numojo.core.complex.complex_ndarray

"ComplexNDArray (numojo.core.complex.complex_ndarray)

Complex NDArray support for NuMojo.

This module provides the ComplexNDArray type, which represents N-dimensional arrays of complex numbers. It includes lifecycle methods, indexing and slicing, operator overloads, IO, trait, and iterator methods, as well as other utility functions.

Structs

ComplexNDArray

struct ComplexNDArray[cdtype: ComplexDType = ComplexDType.float64]

Memory convention: memory_only
Implements: AnyType, Copyable, FloatableRaising, ImplicitlyDestructible, IntableRaising, Movable, Representable, Sized, Stringable, Writable

N-dimensional Complex array.

ComplexNDArray represents an N-dimensional array whose elements are complex numbers, supporting efficient storage, indexing, and mathematical operations. Each element consists of a real and imaginary part, stored in separate buffers.

Attributes: - _re: NDArray[Self.dtype] Buffer for real parts. - _im: NDArray[Self.dtype] Buffer for imaginary parts. - ndim: Int Number of dimensions. - shape: NDArrayShape Shape of the array. - size: Int Total number of elements. - strides: NDArrayStrides Stride information for each dimension. - flags: Flags Memory layout information. - print_options: PrintOptions Formatting options for display.

Notes: - The array is uniquely defined by its data buffers, shape, strides, and element datatype. - Supports both row-major (C) and column-major (F) memory order. - Provides rich indexing, slicing, and broadcasting semantics. - ComplexNDArray should be created using factory functions in nomojo.routines.creation module for convenience.

Parameters:

• cdtype (ComplexDType): The complex data type of the array elements (default: ComplexDType.float64).

Fields

• ndim (Int): Number of Dimensions.
• shape (NDArrayShape): Size and shape of ComplexNDArray.
• size (Int): Size of ComplexNDArray.
• strides (NDArrayStrides): Contains offset, strides.
• flags (Flags): Information about the memory layout of the array.
• print_options (PrintOptions): Per-instance print options (formerly global).

Aliases

dtype

comptime dtype

Value: cdtype.dtype

Corresponding real data type.

__del__is_trivial

comptime __del__is_trivial

Value: False

__move_ctor_is_trivial

comptime __move_ctor_is_trivial

Value: False

__copy_ctor_is_trivial

comptime __copy_ctor_is_trivial

Value: False

Methods

__init__

Overload 1

__init__(out self, var re: NDArray[ComplexNDArray[cdtype].dtype], var im: NDArray[ComplexNDArray[cdtype].dtype])

static

Initialize a ComplexNDArray with given real and imaginary parts.

Args:

• re (NDArray) [var]: Real part of the complex array.
• im (NDArray) [var]: Imaginary part of the complex array.
• self (Self) [out]

Returns:

• Self

Raises

Overload 2

__init__(out self, shape: NDArrayShape, order: String = "C")

static

Initialize a ComplexNDArray with given shape. The memory is not filled with values.

Example:

from numojo.prelude import *
var A = nm.ComplexNDArray[cf32](Shape(2,3,4))

Notes: This constructor should not be used by users directly. Use factory functions in numojo.routines.creation module instead.

Args:

• shape (NDArrayShape): Variadic shape.
• order (String): Memory order C or F.
• self (Self) [out]

Returns:

• Self

Raises

Overload 3

__init__(out self, shape: List[Int], order: String = "C")

static

(Overload) Initialize a ComplexNDArray with given shape (list of integers).

Example:

from numojo.prelude import *
var A = nm.ComplexNDArray[cf32]([2,3,4])

Notes: This constructor should not be used by users directly. Use factory functions in numojo.routines.creation module instead.

Args:

• shape (List): List of shape.
• order (String): Memory order C or F.
• self (Self) [out]

Returns:

• Self

Raises

Overload 4

__init__(out self, shape: VariadicList[Int], order: String = "C")

static

(Overload) Initialize a ComplexNDArray with given shape (variadic list of integers).

Example:

from numojo.prelude import *
var A = nm.ComplexNDArray[cf32](VariadicList(2,3,4))

Notes: This constructor should not be used by users directly. Use factory functions in numojo.routines.creation module instead.

Args:

• shape (VariadicList): Variadic List of shape.
• order (String): Memory order C or F.
• self (Self) [out]

Returns:

• Self

Raises

Overload 5

__init__(out self, shape: List[Int], offset: Int, strides: List[Int])

static

Initialize a ComplexNDArray with a specific shape, offset, and strides.

Example:

from numojo.prelude import *
var shape = [2, 3]
var offset = 0
var strides = [3, 1]
var arr = ComplexNDArray[cf32](shape, offset, strides)

Notes: - This constructor is intended for advanced use cases requiring precise control over memory layout. - The resulting array is uninitialized and should be filled before use. - Both real and imaginary buffers are created with the same shape, offset, and strides.

Args:

• shape (List): List of integers specifying the shape of the array.
• offset (Int): Integer offset into the underlying buffer.
• strides (List): List of integers specifying the stride for each dimension.
• self (Self) [out]

Returns:

• Self

Raises

Overload 6

__init__(out self, shape: NDArrayShape, strides: NDArrayStrides, ndim: Int, size: Int, flags: Flags)

static

Initialize a ComplexNDArray with explicit shape, strides, number of dimensions, size, and flags. This constructor creates an uninitialized ComplexNDArray with the provided properties. No compatibility checks are performed between shape, strides, ndim, size, or flags. This allows construction of arrays with arbitrary metadata, including 0-D arrays (scalars).

