Next: Example programs for 2D histograms, Previous: Reading and writing 2D histograms, Up: Histograms
As in the one-dimensional case, a two-dimensional histogram made by counting events can be regarded as a measurement of a probability distribution. Allowing for statistical error, the height of each bin represents the probability of an event where (x,y) falls in the range of that bin. For a two-dimensional histogram the probability distribution takes the form p(x,y) dx dy where,
p(x,y) = n_{ij}/ (N A_{ij})
In this equation n_{ij} is the number of events in the bin which contains (x,y), A_{ij} is the area of the bin and N is the total number of events. The distribution of events within each bin is assumed to be uniform.
size_t nx, ny
- This is the number of histogram bins used to approximate the probability distribution function in the x and y directions.
double * xrange
- The ranges of the bins in the x-direction are stored in an array of nx + 1 elements pointed to by xrange.
double * yrange
- The ranges of the bins in the y-direction are stored in an array of ny + 1 pointed to by yrange.
double * sum
- The cumulative probability for the bins is stored in an array of nx*ny elements pointed to by sum.
The following functions allow you to create a gsl_histogram2d_pdf
struct which represents a two dimensional probability distribution and
generate random samples from it.
This function allocates memory for a two-dimensional probability distribution of size nx-by-ny and returns a pointer to a newly initialized
gsl_histogram2d_pdf
struct. If insufficient memory is available a null pointer is returned and the error handler is invoked with an error code ofGSL_ENOMEM
.
This function initializes the two-dimensional probability distribution calculated p from the histogram h. If any of the bins of h are negative then the error handler is invoked with an error code of
GSL_EDOM
because a probability distribution cannot contain negative values.