ó ʽ÷Xc @`siddlmZmZmZddlZddlZddlmZddlmZddl Z dddd d d d d gZ d„Z ddej d„Z dej d„Zd„Zdddddedid„Zdddded„Zdddddded„Zdddded„Zdddded„Zd„Zdedddded„ZdS(i(tdivisiontprint_functiontabsolute_importNi(t _ni_support(t _nd_imagetspline_filter1dt spline_filtertgeometric_transformtmap_coordinatestaffine_transformtshifttzoomtrotatecC`stj|ƒ}|S(N(Rt_extend_mode_to_code(tmode((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR ,siiÿÿÿÿcC`s½|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚ntj||ƒ\}}|dkrŽtj|ƒ|d= 2 and <= 5. Parameters ---------- input : array_like The input array. order : int, optional The order of the spline, default is 3. axis : int, optional The axis along which the spline filter is applied. Default is the last axis. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. Default is `numpy.float64`. Returns ------- spline_filter1d : ndarray or None The filtered input. If `output` is given as a parameter, None is returned. iisspline order not supportedsComplex type not supportedi.(ii( t RuntimeErrortnumpytasarrayt iscomplexobjt TypeErrorRt _get_outputtarrayt _check_axistndimRR(tinputtordertaxistoutputt return_value((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR1s c C`sÒ|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚ntj||ƒ\}}|d krÀ|jdkrÀxDt|jƒD]"}t |||d|ƒ|}q—Wn|d|d<|S( sñ Multi-dimensional spline filter. For more details, see `spline_filter1d`. See Also -------- spline_filter1d Notes ----- The multi-dimensional filter is implemented as a sequence of one-dimensional spline filters. The intermediate arrays are stored in the same data type as the output. Therefore, for output types with a limited precision, the results may be imprecise because intermediate results may be stored with insufficient precision. iisspline order not supportedsComplex type not supportediiR.(ii( RRRRRRRRtrangeR(RRRRR((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyRZs c C`sXtj|||||||||| | ƒ |dk rT|jj rT|jtƒn|S(s[ Wrapper around _nd_image.geometric_transform to work around endianness issues N(RRtNonetdtypetisnativetbyteswaptTrue( Rtmappingt coordinatestmatrixtoffsetRRRtcvaltextra_argumentstextra_keywords((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyt_geometric_transform|s tconstantgc C`s%|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚n|d krl|j}n|jdkst|ƒdkrœtdƒ‚nt |ƒ}|rÕ|dkrÕt ||dtj ƒ} n|} t j ||d|ƒ\}} t| |d d d |||||| ƒ | S( sM Apply an arbitrary geometric transform. The given mapping function is used to find, for each point in the output, the corresponding coordinates in the input. The value of the input at those coordinates is determined by spline interpolation of the requested order. Parameters ---------- input : array_like The input array. mapping : {callable, scipy.LowLevelCallable} A callable object that accepts a tuple of length equal to the output array rank, and returns the corresponding input coordinates as a tuple of length equal to the input array rank. output_shape : tuple of ints, optional Shape tuple. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. order : int, optional The order of the spline interpolation, default is 3. The order has to be in the range 0-5. mode : str, optional Points outside the boundaries of the input are filled according to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap'). Default is 'constant'. cval : scalar, optional Value used for points outside the boundaries of the input if ``mode='constant'``. Default is 0.0 prefilter : bool, optional The parameter prefilter determines if the input is pre-filtered with `spline_filter` before interpolation (necessary for spline interpolation of order > 1). If False, it is assumed that the input is already filtered. Default is True. extra_arguments : tuple, optional Extra arguments passed to `mapping`. extra_keywords : dict, optional Extra keywords passed to `mapping`. Returns ------- return_value : ndarray or None The filtered input. If `output` is given as a parameter, None is returned. See Also -------- map_coordinates, affine_transform, spline_filter1d