The global namespace of the CosmoBolognaLib More...

Namespaces
	catalogue
	The namespace of the functions and classes used to handle catalogues of astronomical sources

	chainmesh
	The namespace of the functions and classes used for the chain-mesh method

	cosmology
	The namespace of the functions and classes used for cosmological calculations

	data
	The namespace of the functions and classes used to handle data of any kind.

	glob
	The namespace of the functions and classes of internal auxiliary use

	lognormal
	The namespace of the functions and classes used to construct log-normal mocks

	measure
	The namespace of the functions and classes used to manage any kind of measure

	modelling
	The namespace of the functions and classes used for modelling

	pairs
	The namespace of the functions and classes used to handle pairs of objects

	par
	The namespace of the global parameters and constants

	random
	The namespace of the functions and classes used to handle random numbers

	statistics
	The namespace of the functions and classes used for statistical analyses

	triplets
	The namespace of the functions and classes used to handle triplets of objects

	wrapper
	The namespace of the wrappers

Classes
class	Path
	The class Path. More...

Typedefs
typedef Eigen::Matrix< double, 3, 1 >	Vector3D
	Eigen 3D std::vector.

typedef Eigen::Matrix< double, 4, 1 >	Vector4D
	Eigen 4D matrix.

typedef Eigen::Matrix< std::complex< double >, 1, Eigen::Dynamic >	VectorComplex
	Eigen complex std::vector.

typedef std::function< double(double)>	FunctionDoubleDouble
	typedef of a function returning a double with a double in input

typedef std::function< double(std::vector< double >)>	FunctionDoubleVector
	typedef of a function returning a double with a vector in input

typedef std::function< double(std::vector< double > &)>	FunctionDoubleVectorRef
	typedef of a function returning a double with a vector reference in input

typedef std::function< double(double, std::shared_ptr< void >, std::vector< double > &)>	FunctionDoubleDoublePtrVectorRef
	typedef of a function returning a double with a double, a pointer and a vector reference in input

typedef std::function< double(double, double, std::shared_ptr< void >, std::vector< double > &)>	FunctionDoubleDoubleDoublePtrVectorRef
	typedef of a function returning a double with two double, a pointer and a vector reference in input

typedef std::function< double(std::vector< double >, std::shared_ptr< void >, std::vector< double > &)>	FunctionDoubleVectorPtrVectorRef
	typedef of a function returning a double with a vector, a pointer and a vector reference in input

typedef std::function< std::vector< double >std::vector< double >, std::shared_ptr< void >, std::vector< double > &)>	FunctionVectorVectorPtrVectorRef
	typedef of a function returning a vector with a vector, a pointer and a vector reference in input

typedef std::vector< std::vector< std::vector< int > > >	Tensor3Di
	typedef of a 3D Tensor of int

typedef std::vector< std::vector< std::vector< double > > >	Tensor3Dd
	typedef of a 3D Tensor of double

typedef std::vector< std::vector< std::vector< std::vector< int > > > >	Tensor4Di
	typedef of a 4D Tensor of int

typedef std::function< double(double, std::shared_ptr< void >, std::vector< double >)>	distribution_func
	generic distribution function More...

typedef std::function< double(std::vector< double >, std::shared_ptr< void >)>	nDim_distribution_func
	distribution function used for a n-dimensional distribution More...

Enumerations
enum class	Dim { _1D_ , _2D_ }
	the dimension, used e.g. for pair and triplet vectors More...

enum class	BinType { _linear_ , _logarithmic_ , _custom_ }
	the binning type More...

enum class	CoordinateUnits { _radians_ , _degrees_ , _arcseconds_ , _arcminutes_ }
	the coordinate units More...

enum class	CoordinateType { _comoving_ , _observed_ }
	the coordinate type More...

Functions
template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>
T	castFromValue (const int i)
	cast an object of type enum class from its index More...

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>
T	castFromName (const std::string name, const std::vector< std::string > list)
	cast an object of type enum class from its name More...

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>
std::vector< T >	castFromValues (const std::vector< int > ii)
	cast objects of type enum class from indeces More...

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>
std::vector< T >	castFromNames (const std::vector< std::string > names, const std::vector< std::string > list)
	cast an object of type enum class from names More...

std::vector< std::string >	DimNames ()
	return a vector containing the Dim names More...

std::vector< std::string >	BinTypeNames ()
	return a vector containing the BinType names More...

BinType	BinTypeCast (const int binTypeIndex)
	cast an enum of type BinType from its index More...

BinType	BinTypeCast (const std::string binTypeName)
	cast an enum of type BinType from its name More...

std::vector< BinType >	BinTypeCast (const std::vector< int > binTypeIndeces)
	cast an enum of type BinType from indeces More...

std::vector< BinType >	BinTypeCast (const std::vector< std::string > binTypeNames)
	cast an enum of type BinType from thier names More...

std::vector< std::string >	CoordinateUnitsNames ()
	return a std::vector containing the CoordinateUnits names More...

CoordinateUnits	CoordinateUnitsCast (const int coordinateUnitsIndex)
	cast an enum of type CoordinateUnits from its index More...

CoordinateUnits	CoordinateUnitsCast (const std::string coordinateUnitsName)
	cast an enum of type CoordinateUnits from its name More...

std::vector< CoordinateUnits >	CoordinateUnitsCast (const std::vector< int > coordinateUnitsIndeces)
	cast an enum of type CoordinateUnits from indeces More...

std::vector< CoordinateUnits >	CoordinateUnitsCast (const std::vector< std::string > coordinateUnitsNames)
	cast an enum of type CoordinateUnits from thier names More...

std::vector< std::string >	CoordinateTypeNames ()
	return a std::vector containing the CoordinateType names More...

CoordinateType	CoordinateTypeCast (const int coordinateTypeIndex)
	cast an enum of type CoordinateType from its index More...

CoordinateType	CoordinateTypeCast (const std::string coordinateTypeName)
	cast an enum of type CoordinateType from its name More...

std::vector< CoordinateType >	CoordinateTypeCast (const std::vector< int > coordinateTypeIndeces)
	cast an enum of type CoordinateType from indeces More...

std::vector< CoordinateType >	CoordinateTypeCast (const std::vector< std::string > coordinateTypeNames)
	cast an enum of type CoordinateType from thier names More...

Functions of generic use
double	interpolated (const double _xx, const std::vector< double > xx, const std::vector< double > yy, const std::string type)
	1D interpolation More...

double	interpolated_2D (const double _x1, const double _x2, const std::vector< double > x1, const std::vector< double > x2, const std::vector< std::vector< double >> yy, const std::string type)
	2D interpolation More...

std::vector< double >	linear_interpolation_3D (const std::vector< double > min, std::vector< double > max, std::vector< int > steps, std::vector< std::vector< std::vector< double >>> func, const std::vector< std::vector< double >> pos)
	3D interpolation on a 3D regular grid More...

double	Filter (const double r, const double rc)
	filter W(r/r_c), used e.g. for filtering the correlation function More...

double	legendre_polynomial (const double mu, const int l)
	the order l Legendre polynomial More...

double	legendre_polynomial_integral (double mu, void *params)
	the order l Legendre polynomial integrand More...

double	Legendre_polynomial_mu_average (const int ll, const double mu, const double delta_mu)
	the average of the Legendre polynomial of the l-th order over the mu range More...

double	Legendre_polynomial_mu_average (const double mu_min, const double mu_max, const int ll)
	the average of the Legendre polynomial of the l-th order over the \(\mu=\cos(\theta)\) range More...

double	Legendre_polynomial_theta_average (const double theta_min, const double theta_max, const int ll)
	the average of the Legendre polynomial of the l-th order over the \(\theta\) range More...

double	Legendre_polynomial_triangles_average (const double r12_min, const double r12_max, const double r13_min, const double r13_max, const double r23_min, const double r23_max, const int ll, const double rel_err=1.e-5, const double abs_err=1.e-8, const int nevals=100)
	the average of the Legendre polynomial of the l-th order over the \(r_{12}, r_{13}, r_{23} \) More...

std::vector< std::vector< double > >	Legendre_polynomial_triangles_average (const double r12, const double r13, const double deltaR, const int lMax, const double rel_err=1.e-5, const double abs_err=1.e-8, const int nevals=100)
	the average of the Legendre polynomial up to a maximum order lMax of all triangles with sides r12, r13 More...

std::complex< double >	spherical_harmonics (cbl::CoordinateType coordinate_type, const int l, const int m, const double coord1, const double coord2, const double coord3)
	the order l, degree m spherical harmonics More...

std::vector< std::vector< std::complex< double > > >	spherical_harmonics (const int lmax, const double xx, const double yy, const double zz)
	the spherical harmonics up to \(l_{max}\) More...

std::vector< std::complex< double > >	spherical_harmonics_array (const int lmax, const double xx, const double yy, const double zz)
	the spherical harmonics up to \(l_{max}\) More...

double	j0 (const double xx)
	the l=0 spherical Bessel function More...

double	j2 (const double xx)
	the l=2 spherical Bessel function More...

double	j4 (const double xx)
	the l=4 spherical Bessel function More...

double	jl (const double xx, const int order)
	the order l spherical Bessel function More...

double	j0_distance_average (const double kk, const double r_down, const double r_up)
	the distance average l=0 spherical Bessel function this function is used to obtain the analytic twop monopole covariance More...

double	j2_distance_average (const double kk, const double r_down, const double r_up)
	the distance average l=2 spherical Bessel function this function is used to obtain the analytic twop quadrupole covariance More...

double	jl_spherical_integrand (double rr, void *params)
	the generic integrand to obtain the distance average spherical Bessel function of order l More...

double	jl_distance_average (const double kk, const int order, const double r_down, const double r_up)
	the distance average for the order l-th spherical Bessel function More...

double	trapezoid_integration (const std::vector< double > xx, const std::vector< double > yy)
	integral, computed with the trapezoid rule, using ordered data More...

double	coupling_3j (const int l, const int l_prime, const int l2)
	compute the Wigner 3-j symbol More...

void	read_vector (const std::string file_vector, std::vector< double > &xx, std::vector< double > &vector, const std::vector< int > col={})
	read a vector from file More...

void	read_matrix (const std::string file_matrix, std::vector< double > &xx, std::vector< double > &yy, std::vector< std::vector< double >> &matrix, const std::vector< int > col={})
	read a matrix from file More...

double	determinant_matrix (const std::vector< std::vector< double >> mat)
	compute the determinant of a matrix More...

void	invert_matrix (const std::vector< std::vector< double >> mat, std::vector< std::vector< double >> &mat_inv, const double prec=1.e-10, const int Nres=-1)
	function to invert a matrix More...

void	invert_matrix (const std::vector< std::vector< double >> mat, std::vector< std::vector< double >> &mat_inv, const int i1, const int i2, const double prec=1.e-10, const int Nres=-1)
	function to invert a sub-matrix, extracted from a given matrix More...

void	covariance_matrix (const std::vector< std::vector< double >> mat, std::vector< std::vector< double >> &cov, const bool JK=false)
	compute the covariance matrix from an input dataset More...

void	covariance_matrix (const std::vector< std::string > file, std::vector< double > &rad, std::vector< double > &mean, std::vector< std::vector< double >> &cov, const bool JK=false)
	compute the covariance matrix, reading the dataset from files More...

void	covariance_matrix (const std::vector< std::string > file, const std::string covariance_matrix_file, const bool JK=0)
	compute the covariance matrix, reading the dataset from files, and store it in a file More...

void	read_invert_covariance (const std::string filecov, std::vector< std::vector< double >> &cov, std::vector< std::vector< double >> &cov_inv, const size_t i1, const size_t i2, const double prec=1.e-10, const int Nres=-1)
	read and invert the covariance matrix More...

double	number_from_distribution (const std::vector< double > xx, const std::vector< double > fx, const double xmin, const double xmax, const int seed)
	return a number sampled from a given distribution More...

std::vector< double >	vector_from_distribution (const int nRan, const std::vector< double > xx, const std::vector< double > fx, const double xmin, const double xmax, const int seed)
	return a std::vector of numbers sampled from a given distribution More...

std::vector< size_t >	minimum_maximum_indexes (const std::vector< double > xx, const double x_min, const double x_max)
	return the std::vector indexes corresponding to a given interval More...

double	get_mu (const double r1, const double r2, const double r3)
	get the cosine of the angle between two sides of a triangle More...

double	window_function (const double x, const double min=-1, const double max=1)
	the unnormalized window function More...

double	binomial_coefficient (const int n, const int m)
	get the binomial coefficient More...

double	clebsh_gordan (const int j1, const int j2, const int m1, const int m2, const int j3, const int m3)
	get the Clebsh-Gordan coefficient in the notation \( \sum_{l}\left\langle l_1 l_2 m_1 m_2 \| l_3 m_3 \right\rangle \) More...

template<typename T >
double	sgn (T val)
	sgn the sign function More...

double	wigner3j_auxA (double l1, double l2, double l3, double m1, double m2, double m3)
	Wigner \(3-j\) auxiliar function A. More...

double	wigner3j_auxB (double l1, double l2, double l3, double m1, double m2, double m3)
	Wigner \(3-j\) auxiliar function B. More...

std::vector< double >	wigner3j (double l2, double l3, double m1, double m2, double m3)
	Wigner \(3-j\) symbol. More...

double	wigner3j (double l1, double l2, double l3, double m1, double m2, double m3)
	Wigner \(3-j\) symbol. More...

double	wigner_3j (int j1, int j2, int j3, int m1, int m2, int m3)
	Wigner \(3-j\) symbol, use it for l<100. More...

double	wigner_6j (const int j1, const int j2, const int j3, const int j4, const int j5, const int j6)
	Wigner \(6-j\) symbol. More...

double	three_spherical_bessel_integral (const double r1, const double r2, const double r3, const int L1, const int L2, const int L3)
	compute the integral of three spherical bessel function, from Mehrem (2011) More...

double	average_three_spherical_bessel_integral (const double r1_min, const double r1_max, const double r2_min, const double r2_max, const double r3, const int L1, const int L2, const int L3)
	compute the integral of three spherical bessel function, from Mehrem (2011), averaged on r1-r2 shells More...

std::vector< double >	generate_correlated_data (const std::vector< double > mean, const std::vector< std::vector< double >> covariance, const int idum=213123)
	generate a covariant sample of n points using a covariance matrix More...

std::vector< std::vector< double > >	generate_correlated_data (const int nExtractions, const std::vector< double > mean, const std::vector< std::vector< double >> covariance, const int idum=12312)
	generate a covariant sample of n points using a covariance matrix More...

template<typename T >
void	vectorReadFromBinary (std::ifstream &fin, std::vector< T > &vec, size_t NN)
	reads a vector from a binary file More...

Functions for statistical analyses
double	Average (const std::vector< double > vect)
	the average of a std::vector More...

double	Average (const std::vector< double > vect, const std::vector< double > weight)
	the weighted average of a std::vector More...

double	Sigma (const std::vector< double > vect)
	the standard deviation of a std::vector More...

double	Sigma (const std::vector< double > vect, const std::vector< double > weight)
	the weighted standard deviation of a std::vector More...

std::vector< double >	Quartile (const std::vector< double > Vect)
	the first, second and third quartiles of a std::vector More...

void	Moment (const std::vector< double > data, double &ave, double &adev, double &sdev, double &var, double &skew, double &curt)
	compute the moments of a set of data More...

Special functions
template<typename T >
T	Pol2 (T xx, std::shared_ptr< void > pp, std::vector< double > par)
	the quadratic function More...

template<typename T >
T	Pol3 (T xx, void *pp, std::vector< double > par)
	the cubic function More...

std::vector< double >	linearfit (const double xx)
	linear function More...

std::vector< double >	quadratic (const double xx)
	quadratic function More...

std::vector< double >	cubicfit (const double xx)
	cubic function More...

template<typename T >
T	identity (T xx, std::shared_ptr< void > pp, std::vector< double > par)
	the Identity function More...

template<typename T >
T	rectangular (T xx, std::shared_ptr< void > pp, std::vector< double > par)
	the rectangular distribution More...

double	closest_probability (double xx, std::shared_ptr< void > pp, std::vector< double > par)
	probability of the closest element to x from a list with weights More...

double	distribution_probability (double xx, std::shared_ptr< void > pp, std::vector< double > par)
	probability of an interpolated distribution More...

double	chainMeshInterpolate (std::vector< double > xx, std::shared_ptr< void > pars)
	a multidimension interpolator More...

double	multivariateGaussian (std::vector< double > xx, std::shared_ptr< void > pars)
	the multivariate Gaussian function More...

template<typename T >
T	gaussian (T xx, std::shared_ptr< void > pp, std::vector< double > par)
	the Gaussian function More...

template<typename T >
T	poisson (T xx, std::shared_ptr< void > pp, std::vector< double > par)
	the poisson distribution More...

template<typename T >
T	maxwellian_distr (const T vel, const T sigma)
	the Maxwellian distribution More...

template<typename T >
T	powerlaw (const T xx, const T x0, const T gamma)
	the power-law function More...

template<typename T >
T	double_powerlaw (const T xx, const T x0, const T alpha, const T beta)
	the double power-law function More...

template<typename T >
T	TopHat_WF (const T kR)
	the top-hat window function More...

template<typename T >
T	TopHat_WF_D1 (const T kR)
	the derivative of the top-hat window function More...

template<typename T >
T	Radius (const T Mass, const T Rho)
	the radius of a sphere of a given mass and density More...

template<typename T >
T	volume_sphere (const T RR)
	the volume of a sphere of a given radius More...

template<typename T >
T	Mass (const T RR, const T Rho)
	the mass of a sphere of a given radius and density More...

template<typename T >
T	radial_velocity (const T vx, const T vy, const T vz, const T ra, const T dec)
	the radial velocity More...

template<typename T >
T	P_2 (const T x)
	the Legendre polynomial P₂ More...

template<typename T >
T	P_4 (const T x)
	the Legendre polynomial P₄ More...

template<typename T >
T	P_6 (const T x)
	the Legendre polynomial P₆ More...

Generic operations on functions
void	measure_var_function (const std::vector< double > var, const int bin, const double V_min, const double V_max, const double Volume, std::vector< double > &Var, std::vector< double > &Phi, std::vector< double > &err)
	measure the var function (where "var" could be the mass, the luminosity, the radius, etc.) More...

void	distribution (std::vector< double > &xx, std::vector< double > &fx, std::vector< double > &err, const std::vector< double > FF, const std::vector< double > WW, const int nbin, const bool linear=true, const std::string file_out=par::defaultString, const double fact=1., const double V1=par::defaultDouble, const double V2=par::defaultDouble, const std::string bin_type="Linear", const bool conv=false, const double sigma=0.)
	derive and store the number distribution of a given std::vector More...

double	MC_Int (double func(const double), const double x1, const double x2, const int seed=3213)
	simple Monte Carlo integration of f(x) More...

double	MC_Int (double func(const double, const double AA), const double AA, const double x1, double x2, const int seed=3213)
	simple Monte Carlo integration of f(x,A) More...

double	MC_Int (double func(const double, const double AA, const double BB, const double CC, const double DD, const double EE), const double AA, const double BB, const double CC, const double DD, const double EE, const double x1, const double x2, const int seed=3213)
	simple Monte Carlo integration of f(x,A,B,C,D,E) More...

void	bin_function (const std::string file_grid, double func(double, void ), void par, const int bin, const double x_min, const double x_max, const std::string binning, std::vector< double > &xx, std::vector< double > &yy)
	create a 1D grid given an input function More...

void	bin_function_2D (const std::string file_grid, double func(double , size_t, void ), void *par, const int bin, const double x1_min, const double x1_max, const double x2_min, const double x2_max, const std::string binning, std::vector< double > &xx1, std::vector< double > &xx2, std::vector< std::vector< double >> &yy)
	create a 2D grid given an input function More...

void	convolution (const std::vector< double > f1, const std::vector< double > f2, std::vector< double > &res, const double deltaX)
	convolution of two functions More...

Functions to calculate distances
double	degrees (const double angle, const CoordinateUnits inputUnits=CoordinateUnits::_radians_)
	conversion to degrees More...

double	radians (const double angle, const CoordinateUnits inputUnits=CoordinateUnits::_degrees_)
	conversion to radians More...

double	arcseconds (const double angle, const CoordinateUnits inputUnits=CoordinateUnits::_radians_)
	conversion to arcseconds More...

double	arcminutes (const double angle, const CoordinateUnits inputUnits=CoordinateUnits::_radians_)
	conversion to arcminutes More...

double	converted_angle (const double angle, const CoordinateUnits inputUnits=CoordinateUnits::_radians_, const CoordinateUnits outputUnits=CoordinateUnits::_degrees_)
	conversion to angle units More...

void	polar_coord (const double XX, const double YY, const double ZZ, double &ra, double &dec, double &dd)
	conversion from Cartesian coordinates to polar coordinates More...

void	cartesian_coord (const double ra, const double dec, const double dd, double &XX, double &YY, double &ZZ)
	conversion from polar coordinates to Cartesian coordinates More...

void	polar_coord (const std::vector< double > XX, const std::vector< double > YY, const std::vector< double > ZZ, std::vector< double > &ra, std::vector< double > &dec, std::vector< double > &dd)
	conversion from Cartesian coordinates to polar coordinates used for a set of objects More...

void	cartesian_coord (const std::vector< double > ra, const std::vector< double > dec, const std::vector< double > dd, std::vector< double > &XX, std::vector< double > &YY, std::vector< double > &ZZ)
	conversion from polar coordinates to Cartesian coordinates used for a set of objects More...

double	Euclidean_distance (const double x1, const double x2, const double y1, const double y2, const double z1, const double z2)
	the Euclidean distance in 3D relative to the origin (0,0,0), i.e. the Euclidean norm More...

double	perpendicular_distance (const double ra1, const double ra2, const double dec1, const double dec2, const double d1, const double d2)
	the perpendicular separation, r_p More...

double	angular_distance (const double x1, const double x2, const double y1, const double y2, const double z1, const double z2)
	the angular separation in 3D More...

double	haversine_distance (const double ra1, const double ra2, const double dec1, const double dec2)
	the haversine angular separation More...

void	sdss_atbound (double &angle, const double minval, const double maxval)
	check if ra coordinate is inside the boundaries More...

void	sdss_atbound2 (double &theta, double &phi)
	set the angular coordinates in the SDSS boundaries More...

void	eq2sdss (const std::vector< double > ra, const std::vector< double > dec, std::vector< double > &lambda, std::vector< double > &eta)
	convert from equatorial coordinates R.A., Dec to sdss coordinates \( \lambda, \eta \) More...

void	sdss2eq (const std::vector< double > lambda, const std::vector< double > eta, std::vector< double > &ra, std::vector< double > &dec)
	convert sdss coordinates \( \lambda, \eta \) to R.A., Dec. More...

void	sdss_stripe (const std::vector< double > eta, const std::vector< double > lambda, std::vector< int > &stripe, std::vector< int > &str_u)
	compute the SDSS stripe given SDSS coordinates \( \lambda, \eta \) More...

