Generic index bootstrap.

Numerical and physical constants.

Abstract class for one-dimensional harmonic-oscillator evolution using the complex-structure formalism.

Abstract class for implementing data objects.

This object is an abstract class for one variable distribution data.

This object is designate to data that is described by a bivariate and arbitrary distribution.

Funnel distribution.

Gaussian data — inverse covariance provided.

Gaussian data — covariance provided.

Multivariate Normal Distribution — covariance provided.

Gaussian data — diagonal covariance provided.

Gaussian Mixture 2d distribution.

Abstract class for implementing poisson distributed data.

Rosenbrock distribution.

A set of NcmData objects.

Numerical differentiation object.

Abstract class for implementing logarithm fast fourier transform.

Logarithm fast fourier transform for a kernel given by the square of a Gaussian window function.

Logarithm fast fourier transform for a kernel given by the spatial correlation function multipoles.

Logarithm fast fourier transform for the base kernel for angular projections.

Logarithm fast fourier transform for a kernel given by the square of the spherical Bessel function of order one.

Abstract class for implementing fitting methods.

Ensemble sampler Markov Chain Monte Carlo analysis.

Ensemble sampler Markov Chain Monte Carlo walker class.

Ensemble sampler Markov Chain Monte Carlo walker - apes move.

Ensemble sampler Markov Chain Monte Carlo walker - stretch move.

Ensemble sampler Markov Chain Monte Carlo walker - walk move.

Best-fit finder — GSL least squares algorithms.

Best-fit finder — GSL non-linear minimization algorithms.

Best-fit finder — GSL non-linear minimization (simplex) algorithms.

Best-fit finder — Levenberg-Marquardt nonlinear least squares algorithm library.

Monte Carlo analysis.

Monte Carlo and bootstrap analysis.

Markov Chain Monte Carlo analysis.

Interface for NLopt optmization library.

State of a NcmFit object.

A generic cache for functions values.

Ordered sample set for vector-valued functions $\vec{F}: \mathbb{R} \to \mathbb{R}^n$.

One dimensional integration object.

Function pointer one dimensional integration object.

N-dimensional integration object.

Index set object.

Likelihood ratio for one dimensional parameter analysis.

Likelihood ratio object for bidimensional parameter analysis.

Likelihood combining a NcmDataset and priors.

Matrix object representing an array of doubles.

Abstract class for implementing models.

A NcmModel builder.

Control object for testing updates on model status.

Multivariate Normal Distribution mean model.

Multivariate Normal Distribution mean model.

Multivariate Normal Distribution mean model.

Abstract class to implement MPI jobs.

MPI job object for evaluating fit steps.

MPI job object for running NcmFit.

MPI job object for running MCMC steps.

Test implementation of MPI job class.

A set of different NcmModel objects.

Ordered catalog of different NcmMSet parameter values.

Abstract class for arbitrary MSet functions.

Abstract class for arbitrary MSet functions - bindable version.

NcmMSet Functions list.

Abstract Class for a transition kernel and prior.

Catalog sampler.

Multivariate flat sampler.

A multivariate gaussian sampler.

Non-negative linear least-squares.

Automatic generation of splines from ODE solvers.

A Poisson–Lognormal 1D integrator using mode finding (GSL Lambert-W), shifted Gauss–Hermite, or Laplace fallback.

Abstrac class for power spectrum implementation.

Class to compute the 3d spatial correlation function from the power spectrum.

Class to compute filtered power spectrum.

Class to compute spherical projection of power spectra.

Power spectrum implementation using a 2D spline.

Base class for prior distributions.

Base class for flat prior distributions.

Flat prior on a derived quantity.

Flat prior on a sampling parameter.

A gaussian prior for NcmLikelihood.

Gaussian prior on a parameter.

Gaussian prior on a parameter.

Abstract class for model reparametrization.

Linear reparametrization object.

Encapsulated GNU Scientific Library (GSL) random number generator with support for multhreading.

Base class for spherical Bessel function integrators.

