Transpose¶
Status: Stable
documented, exercised by the test suite and/or worked examples, with no known limitations recorded.
Description¶
Transpose[list]
Transposes the first two levels of list (swaps rows and columns of a matrix).
Transpose[list, {n1, n2, ...}]
Gives the transpose of list so that level k in list is level nk in the result. The spec must be a permutation of {1, ..., r} where r is the depth of list. A repeated index (e.g. {1, 1}) selects the corresponding diagonal. list must be a rectangular array.
Examples (7)¶
Every input below was run against the current Mathilda build and its output recorded.
Basic examples (2)¶
In[1]:= Transpose[{{a, b}, {c, d}}]
Out[1]= {{a, c}, {b, d}}
In[2]:= Transpose[{{a, b}, {c, d}}, {1, 1}]
Out[2]= {a, d}
Applications (5)¶
In[3]:= Transpose[{{1, 2, 3}, {4, 5, 6}}]
Out[3]= {{1, 4}, {2, 5}, {3, 6}}
In[4]:= Transpose[{{1, 2}, {3, 4}}]
Out[4]= {{1, 3}, {2, 4}}
In[5]:= Transpose[{{1, 2, 3}, {4, 5, 6}, {7, 8, 9}}, {1, 1}]
Out[5]= {1, 5, 9}
In[6]:= Transpose[{{a, b, c}, {d, e, f}}] . {{a, b, c}, {d, e, f}}
Out[6]= {{a^2 + d^2, a b + d e, a c + d f}, {a b + d e, b^2 + e^2, b c + e f}, {a c + d f, b c + e f, c^2 + f^2}}
In[7]:= m = {{0, 1, 2}, {-1, 0, 3}, {-2, -3, 0}}; m + Transpose[m]
Out[7]= {{0, 0, 0}, {0, 0, 0}, {0, 0, 0}}
Performance¶
Against other systems, from the benchmark suite (same input, results cross-checked for agreement):
| case | Mathilda | Wolfram | Python |
|---|---|---|---|
| Transpose then Dot (fused?) | 37.1 s | 63.1 s | 18.6 s |
| Partition window 8, offset 1 | 2.39 s | 32.7 s | 5.24 s |
| Transpose 2000x2000 | 1.58 s | 0.736 s | 2.73 s |
| Take rows 1;;1000 of 2000x2000 | 0.215 s | 0.275 s | 0.213 s |
| column slice m[[All, 1]] | 0.004 s | 0.007 s | 0.001 s |
| ArrayReshape 2x10^6 to 1000x2000 | -- | 0.119 s | 0.216 s |
Implementation notes¶
Algorithm. builtin_transpose swaps the levels of a rectangular nested-List array. It
measures the array shape with get_array_dimensions (requiring depth ≥ 2 and rectangularity),
then either uses the default permutation {2, 1, 3, …} (one-argument form swaps the first two
levels) or the explicit permutation given as the second argument. build_transposed recursively
materialises the output array by mapping each output index path back to an input index path
through the permutation and copying the leaf via get_element_at. For a 2-D matrix (list of
rows) this is the ordinary m[i][j] -> m[j][i] swap. Returns NULL (unevaluated) for
non-rectangular or non-List inputs. ConjugateTranspose is Conjugate[Transpose[...]].
Protected.- Works only on rectangular arrays.
Transpose[m, {1, 1}]extracts the diagonal of a square matrix.
Attributes: Protected.
References¶
- R. A. Horn and C. R. Johnson, Matrix Analysis, 2nd ed., Cambridge University Press, 2013 — the matrix transpose and index permutations of tensors.
- Source:
src/list.c - Specification:
docs/spec/builtins/structural-manipulation.md - Tests:
tests/test_compile.c - Tests:
tests/test_conjugate_transpose.c - Tests:
tests/test_fit.c - Tests:
tests/test_hankelmatrix.c
Notes & additional examples¶
Notes¶
With one argument Transpose swaps the first two levels of a list, turning a 2x3 matrix into a 3x2 one. The optional permutation spec generalises this to arbitrary index reorderings of a rectangular array. A repeated index in the spec — {1, 1} in the third example — extracts the corresponding diagonal, here the main diagonal {1, 5, 9} of the 3x3 matrix. The spec must be a permutation of {1, ..., r} where r is the depth of the list.