Package ai.sklearn4j.core.libraries.numpy

Class Numpy

java.lang.Object

ai.sklearn4j.core.libraries.numpy.Numpy

public final class Numpy
extends Object

Implementation of the Numpy library APIs.

Constructor Summary

Constructors

Constructor	Description
Numpy()

Method Summary

Modifier and Type	Method	Description
static NumpyArray	abs(NumpyArray<Double> array)	Calculate the absolute value element-wise.
static NumpyArray	add(NumpyArray array, byte value)	Adds a byte value to numpy arrays.
static NumpyArray<Double>	add(NumpyArray array, double value)	Adds a double value to numpy arrays.
static NumpyArray<Float>	add(NumpyArray array, float value)	Adds a float value to numpy arrays.
static NumpyArray	add(NumpyArray array, int value)	Adds a int value to numpy arrays.
static NumpyArray	add(NumpyArray array, long value)	Adds a long value to numpy arrays.
static NumpyArray	add(NumpyArray array, short value)	Adds a short value to numpy arrays.
static NumpyArray	add(NumpyArray a1, NumpyArray a2)	Adds two numpy arrays.
static <Type> NumpyArray<Long>	argmax(NumpyArray<Type> array, int axis, boolean keepDimensions)	Returns the indices of the maximum values along an axis.
static NumpyArray<Double>	arrayMax(NumpyArray<Double> array, int axis, boolean keepDimensions)	Returns the maximum values along an axis.
static NumpyArray<Byte>	atLeast2D(byte value)	Wraps an atomic byte value into a 2 dimensional array.
static NumpyArray<Double>	atLeast2D(double value)	Wraps an atomic double value into a 2 dimensional array.
static NumpyArray<Float>	atLeast2D(float value)	Wraps an atomic float value into a 2 dimensional array.
static NumpyArray<Integer>	atLeast2D(int value)	Wraps an atomic int value into a 2 dimensional array.
static NumpyArray<Long>	atLeast2D(long value)	Wraps an atomic long value into a 2 dimensional array.
static NumpyArray<Short>	atLeast2D(short value)	Wraps an atomic short value into a 2 dimensional array.
static <Type> NumpyArray<Type>	atLeast2D(NumpyArray<Type> array)	Wraps a numpy array into a 2 dimensional array if the number dimensions is less than 2.
static NumpyArray<Double>	clip(NumpyArray<Double> array, double min, double max)	Clip (limit) the values in an array.
static NumpyArray<Double>	divide(NumpyArray<Double> array, double factor)	Divides a numpy array by a double value.
static NumpyArray<Float>	divide(NumpyArray<Float> array, float factor)	Divides a numpy array by a float value.
static NumpyArray	divide(NumpyArray a1, NumpyArray a2)	Divides two numpy arrays.
static NumpyArray<Double>	exp(NumpyArray array)	Calculate the exponential of all elements in the input array.
static NumpyArray<Double>	log(NumpyArray array)	Natural logarithm, element-wise.
static NumpyArray<Double>	multiply(NumpyArray<Double> array, double factor)	Multiplies a numpy array by a double value.
static NumpyArray<Float>	multiply(NumpyArray<Float> array, float factor)	Multiplies a numpy array by a float value.
static NumpyArray	multiply(NumpyArray a1, NumpyArray a2)	Multiplies two numpy arrays.
static NumpyArray<Double>	pow(NumpyArray array, double power)	Performs an element-wise power operation on a given NumpyArray.
static NumpyArray<Double>	sqrt(NumpyArray array)	Return the non-negative square-root of an array, element-wise.
static NumpyArray	squeeze(NumpyArray array)	Remove axes of length one from the array.
static NumpyArray	subtract(NumpyArray array, byte value)	Subtract a byte value from numpy arrays.
static NumpyArray<Double>	subtract(NumpyArray array, double value)	Subtract a double value from numpy arrays.
static NumpyArray<Float>	subtract(NumpyArray array, float value)	Subtract a float value from numpy arrays.
static NumpyArray	subtract(NumpyArray array, int value)	Subtract a int value from numpy arrays.
static NumpyArray	subtract(NumpyArray array, long value)	Subtract a long value from numpy arrays.
static NumpyArray	subtract(NumpyArray array, short value)	Subtract a short value from numpy arrays.
static NumpyArray	subtract(NumpyArray a1, NumpyArray a2)	Subtract two numpy arrays.
static NumpyArray	sum(NumpyArray array, int axis, boolean keepDimensions)	Sums the values of a NumpyArray along a specified axis.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Numpy

public Numpy()

