April 27th, 2023 –- 11AM - 12PM PST
https://scientific-python.org/summits/sparse/meeting2/
juanitagomezr2112@gmail.com
jim22k@gmail.com
dschult@colgate.edu
einstein.edison@gmail.com (Hameer Abbasi)
nabdennur@gmail.com
adam.li@columbia.edu
perimosocordiae@gmail.com (CJ)
erik.n.welch@gmail.com
Julien Jerphanion git@jjerphan.xyz
Julien Jerphanion
Ross Barnowski
Dan Schult
CJ Carey
https://sparse.pydata.org/en/stable/
https://github.com/hameerabbasi/xsparse
https://github.com/Quansight-Labs/ndindex
https://github.com/scipy/scipy/pull/16108
https://github.com/scipy/scipy/pull/16033
https://github.com/scipy/scipy/pull/16033#issuecomment-1120091359
A tool that understands the structure of code, and can make modifications. You can then ask to upgrade from scipy 0.x to scipy 0.y, and it would make some of the changes for you so you are not faced with deprecation warnings.
Example in NetworkX:
https://github.com/networkx/networkx/pull/5139
Some potential tools:
https://github.com/ssbr/refex
https://github.com/python-rope/rope
https://github.com/charliermarsh/ruff
tl;dr Current problems with matrices:
Scipy sparse matrices convertion to dense array return numpy matrices
silently wrong answers with scipy matrices are a reason for removing this semantic
CJ Carey: not keen to vendoring numpy matrix within scipy, having a separate package for numpy matrice
Have sparse matrices by small wrappers over sparse arrays and then migrate
No sparse 1D array for now.