Functions to model the correlation function
double	xi_from_Pk (const double rr, const std::vector< double > lgkk, const std::vector< double > lgPk, const double k_min=0., const double k_max=100., const double aa=0., const double prec=1.e-2)
	the two-point correlation function computed from the Fourier transform of the power spectrum More...

double	xi_from_Pk (const double rr, const std::string file, const int c1=1, const int c2=2, const double k_min=0., const double k_max=100., const double aa=0., const double prec=1.e-2)
	the two-point correlation function computed from the Fourier transform of the power spectrum read from a file More...

double	Pk_from_xi (const double kk, const std::vector< double > lgrr, const std::vector< double > lgxi, const double r_min=0.03, const double r_max=100.)
	the power spectrum computed from the Fourier transform of the two-point correlation function More...

double	Pk_from_xi (const double kk, const std::string file, const int c1=1, const int c2=2, const double r_min=0.03, const double r_max=100.)
	the power spectrum computed from the Fourier transform of the two-point correlation function read from a file More...

double	wp (const double rp, const std::vector< double > rr, const std::vector< double > xi, const double r_max=100.)
	the projected two-point correlation function More...

double	wp (const double rp, const std::string file, const double r_max=100.)
	the projected two-point correlation function More...

double	sigmaR (const double RR, const int corrType, const std::vector< double > rr, const std::vector< double > corr)
	the rms mass fluctuation within a given radius More...

double	xi_projected_powerlaw (const double rp, const double r0, const double gamma)
	the projected correlation function, w_p(r_p), computed by modelling the two-point correlation function, ξ(r), as a power-law More...

double	xi_ratio (const double beta)
	the ratio between the redshift-space and real-space correlation functions More...

double	xi_ratio (const double f_sigma8, const double bias_sigma8)
	the ratio between the redshift-space and real-space correlation functions More...

double	error_xi_ratio (const double beta, const double error_beta)
	error on the ratio between the redshift-space and real-space correlation functions More...

double	barred_xi_direct (const double RR, const std::vector< double > rr, const std::vector< double > xi, const double rAPP=0., const double r0=-1., const double gamma=1.)
	the barred correlation function More...

double	barred_xi__direct (const double RR, const std::vector< double > rr, const std::vector< double > xi, const double rAPP=0., const double r0=-1., const double gamma=1.)
	the double barred correlation function More...

double	barred_xi_ (const double RR, const std::vector< double > rr, const std::vector< double > xi, const double rAPP=0., const double r0=-1., const double gamma=1.)
	the barred correlation function More...

double	barred_xi__ (const double RR, const std::vector< double > rr, const std::vector< double > xi, const double rAPP=0., const double r0=-1., const double gamma=1.)
	the double barred correlation function More...

double	multipole_xi0 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> xi)
	xi₀(s) from ξ(r,μ) More...

double	multipole_xi2 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> xi)
	xi₂(s) from ξ(r,μ) More...

double	multipole_xi4 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> xi)
	xi₄(s) from ξ(r,μ) More...

double	error_multipole_xi0 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> error)
	error on xi₀(s) from ξ(r,μ) More...

double	error_multipole_xi2 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> error)
	error on xi₂(s) from ξ(r,μ) More...

double	error_multipole_xi4 (const int indexR, const std::vector< double > mu, const std::vector< std::vector< double >> error)
	error on xi₄(s) from ξ(r,μ) More...

double	multipole_xi0 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> xi, const double delta_s)
	xi₀(s) from ξ(r_p,π) More...

double	multipole_xi2 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> xi, const double delta_s)
	xi₂(s) from ξ(r_p,π) More...

double	multipole_xi4 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> xi, const double delta_s)
	xi₄(s) from ξ(r_p,π) More...

double	error_multipole_xi0 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> error, const double delta_s)
	error on xi₀(s) from ξ(r_p,π) More...

double	error_multipole_xi2 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> error, const double delta_s)
	error on xi₂(s) from ξ(r_p,π) More...

double	error_multipole_xi4 (const double ss, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double >> error, const double delta_s)
	error on xi₄(s) from ξ(r_p,π) More...

double	multipole_xi0_model (const double beta, const double xi_real)
	the model multipole ξ₀ of the two-point correlation function More...

double	multipole_xi0_model (const double f_sigma8, const double bias_sigma8, const double sigma8z, const double xi_matter)
	the model multipole ξ₀ of the two-point correlation function More...

double	multipole_xi2_model (const double beta, const double xi_real, const double xi_)
	the model multipole ξ₂ of the two-point correlation function More...

double	multipole_xi4_model (const double beta, const double xi_real, const double xi_, const double xi__)
	the model multipole ξ₄ of the two-point correlation function More...

double	xi2D_lin_model (const double beta, const double bias, const double xi_real, const double xi_, const double xi__, const double P_2, const double P_4)
	the linear dispersion model for ξ(r_p,π) More...

double	xi2D_lin_model (const double rp, const double pi, const double beta, const double bias, const std::vector< double > rad_real, const std::vector< double > xi_real, const std::vector< double > xi_, const std::vector< double > xi__, const int index=-1, const bool bias_nl=0, const double bA=0.)
	the linear dispersion model for ξ(r_p,π) More...

double	xi2D_model (const double rp, const double pi, const double beta, const double bias, const double sigmav, const std::vector< double > rad_real, const std::vector< double > xi_real, const std::vector< double > xi_, const std::vector< double > xi__, const double var, const int FV, int index=-1, const bool bias_nl=0, const double bA=0., const double v_min=-3000., const double v_max=3000., const int step_v=500)
	the non-linear dispersion model for ξ(r_p,π) More...

double	xi2D_lin_model (const double rp, const double pi, const double beta, const double bias, const std::shared_ptr< void > funcXiR, const std::shared_ptr< void > funcXiR_, const std::shared_ptr< void > funcXiR__, const bool bias_nl=0, const double bA=0.)
	the linear dispersion model for ξ(r_p,π) More...

double	xi2D_model (const double rp, const double pi, const double beta, const double bias, const double sigmav, const std::shared_ptr< void > funcXiR, const std::shared_ptr< void > funcXiR_, const std::shared_ptr< void > funcXiR__, const double var, const int FV, const bool bias_nl=0, const double bA=0., const double v_min=-3000., const double v_max=3000., const int step_v=500)
	the non-linear dispersion model for ξ(r_p,π) More...

double	f_v (const double vel, const double sigmav, const int FV)
	pairwise velocity distribution More...

double	f_v (const double vel, const double rp, const double pi, const double var, const double sigmav0, const double cmu, const double cs1, const double cs2)
	pairwise velocity distribution More...

double	f_star (const double xx, const double f_g, const double k_star)
	velocity distribution used to model BAO More...

double	b_nl (const double rr, const double bA, const double bB=10., const double bC=4.)
	a possible parameterization of the non-linear bias More...

double	relative_error_beta (const double bias, const double Volume, const double density)
	estimated relative error on \(\beta=f/b\) More...

double	Pkl_Kaiser_integrand (const double mu, void *parameters)
	integrand of the 2d power spectrum to obtain power spectrum multipole More...

double	sigma2_integrand (const double mu, void *parameters)
	integrand of the 2d power spectrum to obtain sigma^2(k) More...

double	covariance_XiMultipoles_integrand (const double kk, void *parameters)
	integrand to obtain the 2PCF multipoles More...

double	XiMultipoles_integrand (const double kk, void *parameters)
	integrand to obtain covariance for the 2PCF multipoles More...

double	XiMultipoles_from_Xi2D_integrand (const double mu, void *parameters)
	integrand to obtain the 2PCF multipoles from 2D 2pcf in polar coordinates More...

double	Pkl_Kaiser_integral (const int order, const double bias, const double f)
	function to obtain the Kaiser factor More...

std::vector< double >	Pk0_Kaiser (const std::vector< double > kk, const std::vector< double > Pk, const double bias, const double f)
	function to obtain the linear RSD power spectrum monopole More...

std::vector< double >	Pk2_Kaiser (const std::vector< double > kk, const std::vector< double > Pk, const double bias, const double f)
	function to obtain the linear RSD power spectrum quadrupole More...

std::vector< double >	Pk4_Kaiser (const std::vector< double > kk, const std::vector< double > Pk, const double bias, const double f)
	function to obtain the linear RSD power spectrum hexadecapole More...

std::vector< std::vector< double > >	Pkl_Kaiser (const std::vector< int > orders, const std::vector< double > kk, const std::vector< double > Pk, const double bias, const double f)
	function to obtain Pk multipoles from linear RSD (Kaiser) More...

std::vector< double >	Xi0 (const std::vector< double > r, const std::vector< double > kk, const std::vector< double > Pk0, const double k_cut=0.7, const double cut_pow=2, const int IntegrationMethod=1)
	function to obtain the two point correlation funciton monopole More...

std::vector< double >	Xi2 (const std::vector< double > rr, const std::vector< double > kk, const std::vector< double > Pk2, const double k_cut=0.58, const double cut_pow=4, const int IntegrationMethod=1)
	function to obtain the two point correlation function quadrupole More...

std::vector< double >	Xi4 (const std::vector< double > rr, const std::vector< double > kk, const std::vector< double > Pk4, const double k_cut=0.6, const double cut_pow=2, const int IntegrationMethod=1)
	function to obtain the two point correlation function hexadecapole More...

std::vector< std::vector< double > >	Xi02_AP (const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::vector< double > rl, const std::vector< double > Xi0, const std::vector< double > Xi2)
	function to obtain the monopole and quadrupole of the two point correlation function More...

std::vector< std::vector< double > >	Xi024_AP (const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::vector< double > rl, const std::vector< double > Xi0, const std::vector< double > Xi2, const std::vector< double > Xi4)
	function to obtain the monopole, quadrupole and hexadecapole of the two-point correlation function More...

std::vector< std::vector< double > >	XiWedges_AP (const std::vector< double > mu_min, const std::vector< double > delta_mu, const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::vector< double > rl, const std::vector< double > Xi0, const std::vector< double > Xi2, const std::vector< double > Xi4)
	function to obtain the 2pcf wedges More...

std::vector< std::vector< double > >	sigma2_k (const double nObjects, const double Volume, const std::vector< double > kk, const std::vector< std::vector< double >> Pk_multipoles, const std::vector< int > orders)
	multipole expansion of the per-mode covariance sigma2_k (see Grieb et al. 2016, eq. 15 https://arxiv.org/pdf/1509.04293) More...

void	Covariance_XiMultipoles (std::vector< double > &rr, std::vector< std::vector< double >> &covariance, const int nbins, const double rMin, const double rMax, const double nObjects, const double Volume, const std::vector< double > kk, const std::vector< std::vector< double >> Pk_multipoles, const std::vector< int > orders, const cbl::BinType bin_type=cbl::BinType::_linear_)
	Covariance matrix for two-point correlation multipoles (see Grieb et al. 2016, Eq. 18 https://arxiv.org/pdf/1509.04293) More...

void	Covariance_XiWedges (std::vector< double > &rr, std::vector< std::vector< double >> &covariance, const std::vector< double > mu, const std::vector< double > delta_mu, const int nbins, const double rMin, const double rMax, const double nObjects, const double Volume, const std::vector< double > kk, const std::vector< std::vector< double >> Pk_multipoles, const std::vector< int > orders, const cbl::BinType bin_type=cbl::BinType::_linear_)
	Covariance matrix for two-point correlation wedges (see Grieb et al. 2016, Eq. 19 https://arxiv.org/pdf/1509.04293) More...

std::vector< std::vector< double > >	Xi02_AP (const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::shared_ptr< glob::FuncGrid > xi0_interp, const std::shared_ptr< glob::FuncGrid > xi2_interp)
	function to obtain the monopole and quadrupole of the two point correlation function More...

std::vector< std::vector< double > >	Xi024_AP (const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::shared_ptr< glob::FuncGrid > xi0_interp, const std::shared_ptr< glob::FuncGrid > xi2_interp, const std::shared_ptr< glob::FuncGrid > xi4_interp)
	function to obtain the monopole, quadrupole and hexadecapole of the two-point correlation function More...

std::vector< std::vector< double > >	XiWedges_AP (const std::vector< double > mu_min, const std::vector< double > delta_mu, const double alpha_perpendicular, const double alpha_parallel, const std::vector< double > rr, const std::shared_ptr< glob::FuncGrid > xi0_interp, const std::shared_ptr< glob::FuncGrid > xi2_interp, const std::shared_ptr< glob::FuncGrid > xi4_interp)
	function to obtain the 2pcf wedges More...

Generic functions that use the class Catalogue
catalogue::Catalogue	operator+ (const catalogue::Catalogue &c1, const catalogue::Catalogue &c2)
	overloading of the + operator, to sum two catalogues More...

Generic functions that use the class Cosmology
void	Vmax_DC_distribution (std::vector< double > &dc, std::vector< double > &nObj, const std::vector< double > D_C, const std::vector< double > zobj_min, const std::vector< double > zobj_max, const double z_min, const double z_max, const double zbin_min, const double zbin_max, cosmology::Cosmology &cosm, const double Area, const int nObjRan, const bool norm=1, const std::string file_Vmax=par::defaultString, const double delta_dc_Vmax=100., const int seed=3213)
	get a smoothed distribution of comoving distances, estimated with the V_max method More...

double	AP_shift_r (const double redshift, const cosmology::Cosmology &cosm1, const cosmology::Cosmology &cosm2)
	the Alcock-Pacinski factor used to shift comoving distances More...

double	AP_shift_rp (const double redshift, const cosmology::Cosmology &cosm1, const cosmology::Cosmology &cosm2)
	the Alcock-Pacinski factor used to shift comoving distances perpendicular to the line-of-sight, r_p More...

double	AP_shift_pi (const double redshift, const cosmology::Cosmology &cosm1, const cosmology::Cosmology &cosm2)
	the Alcock-Pacinski factor used to shift comoving distances parallel to the line-of-sight, π More...

void	max_separations_AP (const double Rp_max, const double Pi_max, const double redshift, const cosmology::Cosmology &cosm1, const std::vector< cosmology::Cosmology > &cosm2, double &rpM_AP, double &piM_AP, double &rM_AP)
	the maximum comoving separations to be used for the AP test, for a given set of test cosmologies More...

double	converted_xi (const double RR, const double redshift, const std::vector< double > rr, const std::vector< double > Xi, const cosmology::Cosmology &cosm1, const cosmology::Cosmology &cosm2, const bool direction)
	the 1D two-point correlation function converted from one cosmology to another one More...

double	converted_xi (const double RP, const double PI, const double redshift, const std::vector< double > rp, const std::vector< double > pi, const std::vector< std::vector< double > > Xi, const cosmology::Cosmology &cosm1, const cosmology::Cosmology &cosm2, const bool direction)
	the 2D two-point correlation function converted from one cosmology to another one More...

Generic functions that use one or more classes of the CosmoBolognaLib
void	redshift_range (const double mean_redshift, const double boxSide, cosmology::Cosmology &real_cosm, double &redshift_min, double &redshift_max)
	compute the redsfhit range of a simulation box centered at z=mean_redshift More...

double	volume (const double boxSize, const int frac, const double Bord, const double mean_redshift, cosmology::Cosmology &real_cosm)
	get the volume of a simulation box More...

void	coord_zSpace (std::vector< double > &ra, std::vector< double > &dec, std::vector< double > &redshift, std::vector< double > &xx, std::vector< double > &yy, std::vector< double > &zz, const std::vector< double > vx, const std::vector< double > vy, const std::vector< double > vz, const double sigmaV, cosmology::Cosmology &real_cosm, const double mean_redshift, const double redshift_min, const double redshift_max, const int seed=3213)
	convert a set of coordinates from real-space to redshift-space More...

void	create_mocks (const std::vector< double > xx, const std::vector< double > yy, const std::vector< double > zz, const std::vector< double > vx, const std::vector< double > vy, const std::vector< double > vz, const std::vector< double > var1, const std::vector< double > var2, const std::vector< double > var3, const std::string output_dir, const double boxSize, const int frac, const double Bord, const double mean_redshift, cosmology::Cosmology &real_cosm, const int REAL, const double sigmaV, const int idum, double &Volume)
	create a mock catalogue, subdividing a box into sub-boxes and recentering More...

void	set_ObjectRegion_SubBoxes (catalogue::Catalogue &data, const int nx, const int ny, const int nz)
	set the object region in sub-boxes More...

void	set_ObjectRegion_mangle (catalogue::Catalogue &data, const int nSamples, const std::string polygonfile)
	set the object region in sub-regions using mangle More...

void	set_ObjectRegion_SubBoxes (catalogue::Catalogue &data, catalogue::Catalogue &random, const int nx, const int ny, const int nz)
	set the object region in sub-boxes More...

std::vector< double >	colatitude (std::vector< double > latitude)
	convert to colatitude More...

void	set_ObjectRegion_Tiles_Redshift (catalogue::Catalogue &data, catalogue::Catalogue &random, const int nz)
	set data and random objects' regions given R.A.-Dec tiles and a number of redshift sub-samples. The user must set the identification number of the tiles (cbl::catalogue::Var::_Region_), with cbl::catalogue::Catalogue::set_region(), both in the input data catalogue and in the random catalogue. More...

void	set_ObjectRegion_RaDec (catalogue::Catalogue &data, const int nCells_Ra, const int nCells_Dec, const bool use_colatitude=true)
	set the object region in angular SubBoxes More...

void	set_ObjectRegion_RaDec (catalogue::Catalogue &data, catalogue::Catalogue &random, const int nCells_Ra, const int nCells_Dec, const bool use_colatitude=true)
	set the object region in angular SubBoxes More...

void	set_ObjectRegion_mangle (catalogue::Catalogue &data, catalogue::Catalogue &random, const int nSamples, const std::string polygonfile)
	set the object region in sub-regions using mangle More...

void	set_ObjectRegion_SDSS_stripes (catalogue::Catalogue &data, catalogue::Catalogue &random)
	set the object region in SDSS stripes More...

void	check_regions (catalogue::Catalogue &data, catalogue::Catalogue &random)
	check if the subdivision process produced the correct results More...

Generic functions for density field reconstruction
void	reconstruction_fourier_space (const catalogue::Catalogue data, const catalogue::Catalogue random, const bool random_RSD, const cosmology::Cosmology cosmology, const double redshift, const double bias, const double cell_size, const double smoothing_radius, const int interpolation_type=0)
	compute the non linear displacements of the density field More...

catalogue::Catalogue	displaced_catalogue (const catalogue::Catalogue input_catalogue)
	return a sample with objects displaced, according to the internal variables m_x_displacement, m_y_displacement, m_z_displacement More...

Functions to provide 2PCF/3PCF forecasts
std::vector< double >	fit_covariance_matrix_2PCF_monopole (const std::vector< double > mean, const std::vector< std::vector< double >> mock_xi0, const bool doJK, const cbl::cosmology::Cosmology cosmology, const double nObjects, const double Volume, const double bias, const double redshift, const double rMin, const double rMax, const int nbins, const cbl::BinType bin_type, const std::string method_Pk="CAMB", const double sigma_NL=0., const bool NL=true)
	fit the input covariance matrix using the gaussian model, varying the number of objects and the volume of the sample More...

std::shared_ptr< cbl::data::Data >	generate_mock_2PCF_monopole (const cbl::cosmology::Cosmology cosmology, const double bias, const double nObjects, const double Volume, const double redshift, const double rMin, const double rMax, const int nbins, const cbl::BinType bin_type, const std::string method_Pk="CAMB", const double sigma_NL=0., const bool NL=true)
	generate mock measurementes of the 2PCF monopole from gaussian covariance matrix More...

std::shared_ptr< cbl::data::Data >	generate_mock_2PCF_multipoles (const cbl::cosmology::Cosmology cosmology, const double bias, const double nObjects, const double Volume, const double redshift, const double rMin, const double rMax, const int nbins, const cbl::BinType bin_type, const std::string method_Pk="CAMB", const double sigma_NL=0., const bool NL=true)
	generate mock measurementes of the 2PCF multipoles from gaussian covariance matrix More...

Functions of generic use <br>
std::ostream &	headerCBL (std::ostream &stream)
	provide the header for all internal messages More...

void	WarningMsgCBL (const std::string msg, const std::string functionCBL, const std::string fileCBL)
	internal CBL warning message More...

int	Error (const std::string msg, const cbl::glob::ExitCode exitCode=cbl::glob::ExitCode::_error_, const std::string header="\n")
	throw an exception More...

int	ErrorCBL (const std::string msg, const std::string functionCBL, const std::string fileCBL, const cbl::glob::ExitCode exitCode=cbl::glob::ExitCode::_error_)
	throw an exception: it is used for handling exceptions inside the CosmoBolognaLib More...

void	Beep (const std::string beep="beep")
	produce a beep More...

bool	isSet (const std::string var)
	check if the value of a [string] variable has already been set More...

bool	isSet (const int var)
	check if the value of a [int] variable has already been set More...

bool	isSet (const long var)
	check if the value of a [long] variable has already been set More...

bool	isSet (const double var)
	check if the value of a [double] variable has already been set More...

bool	isSet (const std::vector< double > vect)
	check if the values of a [double] std::vector have already been set More...

bool	isSet (const std::vector< unsigned int > vect)
	check if the values of a [unsigned int] std::vector have already been set More...

bool	isSet (const std::vector< std::vector< unsigned int >> vect)
	check if the values of a [unsigned int] std::vector<std::vector> have already been set More...

template<typename T >
std::string	conv (const T val, const char *fact)
	convert a number to a std::string More...

template<typename T >
int	nint (const T val)
	the nearest integer More...

template<typename T >
T	Log (const T val, const double fact=0.9)
	common logarithm (i.e. logarithm to base 10) More...

template<typename T >
T	Ln (const T val, const double fact=0.9)
	natural logarithm More...

template<typename T >
T	closest (T x, T a, T b)
	given a number x, return the closest of two values a, b More...

template<typename T >
T	index_closest (T x, std::vector< T > vv)
	given a number x, return the index of the closest element to x in vv More...

template<typename T >
T	closest (T x, std::vector< T > values)
	given a number x, return the closest value in a std::vector More...

short	ShortSwap (const short s)
	endian conversion of a short variable More...

int	IntSwap (const int i)
	endian conversion of an integer variable More...

long long	LongSwap (const long long i)
	endian conversion of a long integer variable More...

float	FloatSwap (const float f)
	endian conversion of a float variable More...

double	DoubleSwap (const double d)
	endian conversion of a double variable More...

double	round_to_digits (const double num, const int ndigits)
	reduce the digit figures of an input double More...

double	round_to_precision (const double num, const int ndigits)
	reduce the precision of an input double More...

void	checkIO (const std::ifstream &fin, const std::string file="NULL")
	check if an input file can be opened More...

void	checkIO (const std::ofstream &fout, const std::string file="NULL")
	check if an output file can be opened More...

void	set_EnvVar (const std::vector< std::string > Var)
	set evironment variables More...

void	check_EnvVar (const std::string Var)
	check if an environment variable exists More...

int	used_memory (const int type)
	get the memory used by current process in kB More...

int	check_memory (const double frac, const bool exit=true, const std::string func="", const int type=1)
	check if the memory used by current process is larger than a given fraction of the available memory More...

Functions to manipulate std::vectors and matrices
template<typename T >
void	Print (const T value, const int prec, const int ww, const std::string header="", const std::string end="\n", const bool use_coutCBL=true, std::ostream &stream=std::cout, const std::string colour=cbl::par::col_default)
	function to print values with a proper homegenised format More...

template<typename T >
void	Print (const std::vector< T > vect, const int prec=4, const int ww=8)
	print the elements of a std::vector of non string values on the screen More...

void	Print (const std::vector< std::string > vect)
	print the elements of a std::vector of string values on the screen More...

template<typename T >
void	Print (const std::vector< T > vect1, const std::vector< T > vect2, const int prec=4, const int ww=8)
	print the elements of a two std::vectors of non string values on the screen More...

void	Print (const std::vector< std::string > vect1, const std::vector< std::string > vect2)
	print the elements of two std::vectors of string values on the screen More...

template<typename T >
void	Print (const std::vector< T > vect1, const std::vector< T > vect2, const std::vector< T > vect3, const int prec=4, const int ww=8)
	print the elements of a three std::vectors of non string values on the screen More...

void	Print (const std::vector< std::string > vect1, const std::vector< std::string > vect2, const std::vector< std::string > vect3)
	print the elements of two std::vectors of string values on the screen More...

template<typename T >
void	Print (const std::vector< std::vector< T >> mat, const int prec=4, const int ww=8)
	print the elements of a matrix of non string values on the screen More...

void	Print (const std::vector< std::vector< std::string >> mat)
	print the elements of a matrix of string values on the screen More...

template<typename T >
T	Min (const std::vector< T > vect)
	minimum element of a std::vector More...

template<typename T >
T	Max (const std::vector< T > vect)
	maximum element of a std::vector More...

template<typename T >
std::vector< T >	different_elements (const std::vector< T > vect_input)
	get the unique elements of a std::vector More...

template<typename T >
int	N_different_elements (const std::vector< T > vect_input)
	get the number of unique elements of a std::vector More...

void	unique_unsorted (std::vector< int > &vv)
	erase all the equal elements of the input std::vector More...

void	unique_unsorted (std::vector< double > &vv)
	erase all the equal elements of the input std::vector More...

void	unique_unsorted (std::vector< std::string > &vv)
	erase all the equal elements of the input std::vector More...

template<typename T >
void	Erase (std::vector< T > &vv, std::vector< int > ind)
	erase some elements of a std::vector More...

template<typename T >
void	Erase_lines (std::vector< std::vector< T > > &Mat, std::vector< int > ll)
	erase some lines of a matrix More...

template<typename T >
void	Erase_columns (std::vector< std::vector< T > > &Mat, std::vector< int > col)
	erase some columns of a matrix More...

template<typename T >
void	SubMatrix (std::vector< T > &xx, std::vector< T > &yy, std::vector< std::vector< T > > &Mat, T val)
	select a submatrix containing lines and columns with all elements major than val More...

template<typename T >
bool	isDimEqual (const std::vector< T > vect1, const std::vector< T > vect2)
	check if the dimensions of two std::vectors are equal More...

template<typename T >
bool	isDimEqual (const std::vector< std::vector< T > > mat1, const std::vector< std::vector< T > > mat2)
	check if the dimensions of two matrices are equal More...

template<typename T >
void	checkDim (const std::vector< T > vect, const int val, const std::string vector, bool equal=true)
	check if the dimension of a std::vector is equal/lower than an input value More...

template<typename T >
void	checkDim (const std::vector< T > mat, const int val_i, const int val_j, const std::string matrix, const bool equal=true)
	check if the dimensions of a matrix are higher than two input values More...

template<typename T >
void	checkEqual (const std::vector< T > vect1, const std::vector< T > vect2)
	check if two std::vectors are equal More...

template<typename T >
std::vector< T >	linear_bin_vector (const size_t nn, const T min, const T max)
	fill a std::vector with linearly spaced values More...

template<typename T >
std::vector< T >	logarithmic_bin_vector (const size_t nn, const T min, const T max)
	fill a std::vector with logarithmically spaced values More...

template<typename T >
int	locate (const std::vector< T > &vv, const T xx)
	locate a value in a given std::vector More...

template<typename T >
std::vector< T >	extract_elements (std::vector< T > vec, std::vector< unsigned int > index)
	extract elements from a given vector More...

template<typename T >
std::vector< T >	flatten (std::vector< std::vector< T >> matrix)
	flatten a \(\left( n\times m \right)\) matrix in a vector of size \(x\times m\) More...

template<typename T >
std::vector< std::vector< T > >	reshape (std::vector< T > vec, const int size1, const int size2)
	reshape a vector into a matrix of given number of rows and columns More...

template<typename T >
std::vector< std::vector< T > >	transpose (std::vector< std::vector< T >> matrix)
	transpose a matrix More...

template<typename T >
bool	inRange (T value, T min, T max, bool include_limits=true)
	return false \( \rightarrow \) value outside the range; true \( \rightarrow \) value inside the range More...

template<typename T >
bool	inRange (std::vector< T > value, std::vector< T > min, std::vector< T > max, bool include_limits=true)
	return false \( \rightarrow \) if values are outside the range; true \( \rightarrow \) if values are inside the range More...

template<typename T >
bool	inRange (std::vector< T > value, std::vector< std::vector< T >> ranges, bool include_limits=true)
	return false \( \rightarrow \) values outside the range; true \( \rightarrow \) values inside the range More...

template<typename T >
T	v_M_vt (const std::vector< T > vv, const std::vector< std::vector< T >> MM)
	return the value of More...

void	sort_2vectors (std::vector< double >::iterator p1, std::vector< double >::iterator p2, const int dim)
	sort the elements of a std::vectors, and the elements of a second std::vector according to the first sorting More...

void	sort_3vectors (std::vector< double >::iterator p1, std::vector< double >::iterator p2, std::vector< double >::iterator p3, const int dim)
	sort the elements of a std::vectors, and the elements of two other std::vectors according to the first sorting More...

void	sort_4vectors (std::vector< double >::iterator p1, std::vector< double >::iterator p2, std::vector< double >::iterator p3, std::vector< double >::iterator p4, const int dim)
	sort the elements of a std::vectors, and the elements of three other std::vectors according to the first sorting More...

int	makeDir (std::string path, const std::string rootPath=".", const mode_t mode=0777, const bool verbose=false)
	function to create multiple directories More...

std::vector< std::vector< double > >	operator* (const std::vector< std::vector< double > > &Mat1, const std::vector< std::vector< double > > &Mat2)
	matrix multiplication More...

template<typename T >
std::vector< T >	slice (const std::vector< T > v, const int start=0, const int end=-1)
	slice a std::vector from start to stop More...

std::vector< std::vector< double > >	read_file (const std::string file_name, const std::string path_name, const std::vector< int > column_data, const int skip_nlines=0)
	read a data from a file ASCII More...

std::vector< std::vector< double > >	read_file (const std::string file_name, const std::string path_name, const std::vector< int > column_data, const std::string delimiter, const char comment='#')
	read a data from a file ASCII. Useful e.g. when the data are written between comment lines. More...

