Special functions (scipy.special)#

Almost all of the functions below accept NumPy arrays as inputarguments as well as single numbers. This means they followbroadcasting and automatic array-looping rules. Technically,they areNumPy universal functions.Functions which do not accept NumPy arrays are marked by a warningin the section description.

See also

scipy.special.cython_special – Typed Cython versions of special functions

Error handling#

Errors are handled by returning NaNs or other appropriate values.Some of the special function routines can emit warnings or raiseexceptions when an error occurs. By default this is disabled, exceptfor memory allocation errors, which result in an exception being raised.To query and control the current error handling state the followingfunctions are provided.

geterr()

Get the current way of handling special-function errors.

seterr(**kwargs)

Set how special-function errors are handled.

errstate(**kwargs)

Context manager for special-function error handling.

SpecialFunctionWarning

Warning that can be emitted by special functions.

SpecialFunctionError

Exception that can be raised by special functions.

Available functions#

Airy functions#

airy(z[, out])

Airy functions and their derivatives.

airye(z[, out])

Exponentially scaled Airy functions and their derivatives.

ai_zeros(nt)

Computent zeros and values of the Airy function Ai and its derivative.

bi_zeros(nt)

Computent zeros and values of the Airy function Bi and its derivative.

itairy(x[, out])

Integrals of Airy functions

Elliptic functions and integrals#

ellipj(u, m[, out])

Jacobi elliptic functions

ellipk(m[, out])

Complete elliptic integral of the first kind.

ellipkm1(p[, out])

Complete elliptic integral of the first kind aroundm = 1

ellipkinc(phi, m[, out])

Incomplete elliptic integral of the first kind

ellipe(m[, out])

Complete elliptic integral of the second kind

ellipeinc(phi, m[, out])

Incomplete elliptic integral of the second kind

elliprc(x, y[, out])

Degenerate symmetric elliptic integral.

elliprd(x, y, z[, out])

Symmetric elliptic integral of the second kind.

elliprf(x, y, z[, out])

Completely-symmetric elliptic integral of the first kind.

elliprg(x, y, z[, out])

Completely-symmetric elliptic integral of the second kind.

elliprj(x, y, z, p[, out])

Symmetric elliptic integral of the third kind.

Bessel functions#

jv(v, z[, out])

Bessel function of the first kind of real order and complex argument.

jve(v, z[, out])

Exponentially scaled Bessel function of the first kind of orderv.

yn(n, x[, out])

Bessel function of the second kind of integer order and real argument.

yv(v, z[, out])

Bessel function of the second kind of real order and complex argument.

yve(v, z[, out])

Exponentially scaled Bessel function of the second kind of real order.

iv(v, z[, out])

Modified Bessel function of the first kind of real order.

ive(v, z[, out])

Exponentially scaled modified Bessel function of the first kind.

kn(n, x[, out])

Modified Bessel function of the second kind of integer ordern

kv(v, z[, out])

Modified Bessel function of the second kind of real orderv

kve(v, z[, out])

Exponentially scaled modified Bessel function of the second kind.

hankel1(v, z[, out])

Hankel function of the first kind

hankel1e(v, z[, out])

Exponentially scaled Hankel function of the first kind

hankel2(v, z[, out])

Hankel function of the second kind

hankel2e(v, z[, out])

Exponentially scaled Hankel function of the second kind

wright_bessel(a, b, x[, out])

Wright's generalized Bessel function.

log_wright_bessel(a, b, x[, out])

Natural logarithm of Wright's generalized Bessel function, seewright_bessel.

The following function does not accept NumPy arrays (it is not auniversal function):

lmbda(v, x)

Jahnke-Emden Lambda function, Lambdav(x).

