.github/workflows/run-tests.yml

@@ -8,14 +8,14 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.7, 3.8, 3.9]
         include:
-          - python-version: 3.6
-            tox-env: py36
           - python-version: 3.7
             tox-env: py37
           - python-version: 3.8
             tox-env: py38
+          - python-version: 3.9
+            tox-env: py39
     steps:
       - name: checkout latest commit
         uses: actions/checkout@v2

README.md

@@ -80,12 +80,17 @@ $ atldld info version --help
 $ atldld info cache
 ```
 
-One can also obtain dataset and dataset information through the CLI.
+One can also get dataset information through the CLI.
 ```bash
 $ atldld dataset info $DATASET_ID
 $ atldld dataset preview $DATASET_ID
-$ atldld dataset download $DATASET_ID
 ```
+
+To download a dataset use the `atldld download` command.
+```shell
+$ atldld download dataset $DATASET_ID
+```
+
 For further information please refer to the help part of the corresponding
 command.
 
@@ -125,4 +130,4 @@ matrix_3d = get_3d(dataset_id=DATASET_ID)
 
 The development of this software was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.
 
-Copyright (c) 2021 Blue Brain Project/EPFL
+Copyright (c) 2021-2022 Blue Brain Project/EPFL

setup.py

@@ -21,14 +21,11 @@
 install_requires = [
     "Pillow",
     "appdirs",
-    "click",
+    "click>=8",
     "dataclasses; python_version < '3.7'",
     "matplotlib",
     "numpy",
-    "opencv-python",
-    "pandas",
     "requests",
-    "responses",
     "scikit-image",
 ]
 extras_require = {
@@ -48,6 +45,12 @@
     "docs": ["sphinx>=1.3", "sphinx-bluebrain-theme"],
 }
 
+try:
+    # Could already be installed on the system
+    import cv2  # noqa
+except ImportError:
+    install_requires.append("opencv-python")
+
 description = "Search, download, and prepare atlas data."
 long_description = """
 Among different sources of data, Allen Brain Institute

src/atldld/cli/dataset.py

@@ -15,7 +15,6 @@
 # You should have received a copy of the GNU Lesser General Public License
 # along with this program.  If not, see <https://www.gnu.org/licenses/>.
 """Implementation of the "atldld dataset" subcommand."""
-import pathlib
 from typing import Any, Dict, Optional, Sequence
 
 import click
@@ -111,114 +110,6 @@ def dataset_info(dataset_id):
     click.secho(textwrap.dedent(output).strip(), fg="green")
 
 
-@dataset_cmd.command(
-    "download", help="Download and synchronize an entire section dataset"
-)
-@click.argument("dataset_id", type=str)
-@click.argument(
-    "output_folder",
-    type=click.Path(exists=False, dir_okay=True, path_type=pathlib.Path),
-)
-@click.option(
-    "--downsample-ref",
-    type=int,
-    default=25,
-    show_default=True,
-    help="Downsampling coefficient for the reference space. Determines the size "
-    "of the synchronized image.",
-)
-@click.option(
-    "--downsample-img",
-    type=int,
-    default=0,
-    show_default=True,
-    help="Downsampling coefficient for the image download.",
-)
-@click.option(
-    "-e",
-    "--include-expression",
-    is_flag=True,
-    help="Include expression image.",
-)
-def dataset_download(
-    dataset_id,
-    output_folder,
-    downsample_ref,
-    downsample_img,
-    include_expression,
-):
-    """Download and synchronize an entire section dataset."""
-    import json
-    import textwrap
-
-    from PIL import Image
-
-    from atldld.sync import DatasetDownloader, DatasetNotFoundError
-
-    # Prepare paths
-    if not output_folder.exists():
-        output_folder.mkdir(parents=True)
-    metadata_path = output_folder / "metadata.json"
-
-    downloader = DatasetDownloader(
-        dataset_id,
-        downsample_ref=downsample_ref,
-        downsample_img=downsample_img,
-        include_expression=include_expression,
-    )
-    cli_input = f"""
-    Dataset ID               : {dataset_id}
-    Downsample reference     : {downsample_ref}
-    Downsample image         : {downsample_img}
-    Include expression       : {include_expression}
-    Output folder            : {output_folder}
-    """
-    click.secho(textwrap.dedent(cli_input).strip(), fg="blue")
-
-    try:
-        downloader.fetch_metadata()
-    except DatasetNotFoundError as exc:
-        raise click.ClickException(str(exc))
-    n_images = len(downloader)
-
-    additional_info = f"""
-    Number of section images : {n_images}
-    Section thickness        : {downloader.metadata["dataset"]["section_thickness"]}µm
-    Plane of section         : {downloader.metadata["dataset"]["plane_of_section_id"]}
-    """
-    click.secho(textwrap.dedent(additional_info).strip(), fg="green")
-
-    metadata = {
-        "dataset_id": dataset_id,
-        "downsample_ref": downsample_ref,
-        "downsample_img": downsample_img,
-        "plane_of_section": downloader.metadata["dataset"]["plane_of_section_id"],
-        "section_thickness": downloader.metadata["dataset"]["section_thickness"],
-        "per_image": {},
-    }
-
-    with click.progressbar(downloader.run(), length=n_images) as progress:
-        for image_id, section_coordinate, img, img_expr, df in progress:
-            img_synced = df.warp(img, c=img[0, 0].tolist())
-
-            img_path = output_folder / f"{image_id}.png"
-            Image.fromarray(img_synced, mode="RGB").save(img_path)
-
-            if img_expr is not None:
-                img_expr_synced = df.warp(img_expr)
-                img_expr_path = output_folder / f"{image_id}_expr.png"
-                Image.fromarray(img_expr_synced, mode="RGB").save(img_expr_path)
-
-            metadata["per_image"][image_id] = {
-                "section_coordinate": section_coordinate,
-                "section_coordinate_scaled": section_coordinate
-                / metadata["section_thickness"],
-            }
-
-    with metadata_path.open("w") as f:
-        json.dump(metadata, f, indent=4)
-
-
 @dataset_cmd.command("preview", help="Plot a preview of dataset slices")
 @click.argument("dataset_id", type=int)
 @click.option(