Documentation - Githubissues

In the process of rewriting documentation, consider the previous list of edits:

General

[ ] Add a link to project/tool site for each tool mentioned on http://m2g.io/tutorials/available_data.html
[ ] For running reliability, http://m2g.io/tutorials/validation.html#computing-reliability-on-your-data is great - we want to be a little more clear about what each of the things is in the {}. Can we clarify, maybe using one of the nightly build data sets?
[ ] On http://m2g.io/tutorials/sample_data.html, put the two line code snippets with how to do frob norm and edge counts
[ ] Clarify runtime for graphs on validation page as through small graphs. Perhaps give at least limited (approximate) timing for big graphs (run time, not wall time)
[ ] We ran a third dataset, right? The MRN data? We should say this on the validation page, even though there was no TRT (just explain)
[ ] Add data derivatives to nightly run for each data set, not just KKI
[x] Rename data on data public to m2g_v1_1_2 consistent with pull request
[x] Tag release of 1_1_2.
[ ] Add an adjacency matrix (PNG) of at least one of the sample results, and give single line code used to generate (For running reliability, http://m2g.io/tutorials/validation.html#computing-reliability-on-your-data)
[ ] Explain why we ran multiple atlases on validation page and what that means (2-3 sentences).
[ ] Add lessons learned from running pipeline under FAQ page - places where people might get stuck (e.g., running big graphs, setting memory allocations)
[ ] How much RAM/cores are needed for a single subject? Either put in validation or setup. Maybe one number for small directions and one for large.
[ ] Capture all covariate information in one place for now until we have a lims option
[ ] Add additional reliability info somewhere (links or in page) for datasets in addition to MNR score. We produce other really interesting/helpful debug information
[ ] Document what information is produced by reliability function - sphinx-ing it might be the way to go (couldn't find it if it exists)
[ ] Put LONI 6.0.1 versions for all platforms somewhere private
[ ] Make it slightly easier with instructions to mount a drive on EC2. FAQs?
[ ] Explain how to open screenshare on a mac. FAQs?
[ ] Add recommended EC2 instance size (name) - let's provide a simple recommendation and also a note on cost ($0.XX/hour).
High Level
[ ] Sample data should be used consistently for all examples
[ ] Parallel explanations and formats across headings and pages
[ ] Code block and ipython notebook to reproduce reliability numbers
[ ] Line up all m2g architecture and figures with new python classes: data wrangling, registration, diffusion (processing), graph generation, (utilities)
Cleanup
[ ] ITK-SNAP should be styled that way (vs. itk-snap or similar)
[ ] On overview page, add explicitly what the m2g pipeline produces in terms of output (high level graphs (adjacency matrices), showing ...
[ ] Move data formats and access to Data formats page, and link to that in public data
[ ] Provide link to each of the software tools we recommend. Does MIPAV do the same things as mricron?
[ ] Link to spec for fiber dat file
[ ] Link to something explaining graphml
[ ] Explain the details (each file/folder) of the sample data
[ ] Preprocessing -> wrangling throughout
[ ] webservice -> webservices
[ ] Need parallel structure in data formats page (explain outputs in more detail, for example)
[ ] Commit demo workflow to repo rather than making a separate download, and tell people where this is
NeuroData
[ ] Rename to developer guide
[ ] Add information indicating: where master setup script is (i.e., embedded in rst file), quarterly release schedule, how people can contribute
Validation
[ ] Add picture for reliability
[ ] Add and explain outputs from reliability for each validation run
[ ] Link validation to v1.1.2 release
[ ] SWU4 - analysis of removed subjects
[ ] validation -> point explicitly to small graphs that are produced
Sample Data
[ ] Provide ipython notebook to reproduce table.
[ ] This page should be called system test - break out sample data
[ ] Add expected same scan/same subject difference between example outputs and test run(for deterministic runs = 0)
[ ] Add binary edge counts
[ ] Add picture of sample adjacency matrix - point people to graph explorer
Install Instructions
[ ] rename page to install instructions for m2g
[ ] add ami link explicitly and prominently (how do i use should be more prominent than setup)
[ ] revise and rerelease AMI
[ ] grab camino release - we should be pulling a particular release, not master. Make sure we grab the one that was used for the validation
[ ] igraph - get specific release and get rid of gist stuff (pipe single command to file or similar
[ ] m2g - get tagged version
[ ] separate loni stuff into separate block
[ ] we should grab setup data vs. all of kki
[ ] echo "export m2g=/mrimages" <-- need trailing quote
[ ] take out words like install, configure, update, setup, except the h1 heading at top
Basic Usage
[ ] Rename to Pipeline Overview
[ ] m2g Diffusion processing pipeline figure (crop so that spacing is good)
[ ] fix parallelism in each paragraph - choose either pseudocode or preferably description of what's going on
[ ] Add a single line explaining docs.scripts.m2g() namespace
[ ] Explain exported outputs so that pin count lines up (one line explanation is all we need)
[ ] Note that this is a LONI implementation of our pipeline
Advanced Usage
[ ] m2g_home is already set in data path block and doesn't need to be reset
[ ] rename as bash implementation/walkthrough
[ ] remove timing and ram estimates
[ ] explain that setup is required, except for LONI block
[ ] When you reference CLI, briefly explain what that is (same as GUI, but will run workflow from command line
[ ] Running test workflow on the sample data (link to system test)

neurodata / m2g

Documentation #45

General

High Level

Cleanup

NeuroData

Validation

Sample Data

Install Instructions

Basic Usage

Advanced Usage