Zeros of Bessel functions#

The following functions do not accept NumPy arrays (they are notuniversal functions):

jnjnp_zeros(nt)

Compute zeros of integer-order Bessel functions Jn and Jn'.

jnyn_zeros(n, nt)

Compute nt zeros of Bessel functions Jn(x), Jn'(x), Yn(x), and Yn'(x).

jn_zeros(n, nt)

Compute zeros of integer-order Bessel functions Jn.

jnp_zeros(n, nt)

Compute zeros of integer-order Bessel function derivatives Jn'.

yn_zeros(n, nt)

Compute zeros of integer-order Bessel function Yn(x).

ynp_zeros(n, nt)

Compute zeros of integer-order Bessel function derivatives Yn'(x).

y0_zeros(nt[, complex])

Compute nt zeros of Bessel function Y0(z), and derivative at each zero.

y1_zeros(nt[, complex])

Compute nt zeros of Bessel function Y1(z), and derivative at each zero.

y1p_zeros(nt[, complex])

Compute nt zeros of Bessel derivative Y1'(z), and value at each zero.

Faster versions of common Bessel functions#

j0(x[, out])

Bessel function of the first kind of order 0.

j1(x[, out])

Bessel function of the first kind of order 1.

y0(x[, out])

Bessel function of the second kind of order 0.

y1(x[, out])

Bessel function of the second kind of order 1.

i0(x[, out])

Modified Bessel function of order 0.

i0e(x[, out])

Exponentially scaled modified Bessel function of order 0.

i1(x[, out])

Modified Bessel function of order 1.

i1e(x[, out])

Exponentially scaled modified Bessel function of order 1.

k0(x[, out])

Modified Bessel function of the second kind of order 0,\(K_0\).

k0e(x[, out])

Exponentially scaled modified Bessel function K of order 0

k1(x[, out])

Modified Bessel function of the second kind of order 1,\(K_1(x)\).

k1e(x[, out])

Exponentially scaled modified Bessel function K of order 1

Integrals of Bessel functions#

itj0y0(x[, out])

Integrals of Bessel functions of the first kind of order 0.

it2j0y0(x[, out])

Integrals related to Bessel functions of the first kind of order 0.

iti0k0(x[, out])

Integrals of modified Bessel functions of order 0.

it2i0k0(x[, out])

Integrals related to modified Bessel functions of order 0.

besselpoly(a, lmb, nu[, out])

Weighted integral of the Bessel function of the first kind.

Derivatives of Bessel functions#

jvp(v, z[, n])

Compute derivatives of Bessel functions of the first kind.

yvp(v, z[, n])

Compute derivatives of Bessel functions of the second kind.

ivp(v, z[, n])

Compute derivatives of modified Bessel functions of the first kind.

kvp(v, z[, n])

Compute derivatives of real-order modified Bessel function Kv(z)

h1vp(v, z[, n])

Compute derivatives of Hankel function H1v(z) with respect toz.

h2vp(v, z[, n])

Compute derivatives of Hankel function H2v(z) with respect toz.

Spherical Bessel functions#

spherical_jn(n, z[, derivative])

Spherical Bessel function of the first kind or its derivative.

spherical_yn(n, z[, derivative])

Spherical Bessel function of the second kind or its derivative.

spherical_in(n, z[, derivative])

Modified spherical Bessel function of the first kind or its derivative.

spherical_kn(n, z[, derivative])

Modified spherical Bessel function of the second kind or its derivative.

Riccati-Bessel functions#

The following functions do not accept NumPy arrays (they are notuniversal functions):

riccati_jn(n, x)

Compute Riccati-Bessel function of the first kind and its derivative.

riccati_yn(n, x)

Compute Riccati-Bessel function of the second kind and its derivative.

Struve functions#

struve(v, x[, out])

Struve function.

modstruve(v, x[, out])

Modified Struve function.

itstruve0(x[, out])

Integral of the Struve function of order 0.

it2struve0(x[, out])

Integral related to the Struve function of order 0.

itmodstruve0(x[, out])

Integral of the modified Struve function of order 0.

Raw statistical functions#

See also

scipy.stats: Friendly versions of these functions.

