diff --git a/qim3d/filters/_common_filter_methods.py b/qim3d/filters/_common_filter_methods.py
index 59b0be1291ff2f3480b44dc3df524c9794a2c6ed..026d292691b0d00946c78e832fb1e8571226fd80 100644
--- a/qim3d/filters/_common_filter_methods.py
+++ b/qim3d/filters/_common_filter_methods.py
@@ -8,9 +8,10 @@ from skimage import morphology
import dask.array as da
import dask_image.ndfilters as dask_ndfilters
-from qim3d.utils._logger import log
+from qim3d.utils import log
__all__ = [
+ "FilterBase",
"Gaussian",
"Median",
"Maximum",
diff --git a/qim3d/gui/annotation_tool.py b/qim3d/gui/annotation_tool.py
index 5ebae5f76cefe4d983f9dd1ac1dd24e5127feb62..79910e763048887c0f8f0fe1bd24d7fe7deaf6d3 100644
--- a/qim3d/gui/annotation_tool.py
+++ b/qim3d/gui/annotation_tool.py
@@ -27,10 +27,7 @@ import tempfile
import gradio as gr
import numpy as np
from PIL import Image
-
-from qim3d.io import load, save
-from qim3d.operations._common_operations_methods import overlay_rgb_images
-from qim3d.gui.interface import BaseInterface
+import qim3d
# TODO: img in launch should be self.img
@@ -68,7 +65,7 @@ class Interface(BaseInterface):
for temp_file in temp_path_list:
mask_file = os.path.basename(temp_file)
mask_name = os.path.splitext(mask_file)[0]
- masks[mask_name] = load(temp_file)
+ masks[mask_name] = qim3d.io.load(temp_file)
return masks
@@ -98,7 +95,7 @@ class Interface(BaseInterface):
def create_preview(self, img_editor: gr.ImageEditor) -> np.ndarray:
background = img_editor["background"]
masks = img_editor["layers"][0]
- overlay_image = overlay_rgb_images(background, masks)
+ overlay_image = qim3d.operations.overlay_rgb_images(background, masks)
return overlay_image
def cerate_download_list(self, img_editor: gr.ImageEditor) -> list[str]:
@@ -122,7 +119,7 @@ class Interface(BaseInterface):
filepath = os.path.join(self.temp_dir, filename)
files_list.append(filepath)
- save(filepath, mask, replace=True)
+ qim3d.io.save(filepath, mask, replace=True)
self.temp_files.append(filepath)
return files_list
diff --git a/qim3d/gui/iso3d.py b/qim3d/gui/iso3d.py
index c7d4620ff1ebdf0df84255cf9a733de047b54d9e..2725403f094dd58e89030f23dba06982551491f4 100644
--- a/qim3d/gui/iso3d.py
+++ b/qim3d/gui/iso3d.py
@@ -22,9 +22,8 @@ import numpy as np
import plotly.graph_objects as go
from scipy import ndimage
-from qim3d.io import load
+import qim3d
from qim3d.utils._logger import log
-
from qim3d.gui.interface import InterfaceWithExamples
@@ -46,7 +45,7 @@ class Interface(InterfaceWithExamples):
def load_data(self, gradiofile: gr.File):
try:
- self.vol = load(gradiofile.name)
+ self.vol = qim3d.io.load(gradiofile.name)
assert self.vol.ndim == 3
except AttributeError:
raise gr.Error("You have to select a file")
diff --git a/qim3d/gui/layers2d.py b/qim3d/gui/layers2d.py
index febd16a506bcba477eed1d0f42ba6e20b763d610..8b7ae4419f2fc388c8e020d2b39556c83d585ff4 100644
--- a/qim3d/gui/layers2d.py
+++ b/qim3d/gui/layers2d.py
@@ -21,7 +21,6 @@ import os
import gradio as gr
import numpy as np
-
from .interface import BaseInterface
# from qim3d.processing import layers2d as l2d
@@ -358,7 +357,7 @@ class Interface(BaseInterface):
raise gr.Error("Invalid file path")
try:
- self.data = load(
+ self.data = qim3d.io.load(
file_path,
progress_bar=False
)
@@ -403,7 +402,7 @@ class Interface(BaseInterface):
if self.is_transposed(slicing_axis, segmenting_axis):
slice = np.rot90(slice)
- self.__dict__[seg_key] = segment_layers(slice, inverted = inverted, n_layers = n_layers, delta = delta, min_margin = min_margin, wrap = wrap)
+ self.__dict__[seg_key] = qim3d.processing.segment_layers(slice, inverted = inverted, n_layers = n_layers, delta = delta, min_margin = min_margin, wrap = wrap)
return process
@@ -456,13 +455,13 @@ class Interface(BaseInterface):
seg = np.rot90(seg, k = 3)
# slice = 255 * (slice/np.max(slice))
# return image_with_overlay(np.repeat(slice[..., None], 3, -1), seg, alpha)
- return overlay_rgb_images(slice, seg, alpha)
+ return qim3d.operations.overlay_rgb_images(slice, seg, alpha)
else:
- lines = get_lines(seg)
+ lines = qim3d.processing.get_lines(seg)
if self.is_transposed(slicing_axis, segmenting_axis):
- return image_with_lines(np.rot90(slice), lines, line_thickness).rotate(270, expand = True)
+ return qim3d.viz.image_with_lines(np.rot90(slice), lines, line_thickness).rotate(270, expand = True)
else:
- return image_with_lines(slice, lines, line_thickness)
