auto publish to pypi on tagged commit

.github/workflows/test_and_deploy.yml

@@ -0,0 +1,63 @@
+name: tests
+
+on:
+  push:
+    branches:
+      - "main"
+    tags:
+      - "v**"
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  linting:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: neuroinformatics-unit/actions/lint@v2
+
+  manifest:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: neuroinformatics-unit/actions/check_manifest@v2
+
+  test:
+    needs: [linting, manifest]
+    name: ${{ matrix.os }} py${{ matrix.python-version }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest]
+        python-version: ["3.11", "3.12", "3.13"]
+        include:
+          - os: macos-latest
+            python-version: "3.11"
+          - os: windows-latest
+            python-version: "3.11"
+
+    steps:
+      - uses: neuroinformatics-unit/actions/test@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+          secret-codecov-token: ${{ secrets.CODECOV_TOKEN }}
+
+  build_sdist_wheels:
+    name: Build source distribution and wheel
+    needs: [test]
+    if: github.event_name == 'push' && github.ref_type == 'tag'
+    runs-on: ubuntu-latest
+    steps:
+      - uses: neuroinformatics-unit/actions/build_sdist_wheels@v2
+
+  upload_all:
+    name: Publish build distributions
+    needs: [build_sdist_wheels]
+    if: github.event_name == 'push' && github.ref_type == 'tag'
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/download-artifact@v4
+        with:
+          name: artifact
+          path: dist
+      - uses: pypa/gh-action-pypi-publish@release/v1

.gitignore

@@ -6,7 +6,7 @@ demo_data
 create_transformation_for_ages/deformations_from_elastix
 create_transformation_for_ages/
 .vscode/
-
+testing.py
 # Byte-compiled / optimized / DLL files
 __pycache__/
 brainglobe_ccf_translator/__pycache__/
@@ -168,4 +168,4 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+#.idea/

.pre-commit-config.yaml

@@ -1,5 +1,3 @@
-
-
 # Configuring https://pre-commit.ci/
 ci:
     autoupdate_schedule: monthly
@@ -30,12 +28,14 @@ repos:
           - id: mypy
             additional_dependencies:
                 - types-setuptools
+                - types-requests
+            exclude: ^utilities/
     - repo: https://github.com/mgedmin/check-manifest
       rev: "0.50"
       hooks:
           - id: check-manifest
             args: [--no-build-isolation]
-            additional_dependencies: [setuptools-scm]
+            additional_dependencies: [setuptools-scm, wheel]
     - repo: https://github.com/codespell-project/codespell
       # Configuration for codespell is in pyproject.toml
       rev: v2.3.0

