scipy API reference
400 public APIs from scipy (scipy/scipy) — 143 classes, 166 functions, 91 methods. Signatures extracted by static analysis of the actual source.
Repository: scipy/scipy
| Kind | Count |
|---|---|
| Classes | 143 |
| Functions | 166 |
| Methods | 91 |
API list
func
.spin.cmds.bench(ctx, tests, submodule, compare, verbose, quick, commits, array_api_backend, dry_run, build, build_dir, *args, **kwargs)🔧 Run benchmarks.
func
.spin.cmds.notes(ctx_obj, version_args)Release notes and log generation.
func
.spin.cmds.refguide_check(ctx, build_dir, *args, **kwargs)🔧 Run refguide check.
class
scipy._external.packaging_version.src.version.InvalidVersionRaised when a version string is not a valid version.
class
scipy._external.packaging_version.src.version.VersionThis class abstracts handling of a project's versions.
method
scipy._external.packaging_version.src.version.Version.base_version() -> strThe "base version" of the version.
method
scipy._external.packaging_version.src.version.Version.dev() -> int | NoneThe development number of the version.
method
scipy._external.packaging_version.src.version.Version.epoch() -> intThe epoch of the version.
method
scipy._external.packaging_version.src.version.Version.is_devrelease() -> boolWhether this version is a development release.
method
scipy._external.packaging_version.src.version.Version.is_postrelease() -> boolWhether this version is a post-release.
method
scipy._external.packaging_version.src.version.Version.is_prerelease() -> boolWhether this version is a pre-release.
method
scipy._external.packaging_version.src.version.Version.local() -> str | NoneThe local version segment of the version.
method
scipy._external.packaging_version.src.version.Version.post() -> int | NoneThe post-release number of the version.
method
scipy._external.packaging_version.src.version.Version.pre() -> tuple[str, int] | NoneThe pre-release segment of the version.
method
scipy._external.packaging_version.src.version.Version.public() -> strThe public portion of the version.
func
scipy._external.packaging_version.src.version.parse(version:str) -> VersionParse the given version string.
func
scipy._lib._array_api.get_native_namespace_name(xp:ModuleType) -> strReturn name for native namespace (without array_api_compat prefix).
func
scipy._lib._array_api.xp_compat_namespace(xp:ModuleType | None) -> ModuleTypeReturn the array-api-compat(ible) namespace corresponding to `xp`.
func
scipy._lib._array_api.xp_copy(x:Array, *xp:ModuleType | None=None) -> ArrayCopies an array.
func
scipy._lib._array_api_docs_tables.calculate_table_statistics(flat_table:list[dict[str, str]]) -> dict[str, dict[str, int]]Get counts of what is supported per module.
func
scipy._lib._array_api_override.array_namespace(*sparse_ok=False, *arrays:Array) -> ModuleTypeGet the array API compatible namespace for the arrays xs.
class
scipy._lib._ccallback.LowLevelCallableLow-level callback function.
func
scipy._lib._docscrape.NumpyDocString.parse_item_name(text)Match ':role:`name`' or 'name'.
class
scipy._lib._docscrape.ReaderA line-based string reader.
func
scipy._lib._docscrape.dedent_lines(lines)Deindent a list of lines maximally
func
scipy._lib._gcutils.set_gc_state(state)Set status of garbage collector
func
scipy._lib._sparse.issparse(x)Is `x` either sparse array or sparse matrix type?
class
scipy._lib._testutils.FPUModeChangeWarningWarning about FPU mode change
func
scipy._lib._util.broadcastable(shape_a:tuple[int, ...], shape_b:tuple[int, ...]) -> boolCheck if two shapes are broadcastable.
class
scipy._lib.doccer.DecoratorA decorator of a function.
func
scipy._lib.doccer.docformat(docstring:str, docdict:Mapping[str, str] | None=None) -> strFill a function docstring from variables in dictionary.
func
scipy._lib.doccer.filldoc(docdict:Mapping[str, str], unindent_params:bool=True) -> DecoratorReturn docstring decorator using docdict variable dictionary.
func
scipy._lib.doccer.unindent_dict(docdict:Mapping[str, str]) -> dict[str, str]Unindent all strings in a docdict.
func
scipy._lib.doccer.unindent_string(docstring:str) -> strSet docstring to minimum indent for all lines, including first.
class
scipy.cluster.hierarchy._hierarchy_impl.ClusterNodeA tree node class for representing a cluster.
class
scipy.cluster.hierarchy._hierarchy_impl.ClusterWarningA ``UserWarning`` raised during clustering.
func
scipy.cluster.hierarchy._hierarchy_impl.centroid(y)Perform centroid/UPGMC linkage.
func
scipy.cluster.hierarchy._hierarchy_impl.leaves_list(Z)Return a list of leaf node ids.
func
scipy.cluster.hierarchy._hierarchy_impl.median(y)Perform median/WPGMC linkage.
class
scipy.cluster.vq._vq_impl.ClusterErrorAn ``Exception`` raised during clustering.
class
scipy.constants._codata.ConstantWarningAccessing a constant no longer in current CODATA data set.
func
scipy.constants._codata.find(sub:str | None=None, disp:bool=False) -> AnyReturn list of physical_constant keys containing a given string.
func
scipy.constants._codata.precision(key:str) -> floatRelative precision in physical_constants indexed by key.
func
scipy.constants._codata.unit(key:str) -> strUnit in physical_constants indexed by key.
func
scipy.constants._codata.value(key:str) -> floatValue in physical_constants indexed by key.
func
scipy.constants._constants.lambda2nu(lambda_:'npt.ArrayLike') -> AnyConvert wavelength to optical frequency.
