def test_works_on_xyz_with_scale(self):
tuning_transformer = TuningTransformer(scale=0.5)
self.assertEquals([0.75, 0.75],
tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5],
tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.25, 0.25],
tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_works_on_xyz(self):
tuning_transformer = TuningTransformer()
self.assertEquals([1.0, 1.0],
tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5],
tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.0, 0.0],
tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_can_change_tuning_transformer_scale(self):
tuning_transformer = TuningTransformer(scale=1.0)
self.assertEquals([1.0, 1.0],
tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5],
tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.0, 0.0],
tuning_transformer.transform([0.0, 0.0, 1.0]))
tuning_transformer.set_scale(0.5)
self.assertEquals([0.75, 0.75],
tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5],
tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.25, 0.25],
tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_can_change_tuning_transformer_scale(self):
tuning_transformer = TuningTransformer(scale=1.0)
self.assertEquals([1.0, 1.0], tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5], tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.0, 0.0], tuning_transformer.transform([0.0, 0.0, 1.0]))
tuning_transformer.set_scale(0.5)
self.assertEquals([0.75, 0.75], tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5], tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.25, 0.25], tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_can_change_transformer(self):
samples_per_second = 4
laser_size = 0.5
path2audio = PathToPoints(samples_per_second, self.transformer,
laser_size)
path2audio.set_transformer(TuningTransformer())
expected = numpy.array([[1.0, 1.0], [1.0, 1.0]])
actual = path2audio.process([1.0, 1.0, 1.0], [1.0, 1.0, 1.0], 1.0)
self.assertNumpyArrayClose(expected, actual)
def test_should_adjust_if_request_points_out_of_bounds(self):
tuning_transformer = TuningTransformer(scale=1.0)
self.assertEquals([1.0, 1.0],
tuning_transformer.transform([1.1, 1.0, 1.0]))
self.assertEquals([0.0, 1.0],
tuning_transformer.transform([-0.1, 1.0, 1.0]))
self.assertEquals([1.0, 1.0],
tuning_transformer.transform([1.0, 1.1, 1.0]))
self.assertEquals([1.0, 0.0],
tuning_transformer.transform([1.0, -0.1, 1.0]))
def _unapply_calibration(self):
self._path_to_points.set_transformer(
TuningTransformer(scale=self._configuration.calibration.max_deflection))
def __init__(self, configuration_manager):
logger.info("Calibartion API Startup")
self._configuration_manager = configuration_manager
self._configuration = self._configuration_manager.load()
self._point_generator = SinglePointGenerator()
self._blink_generator = BlinkGenerator()
self._orientaiton_generator = OrientationGenerator()
self._alignment_generator = CalibrationLineGenerator()
self._scale_generator = ScaleGenerator(speed=2.0, radius=1.0)
self._test_patterns = {
'Hilbert Space Filling Curve': HilbertGenerator(),
'Square': SquareGenerator(),
'Circle': CircleGenerator(),
'Spiral': SpiralGenerator(),
'Memory Hourglass': MemoryHourglassGenerator(),
'Damping Test': DampingTestGenerator(),
'NESW': NESWGenerator(),
'Twitch': TwitchGenerator(),
}
self._current_generator = self._point_generator
self._laser_control = LaserControl(self._configuration.cure_rate.override_laser_power_amount)
transformer = TuningTransformer(scale=self._configuration.calibration.max_deflection)
self._controller = None
logger.debug("Setting up audiowriter")
self._current_generator = self._point_generator
self._state = MachineState()
self._status = MachineStatus()
self._communicator = UsbPacketCommunicator(self._configuration.circut.calibration_queue_length)
self._communicator.start()
self._disseminator = MicroDisseminator(
self._laser_control,
self._communicator,
self._configuration.circut.data_rate
)
self._path_to_points = PathToPoints(
self._disseminator.samples_per_second,
transformer,
self._configuration.options.laser_thickness_mm
)
post_fire_delay_speed = None
slew_delay_speed = None
if self._configuration.options.post_fire_delay:
post_fire_delay_speed = self._configuration.options.laser_thickness_mm / (float(self._configuration.options.post_fire_delay) / 1000.0)
if self._configuration.options.slew_delay:
slew_delay_speed = self._configuration.options.laser_thickness_mm / (float(self._configuration.options.slew_delay) / 1000.0)
self._writer = LayerWriter(
self._disseminator,
self._path_to_points,
self._laser_control,
self._state,
post_fire_delay_speed=post_fire_delay_speed,
slew_delay_speed=slew_delay_speed
)
self._layer_processing = LayerProcessing(
self._writer,
self._state,
self._status,
)
self._controller = Controller(
self._writer,
self._layer_processing,
self._current_generator,
self._status,
abort_on_error=False,
)
self.make_pattern_fit()
self._controller.start()
def test_should_adjust_if_request_points_out_of_bounds(self):
tuning_transformer = TuningTransformer(scale=1.0)
self.assertEquals([1.0, 1.0], tuning_transformer.transform([1.1, 1.0, 1.0]))
self.assertEquals([0.0, 1.0], tuning_transformer.transform([-0.1, 1.0, 1.0]))
self.assertEquals([1.0, 1.0], tuning_transformer.transform([1.0, 1.1, 1.0]))
self.assertEquals([1.0, 0.0], tuning_transformer.transform([1.0, -0.1, 1.0]))
def test_works_on_xyz_with_scale(self):
tuning_transformer = TuningTransformer(scale=0.5)
self.assertEquals([0.75, 0.75], tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5], tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.25, 0.25], tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_works_on_xyz(self):
tuning_transformer = TuningTransformer()
self.assertEquals([1.0, 1.0], tuning_transformer.transform([1.0, 1.0, 1.0]))
self.assertEquals([0.5, 0.5], tuning_transformer.transform([0.5, 0.5, 1.0]))
self.assertEquals([0.0, 0.0], tuning_transformer.transform([0.0, 0.0, 1.0]))
def test_should_kaboom_if_scale_not_greater_then_0(self):
with self.assertRaises(Exception):
TuningTransformer(scale=0.0)