Binomial distribution#

bdtr(k, n, p[, out])

Binomial distribution cumulative distribution function.

bdtrc(k, n, p[, out])

Binomial distribution survival function.

bdtri(k, n, y[, out])

Inverse function tobdtr with respect top.

bdtrik(y, n, p[, out])

Inverse function tobdtr with respect tok.

bdtrin(k, y, p[, out])

Inverse function tobdtr with respect ton.

Beta distribution#

btdtria(p, b, x[, out])

Inverse ofbetainc with respect toa.

btdtrib(a, p, x[, out])

Inverse ofbetainc with respect tob.

F distribution#

fdtr(dfn, dfd, x[, out])

F cumulative distribution function.

fdtrc(dfn, dfd, x[, out])

F survival function.

fdtri(dfn, dfd, p[, out])

Thep-th quantile of the F-distribution.

fdtridfd(dfn, p, x[, out])

Inverse tofdtr vs dfd

Gamma distribution#

gdtr(a, b, x[, out])

Gamma distribution cumulative distribution function.

gdtrc(a, b, x[, out])

Gamma distribution survival function.

gdtria(p, b, x[, out])

Inverse ofgdtr vs a.

gdtrib(a, p, x[, out])

Inverse ofgdtr vs b.

gdtrix(a, b, p[, out])

Inverse ofgdtr vs x.

Negative binomial distribution#

nbdtr(k, n, p[, out])

Negative binomial cumulative distribution function.

nbdtrc(k, n, p[, out])

Negative binomial survival function.

nbdtri(k, n, y[, out])

Returns the inverse with respect to the parameterp ofy=nbdtr(k,n,p), the negative binomial cumulative distribution function.

nbdtrik(y, n, p[, out])

Negative binomial percentile function.

nbdtrin(k, y, p[, out])

Inverse ofnbdtr vsn.

Noncentral F distribution#

ncfdtr(dfn, dfd, nc, f[, out])

Cumulative distribution function of the non-central F distribution.

ncfdtridfd(dfn, p, nc, f[, out])

Calculate degrees of freedom (denominator) for the noncentral F-distribution.

ncfdtridfn(p, dfd, nc, f[, out])

Calculate degrees of freedom (numerator) for the noncentral F-distribution.

ncfdtri(dfn, dfd, nc, p[, out])

Inverse with respect tof of the CDF of the non-central F distribution.

ncfdtrinc(dfn, dfd, p, f[, out])

Calculate non-centrality parameter for non-central F distribution.

Noncentral t distribution#

nctdtr(df, nc, t[, out])

Cumulative distribution function of the non-centralt distribution.

nctdtridf(p, nc, t[, out])

Calculate degrees of freedom for non-central t distribution.

nctdtrit(df, nc, p[, out])

Inverse cumulative distribution function of the non-central t distribution.

nctdtrinc(df, p, t[, out])

Calculate non-centrality parameter for non-central t distribution.

Normal distribution#

nrdtrimn(p, std, x[, out])

Calculate mean of normal distribution given other params.

nrdtrisd(mn, p, x[, out])

Calculate standard deviation of normal distribution given other params.

ndtr(x[, out])

Cumulative distribution of the standard normal distribution.

log_ndtr(x[, out])

Logarithm of Gaussian cumulative distribution function.

ndtri(y[, out])

Inverse ofndtr vs x

ndtri_exp(y[, out])

Inverse oflog_ndtr vs x.

Poisson distribution#

pdtr(k, m[, out])

Poisson cumulative distribution function.

pdtrc(k, m[, out])

Poisson survival function

pdtri(k, y[, out])

Inverse topdtr vs m

pdtrik(p, m[, out])

Inverse topdtr vsk.

Student t distribution#

stdtr(df, t[, out])

Student t distribution cumulative distribution function

stdtridf(p, t[, out])

Inverse ofstdtr vs df

stdtrit(df, p[, out])

Thep-th quantile of the student t distribution.

Chi square distribution#

chdtr(v, x[, out])

Chi square cumulative distribution function.

chdtrc(v, x[, out])

Chi square survival function.

chdtri(v, p[, out])

Inverse tochdtrc with respect tox.

chdtriv(p, x[, out])

Inverse tochdtr with respect tov.

