Class NDArray

Namespace: NumSharp

Assembly: NumSharp.dll

Container protocol implementation for NDArray. Provides Python-compatible container protocol methods: contains, hash, len, iter, getitem, setitem

[SuppressMessage("ReSharper", "ParameterHidesMember")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
[SuppressMessage("ReSharper", "CoVariantArrayConversion")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public class NDArray : IIndex, ICloneable, IEnumerable

Inheritance: object

NDArray

Implements: IIndex

ICloneable

IEnumerable

Derived: NDArray<TDType>

Inherited Members: object.Equals(object, object)

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Extension Methods: LinqExtensions.Yield<T>(T)

NDIteratorExtensions.AsIterator(NDArray, bool)

NDIteratorExtensions.AsIterator<T>(NDArray, bool)

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html

Constructors

NDArray(IArraySlice, Shape, char)

Constructor which takes .NET array dtype and shape is determined from array

public NDArray(IArraySlice values, Shape shape = default, char order = 'C')

Parameters

values IArraySlice
shape Shape
order char

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(UnmanagedStorage)

Creates a new NDArray with this storage.

public NDArray(UnmanagedStorage storage)

Parameters

storage UnmanagedStorage

NDArray(UnmanagedStorage, Shape)

Creates a new NDArray with this storage.

protected NDArray(UnmanagedStorage storage, Shape shape)

Parameters

storage UnmanagedStorage
shape Shape: The shape to set for this NDArray, does not perform checks.

Remarks

Doesn't copy. Does not perform checks for shape.

NDArray(UnmanagedStorage, ref Shape)

Creates a new NDArray with this storage.

protected NDArray(UnmanagedStorage storage, ref Shape shape)

Parameters

storage UnmanagedStorage
shape Shape: The shape to set for this NDArray, does not perform checks.

Remarks

Doesn't copy. Does not perform checks for shape.

NDArray(NPTypeCode)

Constructor for init data type internal storage is 1D with 1 element

public NDArray(NPTypeCode typeCode)

Parameters

typeCode NPTypeCode: Data type of elements

Remarks

This constructor does not call allocation/>

NDArray(NPTypeCode, Shape)

Constructor which initialize elements with 0 type and shape are given.

public NDArray(NPTypeCode dtype, Shape shape)

Parameters

dtype NPTypeCode: internal data type
shape Shape: Shape of NDArray

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(NPTypeCode, Shape, bool)

Constructor which initialize elements with 0 type and shape are given.

public NDArray(NPTypeCode dtype, Shape shape, bool fillZeros)

Parameters

dtype NPTypeCode: internal data type
shape Shape: Shape of NDArray
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(NPTypeCode, TensorEngine)

Constructor for init data type internal storage is 1D with 1 element

protected NDArray(NPTypeCode typeCode, TensorEngine engine)

Parameters

typeCode NPTypeCode: Data type of elements
engine TensorEngine: The engine of this NDArray

Remarks

This constructor does not call allocation/>

NDArray(NPTypeCode, int)

Constructor which initialize elements with length of size

public NDArray(NPTypeCode dtype, int size)

Parameters

dtype NPTypeCode: Internal data type
size int: The size as a single dimension shape

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(NPTypeCode, int, bool)

Constructor which initialize elements with length of size

public NDArray(NPTypeCode dtype, int size, bool fillZeros)

Parameters

dtype NPTypeCode: Internal data type
size int: The size as a single dimension shape
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(NPTypeCode, long)

Constructor which initialize elements with length of size

public NDArray(NPTypeCode dtype, long size)

Parameters

dtype NPTypeCode: Internal data type
size long: The size as a single dimension shape (long for large arrays)

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(NPTypeCode, long, bool)

Constructor which initialize elements with length of size

public NDArray(NPTypeCode dtype, long size, bool fillZeros)

Parameters

dtype NPTypeCode: Internal data type
size long: The size as a single dimension shape (long for large arrays)
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Array, Shape, char)

Constructor which takes .NET array dtype and shape is determined from array

public NDArray(Array values, Shape shape = default, char order = 'C')

Parameters

values Array
shape Shape
order char

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type)

Constructor for init data type internal storage is 1D with 1 element

public NDArray(Type dtype)

Parameters

dtype Type: Data type of elements

Remarks

This constructor does not call allocation/>

NDArray(Type, Shape)

Constructor which initialize elements with 0 type and shape are given.

public NDArray(Type dtype, Shape shape)

Parameters

dtype Type: internal data type
shape Shape: Shape of NDArray

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, Shape, bool)

Constructor which initialize elements with 0 type and shape are given.

public NDArray(Type dtype, Shape shape, bool fillZeros)

Parameters

dtype Type: internal data type
shape Shape: Shape of NDArray
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, Shape, char)

Constructor which initialize elements with 0 type, shape, and order are given.

public NDArray(Type dtype, Shape shape, char order)

Parameters

dtype Type: internal data type
shape Shape: Shape of NDArray
order char: Memory order. Note: Only C-order is supported, F-order parameter is accepted but ignored.

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, TensorEngine)

Constructor for init data type internal storage is 1D with 1 element

protected NDArray(Type dtype, TensorEngine engine)

Parameters

dtype Type: Data type of elements
engine TensorEngine: The engine of this NDArray

Remarks

This constructor does not call allocation/>

NDArray(Type, int)

Constructor which initialize elements with length of size

public NDArray(Type dtype, int size)

Parameters

dtype Type: Internal data type
size int: The size as a single dimension shape

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, int, bool)

Constructor which initialize elements with length of size

public NDArray(Type dtype, int size, bool fillZeros)

Parameters

dtype Type: Internal data type
size int: The size as a single dimension shape
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, long)

Constructor which initialize elements with length of size (long for >2GB arrays)

public NDArray(Type dtype, long size)

Parameters

dtype Type: Internal data type
size long: The size as a single dimension shape

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

NDArray(Type, long, bool)

Constructor which initialize elements with length of size (long for >2GB arrays)

public NDArray(Type dtype, long size, bool fillZeros)

Parameters

dtype Type: Internal data type
size long: The size as a single dimension shape
fillZeros bool: Should set the values of the new allocation to default(dtype)? otherwise - old memory noise

Remarks

This constructor calls IStorage.Allocate(NumSharp.Shape,System.Type)

Fields

Storage

The internal storage that stores data for this NDArray.

protected UnmanagedStorage Storage

Field Value

UnmanagedStorage

tensorEngine

protected TensorEngine tensorEngine

Field Value

TensorEngine

Properties

Address

Gets the address that this NDArray starts from.

protected void* Address { get; }

Property Value

void*

Array

Get: Gets internal storage array by calling IStorage.GetData
Set: Replace internal storage by calling IStorage.ReplaceData(System.Array)

protected IArraySlice Array { get; }

Property Value

IArraySlice

Remarks

Setting does not replace internal storage array.

this[NDArray<bool>]

Used to perform selection based on a boolean mask.

[SuppressMessage("ReSharper", "CoVariantArrayConversion")]
public NDArray this[NDArray<bool> mask] { get; set; }

Exceptions

IndexOutOfRangeException: When one of the indices exceeds limits.
ArgumentException: indices must be of Int type (byte, u/short, u/int, u/long).

this[NDArray<int>[]]

Used to perform selection based on a selection indices.

public NDArray this[params NDArray<int>[] selection] { get; set; }

Parameters

selection NDArray<int>[]

Property Value

NDArray

Remarks

https://numpy.org/doc/stable/user/basics.indexing.html

Exceptions

IndexOutOfRangeException: When one of the indices exceeds limits.
ArgumentException: indices must be of Int type (byte, u/short, u/int, u/long).

this[Slice[]]

Slice the array with Python slice notation like this: ":, 2:7:1, ..., np.newaxis"

public NDArray this[params Slice[] slice] { get; set; }

Parameters

slice Slice[]: A string containing slice notations for every dimension, delimited by comma

Property Value

NDArray: A sliced view

this[long*, int]

Used to perform selection based on given indices.

public NDArray this[long* dims, int ndims] { get; set; }

Parameters

dims long*: The pointer to the dimensions
ndims int: The count of longs in dims

Property Value

NDArray

this[object[]]

Perform slicing, index extraction, masking and indexing all at the same time with mixed index objects

public NDArray this[params object[] indicesObjects] { get; set; }

Parameters

indicesObjects object[]

Property Value

NDArray

this[string]

Slice the array with Python slice notation like this: ":, 2:7:1, ..., np.newaxis"

public NDArray this[string slice] { get; set; }

Parameters

slice string: A string containing slice notations for every dimension, delimited by comma

Property Value

NDArray: A sliced view

Shape

The shape representing this NDArray.

public Shape Shape { get; set; }

Property Value

Shape

T

The transposed array.
Same as self.transpose().

public NDArray T { get; }

Property Value

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.T.html

TensorEngine

The tensor engine that handles this NDArray.

public TensorEngine TensorEngine { get; set; }

Property Value

TensorEngine

Unsafe

Provides an interface for unsafe methods in NDArray.

public NDArray._Unsafe Unsafe { get; }

Property Value

NDArray._Unsafe

base

Gets the array owning the memory, or null if this array owns its data.

public NDArray? @base { get; }

Property Value

NDArray: An NDArray wrapping the base storage for views, or null for arrays that own their data (e.g., created via np.arange, np.zeros, or copy()).

Remarks

NumPy Compatibility: This property mirrors NumPy's ndarray.base attribute. All views chain to the ultimate owner (not intermediate views).

Example:

var a = np.arange(10);    // a.@base == null (owns data)
var b = a["2:5"];         // b.@base.Storage == a.Storage (view)
var c = b["1:2"];         // c.@base.Storage == a.Storage (chains to original!)
var d = a.copy();         // d.@base == null (copy owns data)
var e = a.reshape(2, 5);  // e.@base.Storage == a.Storage (view)

View Detection: Use arr.@base != null or arr.Storage.IsView to detect if an array is a view. Note that arr.@base != null may trigger NDArray's operator overloading for element-wise comparison. Prefer arr.Storage.IsView for simple boolean checks.

Semantic Difference from NumPy: In NumPy, c.base is a returns True (object identity). In NumSharp, c.@base creates a new wrapper each call, so ReferenceEquals(c.@base, a) is false. However, the underlying storage is the same: c.@base.Storage == a.Storage is true.

Memory Safety: The underlying memory is kept alive by the shared Disposer in the MemoryBlock, not by this property. Views remain valid even if the original array reference is garbage collected.