+ return qim3d.viz.image_with_lines(slice, lines, line_thickness)
return plot_output_img
diff --git a/qim3d/gui/local_thickness.py b/qim3d/gui/local_thickness.py
index 461f3e1774fedb3ac61e0f916b3c72bdafff6f92..4a4cbf474ae5283a73ed9305b9969e3dfd0b812b 100644
--- a/qim3d/gui/local_thickness.py
+++ b/qim3d/gui/local_thickness.py
@@ -40,12 +40,11 @@ import gradio as gr
import numpy as np
import tifffile
import localthickness as lt
+import qim3d
-from qim3d.io import load
-from qim3d.gui.interface import InterfaceWithExamples
-class Interface(InterfaceWithExamples):
+class Interface(qim3d.gui.interface.InterfaceWithExamples):
def __init__(self,
img: np.ndarray = None,
verbose:bool = False,
@@ -79,7 +78,7 @@ class Interface(InterfaceWithExamples):
file_idx = np.argmax(creation_time_list)
# Load the temporary file
- vol_lt = load(temp_path_list[file_idx])
+ vol_lt = qim3d.io.load(temp_path_list[file_idx])
return vol_lt
@@ -251,7 +250,7 @@ class Interface(InterfaceWithExamples):
def process_input(self, data: np.ndarray, dark_objects: bool):
# Load volume
try:
- self.vol = load(data.name)
+ self.vol = qim3d.io.load(data.name)
assert self.vol.ndim == 3
except AttributeError:
self.vol = data
diff --git a/qim3d/io/_convert.py b/qim3d/io/_convert.py
index 0d776822689430b733dfa1467ecdff0b48d87bb1..55ab80cb14218ccae8184b2a95488a0de8801431 100644
--- a/qim3d/io/_convert.py
+++ b/qim3d/io/_convert.py
@@ -10,7 +10,7 @@ from tqdm import tqdm
import zarr.core
from qim3d.utils._misc import stringify_path
-from qim3d.io._saving import save
+from qim3d.io import save
class Convert:
diff --git a/qim3d/io/_downloader.py b/qim3d/io/_downloader.py
index 18e36ca591ad2bf0859cc2b05f18d0033de3f8ee..c77d61ccb016e3745c7a15736a179699a2c6cf9a 100644
--- a/qim3d/io/_downloader.py
+++ b/qim3d/io/_downloader.py
@@ -8,7 +8,7 @@ from tqdm import tqdm
from pathlib import Path
from qim3d.io import load
-from qim3d.utils._logger import log
+from qim3d.utils import log
import outputformat as ouf
diff --git a/qim3d/io/_loading.py b/qim3d/io/_loading.py
index e3d7d45bc220a04c0e96e4efd5fbb2f94cc3c99a..b34ac1521daa4c3dee1fbd6f8efba0402ea62c38 100644
--- a/qim3d/io/_loading.py
+++ b/qim3d/io/_loading.py
@@ -23,9 +23,9 @@ from dask import delayed
from PIL import Image, UnidentifiedImageError
import qim3d
-from qim3d.utils._logger import log
+from qim3d.utils import log
from qim3d.utils._misc import get_file_size, sizeof, stringify_path
-from qim3d.utils._system import Memory
+from qim3d.utils import Memory
from qim3d.utils._progress_bar import FileLoadingProgressBar
import trimesh
@@ -718,7 +718,7 @@ class DataLoader:
# Fails
else:
# Find the closest matching path to warn the user
- similar_paths = qim3d.utils.misc.find_similar_paths(path)
+ similar_paths = qim3d.utils._misc.find_similar_paths(path)
if similar_paths:
suggestion = similar_paths[0] # Get the closest match
diff --git a/qim3d/io/_ome_zarr.py b/qim3d/io/_ome_zarr.py
index 36976316b8811380d68cbe1b7f5f43e5c001c4f9..6573831a1e29bbb02607fab777145f2838c8b6d0 100644
--- a/qim3d/io/_ome_zarr.py
+++ b/qim3d/io/_ome_zarr.py
@@ -31,7 +31,7 @@ from skimage.transform import (
resize,
)
-from qim3d.utils._logger import log
+from qim3d.utils import log
from qim3d.utils._progress_bar import OmeZarrExportProgressBar
from qim3d.utils._ome_zarr import get_n_chunks
diff --git a/qim3d/io/_saving.py b/qim3d/io/_saving.py
index a7053c00fde4b7d4541b1a01286f18ad669e811d..3ef6457f9ae26554cd810547b8a1911072492f7a 100644
--- a/qim3d/io/_saving.py
+++ b/qim3d/io/_saving.py
@@ -37,7 +37,7 @@ from pydicom.dataset import FileDataset, FileMetaDataset
from pydicom.uid import UID
import trimesh
-from qim3d.utils._logger import log
+from qim3d.utils import log
from qim3d.utils._misc import sizeof, stringify_path
diff --git a/qim3d/io/_sync.py b/qim3d/io/_sync.py
index 953bf15b2e5ad6690bd6a077cd29b7b430b22c40..48c17a8cb8d8fba2c3ededc93f252196087b6fc2 100644
--- a/qim3d/io/_sync.py
+++ b/qim3d/io/_sync.py
@@ -2,7 +2,7 @@
import os
import subprocess
import outputformat as ouf
-from qim3d.utils._logger import log
+from qim3d.utils import log
from pathlib import Path
diff --git a/qim3d/ml/_data.py b/qim3d/ml/_data.py
index d54f1bf6d7a457457b8fea638fd8057410d2a853..6050001eef37a7491ab7f2e6d88dec660bf38102 100644
--- a/qim3d/ml/_data.py
+++ b/qim3d/ml/_data.py
@@ -1,7 +1,7 @@
"""Provides a custom Dataset class for building a PyTorch dataset."""