func
scipy.constants._constants.nu2lambda(nu:'npt.ArrayLike') -> AnyConvert optical frequency to wavelength.
func
scipy.fft._backend.register_backend(backend)Register a backend for permanent use.
func
scipy.fft._backend.set_global_backend(backend, coerce=False, only=False, try_last=False)Sets the global fft backend.
class
scipy.fft._debug_backends.EchoBackendBackend that just prints the __ua_function__ arguments
class
scipy.fft._debug_backends.NumPyBackendBackend that uses numpy.fft
func
scipy.fft._fftlog.fht(a, dln, mu, offset=0.0, bias=0.0)Compute the fast Hankel transform.
func
scipy.fft._helper.ifftshift(x, axes=None)The inverse of `fftshift`.
func
scipy.fftpack._basic.fft2(x, shape=None, axes=(-2, -1), overwrite_x=False)2-D discrete Fourier transform.
func
scipy.integrate._bvp.collocation_fun(fun, y, p, x, h)Evaluate collocation residuals.
func
scipy.integrate._bvp.modify_mesh(x, insert_1, insert_2)Insert nodes into a mesh.
class
scipy.integrate._ivp.base.ConstantDenseOutputConstant value interpolator.
class
scipy.integrate._ivp.base.DenseOutputBase class for local interpolant over step made by an ODE solver.
class
scipy.integrate._ivp.base.OdeSolverBase class for ODE solvers.
method
scipy.integrate._ivp.base.OdeSolver.step()Perform one integration step.
class
scipy.integrate._ivp.bdf.BDFImplicit method based on backward-differentiation formulas.
class
scipy.integrate._ivp.common.OdeSolutionContinuous ODE solution.
func
scipy.integrate._ivp.common.norm(x)Compute RMS norm.
func
scipy.integrate._ivp.common.validate_tol(rtol, atol, n)Validate tolerance values.
class
scipy.integrate._ivp.radau.RadauImplicit Runge-Kutta method of Radau IIA family of order 5.
class
scipy.integrate._ivp.rk.DOP853Explicit Runge-Kutta method of order 8.
class
scipy.integrate._ivp.rk.RK23Explicit Runge-Kutta method of order 3(2).
class
scipy.integrate._ivp.rk.RK45Explicit Runge-Kutta method of order 5(4).
class
scipy.integrate._ivp.rk.RungeKuttaBase class for explicit Runge-Kutta methods.
func
scipy.integrate._ivp.rk.rk_step(fun, t, y, f, h, A, B, C, K)Perform a single Runge-Kutta step.
func
scipy.integrate._lebedev.lebedev_rule(n)Lebedev quadrature.
class
scipy.integrate._ode.complex_odeA wrapper of ode for complex systems.
method
scipy.integrate._ode.complex_ode.set_initial_value(y, t=0.0)Set initial conditions y(t) = y.
method
scipy.integrate._ode.complex_ode.set_integrator(name, **integrator_params)Set integrator by name.
class
scipy.integrate._ode.odeA generic interface class to numeric integrators.
method
scipy.integrate._ode.ode.set_initial_value(y, t=0.0)Set initial conditions y(t) = y.
method
scipy.integrate._ode.ode.set_integrator(name, **integrator_params)Set integrator by name.
method
scipy.integrate._ode.ode.successful()Check if integration was successful.
class
scipy.integrate._odepack_py.ODEintWarningWarning raised during the execution of `odeint`.
class
scipy.integrate._quad_vec.DoubleInfiniteFuncArgument transform from (-oo, oo) to (-1, 1)
class
scipy.integrate._quad_vec.SemiInfiniteFuncArgument transform from (start, +-oo) to (0, 1)
class
scipy.integrate._quadpack_py.IntegrationWarningWarning on issues during integration.
func
scipy.integrate._quadpack_py.dblquad(func, a, b, gfun, hfun, args=(), epsabs=1.49e-08, epsrel=1.49e-08)Compute a double integral.
class
scipy.integrate._rules._base.RuleBase class for numerical integration algorithms (cubatures).
class
scipy.integrate._rules._gauss_kronrod.GaussKronrodQuadratureGauss-Kronrod quadrature.
class
scipy.integrate._rules._gauss_legendre.GaussLegendreQuadratureGauss-Legendre quadrature.
class
scipy.integrate._rules._genz_malik.GenzMalikCubatureGenz-Malik cubature.
class
scipy.interpolate._bary_rational.AAAAAA real or complex rational approximation.
class
scipy.interpolate._bsplines.BSplineUnivariate spline in the B-spline basis.
class
scipy.interpolate._cubic.Akima1DInterpolatorAkima "visually pleasing" interpolator (C1 smooth).
class
scipy.interpolate._cubic.CubicSplinePiecewise cubic interpolator to fit values (C2 smooth).
class
scipy.interpolate._cubic.PchipInterpolatorPCHIP shape-preserving interpolator (C1 smooth).
class
scipy.interpolate._fitpack2.BivariateSplineBase class for bivariate splines.
method
scipy.interpolate._fitpack2.BivariateSpline.ev(xi, yi, dx=0, dy=0)Evaluate the spline at points.
class
scipy.interpolate._fitpack2.LSQBivariateSplineWeighted least-squares bivariate spline approximation.
class
scipy.interpolate._fitpack2.LSQUnivariateSpline1-D spline with explicit internal knots.
class
scipy.interpolate._fitpack2.RectBivariateSplineBivariate spline approximation over a rectangular mesh.
class
scipy.interpolate._fitpack2.SmoothBivariateSplineSmooth bivariate spline approximation.