See Also: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.base.html

BaseStorage

IsView

dtype

The dtype of this array.

public Type dtype { get; }

Property Value

Type

dtypesize

public int dtypesize { get; }

Property Value

int

flat

A 1-D iterator over the array.

public NDArray flat { get; }

Property Value

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flat.html

ndim

Dimension count

public int ndim { get; }

Property Value

int

order

public char order { get; }

Property Value

char

shape

Data length of every dimension

public long[] shape { get; set; }

Property Value

long[]

size

Total of elements

public long size { get; }

Property Value

long

strides

public long[] strides { get; }

Property Value

long[]

typecode

The NPTypeCode of this array.

public NPTypeCode typecode { get; }

Property Value

NPTypeCode

Methods

AsGeneric<T>()

Tries to cast to NDArray<TDType>, otherwise creates an alias without reallocating data.

public NDArray<T> AsGeneric<T>() where T : unmanaged

Returns

NDArray<T>: This NDArray as a generic version.

Type Parameters

T: The type of the generic

Exceptions

InvalidOperationException: When T != dtype

AsOrMakeGeneric<T>()

Tries to cast to NDArray<TDType>, otherwise calls NDArray<T>.astype.

public NDArray<T> AsOrMakeGeneric<T>() where T : unmanaged

Returns

NDArray<T>: This NDArray as a generic version.

Type Parameters

T: The type of the generic

Exceptions

InvalidOperationException: When T != dtype

AsString(NDArray)

Converts the entire NDArray to a string.

public static string AsString(NDArray arr)

Parameters

arr NDArray

Returns

string

Remarks

Performs a copy due to String .net-framework limitations.

AsStringArray(NDArray)

Convert to String[] from NDArray

public static string[] AsStringArray(NDArray arr)

Parameters

arr NDArray

Returns

string[]

Clone()

Clone the whole NDArray internal storage is also cloned into 2nd memory area

public NDArray Clone()

Returns

NDArray: Cloned NDArray

CloneData()

public IArraySlice CloneData()

Returns

IArraySlice

CloneData<T>()

public ArraySlice<T> CloneData<T>() where T : unmanaged

Returns

ArraySlice<T>

Type Parameters

T

Contains(object)

Returns true if value is found in the array (linear search). Equivalent to NumPy's value in arr.

public bool Contains(object value)

Parameters

value object: Value to search for.

Returns

bool: True if value exists in the array.

Examples

var arr = np.array(new[] { 1, 2, 3, 4, 5 });
arr.Contains(3);  // true
arr.Contains(10); // false

Remarks

This is a linear O(n) search. For sorted arrays, consider using np.searchsorted. NaN handling: NaN == NaN is false in IEEE 754, so Contains(float.NaN) returns false for arrays containing NaN. Use np.any(np.isnan(arr)) to check for NaN.

CopyTo(IMemoryBlock)

Copies the entire contents of this storage to given address (using Count).

public void CopyTo(IMemoryBlock slice)

Parameters

slice IMemoryBlock: The slice to copy to.

CopyTo(nint)

Copies the entire contents of this storage to given address.

public void CopyTo(nint ptr)

Parameters

ptr nint

CopyTo(void*)

Copies the entire contents of this storage to given address (using Count).

public void CopyTo(void* address)

Parameters

address void*: The address to copy to.

CopyTo<T>(IMemoryBlock<T>)

Copies the entire contents of this storage to given address (using Count).

public void CopyTo<T>(IMemoryBlock<T> block) where T : unmanaged

Parameters

block IMemoryBlock<T>: The slice to copy to.

Type Parameters

T

CopyTo<T>(T*)

Copies the entire contents of this storage to given address.

public void CopyTo<T>(T* address) where T : unmanaged

Parameters

address T*: The address to copy to.

Type Parameters

T

CopyTo<T>(T[])

Copies the entire contents of this storage to given array.

public void CopyTo<T>(T[] array) where T : unmanaged

Parameters

array T[]: The array to copy to.

Type Parameters

T

Data<T>()

Shortcut for access internal elements

public ArraySlice<T> Data<T>() where T : unmanaged

Returns

ArraySlice<T>

Type Parameters

T

Equals(object)

Determines if NDArray data is same

public override bool Equals(object obj)

Parameters

obj object: NDArray to compare

Returns

bool: if reference is same

ExpandEllipsis(object[], int)

protected static IEnumerable<object> ExpandEllipsis(object[] ndarrays, int ndim)

Parameters

ndarrays object[]
ndim int

Returns

IEnumerable<object>

FetchIndices(NDArray, NDArray[], NDArray, bool)

protected static NDArray FetchIndices(NDArray src, NDArray[] indices, NDArray @out, bool extraDim)

Parameters

src NDArray
indices NDArray[]
out NDArray
extraDim bool

Returns

NDArray

FetchIndicesNDNonLinear<T>(NDArray<T>, NDArray[], int, long[], long[], NDArray)

Accepts collapsed

[SuppressMessage("ReSharper", "SuggestVarOrType_Elsewhere")]
protected static NDArray<T> FetchIndicesNDNonLinear<T>(NDArray<T> source, NDArray[] indices, int ndsCount, long[] retShape, long[] subShape, NDArray @out) where T : unmanaged

Parameters

source NDArray<T>
indices NDArray[]
ndsCount int
retShape long[]
subShape long[]
out NDArray

Returns

NDArray<T>

Type Parameters

T

FetchIndicesND<T>(NDArray<T>, NDArray<long>, NDArray[], int, long[], long[], NDArray)

Accepts collapsed

protected static NDArray<T> FetchIndicesND<T>(NDArray<T> src, NDArray<long> offsets, NDArray[] indices, int ndsCount, long[] retShape, long[] subShape, NDArray @out) where T : unmanaged

Parameters

src NDArray<T>
offsets NDArray<long>
indices NDArray[]
ndsCount int
retShape long[]
subShape long[]
out NDArray

Returns

NDArray<T>

Type Parameters

T

FetchIndices<T>(NDArray<T>, NDArray[], NDArray, bool)

protected static NDArray<T> FetchIndices<T>(NDArray<T> source, NDArray[] indices, NDArray @out, bool extraDim) where T : unmanaged

Parameters

source NDArray<T>
indices NDArray[]
out NDArray
extraDim bool

Returns

NDArray<T>

Type Parameters

T

FromMultiDimArray<T>(Array, bool)

Creates an NDArray out of given array of type T

public static NDArray FromMultiDimArray<T>(Array ndarray, bool copy = true) where T : unmanaged

Parameters

ndarray Array
copy bool: true for making

Returns

NDArray

Type Parameters

T

FromString(string)

Converts a string to a vector ndarray of bytes.

public static NDArray FromString(string str)

Parameters

str string

Returns

NDArray

GetAtIndex(long)

Retrieves value of

public object GetAtIndex(long index)

Parameters

index long

Returns

object

GetAtIndex<T>(long)

Retrieves value of

public T GetAtIndex<T>(long index) where T : unmanaged

Parameters

index long

Returns

T

Type Parameters

T

GetBoolean(int[])

Retrieves value of type bool.

public bool GetBoolean(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

bool

Exceptions

NullReferenceException: When DType is not bool

GetBoolean(params long[])

public bool GetBoolean(params long[] indices)

Parameters

indices long[]

Returns

bool

GetByte(int[])

Retrieves value of type byte.

public byte GetByte(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

byte

Exceptions

NullReferenceException: When DType is not byte

GetByte(params long[])

public byte GetByte(params long[] indices)

Parameters

indices long[]

Returns

byte

GetChar(int[])

Retrieves value of type char.

public char GetChar(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

char

Exceptions

NullReferenceException: When DType is not char

GetChar(params long[])

public char GetChar(params long[] indices)

Parameters

indices long[]

Returns

char

GetComplex(int[])

public Complex GetComplex(int[] indices)

Parameters

indices int[]

Returns

Complex

GetComplex(params long[])

public Complex GetComplex(params long[] indices)

Parameters

indices long[]

Returns

Complex

GetData()

Get reference to internal data storage

public IArraySlice GetData()

Returns

IArraySlice: reference to internal storage as System.Array

GetData(int[])

Gets a NDArray at given indices.

public NDArray GetData(int[] indices)

Parameters

indices int[]: The coordinates to the wanted value

Returns

NDArray

Remarks

Does not copy, returns a memory slice - this is similar to this[int[]]

GetData(long[])

Gets a NDArray at given indices.

public NDArray GetData(long[] indices)

Parameters

indices long[]: The coordinates to the wanted value

Returns

NDArray

Remarks

Does not copy, returns a memory slice - this is similar to this[long[]]

GetData<T>()

Gets the internal storage and converts it to T if necessary.

public ArraySlice<T> GetData<T>() where T : unmanaged

Returns

ArraySlice<T>: An array of type T

Type Parameters

T: The returned type.

GetDecimal(int[])

Retrieves value of type decimal.

public decimal GetDecimal(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

decimal

Exceptions

NullReferenceException: When DType is not decimal

GetDecimal(params long[])

public decimal GetDecimal(params long[] indices)

Parameters

indices long[]

Returns

decimal

GetDouble(int[])

Retrieves value of type double.

public double GetDouble(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

double

Exceptions

NullReferenceException: When DType is not double

GetDouble(params long[])

public double GetDouble(params long[] indices)

Parameters

indices long[]

Returns

double

GetEnumerator()

Returns an enumerator that iterates along the first axis.

public IEnumerator GetEnumerator()

Returns

IEnumerator

Remarks

NumPy-compatible iteration behavior:

0-D arrays (scalars): throws TypeError
1-D arrays: yields scalar elements
N-D arrays (N > 1): yields (N-1)-D NDArray slices along first axis

GetHalf(int[])

public Half GetHalf(int[] indices)

Parameters

indices int[]

Returns

Half

GetHalf(params long[])

public Half GetHalf(params long[] indices)

Parameters

indices long[]

Returns

Half

GetHashCode()

NDArray is unhashable because it is mutable.

public override int GetHashCode()

Returns

int: Never returns - always throws.

Remarks

NumPy arrays are unhashable because they are mutable. If an array were used as a dictionary key and then modified, the hash would change, breaking the dictionary's invariants.

This matches NumPy behavior:

>>> hash(np.array([1, 2, 3]))
TypeError: unhashable type: 'numpy.ndarray'

Workarounds:

Use arr.tobytes() as a hashable key (immutable snapshot)
Use ReferenceEqualityComparer.Instance for identity-based dictionaries
Convert to tuple: tuple(arr.ToArray())

Exceptions

NotSupportedException: Always thrown.

GetIndices(NDArray, NDArray[])

Used to perform selection based on indices, equivalent to nd[NDArray[]].

public NDArray GetIndices(NDArray @out, NDArray[] indices)

Parameters

out NDArray
indices NDArray[]

Returns

NDArray

Remarks

https://numpy.org/doc/stable/user/basics.indexing.html

Exceptions

IndexOutOfRangeException: When one of the indices exceeds limits.
ArgumentException: indices must be of Int type (byte, u/short, u/int, u/long).

