Python--scipy.integrate.学习笔记

import sys import warnings from functools import partial from . import _quadpack import numpy as np __all__ = ["quad", "dblquad", "tplquad", "nquad", "IntegrationWarning"] class IntegrationWarning(UserWarning): """ Warning on issues during integration. """ pass def quad(func, a, b, args=(), full_output=0, epsabs=1.49e-8, epsrel=1.49e-8, limit=50, points=None, weight=None, wvar=None, wopts=None, maxp1=50, limlst=50, complex_func=False): """ Compute a definite integral. Integrate func from `a` to `b` (possibly infinite interval) using a technique from the Fortran library QUADPACK. Returns ------- y : float The integral of func from `a` to `b`. abserr : float An estimate of the absolute error in the result. infodict : dict A dictionary containing additional information. message A convergence message. explain Appended only with 'cos' or 'sin' weighting and infinite integration limits, it contains an explanation of the codes in infodict['ierlst'] Other Parameters ---------------- epsabs : float or int, optional Absolute error tolerance. Default is 1.49e-8. `quad` tries to obtain an accuracy of ``abs(i-result) <= max(epsabs, epsrel*abs(i))`` where ``i`` = integral of `func` from `a` to `b`, and ``result`` is the numerical approximation. See `epsrel` below. epsrel : float or int, optional Relative error tolerance. Default is 1.49e-8. If ``epsabs <= 0``, `epsrel` must be greater than both 5e-29 and ``50 * (machine epsilon)``. See `epsabs` above. limit : float or int, optional An upper bound on the number of subintervals used in the adaptive algorithm. points : (sequence of floats,ints), optional A sequence of break points in the bounded integration interval where local difficulties of the integrand may occur (e.g., singularities, discontinuities). The sequence does not have to be sorted. Note that this option cannot be used in conjunction with ``weight``. weight : float or int, optional String indicating weighting function. Full explanation for this and the remaining arguments can be found below. wvar : optional Variables for use with weighting functions. wopts : optional Optional input for reusing Chebyshev moments. maxp1 : float or int, optional An upper bound on the number of Chebyshev moments. limlst : int, optional Upper bound on the number of cycles (>=3) for use with a sinusoidal weighting and an infinite end-point. See Also -------- dblquad : double integral tplquad : triple integral nquad : n-dimensional integrals (uses `quad` recursively) fixed_quad : fixed-order Gaussian quadrature simpson : integrator for sampled data romb : integrator for sampled data scipy.special : for coefficients and roots of orthogonal polynomials Notes ----- For valid results, the integral must converge; behavior for divergent integrals is not guaranteed. **Extra information for quad() inputs and outputs** If full_output is non-zero, then the third output argument (infodict) is a dictionary with entries as tabulated below. For infinite limits, the range is transformed to (0,1) and the optional outputs are given with respect to this transformed range. Let M be the input argument limit and let K be infodict['last']. The entries are: 'neval' The number of function evaluations. 'last' The number, K, of subintervals produced in the subdivision process. 'alist' A rank-1 array of length M, the first K elements of which are the left end points of the subintervals in the partition of the integration range. 'blist' A rank-1 array of length M, the first K elements of which are the right end points of the subintervals. 'rlist' A rank-1 array of length M, the first K elements of which are the integral approximations on the subintervals. 'elist' A rank-1 array of length M, the first K elements of which are the moduli of the absolute error estimates on the subintervals. 'iord' A rank-1 integer array of length M, the first L elements of which are pointers to the error estimates over the subintervals with ``L=K`` if ``K<=M/2+2`` or ``L=M+1-K`` otherwise. Let I be the sequence ``infodict['iord']`` and let E be the sequence ``infodict['elist']``. Then ``E[I[1]], ..., E[I[L]]`` forms a decreasing sequence. If the input argument points is provided (i.e., it is not None), the following additional outputs are placed in the output dictionary. Assume the points sequence is of length P. 