from pathlib import Path
from PIL import Image
-from qim3d.utils._logger import log
+from qim3d.utils import log
import torch
import numpy as np
from typing import Optional, Callable
diff --git a/qim3d/ml/models/_unet.py b/qim3d/ml/models/_unet.py
index 27ee78a4009b235253662c8af50c76baca4870f4..a396d88d38a5ff9809f6e2a0bd1139df1f48eb40 100644
--- a/qim3d/ml/models/_unet.py
+++ b/qim3d/ml/models/_unet.py
@@ -2,7 +2,7 @@
import torch.nn as nn
-from qim3d.utils._logger import log
+from qim3d.utils import log
class UNet(nn.Module):
diff --git a/qim3d/operations/_common_operations_methods.py b/qim3d/operations/_common_operations_methods.py
index 5975c30ea3c43f95995559597c8a61f02790809a..26959254dfd8783f28ad560de6103e3c9f70ce7d 100644
--- a/qim3d/operations/_common_operations_methods.py
+++ b/qim3d/operations/_common_operations_methods.py
@@ -1,6 +1,6 @@
import numpy as np
import qim3d.filters as filters
-from qim3d.utils._logger import log
+from qim3d.utils import log
__all__ = ["remove_background", "fade_mask", "overlay_rgb_images"]
diff --git a/qim3d/processing/_local_thickness.py b/qim3d/processing/_local_thickness.py
index 947f8865cfdbdbed4438d0f1e416498502de0e4a..eb02bb3e04dee57c63a1dabb4a4a8dda4634e991 100644
--- a/qim3d/processing/_local_thickness.py
+++ b/qim3d/processing/_local_thickness.py
@@ -2,7 +2,7 @@
import numpy as np
from typing import Optional
-from qim3d.utils._logger import log
+from qim3d.utils import log
import qim3d
diff --git a/qim3d/processing/_structure_tensor.py b/qim3d/processing/_structure_tensor.py
index f6dc98cd253f05bd89c4a8a8c5cdf9a8fd228c2d..08a6f20ec1cf96c3432831e2914017c58b6cd777 100644
--- a/qim3d/processing/_structure_tensor.py
+++ b/qim3d/processing/_structure_tensor.py
@@ -3,7 +3,7 @@
from typing import Tuple
import logging
import numpy as np
-from qim3d.utils._logger import log
+from qim3d.utils import log
def structure_tensor(
@@ -108,7 +108,7 @@ def structure_tensor(
val, vec = st.eig_special_3d(s_vol, full=full)
if visualize:
- from qim3d.viz._structure_tensor import vectors
+ from qim3d.viz import vectors
display(vectors(vol, vec, **viz_kwargs))
diff --git a/qim3d/tests/processing/test_filters.py b/qim3d/tests/filters/test_filters.py
similarity index 70%
rename from qim3d/tests/processing/test_filters.py
rename to qim3d/tests/filters/test_filters.py
index 5a6d0993fb4ac6cecaf9c26d06b450eeb2a9f893..adbfd0130713b469c9a624a2be5ef72596d209dd 100644
--- a/qim3d/tests/processing/test_filters.py
+++ b/qim3d/tests/filters/test_filters.py
@@ -1,11 +1,10 @@
import qim3d
-from qim3d.filters import *
import numpy as np
import pytest
import re
def test_filter_base_initialization():
- filter_base = qim3d.processing.filters.FilterBase(3,size=2)
+ filter_base = qim3d.filters.FilterBase(3,size=2)
assert filter_base.args == (3,)
assert filter_base.kwargs == {'size': 2}
@@ -13,10 +12,10 @@ def test_gaussian_filter():
input_image = np.random.rand(50, 50)
# Testing the function
- filtered_image_fn = gaussian(input_image,sigma=1.5)
+ filtered_image_fn = qim3d.filters.gaussian(input_image,sigma=1.5)
# Testing the class method
- gaussian_filter_cls = Gaussian(sigma=1.5)
+ gaussian_filter_cls = qim3d.filters.Gaussian(sigma=1.5)
filtered_image_cls = gaussian_filter_cls(input_image)
# Assertions
@@ -28,10 +27,10 @@ def test_median_filter():
input_image = np.random.rand(50, 50)
# Testing the function
- filtered_image_fn = median(input_image, size=3)
+ filtered_image_fn = qim3d.filters.median(input_image, size=3)
# Testing the class method
- median_filter_cls = Median(size=3)
+ median_filter_cls = qim3d.filters.Median(size=3)
filtered_image_cls = median_filter_cls(input_image)
# Assertions
@@ -43,10 +42,10 @@ def test_maximum_filter():
input_image = np.random.rand(50, 50)
# Testing the function
- filtered_image_fn = maximum(input_image, size=3)
+ filtered_image_fn = qim3d.filters.maximum(input_image, size=3)
# Testing the class method
- maximum_filter_cls = Maximum(size=3)
+ maximum_filter_cls = qim3d.filters.Maximum(size=3)
filtered_image_cls = maximum_filter_cls(input_image)
# Assertions
@@ -58,10 +57,10 @@ def test_minimum_filter():
input_image = np.random.rand(50, 50)
# Testing the function
- filtered_image_fn = minimum(input_image, size=3)
+ filtered_image_fn = qim3d.filters.minimum(input_image, size=3)
# Testing the class method
- minimum_filter_cls = Minimum(size=3)
+ minimum_filter_cls = qim3d.filters.Minimum(size=3)
filtered_image_cls = minimum_filter_cls(input_image)
# Assertions
@@ -73,16 +72,16 @@ def test_sequential_filter_pipeline():
input_image = np.random.rand(50, 50)
# Individual filters
- gaussian_filter = Gaussian(sigma=1.5)
- median_filter = Median(size=3)
- maximum_filter = Maximum(size=3)
+ gaussian_filter = qim3d.filters.Gaussian(sigma=1.5)
+ median_filter = qim3d.filters.Median(size=3)
+ maximum_filter = qim3d.filters.Maximum(size=3)
# Testing the sequential pipeline
- sequential_pipeline = Pipeline(gaussian_filter, median_filter, maximum_filter)
+ sequential_pipeline = qim3d.filters.Pipeline(gaussian_filter, median_filter, maximum_filter)
filtered_image_pipeline = sequential_pipeline(input_image)
