-
Notifications
You must be signed in to change notification settings - Fork 0
/
utils.py
36 lines (28 loc) · 1.22 KB
/
utils.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
import csv
import numpy as np
def read_csv(filename):
return np.genfromtxt(filename, dtype=np.float, delimiter=",")
def train_test_split(data, split_ratio=0.7):
"""Splits data into training and test set according to the split_ratio.
Arguments:
data: dataset as a numpy array
split_ratio: fraction of dataset to split as training data (must be between 0 and 1)
Returns:
Training Data (size = split_ratio * size of original dataset)
Test Data (size = (1 - split_ratio) * size of original dataset)
"""
np.random.shuffle(data)
train_data, test_data = data[:int(split_ratio *
len(data)), :], data[int(split_ratio *
len(data)):, :]
return train_data, test_data
def format_constant_c(name, constant):
# <Insert smug remark about left-pad>
if len(name) < 37:
padding = " " * (38 - len(name) - len("#define "))
else:
padding = "\t"
return "#define {}{}{}".format(name, padding, constant)
def format_array_c(name, array, dtype="float"):
contents = ", ".join(map(str, array))
return "{} {}[{}] = {{{}}};".format(dtype, name, len(array), contents)