Detailed Description

The global namespace of the CosmoBolognaLib

The cbl namespace contains all the main functions and classes of the CosmoBolognaLib

Typedef Documentation

◆ distribution_func

typedef std::function<double(double, std::shared_ptr<void>, std::vector<double>)> cbl::distribution_func

generic distribution function

Returns: distribution function

Definition at line 50 of file RandomNumbers.h.

◆ nDim_distribution_func

typedef std::function<double(std::vector<double>, std::shared_ptr<void>)> cbl::nDim_distribution_func

distribution function used for a n-dimensional distribution

Returns: distribution function

Definition at line 57 of file RandomNumbers.h.

Enumeration Type Documentation

◆ BinType

enum cbl::BinType

strong

the binning type

Enumerator
_linear_	linear binning
_logarithmic_	logarithmic binning
_custom_	custom binning

Definition at line 505 of file Kernel.h.

◆ CoordinateType

enum cbl::CoordinateType

strong

the coordinate type

Enumerator
_comoving_	comoving coordinates (x, y, z)
_observed_	observed coordinates (R.A., Dec, redshift)

Definition at line 624 of file Kernel.h.

◆ CoordinateUnits

enum cbl::CoordinateUnits

strong

the coordinate units

Enumerator
_radians_	angle in radians
_degrees_	angle in degrees
_arcseconds_	angle in arcseconds
_arcminutes_	angle in arcminutes

Definition at line 562 of file Kernel.h.

◆ Dim

enum cbl::Dim

strong

the dimension, used e.g. for pair and triplet vectors

Enumerator
_1D_	1D, used e.g. for 1D pairs, in angular or comoving separations
_2D_	2D pair, used e.g. for 2D pairs, in Cartesian or polar coordinates

Definition at line 483 of file Kernel.h.

Function Documentation

◆ angular_distance()

double cbl::angular_distance	(	const double	x1,
		const double	x2,
		const double	y1,
		const double	y2,
		const double	z1,
		const double	z2
	)

the angular separation in 3D

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Parameters

x1	x coordinate of the first object
x2	x coordinate of the second object
y1	y coordinate of the first object
y2	y coordinate of the second object
z1	z coordinate of the first object
z2	z coordinate of the second object

Returns: the angular separation [radians]

Definition at line 277 of file Func.cpp.

◆ AP_shift_pi()

double cbl::AP_shift_pi	(	const double	redshift,
		const cosmology::Cosmology &	cosm1,
		const cosmology::Cosmology &	cosm2
	)

the Alcock-Pacinski factor used to shift comoving distances parallel to the line-of-sight, π

this function is used to model geometric distortions

Parameters

redshift	the redshift
cosm1	object of class Cosmology
cosm2	object of class Cosmology

Returns: H[cosm2]/H[cosm1], where H is Cosmology::HH

Definition at line 89 of file FuncCosmology.cpp.

◆ AP_shift_r()

double cbl::AP_shift_r	(	const double	redshift,
		const cosmology::Cosmology &	cosm1,
		const cosmology::Cosmology &	cosm2
	)

the Alcock-Pacinski factor used to shift comoving distances

this function is used to model geometric distortions

Parameters

redshift	the redshift
cosm1	object of class Cosmology
cosm2	object of class Cosmology

Returns: D_V[cosm2]/D_V[cosm1], where D_V is Cosmology::D_V

Definition at line 79 of file FuncCosmology.cpp.

◆ AP_shift_rp()

double cbl::AP_shift_rp	(	const double	redshift,
		const cosmology::Cosmology &	cosm1,
		const cosmology::Cosmology &	cosm2
	)

the Alcock-Pacinski factor used to shift comoving distances perpendicular to the line-of-sight, r_p

this function is used to model geometric distortions

Parameters

redshift	the redshift
cosm1	object of class Cosmology
cosm2	object of class Cosmology

Returns: D_A[cosm1]/D_A[cosm2], where D_A is Cosmology::D_A

Definition at line 84 of file FuncCosmology.cpp.

◆ arcminutes()

double cbl::arcminutes	(	const double	angle,
		const CoordinateUnits	inputUnits = `CoordinateUnits::_radians_`
	)

conversion to arcminutes

Parameters

angle	the input angle
inputUnits	the units of the input angle

Returns: the angle in arcminutes

Definition at line 170 of file Func.cpp.

◆ arcseconds()

double cbl::arcseconds	(	const double	angle,
		const CoordinateUnits	inputUnits = `CoordinateUnits::_radians_`
	)

conversion to arcseconds

Parameters

angle	the input angle
inputUnits	the units of the input angle

Returns: the angle in arcseconds

Definition at line 148 of file Func.cpp.

◆ Average() [1/2]

double cbl::Average ( const std::vector< double > vect )

the average of a std::vector

for the derivation of the formulae used here for numerically stable calculation see Chan et al. 1979, Finch 2009 and reference therein

Parameters

vect	the input std::vector

Returns: the average of vect

Examples: correlated_samples.cpp.

Definition at line 870 of file Func.cpp.

◆ Average() [2/2]

double cbl::Average	(	const std::vector< double >	vect,
		const std::vector< double >	weight
	)

the weighted average of a std::vector

for the derivation of the formulae used here for numerically stable calculation see Chan et al. 1979, Finch 2009 and reference therein

Parameters

vect	the input std::vector
weight	the weight

Returns: the weighted average of vect

Definition at line 897 of file Func.cpp.

◆ average_three_spherical_bessel_integral()

double cbl::average_three_spherical_bessel_integral	(	const double	r1_min,
		const double	r1_max,
		const double	r2_min,
		const double	r2_max,
		const double	r3,
		const int	L1,
		const int	L2,
		const int	L3
	)

compute the integral of three spherical bessel function, from Mehrem (2011), averaged on r1-r2 shells

Parameters

r1_min
r1_max
r2_min
r2_max
r3
L1	the order of the first spherical bessel function
L2	the order of the second spherical bessel function
L3	the order of the third spherical bessel function

Returns: the integral of three spherical bessel function, averaged

Definition at line 2585 of file Func.cpp.

◆ b_nl()

double cbl::b_nl	(	const double	rr,
		const double	bA,
		const double	bB = `10.`,
		const double	bC = `4.`
	)

a possible parameterization of the non-linear bias

the non-linear bias (see Chuang&Wang 2012 (1209.0210), eqs. 20-21): \( b(r) = r^{\frac{b_A}{1+(\frac{r}{b_B})^{b_C}}} \)

Parameters

rr	the comoving scale
bA	b_A
bB	b_B
bC	b_C

Returns: b(r)

Definition at line 653 of file FuncXi.cpp.

◆ barred_xi_()

double cbl::barred_xi_	(	const double	RR,
		const std::vector< double >	rr,
		const std::vector< double >	xi,
		const double	rAPP = `0.`,
		const double	r0 = `-1.`,
		const double	gamma = `1.`
	)

the barred correlation function

(see e.g. Hamilton 1992)

\[ \overline{\xi}(r) = \frac{3}{r^3}\int^r_0dr'\xi(r')r'{^2} \]

Parameters

RR	the comoving separation, r, where the barred correlation function is computed
rr	std::vector containing the input comoving separations
xi	std::vector containing the input two-point correlation function
rAPP	comoving scale below which a power-law model for the two-point correlation function is assumed in the integral
r0	the power-law normalization, r₀
gamma	the power-law slope, γ

Returns: \( \overline{\xi}(r) \)

Definition at line 392 of file FuncXi.cpp.

◆ barred_xi__()

double cbl::barred_xi__	(	const double	RR,
		const std::vector< double >	rr,
		const std::vector< double >	xi,
		const double	rAPP = `0.`,
		const double	r0 = `-1.`,
		const double	gamma = `1.`
	)

the double barred correlation function

(see e.g. Hamilton 1992)

\[ \overline{\overline{\xi}}(r) = \frac{5}{r^5}\int^r_0dr'\xi(r')r'{^4} \]

Parameters

RR	the comoving separation, r, where the barred correlation function is computed
rr	std::vector containing the input comoving separations
xi	std::vector containing the input two-point correlation function
rAPP	comoving scale below which a power-law model for the two-point correlation function is assumed in the integral
r0	the power-law normalization, r₀
gamma	the power-law slope, γ

Returns: \( \overline{\overline{\xi}}(r) \)

Definition at line 412 of file FuncXi.cpp.

◆ barred_xi__direct()

double cbl::barred_xi__direct	(	const double	RR,
		const std::vector< double >	rr,
		const std::vector< double >	xi,
		const double	rAPP = `0.`,
		const double	r0 = `-1.`,
		const double	gamma = `1.`
	)

the double barred correlation function

computed with a simple rectangular integration

(see e.g. Hamilton 1992)

\[ \overline{\overline{\xi}}(r) = \frac{5}{r^5}\int^r_0dr'\xi(r')r'{^4} \]

Parameters

RR	the comoving separation, r, where the barred correlation function is computed
rr	std::vector containing the input comoving separations
xi	std::vector containing the input two-point correlation function
rAPP	comoving scale below which a power-law model for the two-point correlation function is assumed in the integral
r0	the power-law normalization, r₀
gamma	the power-law slope, γ

Returns: \( \overline{\overline{\xi}}(r) \)

Definition at line 361 of file FuncXi.cpp.

◆ barred_xi_direct()

double cbl::barred_xi_direct	(	const double	RR,
		const std::vector< double >	rr,
		const std::vector< double >	xi,
		const double	rAPP = `0.`,
		const double	r0 = `-1.`,
		const double	gamma = `1.`
	)

the barred correlation function

computed with a simple rectangular integration

(see e.g. Hamilton 1992)

\[ \overline{\xi}(r) = \frac{3}{r^3}\int^r_0dr'\xi(r')r'{^2} \]

Parameters

RR	the comoving separation, r, where the barred correlation function is computed
rr	std::vector containing the input comoving separations
xi	std::vector containing the input two-point correlation function
rAPP	comoving scale below which a power-law model for the two-point correlation function is assumed in the integral
r0	the power-law normalization, r₀
gamma	the power-law slope, γ

Returns: \( \overline{\xi}(r) \)

Definition at line 331 of file FuncXi.cpp.

◆ Beep()

void cbl::Beep ( const std::string beep = "beep" )

inline

produce a beep

function to produce a nice, useful beep

Parameters

beep	produced sound, to be specified to customize the beep

Examples: fsigma8.cpp.

Definition at line 791 of file Kernel.h.

◆ bin_function()

void cbl::bin_function	(	const std::string	file_grid,
		double	funcdouble, void *,
		void *	par,
		const int	bin,
		const double	x_min,
		const double	x_max,
		const std::string	binning,
		std::vector< double > &	xx,
		std::vector< double > &	yy
	)

create a 1D grid given an input function

Parameters

	file_grid	the file with the input function
[in]	func	the input function
[in]	par	the function parameters
[in]	bin	the number of bins in the grid
[in]	x_min	the minimum limit of the grid
[in]	x_max	the maximum limit of the grid
[in]	binning	the binning type: it can be "lin", "loglin" or "log"
[in,out]	xx	std::vector containing the grid points
[in,out]	yy	std::vector containing the values of the function at the grid points

Definition at line 1118 of file Func.cpp.

◆ bin_function_2D()

void cbl::bin_function_2D	(	const std::string	file_grid,
		double	funcdouble , size_t, void ,
		void *	par,
		const int	bin,
		const double	x1_min,
		const double	x1_max,
		const double	x2_min,
		const double	x2_max,
		const std::string	binning,
		std::vector< double > &	xx1,
		std::vector< double > &	xx2,
		std::vector< std::vector< double >> &	yy
	)

create a 2D grid given an input function

Parameters

[in]	file_grid	the file with the input function
[in]	func	the input function
[in]	par	the function parameters
[in]	bin	the number of bins in the grid
[in]	x1_min	the minimum limit of the grid in one direction
[in]	x1_max	the maximum limit of the grid in one direction
[in]	x2_min	the minimum limit of the grid in one direction
[in]	x2_max	the maximum limit of the grid in one direction
[in]	binning	the binning type: it can be "lin", "loglin" or "log"
[in,out]	xx1	std::vector containing the grid points in one direction
[in,out]	xx2	std::vector containing the grid points in one direction
[in,out]	yy	std::vector containing the values of the function at the grid points

Definition at line 1183 of file Func.cpp.

◆ binomial_coefficient()

double cbl::binomial_coefficient	(	const int	n,
		const int	m
	)

get the binomial coefficient

Parameters

n	first integer
m	second integer

Returns: the binomial coefficient

Definition at line 2217 of file Func.cpp.

◆ BinTypeCast() [1/4]

BinType cbl::BinTypeCast ( const int binTypeIndex )

inline

cast an enum of type BinType from its index

Parameters

binTypeIndex the binType index

Returns: object of class BinType

Definition at line 532 of file Kernel.h.

◆ BinTypeCast() [2/4]

BinType cbl::BinTypeCast ( const std::string binTypeName )

inline

cast an enum of type BinType from its name

Parameters

binTypeName the binType name

Returns: object of class BinType

Definition at line 540 of file Kernel.h.

◆ BinTypeCast() [3/4]

std::vector<BinType> cbl::BinTypeCast ( const std::vector< int > binTypeIndeces )

inline

cast an enum of type BinType from indeces

Parameters

binTypeIndeces the binType indeces

Returns: object of class BinType

Definition at line 548 of file Kernel.h.

◆ BinTypeCast() [4/4]

std::vector<BinType> cbl::BinTypeCast ( const std::vector< std::string > binTypeNames )

inline

cast an enum of type BinType from thier names

Parameters

binTypeNames the binType names

Returns: objects of class BinType

Definition at line 556 of file Kernel.h.

◆ BinTypeNames()

std::vector<std::string> cbl::BinTypeNames ( )

inline

return a vector containing the BinType names

Returns: a vector containing the BinType names

Definition at line 524 of file Kernel.h.

◆ cartesian_coord() [1/2]

void cbl::cartesian_coord	(	const double	ra,
		const double	dec,
		const double	dd,
		double &	XX,
		double &	YY,
		double &	ZZ
	)

conversion from polar coordinates to Cartesian coordinates

Parameters

[in]	ra	the Right Ascension [radians]
[in]	dec	the Declination [radians]
[in]	dd	the comoving distance
[out]	XX	the Cartesian coordinate x
[out]	YY	the Cartesian coordinate y
[out]	ZZ	the Cartesian coordinate z

Definition at line 221 of file Func.cpp.

◆ cartesian_coord() [2/2]

void cbl::cartesian_coord	(	const std::vector< double >	ra,
		const std::vector< double >	dec,
		const std::vector< double >	dd,
		std::vector< double > &	XX,
		std::vector< double > &	YY,
		std::vector< double > &	ZZ
	)

conversion from polar coordinates to Cartesian coordinates used for a set of objects

Parameters

[in]	ra	std::vector containing the Right Ascension values [radians]
[in]	dec	std::vector containing the Declination values [radians]
[in]	dd	std::vector containing the comoving distances
[out]	XX	std::vector containing the Cartesian coordinates x
[out]	YY	std::vector containing the Cartesian coordinates y
[out]	ZZ	std::vector containing the Cartesian coordinates z

Definition at line 237 of file Func.cpp.

◆ castFromName()

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>

T cbl::castFromName	(	const std::string	name,
		const std::vector< std::string >	list
	)

cast an object of type enum class from its name

Parameters

name	the enum name
list	std::vector containing the names of the enum

Returns: object of class T

Definition at line 59 of file EnumCast.h.

◆ castFromNames()

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>

std::vector<T> cbl::castFromNames	(	const std::vector< std::string >	names,
		const std::vector< std::string >	list
	)

cast an object of type enum class from names

Parameters

names	the enum names
list	std::vector containing the names of the enum

Returns: object of class T

Definition at line 97 of file EnumCast.h.

◆ castFromValue()

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>

T cbl::castFromValue ( const int i )

cast an object of type enum class from its index

Parameters

i	the enum index

Returns: object of class T

Definition at line 47 of file EnumCast.h.

◆ castFromValues()

template<typename T , typename std::enable_if< std::is_enum< T >::value >::type * = nullptr>

std::vector<T> cbl::castFromValues ( const std::vector< int > ii )

cast objects of type enum class from indeces

Parameters

ii	the enum indeces

Returns: object of class T

Definition at line 79 of file EnumCast.h.

◆ chainMeshInterpolate()

double cbl::chainMeshInterpolate	(	std::vector< double >	xx,
		std::shared_ptr< void >	pars
	)

a multidimension interpolator

Parameters

xx	the coordinates of the points to interpolate
pars	vector containing an object ChainMesh and the maximum number of points used to interpolate

Returns: the interpolated value

Definition at line 68 of file Func.cpp.

◆ check_EnvVar()

void cbl::check_EnvVar ( const std::string Var )

check if an environment variable exists

Parameters

Var	the evironment variable to be checked

Definition at line 196 of file Kernel.cpp.

◆ check_memory()

int cbl::check_memory	(	const double	frac,
		const bool	exit = `true`,
		const std::string	func = `""`,
		const int	type = `1`
	)

check if the memory used by current process is larger than a given fraction of the available memory

Warning: this function works only on Linux systems

Parameters

frac	the fraction of the available memory that is allowed
func	a std::string that should contain the name of the function from which check_memory is called; it is used when printing the error message
exit	0 \(\rightarrow\) warning message; 1 \(\rightarrow\) error message; (and exit)
type	1 \(\rightarrow\) Physical Memory (RAM); 2 \(\rightarrow\) Virtual Memory

Returns: 0 \(\rightarrow\) memory problems; 1 \(\rightarrow\) no memory problems

Definition at line 252 of file Kernel.cpp.

◆ check_regions()

void cbl::check_regions	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random
	)

check if the subdivision process produced the correct results

Parameters

data	input data catalogue
random	random catalogue

Definition at line 601 of file SubSample.cpp.

◆ checkDim() [1/2]

template<typename T >

void cbl::checkDim	(	const std::vector< T >	mat,
		const int	val_i,
		const int	val_j,
		const std::string	matrix,
		const bool	equal = `true`
	)

check if the dimensions of a matrix are higher than two input values

Parameters

mat	a matrix
val_i	an input value
val_j	an input value
matrix	the name of the matrix (using only to write the error message)
equal	true \(\rightarrow\) check if the dimension is equal to val; false \(\rightarrow\) check if the dimension is lower than val

Definition at line 1556 of file Kernel.h.

◆ checkDim() [2/2]

template<typename T >

void cbl::checkDim	(	const std::vector< T >	vect,
		const int	val,
		const std::string	vector,
		bool	equal = `true`
	)

check if the dimension of a std::vector is equal/lower than an input value

Parameters

vect	a std::vector
val	the input value
vector	the name of the std::vector (used only to write the error message)
equal	true \(\rightarrow\) check if the dimension is equal to val; false \(\rightarrow\) check if the dimension is lower than val

Definition at line 1532 of file Kernel.h.

◆ checkEqual()

template<typename T >

void cbl::checkEqual	(	const std::vector< T >	vect1,
		const std::vector< T >	vect2
	)

check if two std::vectors are equal

this function returns either an error if the given std::vectors are different, or nothing if they are equal

Parameters

vect1	a std::vector
vect2	a std::vector

Definition at line 1587 of file Kernel.h.

◆ checkIO() [1/2]

void cbl::checkIO	(	const std::ifstream &	fin,
		const std::string	file = `"NULL"`
	)

check if an input file can be opened

Parameters

fin	std::ifstream object
file	the file name

Examples: catalogue.cpp, data1D.cpp, and model_3pt.cpp.

Definition at line 160 of file Kernel.cpp.

◆ checkIO() [2/2]

void cbl::checkIO	(	const std::ofstream &	fout,
		const std::string	file = `"NULL"`
	)

check if an output file can be opened

Parameters

fout	std::ofstream object
file	the file name

Definition at line 173 of file Kernel.cpp.

◆ clebsh_gordan()

double cbl::clebsh_gordan	(	const int	j1,
		const int	j2,
		const int	m1,
		const int	m2,
		const int	j3,
		const int	m3
	)

get the Clebsh-Gordan coefficient in the notation \( \sum_{l}\left\langle l_1 l_2 m_1 m_2 | l_3 m_3 \right\rangle \)

Parameters

j1	index
j2	index
j3	index
m1	index
m2	index
m3	index

Returns: the Clebsh-Gordan coefficient

Definition at line 2511 of file Func.cpp.

◆ closest() [1/2]

template<typename T >

T cbl::closest	(	T	x,
		std::vector< T >	values
	)

given a number x, return the closest value in a std::vector

Parameters

x	the starting value
values	std::vector of values

Returns: the closest value in the std::vector

Definition at line 984 of file Kernel.h.

◆ closest() [2/2]

template<typename T >

T cbl::closest	(	T	x,
		T	a,
		T	b
	)

given a number x, return the closest of two values a, b

Parameters

x	the starting value
a	the first number to test
b	the second number to test

Returns: a if x is closer to a, b if x is closer to b

Definition at line 948 of file Kernel.h.

◆ closest_probability()

double cbl::closest_probability	(	double	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

probability of the closest element to x from a list with weights

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients:

Returns: the weight of closest element from a discrete list to x

Warning: par is not used, it is necessary only for GSL operations

Definition at line 47 of file Func.cpp.

◆ colatitude()

vector< double > cbl::colatitude ( std::vector< double > latitude )

convert to colatitude

\[ \theta = 90 - \delta \]

Parameters

latitude vector containing the latitudes

Returns: vector containing the colatitude

Definition at line 484 of file SubSample.cpp.

◆ conv()

template<typename T >

std::string cbl::conv	(	const T	val,
		const char *	fact
	)

convert a number to a std::string

Parameters

val	number of any type
fact	output format

Returns: a std::string containing T

Examples: Pk_BoltzmannSolver.cpp, and fsigma8.cpp.

Definition at line 903 of file Kernel.h.

◆ converted_angle()

double cbl::converted_angle	(	const double	angle,
		const CoordinateUnits	inputUnits = `CoordinateUnits::_radians_`,
		const CoordinateUnits	outputUnits = `CoordinateUnits::_degrees_`
	)

conversion to angle units

Parameters

angle	the input angle
inputUnits	the units of the input angle
outputUnits	the units of the output angle

Returns: the angle in the converted units

Definition at line 192 of file Func.cpp.

◆ converted_xi() [1/2]

double cbl::converted_xi	(	const double	RP,
		const double	PI,
		const double	redshift,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double > >	Xi,
		const cosmology::Cosmology &	cosm1,
		const cosmology::Cosmology &	cosm2,
		const bool	direction
	)

the 2D two-point correlation function converted from one cosmology to another one

Parameters

RP	the comoving separation perpendicular to the line-of-sight, R_p
PI	the comoving separation parallel to the line-of-sight, Π
redshift	the redshift
rp	vector containing the comoving separations perpendicular to the line-of-sight, r_p
pi	vector containing the comoving separations parallel to the line-of-sight, π
Xi	matrix containing the two-point correlation function, ξ(r_p,π)
cosm1	object of class Cosmology
cosm2	object of class Cosmology
direction	0 → cosm2 \( \rightarrow \) cosm1; 1 → cosm1 \( \rightarrow \) cosm2;

Returns: the converted two-point correlation function, ξ(R_p,Π)

Definition at line 140 of file FuncCosmology.cpp.

◆ converted_xi() [2/2]

double cbl::converted_xi	(	const double	RR,
		const double	redshift,
		const std::vector< double >	rr,
		const std::vector< double >	Xi,
		const cosmology::Cosmology &	cosm1,
		const cosmology::Cosmology &	cosm2,
		const bool	direction
	)

the 1D two-point correlation function converted from one cosmology to another one

Parameters

RR	the comoving separation, R
redshift	the redshift
rr	vector containing the comoving separations, r
Xi	vector containing the two-point correlation function, ξ(r)
cosm1	object of class Cosmology
cosm2	object of class Cosmology
direction	0 → cosm2 \( \rightarrow \) cosm1; 1 → cosm1 \( \rightarrow \) cosm2;

Returns: the converted two-point correlation function, ξ(R)

Definition at line 117 of file FuncCosmology.cpp.

◆ convolution()

void cbl::convolution	(	const std::vector< double >	f1,
		const std::vector< double >	f2,
		std::vector< double > &	res,
		const double	deltaX
	)

convolution of two functions

Get the convolution of the two functions f₁(x) and f₂(x), and store it in the output std::vector res. The two functions have to be defined on the same x-axis range, with equal number of points, Δx = (x_max-x_min)/n_x.

Parameters

[in]	f1	first function, f₁(x)
[in]	f2	second function, f₂(x)
[out]	res	convolution function
[in]	deltaX	Δx = (x_max-x_min)/n_x

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 1580 of file Func.cpp.

◆ coord_zSpace()

void cbl::coord_zSpace	(	std::vector< double > &	ra,
		std::vector< double > &	dec,
		std::vector< double > &	redshift,
		std::vector< double > &	xx,
		std::vector< double > &	yy,
		std::vector< double > &	zz,
		const std::vector< double >	vx,
		const std::vector< double >	vy,
		const std::vector< double >	vz,
		const double	sigmaV,
		cosmology::Cosmology &	real_cosm,
		const double	mean_redshift,
		const double	redshift_min,
		const double	redshift_max,
		const int	seed = `3213`
	)

convert a set of coordinates from real-space to redshift-space

Parameters

[in,out]	ra	vector containing the Right Ascensions
[in,out]	dec	vector containing the Declinations
[in,out]	redshift	vector containing the redshifts
[in,out]	xx	vector containing the x coordinates
[in,out]	yy	vector containing the y coordinates
[in,out]	zz	vector containing the z coordinates
[in]	vx	vector containing the peculiar velocities along the x direction
[in]	vy	vector containing the peculiar velocities along the y direction
[in]	vz	vector containing the peculiar velocities along the z direction
[in]	sigmaV	the error on the peculiar velocities
[in]	real_cosm	an object of class Cosmology
[in]	mean_redshift	the mean redshift
[in]	redshift_min	the minimum redshift
[in]	redshift_max	the maximum redshift
[in]	seed	the random seed

Definition at line 94 of file Func.cpp.