# Testing the equivalence to maximum(median(gaussian(input,**kwargs),**kwargs),**kwargs)
- expected_output = maximum(median(gaussian(input_image, sigma=1.5), size=3), size=3)
+ expected_output = qim3d.filters.maximum(qim3d.filters.median(qim3d.filters.gaussian(input_image, sigma=1.5), size=3), size=3)
# Assertions
assert filtered_image_pipeline.shape == expected_output.shape == input_image.shape
@@ -93,16 +92,16 @@ def test_sequential_filter_appending():
input_image = np.random.rand(50, 50)
# Individual filters
- gaussian_filter = Gaussian(sigma=1.5)
- median_filter = Median(size=3)
- maximum_filter = Maximum(size=3)
+ gaussian_filter = qim3d.filters.Gaussian(sigma=1.5)
+ median_filter = qim3d.filters.Median(size=3)
+ maximum_filter = qim3d.filters.Maximum(size=3)
# Sequential pipeline with filter initialized at the beginning
- sequential_pipeline_initial = Pipeline(gaussian_filter, median_filter, maximum_filter)
+ sequential_pipeline_initial = qim3d.filters.Pipeline(gaussian_filter, median_filter, maximum_filter)
filtered_image_initial = sequential_pipeline_initial(input_image)
# Sequential pipeline with filter appended
- sequential_pipeline_appended = Pipeline(gaussian_filter, median_filter)
+ sequential_pipeline_appended = qim3d.filters.Pipeline(gaussian_filter, median_filter)
sequential_pipeline_appended.append(maximum_filter)
filtered_image_appended = sequential_pipeline_appended(input_image)
@@ -113,7 +112,7 @@ def test_sequential_filter_appending():
def test_assertion_error_not_filterbase_subclass():
# Get valid filter classes
- valid_filters = [subclass.__name__ for subclass in qim3d.processing.filters.FilterBase.__subclasses__()]
+ valid_filters = [subclass.__name__ for subclass in qim3d.filters.FilterBase.__subclasses__()]
# Create invalid object
invalid_filter = object() # An object that is not an instance of FilterBase
@@ -124,4 +123,4 @@ def test_assertion_error_not_filterbase_subclass():
# Use pytest.raises to catch the AssertionError
with pytest.raises(AssertionError, match=re.escape(message)):
- sequential_pipeline = Pipeline(invalid_filter)
\ No newline at end of file
+ sequential_pipeline = qim3d.filters.Pipeline(invalid_filter)
\ No newline at end of file
diff --git a/qim3d/tests/io/test_downloader.py b/qim3d/tests/io/test_downloader.py
index 6fc0846405462a20bd19eb90160889ea573e1fbb..a6791aa0a60b0133824e62e68146f469a48f9c9c 100644
--- a/qim3d/tests/io/test_downloader.py
+++ b/qim3d/tests/io/test_downloader.py
@@ -1,40 +1,61 @@
import qim3d
import os
+import pytest
+from pathlib import Path
+import shutil
-def test_download():
- folder = 'Cowry_Shell'
- file = 'Cowry_DOWNSAMPLED.tif'
- path = os.path.join(folder,file)
+@pytest.fixture
+def setup_temp_folder():
+ """Fixture to create and clean up a temporary folder for tests."""
+ folder = "Cowry_Shell"
+ file = "Cowry_DOWNSAMPLED.tif"
+ path = Path(folder) / file
- dl = qim3d.io.Downloader()
+ # Ensure clean environment before running tests
+ if Path(folder).exists():
+ shutil.rmtree(folder)
+ yield folder, path
- dl.Cowry_Shell.Cowry_DOWNSAMPLED()
+ # Cleanup after tests
+ if path.exists():
+ path.unlink()
+ if Path(folder).exists():
+ shutil.rmtree(folder)
- img = qim3d.io.load(path)
+def test_download(setup_temp_folder):
+ folder, path = setup_temp_folder
- # Remove temp file
- os.remove(path)
- os.rmdir(folder)
+ dl = qim3d.io.Downloader()
+ dl.Cowry_Shell.Cowry_DOWNSAMPLED()
- assert img.shape == (500,350,350)
+ # Verify the file was downloaded correctly
+ assert path.exists(), f"{path} does not exist after download."
-def test_get_file_size_right():
- coal_file = 'https://archive.compute.dtu.dk/download/public/projects/viscomp_data_repository/Coal/CoalBrikett.tif'
- size = qim3d.io.downloader._get_file_size(coal_file)
+ img = qim3d.io.load(str(path))
+ assert img.shape == (500, 350, 350)
- assert size == 2_400_082_900
+ # Cleanup is handled by the fixture
-def test_get_file_size_wrong():
- file_to_folder = 'https://archive.compute.dtu.dk/files/public/projects/viscomp_data_repository/'
- size = qim3d.io.downloader._get_file_size(file_to_folder)
+def test_get_file_size():
+ """Tests for correct and incorrect file size retrieval."""
+ coal_file = "https://archive.compute.dtu.dk/download/public/projects/viscomp_data_repository/Coal/CoalBrikett.tif"
+ folder_url = "https://archive.compute.dtu.dk/files/public/projects/viscomp_data_repository/"
- assert size == -1
+ # Correct file size
+ size = qim3d.io._downloader._get_file_size(coal_file)
+ assert size == 2_400_082_900, f"Expected size mismatch for {coal_file}."
+
+ # Wrong URL (not a file)
+ size = qim3d.io._downloader._get_file_size(folder_url)
+ assert size == -1, "Expected size -1 for non-file URL."
def test_extract_html():
- url = 'https://archive.compute.dtu.dk/files/public/projects/viscomp_data_repository'
- html = qim3d.io.downloader._extract_html(url)
-
- assert 'data-path="/files/public/projects/viscomp_data_repository"' in html
+ url = "https://archive.compute.dtu.dk/files/public/projects/viscomp_data_repository"
+ html = qim3d.io._downloader._extract_html(url)
+
+ assert 'data-path="/files/public/projects/viscomp_data_repository"' in html, \
+ "Expected HTML content not found in extracted HTML."
