Batch modernization phase 1: offline BatchPCA, dataset loaders, converter completion

CHANGELOG.md

@@ -11,6 +11,37 @@ those changes.
 
 ## [Unreleased]
 
+## [1.55.0] - 2026-07-16
+
+### Added
+
+- `batch.BatchPCA`: batchwise-unfolded (multiway) PCA for batch trajectory
+  data. Unfolds an aligned batch-data dictionary batchwise (one row per batch),
+  optionally joins an initial-conditions (Z) block onto that row, mean-centres
+  and scales every column, and fits the existing `multivariate.PCA` by
+  composition. Exposes batch-level scores, SPE and Hotelling's T2 with control
+  limits, plus contribution and score/SPE/loading plot forwarders. This is the
+  Nomikos-MacGregor batch monitoring model.
+- `batch.time_varying_loading_plot` and `batch.contribution_at_time_plot`: two
+  plotly plots for the unfolded model, showing a component's loadings over time
+  (one trace per tag) and the per-tag contribution to SPE or T2 at a chosen
+  time sample.
+- `batch.load_nylon`, `batch.load_dryer`, and `batch.load_batch_fake_data`:
+  loader functions returning the bundled batch datasets as the standard
+  batch-data dictionary.
+
+### Changed
+
+- The `batch.data_input` converters `melted_to_wide`, `wide_to_dict`, and
+  `wide_to_melted` are now implemented (they previously returned an empty
+  dict / frame / `None`). They compose the existing conversions and round-trip
+  with `dict_to_wide` / `dict_to_melted`.
+
+### Fixed
+
+- `batch.plotting.plot_to_HTML` now passes the correct `responsive` Plotly
+  config key (previously the misspelled `resonsive` was silently ignored).
+
 ## [1.54.0] - 2026-07-13
 
 ### Changed
@@ -2509,7 +2540,8 @@ this entry records them together.
 - Reworked the README with a sharper value proposition and a
   "Why not scikit-learn?" comparison table.
 
-[Unreleased]: https://github.com/kgdunn/process-improve/compare/v1.54.0...HEAD
+[Unreleased]: https://github.com/kgdunn/process-improve/compare/v1.55.0...HEAD
+[1.55.0]: https://github.com/kgdunn/process-improve/compare/v1.54.0...v1.55.0
 [1.54.0]: https://github.com/kgdunn/process-improve/compare/v1.53.0...v1.54.0
 [1.53.0]: https://github.com/kgdunn/process-improve/compare/v1.52.4...v1.53.0
 [1.52.4]: https://github.com/kgdunn/process-improve/compare/v1.52.3...v1.52.4

CITATION.cff

@@ -12,8 +12,8 @@ authors:
 repository-code: "https://github.com/kgdunn/process-improve"
 url: "https://kgdunn.github.io/process-improve/"
 license: MIT
-version: 1.54.0
-date-released: "2026-07-13"
+version: 1.55.0
+date-released: "2026-07-16"
 keywords:
   - chemometrics
   - multivariate analysis

docs/api/batch.rst

@@ -1,6 +1,18 @@
 Batch Data Analysis
 ===================
 
+.. automodule:: process_improve.batch.datasets
+   :members:
+   :show-inheritance:
+
+.. autoclass:: process_improve.batch.BatchPCA
+   :members:
+   :show-inheritance:
+
+.. automodule:: process_improve.batch._batch_plots
+   :members:
+   :show-inheritance:
+
 .. automodule:: process_improve.batch.features
    :members:
    :undoc-members:

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "process-improve"
-version = "1.54.0"
+version = "1.55.0"
 description = 'Designed Experiments; Latent Variables (PCA, PLS, multivariate methods with missing data); Process Monitoring; Batch data analysis.'
 readme = "README.md"
 license = "MIT"

src/process_improve/batch/__init__.py

@@ -1,13 +1,24 @@
-"""Batch process data analysis: alignment, feature extraction, and visualization."""
+"""Batch process data analysis: alignment, feature extraction, modelling, and visualization."""
 
+from process_improve.batch._batch_pca import BatchPCA
+from process_improve.batch._batch_plots import (
+    contribution_at_time_plot,
+    time_varying_loading_plot,
+)
 from process_improve.batch.data_input import (
     check_valid_batch_dict,
     dict_to_melted,
     dict_to_wide,
     melted_to_dict,
     melted_to_wide,
+    wide_to_dict,
     wide_to_melted,
 )
+from process_improve.batch.datasets import (
+    load_batch_fake_data,
+    load_dryer,
+    load_nylon,
+)
 from process_improve.batch.features import (
     cross,
     f_agemax,
@@ -36,10 +47,13 @@
 )
 
 __all__ = [
+    # Modelling
+    "BatchPCA",
     # Preprocessing/alignment
     "batch_dtw",
     # Data input/conversion
     "check_valid_batch_dict",
+    "contribution_at_time_plot",
     "cross",
     "determine_scaling",
     "dict_to_melted",
@@ -63,8 +77,14 @@
     "f_std",
     "f_sum",
     "find_reference_batch",
+    # Dataset loaders
+    "load_batch_fake_data",
+    "load_dryer",
+    "load_nylon",
     "melted_to_dict",
     "melted_to_wide",
     "resample_to_reference",
+    "time_varying_loading_plot",
+    "wide_to_dict",
     "wide_to_melted",
 ]