sgpykit.util.matlab

Functions

`ce`(*args)	Replacement for the matlab {} operator to create cells.
`cell`(shape)	Returns an empty cell (numpy) array with the given shape (empty nD-matrix).
`eig`(var)	Compute the eigenvalues and eigenvectors of a matrix.
`fieldnames`(s)	Get the field names of a Struct or StructArray.
`find`(X[, n, direction])	Find non-zero elements in an array.
`fliplr`(arr)	Flip the elements of the array from left to right.
`get_shape_of_cells`(objects)	Get the shape of the first Cell object in the list of objects.
`ifft`(arr)	Compute the inverse FFT of a 1D or 2D array, matching MATLAB's ifft() behavior.
`intersect`(x, y)	Find the intersection of two arrays.
`is_numeric_scalar`(item)	Check if an item is a numeric scalar.
`iscell`(var)	Check if the given variable is a Cell.
`isfield`(var, sel)	Check if the given field exists in the struct.
`isnumeric`(obj)	Check if the object is numeric.
`issorted`(matrix[, typ])	Check if the matrix is sorted.
`isstruct`(var)	Check if the given variable is an instance of Struct or StructArray.
`logical`(var)	Convert array to boolean (0=false, else=true).
`reshape`(var, r[, c])	Reshape an array.
`save`(filename, *args)	Save NumPy arrays to a MATLAB file.
`savemat`(file_name, mdict[, appendmat, ...])	Save a dictionary of names and arrays into a MATLAB-style .mat file.
`setdiff`(A, B[, kind])	Set difference of two arrays.
`sort`(arr[, axis, direction])	Sort an array in ascending or descending order.
`sortrows`(A)	Sort rows of a matrix in ascending order.
`struct`(args, *kwargs)	Create a Struct or StructArray from given arguments.
`unique`(var[, by])	Incomplete matlabs unique() function.

Classes

`Cell`(shape[, dtype])	A 1D or 2D container class that extends Python's built-in list.
`Sequence`()	All the operations on a read-only sequence.
`Struct`(**kwargs)	A simple struct-like class that allows attribute access and dictionary-like item access.
`StructArray`(args, *kwargs)

sgpykit.util.matlab.ce(*args)[source]

Replacement for the matlab {} operator to create cells. The cell elements must be of same data type.

Parameters:

*argstuple: Elements to be placed in the cell array.

Returns:

Cell: The created cell array.

sgpykit.util.matlab.cell(shape)[source]

Returns an empty cell (numpy) array with the given shape (empty nD-matrix).

2D cell objects can be flat indexed, e.g. c[0,2] or c[2]. Higher dimensions than 2D are not supported. If shape is a single integer N, create a NxN cell

Parameters:

shapeint or tuple: The shape of the cell array. If an integer, creates a square cell array.

Returns:

Cell: The empty cell array.

sgpykit.util.matlab.eig(var)[source]

Compute the eigenvalues and eigenvectors of a matrix.

Parameters:

vararray_like: Input matrix.

Returns:

tuple: Eigenvectors and eigenvalues.

sgpykit.util.matlab.fieldnames(s)[source]

Get the field names of a Struct or StructArray.

Parameters:

sStruct or StructArray: The struct or struct array.

Returns:

list: The list of field names.

sgpykit.util.matlab.find(X, n=None, direction='first')[source]

Find non-zero elements in an array.

Parameters:

Xarray_like: Input array.
nint, optional: Maximum number of elements to return. Default is None.
directionstr, optional: Direction to search (‘first’ or ‘last’). Default is ‘first’.

Returns:

tuple: Indices and values of non-zero elements.

sgpykit.util.matlab.fliplr(arr)[source]

Flip the elements of the array from left to right.

Parameters:

arrarray_like: Input array to be flipped.

Returns:

ndarray: Flipped array.

sgpykit.util.matlab.ifft(arr)[source]

Compute the inverse FFT of a 1D or 2D array, matching MATLAB’s ifft() behavior.

Parameters:

arrarray_like: A 1D or 2D numpy array.

Returns:

ndarray: The inverse FFT of the input array.

