Nick/matlab support (#360)

* Internal: Try new link checker

* Internal: Add codespell and fix typos.

* Internal: See if codespell precommit finds config.

* Internal: Found config. Now enable reading it

* MATLAB: Add initial support for more matlab support.

Closes #350

pyttb/__init__.py

@@ -19,6 +19,7 @@
 from pyttb.import_data import import_data
 from pyttb.khatrirao import khatrirao
 from pyttb.ktensor import ktensor
+from pyttb.matlab import matlab_support
 from pyttb.sptenmat import sptenmat
 from pyttb.sptensor import sptendiag, sptenrand, sptensor
 from pyttb.sptensor3 import sptensor3
@@ -51,6 +52,7 @@ def ignore_warnings(ignore=True):
     import_data.__name__,
     khatrirao.__name__,
     ktensor.__name__,
+    matlab_support.__name__,
     sptenmat.__name__,
     sptendiag.__name__,
     sptenrand.__name__,

pyttb/matlab/__init__.py

@@ -0,0 +1 @@
+"""Partial support of MATLAB users in PYTTB."""

pyttb/matlab/matlab_support.py

@@ -0,0 +1,38 @@
+"""A limited number of utilities to support users coming from MATLAB."""
+
+# Copyright 2024 National Technology & Engineering Solutions of Sandia,
+# LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
+# U.S. Government retains certain rights in this software.
+
+from typing import Optional, Union
+
+import numpy as np
+
+from pyttb.tensor import tensor
+
+from .matlab_utilities import _matlab_array_str
+
+PRINT_CLASSES = Union[tensor, np.ndarray]
+
+
+def matlab_print(
+    data: Union[tensor, np.ndarray],
+    format: Optional[str] = None,
+    name: Optional[str] = None,
+):
+    """Print data in a format more similar to MATLAB.
+
+    Arguments
+    ---------
+    data: Object to print
+    format: Numerical formatting
+    """
+    if not isinstance(data, (tensor, np.ndarray)):
+        raise ValueError(
+            f"matlab_print only supports inputs of type {PRINT_CLASSES} but got"
+            f" {type(data)}."
+        )
+    if isinstance(data, np.ndarray):
+        print(_matlab_array_str(data, format, name))
+        return
+    print(data._matlab_str(format, name))

pyttb/matlab/matlab_utilities.py

@@ -0,0 +1,68 @@
+"""Internal tools to aid in building MATLAB support.
+
+Tensor classes can use these common tools, where matlab_support uses tensors.
+matlab_support can depend on this, but tensors and this shouldn't depend on it.
+Probably best for everything here to be private functions.
+"""
+
+# Copyright 2024 National Technology & Engineering Solutions of Sandia,
+# LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
+# U.S. Government retains certain rights in this software.
+
+import textwrap
+from typing import Optional, Tuple, Union
+
+import numpy as np
+
+
+def _matlab_array_str(
+    array: np.ndarray,
+    format: Optional[str] = None,
+    name: Optional[str] = None,
+    skip_name: bool = False,
+) -> str:
+    """Convert numpy array to string more similar to MATLAB."""
+    if name is None:
+        name = type(array).__name__
+    header_str = ""
+    body_str = ""
+    if len(array.shape) > 2:
+        matlab_str = ""
+        # Iterate over all possible slices (in Fortran order)
+        for index in np.ndindex(
+            array.shape[2:][::-1]
+        ):  # Skip the first two dimensions and reverse the order
+            original_index = index[::-1]  # Reverse the order back to the original
+            # Construct the slice indices
+            slice_indices: Tuple[Union[int, slice], ...] = (
+                slice(None),
+                slice(None),
+                *original_index,
+            )
+            slice_data = array[slice_indices]
+            matlab_str += f"{name}(:,:, {', '.join(map(str, original_index))}) ="
+            matlab_str += "\n"
+            array_str = _matlab_array_str(slice_data, format, name, skip_name=True)
+            matlab_str += textwrap.indent(array_str, "\t")
+            matlab_str += "\n"
+        return matlab_str[:-1]  # Trim extra newline
+    elif len(array.shape) == 2:
+        header_str += f"{name}(:,:) ="
+        for row in array:
+            if format is None:
+                body_str += " ".join(f"{val}" for val in row)
+            else:
+                body_str += " ".join(f"{val:{format}}" for val in row)
+            body_str += "\n"
+    else:
+        header_str += f"{name}(:) ="
+        for val in array:
+            if format is None:
+                body_str += f"{val}"
+            else:
+                body_str += f"{val:{format}}"
+            body_str += "\n"
+
+    if skip_name:
+        return body_str
+    return header_str + "\n" + textwrap.indent(body_str[:-1], "\t")

pyttb/tensor.py

@@ -7,6 +7,7 @@
 from __future__ import annotations
 
 import logging
+import textwrap
 from collections.abc import Iterable
 from inspect import signature
 from itertools import combinations_with_replacement, permutations
@@ -30,6 +31,7 @@
 from scipy import sparse
 
 import pyttb as ttb
+from pyttb.matlab.matlab_utilities import _matlab_array_str
 from pyttb.pyttb_utils import (
     IndexVariant,
     OneDArray,
@@ -2723,6 +2725,23 @@ def __repr__(self):
 
     __str__ = __repr__
 
+    def _matlab_str(
+        self, format: Optional[str] = None, name: Optional[str] = None
+    ) -> str:
+        """Non-standard representation to be more similar to MATLAB."""
+        header = name
+        if name is None:
+            name = "data"
+        if header is None:
+            header = "This"
+
+        matlab_str = f"{header} is a tensor of shape " + " x ".join(
+            map(str, self.shape)
+        )
+
+        array_str = _matlab_array_str(self.data, format, name)
+        return matlab_str + "\n" + textwrap.indent(array_str, "\t")
+
 
 def tenones(shape: Shape, order: Union[Literal["F"], Literal["C"]] = "F") -> tensor:
     """Create a tensor of all ones.

tests/matlab/test_matlab_support.py

@@ -0,0 +1,44 @@
+# Copyright 2024 National Technology & Engineering Solutions of Sandia,
+# LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
+# U.S. Government retains certain rights in this software.
+
+import numpy as np
+import pytest
+
+from pyttb import matlab_support, tensor
+
+
+def test_matlab_printing_negative():
+    with pytest.raises(ValueError):
+        matlab_support.matlab_print("foo")
+
+
+def test_np_printing():
+    """These are just smoke tests since formatting needs manual style verification."""
+    # Check different dimensionality support
+    one_d_array = np.ones((1,))
+    matlab_support.matlab_print(one_d_array)
+    two_d_array = np.ones((1, 1))
+    matlab_support.matlab_print(two_d_array)
+    three_d_array = np.ones((1, 1, 1))
+    matlab_support.matlab_print(three_d_array)
+
+    # Check name and format
+    matlab_support.matlab_print(one_d_array, format="5.1f", name="X")
+    matlab_support.matlab_print(two_d_array, format="5.1f", name="X")
+    matlab_support.matlab_print(three_d_array, format="5.1f", name="X")
+
+
+def test_dense_printing():
+    """These are just smoke tests since formatting needs manual style verification."""
+    # Check different dimensionality support
+    example = tensor(np.arange(16), shape=(2, 2, 2, 2))
+    # 4D
+    matlab_support.matlab_print(example)
+    # 2D
+    matlab_support.matlab_print(example[:, :, 0, 0])
+    # 1D
+    matlab_support.matlab_print(example[:, 0, 0, 0])
+
+    # Check name and format
+    matlab_support.matlab_print(example, format="5.1f", name="X")