ó ÚÆ÷Xc@`sVdZddlmZmZmZddlZddlZddlZddl m Z ddl m Z e ej ƒdkrŠejjZn d„Zdd„Ze ej ƒd krÇdd lmZnd „Zd „Zed „Ze ej ƒdkr ddlmZneeed„Ze ej ƒdkrFejjjZn ed„ZdS(s4Functions copypasted from newer versions of numpy. i(tdivisiontprint_functiontabsolute_importN(t import_nose(t NumpyVersions 1.7.0.devc O`s™tjdtƒ}tjdƒ|||Ž}t|ƒdksYtd|jƒ‚n|dj|k rtd|j||dfƒ‚nWdQX|S(s^ Fail unless the given callable throws the specified warning. This definition is copypasted from numpy 1.9.0.dev. The version in earlier numpy returns None. Parameters ---------- warning_class : class The class defining the warning that `func` is expected to throw. func : callable The callable to test. *args : Arguments Arguments passed to `func`. **kwargs : Kwargs Keyword arguments passed to `func`. Returns ------- The value returned by `func`. trecordtalwaysis!No warning raised when calling %ss(First warning for %s is not a %s( is %s)N(twarningstcatch_warningstTruet simplefiltertlentAssertionErrort__name__tcategory(t warning_classtfunctargstkwtltresult((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyt _assert_warnss #cO`sRt}tƒ}tjjdkr0|jj}n |jj}||||||ŽS(sc Fail unless an exception of class exception_class and with message that matches expected_regexp is thrown by callable when invoked with arguments args and keyword arguments kwargs. Name of this function adheres to Python 3.2+ reference, but should work in all versions down to 2.6. Notes ----- .. versionadded:: 1.8.0 i(R Rtsyst version_infotmajorttoolstassert_raises_regextassert_raises_regexp(texception_classtexpected_regexpt callable_objRtkwargst__tracebackhide__tnosetfuncname((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyR5s    s1.10.0(t broadcast_tocC`sPt|ƒt|ƒk rL|jdt|ƒƒ}|jrL|j|ƒqLn|S(Nttype(R$tviewt__array_finalize__(toriginal_arrayt new_array((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyt_maybe_view_as_subclassSs  c C`sõtj|ƒrt|ƒn|f}tj|dtd|ƒ}| r^|jr^tdƒ‚ntd„|Dƒƒrƒtdƒ‚ntj|fdddd gd d gd |d dƒj d}t ||ƒ}| rñ|j j rñt |j _ n|S(Ntcopytsuboks/cannot broadcast a non-scalar to a scalar arraycs`s|]}|dkVqdS(iN((t.0tsize((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pys dss4all elements of broadcast shape must be non-negativetflagst multi_indextrefs_okt zerosize_oktop_flagstreadonlyt itershapetordertCi(tnptiterablettupletarraytFalsetshapet ValueErrortanytnditertitviewsR)R.t writeableR (R:R<R+R3t broadcastR((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyt _broadcast_to_s$cC`st||d|dtƒS(NR+R3(RCR (R:R<R+((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyR#oss1.9.0(tuniquec C`sþtj|ƒjƒ}|p|}|p*|}|jdkrÇ|sK|}nx|f}|ry|tjdtjƒf7}n|rž|tjdtjƒf7}n|rÃ|tjdtjƒf7}n|S|rø|jd|râdndƒ}||}n|jƒ|}tj t g|d|d kfƒ} |sA|| }n¹|| f}|rh||| f7}n|r¶tj | ƒd} tj|j dtjƒ} | | |<|| f7}n|rútj tj | ƒ|jgfƒ} |tj| ƒf7}n|S(sP Find the unique elements of an array. Returns the sorted unique elements of an array. There are three optional outputs in addition to the unique elements: the indices of the input array that give the unique values, the indices of the unique array that reconstruct the input array, and the number of times each unique value comes up in the input array. Parameters ---------- ar : array_like Input array. This will be flattened if it is not already 1-D. return_index : bool, optional If True, also return the indices of `ar` that result in the unique array. return_inverse : bool, optional If True, also return the indices of the unique array that can be used to reconstruct `ar`. return_counts : bool, optional If True, also return the number of times each unique value comes up in `ar`. .. versionadded:: 1.9.0 Returns ------- unique : ndarray The sorted unique values. unique_indices : ndarray, optional The indices of the first occurrences of the unique values in the (flattened) original array. Only provided if `return_index` is True. unique_inverse : ndarray, optional The indices to