mbednarski

from __future__ import print_function, division

import random

import numpy as np
import gym
import time
from sklearn.neighbors import NearestNeighbors

import logging

mbednarski

from __future__ import print_function, division
import itertools as iter

import random

import numpy as np
import gym
import time
from sklearn.neighbors import NearestNeighbors

mbednarski

from __future__ import print_function, division
import itertools as iter

import random

import numpy as np
import gym
from gym import wrappers

from sklearn.kernel_approximation import RBFSampler

mbednarski

from __future__ import print_function, division

import gym

import numpy as np
import matplotlib as plt
import logging
import matplotlib.pyplot as plt
logging.disable(logging.CRITICAL)
np.seterr('raise')

mbednarski

from __future__ import print_function, division

import gym

import numpy as np
import matplotlib as plt
import logging
import matplotlib.pyplot as plt
logging.disable(logging.CRITICAL)
np.seterr('raise')

mbednarski

from __future__ import print_function, division

import gym

import numpy as np
import matplotlib as plt
import logging
import matplotlib.pyplot as plt

logging.disable(logging.CRITICAL)

mbednarski

import click
import pandas as pd


def get_featues(dframe):
    return dframe[['x0', 'x1', 'x2', 'x3']]


def get_label(dframe):
    return dframe['y']

mbednarski

import click
import matplotlib

matplotlib.use('agg')
import seaborn as sns

import sys

sys.path.append('src')

mbednarski

from src.data import read_raw_data, preprocess_data, get_featues, get_label


def test_raw_shape():
    dframe = read_raw_data()
    assert dframe.shape == (150, 5)


def test_get_features_shape():
    dframe = read_raw_data()

mbednarski

import pickle
import sys

from sklearn.ensemble import RandomForestClassifier

sys.path.append('src')

from data import get_featues, get_label