{"push_id":2480715312,"size":3,"distinct_size":3,"ref":"refs/heads/feature-terms","head":"b5820c02db014f6d428d4f8c4fb81ed9743569b8","before":"1533f82f6793a738dd6f6c0d70eab2ac03d4cee5","commits":[{"sha":"953d45c29fecd8bc43c39184f279aa08de0c115d","author":{"name":"Erik Nielsen","email":"8322194e3d7b3cfcca1cac1e457c23c75bafd2c7@sandia.gov"},"message":"Continues WIP adding term-based calcs.  Can do simple (&slow) GST now.\n\nGateTermCalc and TermEvalTree have been fleshed out enough to function\nin running simple GST using LindbladTermGate objects.  There's still\na lot of unnecessary slow stuff - the bottleneck currently is the\npr_as_poly calls, which are called more often than they need to\nbe.  But simple 1Q GST runs and jacobian computation has been\nchecked against dense matrix methods to verify everything looks\ncorrect -- just slow (100x or so slower than mx methods for 1Q).\n\nNote that this commit removes the num_variables member from\nPolynomial.","distinct":true,"url":"https://api.github.com/repos/pyGSTio/pyGSTi/commits/953d45c29fecd8bc43c39184f279aa08de0c115d"},{"sha":"ebe220d4cd6c374f8531a4745d7ca624e5df9fc2","author":{"name":"Erik Nielsen","email":"8322194e3d7b3cfcca1cac1e457c23c75bafd2c7@sandia.gov"},"message":"Adds more evaltree_cache plumbing, reducing calls to pr_as_poly.\n\nBy allowing more core, logl, and chi2 routines to take an already-\nbuilt evaluation tree via the evaltree_cache argument, the *same*\nevaltree can be used throughout a do_long_sequence_gst calls, which\nsignificantly speeds up the term-based calc b/c the tree holds\ncached \"raw\" polyomials created via the slow pr_as_poly routine.","distinct":true,"url":"https://api.github.com/repos/pyGSTio/pyGSTi/commits/ebe220d4cd6c374f8531a4745d7ca624e5df9fc2"},{"sha":"b5820c02db014f6d428d4f8c4fb81ed9743569b8","author":{"name":"Erik Nielsen","email":"8322194e3d7b3cfcca1cac1e457c23c75bafd2c7@sandia.gov"},"message":"Adds some gate-term-calc optimizations.\n\nAfter some profiling, these changes were made to speed up pr_as_poly\ncalculation (but they're still much slower than dense mx methods\nfor 1Q).","distinct":true,"url":"https://api.github.com/repos/pyGSTio/pyGSTi/commits/b5820c02db014f6d428d4f8c4fb81ed9743569b8"}]}
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