Non-central chi square distribution#

chndtr(x, df, nc[, out])

Non-central chi square cumulative distribution function

chndtridf(x, p, nc[, out])

Inverse tochndtr vsdf

chndtrinc(x, df, p[, out])

Inverse tochndtr vsnc

chndtrix(p, df, nc[, out])

Inverse tochndtr vsx

Kolmogorov distribution#

smirnov(n, d[, out])

Kolmogorov-Smirnov complementary cumulative distribution function

smirnovi(n, p[, out])

Inverse tosmirnov

kolmogorov(y[, out])

Complementary cumulative distribution (Survival Function) function of Kolmogorov distribution.

kolmogi(p[, out])

Inverse Survival Function of Kolmogorov distribution

Box-Cox transformation#

boxcox(x, lmbda[, out])

Compute the Box-Cox transformation.

boxcox1p(x, lmbda[, out])

Compute the Box-Cox transformation of 1 +x.

inv_boxcox(y, lmbda[, out])

Compute the inverse of the Box-Cox transformation.

inv_boxcox1p(y, lmbda[, out])

Compute the inverse of the Box-Cox transformation.

Sigmoidal functions#

logit(x[, out])

Logit ufunc for ndarrays.

expit(x[, out])

Expit (a.k.a.

log_expit(x[, out])

Logarithm of the logistic sigmoid function.

Miscellaneous#

tklmbda(x, lmbda[, out])

Cumulative distribution function of the Tukey lambda distribution.

owens_t(h, a[, out])

Owen's T Function.

Information Theory functions#

entr(x[, out])

Elementwise function for computing entropy.

rel_entr(x, y[, out])

Elementwise function for computing relative entropy.

kl_div(x, y[, out])

Elementwise function for computing Kullback-Leibler divergence.

huber(delta, r[, out])

Huber loss function.

pseudo_huber(delta, r[, out])

Pseudo-Huber loss function.

Gamma and related functions#

gamma(z[, out])

gamma function.

gammaln(x[, out])

Logarithm of the absolute value of the gamma function.

loggamma(z[, out])

Principal branch of the logarithm of the gamma function.

gammasgn(x[, out])

Sign of the gamma function.

gammainc(a, x[, out])

Regularized lower incomplete gamma function.

gammaincinv(a, y[, out])

Inverse to the regularized lower incomplete gamma function.

gammaincc(a, x[, out])

Regularized upper incomplete gamma function.

gammainccinv(a, y[, out])

Inverse of the regularized upper incomplete gamma function.

beta(a, b[, out])

Beta function.

betaln(a, b[, out])

Natural logarithm of absolute value of beta function.

betainc(a, b, x[, out])

Regularized incomplete beta function.

betaincc(a, b, x[, out])

Complement of the regularized incomplete beta function.

betaincinv(a, b, y[, out])

Inverse of the regularized incomplete beta function.

betainccinv(a, b, y[, out])

Inverse of the complemented regularized incomplete beta function.

psi(z[, out])

The digamma function.

rgamma(z[, out])

Reciprocal of the gamma function.

polygamma(n, x)

Polygamma functions.

multigammaln(a, d)

Returns the log of multivariate gamma, also sometimes called the generalized gamma.

digamma(z[, out])

The digamma function.

poch(z, m[, out])

Pochhammer symbol.

Error function and Fresnel integrals#

erf(z[, out])

Returns the error function of complex argument.

erfc(x[, out])

Complementary error function,1-erf(x).

erfcx(x[, out])

Scaled complementary error function,exp(x**2)*erfc(x).

erfi(z[, out])

Imaginary error function,-ierf(iz).

erfinv(y[, out])

Inverse of the error function.

erfcinv(y[, out])

Inverse of the complementary error function.

wofz(z[, out])

Faddeeva function

dawsn(x[, out])

Dawson's integral.

fresnel(z[, out])

Fresnel integrals.

fresnel_zeros(nt)

Compute nt complex zeros of sine and cosine Fresnel integrals S(z) and C(z).

modfresnelp(x[, out])

Modified Fresnel positive integrals

modfresnelm(x[, out])

Modified Fresnel negative integrals

voigt_profile(x, sigma, gamma[, out])

Voigt profile.

