brk-code

scipy の API リファレンス

scipy (scipy/scipy) の公開 API 400 件 —— クラス 143、関数 166、メソッド 91。実際のソースを静的解析して抽出した正確なシグネチャを掲載しています。

リポジトリ: scipy/scipy

種別件数
クラス143
関数166
メソッド91

API 一覧

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.
classscipy._external.packaging_version.src.version.InvalidVersion
Raised when a version string is not a valid version.
classscipy._external.packaging_version.src.version.Version
This class abstracts handling of a project's versions.
methodscipy._external.packaging_version.src.version.Version.base_version() -> str
The "base version" of the version.
methodscipy._external.packaging_version.src.version.Version.dev() -> int | None
The development number of the version.
methodscipy._external.packaging_version.src.version.Version.epoch() -> int
The epoch of the version.
methodscipy._external.packaging_version.src.version.Version.is_devrelease() -> bool
Whether this version is a development release.
methodscipy._external.packaging_version.src.version.Version.is_postrelease() -> bool
Whether this version is a post-release.
methodscipy._external.packaging_version.src.version.Version.is_prerelease() -> bool
Whether this version is a pre-release.
methodscipy._external.packaging_version.src.version.Version.local() -> str | None
The local version segment of the version.
methodscipy._external.packaging_version.src.version.Version.post() -> int | None
The post-release number of the version.
methodscipy._external.packaging_version.src.version.Version.pre() -> tuple[str, int] | None
The pre-release segment of the version.
methodscipy._external.packaging_version.src.version.Version.public() -> str
The public portion of the version.
funcscipy._external.packaging_version.src.version.parse(version:str) -> Version
Parse the given version string.
funcscipy._lib._array_api.get_native_namespace_name(xp:ModuleType) -> str
Return name for native namespace (without array_api_compat prefix).
funcscipy._lib._array_api.xp_compat_namespace(xp:ModuleType | None) -> ModuleType
Return the array-api-compat(ible) namespace corresponding to `xp`.
funcscipy._lib._array_api.xp_copy(x:Array, *xp:ModuleType | None=None) -> Array
Copies an array.
funcscipy._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.
funcscipy._lib._array_api_override.array_namespace(*sparse_ok=False, *arrays:Array) -> ModuleType
Get the array API compatible namespace for the arrays xs.
classscipy._lib._ccallback.LowLevelCallable
Low-level callback function.
funcscipy._lib._docscrape.NumpyDocString.parse_item_name(text)
Match ':role:`name`' or 'name'.
classscipy._lib._docscrape.Reader
A line-based string reader.
funcscipy._lib._docscrape.dedent_lines(lines)
Deindent a list of lines maximally
funcscipy._lib._gcutils.set_gc_state(state)
Set status of garbage collector
funcscipy._lib._sparse.issparse(x)
Is `x` either sparse array or sparse matrix type?
classscipy._lib._testutils.FPUModeChangeWarning
Warning about FPU mode change
funcscipy._lib._util.broadcastable(shape_a:tuple[int, ...], shape_b:tuple[int, ...]) -> bool
Check if two shapes are broadcastable.
classscipy._lib.doccer.Decorator
A decorator of a function.
funcscipy._lib.doccer.docformat(docstring:str, docdict:Mapping[str, str] | None=None) -> str
Fill a function docstring from variables in dictionary.
funcscipy._lib.doccer.filldoc(docdict:Mapping[str, str], unindent_params:bool=True) -> Decorator
Return docstring decorator using docdict variable dictionary.
funcscipy._lib.doccer.unindent_dict(docdict:Mapping[str, str]) -> dict[str, str]
Unindent all strings in a docdict.
funcscipy._lib.doccer.unindent_string(docstring:str) -> str
Set docstring to minimum indent for all lines, including first.
classscipy.cluster.hierarchy._hierarchy_impl.ClusterNode
A tree node class for representing a cluster.
classscipy.cluster.hierarchy._hierarchy_impl.ClusterWarning
A ``UserWarning`` raised during clustering.
funcscipy.cluster.hierarchy._hierarchy_impl.centroid(y)
Perform centroid/UPGMC linkage.
funcscipy.cluster.hierarchy._hierarchy_impl.leaves_list(Z)
Return a list of leaf node ids.
funcscipy.cluster.hierarchy._hierarchy_impl.median(y)
Perform median/WPGMC linkage.
classscipy.cluster.vq._vq_impl.ClusterError
An ``Exception`` raised during clustering.
classscipy.constants._codata.ConstantWarning
Accessing a constant no longer in current CODATA data set.
funcscipy.constants._codata.find(sub:str | None=None, disp:bool=False) -> Any
Return list of physical_constant keys containing a given string.
funcscipy.constants._codata.precision(key:str) -> float
Relative precision in physical_constants indexed by key.
funcscipy.constants._codata.unit(key:str) -> str
Unit in physical_constants indexed by key.
funcscipy.constants._codata.value(key:str) -> float
Value in physical_constants indexed by key.
funcscipy.constants._constants.lambda2nu(lambda_:'npt.ArrayLike') -> Any
Convert wavelength to optical frequency.
funcscipy.constants._constants.nu2lambda(nu:'npt.ArrayLike') -> Any
Convert optical frequency to wavelength.
funcscipy.fft._backend.register_backend(backend)
Register a backend for permanent use.
funcscipy.fft._backend.set_global_backend(backend, coerce=False, only=False, try_last=False)
Sets the global fft backend.