class
scipy.interpolate._fitpack2.UnivariateSpline1-D smoothing spline fit to a given set of data points.
method
scipy.interpolate._fitpack2.UnivariateSpline.get_coeffs()Return spline coefficients.
method
scipy.interpolate._fitpack2.UnivariateSpline.roots()Return the zeros of the spline.
func
scipy.interpolate._fitpack_py.insert(x, tck, m=1, per=0)Insert knots into a B-spline.
func
scipy.interpolate._fitpack_py.sproot(tck, mest=10)Find the roots of a cubic B-spline.
class
scipy.interpolate._fitpack_repro.FThe r.h.s.
class
scipy.interpolate._fitpack_repro.FperiodicFit a smooth periodic B-spline curve to given data points.
func
scipy.interpolate._fitpack_repro.add_knot(x, t, k, residuals, periodic=False)Add a new knot.
class
scipy.interpolate._interpolate.BPolyPiecewise polynomial in the Bernstein basis.
class
scipy.interpolate._interpolate.NdPPolyPiecewise tensor product polynomial.
class
scipy.interpolate._interpolate.PPolyPiecewise polynomial in the power basis.
class
scipy.interpolate._interpolate.interp1dInterpolate a 1-D function (legacy).
method
scipy.interpolate._interpolate.interp1d.fill_value()The fill value.
class
scipy.interpolate._ndbspline.NdBSplineTensor product spline object.
class
scipy.interpolate._ndgriddata.NearestNDInterpolatorNearest-neighbor interpolator in N > 1 dimensions.
class
scipy.interpolate._polyint.KroghInterpolatorKrogh interpolator (C∞ smooth).
class
scipy.interpolate._rbfinterp.RBFInterpolatorRadial basis function interpolator in N ≥ 1 dimensions.
class
scipy.io._fortran.FortranEOFErrorIndicates that the file ended properly.
method
scipy.io._fortran.FortranFile.close()Closes the file.
class
scipy.io._fortran.FortranFormattingErrorIndicates that the file ended mid-record.
class
scipy.io._harwell_boeing._fortran_format_parser.FortranFormatParserParser for Fortran format strings.
class
scipy.io._harwell_boeing.hb.HBMatrixTypeClass to hold the matrix type.
func
scipy.io._harwell_boeing.hb.hb_read(path_or_open_file, *spmatrix=_NoValue)Read HB-format file.
func
scipy.io._harwell_boeing.hb.hb_write(path_or_open_file, m, hb_info=None)Write HB-format file.
class
scipy.io._idl.ObjectPointerClass used to define object pointers
class
scipy.io._idl.PointerClass used to define pointers
func
scipy.io._idl.readsav(file_name, idict=None, python_dict=False, uncompressed_file_name=None, verbose=False)Read an IDL .sav file.
class
scipy.io._netcdf.netcdf_fileA file object for NetCDF data.
method
scipy.io._netcdf.netcdf_file.close()Closes the NetCDF file.
class
scipy.io._netcdf.netcdf_variableA data object for netcdf files.
method
scipy.io._netcdf.netcdf_variable.itemsize()Return the itemsize of the variable.
method
scipy.io._netcdf.netcdf_variable.typecode()Return the typecode of the variable.
class
scipy.io.arff._arffread.ArffErrorBase exception for errors when reading ARFF files.
method
scipy.io.arff._arffread.Attribute.parse_data(data_str)Parse a value of this type.
class
scipy.io.arff._arffread.MetaDataSmall container to keep useful information on an ARFF dataset.
method
scipy.io.arff._arffread.MetaData.names()Return the list of attribute names.
method
scipy.io.arff._arffread.MetaData.types()Return the list of attribute types.
class
scipy.io.arff._arffread.ParseArffErrorException for syntax and parsing errors in ARFF files.
func
scipy.io.arff._arffread.loadarff(f)Read an arff file.
func
scipy.io.arff._arffread.read_header(ofile)Read the header of the iterable ofile.
func
scipy.io.matlab._mio.loadmat(file_name, mdict=None, appendmat=True, *spmatrix=_NoValue, **kwargs)Load MATLAB file.
func
scipy.io.matlab._mio.whosmat(file_name, appendmat=True, **kwargs)List variables inside a MATLAB file.
class
scipy.io.matlab._mio4.MatFile4ReaderReader for Mat4 files
method
scipy.io.matlab._mio4.MatFile4Reader.list_variables()list variables from stream
class
scipy.io.matlab._mio4.MatFile4WriterClass for writing matlab 4 format files
class
scipy.io.matlab._mio4.VarReader4Class to read matlab 4 variables
method
scipy.io.matlab._mio4.VarReader4.read_header()Read and return header for variable
class
scipy.io.matlab._mio5.EmptyStructMarkerClass to indicate presence of empty matlab struct on output
class
scipy.io.matlab._mio5.MatFile5WriterClass for writing mat5 files
class
scipy.io.matlab._mio5.VarWriter5Generic matlab matrix writing class
method
scipy.io.matlab._mio5.VarWriter5.write_element(arr, mdtype=None)write tag and data
method
scipy.io.matlab._mio5.VarWriter5.write_sparse(arr)Sparse matrices are 2D
class
scipy.io.matlab._mio5_params.MatlabFunctionSubclass for a MATLAB function.
class
scipy.io.matlab._mio5_params.MatlabObjectSubclass of ndarray to signal this is a matlab object.
class
scipy.io.matlab._mio5_params.MatlabOpaqueSubclass for a MATLAB opaque matrix.
class
scipy.io.matlab._mio5_params.mat_structPlaceholder for holding read data from structs.