+
diff --git a/qim3d/tests/models/test_unet.py b/qim3d/tests/ml/models/test_unet.py
similarity index 64%
rename from qim3d/tests/models/test_unet.py
rename to qim3d/tests/ml/models/test_unet.py
index 80b17605329af78f3b04cdcedd35de60608577f6..9f32bfce12be3a21238f2d2d388e59f873a8ef1c 100644
--- a/qim3d/tests/models/test_unet.py
+++ b/qim3d/tests/ml/models/test_unet.py
@@ -3,13 +3,13 @@ import torch
# unit tests for UNet()
def test_starting_unet():
- unet = qim3d.models.UNet()
+ unet = qim3d.ml.models.UNet()
assert unet.size == 'medium'
def test_forward_pass():
- unet = qim3d.models.UNet()
+ unet = qim3d.ml.models.UNet()
# Size: B x C x H x W
x = torch.ones([1,1,256,256])
@@ -19,14 +19,14 @@ def test_forward_pass():
# unit tests for Hyperparameters()
def test_hyper():
- unet = qim3d.models.UNet()
- hyperparams = qim3d.models.Hyperparameters(unet)
+ unet = qim3d.ml.models.UNet()
+ hyperparams = qim3d.ml.models.Hyperparameters(unet)
assert hyperparams.n_epochs == 10
def test_hyper_dict():
- unet = qim3d.models.UNet()
- hyperparams = qim3d.models.Hyperparameters(unet)
+ unet = qim3d.ml.models.UNet()
+ hyperparams = qim3d.ml.models.Hyperparameters(unet)
hyper_dict = hyperparams()
diff --git a/qim3d/tests/models/test_models.py b/qim3d/tests/ml/test_models.py
similarity index 62%
rename from qim3d/tests/models/test_models.py
rename to qim3d/tests/ml/test_models.py
index 83543b76299d400ac6c848fd6e6213a428e1bfd0..547310f303e5b78ca0036dd2be464673e0975384 100644
--- a/qim3d/tests/models/test_models.py
+++ b/qim3d/tests/ml/test_models.py
@@ -12,16 +12,16 @@ def test_model_summary():
folder = "folder_data"
temp_data(folder, img_shape=img_shape, n=n)
- unet = qim3d.models.UNet(size="small")
- augment = qim3d.models.Augmentation(transform_train=None)
- train_set, val_set, test_set = qim3d.models.prepare_datasets(
+ unet = qim3d.ml.models.UNet(size="small")
+ augment = qim3d.ml.Augmentation(transform_train=None)
+ train_set, val_set, test_set = qim3d.ml.prepare_datasets(
folder, 1 / 3, unet, augment
)
- _, val_loader, _ = qim3d.models.prepare_dataloaders(
+ _, val_loader, _ = qim3d.ml.prepare_dataloaders(
train_set, val_set, test_set, batch_size=1, num_workers=1, pin_memory=False
)
- summary = qim3d.models.model_summary(val_loader, unet)
+ summary = qim3d.ml.model_summary(val_loader, unet)
assert summary.input_size[0] == (1, 1) + img_shape
@@ -33,11 +33,11 @@ def test_inference():
folder = "folder_data"
temp_data(folder)
- unet = qim3d.models.UNet(size="small")
- augment = qim3d.models.Augmentation(transform_train=None)
- train_set, _, _ = qim3d.models.prepare_datasets(folder, 1 / 3, unet, augment)
+ unet = qim3d.ml.models.UNet(size="small")
+ augment = qim3d.ml.Augmentation(transform_train=None)
+ train_set, _, _ = qim3d.ml.prepare_datasets(folder, 1 / 3, unet, augment)
- _, targ, _ = qim3d.models.inference(train_set, unet)
+ _, targ, _ = qim3d.ml.inference(train_set, unet)
assert tuple(targ[0].unique()) == (0, 1)
@@ -49,11 +49,11 @@ def test_inference_tuple():
folder = "folder_data"
temp_data(folder)
- unet = qim3d.models.UNet(size="small")
+ unet = qim3d.ml.models.UNet(size="small")
data = [1, 2, 3]
with pytest.raises(ValueError, match="Data items must be tuples"):
- qim3d.models.inference(data, unet)
+ qim3d.ml.inference(data, unet)
temp_data(folder, remove=True)
@@ -63,11 +63,11 @@ def test_inference_tensor():
folder = "folder_data"
temp_data(folder)
- unet = qim3d.models.UNet(size="small")
+ unet = qim3d.ml.models.UNet(size="small")
data = [(1, 2)]
with pytest.raises(ValueError, match="Data items must consist of tensors"):
- qim3d.models.inference(data, unet)
+ qim3d.ml.inference(data, unet)
temp_data(folder, remove=True)
@@ -77,12 +77,12 @@ def test_inference_dim():
folder = "folder_data"
temp_data(folder)
- unet = qim3d.models.UNet(size="small")
+ unet = qim3d.ml.models.UNet(size="small")
data = [(ones(1), ones(1))]
# need the r"" for special characters
with pytest.raises(ValueError, match=r"Input image must be \(C,H,W\) format"):
- qim3d.models.inference(data, unet)
+ qim3d.ml.inference(data, unet)
temp_data(folder, remove=True)
@@ -94,17 +94,17 @@ def test_train_model():
n_epochs = 1
- unet = qim3d.models.UNet(size="small")
- augment = qim3d.models.Augmentation(transform_train=None)
- hyperparams = qim3d.models.Hyperparameters(unet, n_epochs=n_epochs)
- train_set, val_set, test_set = qim3d.models.prepare_datasets(
+ unet = qim3d.ml.models.UNet(size="small")
+ augment = qim3d.ml.Augmentation(transform_train=None)
+ hyperparams = qim3d.ml.Hyperparameters(unet, n_epochs=n_epochs)
+ train_set, val_set, test_set = qim3d.ml.prepare_datasets(
folder, 1 / 3, unet, augment
)
- train_loader, val_loader, _ = qim3d.models.prepare_dataloaders(
+ train_loader, val_loader, _ = qim3d.ml.prepare_dataloaders(
