def test_given_a_basic_mapping_yields_expected_results_with_scale_change(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 0.5
transformer = HomogenousTransformer(scale, height, lower_points, upper_points)
test_points = [[1.0, 1.0, 0.0], [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0], [0.5, 0.5, 0.0]]
expected_points_pre = [(0.75, 0.75), (0.25, 0.25), (0.5, 0.5), (0.625, 0.625)]
expected_points_post = [(1.0, 1.0), (0.0, 0.0), (0.5, 0.5), (0.75, 0.75)]
actual_points_pre = [transformer.transform(point) for point in test_points]
transformer.set_scale(1.0)
actual_points_post = [transformer.transform(point) for point in test_points]
self.assertEquals(expected_points_pre, actual_points_pre)
self.assertEquals(expected_points_post, actual_points_post)
def test_given_a_basic_mapping_yields_expected_results(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points, upper_points)
test_points = [
[1.0, 1.0, 0.0], [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0], [0.5, 0.5, 0.0],
[1.0, 1.0, 2.5], [-1.0, -1.0, 2.5], [0.0, 0.0, 2.5], [0.5, 0.5, 2.5],
[1.0, 1.0, 5.0], [-1.0, -1.0, 5.0], [0.0, 0.0, 5.0], [0.5, 0.5, 5.0]]
expected_points = [((x + 1.0) / 2.0, (y + 1.0) / 2.0) for (x, y, z) in test_points]
actual_points = [transformer.transform(point) for point in test_points]
self.assertEquals(expected_points, actual_points)
def test_given_a_basic_mapping_yields_expected_results_with_scale(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 0.5
transformer = HomogenousTransformer(scale, height, lower_points,
upper_points)
test_points = [[1.0, 1.0, 0.0], [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0],
[0.5, 0.5, 0.0]]
expected_points = [(0.75, 0.75), (0.25, 0.25), (0.5, 0.5),
(0.625, 0.625)]
actual_points = [transformer.transform(point) for point in test_points]
self.assertEquals(expected_points, actual_points)
def test_given_a_basic_mapping_yields_expected_results(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points,
upper_points)
test_points = [[1.0, 1.0, 0.0], [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0],
[0.5, 0.5, 0.0], [1.0, 1.0, 2.5], [-1.0, -1.0, 2.5],
[0.0, 0.0, 2.5], [0.5, 0.5, 2.5], [1.0, 1.0, 5.0],
[-1.0, -1.0, 5.0], [0.0, 0.0, 5.0], [0.5, 0.5, 5.0]]
expected_points = [((x + 1.0) / 2.0, (y + 1.0) / 2.0)
for (x, y, z) in test_points]
actual_points = [transformer.transform(point) for point in test_points]
self.assertEquals(expected_points, actual_points)
def _apply_calibration(self):
self._path_to_points.set_transformer(
HomogenousTransformer(
self._configuration.calibration.max_deflection,
self._configuration.calibration.height,
self._configuration.calibration.lower_points,
self._configuration.calibration.upper_points))
def test_given_a_basic_mapping_yields_expected_results_2(self):
height = 2.0
lower_points = {
(0.75, 0.75): (4.0, 4.0),
(0.25, 0.75): (-4.0, 4.0),
(0.75, 0.25): (4.0, -4.0),
(0.25, 0.25): (-4.0, -4.0)
}
upper_points = {
(1.0, 1.0): (4.0, 4.0),
(0.0, 1.0): (-4.0, 4.0),
(1.0, 0.0): (4.0, -4.0),
(0.0, 0.0): (-4.0, -4.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points,
upper_points)
test_points = [
[4.0, 4.0, 0.0],
[4.0, 4.0, 2.0],
# [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0], [0.5, 0.5, 0.0],
# [1.0, 1.0, 2.5], [-1.0, -1.0,2.5], [0.0, 0.0,2.5], [0.5, 0.5,2.5],
# [1.0, 1.0, 5.0], [-1.0, -1.0, 5.0], [0.0, 0.0, 5.0], [0.5, 0.5, 5.0]
]
