2012年3月26日 · scipy.interpolate's many interpolating splines are capable of providing derivatives. So, using a linear spline ( k=1 ), the derivative of the spline (using the derivative() method) should be equivalent to a forward difference.

2017年5月31日 · Your function fprime is not the derivative. It is a function that returns the derivative (as a Sympy expression).

2013年12月6日 · Is it possible to find derivative of a function using c program. I am using matlab in that it has an inbuilt function diff() which can be used for finding derivative of a function. f(x)=x^2 Is it

2013年5月30日 · numpy.diff(x) computes the difference between adjacent elements in x. just like in the answer by @tsm. As a result you get an array which is 1 element shorter than the original one.

2009年1月8日 · One of the things I'd like to do is to take partial derivatives of the expressions. So if f(x,y) = x^2 + y^2 then the partial of f with respect to x would be 2x, the partial with respect to y would be 2y. I wrote a dinky function using a finite differences method but I'm running into lots of problems with floating point precision.

2009年10月13日 · Typically signal noise impacts the derivative quality more that anything else. If you do have noise in your f(x), Savtizky-Golay is a excellent smoothing algorithm that is often used to compute good derivatives. In a nutshell, SG fits a polynomial locally to your data, the then this polynomial can be used to compute the derivative. Paul

2018年5月14日 · There is a big problem here; surprised no one has mentioned it before. Getting sum and then taking derivative yields the second derivative PLUS the sum of cross-derivatives (and they accumulate more as the for loop continues). In the example above (i.e., x**4), all of those cross-derivatives are zero by construction. –

2015年5月19日 · I am ultimately feeding a munging of the interpolated function into a multi-dimensional minimization routine, so being able to pass analytic derivatives would speed things up a lot rather than having the minimization routine try to calculate them itself. And interp1d must be calculating them internally --- so can I access them?

ValueError: The number of derivatives at boundaries does not match: expected 2, got 0+0 while trying to use cubic interpolation in pandas on a 2d matrix. mat = pd.read_csv("m.csv") mat = mat.interpolate(method='cubic') Csv to reproduce can be downloaded here

2015年6月17日 · I'm interested in computing partial derivatives in Python. I've seen functions which compute derivatives for single variable functions, but not others. It would be great to find something that did the following. f(x,y,z) = 4xy + xsin(z)+ x^3 + z^8y part_deriv(function = f, variable = x) output = 4y + sin(z) +3x^2