PyPiDeploy.md

@@ -1,8 +1,19 @@
-to deploy the package to PyPi
+# Deploying to PyPI
 
+## Automatic Deployment (Recommended)
+
+The package is automatically published to PyPI when you push a version tag:
+
+1. Update your version as needed
+2. Create and push a tag: `git tag v0.1.0 && git push --tags`
+3. The GitHub Action will run tests, build, and upload to PyPI
+
+**Note:** You need to add a `TWINE_API_KEY` secret to your repository with your PyPI API token.
+
+## Manual Deployment
 
 ```bash
-pip install build twine 
+pip install build twine
 python -m build
 twine upload dist/*
-```
+```

README.md

@@ -1,13 +1,13 @@
 # brainglobe-ccf-translator
 ![PyPI - Version](https://img.shields.io/pypi/v/brainglobe-ccf-translator)
 
-CCF translator (brainglobe-ccf-translator) is a tool for translating between common coordinate frameworks using deformation matrices. 
-A longstanding problem in NeuroInformatics has been the inability to easily translate data between common coordinate frameworks. CCF translator aims to solve this. By connecting each new space to an existing one, we can construct a graph of deformations. This means that data can be translated as long as there is a route from one space to another, even if that route passes through multiple other spaces. Now, when new templates for new modalities, strains, or ages are released, users will not be subdivided into unrelated spaces. As long as they are connected to a space which exists in our network, they will be fully connected to all other spaces.  
+CCF translator (brainglobe-ccf-translator) is a tool for translating between common coordinate frameworks using deformation matrices.
+A longstanding problem in NeuroInformatics has been the inability to easily translate data between common coordinate frameworks. CCF translator aims to solve this. By connecting each new space to an existing one, we can construct a graph of deformations. This means that data can be translated as long as there is a route from one space to another, even if that route passes through multiple other spaces. Now, when new templates for new modalities, strains, or ages are released, users will not be subdivided into unrelated spaces. As long as they are connected to a space which exists in our network, they will be fully connected to all other spaces.
 
-CCF translator can also interpolate between spaces and create a new intermediate space. This is primarily useful for development, where, for instance, the midpoint between day 5 and day 7 can be taken and used as a postnatal day 6 reference. It could also be useful for making references of disease progression.  
-
-![a graph of all the available spaces and how they are connected. the spaces are nodes with the space name written on top of them, the edges show which spaces are connected to which other spaces.]
+CCF translator can also interpolate between spaces and create a new intermediate space. This is primarily useful for development, where, for instance, the midpoint between day 5 and day 7 can be taken and used as a postnatal day 6 reference. It could also be useful for making references of disease progression.
 
+**Diagram:**
+a graph of all the available spaces and how they are connected. the spaces are nodes with the space name written on top of them, the edges show which spaces are connected to which other spaces.
 ```mermaid
 graph TD
     allen_mouse_P56 --- demba_dev_mouse_P56
@@ -19,34 +19,45 @@ graph TD
     demba_dev_mouse_P21 --- demba_dev_mouse_P28
     demba_dev_mouse_P28 --- demba_dev_mouse_P56
     demba_dev_mouse_P4 --- demba_dev_mouse_P7
+    dorr_mouse_mri_P84 --- perens_stereotaxic_mri_mouse_P56
 ```
 
-
 ## Use Cases
 One way you can use CCF translator is to view data from one space, in another space. For instance the allen connectivity dataset shows projections from viral tracing studies in the adult brain. We can take any of these projection datasets and view them in the developing brain, for instance post natal day 9.
 ![an image which shows a viral tracing study overlaid on the allen adult ccfv3 template. it shows that same viral tracing data transformed and overlaid on a post natal day 9 template. between the two images is an arrow pointing from the adult to the post natal day 9 brain, above which is text saying CCF translator, implying that CCF translator was used to transform the data from adult to post natal day 9.](https://raw.githubusercontent.com/brainglobe/brainglobe-ccf-translator/main/media/allen_connectivity_transform.png)
 ## Installation
-CCF translator can be installed by running 
+CCF translator can be installed by running
 ```
 pip install brainglobe-ccf-translator
 ```
-Or by cloning this repository and running 
+Or by cloning this repository and running
 ```
 pip install -e .
 ```
 while in the root of the repository.
 ## Currently supported spaces
-the name in CCF translator usually copies the name of the atlas in the brainglobe atlasapi. 
