{ "__type": "IngestedDoc", "__tag": 4010, "_content": {}, "_ordered_sections": [], "item_file": null, "item_line": null, "item_type": null, "aliases": [], "example_section_data": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "see_also": [], "signature": null, "references": null, "qa": "release:1.11.0-notes", "arbitrary": [ { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "This release supports Python 2.6 - 2.7 and 3.2 - 3.5 and contains a number of enhancements and improvements. Note also the build system changes listed below as they may have subtle effects." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "No Windows (TM) binaries are provided for this release due to a broken toolchain. 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However, the resulting datetime is timezone naive " } ] }, { "__type": "Code", "__tag": 4050, "value": ">>> np.datetime64('2000-01-01T00:00:00-08')\nDeprecationWarning: parsing timezone aware datetimes is deprecated;\nthis will raise an error in the future\nnumpy.datetime64('2000-01-01T08:00:00')", "execution_status": null }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "As a corollary to this change, we no longer prohibit casting between datetimes with date units and datetimes with time units. With timezone naive datetimes, the rule for casting from dates to times is no longer ambiguous." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "datetime64 changes" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The return type of the " }, { "__type": "InlineCode", "__tag": 4051, "value": "linalg.norm" }, { "__type": "Text", "__tag": 4046, "value": " function is now floating point without exception. Some of the norm types previously returned integers." } ] } ], "title": [ { "__type": "InlineCode", "__tag": 4051, "value": "linalg.norm" }, { "__type": "Text", "__tag": 4046, "value": " return type changes" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The various fit functions in the numpy polynomial package no longer accept non-integers for degree specification." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "polynomial fit changes" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "This behaviour mimics that of other functions such as " }, { "__type": "InlineCode", "__tag": 4051, "value": "np.inner" }, { "__type": "Text", "__tag": 4046, "value": ". 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Now, " }, { "__type": "InlineCode", "__tag": 4051, "value": "np.dot" }, { "__type": "Text", "__tag": 4046, "value": " will now always raise a " }, { "__type": "InlineCode", "__tag": 4051, "value": "TypeError" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ], "title": [ { "__type": "Emphasis", "__tag": 4047, "children": [ { "__type": "Text", "__tag": 4046, "value": "np.dot" } ] }, { "__type": "Text", "__tag": 4046, "value": " now raises " }, { "__type": "InlineCode", "__tag": 4051, "value": "TypeError" }, { "__type": "Text", "__tag": 4046, "value": " instead of " }, { "__type": "InlineCode", "__tag": 4051, "value": "ValueError" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "BulletList", "__tag": 4053, "ordered": false, "start": 1, "children": [ { "__type": "ListItem", "__tag": 4054, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "In " }, { "__type": "InlineCode", "__tag": 4051, "value": "np.lib.split" }, { "__type": "Text", "__tag": 4046, "value": " an empty array in the result always had dimension " }, { "__type": "InlineCode", "__tag": 4051, "value": "(0,)" }, { "__type": "Text", "__tag": 4046, "value": " no matter the dimensions of the array being split. This has been changed so that the dimensions will be preserved. A " }, { "__type": "InlineCode", "__tag": 4051, "value": "FutureWarning" }, { "__type": "Text", "__tag": 4046, "value": " for this change has been in place since Numpy 1.9 but, due to a bug, sometimes no warning was raised and the dimensions were already preserved." } ] } ] } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "FutureWarning to changed behavior" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "These operators are implemented with the " }, { "__type": "InlineCode", "__tag": 4051, "value": "remainder" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "InlineCode", "__tag": 4051, "value": "floor_divide" }, { "__type": "Text", "__tag": 4046, "value": " functions respectively. Those functions are now based around " }, { "__type": "InlineCode", "__tag": 4051, "value": "fmod" }, { "__type": "Text", "__tag": 4046, "value": " and are computed together so as to be compatible with each other and with the Python versions for float types. The results should be marginally more accurate or outright bug fixes compared to the previous results, but they may differ significantly in cases where roundoff makes a difference in the integer returned by " }, { "__type": "InlineCode", "__tag": 4051, "value": "floor_divide" }, { "__type": "Text", "__tag": 4046, "value": ". Some corner cases also change, for instance, NaN is always returned for both functions when the divisor is zero, " }, { "__type": "InlineCode", "__tag": 4051, "value": "divmod(1.0, inf)" }, { "__type": "Text", "__tag": 4046, "value": " returns " }, { "__type": "InlineCode", "__tag": 4051, "value": "(0.0, 1.0)" }, { "__type": "Text", "__tag": 4046, "value": " except on MSVC 2008, and " }, { "__type": "InlineCode", "__tag": 4051, "value": "divmod(-1.0, inf)" }, { "__type": "Text", "__tag": 4046, "value": " returns " }, { "__type": "InlineCode", "__tag": 4051, "value": "(-1.0, inf)" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ], "title": [ { "__type": "InlineCode", "__tag": 4051, "value": "%" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "InlineCode", "__tag": 4051, "value": "//" }, { "__type": "Text", "__tag": 4046, "value": " operators" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Removed the " }, { "__type": "InlineCode", "__tag": 4051, "value": "check_return" }, { "__type": "Text", "__tag": 4046, "value": " and " }, { "__type": "InlineCode", "__tag": 4051, "value": "inner_loop_selector" }, { "__type": "Text", "__tag": 4046, "value": " members of the " }, { "__type": "InlineCode", "__tag": 4051, "value": "PyUFuncObject" }, { "__type": "Text", "__tag": 4046, "value": " struct (replacing them with " }, { "__type": "InlineCode", "__tag": 4051, "value": "reserved" }, { "__type": "Text", "__tag": 4046, "value": " slots to preserve struct layout). These were never used for anything, so it's unlikely that any third-party code is using them either, but we mention it here for completeness." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "C API" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "In python 2, objects which are instances of old-style user-defined classes no longer automatically count as 'object' type in the dtype-detection handler. Instead, as in python 3, they may potentially count as sequences, but only if they define both a " }, { "__type": "InlineRole", "__tag": 4003, "value": "__len__", "domain": null, "role": null, "inventory": null }, { "__type": "Text", "__tag": 4046, "value": " and a " }, { "__type": "InlineRole", "__tag": 4003, "value": "__getitem__", "domain": null, "role": null, "inventory": null }, { "__type": "Text", "__tag": 4046, "value": " method. This fixes a segfault and inconsistency between python 2 and 3." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "object dtype detection for old-style classes" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "BulletList", "__tag": 4053, "ordered": false, "start": 1, "children": [ { "__type": "ListItem", "__tag": 4054, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "InlineCode", "__tag": 4051, "value": "np.histogram" }, { "__type": "Text", "__tag": 4046, "value": " now provides plugin estimators for automatically estimating the optimal number of bins. Passing one of ['auto', 'fd', 'scott', 'rice', 'sturges'] as the argument to 'bins' results in the corresponding estimator being used." } ] } ] }, { "__type": "ListItem", "__tag": 4054, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "A benchmark suite using " }, { "__type": "Link", "__tag": 4049, "children": [ { "__type": "Text", "__tag": 4046, "value": "Airspeed Velocity" } ], "url": "https://asv.readthedocs.io/", "title": "" }, { "__type": "Text", "__tag": 4046, "value": " has been added, converting the previous vbench-based one. You can run the suite locally via " }, { "__type": "InlineCode", "__tag": 4051, "value": "python runtests.py --bench" }, { "__type": "Text", "__tag": 4046, "value": ". 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Such behavior will not be allowed in future releases." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "Invalid arguments for array ordering" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The Python standard library random number generator was previously exposed in the " }, { "__type": "InlineCode", "__tag": 4051, "value": "testing" }, { "__type": "Text", "__tag": 4046, "value": " namespace as " }, { "__type": "InlineCode", "__tag": 4051, "value": "testing.rand" }, { "__type": "Text", "__tag": 4046, "value": ". Using this generator is not recommended and it will be removed in a future release. 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However, " }, { "__type": "InlineCode", "__tag": 4051, "value": "np.random.random_integers" }, { "__type": "Text", "__tag": 4046, "value": " will not be removed anytime soon." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "Random integer generation on a closed interval" } ], "level": 2, "target": null }, { "__type": "Section", "__tag": 4015, "children": [], "title": [ { "__type": "Text", "__tag": 4046, "value": "FutureWarnings" } ], "level": 1, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Currently a slice of a masked array contains a view of the original data and a copy-on-write view of the mask. Consequently, any changes to the slice's mask will result in a copy of the original mask being made and that new mask being changed rather than the original. For example, if we make a slice of the original like so, " }, { "__type": "InlineCode", "__tag": 4051, "value": "view = original[:]" }, { "__type": "Text", "__tag": 4046, "value": ", then modifications to the data in one array will affect the data of the other but, because the mask will be copied during assignment operations, changes to the mask will remain local. A similar situation occurs when explicitly constructing a masked array using " }, { "__type": "InlineCode", "__tag": 4051, "value": "MaskedArray(data, mask)" }, { "__type": "Text", "__tag": 4046, "value": ", the returned array will contain a view of " }, { "__type": "InlineCode", "__tag": 4051, "value": "data" }, { "__type": "Text", "__tag": 4046, "value": " but the mask will be a copy-on-write view of " }, { "__type": "InlineCode", "__tag": 4051, "value": "mask" }, { "__type": "Text", "__tag": 4046, "value": "." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "In the future, these cases will be normalized so that the data and mask arrays are treated the same way and modifications to either will propagate between views. In 1.11, numpy will issue a " }, { "__type": "InlineCode", "__tag": 4051, "value": "MaskedArrayFutureWarning" }, { "__type": "Text", "__tag": 4046, "value": " warning whenever user code modifies the mask of a view that in the future may cause values to propagate back to the original. To silence these warnings and make your code robust against the upcoming changes, you have two options: if you want to keep the current behavior, call " }, { "__type": "InlineCode", "__tag": 4051, "value": "masked_view.unshare_mask()" }, { "__type": "Text", "__tag": 4046, "value": " before modifying the mask. If you want to get the future behavior early, use " }, { "__type": "InlineCode", "__tag": 4051, "value": "masked_view._sharedmask = False" }, { "__type": "Text", "__tag": 4046, "value": ". However, note that setting the " }, { "__type": "InlineCode", "__tag": 4051, "value": "_sharedmask" }, { "__type": "Text", "__tag": 4046, "value": " attribute will break following explicit calls to " }, { "__type": "InlineCode", "__tag": 4051, "value": "masked_view.unshare_mask()" }, { "__type": "Text", "__tag": 4046, "value": "." } ] } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "Assigning to slices/views of " }, { "__type": "InlineCode", "__tag": 4051, "value": "MaskedArray" } ], "level": 2, "target": null } ], "local_refs": [] }