328 lines
11 KiB
Python
328 lines
11 KiB
Python
import time
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from typing import Tuple
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from functools import reduce
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import uuid
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import itertools
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import logging
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from openflexure_microscope.camera.base import generate_basename
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from openflexure_microscope.devel import (
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MicroscopePlugin,
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update_task_progress,
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update_task_data,
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)
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from .api import TileScanAPI
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def construct_grid(initial, step_sizes, n_steps, style="raster"):
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"""
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Given an initial position, step sizes, and number of steps,
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construct a 2-dimensional list of scan x-y positions.
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"""
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arr = []
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for i in range(n_steps[0]): # x axis
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arr.append([])
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for j in range(n_steps[1]): # y axis
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# Create a coordinate array
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coord = [initial[ax] + [i, j][ax] * step_sizes[ax] for ax in range(2)]
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# Append coordinate array to position grid
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arr[i].append(tuple(coord))
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# Style modifiers
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if style == "snake":
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for i, line in enumerate(arr):
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if i % 2 != 0:
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line.reverse()
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return arr
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def flatten_grid(grid):
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"""
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Convert a 3D list of scan positions into a flat list
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of sequential positions.
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"""
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grid = list(itertools.chain(*grid))
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return grid
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class ScanPlugin(MicroscopePlugin):
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"""
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Stack and tile plugin
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"""
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api_views = {"/tile": TileScanAPI}
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def __init__(self):
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MicroscopePlugin.__init__(self)
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self.images_to_be_captured: int = 1
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update_task_data({"images_to_be_captured": self.images_to_be_captured})
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@property
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def progress(self):
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progress = (self.images_captured_so_far / self.images_to_be_captured) * 100
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logging.info(progress)
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return progress
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def capture(
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self,
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basename,
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scan_id,
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temporary: bool = False,
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use_video_port: bool = False,
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resize: Tuple[int, int] = None,
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bayer: bool = False,
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metadata: dict = {},
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tags: list = [],
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):
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# Construct a tile filename
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filename = "{}_{}_{}_{}".format(basename, *self.microscope.stage.position)
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folder = "SCAN_{}".format(basename)
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# Create output object
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output = self.microscope.camera.new_image(
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temporary=temporary, filename=filename, folder=folder
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)
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# Capture
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self.microscope.camera.capture(
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output.file, use_video_port=use_video_port, resize=resize, bayer=bayer
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)
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# Affix metadata
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if "scan" not in tags:
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tags.append("scan")
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# Inject system metadata
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output.put_metadata(self.microscope.metadata, system=True)
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# Insert custom metadata
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output.put_metadata(metadata)
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# Insert custom tags
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output.put_tags(tags)
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def tile(
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self,
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basename: str = None,
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temporary: bool = False,
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step_size: int = [2000, 1500, 100],
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grid: list = [3, 3, 5],
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style="raster",
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autofocus_dz: int = 50,
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use_video_port: bool = False,
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resize: Tuple[int, int] = None,
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bayer: bool = False,
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fast_autofocus=False,
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metadata: dict = {},
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tags: list = [],
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):
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# Keep task progress
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# TODO: Make this line not nasty
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self.images_to_be_captured = reduce((lambda x, y: x * y), grid)
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self.images_captured_so_far = 0
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# Generate a basename if none given
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if not basename:
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basename = generate_basename()
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# Generate a stack ID
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scan_id = uuid.uuid4().hex
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# Store initial position
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initial_position = self.microscope.stage.position
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# Add scan metadata
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if "time" not in metadata:
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metadata["time"] = generate_basename()
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metadata.update(
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{
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"scan_id": scan_id,
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"basename": basename,
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"scan_parameters": {
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"step_size": step_size,
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"grid": grid,
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"style": style,
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"autofocus_dz": autofocus_dz,
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},
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}
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)
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# Check if autofocus is enabled
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if (
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autofocus_dz
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and hasattr(self.microscope.plugins, "default_autofocus")
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and self.microscope.has_real_stage()
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and self.microscope.has_real_camera()
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):
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autofocus_enabled = True
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else:
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autofocus_enabled = False
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if fast_autofocus and not hasattr(
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self.microscope.plugins.default_autofocus, "monitor_sharpness"
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):
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logging.warning(
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"Can't use fast autofocus in the scan - the default plugin doesn't support monitor_sharpness; maybe it is too old?"