The following functions do not accept NumPy arrays (they are notuniversal functions):

erf_zeros(nt)

Compute the first nt zero in the first quadrant, ordered by absolute value.

fresnelc_zeros(nt)

Compute nt complex zeros of cosine Fresnel integral C(z).

fresnels_zeros(nt)

Compute nt complex zeros of sine Fresnel integral S(z).

Legendre functions#

legendre_p(n, z, *[, diff_n])

Legendre polynomial of the first kind.

legendre_p_all(n, z, *[, diff_n])

All Legendre polynomials of the first kind up to the specified degreen and all derivatives up to orderdiff_n.

assoc_legendre_p(n, m, z, *[, branch_cut, ...])

Associated Legendre polynomial of the first kind.

assoc_legendre_p_all(n, m, z, *[, ...])

All associated Legendre polynomials of the first kind up to the specified degreen, orderm, and all derivatives up to orderdiff_n.

sph_legendre_p(n, m, theta, *[, diff_n])

Spherical Legendre polynomial of the first kind.

sph_legendre_p_all(n, m, theta, *[, diff_n])

All spherical Legendre polynomials of the first kind up to the specified degreen, orderm, and all derivatives up to orderdiff_n.

sph_harm_y(n, m, theta, phi, *[, diff_n])

Spherical harmonics.

sph_harm_y_all(n, m, theta, phi, *[, diff_n])

All spherical harmonics up to the specified degreen, orderm, and all derivatives up to orderdiff_n.

The following functions are in the process of being deprecated in favor of the above,which provide a more flexible and consistent interface.

lpmv(m, v, x[, out])

Associated Legendre function of integer order and real degree.

lqn(n, z)

Legendre function of the second kind.

lqmn(m, n, z)

Sequence of associated Legendre functions of the second kind.

Ellipsoidal harmonics#

ellip_harm(h2, k2, n, p, s[, signm, signn])

Ellipsoidal harmonic functions E^p_n(l)

ellip_harm_2(h2, k2, n, p, s)

Ellipsoidal harmonic functions F^p_n(l)

ellip_normal(h2, k2, n, p)

Ellipsoidal harmonic normalization constants gamma^p_n

Orthogonal polynomials#

The following functions evaluate values of orthogonal polynomials:

assoc_laguerre(x, n[, k])

Compute the generalized (associated) Laguerre polynomial of degree n and order k.

eval_legendre(n, x[, out])

Evaluate Legendre polynomial at a point.

eval_chebyt(n, x[, out])

Evaluate Chebyshev polynomial of the first kind at a point.

eval_chebyu(n, x[, out])

Evaluate Chebyshev polynomial of the second kind at a point.

eval_chebyc(n, x[, out])

Evaluate Chebyshev polynomial of the first kind on [-2, 2] at a point.

eval_chebys(n, x[, out])

Evaluate Chebyshev polynomial of the second kind on [-2, 2] at a point.

eval_jacobi(n, alpha, beta, x[, out])

Evaluate Jacobi polynomial at a point.

eval_laguerre(n, x[, out])

Evaluate Laguerre polynomial at a point.

eval_genlaguerre(n, alpha, x[, out])

Evaluate generalized Laguerre polynomial at a point.

eval_hermite(n, x[, out])

Evaluate physicist's Hermite polynomial at a point.

eval_hermitenorm(n, x[, out])

Evaluate probabilist's (normalized) Hermite polynomial at a point.

eval_gegenbauer(n, alpha, x[, out])

Evaluate Gegenbauer polynomial at a point.

eval_sh_legendre(n, x[, out])

Evaluate shifted Legendre polynomial at a point.

eval_sh_chebyt(n, x[, out])

Evaluate shifted Chebyshev polynomial of the first kind at a point.

eval_sh_chebyu(n, x[, out])

Evaluate shifted Chebyshev polynomial of the second kind at a point.

eval_sh_jacobi(n, p, q, x[, out])

Evaluate shifted Jacobi polynomial at a point.

