Class StatisticRoutines
- Namespace
- NeuralNetworks.Core
- Assembly
- NeuralNetworks.dll
Provides extension methods for computing common statistics on single- and multi-dimensional float arrays, including argmax, min, max, sum, mean, standard deviation, and per-column aggregates.
public static class StatisticRoutines- Inheritance
-
StatisticRoutines
- Inherited Members
Remarks
Methods are implemented for one-dimensional vectors and for two-, three-, and four-dimensional arrays. Standard deviation is computed as population standard deviation (dividing by the total element count).
Methods
Argmax(float[,])
Computes the index of the maximum value for each row.
public static int[] Argmax(this float[,] source)Parameters
sourcefloat[,]The two-dimensional array to evaluate.
Returns
- int[]
An array of length equal to the number of rows, where each element is the column index of the maximum value in that row.
Argmax(float[])
Computes the index of the maximum value for each row.
public static int Argmax(this float[] source)Parameters
sourcefloat[]The array to evaluate.
Returns
- int
The index of the maximum value in the array.
Max(float[,,,])
Returns the maximum element value across all elements of a four-dimensional array.
public static float Max(this float[,,,] source)Parameters
sourcefloat[,,,]The array to scan.
Returns
- float
The maximum value found.
Max(float[,,])
Returns the maximum element value across all elements of a three-dimensional array.
public static float Max(this float[,,] source)Parameters
sourcefloat[,,]The array to scan.
Returns
- float
The maximum value found.
Max(float[,])
Returns the maximum element value across all elements of a two-dimensional array.
public static float Max(this float[,] source)Parameters
sourcefloat[,]The array to scan.
Returns
- float
The maximum value found.
Mean(float[,,,])
Calculates the mean of all elements in the source.
public static float Mean(this float[,,,] source)Parameters
sourcefloat[,,,]The array whose mean will be computed.
Returns
- float
The arithmetic mean of all elements.
Mean(float[,,])
Calculates the mean of all elements in the source.
public static float Mean(this float[,,] source)Parameters
sourcefloat[,,]The array whose mean will be computed.
Returns
- float
The arithmetic mean of all elements.
Mean(float[,])
Calculates the mean of all elements in the source.
public static float Mean(this float[,] source)Parameters
sourcefloat[,]The array whose mean will be computed.
Returns
- float
The arithmetic mean of all elements.
MeanByColumn(float[,])
Calculates the mean of each column in the source.
public static float[] MeanByColumn(this float[,] source)Parameters
sourcefloat[,]The two-dimensional array to process.
Returns
- float[]
A one-dimensional array where each element is the mean of a column.
Min(float[,,,])
Returns the minimum element value across all elements of a four-dimensional array.
public static float Min(this float[,,,] source)Parameters
sourcefloat[,,,]The array to scan.
Returns
- float
The minimum value found.
Min(float[,,])
Returns the minimum element value across all elements of a three-dimensional array.
public static float Min(this float[,,] source)Parameters
sourcefloat[,,]The array to scan.
Returns
- float
The minimum value found.
Min(float[,])
Returns the minimum element value across all elements of a two-dimensional array.
public static float Min(this float[,] source)Parameters
sourcefloat[,]The array to scan.
Returns
- float
The minimum value found.
StdDev(float[,,,])
Calculates the standard deviation for all elements of a four-dimensional array.
public static float StdDev(this float[,,,] source)Parameters
sourcefloat[,,,]The array whose standard deviation will be computed.
Returns
- float
The standard deviation of all elements.
Remarks
Standard deviation is calculated using the formula: sqrt(sum((x - mean)^2) / N), where N is the number
of all elements in the array.
StdDev(float[,,])
Calculates the standard deviation for all elements of a three-dimensional array.
public static float StdDev(this float[,,] source)Parameters
sourcefloat[,,]The array whose standard deviation will be computed.
Returns
- float
The standard deviation of all elements.
Remarks
Standard deviation is calculated using the formula: sqrt(sum((x - mean)^2) / N), where N is the number
of all elements in the array.
StdDev(float[,])
Calculates the standard deviation for all elements of a two-dimensional array.
public static float StdDev(this float[,] source)Parameters
sourcefloat[,]The array whose standard deviation will be computed.
Returns
- float
The standard deviation of all elements.
Remarks
Standard deviation is calculated using the formula: sqrt(sum((x - mean)^2) / N), where N is the number
of all elements in the array.
Sum(float[,,,])
Calculates the sum of all elements in the four-dimensional array.
public static float Sum(this float[,,,] source)Parameters
sourcefloat[,,,]The array to sum.
Returns
- float
The sum of all elements.
Sum(float[,,])
Calculates the sum of all elements in the three-dimensional array.
public static float Sum(this float[,,] source)Parameters
sourcefloat[,,]The array to sum.
Returns
- float
The sum of all elements.
Sum(float[,])
Calculates the sum of all elements in the two-dimensional array.
public static float Sum(this float[,] source)Parameters
sourcefloat[,]The array to sum.
Returns
- float
The sum of all elements.
SumByColumns(float[,])
Calculates the sum of each column in the source.
public static float[] SumByColumns(this float[,] source)Parameters
sourcefloat[,]The two-dimensional array to process.
Returns
- float[]
A one-dimensional array where each element is the sum of a column.