expected_points = [
(0.75, 0.75),
(1.0, 1.0),
# (0.3750, 0.3750), (0.5000, 0.5000), (0.5625, 0.5625),
# (0.6667, 0.6667), (0.3333, 0.3333), (0.5000, 0.5000), (0.5833, 0.5833),
# (1.0000, 1.0000), (0.0000, 0.0000), (0.5000, 0.5000), (0.7500, 0.7500)
]
actual_points = [transformer.transform(point) for point in test_points]
for idx in range(0, len(test_points)):
self.assertAlmostEquals(expected_points[idx][0],
actual_points[idx][0])
self.assertAlmostEquals(expected_points[idx][1],
actual_points[idx][1])
def test_points_outside_range_clip(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points, upper_points)
test_points = [[-2.0, -2.0, 0.0], [2.0, 2.0, 0.0]]
results = []
for test_point in test_points:
results.append(transformer.transform(test_point))
self.assertEquals([(0.0, 0.0), (1.0, 1.0)], results)
def test_points_outside_range_clip(self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points,
upper_points)
test_points = [[-2.0, -2.0, 0.0], [2.0, 2.0, 0.0]]
results = []
for test_point in test_points:
results.append(transformer.transform(test_point))
self.assertEquals([(0.0, 0.0), (1.0, 1.0)], results)
def test_given_a_basic_mapping_yields_expected_results_2(self):
height = 2.0
lower_points = {
(0.75, 0.75): (4.0, 4.0),
(0.25, 0.75): (-4.0, 4.0),
(0.75, 0.25): (4.0, -4.0),
(0.25, 0.25): (-4.0, -4.0)
}
upper_points = {
(1.0, 1.0): (4.0, 4.0),
(0.0, 1.0): (-4.0, 4.0),
(1.0, 0.0): (4.0, -4.0),
(0.0, 0.0): (-4.0, -4.0)
}
scale = 1.0
transformer = HomogenousTransformer(scale, height, lower_points, upper_points)
test_points = [
[4.0, 4.0, 0.0], [4.0, 4.0, 2.0],
# [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0], [0.5, 0.5, 0.0],
# [1.0, 1.0, 2.5], [-1.0, -1.0,2.5], [0.0, 0.0,2.5], [0.5, 0.5,2.5],
# [1.0, 1.0, 5.0], [-1.0, -1.0, 5.0], [0.0, 0.0, 5.0], [0.5, 0.5, 5.0]
]
expected_points = [
(0.75, 0.75), (1.0, 1.0),
# (0.3750, 0.3750), (0.5000, 0.5000), (0.5625, 0.5625),
# (0.6667, 0.6667), (0.3333, 0.3333), (0.5000, 0.5000), (0.5833, 0.5833),
# (1.0000, 1.0000), (0.0000, 0.0000), (0.5000, 0.5000), (0.7500, 0.7500)
]
actual_points = [transformer.transform(point) for point in test_points]
for idx in range(0,len(test_points)):
self.assertAlmostEquals(expected_points[idx][0], actual_points[idx][0])
self.assertAlmostEquals(expected_points[idx][1], actual_points[idx][1])
def test_given_a_basic_mapping_yields_expected_results_with_scale_change(
self):
height = 1.0
lower_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
upper_points = {
(1.0, 1.0): (1.0, 1.0),
(0.0, 1.0): (-1.0, 1.0),
(1.0, 0.0): (1.0, -1.0),
(0.0, 0.0): (-1.0, -1.0)
}
scale = 0.5
transformer = HomogenousTransformer(scale, height, lower_points,
upper_points)
test_points = [[1.0, 1.0, 0.0], [-1.0, -1.0, 0.0], [0.0, 0.0, 0.0],
[0.5, 0.5, 0.0]]
expected_points_pre = [(0.75, 0.75), (0.25, 0.25), (0.5, 0.5),
(0.625, 0.625)]
expected_points_post = [(1.0, 1.0), (0.0, 0.0), (0.5, 0.5),
(0.75, 0.75)]
actual_points_pre = [
transformer.transform(point) for point in test_points
]
transformer.set_scale(1.0)
actual_points_post = [
transformer.transform(point) for point in test_points
]
for idx in range(0, len(expected_points_pre)):
self.assertAlmostEquals(expected_points_pre[idx][0],
actual_points_pre[idx][0])
self.assertAlmostEquals(expected_points_pre[idx][1],
actual_points_pre[idx][1])
self.assertAlmostEquals(expected_points_post[idx][0],
