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#ifndef mbl_sample_stats_1d_h_
#define mbl_sample_stats_1d_h_
//:
// \file
// \brief Provides simple statistics on a 1D variable and stores the samples
// \author Graham Vincent
#include <vcl_stdexcept.h>
#include <vcl_iostream.h>
#include <vcl_vector.h>
#include <vnl/vnl_vector.h>
#include <vsl/vsl_fwd.h>
#include <mbl/mbl_stats_1d.h>
//: Provides simple statistics on a 1D variable and stores the samples
class mbl_sample_stats_1d
{
vcl_vector<double> samples_;
mbl_stats_1d stats_1d_;
bool use_mvue_;
public:
//! Default ctor
mbl_sample_stats_1d();
//! ctor with a vcl_vector of samples
mbl_sample_stats_1d(const vcl_vector<double> &samples);
//! ctor with a vnl_vector of samples
mbl_sample_stats_1d(const vnl_vector<double> &samples);
~mbl_sample_stats_1d();
//: Sets type of variance normalisation
// \param mvue if true (the default) the variance uses the "minimum variance unbiased estimator" which normalises by n_samples()-1
// else will normalise the variance by n_samples()
void set_use_mvue(bool b) { use_mvue_=b; }
//: Remove all data
void clear();
//: Add given observation
void add_sample(double v);
//: Number of samples
unsigned n_samples() const;
//! vector of samples
const vcl_vector<double>& samples() const { return samples_; }
//: Mean of current samples
double mean() const ;
//: Mean of absolutes current samples
double mean_of_absolutes() const ;
//: Median of current samples
// Take care. if there are no samples, this method returns maximum double (a very large number)
// Always check number of samples first
double median() const;
//: The last value within the n_th percentile of the distribution.
// \note If there are no samples, this method returns maximum double (a very large number).
// \sa quantile().
double nth_percentile(int n) const;
//: Calculate a value at a specified quantile \a q.
// \param q Required quantile 0.0 <= q <= 1.0
// \note Linearly interpolates between the 2 sample values bracketing the specified quantile position.
double quantile(double q) const;
//: Standard deviation of current samples
double sd() const;
//: Standard error (i.e. sd of estimate of the mean)
double stdError() const;
//: Variance of current samples
double variance() const;
//: Returns the skewness of the samples
double skewness() const;
//: Returns the kurtosis of the samples
double kurtosis() const;
//: Min of current samples
// Take care. if there are no samples, this method returns maximum double
// Always check number of samples first
double min() const;
//: Max of current samples
// Take care. if there are no samples, this method returns -ve maximum double
// Always check number of samples first
double max() const;
//: Sum of current samples
double sum() const;
//: Sum of squares of current samples
double sum_squares() const;
//: root mean square of current samples
double rms() const;
//: Add statistics together
mbl_sample_stats_1d& operator+=(const mbl_sample_stats_1d& s1);
//: Print summary of data
void print_summary(vcl_ostream& os) const;
//: Print all data.
// \param delim Separate each value with this character/string.
void print_all(vcl_ostream& os,
const vcl_string& delim="\n") const;
//: Version number for I/O
short version_no() const;
void b_write(vsl_b_ostream& bfs) const;
void b_read(vsl_b_istream& bfs);
//: Test for equality
bool operator==(const mbl_sample_stats_1d& s) const;
friend
mbl_sample_stats_1d operator+(const mbl_sample_stats_1d& s1, const mbl_sample_stats_1d& s2);
};
///////////////////////////////////////////////////////////////////
// Some functions which are convenient when using the stats object
///////////////////////////////////////////////////////////////////
// Create a vector of doubles from the values in sample where the
// corresponding value in mask is greater than zero
template <class S, class M>
vcl_vector<double> mbl_apply_mask(const S &sample, const M &mask)
{
if (sample.size()==0 || sample.size()!=mask.size()) throw vcl_runtime_error("Mask should be the same size as the sample and not empty\n");
mbl_sample_stats_1d stats;
typename S::const_iterator sit=sample.begin();
typename M::const_iterator mit=mask.begin();
vcl_vector<double> ret;
for ( ; sit!=sample.end(); ++sit, ++mit)
{
if ((*mit))
{
ret.push_back(*sit);
}
}
return ret;
}
//: Binary file stream output operator for class reference
void vsl_b_write(vsl_b_ostream& bfs, const mbl_sample_stats_1d& b);
//: Binary file stream input operator for class reference
void vsl_b_read(vsl_b_istream& bfs, mbl_sample_stats_1d& b);
//: Stream output operator for class reference
vcl_ostream& operator<<(vcl_ostream& os,const mbl_sample_stats_1d& stats);
//: Stream output operator for class reference
void vsl_print_summary(vcl_ostream& os,const mbl_sample_stats_1d& stats);
//: Print all data
void vsl_print_all(vcl_ostream& os, const mbl_sample_stats_1d& stats);
#endif // mbl_sample_stats_1d_h_
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