def main_synchrotron(edge_size=400):
# ============= Обработка синхротронных данных =====================
# для неоцентрированных образцов
sample_crop_edges = {
'123493': (None, None),
'123494': (400, 1800),
'123495': (None, None),
'123496': (1200, 2100),
'123497': (None, None),
'123498': (1000, 1900)
}
file_id = '123498'
# for file_id in sample_crop_edges.keys():
# забираем уже отбинаризованый образец с папки database
bin_img = get_bin_img(file_id + '.h5').astype(bool)
# обрезаем картинку
left_edge, right_edge = sample_crop_edges[file_id]
if left_edge and right_edge:
bin_img = bin_img[:, left_edge:right_edge, :]
# наризаем на кубики, показываем это на первом слое (сечении) и строим гистограмму
img_fragments = divide_image_into_cubic_fragments(bin_img,
edge_size=edge_size)
save_first_section_of_img(bin_img, file_id, edge_size)
get_porosity_histogram_disrtibution(img_fragments, file_id, bin_img.shape,
PIXEL_SIZE_MM_SYNCHROTRON)
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}')
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)
cylindric_fragments, cylindric_masks \
= divide_image_into_sector_cylindric_fragments(img3d,
height=len(img3d)//3-1,
radius_coef=radius_coefs[polimer_type])
std, mean = get_mean_porosity_and_std(cylindric_fragments,
cylindric_masks)
data_info = sample_name.split()