◆ CoordinateTypeCast() [1/4]

CoordinateType cbl::CoordinateTypeCast ( const int coordinateTypeIndex )

inline

cast an enum of type CoordinateType from its index

Parameters

coordinateTypeIndex the coordinateType index

Returns: object of class CoordinateType

Definition at line 648 of file Kernel.h.

◆ CoordinateTypeCast() [2/4]

CoordinateType cbl::CoordinateTypeCast ( const std::string coordinateTypeName )

inline

cast an enum of type CoordinateType from its name

Parameters

coordinateTypeName the coordinateType name

Returns: object of class CoordinateType

Definition at line 656 of file Kernel.h.

◆ CoordinateTypeCast() [3/4]

std::vector<CoordinateType> cbl::CoordinateTypeCast ( const std::vector< int > coordinateTypeIndeces )

inline

cast an enum of type CoordinateType from indeces

Parameters

coordinateTypeIndeces the coordinateType indeces

Returns: object of class CoordinateType

Definition at line 664 of file Kernel.h.

◆ CoordinateTypeCast() [4/4]

std::vector<CoordinateType> cbl::CoordinateTypeCast ( const std::vector< std::string > coordinateTypeNames )

inline

cast an enum of type CoordinateType from thier names

Parameters

coordinateTypeNames the coordinateType names

Returns: objects of class CoordinateType

Definition at line 672 of file Kernel.h.

◆ CoordinateTypeNames()

std::vector<std::string> cbl::CoordinateTypeNames ( )

inline

return a std::vector containing the CoordinateType names

Returns: a std::vector containing the CoordinateType names

Definition at line 640 of file Kernel.h.

◆ CoordinateUnitsCast() [1/4]

CoordinateUnits cbl::CoordinateUnitsCast ( const int coordinateUnitsIndex )

inline

cast an enum of type CoordinateUnits from its index

Parameters

coordinateUnitsIndex the coordinateUnits index

Returns: object of class CoordinateUnits

Definition at line 593 of file Kernel.h.

◆ CoordinateUnitsCast() [2/4]

CoordinateUnits cbl::CoordinateUnitsCast ( const std::string coordinateUnitsName )

inline

cast an enum of type CoordinateUnits from its name

Parameters

coordinateUnitsName the coordinateUnits name

Returns: object of class CoordinateUnits

Definition at line 601 of file Kernel.h.

◆ CoordinateUnitsCast() [3/4]

std::vector<CoordinateUnits> cbl::CoordinateUnitsCast ( const std::vector< int > coordinateUnitsIndeces )

inline

cast an enum of type CoordinateUnits from indeces

Parameters

coordinateUnitsIndeces the coordinateUnits indeces

Returns: object of class CoordinateUnits

Definition at line 609 of file Kernel.h.

◆ CoordinateUnitsCast() [4/4]

std::vector<CoordinateUnits> cbl::CoordinateUnitsCast ( const std::vector< std::string > coordinateUnitsNames )

inline

cast an enum of type CoordinateUnits from thier names

Parameters

coordinateUnitsNames the coordinateUnits names

Returns: objects of class CoordinateUnits

Definition at line 617 of file Kernel.h.

◆ CoordinateUnitsNames()

std::vector<std::string> cbl::CoordinateUnitsNames ( )

inline

return a std::vector containing the CoordinateUnits names

Returns: a std::vector containing the CoordinateUnits names

Definition at line 585 of file Kernel.h.

◆ coupling_3j()

double cbl::coupling_3j	(	const int	l,
		const int	l_prime,
		const int	l2
	)

compute the Wigner 3-j symbol

compute the Wigner 3-j symbol of type

\[ \left(\begin{array}{ccc}{l}} & {l^'} & {l_2}} \\ {m_{1}} & {m_{2}} & {m_{3}}\end{array}\right) \]

Parameters

l	the first index
l_prime	the second index
l2	the third index

Returns: the Wigner 3-j symbol

Definition at line 2520 of file Func.cpp.

◆ covariance_matrix() [1/3]

void cbl::covariance_matrix	(	const std::vector< std::string >	file,
		const std::string	covariance_matrix_file,
		const bool	JK = `0`
	)

compute the covariance matrix, reading the dataset from files, and store it in a file

Parameters

[in]	file	the std::vector containing the input files
[out]	covariance_matrix_file	the output covariance matrix file
[in]	JK	false → normalize to 1/(n-1); true → normalize to n-1/n (for Jackknife)

Definition at line 849 of file Func.cpp.

◆ covariance_matrix() [2/3]

void cbl::covariance_matrix	(	const std::vector< std::string >	file,
		std::vector< double > &	rad,
		std::vector< double > &	mean,
		std::vector< std::vector< double >> &	cov,
		const bool	JK = `false`
	)

compute the covariance matrix, reading the dataset from files

Parameters

[in]	file	the std::vector containing the input files
[out]	rad	the std::vector containing the binned radii
[out]	mean	the std::vector containing the mean values
[out]	cov	the output covariance matrix
[in]	JK	false → normalize to 1/(n-1); true → normalize to n-1/n (for Jackknife)

Definition at line 807 of file Func.cpp.

◆ covariance_matrix() [3/3]

void cbl::covariance_matrix	(	const std::vector< std::vector< double >>	mat,
		std::vector< std::vector< double >> &	cov,
		const bool	JK = `false`
	)

compute the covariance matrix from an input dataset

Parameters

[in]	mat	the data input matrix
[out]	cov	the output covariance matrix
[in]	JK	false → normalize to 1/(n-1); true → normalize to n-1/n (for Jackknife)

Examples: correlated_samples.cpp, and covsample.cpp.

Definition at line 761 of file Func.cpp.

◆ Covariance_XiMultipoles()

void cbl::Covariance_XiMultipoles	(	std::vector< double > &	rr,
		std::vector< std::vector< double >> &	covariance,
		const int	nbins,
		const double	rMin,
		const double	rMax,
		const double	nObjects,
		const double	Volume,
		const std::vector< double >	kk,
		const std::vector< std::vector< double >>	Pk_multipoles,
		const std::vector< int >	orders,
		const cbl::BinType	bin_type = `cbl::BinType::_linear_`
	)

Covariance matrix for two-point correlation multipoles (see Grieb et al. 2016, Eq. 18 https://arxiv.org/pdf/1509.04293)

\[ C_{\ell_{1} \ell_{2}}^{\epsilon}\left(s_{i}, s_{j}\right)=\frac{\mathrm{i}^{\ell_{1}+\ell_{2}}}{2 \pi^{2}} \int_{0}^{\infty} k^{2} \sigma_{\ell_{1} \ell_{2}}^{2}(k) \bar{\jmath}_{\ell_{1}}\left(k s_{i}\right) \bar{\jmath}_{\ell_{2}}\left(k s_{j}\right) \mathrm{d} k \]

where \(\sigma_{\ell_{1} \ell_{2}}^{2}(k)\) is the multipole expansion of the per-mode covariance sigma2_k, computed by cbl::sigma2_k and \(\bar{\jmath}\) is the shell-averaged Bessel function, computed by cbl::jl_distance_average.

Parameters

rr	output scales
covariance	analytic covariance matrix
nbins	number of configuration space bins
rMin	minimum configuration space scale
rMax	maximum configuration space scale
nObjects	number of objects in the sample
Volume	the sample volume
kk	the scales kk
Pk_multipoles	the power spectrum multipoles
orders	the power spectrum multipoles orders
bin_type	the bin type

Definition at line 994 of file FuncMultipoles.cpp.

◆ covariance_XiMultipoles_integrand()

double cbl::covariance_XiMultipoles_integrand	(	const double	kk,
		void *	parameters
	)

integrand to obtain the 2PCF multipoles

Parameters

kk	the value kk
parameters	the parameters for the integration

Returns: the 2pcf multipoles integrand

Definition at line 466 of file FuncMultipoles.cpp.

◆ Covariance_XiWedges()

void cbl::Covariance_XiWedges	(	std::vector< double > &	rr,
		std::vector< std::vector< double >> &	covariance,
		const std::vector< double >	mu,
		const std::vector< double >	delta_mu,
		const int	nbins,
		const double	rMin,
		const double	rMax,
		const double	nObjects,
		const double	Volume,
		const std::vector< double >	kk,
		const std::vector< std::vector< double >>	Pk_multipoles,
		const std::vector< int >	orders,
		const cbl::BinType	bin_type = `cbl::BinType::_linear_`
	)

Covariance matrix for two-point correlation wedges (see Grieb et al. 2016, Eq. 19 https://arxiv.org/pdf/1509.04293)

\[ C_{\mu \mu^{\prime}}^{\xi}\left(s_{i}, s_{j}\right)= \sum_{\ell_{1}, \ell_{2}} \frac{\mathrm{i}^{\ell_{1}+\ell_{2}}}{2 \pi^{2}} \overline{\mathcal{L}}_{\ell_{1}, \mu} \overline{\mathcal{L}}_{\ell_{2}, \mu^{\prime}} \times \int_{0}^{\infty} k^{2} \sigma_{\ell_{1} \ell_{2}}^{2}(k) \bar{\jmath}_{\ell_{1}}\left(k s_{i}\right) \bar{\jmath}_{\ell_{2}}\left(k s_{j}\right) \mathrm{d} k \]

where \(\sigma_{\ell_{1} \ell_{2}}^{2}(k)\) is the multipole expansion of the per-mode covariance computed by cbl::sigma2_k, \(\bar{\jmath}\) is the shell-averaged Bessel function, computed by cbl::jl_distance_average an \(\overline{\mathcal{L}}\) is the average of the Legendre polynomial over the \(\mu\) bin, computed by cbl::Legendre_polynomial_mu_average.

Parameters

rr	output scales
covariance	analytic covariance matrix
mu	the lower wedge integratin limit
delta_mu	the wedge mu bin size
nbins	number of configuration space bins
rMin	minimum configuration space scale
rMax	maximum configuration space scale
nObjects	number of objects in the sample
Volume	the sample volume
kk	the scales kk
Pk_multipoles	the power spectrum multipoles
orders	the power spectrum multipoles orders
bin_type	the bin type

Definition at line 1096 of file FuncMultipoles.cpp.

◆ create_mocks()

void cbl::create_mocks	(	const std::vector< double >	xx,
		const std::vector< double >	yy,
		const std::vector< double >	zz,
		const std::vector< double >	vx,
		const std::vector< double >	vy,
		const std::vector< double >	vz,
		const std::vector< double >	var1,
		const std::vector< double >	var2,
		const std::vector< double >	var3,
		const std::string	output_dir,
		const double	boxSize,
		const int	frac,
		const double	Bord,
		const double	mean_redshift,
		cosmology::Cosmology &	real_cosm,
		const int	REAL,
		const double	sigmaV,
		const int	idum,
		double &	Volume
	)

create a mock catalogue, subdividing a box into sub-boxes and recentering

Parameters

[in]	xx	vector containing the x coordinates
[in]	yy	vector containing the y coordinates
[in]	zz	vector containing the z coordinates
[in]	vx	vector containing the peculiar velocities along the x direction
[in]	vy	vector containing the peculiar velocities along the y direction
[in]	vz	vector containing the peculiar velocities along the z direction
[in]	var1	vector containing a generic quantity (e.g. masses or luminosities)
[in]	var2	vector containing a generic quantity (e.g. masses or luminosities)
[in]	var3	vector containing a generic quantity (e.g. masses or luminosities)
[in]	output_dir	name of directory used to store the outputs
[in]	boxSize	the box side
[in]	frac	the side fraction (if the input box is a sub-box of a box with side equal to boxSize)
[in]	Bord	the redshift interval that is cutted at the bords of the box
[in]	mean_redshift	the mean redshift
[in]	real_cosm	an object of class Cosmology
[in]	REAL	0 → redshift-space; 1 → real-space
[in]	sigmaV	the error on the peculiar velocities
[in]	idum	the random seed
[out]	Volume	the mock volume

Definition at line 187 of file Func.cpp.

◆ cubicfit()

std::vector<double> cbl::cubicfit ( const double xx )

inline

cubic function

Parameters

xx	the coordinate x

Returns: a std::vector of containing [1, x, x², x³]

Definition at line 1034 of file Func.h.

◆ degrees()

double cbl::degrees	(	const double	angle,
		const CoordinateUnits	inputUnits = `CoordinateUnits::_radians_`
	)

conversion to degrees

Parameters

angle	the input angle
inputUnits	the units of the input angle

Returns: the angle in degrees

Definition at line 104 of file Func.cpp.

◆ determinant_matrix()

double cbl::determinant_matrix ( const std::vector< std::vector< double >> mat )

compute the determinant of a matrix

Parameters

mat	the matrix

Returns: the determinant

Definition at line 648 of file Func.cpp.

◆ different_elements()

template<typename T >

std::vector<T> cbl::different_elements ( const std::vector< T > vect_input )

get the unique elements of a std::vector

Parameters

[in] vect_input the input std::vector

Returns: std::vector containing the unique elements of the input std::vector

Definition at line 1349 of file Kernel.h.

◆ DimNames()

std::vector<std::string> cbl::DimNames ( )

inline

return a vector containing the Dim names

Returns: a vector containing the Dim names

Definition at line 499 of file Kernel.h.

◆ displaced_catalogue()

cbl::catalogue::Catalogue cbl::displaced_catalogue ( const catalogue::Catalogue input_catalogue )

return a sample with objects displaced, according to the internal variables m_x_displacement, m_y_displacement, m_z_displacement

Parameters

input_catalogue input catalogue

Returns: the displaced catalogue

Definition at line 145 of file Reconstruction.cpp.

◆ distribution()

void cbl::distribution	(	std::vector< double > &	xx,
		std::vector< double > &	fx,
		std::vector< double > &	err,
		const std::vector< double >	FF,
		const std::vector< double >	WW,
		const int	nbin,
		const bool	linear = `true`,
		const std::string	file_out = `par::defaultString`,
		const double	fact = `1.`,
		const double	V1 = `par::defaultDouble`,
		const double	V2 = `par::defaultDouble`,
		const std::string	bin_type = `"Linear"`,
		const bool	conv = `false`,
		const double	sigma = `0.`
	)

derive and store the number distribution of a given std::vector

Parameters

[out]	xx	std::vector containing the binned values of the variable
[out]	fx	std::vector containing the binned values of the distribution
[out]	err	std::vector containing the binned Poisson errors
[in]	FF	std::vector containing the given set of data
[in]	WW	std::vector containing the weights
[in]	nbin	the number of bins
[in]	linear	true → linear binning; false → logarithmic binning
[in]	file_out	the output file where the distribution is stored
[in]	fact	factor used to normalized the distribution
[in]	V1	the minimum limit of the distribution
[in]	V2	the maximum limit of the distribution
[in]	bin_type	"Linear" → dn/dvar; "Log10" → dn/dlog(var); "Log" → dn/dln(var)
[in]	conv	true → compute the Gaussian convolvolution of the distribution; false → do not convolve
[in]	sigma	σ of the Gaussian kernel

Examples: randomNumbers.cpp.

Definition at line 1654 of file Func.cpp.

◆ distribution_probability()

double cbl::distribution_probability	(	double	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

probability of an interpolated distribution

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients:

Returns: the weight of closest element from a discrete list to x

Warning: par is not used, it is necessary only for GSL operations

Definition at line 58 of file Func.cpp.

◆ double_powerlaw()

template<typename T >

T cbl::double_powerlaw	(	const T	xx,
		const T	x0,
		const T	alpha,
		const T	beta
	)

the double power-law function

Parameters

xx	the variable x
x0	the normalization, x₀
alpha	the slope, α
beta	the slope, β

Returns: the double power-law function

Definition at line 1184 of file Func.h.

◆ DoubleSwap()

double cbl::DoubleSwap ( const double d )

endian conversion of a double variable

Parameters

d	a double variable

Returns: the converted variable d

Definition at line 109 of file Kernel.cpp.

◆ eq2sdss()

void cbl::eq2sdss	(	const std::vector< double >	ra,
		const std::vector< double >	dec,
		std::vector< double > &	lambda,
		std::vector< double > &	eta
	)

convert from equatorial coordinates R.A., Dec to sdss coordinates \( \lambda, \eta \)

Parameters

ra	vector containing R.A. values
dec	vector containing Dec. values
lambda	vector containing the \( \lambda \) values
eta	vector containing the \( \eta \) values

Definition at line 1373 of file Func.cpp.

◆ Erase()

template<typename T >

void cbl::Erase	(	std::vector< T > &	vv,
		std::vector< int >	ind
	)

erase some elements of a std::vector

Parameters

[in,out]	vv	a std::vector
[in]	ind	a std::vector containing the elements of the input std::vector vv to be erased

Examples: vectors.cpp.

Definition at line 1395 of file Kernel.h.

◆ Erase_columns()

template<typename T >

void cbl::Erase_columns	(	std::vector< std::vector< T > > &	Mat,
		std::vector< int >	col
	)

erase some columns of a matrix

Parameters

[in,out]	Mat	a matrix (i.e. a std::vector of std::vectors)
[in]	col	a std::vector containing the columns of the input matrix Mat to be erased

Examples: vectors.cpp.

Definition at line 1431 of file Kernel.h.

◆ Erase_lines()

template<typename T >

void cbl::Erase_lines	(	std::vector< std::vector< T > > &	Mat,
		std::vector< int >	ll
	)

erase some lines of a matrix

Parameters

[in,out]	Mat	a matrix (i.e. a std::vector of std::vectors)
[in]	ll	a std::vector containing the lines of the input matrix Mat to be erased

Examples: vectors.cpp.

Definition at line 1413 of file Kernel.h.

◆ Error()

int cbl::Error	(	const std::string	msg,
		const cbl::glob::ExitCode	exitCode = `cbl::glob::ExitCode::_error_`,
		const std::string	header = `"\n"`
	)

inline

throw an exception

Parameters

msg	the message describing the exception
exitCode	the exit status
header	header of the error message

Returns: integer

Definition at line 761 of file Kernel.h.

◆ error_multipole_xi0() [1/2]

double cbl::error_multipole_xi0	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	error,
		const double	delta_s
	)

error on xi₀(s) from ξ(r_p,π)

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
error	matrix containing the errors of ξ(r,μ)
delta_s	bin size

Returns: error on xi₀(s)

Definition at line 207 of file FuncMultipoles.cpp.

◆ error_multipole_xi0() [2/2]

double cbl::error_multipole_xi0	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	error
	)

error on xi₀(s) from ξ(r,μ)

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
error	matrix containing the errors of ξ(r,μ)

Returns: error on xi₀(s)

Definition at line 90 of file FuncMultipoles.cpp.

◆ error_multipole_xi2() [1/2]

double cbl::error_multipole_xi2	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	error,
		const double	delta_s
	)

error on xi₂(s) from ξ(r_p,π)

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
error	matrix containing the errors of ξ(r,μ)
delta_s	bin size

Returns: error on xi₂(s)

Definition at line 231 of file FuncMultipoles.cpp.

◆ error_multipole_xi2() [2/2]

double cbl::error_multipole_xi2	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	error
	)

error on xi₂(s) from ξ(r,μ)

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
error	matrix containing the errors of ξ(r,μ)

Returns: error on xi₂(s)

Definition at line 105 of file FuncMultipoles.cpp.

◆ error_multipole_xi4() [1/2]

double cbl::error_multipole_xi4	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	error,
		const double	delta_s
	)

error on xi₄(s) from ξ(r_p,π)

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
error	matrix containing the errors of ξ(r,μ)
delta_s	bin size

Returns: error on xi₄(s)

Definition at line 255 of file FuncMultipoles.cpp.

◆ error_multipole_xi4() [2/2]

double cbl::error_multipole_xi4	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	error
	)

error on xi₄(s) from ξ(r,μ)

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
error	matrix containing the errors of ξ(r,μ)

Returns: error on xi₄(s)

Definition at line 120 of file FuncMultipoles.cpp.

◆ error_xi_ratio()

double cbl::error_xi_ratio	(	const double	beta,
		const double	error_beta
	)

error on the ratio between the redshift-space and real-space correlation functions

as predicted by the large-scale limit of the Kaiser/Hamilton model:

\[ \delta\left[\frac{\xi(s)}{\xi(r)}\right] = \left(\frac{2}{3} + \frac{2\beta}{5}\right)\cdot\delta(\beta) \]

Parameters

beta	β=f/b
error_beta	error on β

Returns: δ[ξ(s)/ξ(r)]

Definition at line 322 of file FuncXi.cpp.

◆ ErrorCBL()

int cbl::ErrorCBL	(	const std::string	msg,
		const std::string	functionCBL,
		const std::string	fileCBL,
		const cbl::glob::ExitCode	exitCode = `cbl::glob::ExitCode::_error_`
	)

inline

throw an exception: it is used for handling exceptions inside the CosmoBolognaLib

Parameters

msg	the message describing the exception
functionCBL	the CBL function where the exception is raised
fileCBL	the CBL file containing the function where the exception is raised
exitCode	the exit status

Returns: integer

Definition at line 780 of file Kernel.h.

◆ Euclidean_distance()

double cbl::Euclidean_distance	(	const double	x1,
		const double	x2,
		const double	y1,
		const double	y2,
		const double	z1,
		const double	z2
	)

the Euclidean distance in 3D relative to the origin (0,0,0), i.e. the Euclidean norm

Parameters

x1	x coordinate of the first object
x2	x coordinate of the second object
y1	y coordinate of the first object
y2	y coordinate of the second object
z1	z coordinate of the first object
z2	z coordinate of the second object

Returns: the Euclidean distance

Definition at line 250 of file Func.cpp.

◆ extract_elements()

template<typename T >

std::vector<T> cbl::extract_elements	(	std::vector< T >	vec,
		std::vector< unsigned int >	index
	)

extract elements from a given vector

Parameters

vec	the input vector
index	vector containing the index of values to extract

Returns: the vector with requested elements

Definition at line 1669 of file Kernel.h.

◆ f_star()

double cbl::f_star	(	const double	xx,
		const double	f_g,
		const double	k_star
	)

velocity distribution used to model BAO

(see Chuang&Wang 2012, 1209.0210)

Parameters

xx	s
f_g	f_g
k_star	k_*

Returns: f_*

Definition at line 642 of file FuncXi.cpp.

◆ f_v() [1/2]

double cbl::f_v	(	const double	vel,
		const double	rp,
		const double	pi,
		const double	var,
		const double	sigmav0,
		const double	cmu,
		const double	cs1,
		const double	cs2
	)

pairwise velocity distribution

(see Chuang&Wang 2012 (1209.0210), eq. 25)

Parameters

vel	comoving velocity
rp	r_p: comoving separation perpendicular to the line-of-sight
pi	π: comoving separation parallel to the line-of-sight
var	1/[H(z)a(z)]
sigmav0	σ_v,0
cmu	C_μ
cs1	C_σ1
cs2	C_σ2

Returns: f(v)

Definition at line 627 of file FuncXi.cpp.

◆ f_v() [2/2]

double cbl::f_v	(	const double	vel,
		const double	sigmav,
		const int	FV
	)

pairwise velocity distribution

Parameters

vel	comoving velocity
sigmav	σ₁₂
FV	0 \( \rightarrow \) exponential; \( \rightarrow \) 1 gaussian

Returns: f(v)

Definition at line 616 of file FuncXi.cpp.

◆ Filter()

double cbl::Filter	(	const double	r,
		const double	rc
	)

filter W(r/r_c), used e.g. for filtering the correlation function

Parameters

r	the scale at which calculate the filter value
rc	the characteristic filter scale

Returns: the filter

Definition at line 94 of file Func.cpp.

◆ fit_covariance_matrix_2PCF_monopole()

std::vector< double > cbl::fit_covariance_matrix_2PCF_monopole	(	const std::vector< double >	mean,
		const std::vector< std::vector< double >>	mock_xi0,
		const bool	doJK,
		const cbl::cosmology::Cosmology	cosmology,
		const double	nObjects,
		const double	Volume,
		const double	bias,
		const double	redshift,
		const double	rMin,
		const double	rMax,
		const int	nbins,
		const cbl::BinType	bin_type,
		const std::string	method_Pk = `"CAMB"`,
		const double	sigma_NL = `0.`,
		const bool	NL = `true`
	)

fit the input covariance matrix using the gaussian model, varying the number of objects and the volume of the sample

Parameters

mean	the 2PCF mean value
mock_xi0	the 2CPF of the mocks
doJK	0 → normalize to 1/(n-1); 1 → normalize to n-1/n (for Jackknife)
cosmology	the cosmology
nObjects	the number of objects in the sample
Volume	the volume of the sample
bias	the bias of the sample
redshift	the redshift of the sample
rMin	the minimum scale
rMax	the maximum scale
nbins	the number of bins
bin_type	the binning type
method_Pk	method used to compute the power spectrum; valid choices for method_Pk are: CAMB [http://camb.info/], CLASS [http://class-code.net/], MPTbreeze-v1 [http://arxiv.org/abs/1207.1465], EisensteinHu [http://background.uchicago.edu/~whu/transfer/transferpage.html]
sigma_NL	the BAO damping parameter
NL	0 \(\rightarrow\) linear power spectrum; 1 \(\rightarrow\) non-linear power spectrum

Returns: the best-fit values

Definition at line 46 of file Forecast.cpp.

◆ flatten()

template<typename T >

std::vector<T> cbl::flatten ( std::vector< std::vector< T >> matrix )

flatten a \(\left( n\times m \right)\) matrix in a vector of size \(x\times m\)

Parameters

matrix the input matrix

Returns: the vectorized matrix

Definition at line 1686 of file Kernel.h.

◆ FloatSwap()

float cbl::FloatSwap ( const float f )

endian conversion of a float variable

Parameters

f	a flot variable

Returns: the converted variable f

Definition at line 89 of file Kernel.cpp.

◆ gaussian()

template<typename T >

T cbl::gaussian	(	T	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

the Gaussian function

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients: par[0]=mean, par[1]=&sigma, pars[2]=normalization

Returns: the Gaussian function

Warning: pp is not used, it is necessary only for GSL operations

Definition at line 1127 of file Func.h.