Notes: - This constructor is intended for advanced or internal use cases requiring manual control. - The resulting array is uninitialized; values must be set before use. - No validation is performed on the consistency of the provided arguments.

Args:

• shape (NDArrayShape): Shape of the array.
• strides (NDArrayStrides): Strides for each dimension.
• ndim (Int): Number of dimensions.
• size (Int): Total number of elements.
• flags (Flags): Memory layout flags.
• self (Self) [out]

Returns:

• Self

Overload 7

__init__(out self, *, copy: Self)

static

Copy copy into self.

Args:

• copy (Self)
• self (Self) [out]

Returns:

• Self

Overload 8

__init__(out self, *, deinit take: Self)

static

Move other into self.

Args:

• take (Self) [deinit]
• self (Self) [out]

Returns:

• Self

__bool__

__bool__(self) -> Bool

Check if the complex array is non-zero.

For a 0-D or length-1 complex array, returns True if the complex number is non-zero (i.e., either real or imaginary part is non-zero).

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape())  # 0-D array
A._re._buf.ptr[] = 1.0
A._im._buf.ptr[] = 0.0
var result = A.__bool__()  # True

Args:

• self (Self)

Returns:

• Bool

Raises

Error: If the array is not 0-D or length-1.

__getitem__

Overload 1

__getitem__(self) -> ComplexSIMD[cdtype]

Gets the value of the 0-D Complex array.

Examples:

import numojo as nm
from numojo.prelude import *
var a = nm.arange[cf32](CScalar[cf32](1))[0]
print(a[]) # gets values of the 0-D complex array.

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

Error: If the array is not 0-d.

Overload 2

__getitem__(self, index: Item) -> ComplexSIMD[cdtype]

Get the value at the index list.

Examples:

>>>import numojo as nm
>>>var A = nm.full[nm.f32](nm.Shape(2, 5), ComplexSIMD[nm.f32](1.0, 1.0))
>>>print(A[Item(1, 2)]) # gets values of the element at (1, 2).
```.

**Args:**

- `self` (`Self`)
- `index` (`Item`): Index list.

**Returns:**

- `ComplexSIMD`

!!! failure "Raises"
    Error: If the length of `index` does not match the number of dimensions.
Error: If any of the index elements exceeds the size of the dimension of the array.

###### Overload 3

```mojo
__getitem__(self, idx: Int) -> Self

Single-axis integer slice (first dimension). Returns a slice of the complex array taken at axis 0 position idx. Dimensionality is reduced by exactly one; a 1-D source produces a 0-D ComplexNDArray (scalar wrapper). Negative indices are supported and normalized. The result preserves the source memory order (C/F).

Notes: Performance fast path: For C-contiguous arrays the slice for both real and imaginary parts is copied with single memcpy calls. For F-contiguous or arbitrary stride layouts, a generic stride-based copier is used for both components. (Future: return a non-owning view).

Example:

import numojo as nm
from numojo.prelude import *
var a = nm.arange[cf32](CScalar[cf32](0), CScalar[cf32](12), CScalar[cf32](1)).reshape(Shape(3, 4))
print(a.shape)        # (3,4)
print(a[1].shape)     # (4,)  -- 1-D slice
print(a[-1].shape)    # (4,)  -- negative index
var b = nm.arange[cf32](CScalar[cf32](6)).reshape(nm.Shape(6))
print(b[2])           # 0-D array (scalar wrapper)

Args:

• self (Self)
• idx (Int): Integer index along the first (axis 0) dimension. Supports negative indices in [-shape[0], shape[0]).

Returns:

• Self

Raises

IndexError: If the array is 0-D.

IndexError: If idx (after normalization) is out of bounds.

Overload 4

__getitem__(self, var *slices: Slice) -> Self

Retrieves a slice or sub-array from the current array using variadic slice arguments.

NOTES: - This method creates a new array; Views are not currently supported. - Negative indices and step sizes are supported as per standard slicing semantics.

Examples:

import numojo as nm
var a = numojo.arange(10).reshape(nm.Shape(2, 5))
var b = a[:, 2:4]
print(b) # Output: 2x2 sliced array corresponding to columns 2 and 3 of each row.

Constraints

• The number of slices provided must not exceed the number of array dimensions.

• Each slice must be valid for its corresponding dimension.

Args:

• self (Self)
• *slices (Slice) [var]: Variadic list of Slice objects, one for each dimension to be sliced.

Returns:

• Self

Raises

IndexError: If any slice is out of bounds for its corresponding dimension.

ValueError: If the number of slices does not match the array's dimensions.

Overload 5

__getitem__(self, var slice_list: List[Slice]) -> Self

Retrieves a sub-array from the current array using a list of slice objects, enabling advanced slicing operations across multiple dimensions.

NOTES: - This method supports advanced slicing similar to NumPy's multi-dimensional slicing. - The returned array shares data with the original array if possible.

Example:

import numojo as nm
from numojo.prelude import *
var a = nm.arange[cf32](CScalar[cf32](10.0, 10.0)).reshape(nm.Shape(2, 5))
var b = a[[Slice(0, 2, 1), Slice(2, 4, 1)]]  # Equivalent to arr[:, 2:4], returns a 2x2 sliced array.
print(b)

Constraints

• The length of slice_list must not exceed the number of dimensions in the array.

• Each Slice in slice_list must be valid for its respective dimension.