classscipy.fft._debug_backends.EchoBackend
Backend that just prints the __ua_function__ arguments
classscipy.fft._debug_backends.NumPyBackend
Backend that uses numpy.fft
funcscipy.fft._fftlog.fht(a, dln, mu, offset=0.0, bias=0.0)
Compute the fast Hankel transform.
funcscipy.fft._helper.ifftshift(x, axes=None)
The inverse of `fftshift`.
funcscipy.fftpack._basic.fft2(x, shape=None, axes=(-2, -1), overwrite_x=False)
2-D discrete Fourier transform.
funcscipy.integrate._bvp.collocation_fun(fun, y, p, x, h)
Evaluate collocation residuals.
funcscipy.integrate._bvp.modify_mesh(x, insert_1, insert_2)
Insert nodes into a mesh.
classscipy.integrate._ivp.base.ConstantDenseOutput
Constant value interpolator.
classscipy.integrate._ivp.base.DenseOutput
Base class for local interpolant over step made by an ODE solver.
classscipy.integrate._ivp.base.OdeSolver
Base class for ODE solvers.
methodscipy.integrate._ivp.base.OdeSolver.step()
Perform one integration step.
classscipy.integrate._ivp.bdf.BDF
Implicit method based on backward-differentiation formulas.
classscipy.integrate._ivp.common.OdeSolution
Continuous ODE solution.
funcscipy.integrate._ivp.common.norm(x)
Compute RMS norm.
funcscipy.integrate._ivp.common.validate_tol(rtol, atol, n)
Validate tolerance values.
classscipy.integrate._ivp.radau.Radau
Implicit Runge-Kutta method of Radau IIA family of order 5.
classscipy.integrate._ivp.rk.DOP853
Explicit Runge-Kutta method of order 8.
classscipy.integrate._ivp.rk.RK23
Explicit Runge-Kutta method of order 3(2).
classscipy.integrate._ivp.rk.RK45
Explicit Runge-Kutta method of order 5(4).
classscipy.integrate._ivp.rk.RungeKutta
Base class for explicit Runge-Kutta methods.
funcscipy.integrate._ivp.rk.rk_step(fun, t, y, f, h, A, B, C, K)
Perform a single Runge-Kutta step.
funcscipy.integrate._lebedev.lebedev_rule(n)
Lebedev quadrature.
classscipy.integrate._ode.complex_ode
A wrapper of ode for complex systems.
methodscipy.integrate._ode.complex_ode.set_initial_value(y, t=0.0)
Set initial conditions y(t) = y.
methodscipy.integrate._ode.complex_ode.set_integrator(name, **integrator_params)
Set integrator by name.
classscipy.integrate._ode.ode
A generic interface class to numeric integrators.
methodscipy.integrate._ode.ode.set_initial_value(y, t=0.0)
Set initial conditions y(t) = y.
methodscipy.integrate._ode.ode.set_integrator(name, **integrator_params)
Set integrator by name.
methodscipy.integrate._ode.ode.successful()
Check if integration was successful.
classscipy.integrate._odepack_py.ODEintWarning
Warning raised during the execution of `odeint`.
classscipy.integrate._quad_vec.DoubleInfiniteFunc
Argument transform from (-oo, oo) to (-1, 1)
classscipy.integrate._quad_vec.SemiInfiniteFunc
Argument transform from (start, +-oo) to (0, 1)
classscipy.integrate._quadpack_py.IntegrationWarning
Warning on issues during integration.
funcscipy.integrate._quadpack_py.dblquad(func, a, b, gfun, hfun, args=(), epsabs=1.49e-08, epsrel=1.49e-08)
Compute a double integral.
classscipy.integrate._rules._base.Rule
Base class for numerical integration algorithms (cubatures).
classscipy.integrate._rules._gauss_kronrod.GaussKronrodQuadrature
Gauss-Kronrod quadrature.
classscipy.integrate._rules._gauss_legendre.GaussLegendreQuadrature
Gauss-Legendre quadrature.
classscipy.integrate._rules._genz_malik.GenzMalikCubature
Genz-Malik cubature.
classscipy.interpolate._bary_rational.AAA
AAA real or complex rational approximation.
classscipy.interpolate._bsplines.BSpline
Univariate spline in the B-spline basis.
classscipy.interpolate._cubic.Akima1DInterpolator
Akima "visually pleasing" interpolator (C1 smooth).
classscipy.interpolate._cubic.CubicSpline
Piecewise cubic interpolator to fit values (C2 smooth).
classscipy.interpolate._cubic.PchipInterpolator
PCHIP shape-preserving interpolator (C1 smooth).
classscipy.interpolate._fitpack2.BivariateSpline
Base class for bivariate splines.
methodscipy.interpolate._fitpack2.BivariateSpline.ev(xi, yi, dx=0, dy=0)
Evaluate the spline at points.
classscipy.interpolate._fitpack2.LSQBivariateSpline
Weighted least-squares bivariate spline approximation.
classscipy.interpolate._fitpack2.LSQUnivariateSpline
1-D spline with explicit internal knots.
classscipy.interpolate._fitpack2.RectBivariateSpline
Bivariate spline approximation over a rectangular mesh.
classscipy.interpolate._fitpack2.SmoothBivariateSpline
Smooth bivariate spline approximation.
classscipy.interpolate._fitpack2.UnivariateSpline
1-D smoothing spline fit to a given set of data points.
methodscipy.interpolate._fitpack2.UnivariateSpline.get_coeffs()
Return spline coefficients.
methodscipy.interpolate._fitpack2.UnivariateSpline.roots()
Return the zeros of the spline.
funcscipy.interpolate._fitpack_py.insert(x, tck, m=1, per=0)
Insert knots into a B-spline.
