Esempio n. 1
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def test_descriptive_stats():
    check_values = []

    scheduler = HistoricNetworkScheduler(0, 1000)
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])

    max_value = Max(network, values)
    min_value = Min(network, values)
    avg = Mean(network, values)
    stddev = Stddev(network, values)

    check_values.extend([max_value, min_value, avg, stddev])

    # noinspection PyUnusedLocal
    def print_stats(params):
        print(f"min = {min_value.get_value()}; max = {max_value.get_value()}; "
              f"avg = {avg.get_value():.2f}; stddev = {stddev.get_value():.2f}")

    Lambda(network, [min_value, max_value, avg, stddev], print_stats)

    scheduler.run()
    assert check_values[0].get_value() == 8.3
    assert check_values[1].get_value() == 0.0
    assert math.isclose(check_values[2].get_value(), 3.7, abs_tol=0.00001)
    assert math.isclose(check_values[3].get_value(), 3.24507, abs_tol=0.00001)
Esempio n. 2
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async def main():
    scheduler = RealtimeNetworkScheduler()
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])
    mapper = Map(network, values, lambda x: round(x))
    accumulator = Scan(network, mapper)
    Do(network, accumulator, lambda: print(f"{accumulator.get_value()}"))
Esempio n. 3
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def test_filter():
    scheduler = HistoricNetworkScheduler(0, 30 * 1000)
    network = scheduler.get_network()
    values = From(scheduler, [0.0, -3.2, 2.1, -2.9, 8.3, -5.7])
    filt = Filter(network, values, lambda x: x >= 0.0)
    Do(network, filt, lambda: print(f'{filt.get_value()}'))
    scheduler.run()
    assert filt.get_value() == 8.3
Esempio n. 4
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def test_map_reduce():
    scheduler = HistoricNetworkScheduler(0, 30 * 1000)
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])
    mapper = Map(network, values, lambda x: round(x))
    accumulator = Scan(network, mapper)
    Do(network, accumulator, lambda: print(f'{accumulator.get_value()}'))
    scheduler.run()
    assert accumulator.get_value() == 22.0
Esempio n. 5
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def test_running_sum():
    check_values = []

    scheduler = HistoricNetworkScheduler(0, 1000)
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])
    total = RunningSum(network, values)
    check_values.append(total)
    Lambda(network, total, lambda x: print(f'{x[0].get_value():.2f}'))

    scheduler.run()
    assert check_values[0].get_value() == 22.2
Esempio n. 6
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async def main():
    scheduler = RealtimeNetworkScheduler()
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])

    max_value = Max(network, values)
    min_value = Min(network, values)
    avg = Mean(network, values)
    stddev = Stddev(network, values)

    # noinspection PyUnusedLocal
    def print_stats(params):
        print(
            f"min = {min_value.get_value()}; max = {max_value.get_value()}; "
            f"avg = {avg.get_value():.2f}; stddev = {stddev.get_value():.2f}")

    Lambda(network, [min_value, max_value, avg, stddev], print_stats)
Esempio n. 7
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async def main():
    scheduler = RealtimeNetworkScheduler()
    network = scheduler.get_network()
    values = From(scheduler, [0.0, 3.2, 2.1, 2.9, 8.3, 5.7])
    total = RunningSum(network, values)
    Lambda(network, total, lambda x: print(f'{x[0].get_value():.2f}'))
Esempio n. 8
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def test_hello_world():
    scheduler = HistoricNetworkScheduler(0, 30 * 1000)
    signal = From(scheduler, ['world'])
    Do(scheduler.get_network(), signal,
       lambda: print(f'Hello, {signal.get_value()}!'))
    scheduler.run()
Esempio n. 9
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async def main():
    scheduler = RealtimeNetworkScheduler()
    signal = From(scheduler, ["world"])
    Do(scheduler.get_network(), signal,
       lambda: print(f"Hello, {signal.get_value()}!"))
Esempio n. 10
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async def main():
    scheduler = RealtimeNetworkScheduler()
    network = scheduler.get_network()
    values = From(scheduler, [0.0, -3.2, 2.1, -2.9, 8.3, -5.7])
    filt = Filter(network, values, lambda x: x >= 0.0)
    Do(network, filt, lambda: print(f"{filt.get_value()}"))