🎉(deprecation) add plaid version in infos of Dataset and ProblemDefinition

.gitignore

@@ -5,9 +5,10 @@ tests/post/*.yaml
 tests/problem_definition/*.csv
 examples/**/*.png
 tests/problem_definition/split.csv
+
 # Heavy data
 *.cgns
-!notebooks/ex_rotor37_pv.cgns
+!tests/post/**/*.cgns
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -59,10 +60,6 @@ report.xml
 
 # VisualStudioCode
 .vscode/*
-!.vscode/settings.json
-!.vscode/tasks.json
-!.vscode/launch.json
-!.vscode/extensions.json
 *.code-workspace
 **/.vscode
 *-jvsc-*.ipynb

CHANGELOG.md

@@ -9,16 +9,21 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- (docs) explain release process in Contributing page
-
 ### Changed
 
+- (sample) Restructuring of the Sample class to store a global (tensor of arbitrary order) at a given time step: replaces scalar and time_series. All Sample data are now stored in CGNS trees.
 
 ### Fixes
 
+- (docs) explain release process in Contributing page
+
+### Changed
+
 
 ### Removed
 
+- (sample) time_series support, now handle directly globals at time steps.
+
 
 ## [0.1.9] - 2025-09-24
 

docs/source/core_concepts/dataset.md

@@ -63,7 +63,6 @@ ids = dataset.get_sample_ids()
 
 ```python
 dataset.get_scalar_names(ids=None)
-dataset.get_time_series_names(ids=None)
 dataset.get_field_names(ids=None, zone_name=None, base_name=None)
 
 # Structured, hashable descriptors of features (recommended)

docs/source/core_concepts/feature_identifiers.md

@@ -6,7 +6,7 @@ title: Feature identifiers
 
 Feature identifiers are a concise, unambiguous way to point to any feature in PLAID. They replace legacy name-only APIs (now deprecated) and make it possible to uniquely address features across time steps, bases, zones and locations.
 
-- A feature is one of: scalar, time_series, field, nodes.
+- A feature is one of: scalar, field, nodes.
 - A FeatureIdentifier is a small dictionary that encodes the feature type and, when relevant, its context (e.g., base, zone, location, time).
 
 Why this matters:
@@ -19,7 +19,6 @@ Why this matters:
 FeatureIdentifier is a `dict[str, str | float]` with a mandatory `type` key. Depending on the feature type, other keys are required or optional:
 
 - scalar: `{"type": "scalar", "name": <str>}`
-- time_series: `{"type": "time_series", "name": <str>}`
 - field: `{"type": "field", "name": <str>, "base_name": <str>, "zone_name": <str>, "location": <str>, "time": <float>}`
   - `location` must be one of: `Vertex`, `EdgeCenter`, `FaceCenter`, `CellCenter`.
   - `base_name`, `zone_name`, `location`, `time` are optional if default value mechanics apply (see {doc}`defaults`).
@@ -37,7 +36,6 @@ Minimal identifiers:
 from plaid.types import FeatureIdentifier
 
 fid_scalar = FeatureIdentifier({"type": "scalar", "name": "Re"})
-fid_ts     = FeatureIdentifier({"type": "time_series", "name": "load_curve"})
 
 fid_field = FeatureIdentifier({
     "type": "field",

docs/source/core_concepts/sample.md

@@ -6,7 +6,6 @@ title: Sample
 
 {py:class}`~plaid.containers.sample.Sample` represents one observation. It contains {doc}`feature_identifiers` among (all optional):
 - scalars: name → value
-- time series: name → (time_sequence, values)
 - meshes containing:
   - nodes: mesh node coordinates, that can be located:
     - in different bases
@@ -17,8 +16,8 @@ title: Sample
     - in different locations in each base/zone among: `Vertex`, `EdgeCenter`, `FaceCenter`, or `CellCenter`
 
 Key APIs include:
-- Feature accessors: {py:meth}`~plaid.containers.sample.Sample.get_scalar`, {py:meth}`~plaid.containers.sample.Sample.get_time_series`, {py:meth}`~plaid.containers.sample.Sample.get_field`, {py:meth}`~plaid.containers.sample.Sample.get_nodes`
-- Feature updates: {py:meth}`~plaid.containers.sample.Sample.add_scalar`, {py:meth}`~plaid.containers.sample.Sample.add_time_series`, {py:meth}`~plaid.containers.sample.Sample.add_field`, {py:meth}`~plaid.containers.sample.Sample.set_nodes`, and high-level identifier-based updates
+- Feature accessors: {py:meth}`~plaid.containers.sample.Sample.get_scalar`, {py:meth}`~plaid.containers.sample.Sample.get_field`, {py:meth}`~plaid.containers.sample.Sample.get_nodes`
+- Feature updates: {py:meth}`~plaid.containers.sample.Sample.add_scalar`, {py:meth}`~plaid.containers.sample.Sample.add_field`, {py:meth}`~plaid.containers.sample.Sample.set_nodes`, and high-level identifier-based updates
 - Discovery: {py:meth}`~plaid.containers.sample.Sample.get_all_features_identifiers()` or {py:meth}`~plaid.containers.sample.Sample.get_all_features_identifiers_by_type()` to list all available features with their context
 
 See also: {doc}`../notebooks` for hands-on examples.

environment.yml

@@ -1,6 +1,7 @@
 name: plaid-dev
 channels:
   - conda-forge
+  - nodefaults
 channel_priority: strict
 dependencies:
   - python=3.11
@@ -16,6 +17,7 @@ dependencies:
   - datasets >=3.0
   - numpy
   - matplotlib-base
+  - optree
 #---# data validation
   - pydantic
 ##### DEV/TESTS/EXAMPLES #####