Post Hackathon Minor Edits

[wrgr]

Part 1

• [ ] 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).

  Part 2

  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)

  Doc 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 page

• [ ] 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)

[gkiar]

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