Notes ----- This function also accepts low-level callback functions with one the following signatures and wrapped in `scipy.LowLevelCallable`: .. code:: c int mapping(npy_intp *output_coordinates, double *input_coordinates, int output_rank, int input_rank, void *user_data) int mapping(intptr_t *output_coordinates, double *input_coordinates, int output_rank, int input_rank, void *user_data) The calling function iterates over the elements of the output array, calling the callback function at each element. The coordinates of the current output element are passed through ``output_coordinates``. The callback function must return the coordinates at which the input must be interpolated in ``input_coordinates``. The rank of the input and output arrays are given by ``input_rank`` and ``output_rank`` respectively. ``user_data`` is the data pointer provided to `scipy.LowLevelCallable` as-is. The callback function must return an integer error status that is zero if something went wrong and one otherwise. If an error occurs, you should normally set the python error status with an informative message before returning, otherwise a default error message is set by the calling function. In addition, some other low-level function pointer specifications are accepted, but these are for backward compatibility only and should not be used in new code. Examples -------- >>> from scipy import ndimage >>> a = np.arange(12.).reshape((4, 3)) >>> def shift_func(output_coords): ... return (output_coords[0] - 0.5, output_coords[1] - 0.5) ... >>> ndimage.geometric_transform(a, shift_func) array([[ 0. , 0. , 0. ], [ 0. , 1.362, 2.738], [ 0. , 4.812, 6.187], [ 0. , 8.263, 9.637]]) iisspline order not supportedsComplex type not supportedis!input and output rank must be > 0RtshapeN(RRRRRRR,RtlenR Rtfloat64RRR*( RR#t output_shapeRRRR't prefilterR(R)tfilteredR((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyRŒs$e  ! c C`sl|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚ntj|ƒ}tj|ƒrtdƒ‚n|jd}|jdks¯t|ƒdkr¾tdƒ‚n|jd|jkrãtdƒ‚nt|ƒ}|r|dkrt ||dtj ƒ}n|}t j ||d |ƒ\}} t |d |d d ||||d d ƒ | S( s` Map the input array to new coordinates by interpolation. The array of coordinates is used to find, for each point in the output, the corresponding coordinates in the input. The value of the input at those coordinates is determined by spline interpolation of the requested order. The shape of the output is derived from that of the coordinate array by dropping the first axis. The values of the array along the first axis are the coordinates in the input array at which the output value is found. Parameters ---------- input : ndarray The input array. coordinates : array_like The coordinates at which `input` is evaluated. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. order : int, optional The order of the spline interpolation, default is 3. The order has to be in the range 0-5. mode : str, optional Points outside the boundaries of the input are filled according to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap'). Default is 'constant'. cval : scalar, optional Value used for points outside the boundaries of the input if ``mode='constant'``. Default is 0.0 prefilter : bool, optional The parameter prefilter determines if the input is pre-filtered with `spline_filter` before interpolation (necessary for spline interpolation of order > 1). If False, it is assumed that the input is already filtered. Default is True. Returns ------- map_coordinates : ndarray The result of transforming the input. The shape of the output is derived from that of `coordinates` by dropping the first axis. See Also -------- spline_filter, geometric_transform, scipy.interpolate Examples -------- >>> from scipy import ndimage >>> a = np.arange(12.).reshape((4, 3)) >>> a array([[ 0., 1., 2.], [ 3., 4., 5.], [ 6., 7., 8.], [ 9., 10., 11.]]) >>> ndimage.map_coordinates(a, [[0.5, 2], [0.5, 1]], order=1) array([ 2., 7.]) Above, the interpolated value of a[0.5, 0.5] gives output[0], while a[2, 1] is