Args:

• self (Self)
• slice_list (List) [var]: List of Slice objects, where each Slice defines the start, stop, and step for the corresponding dimension.

Returns:

• Self

Raises

Error: If slice_list is empty or contains invalid slices.

Overload 6

__getitem__(self, var *slices: Variant[Slice, Int]) -> Self

Get items of ComplexNDArray with a series of either slices or integers.

Examples:

    import numojo as nm
    from numojo.prelude import *
    var a = nm.full[cf32](nm.Shape(2, 5), CScalar[cf32](1.0, 1.0))
    var b = a[1, Slice(2,4)]
    print(b)

Args:

• self (Self)
• *slices (Variant) [var]: A series of either Slice or Int.

Returns:

• Self

Raises

Error: If the number of slices is greater than the number of dimensions of the array.

Overload 7

__getitem__(self, indices: NDArray[DType.int]) -> Self

Get items from 0-th dimension of a ComplexNDArray of indices. If the original array is of shape (i,j,k) and the indices array is of shape (l, m, n), then the output array will be of shape (l,m,n,j,k).

Args:

• self (Self)
• indices (NDArray): Array of indices.

Returns:

• Self

Raises

Error: If the elements of indices are greater than size of the corresponding dimension of the array.

Overload 8

__getitem__(self, indices: List[Int]) -> Self

Get items from 0-th dimension of a ComplexNDArray of indices. It is an overload of __getitem__(self, indices: NDArray[DType.int]) raises -> Self.

Args:

• self (Self)
• indices (List): A list of Int.

Returns:

• Self

Raises

Error: If the elements of indices are greater than size of the corresponding dimension of the array.

Overload 9

__getitem__(self, mask: NDArray[DType.bool]) -> Self

Get item from a ComplexNDArray according to a mask array. If array shape is equal to mask shape, it returns a flattened array of the values where mask is True. If array shape is not equal to mask shape, it returns items from the 0-th dimension of the array where mask is True.

Args:

• self (Self)
• mask (NDArray): NDArray with Dtype.bool.

Returns:

• Self

Raises

Error: If the mask is not a 1-D array (Currently we only support 1-d mask array).

Overload 10

__getitem__(self, mask: List[Bool]) -> Self

Get items from 0-th dimension of a ComplexNDArray according to mask.

Args:

• self (Self)
• mask (List): A list of boolean values.

Returns:

• Self

Raises

Error: If the mask is not a 1-D array (Currently we only support 1-d mask array).

__setitem__

Overload 1

__setitem__(mut self, idx: Int, val: Self)

Assign a single first-axis slice. Replaces the sub-array at axis 0 position idx with val. The shape of val must exactly match self.shape[1:] and its dimensionality must be self.ndim - 1 (or be a 0-D complex scalar when assigning into a 1-D array). Negative indices are supported. Fast path: contiguous memcpy for C-order; otherwise a stride-based generic copy is performed for both real and imaginary parts.

Args:

• self (Self) [mut]
• idx (Int): Integer index along first dimension (supports negatives).
• val (Self): ComplexNDArray slice data to assign.

Raises

IndexError: If array is 0-D or idx out of bounds.

ShapeError: If val shape/dim mismatch with target slice.

Overload 2

__setitem__(mut self, var index: Item, val: ComplexSIMD[cdtype])

Sets the value at the index list.

Examples:

import numojo as nm
from numojo.prelude import *
var A = nm.full[cf32](Shape(2, 2), CScalar[cf32](1.0))
A[Item(0, 1)] = CScalar[cf32](3.0, 4.0)

Args:

• self (Self) [mut]
• index (Item) [var]: Index list.
• val (ComplexSIMD): Value to set.

Raises

Error: If the length of index does not match the number of dimensions.

Error: If any of the indices is out of bound.

Overload 3

__setitem__(mut self, mask: Self, value: ComplexSIMD[cdtype])

Set the value of the array at the indices where the mask is true.

Args:

• self (Self) [mut]
• mask (Self)
• value (ComplexSIMD)

Raises

Overload 4

__setitem__(mut self, var *slices: Slice, *, val: Self)

Retreive slices of an ComplexNDArray from variadic slices.

Example: arr[1:3, 2:4] returns the corresponding sliced ComplexNDArray (2 x 2).

Args:

• self (Self) [mut]
• *slices (Slice) [var]
• val (Self)

Raises

Overload 5

__setitem__(mut self, slices: List[Slice], val: Self)

Sets the slices of an ComplexNDArray from list of slices and ComplexNDArray.

Example: arr[1:3, 2:4] returns the corresponding sliced ComplexNDArray (2 x 2).

Args:

• self (Self) [mut]
• slices (List)
• val (Self)

Raises

Overload 6

__setitem__(self, var *slices: Variant[Slice, Int], *, val: Self)

Get items by a series of either slices or integers.

Args:

• self (Self)
• *slices (Variant) [var]
• val (Self)

Raises

Overload 7

__setitem__(self, index: NDArray[DType.int], val: Self)

Returns the items of the ComplexNDArray from an array of indices.

Refer to __getitem__(self, index: List[Int]).

Args:

• self (Self)
• index (NDArray)
• val (Self)

Raises

Overload 8

__setitem__(mut self, mask: Self, val: Self)

Set the value of the ComplexNDArray at the indices where the mask is true.

Args:

• self (Self) [mut]
• mask (Self)
• val (Self)

Raises

__neg__

__neg__(self) -> Self

Unary negative returns self unless boolean type.

