sgpykit.util.misc

Functions

append(some_list, item)	Append an item to a list and return as a numpy array.
apply_lev2knots(i, lev2knots[, N])	Apply level-to-knots mapping to an index array.
contextmanager(func)	@contextmanager decorator.
generate_multi_indices(shape[, min_idx])	Generate all multi-indices for a given shape.
get_shape_of_cells(objects)	Get the shape of the first Cell object in the list of objects.
is_int_nan(values)	Check if values are the integer NaN workaround.
is_numeric_scalar(item)	Check if an item is a numeric scalar.
matlab_to_python_index(var)	Convert MATLAB-style index to Python-style index.
merge_all_args_to_kwargs(args, kwargs[, ...])	Merge positional and keyword arguments into a single dictionary.
print_plain_int(x)	Print integer values in a plain format.
python_to_matlab_index(var)	Convert Python-style index to MATLAB-style index.
reshape_nested_lists_to_nrows(obj[, nrows])	Reshape nested lists to a specified number of rows.
safe_vstack(*arrays)	Safely stack arrays vertically, filtering out empty arrays.
time_block([description])	Measure and print the execution time of a code block.
to_array(item, n)	Create an array of length n with the given item.
unique_rows_stable(A, B)	Find unique rows in the combined array of A and B, maintaining order.

Classes

Cell(shape[, dtype])

A 1D or 2D container class that extends Python's built-in list.

sgpykit.util.misc.append(some_list, item)

Append an item to a list and return as a numpy array.

Parameters:

some_listlist

List to append to.

itemany

Item to append.

Returns:

numpy.ndarray

Array with the item appended.

sgpykit.util.misc.apply_lev2knots(i, lev2knots, N=None)

Apply level-to-knots mapping to an index array.

Parameters:

inumpy.ndarray

Array of 0-based indices.

lev2knotslist or Cell or callable

Level-to-knots mapping function or list of functions.

Nint, optional

Number of dimensions (default is None).

Returns:

numpy.ndarray

Mapped indices.

sgpykit.util.misc.generate_multi_indices(shape, min_idx=0)

Generate all multi-indices for a given shape.

Parameters:

shapetuple

Shape of the multi-indices to generate.

min_idxint, optional

Minimum index value (default is 0).

Returns:

numpy.ndarray

Array of multi-indices.

sgpykit.util.misc.get_shape_of_cells(objects)

Get the shape of the first Cell object in the list of objects.

Parameters:

objectslist

List of objects to check for Cell type and shape.

Returns:

numpy.ndarray or None

Shape of the first Cell object found, or None if no Cell object is found.

sgpykit.util.misc.is_int_nan(values)

Check if values are the integer NaN workaround.

Parameters:

valuesnumpy.ndarray

Values to check.

Returns:

numpy.ndarray

Boolean array indicating which values are the integer NaN workaround.

sgpykit.util.misc.matlab_to_python_index(var)

Convert MATLAB-style index to Python-style index.

Parameters:

varint or numpy.ndarray

MATLAB-style index or array of indices.

Returns:

int or numpy.ndarray

Python-style index or array of indices.

sgpykit.util.misc.merge_all_args_to_kwargs(args, kwargs, to_lowercase=False)

Merge positional and keyword arguments into a single dictionary.

Parameters:

argslist

Positional arguments.

kwargsdict

Keyword arguments.

to_lowercasebool, optional

Convert keys to lowercase (default is False).

Returns:

tuple

Tuple of merged keyword arguments and format string.

sgpykit.util.misc.print_plain_int(x)

Print integer values in a plain format.

Parameters:

xint or list or tuple

Integer or list/tuple of integers to print.

sgpykit.util.misc.python_to_matlab_index(var)

Convert Python-style index to MATLAB-style index.

Parameters:

varint or array-like

Python-style index or array of indices.

Returns:

int or numpy.ndarray

MATLAB-style index or array of indices.

sgpykit.util.misc.reshape_nested_lists_to_nrows(obj, nrows=2)

Reshape nested lists to a specified number of rows.

Parameters:

objlist

Nested list to reshape.

nrowsint, optional

Number of rows (default is 2).

Returns:

list

Reshaped list.

sgpykit.util.misc.safe_vstack(*arrays)

Safely stack arrays vertically, filtering out empty arrays.

Parameters:

*arraysnumpy.ndarray

Arrays to stack.

Returns:

numpy.ndarray

Stacked array.

sgpykit.util.misc.time_block(description='')

Measure and print the execution time of a code block.

Args:

description (str): Optional description of the timed block.

sgpykit.util.misc.to_array(item, n)

Create an array of length n with the given item.

Parameters:

itemany

Item to repeat.

nint

Length of the array.

Returns:

list

Array of length n with the given item.

sgpykit.util.misc.unique_rows_stable(A, B)

Find unique rows in the combined array of A and B, maintaining order.

Parameters:

Anumpy.ndarray

First array.

Bnumpy.ndarray

Second array.

Returns:

numpy.ndarray

Array of unique rows.