shared3p_statistics_distribution.sc

shared3p_statistics_distribution.sc

Module for visualising distribution of data.

Functions:

discreteDistributionCount

discreteDistributionCount(with stepSize)

heatmap

histogram

discreteDistributionCount

Find discrete distribution of an input vector.

Detailed Description

D - any protection domain

Supported types - int32 / int64

Parameters

data

- input vector

isAvailable

- vector indicating which elements of the input vector are available

min

- fixed lowest value in returned matrix (lower values from input vector are discarded)

max

- fixed highest value in returned matrix (higher values from input vector are discarded)

K

- minimum input size

returns a matrix where the first row contains discrete distribution values and the second row contains counts for each value

Leaks max - min

Function Overloads

D int32 discreteDistributionCount(D int32[[1]] data, D bool[[1]] isAvailable, D int32 min, D int32 max, uint K)

D int64 discreteDistributionCount(D int64[[1]] data, D bool[[1]] isAvailable, D int64 min, D int64 max, uint K)

discreteDistributionCount(with stepSize)

Find discrete distribution of an input vector.

Detailed Description

D - any protection domain

Supported types - int32 / int64

Parameters

data

- input vector

isAvailable

- vector indicating which elements of the input vector are available

min

- fixed lowest value in returned matrix (lower values from input vector are discarded)

max

- fixed highest value in returned matrix (higher values from input vector are discarded)

stepSize

- difference between adjacent values in returned matrix (values in returned matrix are: min, min + stepSize, min + 2*stepSize, min + 3*stepSize, …​). Other values from input vector are discarded.

K

- minimum input size

returns a matrix where the first row contains discrete distribution values and the second row contains counts for each value

Leaks (max - min) / stepSize

Function Overloads

D int32 discreteDistributionCount(D int32[[1]] data, D bool[[1]] isAvailable, D int32 min, D int32 max, D int32 stepSize, uint K)

D int64 discreteDistributionCount(D int64[[1]] data, D bool[[1]] isAvailable, D int64 min, D int64 max, D int64 stepSize, uint K)

heatmap

Create a heatmap.

Detailed Description

D - shared3p

Supported types - int32 / int64 / float32 / float64

Parameters

x

- first sample

y

- second sample

xIsAvailable

- vector indicating which elements of x are available

yIsAvailable

- vector indicating which elements of y are available

K

- minimal length of bin side

A heatmap (in this case) is a plot of two variables of a set of data. It can be used to visualise data in the same way as a scatterplot while leaking less information about individual values. Values of sample x will determine coordinates on the x axis and values of sample y will determine coordinates on the y axis. Instead of displaying individual points, this function counts the number of points in fixed rectangular areas (called bins). The counts will then be replaced with ranges.

returns a matrix with two rows. The second row is a flattened matrix with as many elements as there are bins in the heatmap. The second row may actually be longer if there’s less than 8 elements in the matrix. Each bin will contain a number, starting from 1, which indicates the frequency range of the bin. When plotting, a bin with matrix coordinates (i, j) and value z will have its lower left point at (xmin + i · xstep, ymin + j · ystep), will have dimensions (xstep, ystep) and will indicate a frequency count in the range [zmin + z · zstep, zmin + (z + 1) · zstep). The first 8 elements of the first row are

xmin

beginning of x-axis

ymin

beginning of y-axis

xstep

difference of x-axis tics

ystep

difference of y-axis tics

zmin

beginning of z-axis

zstep

difference of z-axis tics

rows

number of rows in the matrix

columns

number of columns in the matrix

Leaks the minimum and maximum values in both inputs

Function Overloads

D int32 heatmap(D int32[[1]] x, D int32[[1]] y, D bool[[1]] xIsAvailable, D bool[[1]] yIsAvailable, uint K)

D int64 heatmap(D int64[[1]] x, D int64[[1]] y, D bool[[1]] xIsAvailable, D bool[[1]] yIsAvailable, uint K)

D float32 heatmap(D float32[[1]] x, D float32[[1]] y, D bool[[1]] xIsAvailable, D bool[[1]] yIsAvailable, uint K)

D float64 heatmap(D float64[[1]] x, D float64[[1]] y, D bool[[1]] xIsAvailable, D bool[[1]] yIsAvailable, uint K)

histogram

Create a histogram.

Detailed Description

D - any protection domain

Supported types - int32 / int64 / float32 / float64

Parameters

data

- input vector

isAvailable

- vector indicating which elements of the input vector are available

returns a matrix where the first row contains histogram bin boundaries and the second row contains counts for each bin (note that the last element of the second row is always 0 because for n bins we have n+1 boundaries). An element x belongs to a bin with boundaries (a, b) if a < x ⇐ b.

Leaks the minimum and maximum values in the input

Leaks the number of missing values in the input

Function Overloads

D int32 histogram(D int32[[1]] data, D bool[[1]] isAvailable)

D int64 histogram(D int64[[1]] data, D bool[[1]] isAvailable)

D float32 histogram(D float32[[1]] data, D bool[[1]] isAvailable)

D float64 histogram(D float64[[1]] data, D bool[[1]] isAvailable)