+the name in CCF translator usually copies the name of the atlas in the brainglobe atlasapi.
 | Framework Name | name in api | supported age range
-| -------------- | ----------- | ----------- 
+| -------------- | ----------- | -----------
 | Allen mouse CCFv3 | allen_mouse | 56
 | Demba developmental mouse | demba_dev_mouse| 4-56
 | Gubra lightsheet mouse | perens_multimodal_lsfm| 56
 | Gubra MRI mouse | perens_stereotaxic_mri_mouse| 56
 | Princeton lightsheet mouse | princeton_mouse| 56
+| Dorr MRI mouse | dorr_mouse_mri | 84
+
+
+We also support brainglobe atlas api names which are in existing coordinate frameworks. For instance you can specify osten_mouse and CCF translator will autoconvert this to allen_mouse.
+| atlas api name | converts to  | supported age range
+| -------------- | ----------- | -----------
+| osten_mouse | allen_mouse | 56
+| allen_mouse_bluebrain_barrels | allen_mouse| 56
+| kim_mouse | allen_mouse | 56
+| demba_allen_seg_dev_mouse | demba_dev_mouse | 4-56
+
 ## Usage
 **Transforming points**
-To take a coordinate in one volume and find the equivalent coordinate in a second volume is quite simple in CCF translator. 
+To take a coordinate in one volume and find the equivalent coordinate in a second volume is quite simple in CCF translator.
 ```python
 import numpy as np
 import brainglobe_ccf_translator
@@ -61,13 +72,13 @@ print(f"new points are {pset.values}")
 new points are [[267 250 286] [452 247 414]]
  ```
 **Transforming volumes**
-All of our transforms assume you retrieved the atlas from the brianglobe-atlasapi. 
+All of our transforms assume you retrieved the atlas from the brianglobe-atlasapi.
 To run the volume examples you will want to install brainglobe-atlasapi using the following
 ```
 pip install brainglobe-atlasapi
 ```
 
-Transforming a volume is equally simple, here we get the volume from the brainglobe api, but you can load it however you like. In the Demba space the valid ages are from 4 to 56, and all of these are valid targets for transformation. 
+Transforming a volume is equally simple, here we get the volume from the brainglobe api, but you can load it however you like. In the Demba space the valid ages are from 4 to 56, and all of these are valid targets for transformation.
 ```python
 from brainglobe_atlasapi.bg_atlas import BrainGlobeAtlas
 import brainglobe_ccf_translator
@@ -91,7 +102,7 @@ ccft_vol.transform(target_age, 'demba_dev_mouse')
 ccft_vol.save(rf"demo_data/P{target_age}_template_{voxel_size_micron}um.nii.gz")
 ```
 ## Contributing
-If you would like to add a new space or connect an existing one, please create a deformation matrix and/or describe the required reorientation, flipping, cropping, and padding of the axis between this space and one that already exists in the network, and then open an issue in this repository.  Ideally, choose a space which covers all the areas which are covered in your space. While the Allen CCFv3 is very popular, it is missing the anterior olfactory bulb and the caudal portion of the cerebellum and brain stem, so it is not the optimal choice. 
+If you would like to add a new space or connect an existing one, please create a deformation matrix and/or describe the required reorientation, flipping, cropping, and padding of the axis between this space and one that already exists in the network, and then open an issue in this repository.  Ideally, choose a space which covers all the areas which are covered in your space. While the Allen CCFv3 is very popular, it is missing the anterior olfactory bulb and the caudal portion of the cerebellum and brain stem, so it is not the optimal choice.
 
 ## Citation
 CCF translator was first described in [DeMBA: a developmental atlas for navigating the mouse brain in space and time](https://www.biorxiv.org/content/10.1101/2024.06.14.598876v1). If you use CCF translator, please cite that paper.

brainglobe_ccf_translator/PointSet.py

@@ -1,16 +1,18 @@
-from .deformation import apply_deformation, route_calculation
-import pandas as pd
 import os
+
 import numpy as np
+import pandas as pd
+
 from . import config
+from .deformation import apply_deformation, route_calculation
+from .space_utils import validate_space_name
 
 base_path = os.path.dirname(__file__)
 
 
 class PointSet:
     def __init__(self, values, space, voxel_size_micron, age_PND):
         self.values = np.array(values).astype(float)
-        self.space = space
         self.voxel_size_micron = voxel_size_micron
         self.age_PND = age_PND
         # Setup brainglobe dir
@@ -22,17 +24,21 @@ def __init__(self, values, space, voxel_size_micron, age_PND):
         try:
             metadata = pd.read_csv(metadata_path)
         except FileNotFoundError:
-            raise FileNotFoundError(f"Metadata file not found at {metadata_path}")
+            raise FileNotFoundError(
+                f"Metadata file not found at {metadata_path}"
+            )
