numpy.core.defchararray.isdecimal(a) [source] For each element, return True if there are only decimal characters in the element. Calls unicode.isdecimal element-wise. Decimal characters include digit characters, and all characters that that can be used to form decimal-radix numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO. Parameters: a : array_like, unicode Input array. Returns: out : ndarray, bool Array of booleans identical in shape to a. See also unicode.isdecimal

classmethod Legendre.fromroots(roots, domain=[], window=None) [source] Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parameters: roots : array_like List of roots. domain : {[], None, array_like}, optional Domain for the resulting series. If None the domain is the interval from the smallest root to the largest. If [] the domain is the class domain. The default is []. wind

numpy.fmax(x1, x2[, out]) = Element-wise maximum of array elements. Compare two arrays and returns a new array containing the element-wise maxima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first is returned. The latter distinction is important for complex NaNs, which are defined as at least one of the real or imaginary parts being a NaN. The net effect is that NaNs are ignored when possible. Parameters: x1, x2

numpy.fmin(x1, x2[, out]) = Element-wise minimum of array elements. Compare two arrays and returns a new array containing the element-wise minima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first is returned. The latter distinction is important for complex NaNs, which are defined as at least one of the real or imaginary parts being a NaN. The net effect is that NaNs are ignored when possible. Parameters: x1, x2

MaskedArray.__rshift__ x.__rshift__(y) <==> x>>y

numpy.isneginf(x, y=None) [source] Test element-wise for negative infinity, return result as bool array. Parameters: x : array_like The input array. y : array_like, optional A boolean array with the same shape and type as x to store the result. Returns: y : ndarray A boolean array with the same dimensions as the input. If second argument is not supplied then a numpy boolean array is returned with values True where the corresponding element of the input is negative infinity and value

numpy.mod(x1, x2[, out]) = Return element-wise remainder of division. Computes the remainder complementary to the floor_divide function. It is equivalent to the Python modulus operator``x1 % x2`` and has the same sign as the divisor x2. It should not be confused with the Matlab(TM) rem function. Parameters: x1 : array_like Dividend array. x2 : array_like Divisor array. out : ndarray, optional Array into which the output is placed. Its type is preserved and it must be of the right sha

ndarray.squeeze(axis=None) Remove single-dimensional entries from the shape of a. Refer to numpy.squeeze for full documentation. See also numpy.squeeze equivalent function

classmethod Polynomial.fromroots(roots, domain=[], window=None) [source] Return series instance that has the specified roots. Returns a series representing the product (x - r[0])*(x - r[1])*...*(x - r[n-1]), where r is a list of roots. Parameters: roots : array_like List of roots. domain : {[], None, array_like}, optional Domain for the resulting series. If None the domain is the interval from the smallest root to the largest. If [] the domain is the class domain. The default is []. wi

numpy.conj(x[, out]) = Return the complex conjugate, element-wise. The complex conjugate of a complex number is obtained by changing the sign of its imaginary part. Parameters: x : array_like Input value. Returns: y : ndarray The complex conjugate of x, with same dtype as y. Examples >>> np.conjugate(1+2j) (1-2j) >>> x = np.eye(2) + 1j * np.eye(2) >>> np.conjugate(x) array([[ 1.-1.j, 0.-0.j], [ 0.-0.j, 1.-1.j]])