pbrod/numdifftools

Emitted when using dict() to create a dictionary instead of a literal '{ ... }'. The literal is faster as it avoids an additional function call.

Emitted when calling the super() builtin with the current class and instance. On Python 3 these arguments are the default and they can be omitted.

Used when a method or function is too complex based on McCabe Complexity Cyclomatic

Used when the name doesn't conform to naming rules associated to its type (constant, variable, class...).

Used when a function or method takes too many arguments.

Used when we detect a string that is being formatted with format() or % which could potentially be a f-string. The use of f-strings is preferred. Requires Python 3.6 and py-version >= 3.6.

It is better to specify an encoding when opening documents. Using the system default implicitly can create problems on other operating systems. See https://peps.python.org/pep-0597/

Indicates that a set of similar lines has been detected among multiple file. This usually means that the code should be refactored to avoid this duplication. ==numdifftools.ndscipy:[86:143] ==numdifftools.ndstatsmodels:[298:355] class Gradient(Jacobian): ``` Calculate Gradient with finite difference approximation

Parameters

fun : function function of one array fun(x, *args, **kwds) step : float, optional Stepsize, if None, optimal stepsize is used, i.e., x * _EPS for method==complex x * _EPS(1/2) for method==forward x * _EPS(1/3) for method==central. method : {'central', 'complex', 'forward', 'backward'} defines the method used in the approximation.

Examples

import numpy as np import numdifftools.nd_statsmodels as nd fun = lambda x: np.sum(x**2) dfun = nd.Gradient(fun) np.allclose(dfun([1,2,3]), [ 2., 4., 6.]) True

# At [x,y] = [1,1], compute the numerical gradient # of the function sin(x-y) + y*exp(x)

sin = np.sin; exp = np.exp z = lambda xy: sin(xy[0]-xy[1]) + xy[1]*exp(xy[0]) dz = nd.Gradient(z) grad2 = dz([1, 1]) np.allclose(grad2, [ 3.71828183, 1.71828183]) True

# At the global minimizer (1,1) of the Rosenbrock function, # compute the gradient. It should be essentially zero.

rosen = lambda x : (1-x[0])2 + 105.*(x[1]-x[0]2)**2 rd = nd.Gradient(rosen) grad3 = rd([1,1]) np.allclose(grad3,[0, 0]) True

See also

Hessian, Jacobian ```

def call(self, x, args, *kwds): return super(Gradient, self).call(np.atleast_1d(x).ravel(), args, *kwds).squeeze()

if name == 'main': from numdifftools.testing import testdocstrings testdocstrings(file)

Emitted when using dict() to create a dictionary instead of a literal '{ ... }'. The literal is faster as it avoids an additional function call.

Used when pylint has been unable to import a module.

Used when a class inherit from object, which under python3 is implicit, hence can be safely removed from bases.

Used when a function or method takes too many arguments.

Used when a line is longer than a given number of characters.

Used when a line is longer than a given number of characters.

Used when a function or method has no docstring. Some special methods like init do not require a docstring.

Used when we detect a string that is being formatted with format() or % which could potentially be a f-string. The use of f-strings is preferred. Requires Python 3.6 and py-version >= 3.6.

Used when the name doesn't conform to naming rules associated to its type (constant, variable, class...).

Used when class has too few public methods, so be sure it's really worth it.

Used when a function or method has no docstring. Some special methods like init do not require a docstring.

Used when PEP8 import order is not respected (standard imports first, then third-party libraries, then local imports).