Change versions. Prepare for .rc.2

.github/workflows/build-upload.yml

@@ -27,8 +27,8 @@ jobs:
     - name: Build DECODE
       run: |
         cd ./conda
-        $CONDA/bin/conda-build -c turagalab -c turagalab/label/dev -c pytorch -c conda-forge decode
-        $CONDA/bin/conda-build -c turagalab -c turagalab/label/dev -c pytorch -c conda-forge decode --output > $FILENAMES
+        $CONDA/bin/conda-build -c turagalab -c turagalab/label/rc -c turagalab/label/dev -c pytorch -c conda-forge decode
+        $CONDA/bin/conda-build -c turagalab -c turagalab/label/rc -c turagalab/label/dev -c pytorch -c conda-forge decode --output > $FILENAMES
 
     - name: Change anaconda label on release
       if: github.event.release
@@ -83,4 +83,3 @@ jobs:
         asset_path: ./dist/${{ steps.pip-build.outputs.wheel_filename }}
         asset_name: ${{ steps.pip-build.outputs.wheel_filename }}
         asset_content_type: binary/octet-stream
-

README.md

@@ -11,8 +11,10 @@ DECODE works by training a DEep COntext DEpendent (DECODE) neural network to det
 
 The easiest way to try out the algorithm is to have a look at the Google Colab Notebooks we provide for training our algorithm and fitting experimental data. For installation instructions and further information please **refer to our** [**docs**](https://decode.readthedocs.io).
 You can find these here:
-- DECODE Training [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/18V1TLLu63CXSWihwoGX7ZQ5wj0Qk7GnD?usp=sharing)
-- DECODE Fitting [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1O0mjuOjaOl0wnLZ11Xo92IsWrgqtXL17?usp=sharing)
+- DECODE Training (**NEW: v0.10rc**) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]()
+- DECODE Training (v0.9) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/18V1TLLu63CXSWihwoGX7ZQ5wj0Qk7GnD?usp=sharing)
+- DECODE Fitting (**NEW: v0.10rc**) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)]()
+- DECODE Fitting (v0.9) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1O0mjuOjaOl0wnLZ11Xo92IsWrgqtXL17?usp=sharing)
 - [Documentation](https://decode.readthedocs.io)
 
 

conda/decode/meta.yaml

@@ -1,6 +1,6 @@
 package:
   name: decode
-  version: "0.10.0.rc.1"  # do not modify by hand set and sync with bumpversion
+  version: "0.10.0.rc.1"  # do not modify by hand; set and sync with bumpversion
 
 source:
      - path: ../..
@@ -36,7 +36,7 @@ requirements:
     - seaborn=0.10
     - scikit-image
     - scikit-learn
-    - spline>=0.10.0.alpha.2
+    - spline>=0.10.0.rc.2
     - tensorboard
     - tifffile>=2021.1
     - tqdm
@@ -50,10 +50,5 @@ requirements:
 
 about:
     home: https://github.com/turagaLab/decode
-    # dev_url: github url
-    # doc_url: doc url
-    # license: GPL-3.0
-    # license_family: GPL
-    # license_file: {{ SRC_DIR }}/LICENSE
     summary: "High-Density 3D Single-Molecule Localisation Microscopy using Convolutional Neural Networks."
     description: "Installation must add the respective channels for the dependencies (i.e. PyTorch and the spline package): ```conda install decode -c turagalab -c pytorch -c conda-forge```"

environment.yaml

@@ -1,8 +1,9 @@
-name: decode_dev
+name: decode_dev_src
 
 channels:
-  - turagalab/label/dev
   - turagalab
+  - turagalab/label/rc
+  - turagalab/label/dev
   - pytorch
   - conda-forge
   - defaults
@@ -39,7 +40,7 @@ dependencies:
   - seaborn=0.10
   - scikit-image
   - scikit-learn
-  - spline>=0.10.0.alpha.2
+  - spline>=0.10.0.rc.2
   - tensorboard
   - tifffile>=2020.2
   - tqdm

gateway.yaml

@@ -56,6 +56,6 @@ examples:
 
 wheels:
   decode: https://github.com/TuragaLab/DECODE/releases/download/v0.9.3/decode-0.9.3-py3-none-any.whl
-  decode_rc: https://github.com/TuragaLab/DECODE/releases/download/v0.10.0.rc.1/decode-0.10.0rc1-py3-none-any.whl
+  decode_rc: https://github.com/TuragaLab/DECODE/releases/download/v0.10.0.rc.2/decode-0.10.0rc2-py3-none-any.whl
   spline_py37: https://github.com/TuragaLab/SplinePSF/releases/download/v0.9/spline-0.9-cp37-cp37m-linux_x86_64.whl
-  spline_py37_rc: https://github.com/TuragaLab/SplinePSF/releases/download/v0.10.0.alpha.2/spline-0.10.0a2-cp37-cp37m-linux_x86_64.whl
+  spline_py37_rc: https://github.com/TuragaLab/SplinePSF/releases/download/v0.10.0.rc.2/spline-0.10.0rc2-cp37-cp37m-linux_x86_64.whl

setup.py

@@ -16,9 +16,9 @@
     # pip needs requirements here; keep in sync with meta.yaml!
     requirements = [
         "numpy",
-        # HACK: We omit torch version to be as flexible to the torchversion
+        # HACK: We omit torch version to be as flexible to the version
         # as we can so that slight changes on colab do not break so fast
-        # that's why we deviate from requirements.txt
+        # that's why we deviate from enviornment.yaml
         "torch",
         "click",
         "deprecated",