train_set, val_set, test_set, batch_size=1, num_workers=1, pin_memory=False
)
- train_loss, _ = qim3d.models.train_model(
+ train_loss, _ = qim3d.ml.train_model(
unet, hyperparams, train_loader, val_loader, plot=False, return_loss=True
)
diff --git a/qim3d/tests/processing/test_connected_components.py b/qim3d/tests/segmentation/test_connected_components.py
similarity index 100%
rename from qim3d/tests/processing/test_connected_components.py
rename to qim3d/tests/segmentation/test_connected_components.py
diff --git a/qim3d/tests/utils/test_augmentations.py b/qim3d/tests/utils/test_augmentations.py
index 289ebcb4a723c6ab9432ca375d51e4a4cd01479a..809e7ddbe2771519a5c71d4032edd7ebbd029d7f 100644
--- a/qim3d/tests/utils/test_augmentations.py
+++ b/qim3d/tests/utils/test_augmentations.py
@@ -5,13 +5,13 @@ import pytest
# unit tests for Augmentation()
def test_augmentation():
- augment_class = qim3d.models.Augmentation()
+ augment_class = qim3d.ml.Augmentation()
assert augment_class.resize == "crop"
def test_augment():
- augment_class = qim3d.models.Augmentation()
+ augment_class = qim3d.ml.Augmentation()
album_augment = augment_class.augment(256, 256)
@@ -26,11 +26,11 @@ def test_resize():
ValueError,
match=f"Invalid resize type: {resize_str}. Use either 'crop', 'resize' or 'padding'.",
):
- augment_class = qim3d.models.Augmentation(resize=resize_str)
+ augment_class = qim3d.ml.Augmentation(resize=resize_str)
def test_levels():
- augment_class = qim3d.models.Augmentation()
+ augment_class = qim3d.ml.Augmentation()
level = "Not a valid level"
diff --git a/qim3d/tests/utils/test_data.py b/qim3d/tests/utils/test_data.py
index 32b290a86b55a0c23a7d75d551559437b3df7b7e..81beef5334ddf4bbdd20de34b6d52f55a13f6307 100644
--- a/qim3d/tests/utils/test_data.py
+++ b/qim3d/tests/utils/test_data.py
@@ -10,7 +10,7 @@ def test_dataset():
folder = 'folder_data'
temp_data(folder, img_shape = img_shape)
- images = qim3d.models.Dataset(folder)
+ images = qim3d.ml.Dataset(folder)
assert images[0][0].shape == img_shape
@@ -19,19 +19,19 @@ def test_dataset():
# unit tests for check_resize()
def test_check_resize():
- h_adjust,w_adjust = qim3d.models.data.check_resize(240,240,resize = 'crop',n_channels = 6)
+ h_adjust,w_adjust = qim3d.ml._data.check_resize(240,240,resize = 'crop',n_channels = 6)
assert (h_adjust,w_adjust) == (192,192)
def test_check_resize_pad():
- h_adjust,w_adjust = qim3d.models.data.check_resize(16,16,resize = 'padding',n_channels = 6)
+ h_adjust,w_adjust = qim3d.ml._data.check_resize(16,16,resize = 'padding',n_channels = 6)
assert (h_adjust,w_adjust) == (64,64)
def test_check_resize_fail():
with pytest.raises(ValueError,match="The size of the image is too small compared to the depth of the UNet. Choose a different 'resize' and/or a smaller model."):
- h_adjust,w_adjust = qim3d.models.data.check_resize(16,16,resize = 'crop',n_channels = 6)
+ h_adjust,w_adjust = qim3d.ml._data.check_resize(16,16,resize = 'crop',n_channels = 6)
# unit tests for prepare_datasets()
@@ -42,9 +42,9 @@ def test_prepare_datasets():
folder = 'folder_data'
img = temp_data(folder,n = n)
- my_model = qim3d.models.UNet()
- my_augmentation = qim3d.models.Augmentation(transform_test='light')
- train_set, val_set, test_set = qim3d.models.prepare_datasets(folder,validation,my_model,my_augmentation)
+ my_model = qim3d.ml.models.UNet()
+ my_augmentation = qim3d.ml.Augmentation(transform_test='light')
+ train_set, val_set, test_set = qim3d.ml.prepare_datasets(folder,validation,my_model,my_augmentation)
assert (len(train_set),len(val_set),len(test_set)) == (int((1-validation)*n), int(n*validation), n)
@@ -56,7 +56,7 @@ def test_validation():
validation = 10
with pytest.raises(ValueError,match = "The validation fraction must be a float between 0 and 1."):
- augment_class = qim3d.models.prepare_datasets('folder',validation,'my_model','my_augmentation')
+ augment_class = qim3d.ml.prepare_datasets('folder',validation,'my_model','my_augmentation')
# unit test for prepare_dataloaders()
@@ -65,11 +65,11 @@ def test_prepare_dataloaders():
temp_data(folder)
batch_size = 1
- my_model = qim3d.models.UNet()
- my_augmentation = qim3d.models.Augmentation()
- train_set, val_set, test_set = qim3d.models.prepare_datasets(folder,1/3,my_model,my_augmentation)
+ my_model = qim3d.ml.models.UNet()
+ my_augmentation = qim3d.ml.Augmentation()
+ train_set, val_set, test_set = qim3d.ml.prepare_datasets(folder,1/3,my_model,my_augmentation)
- _,val_loader,_ = qim3d.models.prepare_dataloaders(train_set,val_set,test_set,
+ _,val_loader,_ = qim3d.ml.prepare_dataloaders(train_set,val_set,test_set,
batch_size,num_workers = 1,
pin_memory = False)
diff --git a/qim3d/tests/utils/test_doi.py b/qim3d/tests/utils/test_doi.py
index 0db54357db9366f416a1e72cbef0ef10c640dc0a..859ebdb92baefca4eba721b3ac71fb00e1d5dec6 100644