class
scipy.io.matlab._miobase.MatReadErrorException indicating a read issue.
class
scipy.io.matlab._miobase.MatReadWarningWarning class for read issues.
class
scipy.io.matlab._miobase.MatVarReaderAbstract class defining required interface for var readers
method
scipy.io.matlab._miobase.MatVarReader.array_from_header(header)Reads array given header
method
scipy.io.matlab._miobase.MatVarReader.read_header()Returns header
class
scipy.io.matlab._miobase.MatWriteErrorException indicating a write issue.
class
scipy.io.matlab._miobase.MatWriteWarningWarning class for write issues.
func
scipy.io.matlab._miobase.arr_to_chars(arr)Convert string array to char array
func
scipy.io.wavfile.read(filename, mmap=False)Open a WAV file.
func
scipy.io.wavfile.write(filename, rate, data)Write a NumPy array as a WAV file.
func
scipy.linalg._basic.det(a, overwrite_a=False, check_finite=True)Compute the determinant of a matrix.
func
scipy.linalg._decomp_polar.polar(a, side='right')Compute the polar decomposition.
func
scipy.linalg._matfuncs.coshm(A)Compute the hyperbolic matrix cosine.
func
scipy.linalg._matfuncs.cosm(A)Compute the matrix cosine.
func
scipy.linalg._matfuncs.expm(A)Compute the matrix exponential of an array.
func
scipy.linalg._matfuncs.khatri_rao(a, b)Khatri-Rao product of two matrices.
func
scipy.linalg._matfuncs.logm(A)Compute matrix logarithm.
func
scipy.linalg._matfuncs.signm(A)Matrix sign function.
func
scipy.linalg._matfuncs.sinhm(A)Compute the hyperbolic matrix sine.
func
scipy.linalg._matfuncs.sinm(A)Compute the matrix sine.
func
scipy.linalg._matfuncs.sqrtm(A)Compute, if exists, the matrix square root.
func
scipy.linalg._matfuncs.tanhm(A)Compute the hyperbolic matrix tangent.
func
scipy.linalg._matfuncs.tanm(A)Compute the matrix tangent.
func
scipy.linalg._misc.norm(a, ord=None, axis=None, keepdims=False, check_finite=True)Matrix or vector norm.
func
scipy.linalg._special_matrices.circulant(c)Construct a circulant matrix.
func
scipy.linalg._special_matrices.companion(a)Create a companion matrix.
func
scipy.linalg._special_matrices.convolution_matrix(a, n, mode='full')Construct a convolution matrix.
func
scipy.linalg._special_matrices.dft(n, scale=None)Discrete Fourier transform matrix.
func
scipy.linalg._special_matrices.fiedler(a)Returns a symmetric Fiedler matrix.
func
scipy.linalg._special_matrices.fiedler_companion(a)Returns a Fiedler companion matrix.
func
scipy.linalg._special_matrices.hadamard(n, dtype=int)Construct a Hadamard matrix.
func
scipy.linalg._special_matrices.hankel(c, r=None)Construct a Hankel matrix.
func
scipy.linalg._special_matrices.helmert(n, full=False)Create a Helmert matrix of order `n`.
func
scipy.linalg._special_matrices.hilbert(n)Create a Hilbert matrix of order `n`.
func
scipy.linalg._special_matrices.leslie(f, s)Create a Leslie matrix.
func
scipy.linalg._special_matrices.pascal(n, kind='symmetric', exact=True)Returns the n x n Pascal matrix.
func
scipy.linalg._special_matrices.toeplitz(c, r=None)Construct a Toeplitz matrix.
func
scipy.linalg.blas.find_best_blas_type(arrays=(), dtype=None)Find best-matching BLAS/LAPACK type.
func
scipy.linalg.interpolative.id_to_svd(B, idx, proj)Convert ID to SVD.
func
scipy.linalg.interpolative.interp_decomp(A, eps_or_k, rand=True, rng=None)Compute ID of a matrix.
func
scipy.linalg.interpolative.reconstruct_matrix_from_id(B, idx, proj)Reconstruct matrix from its ID.
func
scipy.linalg.interpolative.svd(A, eps_or_k, rand=True, rng=None)Compute SVD of a matrix via an ID.
func
scipy.ndimage._filters.prewitt(input, axis=-1, output=None, mode='reflect', cval=0.0)Calculate a Prewitt filter.
func
scipy.ndimage._filters.sobel(input, axis=-1, output=None, mode='reflect', cval=0.0)Calculate a Sobel filter.
func
scipy.ndimage._interpolation.rotate(input, angle, axes=(1, 0), reshape=True, output=None, order=3, mode='constant', cval=0.0, prefilter=True)Rotate an array.
func
scipy.ndimage._interpolation.shift(input, shift, output=None, order=3, mode='constant', cval=0.0, prefilter=True)Shift an array.
func
scipy.ndimage._interpolation.spline_filter(input, order=3, output=np.float64, mode='mirror')Multidimensional spline filter.
func
scipy.ndimage._interpolation.zoom(input, zoom, output=None, order=3, mode='constant', cval=0.0, prefilter=True, *grid_mode=False)Zoom an array.
func
scipy.ndimage._measurements.do_map(inputs, output)labels must be sorted
func
scipy.ndimage._measurements.find_objects(input, max_label=0)Find objects in a labeled array.
func
scipy.ndimage._measurements.label(input, structure=None, output=None)Label features in an array.
func
scipy.ndimage._measurements.sum(input, labels=None, index=None)Calculate the sum of the values of the array.
func
scipy.ndimage._measurements.sum_labels(input, labels=None, index=None)Calculate the sum of the values of the array.
class
scipy.optimize._basinhopping.AdaptiveStepsizeClass to implement adaptive stepsize.
class
scipy.optimize._basinhopping.MetropolisMetropolis acceptance criterion.
class
scipy.optimize._basinhopping.MinimizerWrapperwrap a minimizer function as a minimizer class
class
scipy.optimize._basinhopping.StorageClass used to store the lowest energy structure
class
scipy.optimize._constraints.BoundsBounds constraint on the variables.
class
scipy.optimize._constraints.LinearConstraintLinear constraint on the variables.
class
scipy.optimize._constraints.NonlinearConstraintNonlinear constraint on the variables.
class
scipy.optimize._constraints.PreparedConstraintConstraint prepared from a user defined constraint.
class
scipy.optimize._differentiable_functions.IdentityVectorFunctionIdentity vector function and its derivatives.
class
scipy.optimize._differentiable_functions.LinearVectorFunctionLinear vector function and its derivatives.
class
scipy.optimize._differentiable_functions.ScalarFunctionScalar function and its derivatives.
class
scipy.optimize._differentiable_functions.VectorFunctionVector function and its derivatives.
class
scipy.optimize._dual_annealing.EnergyStateClass used to record the energy state.
class
scipy.optimize._hessian_update_strategy.HessianUpdateStrategyInterface for implementing Hessian update strategies.
method
scipy.optimize._hessian_update_strategy.HessianUpdateStrategy.initialize(n, approx_type)Initialize internal matrix.
method
scipy.optimize._hessian_update_strategy.HessianUpdateStrategy.update(delta_x, delta_grad)Update internal matrix.
class
scipy.optimize._hessian_update_strategy.SR1Symmetric-rank-1 Hessian update strategy.
func
scipy.optimize._isotonic.isotonic_regression(y:'npt.ArrayLike', *weights:'npt.ArrayLike | None'=None, *increasing:bool=True) -> OptimizeResultNonparametric isotonic regression.
func
scipy.optimize._lsq.common.in_bounds(x, lb, ub)Check if a point lies within bounds.
func
scipy.optimize._lsq.common.left_multiplied_operator(J, d)Return diag(d) J as LinearOperator.
func
scipy.optimize._lsq.common.left_multiply(J, d, copy=True)Compute diag(d) J.
func
scipy.optimize._lsq.common.phi_and_derivative(alpha, suf, s, Delta)Function of which to find zero.
func
scipy.optimize._lsq.common.right_multiplied_operator(J, d)Return J diag(d) as LinearOperator.
func
scipy.optimize._lsq.common.right_multiply(J, d, copy=True)Compute J diag(d).
class
scipy.optimize._nonlin.AndersonFind a root of a function, using (extended) Anderson mixing.
class
scipy.optimize._nonlin.JacobianCommon interface for Jacobians or Jacobian approximations.
class
scipy.optimize._nonlin.LowRankMatrixA matrix represented as ..
method
scipy.optimize._nonlin.LowRankMatrix.matvec(v)Evaluate w = M v
method
scipy.optimize._nonlin.LowRankMatrix.rmatvec(v)Evaluate w = M^H v
method
scipy.optimize._nonlin.LowRankMatrix.rsolve(v, tol=0)Evaluate w = M^-H v
method
scipy.optimize._nonlin.LowRankMatrix.solve(v, tol=0)Evaluate w = M^-1 v
class
scipy.optimize._nonlin.TerminationConditionTermination condition for an iteration.
class
scipy.optimize._optimize.OptimizeResultRepresents the optimization result.
class
scipy.optimize._optimize.OptimizeWarningGeneral warning for :mod:`scipy.optimize`.
func
scipy.optimize._optimize.rosen(x)The Rosenbrock function.
func
scipy.optimize._optimize.rosen_der(x)The derivative (i.e.
class
scipy.optimize._shgo_lib._vertex.FieldWrapperObject to wrap field to pass to `multiprocessing.Pool`.
class
scipy.optimize._shgo_lib._vertex.VertexBaseBase class for a vertex.
class
scipy.optimize._shgo_lib._vertex.VertexCacheBaseBase class for a vertex cache for a simplicial complex.
method
scipy.optimize._shgo_lib._vertex.VertexCacheBase.size()Returns the size of the vertex cache.
class
scipy.optimize._trustregion_constr.minimize_trustregion_constr.HessianLinearOperatorBuild LinearOperator from hessp
func
scipy.optimize._trustregion_constr.qp_subproblem.inside_box_boundaries(x, lb, ub)Check if lb <= x <= ub.
func
scipy.optimize._trustregion_constr.qp_subproblem.reinforce_box_boundaries(x, lb, ub)Return clipped value of x
class
scipy.optimize._trustregion_dogleg.DoglegSubproblemQuadratic subproblem solved by the dogleg method
func
scipy.optimize._tstutils.aps03_f(x, a, b)Rapidly changing at the root
func
scipy.optimize._tstutils.aps04_f(x, n, a)Medium-degree polynomial
func
scipy.optimize._tstutils.aps05_f(x)Simple Trigonometric function
func
scipy.optimize._tstutils.aps08_f(x, n)Degree n polynomial
func
scipy.optimize._tstutils.aps10_f(x, n)Exponential plus a polynomial
func
scipy.optimize._tstutils.aps12_f(x, n)nth root of x, with a zero at x=n
func
scipy.optimize._tstutils.cplx01_f(z, n, a)z**n-a: Use to find the nth root of a
func
scipy.optimize._tstutils.cplx02_f(z, a)e**z - a: Use to find the log of a
func
scipy.optimize._tstutils.f1(x)f1 is a quadratic with roots at 0 and 1
func
scipy.optimize._tstutils.f2(x)f2 is a symmetric parabola, x**2 - 1
func
scipy.optimize._tstutils.f3(x)A quartic with roots at 0, 1, 2 and 3
class
scipy.optimize._zeros_py.RootResultsRepresents the root finding result.