For bolean use __invert__(~)

Args:

• self (Self)

Returns:

• Self

Raises

__pos__

__pos__(self) -> Self

Unary positive returns self unless boolean type.

Args:

• self (Self)

Returns:

• Self

Raises

__lt__

Overload 1

__lt__(self, other: Self) -> NDArray[DType.bool]

Itemwise less than comparison by magnitude.

For complex numbers, compares the magnitudes: |self| < |other|. This provides a natural ordering for complex numbers.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var result = A < B  # Compare by magnitude

Notes: Complex number ordering is not naturally defined. This implementation compares by magnitude (absolute value) to provide a consistent ordering.

Args:

• self (Self)
• other (Self): The other ComplexNDArray to compare with.

Returns:

• NDArray

Raises

Overload 2

__lt__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise less than comparison with scalar by magnitude.

Args:

• self (Self)
• other (ComplexSIMD): The ComplexSIMD scalar to compare with.

Returns:

• NDArray

Raises

Overload 3

__lt__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> NDArray[DType.bool]

Itemwise less than comparison with real scalar by magnitude.

Args:

• self (Self)
• other (Scalar): The real scalar to compare with.

Returns:

• NDArray

Raises

__le__

Overload 1

__le__(self, other: Self) -> NDArray[DType.bool]

Itemwise less than or equal comparison by magnitude.

For complex numbers, compares the magnitudes: |self| <= |other|.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var result = A <= B  # Compare by magnitude

Args:

• self (Self)
• other (Self): The other ComplexNDArray to compare with.

Returns:

• NDArray

Raises

Overload 2

__le__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise less than or equal comparison with scalar by magnitude.

Args:

• self (Self)
• other (ComplexSIMD): The ComplexSIMD scalar to compare with.

Returns:

• NDArray

Raises

Overload 3

__le__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> NDArray[DType.bool]

Itemwise less than or equal comparison with real scalar by magnitude.

Args:

• self (Self)
• other (Scalar): The real scalar to compare with.

Returns:

• NDArray

Raises

__eq__

Overload 1

__eq__(self, other: Self) -> NDArray[DType.bool]

Itemwise equivalence.

Args:

• self (Self)
• other (Self)

Returns:

• NDArray

Raises

Overload 2

__eq__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise equivalence between scalar and ComplexNDArray.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• NDArray

Raises

__ne__

Overload 1

__ne__(self, other: Self) -> NDArray[DType.bool]

Itemwise non-equivalence.

Args:

• self (Self)
• other (Self)

Returns:

• NDArray

Raises

Overload 2

__ne__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise non-equivalence between scalar and ComplexNDArray.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• NDArray

Raises

__gt__

Overload 1

__gt__(self, other: Self) -> NDArray[DType.bool]

Itemwise greater than comparison by magnitude.

For complex numbers, compares the magnitudes: |self| > |other|.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var result = A > B  # Compare by magnitude

Notes: Complex number ordering is not naturally defined. This implementation compares by magnitude (absolute value) to provide a consistent ordering.

Args:

• self (Self)
• other (Self): The other ComplexNDArray to compare with.

Returns:

• NDArray

Raises

Overload 2

__gt__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise greater than comparison with scalar by magnitude.

Args:

• self (Self)
• other (ComplexSIMD): The ComplexSIMD scalar to compare with.

Returns:

• NDArray

Raises

Overload 3

__gt__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> NDArray[DType.bool]

Itemwise greater than comparison with real scalar by magnitude.

Args:

• self (Self)
• other (Scalar): The real scalar to compare with.

Returns:

• NDArray

Raises

__ge__

Overload 1

__ge__(self, other: Self) -> NDArray[DType.bool]

Itemwise greater than or equal comparison by magnitude.

For complex numbers, compares the magnitudes: |self| >= |other|.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var result = A >= B  # Compare by magnitude

Args:

• self (Self)
• other (Self): The other ComplexNDArray to compare with.

Returns:

• NDArray

Raises

Overload 2

__ge__(self, other: ComplexSIMD[cdtype]) -> NDArray[DType.bool]

Itemwise greater than or equal comparison with scalar by magnitude.

Args:

• self (Self)
• other (ComplexSIMD): The ComplexSIMD scalar to compare with.

Returns:

• NDArray

Raises

Overload 3

__ge__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> NDArray[DType.bool]

Itemwise greater than or equal comparison with real scalar by magnitude.

Args:

• self (Self)
• other (Scalar): The real scalar to compare with.

Returns:

• NDArray

Raises

__add__

Overload 1

__add__(self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexNDArray + ComplexSIMD.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__add__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray + Scalar.

Args:

• self (Self)
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__add__(self, other: Self) -> Self

Enables ComplexNDArray + ComplexNDArray.

Args:

• self (Self)
• other (Self)

Returns:

• Self

Raises

Overload 4

__add__(self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray + NDArray.

Args:

• self (Self)
• other (NDArray)

Returns:

• Self

Raises

__sub__

Overload 1

__sub__(self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexNDArray - ComplexSIMD.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__sub__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray - Scalar.

Args:

• self (Self)
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__sub__(self, other: Self) -> Self

Enables ComplexNDArray - ComplexNDArray.

Args:

• self (Self)
• other (Self)

Returns:

• Self

Raises

Overload 4

__sub__(self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray - NDArray.

Args:

• self (Self)
• other (NDArray)

Returns:

• Self

Raises

__mul__

Overload 1

__mul__(self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexNDArray * ComplexSIMD.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__mul__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray * Scalar.