funcscipy.interpolate._fitpack_py.sproot(tck, mest=10)
Find the roots of a cubic B-spline.
classscipy.interpolate._fitpack_repro.F
The r.h.s.
classscipy.interpolate._fitpack_repro.Fperiodic
Fit a smooth periodic B-spline curve to given data points.
funcscipy.interpolate._fitpack_repro.add_knot(x, t, k, residuals, periodic=False)
Add a new knot.
classscipy.interpolate._interpolate.BPoly
Piecewise polynomial in the Bernstein basis.
classscipy.interpolate._interpolate.NdPPoly
Piecewise tensor product polynomial.
classscipy.interpolate._interpolate.PPoly
Piecewise polynomial in the power basis.
classscipy.interpolate._interpolate.interp1d
Interpolate a 1-D function (legacy).
methodscipy.interpolate._interpolate.interp1d.fill_value()
The fill value.
classscipy.interpolate._ndbspline.NdBSpline
Tensor product spline object.
classscipy.interpolate._ndgriddata.NearestNDInterpolator
Nearest-neighbor interpolator in N > 1 dimensions.
classscipy.interpolate._polyint.KroghInterpolator
Krogh interpolator (C∞ smooth).
classscipy.interpolate._rbfinterp.RBFInterpolator
Radial basis function interpolator in N ≥ 1 dimensions.
classscipy.io._fortran.FortranEOFError
Indicates that the file ended properly.
methodscipy.io._fortran.FortranFile.close()
Closes the file.
classscipy.io._fortran.FortranFormattingError
Indicates that the file ended mid-record.
classscipy.io._harwell_boeing._fortran_format_parser.FortranFormatParser
Parser for Fortran format strings.
classscipy.io._harwell_boeing.hb.HBMatrixType
Class to hold the matrix type.
funcscipy.io._harwell_boeing.hb.hb_read(path_or_open_file, *spmatrix=_NoValue)
Read HB-format file.
funcscipy.io._harwell_boeing.hb.hb_write(path_or_open_file, m, hb_info=None)
Write HB-format file.
classscipy.io._idl.ObjectPointer
Class used to define object pointers
classscipy.io._idl.Pointer
Class used to define pointers
funcscipy.io._idl.readsav(file_name, idict=None, python_dict=False, uncompressed_file_name=None, verbose=False)
Read an IDL .sav file.
classscipy.io._netcdf.netcdf_file
A file object for NetCDF data.
methodscipy.io._netcdf.netcdf_file.close()
Closes the NetCDF file.
classscipy.io._netcdf.netcdf_variable
A data object for netcdf files.
methodscipy.io._netcdf.netcdf_variable.itemsize()
Return the itemsize of the variable.
methodscipy.io._netcdf.netcdf_variable.typecode()
Return the typecode of the variable.
classscipy.io.arff._arffread.ArffError
Base exception for errors when reading ARFF files.
methodscipy.io.arff._arffread.Attribute.parse_data(data_str)
Parse a value of this type.
classscipy.io.arff._arffread.MetaData
Small container to keep useful information on an ARFF dataset.
methodscipy.io.arff._arffread.MetaData.names()
Return the list of attribute names.
methodscipy.io.arff._arffread.MetaData.types()
Return the list of attribute types.
classscipy.io.arff._arffread.ParseArffError
Exception for syntax and parsing errors in ARFF files.
funcscipy.io.arff._arffread.loadarff(f)
Read an arff file.
funcscipy.io.arff._arffread.read_header(ofile)
Read the header of the iterable ofile.
funcscipy.io.matlab._mio.loadmat(file_name, mdict=None, appendmat=True, *spmatrix=_NoValue, **kwargs)
Load MATLAB file.
funcscipy.io.matlab._mio.whosmat(file_name, appendmat=True, **kwargs)
List variables inside a MATLAB file.
classscipy.io.matlab._mio4.MatFile4Reader
Reader for Mat4 files
methodscipy.io.matlab._mio4.MatFile4Reader.list_variables()
list variables from stream
classscipy.io.matlab._mio4.MatFile4Writer
Class for writing matlab 4 format files
classscipy.io.matlab._mio4.VarReader4
Class to read matlab 4 variables
methodscipy.io.matlab._mio4.VarReader4.read_header()
Read and return header for variable
classscipy.io.matlab._mio5.EmptyStructMarker
Class to indicate presence of empty matlab struct on output
classscipy.io.matlab._mio5.MatFile5Writer
Class for writing mat5 files
classscipy.io.matlab._mio5.VarWriter5
Generic matlab matrix writing class
methodscipy.io.matlab._mio5.VarWriter5.write_element(arr, mdtype=None)
write tag and data
methodscipy.io.matlab._mio5.VarWriter5.write_sparse(arr)
Sparse matrices are 2D
classscipy.io.matlab._mio5_params.MatlabFunction
Subclass for a MATLAB function.
classscipy.io.matlab._mio5_params.MatlabObject
Subclass of ndarray to signal this is a matlab object.
classscipy.io.matlab._mio5_params.MatlabOpaque
Subclass for a MATLAB opaque matrix.
classscipy.io.matlab._mio5_params.mat_struct
Placeholder for holding read data from structs.
classscipy.io.matlab._miobase.MatReadError
Exception indicating a read issue.
classscipy.io.matlab._miobase.MatReadWarning
Warning class for read issues.
classscipy.io.matlab._miobase.MatVarReader
Abstract class defining required interface for var readers
methodscipy.io.matlab._miobase.MatVarReader.array_from_header(header)
Reads array given header
methodscipy.io.matlab._miobase.MatVarReader.read_header()
Returns header
classscipy.io.matlab._miobase.MatWriteError
Exception indicating a write issue.