Method Detail

argmax

public static <Type> NumpyArray<Long> argmax(NumpyArray<Type> array,
                                             int axis,
                                             boolean keepDimensions)

Returns the indices of the maximum values along an axis. See: https://numpy.org/doc/stable/reference/generated/numpy.argmax.html

Parameters:

array - The input multidimensional array.

axis - The axis which the argmax should reduce to.

keepDimensions - A flag to specify whether to keep the reduced dimension in the output.

Returns:

Array of indices into the array. It has the same shape as a.shape with the dimension along axis removed.

pow

public static NumpyArray<Double> pow(NumpyArray array,
                                     double power)

Performs an element-wise power operation on a given NumpyArray. See: https://numpy.org/doc/stable/reference/generated/numpy.power.html

Parameters:

array - Input array.

power - The value of the power.

Returns:

An array with same dimension with the requested power calculation.

sum

public static NumpyArray sum(NumpyArray array,
                             int axis,
                             boolean keepDimensions)

Sums the values of a NumpyArray along a specified axis. See: https://numpy.org/doc/stable/reference/generated/numpy.sum.html

Parameters:

array - Input array.

axis - Axis along which a sum is performed.

keepDimensions - A flag to specify whether to keep the reduced dimension in the output.

Returns:

An array with the same shape as a, with the specified axis removed.

exp

public static NumpyArray<Double> exp(NumpyArray array)

Calculate the exponential of all elements in the input array. https://numpy.org/doc/stable/reference/generated/numpy.exp.html

Parameters:

array - Input values.

Returns:

Output array, element-wise exponential of x.

log

public static NumpyArray<Double> log(NumpyArray array)

Natural logarithm, element-wise.

The natural logarithm log is the inverse of the exponential function, so that log(exp(x)) = x. The natural logarithm is logarithm in base e.

Parameters:

array - Input values.

Returns:

Output array, element-wise log of x.

subtract

public static NumpyArray subtract(NumpyArray a1,
                                  NumpyArray a2)

Subtract two numpy arrays.

Parameters:

a1 - Left-hand side of the expression.

a2 - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray add(NumpyArray a1,
                             NumpyArray a2)

Adds two numpy arrays.

Parameters:

a1 - Left-hand side of the expression.

a2 - Right-hand side of the expression.

Returns:

The addition result.

add

public static NumpyArray<Double> add(NumpyArray array,
                                     double value)

Adds a double value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray<Double> subtract(NumpyArray array,
                                          double value)

Subtract a double value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray<Float> add(NumpyArray array,
                                    float value)

Adds a float value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray<Float> subtract(NumpyArray array,
                                         float value)

Subtract a float value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray add(NumpyArray array,
                             byte value)

Adds a byte value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray subtract(NumpyArray array,
                                  byte value)

Subtract a byte value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray add(NumpyArray array,
                             short value)

Adds a short value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray subtract(NumpyArray array,
                                  short value)

Subtract a short value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray add(NumpyArray array,
                             int value)

Adds a int value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray subtract(NumpyArray array,
                                  int value)

Subtract a int value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

add

public static NumpyArray add(NumpyArray array,
                             long value)

Adds a long value to numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The addition result.

subtract

public static NumpyArray subtract(NumpyArray array,
                                  long value)

Subtract a long value from numpy arrays.

Parameters:

array - Left-hand side of the expression.

value - Right-hand side of the expression.

Returns:

The subtraction result.

multiply

public static NumpyArray multiply(NumpyArray a1,
                                  NumpyArray a2)

Multiplies two numpy arrays.

Parameters:

a1 - Left-hand side of the expression.

a2 - Right-hand side of the expression.

