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118 lines
4.1 KiB
118 lines
4.1 KiB
""" Sensospot Images |
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Creating nice spot images from scans |
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""" |
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__version__ = "0.0.1" |
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from pathlib import Path |
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import sys |
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from sensospot_data import parse_file |
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from sensospot_data.parameters import _search_measurement_params_file |
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from .images import recalculate, get_position, annotate_image, load_array_image, crop |
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from .parameters import get_spot_parameters, get_array_parameters |
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def calulate_pixel_size(data_frame, array_definition): |
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first = get_position(data_frame.iloc[0], actual=False) |
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last = get_position(data_frame.iloc[-1], actual=False) |
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x_dist_pixel = last.x - first.x |
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y_dist_pixel = last.y - first.y |
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ad = array_definition |
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x_dist_um = ad.dist_x * (ad.size_x - 1) |
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y_dist_um = ad.dist_y * (ad.size_y - 1) |
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if x_dist_um == 0: |
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# only one spot in x direction |
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return x_dist_um / x_dist_pixel |
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elif y_dist_um == 0: |
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# only one spot in x direction |
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return y_dist_um / y_dist_pixel |
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# more than one spot in each direction |
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x_pixel_size = x_dist_um / x_dist_pixel |
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y_pixel_size = y_dist_um / y_dist_pixel |
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return (x_pixel_size + y_pixel_size) / 2 |
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def get_example_data_path(input_dir): |
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input_path = Path(input_dir) |
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tif_files = input_path.glob("*.tif") |
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example_tif = next(tif_files) |
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return example_tif.with_suffix(".csv") |
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def get_filename_prefix(input_dir): |
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file_path = get_example_data_path(input_dir) |
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example_name = file_path.stem |
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prefix, well, exposure = example_name.rsplit("_", 2) |
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return prefix |
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def retrieve_spot_parameters(input_dir, scale): |
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parameters_path = _search_measurement_params_file(input_dir) |
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if parameters_path is None: |
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sys.exit(f"Could not find parameter files in {input_dir}") |
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array_parameters = get_array_parameters(parameters_path) |
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spot_parameters = get_spot_parameters(parameters_path, array_parameters) |
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example_data_path = get_example_data_path(input_dir) |
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example_data = parse_file(example_data_path) |
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pixel_size = calulate_pixel_size(example_data, array_parameters) |
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return recalculate(spot_parameters, scale / pixel_size) |
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def search_image_files(input_dir, wells, exposures): |
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input_path = Path(input_dir) |
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prefix = get_filename_prefix(input_path) |
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tmp_pattern = f"{prefix}_*{wells}*_*{exposures}.tif" |
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pattern = tmp_pattern.replace("***", "*").replace("**", "*") |
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return input_path.glob(pattern) |
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def create_file_map(input_dir, wells, exposures): |
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file_map = {} |
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for tif_path in search_image_files(input_dir, wells, exposures): |
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rest, exposure = tif_path.stem.rsplit("_", 1) |
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csv_path = tif_path.parent / f"{rest}_1.csv" |
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if csv_path.is_file(): |
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if csv_path not in file_map: |
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file_map[csv_path] = [] |
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file_map[csv_path].append(tif_path) |
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return file_map |
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def process_image(image_file, spot_parameters, spot_data, scale): |
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img = load_array_image(image_file, scale=scale) |
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annotate_image(img, spot_parameters, spot_data, scale) |
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return img |
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def create_crops(output_path, img, image_path, spot_parameters, array_data, scale): |
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base_name = image_path.stem |
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for index, spot_data in array_data.iterrows(): |
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cropped_img = crop(img, spot_parameters, spot_data, scale) |
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new_path = output_path / f"{base_name}_{index + 1:03}.tif" |
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cropped_img.save(new_path) |
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def process(input_dir, output_dir, scale=3, wells="*", exposures="*", add_single_spots=False): |
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spot_parameters = retrieve_spot_parameters(input_dir, scale) |
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file_map = create_file_map(input_dir, wells, exposures) |
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output_path = Path(output_dir) |
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if not output_path.is_dir(): |
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sys.exit(f"Could not find output directory: {output_dir}") |
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for data_file, image_files in file_map.items(): |
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array_data = parse_file(data_file) |
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print(data_file) |
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for image_path in image_files: |
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img = process_image(image_path, spot_parameters, array_data, scale) |
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img.save(output_path / image_path.name) |
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if add_single_spots: |
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create_crops(output_path, img, image_path, spot_parameters, array_data, scale) |
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