reconstruct the (flattened) original array from the unique array. Only provided if `return_inverse` is True. unique_counts : ndarray, optional The number of times each of the unique values comes up in the original array. Only provided if `return_counts` is True. .. versionadded:: 1.9.0 Notes ----- Taken over from numpy 1.12.0-dev (c8408bf9c). Omitted examples, see numpy documentation for those. itkindt mergesortt quicksortiiÿÿÿÿtdtype(R7t asanyarraytflattenR-temptytbooltintptargsorttsortt concatenateR tcumsumR<tnonzerotdiff( tart return_indextreturn_inverset return_countstoptional_indicestoptional_returnstrettpermtauxtflagtiflagtinv_idxtidx((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyRDwsD0      &   %s 1.12.0.devcC`sÜtj|ddddƒ}|jjdkrB|jtjƒ}nt|ttfƒritj |ƒ}nt|tj ƒrÅ|r¡|j |j d|j ƒ}qÅ|j |j krÅtdƒ‚qÅntj||ddƒS( s™ Evaluate a polynomial specified by its roots at points x. This function is copypasted from numpy 1.12.0.dev. If `r` is of length `N`, this function returns the value .. math:: p(x) = \prod_{n=1}^{N} (x - r_n) The parameter `x` is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either `x` or its elements must support multiplication and addition both with themselves and with the elements of `r`. If `r` is a 1-D array, then `p(x)` will have the same shape as `x`. If `r` is multidimensional, then the shape of the result depends on the value of `tensor`. If `tensor is ``True`` the shape will be r.shape[1:] + x.shape; that is, each polynomial is evaluated at every value of `x`. If `tensor` is ``False``, the shape will be r.shape[1:]; that is, each polynomial is evaluated only for the corresponding broadcast value of `x`. Note that scalars have shape (,). Parameters ---------- x : array_like, compatible object If `x` is a list or tuple, it is converted to an ndarray, otherwise it is left unchanged and treated as a scalar. In either case, `x` or its elements must support addition and multiplication with with themselves and with the elements of `r`. r : array_like Array of roots. If `r` is multidimensional the first index is the root index, while the remaining indices enumerate multiple polynomials. For instance, in the two dimensional case the roots of each polynomial may be thought of as stored in the columns of `r`. tensor : boolean, optional If True, the shape of the roots array is extended with ones on the right, one for each dimension of `x`. Scalars have dimension 0 for this action. The result is that every column of coefficients in `r` is evaluated for every element of `x`. If False, `x` is broadcast over the columns of `r` for the evaluation. This keyword is useful when `r` is multidimensional. The default value is True. Returns ------- values : ndarray, compatible object The shape of the returned array is described above. See Also -------- polyroots, polyfromroots, polyval Examples -------- >>> from numpy.polynomial.polynomial import polyvalfromroots >>> polyvalfromroots(1, [1,2,3]) 0.0 >>> a = np.arange(4).reshape(2,2) >>> a array([[0, 1], [2, 3]]) >>> polyvalfromroots(a, [-1, 0, 1]) array([[ -0., 0.], [ 6., 24.]]) >>> r = np.arange(-2, 2).reshape(2,2) # multidimensional coefficients >>> r # each column of r defines one polynomial array([[-2, -1], [ 0, 1]]) >>> b = [-2, 1] >>> polyvalfromroots(b, r, tensor=True) array([[-0., 3.], [ 3., 0.]]) >>> polyvalfromroots(b, r, tensor=False) array([-0., 0.]) tndminiR*is ?bBhHiIlLqQpPs,x.ndim must be < r.ndim when tensor == Falsetaxis(i(R7R:RHtchartastypetdoublet isinstanceR9tlisttasarraytndarraytreshapeR<tndimR=tprod(txtrttensor((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pytpolyvalfromrootsÕsK (t__doc__t __future__RRRRRtnumpyR7tnumpy.testing.nosetesterRtscipy._lib._versionRt __version__ttestingt assert_warnsRtNoneRR#R)RCR;RDt polynomialRpR (((s7/tmp/pip-build-X4mzal/scipy/scipy/_lib/_numpy_compat.pyts*    $   [