GetIndicesFromSlice(Shape, Slice, int)

Converts a slice to indices for the special case where slices are mixed with NDArrays in this[...]

protected static NDArray<long> GetIndicesFromSlice(Shape shape, Slice slice, int axis)

Parameters

shape Shape
slice Slice
axis int

Returns

NDArray<long>

GetIndicesFromSlice(long[], Slice, int)

Converts a slice to indices for the special case where slices are mixed with NDArrays in this[...]

protected static NDArray<long> GetIndicesFromSlice(long[] shape, Slice slice, int axis)

Parameters

shape long[]
slice Slice
axis int

Returns

NDArray<long>

GetInt16(int[])

Retrieves value of type short.

public short GetInt16(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

short

Exceptions

NullReferenceException: When DType is not short

GetInt16(params long[])

public short GetInt16(params long[] indices)

Parameters

indices long[]

Returns

short

GetInt32(int[])

Retrieves value of type int.

public int GetInt32(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

int

Exceptions

NullReferenceException: When DType is not int

GetInt32(params long[])

public int GetInt32(params long[] indices)

Parameters

indices long[]

Returns

int

GetInt64(int[])

Retrieves value of type long.

public long GetInt64(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

long

Exceptions

NullReferenceException: When DType is not long

GetInt64(params long[])

public long GetInt64(params long[] indices)

Parameters

indices long[]

Returns

long

GetNDArrays(int)

Get all NDArray slices at that specific dimension.

[SuppressMessage("ReSharper", "LoopCanBeConvertedToQuery")]
public NDArray[] GetNDArrays(int axis = 0)

Parameters

axis int: Zero-based dimension index on which axis and forward of it to select data., e.g. dimensions=1, shape is (2,2,3,3), returned shape = 4 times of (3,3)

Returns

NDArray[]

Examples

var nd = np.arange(27).reshape(3,1,3,3);
var ret = nd.GetNDArrays(1);
Assert.IsTrue(ret.All(n=>n.Shape == new Shape(3,3));
Assert.IsTrue(ret.Length == 3);
var nd = np.arange(27).reshape(3,1,3,3);

var ret = nd.GetNDArrays(0);
Assert.IsTrue(ret.All(n=>n.Shape == new Shape(1,3,3));
Assert.IsTrue(ret.Length == 3);

Remarks

Does not perform copy.

GetSByte(int[])

public sbyte GetSByte(int[] indices)

Parameters

indices int[]

Returns

sbyte

GetSByte(params long[])

public sbyte GetSByte(params long[] indices)

Parameters

indices long[]

Returns

sbyte

GetSingle(int[])

Retrieves value of type float.

public float GetSingle(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

float

Exceptions

NullReferenceException: When DType is not float

GetSingle(params long[])

public float GetSingle(params long[] indices)

Parameters

indices long[]

Returns

float

GetString(params long[])

Get a string out of a vector of chars.

public string GetString(params long[] indices)

Parameters

indices long[]

Returns

string

Remarks

Performs a copy due to String .net-framework limitations.

GetStringAt(long)

Get a string out of a vector of chars.

public string GetStringAt(long offset)

Parameters

offset long

Returns

string

Remarks

Performs a copy due to String .net-framework limitations.

GetUInt16(int[])

Retrieves value of type ushort.

public ushort GetUInt16(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

ushort

Exceptions

NullReferenceException: When DType is not ushort

GetUInt16(params long[])

public ushort GetUInt16(params long[] indices)

Parameters

indices long[]

Returns

ushort

GetUInt32(int[])

Retrieves value of type uint.

public uint GetUInt32(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

uint

Exceptions

NullReferenceException: When DType is not uint

GetUInt32(params long[])

public uint GetUInt32(params long[] indices)

Parameters

indices long[]

Returns

uint

GetUInt64(int[])

Retrieves value of type ulong.

public ulong GetUInt64(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

ulong

Exceptions

NullReferenceException: When DType is not ulong

GetUInt64(params long[])

public ulong GetUInt64(params long[] indices)

Parameters

indices long[]

Returns

ulong

GetValue(int[])

Retrieves value of unspecified type (will figure using DType).

public object GetValue(int[] indices)

Parameters

indices int[]: The shape's indices to get.

Returns

object

Exceptions

NullReferenceException: When DType is not object

GetValue(params long[])

Retrieves value of unspecified type (will figure using DType).

public object GetValue(params long[] indices)

Parameters

indices long[]: The shape's indices to get.

Returns

object

Exceptions

NullReferenceException: When DType is not object

GetValue<T>(int[])

Retrieves value of unspecified type (will figure using DType).

public T GetValue<T>(int[] indices) where T : unmanaged

Parameters

indices int[]: The shape's indices to get.

Returns

T

Type Parameters

T

Exceptions

NullReferenceException: When DType is not object

GetValue<T>(params long[])

Get a single value from NDArray as type T.

public T GetValue<T>(params long[] indices) where T : unmanaged

Parameters

indices long[]: The shape's indices to get.

Returns

T

Type Parameters

T

Exceptions

NullReferenceException: When DType is not object

MakeGeneric<T>()

Creates an alias without reallocating data.

public NDArray<T> MakeGeneric<T>() where T : unmanaged

Returns

NDArray<T>: This NDArray as a generic version.

Type Parameters

T: The type of the generic

Exceptions

InvalidOperationException: When T != dtype

Normalize()

Normalizes all entries into the range between 0 and 1

Note: this is not a numpy function.

public void Normalize()

NormalizeIndexArray(NDArray)

Normalizes an index array for fancy indexing. NumPy accepts all integer types (int8/16/32/64, uint8/16/32/64) for indexing. Non-integer types (float, decimal, char, bool) raise IndexError. We keep Int32/Int64 as-is; other integer types are converted to Int64.

protected static NDArray NormalizeIndexArray(NDArray indices)

Parameters

indices NDArray: The index array to normalize.

Returns

NDArray: The normalized index array (Int32 or Int64).

Exceptions

IndexOutOfRangeException: When the index array is not an integer type.

PrepareIndexGetters(Shape, NDArray[])

Generates index getter function based on given indices.

protected static Func<long, long>[] PrepareIndexGetters(Shape srcShape, NDArray[] indices)

Parameters

srcShape Shape: The shape to get indice from
indices NDArray[]: The indices trying to index.

Returns

Func<long, long>[]

ReplaceData(IArraySlice)

Sets values as the internal data source and changes the internal storage data type to values type.

public void ReplaceData(IArraySlice values)

Parameters

values IArraySlice

Remarks

Does not copy values and doesn't change shape.

ReplaceData(IArraySlice, Type)

Sets values as the internal data source and changes the internal storage data type to values type.

public void ReplaceData(IArraySlice values, Type dtype)

Parameters

values IArraySlice
dtype Type

Remarks

Does not copy values and doesn't change shape.

ReplaceData(NDArray)

Sets nd as the internal data storage and changes the internal storage data type to nd type.

public void ReplaceData(NDArray nd)

Parameters

nd NDArray

Remarks

Does not copy values and does change shape and dtype.

ReplaceData(Array)

Sets values as the internal data storage and changes the internal storage data type to values type.

public void ReplaceData(Array values)

Parameters

values Array

Remarks

Does not copy values.

ReplaceData(Array, NPTypeCode)

Set an Array to internal storage, cast it to new dtype and if necessary change dtype

public void ReplaceData(Array values, NPTypeCode typeCode)

Parameters

values Array
typeCode NPTypeCode

Remarks

Does not copy values unless cast is necessary and doesn't change shape.

ReplaceData(Array, Type)

Sets values as the internal data storage and changes the internal storage data type to dtype and casts values if necessary.

public void ReplaceData(Array values, Type dtype)

Parameters

values Array: The values to set as internal data soruce
dtype Type: The type to change this storage to and the type to cast values if necessary.

Remarks

Does not copy values unless cast is necessary.

Scalar(object)

Creates a scalar NDArray of value and dtype.

public static NDArray Scalar(object value)

Parameters

value object: The value of the scalar

Returns

NDArray

Remarks

In case when value is not dtype, Converts.ChangeType(object,System.Type) will be called.

Scalar(object, NPTypeCode)

Creates a scalar NDArray of value and dtype.

public static NDArray Scalar(object value, NPTypeCode typeCode)

Parameters

value object: The value of the scalar
typeCode NPTypeCode: The type code of the scalar.

Returns

NDArray

Remarks

In case when value is not dtype, Converts.ChangeType(object,System.Type) will be called.

Scalar(object, Type)

Creates a scalar NDArray of value and dtype.

public static NDArray Scalar(object value, Type dtype)

Parameters

value object: The value of the scalar
dtype Type: The type of the scalar.

Returns

NDArray

Remarks

In case when value is not dtype, Converts.ChangeType(object,System.Type) will be called.

Scalar<T>(object)

Creates a scalar NDArray of value and dtype.

public static NDArray Scalar<T>(object value) where T : unmanaged

Parameters

value object: The value of the scalar, attempt to convert will be performed

Returns

NDArray

Type Parameters

T

Remarks

In case when value is not dtype, Converts.ChangeType(object,System.Type) will be called.

Scalar<T>(T)

Creates a scalar NDArray of value and dtype.

public static NDArray Scalar<T>(T value) where T : unmanaged

Parameters

value T: The value of the scalar

Returns

NDArray

Type Parameters

T

Remarks

In case when value is not dtype, Converts.ChangeType(object,System.Type) will be called.

SetAtIndex(object, long)

Retrieves value at given linear (offset) index.

public void SetAtIndex(object obj, long index)

Parameters

obj object
index long

SetAtIndex<T>(T, long)

Retrieves value of

public void SetAtIndex<T>(T value, long index) where T : unmanaged

Parameters

value T
index long

Type Parameters

T

SetBoolean(bool, int[])

Sets a bool at specific coordinates.

public void SetBoolean(bool value, int[] indices)

Parameters

value bool: The values to assign
indices int[]: The coordinates to set value at.

SetBoolean(bool, params long[])

Sets a bool at specific coordinates.

public void SetBoolean(bool value, params long[] indices)

Parameters

value bool: The value to assign
indices long[]: The coordinates to set value at.

SetByte(byte, int[])

Sets a byte at specific coordinates.

public void SetByte(byte value, int[] indices)

Parameters

value byte: The values to assign
indices int[]: The coordinates to set value at.

SetByte(byte, params long[])

Sets a byte at specific coordinates.

public void SetByte(byte value, params long[] indices)

Parameters

value byte: The value to assign
indices long[]: The coordinates to set value at.