The following functions compute roots and quadrature weights fororthogonal polynomials:

roots_legendre(n[, mu])

Gauss-Legendre quadrature.

roots_chebyt(n[, mu])

Gauss-Chebyshev (first kind) quadrature.

roots_chebyu(n[, mu])

Gauss-Chebyshev (second kind) quadrature.

roots_chebyc(n[, mu])

Gauss-Chebyshev (first kind) quadrature.

roots_chebys(n[, mu])

Gauss-Chebyshev (second kind) quadrature.

roots_jacobi(n, alpha, beta[, mu])

Gauss-Jacobi quadrature.

roots_laguerre(n[, mu])

Gauss-Laguerre quadrature.

roots_genlaguerre(n, alpha[, mu])

Gauss-generalized Laguerre quadrature.

roots_hermite(n[, mu])

Gauss-Hermite (physicist's) quadrature.

roots_hermitenorm(n[, mu])

Gauss-Hermite (statistician's) quadrature.

roots_gegenbauer(n, alpha[, mu])

Gauss-Gegenbauer quadrature.

roots_sh_legendre(n[, mu])

Gauss-Legendre (shifted) quadrature.

roots_sh_chebyt(n[, mu])

Gauss-Chebyshev (first kind, shifted) quadrature.

roots_sh_chebyu(n[, mu])

Gauss-Chebyshev (second kind, shifted) quadrature.

roots_sh_jacobi(n, p1, q1[, mu])

Gauss-Jacobi (shifted) quadrature.

The functions below, in turn, return the polynomial coefficients inorthopoly1d objects, which function similarly asnumpy.poly1d.Theorthopoly1d class also has an attributeweights, which returnsthe roots, weights, and total weights for the appropriate form of Gaussianquadrature. These are returned in annx3 array with roots in the firstcolumn, weights in the second column, and total weights in the final column.Note thatorthopoly1d objects are converted topoly1d when doingarithmetic, and lose information of the original orthogonal polynomial.

legendre(n[, monic])

Legendre polynomial.

chebyt(n[, monic])

Chebyshev polynomial of the first kind.

chebyu(n[, monic])

Chebyshev polynomial of the second kind.

chebyc(n[, monic])

Chebyshev polynomial of the first kind on\([-2, 2]\).

chebys(n[, monic])

Chebyshev polynomial of the second kind on\([-2, 2]\).

jacobi(n, alpha, beta[, monic])

Jacobi polynomial.

laguerre(n[, monic])

Laguerre polynomial.

genlaguerre(n, alpha[, monic])

Generalized (associated) Laguerre polynomial.

hermite(n[, monic])

Physicist's Hermite polynomial.

hermitenorm(n[, monic])

Normalized (probabilist's) Hermite polynomial.

gegenbauer(n, alpha[, monic])

Gegenbauer (ultraspherical) polynomial.

sh_legendre(n[, monic])

Shifted Legendre polynomial.

sh_chebyt(n[, monic])

Shifted Chebyshev polynomial of the first kind.

sh_chebyu(n[, monic])

Shifted Chebyshev polynomial of the second kind.

sh_jacobi(n, p, q[, monic])

Shifted Jacobi polynomial.

Warning

Computing values of high-order polynomials (aroundorder>20) usingpolynomial coefficients is numerically unstable. To evaluate polynomialvalues, theeval_* functions should be used instead.

Hypergeometric functions#

hyp2f1(a, b, c, z[, out])

Gauss hypergeometric function 2F1(a, b; c; z)

hyp1f1(a, b, x[, out])

Confluent hypergeometric function 1F1.

hyperu(a, b, x[, out])

Confluent hypergeometric function U

hyp0f1(v, z[, out])

Confluent hypergeometric limit function 0F1.

