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Add Analog Stream Writer tests (#515)
* Add Analog Stream Writer tests
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import ctypes | ||
from typing import Callable | ||
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import numpy | ||
import pytest | ||
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import nidaqmx | ||
from nidaqmx.stream_writers import ( | ||
AnalogMultiChannelWriter, | ||
AnalogSingleChannelWriter, | ||
AnalogUnscaledWriter, | ||
) | ||
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def _get_expected_voltage_for_chan(chan_index: int) -> float: | ||
return float(chan_index + 1) | ||
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def _volts_to_codes(volts: float, max_code: int = 32767, max_voltage: float = 10.1) -> int: | ||
return int(volts * max_code / max_voltage) | ||
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VOLTAGE_EPSILON = 1e-3 | ||
# NOTE: You can't scale from volts to codes correctly without knowing the internal calibration | ||
# constants. The internal reference has a healthy amount of overrange to ensure we can calibrate to | ||
# device specifications. I've used 10.1 volts above to approximate that, but 100mv of accuracy is | ||
# also fine since the expected output of each channel value will be 1 volt apart. | ||
VOLTAGE_EPSILON_FOR_RAW = 1e-1 | ||
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@pytest.fixture | ||
def ao_single_channel_task( | ||
generate_task: Callable[[], nidaqmx.Task], | ||
real_x_series_multiplexed_device: nidaqmx.system.Device, | ||
) -> nidaqmx.Task: | ||
task = generate_task() | ||
chan_index = 0 | ||
offset = _get_expected_voltage_for_chan(chan_index) | ||
chan = task.ao_channels.add_ao_voltage_chan( | ||
real_x_series_multiplexed_device.ao_physical_chans[chan_index].name, | ||
min_val=0.0, | ||
max_val=offset + VOLTAGE_EPSILON, | ||
) | ||
# forcing the maximum range for binary read scaling to be predictable | ||
chan.ao_dac_rng_high = 10 | ||
chan.ao_dac_rng_low = -10 | ||
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# we'll be doing simple on-demand, so start the task now | ||
task.start() | ||
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# set the output to a known initial value | ||
task.write(0.0) | ||
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return task | ||
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@pytest.fixture | ||
def ai_single_channel_loopback_task( | ||
generate_task: Callable[[], nidaqmx.Task], | ||
real_x_series_multiplexed_device: nidaqmx.system.Device, | ||
) -> nidaqmx.Task: | ||
task = generate_task() | ||
chan_index = 0 | ||
task.ai_channels.add_ai_voltage_chan( | ||
f"{real_x_series_multiplexed_device.name}/_ao{chan_index}_vs_aognd", | ||
min_val=-10, | ||
max_val=10, | ||
) | ||
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# we'll be doing simple on-demand, so start the task now | ||
task.start() | ||
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return task | ||
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@pytest.fixture | ||
def ao_multi_channel_task( | ||
generate_task: Callable[[], nidaqmx.Task], | ||
real_x_series_multiplexed_device: nidaqmx.system.Device, | ||
) -> nidaqmx.Task: | ||
task = generate_task() | ||
num_chans = 2 | ||
for chan_index in range(num_chans): | ||
offset = _get_expected_voltage_for_chan(chan_index) | ||
chan = task.ao_channels.add_ao_voltage_chan( | ||
real_x_series_multiplexed_device.ao_physical_chans[chan_index].name, | ||
min_val=0.0, | ||
max_val=offset + VOLTAGE_EPSILON, | ||
) | ||
# forcing the maximum range for binary read scaling to be predictable | ||
chan.ao_dac_rng_high = 10 | ||
chan.ao_dac_rng_low = -10 | ||
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# we'll be doing simple on-demand, so start the task now | ||
task.start() | ||
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# set the output to a known initial value | ||
task.write([0.0 for _ in range(num_chans)]) | ||
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return task | ||
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@pytest.fixture | ||
def ai_multi_channel_loopback_task( | ||
generate_task: Callable[[], nidaqmx.Task], | ||
real_x_series_multiplexed_device: nidaqmx.system.Device, | ||
) -> nidaqmx.Task: | ||
task = generate_task() | ||
num_chans = 2 | ||
for chan_index in range(num_chans): | ||
task.ai_channels.add_ai_voltage_chan( | ||
f"{real_x_series_multiplexed_device.name}/_ao{chan_index}_vs_aognd", | ||
min_val=-10, | ||
max_val=10, | ||
) | ||
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# we'll be doing simple on-demand, so start the task now | ||
