def test_neuralNetwork_set():
inputs = 6
outputs = 4
layers = 3
neurons = 87
nn = NeuralNetwork(inputs=inputs,
outputs=outputs,
layers=layers,
neurons=neurons)
new_inputs = 35
new_outputs = 23
new_layers = 3
new_neurons = 10
# Only the inputs should change
nn.set(inputs=new_inputs)
assert nn.inputs == new_inputs
assert nn.outputs == outputs
assert nn.layers == layers
assert nn.neurons == neurons
# Only the inputs and the outputs should have changed
nn.set(outputs=new_outputs)
assert nn.inputs == new_inputs
assert nn.outputs == new_outputs
assert nn.layers == layers
assert nn.neurons == neurons
# Inputs, outputs, and the number of layers should have changed
nn.set(layers=new_layers)
assert nn.inputs == new_inputs
assert nn.outputs == new_outputs
assert nn.layers == new_layers
assert nn.neurons == neurons
# All the values should be new at this point
nn.set(neurons=new_neurons)
assert nn.inputs == new_inputs
assert nn.outputs == new_outputs
assert nn.layers == new_layers
assert nn.neurons == new_neurons