SetChar(char, int[])

Sets a char at specific coordinates.

public void SetChar(char value, int[] indices)

Parameters

value char: The values to assign
indices int[]: The coordinates to set value at.

SetChar(char, params long[])

Sets a char at specific coordinates.

public void SetChar(char value, params long[] indices)

Parameters

value char: The value to assign
indices long[]: The coordinates to set value at.

SetComplex(Complex, int[])

public void SetComplex(Complex value, int[] indices)

Parameters

value Complex
indices int[]

SetComplex(Complex, params long[])

public void SetComplex(Complex value, params long[] indices)

Parameters

value Complex
indices long[]

SetData(IArraySlice, int[])

Set a IArraySlice at given indices.

public void SetData(IArraySlice value, int[] indices)

Parameters

value IArraySlice: The value to set
indices int[]: The

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetData(IArraySlice, params long[])

Set a IArraySlice at given indices (long version).

public void SetData(IArraySlice value, params long[] indices)

Parameters

value IArraySlice: The value to set
indices long[]: The indices (long version)

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetData(NDArray, int[])

Set a NDArray at given indices.

public void SetData(NDArray value, int[] indices)

Parameters

value NDArray: The value to set
indices int[]: The

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetData(NDArray, params long[])

Set a NDArray at given indices (long version).

public void SetData(NDArray value, params long[] indices)

Parameters

value NDArray: The value to set
indices long[]: The indices (long version)

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetData(object)

public void SetData(object p)

Parameters

p object

SetData(object, int[])

Set a NDArray, IArraySlice, Array or a scalar value at given indices.

public void SetData(object value, int[] indices)

Parameters

value object: The value to set
indices int[]: The

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetDecimal(decimal, int[])

Sets a decimal at specific coordinates.

public void SetDecimal(decimal value, int[] indices)

Parameters

value decimal: The values to assign
indices int[]: The coordinates to set value at.

SetDecimal(decimal, params long[])

Sets a decimal at specific coordinates.

public void SetDecimal(decimal value, params long[] indices)

Parameters

value decimal: The value to assign
indices long[]: The coordinates to set value at.

SetDouble(double, int[])

Sets a double at specific coordinates.

public void SetDouble(double value, int[] indices)

Parameters

value double: The values to assign
indices int[]: The coordinates to set value at.

SetDouble(double, params long[])

Sets a double at specific coordinates.

public void SetDouble(double value, params long[] indices)

Parameters

value double: The values to assign
indices long[]: The coordinates to set value at.

SetHalf(Half, int[])

public void SetHalf(Half value, int[] indices)

Parameters

value Half
indices int[]

SetHalf(Half, params long[])

public void SetHalf(Half value, params long[] indices)

Parameters

value Half
indices long[]

SetIndices(NDArray, NDArray[])

Used to perform set a selection based on indices, equivalent to nd[NDArray[]] = values.

public void SetIndices(NDArray values, NDArray[] indices)

Parameters

values NDArray: The values to set via .
indices NDArray[]

Remarks

https://numpy.org/doc/stable/user/basics.indexing.html

Exceptions

IndexOutOfRangeException: When one of the indices exceeds limits.
ArgumentException: indices must be of Int type (byte, u/short, u/int, u/long).
NumSharpException: If this array is not writeable (e.g., broadcast array).

SetIndices(NDArray, NDArray[], NDArray)

protected static void SetIndices(NDArray src, NDArray[] indices, NDArray values)

Parameters

src NDArray
indices NDArray[]
values NDArray

SetIndices(object[], NDArray)

protected void SetIndices(object[] indicesObjects, NDArray values)

Parameters

indicesObjects object[]
values NDArray

SetIndicesNDNonLinear<T>(NDArray<T>, NDArray[], int, long[], long[], NDArray<T>)

Accepts collapsed

[SuppressMessage("ReSharper", "SuggestVarOrType_Elsewhere")]
protected static void SetIndicesNDNonLinear<T>(NDArray<T> source, NDArray[] indices, int ndsCount, long[] retShape, long[] subShape, NDArray<T> values) where T : unmanaged

Parameters

source NDArray<T>
indices NDArray[]
ndsCount int
retShape long[]
subShape long[]
values NDArray<T>

Type Parameters

T

SetIndicesND<T>(NDArray<T>, NDArray<long>, NDArray[], int, long[], long[], NDArray<T>)

Accepts collapsed

protected static void SetIndicesND<T>(NDArray<T> dst, NDArray<long> dstOffsets, NDArray[] dstIndices, int ndsCount, long[] retShape, long[] subShape, NDArray<T> values) where T : unmanaged

Parameters

dst NDArray<T>
dstOffsets NDArray<long>
dstIndices NDArray[]
ndsCount int
retShape long[]
subShape long[]
values NDArray<T>

Type Parameters

T

SetIndices<T>(NDArray<T>, NDArray[], NDArray)

protected static void SetIndices<T>(NDArray<T> source, NDArray[] indices, NDArray values) where T : unmanaged

Parameters

source NDArray<T>
indices NDArray[]
values NDArray

Type Parameters

T

SetInt16(short, int[])

Sets a short at specific coordinates.

public void SetInt16(short value, int[] indices)

Parameters

value short: The values to assign
indices int[]: The coordinates to set value at.

SetInt16(short, params long[])

Sets a short at specific coordinates.

public void SetInt16(short value, params long[] indices)

Parameters

value short: The value to assign
indices long[]: The coordinates to set value at.

SetInt32(int, int[])

Sets a int at specific coordinates.

public void SetInt32(int value, int[] indices)

Parameters

value int: The values to assign
indices int[]: The coordinates to set value at.

SetInt32(int, params long[])

Sets a int at specific coordinates.

public void SetInt32(int value, params long[] indices)

Parameters

value int: The values to assign
indices long[]: The coordinates to set value at (long version).

SetInt64(long, int[])

Sets a long at specific coordinates.

public void SetInt64(long value, int[] indices)

Parameters

value long: The values to assign
indices int[]: The coordinates to set value at.

SetInt64(long, params long[])

Sets a long at specific coordinates.

public void SetInt64(long value, params long[] indices)

Parameters

value long: The values to assign
indices long[]: The coordinates to set value at (long version).

SetSByte(sbyte, int[])

public void SetSByte(sbyte value, int[] indices)

Parameters

value sbyte
indices int[]

SetSByte(sbyte, params long[])

public void SetSByte(sbyte value, params long[] indices)

Parameters

value sbyte
indices long[]

SetSingle(float, int[])

Sets a float at specific coordinates.

public void SetSingle(float value, int[] indices)

Parameters

value float: The values to assign
indices int[]: The coordinates to set value at.

SetSingle(float, params long[])

Sets a float at specific coordinates.

public void SetSingle(float value, params long[] indices)

Parameters

value float: The value to assign
indices long[]: The coordinates to set value at.

SetString(string, params long[])

public void SetString(string value, params long[] indices)

Parameters

value string
indices long[]

SetStringAt(string, long)

public void SetStringAt(string value, long offset)

Parameters

value string
offset long

SetUInt16(ushort, int[])

Sets a ushort at specific coordinates.

public void SetUInt16(ushort value, int[] indices)

Parameters

value ushort: The values to assign
indices int[]: The coordinates to set value at.

SetUInt16(ushort, params long[])

Sets a ushort at specific coordinates.

public void SetUInt16(ushort value, params long[] indices)

Parameters

value ushort: The value to assign
indices long[]: The coordinates to set value at.

SetUInt32(uint, int[])

Sets a uint at specific coordinates.

public void SetUInt32(uint value, int[] indices)

Parameters

value uint: The values to assign
indices int[]: The coordinates to set value at.

SetUInt32(uint, params long[])

Sets a uint at specific coordinates.

public void SetUInt32(uint value, params long[] indices)

Parameters

value uint: The value to assign
indices long[]: The coordinates to set value at.

SetUInt64(ulong, int[])

Sets a ulong at specific coordinates.

public void SetUInt64(ulong value, int[] indices)

Parameters

value ulong: The values to assign
indices int[]: The coordinates to set value at.

SetUInt64(ulong, params long[])

Sets a ulong at specific coordinates.

public void SetUInt64(ulong value, params long[] indices)

Parameters

value ulong: The value to assign
indices long[]: The coordinates to set value at.

SetValue(object, int[])

Set a single value at given indices.

public void SetValue(object value, int[] indices)

Parameters

value object: The value to set
indices int[]: The

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetValue(object, params long[])

Set a single value at given indices.

public void SetValue(object value, params long[] indices)

Parameters

value object: The value to set
indices long[]: The coordinates (long version).

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetValue<T>(T, int[])

Set a single value at given indices.

public void SetValue<T>(T value, int[] indices) where T : unmanaged

Parameters

value T: The value to set
indices int[]: The

Type Parameters

T

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

SetValue<T>(T, params long[])

Set a single value at given indices.

public void SetValue<T>(T value, params long[] indices) where T : unmanaged

Parameters

value T: The value to set
indices long[]: The coordinates (long version).

Type Parameters

T

Remarks

Does not change internal storage data type.
If value does not match DType, value will be converted.

ToArray<T>()

public T[] ToArray<T>() where T : unmanaged

Returns

T[]

Type Parameters

T

ToByteArray()

public byte[] ToByteArray()

Returns

byte[]

ToJaggedArray<T>()

public Array ToJaggedArray<T>() where T : unmanaged

Returns

Array

Type Parameters

T

ToMuliDimArray<T>()

public Array ToMuliDimArray<T>() where T : unmanaged

Returns

Array

Type Parameters

T

ToString()

Returns a string that represents the current object.

public override string ToString()

Returns

string: A string that represents the current object.

ToString(bool)

public string ToString(bool flat)

Parameters

flat bool

Returns

string

contains(object)

Python-compatible contains method. Equivalent to Contains(object).

public bool __contains__(object value)

Parameters

value object: Value to search for.

Returns

bool: True if value exists in the array.

Remarks

This method exists for Python interoperability and naming consistency. In Python: value in arr calls arr.contains(value)

getitem(int)

Python-compatible getitem method with integer index.

public NDArray __getitem__(int index)

Parameters

index int: Index along the first axis.

Returns

NDArray: Element or slice at the given index.

Remarks

Equivalent to arr[index] in Python. Supports negative indexing (-1 = last element).

getitem(params int[])

Python-compatible getitem method with params indices.

public NDArray __getitem__(params int[] indices)

Parameters

indices int[]: Indices for each dimension.

Returns

NDArray: Element or slice at the given indices.

getitem(long)

Python-compatible getitem method with long index.

public NDArray __getitem__(long index)

Parameters

index long: Index along the first axis.