task.start() | ||
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return task | ||
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def test___analog_single_channel_writer___write_one_sample___updates_output( | ||
ao_single_channel_task: nidaqmx.Task, | ||
ai_single_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogSingleChannelWriter(ao_single_channel_task.out_stream) | ||
expected = _get_expected_voltage_for_chan(0) | ||
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writer.write_one_sample(expected) | ||
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assert ai_single_channel_loopback_task.read() == pytest.approx(expected, abs=VOLTAGE_EPSILON) | ||
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def test___analog_single_channel_writer___write_many_sample___updates_output( | ||
ao_single_channel_task: nidaqmx.Task, | ||
ai_single_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogSingleChannelWriter(ao_single_channel_task.out_stream) | ||
samples_to_write = 10 | ||
expected = _get_expected_voltage_for_chan(0) | ||
# sweep up to the expected value, the only one we'll validate | ||
data = numpy.linspace(0.0, expected, num=samples_to_write, dtype=numpy.float64) | ||
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samples_written = writer.write_many_sample(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_single_channel_loopback_task.read() == pytest.approx(expected, abs=VOLTAGE_EPSILON) | ||
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def test___analog_single_channel_writer___write_many_sample_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_single_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogSingleChannelWriter(ao_single_channel_task.out_stream) | ||
samples_to_write = 10 | ||
expected = _get_expected_voltage_for_chan(0) | ||
data = numpy.full(samples_to_write, expected, dtype=numpy.float32) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_many_sample(data) | ||
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assert "float64" in exc_info.value.args[0] | ||
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def test___analog_multi_channel_writer___write_one_sample___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogMultiChannelWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
data = numpy.asarray(expected, dtype=numpy.float64) | ||
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writer.write_one_sample(data) | ||
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assert ai_multi_channel_loopback_task.read() == pytest.approx(expected, abs=VOLTAGE_EPSILON) | ||
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def test___analog_multi_channel_writer___write_one_sample_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogMultiChannelWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
data = numpy.full(num_channels, 0.0, dtype=numpy.float32) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
writer.write_one_sample(data) | ||
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assert "float64" in exc_info.value.args[0] | ||
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def test___analog_multi_channel_writer___write_many_sample___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogMultiChannelWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
# sweep up to the expected values, the only one we'll validate | ||
data = numpy.ascontiguousarray( | ||
numpy.transpose( | ||
numpy.linspace( | ||
[0.0 for _ in range(num_channels)], | ||
expected, | ||
num=samples_to_write, | ||
dtype=numpy.float64, | ||
) | ||
) | ||
) | ||
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samples_written = writer.write_many_sample(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_multi_channel_loopback_task.read() == pytest.approx(expected, abs=VOLTAGE_EPSILON) | ||
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def test___analog_multi_channel_writer___write_many_sample_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogMultiChannelWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
data = numpy.full((num_channels, samples_to_write), 0.0, dtype=numpy.float32) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_many_sample(data) | ||
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assert "float64" in exc_info.value.args[0] | ||
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def test___analog_unscaled_writer___write_int16___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
# sweep up to the expected values, the only one we'll validate | ||
data = numpy.ascontiguousarray( | ||
numpy.transpose( | ||
numpy.linspace( | ||
[0 for _ in range(num_channels)], | ||
[_volts_to_codes(v) for v in expected], | ||
