U Cv fg@sHddlmZddlZddlZddlmZddlmZddl m Z m Z m Z m Z mZmZddlZddlZddlmZddlmZddlmZmZdd lmZdd lmZmZm Z dd l!m"Z"m#Z#dd l$m%Z%m&Z&dd l'm(Z(m)Z)ddl*m+Z+m,Z,ddl-m.Z.m/Z/e rddl0m1Z1ddl2m3Z3ddddddZ4GdddZ5Gddde5Z6Gddde5Z7Gddde5Z8dWd d!Z9dXdd#d$d%d&d'Z:dYd)d*d+d,d-d.d/d0d1Z;d2d3Zd\d9d:Z?d;d<Z@d]d+d$d>d?d@ZAdAdBZBdCdDZCdEdFZDdGdHZEd+dIdJdKZFd+dIdLdMZGdNdOZHdPdQZId"dRdSdTZJdUdVZKdS)^) annotationsN)partial)Number) TYPE_CHECKINGAnyCallableHashableSequenceget_args)Version)utils)_contains_datetime_like_objects ones_like) apply_ufunc)datetime_to_numericpushtimedelta_to_numeric)OPTIONS_get_keep_attrs)is_duck_dask_array mod_version)Interp1dOptions InterpOptions) OrderedSet is_scalar)Variablebroadcast_variables) DataArray)DatasetzDataset | DataArray | Variablerr)objdimindexcCst|g|}t||}|}||}|j|d|d}|j|dd|||i|j|d|d|d| }|S)zv Return an object where each NaN element in 'obj' is replaced by the length of the gap the element is in. )r rupper)r label) rrZnotnullwhereffillZfillnaZdiffZreindexbfillmax)rr r!arangeZvalidZ valid_arangeZcumulative_nansnan_block_lengthsr+7/tmp/pip-unpacked-wheel-h316xyqg/xarray/core/missing.py_get_nan_block_lengthss&     r-c@sBeZdZUdZded<ded<ded<ded<d d Zd d Zd S)BaseInterpolatorz@Generic interpolator class for normalizing interpolation methodszdict[str, Any] cons_kwargs call_kwargsrfstrmethodcCs|j|f|jSN)r1r0selfxr+r+r,__call__AszBaseInterpolator.__call__cCsdj|jj|jdS)Nz{type}: method={method})typer3)format __class____name__r3)r6r+r+r,__repr__DszBaseInterpolator.__repr__N)r< __module__ __qualname____doc____annotations__r8r=r+r+r+r,r.9s r.c@s"eZdZdZdddZddZdS) NumpyInterpolatorzVOne-dimensional linear interpolation. See Also -------- numpy.interp linearNcCs|dkrtd||_tj|_i|_d|i|_||_||_|j j dkrLtj ntj tj d}|dkrr||_ ||_ nPt|trt|dkr|d|_ |d|_ n$t|r||_ ||_ nt|d dS) NrCz7only method `linear` is valid for the NumpyInterpolatorperiodc?rz is not a valid fill_value) ValueErrorr3npinterpr1r/r0_xi_yidtypekindnan_left_right isinstancer lenr)r6xiyir3 fill_valuerDrPr+r+r,__init__Rs& "  zNumpyInterpolator.__init__cCs&|j||j|jf|j|jd|jS)N)leftright)r1rLrMrQrRr0r5r+r+r,r8mszNumpyInterpolator.__call__)rCNN)r<r>r?r@rXr8r+r+r+r,rBJs rBc@seZdZdZdddZdS)ScipyInterpolatorznInterpolate a 1-D function using Scipy interp1d See Also -------- scipy.interpolate.interp1d NTFc Ksddlm} |dkrtd|dkr8|dkr4td|}||_| |_i|_|jjdkr\tj ntj tj d} |dkr|dkr| | f}n |dkr| }| ||f|j||||d |j|_ dS) Nr)interp1dzPmethod is a required argument, please supply a valid scipy.inter1d method (kind)Z polynomialz(order is required when method=polynomialrErFrC)rOrW bounds_error assume_sortedcopy) scipy.interpolater\rIr3r/r0rNrOrJrPr1) r6rUrVr3rWr^r_r]orderkwargsr\rPr+r+r,rXs: " zScipyInterpolator.