numpy.npv(rate, values) [source] Returns the NPV (Net Present Value) of a cash flow series. Parameters: rate : scalar The discount rate. values : array_like, shape(M, ) The values of the time series of cash flows. The (fixed) time interval between cash flow ?events? must be the same as that for which rate is given (i.e., if rate is per year, then precisely a year is understood to elapse between each cash flow event). By convention, investments or ?deposits? are negative, income or ?with

recarray.diagonal(offset=0, axis1=0, axis2=1) Return specified diagonals. In NumPy 1.9 the returned array is a read-only view instead of a copy as in previous NumPy versions. In a future version the read-only restriction will be removed. Refer to numpy.diagonal for full documentation. See also numpy.diagonal equivalent function

record.tofile() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The

record.item() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The

numpy.polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False) [source] Least squares polynomial fit. Fit a polynomial p(x) = p[0] * x**deg + ... + p[deg] of degree deg to points (x, y). Returns a vector of coefficients p that minimises the squared error. Parameters: x : array_like, shape (M,) x-coordinates of the M sample points (x[i], y[i]). y : array_like, shape (M,) or (M, K) y-coordinates of the sample points. Several data sets of sample points sharing the same x-coordinates c

chararray.imag The imaginary part of the array. Examples >>> x = np.sqrt([1+0j, 0+1j]) >>> x.imag array([ 0. , 0.70710678]) >>> x.imag.dtype dtype('float64')

matrix.flags Information about the memory layout of the array. Notes The flags object can be accessed dictionary-like (as in a.flags['WRITEABLE']), or by using lowercased attribute names (as in a.flags.writeable). Short flag names are only supported in dictionary access. Only the UPDATEIFCOPY, WRITEABLE, and ALIGNED flags can be changed by the user, via direct assignment to the attribute or dictionary entry, or by calling ndarray.setflags. The array flags cannot be set arbitrarily: UPDATEIF

Polynomial.has_samecoef(other) [source] Check if coefficients match. New in version 1.6.0. Parameters: other : class instance The other class must have the coef attribute. Returns: bool : boolean True if the coefficients are the same, False otherwise.

numpy.polydiv(u, v) [source] Returns the quotient and remainder of polynomial division. The input arrays are the coefficients (including any coefficients equal to zero) of the ?numerator? (dividend) and ?denominator? (divisor) polynomials, respectively. Parameters: u : array_like or poly1d Dividend polynomial?s coefficients. v : array_like or poly1d Divisor polynomial?s coefficients. Returns: q : ndarray Coefficients, including those equal to zero, of the quotient. r : ndarray Coe

MaskedArray.min(axis=None, out=None, fill_value=None) [source] Return the minimum along a given axis. Parameters: axis : {None, int}, optional Axis along which to operate. By default, axis is None and the flattened input is used. out : array_like, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. fill_value : {var}, optional Value used to fill in the masked values. If None, use the output of minimum_fill