57 namespace numbercounts {
79 std::shared_ptr<catalogue::Catalogue>
m_data;
113 {
ErrorCBL(
"",
"m_measurePoisson",
"NumberCounts.h");
return NULL; }
126 { (void)dir_output_resample;
ErrorCBL(
"",
"m_measureJackknife",
"NumberCounts.h");
return NULL; }
143 { (void)dir_output_resample; (void)nResamplings; (void)seed;
ErrorCBL(
"",
"m_measureBootstrap",
"NumberCounts.h");
return NULL; }
219 { (void)errorType; (void)dir_output_resample; (void)nResamplings; (void)seed; (void)
conv; (void)sigma;
ErrorCBL(
"",
"measure",
"NumberCounts.h"); }
235 { (void)dir; (void)file; (void)rank;
ErrorCBL(
"",
"write",
"NumberCounts.h"); }
252 { (void)dir; (void)file;
ErrorCBL(
"",
"write_covariance",
"NumberCounts.h"); }
261 virtual void compute_covariance (
const std::vector<std::shared_ptr<glob::Histogram>> histo,
const bool JK)
262 { (void)histo; (void)JK;
ErrorCBL(
"",
"compute_covariance",
"NumberCounts.h"); }
272 { (void)sigma;
ErrorCBL(
"",
"Gaussian_smoothing",
"NumberCounts.h");
return NULL; }
Class used to handle binned variables.
virtual void write(const std::string dir=par::defaultString, const std::string file=par::defaultString, const int rank=0) const
write the measured number counts
std::shared_ptr< glob::Histogram > histogram()
return the binned counts
virtual void write_covariance(const std::string dir, const std::string file) const
write the measured covariance matrix
std::shared_ptr< catalogue::Catalogue > m_data
input data catalogue
std::shared_ptr< glob::Histogram > m_histogram
number counts type
void set_data(const catalogue::Catalogue data)
add a data catalogue
virtual std::shared_ptr< data::Data > m_measurePoisson()
measure the number counts with Poisson errors
virtual void measure(const ErrorType errorType=ErrorType::_Poisson_, const std::string dir_output_resample=par::defaultString, const int nResamplings=0, const int seed=3213, const bool conv=false, const double sigma=0.)
measure the number counts
virtual void compute_covariance(const std::vector< std::shared_ptr< glob::Histogram >> histo, const bool JK)
compute the covariance matrix
NumberCounts()=default
default constructor
glob::HistogramType m_HistogramType
the histogram type
std::shared_ptr< catalogue::Catalogue > catalogue()
function to get the protected member m_data
virtual ~NumberCounts()=default
default destructor
virtual std::shared_ptr< data::Data > m_measureJackknife(const std::string dir_output_resample=par::defaultString)
measure the number counts with Jackknife covariance matrix
virtual std::shared_ptr< data::Data > Gaussian_smoothing(const double sigma)
apply a Gaussian filter to the distribution
virtual std::shared_ptr< data::Data > m_measureBootstrap(const std::string dir_output_resample=par::defaultString, const int nResamplings=0, const int seed=3213)
measure the number counts with Bootstrap covariance matrix
double fact()
return the normalization factor
glob::HistogramType HistogramType()
return the type of histogram normalization
double m_fact
the normalization factor
static const std::string defaultString
default std::string value
HistogramType
the histogram type
ErrorType
the two-point correlation function error type
@ _Poisson_
Poissonian error.
The global namespace of the CosmoBolognaLib
std::string conv(const T val, const char *fact)
convert a number to a std::string
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