actual_points_post[idx][0])
self.assertAlmostEquals(expected_points_post[idx][1],
actual_points_post[idx][1])
def print_layers(self,
layer_generator,
print_sub_layers=True,
dry_run=False,
force_source_speed=False):
logger.info("Shuffled: %s" %
self._configuration.options.use_shufflelayers)
logger.info("Sublayered: %s" %
self._configuration.options.use_sublayers)
logger.info("Overlapped: %s" % self._configuration.options.use_overlap)
if self._configuration.options.use_sublayers and print_sub_layers:
layer_generator = SubLayerGenerator(
layer_generator,
self._configuration.options.sublayer_height_mm)
if self._configuration.options.use_shufflelayers:
layer_generator = ShuffleGenerator(
layer_generator,
self._configuration.options.shuffle_layers_amount)
if self._configuration.options.use_overlap:
layer_generator = OverLapGenerator(
layer_generator, self._configuration.options.overlap_amount)
if self._configuration.serial.on:
self._commander = SerialCommander(self._configuration.serial.port)
else:
self._commander = NullCommander()
self.laser_control = LaserControl(
self._configuration.cure_rate.override_laser_power_amount)
transformer = HomogenousTransformer(
self._configuration.calibration.max_deflection,
self._configuration.calibration.height,
self._configuration.calibration.lower_points,
self._configuration.calibration.upper_points,
)
state = MachineState()
self._status = MachineStatus()
if dry_run:
abort_on_error = False
else:
abort_on_error = True
self._zaxis = self._get_zaxis(dry_run)
disseminator = self._get_digital_disseminator(dry_run)
path_to_points = PathToPoints(
disseminator.samples_per_second, transformer,
self._configuration.options.laser_thickness_mm)
if force_source_speed:
override_draw_speed = None
override_move_speed = None
else:
override_draw_speed = self._configuration.cure_rate.draw_speed if self._configuration.cure_rate.use_draw_speed else None
override_move_speed = self._configuration.cure_rate.move_speed if self._configuration.cure_rate.use_draw_speed else None
pre_layer_delay = self._configuration.options.pre_layer_delay if self._configuration.options.pre_layer_delay else 0.0
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)
if self._configuration.options.wait_after_move_milliseconds > 0:
wait_speed = self._configuration.options.laser_thickness_mm / (
float(self._configuration.options.wait_after_move_milliseconds)
/ 1000.0)
else:
wait_speed = None
self._writer = LayerWriter(disseminator,
path_to_points,
self.laser_control,
state,
move_distance_to_ignore=self._configuration.
options.laser_thickness_mm,
override_draw_speed=override_draw_speed,
override_move_speed=override_move_speed,
wait_speed=wait_speed,
post_fire_delay_speed=post_fire_delay_speed,
slew_delay_speed=slew_delay_speed)
self._layer_processing = LayerProcessing(
self._writer,
state,
self._status,
self._zaxis,
self._configuration.dripper.max_lead_distance_mm,
self._commander,
pre_layer_delay,
self._configuration.serial.layer_started,
self._configuration.serial.layer_ended,
self._configuration.serial.print_ended,
self._configuration.serial.on_command,
self._configuration.serial.off_command,
)
if self._zaxis:
self._zaxis.set_call_back(self._status.drip_call_back)
self._zaxis.start()
self._controller = Controller(
self._writer,
self._layer_processing,
layer_generator,
self._status,
abort_on_error=abort_on_error,
)
self._controller.start()