output[1]. >>> inds = np.array([[0.5, 2], [0.5, 4]]) >>> ndimage.map_coordinates(a, inds, order=1, cval=-33.3) array([ 2. , -33.3]) >>> ndimage.map_coordinates(a, inds, order=1, mode='nearest') array([ 2., 8.]) >>> ndimage.map_coordinates(a, inds, order=1, cval=0, output=bool) array([ True, False], dtype=bool) iisspline order not supportedsComplex type not supportedis!input and output rank must be > 0s"invalid shape for coordinate arrayRR,N(RRRRRR,RR-R RR.RRR*R( RR$RRRR'R0R/R1R((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyRs,J ! c C`s|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚n|dkrl|j}n|jdkst|ƒdkrœtdƒ‚nt |ƒ}|rÕ|dkrÕt ||dtj ƒ} n|} t j ||d|ƒ\}} tj|d tj ƒ}|jdks3|jddkrBtd ƒ‚n|jd|jkrgtd ƒ‚n|jd kr›|jd|jkr›td ƒ‚n|jjs¶|jƒ}nt j||jƒ}tj|d tj ƒ}|jdks|jddkrtdƒ‚n|jjs/|jƒ}n|jdkrqtjdƒtj| |||||||ƒn(t| dd||||||ddƒ | S(s> Apply an affine transformation. The given matrix and offset are used to find for each point in the output the corresponding coordinates in the input by an affine transformation. The value of the input at those coordinates is determined by spline interpolation of the requested order. Points outside the boundaries of the input are filled according to the given mode. Given an output image pixel index vector ``o``, the pixel value is determined from the input image at position ``np.dot(matrix,o) + offset``. A diagonal matrix can be specified by supplying a one-dimensional array-like to the matrix parameter, in which case a more efficient algorithm is applied. .. versionchanged:: 0.18.0 Previously, the exact interpretation of the affine transformation depended on whether the matrix was supplied as a one-dimensional or two-dimensional array. If a one-dimensional array was supplied to the matrix parameter, the output pixel value at index ``o`` was determined from the input image at position ``matrix * (o + offset)``. Parameters ---------- input : ndarray The input array. matrix : ndarray The matrix must be two-dimensional or can also be given as a one-dimensional sequence or array. In the latter case, it is assumed that the matrix is diagonal. A more efficient algorithms is then applied that exploits the separability of the problem. offset : float or sequence, optional The offset into the array where the transform is applied. If a float, `offset` is the same for each axis. If a sequence, `offset` should contain one value for each axis. output_shape : tuple of ints, optional Shape tuple. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. order : int, optional The order of the spline interpolation, default is 3. The order has to be in the range 0-5. mode : str, optional Points outside the boundaries of the input are filled according to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap'). Default is 'constant'. cval : scalar, optional Value used for points outside the boundaries of the input if ``mode='constant'``. Default is 0.0 prefilter : bool, optional The parameter prefilter determines if the input is pre-filtered with `spline_filter` before interpolation (necessary for spline interpolation of order > 1). If False, it is assumed that the input is already filtered. Default is True. Returns ------- affine_transform : ndarray or None The transformed input. If `output` is given as a parameter, None is returned. iisspline order not supportedsComplex type not supportedis!input and output rank must be > 0RR,Ris no proper affine matrix provideds&affine matrix has wrong number of rowss)affine matrix has wrong number of columnssno proper offset provideds}The behaviour of affine_transform with a one-dimensional array supplied for the matrix parameter has changed in scipy 0.18.0.N(ii(RRRRRRR,RR-R RR.RRtflagst contiguoustcopyt_normalize_sequencetwarningstwarnRt zoom_shiftR*( RR%R&R/RRRR'R0R1R((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR isLD  ! "% "  c C`sN|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚n|jdkrrtdƒ‚nt|ƒ}|r«|dkr«t||dtjƒ}n|}t j ||ƒ\}}t j ||jƒ}g|D] } | ^qå}tj|dtjƒ}|j j s+|jƒ}ntj|d |||||ƒ|S( sï Shift an array. The array is shifted using spline interpolation of the requested order. Points outside the boundaries of the input are filled according to the given mode. Parameters ---------- input : ndarray The input array. shift : float or sequence, optional The shift along the axes. If a float, `shift` is the same for each axis. If a sequence, `shift` should contain one value for each axis. