rahix/openflexure-microscope-server
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Removed the need for steps_generate function

Browse source
This commit is contained in:
Chish36 2025-07-25 08:58:04 +01:00 • committed by Julian Stirling
parent e74ac9d859
commit 61c3877202
1 changed files with 32 additions and 21 deletions
Download patch file Download diff file Expand all files Collapse all files

53
src/openflexure_microscope_server/things/stage_measure.py
View file

@ -56,22 +56,6 @@ def dict_generate(fov_perc: int, stream_resolution: list[int], direction: int, f
}
return xy_dict
def steps_generate(small_step: int, z_perc: int, big_step: int, direction: int, stream_resolution: list) -> tuple:
'''Creates all required dictionaries of all necessary step sizes.'''
step_sizes_big = dict_generate(big_step, stream_resolution, direction)
step_sizes_small = dict_generate(small_step, stream_resolution, direction)
minimum_offset_small = dict_generate(
small_step, stream_resolution, direction, factor=0.65
)
z_steps = dict_generate(z_perc, stream_resolution, direction)
minimum_offset_z = dict_generate(z_perc, stream_resolution, direction, factor=0.65)
wrong_axis_max_small = dict_generate(
small_step, stream_resolution, direction, factor=0.1
)
wrong_axis_max_z = dict_generate(z_perc, stream_resolution, direction, 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(positions: list, axis: str, relative_move: float, stage: StageDep, csm: CSMDep) -> float:
"""Predicts the next z position for a 'big' move using an array of previous positions. This avoids long autofocuses and reduces the possibility of colliding with
the sample.
@ -198,15 +182,20 @@ class RangeofMotionThing(Thing):
# Generate required dictionaries for step sizes and minimum offsets
stream_resolution = cam.stream_resolution
step_sizes_small, minimum_offset_small, z_steps, minimum_offset_z, step_sizes_big, wrong_axis_max_small, wrong_axis_max_z = steps_generate(20, 50, 200, direction, stream_resolution=stream_resolution)
small_step = 20
medium_step = 50
big_step = 200
minimum_offset_small = dict_generate(small_step, stream_resolution, direction, factor=0.65)
wrong_axis_max_small = dict_generate(small_step, stream_resolution, direction, factor=0.1)
wrong_axis_max_z = dict_generate(medium_step, stream_resolution, direction, factor=0.1)
step_sizes_big = dict_generate(big_step, stream_resolution, direction)
delta = {
'x':0,
'y':0
}
logger.info(f"Using the follwing steps: {step_sizes_small, minimum_offset_small, z_steps, minimum_offset_z, step_sizes_big}")
parasitic_motion = False
stage_coords.append(stage.position)
@ -216,7 +205,17 @@ class RangeofMotionThing(Thing):
# Medium sized steps
for loop in range(5):
image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
delta, offset, focus_data, wrong_axis = move_and_measure(step_size = z_steps, axis = axis, delta = delta, image1 = image1, autofocus_proc = True, focus_data = focus_data, csm = csm, autofocus = autofocus, cam = cam)
delta, offset, focus_data, wrong_axis = move_and_measure(
step_size=dict_generate(medium_step, stream_resolution, direction),
axis=axis,
delta=delta,
image1=image1,
autofocus_proc=True,
focus_data=focus_data,
csm=csm,
autofocus=autofocus,
cam=cam,
)
logger.info(f"Offset measured as {delta[axis]}")
stage_coords.append(stage.position)
cor_lat_steps.append(offset)
@ -252,7 +251,19 @@ class RangeofMotionThing(Thing):
# Turn into function
for loop in range(3):
image1 = cv2.resize(np.array(Image.open(cam.grab_jpeg().open())), dsize=(0,0), fx= 1, fy= 1)
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)
delta, offset, focus_data, wrong_axis = move_and_measure(
step_size=dict_generate(
small_step, stream_resolution, direction
),
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]) < np.abs(minimum_offset_small[axis]) and failure_count < 3: