Merge pull request #1769 from graphistry/release/0.58.0-changelog

docs(changelog): cut 0.58.0

Merge pull request #1659 from graphistry/dev/v0.57.0

Release v0.57.0

Merge pull request #1646 from graphistry/dev/v0.56.1

Release 0.56.0

chore(release): cut 0.55.1 changelog section (#1323)

chore(release): cut 0.55.0 changelog section (#1315)

docs(changelog): cut 0.54.1 (#1105)

feat(layout): built-in treemap layout, remove external dep, vectorize…

… transforms (#1059)

* feat(layout): replace external treemap layout dep with built-in vectorized implementation

- Add graphistry/layout/gib/_squarify.py: pure Python + numpy squarified
  treemap layout algorithm (normalize_sizes + squarify + internal helpers)
- Wire treemap.py to use the built-in implementation
- Remove third-party dep from setup.py and mypy.ini
- Add graphistry/tests/layout/test_treemap.py: 356 unit tests covering
  normalize_sizes, squarify geometry invariants, strip-loop boundary
  conditions, float-accumulation stress, numpy array inputs, and
  treemap() end-to-end integration; cross-validated against reference

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* perf(layout): remove numpy dep from treemap layout; use built-in sum()

np.sum() has ~3µs per-call overhead on small lists vs Python's sum() at ~100ns.
Switching to sum() restores performance parity with the removed external dep
(1.00-1.03x across n=2-500 partitions, verified on local + dgx-spark).
Also removes the now-unnecessary numpy import from _squarify.py.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* perf(treemap): vectorize coordinate transforms + add layout benchmark

Replace four per-row dict .map() lookups in partitioned_layout.py with
two vectorized DataFrame merges (normalize + global positioning), giving
O(nodes) work in a single join instead of 4× serial Python dict scans.

Also fix treemap.py to compute partition_ids once outside the
comprehension (was calling reset_index() inside the loop).

Add benchmarks/layout/treemap.py with pre-resident data design:
- DataFrame built once before timing loop (measures only treemap() call)
- CPU=pandas in memory, GPU=cuDF on device (when available)
- Algorithm-only sweep (ref vs built-in) + E2E sweep (cpu vs gpu)
- RESULTS.md written alongside script

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* perf(treemap): update RESULTS.md with GPU benchmark from dgx-spark

E2E numbers with pre-resident data (pandas in-memory vs cuDF on-device):
- CPU baseline: ~250µs (3× faster than pre-vectorization ~800µs)
- GPU crossover: ~50k total nodes; at 500k nodes GPU is 1.30× faster
- Algorithm-only: 1.00–1.02× parity with reference across n=2–500

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(treemap): use engine-native DataFrame for offsets; gitignore RESULTS.md

- partitioned_layout.py: replace pd.DataFrame(partition_offsets) with
  df_cons(engine)(partition_offsets) so the offsets table is cuDF-native
  on the GPU path, not a pandas frame merged into a cuDF DataFrame
- benchmarks/layout/.gitignore: exclude RESULTS.md (machine-specific output)
- git rm benchmarks/layout/RESULTS.md (not source, belongs in .gitignore)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore(release): promote Development to 0.54.0 in CHANGELOG

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(treemap): avoid suffix collision in global-transform merge

Rename offsets columns to ox/oy/odx/ody before merging so columns that
only exist on the right side (dx, dy) don't silently drop their suffix.
Previously dx/dy came through unsuffixed (no collision) while x/y got
_local/_offset suffixes, causing KeyError: 'dx_offset' at runtime.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>

docs(changelog): cut 0.53.16

docs(changelog): cut 0.53.15

Move #994/#997/#998 entries from 0.53.13 section (where squash merge
placed them) to new 0.53.15 release section.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>