◆ generate_correlated_data() [1/2]

std::vector< std::vector< double > > cbl::generate_correlated_data	(	const int	nExtractions,
		const std::vector< double >	mean,
		const std::vector< std::vector< double >>	covariance,
		const int	idum = `12312`
	)

generate a covariant sample of n points using a covariance matrix

Parameters

nExtractions	the number of correlated samples to extract
mean	the mean values for the sample
covariance	the covariance matrix of the sample
idum	seed for random number generator

Returns: std::vector containing a correlated samples of given mean and covariance

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 2613 of file Func.cpp.

◆ generate_correlated_data() [2/2]

std::vector< double > cbl::generate_correlated_data	(	const std::vector< double >	mean,
		const std::vector< std::vector< double >>	covariance,
		const int	idum = `213123`
	)

generate a covariant sample of n points using a covariance matrix

Parameters

mean	the mean values for the sample
covariance	the covariance matrix of the sample
idum	seed for random number generator

Returns: std::vector containing a correlated sample of given mean and covariance

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Examples: correlated_samples.cpp, and covsample.cpp.

Definition at line 2142 of file Func.cpp.

◆ generate_mock_2PCF_monopole()

std::shared_ptr< cbl::data::Data > cbl::generate_mock_2PCF_monopole	(	const cbl::cosmology::Cosmology	cosmology,
		const double	bias,
		const double	nObjects,
		const double	Volume,
		const double	redshift,
		const double	rMin,
		const double	rMax,
		const int	nbins,
		const cbl::BinType	bin_type,
		const std::string	method_Pk = `"CAMB"`,
		const double	sigma_NL = `0.`,
		const bool	NL = `true`
	)

generate mock measurementes of the 2PCF monopole from gaussian covariance matrix

Parameters

cosmology	the cosmology
bias	the bias of the sample
nObjects	the number of objects in the sample
Volume	the volume of the sample
redshift	the redshift of the sample
rMin	the minimum scale
rMax	the maximum scale
nbins	the number of bins
bin_type	the binning type
method_Pk	method used to compute the power spectrum; valid choices for method_Pk are: CAMB [http://camb.info/], CLASS [http://class-code.net/], MPTbreeze-v1 [http://arxiv.org/abs/1207.1465], EisensteinHu [http://background.uchicago.edu/~whu/transfer/transferpage.html]
sigma_NL	the BAO damping parameter
NL	0 \(\rightarrow\) linear power spectrum; 1 \(\rightarrow\) non-linear power spectrum

Returns: the best-fit values

Definition at line 143 of file Forecast.cpp.

◆ generate_mock_2PCF_multipoles()

std::shared_ptr< cbl::data::Data > cbl::generate_mock_2PCF_multipoles	(	const cbl::cosmology::Cosmology	cosmology,
		const double	bias,
		const double	nObjects,
		const double	Volume,
		const double	redshift,
		const double	rMin,
		const double	rMax,
		const int	nbins,
		const cbl::BinType	bin_type,
		const std::string	method_Pk = `"CAMB"`,
		const double	sigma_NL = `0.`,
		const bool	NL = `true`
	)

generate mock measurementes of the 2PCF multipoles from gaussian covariance matrix

Parameters

cosmology	the cosmology
bias	the bias of the sample
nObjects	the number of objects in the sample
Volume	the volume of the sample
redshift	the redshift of the sample
rMin	the minimum scale
rMax	the maximum scale
nbins	the number of bins
bin_type	the binning type
method_Pk	method used to compute the power spectrum; valid choices for method_Pk are: CAMB [http://camb.info/], CLASS [http://class-code.net/], MPTbreeze-v1 [http://arxiv.org/abs/1207.1465], EisensteinHu [http://background.uchicago.edu/~whu/transfer/transferpage.html]
sigma_NL	the BAO damping parameter
NL	0 \(\rightarrow\) linear power spectrum; 1 \(\rightarrow\) non-linear power spectrum

Returns: the best-fit values

Definition at line 165 of file Forecast.cpp.

◆ get_mu()

double cbl::get_mu	(	const double	r1,
		const double	r2,
		const double	r3
	)

get the cosine of the angle between two sides of a triangle

\( mu = \frac{r_1^2+r_2^2-r_3^3}{2 \cdot r_1 \cdot r_2}\)

Parameters

r1	the first side of the triangle
r2	the second side of the triangle
r3	the third side of the triangle

Returns: the cosine of the angle between two sides of a triangle

Definition at line 2529 of file Func.cpp.

◆ haversine_distance()

double cbl::haversine_distance	(	const double	ra1,
		const double	ra2,
		const double	dec1,
		const double	dec2
	)

the haversine angular separation

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Parameters

ra1	the Right Ascension of the first object [radians]
ra2	the Right Ascension of the second object [radians]
dec1	the Declination of the first object [radians]
dec2	the Declination of the second object [radians]

Returns: the haversine angular separation [radians]

Definition at line 286 of file Func.cpp.

◆ headerCBL()

std::ostream& cbl::headerCBL ( std::ostream & stream )

inline

provide the header for all internal messages

Parameters

stream an std::ostream object

Returns: the header for internal messages

Definition at line 727 of file Kernel.h.

◆ identity()

template<typename T >

T cbl::identity	(	T	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

the Identity function

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector

Returns: 1.

Warning: pp and par are not used, but they are necessary in the function template

Definition at line 1053 of file Func.h.

◆ index_closest()

template<typename T >

T cbl::index_closest	(	T	x,
		std::vector< T >	vv
	)

given a number x, return the index of the closest element to x in vv

Parameters

x	the value
vv	the std::vector

Returns: the index of the closest element to x in vv

Definition at line 965 of file Kernel.h.

◆ inRange() [1/3]

template<typename T >

bool cbl::inRange	(	std::vector< T >	value,
		std::vector< std::vector< T >>	ranges,
		bool	include_limits = `true`
	)

return false \( \rightarrow \) values outside the range; true \( \rightarrow \) values inside the range

Parameters

value	vector containing the values
ranges	vector containing the ranges
include_limits	true \( \rightarrow \) include limits; false \( \rightarrow \) exclude limits.

Returns: vector of booleans: false \( \rightarrow \) if values outside the range; true \( \rightarrow \) values inside the range

Definition at line 1814 of file Kernel.h.

◆ inRange() [2/3]

template<typename T >

bool cbl::inRange	(	std::vector< T >	value,
		std::vector< T >	min,
		std::vector< T >	max,
		bool	include_limits = `true`
	)

return false \( \rightarrow \) if values are outside the range; true \( \rightarrow \) if values are inside the range

Parameters

value	vector containing the values
min	vector containing the lower limits
max	vector containing the upper limits
include_limits	true \( \rightarrow \) include limits; false \( \rightarrow \) exclude limits.

Returns: vector of booleans: false \( \rightarrow \) values outside the range; true \( \rightarrow \) values inside the range

Definition at line 1789 of file Kernel.h.

◆ inRange() [3/3]

template<typename T >

bool cbl::inRange	(	T	value,
		T	min,
		T	max,
		bool	include_limits = `true`
	)

return false \( \rightarrow \) value outside the range; true \( \rightarrow \) value inside the range

Parameters

value	the value
min	the lower limit
max	the upper limit
include_limits	true \( \rightarrow \) include limits; false \( \rightarrow \) exclude limits.

Returns: false \( \rightarrow \) values outside the range; true \( \rightarrow \) value inside the range

Definition at line 1759 of file Kernel.h.

◆ interpolated()

double cbl::interpolated	(	const double	_xx,
		const std::vector< double >	xx,
		const std::vector< double >	yy,
		const std::string	type
	)

1D interpolation

Parameters

[in]	_xx	the point where the input function will be interpolated or extrapolated
[in]	xx	std::vector containing the binned values of x
[in]	yy	std::vector containing the binned values of the function, y(x), to be interpolated or extrapolated
[in]	type	the method used to interpolate or extrapolate: "Linear" → linear interpolation; "Poly" → polynomial interpolation; "Spline" → cubic spline interpolation; "Rat" → diagonal rational function interpolation; "BaryRat" → barycentric rational interpolation

Returns: the interpolated value of the input function

Warning: if _xx is outside the range of the input std::vector xx, the returned value is the extrapolation

Definition at line 445 of file Func.cpp.

◆ interpolated_2D()

double cbl::interpolated_2D	(	const double	_x1,
		const double	_x2,
		const std::vector< double >	x1,
		const std::vector< double >	x2,
		const std::vector< std::vector< double >>	yy,
		const std::string	type
	)

2D interpolation

Parameters

[in]	_x1	the point in the first dimension where the input function will be interpolated
[in]	_x2	the point in the second dimension where the input function will be interpolated
[in]	x1	std::vector containing the binned values of x in the first dimension
[in]	x2	std::vector containing the binned values of x in the second dimension
[in]	yy	std::vector containing the binned values of the function, y(x), to be interpolated or extrapolated
[in]	type	the method used to interpolate or extrapolate: "Linear" → linear interpolation; "Poly" → polynomial interpolation; "Spline" → cubic spline interpolation; "Rat" → diagonal rational function interpolation; "BaryRat" → barycentric rational interpolation

Returns: the interpolated or extrapolated value of the input function

Warning: if _x1 and/or _x2 are outside the range of the input std::vectors x1 and/or x2, the returned value is the extrapolatation

Definition at line 502 of file Func.cpp.

◆ IntSwap()

int cbl::IntSwap ( const int i )

endian conversion of an integer variable

Parameters

i	an integer variable

Returns: the converted variable i

Definition at line 57 of file Kernel.cpp.

◆ invert_matrix() [1/2]

void cbl::invert_matrix	(	const std::vector< std::vector< double >>	mat,
		std::vector< std::vector< double >> &	mat_inv,
		const double	prec = `1.e-10`,
		const int	Nres = `-1`
	)

function to invert a matrix

this function implements the inversion of a given matrix using the GSL

if the input matrix is a covariance estimated with a finite number (Nres>0) of resamples (e.g. via jackknife or bootstrap), the inverted matrix is corrected as follows (Hartlap, Simon and Schneider 2006):

\[ \hat{C}^{-1}=\left(1-\frac{n_b+1}{N_{res}-1}\right)C^{-1} \]

where \(n_b\) is the number of bins and \(N_{res}\) is the number of resamplings

Parameters

[in]	mat	the matrix to be inverted
[out]	mat_inv	the inverted matrix
[in]	prec	the precision required
[in]	Nres	\(N_{res}\), the number of catalogue resamplings used to estimate the covariance matrix; \(N_{res}=-1\) if the covariance matrix has not been estimated with resampling methods

Definition at line 673 of file Func.cpp.

◆ invert_matrix() [2/2]

void cbl::invert_matrix	(	const std::vector< std::vector< double >>	mat,
		std::vector< std::vector< double >> &	mat_inv,
		const int	i1,
		const int	i2,
		const double	prec = `1.e-10`,
		const int	Nres = `-1`
	)

function to invert a sub-matrix, extracted from a given matrix

this function implements the inversion of a sub-matrix, extracted from a given matrix, using the GSL

if the input matrix is a covariance estimated with a finite number (Nres>0) of resamples (e.g. via jackknife or bootstrap), the inverted matrix is corrected as follows (Hartlap, Simon and Schneider 2006):

\[ \hat{C}^{-1}=\left(1-\frac{n_b+1}{N_{res}-1}\right)C^{-1} \]

where \(n_b\) is the number of bins and \(N_{res}\) is the number of resamplings

Parameters

[in]	mat	the matrix to be inverted
[out]	mat_inv	the inverted matrix
[in]	i1	minimum index considered
[in]	i2	maximum index considered
[in]	prec	the precision required
[in]	Nres	\(N_{res}\), the number of catalogue resamplings used to estimate the covariance matrix; \(N_{res}=-1\) if the covariance matrix has not been estimated with resampling methods

Definition at line 705 of file Func.cpp.

◆ isDimEqual() [1/2]

template<typename T >

bool cbl::isDimEqual	(	const std::vector< std::vector< T > >	mat1,
		const std::vector< std::vector< T > >	mat2
	)

check if the dimensions of two matrices are equal

Parameters

mat1	a matrix
mat2	a matrix

Returns: 0 \(\rightarrow\) the dimensions are different; 1 \(\rightarrow\) the dimensions are equal

Definition at line 1506 of file Kernel.h.

◆ isDimEqual() [2/2]

template<typename T >

bool cbl::isDimEqual	(	const std::vector< T >	vect1,
		const std::vector< T >	vect2
	)

check if the dimensions of two std::vectors are equal

Parameters

vect1	a std::vector
vect2	a std::vector

Returns: 0 \(\rightarrow\) the dimensions are different; 1 \(\rightarrow\) the dimensions are equal

Definition at line 1493 of file Kernel.h.

◆ isSet() [1/7]

bool cbl::isSet ( const double var )

inline

check if the value of a [double] variable has already been set

Parameters

var	a double variable

Returns: if var>par::defaultDouble \( \rightarrow \) true; else \( \rightarrow \) false

Definition at line 836 of file Kernel.h.

◆ isSet() [2/7]

bool cbl::isSet ( const int var )

inline

check if the value of a [int] variable has already been set

Parameters

var	a int variable

Returns: if var>par::defaultInt \( \rightarrow \) true; else \( \rightarrow \) false

Definition at line 814 of file Kernel.h.

◆ isSet() [3/7]

bool cbl::isSet ( const long var )

inline

check if the value of a [long] variable has already been set

Parameters

var	a long variable

Returns: if var>par::defaultLong \( \rightarrow \) true; else \( \rightarrow \) false

Definition at line 825 of file Kernel.h.

◆ isSet() [4/7]

bool cbl::isSet ( const std::string var )

inline

check if the value of a [string] variable has already been set

Parameters

var	a string variable

Returns: if var is different than par::defaultString \( \rightarrow \) true; else \( \rightarrow \) false

Definition at line 803 of file Kernel.h.

◆ isSet() [5/7]

bool cbl::isSet ( const std::vector< double > vect )

inline

check if the values of a [double] std::vector have already been set

Parameters

vect	a vactor of double values

Returns: if vect[i]<par::defaultDouble \(\forall\) i \( \rightarrow \) false; else \( \rightarrow \) true

Definition at line 848 of file Kernel.h.

◆ isSet() [6/7]

bool cbl::isSet ( const std::vector< std::vector< unsigned int >> vect )

inline

check if the values of a [unsigned int] std::vector<std::vector> have already been set

Parameters

vect	a vactor of double values

Returns: if vect[i]<par::defaultDouble \(\forall\) i \( \rightarrow \) false; else \( \rightarrow \) true

Definition at line 884 of file Kernel.h.

◆ isSet() [7/7]

bool cbl::isSet ( const std::vector< unsigned int > vect )

inline

check if the values of a [unsigned int] std::vector have already been set

Parameters

vect	a vactor of double values

Returns: if vect[i]<par::defaultDouble \(\forall\) i \( \rightarrow \) false; else \( \rightarrow \) true

Definition at line 866 of file Kernel.h.

◆ j0()

double cbl::j0 ( const double xx )

the l=0 spherical Bessel function

Parameters

xx	the variable x

Returns: the l=0 spherical Bessel function

Definition at line 2039 of file Func.cpp.

◆ j0_distance_average()

double cbl::j0_distance_average	(	const double	kk,
		const double	r_down,
		const double	r_up
	)

the distance average l=0 spherical Bessel function this function is used to obtain the analytic twop monopole covariance

Parameters

kk	the variable k
r_down	the lower limit of the twopcf bin
r_up	the upper limit of the twopcf bin

Returns: the distance average l=0 spherical Bessel function

Definition at line 2075 of file Func.cpp.

◆ j2()

double cbl::j2 ( const double xx )

the l=2 spherical Bessel function

Parameters

xx	the variable x

Returns: the l=2 spherical Bessel function

Definition at line 2048 of file Func.cpp.

◆ j2_distance_average()

double cbl::j2_distance_average	(	const double	kk,
		const double	r_down,
		const double	r_up
	)

the distance average l=2 spherical Bessel function this function is used to obtain the analytic twop quadrupole covariance

Parameters

kk	the variable k
r_down	the lower limit of the twopcf bin
r_up	the upper limit of the twopcf bin

Returns: the distance average l=2 spherical Bessel function

Definition at line 2087 of file Func.cpp.

◆ j4()

double cbl::j4 ( const double xx )

the l=4 spherical Bessel function

Parameters

xx	the variable x

Returns: the l=4 spherical Bessel function

Definition at line 2057 of file Func.cpp.

◆ jl()

double cbl::jl	(	const double	xx,
		const int	order
	)

the order l spherical Bessel function

Parameters

xx	the variable x
order	the order l of spherical Bessel function

Returns: the order l spherical Bessel function

Definition at line 2066 of file Func.cpp.

◆ jl_distance_average()

double cbl::jl_distance_average	(	const double	kk,
		const int	order,
		const double	r_down,
		const double	r_up
	)

the distance average for the order l-th spherical Bessel function

Parameters

kk	the variable k
order	the shperical Bessel function order
r_down	the lower limit of the twopcf bin
r_up	the upper limit of the twopcf bin

Returns: the distance average l spherical Bessel function

Definition at line 2109 of file Func.cpp.

◆ jl_spherical_integrand()

double cbl::jl_spherical_integrand	(	double	rr,
		void *	params
	)

the generic integrand to obtain the distance average spherical Bessel function of order l

Parameters

rr	the variable r
params	the parameters for the function

Returns: the distance average l=2 spherical Bessel function

Definition at line 2099 of file Func.cpp.

◆ legendre_polynomial()

double cbl::legendre_polynomial	(	const double	mu,
		const int	l
	)

the order l Legendre polynomial

Parameters

mu	the variable mu
l	the order l Legendre polynomial

Returns: the order l Legendre polynomial

Definition at line 1786 of file Func.cpp.

◆ legendre_polynomial_integral()

double cbl::legendre_polynomial_integral	(	double	mu,
		void *	params
	)

the order l Legendre polynomial integrand

Parameters

mu	the variable mu
params	the parameters for the function

Returns: the order l Legendre polynomial integrand

Definition at line 1795 of file Func.cpp.

◆ Legendre_polynomial_mu_average() [1/2]

double cbl::Legendre_polynomial_mu_average	(	const double	mu_min,
		const double	mu_max,
		const int	ll
	)

the average of the Legendre polynomial of the l-th order over the \(\mu=\cos(\theta)\) range

Parameters

mu_min	the lower limit of integration of the Legendre polynomial
mu_max	the upper limit of integration of the Legendre polynomial
ll	the order of the Legendre polynomial

Returns: the average of the Legendre polynomial of the l-th order over the mu range

Definition at line 1816 of file Func.cpp.

◆ Legendre_polynomial_mu_average() [2/2]

double cbl::Legendre_polynomial_mu_average	(	const int	ll,
		const double	mu,
		const double	delta_mu
	)

the average of the Legendre polynomial of the l-th order over the mu range

Parameters

ll	the order of the Legendre polynomial
mu	the order of the Legendre polynomial
delta_mu	the order of the Legendre polynomial

Returns: the average of the Legendre polynomial of the l-th order over the mu range

Definition at line 1806 of file Func.cpp.

◆ Legendre_polynomial_theta_average()

double cbl::Legendre_polynomial_theta_average	(	const double	theta_min,
		const double	theta_max,
		const int	ll
	)

the average of the Legendre polynomial of the l-th order over the \(\theta\) range

Parameters

theta_min	the lower limit of integration of the Legendre polynomial
theta_max	the upper limit of integration of the Legendre polynomial
ll	the order of the Legendre polynomial

Returns: the average of the Legendre polynomial of the l-th order over the mu range

Definition at line 1827 of file Func.cpp.

◆ Legendre_polynomial_triangles_average() [1/2]

vector< vector< double > > cbl::Legendre_polynomial_triangles_average	(	const double	r12,
		const double	r13,
		const double	deltaR,
		const int	lMax,
		const double	rel_err = `1.e-5`,
		const double	abs_err = `1.e-8`,
		const int	nevals = `100`
	)

the average of the Legendre polynomial up to a maximum order lMax of all triangles with sides r12, r13

Parameters

r12	first triangle side
r13	second triangle side
deltaR	the bin width
lMax	the maximum Legedre polynomial order
rel_err	the relative error
abs_err	the absolute error
nevals	the maximum number of integrals evaluation

Returns: the average of the Legendre polynomial of the l-th order over the mu range

Definition at line 1866 of file Func.cpp.

◆ Legendre_polynomial_triangles_average() [2/2]

double cbl::Legendre_polynomial_triangles_average	(	const double	r12_min,
		const double	r12_max,
		const double	r13_min,
		const double	r13_max,
		const double	r23_min,
		const double	r23_max,
		const int	ll,
		const double	rel_err = `1.e-5`,
		const double	abs_err = `1.e-8`,
		const int	nevals = `100`
	)

the average of the Legendre polynomial of the l-th order over the \(r_{12}, r_{13}, r_{23} \)

Parameters

r12_min	the lower limit of integration for \(r_{12}\)
r12_max	the upper limit of integration for \(r_{12}\)
r13_min	the lower limit of integration for \(r_{13}\)
r13_max	the upper limit of integration for \(r_{13}\)
r23_min	the lower limit of integration for \(r_{23}\)
r23_max	the upper limit of integration for \(r_{23}\)
ll	the order of the Legendre polynomial
rel_err	the relative error
abs_err	the absolute error
nevals	the maximum number of integrals evaluation

Returns: the average of the Legendre polynomial of the l-th order over the mu range

Definition at line 1836 of file Func.cpp.

◆ linear_bin_vector()

template<typename T >

std::vector<T> cbl::linear_bin_vector	(	const size_t	nn,
		const T	min,
		const T	max
	)

fill a std::vector with linearly spaced values

Parameters

[in]	nn	the number of steps, i.e. the final dimension of vv
[in]	min	the minimum value of the range of values
[in]	max	the maximum value of the range of values

Returns: a linearly spaced vector

Examples: model_power_spectrum_angular.cpp.

Definition at line 1604 of file Kernel.h.

◆ linear_interpolation_3D()

std::vector< double > cbl::linear_interpolation_3D	(	const std::vector< double >	min,
		std::vector< double >	max,
		std::vector< int >	steps,
		std::vector< std::vector< std::vector< double >>>	func,
		const std::vector< std::vector< double >>	pos
	)

3D interpolation on a 3D regular grid

Parameters

min	Vector of minimum grid values: [minX, minY, minZ]
max	Vector of maximum grid values: [maxX, maxY, maxZ]
steps	Vector of step values in the three grid dimensions: [stepX, stepY, stepZ] The grid can therefore have different steps in different dimensions
func	Orderd matrix of the values of the function to be interpolated, defined in the various points of the grid. Each element is called as func[X][Y][Z]
pos	Vector of points to interpolate on. It must have dimension [Npoints][3]

Returns: The interpolated values

Warning: Interpolation only. No extrapolation will be performed

Definition at line 546 of file Func.cpp.

◆ linearfit()

std::vector<double> cbl::linearfit ( const double xx )

inline

linear function

Parameters

xx	the coordinate x

Returns: a std::vector containing [1, x]

Definition at line 1007 of file Func.h.

◆ Ln()

template<typename T >

T cbl::Ln	(	const T	val,
		const double	fact = `0.9`
	)

natural logarithm

Parameters

val	a number
fact	factor multiplying par::defaultDouble

Returns: if val>0 \( \rightarrow \) log(val); else \( \rightarrow \) par::defaultDouble

Definition at line 937 of file Kernel.h.

◆ locate()

template<typename T >

int cbl::locate	(	const std::vector< T > &	vv,
		const T	xx
	)

locate a value in a given std::vector

Author: Carlo Giocoli; cgioc.nosp@m.oli@.nosp@m.gmail.nosp@m..com

Parameters

vv	a std::vector of generic values
xx	a generic number

Returns: the std::vector index i such that vv[i]~xx

Definition at line 1638 of file Kernel.h.

◆ Log()

template<typename T >

T cbl::Log	(	const T	val,
		const double	fact = `0.9`
	)

common logarithm (i.e. logarithm to base 10)

Parameters

val	a number
fact	factor multiplying par::defaultDouble

Returns: if val>0 \( \rightarrow \) log10(val); else \( \rightarrow \) par::defaultDouble

Definition at line 926 of file Kernel.h.

◆ logarithmic_bin_vector()

template<typename T >

std::vector<T> cbl::logarithmic_bin_vector	(	const size_t	nn,
		const T	min,
		const T	max
	)

fill a std::vector with logarithmically spaced values

Parameters

[in]	nn	the number of steps, i.e. the final dimension of vv
[in]	min	the minimum value of the range of values
[in]	max	the maximum value of the range of values

Returns: a logarithmically spaced vector

Examples: Pk_BoltzmannSolver.cpp, model_2pt_monopole_RSD.cpp, and sizeFunction.cpp.

Definition at line 1621 of file Kernel.h.

◆ LongSwap()

long long cbl::LongSwap ( const long long i )

endian conversion of a long integer variable

Parameters

i	a long integer variable

Returns: the converted variable i

Definition at line 71 of file Kernel.cpp.

◆ makeDir()

int cbl::makeDir	(	std::string	path,
		const std::string	rootPath = `"."`,
		const mode_t	mode = `0777`,
		const bool	verbose = `false`
	)

function to create multiple directories

http://mylinuxtechcorner.blogspot.com/2012/09/c-version-for-mkdir-p.html

Parameters

path	the name of the directory (or directories) to be created recursively (with parents)
rootPath	the path to the root directory
mode	the permissions for the directory
verbose	if true it shows a warning message when the directory to be created already exists

Returns: 0 if no error occurs

Definition at line 381 of file Kernel.cpp.

◆ Mass()

template<typename T >

T cbl::Mass	(	const T	RR,
		const T	Rho
	)

the mass of a sphere of a given radius and density

Parameters

RR	the radius
Rho	the density

Returns: the mass

Definition at line 1243 of file Func.h.

◆ Max()

template<typename T >

T cbl::Max ( const std::vector< T > vect )

maximum element of a std::vector

Parameters

vect	a std::vector

Returns: the maximum element of the std::vector vect

Examples: model_cosmology.cpp.

Definition at line 1336 of file Kernel.h.