Args:

• self (Self)
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__mul__(self, other: Self) -> Self

Enables ComplexNDArray * ComplexNDArray.

Args:

• self (Self)
• other (Self)

Returns:

• Self

Raises

Overload 4

__mul__(self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray * NDArray.

Args:

• self (Self)
• other (NDArray)

Returns:

• Self

Raises

__matmul__

__matmul__(self, other: Self) -> Self

Args:

• self (Self)
• other (Self)

Returns:

• Self

Raises

__truediv__

Overload 1

__truediv__(self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexNDArray / ComplexSIMD.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__truediv__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray / ComplexSIMD.

Args:

• self (Self)
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__truediv__(self, other: Self) -> Self

Enables ComplexNDArray / ComplexNDArray.

Args:

• self (Self)
• other (Self)

Returns:

• Self

Raises

Overload 4

__truediv__(self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables ComplexNDArray / NDArray.

Args:

• self (Self)
• other (NDArray)

Returns:

• Self

Raises

__pow__

Overload 1

__pow__(self, p: Int) -> Self

Raise complex array to integer power element-wise.

Uses De Moivre's formula for complex exponentiation: (r * e^(i*theta))n = r^n * e^(i*n*theta)

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = A ** 3  # Cube each element

Args:

• self (Self)
• p (Int): Integer exponent.

Returns:

• Self

Raises

Overload 2

__pow__(self, rhs: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Raise complex array to real scalar power element-wise.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = A ** 2.5  # Raise to power 2.5

Args:

• self (Self)
• rhs (Scalar): Real scalar exponent.

Returns:

• Self

Raises

Overload 3

__pow__(self, p: Self) -> Self

Raise complex array to complex array power element-wise.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var B = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
var C = A ** B  # Element-wise complex power

Args:

• self (Self)
• p (Self): ComplexNDArray exponent.

Returns:

• Self

Raises

Error: If arrays have different sizes.

__radd__

Overload 1

__radd__(mut self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexSIMD + ComplexNDArray.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__radd__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables Scalar + ComplexNDArray.

Args:

• self (Self) [mut]
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__radd__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables NDArray + ComplexNDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Returns:

• Self

Raises

__rsub__

Overload 1

__rsub__(mut self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexSIMD - ComplexNDArray.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__rsub__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables Scalar - ComplexNDArray.

Args:

• self (Self) [mut]
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__rsub__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables NDArray - ComplexNDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Returns:

• Self

Raises

__rmul__

Overload 1

__rmul__(self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexSIMD * ComplexNDArray.

Args:

• self (Self)
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__rmul__(self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables Scalar * ComplexNDArray.

Args:

• self (Self)
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__rmul__(self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables NDArray * ComplexNDArray.

Args:

• self (Self)
• other (NDArray)

Returns:

• Self

Raises

__rtruediv__

Overload 1

__rtruediv__(mut self, other: ComplexSIMD[cdtype]) -> Self

Enables ComplexSIMD / ComplexNDArray.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Returns:

• Self

Raises

Overload 2

__rtruediv__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Enables Scalar / ComplexNDArray.

Args:

• self (Self) [mut]
• other (Scalar)

Returns:

• Self

Raises

Overload 3

__rtruediv__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype]) -> Self

Enables NDArray / ComplexNDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Returns:

• Self

Raises

__iadd__

Overload 1

__iadd__(mut self, other: ComplexSIMD[cdtype])

Enables ComplexNDArray += ComplexSIMD.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Raises

Overload 2

__iadd__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray += Scalar.

Args:

• self (Self) [mut]
• other (Scalar)

Raises

Overload 3

__iadd__(mut self, other: Self)

Enables ComplexNDArray += ComplexNDArray.

Args:

• self (Self) [mut]
• other (Self)

Raises

Overload 4

__iadd__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray += NDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Raises

__isub__

Overload 1

__isub__(mut self, other: ComplexSIMD[cdtype])

Enables ComplexNDArray -= ComplexSIMD.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Raises

Overload 2

__isub__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray -= Scalar.

Args:

• self (Self) [mut]
• other (Scalar)

Raises

Overload 3

__isub__(mut self, other: Self)

Enables ComplexNDArray -= ComplexNDArray.

Args:

• self (Self) [mut]
• other (Self)

Raises

Overload 4

__isub__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray -= NDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Raises

__imul__

Overload 1

__imul__(mut self, other: ComplexSIMD[cdtype])

Enables ComplexNDArray *= ComplexSIMD.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Raises

Overload 2

__imul__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray *= Scalar.

Args:

• self (Self) [mut]
• other (Scalar)

Raises

Overload 3

__imul__(mut self, other: Self)

Enables ComplexNDArray *= ComplexNDArray.

Args:

• self (Self) [mut]
• other (Self)

Raises

Overload 4

__imul__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray *= NDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Raises

__itruediv__

Overload 1

__itruediv__(mut self, other: ComplexSIMD[cdtype])

Enables ComplexNDArray /= ComplexSIMD.

Args:

• self (Self) [mut]
• other (ComplexSIMD)

Raises

Overload 2

__itruediv__(mut self, other: Scalar[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray /= Scalar.

Args:

• self (Self) [mut]
• other (Scalar)

Raises

Overload 3

__itruediv__(mut self, other: Self)

Enables ComplexNDArray /= ComplexNDArray.

Args:

• self (Self) [mut]
• other (Self)

Raises

Overload 4

__itruediv__(mut self, other: NDArray[ComplexNDArray[cdtype].dtype])

Enables ComplexNDArray /= NDArray.