Returns

NDArray: Element or slice at the given index.

getitem(string)

Python-compatible getitem method with slice string.

public NDArray __getitem__(string slice)

Parameters

slice string: Slice specification (e.g., "1:3", "::-1", "..., 0").

Returns

NDArray: Sliced view of the array.

Remarks

Equivalent to arr[slice] in Python. Examples:

arr.__getitem__(":3")      // First 3 elements
arr.__getitem__("1:-1")    // All but first and last
arr.__getitem__("::-1")    // Reversed
arr.__getitem__("..., 0")  // All rows, first column

hash()

Python-compatible hash method. NDArray is unhashable because it is mutable.

public int __hash__()

Returns

int: Never returns - always throws.

Remarks

This method exists for Python interoperability and naming consistency. In Python: hash(arr) calls arr.hash()

NumPy behavior:

>>> arr = np.array([1, 2, 3])
>>> hash(arr)
TypeError: unhashable type: 'numpy.ndarray'

Exceptions

NotSupportedException: Always thrown.

iter()

Python-compatible iter method. Returns an enumerator over the first axis.

public IEnumerator __iter__()

Returns

IEnumerator: Enumerator yielding NDArray slices along the first axis.

Remarks

This matches NumPy behavior:

>>> for row in np.array([[1, 2], [3, 4]]):
...     print(row)
[1 2]
[3 4]

For 1-D arrays, iterates over scalar elements. For N-D arrays, iterates over (N-1)-D slices.

len()

Python-compatible len method. Returns the length of the first dimension (like Python's len()).

public long __len__()

Returns

long: Length of the first dimension, or 1 for scalars.

Remarks

This matches NumPy behavior:

>>> len(np.array([1, 2, 3]))
3
>>> len(np.array([[1, 2], [3, 4]]))
2  # First dimension
>>> len(np.array(5))
TypeError: len() of unsized object

Note: For scalars (0-d arrays), NumPy raises TypeError. NumSharp returns 1 for consistency with C# conventions. Use size for total element count.

setitem(int, object)

Python-compatible setitem method with integer index.

public void __setitem__(int index, object value)

Parameters

index int: Index along the first axis.
value object: Value to set (scalar or NDArray).

setitem(long, object)

Python-compatible setitem method with long index.

public void __setitem__(long index, object value)

Parameters

index long: Index along the first axis.
value object: Value to set (scalar or NDArray).

setitem(string, object)

Python-compatible setitem method with slice string.

public void __setitem__(string slice, object value)

Parameters

slice string: Slice specification.
value object: Value to set (scalar or NDArray).

amax(int, bool, Type)

Return the maximum of an array or maximum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray amax(int axis, bool keepdims = false, Type dtype = null)

Parameters

axis int: Axis or axes along which to operate.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

amax(Type)

Return the maximum of an array or maximum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray amax(Type dtype = null)

Parameters

dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

amax<T>()

Return the maximum of an array or maximum along an axis.

public T amax<T>() where T : unmanaged

Returns

T: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Type Parameters

T: The expected return type, cast will be performed if necessary.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

amin(int, bool, Type)

Return the minimum of an array or minimum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray amin(int axis, bool keepdims = false, Type dtype = null)

Parameters

axis int: Axis or axes along which to operate.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

amin(Type)

Return the minimum of an array or minimum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray amin(Type dtype = null)

Parameters

dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

amin<T>()

Return the minimum of an array or minimum along an axis.

public T amin<T>() where T : unmanaged

Returns

T: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Type Parameters

T: The expected return type, cast will be performed if necessary.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

argmax()

Returns the index of the maximum value (flattened array).

public long argmax()

Returns

long: The index of the maximal value in the flattened array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.argmax.html

argmax(int, bool)

Returns the indices of the maximum values along an axis.

public NDArray argmax(int axis, bool keepdims = false)

Parameters

axis int: The axis along which to operate. By default, the index is into the flattened array.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one.

Returns

NDArray: Array of indices into the array. It has the same shape as a.shape with the dimension along axis removed (unless keepdims is True).

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.argmax.html

argmin()

Returns the index of the minimum value (flattened array).

public long argmin()

Returns

long: The index of the minimum value in the flattened array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.argmin.html

argmin(int, bool)

Returns the indices of the minimum values along an axis.

public NDArray argmin(int axis, bool keepdims = false)

Parameters

axis int: The axis along which to operate. By default, the index is into the flattened array.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one.

Returns

NDArray: Array of indices into the array. It has the same shape as a.shape with the dimension along axis removed (unless keepdims is True).

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.argmin.html

argsort<T>(int)

Returns the indices that would sort an array.

Perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as a that index data along the given axis in sorted order. Supports arrays with >2B elements using long indexing.

public NDArray argsort<T>(int axis = -1) where T : unmanaged

Parameters

axis int

Returns

NDArray

Type Parameters

T

array_equal(NDArray)

True if two arrays have the same shape and elements, False otherwise.

public bool array_equal(NDArray rhs)

Parameters

rhs NDArray: Input array.

Returns

bool: Returns True if the arrays are equal.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.array_equal.html

astype(NPTypeCode, bool)

Copy of the array, cast to a specified type.

public NDArray astype(NPTypeCode typeCode, bool copy = true)

Parameters

typeCode NPTypeCode
copy bool: By default, astype always returns a newly allocated array. If this is set to false, the input internal array is replaced instead of returning a new NDArray with the casted data.

Returns

NDArray: An NDArray of given dtype.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html

astype(Type, bool)

Copy of the array, cast to a specified type.

[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray astype(Type dtype, bool copy = true)

Parameters

dtype Type: The dtype to cast this array.
copy bool: By default, astype always returns a newly allocated array. If this is set to false, the input internal array is replaced instead of returning a new NDArray with the casted data.

Returns

NDArray: An NDArray of given dtype.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html

convolve(NDArray, string)

Returns the discrete, linear convolution of two one-dimensional sequences.

The convolution operator is often seen in signal processing, where it models the effect of a linear time-invariant system on a signal[1]. In probability theory, the sum of two independent random variables is distributed according to the convolution of their individual distributions.

If v is longer than a, the arrays are swapped before computation.

public NDArray convolve(NDArray v, string mode = "full")

Parameters

v NDArray: The second one-dimensional input array.
mode string: 'full', 'same', or 'valid'. Default is 'full'.

Returns

NDArray: Discrete, linear convolution of a and v.

Remarks

NumPy Reference: https://numpy.org/doc/stable/reference/generated/numpy.convolve.html

The convolution product is only given for points where the signals overlap completely. Values outside the signal boundary have no effect.

copy(char)

Return a copy of the array.

public NDArray copy(char order = 'C')

Parameters

order char

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.copy.html

cumsum(int?, Type)

Return the cumulative sum of the elements along a given axis.

public NDArray cumsum(int? axis = null, Type dtype = null)

Parameters

axis int?: Axis along which the cumulative sum is computed. The default (-1) is to compute the cumsum over the flattened array.
dtype Type: Type of the returned array and of the accumulator in which the elements are summed. If dtype is not specified, it defaults to the dtype of a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used.

Returns

NDArray: A new array holding the result is returned unless out is specified, in which case a reference to out is returned. The result has the same size as a, and the same shape as a if axis is not None or a is a 1-d array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.cumsum.html

delete(IEnumerable)

public NDArray delete(IEnumerable delete)

Parameters

delete IEnumerable

Returns

NDArray

dot(NDArray)

Dot product of two arrays. See remarks.

public NDArray dot(NDArray b)

Parameters

b NDArray: Rhs, Second argument.

Returns

NDArray: Returns the dot product of a and b. If a and b are both scalars or both 1-D arrays then a scalar is returned; otherwise an array is returned. If out is given, then it is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.dot.html
Specifically,
- If both a and b are 1-D arrays, it is inner product of vectors (without complex conjugation).
- If both a and b are 2-D arrays, it is matrix multiplication, but using matmul or a @ b is preferred.
- If either a or b is 0-D(scalar), it is equivalent to multiply and using numpy.multiply(a, b) or a* b is preferred.
- If a is an N-D array and b is a 1-D array, it is a sum product over the last axis of a and b.
- If a is an N-D array and b is an M-D array(where M>=2), it is a sum product over the last axis of a and the second-to-last axis of b:
dot(a, b)[i,j,k,m] = sum(a[i,j,:] * b[k,:,m])

dstack(params NDArray[])

Stack arrays in sequence depth wise (along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of shape(M, N) have been reshaped to(M, N,1) and 1-D arrays of shape(N,) have been reshaped to(1, N,1). Rebuilds arrays divided by dsplit. This function makes most sense for arrays with up to 3 dimensions.For instance, for pixel-data with a height(first axis), width(second axis), and r/g/b channels(third axis). The functions concatenate, stack and block provide more general stacking and concatenation operations.

public NDArray dstack(params NDArray[] tup)

Parameters

tup NDArray[]: The arrays must have the same shape along all but the third axis. 1-D or 2-D arrays must have the same shape.

Returns

NDArray: The array formed by stacking the given arrays, will be at least 3-D.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.dstack.html

flatten(char)

Return a copy of the array collapsed into one dimension.

public NDArray flatten(char order = 'C')

Parameters

order char: The order in which to read the elements. 'C' means row-major (C-style), 'F' means column-major (Fortran-style). NumSharp only supports 'C' order; this parameter is accepted for API compatibility but 'F' is ignored.

Returns

NDArray: A copy of the input array, flattened to one dimension.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flatten.html NumPy: flatten() ALWAYS returns a copy. Use ravel() for a view when possible.

hstack(params NDArray[])

Stack arrays in sequence horizontally (column wise). This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis.Rebuilds arrays divided by hsplit. This function makes most sense for arrays with up to 3 dimensions.For instance, for pixel-data with a height(first axis), width(second axis), and r/g/b channels(third axis). The functions concatenate, stack and block provide more general stacking and concatenation operations.

public NDArray hstack(params NDArray[] tup)

Parameters

tup NDArray[]: The arrays must have the same shape along all but the second axis, except 1-D arrays which can be any length.

Returns

NDArray: The array formed by stacking the given arrays.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.hstack.html

inv()

public NDArray inv()

Returns

NDArray

item()

Copy an element of an array to a standard Python scalar and return it.

public object item()

Returns

object: A copy of the specified element of the array as a suitable Python scalar.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html

When called without arguments, works only for arrays with one element (size 1), which can have any shape (0-d, 1-element 1-d, 1x1 2-d, etc.).

This is the NumPy 2.x replacement for the deprecated np.asscalar().