class
scipy.signal._czt.CZTCreate a callable chirp z-transform function.
class
scipy.signal._czt.ZoomFFTCreate a callable zoom FFT transform function.
class
scipy.signal._filter_design.BadCoefficientsWarning about badly conditioned filter coefficients.
func
scipy.signal._filter_design.G(w)Gain of filter
func
scipy.signal._filter_design.cutoff(w)When gain = -3 dB, return 0
func
scipy.signal._filter_design.gammatone(freq, ftype, order=None, numtaps=None, fs=None, *xp=None, *device=None)Gammatone filter design.
func
scipy.signal._lti_conversion.ss2tf(A, B, C, D, input=0)State-space to transfer function.
class
scipy.signal._ltisys.StateSpaceLinear Time Invariant system in state-space form.
method
scipy.signal._ltisys.StateSpace.A()State matrix of the `StateSpace` system.
method
scipy.signal._ltisys.StateSpace.B()Input matrix of the `StateSpace` system.
method
scipy.signal._ltisys.StateSpace.C()Output matrix of the `StateSpace` system.
class
scipy.signal._ltisys.TransferFunctionLinear Time Invariant system class in transfer function form.
class
scipy.signal._ltisys.ZerosPolesGainLinear Time Invariant system class in zeros, poles, gain form.
method
scipy.signal._ltisys.ZerosPolesGain.gain()Gain of the `ZerosPolesGain` system.
method
scipy.signal._ltisys.ZerosPolesGain.poles()Poles of the `ZerosPolesGain` system.
method
scipy.signal._ltisys.ZerosPolesGain.zeros()Zeros of the `ZerosPolesGain` system.
func
scipy.signal._ltisys.dimpulse(system, x0=None, t=None, n=None)Impulse response of discrete-time system.
class
scipy.signal._ltisys.dltiDiscrete-time linear time invariant system base class.
method
scipy.signal._ltisys.dlti.dt()Return the sampling time of the system.
func
scipy.signal._ltisys.dstep(system, x0=None, t=None, n=None)Step response of discrete-time system.
class
scipy.signal._ltisys.ltiContinuous-time linear time invariant system base class.
func
scipy.signal._polyutils.polyroots(coef, *xp)numpy.roots, best-effor replacement
func
scipy.signal._polyutils.polyval(p, x, *xp)Old-style polynomial, `np.polyval`
func
scipy.signal._signaltools.convolve(in1, in2, mode='full', method='auto')Convolve two N-dimensional arrays.
func
scipy.signal._signaltools.medfilt2d(input, kernel_size=3)Median filter a 2-dimensional array.
func
scipy.signal._waveforms.square(t, duty=0.5)Return a periodic square-wave waveform.
func
scipy.signal.windows._windows.bartlett(M, sym=True, *xp=None, *device=None)Return a Bartlett window.
func
scipy.signal.windows._windows.blackman(M, sym=True, *xp=None, *device=None)Return a Blackman window.
func
scipy.signal.windows._windows.bohman(M, sym=True, *xp=None, *device=None)Return a Bohman window.
func
scipy.signal.windows._windows.chebwin(M, at, sym=True, *xp=None, *device=None)Return a Dolph-Chebyshev window.
func
scipy.signal.windows._windows.flattop(M, sym=True, *xp=None, *device=None)Return a flat top window.
func
scipy.signal.windows._windows.gaussian(M, std, sym=True, *xp=None, *device=None)Return a Gaussian window.
func
scipy.signal.windows._windows.hamming(M, sym=True, *xp=None, *device=None)Return a Hamming window.
func
scipy.signal.windows._windows.hann(M, sym=True, *xp=None, *device=None)Return a Hann window.
func
scipy.signal.windows._windows.kaiser(M, beta, sym=True, *xp=None, *device=None)Return a Kaiser window.
func
scipy.signal.windows._windows.parzen(M, sym=True, *xp=None, *device=None)Return a Parzen window.
func
scipy.signal.windows._windows.taylor(M, nbar=4, sll=30, norm=True, sym=True, *xp=None, *device=None)Return a Taylor window.
func
scipy.signal.windows._windows.triang(M, sym=True, *xp=None, *device=None)Return a triangular window.
class
scipy.sparse._base.SparseWarningGeneral warning for :mod:`scipy.sparse`.
func
scipy.sparse._base.isspmatrix(x)Is `x` of a sparse matrix type?
class
scipy.sparse._base.sparrayA namespace class to separate sparray from spmatrix.
class
scipy.sparse._bsr.bsr_arrayBlock Sparse Row format sparse array.
class
scipy.sparse._bsr.bsr_matrixBlock Sparse Row format sparse matrix.
func
scipy.sparse._bsr.isspmatrix_bsr(x)Is `x` of a bsr_matrix type?
func
scipy.sparse._construct.expand_dims(A, *axis=0)Add trivial axes to an array.
func
scipy.sparse._construct.identity(n, dtype='d', format=None)Identity matrix in sparse format.
func
scipy.sparse._construct.matrix_transpose(A)Return the matrix transpose of `A`.
func
scipy.sparse._construct.swapaxes(A, axis1, axis2)Interchange two axes of an array.
class
scipy.sparse._coo.coo_arrayA sparse array in COOrdinate format.
class
scipy.sparse._coo.coo_matrixA sparse matrix in COOrdinate format.
