io_data.py

import csv
import numpy as np

def get_data(csv_name, one_hot):
    data_x = []
    labels = []

    with open(csv_name, 'r') as f:
        next(f, None)
        reader = csv.reader(f)
        for row in reader:
            data_x.append(row[1:])
            labels.append(row[0])

    # train_x = [int(x) for x in row for row in train_x]
    # labels = [int(x) for x in labels]
    data_x = np.array(data_x, dtype=np.int32)
    labels = np.array(labels, dtype=np.int32)

    data_x = data_x.astype(dtype=np.float32)

    if one_hot:
        a = np.array(labels)
        b = np.zeros((len(labels), 225))
        b[np.arange(len(labels)), a] = 1
        data_y = b
    else:
        data_y = labels

    return data_x, data_y


def get_train_test_data(one_hot = True):
    data_x, data_y = get_data('data/data.csv', one_hot)
    data_cnt = len(data_x)
    train_cnt = data_cnt*3//4
    train_x = data_x[0:train_cnt]
    train_y = data_y[0:train_cnt]
    test_x = data_x[train_cnt:]
    test_y = data_y[train_cnt:]


    print(train_x)
    print(train_y)
    print(test_x)
    print(test_y)


    return train_x, train_y, test_x, test_y

"""
def get_train_data(one_hot = True):
    return get_data('data/train.csv', one_hot)


def get_test_data(one_hot = True):
    return get_data('data/test.csv', one_hot)
"""

"""
def save_result(pred_y):
    with open('data/result.csv', 'w') as f:
        writer = csv.writer(f)
        writer.writerow(["Id", "Label"])
        for idx, y in zip(range(1, len(pred_y)+1), pred_y):
            writer.writerow([idx, y])
"""