classscipy.io.matlab._miobase.MatWriteWarning
Warning class for write issues.
funcscipy.io.matlab._miobase.arr_to_chars(arr)
Convert string array to char array
funcscipy.io.wavfile.read(filename, mmap=False)
Open a WAV file.
funcscipy.io.wavfile.write(filename, rate, data)
Write a NumPy array as a WAV file.
funcscipy.linalg._basic.det(a, overwrite_a=False, check_finite=True)
Compute the determinant of a matrix.
funcscipy.linalg._decomp_polar.polar(a, side='right')
Compute the polar decomposition.
funcscipy.linalg._matfuncs.coshm(A)
Compute the hyperbolic matrix cosine.
funcscipy.linalg._matfuncs.cosm(A)
Compute the matrix cosine.
funcscipy.linalg._matfuncs.expm(A)
Compute the matrix exponential of an array.
funcscipy.linalg._matfuncs.khatri_rao(a, b)
Khatri-Rao product of two matrices.
funcscipy.linalg._matfuncs.logm(A)
Compute matrix logarithm.
funcscipy.linalg._matfuncs.signm(A)
Matrix sign function.
funcscipy.linalg._matfuncs.sinhm(A)
Compute the hyperbolic matrix sine.
funcscipy.linalg._matfuncs.sinm(A)
Compute the matrix sine.
funcscipy.linalg._matfuncs.sqrtm(A)
Compute, if exists, the matrix square root.
funcscipy.linalg._matfuncs.tanhm(A)
Compute the hyperbolic matrix tangent.
funcscipy.linalg._matfuncs.tanm(A)
Compute the matrix tangent.
funcscipy.linalg._misc.norm(a, ord=None, axis=None, keepdims=False, check_finite=True)
Matrix or vector norm.
funcscipy.linalg._special_matrices.circulant(c)
Construct a circulant matrix.
funcscipy.linalg._special_matrices.companion(a)
Create a companion matrix.
funcscipy.linalg._special_matrices.convolution_matrix(a, n, mode='full')
Construct a convolution matrix.
funcscipy.linalg._special_matrices.dft(n, scale=None)
Discrete Fourier transform matrix.
funcscipy.linalg._special_matrices.fiedler(a)
Returns a symmetric Fiedler matrix.
funcscipy.linalg._special_matrices.fiedler_companion(a)
Returns a Fiedler companion matrix.
funcscipy.linalg._special_matrices.hadamard(n, dtype=int)
Construct a Hadamard matrix.
funcscipy.linalg._special_matrices.hankel(c, r=None)
Construct a Hankel matrix.
funcscipy.linalg._special_matrices.helmert(n, full=False)
Create a Helmert matrix of order `n`.
funcscipy.linalg._special_matrices.hilbert(n)
Create a Hilbert matrix of order `n`.
funcscipy.linalg._special_matrices.leslie(f, s)
Create a Leslie matrix.
funcscipy.linalg._special_matrices.pascal(n, kind='symmetric', exact=True)
Returns the n x n Pascal matrix.
funcscipy.linalg._special_matrices.toeplitz(c, r=None)
Construct a Toeplitz matrix.
funcscipy.linalg.blas.find_best_blas_type(arrays=(), dtype=None)
Find best-matching BLAS/LAPACK type.
funcscipy.linalg.interpolative.id_to_svd(B, idx, proj)
Convert ID to SVD.
funcscipy.linalg.interpolative.interp_decomp(A, eps_or_k, rand=True, rng=None)
Compute ID of a matrix.
funcscipy.linalg.interpolative.reconstruct_matrix_from_id(B, idx, proj)
Reconstruct matrix from its ID.
funcscipy.linalg.interpolative.svd(A, eps_or_k, rand=True, rng=None)
Compute SVD of a matrix via an ID.
funcscipy.ndimage._filters.prewitt(input, axis=-1, output=None, mode='reflect', cval=0.0)
Calculate a Prewitt filter.
funcscipy.ndimage._filters.sobel(input, axis=-1, output=None, mode='reflect', cval=0.0)
Calculate a Sobel filter.
funcscipy.ndimage._interpolation.rotate(input, angle, axes=(1, 0), reshape=True, output=None, order=3, mode='constant', cval=0.0, prefilter=True)
Rotate an array.
funcscipy.ndimage._interpolation.shift(input, shift, output=None, order=3, mode='constant', cval=0.0, prefilter=True)
Shift an array.
funcscipy.ndimage._interpolation.spline_filter(input, order=3, output=np.float64, mode='mirror')
Multidimensional spline filter.
funcscipy.ndimage._interpolation.zoom(input, zoom, output=None, order=3, mode='constant', cval=0.0, prefilter=True, *grid_mode=False)
Zoom an array.
funcscipy.ndimage._measurements.do_map(inputs, output)
labels must be sorted
funcscipy.ndimage._measurements.find_objects(input, max_label=0)
Find objects in a labeled array.
funcscipy.ndimage._measurements.label(input, structure=None, output=None)
Label features in an array.
funcscipy.ndimage._measurements.sum(input, labels=None, index=None)
Calculate the sum of the values of the array.
funcscipy.ndimage._measurements.sum_labels(input, labels=None, index=None)
Calculate the sum of the values of the array.
classscipy.optimize._basinhopping.AdaptiveStepsize
Class to implement adaptive stepsize.
classscipy.optimize._basinhopping.Metropolis
Metropolis acceptance criterion.
classscipy.optimize._basinhopping.MinimizerWrapper
wrap a minimizer function as a minimizer class
classscipy.optimize._basinhopping.Storage
Class used to store the lowest energy structure
classscipy.optimize._constraints.Bounds
Bounds constraint on the variables.
