U /e' @sddlZddlZddlmZddlmZeejZ e edkZ e edkZ e edkZ e edkZ e edkZzeneejd d d d ejd d d ed reejd ddddreed d d sedejZejjZW5QRXWn<ek r*d$ddZejjeejjdd ZYnXGdddZeeddZd%ddZe rfejjjZnd&dddddZd'd d!Ze rdd"l m!Z!m"Z"ndd#l#m$Z$e$Z!Z"dS)(N)parse) derived_fromz1.20.0z1.21.0z1.22.0z1.23.0z1.24.0g?Zunsafe)casting)rdtypeg?i8)rzIDivide not working with dtype: https://github.com/numpy/numpy/issues/3484cCs$t|||}|dk r ||}|S)zImplementation of numpy.divide that works with dtype kwarg. Temporary compatibility fix for a bug in numpy's version. 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When kwargs are passed, as in ``map_reduce([[1, 2], 3, 4], **kw)``, this becomes:: kw1 = f_kwargs(**kw) kw2 = f_kwargs(**kw1) f_reduce([ f_reduce([ f_map(1), **kw2) f_map(2, **kw2) ], **kw1), f_map(3, **kw1), f_map(4, **kw1) ]], **kw) cs@|s|f|Sf|fdd|Df|SdS)Nc3s|]}|fVqdSrr).0xi)f next_kwargsrr nsz2_Recurser.map_reduce..f..rrrf_kwargsf_mapf_reducer)rrris   z_Recurser.map_reduce..fr)rr r!r"r rrrr map_reduce@s)z_Recurser.map_reducerccsL||}|||fV|sdSt|D] \}}||||fEdHq&dS)aB Iterate over x, yielding (index, value, entering), where * ``index``: a tuple of indices up to this point * ``value``: equal to ``x[index[0]][...][index[-1]]``. On the first iteration, is ``x`` itself * ``entering``: bool. 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Also known as rolling or moving window, the window slides across all dimensions of the array and extracts subsets of the array at all window positions. .. versionadded:: 1.20.0 Parameters ---------- x : array_like Array to create the sliding window view from. window_shape : int or tuple of int Size of window over each axis that takes part in the sliding window. If `axis` is not present, must have same length as the number of input array dimensions. Single integers `i` are treated as if they were the tuple `(i,)`. axis : int or tuple of int, optional Axis or axes along which the sliding window is applied. By default, the sliding window is applied to all axes and `window_shape[i]` will refer to axis `i` of `x`. If `axis` is given as a `tuple of int`, `window_shape[i]` will refer to the axis `axis[i]` of `x`. Single integers `i` are treated as if they were the tuple `(i,)`. subok : bool, optional If True, sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default). writeable : bool, optional When true, allow writing to the returned view. The default is false, as this should be used with caution: the returned view contains the same memory location multiple times, so writing to one location will cause others to change. Returns ------- view : ndarray Sliding window view of the array. The sliding window dimensions are inserted at the end, and the original dimensions are trimmed as required by the size of the sliding window. That is, ``view.shape = x_shape_trimmed + window_shape``, where ``x_shape_trimmed`` is ``x.shape`` with every entry reduced by one less than the corresponding window size. r)r3F)copyrHz-`window_shape` cannot contain negative valuesNzOSince axis is `None`, must provide window_shape for all dimensions of `x`; got z' window_shape elements and `x.ndim` is .T)Zallow_duplicatez8Must provide matching length window_shape and axis; got z window_shape elements and z axes elements.c3s|]}j|VqdSr)strides)raxr rrrsz&sliding_window_view..z4window shape cannot be larger than input array shaper)rLshaperHrI)Znumpy.core.numericr3r iterabletuplearrayanyr6r7r4r5rLrCrOr9lib stride_tricksZ as_strided) r Z window_shaperErHrIr3Zwindow_shape_arrayZ out_stridesZx_shape_trimmedrMZdimZ out_shaperrNrsliding_window_views@,    rVlinearcCs(trtj|||dStj|||dSdS)N)method) interpolation) _numpy_122r percentile)r<qrXrrrr[sr[) ArrayLike DTypeLike)Any)NN)r)N)rW)%warningsZnumpyr Zpackaging.versionr parse_versionZ dask.utilsr __version__Z _np_versionZ _numpy_120Z _numpy_121rZZ _numpy_123Z _numpy_124catch_warningsZallcloser float TypeErrormaZ ma_divider1Z_DomainedBinaryOperationZ_DomainSafeDividerrArGrTrUrVr[Z numpy.typingr]r^typingr_rrrrsb            S    Y