--- a/qim3d/tests/utils/test_doi.py
+++ b/qim3d/tests/utils/test_doi.py
@@ -4,12 +4,12 @@ doi = "https://doi.org/10.1007/s10851-021-01041-3"
def test_get_bibtex():
- bibtext = qim3d.utils.doi.get_bibtex(doi)
+ bibtext = qim3d.utils._doi.get_bibtex(doi)
assert "Measuring Shape Relations Using r-Parallel Sets" in bibtext
def test_get_reference():
- reference = qim3d.utils.doi.get_reference(doi)
+ reference = qim3d.utils._doi.get_reference(doi)
assert "Stephensen" in reference
diff --git a/qim3d/tests/utils/test_helpers.py b/qim3d/tests/utils/test_helpers.py
index 04ae8e63db39d1b47a9fe1f6ae24aecc29c29ac4..cdbbedc4589f9801077444605874916a8558f0c1 100644
--- a/qim3d/tests/utils/test_helpers.py
+++ b/qim3d/tests/utils/test_helpers.py
@@ -33,7 +33,7 @@ def test_get_local_ip():
else:
return False
- local_ip = qim3d.utils.misc.get_local_ip()
+ local_ip = qim3d.utils._misc.get_local_ip()
assert validate_ip(local_ip) == True
@@ -42,7 +42,7 @@ def test_stringify_path1():
"""Test that the function converts os.PathLike objects to strings"""
blobs_path = Path(qim3d.__file__).parents[0] / "img_examples" / "blobs_256x256.tif"
- assert str(blobs_path) == qim3d.utils.misc.stringify_path(blobs_path)
+ assert str(blobs_path) == qim3d.utils._misc.stringify_path(blobs_path)
def test_stringify_path2():
@@ -50,4 +50,4 @@ def test_stringify_path2():
# Create test_path
test_path = os.path.join("this", "path", "doesnt", "exist.tif")
- assert test_path == qim3d.utils.misc.stringify_path(test_path)
+ assert test_path == qim3d.utils._misc.stringify_path(test_path)
diff --git a/qim3d/tests/viz/test_img.py b/qim3d/tests/viz/test_img.py
index ec9599105a9cdccb3d44fdfa048f0a452cd47c8a..d33d00cc54e0d989cf870e474343e2787e069cfd 100644
--- a/qim3d/tests/viz/test_img.py
+++ b/qim3d/tests/viz/test_img.py
@@ -36,11 +36,11 @@ def test_grid_pred():
n = 4
temp_data(folder, n=n)
- model = qim3d.models.UNet()
- augmentation = qim3d.models.Augmentation()
- train_set, _, _ = qim3d.models.prepare_datasets(folder, 0.1, model, augmentation)
+ model = qim3d.ml.models.UNet()
+ augmentation = qim3d.ml.Augmentation()
+ train_set, _, _ = qim3d.ml.prepare_datasets(folder, 0.1, model, augmentation)
- in_targ_pred = qim3d.models.inference(train_set, model)
+ in_targ_pred = qim3d.ml.inference(train_set, model)
fig = qim3d.viz.grid_pred(in_targ_pred)
@@ -52,7 +52,7 @@ def test_grid_pred():
# unit tests for slices function
def test_slices_numpy_array_input():
example_volume = np.ones((10, 10, 10))
- fig = qim3d.viz.slices_grid(example_volume, n_slices=1)
+ fig = qim3d.viz.slices_grid(example_volume, num_slices=1)
assert isinstance(fig, plt.Figure)
@@ -77,7 +77,7 @@ def test_slices_wrong_position_format1():
ValueError,
match='Position not recognized. Choose an integer, list of integers or one of the following strings: "start", "mid" or "end".',
):
- qim3d.viz.slices_grid(example_volume, position="invalid_slice")
+ qim3d.viz.slices_grid(example_volume, slice_positions="invalid_slice")
def test_slices_wrong_position_format2():
@@ -86,7 +86,7 @@ def test_slices_wrong_position_format2():
ValueError,
match='Position not recognized. Choose an integer, list of integers or one of the following strings: "start", "mid" or "end".',
):
- qim3d.viz.slices_grid(example_volume, position=1.5)
+ qim3d.viz.slices_grid(example_volume, slice_positions=1.5)
def test_slices_wrong_position_format3():
@@ -95,16 +95,16 @@ def test_slices_wrong_position_format3():
ValueError,
match='Position not recognized. Choose an integer, list of integers or one of the following strings: "start", "mid" or "end".',
):
- qim3d.viz.slices_grid(example_volume, position=[1, 2, 3.5])
+ qim3d.viz.slices_grid(example_volume, slice_positions=[1, 2, 3.5])
def test_slices_invalid_axis_value():
example_volume = np.ones((10, 10, 10))
with pytest.raises(
ValueError,
- match="Invalid value for 'axis'. It should be an integer between 0 and 2",
+ match=f"Invalid value for 'slice_axis'. It should be an integer between 0 and {example_volume.ndim - 1}.",
):
- qim3d.viz.slices_grid(example_volume, axis=3)
+ qim3d.viz.slices_grid(example_volume, slice_axis=3)
def test_slices_interpolation_option():
@@ -113,8 +113,8 @@ def test_slices_interpolation_option():
interpolation_method = "bilinear"
fig = qim3d.viz.slices_grid(
example_volume,
- n_slices=1,
- img_width=img_width,
+ num_slices=1,
+ image_width=img_width,
interpolation=interpolation_method,
)
@@ -128,27 +128,27 @@ def test_slices_interpolation_option():
def test_slices_multiple_slices():
example_volume = np.ones((10, 10, 10))
- img_width = 3
- n_slices = 3
- fig = qim3d.viz.slices_grid(example_volume, n_slices=n_slices, img_width=img_width)
+ image_width = 3
+ num_slices = 3
+ fig = qim3d.viz.slices_grid(example_volume, num_slices=num_slices, image_width=image_width)
