v0.4.0 — Load as first-class lifecycle phase + Xarray interoperability

What's new in 0.4.0

Breaking change — ModelExecutor.run signature

run(self, record) → run(self, data, record)

data is the direct return value of load(), injected by the platform.
Executors that called self.load(record) inside run() must remove that call
and receive the loaded data as the first argument instead.

Executor lifecycle orchestration

• New dissmodel/executor/runner.py with execute_lifecycle — the canonical
  validate → load → run → save loop, shared by the CLI and the platform
  job_runner. Each phase is timed independently and written to
  record.metrics (time_load_sec now visible separately from time_run_sec).
• execute_lifecycle exported from dissmodel.executor.
• ExecutorTestHarness updated to call load → run(data, record) in sequence
  and to reject the old one-parameter run signature with a clear error message.

RasterBackend — Xarray interoperability

• RasterBackend.to_xarray(time=None) — converts to xr.Dataset with (y, x)
  dimensions, spatial coordinates from rasterio Affine transform, and CRS as
  spatial_ref (CF-1.8 / rioxarray convention).
• RasterBackend.from_xarray(ds) — builds a backend from an xr.Dataset or
  xr.DataArray, recovering transform and CRS when available.
• RasterBackend.__init__ now accepts transform and crs keyword arguments.

Tests

Full executor test suite added under tests/executor/:
test_runner, test_registry, test_cli, test_testing — with
_isolate_registry autouse fixture preventing cross-test registry pollution.

Removed

• make_raster_grid() alias (deprecated since 0.3.0)
• regular_grid() alias (deprecated since 0.2.1)

---

Migration guide for executor authors:

# Before (0.3.x)
def run(self, record: ExperimentRecord):
    data = self.load(record)
    ...

# After (0.4.0)
def run(self, data, record: ExperimentRecord):
    # data injected by execute_lifecycle — no I/O here
    ...

Full changelog: CHANGELOG.md

v0.3.0

What's Changed

Added

Sync models — automatic .past snapshot semantics (equivalent to TerraME's cs:synchronize()):

• SyncSpatialModel — vector substrate, manages <col>_past columns automatically
• SyncRasterModel — raster substrate, manages <n>_past arrays automatically
• Both expose a public synchronize() method

I/O — dissmodel.geo.raster.io

• shapefile_to_raster_backend — load any vector file (Shapefile, GeoJSON, GPKG, ZIP) directly into a RasterBackend, with automatic "mask" band
• save_raster_backend — write arrays to GeoTIFF without a band_spec
• load_geotiff / save_geotiff updated with .zip support

RasterMap — new visualization options: scheme (equal_interval, quantiles), legend, auto_mask, save_frames

Map — headless fallback (saves PNGs), new figsize, interval, save_frames parameters

Fixed

• RasterMap: multiple instances now maintain independent windows — plt.close("all") no longer closes other figures
• Map: AttributeError: 'Map' object has no attribute 'fig' with Streamlit
• Map: no longer raises RuntimeError when no display is available
• make_raster_grid() deprecated → raster_grid() (alias kept until v0.4.0)

Full changelog: CHANGELOG.md

v0.2.1

What's Changed

API improvements

• parse_idx now returns GridPos(row, col) — a namedtuple that eliminates the
  (col, row) vs (row, col) ambiguity. Tuple unpacking remains fully compatible,
  so existing code continues to work without changes.
• regular_grid() renamed to vector_grid() for symmetry with the raster substrate.
  The old name is kept as a DeprecationWarning alias and will be removed in v0.3.0.
• GridPos is now exported from dissmodel.geo.vector.regular_grid.

Bug fixes

• Fixed TypeError: parameter 'kwargs' not allowed in RasterModel.setup() and
  RasterCellularAutomaton.setup() caused by a salabim incompatibility with **kwargs.

Documentation

• API reference split into api/geo/vector.md and api/geo/raster.md.
• getting_started.md expanded with execution modes and substrate comparison table.
• visualization.md updated to cover RasterMap.
• core.md expanded with OOP modeling section and per-model time control example.
• CHANGELOG.md updated.

Upgrade notes

# before
from dissmodel.geo import regular_grid
gdf = regular_grid(dimension=(30, 30), resolution=1)

# after
from dissmodel.geo.vector.regular_grid import vector_grid
gdf = vector_grid(dimension=(30, 30), resolution=1)

# parse_idx
from dissmodel.geo.vector.regular_grid import parse_idx
pos = parse_idx("3-4")
pos.row  # 3
pos.col  # 4

Full changelog: [CHANGELOG.md](https://github.com/lambdageo/dissmodel/blob/main/CHANGELOG.md)

Add Raster/NumPy Backend for Cellular Automata Models

This release introduces a RasterBackend that allows cellular automata models in DisSModel to run using NumPy arrays instead of iterating over GeoDataFrame rows.

The existing vector backend (GeoPandas + libpysal) remains unchanged. The raster backend is an optional execution engine behind the same API.

0.1.5

• Description:

## What's new in v0.1.5

- Consolidated all dependencies in `pyproject.toml`
- NumPy docstrings and type annotations across all modules
- All CA and SysDyn models refactored to English
- Fixed PATTERN fill ID convention (`row-col`)
- Performance: `neighbor_values()` in all CA rules
- Fixed `Environment` salabim animation crash in headless environments
- Added CLI, Streamlit and Jupyter notebook examples for all models
- MkDocs documentation with mkdocstrings
- CI workflow with pytest and mypy

0.1.4

Merge pull request #10 from profsergiocosta/doc

Doc

0.1.3b_fix

Update pyproject.toml