Merge branch 'doc/update_install_info' into 'master'

DOC: Update documentation for new release process.

Closes #21

See merge request fsl/fsl_mrs!39

.gitlab-ci.yml

@@ -83,7 +83,7 @@ pytest:
   - source ~/.bashrc 
   - conda create -n fsl_mrs -y python=3.7
   - conda activate fsl_mrs
-  - conda install -y -c conda-forge -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/channel/ --file requirements.txt
+  - conda install -y -c conda-forge -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public/ --file requirements.txt
   - conda install -y -c conda-forge pytest
   - pip install .
   script:

CHANGELOG.rst

@@ -13,6 +13,8 @@ This document contains the FSL-MRS release history in reverse chronological orde
 - Allow tissue fractions with larger errors, but normalise. Error thrown if sum < 0.9.
 - Specialist phase & frequency alignment via dynamic fitting added.
 - Added fsl_mrs_preproc_edit as a script for preprocessing edited data.
+- Updated documentation with new install instructions.
+- Updated interactive fitting documentation
 
 1.1.8 (Tuesday 5th October 2021)
 --------------------------------

README.md

@@ -21,7 +21,7 @@ Then activate the environment:
 Finally install FSL-MRS and its dependencies from the FSL conda channel.
 
     conda install -c conda-forge -c defaults \
-                  -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/channel/ \
+                  -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public/ \
                   fsl_mrs
 
 ### Source code

docs/user_docs/fitting.rst

@@ -17,7 +17,7 @@ A basic call to :code:`fsl_mrs`, the SVS wrapper script, is as follows:
             --basis my_basis_spectra \
             --output example_fit
 
-This will run nonlinear optimisation using the Truncated Newton algorithm, as implemented in Scipy, and will produce a simple PNG file summarising the fit, and several CSV files containing concentrations, uncertainties, and QC parameters for further analysis. 
+This will run non-linear optimisation using the Truncated Newton algorithm, as implemented in Scipy, and will produce a simple PNG file summarising the fit, and several CSV files containing concentrations, uncertainties, and QC parameters for further analysis. 
 
 A more complete call to :code:`fsl_mrs` may be as follows.
 
@@ -67,31 +67,31 @@ Output
 Results from :code:`fsl_mrsi` are stored in a single folder containing the following output:
 
 - An interactive HTML report showing the fit to the average FID across all voxels in the mask.
-- NIFTI files summarising parameters, concentrations, and QC measures (one such file per metabolite)
-- Model prediction in the time domain (NIFTI)
-- Residuals (NIFTI)
-- Fitted Baseline (NIFTI)
+- NIfTI files summarising parameters, concentrations, and QC measures (one such file per metabolite)
+- Model prediction in the time domain (NIfTI)
+- Residuals (NIfTI)
+- Fitted Baseline (NIfTI)
 
-The above NIFTI output can all be visualied in FSLeyes alongside the original data.
+The above NIfTI output can all be visualised in FSLeyes alongside the original data.
 
 Python & Interactive Interface
 ------------------------------
 
 FSL-MRS can also be used in an interactive Python environment. The following is an example fitting and visualisation of data that has already been processed (e.g. with :code:`fsl_mrs_proc`). 
 
-In an IPython or Jupyter Notebook environment, run the follwing (the example data resides in the main :code:`fsl_mrs` package folder):
+In an IPython or Jupyter Notebook environment, run the following (the example data resides in the main :code:`fsl_mrs` package folder):
 
 Loading and preparing the data:
 
 ::
 
-    from fsl_mrs import MRS
+    from fsl_mrs.utils import mrs_io
 
     FID_file     = 'example_usage/example_data/metab.nii'
     basis_folder = 'example_usage/example_data/steam_11ms'    
 
-    mrs = MRS()
-    mrs.from_files(FID_file,basis_folder)
+    data = mrs_io.read_FID(FID_file)
+    mrs = data.mrs(basis_file=basis_folder)
     mrs.processForFitting()
 
 Fitting the model to the data:

docs/user_docs/install.rst

@@ -24,7 +24,7 @@ The primary installation method is via *conda*. After installing conda and creat
 ::
 
     conda install -c conda-forge -c defaults \
-                  -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/channel/ \
+                  -c https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public/ \
                   fsl_mrs
 
 Example data with conda

release_instructions.md

@@ -9,14 +9,19 @@ Instructions for releasing a new version of FSL-MRS
 5. Check all tests pass.
 6. Merge to fsl/fsl_mrs:master.
 7. Repeat with other features.
+
+Each time the fsl/fsl_mrs master branch is updated and the CI pipeline is run, the `trigger-staging-package` job triggers a pipeline on the conda recipe repository to build a package from the current state of master. This can be turned into a development release by running the `deploy-conda-package` on the latest job of `fsl/conda/fsl_mrs`. This will be published to the same channel and have a format `<last_tag>.YYMMDD`.
+
 8. For new version create new tag -tag name should be "x.x.x" with the message "Vx.x.x". New changelog contents are copied into release notes.
-9. This will trigger doc build (published [here](https://open.win.ox.ac.uk/pages/fsl/fsl_mrs/)) and package build (currently broken).
-10. Update local master.  
+9. This will trigger doc build (published [here](https://open.win.ox.ac.uk/pages/fsl/fsl_mrs/)) and package build.
+10. Trigger the package build by accepting the relevant merge request on [fsl/conda/fsl_mrs](https://git.fmrib.ox.ac.uk/fsl/conda/fsl_mrs) branch. This will trigger a pipeline from which the conda package be released. Do this by manually triggering the `deploy-conda-package` job after the build has run.
+11. New packages will be published to the [FSL conda channel](https://fsl.fmrib.ox.ac.uk/fsldownloads/fslconda/public/).
+12. To request a version to be included in the next FSL release manually trigger the `update-fsl-manifest` job. This opens a MR for the development team on the [manifest repository](https://git.fmrib.ox.ac.uk/fsl/conda/manifest/).
+
+13. Optionally update local and fork master.  
     ```git fetch upstream --tags```  
     ```git checkout master```  
     ```git merge upstream/master```  
     ```git push origin --tags```
-11. Trigger manual package build using the [fsl/conda/fsl-mrs:pre-conda](https://git.fmrib.ox.ac.uk/fsl/conda/fsl-mrs:pre-conda) branch. Do this by updating the version number [here](https://git.fmrib.ox.ac.uk/fsl/conda/fsl-mrs/-/blob/mnt/pre-conda/meta.yaml#L6). This will trigger a pipeline from which the conda package can be downloaded (*Download build-noarch-conda-package:archive artifact*).
-12. Send to MW for manual upload to the FSL conda channel.
 
 For local development installation run: ```pip install --no-deps -e .```
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