# Add assertions for the expected number of subplots in the figure
- assert len(fig.get_axes()) == n_slices
+ assert len(fig.get_axes()) == num_slices
def test_slices_axis_argument():
# Non-symmetric input
example_volume = np.arange(1000).reshape((10, 10, 10))
- img_width = 3
+ image_width = 3
# Call the function with different values of the axis
fig_axis_0 = qim3d.viz.slices_grid(
- example_volume, n_slices=1, img_width=img_width, axis=0
+ example_volume, num_slices=1, image_width=image_width, slice_axis=0
)
fig_axis_1 = qim3d.viz.slices_grid(
- example_volume, n_slices=1, img_width=img_width, axis=1
+ example_volume, num_slices=1, image_width=image_width, slice_axis=1
)
fig_axis_2 = qim3d.viz.slices_grid(
- example_volume, n_slices=1, img_width=img_width, axis=2
+ example_volume, num_slices=1, image_width=image_width, slice_axis=2
)
# Ensure that different axes result in different plots
@@ -216,7 +216,7 @@ def test_orthogonal_with_numpy_array():
# Create a sample NumPy array
vol = np.random.rand(10, 10, 10)
# Call the orthogonal function with the NumPy array
- orthogonal_obj = qim3d.viz.orthogonal(vol)
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(vol)
# Assert that the orthogonal object is created successfully
assert isinstance(orthogonal_obj, widgets.HBox)
@@ -225,28 +225,28 @@ def test_orthogonal_with_torch_tensor():
# Create a sample PyTorch tensor
vol = torch.rand(10, 10, 10)
# Call the orthogonal function with the PyTorch tensor
- orthogonal_obj = qim3d.viz.orthogonal(vol)
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(vol)
# Assert that the orthogonal object is created successfully
assert isinstance(orthogonal_obj, widgets.HBox)
def test_orthogonal_with_different_parameters():
# Test with different colormaps
- for cmap in ["viridis", "gray", "plasma"]:
- orthogonal_obj = qim3d.viz.orthogonal(np.random.rand(10, 10, 10), cmap=cmap)
+ for color_map in ["viridis", "gray", "plasma"]:
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(np.random.rand(10, 10, 10), color_map=color_map)
assert isinstance(orthogonal_obj, widgets.HBox)
# Test with different image sizes
- for img_height, img_width in [(2, 2), (4, 4)]:
- orthogonal_obj = qim3d.viz.orthogonal(
- np.random.rand(10, 10, 10), img_height=img_height, img_width=img_width
+ for image_height, image_width in [(2, 2), (4, 4)]:
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(
+ np.random.rand(10, 10, 10), image_height=image_height, image_width=image_width
)
assert isinstance(orthogonal_obj, widgets.HBox)
# Test with show_position set to True and False
- for show_position in [True, False]:
- orthogonal_obj = qim3d.viz.orthogonal(
- np.random.rand(10, 10, 10), show_position=show_position
+ for display_positions in [True, False]:
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(
+ np.random.rand(10, 10, 10), display_positions=display_positions
)
assert isinstance(orthogonal_obj, widgets.HBox)
@@ -255,7 +255,7 @@ def test_orthogonal_initial_slider_value():
# Create a sample NumPy array
vol = np.random.rand(10, 7, 19)
# Call the orthogonal function with the NumPy array
- orthogonal_obj = qim3d.viz.orthogonal(vol)
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(vol)
for idx, slicer in enumerate(orthogonal_obj.children):
assert slicer.children[0].value == vol.shape[idx] // 2
@@ -264,7 +264,7 @@ def test_orthogonal_slider_description():
# Create a sample NumPy array
vol = np.random.rand(10, 10, 10)
# Call the orthogonal function with the NumPy array
- orthogonal_obj = qim3d.viz.orthogonal(vol)
+ orthogonal_obj = qim3d.viz.slicer_orthogonal(vol)
for idx, slicer in enumerate(orthogonal_obj.children):
assert slicer.children[0].description == ["Z", "Y", "X"][idx]
diff --git a/qim3d/utils/__init__.py b/qim3d/utils/__init__.py
index 0c7d5b30a7b3daf15b80d5995e6d0e4a1f18e5cc..fab0c339cfa63a4fd86f5420cc0f90e4a2738597 100644
--- a/qim3d/utils/__init__.py
+++ b/qim3d/utils/__init__.py
@@ -1,6 +1,8 @@
from . import _doi
from ._system import Memory
+from ._logger import log
+
from ._misc import (
get_local_ip,
port_from_str,
@@ -13,4 +15,4 @@ from ._misc import (
scale_to_float16,
)
-from ._server import start_http_server
\ No newline at end of file
+from ._server import start_http_server
diff --git a/qim3d/utils/_misc.py b/qim3d/utils/_misc.py
index 3d8660b445a65577ef3b4c7d16af613b44785aac..090672d2fc5370d16bd56c28c384b9efb4c528e7 100644
--- a/qim3d/utils/_misc.py
+++ b/qim3d/utils/_misc.py
@@ -153,7 +153,7 @@ def get_file_size(file_path: str) -> int:
try:
file_size = os.path.getsize(file_path)
except FileNotFoundError:
- similar_paths = qim3d.utils.misc.find_similar_paths(file_path)
+ similar_paths = qim3d.utils._misc.find_similar_paths(file_path)
if similar_paths:
suggestion = similar_paths[0] # Get the closest match