{ "__type": "IngestedDoc", "__tag": 4010, "_content": { "Notes": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "The number of data points must be larger than the spline degree " }, { "__type": "ParamRef", "__tag": 4071, "name": "k" }, { "__type": "Text", "__tag": 4046, "value": "." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Strong", "__tag": 4048, "children": [ { "__type": "Text", "__tag": 4046, "value": "NaN handling" } ] }, { "__type": "Text", "__tag": 4046, "value": ": If the input arrays contain " }, { "__type": "InlineCode", "__tag": 4051, "value": "nan" }, { "__type": "Text", "__tag": 4046, "value": " values, the result is not useful, since the underlying spline fitting routines cannot deal with " }, { "__type": "InlineCode", "__tag": 4051, "value": "nan" }, { "__type": "Text", "__tag": 4046, "value": ". A workaround is to use zero weights for not-a-number data points:" } ] }, { "__type": "Code", "__tag": 4050, "value": ">>> import numpy as np\n>>> from scipy.interpolate import UnivariateSpline\n>>> x, y = np.array([1, 2, 3, 4]), np.array([1, np.nan, 3, 4])\n>>> w = np.isnan(y)\n>>> y[w] = 0.\n>>> spl = UnivariateSpline(x, y, w=~w)", "execution_status": null }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Notice the need to replace a " }, { "__type": "InlineCode", "__tag": 4051, "value": "nan" }, { "__type": "Text", "__tag": 4046, "value": " by a numerical value (precise value does not matter as long as the corresponding weight is zero.)" } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Strong", "__tag": 4048, "children": [ { "__type": "Text", "__tag": 4046, "value": "Array API Standard Support" } ] } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "CrossRef", "__tag": 4002, "value": "UnivariateSpline", "reference": { "__type": "LocalRef", "__tag": 4022, "kind": "module", "path": "scipy.interpolate._fitpack2:UnivariateSpline" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " is not in-scope for support of Python Array API Standard compatible backends other than NumPy." } ] }, { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "See " }, { "__type": "InlineRole", "__tag": 4003, "value": "dev-arrayapi", "domain": null, "role": "ref", "inventory": null }, { "__type": "Text", "__tag": 4046, "value": " for more information." } ] } ], "title": [], "level": 0, "target": null }, "Warns": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Raises": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Yields": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Methods": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Returns": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Summary": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "1-D smoothing spline fit to a given set of data points." } ] } ], "title": [], "level": 0, "target": null }, "Receives": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Warnings": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Attributes": { "__type": "Section", "__tag": 4015, "children": [], "title": [], "level": 0, "target": null }, "Parameters": { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Parameters", "__tag": 4026, "children": [ { "__type": "DocParam", "__tag": 4016, "name": "x", "annotation": "(N,) array_like", "desc": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "1-D array of independent input data. 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