Exemple #1
0
def calc_histograms_lab_setups():
    for polimer_type in ["PDL-05", "PDLG-5002"]:
        radius_coefs = {"PDL-05": 0.9, "PDLG-5002": 0.95}

        paths = file_paths.get_benchtop_setup_paths(polimer_type)

        for sample_id in range(len(paths)):
            sample_name = list(paths.keys())[sample_id]
            print(
                f"============== {sample_id} sample: {sample_name} =============="
            )

            img3d = get_bin_img(sample_name)
            print('tot: ', np.sum(img3d) / img3d.size)

            fig, ax = plt.subplots()
            ax.imshow(img3d[0], cmap="gray")
            dm.save_plot(fig, "previews", f'{sample_id} bin ' + sample_name)

            cylindric_fragments, cylindric_masks \
                = divide_image_into_sector_cylindric_fragments(img3d,
                                                                height=len(img3d)//3-1,
                                                                radius_coef=radius_coefs[polimer_type])

            fig = get_porosity_histogram_disrtibution(
                cylindric_fragments,
                sample_name,
                img3d.shape,
                pixel_size_mm=PIXEL_SIZE_MM_SETUP,
                masks=cylindric_masks,
                radius_coef=radius_coefs[polimer_type])

            dm.save_plot(fig, SAVE_IMG_DESKTOP_SETUP_FOLDER,
                         f'hist {sample_id} {sample_name}')
Exemple #2
0
                sample_name,
                img3d.shape,
                pixel_size_mm=PIXEL_SIZE_MM_SETUP,
                masks=cylindric_masks,
                radius_coef=radius_coefs[polimer_type])

            dm.save_plot(fig, SAVE_IMG_DESKTOP_SETUP_FOLDER,
                         f'hist {sample_id} {sample_name}')


if __name__ == '__main__':

    polimer_type = ["PDL-05", "PDLG-5002"][0]
    radius_coefs = {"PDL-05": 0.9, "PDLG-5002": 0.95}

    paths = file_paths.get_benchtop_setup_paths(polimer_type)
    df = dm.load_data("setup_culindric_porosities.csv")
    #df =  pd.DataFrame(columns = ['polimer_type', 'sample_number', 'date', 'mean', 'std'])

    for sample_id in range(len(paths)):
        sample_name = list(paths.keys())[sample_id]
        print(
            f"============== {sample_id} sample: {sample_name} ==============")
        print(sample_name.split())

        img3d = ~get_bin_img(sample_name)
        print('tot: ', np.sum(img3d) / img3d.size)

        fig, ax = plt.subplots()
        ax.imshow(img3d[0], cmap="gray")
        dm.save_plot(fig, "previews", f'{sample_id} bin ' + sample_name)