Made changes based on ruff-lint-increased feedback
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Chish36
Julian Stirling
parent
32129125d6
commit
6579a65f84
1 changed files with 89 additions and 36 deletions
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@ -1,11 +1,15 @@
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"""File contains all the functions used to measure the range of motion of the OpenFlexure Microscope translation stage.
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"""File contains all the functions used to measure the range of motion.
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The range of motion is measured by first taking 5 'medium' sized steps which gives enough positions to predict future z positions. Next, one 'big' step is taken followed by 3
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'small' steps to test that the stage is still moving as expected and has not reached the edge. Once the edge has been found and too account for the possibility that a 'big'
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step was take just before the edge was reached, the stage is moved in a sequence of increasing pixel sizes in the opposite direction until motion is detected. This is
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The range of motion is measured by first taking 5 'medium' sized steps which gives enough positions
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to predict future z positions. Next, one 'big' step is taken followed by 3
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'small' steps to test that the stage is still moving as expected and has not reached the edge.
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Once the edge has been found and too account for the possibility that a 'big'
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step was take just before the edge was reached, the stage is moved in a sequence
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of increasing pixel sizes in the opposite direction until motion is detected. This is
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position is taken as the true final position.
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Throughout the test, parasitic motion(motion in the axis not being measured) is tracked and an error is raised if it exceeds a reasonable amount.
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Throughout the test, parasitic motion(motion in the axis not being measured)
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is tracked and an error is raised if it exceeds a reasonable amount.
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"""
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import numpy as np
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@ -31,7 +35,11 @@ CSMDep = lt.deps.direct_thing_client_dependency(
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AutofocusDep = lt.deps.direct_thing_client_dependency(AutofocusThing, "/autofocus/")
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def generate_move_dicts(fov_perc: int, stream_resolution: list[int], direction: int, factor: float = 1) -> dict[str, float]:
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def generate_move_dicts(fov_perc: int,
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stream_resolution: list[int],
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direction: int,
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factor: float = 1
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) -> dict[str, float]:
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"""Create a single dictionary of x and y moves for moving in image coordinates.
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:param fov_perc: The percentage of field of view the stage should move by.
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@ -46,12 +54,19 @@ def generate_move_dicts(fov_perc: int, stream_resolution: list[int], direction:
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}
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def predict_z(positions: list, axis: str, relative_move: float, stage: StageDep, csm: CSMDep) -> float:
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def predict_z(positions: list,
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axis: str,
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relative_move: float,
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stage: StageDep,
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csm: CSMDep
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) -> float:
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"""Predict the next z position for a move using previous positions.
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:params positions: The list of positions used for predicting z. This will usually be a list of all previuos positions.
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:params positions: The list of positions used for predicting z.
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This will usually be a list of all previous positions.
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:params axis: The axis in which the stage is moving. This must be 'x' or 'y'.
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:params relative_move: The move which the function is trying to predict z for. Here, this is inputted with units of pixels.
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:params relative_move: The move which the function is trying to predict z for.
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Here, this is inputted with units of pixels.
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:return: A number of pixels the stage needs to move in z.
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"""
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pixel_step = {
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@ -68,8 +83,10 @@ 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, data,
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image1, autofocus_proc: bool,
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axis: str,
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data,
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image1,
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autofocus_proc: bool,
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csm: CSMDep,
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autofocus: AutofocusDep,
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cam:CamDep) -> tuple:
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@ -80,7 +97,8 @@ def move_and_measure(
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:params data: The object used to track stage coordinates, correlation and delta.
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:params image1: An image taken before moving to be correlated with image2.
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:params autofocus_proc: If true, looping.autofocus will be used after the stage moves.
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:return: All required data for the next move. This includes the updated delta value and offset. Also returns what wrong_axis is i.e. if the direction is 'x', wrong_axis = 'y'.
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:return: All required data for the next move. This includes the updated delta value and offset.
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Also returns what wrong_axis is i.e. if the direction is 'x', wrong_axis = 'y'.
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"""
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if axis == 'x':
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csm.move_in_image_coordinates(x = step_size['x'], y = 0)
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@ -91,7 +109,12 @@ def move_and_measure(
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if autofocus_proc:
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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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offset = [x * 1 for x in fft_image_tracking.displacement_between_images(
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image_0 = image1,
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image_1 = image2,
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sigma=10,
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fractional_threshold=0.1,
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pad=True)] # Units is pixels
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data.delta['x'] = int(offset[1])
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data.delta['y'] = int(offset[0])
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@ -108,19 +131,20 @@ def acquire_z_predict_points(
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autofocus: AutofocusDep,
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logger: lt.deps.InvocationLogger,
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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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"""Complete 5 medium sized steps to collect stage coordinates for prediction.
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:params stream_resolution: The resolution of the stream from the camera.
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:param direction: The direction the stage moves.
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:params axis: The axis which is being measured. This must be 'x' or 'y'.
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:params data: The object used to track stage coordinates, correlation and delta.
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:return: Stage_coords and cor_lat_steps are lists of data tracked throughout the test. Delta is updated and tracked after each move.
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:return: Stage_coords and cor_lat_steps are lists of data tracked throughout the test.
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Delta is updated and tracked after each move.
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"""
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medium_step = 50
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wrong_axis_max_medium = generate_move_dicts(
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medium_step, stream_resolution, direction, factor=0.1
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)
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for loop in range(5):
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for _loop in range(5):
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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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@ -160,13 +184,19 @@ def check_stage_operation(
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:param direction: The direction the stage moves.
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:params axis: The axis which is being measured. This must be 'x' or 'y'.
