numpy.bincount(x, weights=None, minlength=None) Count number of occurrences of each value in array of non-negative ints. The number of bins (of size 1) is one larger than the largest value in x. If minlength is specified, there will be at least this number of bins in the output array (though it will be longer if necessary, depending on the contents of x). Each bin gives the number of occurrences of its index value in x. If weights is specified the input array is weighted by it, i.e. if a va

ndarray.dump(file) Dump a pickle of the array to the specified file. The array can be read back with pickle.load or numpy.load. Parameters: file : str A string naming the dump file.

ndarray.__iadd__ x.__iadd__(y) <==> x+=y

numpy.polynomial.polynomial.polyvander3d(x, y, z, deg) [source] Pseudo-Vandermonde matrix of given degrees. Returns the pseudo-Vandermonde matrix of degrees deg and sample points (x, y, z). If l, m, n are the given degrees in x, y, z, then The pseudo-Vandermonde matrix is defined by where 0 <= i <= l, 0 <= j <= m, and 0 <= j <= n. The leading indices of V index the points (x, y, z) and the last index encodes the powers of x, y, and z. If V = polyvander3d(x, y, z, [xdeg,

numpy.ipmt(rate, per, nper, pv, fv=0.0, when='end') [source] Compute the interest portion of a payment. Parameters: rate : scalar or array_like of shape(M, ) Rate of interest as decimal (not per cent) per period per : scalar or array_like of shape(M, ) Interest paid against the loan changes during the life or the loan. The per is the payment period to calculate the interest amount. nper : scalar or array_like of shape(M, ) Number of compounding periods pv : scalar or array_like of sh

numpy.fft.hfft(a, n=None, axis=-1, norm=None) [source] Compute the FFT of a signal which has Hermitian symmetry (real spectrum). Parameters: a : array_like The input array. n : int, optional Length of the transformed axis of the output. For n output points, n//2+1 input points are necessary. If the input is longer than this, it is cropped. If it is shorter than this, it is padded with zeros. If n is not given, it is determined from the length of the input along the axis specified by axi

class numpy.poly1d(c_or_r, r=0, variable=None) [source] A one-dimensional polynomial class. A convenience class, used to encapsulate ?natural? operations on polynomials so that said operations may take on their customary form in code (see Examples). Parameters: c_or_r : array_like The polynomial?s coefficients, in decreasing powers, or if the value of the second parameter is True, the polynomial?s roots (values where the polynomial evaluates to 0). For example, poly1d([1, 2, 3]) returns a

ndarray.__sub__ x.__sub__(y) <==> x-y

dtype.names Ordered list of field names, or None if there are no fields. The names are ordered according to increasing byte offset. This can be used, for example, to walk through all of the named fields in offset order. Examples >>> dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))]) >>> dt.names ('name', 'grades')

numpy.nanmin(a, axis=None, out=None, keepdims=False) [source] Return minimum of an array or minimum along an axis, ignoring any NaNs. When all-NaN slices are encountered a RuntimeWarning is raised and Nan is returned for that slice. Parameters: a : array_like Array containing numbers whose minimum is desired. If a is not an array, a conversion is attempted. axis : int, optional Axis along which the minimum is computed. The default is to compute the minimum of the flattened array. out :