Reverted logging style
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e25c23cf1c
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24 changed files with 100 additions and 106 deletions
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@ -83,7 +83,7 @@ class JPEGSharpnessMonitor:
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raise e
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if stop < 1:
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stop = len(jpeg_times)
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logging.debug("changing stop to {}", (stop))
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logging.debug("changing stop to %s", (stop))
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jpeg_times = jpeg_times[start:stop]
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jpeg_zs = np.interp(jpeg_times, stage_times, stage_zs)
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return jpeg_times, jpeg_zs, jpeg_sizes[start:stop]
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@ -258,13 +258,12 @@ def fast_up_down_up_autofocus(
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# Ensure the MJPEG stream has started
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microscope.camera.start_stream_recording()
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df = dz # TODO: refactor so I actually use dz in the code below!
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logging.debug("Initial move")
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if initial_move_up:
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m.focus_rel(df / 2)
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m.focus_rel(dz / 2)
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# move down
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logging.debug("Move down")
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i, z = m.focus_rel(-df)
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i, z = m.focus_rel(-dz)
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# now inspect where the sharpest point is, and estimate the sharpness
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# (JPEG size) that we should find at the start of the Z stack
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_, jz, js = m.move_data(i)
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@ -285,14 +284,13 @@ def fast_up_down_up_autofocus(
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inow = np.argmax(
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js < current_js
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) # use the curve we recorded to estimate our position
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# TODO: fancy interpolation stuff
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# So, the Z position corresponding to our current sharpness value is zs[inow]
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# That means we should move forwards, by best_z - zs[inow]
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logging.debug("Correction move")
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correction_move = best_z + target_z - jz[inow]
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logging.debug(
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"Fast autofocus scan: correcting backlash by moving {} steps",
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"Fast autofocus scan: correcting backlash by moving %s steps",
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(correction_move),
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)
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m.focus_rel(correction_move)
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