__init__)NNTFFNr<r>r?r@rXr+r+r+r,r[xs r[c@seZdZdZdddZdS) SplineInterpolatorzOne-dimensional smoothing spline fit to a given set of data points. See Also -------- scipy.interpolate.UnivariateSpline splineNrc Ksbddlm} |dkrtd||_||_||d|_|dk rDtd| ||fd|i|j|_dS)Nr)UnivariateSplinerez8only method `spline` is valid for the SplineInterpolator)nuextz.SplineInterpolator does not support fill_valuek)r`rgrIr3r/r0r1) r6rUrVr3rWrarhrirbrgr+r+r,rXs  zSplineInterpolator.__init__)reNrfrNrcr+r+r+r,rds rdcKsXt||j|jd}|jD]4\}}||jkrJ||fd|i|||<q|||<q|S)zWrapper for datasets)coordsattrsr )r9rkrlZ data_varsitemsdims)funcr6r rbZdsnamevarr+r+r,_apply_over_vars_with_dims   rrTz str | boolbool)r use_coordinatestrictc Cs`ddlm}|dkr4||}tj|j|tjdS|dkrH||}n4|j|}|j dkrtt d|d|j d | }t |t jr||_|r|jst d |jd |jst d |jd t ||t jfrt|dd dd}t ||r|j}tt||dd|fd}z|jtj}Wn8tt fk rZtd |jdt|jdYnX|S)aSReturn index to use for x values in interpolation or curve fitting. 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Received r{)rtT)defaultignoreZoverflowz invalid valueZ parallelized)Zinput_core_dimsZoutput_core_dims output_dtypesdaskZ vectorizerz6max_gap not implemented for unlabeled coordinates yet.)"r|rwNotImplementedError_get_valid_fill_maskr9r<rrIZ_indexesrSZto_pandas_indexrrrrrJnumberrr_get_interpolatorrfunc_interpolate_narwarningscatch_warningsfilterwarningsRuntimeWarningrrN transposernr%rkr-)r6r rtr3rrrrbrwZvalidsZmax_typer! interp_class interpolatorrr*r+r+r, interp_na5sn              rc Ksf|}t|}|}|}|dks8|t|dkr<|S|||||f|}|||||<|S)z8helper function to apply interpolation along 1 dimensionrrH)r_risnullsumrT) ryr7rboutZnansZnonansZn_nansr1r+r+r,rs rr$cCs*tj||d}t|||d}tj||dS)zinverse of ffillr)rn)rJZflipr)rrrr+r+r,_bfillsrc CsXtdstd||}|dk r&|n|j|}tt|dd|jgt||ddj|j S)zforward fill missing valuesuse_bottleneckzaffill requires bottleneck to be enabled. Call `xr.set_options(use_bottleneck=True)` to enable it.NallowedTrrrrrrb) r RuntimeErrorr}r~rrrNdictrrnrr rrZ_limitr+r+r,r&s   r&c CsXtdstd||}|dk r&|n|j|}tt|dd|jgt||ddj|j S)zbackfill missing valuesrzabfill requires bottleneck to be enabled. Call `xr.set_options(use_bottleneck=True)` to enable it.NrTrr) rrr}r~rrrNrrrnrr+r+r,r's   r'c CsRzddlm}t||WStk rL}ztd|d|W5d}~XYnXdS)z*Import interpolant from scipy.interpolate.r) interpolatezInterpolation with method z requires scipy.N)Zscipyrgetattr ImportError)Z interpolantr3rer+r+r,_import_interpolants   rF)r3vectorizeable_onlycKstt}tddttD}|dkrL|dddksL|sL|j|dt}n||kr||krp|j|dt}n|rt|d|nx|d krt d |}nd|d krt d |}nP|d krt d|}n<|dkr|j|dt }n"|dkrt d|}nt|dnt|d||fS)helper function to select the appropriate interpolator class returns interpolator class and keyword arguments for the class css |]}t|D] }|VqqdSr4)r ).0vvvr+r+r, s z$_get_interpolator..rCrWNZ extrapolater3z< is not a vectorizeable interpolator. Available methods are Z barycentricZBarycentricInterpolatorZkrogZKroghInterpolatorZpchipZPchipInterpolatorreZakimaZAkima1DInterpolatorz" is not a valid scipy interpolatorz is not a valid interpolator) r rtuplergetupdaterBr[rIrrd)r3rrbZinterp1d_methods