func
scipy.sparse._coo.isspmatrix_coo(x)Is `x` of coo_matrix type?
class
scipy.sparse._csc.csc_arrayCompressed Sparse Column array.
class
scipy.sparse._csc.csc_matrixCompressed Sparse Column matrix.
func
scipy.sparse._csc.isspmatrix_csc(x)Is `x` of csc_matrix type?
class
scipy.sparse._csr.csr_arrayCompressed Sparse Row array.
class
scipy.sparse._csr.csr_matrixCompressed Sparse Row matrix.
func
scipy.sparse._csr.isspmatrix_csr(x)Is `x` of csr_matrix type?
class
scipy.sparse._dia.dia_arraySparse array with DIAgonal storage.
class
scipy.sparse._dia.dia_matrixSparse matrix with DIAgonal storage.
func
scipy.sparse._dia.isspmatrix_dia(x)Is `x` of dia_matrix type?
class
scipy.sparse._dok.dok_arrayDictionary Of Keys based sparse array.
class
scipy.sparse._dok.dok_matrixDictionary Of Keys based sparse matrix.
method
scipy.sparse._dok.dok_matrix.get_shape()Get shape of a sparse matrix.
func
scipy.sparse._dok.isspmatrix_dok(x)Is `x` of dok_array type?
func
scipy.sparse._lil.isspmatrix_lil(x)Is `x` of lil_matrix type?
class
scipy.sparse._lil.lil_arrayRow-based LIst of Lists sparse array.
class
scipy.sparse._lil.lil_matrixRow-based LIst of Lists sparse matrix.
class
scipy.sparse._matrix.spmatrixThis class provides a base class for all sparse matrix classes.
method
scipy.sparse._matrix.spmatrix.get_shape()Get the shape of the matrix
method
scipy.sparse._matrix.spmatrix.getformat()Matrix storage format
method
scipy.sparse._matrix.spmatrix.set_shape(shape)Set the shape of the matrix in-place
func
scipy.sparse._sputils.get_sum_dtype(dtype:np.dtype) -> np.dtype | type[np.generic]Mimic numpy's casting for np.sum
func
scipy.sparse._sputils.isintlike(x) -> boolIs x appropriate as an index into a sparse matrix?
func
scipy.sparse._sputils.isscalarlike(x) -> boolIs x either a scalar, an array scalar, or a 0-dim array?
func
scipy.sparse._sputils.isshape(x, nonneg=False, *allow_nd=(2,), *check_nd=True) -> boolIs x a valid tuple of dimensions?
class
scipy.sparse.linalg._dsolve.linsolve.MatrixRankWarningWarning for exactly singular matrices.
class
scipy.sparse.linalg._eigen.arpack.arpack.ArpackErrorARPACK error.
class
scipy.sparse.linalg._eigen.arpack.arpack.ArpackNoConvergenceARPACK iteration did not converge.
class
scipy.sparse.linalg._expm_multiply.LazyOperatorNormInfoInformation about an operator is lazily computed.
method
scipy.sparse.linalg._expm_multiply.LazyOperatorNormInfo.onenorm()Compute the exact 1-norm.
method
scipy.sparse.linalg._expm_multiply.LazyOperatorNormInfo.set_scale(scale)Set the scale parameter.
class
scipy.sparse.linalg._interface.LinearOperatorCommon interface for performing matrix vector products.
method
scipy.sparse.linalg._interface.LinearOperator.H()Hermitian adjoint.
method
scipy.sparse.linalg._interface.LinearOperator.T()Transpose.
method
scipy.sparse.linalg._interface.LinearOperator.adjoint()Hermitian adjoint.
method
scipy.sparse.linalg._interface.LinearOperator.dot(x)Multi-purpose multiplication method.
method
scipy.sparse.linalg._interface.LinearOperator.matmat(X)Matrix-matrix multiplication.
method
scipy.sparse.linalg._interface.LinearOperator.matvec(x)Matrix-vector multiplication.
method
scipy.sparse.linalg._interface.LinearOperator.transpose()Transpose.
class
scipy.sparse.linalg._interface.MatrixLinearOperatorOperator defined by a matrix `A` which implements ``@``.
func
scipy.sparse.linalg._interface.aslinearoperator(A)Return `A` as a `LinearOperator`.
func
scipy.sparse.linalg._matfuncs.inv(A)Compute the inverse of a sparse arrays.
func
scipy.sparse.linalg._norm.norm(x, ord=None, axis=None)Norm of a sparse matrix.
func
scipy.spatial._geometric_slerp.geometric_slerp(start:'npt.ArrayLike', end:'npt.ArrayLike', t:'npt.ArrayLike', tol:float=1e-07) -> np.ndarrayGeometric spherical linear interpolation.
class
scipy.spatial._kdtree.KDTreekd-tree for quick nearest-neighbor lookup.
class
scipy.spatial._kdtree.RectangleHyperrectangle class.
method
scipy.spatial._kdtree.Rectangle.split(d, split)Produce two hyperrectangles by splitting.
func
scipy.spatial._kdtree.distance_matrix(x, y, p=2.0, threshold=1000000)Compute the distance matrix.
class
scipy.spatial._spherical_voronoi.SphericalVoronoiVoronoi diagrams on the surface of a sphere.
func
scipy.spatial.distance._distance.chebyshev(u, v, w=None)Compute the Chebyshev distance.
class
scipy.spatial.transform._rigid_transform.RigidTransformRigid transform in 3 dimensions.
method
scipy.spatial.transform._rigid_transform.RigidTransform.apply(vector:ArrayLike, inverse:bool=False) -> ArrayApply the transform to a vector.