◆ max_separations_AP()

void cbl::max_separations_AP	(	const double	Rp_max,
		const double	Pi_max,
		const double	redshift,
		const cosmology::Cosmology &	cosm1,
		const std::vector< cosmology::Cosmology > &	cosm2,
		double &	rpM_AP,
		double &	piM_AP,
		double &	rM_AP
	)

the maximum comoving separations to be used for the AP test, for a given set of test cosmologies

Parameters

[in]	Rp_max	the maximum value of the comoving distance perpendicular to the line-of-sight, r_p,MAX, in the cosmology cosm1
[in]	Pi_max	the maximum value of the comoving distance parallel to the line-of-sight, π_MAX, in the cosmology cosm1
[in]	redshift	the redshift
[in]	cosm1	object of class Cosmology: the assumed (or real) cosmology
[in]	cosm2	a vector of objects of class Cosmology: the test cosmologies
[out]	rpM_AP	the maximum value of the comoving distance perpendicular to the line-of-sight, r_p,MAX, over all the test cosmologies cosm2
[out]	piM_AP	the maximum value of the comoving distance parallel to the line-of-sight, π_MAX, over all the test cosmologies cosm2
[out]	rM_AP	the maximum value of the comoving distance over all the test cosmologies cosm2

Definition at line 98 of file FuncCosmology.cpp.

◆ maxwellian_distr()

template<typename T >

T cbl::maxwellian_distr	(	const T	vel,
		const T	sigma
	)

the Maxwellian distribution

Parameters

vel	velocity
sigma	σ

Returns: the Maxwellian distribution, P(vel)

Definition at line 1157 of file Func.h.

◆ MC_Int() [1/3]

double cbl::MC_Int	(	double	funcconst double,
		const double	x1,
		const double	x2,
		const int	seed = `3213`
	)

simple Monte Carlo integration of f(x)

Parameters

func	the function f(x)
x1	minimum limit of the integral
x2	maximum limit of the integral
seed	the seed for random number generation

Returns: \(\int_{x1}^{x2} f(x)dx\)

Definition at line 295 of file Func.cpp.

◆ MC_Int() [2/3]

double cbl::MC_Int	(	double	funcconst double, const double AA,
		const double	AA,
		const double	x1,
		double	x2,
		const int	seed = `3213`
	)

simple Monte Carlo integration of f(x,A)

Parameters

func	the function f(x,A)
AA	parameter of the function, A
x1	minimum limit of the integral
x2	maximum limit of the integral
seed	the seed for random number generation

Returns: \(\int_{x1}^{x2} f(x)dx\)

Definition at line 345 of file Func.cpp.

◆ MC_Int() [3/3]

double cbl::MC_Int	(	double	funcconst double, const double AA, const double BB, const double CC, const double DD, const double EE,
		const double	AA,
		const double	BB,
		const double	CC,
		const double	DD,
		const double	EE,
		const double	x1,
		const double	x2,
		const int	seed = `3213`
	)

simple Monte Carlo integration of f(x,A,B,C,D,E)

Parameters

func	the function f(x,A,B,C,D,E)
AA	parameter of the function, A
BB	parameter of the function, B
CC	parameter of the function, C
DD	parameter of the function, D
EE	parameter of the function, E
x1	minimum limit of the integral
x2	maximum limit of the integral
seed	the seed for random number generation

Returns: \(\int_{x1}^{x2} f(x,A,B,C,D,E)dx\)

Definition at line 395 of file Func.cpp.

◆ measure_var_function()

void cbl::measure_var_function	(	const std::vector< double >	var,
		const int	bin,
		const double	V_min,
		const double	V_max,
		const double	Volume,
		std::vector< double > &	Var,
		std::vector< double > &	Phi,
		std::vector< double > &	err
	)

measure the var function (where "var" could be the mass, the luminosity, the radius, etc.)

Parameters

[in]	var	std::vector containing the set of data
[in]	bin	the number of bin used
[in]	V_min	the minimum value of the range
[in]	V_max	the maximum value of the range
[in]	Volume	the volume
[out]	Var	std::vector containing the binned values of "var"
[out]	Phi	std::vector containing the binned values of the var function
[out]	err	std::vector containing the Poisson errors

Definition at line 1084 of file Func.cpp.

◆ Min()

template<typename T >

T cbl::Min ( const std::vector< T > vect )

minimum element of a std::vector

Parameters

vect	a std::vector

Returns: the minimum element of the std::vector vect

Examples: model_cosmology.cpp.

Definition at line 1324 of file Kernel.h.

◆ minimum_maximum_indexes()

std::vector< size_t > cbl::minimum_maximum_indexes	(	const std::vector< double >	xx,
		const double	x_min,
		const double	x_max
	)

return the std::vector indexes corresponding to a given interval

Parameters

xx	input std::vector
x_min	minimum x value
x_max	maximum x value

Returns: the 2D std::vector containing the indexes

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 1503 of file Func.cpp.

◆ Moment()

void cbl::Moment	(	const std::vector< double >	data,
		double &	ave,
		double &	adev,
		double &	sdev,
		double &	var,
		double &	skew,
		double &	curt
	)

compute the moments of a set of data

Parameters

[in]	data	the std::vector containing the input data
[out]	ave	the mean
[out]	adev	the average deviation
[out]	sdev	the standard deviation
[out]	var	the variance
[out]	skew	the skewness
[out]	curt	the kurtosis

Definition at line 1058 of file Func.cpp.

◆ multipole_xi0() [1/2]

double cbl::multipole_xi0	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	xi,
		const double	delta_s
	)

xi₀(s) from ξ(r_p,π)

\[ \xi_0(s) = \frac{1}{2}\int_{-1}^1\xi(s,\mu)d\mu \]

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
xi	matrix containing the values of ξ(r,μ)
delta_s	bin size

Returns: xi₀(s)

Definition at line 135 of file FuncMultipoles.cpp.

◆ multipole_xi0() [2/2]

double cbl::multipole_xi0	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	xi
	)

xi₀(s) from ξ(r,μ)

\[ \xi_0(s) = \frac{1}{2}\int_{-1}^1\xi(s,\mu)d\mu \]

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
xi	matrix containing the values of ξ(r,μ)

Returns: xi₀(s)

Definition at line 45 of file FuncMultipoles.cpp.

◆ multipole_xi0_model() [1/2]

double cbl::multipole_xi0_model	(	const double	beta,
		const double	xi_real
	)

the model multipole ξ₀ of the two-point correlation function

Parameters

beta	β=f/b, where f is the linear growth rate and b is the bias
xi_real	the real-space two-point correlation function

Returns: the multipole ξ₀

Definition at line 353 of file FuncMultipoles.cpp.

◆ multipole_xi0_model() [2/2]

double cbl::multipole_xi0_model	(	const double	f_sigma8,
		const double	bias_sigma8,
		const double	sigma8z,
		const double	xi_matter
	)

the model multipole ξ₀ of the two-point correlation function

Parameters

f_sigma8	f*σ₈
bias_sigma8	b*σ₈
sigma8z	σ₈
xi_matter	the real-space two-point correlation function of the dark matter

Returns: the multipole ξ₀

Definition at line 362 of file FuncMultipoles.cpp.

◆ multipole_xi2() [1/2]

double cbl::multipole_xi2	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	xi,
		const double	delta_s
	)

xi₂(s) from ξ(r_p,π)

\[ \xi_2(s) = \frac{5}{2}\int_{-1}^1\xi(s,\mu)L_2(\mu)d\mu \]

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
xi	matrix containing the values of ξ(r,μ)
delta_s	bin size

Returns: xi₂(s)

Definition at line 159 of file FuncMultipoles.cpp.

◆ multipole_xi2() [2/2]

double cbl::multipole_xi2	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	xi
	)

xi₂(s) from ξ(r,μ)

\[ \xi_2(s) = \frac{5}{2}\int_{-1}^1\xi(s,\mu)L_2(\mu)d\mu \]

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
xi	matrix containing the values of ξ(r,μ)

Returns: xi₂(s)

Definition at line 60 of file FuncMultipoles.cpp.

◆ multipole_xi2_model()

double cbl::multipole_xi2_model	(	const double	beta,
		const double	xi_real,
		const double	xi_
	)

the model multipole ξ₂ of the two-point correlation function

Parameters

beta	β=f/b, where f is the linear growth rate and b is the bias
xi_real	the real-space two-point correlation function
xi_	\( \overline{\xi}(r) \)

Returns: the multipole ξ₂

Definition at line 388 of file FuncMultipoles.cpp.

◆ multipole_xi4() [1/2]

double cbl::multipole_xi4	(	const double	ss,
		const std::vector< double >	rp,
		const std::vector< double >	pi,
		const std::vector< std::vector< double >>	xi,
		const double	delta_s
	)

xi₄(s) from ξ(r_p,π)

\[ \xi_4(s) = \frac{9}{2}\int_{-1}^1\xi(s,\mu)L_4(\mu)d\mu \]

Parameters

ss	comoving scale where the multipole is computed
rp	std::vector containing the values of r_p
pi	std::vector containing the values of π
xi	matrix containing the values of ξ(r,μ)
delta_s	bin size

Returns: xi₄(s)

Definition at line 183 of file FuncMultipoles.cpp.

◆ multipole_xi4() [2/2]

double cbl::multipole_xi4	(	const int	indexR,
		const std::vector< double >	mu,
		const std::vector< std::vector< double >>	xi
	)

xi₄(s) from ξ(r,μ)

\[ \xi_4(s) = \frac{9}{2}\int_{-1}^1\xi(s,\mu)L_4(\mu)d\mu \]

Parameters

indexR	index correspondent to the comoving separation where the multipole is computed
mu	std::vector containing the angle between the separation std::vector and the line of sight
xi	matrix containing the values of ξ(r,μ)

Returns: xi₄(s)

Definition at line 75 of file FuncMultipoles.cpp.

◆ multipole_xi4_model()

double cbl::multipole_xi4_model	(	const double	beta,
		const double	xi_real,
		const double	xi_,
		const double	xi__
	)

the model multipole ξ₄ of the two-point correlation function

Parameters

beta	β=f/b, where f is the linear growth rate and b is the bias
xi_real	the real-space two-point correlation function
xi_	\( \overline{\xi}(r) \)
xi__	\( \overline{\overline{\xi}}(r) \)

Returns: the multipole ξ₄

Definition at line 397 of file FuncMultipoles.cpp.

◆ multivariateGaussian()

double cbl::multivariateGaussian	(	std::vector< double >	xx,
		std::shared_ptr< void >	pars
	)

the multivariate Gaussian function

Parameters

xx	the variable x
pars	vector of vectors containing the elements (vectors): pars[0]=mean, pars[1]=&sigma

Returns: the pdf of the multivariate Gaussian

Definition at line 79 of file Func.cpp.

◆ N_different_elements()

template<typename T >

int cbl::N_different_elements ( const std::vector< T > vect_input )

get the number of unique elements of a std::vector

Parameters

vect_input the input std::vector

Returns: the number of unique elements of the input std::vector

Definition at line 1364 of file Kernel.h.

◆ nint()

template<typename T >

int cbl::nint ( const T val )

the nearest integer

Parameters

val a number

Returns: the integer value nearest to val

Definition at line 915 of file Kernel.h.

◆ number_from_distribution()

double cbl::number_from_distribution	(	const std::vector< double >	xx,
		const std::vector< double >	fx,
		const double	xmin,
		const double	xmax,
		const int	seed
	)

return a number sampled from a given distribution

Parameters

xx	std::vector containing the x variables
fx	std::vector containing the f(x) variables
xmin	minimum value of the variable
xmax	maximum value of the variable
seed	random seed

Returns: a std::vector containing the numbers extracted from the given distribution

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 1446 of file Func.cpp.

◆ operator*()

std::vector<std::vector<double> > cbl::operator*	(	const std::vector< std::vector< double > > &	Mat1,
		const std::vector< std::vector< double > > &	Mat2
	)

inline

matrix multiplication

overloading of the * operator used to multiplicate two matrices

Parameters

Mat1	STL std::vector of std::vectors, i.e. a matrix
Mat2	STL std::vector of std::vectors, i.e. a matrix

Returns: Mat1*Mat2

Definition at line 1922 of file Kernel.h.

◆ operator+()

catalogue::Catalogue cbl::operator+	(	const catalogue::Catalogue &	c1,
		const catalogue::Catalogue &	c2
	)

inline

overloading of the + operator, to sum two catalogues

Parameters

c1	object of class Catalogue
c2	object of class Catalogue

Returns: the result of the + operator

Definition at line 58 of file GlobalFunc.h.

◆ P_2()

template<typename T >

T cbl::P_2 ( const T x )

the Legendre polynomial P₂

Parameters

x	the variable x

Returns: P₂

Definition at line 1269 of file Func.h.

◆ P_4()

template<typename T >

T cbl::P_4 ( const T x )

the Legendre polynomial P₄

Parameters

x	the variable x

Returns: P₄

Definition at line 1280 of file Func.h.

◆ P_6()

template<typename T >

T cbl::P_6 ( const T x )

the Legendre polynomial P₆

Parameters

x	the variable x

Returns: P₆

Definition at line 1291 of file Func.h.

◆ perpendicular_distance()

double cbl::perpendicular_distance	(	const double	ra1,
		const double	ra2,
		const double	dec1,
		const double	dec2,
		const double	d1,
		const double	d2
	)

the perpendicular separation, r_p

Parameters

ra1	the Right Ascension of the first object [radians]
ra2	the Right Ascension of the second object [radians]
dec1	the Declination of the first object [radians]
dec2	the Declination of the second object [radians]
d1	the comoving distance of the first object
d2	the comoving distance of the second object

Returns: the perpendicular separation, r_p

Definition at line 259 of file Func.cpp.

◆ Pk0_Kaiser()

std::vector< double > cbl::Pk0_Kaiser	(	const std::vector< double >	kk,
		const std::vector< double >	Pk,
		const double	bias,
		const double	f
	)

function to obtain the linear RSD power spectrum monopole

Parameters

kk	the scales k
Pk	the power spectrum
bias	the bias factor
f	the linear growth factor

Returns: the linear RSD power spectrum monopole

Definition at line 501 of file FuncMultipoles.cpp.

◆ Pk2_Kaiser()

std::vector< double > cbl::Pk2_Kaiser	(	const std::vector< double >	kk,
		const std::vector< double >	Pk,
		const double	bias,
		const double	f
	)

function to obtain the linear RSD power spectrum quadrupole

Parameters

kk	the scales k
Pk	the power spectrum
bias	the bias factor
f	the linear growth factor

Returns: the linear RSD power spectrum quadrupole

Definition at line 516 of file FuncMultipoles.cpp.

◆ Pk4_Kaiser()

std::vector< double > cbl::Pk4_Kaiser	(	const std::vector< double >	kk,
		const std::vector< double >	Pk,
		const double	bias,
		const double	f
	)

function to obtain the linear RSD power spectrum hexadecapole

Parameters

kk	the scales k
Pk	the power spectrum
bias	the bias factor
f	the linear growth factor

Returns: the linear RSD power spectrum hexadecapole

Definition at line 531 of file FuncMultipoles.cpp.

◆ Pk_from_xi() [1/2]

double cbl::Pk_from_xi	(	const double	kk,
		const std::string	file,
		const int	c1 = `1`,
		const int	c2 = `2`,
		const double	r_min = `0.03`,
		const double	r_max = `100.`
	)

the power spectrum computed from the Fourier transform of the two-point correlation function read from a file

Parameters

kk	the wave std::vector, k
file	name of the file where the two-point correlation function is stored
c1	the column of the file corresponding to the comoving separation, r
c2	the column of the file corresponding to the two-point correlation function, ξ(r)
r_min	the minimum value of the comoving separation used in the integral of the Fourier transform
r_max	the maximum value of the comoving separation used in the integral of the Fourier transform

Returns: the power spectrum, P(k)

Definition at line 160 of file FuncXi.cpp.

◆ Pk_from_xi() [2/2]

double cbl::Pk_from_xi	(	const double	kk,
		const std::vector< double >	lgrr,
		const std::vector< double >	lgxi,
		const double	r_min = `0.03`,
		const double	r_max = `100.`
	)

the power spectrum computed from the Fourier transform of the two-point correlation function

Parameters

kk	the wave std::vector, k
lgrr	std::vector containing the logarithm of the comoving separations, log₁₀r
lgxi	std::vector containing the logarithm of the two-point correlation function, log₁₀ξ(r)
r_min	the minimum value of the comoving separation used in the integral of the Fourier transform
r_max	the maximum value of the comoving separation used in the integral of the Fourier transform

Returns: the power spectrum, P(k)

Definition at line 141 of file FuncXi.cpp.

◆ Pkl_Kaiser()

std::vector< std::vector< double > > cbl::Pkl_Kaiser	(	const std::vector< int >	orders,
		const std::vector< double >	kk,
		const std::vector< double >	Pk,
		const double	bias,
		const double	f
	)

function to obtain Pk multipoles from linear RSD (Kaiser)

Parameters

orders	the l-th multipole desired
kk	the scales k
Pk	the power spectrum
bias	the bias factor
f	the linear growth factor

Returns: the power spectrum multipoles

Definition at line 546 of file FuncMultipoles.cpp.

◆ Pkl_Kaiser_integral()

double cbl::Pkl_Kaiser_integral	(	const int	order,
		const double	bias,
		const double	f
	)

function to obtain the Kaiser factor

Parameters

order	the expansion order
bias	the bias factor
f	the linear growth factor

Returns: the Kaiser integral

Definition at line 480 of file FuncMultipoles.cpp.

◆ Pkl_Kaiser_integrand()

double cbl::Pkl_Kaiser_integrand	(	const double	mu,
		void *	parameters
	)

integrand of the 2d power spectrum to obtain power spectrum multipole

Parameters

mu	the value mu
parameters	the parameters for the integration

Returns: the power spectrum multipoles integrand

Definition at line 409 of file FuncMultipoles.cpp.

◆ poisson()

template<typename T >

T cbl::poisson	(	T	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

the poisson distribution

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients: par[0]=mean,

Returns: the poisson distribution

Warning: pp is not used, it is necessary only for GSL operations

Definition at line 1143 of file Func.h.

◆ Pol2()

template<typename T >

T cbl::Pol2	(	T	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

the quadratic function

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients

Returns: the quadratic function: par[0]*x²+par[1]*x+par[2]

Warning: pp is not used, it is necessary only for GSL operations

Definition at line 981 of file Func.h.

◆ Pol3()

template<typename T >

T cbl::Pol3	(	T	xx,
		void *	pp,
		std::vector< double >	par
	)

the cubic function

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients

Returns: the cubic function: par[0]*x³+par[1]*x²+par[2]*x+par[3]

Warning: pp is not used, it is necessary only for GSL operations

Definition at line 997 of file Func.h.

◆ polar_coord() [1/2]

void cbl::polar_coord	(	const double	XX,
		const double	YY,
		const double	ZZ,
		double &	ra,
		double &	dec,
		double &	dd
	)

conversion from Cartesian coordinates to polar coordinates

Parameters

[in]	XX	the Cartesian coordinate x
[in]	YY	the Cartesian coordinate y
[in]	ZZ	the Cartesian coordinate z
[out]	ra	the Right Ascension [radians]
[out]	dec	the Declination [radians]
[out]	dd	the comoving distance

Definition at line 214 of file Func.cpp.

◆ polar_coord() [2/2]

void cbl::polar_coord	(	const std::vector< double >	XX,
		const std::vector< double >	YY,
		const std::vector< double >	ZZ,
		std::vector< double > &	ra,
		std::vector< double > &	dec,
		std::vector< double > &	dd
	)

conversion from Cartesian coordinates to polar coordinates used for a set of objects

Parameters

[in]	XX	std::vector containing the Cartesian coordinates x
[in]	YY	std::vector containing the Cartesian coordinates y
[in]	ZZ	std::vector containing the Cartesian coordinates z
[out]	ra	std::vector containing the Right Ascension values [radians]
[out]	dec	std::vector containing the Declination values [radians]
[out]	dd	std::vector containing the comoving distances

Definition at line 228 of file Func.cpp.

◆ powerlaw()

template<typename T >

T cbl::powerlaw	(	const T	xx,
		const T	x0,
		const T	gamma
	)

the power-law function

Parameters

xx	the variable x
x0	the normalization, x₀
gamma	the slope, γ

Returns: the power-law function: (x/x₀)^γ

Definition at line 1170 of file Func.h.

◆ Print() [1/9]

void cbl::Print ( const std::vector< std::string > vect )

inline

print the elements of a std::vector of string values on the screen

Parameters

vect	a std::vector

Definition at line 1181 of file Kernel.h.

◆ Print() [2/9]

void cbl::Print	(	const std::vector< std::string >	vect1,
		const std::vector< std::string >	vect2
	)

inline

print the elements of two std::vectors of string values on the screen

Parameters

vect1	a std::vector
vect2	a std::vector

Definition at line 1218 of file Kernel.h.

◆ Print() [3/9]

void cbl::Print	(	const std::vector< std::string >	vect1,
		const std::vector< std::string >	vect2,
		const std::vector< std::string >	vect3
	)

inline

print the elements of two std::vectors of string values on the screen

Parameters

vect1	a std::vector
vect2	a std::vector
vect3	a std::vector

Definition at line 1266 of file Kernel.h.

◆ Print() [4/9]

void cbl::Print ( const std::vector< std::vector< std::string >> mat )

inline

print the elements of a matrix of string values on the screen

Parameters

mat	a matrix (i.e. a std::vector of std::vectors)

Definition at line 1305 of file Kernel.h.

◆ Print() [5/9]

template<typename T >

void cbl::Print	(	const std::vector< std::vector< T >>	mat,
		const int	prec = `4`,
		const int	ww = `8`
	)

print the elements of a matrix of non string values on the screen

Parameters

mat	a matrix (i.e. a std::vector of std::vectors)
prec	decimal precision
ww	number of characters to be used as field width

Definition at line 1287 of file Kernel.h.

◆ Print() [6/9]

template<typename T >

void cbl::Print	(	const std::vector< T >	vect,
		const int	prec = `4`,
		const int	ww = `8`
	)

print the elements of a std::vector of non string values on the screen

Parameters

vect	a std::vector
prec	decimal precision
ww	number of characters to be used as field width

Definition at line 1169 of file Kernel.h.

◆ Print() [7/9]

template<typename T >

void cbl::Print	(	const std::vector< T >	vect1,
		const std::vector< T >	vect2,
		const int	prec = `4`,
		const int	ww = `8`
	)

print the elements of a two std::vectors of non string values on the screen

Parameters

vect1	a std::vector
vect2	a std::vector
prec	decimal precision
ww	number of characters to be used as field width

Definition at line 1198 of file Kernel.h.

◆ Print() [8/9]

template<typename T >

void cbl::Print	(	const std::vector< T >	vect1,
		const std::vector< T >	vect2,
		const std::vector< T >	vect3,
		const int	prec = `4`,
		const int	ww = `8`
	)

print the elements of a three std::vectors of non string values on the screen

Parameters

vect1	a std::vector
vect2	a std::vector
vect3	a std::vector
prec	decimal precision
ww	number of characters to be used as field width

Definition at line 1243 of file Kernel.h.

◆ Print() [9/9]

template<typename T >

void cbl::Print	(	const T	value,
		const int	prec,
		const int	ww,
		const std::string	header = `""`,
		const std::string	end = `"\n"`,
		const bool	use_coutCBL = `true`,
		std::ostream &	stream = `std::cout`,
		const std::string	colour = `cbl::par::col_default`
	)

function to print values with a proper homegenised format

Parameters

value	the value print
prec	decimal precision
ww	number of characters to be used as field width
header	string that is added at the beginning of the line
end	string that is added at the end of the line
use_coutCBL	if true, coutCBL is used instead of std::cout
stream	object of class std::ostream
colour	output colour

Examples: 2pt_monopole_errors.cpp, correlated_samples.cpp, minimisation_gsl.cpp, and vectors.cpp.

Definition at line 1142 of file Kernel.h.

◆ quadratic()

std::vector<double> cbl::quadratic ( const double xx )

inline

quadratic function

Parameters

xx	the coordinate x

Returns: a std::vector containing [1, x, x²]

Definition at line 1020 of file Func.h.

◆ Quartile()

vector< double > cbl::Quartile ( const std::vector< double > Vect )

the first, second and third quartiles of a std::vector

Parameters

Vect	the input std::vector

Returns: a std::vector containing the first, second and third quartiles

Definition at line 1002 of file Func.cpp.

◆ radial_velocity()

template<typename T >

T cbl::radial_velocity	(	const T	vx,
		const T	vy,
		const T	vz,
		const T	ra,
		const T	dec
	)

the radial velocity

Parameters

vx	the velocity along the x direction
vy	the velocity along the y direction
vz	the velocity along the z direction
ra	the Right Ascension
dec	the Declination

Returns: the radial velocity

Definition at line 1258 of file Func.h.

◆ radians()

double cbl::radians	(	const double	angle,
		const CoordinateUnits	inputUnits = `CoordinateUnits::_degrees_`
	)

conversion to radians

Parameters

angle	the input angle
inputUnits	the units of the input angle

Returns: the angle in radians

Definition at line 126 of file Func.cpp.

◆ Radius()

template<typename T >

T cbl::Radius	(	const T	Mass,
		const T	Rho
	)

the radius of a sphere of a given mass and density

Parameters

Mass	the mass
Rho	the density

Returns: the radius

Definition at line 1220 of file Func.h.

◆ read_file() [1/2]

std::vector< std::vector< double > > cbl::read_file	(	const std::string	file_name,
		const std::string	path_name,
		const std::vector< int >	column_data,
		const int	skip_nlines = `0`
	)

read a data from a file ASCII

Parameters

file_name	the name of the file to read
path_name	the path where the file is stored
column_data	vector containing the indices of the columns to read, starting the counting from 1
skip_nlines	the number of lines to skip

Returns: a vector of vectors containing the columns (first index) and the lines (second index) read from the file

Author: Sofia Contarini; sofia.nosp@m..con.nosp@m.tarin.nosp@m.i3@u.nosp@m.nibo..nosp@m.it

Definition at line 410 of file Kernel.cpp.

◆ read_file() [2/2]

std::vector< std::vector< double > > cbl::read_file	(	const std::string	file_name,
		const std::string	path_name,
		const std::vector< int >	column_data,
		const std::string	delimiter,
		const char	comment = `'#'`
	)

read a data from a file ASCII. Useful e.g. when the data are written between comment lines.