Args:

• self (Self) [mut]
• other (NDArray)

Raises

__ipow__

__ipow__(mut self, p: Int)

In-place raise to integer power.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
A **= 3  # Cube in place

Args:

• self (Self) [mut]
• p (Int): Integer exponent.

Raises

normalize

normalize(self, idx: Int, dim: Int) -> Int

Normalize a potentially negative index to its positive equivalent within the bounds of the given dimension.

Args:

• self (Self)
• idx (Int): The index to normalize. Can be negative to indicate indexing from the end (e.g., -1 refers to the last element).
• dim (Int): The size of the dimension to normalize against.

Returns:

• Int

item

Overload 1

item(self, var index: Int) -> ComplexSIMD[cdtype]

Return the scalar at the coordinates. If one index is given, get the i-th item of the complex array (not buffer). It first scans over the first row, even it is a column-major array. If more than one index is given, the length of the indices must match the number of dimensions of the array. If the ndim is 0 (0-D array), get the value as a mojo scalar.

Examples:

>>> import numojo as nm
>>> var A = nm.full[nm.f32](Shape(2, 2, 2), ComplexSIMD[nm.f32](1.0, 1.0))
>>> print(A.item(10)) # returns the 10-th item of the complex array.
```.

**Args:**

- `self` (`Self`)
- `index` (`Int`) `[var]`: Index of item, counted in row-major way.

**Returns:**

- `ComplexSIMD`

!!! failure "Raises"
    Error if array is 0-D array (numojo scalar).
Error if index is equal or larger than array size.

###### Overload 2

```mojo
item(self, *index: Int) -> ComplexSIMD[cdtype]

Return the scalar at the coordinates. If one index is given, get the i-th item of the complex array (not buffer). It first scans over the first row, even it is a colume-major array. If more than one index is given, the length of the indices must match the number of dimensions of the array. For 0-D complex array (numojo scalar), return the scalar value.

Examples:

>>> import numojo as nm
>>> var A = nm.full[nm.f32](Shape(2, 2, 2), ComplexSIMD[nm.f32](1.0, 1.0))
>>> print(A.item(1, 1, 1)) # returns the 10-th item of the complex array.
```.

**Args:**

- `self` (`Self`)
- `*index` (`Int`): The coordinates of the item.

**Returns:**

- `ComplexSIMD`

!!! failure "Raises"
    Error: If the number of indices is not equal to the number of dimensions of the array.
Error: If the index is equal or larger than size of dimension.


</div>

<div class="fn-card" markdown="1">

##### `load`

###### Overload 1

```mojo
load(self, var index: Int) -> ComplexSIMD[cdtype]

Safely retrieve i-th item from the underlying buffer.

A.load(i) differs from A._buf.ptr[i] due to boundary check.

Examples:

>>> import numojo as nm
>>> var A = nm.full[nm.f32](Shape(2, 2, 2), ComplexSIMD[nm.f32](1.0, 1.0))
>>> print(A.load(10)) # returns the 10-th item of the complex array.
```.

**Args:**

- `self` (`Self`)
- `index` (`Int`) `[var]`: Index of the item.

**Returns:**

- `ComplexSIMD`

!!! failure "Raises"
    Index out of bounds.

###### Overload 2

```mojo
load[width: Int = 1](self, index: Int) -> ComplexSIMD[cdtype, width]

Safely loads a ComplexSIMD element of size width at index from the underlying buffer.

To bypass boundary checks, use self._buf.ptr.load directly.

Parameters:

• width (Int)

Args:

• self (Self)
• index (Int): Index of the item.

Returns:

• ComplexSIMD

Raises

Index out of boundary.

Overload 3

load[width: Int = 1](self, *indices: Int) -> ComplexSIMD[cdtype, width]

Safely loads a ComplexSIMD element of size width at given variadic indices from the underlying buffer.

To bypass boundary checks, use self._buf.ptr.load directly.

Examples:

>>> import numojo as nm
>>> var A = nm.full[nm.f32](Shape(2, 2, 2), ComplexSIMD[nm.f32](1.0, 1.0))
>>> print(A.load(0, 1, 1))
```.

**Parameters:**

- `width` (`Int`)

**Args:**

- `self` (`Self`)
- `*indices` (`Int`): Variadic indices.

**Returns:**

- `ComplexSIMD`

!!! failure "Raises"
    Error: If the length of indices does not match the number of dimensions.
Error: If any of the indices is out of bound.


</div>

<div class="fn-card" markdown="1">

##### `__int__`

```mojo
__int__(self) -> Int

Gets Int representation of the complex array's real part.

Only 0-D arrays or length-1 arrays can be converted to scalars. The imaginary part is discarded.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape())  # 0-D array
A._re._buf.ptr[] = 42.7
A._im._buf.ptr[] = 3.14
print(A.__int__())  # 42 (only real part)

Args:

• self (Self)

Returns:

• Int

Raises

Error: If the array is not 0-D or length-1.

__float__

__float__(self) -> Float64

Gets Float64 representation of the complex array's magnitude.

Only 0-D arrays or length-1 arrays can be converted to scalars. Returns the magnitude (absolute value) of the complex number.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape())  # 0-D array
A._re._buf.ptr[] = 3.0
A._im._buf.ptr[] = 4.0
print(A.__float__())  # 5.0 (magnitude)

Args:

• self (Self)

Returns:

• Float64

Raises

Error: If the array is not 0-D or length-1.