method
scipy.spatial.transform._rigid_transform.RigidTransform.from_dual_quat(dual_quat:ArrayLike, *scalar_first:bool=False) -> RigidTransformInitialize from a unit dual quaternion.
method
scipy.spatial.transform._rigid_transform.RigidTransform.from_exp_coords(exp_coords:ArrayLike) -> RigidTransformInitialize from exponential coordinates of transform.
method
scipy.spatial.transform._rigid_transform.RigidTransform.from_matrix(matrix:ArrayLike) -> RigidTransformInitialize from a 4x4 transformation matrix.
method
scipy.spatial.transform._rigid_transform.RigidTransform.from_rotation(rotation:Rotation) -> RigidTransformInitialize from a rotation, without a translation.
method
scipy.spatial.transform._rigid_transform.RigidTransform.identity(num:int | None=None, *shape:int | tuple[int, ...] | None=None) -> RigidTransformInitialize an identity transform.
method
scipy.spatial.transform._rigid_transform.RigidTransform.inv() -> RigidTransformInvert this transform.
method
scipy.spatial.transform._rigid_transform.RigidTransform.mean(weights:ArrayLike | None=None, axis:None | int | tuple[int, ...]=None) -> RigidTransformGet the mean of the transforms.
method
scipy.spatial.transform._rigid_transform.RigidTransform.rotation() -> RotationReturn the rotation component of the transform.
method
scipy.spatial.transform._rigid_transform.RigidTransform.shape() -> tuple[int, ...]The shape of the transform's leading dimensions.
func
scipy.spatial.transform._rigid_transform.normalize_dual_quaternion(dual_quat:ArrayLike) -> ArrayNormalize dual quaternion.
func
scipy.spatial.transform._rigid_transform_xp.normalize_dual_quaternion(dual_quat:Array) -> ArrayNormalize dual quaternion.
class
scipy.spatial.transform._rotation.RotationRotation in 3 dimensions.
method
scipy.spatial.transform._rotation.Rotation.apply(vectors:ArrayLike, inverse:bool=False) -> ArrayApply this rotation to a set of vectors.
method
scipy.spatial.transform._rotation.Rotation.as_davenport(axes:ArrayLike, order:str, degrees:bool=False, *suppress_warnings:bool=False) -> ArrayRepresent as Davenport angles.
method
scipy.spatial.transform._rotation.Rotation.as_euler(seq:str, degrees:bool=False, *suppress_warnings:bool=False) -> ArrayRepresent as Euler angles.
method
scipy.spatial.transform._rotation.Rotation.as_matrix() -> ArrayRepresent as rotation matrix.
method
scipy.spatial.transform._rotation.Rotation.as_mrp() -> ArrayRepresent as Modified Rodrigues Parameters (MRPs).
method
scipy.spatial.transform._rotation.Rotation.as_quat(canonical:bool=False, *scalar_first:bool=False) -> ArrayRepresent as quaternions.
method
scipy.spatial.transform._rotation.Rotation.as_rotvec(degrees:bool=False) -> ArrayRepresent as rotation vectors.
method
scipy.spatial.transform._rotation.Rotation.create_group(group:str, axis:str='Z') -> RotationCreate a 3D rotation group.
method
scipy.spatial.transform._rotation.Rotation.from_davenport(axes:ArrayLike, order:str, angles:ArrayLike | float, degrees:bool=False) -> RotationInitialize from Davenport angles.
method
scipy.spatial.transform._rotation.Rotation.from_euler(seq:str, angles:ArrayLike, degrees:bool=False) -> RotationInitialize from Euler angles.
method
scipy.spatial.transform._rotation.Rotation.from_matrix(matrix:ArrayLike, *assume_valid:bool=False) -> RotationInitialize from rotation matrix.
method
scipy.spatial.transform._rotation.Rotation.from_mrp(mrp:ArrayLike) -> RotationInitialize from Modified Rodrigues Parameters (MRPs).
method
scipy.spatial.transform._rotation.Rotation.from_quat(quat:ArrayLike, *scalar_first:bool=False) -> RotationInitialize from quaternions.
method
scipy.spatial.transform._rotation.Rotation.from_rotvec(rotvec:ArrayLike, degrees:bool=False) -> RotationInitialize from rotation vectors.
method
scipy.spatial.transform._rotation.Rotation.identity(num:int | None=None, *shape:int | tuple[int, ...] | None=None) -> RotationGet identity rotation(s).
method
scipy.spatial.transform._rotation.Rotation.inv() -> RotationInvert this rotation.
method
scipy.spatial.transform._rotation.Rotation.magnitude() -> ArrayGet the magnitude(s) of the rotation(s).
method
scipy.spatial.transform._rotation.Rotation.mean(weights:ArrayLike | None=None, axis:None | int | tuple[int, ...]=None) -> RotationGet the mean of the rotations.
method
scipy.spatial.transform._rotation.Rotation.shape() -> tuple[int, ...]The shape of the rotation's leading dimensions.
method
scipy.spatial.transform._rotation.Rotation.single() -> boolWhether this instance represents a single rotation.
class
scipy.spatial.transform._rotation.SlerpSpherical Linear Interpolation of Rotations.
func
scipy.spatial.transform._rotation.select_backend(xp:ModuleType, cython_compatible:bool)Select the backend for the given array library.
func
scipy.special._basic.bernoulli(n)Bernoulli numbers B0..Bn (inclusive).
About this data
These signatures were extracted from the public source of scipy/scipy
using Python's ast module. Argument names, default values,
type annotations and return types are taken verbatim from the code.
Implementation bodies are never stored. See
how it works for details.