Parameters

file_name	the name of the file to read
path_name	the path where the file is stored
column_data	vector containing the indices of the columns to read, starting the counting from 0
delimiter	the delimiter between the columns
comment	the comment char at the beginning of the line

Returns: a vector of vectors containing the columns (first index) and the lines (second index) read from the file

Author: Giorgio Lesci; giorg.nosp@m.io.l.nosp@m.esci2.nosp@m.@uni.nosp@m.bo.it

Definition at line 464 of file Kernel.cpp.

◆ read_invert_covariance()

void cbl::read_invert_covariance	(	const std::string	filecov,
		std::vector< std::vector< double >> &	cov,
		std::vector< std::vector< double >> &	cov_inv,
		const size_t	i1,
		const size_t	i2,
		const double	prec = `1.e-10`,
		const int	Nres = `-1`
	)

read and invert the covariance matrix

Parameters

[in]	filecov	input file where the covariance matrix is stored
[out]	cov	the covariance matrix
[out]	cov_inv	the inverse of the covariance matrix
[in]	i1	mininum index
[in]	i2	maximum index
[in]	prec	the precision required
[in]	Nres	\(N_{res}\), the number of catalogue resamplings used to estimate the covariance matrix; \(N_{res}=-1\) if the covariance matrix has not been estimated with resampling methods

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 1522 of file Func.cpp.

◆ read_matrix()

void cbl::read_matrix	(	const std::string	file_matrix,
		std::vector< double > &	xx,
		std::vector< double > &	yy,
		std::vector< std::vector< double >> &	matrix,
		const std::vector< int >	col = `{}`
	)

read a matrix from file

Parameters

[in]	file_matrix	input file where the matrix is stored
[out]	xx	the variable in row
[out]	yy	the variable in column
[out]	matrix	the matrix
[in]	col	the columns to be read

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 612 of file Func.cpp.

◆ read_vector()

void cbl::read_vector	(	const std::string	file_vector,
		std::vector< double > &	xx,
		std::vector< double > &	vector,
		const std::vector< int >	col = `{}`
	)

read a vector from file

Parameters

[in]	file_vector	input file where the vector is stored
[out]	xx	the variable
[out]	vector	the vector
[in]	col	the columns to be read

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 582 of file Func.cpp.

◆ reconstruction_fourier_space()

void cbl::reconstruction_fourier_space	(	const catalogue::Catalogue	data,
		const catalogue::Catalogue	random,
		const bool	random_RSD,
		const cosmology::Cosmology	cosmology,
		const double	redshift,
		const double	bias,
		const double	cell_size,
		const double	smoothing_radius,
		const int	interpolation_type = `0`
	)

compute the non linear displacements of the density field

Parameters

data	the data catalogue
random	the random catalogue
random_RSD	true \( \rightarrow \) RSD displacements for the random sample; false no-RSD displacements for the random sample
cosmology	the cosmology
redshift	the redshift
bias	the bias
cell_size	the cell size for density field computation
smoothing_radius	the smoothing radius for density field computation
interpolation_type	0 \( \rightarrow \) compute density field using Nearest Grid Point (NGP) method; 0 \( \rightarrow \) compute density field using Cloud-in-cell (CIC) method

Definition at line 45 of file Reconstruction.cpp.

◆ rectangular()

template<typename T >

T cbl::rectangular	(	T	xx,
		std::shared_ptr< void >	pp,
		std::vector< double >	par
	)

the rectangular distribution

Parameters

xx	the variable x
pp	a void pointer
par	a std::vector containing the coefficients: par[0]=lower limix, par[1]=upper limit;

Returns: the probability of x

Warning: pp is not used, but they are necessary in the function template

Definition at line 1071 of file Func.h.

◆ redshift_range()

void cbl::redshift_range	(	const double	mean_redshift,
		const double	boxSide,
		cosmology::Cosmology &	real_cosm,
		double &	redshift_min,
		double &	redshift_max
	)

compute the redsfhit range of a simulation box centered at z=mean_redshift

Parameters

[in]	mean_redshift	the mean redshift
[in]	boxSide	the box side
[in]	real_cosm	an object of class Cosmology
[out]	redshift_min	the minimum redshift
[out]	redshift_max	the maximum redshift

Definition at line 45 of file Func.cpp.

◆ relative_error_beta()

double cbl::relative_error_beta	(	const double	bias,
		const double	Volume,
		const double	density
	)

estimated relative error on \(\beta=f/b\)

\( \delta\beta/\beta\sim Cb^{0.7}V^{-0.5} \exp\left[n_0/(b^2n)\right] \)

where \(n_0=1.7\times10^{-4} h^3 Mpc^{-3}\) and \(C=4.9\times10^2 h^{-1.5} Mpc^{1.5}\)

see Eq. 20 of Bianchi et al. 2012, http://arxiv.org/abs/1203.1545

Parameters

bias	the linear galaxy bias, b
Volume	the survey volume, V
density	the galaxy density, n

Returns: \(\delta\beta/\beta\)

Definition at line 1072 of file Func.cpp.

◆ reshape()

template<typename T >

std::vector<std::vector<T> > cbl::reshape	(	std::vector< T >	vec,
		const int	size1,
		const int	size2
	)

reshape a vector into a matrix of given number of rows and columns

Parameters

vec	the input vector
size1	the number of rows
size2	the number of columns

Returns: the reshaped matrix

Definition at line 1707 of file Kernel.h.

◆ round_to_digits()

double cbl::round_to_digits	(	const double	num,
		const int	ndigits
	)

reduce the digit figures of an input double

e.g. round(0.2363, 2) = 0.24, round(13.24, 1) = 10

Parameters

num	the input double number
ndigits	the number of digit figures

Returns: the input number with the required digit figures

Definition at line 133 of file Kernel.cpp.

◆ round_to_precision()

double cbl::round_to_precision	(	const double	num,
		const int	ndigits
	)

reduce the precision of an input double

e.g. round(0.2363, 2) = 0.23, round(13.24, 1) = 13.2

Parameters

num	the input double number
ndigits	the number of digit figures

Returns: the input number with the required digit figures

Definition at line 150 of file Kernel.cpp.

◆ sdss2eq()

void cbl::sdss2eq	(	const std::vector< double >	lambda,
		const std::vector< double >	eta,
		std::vector< double > &	ra,
		std::vector< double > &	dec
	)

convert sdss coordinates \( \lambda, \eta \) to R.A., Dec.

Parameters

lambda	vector containing the \( \lambda \) values
eta	vector containing the \( \eta \) values
ra	vector containing R.A. values
dec	vector containing Dec. values

Definition at line 1397 of file Func.cpp.

◆ sdss_atbound()

void cbl::sdss_atbound	(	double &	angle,
		const double	minval,
		const double	maxval
	)

check if ra coordinate is inside the boundaries

Parameters

angle	the angle
minval	angle lower limit
maxval	angle upper limit

Definition at line 1347 of file Func.cpp.

◆ sdss_atbound2()

void cbl::sdss_atbound2	(	double &	theta,
		double &	phi
	)

set the angular coordinates in the SDSS boundaries

Parameters

theta	the first angular coordinate
phi	the second angular coordinate

Definition at line 1356 of file Func.cpp.

◆ sdss_stripe()

void cbl::sdss_stripe	(	const std::vector< double >	eta,
		const std::vector< double >	lambda,
		std::vector< int > &	stripe,
		std::vector< int > &	str_u
	)

compute the SDSS stripe given SDSS coordinates \( \lambda, \eta \)

Parameters

eta	vector containing the \( \eta \) values
lambda	vector containing the \( \lambda \) values
stripe	vector containing the stripe value
str_u	vector containing the list of stripes

Definition at line 1420 of file Func.cpp.

◆ set_EnvVar()

void cbl::set_EnvVar ( const std::vector< std::string > Var )

set evironment variables

Parameters

Var	std::vector containing the evironment variables to be set

Definition at line 186 of file Kernel.cpp.

◆ set_ObjectRegion_mangle() [1/2]

void cbl::set_ObjectRegion_mangle	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random,
		const int	nSamples,
		const std::string	polygonfile
	)

set the object region in sub-regions using mangle

Parameters

data	input data catalogue
random	random catalogue
nSamples	number of sub-regions
polygonfile	name of the input file with polygons

Definition at line 387 of file SubSample.cpp.

◆ set_ObjectRegion_mangle() [2/2]

void cbl::set_ObjectRegion_mangle	(	catalogue::Catalogue &	data,
		const int	nSamples,
		const std::string	polygonfile
	)

set the object region in sub-regions using mangle

Parameters

data	input data catalogue
nSamples	number of sub-regions
polygonfile	name of the input file with polygons

Definition at line 268 of file SubSample.cpp.

◆ set_ObjectRegion_RaDec() [1/2]

void cbl::set_ObjectRegion_RaDec	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random,
		const int	nCells_Ra,
		const int	nCells_Dec,
		const bool	use_colatitude = `true`
	)

set the object region in angular SubBoxes

Parameters

data	input data catalogue
random	random catalogue
nCells_Ra	the number of cells along the R.A. direction
nCells_Dec	the number of cells along the Dec. direction
use_colatitude	convert declination to colatitude. This allows a contigous pixelization. Default is true. Set to false if you sample already uses colatitude

Warning: The cell area is:
\[ S \, = \Delta \alpha \left(cos(\delta_{max})-\cos(\delta_{min})\right) \]
with \(\alpha\) the right ascension and \(\delta\) the declination. The area discretization is done w.r.t. the right ascension and the cosine of the declination. This implies that the number of cells in the declination axis will not correspond to a constant spacing in \(\delta\).

Definition at line 541 of file SubSample.cpp.

◆ set_ObjectRegion_RaDec() [2/2]

void cbl::set_ObjectRegion_RaDec	(	catalogue::Catalogue &	data,
		const int	nCells_Ra,
		const int	nCells_Dec,
		const bool	use_colatitude = `true`
	)

set the object region in angular SubBoxes

Parameters

data	input data catalogue
nCells_Ra	the number of cells along the R.A. direction
nCells_Dec	the number of cells along the Dec. direction
use_colatitude	convert declination to colatitude. This allows a contigous pixelization. Default is true. Set to false if you sample already uses colatitude

Warning: The cell area is:
\[ S \, = \Delta \alpha \left(cos(\delta_{max})-\cos(\delta_{min})\right) \]
with \(\alpha\) the right ascension and \(\delta\) the declination. The area discretization is done w.r.t. the right ascension and the cosine of the declination. This implies that the number of cells in the declination axis will not correspond to a constant spacing in \(\delta\).

Examples: numberCounts_errors.cpp, and power_spectrum_angular.cpp.

Definition at line 498 of file SubSample.cpp.

◆ set_ObjectRegion_SDSS_stripes()

void cbl::set_ObjectRegion_SDSS_stripes	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random
	)

set the object region in SDSS stripes

Parameters

data	input data catalogue
random	random catalogue

Definition at line 672 of file SubSample.cpp.

◆ set_ObjectRegion_SubBoxes() [1/2]

void cbl::set_ObjectRegion_SubBoxes	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random,
		const int	nx,
		const int	ny,
		const int	nz
	)

set the object region in sub-boxes

Parameters

data	input data catalogue
random	random catalogue
nx	side fraction used to divide the box in the x direction
ny	side fraction used to divide the box in the y direction
nz	side fraction used to divide the box in the z direction

Definition at line 338 of file SubSample.cpp.

◆ set_ObjectRegion_SubBoxes() [2/2]

void cbl::set_ObjectRegion_SubBoxes	(	catalogue::Catalogue &	data,
		const int	nx,
		const int	ny,
		const int	nz
	)

set the object region in sub-boxes

Parameters

data	input data catalogue
nx	side fraction used to divide the box in the x direction
ny	side fraction used to divide the box in the y direction
nz	side fraction used to divide the box in the z direction

Examples: 2pt_monopole_errors.cpp, and 3pt.cpp.

Definition at line 236 of file SubSample.cpp.

◆ set_ObjectRegion_Tiles_Redshift()

void cbl::set_ObjectRegion_Tiles_Redshift	(	catalogue::Catalogue &	data,
		catalogue::Catalogue &	random,
		const int	nz
	)

set data and random objects' regions given R.A.-Dec tiles and a number of redshift sub-samples. The user must set the identification number of the tiles (cbl::catalogue::Var::_Region_), with cbl::catalogue::Catalogue::set_region(), both in the input data catalogue and in the random catalogue.

Author: Giorgio Lesci (giorg.nosp@m.io.l.nosp@m.esci2.nosp@m.@uni.nosp@m.bo.it)

Parameters

data	input data catalogue
random	random catalogue
nz	number of redshift sub-samples

Definition at line 44 of file SubSample.cpp.

◆ sgn()

template<typename T >

double cbl::sgn ( T val )

sgn the sign function

Parameters

val	the input value

Returns: the sign value

Definition at line 2227 of file Func.cpp.

◆ ShortSwap()

short cbl::ShortSwap ( const short s )

endian conversion of a short variable

Parameters

s	a short variable

Returns: the converted variable s

Definition at line 45 of file Kernel.cpp.

◆ Sigma() [1/2]

double cbl::Sigma ( const std::vector< double > vect )

the standard deviation of a std::vector

for the derivation of the formulae used here for numerically stable calculation see Chan et al. 1979, Finch 2009 and reference therein

Parameters

vect	the input std::vector

Returns: σ

Examples: correlated_samples.cpp.

Definition at line 925 of file Func.cpp.

◆ Sigma() [2/2]

double cbl::Sigma	(	const std::vector< double >	vect,
		const std::vector< double >	weight
	)

the weighted standard deviation of a std::vector

for the derivation of the formulae used here for numerically stable calculation see Chan et al. 1979, Finch 2009 and reference therein

Parameters

vect	the input std::vector
weight	the weight

Returns: σ

Definition at line 963 of file Func.cpp.

◆ sigma2_integrand()

double cbl::sigma2_integrand	(	const double	mu,
		void *	parameters
	)

integrand of the 2d power spectrum to obtain sigma^2(k)

Parameters

mu	the value mu
parameters	the parameters for the integration

Returns: the sigma2 integrand

Definition at line 446 of file FuncMultipoles.cpp.

◆ sigma2_k()

std::vector< std::vector< double > > cbl::sigma2_k	(	const double	nObjects,
		const double	Volume,
		const std::vector< double >	kk,
		const std::vector< std::vector< double >>	Pk_multipoles,
		const std::vector< int >	orders
	)

multipole expansion of the per-mode covariance sigma2_k (see Grieb et al. 2016, eq. 15 https://arxiv.org/pdf/1509.04293)

\[ \sigma_{\ell_{1} \ell_{2}}^{2}(k) \equiv \frac{\left(2 \ell_{1}+1\right)\left(2 \ell_{2}+1\right)}{V_{\mathrm{s}}} \times \int_{-1}^{1}\left[P(k, \mu)+\frac{1}{\bar{n}}\right]^{2} \mathcal{L}_{\ell_{1}}(\mu) \mathcal{L}_{\ell_{2}}(\mu) \mathrm{d} \mu \]

where \(P(k, \mu)\) is the polar power spectrum computed from input power spectrum multipoles and \(\mathcal{L}\) are the Legendre polynomials.

Parameters

nObjects	number of objects in the sample
Volume	the sample volume
kk	the scales kk
Pk_multipoles	the power spectrum multipoles
orders	the power spectrum multipoles orders

Returns: the sigma2_k (see i.e. Grieb et al. 2016, eq. 15)

Definition at line 944 of file FuncMultipoles.cpp.

◆ sigmaR()

double cbl::sigmaR	(	const double	RR,
		const int	corrType,
		const std::vector< double >	rr,
		const std::vector< double >	corr
	)

the rms mass fluctuation within a given radius

computed with the spherically averaged correlation function as follows:

\[ \sigma_R^2=\int_0^2dy\,y^2\xi(yR)\left(3-\frac{9y}{4}+\frac{3y^3}{16}\right) \]

or with the projected correlation function as follows:

\[ \sigma_R^2=\frac{1}{R^3}\int_0^\infty dr_p\,r_pw_p(r_p)g(r_p/R) \]

where g(x) is:

\[ \left\{ \begin{array}{ll} \frac{1}{2\pi}\left(3\pi-9x+x^3\right) & \mbox{for}\,x\le2 \\ \frac{1}{2\pi}\left(\frac{-x^4+11x^2-28}{\sqrt{x^2-4}}+x^3-9x+6\sin^{-1}(2/x)\right) & \mbox{for}\,x>2 \\ \end{array} \right. \]

see e.g. Zehavi et al. 2005, ApJ, 621, 22

Parameters

RR	the radius R [Mpc/h]
corrType	1 → the spherically averaged correlation function is used; 2 → the projected correlation function is used
rr	std::vector containing comoving separations
corr	std::vector containing the two-point correlation function

Returns: σ_R: the rms mass fluctuation within a radius R [Mpc/h]

Definition at line 227 of file FuncXi.cpp.

◆ slice()

template<typename T >

std::vector<T> cbl::slice	(	const std::vector< T >	v,
		const int	start = `0`,
		const int	end = `-1`
	)

slice a std::vector from start to stop

Parameters

v	original std::vector
start	starting position
end	ending position

Returns: the sliced std::vector

Definition at line 1947 of file Kernel.h.

◆ sort_2vectors()

void cbl::sort_2vectors	(	std::vector< double >::iterator	p1,
		std::vector< double >::iterator	p2,
		const int	dim
	)

sort the elements of a std::vectors, and the elements of a second std::vector according to the first sorting

Parameters

p1	iterator to the first std::vector
p2	iterator to the second std::vector
dim	dimension of the two std::vectors

Definition at line 323 of file Kernel.cpp.

◆ sort_3vectors()

void cbl::sort_3vectors	(	std::vector< double >::iterator	p1,
		std::vector< double >::iterator	p2,
		std::vector< double >::iterator	p3,
		const int	dim
	)

sort the elements of a std::vectors, and the elements of two other std::vectors according to the first sorting

Parameters

p1	iterator to the first std::vector
p2	iterator to the second std::vector
p3	iterator to the third std::vector
dim	dimension of the three std::vectors

Definition at line 341 of file Kernel.cpp.

◆ sort_4vectors()

void cbl::sort_4vectors	(	std::vector< double >::iterator	p1,
		std::vector< double >::iterator	p2,
		std::vector< double >::iterator	p3,
		std::vector< double >::iterator	p4,
		const int	dim
	)

sort the elements of a std::vectors, and the elements of three other std::vectors according to the first sorting

Parameters

p1	iterator to the first std::vector
p2	iterator to the second std::vector
p3	iterator to the third std::vector
p4	iterator to the four std::vector
dim	dimension of the four std::vectors

Definition at line 359 of file Kernel.cpp.

◆ spherical_harmonics() [1/2]

complex< double > cbl::spherical_harmonics	(	cbl::CoordinateType	coordinate_type,
		const int	l,
		const int	m,
		const double	coord1,
		const double	coord2,
		const double	coord3
	)

the order l, degree m spherical harmonics

Parameters

coordinate_type	the coordinate type (comoving, observed)
l	the degree l
m	the order m
coord1	the variable 1 (xx or RA)
coord2	the variable 2 (yy or Dec)
coord3	the variable 3 (zz or redshift)

Returns: the order l, degree m spherical harmonics

Definition at line 1939 of file Func.cpp.

◆ spherical_harmonics() [2/2]

std::vector< std::vector< complex< double > > > cbl::spherical_harmonics	(	const int	lmax,
		const double	xx,
		const double	yy,
		const double	zz
	)

the spherical harmonics up to \(l_{max}\)

Parameters

lmax	the maximum degree l
xx	the variable x
yy	the variable y
zz	the variable z

Returns: the spherical harmonics up to \(l_{max}\)

Definition at line 1973 of file Func.cpp.

◆ spherical_harmonics_array()

std::vector< std::complex< double > > cbl::spherical_harmonics_array	(	const int	lmax,
		const double	xx,
		const double	yy,
		const double	zz
	)

the spherical harmonics up to \(l_{max}\)

Parameters

lmax	the maximum degree l
xx	the variable x
yy	the variable y
zz	the variable z

Returns: the spherical harmonics up to \(l_{max}\)

Definition at line 2009 of file Func.cpp.

◆ SubMatrix()

template<typename T >

void cbl::SubMatrix	(	std::vector< T > &	xx,
		std::vector< T > &	yy,
		std::vector< std::vector< T > > &	Mat,
		T	val
	)

select a submatrix containing lines and columns with all elements major than val

Warning: this function works only with rectangular matrices and only for a small set of specific cases: use it with care and check carefully the results!

Parameters

[in,out]	xx	the std::vector x
[in,out]	yy	the std::vector y
[in,out]	Mat	the matrix Mat(x,y) (i.e. a std::vector of std::vectors)
[in]	val	a number

Definition at line 1461 of file Kernel.h.

◆ three_spherical_bessel_integral()

double cbl::three_spherical_bessel_integral	(	const double	r1,
		const double	r2,
		const double	r3,
		const int	L1,
		const int	L2,
		const int	L3
	)

compute the integral of three spherical bessel function, from Mehrem (2011)

\[ \int_{0}^{\infty} k^{2} j_{L_{1}}\left(k r_{1}\right) j_{L_{2}}\left(k r_{2}\right) j_{L_{3}}\left(k r_{3}\right) d k = \frac{\pi \beta(\Delta)}{8 \pi^2 r_{1} r_{2} r_{3} \left\langle L_{1} L_{2} 00 | L_{3} 0\right\rangle}(i)^{L_{1}+L_{2}+L_{3}} \left(2 L_{3}+1\right)\left(\frac{r_{1}}{r_{3}}\right)^{L_{3}} \sum_{L=0}^{L_{3}}\left(\begin{array}{c}{2 L_{3}} \\ {2 L}\end{array}\right)^{1 / 2}\left(\frac{r_{2}}{r_{1}}\right)^{L} \times \sum_{l}\left\langle L_{1}\left(L_{3}-L\right) 00 | 0\right\rangle \left\langle L_{2} L 00 | l 0\right\rangle\left\{\begin{array}{lll}{L_{1}} & {L_{2}} & {L_{3}} \\ {L} & {L_{3}-L} & {l}\end{array}\right\} P_{l}(\Delta) \]

where \(\sum_{l}\left\langle l_1 l_2 m_1 m_2 | l_3 m_3 \right\rangle\) is the Clebsh-Gordan coefficient, computed by cbl::clebsh_gordan, and \(\left\{\begin{array}{lll}{L_{1}} & {L_{2}} & {L_{3}} \\ {L} & {L_{3}-L} & {l}\end{array}\right\}\) is the \(6-j\) Wigner symbol.

Parameters

r1
r2
r3
L1	the order of the first spherical bessel function
L2	the order of the second spherical bessel function
L3	the order of the third spherical bessel function

Returns: the integral of three spherical bessel function

Definition at line 2554 of file Func.cpp.

◆ TopHat_WF()

template<typename T >

T cbl::TopHat_WF ( const T kR )

the top-hat window function

Parameters

kR	the variable k*R

Returns: the top-hat window function

Definition at line 1195 of file Func.h.

◆ TopHat_WF_D1()

template<typename T >

T cbl::TopHat_WF_D1 ( const T kR )

the derivative of the top-hat window function

Parameters

kR	the variable k*R

Returns: the derivative of the top-hat window function

Definition at line 1208 of file Func.h.

◆ transpose()

template<typename T >

std::vector<std::vector<T> > cbl::transpose ( std::vector< std::vector< T >> matrix )

transpose a matrix

Parameters

matrix the input matrix

Returns: the transposed matrix

Examples: correlated_samples.cpp.

Definition at line 1729 of file Kernel.h.

◆ trapezoid_integration()

double cbl::trapezoid_integration	(	const std::vector< double >	xx,
		const std::vector< double >	yy
	)

integral, computed with the trapezoid rule, using ordered data

Parameters

xx	the point in which function is defined
yy	values of the function

Returns: the definite integral of the function

Definition at line 2203 of file Func.cpp.

◆ unique_unsorted() [1/3]

void cbl::unique_unsorted ( std::vector< double > & vv )

erase all the equal elements of the input std::vector

Parameters

[in,out] vv a std::vector of double values

Definition at line 296 of file Kernel.cpp.

◆ unique_unsorted() [2/3]

void cbl::unique_unsorted ( std::vector< int > & vv )

erase all the equal elements of the input std::vector

Parameters

[in,out] vv a std::vector of integer values

Definition at line 284 of file Kernel.cpp.

◆ unique_unsorted() [3/3]

void cbl::unique_unsorted ( std::vector< std::string > & vv )

erase all the equal elements of the input std::vector

Parameters

[in,out] vv a std::vector of integer values

Definition at line 308 of file Kernel.cpp.

◆ used_memory()

int cbl::used_memory ( const int type )

get the memory used by current process in kB

Warning: this function works only on Linux systems

Parameters

type	1 \(\rightarrow\) Physical Memory (RAM); 2 \(\rightarrow\) Virtual Memory

Returns: the Physical (RAM) or Virtual Memory used by current process in kB

Definition at line 211 of file Kernel.cpp.

◆ v_M_vt()

template<typename T >

T cbl::v_M_vt	(	const std::vector< T >	vv,
		const std::vector< std::vector< T >>	MM
	)

return the value of

\[ \vec{x} M \vec{x}^T \]

Parameters

[in]	vv	the std::vector v
[in]	MM	the matrix M

Returns: result

Definition at line 1833 of file Kernel.h.

◆ vector_from_distribution()

std::vector< double > cbl::vector_from_distribution	(	const int	nRan,
		const std::vector< double >	xx,
		const std::vector< double >	fx,
		const double	xmin,
		const double	xmax,
		const int	seed
	)

return a std::vector of numbers sampled from a given distribution

Parameters

nRan	number of elements to be extracted
xx	std::vector containing the x variables
fx	std::vector containing the f(x) variables
xmin	minimum value of the variable
xmax	maximum value of the variable
seed	random seed

Returns: a std::vector containing the numbers extracted from the given distribution

Author: Alfonso Veropalumbo; alfon.nosp@m.so.v.nosp@m.eropa.nosp@m.lumb.nosp@m.o@uni.nosp@m.bo.i.nosp@m.t

Definition at line 1455 of file Func.cpp.

