« Changelog History


adaptive v0.7.3 Release Notes

Release Date: 2019-01-29 // over 5 years ago

  • Full Changelog

    Implemented enhancements:

    • ➕ Add a sequential executor #138
    • ➕ Add tests for 1D interpolator learner #136
    • ➕ Add integration learner #135
    • 👉 Make the runner work with asyncio and inside Jupyter notebooks #133
    • ➕ Add module for notebook integration and shortcuts for common executors #132
    • ➕ Add homogeneous sampling learner #131
    • ➕ Add a "balancing" learner #130
    • Implement 2D and 3D learners #129
    • ➕ Add a 0D averaging learner #128
    • Write interpolate for the 1D learner such that it is more efficient #126
    • Gracefully handle exceptions when evaluating the function to be learned #125
    • 👍 Allow BalancingLearner to return arbitrary number of points from 'choose_points' #124
    • 0️⃣ Increase the default refresh rate for 'live_plot' #120
    • ✂ remove default number of points to choose in choose\_points #118
    • Consider using Gaussian process optimization as a learner #115
    • 👉 Make distributed.Client work with automatic scaling of the cluster #104
    • 👌 Improve plotting for learners #83
    • 🔨 (refactor) learner.tell(x, None) might be renamed to learner.tell_pending(x) #73
    • (feature) make interactive plots for learnerND plot_slice method #64
    • 0️⃣ (LearnerND) make default loss function better #63
    • 👍 allow for N-d output #60
    • ➕ add cross-section plot #58
    • (BalancingLearner) make new balancinglearner that looks at the total loss rather than loss improvement #36
    • (LearnerND) allow any convex hull as domain #25
    • (Learner1D) add possibility to use the direct neighbors in the loss #20

    🛠 Fixed bugs:

    • Distinguish actual loss and estimated loss #139
    • Set the bounds in a smarter way #127
    • some points get cluttered #86
    • 2D learner specifies a 1D point causing 2D learner to fail #81
    • Method 'Learner.tell' is ambiguous #80
    • Learner1D fails with extremely narrow features #78
    • AverageLearner math domain error #77
    • (LearnerND) scale y-values #61
    • Learner1D breaks if right bound is added before the left bound #45
    • Learner1D's bound check algo in self.ask doesn't take self.data or self.pending_points #44
    • Learner1D fails when function returns a list instead of a numpy.array #43
    • Learner1D fails when a point (x, None) is added when x already exists #42
    • Learner1D.ask breaks when adding points in some order #41
    • Learner1D doesn't correctly set the interpolated loss when a point is added #40
    • Learner1D could in some situations return -inf as loss improvement, which would make balancinglearner never choose to improve #35
    • ✅ LearnerND fails for BalancingLearner test #34
    • Learner2D suggests same point twice #30
    • (LearnerND) if you stop the runner, and then try to continue, it fails. #23

    Closed issues:

    • ➕ Add Authors file and review license #137
    • 👉 make the runner request points until it's using all cores #123
    • Remove _choose_points #121
    • 🛠 Fix extremely long kernel restart times #119
    • live plotting: add a universal visual cue that the goal is achieved. #117
    • ipyparallel shouldn't be a dependency #114
    • adaptive fails to discover features #113
    • ➕ add tests for 2D learner #111
    • DataSaver doesn't work with the BalancingLearner #110
    • ✂ deleted issue #108
    • removing optional dependencies #106
    • 👌 Improve ipython event loop integration #105
    • 🚀 Use holoviews.TriMesh when it makes it to a release #103
    • 💾 save live plots into internal datastructure #101
    • To-dos before making the repo public #100
    • set the correct loss_improvement for the AverageLearner #95
    • Ensure a minimum resolution #92
    • 🔄 change the error message in runner #91
    • 🏁 The ProcessPoolExecutor doesn't work on Windows #90
    • 1D and 2D learner: stop interpolating function instead of the loss #87
    • Discontinuities in zero should be detected and be approximated with some margin #85
    • (minor bug) learner.choose_points gives wrong number of points in one very particular case #84
    • 2D: if boundary point fails it will never be re-evaluated ... #82
    • Learner2D + BalancingLearner too slow to use on many cores #79
    • BalancingLearner.from_product doesn't work with the DataSaver #74
    • 🚧 Follow-up from "WIP: Add LearnerND that does not interpolate the values of pending points" #70
    • (triangulation) make method for finding initial simplex part of the triangulation class #68
    • 🔨 (refactor) LearnerND._ask can be refactored to be so much more readable #67
    • 👍 (LearnerND) make choose point in simplex better #62
    • 👉 Make learnerND datastructures immutable where possible #54
    • 📇 Rename LearnerND to TriangulatingLearner #51
    • tell_many method #49
    • 📚 Set up documentation #48
    • 🗄 DeprecationWarning: sorted_dict.iloc is deprecated. Use SortedDict.keys() instead. #47
    • The example given in data_saver.py doesn't compile. #46
    • What should learners do when fed the same point twice #39
    • How should learners handle data that is outside of the domain #38
    • ✅ No tests for the 'BalancingLearner' #37
    • 🚀 release 0.6.0 #33
    • 👉 Make BaseRunner an abstract base class #32
    • (BalancingLearner) loss is cached incorrectly #31
    • LearnerND triangulation incomplete #29
    • (LearnerND) flat simplices are sometimes added on the surface of the triangulation #28
    • (LearnerND) add iso-surface plot feature #27
    • 👉 make BalancingLearner work with the live_plot #26
    • test_balancing_learner[Learner2D-ring_of_fire-learner_kwargs2] fails sometimes #24
    • widgets don't show up on adaptive.readthedocs.io #21
    • How to handle NaN? #18
    • ✂ Remove public 'fname' learner attribute #17
    • 🚀 Release v0.7.0 #14
    • (Learner1D) improve time complexity #13
    • 📚 Typo in documentation foradaptive.learner.learner2D.uniform\_loss\(ip\) #12
    • (LearnerND) fix plotting of scaled domains #11
    • suggested points lie outside of domain #7
    • DEVELOPMENT IS ON GITLAB: https://gitlab.kwant-project.org/qt/adaptive #5

    🔀 Merged pull requests: