import os
import time
import logging
logging.basicConfig(
format="%(levelname)s:%(asctime)s %(message)s",
datefmt="%m/%d/%Y %I:%M:%S %p",
level=logging.DEBUG,
filename=os.getenv("LOGFILE"),
)
LOGGER = logging.getLogger(__name__)
timestr = time.strftime("%Y%m%d-%H%M%S")
[docs]def prepare_data_decicion_lib(data_set: object, columns: list = None) -> tuple():
"""
only for scikit learn datasets
"""
if columns is None:
X = data_set.data[:, :2]
else:
assert (
len(columns) == 2
), "Length of the columns input must be equalt to two. Otherwise the plotting of the decision boundary can't work"
X = np.zeros((len(data_set.target), 2))
X[:, 0] = data_set.data[:, columns[0]]
X[:, 1] = data_set.data[:, columns[1]]
y = data_set.target
return (X, y)
[docs]def get_grid_positions(rows: int, cols: int):
grid = []
for i in range(2, rows):
for j in range(cols):
grid.append((i, j))
return grid