◆ vectorReadFromBinary()

template<typename T >

void cbl::vectorReadFromBinary	(	std::ifstream &	fin,
		std::vector< T > &	vec,
		size_t	NN
	)

reads a vector from a binary file

Parameters

fin	input stream
vec	the vector container where data will be stored
NN	the number of elements to be read

Author: Tommaso Ronconi; tronc.nosp@m.oni@.nosp@m.sissa.nosp@m..it

Definition at line 867 of file Func.h.

◆ Vmax_DC_distribution()

void cbl::Vmax_DC_distribution	(	std::vector< double > &	dc,
		std::vector< double > &	nObj,
		const std::vector< double >	D_C,
		const std::vector< double >	zobj_min,
		const std::vector< double >	zobj_max,
		const double	z_min,
		const double	z_max,
		const double	zbin_min,
		const double	zbin_max,
		cosmology::Cosmology &	cosm,
		const double	Area,
		const int	nObjRan,
		const bool	norm = `1`,
		const std::string	file_Vmax = `par::defaultString`,
		const double	delta_dc_Vmax = `100.`,
		const int	seed = `3213`
	)

get a smoothed distribution of comoving distances, estimated with the V_max method

this function is useful to construct random catalogues

Parameters

[out]	dc	d_c: vector containing the output values of the binned comoving distances
[out]	nObj	vector containing the smoothed number of objects at each d_c, estimated with the V_max method
[in]	D_C	vector containing the comoving distances of the objects
[in]	zobj_min	minimum redshift of the objects
[in]	zobj_max	maximum redshift of the objects
[in]	z_min	minimum redshift used to enlarge the range, useful to smooth the redshift distributions
[in]	z_max	maximum redshift used to enlarge the range, useful to smooth the redshift distributions
[in]	zbin_min	minimum redshift of the output binning
[in]	zbin_max	maximum redshift of the output binning
[in]	cosm	object of class Cosmology
[in]	Area	area of the survey
[in]	nObjRan	number of random objects used to assess the smoothed distribution
[in]	norm	0 → don't normalize; 1 → normalize the distribution to the number of objects
[in]	file_Vmax	the output file used to store the smoothed distribution
[in]	delta_dc_Vmax	Δd_c: the bin size of the output smoothed distribution
[in]	seed	the random seed

Definition at line 44 of file FuncCosmology.cpp.

◆ volume()

double cbl::volume	(	const double	boxSize,
		const int	frac,
		const double	Bord,
		const double	mean_redshift,
		cosmology::Cosmology &	real_cosm
	)

get the volume of a simulation box

Parameters

boxSize	the box side
frac	the side fraction (if the input box is a sub-box of a box with side equal to boxSize)
Bord	the redshift interval that is cutted at the bords of the box
mean_redshift	the mean redshift
real_cosm	an object of class Cosmology

Returns: the volume of the simulation

Definition at line 78 of file Func.cpp.

◆ volume_sphere()

template<typename T >

T cbl::volume_sphere ( const T RR )

the volume of a sphere of a given radius

Parameters

RR	the radius

Returns: the volume

Definition at line 1231 of file Func.h.

◆ WarningMsgCBL()

void cbl::WarningMsgCBL	(	const std::string	msg,
		const std::string	functionCBL,
		const std::string	fileCBL
	)

inline

internal CBL warning message

Parameters

msg	std::string containing the warning message
functionCBL	the CBL function in which the warning message is called
fileCBL	the CBL file containing the function in which the warning message is called

Definition at line 747 of file Kernel.h.

◆ wigner3j() [1/2]

double cbl::wigner3j	(	double	l1,
		double	l2,
		double	l3,
		double	m1,
		double	m2,
		double	m3
	)

Wigner \(3-j\) symbol.

Parameters

l1	index
l2	index
l3	index
m1	index
m2	index
m3	index

Returns: the Clebsh-Gordan coefficient

Definition at line 2464 of file Func.cpp.

◆ wigner3j() [2/2]

std::vector< double > cbl::wigner3j	(	double	l2,
		double	l3,
		double	m1,
		double	m2,
		double	m3
	)

Wigner \(3-j\) symbol.

Parameters

l2	index
l3	index
m1	index
m2	index
m3	index

Returns: the Clebsh-Gordan coefficient

Definition at line 2267 of file Func.cpp.

◆ wigner3j_auxA()

double cbl::wigner3j_auxA	(	double	l1,
		double	l2,
		double	l3,
		double	m1,
		double	m2,
		double	m3
	)

Wigner \(3-j\) auxiliar function A.

Parameters

l1	index
l2	index
l3	index
m1	index
m2	index
m3	index

Returns: value used in wigner_3j

Definition at line 2240 of file Func.cpp.

◆ wigner3j_auxB()

double cbl::wigner3j_auxB	(	double	l1,
		double	l2,
		double	l3,
		double	m1,
		double	m2,
		double	m3
	)

Wigner \(3-j\) auxiliar function B.

Parameters

l1	index
l2	index
l3	index
m1	index
m2	index
m3	index

Returns: value used in wigner_3j

Definition at line 2253 of file Func.cpp.

◆ wigner_3j()

double cbl::wigner_3j	(	int	j1,
		int	j2,
		int	j3,
		int	m1,
		int	m2,
		int	m3
	)

Wigner \(3-j\) symbol, use it for l<100.

Parameters

j1	index
j2	index
j3	index
m1	index
m2	index
m3	index

Returns: the Clebsh-Gordan coefficient

Definition at line 2493 of file Func.cpp.

◆ wigner_6j()

double cbl::wigner_6j	(	const int	j1,
		const int	j2,
		const int	j3,
		const int	j4,
		const int	j5,
		const int	j6
	)

Wigner \(6-j\) symbol.

Parameters

j1	index
j2	index
j3	index
j4	index
j5	index
j6	index

Returns: the Clebsh-Gordan coefficient

Definition at line 2502 of file Func.cpp.

◆ window_function()

double cbl::window_function	(	const double	x,
		const double	min = `-1`,
		const double	max = `1`
	)

the unnormalized window function

Parameters

x	the function variable
min	window function minimum
max	windof function maximum

Returns: unnormalized window function

Definition at line 2538 of file Func.cpp.

◆ wp() [1/2]

double cbl::wp	(	const double	rp,
		const std::string	file,
		const double	r_max = `100.`
	)

the projected two-point correlation function

this function estimates the projected correlation function by integrating a given two-point correlation function as follows:

\[ w_p(r_p)=\int_{r_p}^{r_{max}}\frac{\xi(r)}{\sqrt{r^2-r_p^2}}rdr \]

the two-point correlation function is read from a file

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
file	name of the file where the two-point correlation function is stored
r_max	the maximum value of the comoving separation used in the integral

Returns: the projected correlation function, w_p(r_p)

Definition at line 207 of file FuncXi.cpp.

◆ wp() [2/2]

double cbl::wp	(	const double	rp,
		const std::vector< double >	rr,
		const std::vector< double >	xi,
		const double	r_max = `100.`
	)

the projected two-point correlation function

this function estimates the projected correlation function by integrating a given two-point correlation function as follows:

\[ w_p(r_p)=2\int_{r_p}^{r_{max}}\frac{\xi(r)}{\sqrt{r^2-r_p^2}}r{\rm d}r \]

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
rr	std::vector containing the central values of the binned comoving separations, r
xi	std::vector containing the central values of the binned two-point correlation function, ξ(r)
r_max	the maximum value of the comoving separation used in the integral

Returns: the projected correlation function, w(r_p)

Definition at line 192 of file FuncXi.cpp.

◆ Xi0()

std::vector< double > cbl::Xi0	(	const std::vector< double >	r,
		const std::vector< double >	kk,
		const std::vector< double >	Pk0,
		const double	k_cut = `0.7`,
		const double	cut_pow = `2`,
		const int	IntegrationMethod = `1`
	)

function to obtain the two point correlation funciton monopole

Parameters

r	the scales r
kk	the scales k
Pk0	the power spectrum monopole
k_cut	the k scale to cut the integrand
cut_pow	the power of the integrand cut
IntegrationMethod	method for integration

Returns: the linear RSD power spectrum monopole

Definition at line 569 of file FuncMultipoles.cpp.

◆ Xi024_AP() [1/2]

std::vector< std::vector< double > > cbl::Xi024_AP	(	const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::shared_ptr< glob::FuncGrid >	xi0_interp,
		const std::shared_ptr< glob::FuncGrid >	xi2_interp,
		const std::shared_ptr< glob::FuncGrid >	xi4_interp
	)

function to obtain the monopole, quadrupole and hexadecapole of the two-point correlation function

Parameters

alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
xi0_interp	the xi0 interpolator
xi2_interp	the xi2 interpolator
xi4_interp	the xi4 interpolator

Returns: the monopole, quadrupole and hexadecapole of the two point correlation function

Definition at line 772 of file FuncMultipoles.cpp.

◆ Xi024_AP() [2/2]

std::vector< std::vector< double > > cbl::Xi024_AP	(	const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::vector< double >	rl,
		const std::vector< double >	Xi0,
		const std::vector< double >	Xi2,
		const std::vector< double >	Xi4
	)

function to obtain the monopole, quadrupole and hexadecapole of the two-point correlation function

Parameters

alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
rl	the scales at which the multipoles are defined
Xi0	the 2pfc monopole
Xi2	the 2pfc quadrupole
Xi4	the 2pfc hexadecapole

Returns: the monopole, quadrupole and hexadecapole of the two point correlation function

Definition at line 853 of file FuncMultipoles.cpp.

◆ Xi02_AP() [1/2]

std::vector< std::vector< double > > cbl::Xi02_AP	(	const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::shared_ptr< glob::FuncGrid >	xi0_interp,
		const std::shared_ptr< glob::FuncGrid >	xi2_interp
	)

function to obtain the monopole and quadrupole of the two point correlation function

Parameters

alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
xi0_interp	the xi0 interpolator
xi2_interp	the xi2 interpolator

Returns: the monopole and quadrupole of the two point correlation function

Definition at line 736 of file FuncMultipoles.cpp.

◆ Xi02_AP() [2/2]

std::vector< std::vector< double > > cbl::Xi02_AP	(	const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::vector< double >	rl,
		const std::vector< double >	Xi0,
		const std::vector< double >	Xi2
	)

function to obtain the monopole and quadrupole of the two point correlation function

Parameters

alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
rl	the scales at which the multipoles are defined
Xi0	the 2pfc monopole
Xi2	the 2pfc quadrupole

Returns: the monopole and quadrupole of the two point correlation function

Definition at line 811 of file FuncMultipoles.cpp.

◆ Xi2()

std::vector< double > cbl::Xi2	(	const std::vector< double >	rr,
		const std::vector< double >	kk,
		const std::vector< double >	Pk2,
		const double	k_cut = `0.58`,
		const double	cut_pow = `4`,
		const int	IntegrationMethod = `1`
	)

function to obtain the two point correlation function quadrupole

Parameters

rr	the scales r
kk	the scales k
Pk2	the power spectrum quadrupole
k_cut	the k scale to cut the integrand
cut_pow	the power of the integrand cut
IntegrationMethod	method for integration

Returns: the linear RSD power spectrum quadrupole

Definition at line 624 of file FuncMultipoles.cpp.

◆ xi2D_lin_model() [1/3]

double cbl::xi2D_lin_model	(	const double	beta,
		const double	bias,
		const double	xi_real,
		const double	xi_,
		const double	xi__,
		const double	P_2,
		const double	P_4
	)

the linear dispersion model for ξ(r_p,π)

Parameters

beta	β=f/b, where f is the linear growth rate and b is the bias
bias	the bias
xi_real	the real-space correlation function
xi_	\( \overline{\xi}(r) \)
xi__	\( \overline{\overline{\xi}}(r) \)
P_2	the Legendre polynomial P₂
P_4	the Legendre polynomial P₄

Returns: ξ(r_p,π)

Definition at line 473 of file FuncXi.cpp.

◆ xi2D_lin_model() [2/3]

double cbl::xi2D_lin_model	(	const double	rp,
		const double	pi,
		const double	beta,
		const double	bias,
		const std::shared_ptr< void >	funcXiR,
		const std::shared_ptr< void >	funcXiR_,
		const std::shared_ptr< void >	funcXiR__,
		const bool	bias_nl = `0`,
		const double	bA = `0.`
	)

the linear dispersion model for ξ(r_p,π)

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
pi	π: comoving separation parallel to the line-of-sight
beta	β=f/b, where f is the linear growth rate and b is the bias
bias	the bias
funcXiR	pointer to an object of type FuncGrid, to interpolate on \( \xi(r) \)
funcXiR_	pointer to an object of type FuncGrid, to interpolate on \( \overline{\xi}(r) \)
funcXiR__	pointer to an object of type FuncGrid, to interpolate on \( \overline{\overline{\xi}} (r) \)
bias_nl	0 \( \rightarrow \) linear bias; \( \rightarrow \) 1 non-linear bias
bA	the parameter b_A used to model the bias

Returns: ξ(r_p,π)

Definition at line 664 of file FuncXi.cpp.

◆ xi2D_lin_model() [3/3]

double cbl::xi2D_lin_model	(	const double	rp,
		const double	pi,
		const double	beta,
		const double	bias,
		const std::vector< double >	rad_real,
		const std::vector< double >	xi_real,
		const std::vector< double >	xi_,
		const std::vector< double >	xi__,
		const int	index = `-1`,
		const bool	bias_nl = `0`,
		const double	bA = `0.`
	)

the linear dispersion model for ξ(r_p,π)

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
pi	π: comoving separation parallel to the line-of-sight
beta	β=f/b, where f is the linear growth rate and b is the bias
bias	the bias
rad_real	std::vector containing the binnend values of the comoving separations
xi_real	std::vector containing the binnend values of the real-space correlation function
xi_	std::vector containing the binnend values of \( \overline{\xi}(r) \)
xi__	std::vector containing the binnend values of \( \overline{\overline{\xi}}(r) \)
index	index for internal use
bias_nl	0 \( \rightarrow \) linear bias; \( \rightarrow \) 1 non-linear bias
bA	the parameter b_A used to model the bias

Returns: ξ(r_p,π)

Definition at line 491 of file FuncXi.cpp.

◆ xi2D_model() [1/2]

double cbl::xi2D_model	(	const double	rp,
		const double	pi,
		const double	beta,
		const double	bias,
		const double	sigmav,
		const std::shared_ptr< void >	funcXiR,
		const std::shared_ptr< void >	funcXiR_,
		const std::shared_ptr< void >	funcXiR__,
		const double	var,
		const int	FV,
		const bool	bias_nl = `0`,
		const double	bA = `0.`,
		const double	v_min = `-3000.`,
		const double	v_max = `3000.`,
		const int	step_v = `500`
	)

the non-linear dispersion model for ξ(r_p,π)

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
pi	π: comoving separation parallel to the line-of-sight
beta	β=f/b, where f is the linear growth rate and b is the bias
bias	the bias
sigmav	σ₁₂
funcXiR	pointer to an object of type FuncGrid, to interpolate on \( \xi(r) \)
funcXiR_	pointer to an object of type FuncGrid, to interpolate on \( \overline{\xi}(r) \)
funcXiR__	pointer to an object of type FuncGrid, to interpolate on \( \overline{\overline{\xi}} (r) \)
var	1/[H(z)a(z)]
FV	0 \( \rightarrow \) exponential; \( \rightarrow \) 1 gaussian
bias_nl	0 \( \rightarrow \) linear bias; \( \rightarrow \) 1 non-linear bias
bA	the parameter b_A used to model the bias
v_min	the minimum value of the velocity used in the convolution
v_max	the maximum value of the velocity used in the convolution
step_v	the step of the convolution integral

Returns: ξ(r_p,π)

Definition at line 696 of file FuncXi.cpp.

◆ xi2D_model() [2/2]

double cbl::xi2D_model	(	const double	rp,
		const double	pi,
		const double	beta,
		const double	bias,
		const double	sigmav,
		const std::vector< double >	rad_real,
		const std::vector< double >	xi_real,
		const std::vector< double >	xi_,
		const std::vector< double >	xi__,
		const double	var,
		const int	FV,
		int	index = `-1`,
		const bool	bias_nl = `0`,
		const double	bA = `0.`,
		const double	v_min = `-3000.`,
		const double	v_max = `3000.`,
		const int	step_v = `500`
	)

the non-linear dispersion model for ξ(r_p,π)

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
pi	π: comoving separation parallel to the line-of-sight
beta	β=f/b, where f is the linear growth rate and b is the bias
bias	the bias
sigmav	σ₁₂
rad_real	std::vector containing the binnend values of the comoving separations
xi_real	std::vector containing the binnend values of the real-space correlation function
xi_	std::vector containing the binnend values of \( \overline{\xi}(r) \)
xi__	std::vector containing the binnend values of \( \overline{\overline{\xi}}(r) \)
var	1/[H(z)a(z)]
FV	0 \( \rightarrow \) exponential; \( \rightarrow \) Gaussian
index	index for internal use
bias_nl	0 \( \rightarrow \) linear bias; \( \rightarrow \) non-linear bias
bA	the parameter b_A used to model the bias
v_min	the minimum value of the velocity used in the convolution
v_max	the maximum value of the velocity used in the convolution
step_v	the step of the convolution integral

Returns: ξ(r_p,π)

Definition at line 574 of file FuncXi.cpp.

◆ Xi4()

std::vector< double > cbl::Xi4	(	const std::vector< double >	rr,
		const std::vector< double >	kk,
		const std::vector< double >	Pk4,
		const double	k_cut = `0.6`,
		const double	cut_pow = `2`,
		const int	IntegrationMethod = `1`
	)

function to obtain the two point correlation function hexadecapole

Parameters

rr	the scales r
kk	the scales k
Pk4	the power spectrum hexadecapole
k_cut	the k scale to cut the integrand
cut_pow	the power of the integrand cut
IntegrationMethod	method for integration

Returns: the linear RSD power spectrum hexadecapole

Definition at line 680 of file FuncMultipoles.cpp.

◆ xi_from_Pk() [1/2]

double cbl::xi_from_Pk	(	const double	rr,
		const std::string	file,
		const int	c1 = `1`,
		const int	c2 = `2`,
		const double	k_min = `0.`,
		const double	k_max = `100.`,
		const double	aa = `0.`,
		const double	prec = `1.e-2`
	)

the two-point correlation function computed from the Fourier transform of the power spectrum read from a file

Parameters

rr	the comoving separation, r
file	name of the file where the power spectrum is stored
c1	the column of the file corresponding to the wave std::vector, k
c2	the column of the file corresponding to the power spectrum, P(k)
k_min	the minimum value of the wave std::vector used in the integral of the Fourier transform
k_max	the maximum value of the wave std::vector used in the integral of the Fourier transform
aa	parameter used to smooth the integrand, given by the eq. 24 of Anderson et al. 2012
prec	accuracy of the GSL integration

Returns: the two-point correlation function, ξ(r)

Definition at line 109 of file FuncXi.cpp.

◆ xi_from_Pk() [2/2]

double cbl::xi_from_Pk	(	const double	rr,
		const std::vector< double >	lgkk,
		const std::vector< double >	lgPk,
		const double	k_min = `0.`,
		const double	k_max = `100.`,
		const double	aa = `0.`,
		const double	prec = `1.e-2`
	)

the two-point correlation function computed from the Fourier transform of the power spectrum

Parameters

rr	the comoving separation, r
lgkk	std::vector containing the logarithm of the wave std::vectors, log₁₀k
lgPk	std::vector containing the logarithm of the power spectrum, log₁₀P(k)
k_min	the minimum value of the wave std::vector used in the integral of the Fourier transform
k_max	the maximum value of the wave std::vector used in the integral of the Fourier transform
aa	parameter used to smooth the integrand, given by the eq. 24 of Anderson et al. 2012
prec	accuracy of the GSL integration

Returns: the two-point correlation function, ξ(r)

Definition at line 80 of file FuncXi.cpp.

◆ xi_projected_powerlaw()

double cbl::xi_projected_powerlaw	(	const double	rp,
		const double	r0,
		const double	gamma
	)

the projected correlation function, w_p(r_p), computed by modelling the two-point correlation function, ξ(r), as a power-law

Parameters

rp	r_p: comoving separation perpendicular to the line-of-sight
r0	r₀: the clustering normalization
gamma	γ: the clustering slope

Returns: the projected correlation function w_p(r_p)

Definition at line 278 of file FuncXi.cpp.

◆ xi_ratio() [1/2]

double cbl::xi_ratio ( const double beta )

the ratio between the redshift-space and real-space correlation functions

as predicted by the large-scale limit of the Kaiser/Hamilton model:

\[ \frac{\xi(s)}{\xi(r)} = 1 + \frac{2\beta}{3} + \frac{\beta^2}{5} \]

Parameters

beta	β=f/b, where f is the linear growth rate and b is the bias

Returns: ξ(s)/ξ(r)

Definition at line 287 of file FuncXi.cpp.

◆ xi_ratio() [2/2]

double cbl::xi_ratio	(	const double	f_sigma8,
		const double	bias_sigma8
	)

the ratio between the redshift-space and real-space correlation functions

as predicted by the large-scale limit of the Kaiser/Hamilton model:

\[ \frac{\xi(s)}{\xi(r)} = 1 + \frac{2}{3}\frac{f\sigma_8}{b\sigma_8} + \frac{1}{5}\left(\frac{f\sigma_8}{b\sigma_8}\right)^2 \]

Parameters

f_sigma8	f*σ₈
bias_sigma8	b*σ₈

Returns: ξ(s)/ξ(r)

Definition at line 296 of file FuncXi.cpp.

◆ XiMultipoles_from_Xi2D_integrand()

double cbl::XiMultipoles_from_Xi2D_integrand	(	const double	mu,
		void *	parameters
	)

integrand to obtain the 2PCF multipoles from 2D 2pcf in polar coordinates

Parameters

mu	the value mu
parameters	the parameters for the integration

Returns: the 2pcf multipoles integrand

Definition at line 435 of file FuncMultipoles.cpp.

◆ XiMultipoles_integrand()

double cbl::XiMultipoles_integrand	(	const double	kk,
		void *	parameters
	)

integrand to obtain covariance for the 2PCF multipoles

Parameters

kk	the value kk
parameters	the parameters for the integration

Returns: the covariance of 2pcf multipoles integrand

Definition at line 420 of file FuncMultipoles.cpp.

◆ XiWedges_AP() [1/2]

std::vector< std::vector< double > > cbl::XiWedges_AP	(	const std::vector< double >	mu_min,
		const std::vector< double >	delta_mu,
		const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::shared_ptr< glob::FuncGrid >	xi0_interp,
		const std::shared_ptr< glob::FuncGrid >	xi2_interp,
		const std::shared_ptr< glob::FuncGrid >	xi4_interp
	)

function to obtain the 2pcf wedges

Parameters

mu_min	the lower limit of integration for wedges
delta_mu	the mu width for wedges
alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
xi0_interp	the xi0 interpolator
xi2_interp	the xi2 interpolator
xi4_interp	the xi4 interpolator

Returns: the 2pcf wedges

Definition at line 901 of file FuncMultipoles.cpp.

◆ XiWedges_AP() [2/2]

std::vector< std::vector< double > > cbl::XiWedges_AP	(	const std::vector< double >	mu_min,
		const std::vector< double >	delta_mu,
		const double	alpha_perpendicular,
		const double	alpha_parallel,
		const std::vector< double >	rr,
		const std::vector< double >	rl,
		const std::vector< double >	Xi0,
		const std::vector< double >	Xi2,
		const std::vector< double >	Xi4
	)

function to obtain the 2pcf wedges

Parameters

mu_min	the lower limit of integration for wedges
delta_mu	the mu width for wedges
alpha_perpendicular	the shift along the line of sight
alpha_parallel	the shift parallel to the line of sight
rr	the scales r
rl	the scales at which the multipoles are defined
Xi0	the 2pfc monopole
Xi2	the 2pfc quadrupole
Xi4	the 2pfc hecadecapole

Returns: the 2pcf wedges

Definition at line 923 of file FuncMultipoles.cpp.

Namespaces

Classes

Typedefs

Enumerations

Functions

Detailed Description

Typedef Documentation

◆ distribution_func

◆ nDim_distribution_func

Enumeration Type Documentation

◆ BinType

◆ CoordinateType

◆ CoordinateUnits

◆ Dim

Function Documentation

◆ angular_distance()

◆ AP_shift_pi()

◆ AP_shift_r()

◆ AP_shift_rp()

◆ arcminutes()

◆ arcseconds()

◆ Average() [1/2]

◆ Average() [2/2]

◆ average_three_spherical_bessel_integral()

◆ b_nl()

◆ barred_xi_()

◆ barred_xi__()

◆ barred_xi__direct()

◆ barred_xi_direct()

◆ Beep()

◆ bin_function()

◆ bin_function_2D()

◆ binomial_coefficient()

◆ BinTypeCast() [1/4]

◆ BinTypeCast() [2/4]

◆ BinTypeCast() [3/4]

◆ BinTypeCast() [4/4]

◆ BinTypeNames()

◆ cartesian_coord() [1/2]

◆ cartesian_coord() [2/2]

◆ castFromName()

◆ castFromNames()

◆ castFromValue()

◆ castFromValues()

◆ chainMeshInterpolate()

◆ check_EnvVar()

◆ check_memory()

◆ check_regions()

◆ checkDim() [1/2]

◆ checkDim() [2/2]

◆ checkEqual()

◆ checkIO() [1/2]

◆ checkIO() [2/2]

◆ clebsh_gordan()

◆ closest() [1/2]

◆ closest() [2/2]

◆ closest_probability()

◆ colatitude()

◆ conv()

◆ converted_angle()

◆ converted_xi() [1/2]

◆ converted_xi() [2/2]

◆ convolution()

◆ coord_zSpace()

◆ CoordinateTypeCast() [1/4]

◆ CoordinateTypeCast() [2/4]

◆ CoordinateTypeCast() [3/4]

◆ CoordinateTypeCast() [4/4]

◆ CoordinateTypeNames()

◆ CoordinateUnitsCast() [1/4]

◆ CoordinateUnitsCast() [2/4]

◆ CoordinateUnitsCast() [3/4]

◆ CoordinateUnitsCast() [4/4]

◆ CoordinateUnitsNames()

◆ coupling_3j()

◆ covariance_matrix() [1/3]

◆ covariance_matrix() [2/3]

◆ covariance_matrix() [3/3]

◆ Covariance_XiMultipoles()

◆ covariance_XiMultipoles_integrand()