         except pd.errors.ParserError:
             raise ValueError(f"Error parsing metadata file at {metadata_path}")
 
         self.metadata = metadata
+        self.space = validate_space_name(space, self.metadata)
 
     def transform(self, target_age=None, target_space=None):
         values = self.values
         if len(values.shape) == 1:
             values = values.reshape(1, -1)
         source = f"{self.space}_P{self.age_PND}"
+        target_space = validate_space_name(target_space, self.metadata)
         target = f"{target_space}_P{target_age}"
         row_template = "{}_physical_size_micron"
         source = f"{self.space}_P{self.age_PND}"
@@ -41,7 +47,10 @@ def transform(self, target_age=None, target_space=None):
         route = route_calculation.calculate_route(target, source, G)
         deform_arr, pad_sum, flip_sum, dim_order_sum, final_voxel_size = (
             apply_deformation.combine_route(
-                route, self.voxel_size_micron, self.deformation_dir, self.metadata
+                route,
+                self.voxel_size_micron,
+                self.deformation_dir,
+                self.metadata,
             )
         )
         previous = "_".join(route[1].split("_")[:-1])

brainglobe_ccf_translator/Volume.py

@@ -1,13 +1,3 @@
-import numpy as np
-from .deformation import apply_deformation, route_calculation
-from . import config
-import pandas as pd
-import json
-import os
-import nibabel as nib
-from typing import Any
-
-
 """
 At present the order of transformations is:
 transpose
@@ -18,6 +8,17 @@
 So the transform should be in the shape of the output
 """
 
+import os
+from typing import Any
+
+import nibabel as nib
+import numpy as np
+import pandas as pd
+
+from . import config
+from .deformation import apply_deformation, route_calculation
+from .space_utils import validate_space_name
+
 
 class Volume:
     def __init__(
@@ -39,7 +40,6 @@ def __init__(
         segmentation_file (bool): Flag indicating if a segmentation file is used.
         """
         self.values = values
-        self.space = space
         self.voxel_size_micron = voxel_size_micron
         self.age_PND = age_PND
         self.segmentation_file = segmentation_file
@@ -53,15 +53,19 @@ def __init__(
         try:
             metadata = pd.read_csv(metadata_path)
         except FileNotFoundError:
-            raise FileNotFoundError(f"Metadata file not found at {metadata_path}")
+            raise FileNotFoundError(
+                f"Metadata file not found at {metadata_path}"
+            )
         except pd.errors.ParserError:
             raise ValueError(f"Error parsing metadata file at {metadata_path}")
 
         self.metadata = metadata
+        self.space = validate_space_name(space, self.metadata)
 
     def transform(self, target_age, target_space):
         array = self.values
         source = f"{self.space}_P{self.age_PND}"
+        target_space = validate_space_name(target_space, self.metadata)
         target = f"{target_space}_P{target_age}"
         if source == target:
             print("volume is already in that space")
@@ -70,28 +74,32 @@ def transform(self, target_age, target_space):
         route = route_calculation.calculate_route(source, target, G)
         deform_arr, pad_sum, flip_sum, dim_order_sum, final_voxel_size = (
             apply_deformation.combine_route(
-                route, self.voxel_size_micron, self.deformation_dir, self.metadata
+                route,
+                self.voxel_size_micron,
+                self.deformation_dir,
+                self.metadata,
             )
         )
         array = np.transpose(array, dim_order_sum)
         for i in range(len(flip_sum)):
             if flip_sum[i]:
                 array = np.flip(array, axis=i)
         if deform_arr is not None:
-
             # original_input_shape = np.array([456.0, 668.0, 320.0])
             if final_voxel_size != self.voxel_size_micron:
                 original_input_shape = np.shape(array)
-                original_input_shape = np.array(original_input_shape)[dim_order_sum]
-                new_input_shape = np.array(array.shape) * (
-                    final_voxel_size / self.voxel_size_micron
-                )
+                original_input_shape = np.array(original_input_shape)[
+                    dim_order_sum
+                ]
+
                 deform_arr = apply_deformation.resize_transform(
                     deform_arr,
                     (1, *([final_voxel_size / self.voxel_size_micron] * 3)),
                 )
             order = 0 if self.segmentation_file else 1
-            array = apply_deformation.apply_transform(array, deform_arr, order=order)
+            array = apply_deformation.apply_transform(
+                array, deform_arr, order=order
+            )
         else:
             array = apply_deformation.pad_neg(array, pad_sum, mode="constant")
         self.values = array