OEFPHistogram

class OEFPHistogram

The OEFPHistogram class is used to hold a histogram of similarity scores.

This class is an efficient way to obtain statistics on large databases which would be unfeasible to keep as full NxN similarity matrices.

The following classes derive from this class:

OEFPVariogram

Constructors

OEFPHistogram(numBins: int = 200, min: float = 0.0,
              max: float = 1.0) -> OEFPHistogram
OEFPHistogram(arg2: OEFPHistogram) -> OEFPHistogram

Creates an OEFPHistogram object with given number of bins and range.

nrbins: Number of bins in the histogram. (default=200)
min: Minimum bound (inclusive) of the histogram range. (default = 0.0)
max: Maximum bound (inclusive) of the histogram range. (default = 1.0)

Note

The default range of [0,1] covers all built-in similarity measures.

AddSample

AddSample(sample: float) -> int

Adds the sample into the histogram by incrementing the count in the relevant bin. Returns the bin index that the sample went into.

GetBinBoundaries

GetBinBoundaries() -> Iterable[float]

Returns an iterator over the boundaries for each bin.

Note

The number of elements in this iterator is equal to OEFPHistogram.NumBins +1.

GetBinCenters

GetBinCenters() -> Iterable[float]

Returns an iterator over the center value for each bin.

Note

The number of elements in this iterator is equal to OEFPHistogram.NumBins.

Hint

It is generally reasonable to plot the results of OEFPHistogram.GetCounts or OEFPHistogram.GetDensity against the bin centers returned by this method.

GetBinIdx

GetBinIdx(sample: float) -> int

Returns the bin index that the sample would go into without actually adding the sample into the bin.

GetBinWidth

GetBinWidth() -> float

Returns the width of bins in the histogram.

GetCounts

GetCounts() -> Iterable[int]

Returns an iterator over the bin counts.

Note

Even though counts are returned as unsigned integers, they are internally kept as size_t. If the counts are overflowing the unsigned int type of the system, it may be more appropriate to use the normalized OEFPHistogram.GetDensity instead.

GetDensity

GetDensity() -> Iterable[float]

Returns an iterator over the probability density for each bin.

Note

Result is equivalent to OEFPHistogram.GetCounts normalized by OEFPHistogram.NumSamples.

GetMax

GetMax() -> float

Returns upper bound (inclusive) of the histogram range.

GetMin

GetMin() -> float

Returns lower bound (inclusive) of the histogram range.

Mean

Mean() -> float

Approximates and returns the sample mean over the histogram.

Note

This approximation is affected by number of bins in the histogram.

NumBins

NumBins() -> int

Returns the number of bins in the histogram.

NumSamples

NumSamples() -> int

Returns the total number of samples in the histogram.

Std

Std() -> float

Approximates and returns the sample standard deviation over the histogram.

Note

This approximation is affected by number of bins in the histogram.