184 lines
6.7 KiB
Python
184 lines
6.7 KiB
Python
"""Test the functionality specific to the simulated camera."""
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import logging
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import time
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import numpy as np
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import pytest
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from hypothesis import given
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from hypothesis import strategies as st
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import labthings_fastapi as lt
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from openflexure_microscope_server.things.camera import simulation
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from openflexure_microscope_server.things.camera.simulation import SimulatedCamera
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from openflexure_microscope_server.things.stage.dummy import DummyStage
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from ..shared_utils.lt_test_utils import LabThingsTestEnv
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@pytest.fixture
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def test_env() -> LabThingsTestEnv:
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"""Yield a test environment with the Simulated Camera and Dummy Stage."""
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thing_conf = {"camera": SimulatedCamera, "stage": DummyStage}
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with LabThingsTestEnv(things=thing_conf) as env:
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yield env
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@pytest.fixture
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def camera(test_env) -> lt.Thing:
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"""Return the SimulatedCamera Thing set up in the test environment."""
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return test_env.get_thing_by_type(SimulatedCamera)
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@pytest.fixture
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def stage(test_env) -> lt.Thing:
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"""Return the DummyStage Thing set up in the test environment."""
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return test_env.get_thing_by_type(DummyStage)
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def test_downsample_shape_2d():
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"""Test downsampling for 2D array."""
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shape_2d = (100, 80)
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result_2d = simulation._downsample_shape(shape_2d)
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assert len(result_2d) == 2
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assert result_2d == (100 // simulation.DOWNSAMPLE, 80 // simulation.DOWNSAMPLE)
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def test_downsample_shape_3d():
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"""Test downsampling for 3D array, should not affect 3rd axis or shape."""
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shape_3d = (120, 60, 3)
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result_3d = simulation._downsample_shape(shape_3d)
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assert len(result_3d) == 3
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assert result_3d == (120 // simulation.DOWNSAMPLE, 60 // simulation.DOWNSAMPLE, 3)
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def test_downsample_shape_invalid_length():
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"""Shapes that are not length 2 or 3 should raise ValueError."""
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with pytest.raises(ValueError, match="Shape should be a 2 or 3 element tuple."):
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simulation._downsample_shape((1,))
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with pytest.raises(ValueError, match="Shape should be a 2 or 3 element tuple."):
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simulation._downsample_shape((1, 2, 3, 4))
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def all_colours_present(
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col_str: str, colours: list[tuple[int, int, int]], tries: int = 100
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) -> bool:
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"""Check that for a given colour string that all listed colours are returned.
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A helper function for testing simulation.colour_str_to_colour. As the result is
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randomised the test just tries multiple times. In theory could fail, so pick
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tries high enough if there are lots of colours in col_str.
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"""
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found = [False for _c in colours]
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for _i in range(tries):
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col_tuple = simulation.colour_str_to_colour(col_str)
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if col_tuple not in colours:
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raise ValueError("Unexpected colour returned.")
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found[colours.index(col_tuple)] = True
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# Don't exit early or we don't confrm that extra colours are not returned.
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return all(found)
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def test_colour_str_to_colour():
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"""Test colour_str_to_colour with some basic predefined test cases."""
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# A basic test
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assert simulation.colour_str_to_colour("#123456") == (0x12, 0x34, 0x56)
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# A basic test with a trailing semicolon and surrounding spacing
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assert simulation.colour_str_to_colour(" #123456 ; ") == (0x12, 0x34, 0x56)
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# A 2 colour test
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assert all_colours_present(
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"#123456; #654321", [(0x12, 0x34, 0x56), (0x65, 0x43, 0x21)]
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)
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# A failure_test (to check the helper function works!)
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with pytest.raises(ValueError, match="Unexpected colour returned."):
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assert all_colours_present(
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"#123456; #654321", [(0x12, 0x34, 0x56), (0x11, 0x11, 0x11)]
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)
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# And some incorrect strings that should fire an error in colour_str_to_colour
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bad_colours = ["foobar", "pink", "#123", "#123456, #654321"]
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for colour_str in bad_colours:
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with pytest.raises(
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ValueError, match=r".*not a valid colour. Please use HTML hex notation."
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):
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simulation.colour_str_to_colour(colour_str)
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@given(st.from_regex(simulation.COLOUR_LIST_REGEX, fullmatch=True))
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def test_colour_list_regex(colour_str):
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"""Check that anything matching the regex doesn't error when generating colours.
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This will error if colour_str when splot into individual colours produces
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# an incorrect colour. Trying 100 times for each colour_str as the returned colour
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is randomised. Hypothesis will try to create the strings that match the regex but
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break the test.
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"""
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for _ in range(100):
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simulation.colour_str_to_colour(colour_str)
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def test_canvas_regeneration(camera, caplog):
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"""Check canvas is regenerated if blob density of colour are changed."""
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cached_canvas = camera.canvas
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original_colour = camera.colour
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# First try a bad colour string
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with caplog.at_level(logging.WARNING):
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camera.colour = "foobar"
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assert len(caplog.messages) == 1
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assert caplog.messages[0] == "foobar is not a valid colour string."
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# Value and canvas unchanged
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assert camera.colour == original_colour
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assert camera.canvas is cached_canvas
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# Set a valid colour
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camera.colour = "#123456"
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assert camera.colour == "#123456"
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# canvas updated
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assert camera.canvas is not cached_canvas
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# Cache again
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cached_canvas = camera.canvas
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camera.blob_density = 321
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assert camera.blob_density == 321
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# Canvas updated again
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assert camera.canvas is not cached_canvas
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def test_infinite_sample(camera, stage):
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"""Check that setting camera.repeating makes the sample infinite."""
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# Turn off noise to make comparison easier
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camera.noise_level = 0
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assert not camera.repeating
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cached_canvas = camera.canvas
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array_not_repeating = camera.capture_array()
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camera.repeating = True
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time.sleep(0.2) # Ensure frame regenerates
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# Canvas shouldn't regenerate
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assert camera.canvas is cached_canvas
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array_repeating = camera.capture_array()
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# Images are identical whether or not repeating
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assert np.array_equal(array_not_repeating, array_repeating)
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# Move outside the non-repeating sample area
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stage._hardware_position["x"] = 100_000_000
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camera.repeating = False
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time.sleep(0.2) # Ensure frame regenerates
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# If not repeating the array is just background
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assert np.all(camera.capture_array() == simulation.BG_COLOR)
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# Turn on repeating
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camera.repeating = True
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time.sleep(0.2) # Ensure frame regenerates
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# Sample is now infitine, so not all background
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assert not np.all(camera.capture_array() == simulation.BG_COLOR)
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def test_simulation_cam_calibration(camera):
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"""Test that the simulated camera can be calibrated and reports calibration correctly."""
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assert camera.calibration_required
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camera.full_auto_calibrate()
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assert not camera.calibration_required
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assert camera.background_detector_status.ready
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