classscipy.optimize._constraints.LinearConstraint
Linear constraint on the variables.
classscipy.optimize._constraints.NonlinearConstraint
Nonlinear constraint on the variables.
classscipy.optimize._constraints.PreparedConstraint
Constraint prepared from a user defined constraint.
classscipy.optimize._differentiable_functions.IdentityVectorFunction
Identity vector function and its derivatives.
classscipy.optimize._differentiable_functions.LinearVectorFunction
Linear vector function and its derivatives.
classscipy.optimize._differentiable_functions.ScalarFunction
Scalar function and its derivatives.
classscipy.optimize._differentiable_functions.VectorFunction
Vector function and its derivatives.
classscipy.optimize._dual_annealing.EnergyState
Class used to record the energy state.
classscipy.optimize._hessian_update_strategy.HessianUpdateStrategy
Interface for implementing Hessian update strategies.
methodscipy.optimize._hessian_update_strategy.HessianUpdateStrategy.initialize(n, approx_type)
Initialize internal matrix.
methodscipy.optimize._hessian_update_strategy.HessianUpdateStrategy.update(delta_x, delta_grad)
Update internal matrix.
classscipy.optimize._hessian_update_strategy.SR1
Symmetric-rank-1 Hessian update strategy.
funcscipy.optimize._isotonic.isotonic_regression(y:'npt.ArrayLike', *weights:'npt.ArrayLike | None'=None, *increasing:bool=True) -> OptimizeResult
Nonparametric isotonic regression.
funcscipy.optimize._lsq.common.in_bounds(x, lb, ub)
Check if a point lies within bounds.
funcscipy.optimize._lsq.common.left_multiplied_operator(J, d)
Return diag(d) J as LinearOperator.
funcscipy.optimize._lsq.common.left_multiply(J, d, copy=True)
Compute diag(d) J.
funcscipy.optimize._lsq.common.phi_and_derivative(alpha, suf, s, Delta)
Function of which to find zero.
funcscipy.optimize._lsq.common.right_multiplied_operator(J, d)
Return J diag(d) as LinearOperator.
funcscipy.optimize._lsq.common.right_multiply(J, d, copy=True)
Compute J diag(d).
classscipy.optimize._nonlin.Anderson
Find a root of a function, using (extended) Anderson mixing.
classscipy.optimize._nonlin.Jacobian
Common interface for Jacobians or Jacobian approximations.
classscipy.optimize._nonlin.LowRankMatrix
A matrix represented as ..
methodscipy.optimize._nonlin.LowRankMatrix.matvec(v)
Evaluate w = M v
methodscipy.optimize._nonlin.LowRankMatrix.rmatvec(v)
Evaluate w = M^H v
methodscipy.optimize._nonlin.LowRankMatrix.rsolve(v, tol=0)
Evaluate w = M^-H v
methodscipy.optimize._nonlin.LowRankMatrix.solve(v, tol=0)
Evaluate w = M^-1 v
classscipy.optimize._nonlin.TerminationCondition
Termination condition for an iteration.
classscipy.optimize._optimize.OptimizeResult
Represents the optimization result.
classscipy.optimize._optimize.OptimizeWarning
General warning for :mod:`scipy.optimize`.
funcscipy.optimize._optimize.rosen(x)
The Rosenbrock function.
funcscipy.optimize._optimize.rosen_der(x)
The derivative (i.e.
classscipy.optimize._shgo_lib._vertex.FieldWrapper
Object to wrap field to pass to `multiprocessing.Pool`.
classscipy.optimize._shgo_lib._vertex.VertexBase
Base class for a vertex.
classscipy.optimize._shgo_lib._vertex.VertexCacheBase
Base class for a vertex cache for a simplicial complex.
methodscipy.optimize._shgo_lib._vertex.VertexCacheBase.size()
Returns the size of the vertex cache.
classscipy.optimize._trustregion_constr.minimize_trustregion_constr.HessianLinearOperator
Build LinearOperator from hessp
funcscipy.optimize._trustregion_constr.qp_subproblem.inside_box_boundaries(x, lb, ub)
Check if lb <= x <= ub.
funcscipy.optimize._trustregion_constr.qp_subproblem.reinforce_box_boundaries(x, lb, ub)
Return clipped value of x
classscipy.optimize._trustregion_dogleg.DoglegSubproblem
Quadratic subproblem solved by the dogleg method
funcscipy.optimize._tstutils.aps03_f(x, a, b)
Rapidly changing at the root
funcscipy.optimize._tstutils.aps04_f(x, n, a)
Medium-degree polynomial
funcscipy.optimize._tstutils.aps05_f(x)
Simple Trigonometric function
funcscipy.optimize._tstutils.aps08_f(x, n)
Degree n polynomial
funcscipy.optimize._tstutils.aps10_f(x, n)
Exponential plus a polynomial
funcscipy.optimize._tstutils.aps12_f(x, n)
nth root of x, with a zero at x=n
funcscipy.optimize._tstutils.cplx01_f(z, n, a)
z**n-a: Use to find the nth root of a
funcscipy.optimize._tstutils.cplx02_f(z, a)
e**z - a: Use to find the log of a
funcscipy.optimize._tstutils.f1(x)
f1 is a quadratic with roots at 0 and 1
funcscipy.optimize._tstutils.f2(x)
f2 is a symmetric parabola, x**2 - 1
funcscipy.optimize._tstutils.f3(x)
A quartic with roots at 0, 1, 2 and 3
classscipy.optimize._zeros_py.RootResults
Represents the root finding result.
