Merge pull request #1 from jhonsnow456/patch1-README

Patch1 readme

README.md

@@ -138,7 +138,7 @@ To test pull requests, use
 
 ## Regenerate Experimental <span class="title-ref">LaTeX</span> Parser/Lexer
 
-The parser and lexer generated with the [ANTLR4](http://antlr4.org)
+The parser and lexer were generated with the [ANTLR4](http://antlr4.org)
 toolchain in `sympy/parsing/latex/_antlr` and checked into the repo.
 Presently, most users should not need to regenerate these files, but
 if you plan to work on this feature, you will need the `antlr4`
@@ -197,7 +197,7 @@ on Stack Overflow using the [sympy](https://stackoverflow.com/questions/tagged/s
 
 SymPy was started by Ondřej Čertík in 2005, he wrote some code during
 the summer, then he wrote some more code during summer 2006. In February
-2007, Fabian Pedregosa joined the project and helped fixed many things,
+2007, Fabian Pedregosa joined the project and helped fix many things,
 contributed documentation, and made it alive again. 5 students (Mateusz
 Paprocki, Brian Jorgensen, Jason Gedge, Robert Schwarz, and Chris Wu)
 improved SymPy incredibly during summer 2007 as part of the Google
@@ -270,7 +270,7 @@ A BibTeX entry for LaTeX users is
 ```
 
 SymPy is BSD licensed, so you are free to use it whatever you like, be
-it academic, commercial, creating forks or derivatives, as long as you
+it academic, commercial, creating forks, or derivatives, as long as you
 copy the BSD statement if you redistribute it (see the LICENSE file for
 details). That said, although not required by the SymPy license, if it
 is convenient for you, please cite SymPy when using it in your work and

sympy/tensor/array/expressions/conv_array_to_matrix.py

@@ -4,6 +4,7 @@
 from functools import singledispatch
 from itertools import accumulate
 
+from sympy import MatMul, Basic
 from sympy.assumptions.ask import (Q, ask)
 from sympy.core.mul import Mul
 from sympy.core.singleton import S
@@ -129,6 +130,43 @@ def _support_function_tp1_recognize(contraction_indices, args):
     return editor.to_array_contraction()
 
 
+def _find_trivial_matrices_rewrite(expr: ArrayTensorProduct):
+    # If there are matrices of trivial shape in the tensor product (i.e. shape
+    # (1, 1)), try to check if there is a suitable non-trivial MatMul where the
+    # expression can be inserted.
+
+    # For example, if "a" has shape (1, 1) and "b" has shape (k, 1), the
+    # expressions "ArrayTensorProduct(a, b*b.T)" can be rewritten as
+    # "b*a*b.T"
+
+    trivial_matrices = []
+    pos: Optional[int] = None
+    first: Optional[MatrixExpr] = None
+    second: Optional[MatrixExpr] = None
+    removed: List[int] = []
+    counter: int = 0
+    args: List[Optional[Basic]] = [i for i in expr.args]
+    for i, arg in enumerate(expr.args):
+        if isinstance(arg, MatrixExpr):
+            if arg.shape == (1, 1):
+                trivial_matrices.append(arg)
+                args[i] = None
+                removed.extend([counter, counter+1])
+            elif pos is None and isinstance(arg, MatMul):
+                margs = arg.args
+                for j, e in enumerate(margs):
+                    if isinstance(e, MatrixExpr) and e.shape[1] == 1:
+                        pos = i
+                        first = MatMul.fromiter(margs[:j+1])
+                        second = MatMul.fromiter(margs[j+1:])
+                        break
+        counter += get_rank(arg)
+    if pos is None:
+        return expr, []
+    args[pos] = (first*MatMul.fromiter(i for i in trivial_matrices)*second).doit()
+    return ArrayTensorProduct(*[i for i in args if i is not None]), removed
+
+
 @singledispatch
 def _array2matrix(expr):
     return expr
@@ -369,7 +407,11 @@ def _(expr: ArrayTensorProduct):
         else:
             newargs.append(arg)
             pending = None
-    return _a2m_tensor_product(*newargs), sorted(removed)
+    newexpr, newremoved = _a2m_tensor_product(*newargs), sorted(removed)
+    if isinstance(newexpr, ArrayTensorProduct):
+        newexpr, newremoved2 = _find_trivial_matrices_rewrite(newexpr)
+        newremoved = _combine_removed(-1, newremoved, newremoved2)
+    return newexpr, newremoved
 
 
 @_remove_trivial_dims.register(ArrayAdd) # type: ignore

sympy/tensor/array/expressions/tests/test_convert_array_to_matrix.py

@@ -14,7 +14,7 @@
 from sympy.matrices import Trace, MatMul, Transpose
 from sympy.tensor.array.expressions.array_expressions import ZeroArray, OneArray, \
     ArrayTensorProduct, ArrayAdd, PermuteDims, ArrayDiagonal, \
-    ArrayContraction, ArrayElement
+    ArrayContraction, ArrayElement, ArraySymbol
 from sympy.testing.pytest import raises
 
 
@@ -393,6 +393,19 @@ def test_arrayexpr_convert_array_to_matrix_remove_trivial_dims():
     assert ret == PermuteDims(ArrayContraction(ArrayTensorProduct(A, B, C, M), (3, 4)), [0, 2, 3, 4, 5, 1])
     assert removed == []
 
+    # Trivial matrices are sometimes inserted into MatMul expressions:
+
+    cg = ArrayTensorProduct(b*b.T, a.T*a)
+    ret, removed = _remove_trivial_dims(cg)
+    assert ret == b*a.T*a*b.T
+    assert removed == [2, 3]
+
+    Xs = ArraySymbol("X", (3, 2, k))
+    cg = ArrayTensorProduct(M, Xs, b.T*c, a*a.T, b*b.T, c.T*d)
+    ret, removed = _remove_trivial_dims(cg)
+    assert ret == ArrayTensorProduct(M, Xs, a*b.T*c*c.T*d*a.T, b*b.T)
+    assert removed == [5, 6, 11, 12]
+
 
 def test_arrayexpr_convert_array_to_matrix_diag2contraction_diagmatrix():
     cg = ArrayDiagonal(ArrayTensorProduct(M, a), (1, 2))