Exceptions

IncorrectSizeException: If array size is not 1.

item(long)

Copy an element of an array to a standard Python scalar and return it.

public object item(long index)

Parameters

index long: Flat index of element to extract (supports negative indexing).

Returns

object: A copy of the specified element of the array as a suitable Python scalar.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html

item(long, long)

Copy an element of an array to a standard Python scalar and return it.

public object item(long i, long j)

Parameters

i long: Index along first dimension.
j long: Index along second dimension.

Returns

object: A copy of the specified element of the array as a suitable Python scalar.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html

item(long, long, long)

Copy an element of an array to a standard Python scalar and return it.

public object item(long i, long j, long k)

Parameters

i long: Index along first dimension.
j long: Index along second dimension.
k long: Index along third dimension.

Returns

object: A copy of the specified element of the array as a suitable Python scalar.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html

item(params long[])

Copy an element of an array to a standard Python scalar and return it.

public object item(params long[] indices)

Parameters

indices long[]: Indices of element to extract (one per dimension).

Returns

object: A copy of the specified element of the array as a suitable Python scalar.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.item.html

item<T>()

Copy an element of an array to a standard Python scalar and return it.

public T item<T>() where T : unmanaged

Returns

T: A copy of the specified element of the array as a typed scalar.

Type Parameters

T: The type to convert the value to.

Exceptions

IncorrectSizeException: If array size is not 1.

item<T>(long)

Copy an element of an array to a standard Python scalar and return it.

public T item<T>(long index) where T : unmanaged

Parameters

index long: Flat index of element to extract (supports negative indexing).

Returns

T: A copy of the specified element of the array as a typed scalar.

Type Parameters

T: The type to convert the value to.

item<T>(long, long)

Copy an element of an array to a standard Python scalar and return it.

public T item<T>(long i, long j) where T : unmanaged

Parameters

i long: Index along first dimension.
j long: Index along second dimension.

Returns

T: A copy of the specified element of the array as a typed scalar.

Type Parameters

T: The type to convert the value to.

item<T>(long, long, long)

Copy an element of an array to a standard Python scalar and return it.

public T item<T>(long i, long j, long k) where T : unmanaged

Parameters

i long: Index along first dimension.
j long: Index along second dimension.
k long: Index along third dimension.

Returns

T: A copy of the specified element of the array as a typed scalar.

Type Parameters

T: The type to convert the value to.

item<T>(params long[])

Copy an element of an array to a standard Python scalar and return it.

public T item<T>(params long[] indices) where T : unmanaged

Parameters

indices long[]: Indices of element to extract (one per dimension).

Returns

T: A copy of the specified element of the array as a typed scalar.

Type Parameters

T: The type to convert the value to.

itemset(Shape, object)

Insert scalar into an array (scalar is cast to array’s dtype, if possible)

public void itemset(Shape shape, object val)

Parameters

shape Shape
val object

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.put.html

itemset(ref Shape, object)

Insert scalar into an array (scalar is cast to array’s dtype, if possible)

public void itemset(ref Shape shape, object val)

Parameters

shape Shape
val object

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.put.html

itemset(int[], object)

Insert scalar into an array (scalar is cast to array’s dtype, if possible)

public void itemset(int[] shape, object val)

Parameters

shape int[]
val object

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.put.html

itemset<T>(int[], T)

Insert scalar into an array (scalar is cast to array’s dtype, if possible)

public void itemset<T>(int[] shape, T val) where T : unmanaged

Parameters

shape int[]
val T

Type Parameters

T

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.put.html

lstqr(NDArray, double)

Least Square method

Determines NDArray X which reduces least square error of Linear System A * X = B. This NDArray is equal to A.

public NDArray lstqr(NDArray nDArrayB, double rcon = 0.0001)

Parameters

nDArrayB NDArray: Result NDArray B
rcon double

Returns

NDArray: NArray X

matrix_power(int)

public NDArray matrix_power(int power)

Parameters

power int

Returns

NDArray

max(int, bool, Type)

Return the maximum of an array or maximum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray max(int axis, bool keepdims = false, Type dtype = null)

Parameters

axis int: Axis or axes along which to operate.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

max(Type)

Return the maximum of an array or maximum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray max(Type dtype = null)

Parameters

dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

max<T>()

Return the maximum of an array or maximum along an axis.

public T max<T>() where T : unmanaged

Returns

T: Maximum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Type Parameters

T: The expected return type, cast will be performed if necessary.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amax.html

mean()

Compute the arithmetic mean along the specified axis. Returns the average of the array elements. The average is taken over the flattened array by default, otherwise over the specified axis. float64 intermediate and return values are used for integer inputs.

public NDArray mean()

Returns

NDArray: returns a new array containing the mean values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.mean.html

mean(int)

public NDArray mean(int axis)

Parameters

axis int: Axis or axes along which the means are computed. The default is to compute the mean of the flattened array.

Returns

NDArray: returns a new array containing the mean values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.mean.html

mean(int, NPTypeCode, bool)

public NDArray mean(int axis, NPTypeCode type, bool keepdims = false)

Parameters

axis int: Axis or axes along which the means are computed. The default is to compute the mean of the flattened array.
type NPTypeCode: Type to use in computing the mean. For integer inputs, the default is float64; for floating point inputs, it is the same as the input dtype.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the mean method of sub-classes of ndarray, however any non-default value will be.If the sub-class’ method does not implement keepdims any exceptions will be raised.

Returns

NDArray: returns a new array containing the mean values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.mean.html

mean(int, bool)

public NDArray mean(int axis, bool keepdims)

Parameters

axis int: Axis or axes along which the means are computed. The default is to compute the mean of the flattened array.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the mean method of sub-classes of ndarray, however any non-default value will be.If the sub-class’ method does not implement keepdims any exceptions will be raised.

Returns

NDArray: returns a new array containing the mean values, otherwise a reference to the output array is returned.

mean(int, Type, bool)

public NDArray mean(int axis, Type type, bool keepdims = false)

Parameters

axis int: Axis or axes along which the means are computed. The default is to compute the mean of the flattened array.
type Type: Type to use in computing the mean. For integer inputs, the default is float64; for floating point inputs, it is the same as the input dtype.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the mean method of sub-classes of ndarray, however any non-default value will be.If the sub-class’ method does not implement keepdims any exceptions will be raised.

Returns

NDArray: returns a new array containing the mean values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.mean.html

mgrid(NDArray)

nd_grid instance which returns a dense multi-dimensional “meshgrid”. An instance of numpy.lib.index_tricks.nd_grid which returns an dense (or fleshed out) mesh-grid when indexed, so that each returned argument has the same shape. The dimensions and number of the output arrays are equal to the number of indexing dimensions.If the step length is not a complex number, then the stop is not inclusive.

public (NDArray, NDArray) mgrid(NDArray rhs)

Parameters

rhs NDArray

Returns

(NDArray Lhs, NDArray Rhs): mesh-grid ndarrays all of the same dimensions

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.mgrid.html

min(int, bool, Type)

Return the minimum of an array or minimum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray min(int axis, bool keepdims = false, Type dtype = null)

Parameters

axis int: Axis or axes along which to operate.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

min(Type)

Return the minimum of an array or minimum along an axis.

[SuppressMessage("ReSharper", "TooWideLocalVariableScope")]
[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray min(Type dtype = null)

Parameters

dtype Type: the type expected as a return, null will remain the same dtype.

Returns

NDArray: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

min<T>()

Return the minimum of an array or minimum along an axis.

public T min<T>() where T : unmanaged

Returns

T: Minimum of a. If axis is None, the result is a scalar value. If axis is given, the result is an array of dimension a.ndim - 1.

Type Parameters

T: The expected return type, cast will be performed if necessary.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.amin.html

multi_dot(params NDArray[])

public NDArray multi_dot(params NDArray[] np2Multi)

Parameters

np2Multi NDArray[]

Returns

NDArray

negate()

Negates all values by performing: -x

public NDArray negate()

Returns

NDArray

negative()

Numerical negative, element-wise. Returns -x for each element (negates ALL values, not just positive).

public NDArray negative()

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.negative.html

positive()

Numerical positive, element-wise. This is an identity operation - returns +x (a copy of the input). Equivalent to np.array(a, copy=True).

public NDArray positive()

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.positive.html

prod(int?, Type, bool)

Return the product of array elements over a given axis.

public NDArray prod(int? axis = null, Type dtype = null, bool keepdims = false)

Parameters

axis int?: Axis or axes along which a product is performed. The default, axis=None, will calculate the product of all the elements in the input array. If axis is negative it counts from the last to the first axis.
dtype Type: The type of the returned array, as well as of the accumulator in which the elements are multiplied. The dtype of a is used by default unless a has an integer dtype of less precision than the default platform integer. In that case, if a is signed then the platform integer is used while if a is unsigned then an unsigned integer of the same precision as the platform integer is used.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.

Returns

NDArray: An array shaped as a but with the specified axis removed.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.prod.html

qr()

public (NDArray, NDArray) qr()

Returns

(NDArray Lhs, NDArray Rhs)

ravel()

Return a contiguous flattened array. A 1-D array, containing the elements of the input, is returned

public NDArray ravel()

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ravel.html

reshape(Shape)

Gives a new shape to an array without changing its data.

public NDArray reshape(Shape newShape)

Parameters

newShape Shape: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape(ref Shape)

Gives a new shape to an array without changing its data.

public NDArray reshape(ref Shape newShape)

Parameters

newShape Shape: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape(int[])

Gives a new shape to an array without changing its data.

[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray reshape(int[] shape)

Parameters

shape int[]: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape(params long[])

Gives a new shape to an array without changing its data.

[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray reshape(params long[] shape)

Parameters

shape long[]: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html

reshape_unsafe(Shape)

Gives a new shape to an array without changing its data.

public NDArray reshape_unsafe(Shape newshape)

Parameters

newshape Shape: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape_unsafe(ref Shape)

Gives a new shape to an array without changing its data.

public NDArray reshape_unsafe(ref Shape newshape)

Parameters

newshape Shape: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape_unsafe(int[])

Gives a new shape to an array without changing its data.

[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray reshape_unsafe(int[] shape)

Parameters

shape int[]: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.reshape.html

reshape_unsafe(params long[])

Gives a new shape to an array without changing its data.

[SuppressMessage("ReSharper", "ParameterHidesMember")]
public NDArray reshape_unsafe(params long[] shape)

Parameters

shape long[]: The new shape should be compatible with the original shape. If an integer, then the result will be a 1-D array of that length. One shape dimension can be -1. In this case, the value is inferred from the length of the array and remaining dimensions.

