Data binning

[phajy]

We can add new grouping methods such as minimum signal-to-noise ratio.

Multiple datasets could be grouped in the same way so they can be summed for fitting or plotting purposes. In addition provide a method to copying the binning from a template spectrum.

Some existing relevant functions include the following.

SpectralFitting.jl/src/datasets/spectraldata.jl

Lines 273 to 305 in 8b9bbd1

	function regroup!(dataset::SpectralData, grouping; safety_copy = false)
	grp::typeof(grouping) = if safety_copy
	copy(grouping)
	else
	grouping
	end
	itt = GroupingIterator(grp)
	for i in itt
	dataset.energy_low[i[1]] = dataset.energy_low[i[2]]
	dataset.energy_high[i[1]] = dataset.energy_high[i[3]]
	end
	if has_background(dataset)
	regroup!(dataset.background, grp)
	end
	regroup!(dataset.response, grp)
	regroup!(dataset.spectrum, grp)
	resize!(dataset.data_mask, length(itt))
	resize!(dataset.energy_low, length(itt))
	resize!(dataset.energy_high, length(itt))
	# set everything to unmasked
	dataset.data_mask .= 1
	dataset
	end
	function regroup!(dataset::SpectralData; min_counts = nothing)
	if !isnothing(min_counts)
	group_min_counts!(dataset.spectrum, min_counts)
	end
	regroup!(dataset, dataset.spectrum.grouping)
	end

SpectralFitting.jl/src/datasets/spectrum.jl

Lines 86 to 109 in 8b9bbd1

	function group_min_counts!(spectrum::Spectrum, min_counts::Int)
	NEW_GRP = 1
	CONTINUE_GRP = 0
	function _counts(x)
	if spectrum.units == u"counts"
	convert(Int, x)
	elseif spectrum.units == u"counts / s"
	convert(Int, x * spectrum.exposure_time)
	end
	end
	sum::Int = 0
	for (i, f) in enumerate(spectrum.data)
	c = _counts(f)
	sum += c
	if sum >= min_counts
	spectrum.grouping[i] = NEW_GRP
	sum = 0
	else
	spectrum.grouping[i] = CONTINUE_GRP
	end
	end
	end

And the file grouping.jl