From 7f66235cac4b2fc589373dcce3d37ea4c5b3f3f0 Mon Sep 17 00:00:00 2001 From: Richard Bowman Date: Wed, 6 Apr 2022 23:36:55 +0100 Subject: [PATCH] Lint and type fixes --- .../api/default_extensions/scan.py | 58 +++++++++++++------ 1 file changed, 39 insertions(+), 19 deletions(-) diff --git a/openflexure_microscope/api/default_extensions/scan.py b/openflexure_microscope/api/default_extensions/scan.py index 43cb14b2..4253bb6d 100644 --- a/openflexure_microscope/api/default_extensions/scan.py +++ b/openflexure_microscope/api/default_extensions/scan.py @@ -2,10 +2,10 @@ import datetime import logging import time import uuid -from functools import reduce from typing import Dict, List, Optional, Tuple import marshmallow +import numpy as np from labthings import ( current_action, fields, @@ -15,7 +15,6 @@ from labthings import ( ) from labthings.extensions import BaseExtension from labthings.views import ActionView -import numpy as np from typing_extensions import Literal from openflexure_microscope.api.v2.views.actions.camera import FullCaptureArgs @@ -36,7 +35,7 @@ def construct_grid( step_sizes: XyCoordinate, n_steps: XyCoordinate, style: Literal["raster", "snake", "spiral"] = "raster", -): +) -> List[List[XyCoordinate]]: """ Given an initial position, step sizes, and number of steps, construct a 2-dimensional list of scan x-y positions. @@ -96,7 +95,9 @@ def construct_grid( return arr -def closest_point_in_xy(current_position: XyCoordinate, points: List[XyzCoordinate]): +def closest_point_in_xy( + current_position: XyCoordinate, points: List[XyzCoordinate] +) -> Optional[XyzCoordinate]: """Find the closest point in a list Given a 2D position, find the 3D position that's closest in XY and return it. @@ -108,16 +109,14 @@ def closest_point_in_xy(current_position: XyCoordinate, points: List[XyzCoordina return None points_2d = np.asarray(points)[:, :2] - squared_distances = np.sum((points_2d - current_position)**2, axis=1) + squared_distances = np.sum((points_2d - current_position) ** 2, axis=1) # We reverse the distances before searching, as argmin will return the first # point in the event of there being multiple points with the same minimum, # and we want to pick the last one. reverse_min_index = np.argmin(squared_distances[::-1]) # of course, now we must convert the index to be the right way round min_index = len(points) - 1 - reverse_min_index - if min_index != len(points) - 1: - logging.info(f"Using point {min_index} of {len(points)} for focus.") - return points[min_index] + return points[int(min_index)] # The explicit cast is necessary for MyPy ### Capturing @@ -200,7 +199,7 @@ class ScanExtension(BaseExtension): metadata: Optional[dict] = None, annotations: Optional[Dict[str, str]] = None, tags: Optional[List[str]] = None, - detect_empty_fields_and_skip_autofocus: bool = False + detect_empty_fields_and_skip_autofocus: bool = False, ): metadata = metadata or {} annotations = annotations or {} @@ -213,7 +212,7 @@ class ScanExtension(BaseExtension): # Construct an x-y grid (worry about z later) x_y_grid = construct_grid( initial_position[:2], stride_size[:2], grid[:2], style=style - ) # This is a list of lists. + ) # This is a list of lists. # Keep task progress # NB the number of points is found from the number of elements in @@ -225,7 +224,6 @@ class ScanExtension(BaseExtension): if not basename: basename = generate_basename() - # Add dataset metadata dataset_d = { "id": uuid.uuid4(), @@ -252,11 +250,17 @@ class ScanExtension(BaseExtension): if detect_empty_fields_and_skip_autofocus: # Check for the background detect extension if we need it, raise an error now if it's missing. - background_detect_extension = find_extension("org.openflexure.background-detect") + background_detect_extension = find_extension( + "org.openflexure.background-detect" + ) if not background_detect_extension: - raise RuntimeError("Detecting background fields requires the background detect extension and it was not found.") + raise RuntimeError( + "Detecting background fields requires the background detect extension and it was not found." + ) - focused_positions: List[XyzCoordinate] = [] # Positions where we found sharp images + focused_positions: List[ + XyzCoordinate + ] = [] # Positions where we found sharp images # Now step through each point in the x-y coordinate array for line in x_y_grid: @@ -267,7 +271,11 @@ class ScanExtension(BaseExtension): # point, except when we're at the start of a row when it will be the first # point of the preceding row. closest_focused_point = closest_point_in_xy(x_y, focused_positions) - next_z = closest_focused_point[2] if closest_focused_point else initial_position[2] + next_z = ( + closest_focused_point[2] + if closest_focused_point + else initial_position[2] + ) # Move to new grid position logging.debug("Moving to step %s", ([x_y[0], x_y[1], next_z])) microscope.stage.move_abs((x_y[0], x_y[1], next_z)) @@ -279,7 +287,9 @@ class ScanExtension(BaseExtension): logging.debug(f"Background detection verdict: {verdict}") if verdict["classification"] == "background": skip_autofocus = True - logging.info(f"Detected an empty field at {x_y}, skipping autofocus.") + logging.info( + f"Detected an empty field at {x_y}, skipping autofocus." + ) if autofocus_enabled and not skip_autofocus: if fast_autofocus: @@ -297,11 +307,19 @@ class ScanExtension(BaseExtension): here = microscope.stage.position # Check if we've moved worryingly far in Z if closest_focused_point: - lateral_move = np.sqrt(np.sum((np.array(here)[:2] - np.array(closest_focused_point)[:2])**2)) + lateral_move = np.sqrt( + np.sum( + ( + np.array(here)[:2] + - np.array(closest_focused_point)[:2] + ) + ** 2 + ) + ) axial_move = np.abs(here[2] - closest_focused_point[2]) if axial_move > lateral_move * 0.4: autofocus_accepted = False - logging.warn( + logging.warning( f"During a scan, there was a large axial jump from {closest_focused_point}" f" to {here}. This may mean autofocus has failed." ) @@ -473,5 +491,7 @@ class TileScanAPI(ActionView): fast_autofocus=args.get("fast_autofocus"), annotations=args.get("annotations"), tags=args.get("tags"), - detect_empty_fields_and_skip_autofocus=args.get("detect_empty_fields_and_skip_autofocus"), + detect_empty_fields_and_skip_autofocus=args.get( + "detect_empty_fields_and_skip_autofocus" + ), )