# Measure performance

import numpy as np
from lab import neural, io_mnist

def computePrecision(net):
	"""
	Test performance of provided network.

	net : the network to be assessed

	return : ratio of good answers in [0.0 ; 1.0]
	"""

	np_images, np_expected = io_mnist.load_testing_samples()

	nbSamples = np_images.shape[1]

	nbSuccess = 0

	for k in range(nbSamples):
		a0 = np_images[:, k]

		z1 = net.layer1 @ a0 + net.bias1
		a1 = net.activationFunction(z1)

		z2 = net.layer2 @ a1 + net.bias2
		a2 = net.activationFunction(z2)

		# Verify index of highest probability
		if (np.argmax(a2) == np.argmax(np_expected[:,k])):
			nbSuccess += 1

	return nbSuccess / nbSamples