Create a new histogram from this one and another without altering either.
Return the area under the curve.
The number of buckets utilized by this Histogram.
The number of buckets utilized by this Histogram.
Return the list of buckets of this histogram.
Return the list of buckets of this histogram. Primarily useful for debugging and serialization.
Return an array of x, cdf(x) pairs
Return an array of x, cdf(x) pairs
Note the occurance of 'item'.
Note the occurance of 'item'.
The optional parameter 'count' allows histograms to be built more efficiently. Negative counts can be used to remove a particular number of occurances of 'item'.
Note the occurance of 'item'.
Note the occurance of 'item'.
Note the occurance of 'item'.
Note the occurance of 'item'.
The optional parameter 'count' allows histograms to be built more efficiently. Negative counts can be used to remove a particular number of occurances of 'item'.
Note the occurance of 'item'.
Note the occurance of 'item'.
Note the occurances of 'items'.
Note the occurances of 'items'.
Return the list of deltas of this histogram.
Return the list of deltas of this histogram. Primarily useful for debugging.
Execute the given function on each bucket.
Execute the given function on each bucket. The value contained by the bucket is a Double, and the count is an integer (ergo the signature of the function 'f').
Execute the given function on each bucket label.
Execute the given function on each bucket label.
A unit function of one parameter
Get the (approximate) number of occurrences of an item.
Get the (approximate) number of occurrences of an item.
Return the maximum number of buckets of this histogram.
Return the maximum number of buckets of this histogram.
Gets the maximum value this histogram has seen
Gets the maximum value this histogram has seen
Return the approximate mean of the histogram.
Return the approximate mean of the histogram.
Return the approximate median of the histogram.
Return the approximate median of the histogram.
Return the sum of this histogram and the given one (the sum is the histogram that would result from seeing all of the values seen by the two antecedent histograms).
Return the sum of this histogram and the given one (the sum is the histogram that would result from seeing all of the values seen by the two antecedent histograms).
Return the smallest and largest items seen as a tuple.
Return the smallest and largest items seen as a tuple.
Get the minimum value this histogram has seen.
Get the minimum value this histogram has seen.
Return the approximate mode of the distribution.
Return the approximate mode of the distribution. This is done by simply returning the label of most populous bucket (so this answer could be really bad).
Return a mutable copy of this histogram.
Return a mutable copy of this histogram.
For each q in qs, all between 0 and 1, find a number (approximately) at the qth percentile.
For each q in qs, all between 0 and 1, find a number (approximately) at the qth percentile.
A list of quantiles (0.01 == 1th pctile, 0.2 == 20th pctile) to use in generating breaks
Our aim here is to produce values corresponding to the qs which stretch from minValue to maxValue, interpolating based on observed bins along the way
Get the (approximate) percentile of this item.
This method returns the (approximate) quantile breaks of the distribution of points that the histogram has seen so far.
This method returns the (approximate) quantile breaks of the distribution of points that the histogram has seen so far. It is guaranteed that no value in the returned array will be outside the minimum-maximum range of values seen.
The number of breaks desired
Return an array containing the values seen by this histogram.
Return an array containing the values seen by this histogram.
Make a change to the distribution to approximate changing the value of a particular item.
Make a change to the distribution to approximate changing the value of a particular item.
_min and _max, the minimum and maximum values seen by the histogram, are not changed by this.
Generate Statistics.
Generate Statistics.
Total number of samples used to build this histogram.
Total number of samples used to build this histogram.
Uncount item.
Uncount item.
_min and _max, the minimum and maximum values seen by the histogram, are not changed by this.
Update this histogram with the entries from another.
Update this histogram with the entries from another.
Return an array of bucket values.
Return an array of bucket values.
Ben-Haim, Yael, and Elad Tom-Tov. "A streaming parallel decision tree algorithm." The Journal of Machine Learning Research 11 (2010): 849-872.