def validation_section(output_location, repeats=12):
jetzt = datetime.now()
timestamp = jetzt.strftime("%b%d_%H%M_")
testname = str(timestamp + "ValidationTest_Section")
main_output_path = fibermorph.make_subdirectory(output_location, append_name=testname)
dummy_dir = fibermorph.make_subdirectory(main_output_path, append_name="ValidationData")
shape_list = ["circle", "ellipse"]
replist = [el for el in shape_list for i in range(repeats)]
output_path = fibermorph.make_subdirectory(main_output_path, append_name="ValidationAnalysis")
for shape in replist:
print(shape)
df, img, im_path, df_path = dummy_data.dummy_data_gen(
output_directory=dummy_dir,
shape=shape,
min_elem=1,
max_elem=1,
im_width=5200,
im_height=3900,
width=1)
valid_df = pd.DataFrame(df).sort_values(by=[0], axis=1)
min_ax = np.asarray(valid_df)[0][0]
max_ax = np.asarray(valid_df)[0][1]
valid_df['ref_min'] = min_ax
valid_df['ref_max'] = max_ax
valid_df['ref_eccentricity'] = np.sqrt(1 - (min_ax ** 2) / (max_ax ** 2))
valid_df.drop(columns=['ref_height', 'ref_width'])
test_df = fibermorph.analyze_section(im_path, output_path, minsize=0, maxsize=3900, resolution=1.0)
test_df['error_min'] = abs(valid_df['ref_min'] - test_df['min']) / valid_df['ref_min']
test_df['error_max'] = abs(valid_df['ref_max'] - test_df['max']) / valid_df['ref_max']
test_df['error_area'] = abs(valid_df['ref_area'] - test_df['area']) / valid_df['ref_area']
test_df['error_eccentricity'] = np.nan_to_num(
abs(valid_df['ref_eccentricity'] - test_df['eccentricity']) / valid_df['ref_eccentricity'], posinf=0)
valid_df2 = valid_df.join(test_df)
col_list = ['error_min', 'error_max', 'error_area', 'error_eccentricity']
error_df = valid_df2
# error_df = valid_df2[col_list]
im_name = im_path.stem
df_path = pathlib.Path(output_path).joinpath(str(im_name) + "_errordata.csv")
error_df.to_csv(df_path)
print("Results saved as:\n")
print(df_path)
return main_output_path
def create_results_cache():
relpath = "fibermorph/demo"
datadir = pathlib.Path.cwd().joinpath(relpath)
cache = fibermorph.make_subdirectory(datadir, "results_cache")
# Designate where fibermorph should make the directory with all your results - this location must exist!
os.makedirs(cache, exist_ok=True)
output_directory = os.path.abspath(cache)
return output_directory
def get_data(im_type="all"):
relpath = "fibermorph/demo/data"
datadir = pathlib.Path.cwd().joinpath(relpath)
datadir = fibermorph.make_subdirectory(datadir, "tmpdata")
if im_type == "curv" or im_type == "section":
tmpdir = fibermorph.make_subdirectory(datadir, im_type)
urllist = url_files(im_type)
download_im(tmpdir, urllist)
return tmpdir
else:
typelist = ["curv", "section"]
for im_type in typelist:
tmpdir = fibermorph.make_subdirectory(datadir, im_type)
urllist = url_files(im_type)
download_im(tmpdir, urllist)
return True
def real_curv():
"""Downloads curvature data and runs fibermorph_curv analysis.
Returns
-------
bool
True.
"""
input_directory = get_data("curv")
jetzt = datetime.now()
timestamp = jetzt.strftime("%b%d_%H%M_")
testname = str(timestamp + "DemoTest_Curv")
output_location = fibermorph.make_subdirectory(create_results_cache(), append_name=testname)
fibermorph.curvature(input_directory, output_location, jobs=1, resolution=132, window_size_mm=0.5, save_img=True)
return True
def real_section():
"""Downloads section data and runs fibermorph_section analysis.
Returns
-------
bool
True.
"""
input_directory = get_data("section")
jetzt = datetime.now()
timestamp = jetzt.strftime("%b%d_%H%M_")
testname = str(timestamp + "DemoTest_Section")
output_dir = fibermorph.make_subdirectory(create_results_cache(), append_name=testname)
fibermorph.section(input_directory, output_dir, jobs=4, resolution=1.06)
return True
def validation_curv(output_location, repeats=3):
jetzt = datetime.now()
timestamp = jetzt.strftime("%b%d_%H%M_")
testname = str(timestamp + "ValidationTest_Curv")
main_output_path = fibermorph.make_subdirectory(output_location, append_name=testname)
dummy_dir = fibermorph.make_subdirectory(main_output_path, append_name="ValidationData")
shape_list = ["arc", "line"]
replist = [el for el in shape_list for i in range(repeats)]
output_path = fibermorph.make_subdirectory(main_output_path, append_name="ValidationAnalysis")
for shape in replist:
print(shape)
df, img, im_path, df_path = dummy_data.dummy_data_gen(
output_directory=dummy_dir,
shape=shape,
min_elem=10,
max_elem=20,
im_width=5200,
im_height=3900,
width=10)
valid_df = pd.DataFrame(df).sort_values(by=['ref_length'], ignore_index=True).reset_index(drop=True)
test_df = fibermorph.curvature_seq(im_path, output_path, resolution=1, window_size_mm=10, save_img=False, test=True)
test_df2 = pd.DataFrame(test_df).sort_values(by=['length'], ignore_index=True).reset_index(drop=True)
col_list = ['error_length']
if shape == "arc":
valid_df['index1'] = valid_df['ref_length'] * valid_df['ref_radius']
valid_df = pd.DataFrame(valid_df).sort_values(by=['index1'], ignore_index=True).reset_index(drop=True)
test_df2['radius'] = 1 / test_df2['curv_median']
test_df2['index2'] = test_df2['length'] * test_df2['radius']
test_df2 = pd.DataFrame(test_df2).sort_values(by=['index2'], ignore_index=True).reset_index(drop=True)
test_df2['error_radius'] = abs(valid_df['ref_radius'] - test_df2['radius']) / valid_df['ref_radius']
test_df2['error_curvature'] = abs(valid_df['ref_curvature'] - test_df2['curv_median']) / valid_df[
'ref_curvature']
col_list = ['error_radius', 'error_curvature', 'error_length']
test_df2['error_length'] = abs(valid_df['ref_length'] - test_df2['length']) / valid_df['ref_length']
valid_df2 = valid_df.join(test_df2)
error_df = valid_df2
# error_df = valid_df2[col_list]
im_name = im_path.stem
df_path = pathlib.Path(output_path).joinpath(str(im_name) + "_errordata.csv")
error_df.to_csv(df_path)
print("Results saved as:\n")
print(df_path)
shutil.rmtree(pathlib.Path(output_path).joinpath("analysis"))
return main_output_path