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)
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fast_autofocus = False
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z_stack_dz = (
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grid[2] * step_size[2] if grid[2] > 1 else 0
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) # shorthand for Z stack range
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# Construct an x-y grid (worry about z later)
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x_y_grid = construct_grid(
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initial_position, step_size[:2], grid[:2], style=style
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)
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# Keep the initial Z position the same as our current position
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next_z = initial_position[2]
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if fast_autofocus: # If fast autofocus is enabled, make
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next_z += autofocus_dz / 2 # sure we start from the top of the range
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initial_z = next_z # Save this value for use in raster scans
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# Now step through each point in the x-y coordinate array
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for line in x_y_grid:
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# If rastering, rather than snake (or eventually spiral)
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# Return focus to initial position
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if style == "raster":
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next_z = initial_z
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logging.debug("Returning to initial z position")
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self.microscope.stage.move_abs(
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[line[0][0], line[0][1], next_z]
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) # RWB: I think this line is redundant
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for x_y in line:
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# Move to new grid position without changing z
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logging.debug("Moving to step {}".format([x_y[0], x_y[1], next_z]))
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self.microscope.stage.move_abs([x_y[0], x_y[1], next_z])
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# Refocus
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if autofocus_enabled:
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if fast_autofocus:
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self.microscope.plugins.default_autofocus.fast_up_down_up_autofocus(
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dz=autofocus_dz,
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target_z=-z_stack_dz / 2.0, # Finish below the focus
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initial_move_up=False, # We're already at the top of the scan
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)
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# TODO: save the focus data for future reference? Use it for diagnostics?
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else:
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logging.debug("Running autofocus")
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self.microscope.plugins.default_autofocus.autofocus(
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range(-3 * autofocus_dz, 4 * autofocus_dz, autofocus_dz)
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)
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logging.debug("Finished autofocus")
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time.sleep(1) # TODO: Remove
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# If we're not doing a z-stack, just capture
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if grid[2] <= 1:
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self.capture(
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basename,
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scan_id,
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temporary=temporary,
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use_video_port=use_video_port,
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resize=resize,
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bayer=bayer,
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metadata=metadata,
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tags=tags,
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)
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# Update task progress
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self.images_captured_so_far += 1
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update_task_progress(self.progress)
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else:
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logging.debug("Entering z-stack")
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self.stack(
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basename=basename,
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temporary=temporary,
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scan_id=scan_id,
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step_size=step_size[2],
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steps=grid[2],
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center=not fast_autofocus, # fast_autofocus does this for us!
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return_to_start=not fast_autofocus,
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use_video_port=use_video_port,
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resize=resize,
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bayer=bayer,
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metadata=metadata,
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tags=tags,
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)
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# Make sure we use our current best estimate of focus (i.e. the current position) next point
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next_z = self.microscope.stage.position[2]
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if fast_autofocus:
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next_z += (
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autofocus_dz / 2
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) # Fast autofocus requires us to start at the top of the range
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if grid[2] > 1:
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next_z -= int(
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grid[2] / 2.0 * step_size[2]
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) # Z stacking means we're higher up to start with
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logging.debug("Returning to {}".format(initial_position))
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self.microscope.stage.move_abs(initial_position)
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def stack(
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self,
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basename: str = None,
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temporary: bool = False,
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scan_id: str = None,
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step_size: int = 100,
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steps: int = 5,
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center: bool = True,
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return_to_start: bool = True,
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use_video_port: bool = False,
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resize: Tuple[int, int] = None,
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bayer: bool = False,
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metadata: dict = {},
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tags: list = [],
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):
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# Generate a basename if none given
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if not basename:
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basename = generate_basename()
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# Generate a stack ID
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if not scan_id:
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scan_id = uuid.uuid4().hex
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# Add scan metadata
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if not "time" in metadata:
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metadata["time"] = generate_basename()
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# Store initial position
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initial_position = self.microscope.stage.position
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with self.microscope.lock:
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# Move to center scan
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if center:
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logging.debug("Moving to starting position")
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self.microscope.stage.move_rel([0, 0, int((-step_size * steps) / 2)])
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for i in range(steps):
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time.sleep(0.1)
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logging.debug("Capturing...")
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self.capture(
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basename,
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scan_id,
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temporary=temporary,
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use_video_port=use_video_port,
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resize=resize,
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bayer=bayer,
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metadata=metadata,
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tags=tags,
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)
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# Update task progress
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self.images_captured_so_far += 1
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update_task_progress(self.progress)
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if i != steps - 1:
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logging.debug("Moving z by {}".format(step_size))
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self.microscope.stage.move_rel([0, 0, step_size])
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if return_to_start:
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logging.debug("Returning to {}".format(initial_position))
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self.microscope.stage.move_abs(initial_position)
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