__abs__

__abs__(self) -> NDArray[ComplexNDArray[cdtype].dtype]

Compute the magnitude (absolute value) of each complex element.

Returns an NDArray of real values containing the magnitude of each complex number: sqrt(re^2 + im^2).

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 2))
# Fill with some values
var mag = A.__abs__()  # Returns NDArray[f64] with magnitudes

Args:

• self (Self)

Returns:

• NDArray

Raises

__str__

__str__(self) -> String

Enables String(array).

Args:

• self (Self)

Returns:

• String

write_to

write_to[W: Writer](self, mut writer: W)

Writes the array to a writer.

Parameters:

• W (Writer)

Args:

• self (Self)
• writer (W) [mut]: The writer to write the array to.

__repr__

__repr__(self) -> String

Compute the "official" string representation of ComplexNDArray. An example is: fn main() raises: var A = ComplexNDArray[f32](List[ComplexSIMD[f32]](14,97,-59,-4,112,), shape=List[Int](5,)) print(repr(A)) It prints what can be used to construct the array itself: console ComplexNDArray[f32](List[ComplexSIMD[f32]](14,97,-59,-4,112,), shape=List[Int](5,)).

Args:

• self (Self)

Returns:

• String

__len__

__len__(self) -> Int

Args:

• self (Self)

Returns:

• Int

store

Overload 1

store[width: Int = 1](mut self, index: Int, val: ComplexSIMD[cdtype])

Safely stores SIMD element of size width at index of the underlying buffer.

To bypass boundary checks, use self._buf.ptr.store directly.

Parameters:

• width (Int)

Args:

• self (Self) [mut]
• index (Int)
• val (ComplexSIMD)

Raises

Index out of boundary.

Overload 2

store[width: Int = 1](mut self, *indices: Int, *, val: ComplexSIMD[cdtype])

Safely stores SIMD element of size width at given variadic indices of the underlying buffer.

To bypass boundary checks, use self._buf.ptr.store directly.

Parameters:

• width (Int)

Args:

• self (Self) [mut]
• *indices (Int)
• val (ComplexSIMD)

Raises

Index out of boundary.

reshape

reshape(self, shape: NDArrayShape, order: String = "C") -> Self

Returns an array of the same data with a new shape.

Args:

• self (Self)
• shape (NDArrayShape): Shape of returned array.
• order (String): Order of the array - Row major C or Column major F.

Returns:

• Self

Raises

__iter__

__iter__(mut self) -> _ComplexNDArrayIter[origin_of(self), cdtype]

Iterates over elements of the ComplexNDArray and return sub-arrays as view.

Args:

• self (Self) [mut]

Returns:

• _ComplexNDArrayIter

Raises

__reversed__

__reversed__(mut self) -> _ComplexNDArrayIter[origin_of(self), cdtype, False]

Iterates backwards over elements of the ComplexNDArray, returning copied value.

Args:

• self (Self) [mut]

Returns:

• _ComplexNDArrayIter

Raises

itemset

itemset(mut self, index: Variant[Int, List[Int]], item: ComplexSIMD[cdtype])

Set the scalar at the coordinates.

Args:

• self (Self) [mut]
• index (Variant): The coordinates of the item. Can either be Int or List[Int]. If Int is passed, it is the index of i-th item of the whole array. If List[Int] is passed, it is the coordinate of the item.
• item (ComplexSIMD): The scalar to be set.

Raises

conj

conj(self) -> Self

Return the complex conjugate of the ComplexNDArray.

Args:

• self (Self)

Returns:

• Self

Raises

to_ndarray

to_ndarray(self, type: String = "re") -> NDArray[ComplexNDArray[cdtype].dtype]

Args:

• self (Self)
• type (String)

Returns:

• NDArray

Raises

squeeze

squeeze(mut self, axis: Int)

Remove (squeeze) a single dimension of size 1 from the array shape.

Args:

• self (Self) [mut]
• axis (Int): The axis to squeeze. Supports negative indices.

Raises

IndexError: If the axis is out of range.

ShapeError: If the dimension at the given axis is not of size 1.

all

all(self) -> Bool

Check if all complex elements are non-zero.

A complex number is considered "true" if either its real or imaginary part is non-zero.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
# Fill with non-zero values
var result = A.all()  # True if all non-zero

Args:

• self (Self)

Returns:

• Bool

Raises

any

any(self) -> Bool

Check if any complex element is non-zero.

A complex number is considered "true" if either its real or imaginary part is non-zero.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
# Fill with some values
var result = A.any()  # True if any non-zero

Args:

• self (Self)

Returns:

• Bool

Raises

sum

sum(self) -> ComplexSIMD[cdtype]

Sum of all complex array elements.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var total = A.sum()  # Sum of all elements

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

prod

prod(self) -> ComplexSIMD[cdtype]

Product of all complex array elements.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var product = A.prod()  # Product of all elements

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

mean

mean(self) -> ComplexSIMD[cdtype]

Mean (average) of all complex array elements.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var average = A.mean()  # Mean of all elements

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

max

max(self) -> ComplexSIMD[cdtype]

Find the complex element with maximum magnitude.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var max_elem = A.max()  # Element with largest magnitude

Notes: Returns the element with maximum |z| = sqrt(re^2 + im^2).

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

min

min(self) -> ComplexSIMD[cdtype]

Find the complex element with minimum magnitude.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var min_elem = A.min()  # Element with smallest magnitude

Notes: Returns the element with minimum |z| = sqrt(re^2 + im^2).

