"""

Testing code for different neural network configurations.

Adapted for Python 3.5.2

Usage in shell:

python3.5 test.py

Network (network.py and network2.py) parameters:

2nd param is epochs count

3rd param is batch size

4th param is learning rate (eta)

Author:

Michał Dobrzański, 2016

dobrzanski.michal.daniel@gmail.com

"""

# ----------------------

# - read the input data:

import mnist_loader

import numpy as np

training_data, validation_data, test_data = mnist_loader.load_data_wrapper()

training_data = list(training_data)

# ---------------------

import matplotlib.pyplot as plt

# plot first 5 data

plt.figure(figsize=(10, 6))

for i in range(5):

plt.subplot(1, 5, i+1)

plt.imshow(np.array(training_data[i][0]).reshape(28, 28), cmap='gray')

plt.title(f"Label: {np.argmax(training_data[i][1])}")

plt.tight_layout()

plt.show()

# ---------------------

# - network.py example:

import network

net = network.Network([784, 30, 10])

net.SGD(training_data, 30, 10, 3.0, test_data=test_data)