Delta is tracked with class now
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Chish36
Julian Stirling
parent
63bd34f548
commit
4106d0348c
1 changed files with 25 additions and 34 deletions
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@ -68,7 +68,7 @@ def predict_z(positions: list, axis: str, relative_move: float, stage: StageDep,
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def move_and_measure(
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step_size: dict[str, float],
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axis: str, delta: dict[str, int],
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axis: str, data,
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image1, autofocus_proc: bool,
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csm: CSMDep,
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autofocus: AutofocusDep,
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@ -92,23 +92,22 @@ def move_and_measure(
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autofocus.looping_autofocus(dz = 800)
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image2 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
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offset = [x * 1 for x in fft_image_tracking.displacement_between_images(image_0 = image1, image_1 = image2, sigma=10, fractional_threshold=0.1, pad=True)] # Units is pixels
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delta['x'] = int(offset[1])
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delta['y'] = int(offset[0])
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data.delta['x'] = int(offset[1])
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data.delta['y'] = int(offset[0])
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return delta, offset, wrong_axis
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return offset, wrong_axis
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def acquie_z_predict_points(
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stream_resolution: list[int],
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direction: int,
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axis: str,
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delta: dict[str, int],
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data,
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csm: CSMDep,
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cam: CamDep,
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stage: StageDep,
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autofocus: AutofocusDep,
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logger: lt.deps.InvocationLogger,
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) -> dict[str, int]:
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) -> None:
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"""Carries out the medium sized steps section of the range of motion test to get 5 points to make z position predictions with.
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:params stream_resolution: The resolution of the stream from the camera.
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@ -127,29 +126,27 @@ def acquie_z_predict_points(
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image1 = cv2.resize(
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np.array(Image.open(cam.grab_jpeg().open())), dsize=(0, 0), fx=1, fy=1
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)
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delta, offset, wrong_axis = move_and_measure(
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offset, wrong_axis = move_and_measure(
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step_size=generate_move_dicts(medium_step, stream_resolution, direction),
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axis=axis,
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delta=delta,
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data=data,
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image1=image1,
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autofocus_proc=True,
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csm=csm,
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autofocus=autofocus,
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cam=cam,
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)
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logger.info(f"Offset measured as {delta[axis]}")
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logger.info(f"Offset measured as {data.delta[axis]}")
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data.measure(stage.position, offset)
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assert(np.abs(delta[wrong_axis]) < np.abs(wrong_axis_max_medium[wrong_axis]))
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return delta
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assert(np.abs(data.delta[wrong_axis]) < np.abs(wrong_axis_max_medium[wrong_axis]))
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def check_stage_operation(
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small_step: int,
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stream_resolution: list[int],
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direction: int,
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axis: str,
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delta: dict[str, int],
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data,
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minimum_offset_small: dict[str, float],
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csm: CSMDep,
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@ -157,7 +154,7 @@ def check_stage_operation(
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stage: StageDep,
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autofocus: AutofocusDep,
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logger: lt.deps.InvocationLogger,
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) -> dict[str, int]:
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) -> None:
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"""Carries out 3 small moves in a given direction and axis.
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:params small_step: The integer value used to generate the small step sizes.
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@ -177,20 +174,20 @@ def check_stage_operation(
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image1 = cv2.resize(
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np.array(Image.open(cam.grab_jpeg().open())), dsize=(0, 0), fx=1, fy=1
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)
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delta, offset, wrong_axis = move_and_measure(
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offset, wrong_axis = move_and_measure(
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step_size=generate_move_dicts(small_step, stream_resolution, direction),
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axis=axis,
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delta=delta,
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data=data,
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image1=image1,
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autofocus_proc=False,
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csm=csm,
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autofocus=autofocus,
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cam=cam,
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)
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logger.info(f"Offset measured as {delta[axis]}")
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logger.info(f"Offset measured as {data.delta[axis]}")
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while (
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np.abs(delta[axis]) < np.abs(minimum_offset_small[axis])
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np.abs(data.delta[axis]) < np.abs(minimum_offset_small[axis])
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and failure_count < 3
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):
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logger.info(
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@ -211,20 +208,19 @@ def check_stage_operation(
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pad=True,
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)
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] # Units is pixels
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delta["x"] = int(offset[1])
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delta["y"] = int(offset[0])
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data.delta["x"] = int(offset[1])
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data.delta["y"] = int(offset[0])
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logger.info(
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f"Displacement found was {delta[axis]}. Minimum offset is {minimum_offset_small[axis]}"
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f"Displacement found was {data.delta[axis]}. Minimum offset is {minimum_offset_small[axis]}"
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)
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data.measure(stage.position, offset)
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assert np.abs(delta[wrong_axis]) < np.abs(wrong_axis_max_small[wrong_axis])
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assert np.abs(data.delta[wrong_axis]) < np.abs(wrong_axis_max_small[wrong_axis])
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if np.abs(delta[axis]) < np.abs(minimum_offset_small[axis]): # this means the edge has been found
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if np.abs(data.delta[axis]) < np.abs(minimum_offset_small[axis]): # this means the edge has been found
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logger.info("Edge has been found.")
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break
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return delta
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def motion_detection(
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axis: str,
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@ -273,10 +269,11 @@ def motion_detection(
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class RomDataTracker():
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"""Class for tracking range of motion data."""
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def __init__(self, stage_coords, cor_lat_steps):
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def __init__(self, stage_coords, cor_lat_steps, delta):
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"""Define useful data tracked througout test."""
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self.stage_coords = stage_coords
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self.cor_lat_steps = cor_lat_steps
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self.delta = delta
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def measure(self, current_pos, cor):
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"""Store useful data."""
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@ -306,7 +303,7 @@ class RangeofMotionThing(lt.Thing):
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starting_position = list(stage.position.values())
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rom_data = RomDataTracker([], [])
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rom_data = RomDataTracker([], [], {'x':0, 'y':0})
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axis_results = {}
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try:
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@ -324,20 +321,15 @@ class RangeofMotionThing(lt.Thing):
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small_step = 20
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step_sizes_big = generate_move_dicts(big_step, stream_resolution, direction)
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delta = {
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'x':0,
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'y':0
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}
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rom_data.stage_coords.append(stage.position)
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logger.info("Moving the stage in 5 medium sized steps.")
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delta = acquie_z_predict_points(
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acquie_z_predict_points(
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stream_resolution=stream_resolution,
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direction=direction,
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axis=axis,
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delta=delta,
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data=rom_data,
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csm=csm,
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cam=cam,
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@ -352,7 +344,7 @@ class RangeofMotionThing(lt.Thing):
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small_step, stream_resolution, direction, factor=0.65
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)
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while np.abs(delta[axis]) > np.abs(minimum_offset_small[axis]):
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while np.abs(rom_data.delta[axis]) > np.abs(minimum_offset_small[axis]):
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z_diff = predict_z(positions = rom_data.stage_coords, axis = axis, relative_move = step_sizes_big[axis], stage = stage, csm = csm)
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logger.info("Z calibration complete.")
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@ -370,12 +362,11 @@ class RangeofMotionThing(lt.Thing):
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rom_data.stage_coords.append(stage.position)
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delta = check_stage_operation(
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check_stage_operation(
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small_step=small_step,
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stream_resolution=stream_resolution,
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direction=direction,
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axis=axis,
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delta=delta,
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data = rom_data,
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minimum_offset_small=minimum_offset_small,
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csm=csm,
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