FFT-Legendre based spherical Bessel function integrator.

Gauss-Legendre based spherical Bessel function integrator.

Levin-Bessel method for spherical Bessel function integration.

Spectral ODE solver for the spherical Bessel equation in polynomial form using ultraspherical methods.

Serialization, deserialization and duplication object.

Spherical Bessel function array evaluator with automatic cutoff.

Spherical Harmonics object.

Properties of a scalar parameter.

An re-implementation of Healpix.

An re-implementation of Healpix.

Base class for implementing splines.

Base class for implementing bidimensional splines.

Bidimensional bicubic spline.

Implements spline from spline method using The GNU Scientific Library (GSL) as base splines.

Implements bidimensional splines from splines method.

Base class for implementing cubic splines.

Cubic spline implementation given second derivatives.

Cubic spline implementation with ‘not a knot’ boundary conditions.

Test suite to analyze the NcmSplineFunc’s knots distribution.

GSL spline object wrapper.

Radial Basis Function implementation of spline class.

A vector-valued spline function $\vec{F}(x): \mathbb{R} \to \mathbb{R}^n$.

Base class for implementing N-dimensional probability distributions.

Base class for implementing one dimensional probability distributions.

One dimensional probability distribution based on an EPDF.

One dimensional probability distribution based on a spline.

Base class for implementing two-dimensional probability distributions.

Two-dimensional probability distribution based on a spline.

Base class for implementing N-dimensional probability distributions with a fixed density estimator kernel.

An N-dimensional kernel used to compute the kernel density estimation function (KDE) in the NcmStatsDist class.

An N-dimensional Gaussian kernel used to compute the kernel density estimation function (KDE) in the NcmStatsDist class.

An N-dimensional Student’s t kernel used to compute the kernel density estimation function (KDE) in the NcmStatsDist class.

Base class for implementing N-dimensional probability distributions with a variable density estimator kernel.

An online statistics vector.

A timer with ETA support.

Vector object representing arrays of doubles.

Properties of a vector-like parameter.

Binnary splitting algorithms used to evaluate sums fast and with arbitrary precision.

Represents the state of the system.

A 2-dimensional tuple of double precision floating point numbers.

A 3-dimensional tuple of double precision floating point numbers.

Container for gradient functions.

Iterator for traversing samples in a NcmFunctionSampleSet. Provides O(1) access to sample data once positioned, making it efficient for sequential traversal and interval operations.

Fixed-point numerical integration structure. Contains integration bounds and nodes for fixed Gauss-Legendre or other quadrature schemes.

Two-dimensional integrand structure. Holds a function pointer and user data for 2D numerical integration routines.

Three-dimensional integrand structure. Holds a function pointer and user data for 3D numerical integration routines.

Boxed object containing a point in the 2d parameter space.

Object describing a confidence region.

Generic memory pool.

Multi-precision spherical Bessel function recursion structure. This structure holds the state for computing spherical Bessel functions using high-precision MPFR arithmetic with recursion relations.

Structure defining a function in the model set function list. This holds metadata for functions that can be evaluated on model parameter sets.

GObjects array with serialization support.

GObjects dictionary with integer keys.

GObjects dictionary with string keys.

Quaternions algebra, three-vectors and mapping to matrix.

Opaque boxed type for a configured spectral operator.

Recurrence coefficients.

Boxed P values.

Recurrence boxed object.

Recurrence array boxed object.

Structure to hold the coefficients of a bicubic spline.

Variable dictionary.

Variables describing the system evolution state. The state NCM_CSQ1D_EVOL_STATE_ADIABATIC is used to describe the adiabatic evolution of the system, this state use the frame

NCM_CSQ1D_FRAME_ADIAB1 with the variables $(\alpha,\, \delta\gamma)$ to compute the evolution.

The state NCM_CSQ1D_EVOL_STATE_UP and NCM_CSQ1D_EVOL_STATE_UM are used to describe the non-adiabatic evolution of the system, these states use the frame #NCM_CSQ1D_FRAME_ORIG with the variables $(\chi,\, U_+)$ and $(\chi,\, U_-)$ to compute the evolution, respectively.

Frames for the system.

Initial conditions for the system. The initial condition NCM_CSQ1D_INITIAL_CONDITION_TYPE_AD_HOC is used to set an arbitrary initial condition. The initial conditions NCM_CSQ1D_INITIAL_CONDITION_TYPE_ADIABATIC2, NCM_CSQ1D_INITIAL_CONDITION_TYPE_ADIABATIC4 and NCM_CSQ1D_INITIAL_CONDITION_TYPE_NONADIABATIC2 are used to set the initial conditions for the adiabatic and non-adiabatic vacuum initial conditions.

Types of Poisson-distributed data. These specify the data format for Poisson likelihood calculations.

Bootstrap types.

Kernel used to build the approximate posterior.

Posterior estimation method.

Defines the type of gradient calculation.

GSL Multidimensional minimization algorithms.

GSL Multidimensional minimization algorithms without derivatives.

Levmar algorithms.

Montecarlo resample options.

Defines the type of messages to be printed during the fit.

Defines the subclasse of NcmFit to be used.

Cache search direction.

The type of the error estimation used to perform the integral.

The type of the method used to perform the integral.

Root finding methods used by NcmLHRatio1d.

Root finding methods used by NcmLHRatio2d.

This enumerator is only used internally. Only by developers.

Funnel model parameters.

Funnel model parameters.

MVND model parameters.

Rosenbrock model parameters.

Control messages from master to slave. All messages have the same size, specifying tag #NCM_MPI_CTRL_TAG_CMD.

MPI tags for master-slave communication. If NCM_MPI_CTRL_TAG_CMD is used, the message is a control message.

NCM_MPI_CTRL_SLAVE_INIT must be followed by #NCM_MPI_CTRL_TAG_JOB containing the serialized job.

NCM_MPI_CTRL_SLAVE_WORK must be followed by #NCM_MPI_CTRL_TAG_WORK_INPUT containing the serialized input.

NCM_MPI_CTRL_SLAVE_WORK is followed by #NCM_MPI_CTRL_TAG_WORK_RETURN containing the serialized return.

NCM_MPI_CTRL_SLAVE_FREE does not need to be followed by any message. The slave can be reinitialized with #NCM_MPI_CTRL_SLAVE_INIT.

NCM_MPI_CTRL_SLAVE_KILL should not be followed by any message. The slave will exit.

See ncm_mset_catalog_calc_max_ess_time() and ncm_mset_catalog_calc_heidel_diag().

Catalog sync modes.

Method used to estimate the autocorrelation time $\tau$.

Sampling methods.

Method used to solve the intermediate unconstrained least-squares.

NcmParamType indicates if the parameter must be fitted, NCM_PARAM_TYPE_FREE, or if it remains fixed, NCM_PARAM_TYPE_FIXED, when a statistical analysis is carried out.

Filter type to apply to the power spectrum. See also NcmFftlogTophatwin2 and NcmFftlogGausswin2, for the top-hat and Gaussian filters, respectively.

Sphere map coordinate system.

Sphere map pixel ordering.

Enum to choose which base function to be used in the test suite.

Enum to choose which PDF type.

Enumeration to choose which of the functions to be applied when interpolating the input #gsl_function *F, $f$, with the desired rel_error in the range [xi, xf]. The interpolation knots, $\mathbf{x}$, are automatically defined internally by the functions. For more details see [description][numcosmo-NcmSplineFunc.description] above.

Enumeration to choose which GSL interpolation method as backend to be used by the object. It can be used with the function ncm_spline_gsl_new_by_id() when a new NcmSplineGsl is created.

Enumeration to choose which Gaussian RBF interpolation method to be applied by the object.

Gaussian kernel bandwidth type.

Cross-validation method to be applied.

Selects the covariance type to use in the kernel interpolation.

Autoregressive model selection criteria. These criteria are used to automatically select the optimal order for autoregressive models in time series analysis.

Statistical types for vector statistics computation. These determine which statistical quantities are computed and stored during data accumulation.

This enumerator is only used internally. Only by developers.

See ncm_mset_catalog_calc_max_ess_time() and ncm_mset_catalog_calc_heidel_diag().

Options for serialization.

Error codes for the ncm_cfg namespace.

Error codes returned by the NcmModel class.

Error codes returned by the NcmMSet class.

Calculates the Fisher-information matrix I.

Functon $f(x)$ call back.

Functon $f(x)$ call back.

Functon $f(x)$ call back.

Functon $f(x)$ call back.

Vector-valued function type $\vec{F}: \mathbb{R} \to \mathbb{R}^n$. The function should evaluate at x and write the result into y.

The type of the function that must be implemented by a subclass of NcmIntegralND.

The type of the function that must be implemented by a subclass of NcmIntegralND.

Function type for reparameterization. See also NcmReparam.

Function to be integrated with spherical Bessel functions. Computes K(x, k) for the integral ∫K(x,k)*j_ℓ(kx)dx.

Callback function type for the right-hand side forcing term $f(x)$ in the modified spherical Bessel ODE. The function is evaluated at physical coordinates $x \in [a,b]$ and should return $f(x)$ corresponding to the inhomogeneous term.

Function to be used in spectral computations. The function is defined over an interval [a, b] and receives x in that interval. Internally, Chebyshev polynomials work with the transformed variable $t \in [-1, 1]$ where $t = (2x - (a + b))/(b - a)$ and $x = ((b - a)t + (a + b))/2$.

Allocates a new NcmBinSplit.

Evaluates the sum of nt terms and joins the result to the sum stored in bs.

Evaluates the sum until the number of bits of precision is greater or equal to prec.

Computes the value of the sum stored in bs and stores the result in res in the form of a #mpfr_t.

Computes the value of the sum stored in bs and stores the result in res in the form of a double.

Computes the value of the sum stored in bs and stores the result in q. The result is stored in the form of a #mpq_t.

Joins two NcmBinSplit objects, it is assumed that bs_l and bs_r are consecutive in the sum.

Computes the number of bits of precision that would be gained by adding nt terms to the sum.

Transfers the data from var to a.

Creates a variant of array type from a.

Converts argv to a single string.

Enables the GSL error handler.

Transforms the entries into a keyfile kfile group group_name.

Gets the enum value from enum_type by n.

Prints all enum values from enum_type.

Checks if filename exists in the numcosmo path.

Gets the commit hash of the library.

Gets the data directory path. It first checks the environment variable NCM_CFG_DATA_DIR_ENV, then the package data directory and finally the package source directory. If none of these directories exists, it raises an error.

Looks for filename in the data path and returns the full path if found.

Gets the enum value from enum_type by id_name_nick.

Gets the default FFTW flag.

Gets the default FFTW flag as a string.

Gets the planner time out in seconds. A negative value means no time out.

Gets the full path of filename.

Gets the full path base directory.

Gets the version of the library.

Gets the version of the library as a string.

Main library configuration function. Must be called before any other function of NumCosmo.

Main library configuration function. Must be called before any other function of NumCosmo.

Main library configuration function. Must be called before any other function of NumCosmo.

Transforms the entries in a keyfile kfile group group_name into an array of strings representing the command line arguments.

Loads the FFTW wisdom from filename.

Locks the FFTW plan. This is a generic lock for all FFTW plans.

Enables or disables the log file.

Enables or disables the log file flush.

Flushes the log file.

Log a message separator.

Register functions for the ncm_cfg namespace.

Registers the object obj in the GObject type system.

Registers the objects of the library.

Saves the current FFTW wisdom to filename.

Sets BLIS number of threads to n when available.

Sets all log information to stream.

Sets the default FFTW flag (FFTW_ESTIMATE, FFTW_MEASURE, FFTW_PATIENT, FFTW_EXHAUSTIVE) to be used when building plans. The variable timeout sets the maximum time spent on planners.

Sets the default FFTW flag (FFTW_ESTIMATE, FFTW_MEASURE, FFTW_PATIENT, FFTW_EXHAUSTIVE) to be used when building plans. The variable timeout sets the maximum time spent on planners. The argument flag_str is a string representation of the flag:.

Sets the default FFTW flag and planner time out from the environment variables NCM_FFTW_PLANNER and NCM_FFTW_PLANNER_TIMELIMIT. If the environment variables are not set, it uses the fallback_flag and fallback_timeout.

Sets the default FFTW flag and planner time out from the environment variables NCM_FFTW_PLANNER and NCM_FFTW_PLANNER_TIMELIMIT. If the environment variables are not set, it uses the fallback_flag_str and fallback_timeout.

Sets all log information to stream.

Sets all log information to filename.

Sets all log information to stream.

Sets OpenBLAS number of threads to n when available.

Sets OpenBLAS number of threads to n when available.

Sets OpenMP number of threads to n when available.

Transforms str into a comment string.

Unlocks the FFTW plan. This is a generic lock for all FFTW plans.

Checks if the library version is greater or equal to major, minor and micro.

Compare x and y and return -1 if x < y, 0 if x == y and 1 if x > y, all comparisons are done with precision reltol and abstol.

Compares x and y and returns the difference between them relative to their mean.

Computes the first derivative of the relative exponential $(\exp(x) - 1)/x$.

Computes the second derivative of the relative exponential $(\exp(x) - 1)/x$.

Computes the third derivative of the relative exponential $(\exp(x) - 1)/x$.

Computes the relative exponential $(\exp(x) - 1)/x$.

Set the new maximun number of threads to be used by the pool. Note that this function is global changing this will affect every place which uses these functions.

Using the thread pool, evaluate fl in each value of (f-i)/nthreads.

Using the thread pool, evaluate fl sending one worker per index.

Using the thread pool, evaluate fl in each value of (f-i)/nwork.

This function searches for the nearest x_near value previously chosen as the upper integration limit and perform the integration at [x_near, x] interval. This result is summed to that obtained at [0, x_near] and then it is saved in the cache.

This function searchs for the nearest x_near value previously chosed as the lower integration limit and perform the integration at $[x, x_{near}]$ interval. This result is summed to that obtained at $[x_{near}, \infty]$ and then it is saved in the cache.

This function provides a workspace to be used by numerical integration functions of GSL. It keeps a internal pool of workspaces and allocate a new one if the function is called and the pool is empty. It is designed to be used in a multi-thread environment. The workspace must be unlocked in order to return to the pool. This must be done using the #ncm_memory_pool_return.

This function uses a workspace from the pool and gsl_integration_qag function to perform the numerical integration in the [a, b] interval.

This function uses a workspace from the pool and gsl_integration_qagiu function to perform the numerical integration in the $[a, \infty]$ interval.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] using the Cuhre algorithm from the Cuba library.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] using the Divonne algorithm from the Cuba library.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] using the Divonne algorithm from the Cuba library. It uses a peakfinder to find the peaks of the integrand and improve the integration of concentrated functions.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] using the Vegas algorithm from the Cuba library.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] and [zi, zf] using the Cuhre algorithm from the Cuba library.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] and [zi, zf] using the Divonne algorithm from the Cuba library.

This function computes the integral of the function integ->f over the interval [xi, xf] and [yi, yf] and [zi, zf] using the Vegas algorithm from the Cuba library.

This function computes the eigensystem for a real matrix a = A.

This function computes the eigensystem for a real matrix a = A.

DGELQF computes a LQ factorization of a real M-by-N matrix A: A = L * Q.

DGELS solves overdetermined or underdetermined real linear systems involving an M-by-N matrix A, or its transpose, using a QR or LQ factorization of A. It is assumed that A has full rank.

