def test_probabilities():
"""Tests aggregated probabilities for multiple measurementr in a workflow."""
# 3-dimensional model, 2-events time window
model = AngularModel(3, 2)
# Define an input data sequence (tau = 2)
input_data = list()
input_data.append([0.8, 0.8, 1])
input_data.append([0.9, 0.6, 0.9])
# Encode the sequence in the model
for t in range(model.tau):
for dim in range(model.n):
model.encode(input_data[t][dim], dim)
# Check if at least 70% of the shots are 111 (coherent with the input)
shots = 10000
result = model.measure(shots)
assert result["111"] / shots >= 0.7
# Check again for a different input
model.clear()
# Define an input data sequence (tau = 2)
input_data = list()
input_data.append([0.1, 0.2, 1])
input_data.append([0.0, 0.1, 0.9])
# Encode the sequence in the model
for t in range(model.tau):
for dim in range(model.n):
model.encode(input_data[t][dim], dim)
# Check if at least 70% of the shots are 111 (coherent with the input)
result = model.measure(shots)
assert result["100"] / shots >= 0.8
def test_clear():
"""Tests if clear is working correctly"""
model = AngularModel(n=2, tau=2)
model.clear()