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Minor tweaks to z_pred and lowered tolerance for failure

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Chish36 2025-07-24 10:19:09 +01:00 • committed by Julian Stirling
parent 154870142d
commit ada120db9c
1 changed files with 7 additions and 16 deletions
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23
src/openflexure_microscope_server/things/stage_measure.py
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@ -49,27 +49,21 @@ def steps_generate(small_step: int, z_perc: int, big_step: int, dir: int, stream
'''
step_sizes_big = dict_generate(big_step, stream_resolution, dir)
step_sizes_small = dict_generate(small_step, stream_resolution, dir)
minimum_offset_small = dict_generate(small_step, stream_resolution, dir, factor = 0.8)
minimum_offset_small = dict_generate(small_step, stream_resolution, dir, factor = 0.65)
z_steps = dict_generate(z_perc, stream_resolution, dir)
minimum_offset_z = dict_generate(z_perc, stream_resolution, dir, factor = 0.8)
minimum_offset_z = dict_generate(z_perc, stream_resolution, dir, factor = 0.65)
wrong_axis_max_small = dict_generate(small_step, stream_resolution, dir, factor = 0.1)
wrong_axis_max_z = dict_generate(z_perc, stream_resolution, dir, factor = 0.1)
return step_sizes_small, minimum_offset_small, z_steps, minimum_offset_z, step_sizes_big, wrong_axis_max_small, wrong_axis_max_z
def predict_z(pixel_per_step: float, positions: list, axis: str, direction: int, stage: StageDep, cam: CamDep) -> float:
def predict_z(positions: list, axis: str, relative_move: float, stage: StageDep) -> float:
"""
Predicts the next z position for a big move using an array of previous positions.
"""
res_dic = {
'x': cam.stream_resolution[0],
'y': cam.stream_resolution[1]
}
lateral_positions = [i[axis] for i in positions]
z_positions = [i['z'] for i in positions]
parameters, covariance = curve_fit(quadratic, lateral_positions, z_positions)
relative_move = (direction * res_dic[axis])/pixel_per_step # This is the number of steps to cover 200% of the FOV.
z_dest = quadratic(stage.position[axis] + relative_move, *parameters)
z_diff = z_dest - stage.position['z']
@ -123,9 +117,6 @@ class RangeofMotionThing(Thing):
focused_positions = []
axis_results = {}
pixel_per_step = ((1/abs(csm.image_to_stage_displacement_matrix[0][1]))
+ (1/abs(csm.image_to_stage_displacement_matrix[1][0])))/4
# Generate required dictionaries for step sizes and minimum offsets
stream_resolution = cam.stream_resolution
@ -167,7 +158,7 @@ class RangeofMotionThing(Thing):
# 1 big step followed by 3 small steps
while np.abs(delta[axis]) > np.abs(minimum_offset_small[axis]) and parasitic_motion == False:
z_diff = predict_z(pixel_per_step = pixel_per_step, positions = focused_positions, axis = axis, direction = direction, stage = stage, cam = cam)
z_diff = predict_z(positions = focused_positions, axis = axis, relative_move = step_sizes_big[axis], stage = stage)
logger.info(f"Z calibration complete.")
@ -180,10 +171,10 @@ class RangeofMotionThing(Thing):
else:
csm.move_in_image_coordinates(x = 0, y = step_sizes_big['y'])
stage_coords.append(stage.position)
focus_data = autofocus.looping_autofocus(dz = 800)
stage_coords.append(stage.position)
failure_count = 0
for loop in range(3):
@ -191,7 +182,7 @@ class RangeofMotionThing(Thing):
delta, offset, focus_data, wrong_axis = move_and_measure(step_size = step_sizes_small, axis = axis, delta = delta, image1 = image1, autofocus_proc = False, focus_data = focus_data, csm = csm, autofocus = autofocus, cam = cam)
logger.info(f"Offset measured as {delta[axis]}")
while np.abs(delta[axis]) < minimum_offset_small[axis] and failure_count < 3:
while np.abs(delta[axis]) < np.abs(minimum_offset_small[axis]) and failure_count < 3:
logger.info(f"Correlation failed. Refocusing to check. Attempt {failure_count + 1}/3")
focus_data = autofocus.looping_autofocus(dz = 1000)
image2 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)