Returns

NDArray: This will be a new view object if possible; otherwise, it will be a copy. Note there is no guarantee of the memory layout (C- or Fortran- contiguous) of the returned array.

Remarks

https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html

roll(int)

Roll array elements along a given axis.

Elements that roll beyond the last position are re-introduced at the first. The array is flattened before shifting, after which the original shape is restored.

public NDArray roll(int shift)

Parameters

shift int: The number of places by which elements are shifted.

Returns

NDArray: Output array, with the same shape as the input.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.roll.html

roll(int, int)

Roll array elements along a given axis.

Elements that roll beyond the last position are re-introduced at the first.

public NDArray roll(int shift, int axis)

Parameters

shift int: The number of places by which elements are shifted.
axis int: Axis along which elements are shifted.

Returns

NDArray: Output array, with the same shape as the input.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.roll.html

roll(long)

Roll array elements along a given axis.

Elements that roll beyond the last position are re-introduced at the first. The array is flattened before shifting, after which the original shape is restored.

public NDArray roll(long shift)

Parameters

shift long: The number of places by which elements are shifted.

Returns

NDArray: Output array, with the same shape as the input.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.roll.html

roll(long, int)

Roll array elements along a given axis.

Elements that roll beyond the last position are re-introduced at the first.

public NDArray roll(long shift, int axis)

Parameters

shift long: The number of places by which elements are shifted.
axis int: Axis along which elements are shifted.

Returns

NDArray: Output array, with the same shape as the input.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.roll.html

std(bool, int?, NPTypeCode?)

Compute the standard deviation along the specified axis. Returns the standard deviation, a measure of the spread of a distribution, of the array elements. The standard deviation is computed for the flattened array by default, otherwise over the specified axis.

public NDArray std(bool keepdims = false, int? ddof = null, NPTypeCode? dtype = null)

Parameters

keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
ddof int?: Means Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is zero.
dtype NPTypeCode?

Returns

NDArray: returns a new array containing the std values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.std.html

std(int, bool, int?, NPTypeCode?)

public NDArray std(int axis, bool keepdims = false, int? ddof = null, NPTypeCode? dtype = null)

Parameters

axis int: Axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
ddof int?: Means Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is zero.
dtype NPTypeCode?

Returns

NDArray: returns a new array containing the std values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.std.html

sum()

Sum of array elements into a scalar.

public NDArray sum()

Returns

NDArray: An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.sum.html

sum(int)

Sum of array elements over a given axis.

public NDArray sum(int axis)

Parameters

axis int: Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is negative it counts from the last to the first axis.

Returns

NDArray: An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.sum.html

sum(int, bool, NPTypeCode?)

Sum of array elements over a given axis.

public NDArray sum(int axis, bool keepdims, NPTypeCode? typeCode = null)

Parameters

axis int: Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is negative it counts from the last to the first axis.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the sum method of sub-classes of ndarray, however any non-default value will be.If the sub-class’ method does not implement keepdims any exceptions will be raised.
typeCode NPTypeCode?: The type of the returned array and of the accumulator in which the elements are summed. The dtype of a is used by default unless a has an integer dtype of less precision than the default platform integer. In that case, if a is signed then the platform integer is used while if a is unsigned then an unsigned integer of the same precision as the platform integer is used.

Returns

NDArray: An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.sum.html

sum(int, bool, Type)

Sum of array elements over a given axis.

public NDArray sum(int axis, bool keepdims, Type dtype)

Parameters

axis int: Axis or axes along which a sum is performed. The default, axis=None, will sum all of the elements of the input array. If axis is negative it counts from the last to the first axis.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array. If the default value is passed, then keepdims will not be passed through to the sum method of sub-classes of ndarray, however any non-default value will be.If the sub-class’ method does not implement keepdims any exceptions will be raised.
dtype Type: The type of the returned array and of the accumulator in which the elements are summed. The dtype of a is used by default unless a has an integer dtype of less precision than the default platform integer. In that case, if a is signed then the platform integer is used while if a is unsigned then an unsigned integer of the same precision as the platform integer is used.

Returns

NDArray: An array with the same shape as a, with the specified axis removed. If a is a 0-d array, or if axis is None, a scalar is returned. If an output array is specified, a reference to out is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.sum.html

svd()

public (NDArray, NDArray, NDArray) svd()

Returns

(NDArray, NDArray, NDArray)

swapaxes(int, int)

Interchange two axes of an array.

public NDArray swapaxes(int axis1, int axis2)

Parameters

axis1 int: First axis.
axis2 int: Second axis.

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.swapaxes.html

tofile(string)

Write array to a file as text or binary (default).
Data is always written in ‘C’ order, independent of the order of a.
The data produced by this method can be recovered using the function fromfile().

public void tofile(string fid)

Parameters

fid string: An open file object, or a string containing a filename.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tofile.html

tolist()

Return the array as an (possibly nested) list.

public object tolist()

Returns

object

The possibly nested list of array elements.

For 0-d arrays (scalars): returns the scalar value itself
For 1-d arrays: returns List<object> of elements
For n-d arrays: returns nested List<object> structures

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html

Copy of the array data as a (nested) Python list. Data items are converted to the nearest compatible builtin Python type, via the item function.

If a.ndim is 0, then since the depth of the nested list is 0, it will not be a list at all, but a simple Python scalar.

transpose(int[])

Permute the dimensions of an array.

public NDArray transpose(int[] premute = null)

Parameters

premute int[]: By default, reverse the dimensions, otherwise permute the axes according to the values given.

Returns

NDArray: a with its axes permuted. A view is returned whenever possible.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.transpose.html

unique()

public NDArray unique()

Returns

NDArray

uniqueComplex()

B9: Dedicated unique path for Complex, since System.Numerics.Complex does not implement IComparable<Complex> (prevents reuse of the generic unique<T>). Dedup uses EqualityComparer<Complex>.Default (component-wise value equality, NaN==NaN) then sorts using NumPy lex semantics with NaN at end.

protected NDArray uniqueComplex()

Returns

NDArray

unique<T>()

protected NDArray unique<T>() where T : unmanaged, IComparable<T>

Returns

NDArray

Type Parameters

T

var(bool, int?, NPTypeCode?)

public NDArray var(bool keepdims = false, int? ddof = null, NPTypeCode? dtype = null)

Parameters

keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
ddof int?: Means Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is zero.
dtype NPTypeCode?

Returns

NDArray: returns a new array containing the std values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.std.html

var(int, bool, int?, NPTypeCode?)

public NDArray var(int axis, bool keepdims = false, int? ddof = null, NPTypeCode? dtype = null)

Parameters

axis int: Axis or axes along which the standard deviation is computed. The default is to compute the standard deviation of the flattened array.
keepdims bool: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input array.
ddof int?: Means Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements. By default ddof is zero.
dtype NPTypeCode?

Returns

NDArray: returns a new array containing the std values, otherwise a reference to the output array is returned.

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.std.html

view(Type)

New view of array with the same data.

public NDArray view(Type dtype = null)

Parameters

dtype Type: Data-type descriptor of the returned view, e.g., float32 or int16. The default, None, results in the view having the same data-type as a. This argument can also be specified as an ndarray sub-class, which then specifies the type of the returned object (this is equivalent to setting the type parameter).

Returns

NDArray

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.view.html

view<T>()

New view of array with the same data.

public NDArray<T> view<T>() where T : unmanaged

Returns

NDArray<T>

Type Parameters

T

Remarks

https://numpy.org/doc/stable/reference/generated/numpy.ndarray.view.html

vstack(params NDArray[])

Stack arrays in sequence vertically (row wise).
This is equivalent to concatenation along the first axis after 1-D arrays of shape(N,) have been reshaped to(1, N). Rebuilds arrays divided by vsplit.

public NDArray vstack(params NDArray[] tup)

Parameters

tup NDArray[]: The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length.

Returns

NDArray: https://numpy.org/doc/stable/reference/generated/numpy.vstack.html

Operators

operator +(NDArray, NDArray)

public static NDArray operator +(NDArray x, NDArray y)

Parameters

x NDArray
y NDArray

Returns

NDArray

operator +(NDArray, object)

public static NDArray operator +(NDArray left, object right)

Parameters

left NDArray
right object

Returns

NDArray

operator +(object, NDArray)

public static NDArray operator +(object left, NDArray right)

Parameters

left object
right NDArray

Returns

NDArray

operator &(NDArray, NDArray)

Element-wise bitwise AND operation. For boolean arrays: logical AND. For integer arrays: bitwise AND. Supports broadcasting.

public static NDArray operator &(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray

operator &(NDArray, object)

Element-wise bitwise AND with any scalar or array-like.

public static NDArray operator &(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray

operator &(object, NDArray)

Element-wise bitwise AND with any scalar or array-like on left.

public static NDArray operator &(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray

operator |(NDArray, NDArray)

Element-wise bitwise OR operation. For boolean arrays: logical OR. For integer arrays: bitwise OR. Supports broadcasting.

public static NDArray operator |(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray

operator |(NDArray, object)

Element-wise bitwise OR with any scalar or array-like.

public static NDArray operator |(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray

operator |(object, NDArray)

Element-wise bitwise OR with any scalar or array-like on left.

public static NDArray operator |(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray

operator /(NDArray, NDArray)

public static NDArray operator /(NDArray x, NDArray y)

Parameters

x NDArray
y NDArray

Returns

NDArray

operator /(NDArray, object)

public static NDArray operator /(NDArray left, object right)

Parameters

left NDArray
right object

Returns

NDArray

operator /(object, NDArray)

public static NDArray operator /(object left, NDArray right)

Parameters

left object
right NDArray

Returns

NDArray

operator ==(NDArray, NDArray)

Element-wise equal comparison (==). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator ==(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator ==(NDArray, object)

Element-wise equal comparison with scalar (==).

public static NDArray<bool> operator ==(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator ==(object, NDArray)

Element-wise equal comparison with scalar on left (==).

public static NDArray<bool> operator ==(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

operator ^(NDArray, NDArray)

Element-wise bitwise XOR operation. For boolean arrays: logical XOR. For integer arrays: bitwise XOR. Supports broadcasting.

public static NDArray operator ^(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray

operator ^(NDArray, object)

Element-wise bitwise XOR with any scalar or array-like.

public static NDArray operator ^(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray

operator ^(object, NDArray)

Element-wise bitwise XOR with any scalar or array-like on left.

public static NDArray operator ^(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray

explicit operator Array(NDArray)

public static explicit operator Array(NDArray nd)

Parameters

nd NDArray

Returns

Array

explicit operator bool(NDArray)

public static explicit operator bool(NDArray nd)

Parameters

nd NDArray

Returns

bool

explicit operator byte(NDArray)

public static explicit operator byte(NDArray nd)