num=samples_to_write, | ||
dtype=numpy.int16, | ||
) | ||
) | ||
) | ||
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samples_written = writer.write_int16(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_multi_channel_loopback_task.read() == pytest.approx( | ||
expected, abs=VOLTAGE_EPSILON_FOR_RAW | ||
) | ||
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def test___analog_unscaled_writer___write_int16_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
data = numpy.full((num_channels, samples_to_write), 0.0, dtype=numpy.float64) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_int16(data) | ||
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assert "int16" in exc_info.value.args[0] | ||
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def test___analog_unscaled_writer___write_int32___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
# sweep up to the expected values, the only one we'll validate | ||
data = numpy.ascontiguousarray( | ||
numpy.transpose( | ||
numpy.linspace( | ||
[0 for _ in range(num_channels)], | ||
[_volts_to_codes(v) for v in expected], | ||
num=samples_to_write, | ||
dtype=numpy.int32, | ||
) | ||
) | ||
) | ||
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samples_written = writer.write_int32(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_multi_channel_loopback_task.read() == pytest.approx( | ||
expected, abs=VOLTAGE_EPSILON_FOR_RAW | ||
) | ||
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def test___analog_unscaled_writer___write_int32_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
data = numpy.full((num_channels, samples_to_write), 0.0, dtype=numpy.float64) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_int32(data) | ||
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assert "int32" in exc_info.value.args[0] | ||
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def test___analog_unscaled_writer___write_uint16___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
# sweep up to the expected values, the only one we'll validate | ||
data = numpy.ascontiguousarray( | ||
numpy.transpose( | ||
numpy.linspace( | ||
[0 for _ in range(num_channels)], | ||
[_volts_to_codes(v) for v in expected], | ||
num=samples_to_write, | ||
dtype=numpy.uint16, | ||
) | ||
) | ||
) | ||
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samples_written = writer.write_uint16(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_multi_channel_loopback_task.read() == pytest.approx( | ||
expected, abs=VOLTAGE_EPSILON_FOR_RAW | ||
) | ||
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def test___analog_unscaled_writer___write_uint16_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
data = numpy.full((num_channels, samples_to_write), 0.0, dtype=numpy.float64) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_uint16(data) | ||
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assert "uint16" in exc_info.value.args[0] | ||
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def test___analog_unscaled_writer___write_uint32___updates_output( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
ai_multi_channel_loopback_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
expected = [_get_expected_voltage_for_chan(chan_index) for chan_index in range(num_channels)] | ||
# sweep up to the expected values, the only one we'll validate | ||
data = numpy.ascontiguousarray( | ||
numpy.transpose( | ||
numpy.linspace( | ||
[0 for _ in range(num_channels)], | ||
[_volts_to_codes(v) for v in expected], | ||
num=samples_to_write, | ||
dtype=numpy.uint32, | ||
) | ||
) | ||
) | ||
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samples_written = writer.write_uint32(data) | ||
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assert samples_written == samples_to_write | ||
assert ai_multi_channel_loopback_task.read() == pytest.approx( | ||
expected, abs=VOLTAGE_EPSILON_FOR_RAW | ||
) | ||
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def test___analog_unscaled_writer___write_uint32_with_wrong_dtype___raises_error_with_correct_dtype( | ||
ao_multi_channel_task: nidaqmx.Task, | ||
) -> None: | ||
writer = AnalogUnscaledWriter(ao_multi_channel_task.out_stream) | ||
num_channels = ao_multi_channel_task.number_of_channels | ||
samples_to_write = 10 | ||
data = numpy.full((num_channels, samples_to_write), 0.0, dtype=numpy.float64) | ||
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with pytest.raises((ctypes.ArgumentError, TypeError)) as exc_info: | ||
_ = writer.write_uint32(data) | ||
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assert "uint32" in exc_info.value.args[0] |
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