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:params data: The object used to track stage coordinates, correlation and delta.
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:params minimum_offset_small: A dictionary containing the minimum values for a successful correlation.
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:return: Stage_coords and cor_lat_steps are lists of data tracked throughout the test. Delta is updated and tracked after each move.
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:params minimum_offset_small: A dictionary containing the minimum values for
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a successful correlation.
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:return: Stage_coords and cor_lat_steps are lists of data tracked throughout the test.
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Delta is updated and tracked after each move.
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"""
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failure_count = 0
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wrong_axis_max_small = generate_move_dicts(small_step, stream_resolution, direction, factor=0.1)
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wrong_axis_max_small = generate_move_dicts(
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small_step,
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stream_resolution,
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direction,
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factor=0.1)
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for loop in range(3):
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for _loop in range(3):
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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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@ -207,14 +237,16 @@ def check_stage_operation(
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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 {data.delta[axis]}. Minimum offset is {minimum_offset_small[axis]}"
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f"Displacement found was {data.delta[axis]}.\
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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(data.delta[wrong_axis]) < np.abs(wrong_axis_max_small[wrong_axis])
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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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# this means the edge has been found
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if np.abs(data.delta[axis]) < np.abs(minimum_offset_small[axis]):
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logger.info("Edge has been found.")
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break
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@ -229,7 +261,8 @@ def motion_detection(
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"""Move the stage until motion is detected along a specified axis and direction.
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:params axis: The axis in which the stage is moving. This must be 'x' or 'y'.
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:params direction: The direction in which the stage was moving previous to motion detection being used.
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:params direction: The direction in which the stage was moving
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previous to motion detection being used.
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:return: The stage coordinates where motion was detected.
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"""
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displacements = [1,2,4,8,16,32,64,128,256,512] # Array of increasing step sizes
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@ -248,11 +281,21 @@ def motion_detection(
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for loop in range(np.shape(displacements)[0]):
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this_motion_step[axis] = displacements[loop] * direction * -1
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logger.info(f"Testing with step size {this_motion_step[axis]}")
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image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
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image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())),
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dsize=(0,0),
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fx= 1,
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fy= 1)
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csm.move_in_image_coordinates(x = this_motion_step['x'], y = this_motion_step['y'])
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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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image2 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())),
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dsize=(0,0),
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fx= 1,
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fy= 1)
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offset = [x * 1 for x in fft_image_tracking.displacement_between_images(
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image_0 = image1, image_1 = image2, sigma=10, fractional_threshold=0.1, pad=True)] # Units is pixels
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image_0 = image1,
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image_1 = image2,
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sigma=10,
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fractional_threshold=0.1,
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pad=True)]
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delta['x'] = int(offset[1])
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delta['y'] = int(offset[0])
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logger.info(f"Offset measured as {np.abs(delta[axis])}")
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@ -293,7 +336,8 @@ class RangeofMotionThing(lt.Thing):
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:params axis: The axis which is being measured. This must be 'x' or 'y'.
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:params direction: The direction which is being measured. This must be 1 or -1.
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:return: Results dictionary containing stage positions, correlations and the final position.
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:return: Results dictionary containing stage positions,
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correlations and the final position.
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"""
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autofocus.looping_autofocus(dz = 1000)
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@ -303,10 +347,7 @@ class RangeofMotionThing(lt.Thing):
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axis_results = {}
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try:
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if direction == 1:
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dir_word = "positive"
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else:
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dir_word = "negative"
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dir_word = "positive" if direction == 1 else "negative"
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logger.info(f"Beginning the {axis}-axis in the {dir_word} direction")
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@ -338,7 +379,12 @@ class RangeofMotionThing(lt.Thing):
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)
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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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z_diff = predict_z(
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positions = rom_data.stage_coords,
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axis = axis,
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relative_move = step_sizes_big[axis],
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stage = stage,
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csm = csm)
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logger.info("Z calibration complete.")
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stage.move_relative(z = z_diff)
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@ -380,7 +426,11 @@ class RangeofMotionThing(lt.Thing):
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except AssertionError:
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logger.info("Parasitic motion detected.")
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finally:
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stage.move_absolute(x = starting_position[0], y = starting_position[1], z = starting_position[2], block_cancellation=True)
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stage.move_absolute(
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x = starting_position[0],
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y = starting_position[1],
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z = starting_position[2],
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block_cancellation=True)
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return axis_results
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@ -397,7 +447,8 @@ class RangeofMotionThing(lt.Thing):
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:return: Results dictionary separated into keys of each axis and direction.
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"""
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logger.info("Using the stage to measure the Range of Motion. Please ensure you are using a big enough sample.")
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logger.info("Using the stage to measure the Range of Motion.\
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Please ensure you are using a big enough sample.")
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start_time = time.time()
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rom_results = {}
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@ -416,8 +467,10 @@ class RangeofMotionThing(lt.Thing):
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end_time = time.time()
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total_time = (end_time - start_time)/60
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x_range = abs(rom_results["['x', 1]"]["final_position"]["x"] - rom_results["['x', -1]"]["final_position"]["x"])
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y_range = abs(rom_results["['y', 1]"]["final_position"]["y"] - rom_results["['y', -1]"]["final_position"]["y"])
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x_range = abs(rom_results["['x', 1]"]["final_position"]["x"] -
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rom_results["['x', -1]"]["final_position"]["x"])
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y_range = abs(rom_results["['y', 1]"]["final_position"]["y"] -
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rom_results["['y', -1]"]["final_position"]["y"])
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step_range = [x_range, y_range]
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logger.info(f"Range of motion is {x_range} X {y_range}")
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