Parameters

nd NDArray

Returns

byte

explicit operator char(NDArray)

public static explicit operator char(NDArray nd)

Parameters

nd NDArray

Returns

char

explicit operator decimal(NDArray)

public static explicit operator decimal(NDArray nd)

Parameters

nd NDArray

Returns

decimal

explicit operator double(NDArray)

public static explicit operator double(NDArray nd)

Parameters

nd NDArray

Returns

double

explicit operator Half(NDArray)

public static explicit operator Half(NDArray nd)

Parameters

nd NDArray

Returns

Half

explicit operator short(NDArray)

public static explicit operator short(NDArray nd)

Parameters

nd NDArray

Returns

short

explicit operator int(NDArray)

public static explicit operator int(NDArray nd)

Parameters

nd NDArray

Returns

int

explicit operator long(NDArray)

public static explicit operator long(NDArray nd)

Parameters

nd NDArray

Returns

long

explicit operator Complex(NDArray)

public static explicit operator Complex(NDArray nd)

Parameters

nd NDArray

Returns

Complex

explicit operator sbyte(NDArray)

public static explicit operator sbyte(NDArray nd)

Parameters

nd NDArray

Returns

sbyte

explicit operator float(NDArray)

public static explicit operator float(NDArray nd)

Parameters

nd NDArray

Returns

float

explicit operator string(NDArray)

public static explicit operator string(NDArray d)

Parameters

d NDArray

Returns

string

explicit operator ushort(NDArray)

public static explicit operator ushort(NDArray nd)

Parameters

nd NDArray

Returns

ushort

explicit operator uint(NDArray)

public static explicit operator uint(NDArray nd)

Parameters

nd NDArray

Returns

uint

explicit operator ulong(NDArray)

public static explicit operator ulong(NDArray nd)

Parameters

nd NDArray

Returns

ulong

operator >(NDArray, NDArray)

Element-wise greater-than comparison (>). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator >(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator >(NDArray, object)

Element-wise greater-than comparison with scalar (>).

public static NDArray<bool> operator >(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator >(object, NDArray)

Element-wise greater-than comparison with scalar on left (>).

public static NDArray<bool> operator >(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

operator >=(NDArray, NDArray)

Element-wise greater-than-or-equal comparison (>=). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator >=(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator >=(NDArray, object)

Element-wise greater-than-or-equal comparison with scalar (>=).

public static NDArray<bool> operator >=(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator >=(object, NDArray)

Element-wise greater-than-or-equal comparison with scalar on left (>=).

public static NDArray<bool> operator >=(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

implicit operator NDArray(Array)

public static implicit operator NDArray(Array array)

Parameters

array Array

Returns

NDArray

implicit operator NDArray(bool)

public static implicit operator NDArray(bool d)

Parameters

d bool

Returns

NDArray

implicit operator NDArray(byte)

public static implicit operator NDArray(byte d)

Parameters

d byte

Returns

NDArray

implicit operator NDArray(char)

public static implicit operator NDArray(char d)

Parameters

d char

Returns

NDArray

implicit operator NDArray(decimal)

public static implicit operator NDArray(decimal d)

Parameters

d decimal

Returns

NDArray

implicit operator NDArray(double)

public static implicit operator NDArray(double d)

Parameters

d double

Returns

NDArray

implicit operator NDArray(Half)

public static implicit operator NDArray(Half d)

Parameters

d Half

Returns

NDArray

implicit operator NDArray(short)

public static implicit operator NDArray(short d)

Parameters

d short

Returns

NDArray

implicit operator NDArray(int)

public static implicit operator NDArray(int d)

Parameters

d int

Returns

NDArray

implicit operator NDArray(long)

public static implicit operator NDArray(long d)

Parameters

d long

Returns

NDArray

implicit operator NDArray(Complex)

public static implicit operator NDArray(Complex d)

Parameters

d Complex

Returns

NDArray

implicit operator NDArray(sbyte)

public static implicit operator NDArray(sbyte d)

Parameters

d sbyte

Returns

NDArray

implicit operator NDArray(float)

public static implicit operator NDArray(float d)

Parameters

d float

Returns

NDArray

implicit operator NDArray(string)

public static implicit operator NDArray(string str)

Parameters

str string

Returns

NDArray

implicit operator NDArray(ushort)

public static implicit operator NDArray(ushort d)

Parameters

d ushort

Returns

NDArray

implicit operator NDArray(uint)

public static implicit operator NDArray(uint d)

Parameters

d uint

Returns

NDArray

implicit operator NDArray(ulong)

public static implicit operator NDArray(ulong d)

Parameters

d ulong

Returns

NDArray

operator !=(NDArray, NDArray)

Element-wise not-equal comparison (!=). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator !=(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator !=(NDArray, object)

Element-wise not-equal comparison with scalar (!=).

public static NDArray<bool> operator !=(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator !=(object, NDArray)

Element-wise not-equal comparison with scalar on left (!=).

public static NDArray<bool> operator !=(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

operator <<(NDArray, NDArray)

Element-wise left shift. Integer dtypes only. Shifts bits of lhs left by rhs. Broadcast-aware.

public static NDArray operator <<(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray

operator <<(NDArray, object)

Element-wise left shift with any scalar or array-like on RHS. Converts RHS via np.asanyarray(object) (matches NumPy's PyArray_FromAny).

public static NDArray operator <<(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray

operator <(NDArray, NDArray)

Element-wise less-than comparison (<). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator <(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator <(NDArray, object)

Element-wise less-than comparison with scalar (<).

public static NDArray<bool> operator <(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator <(object, NDArray)

Element-wise less-than comparison with scalar on left (<).

public static NDArray<bool> operator <(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

operator <=(NDArray, NDArray)

Element-wise less-than-or-equal comparison (<=). Supports all 12 dtypes and broadcasting.

public static NDArray<bool> operator <=(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray<bool>

operator <=(NDArray, object)

Element-wise less-than-or-equal comparison with scalar (<=).

public static NDArray<bool> operator <=(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray<bool>

operator <=(object, NDArray)

Element-wise less-than-or-equal comparison with scalar on left (<=).

public static NDArray<bool> operator <=(object lhs, NDArray rhs)

Parameters

lhs object
rhs NDArray

Returns

NDArray<bool>

operator !(NDArray)

public static NDArray<bool> operator !(NDArray self)

Parameters

self NDArray

Returns

NDArray<bool>

operator %(NDArray, NDArray)

public static NDArray operator %(NDArray x, NDArray y)

Parameters

x NDArray
y NDArray

Returns

NDArray

operator %(NDArray, object)

public static NDArray operator %(NDArray left, object right)

Parameters

left NDArray
right object

Returns

NDArray

operator %(object, NDArray)

public static NDArray operator %(object left, NDArray right)

Parameters

left object
right NDArray

Returns

NDArray

operator *(NDArray, NDArray)

public static NDArray operator *(NDArray x, NDArray y)

Parameters

x NDArray
y NDArray

Returns

NDArray

operator *(NDArray, object)

public static NDArray operator *(NDArray left, object right)

Parameters

left NDArray
right object

Returns

NDArray

operator *(object, NDArray)

public static NDArray operator *(object left, NDArray right)

Parameters

left object
right NDArray

Returns

NDArray

operator ~(NDArray)

Element-wise bitwise NOT (invert) operation. For boolean arrays: logical NOT (~True = False, ~False = True). For integer arrays: bitwise NOT (~0 = -1, ~1 = -2, etc.).

public static NDArray operator ~(NDArray x)

Parameters

x NDArray

Returns

NDArray

Remarks

Matches NumPy's ~ operator behavior:

Boolean: ~arr is equivalent to np.logical_not(arr)
Integer: ~arr is equivalent to np.invert(arr)

operator >>(NDArray, NDArray)

Element-wise right shift. Integer dtypes only. Shifts bits of lhs right by rhs. Logical shift for unsigned types, arithmetic shift for signed types. Broadcast-aware.

public static NDArray operator >>(NDArray lhs, NDArray rhs)

Parameters

lhs NDArray
rhs NDArray

Returns

NDArray

operator >>(NDArray, object)

Element-wise right shift with any scalar or array-like on RHS. Converts RHS via np.asanyarray(object) (matches NumPy's PyArray_FromAny).

public static NDArray operator >>(NDArray lhs, object rhs)

Parameters

lhs NDArray
rhs object

Returns

NDArray

operator -(NDArray, NDArray)

public static NDArray operator -(NDArray x, NDArray y)

Parameters

x NDArray
y NDArray

Returns

NDArray

operator -(NDArray, object)

public static NDArray operator -(NDArray left, object right)

Parameters

left NDArray
right object

Returns

NDArray

operator -(object, NDArray)

public static NDArray operator -(object left, NDArray right)

Parameters

left object
right NDArray

Returns

NDArray

operator -(NDArray)

public static NDArray operator -(NDArray x)

Parameters

x NDArray

Returns

NDArray

operator +(NDArray)

public static NDArray operator +(NDArray x)

Parameters

x NDArray

Returns

NDArray

Table of Contents

Class NDArray

Remarks

Constructors

NDArray(IArraySlice, Shape, char)

Parameters

Remarks

NDArray(UnmanagedStorage)

Parameters

NDArray(UnmanagedStorage, Shape)

Parameters

Remarks

NDArray(UnmanagedStorage, ref Shape)

Parameters

Remarks

NDArray(NPTypeCode)

Parameters

Remarks

NDArray(NPTypeCode, Shape)

Parameters

Remarks

NDArray(NPTypeCode, Shape, bool)

Parameters

Remarks

NDArray(NPTypeCode, TensorEngine)

Parameters

Remarks

NDArray(NPTypeCode, int)

Parameters

Remarks

NDArray(NPTypeCode, int, bool)

Parameters

Remarks

NDArray(NPTypeCode, long)

Parameters

Remarks

NDArray(NPTypeCode, long, bool)

Parameters

Remarks

NDArray(Array, Shape, char)

Parameters

Remarks

NDArray(Type)

Parameters

Remarks

NDArray(Type, Shape)

Parameters

Remarks

NDArray(Type, Shape, bool)

Parameters

Remarks

NDArray(Type, Shape, char)

Parameters

Remarks

NDArray(Type, TensorEngine)

Parameters

Remarks

NDArray(Type, int)

Parameters

Remarks

NDArray(Type, int, bool)

Parameters

Remarks

NDArray(Type, long)

Parameters

Remarks

NDArray(Type, long, bool)

Parameters

Remarks

Fields

Storage

Field Value

tensorEngine

Field Value

Properties

Address

Property Value

Array

Property Value

Remarks