DGELSD computes the minimum-norm solution to a real linear least squares problem: minimize 2-norm(| b - A*x |) using the singular value decomposition (SVD) of A. A is an M-by-N matrix which may be rank-deficient.

DGEQLF computes a QL factorization of a real M-by-N matrix A: A = Q * L.

DGEQRF computes a QR factorization of a real M-by-N matrix A: A = Q * R.

DGERQF computes a RQ factorization of a real M-by-N matrix A: A = R * Q.

This function computes the solution of $A X = B$ for a general n by n matrix a = A using the LU factorization with partial pivoting and row interchanges. On entry b contain the vectors $B$ and on exit b contain the solutions if the return is 0. The array ipiv records the pivot indices from the factorization.

Calculates and allocs memory to solve the system determined by the parameters.

Runs the dggglm function using the workspace ws.

This function computes the solution of $A X = B$ for a real symmetric positive definite matrix a = A using the Cholesky factorization $A = U^TU$ or $A = LL^T$. On entry b contain the vectors $B$ and on exit b contain the solutions if the return is 0.

This function computes the Cholesky factorization of a real symmetric positive definite matrix a.

This function computes the inverse of a real symmetric positive definite matrix a = A using the Cholesky factorization $A = U^TU$ or $A = LL^T$ computed by ncm_lapack_dpotrf().

This function computes the solution of $A X = B$ for a real symmetric positive definite matrix a = A using the Cholesky factorization $A = U^TU$ or $A = LL^T$ already performed by ncm_lapack_dpotrf(). On entry b contain the vectors $B$ and on exit b contain the solutions if the return is 0.

This function computes the solution to a real system of linear equations $A*X = B$ (B = b), where $A$ is an N-by-N (N = n) symmetric positive definite tridiagonal matrix, and $X$ and $B$ are N-by-NRHS (NRHS = 1) matrices.

Computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix a.

Computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix a.

Purpose #.

Purpose #.

Purpose #.

This function computes the factorization of a real symmetric matrix a, using the Bunch-Kaufman diagonal pivoting method.

This function compute the inverse of a real symmetric indefinite matrix a using the factorization a = UDUT or a = LDLT computed by ncm_lapack_dsytrf().

This function computes the solution of $A X = B$ for a real symmetric positive definite matrix a = A using the Cholesky factorization $A = U^TU$ or $A = LL^T$ already performed by ncm_lapack_dpotrf(). On entry b contain the vectors $B$ and on exit b contain the solutions if the return is 0.

Logs a message.

Logs a message string.

Logs a word wrapped message.

Computes the Hypergeometric function ${}_0F_1(b;x)$.

Frees all buffers created to compute ncm_mpsf_0F1.

Computes the Hypergeometric function ${}_0F_1(b;x)$.

Computes the Spherical Bessel function $j_\ell(x)$.

Computes the Spherical Bessel function $j_\ell(x)$.

Frees all buffers created to compute ncm_mpsf_sbessel functions.

Computes the sine integral $$\mathrm{Si}(x) = \int_0^x \frac{\sin x’}{x’}\mathrm{d}x.$$.

Clears z and all the #mpz_t in the list.

Initializes z and all the #mpz_t in the list.

Computes a rational approximation for x and stores the result in q.

Computes the Hypergeometric function ${}_0F_1(b;x)$.

Computes Spherical Bessel function $j_\ell(x)$.

Computes a spline approximation of the Spherical Bessel $j_\ell$ in the interval $[x_i, x_f]$.

Computes Spherical Bessel function power series coefficients up to order three, i.e., $$\left(j_\ell(x),\; j’\ell(x), \frac{j”\ell(x)}{2!}, \frac{j”’_\ell(x)}{3!}\right).$$.

Computes the sine integral $$\mathrm{Si}(x) = \int_0^x \frac{\sin x’}{x’}\mathrm{d}x.$$.

Creates a word wrapped string.

Calculates $1 - \cos(x)$ using the appropriated taylor series when $\cos(x) \approx 1$.

