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For example, if ``a.shape == (4, 3, 2, 2)``, it is\ninterpreted as a ``(4, 3)``-shaped batch of :math:`2\\times 2` matrices.\nSee :ref:`linalg_batch` for further details.\nTo illustrate:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "a = np.stack((np.eye(2), [[1, 2], [3, 4]]))\n", "execution_status": "success", "out": "" }, { "__type": "Code", "__tag": 4050, "value": "linalg.inv(a)\n", "execution_status": "failure", "out": "array([[[ 1. , 0. ],\n [ 0. , 1. ]],\n\n [[-2. , 1. ],\n [ 1.5, -0.5]]])\n" }, { "__type": "Text", "__tag": 4046, "value": "\nNote that the structure detection runs per-slice: in the example above, each of the\ntwo slices will be independently discovered as being diagonal. Setting an explicit\n``assume_a`` argument will bypass structure detection and use the provided value\nwithout checking:\n\n" }, { "__type": "Code", "__tag": 4050, "value": "a = np.stack((np.eye(2), [[1, 2], [3, 4]]))\n", "execution_status": "success", "out": "" }, { "__type": "Code", "__tag": 4050, "value": "linalg.inv(a, assume_a=\"diagonal\")\n", "execution_status": "failure", "out": "array([[[1. , 0. ],\n [0. , 1. ]],\n\n [[1. , 2. ],\n [3. , 0.25]]])\n" } ], "title": [], "level": 0, "target": null }, "see_also": [], "signature": { "__type": "SignatureNode", "__tag": 4029, "kind": "function", "parameters": [ { "__type": "SigParam", "__tag": 4030, "name": "a", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": { "__type": "Empty", "__tag": 4031 } }, { "__type": "SigParam", "__tag": 4030, "name": "overwrite_a", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "False" }, { "__type": "SigParam", "__tag": 4030, "name": "check_finite", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "POSITIONAL_OR_KEYWORD", "default": "True" }, { "__type": "SigParam", "__tag": 4030, "name": "assume_a", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "KEYWORD_ONLY", "default": "None" }, { "__type": "SigParam", "__tag": 4030, "name": "lower", "annotation": { "__type": "Empty", "__tag": 4031 }, "kind": "KEYWORD_ONLY", "default": "False" } ], "return_annotation": { "__type": "Empty", "__tag": 4031 }, "target_name": "inv" }, "references": null, "qa": "scipy.linalg._basic:inv", "arbitrary": [], "local_refs": [ "a", "ainv", "assume_a", "check_finite", "lower", "overwrite_a" ] }