109 lines
3.5 KiB
Python
109 lines
3.5 KiB
Python
import os
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import pytest
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from navigate.tools.file_functions import delete_folder
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@pytest.mark.parametrize("is_ome", [True, False])
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@pytest.mark.parametrize("multiposition", [True, False])
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@pytest.mark.parametrize("per_stack", [True, False])
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@pytest.mark.parametrize("z_stack", [True, False])
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@pytest.mark.parametrize("stop_early", [True, False])
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def test_tiff_write_read(is_ome, multiposition, per_stack, z_stack, stop_early):
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import numpy as np
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from test.model.dummy import DummyModel
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from navigate.model.data_sources.tiff_data_source import TiffDataSource
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print(
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f"Conditions are is_ome: {is_ome} multiposition: {multiposition} "
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f"per_stack: {per_stack} z_stack: {z_stack} stop_early: {stop_early}"
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)
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# Set up model with a random number of z-steps to modulate the shape
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model = DummyModel()
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z_steps = np.random.randint(1, 3)
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timepoints = np.random.randint(1, 3)
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model.configuration["experiment"]["MicroscopeState"]["image_mode"] = (
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"z-stack" if z_stack else "single"
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)
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model.configuration["experiment"]["MicroscopeState"]["number_z_steps"] = z_steps
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model.configuration["experiment"]["MicroscopeState"][
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"is_multiposition"
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] = multiposition
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model.configuration["experiment"]["MicroscopeState"]["timepoints"] = timepoints
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if per_stack:
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model.configuration["experiment"]["MicroscopeState"][
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"stack_cycling_mode"
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] == "per_stack"
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else:
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model.configuration["experiment"]["MicroscopeState"][
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"stack_cycling_mode"
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] == "per_slice"
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if not os.path.exists("test_save_dir"):
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os.mkdir("test_save_dir")
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# Establish a TIFF data source
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if is_ome:
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fn = "./test_save_dir/test.ome.tif"
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else:
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fn = "./test_save_dir/test.tif"
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ds = TiffDataSource(fn)
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ds.set_metadata_from_configuration_experiment(model.configuration)
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# Populate one image per channel per timepoint per position
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n_images = ds.shape_c * ds.shape_z * ds.shape_t * ds.positions
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data = (np.random.rand(n_images, ds.shape_y, ds.shape_x) * 2**16).astype(
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np.uint16
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)
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file_names_raw = []
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for i in range(n_images):
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ds.write(data[i, ...].squeeze())
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file_names_raw.extend(ds.file_name)
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if stop_early and np.random.rand() > 0.5:
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break
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ds.close()
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# Cannot use list(set()) trick here because ordering is important
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file_names = []
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for fn in file_names_raw:
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if fn not in file_names:
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file_names.append(fn)
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# print(file_names)
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try:
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# For each file...
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for i, fn in enumerate(file_names):
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ds2 = TiffDataSource(fn, "r")
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# Make sure XYZ size is correct (and C and T are each of size 1)
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assert (
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(ds2.shape_x == ds.shape_x)
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and (ds2.shape_y == ds.shape_y)
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and (ds2.shape_c == 1)
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and (ds2.shape_t == 1)
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and (ds2.shape_z == ds.shape_z)
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)
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# Make sure the data copied properly
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np.testing.assert_equal(
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ds2.data, data[i * ds.shape_z : (i + 1) * ds.shape_z, ...].squeeze()
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)
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ds2.close()
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except IndexError as e:
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if stop_early:
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# This file was not written
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pass
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else:
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raise e
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except AssertionError as e:
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if stop_early:
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# This file has an underfilled axes
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pass
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else:
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raise e
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except Exception as e:
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raise e
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finally:
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delete_folder("test_save_dir")
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