classscipy.signal._czt.CZT
Create a callable chirp z-transform function.
classscipy.signal._czt.ZoomFFT
Create a callable zoom FFT transform function.
classscipy.signal._filter_design.BadCoefficients
Warning about badly conditioned filter coefficients.
funcscipy.signal._filter_design.G(w)
Gain of filter
funcscipy.signal._filter_design.cutoff(w)
When gain = -3 dB, return 0
funcscipy.signal._filter_design.gammatone(freq, ftype, order=None, numtaps=None, fs=None, *xp=None, *device=None)
Gammatone filter design.
funcscipy.signal._lti_conversion.ss2tf(A, B, C, D, input=0)
State-space to transfer function.
classscipy.signal._ltisys.StateSpace
Linear Time Invariant system in state-space form.
methodscipy.signal._ltisys.StateSpace.A()
State matrix of the `StateSpace` system.
methodscipy.signal._ltisys.StateSpace.B()
Input matrix of the `StateSpace` system.
methodscipy.signal._ltisys.StateSpace.C()
Output matrix of the `StateSpace` system.
classscipy.signal._ltisys.TransferFunction
Linear Time Invariant system class in transfer function form.
classscipy.signal._ltisys.ZerosPolesGain
Linear Time Invariant system class in zeros, poles, gain form.
methodscipy.signal._ltisys.ZerosPolesGain.gain()
Gain of the `ZerosPolesGain` system.
methodscipy.signal._ltisys.ZerosPolesGain.poles()
Poles of the `ZerosPolesGain` system.
methodscipy.signal._ltisys.ZerosPolesGain.zeros()
Zeros of the `ZerosPolesGain` system.
funcscipy.signal._ltisys.dimpulse(system, x0=None, t=None, n=None)
Impulse response of discrete-time system.
classscipy.signal._ltisys.dlti
Discrete-time linear time invariant system base class.
methodscipy.signal._ltisys.dlti.dt()
Return the sampling time of the system.
funcscipy.signal._ltisys.dstep(system, x0=None, t=None, n=None)
Step response of discrete-time system.
classscipy.signal._ltisys.lti
Continuous-time linear time invariant system base class.
funcscipy.signal._polyutils.polyroots(coef, *xp)
numpy.roots, best-effor replacement
funcscipy.signal._polyutils.polyval(p, x, *xp)
Old-style polynomial, `np.polyval`
funcscipy.signal._signaltools.convolve(in1, in2, mode='full', method='auto')
Convolve two N-dimensional arrays.
funcscipy.signal._signaltools.medfilt2d(input, kernel_size=3)
Median filter a 2-dimensional array.
funcscipy.signal._waveforms.square(t, duty=0.5)
Return a periodic square-wave waveform.
funcscipy.signal.windows._windows.bartlett(M, sym=True, *xp=None, *device=None)
Return a Bartlett window.
funcscipy.signal.windows._windows.blackman(M, sym=True, *xp=None, *device=None)
Return a Blackman window.
funcscipy.signal.windows._windows.bohman(M, sym=True, *xp=None, *device=None)
Return a Bohman window.
funcscipy.signal.windows._windows.chebwin(M, at, sym=True, *xp=None, *device=None)
Return a Dolph-Chebyshev window.
funcscipy.signal.windows._windows.flattop(M, sym=True, *xp=None, *device=None)
Return a flat top window.
funcscipy.signal.windows._windows.gaussian(M, std, sym=True, *xp=None, *device=None)
Return a Gaussian window.
funcscipy.signal.windows._windows.hamming(M, sym=True, *xp=None, *device=None)
Return a Hamming window.
funcscipy.signal.windows._windows.hann(M, sym=True, *xp=None, *device=None)
Return a Hann window.
funcscipy.signal.windows._windows.kaiser(M, beta, sym=True, *xp=None, *device=None)
Return a Kaiser window.
funcscipy.signal.windows._windows.parzen(M, sym=True, *xp=None, *device=None)
Return a Parzen window.
funcscipy.signal.windows._windows.taylor(M, nbar=4, sll=30, norm=True, sym=True, *xp=None, *device=None)
Return a Taylor window.
funcscipy.signal.windows._windows.triang(M, sym=True, *xp=None, *device=None)
Return a triangular window.
classscipy.sparse._base.SparseWarning
General warning for :mod:`scipy.sparse`.
funcscipy.sparse._base.isspmatrix(x)
Is `x` of a sparse matrix type?
classscipy.sparse._base.sparray
A namespace class to separate sparray from spmatrix.
classscipy.sparse._bsr.bsr_array
Block Sparse Row format sparse array.
classscipy.sparse._bsr.bsr_matrix
Block Sparse Row format sparse matrix.
funcscipy.sparse._bsr.isspmatrix_bsr(x)
Is `x` of a bsr_matrix type?
funcscipy.sparse._construct.expand_dims(A, *axis=0)
Add trivial axes to an array.
funcscipy.sparse._construct.identity(n, dtype='d', format=None)
Identity matrix in sparse format.
funcscipy.sparse._construct.matrix_transpose(A)
Return the matrix transpose of `A`.
funcscipy.sparse._construct.swapaxes(A, axis1, axis2)
Interchange two axes of an array.
classscipy.sparse._coo.coo_array
A sparse array in COOrdinate format.
classscipy.sparse._coo.coo_matrix
A sparse matrix in COOrdinate format.
funcscipy.sparse._coo.isspmatrix_coo(x)
Is `x` of coo_matrix type?
classscipy.sparse._csc.csc_array
Compressed Sparse Column array.