'pts' A rank-1 array of length P+2 containing the integration limits and the break points of the intervals in ascending order. This is an array giving the subintervals over which integration will occur. 'level' A rank-1 integer array of length M (=limit), containing the subdivision levels of the subintervals, i.e., if (aa,bb) is a subinterval of ``(pts[1], pts[2])`` where ``pts[0]`` and ``pts[2]`` are adjacent elements of ``infodict['pts']``, then (aa,bb) has level l if ``|bb-aa| = |pts[2]-pts[1]| * 2**(-l)``. 'ndin' A rank-1 integer array of length P+2. After the first integration over the intervals (pts[1], pts[2]), the error estimates over some of the intervals may have been increased artificially in order to put their subdivision forward. This array has ones in slots corresponding to the subintervals for which this happens. **Weighting the integrand** The input variables, *weight* and *wvar*, are used to weight the integrand by a select list of functions. Different integration methods are used to compute the integral with these weighting functions, and these do not support specifying break points. The possible values of weight and the corresponding weighting functions are. ========== =================================== ===================== ``weight`` Weight function used ``wvar`` ========== =================================== ===================== 'cos' cos(w*x) wvar = w 'sin' sin(w*x) wvar = w 'alg' g(x) = ((x-a)**alpha)*((b-x)**beta) wvar = (alpha, beta) 'alg-loga' g(x)*log(x-a) wvar = (alpha, beta) 'alg-logb' g(x)*log(b-x) wvar = (alpha, beta) 'alg-log' g(x)*log(x-a)*log(b-x) wvar = (alpha, beta) 'cauchy' 1/(x-c) wvar = c ========== =================================== ===================== wvar holds the parameter w, (alpha, beta), or c depending on the weight selected. In these expressions, a and b are the integration limits. For the 'cos' and 'sin' weighting, additional inputs and outputs are available. For finite integration limits, the integration is performed using a Clenshaw-Curtis method which uses Chebyshev moments. For repeated calculations, these moments are saved in the output dictionary: 'momcom' The maximum level of Chebyshev moments that have been computed, i.e., if ``M_c`` is ``infodict['momcom']`` then the moments have been computed for intervals of length ``|b-a| * 2**(-l)``, ``l=0,1,...,M_c``. 'nnlog' A rank-1 integer array of length M(=limit), containing the subdivision levels of the subintervals, i.e., an element of this array is equal to l if the corresponding subinterval is ``|b-a|* 2**(-l)``. 'chebmo' A rank-2 array of shape (25, maxp1) containing the computed Chebyshev moments. These can be passed on to an integration over the same interval by passing this array as the second element of the sequence wopts and passing infodict['momcom'] as the first element. If one of the integration limits is infinite, then a Fourier integral is computed (assuming w neq 0). If full_output is 1 and a numerical error is encountered, besides the error message attached to the output tuple, a dictionary is also appended to the output tuple which translates the error codes in the array ``info['ierlst']`` to English messages. The output information dictionary contains the following entries instead of 'last', 'alist', 'blist', 'rlist', and 'elist': 'lst' The number of subintervals needed for the integration (call it ``K_f``). 'rslst' A rank-1 array of length M_f=limlst, whose first ``K_f`` elements contain the integral contribution over the interval ``(a+(k-1)c, a+kc)`` where ``c = (2*floor(|w|) + 1) * pi / |w|`` and ``k=1,2,...,K_f``. 'erlst' A rank-1 array of length ``M_f`` containing the error estimate corresponding to the interval in the same position in ``infodict['rslist']``. 