optional_int_param = IntParameter('my_optional_int', minimum=-10, maximum=10, optional=True)

parameters = [
    bool_param,
    cat_param,
    ChoiceParameter('ints_or_floats', choices=[
        GroupParameter('ints', items=[int_param, optional_int_param]),
        GroupParameter('floats', items=[
            FloatParameter('float1', minimum=0, maximum=1),
            FloatParameter('float2', minimum=0.5, maximum=4.5)
        ])
    ]),
]


# ## Define your scoring function
# 
# The argument names in your scoring function must match the parameter names you defined above.
# 
# Your function can return just a score, or a tuple of (score, variance).

# In[3]:


def scoring_function(my_bool, my_cat, ints_or_floats):
    score = 5 if my_bool is True else -5
    score += 1 if my_cat == 'a' else 3
    if 'ints' in ints_or_floats:
        score += sum(ints_or_floats['ints'].values())
    else:
        score *= sum(ints_or_floats['floats'].values())
    return score


# ## Create your Task
# 
# You can use Goal.max or Goal.min as appropriate. You can also specify the minimum and maximum score values (if known).

# In[4]:


from mindfoundry.optaas.client.client import Goal

task = client.create_task(
    title='Quick Start Example Task',
    parameters=parameters,
    goal=Goal.max,
    min_known_score=-22,
    max_known_score=44
)


# ## Run your Task
# 
# We will run for a maximum of 50 iterations, but we will stop as soon as we reach our score threshold of 32.
# 
# The score threshold is optional - you can omit it and simply run as many iterations as you need.

# In[5]:


best_result = task.run(scoring_function, max_iterations=50, score_threshold=32)
print("Best Result:", best_result)