rahix/openflexure-microscope-server
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Zip files as we scan, saving the regenerated ones to the end

Browse source 
Removed maximum scan size of 750 images

Save json of scan inputs and use it for future stitching (ensures consistent parameters)

Moved looping autofocus to autofocus thing from recentering thing

Rewrote looping autofocus to skip unneeded moves, as if peak is out of range, no need to nicely focus
This commit is contained in:
jaknapper 2024-01-30 18:46:34 +00:00
parent a0b98a1adc
commit e6e809cea4
3 changed files with 139 additions and 53 deletions
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43
src/openflexure_microscope_server/things/autofocus.py
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@ -119,7 +119,7 @@ class JPEGSharpnessMonitor:
raise ValueError(
"No images were captured during the move of the stage. Perhaps the camera is not streaming images?"
)
return jz[np.argmax(js)], jz, js
return jz[np.argmax(js)]
def data_dict(self) -> SharpnessDataArrays:
"""Return the gathered data as a single convenient dictionary"""
@ -161,13 +161,13 @@ class AutofocusThing(Thing):
# z: Final z position after move
i, z = m.focus_rel(dz, block_cancellation=True)
# Get the z position with highest sharpness from the previous move (index i)
fz, heights, sizes = m.sharpest_z_on_move(i)
fz: int = m.sharpest_z_on_move(i)
# Move all the way to the start so it's consistent
i, z = m.focus_rel(-dz)
# Move to the target position fz (relative move of (fz - z))
m.focus_rel(fz - z)
# Return all focus data
return heights, sizes
return m.data_dict()
@thing_action
def move_and_measure(
@ -194,3 +194,40 @@ class AutofocusThing(Thing):
time.sleep(wait)
m.focus_rel(current_dz)
return m.data_dict()
@thing_action
def looping_autofocus(self, stage: Stage, m: SharpnessMonitorDep, dz=2000, start='centre'):
"""Repeatedly autofocus the stage until it looks focused.
This action will run the `fast_autofocus` action until it settles on a point
in the middle 3/5 of its range. Such logic can be helpful if the microscope
is close to focus, but not quite within `dz/2`. It will attempt to autofocus
up to 10 times.
"""
repeat = True
attempts = 0
with m.run():
while repeat and attempts < 10:
if start == 'centre':
stage.move_relative(x = 0, y = 0, z = -dz / 2)
i, z = m.focus_rel(dz, block_cancellation=True)
_, heights, sizes = m.move_data(i)
peak_height = heights[np.argmax(sizes)]
height_min = np.min(heights)
height_max = np.max(heights)
if (
peak_height - height_min < dz / 5
or height_max - peak_height < dz / 5
):
attempts += 1
start = 'centre'
stage.move_absolute(z = peak_height)
else:
repeat = False
stage.move_relative(x = 0, y = 0, z = -dz)
stage.move_absolute(z = peak_height)