abstract class GSL::AbstractHistogram
- GSL::AbstractHistogram
- Reference
- Object
Direct Known Subclasses
Defined in:
gsl/base/histogram.crInstance Method Summary
- #bin(n : Int) : Float64
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#clone : Histogram
Returns an exact copy of this histogram
-
#equal_bins(h : AbstractHistogram) : Bool
This function returns true if the all of the individual bin ranges of the two histograms are identical, and false otherwise.
- #find(x : Float64) : UInt64
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#max_bin : UInt64
This function returns the index of the bin containing the maximum value.
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#max_val : Float64
This function returns the maximum value contained in the histogram bins.
-
#mean : Float64
This function returns the mean of the histogrammed variable, where the histogram is regarded as a probability distribution.
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#min_bin : UInt64
This function returns the index of the bin containing the minimum value.
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#min_val : Float64
This function returns the minimum value contained in the histogram bins.
- #nbins
- #range(n : Int) : Tuple(Float64, Float64)
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#sigma : Float64
This function returns the standard deviation of the histogrammed variable, where the histogram is regarded as a probability distribution.
-
#sum : Float64
This function returns the sum of all bin values.
Instance Method Detail
This function returns true if the all of the individual bin ranges of the two histograms are identical, and false otherwise.
This function returns the index of the bin containing the maximum value. In the case where several bins contain the same maximum value the smallest index is returned.
This function returns the mean of the histogrammed variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation. The accuracy of the result is limited by the bin width.
This function returns the index of the bin containing the minimum value. In the case where several bins contain the same maximum value the smallest index is returned.
This function returns the standard deviation of the histogrammed variable, where the histogram is regarded as a probability distribution. Negative bin values are ignored for the purposes of this calculation. The accuracy of the result is limited by the bin width.
This function returns the sum of all bin values. Negative bin values are included in the sum.