{"push_id":1220480999,"size":3,"distinct_size":3,"ref":"refs/heads/dev","head":"49af8506f5854cf10ec8ce35b4863ec8394d7b5c","before":"0c27468e0c2e101627d59e29685efdae21096c34","commits":[{"sha":"8bc63a37cb8ad0410f0c837a9cedd99070c37f95","author":{"name":"Douglas Moore","email":"0e6c114040083df2acecd1d1b8ed9deb9026210c@dglmoore.com"},"message":"Ensure that arrays are in C-contiguous form\n\nSometimes NumPy arrays change memory layout when they are\nmanipulated, e.g. when they are transposed. This can result in\ninsidious bugs when you pass those arrays to C functions. To\nensure this does not happen, we force the arrays into a\nC-contiguous format before we start to operate on them. This\nalso ensures that we don't have to call `ravel` to bring them\ndown to 1D.","distinct":true,"url":"https://api.github.com/repos/dglmoore/PyInform/commits/8bc63a37cb8ad0410f0c837a9cedd99070c37f95"},{"sha":"a11402b17d8d63bf95449398817ecd4ab9ac681f","author":{"name":"Douglas Moore","email":"0e6c114040083df2acecd1d1b8ed9deb9026210c@dglmoore.com"},"message":"Construct output arrays in the correct shape\n\nRather than constructing the arrays in 1D and then reshaping, just\ncreate them in the correct shape to begin with. They are built in\nC-contiguous order by default, so there is no issue.","distinct":true,"url":"https://api.github.com/repos/dglmoore/PyInform/commits/a11402b17d8d63bf95449398817ecd4ab9ac681f"},{"sha":"49af8506f5854cf10ec8ce35b4863ec8394d7b5c","author":{"name":"Douglas Moore","email":"0e6c114040083df2acecd1d1b8ed9deb9026210c@dglmoore.com"},"message":"Prefer size to len for NumPy arrays\n\nMost of the time, when we are passing arrays to C functions, we\ndon't care about the length of the array (number of rows) we\ncare about the size (total number of elements). This is now\nexplicit, even when the two agree (e.g. 1D arrays).","distinct":true,"url":"https://api.github.com/repos/dglmoore/PyInform/commits/49af8506f5854cf10ec8ce35b4863ec8394d7b5c"}]}
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