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. order : int, optional The order of the spline interpolation, default is 3. The order has to be in the range 0-5. mode : str, optional Points outside the boundaries of the input are filled according to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap'). Default is 'constant'. cval : scalar, optional Value used for points outside the boundaries of the input if ``mode='constant'``. Default is 0.0 prefilter : bool, optional The parameter prefilter determines if the input is pre-filtered with `spline_filter` before interpolation (necessary for spline interpolation of order > 1). If False, it is assumed that the input is already filtered. Default is True. Returns ------- shift : ndarray or None The shifted input. If `output` is given as a parameter, None is returned. iisspline order not supportedsComplex type not supportedis!input and output rank must be > 0RRN(RRRRRRR RR.RRR5R2R3R4RR8R( RR RRRR'R0R1Rtii((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR Ús&*  c C`s|dks|dkr'tdƒ‚ntj|ƒ}tj|ƒrTtdƒ‚n|jdkrrtdƒ‚nt|ƒ}|r«|dkr«t||dtjƒ}n|}t j ||jƒ}t gt |j |ƒD]"\}} tt|| ƒƒ^q܃} t gt |j |ƒD]\}} t|| ƒ^qƒ} | | kratjdtƒntj| tƒd} tjtj|j ƒd| d tj|j d tjƒd | dkƒ}t j||d | ƒ\}} tj|ƒ}tj||d ||||ƒ| S(s“ Zoom an array. The array is zoomed using spline interpolation of the requested order. Parameters ---------- input : ndarray The input array. zoom : float or sequence, optional The zoom factor along the axes. If a float, `zoom` is the same for each axis. If a sequence, `zoom` should contain one value for each axis. output : ndarray or dtype, optional The array in which to place the output, or the dtype of the returned array. order : int, optional The order of the spline interpolation, default is 3. The order has to be in the range 0-5. mode : str, optional Points outside the boundaries of the input are filled according to the given mode ('constant', 'nearest', 'reflect', 'mirror' or 'wrap'). Default is 'constant'. cval : scalar, optional Value used for points outside the boundaries of the input if ``mode='constant'``. Default is 0.0 prefilter : bool, optional The parameter prefilter determines if the input is pre-filtered with `spline_filter` before interpolation (necessary for spline interpolation of order > 1). If False, it is assumed that the input is already filtered. Default is True. Returns ------- zoom : ndarray or None The zoomed input. If `output` is given as a parameter, None is returned. iisspline order not supportedsComplex type not supportedis!input and output rank must be > 0Rs˜From scipy 0.13.0, the output shape of zoom() is calculated with round() instead of int() - for these inputs the size of the returned array has changed.toutRtwhereR,N(RRRRRRR RR.RR5ttupletzipR,tinttroundR6R7t UserWarningRtfloattdividet ones_likeRtascontiguousarrayRR8R(RR RRRR'R0R1R9tjjR/toutput_shape_oldtzoom_divR((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR s:( >8  cC`sž|d|dkr%|d|d 1). If False, it is assumed that the input is already filtered. Default is True. Returns ------- rotate : ndarray or None The rotated input. If `output` is given as a parameter, None is returned. iis invalid rotation plane specifiedi´Rgà?ig@R,R(i(iN(RRtlistRRtpitmathtcostsinRR.R,tdotRKR>tzerosRAR<RRR tproductRtappendtsliceRtreversetremove(#RtangletaxestreshapeRRRR'R0tranktm11tm12tm21tm22R%tiytixtmtrxRIRJRHtoytoxR&ttmpR/RR$tsizeR9t iter_axestostiatoaRE((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyR ts˜/  @        ((ii(t __future__RRRRNRtRRR6t__all__R R.RRR*RR"RRR R R RKR (((s:/tmp/pip-build-7oUkmx/scipy/scipy/ndimage/interpolation.pyts8     )"  wbo  ?  M