classscipy.sparse._csc.csc_matrix
Compressed Sparse Column matrix.
funcscipy.sparse._csc.isspmatrix_csc(x)
Is `x` of csc_matrix type?
classscipy.sparse._csr.csr_array
Compressed Sparse Row array.
classscipy.sparse._csr.csr_matrix
Compressed Sparse Row matrix.
funcscipy.sparse._csr.isspmatrix_csr(x)
Is `x` of csr_matrix type?
classscipy.sparse._dia.dia_array
Sparse array with DIAgonal storage.
classscipy.sparse._dia.dia_matrix
Sparse matrix with DIAgonal storage.
funcscipy.sparse._dia.isspmatrix_dia(x)
Is `x` of dia_matrix type?
classscipy.sparse._dok.dok_array
Dictionary Of Keys based sparse array.
classscipy.sparse._dok.dok_matrix
Dictionary Of Keys based sparse matrix.
methodscipy.sparse._dok.dok_matrix.get_shape()
Get shape of a sparse matrix.
funcscipy.sparse._dok.isspmatrix_dok(x)
Is `x` of dok_array type?
funcscipy.sparse._lil.isspmatrix_lil(x)
Is `x` of lil_matrix type?
classscipy.sparse._lil.lil_array
Row-based LIst of Lists sparse array.
classscipy.sparse._lil.lil_matrix
Row-based LIst of Lists sparse matrix.
classscipy.sparse._matrix.spmatrix
This class provides a base class for all sparse matrix classes.
methodscipy.sparse._matrix.spmatrix.get_shape()
Get the shape of the matrix
methodscipy.sparse._matrix.spmatrix.getformat()
Matrix storage format
methodscipy.sparse._matrix.spmatrix.set_shape(shape)
Set the shape of the matrix in-place
funcscipy.sparse._sputils.get_sum_dtype(dtype:np.dtype) -> np.dtype | type[np.generic]
Mimic numpy's casting for np.sum
funcscipy.sparse._sputils.isintlike(x) -> bool
Is x appropriate as an index into a sparse matrix?
funcscipy.sparse._sputils.isscalarlike(x) -> bool
Is x either a scalar, an array scalar, or a 0-dim array?
funcscipy.sparse._sputils.isshape(x, nonneg=False, *allow_nd=(2,), *check_nd=True) -> bool
Is x a valid tuple of dimensions?
classscipy.sparse.linalg._dsolve.linsolve.MatrixRankWarning
Warning for exactly singular matrices.
classscipy.sparse.linalg._eigen.arpack.arpack.ArpackError
ARPACK error.
classscipy.sparse.linalg._eigen.arpack.arpack.ArpackNoConvergence
ARPACK iteration did not converge.
classscipy.sparse.linalg._expm_multiply.LazyOperatorNormInfo
Information about an operator is lazily computed.
methodscipy.sparse.linalg._expm_multiply.LazyOperatorNormInfo.onenorm()
Compute the exact 1-norm.
methodscipy.sparse.linalg._expm_multiply.LazyOperatorNormInfo.set_scale(scale)
Set the scale parameter.
classscipy.sparse.linalg._interface.LinearOperator
Common interface for performing matrix vector products.
methodscipy.sparse.linalg._interface.LinearOperator.H()
Hermitian adjoint.
methodscipy.sparse.linalg._interface.LinearOperator.T()
Transpose.
methodscipy.sparse.linalg._interface.LinearOperator.adjoint()
Hermitian adjoint.
methodscipy.sparse.linalg._interface.LinearOperator.dot(x)
Multi-purpose multiplication method.
methodscipy.sparse.linalg._interface.LinearOperator.matmat(X)
Matrix-matrix multiplication.
methodscipy.sparse.linalg._interface.LinearOperator.matvec(x)
Matrix-vector multiplication.
methodscipy.sparse.linalg._interface.LinearOperator.transpose()
Transpose.
classscipy.sparse.linalg._interface.MatrixLinearOperator
Operator defined by a matrix `A` which implements ``@``.
funcscipy.sparse.linalg._interface.aslinearoperator(A)
Return `A` as a `LinearOperator`.
funcscipy.sparse.linalg._matfuncs.inv(A)
Compute the inverse of a sparse arrays.
funcscipy.sparse.linalg._norm.norm(x, ord=None, axis=None)
Norm of a sparse matrix.
funcscipy.spatial._geometric_slerp.geometric_slerp(start:'npt.ArrayLike', end:'npt.ArrayLike', t:'npt.ArrayLike', tol:float=1e-07) -> np.ndarray
Geometric spherical linear interpolation.
classscipy.spatial._kdtree.KDTree
kd-tree for quick nearest-neighbor lookup.
classscipy.spatial._kdtree.Rectangle
Hyperrectangle class.
methodscipy.spatial._kdtree.Rectangle.split(d, split)
Produce two hyperrectangles by splitting.
funcscipy.spatial._kdtree.distance_matrix(x, y, p=2.0, threshold=1000000)
Compute the distance matrix.
classscipy.spatial._spherical_voronoi.SphericalVoronoi
Voronoi diagrams on the surface of a sphere.
funcscipy.spatial.distance._distance.chebyshev(u, v, w=None)
Compute the Chebyshev distance.
classscipy.spatial.transform._rigid_transform.RigidTransform
Rigid transform in 3 dimensions.
methodscipy.spatial.transform._rigid_transform.RigidTransform.apply(vector:ArrayLike, inverse:bool=False) -> Array
Apply the transform to a vector.
methodscipy.spatial.transform._rigid_transform.RigidTransform.from_dual_quat(dual_quat:ArrayLike, *scalar_first:bool=False) -> RigidTransform
Initialize from a unit dual quaternion.