Parabolic cylinder functions#

pbdv(v, x[, out])

Parabolic cylinder function D

pbvv(v, x[, out])

Parabolic cylinder function V

pbwa(a, x[, out])

Parabolic cylinder function W.

The following functions do not accept NumPy arrays (they are notuniversal functions):

pbdv_seq(v, x)

Parabolic cylinder functions Dv(x) and derivatives.

pbvv_seq(v, x)

Parabolic cylinder functions Vv(x) and derivatives.

pbdn_seq(n, z)

Parabolic cylinder functions Dn(z) and derivatives.

Mathieu and related functions#

mathieu_a(m, q[, out])

Characteristic value of even Mathieu functions

mathieu_b(m, q[, out])

Characteristic value of odd Mathieu functions

The following functions do not accept NumPy arrays (they are notuniversal functions):

mathieu_even_coef(m, q)

Fourier coefficients for even Mathieu and modified Mathieu functions.

mathieu_odd_coef(m, q)

Fourier coefficients for odd Mathieu and modified Mathieu functions.

The following return both function and first derivative:

mathieu_cem(m, q, x[, out])

Even Mathieu function and its derivative

mathieu_sem(m, q, x[, out])

Odd Mathieu function and its derivative

mathieu_modcem1(m, q, x[, out])

Even modified Mathieu function of the first kind and its derivative

mathieu_modcem2(m, q, x[, out])

Even modified Mathieu function of the second kind and its derivative

mathieu_modsem1(m, q, x[, out])

Odd modified Mathieu function of the first kind and its derivative

mathieu_modsem2(m, q, x[, out])

Odd modified Mathieu function of the second kind and its derivative

Spheroidal wave functions#

pro_ang1(m, n, c, x[, out])

Prolate spheroidal angular function of the first kind and its derivative

pro_rad1(m, n, c, x[, out])

Prolate spheroidal radial function of the first kind and its derivative

pro_rad2(m, n, c, x[, out])

Prolate spheroidal radial function of the second kind and its derivative

obl_ang1(m, n, c, x[, out])

Oblate spheroidal angular function of the first kind and its derivative

obl_rad1(m, n, c, x[, out])

Oblate spheroidal radial function of the first kind and its derivative

obl_rad2(m, n, c, x[, out])

Oblate spheroidal radial function of the second kind and its derivative.

pro_cv(m, n, c[, out])

Characteristic value of prolate spheroidal function

obl_cv(m, n, c[, out])

Characteristic value of oblate spheroidal function

pro_cv_seq(m, n, c)

Characteristic values for prolate spheroidal wave functions.

obl_cv_seq(m, n, c)

Characteristic values for oblate spheroidal wave functions.

The following functions require pre-computed characteristic value:

pro_ang1_cv(m, n, c, cv, x[, out])

Prolate spheroidal angular function pro_ang1 for precomputed characteristic value

pro_rad1_cv(m, n, c, cv, x[, out])

Prolate spheroidal radial function pro_rad1 for precomputed characteristic value

pro_rad2_cv(m, n, c, cv, x[, out])

Prolate spheroidal radial function pro_rad2 for precomputed characteristic value

obl_ang1_cv(m, n, c, cv, x[, out])

Oblate spheroidal angular function obl_ang1 for precomputed characteristic value

obl_rad1_cv(m, n, c, cv, x[, out])

Oblate spheroidal radial function obl_rad1 for precomputed characteristic value

obl_rad2_cv(m, n, c, cv, x[, out])

Oblate spheroidal radial function obl_rad2 for precomputed characteristic value

Kelvin functions#

kelvin(x[, out])

Kelvin functions as complex numbers

kelvin_zeros(nt)

Compute nt zeros of all Kelvin functions.

ber(x[, out])

Kelvin function ber.

bei(x[, out])

Kelvin function bei.

berp(x[, out])

Derivative of the Kelvin function ber.

beip(x[, out])

Derivative of the Kelvin function bei.

ker(x[, out])

Kelvin function ker.

kei(x[, out])

Kelvin function kei.

kerp(x[, out])

Derivative of the Kelvin function ker.

keip(x[, out])

Derivative of the Kelvin function kei.