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

argmax

argmax(self) -> Int

Return the index of the element with maximum magnitude.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var idx = A.argmax()  # Index of element with largest magnitude

Notes: Compares by magnitude: |z| = sqrt(re^2 + im^2).

Args:

• self (Self)

Returns:

• Int

Raises

argmin

argmin(self) -> Int

Return the index of the element with minimum magnitude.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var idx = A.argmin()  # Index of element with smallest magnitude

Notes: Compares by magnitude: |z| = sqrt(re^2 + im^2).

Args:

• self (Self)

Returns:

• Int

Raises

cumsum

cumsum(self) -> Self

Cumulative sum of complex array elements.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(5))
var cumulative = A.cumsum()

Notes: For array [a, b, c, d], returns [a, a+b, a+b+c, a+b+c+d].

Args:

• self (Self)

Returns:

• Self

Raises

cumprod

cumprod(self) -> Self

Cumulative product of complex array elements.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(5))
var cumulative = A.cumprod()

Notes: For array [a, b, c, d], returns [a, a*b, a*b*c, a*b*c*d].

Args:

• self (Self)

Returns:

• Self

Raises

flatten

flatten(self, order: String = "C") -> Self

Return a copy of the array collapsed into one dimension.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 4))
var flat = A.flatten()  # Shape(12)

Args:

• self (Self)
• order (String): Order of flattening - 'C' for row-major or 'F' for column-major.

Returns:

• Self

Raises

fill

fill(mut self, val: ComplexSIMD[cdtype])

Fill all items of array with a complex value.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
A.fill(nm.ComplexSIMD[nm.cf64](1.0, 2.0))  # Fill with 1+2i

Args:

• self (Self) [mut]
• val (ComplexSIMD): Complex value to fill the array with.

row

row(self, id: Int) -> Self

Get the ith row of the matrix.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 4))
var first_row = A.row(0)  # Get first row

Args:

• self (Self)
• id (Int): The row index.

Returns:

• Self

Raises

Error: If ndim is greater than 2.

col

col(self, id: Int) -> Self

Get the ith column of the matrix.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 4))
var first_col = A.col(0)  # Get first column

Args:

• self (Self)
• id (Int): The column index.

Returns:

• Self

Raises

Error: If ndim is greater than 2.

clip

clip(self, a_min: Scalar[ComplexNDArray[cdtype].dtype], a_max: Scalar[ComplexNDArray[cdtype].dtype]) -> Self

Limit the magnitudes of complex values between [a_min, a_max].

Elements with magnitude less than a_min are scaled to have magnitude a_min. Elements with magnitude greater than a_max are scaled to have magnitude a_max. The phase (angle) of each complex number is preserved.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(10))
var clipped = A.clip(1.0, 5.0)  # Clip magnitudes to [1, 5]

Notes: Clips by magnitude while preserving phase angle.

Args:

• self (Self)
• a_min (Scalar): The minimum magnitude.
• a_max (Scalar): The maximum magnitude.

Returns:

• Self

Raises

round

round(self) -> Self

Round the real and imaginary parts of each element to the nearest integer.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(10))
# A contains e.g. 1.7+2.3i
var rounded = A.round()  # Returns 2.0+2.0i

Args:

• self (Self)

Returns:

• Self

Raises

T

Overload 1

T(self) -> Self

Transpose the complex array (reverse all axes).

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 4))
var A_T = A.T()  # Shape(4, 3)

Args:

• self (Self)

Returns:

• Self

Raises

Overload 2

T(self, axes: List[Int]) -> Self

Transpose the complex array according to the given axes permutation.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 3, 4))
var A_T = A.T([2, 0, 1])  # Shape(4, 2, 3)

Args:

• self (Self)
• axes (List): Permutation of axes (e.g., [1, 0, 2]).

Returns:

• Self

Raises

diagonal

diagonal(self, offset: Int = 0) -> Self

Extract the diagonal from a 2D complex array.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(4, 4))
var diag = A.diagonal()      # Main diagonal
var upper = A.diagonal(1)    # First upper diagonal

Args:

• self (Self)
• offset (Int): Offset from the main diagonal (0 for main diagonal).

Returns:

• Self

Raises

Error: If array is not 2D.

trace

trace(self) -> ComplexSIMD[cdtype]

Return the sum of the diagonal elements (trace of the matrix).

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 3))
var tr = A.trace()  # Sum of diagonal elements

Args:

• self (Self)

Returns:

• ComplexSIMD

Raises

Error: If array is not 2D.

tolist

tolist(self) -> List[ComplexSIMD[cdtype]]

Convert the complex array to a List of complex scalars.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 3))
var elements = A.tolist()  # List of 6 complex numbers

Args:

• self (Self)

Returns:

• List

num_elements

num_elements(self) -> Int

Return the total number of elements in the array.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(3, 4, 5))
print(A.num_elements())  # 60

Args:

• self (Self)

Returns:

• Int

resize

resize(mut self, shape: NDArrayShape)

Change shape and size of array in-place.

If the new shape requires more elements, they are filled with zero. If the new shape requires fewer elements, the array is truncated.

Examples:

import numojo as nm
var A = nm.ComplexNDArray[nm.cf64](nm.Shape(2, 3))
A.resize(nm.Shape(3, 4))  # Now 3x4, filled with zeros as needed

Notes: This modifies the array in-place. To get a reshaped copy, use reshape().

Args:

• self (Self) [mut]
• shape (NDArrayShape): The new shape for the array.

Raises