'ierlst' A rank-1 integer array of length ``M_f`` containing an error flag corresponding to the interval in the same position in ``infodict['rslist']``. See the explanation dictionary (last entry in the output tuple) for the meaning of the codes. **Details of QUADPACK level routines** `quad` calls routines from the FORTRAN library QUADPACK. This section provides details on the conditions for each routine to be called and a short description of each routine. The routine called depends on `weight`, `points` and the integration limits `a` and `b`. ================ ============== ========== ===================== QUADPACK routine `weight` `points` infinite bounds ================ ============== ========== ===================== qagse None No No qagie None No Yes qagpe None Yes No qawoe 'sin', 'cos' No No qawfe 'sin', 'cos' No either `a` or `b` qawse 'alg*' No No qawce 'cauchy' No No ================ ============== ========== ===================== The following provides a short description from [1]_ for each routine. qagse is an integrator based on globally adaptive interval subdivision in connection with extrapolation, which will eliminate the effects of integrand singularities of several types. qagie handles integration over infinite intervals. The infinite range is mapped onto a finite interval and subsequently the same strategy as in ``QAGS`` is applied. qagpe serves the same purposes as QAGS, but also allows the user to provide explicit information about the location and type of trouble-spots i.e. the abscissae of internal singularities, discontinuities and other difficulties of the integrand function. qawoe is an integrator for the evaluation of :math:`\\int^b_a \\cos(\\omega x)f(x)dx` or :math:`\\int^b_a \\sin(\\omega x)f(x)dx` over a finite interval [a,b], where :math:`\\omega` and :math:`f` are specified by the user. The rule evaluation component is based on the modified Clenshaw-Curtis technique An adaptive subdivision scheme is used in connection with an extrapolation procedure, which is a modification of that in ``QAGS`` and allows the algorithm to deal with singularities in :math:`f(x)`. qawfe calculates the Fourier transform :math:`\\int^\\infty_a \\cos(\\omega x)f(x)dx` or :math:`\\int^\\infty_a \\sin(\\omega x)f(x)dx` for user-provided :math:`\\omega` and :math:`f`. The procedure of ``QAWO`` is applied on successive finite intervals, and convergence acceleration by means of the :math:`\\varepsilon`-algorithm is applied to the series of integral approximations. qawse approximate :math:`\\int^b_a w(x)f(x)dx`, with :math:`a < b` where :math:`w(x) = (x-a)^{\\alpha}(b-x)^{\\beta}v(x)` with :math:`\\alpha,\\beta > -1`, where :math:`v(x)` may be one of the following functions: :math:`1`, :math:`\\log(x-a)`, :math:`\\log(b-x)`, :math:`\\log(x-a)\\log(b-x)`. The user specifies :math:`\\alpha`, :math:`\\beta` and the type of the function :math:`v`. A globally adaptive subdivision strategy is applied, with modified Clenshaw-Curtis integration on those subintervals which contain `a` or `b`. qawce compute :math:`\\int^b_a f(x) / (x-c)dx` where the integral must be interpreted as a Cauchy principal value integral, for user specified :math:`c` and :math:`f`. The strategy is globally adaptive. Modified Clenshaw-Curtis integration is used on those intervals containing the point :math:`x = c`. **Integration of Complex Function of a Real Variable** A complex valued function, :math:`f`, of a real variable can be written as :math:`f = g + ih`. Similarly, the integral of :math:`f` can be written as .. math:: \\int_a^b f(x) dx = \\int_a^b g(x) dx + i\\int_a^b h(x) dx assuming that the integrals of :math:`g` and :math:`h` exist over the interval :math:`[a,b]` [2]_. Therefore, ``quad`` integrates complex-valued functions by integrating the real and imaginary components separately. References ---------- .. [1] Piessens, Robert; de Doncker-Kapenga, Elise; Überhuber, Christoph W.; Kahaner, David (1983). QUADPACK: A subroutine package for automatic integration. Springer-Verlag. ISBN 978-3-540-12553-2. .. [2] McCullough, Thomas; Phillips, Keith (1973). Foundations of Analysis in the Complex Plane. Holt Rinehart Winston. ISBN 0-03-086370-8 Examples -------- Calculate :math:`\\int^4_0 x^2 dx` and compare with an analytic result >>> from scipy import integrate >>> import numpy as np >>> x2 = lambda x: x**2 >>> integrate.quad(x2, 0, 4) (21.333333333333332, 2.3684757858670003e-13) >>> print(4**3 / 3.) # analytical result 21.3333333333 Calculate :math:`\\int^\\infty_0 e^{-x} dx` >>> invexp = lambda x: np.exp(-x) >>> integrate.quad(invexp, 0, np.inf) (1.0, 5.842605999138044e-11) Calculate :math:`\\int^1_0 a x \\,dx` for :math:`a = 1, 3` >>> f = lambda x, a: a*x >>> y, err = integrate.quad(f, 0, 1, args=(1,)) >>> y 0.5 >>> y, err = integrate.quad(f, 0, 1, args=(3,)) >>> y 1.5 Calculate :math:`\\int^1_0 x^2 + y^2 dx` with ctypes, holding y parameter as 1:: testlib.c => double func(int n, double args[n