Raises:

ValueError: If the input array is not 1D or 2D.

sgpykit.util.matlab.intersect(x, y)[source]

Find the intersection of two arrays.

Parameters:

xarray_like: First input array.
yarray_like: Second input array.

Returns:

tuple: Common elements and their indices in the original arrays.

sgpykit.util.matlab.iscell(var)[source]

Check if the given variable is a Cell.

Parameters:

varany: The variable to check.

Returns:

bool: True if the variable is a Cell, False otherwise.

sgpykit.util.matlab.isfield(var, sel)[source]

Check if the given field exists in the struct.

Parameters:

varstr: The field name to check.
selStruct or StructArray: The struct or struct array.

Returns:

bool: True if the field exists, False otherwise.

sgpykit.util.matlab.isnumeric(obj)[source]

Check if the object is numeric.

Parameters:

objany: The object to check.

Returns:

bool: True if the object is numeric, False otherwise.

sgpykit.util.matlab.issorted(matrix, typ='rows')[source]

Check if the matrix is sorted.

Parameters:

matrixarray_like: Input matrix.
typstr, optional: Type of sorting to check. Default is ‘rows’.

Returns:

bool: True if the matrix is sorted, False otherwise.

sgpykit.util.matlab.isstruct(var)[source]

Check if the given variable is an instance of Struct or StructArray.

Parameters:

varany: The variable to check.

Returns:

bool: True if the variable is an instance of Struct or StructArray, False otherwise.

sgpykit.util.matlab.logical(var)[source]

Convert array to boolean (0=false, else=true).

Parameters:

vararray_like: Input array.

Returns:

ndarray: Boolean array.

sgpykit.util.matlab.reshape(var, r, c=None)[source]

Reshape an array.

Parameters:

vararray_like: Input array.
rint or array_like: New shape or number of rows.
cint, optional: Number of columns. Default is None.

Returns:

ndarray: Reshaped array.

sgpykit.util.matlab.save(filename, *args)[source]

Save NumPy arrays to a MATLAB file.

Parameters:

filenamestr: The name of the file to save.
*argstuple: Variable length argument list of strings and NumPy arrays. The first argument is the filename, followed by pairs of variable names and arrays.

sgpykit.util.matlab.setdiff(A, B, kind='rows')[source]

Set difference of two arrays.

Parameters:

Aarray_like: First input array.
Barray_like: Second input array.
kindstr, optional: Type of set difference (‘rows’ or others). Default is ‘rows’.

Returns:

ndarray: The set difference.

sgpykit.util.matlab.sort(arr, axis=None, direction='ascend')[source]

Sort an array in ascending or descending order.

Parameters:

arrarray_like: Input array.
axisint, optional: Axis along which to sort. Default is None.
directionstr, optional: Direction to sort (‘ascend’ or ‘descend’). Default is ‘ascend’.

Returns:

tuple: Sorted array and sorted indices.

sgpykit.util.matlab.sortrows(A)[source]

Sort rows of a matrix in ascending order.

Parameters:

Aarray_like: Input array.

Returns:

tuple: Sorted array and sorted indices.

sgpykit.util.matlab.struct(*args, **kwargs)[source]

Create a Struct or StructArray from given arguments.

This function mimics MATLAB’s struct behavior. If keyword arguments are provided, it creates a Struct with the given fields. If positional arguments are provided, it creates a Struct with fields from the even-indexed arguments and values from the odd-indexed arguments. If cells are detected, it creates a StructArray.

Parameters:

*argstuple: Positional arguments for field-value pairs.
**kwargsdict: Keyword arguments for field-value pairs.

Returns:

Struct or StructArray: The created struct or struct array.

sgpykit.util.matlab.unique(var, by=None)[source]

Incomplete matlabs unique() function.

https://de.mathworks.com/help/matlab/ref/double.unique.html - ‘first’ and ‘sorted’ are defaults https://numpy.org/doc/stable/reference/generated/numpy.unique.html#numpy-unique

Parameters:

vararray_like: Input array.
bystr, optional: The axis to return indices for repetitions. Default is None.

Returns:

tuple: The unique elements and their indices.