Deliverables for March 13

[toekneesunshine]

Committed

status	deliverable	notes
:thumbsup:	[For Thursday, show Greg the tensor image for a downsampled full brain] https://github.com/NeuroDataDesign/seelviz/blob/gh-pages/Albert_Jupyter/new/Full%2BBrain%2BHighest%2BResolution%20(1).ipynb https://github.com/NeuroDataDesign/seelviz/blob/gh-pages/Albert_Jupyter/new/Full%2BBrain%2BHighest%2BResolution.ipynb https://github.com/NeuroDataDesign/seelviz/blob/gh-pages/Albert_Jupyter/new/Full%2BBrain%2BLess%2BDownsampled.ipynb https://github.com/NeuroDataDesign/seelviz/blob/gh-pages/Albert_Jupyter/new/Full%2BBrain.ipynb	@alee156 @lukezhu1
:thumbsup:	For Monday try to generate tensors using both probabilistic and deterministic methods. Likely will fail so try to get as far as possible and document why it fails and where it fails. https://github.com/NeuroDataDesign/seelviz/blob/gh-pages/Jupyter/fibers.ipynb	@alee156 @lukezhu1
:thumbsup:	For Thursday, investigate why there are discrepancies between MATLAB generated "line" array and Python "line" array. We discovered that it was due to three separate problems. First, we improperly convolved at one step (grr was set to gcc). Second, we switched back from FFTconvolve to regular convolve. Lastly, we removed unnecessary transposes. Results and benchmarks are attached here.	@toekneesunshine @jonl1096
👍	Committed: For Monday, configure Python code to work properly for TIFF stacks. Benchmark results run on TIFFs.	@toekneesunshine @jonl1096
In progress	Reach: Begin implementing code into pipeline.	@toekneesunshine @jonl1096

Note: Probabilistic modeling does not work due to needing a gtable, white matter, and seed mask necessary to work. We also had a lot of trouble running VTK