Calculates $1 - \sin(x)$ using the appropriated taylor series when $\sin(x) \approx 1$.

Calculates $1 + \cos(x)$ using the appropriated taylor series when $\cos(x) \approx -1$.

Calculates $1 + \sin(x)$ using the appropriated taylor series when $\sin(x) \approx -1$.

Extracts the extension .fits or .fit from fits_filename and returns the prefix. If the extension is not found a copy of fits_filename is returned.

Calculates $\cos(2x)$ using the appropriated taylor series when $\sin(x) \approx 1$.

Checks the CVode flag value and prints a message if an error occured.

Prints the statistics of the CVodeMem object cvode.

Calculate the smallest factorization of n such that $n_f = 2^\mu \times 3^\nu \times 5^\alpha \times 7^\beta$ and $n_f \geq n$.

Forwards the error from local_error, adding a prefix message formatted with format and its arguments, if local_error is not NULL. If local_error is NULL, the function does nothing. If error is not NULL, the function forwards local_error to error. If error is NULL, the function calls g_error with local_error.

Extracts the function name and its numerical parameters.

Computes the integral of the Gaussian distribution with mean mu and standard deviation sigma between xl and xu.

Compute the great circle distance (or separation, as defined in astropy) between poistion 1 (ra1, dec1) and position 2 (ra2, dec2). See Great-circle distance, in particular the Vincenty equation (implemented here). The input coordinates ((ra1, dec1), (ra2, dec2)) must be given in decimal degrees.

Calculates $\ln[1+\exp(x)]$.

Computes the logarithm of the integral of the Gaussian distribution with mean mu and standard deviation sigma between xl and xu. Uses the standard normal log integral. If sign is not NULL, the sign of the result (+/-1) is stored in *sign.

Computes the logarithm of the integral of the Gaussian distribution with zero mean and unit variance between xl and xu. If sign is not NULL, the sign of the result (+/-1) is stored in *sign.

Computes $$z_1 = z - \ln\left(\frac{1-i e^{+z} A}{1+i e^{-z} A}\right),$$ where $z = \rho + i\theta$ and return the new $z_1 = \rho_1 + i\theta_1$ into rho1 and $\theta1$.

Computes the integral of the Gaussian distribution with zero mean and unit variance between xl and xu.

Computes the on-sky position angle (East of North) between object1 (ra1, dec1) and object2 (ra2, dec2). The input coordinates ((ra1, dec1), (ra2, dec2)) must be given in decimal degrees.

Converts the the angular separation $\theta$' of a galaxy at redshift$z$’ to the projected physical distance in Mpc.

If error is not NULL, it sets the error message, otherwise it calls g_error. The error message is formatted using format and the arguments.

Computes $\frac{\sinh(x)}{x}$. For small values of x the taylor series is used. For large values of x the value is computed using the standard library function.

Suspend the thread execution for milliseconds.

Calculates $\sqrt{1+x}-1$ using the appropriated expression to avoid round-off when $x \approx 0$.

Initializes a NcmDTuple2 with the given elements.

Initializes a NcmDTuple3 with the given elements.

A convenience macro to define a subclass of NcmIntegralND with a custom user data type.

A convenience macro to define a subclass of NcmIntegralND with a custom user data type and a custom method to free the user data.

Declares a function to get the model id from the model namespace. This macro should be used in the header file of the model.

Defines a function to get the model id from the model namespace.

Defines the function to get the model id from the model namespace. This macro should be used in the source file of the model.

This macro declares a callback structure and the functions to handle it. You must use NCM_UTIL_CALLBACK_ARGS to declare the arguments of the callback function. The argument arg_decl can be empty.

This macro defines the functions to handle the callback structure. You must use NCM_UTIL_CALLBACK_ARGS to declare both the arguments declaration of the callback function and the arguments of the function. They can be empty.

GVariant type string for NcmDTuple2.

GVariant type string for NcmDTuple3.

Id of a main model. Used to identify the main model in hierarchy of models.