valid_methodsrr+r+r,rs@          rcKs>ddg}||kr(|j|dtd|}nt|d||fS)rrCnearestrZinterpnzH is not a valid interpolator for interpolating over multiple dimensions.)rrrI)r3rbrrr+r+r,_get_interpolator_nd s  rcCsJ||di}t|jd}|jfddi|j|ddj|dd|kS)zQhelper function to determine values that can be filled when limit is not NonerHZ_windowZ min_periodsF)rW)Zskipna)r Zget_temp_dimnamernrZrollingZ constructr)rr rkwZnew_dimr+r+r,rs  rc Csi}|D]\}\}}t|j}t|j}|}|j|gdd} |j|gdd} tt | dd| d||<||||f||<q |j f||fS)zwSpeed up for linear and nearest neighbor method. Only consider a subspace that is needed for the interpolation rrrGr) rmrJZnanminrZnanmaxrZ get_indexeritemslicer(Zisel) rqindexes_coordsZindexesr r7new_xminvalmaxvalr!ZiminZimaxr+r+r, _localize-s  rcCstt|}t|}tt|D]N}t||r||j}||j|tjd||<||j|tjd||<q||fS)zrMake x and new_x float. This is particularly useful for datetime dtype. x, new_x: tuple of np.ndarray )ryrN) listrangerTr rminZ _to_numericrJr)r7riZxminr+r+r, _floatize_x=s rrc ss |S|dd|d<|}tD]̉|}ttfddD\}}t|}fdd|jD}|} |t|dj} t|j| j ||||} t | | |j d}t } |jD],} | kr| | djq| | q|j| }q(|S) aMake an interpolation of Variable Parameters ---------- var : Variable indexes_coords Mapping from dimension name to a pair of original and new coordinates. Original coordinates should be sorted in strictly ascending order. Note that all the coordinates should be Variable objects. method : string One of {'linear', 'nearest', 'zero', 'slinear', 'quadratic', 'cubic'}. For multidimensional interpolation, only {'linear', 'nearest'} can be used. **kwargs keyword arguments to be passed to scipy.interpolate Returns ------- Interpolated Variable See Also -------- DataArray.interp Dataset.interp r]Fcsg|] }|qSr+r+rdrr+r, xszinterp..csg|]}|kr|qSr+r+rrnr+r,r|sr)rlrH)r_rdecompose_interprziprrn interp_funcrrzrrlrradd)rqrr3rbresultr7rZ destinationZbroadcast_dimsZ original_dimsZnew_dimsZinterpedZout_dimsrr+)rnrr,rKQs6     rKc s|s |St|dkr2t|fddi|\}}nt|f|\}}t|rddlm}|jt|tt tt dj}fddt |D}dd|D}fd dD} d d| D} |t f|| } |j | \} } t d d t | | ddd D} | dt| dd dfddt djD} |dkoddjdk }t|jjtjstj}n|j}tdtdkrd}n|j}|jt|f| |||d|| |ddSt||||S)a~ multi-dimensional interpolation for array-like. Interpolated axes should be located in the last position. Parameters ---------- var : np.ndarray or dask.array.Array Array to be interpolated. The final dimension is interpolated. x : a list of 1d array. Original coordinates. Should not contain NaN. new_x : a list of 1d array New coordinates. Should not contain NaN. method : string {'linear', 'nearest', 'zero', 'slinear', 'quadratic', 'cubic'} for 1-dimensional interpolation. {'linear', 'nearest'} for multidimensional interpolation **kwargs Optional keyword arguments to be passed to scipy.interpolator Returns ------- interpolated: array Interpolated array Notes ----- This requiers scipy installed. 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