Returns:

The multiplication result.

multiply

public static NumpyArray<Double> multiply(NumpyArray<Double> array,
                                          double factor)

Multiplies a numpy array by a double value. The operation is element-wise.

Parameters:

array - The input array to be multiplied.

factor - The value to be multiplied with.

Returns:

A numpy array of the calculation result.

multiply

public static NumpyArray<Float> multiply(NumpyArray<Float> array,
                                         float factor)

Multiplies a numpy array by a float value. The operation is element-wise.

Parameters:

array - The input array to be multiplied.

factor - The value to be multiplied with.

Returns:

A numpy array of the calculation result.

divide

public static NumpyArray divide(NumpyArray a1,
                                NumpyArray a2)

Divides two numpy arrays.

Parameters:

a1 - Left-hand side of the expression.

a2 - Right-hand side of the expression.

Returns:

The multiplication result.

divide

public static NumpyArray<Double> divide(NumpyArray<Double> array,
                                        double factor)

Divides a numpy array by a double value. The operation is element-wise.

Parameters:

array - The input array to be divided.

factor - The value to be divided by.

Returns:

A numpy array of the calculation result.

divide

public static NumpyArray<Float> divide(NumpyArray<Float> array,
                                       float factor)

Divides a numpy array by a float value. The operation is element-wise.

Parameters:

array - The input array to be divided.

factor - The value to be divided by.

Returns:

A numpy array of the calculation result.

atLeast2D

public static NumpyArray<Double> atLeast2D(double value)

Wraps an atomic double value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static NumpyArray<Float> atLeast2D(float value)

Wraps an atomic float value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static NumpyArray<Long> atLeast2D(long value)

Wraps an atomic long value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static NumpyArray<Integer> atLeast2D(int value)

Wraps an atomic int value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static NumpyArray<Short> atLeast2D(short value)

Wraps an atomic short value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static NumpyArray<Byte> atLeast2D(byte value)

Wraps an atomic byte value into a 2 dimensional array.

Parameters:

value - The value to be wrapped into an array.

Returns:

A two dimensional array that wraps the given value.

atLeast2D

public static <Type> NumpyArray<Type> atLeast2D(NumpyArray<Type> array)

Wraps a numpy array into a 2 dimensional array if the number dimensions is less than 2.

Parameters:

array - The array to be wrapped into a 2 dimensional array.

Returns:

A two dimensional array that wraps the given value.

arrayMax

public static NumpyArray<Double> arrayMax(NumpyArray<Double> array,
                                          int axis,
                                          boolean keepDimensions)

Returns the maximum values along an axis. See: https://numpy.org/doc/stable/reference/generated/numpy.amax.html

Parameters:

array - The input multidimensional array.

axis - The axis which the amax should reduce to.

keepDimensions - A flag to specify whether to keep the reduced dimension in the output.

Returns:

Array of maximum into the array. It has the same shape as a.shape with the dimension along axis removed.

squeeze

public static NumpyArray squeeze(NumpyArray array)

Remove axes of length one from the array.

Parameters:

array - The array to squeeze.

Returns:

An array without any dimension of length 1.

clip

public static NumpyArray<Double> clip(NumpyArray<Double> array,
                                      double min,
                                      double max)

Clip (limit) the values in an array.

Given an interval, values outside the interval are clipped to the interval edges. For example, if an interval of [0, 1] is specified, values smaller than 0 become 0, and values larger than 1 become 1.

Equivalent to but faster than np.minimum(a_max, np.maximum(a, a_min)).

Parameters:

array - Array containing elements to clip.

min - The minimum value to clip.

max - The maximum value to clip.

Returns:

An array with the elements of array, but where values less than min are replaced with min, and those greater than max with max.

abs

public static NumpyArray abs(NumpyArray<Double> array)

Calculate the absolute value element-wise.

Parameters:

array - Input array.

Returns:

An ndarray containing the absolute value of each element in x.

sqrt

public static NumpyArray<Double> sqrt(NumpyArray array)

Return the non-negative square-root of an array, element-wise.

Parameters:

array - The values whose square-roots are required.

Returns:

An array of the same shape as x, containing the positive square-root of each element in x.