methodscipy.spatial.transform._rigid_transform.RigidTransform.from_exp_coords(exp_coords:ArrayLike) -> RigidTransform
Initialize from exponential coordinates of transform.
methodscipy.spatial.transform._rigid_transform.RigidTransform.from_matrix(matrix:ArrayLike) -> RigidTransform
Initialize from a 4x4 transformation matrix.
methodscipy.spatial.transform._rigid_transform.RigidTransform.from_rotation(rotation:Rotation) -> RigidTransform
Initialize from a rotation, without a translation.
methodscipy.spatial.transform._rigid_transform.RigidTransform.identity(num:int | None=None, *shape:int | tuple[int, ...] | None=None) -> RigidTransform
Initialize an identity transform.
methodscipy.spatial.transform._rigid_transform.RigidTransform.inv() -> RigidTransform
Invert this transform.
methodscipy.spatial.transform._rigid_transform.RigidTransform.mean(weights:ArrayLike | None=None, axis:None | int | tuple[int, ...]=None) -> RigidTransform
Get the mean of the transforms.
methodscipy.spatial.transform._rigid_transform.RigidTransform.rotation() -> Rotation
Return the rotation component of the transform.
methodscipy.spatial.transform._rigid_transform.RigidTransform.shape() -> tuple[int, ...]
The shape of the transform's leading dimensions.
funcscipy.spatial.transform._rigid_transform.normalize_dual_quaternion(dual_quat:ArrayLike) -> Array
Normalize dual quaternion.
funcscipy.spatial.transform._rigid_transform_xp.normalize_dual_quaternion(dual_quat:Array) -> Array
Normalize dual quaternion.
classscipy.spatial.transform._rotation.Rotation
Rotation in 3 dimensions.
methodscipy.spatial.transform._rotation.Rotation.apply(vectors:ArrayLike, inverse:bool=False) -> Array
Apply this rotation to a set of vectors.
methodscipy.spatial.transform._rotation.Rotation.as_davenport(axes:ArrayLike, order:str, degrees:bool=False, *suppress_warnings:bool=False) -> Array
Represent as Davenport angles.
methodscipy.spatial.transform._rotation.Rotation.as_euler(seq:str, degrees:bool=False, *suppress_warnings:bool=False) -> Array
Represent as Euler angles.
methodscipy.spatial.transform._rotation.Rotation.as_matrix() -> Array
Represent as rotation matrix.
methodscipy.spatial.transform._rotation.Rotation.as_mrp() -> Array
Represent as Modified Rodrigues Parameters (MRPs).
methodscipy.spatial.transform._rotation.Rotation.as_quat(canonical:bool=False, *scalar_first:bool=False) -> Array
Represent as quaternions.
methodscipy.spatial.transform._rotation.Rotation.as_rotvec(degrees:bool=False) -> Array
Represent as rotation vectors.
methodscipy.spatial.transform._rotation.Rotation.create_group(group:str, axis:str='Z') -> Rotation
Create a 3D rotation group.
methodscipy.spatial.transform._rotation.Rotation.from_davenport(axes:ArrayLike, order:str, angles:ArrayLike | float, degrees:bool=False) -> Rotation
Initialize from Davenport angles.
methodscipy.spatial.transform._rotation.Rotation.from_euler(seq:str, angles:ArrayLike, degrees:bool=False) -> Rotation
Initialize from Euler angles.
methodscipy.spatial.transform._rotation.Rotation.from_matrix(matrix:ArrayLike, *assume_valid:bool=False) -> Rotation
Initialize from rotation matrix.
methodscipy.spatial.transform._rotation.Rotation.from_mrp(mrp:ArrayLike) -> Rotation
Initialize from Modified Rodrigues Parameters (MRPs).
methodscipy.spatial.transform._rotation.Rotation.from_quat(quat:ArrayLike, *scalar_first:bool=False) -> Rotation
Initialize from quaternions.
methodscipy.spatial.transform._rotation.Rotation.from_rotvec(rotvec:ArrayLike, degrees:bool=False) -> Rotation
Initialize from rotation vectors.
methodscipy.spatial.transform._rotation.Rotation.identity(num:int | None=None, *shape:int | tuple[int, ...] | None=None) -> Rotation
Get identity rotation(s).
methodscipy.spatial.transform._rotation.Rotation.inv() -> Rotation
Invert this rotation.
methodscipy.spatial.transform._rotation.Rotation.magnitude() -> Array
Get the magnitude(s) of the rotation(s).
methodscipy.spatial.transform._rotation.Rotation.mean(weights:ArrayLike | None=None, axis:None | int | tuple[int, ...]=None) -> Rotation
Get the mean of the rotations.
methodscipy.spatial.transform._rotation.Rotation.shape() -> tuple[int, ...]
The shape of the rotation's leading dimensions.
methodscipy.spatial.transform._rotation.Rotation.single() -> bool
Whether this instance represents a single rotation.
classscipy.spatial.transform._rotation.Slerp
Spherical Linear Interpolation of Rotations.
funcscipy.spatial.transform._rotation.select_backend(xp:ModuleType, cython_compatible:bool)
Select the backend for the given array library.
funcscipy.special._basic.bernoulli(n)
Bernoulli numbers B0..Bn (inclusive).

この情報について

掲載しているシグネチャは scipy/scipy の公開ソースコードを Python の ast モジュールで静的解析し、引数名・デフォルト値・ 型注釈・戻り値型をそのまま抽出したものです。実装コードは保存していません。 詳しくは仕組みの解説をご覧ください。

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