The following functions do not accept NumPy arrays (they are notuniversal functions):

ber_zeros(nt)

Compute nt zeros of the Kelvin function ber.

bei_zeros(nt)

Compute nt zeros of the Kelvin function bei.

berp_zeros(nt)

Compute nt zeros of the derivative of the Kelvin function ber.

beip_zeros(nt)

Compute nt zeros of the derivative of the Kelvin function bei.

ker_zeros(nt)

Compute nt zeros of the Kelvin function ker.

kei_zeros(nt)

Compute nt zeros of the Kelvin function kei.

kerp_zeros(nt)

Compute nt zeros of the derivative of the Kelvin function ker.

keip_zeros(nt)

Compute nt zeros of the derivative of the Kelvin function kei.

Combinatorics#

comb(N, k, *[, exact, repetition])

The number of combinations of N things taken k at a time.

perm(N, k[, exact])

Permutations of N things taken k at a time, i.e., k-permutations of N.

stirling2(N, K, *[, exact])

Generate Stirling number(s) of the second kind.

Lambert W and related functions#

lambertw(z[, k, tol])

Lambert W function.

wrightomega(z[, out])

Wright Omega function.

Other special functions#

agm(a, b[, out])

Compute the arithmetic-geometric mean ofa andb.

bernoulli(n)

Bernoulli numbers B0..Bn (inclusive).

binom(x, y[, out])

Binomial coefficient considered as a function of two real variables.

diric(x, n)

Periodic sinc function, also called the Dirichlet kernel.

euler(n)

Euler numbers E(0), E(1), ..., E(n).

expn(n, x[, out])

Generalized exponential integral En.

exp1(z[, out])

Exponential integral E1.

expi(x[, out])

Exponential integral Ei.

factorial(n[, exact, extend])

The factorial of a number or array of numbers.

factorial2(n[, exact, extend])

Double factorial.

factorialk(n, k[, exact, extend])

Multifactorial of n of order k, n(!!...!).

shichi(x[, out])

Hyperbolic sine and cosine integrals.

sici(x[, out])

Sine and cosine integrals.

softmax(x[, axis])

Compute the softmax function.

log_softmax(x[, axis])

Compute the logarithm of the softmax function.

spence(z[, out])

Spence's function, also known as the dilogarithm.

zeta(x[, q, out])

Riemann or Hurwitz zeta function.

zetac(x[, out])

Riemann zeta function minus 1.

softplus(x, **kwargs)

Compute the softplus function element-wise.

Convenience functions#

cbrt(x[, out])

Element-wise cube root ofx.

exp10(x[, out])

Compute10**x element-wise.

exp2(x[, out])

Compute2**x element-wise.

radian(d, m, s[, out])

Convert from degrees to radians.

cosdg(x[, out])

Cosine of the anglex given in degrees.

sindg(x[, out])

Sine of the anglex given in degrees.

tandg(x[, out])

Tangent of anglex given in degrees.

cotdg(x[, out])

Cotangent of the anglex given in degrees.

log1p(x[, out])

Calculates log(1 + x) for use whenx is near zero.

expm1(x[, out])

Computeexp(x)-1.

cosm1(x[, out])

cos(x) - 1 for use whenx is near zero.

powm1(x, y[, out])

Computesx**y-1.

round(x[, out])

Round to the nearest integer.

xlogy(x, y[, out])

Computex*log(y) so that the result is 0 ifx=0.

xlog1py(x, y[, out])

Computex*log1p(y) so that the result is 0 ifx=0.

logsumexp(a[, axis, b, keepdims, return_sign])

Compute the log of the sum of exponentials of input elements.

exprel(x[, out])

Relative error exponential,(exp(x)-1)/x.

sinc(x)

Return the normalized sinc function.

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