Added CRAN-safe Smart-Grid Smart-City (SGSC) support
through elcf4r_download_sgsc(),
elcf4r_read_sgsc() and the compact shipped example panel
elcf4r_sgsc_example. The full Data.gov.au 7zip archive and
extracted raw CSV are not redistributed and are never downloaded by
examples, tests or vignettes.
elcf4R 0.4.2
Added package DOI.
elcf4R 0.4.0
Added scaffolded download/read support for IDEAL through
elcf4r_download_ideal() and
elcf4r_read_ideal(), focused on extracted hourly
aggregate-electricity summaries from
auxiliarydata.zip.
Added scaffolded download/read support for GX through
elcf4r_download_gx() and elcf4r_read_gx(),
with support for either the official SQLite database or flat exports
normalized into the common panel schema.
Added offline tests for IDEAL and GX download-resolution helpers and
normalization readers, including GX SQLite-table detection.
Updated package docs and the dataset vignette to describe IDEAL as
an unshipped household-level scaffold under the current
CC BY 4.0 source record, and GX as an unshipped secondary
transformer/community-level scaffold with explicit licence
re-verification guidance before redistribution.
Removed implicit RETICULATE_PYTHON mutation from the
LSTM backend probe and added explicit, user-driven Python selection
through elcf4r_use_tensorflow_env().
Tightened CRAN-facing package metadata and examples, including a
shorter elcf4r_benchmark() help example that runs on a toy
single-entity panel.
elcf4R 0.3.0
Replaced the previous KWF baseline with a wavelet-based
implementation using wavelets, deterministic calendar
groups, kernel weighting and approximation/detail mean correction.
Replaced the unused src/kwf_core.cpp placeholder with
compiled KWF helper routines for distances, kernel weights, group
restriction and mean-corrected forecasts, and wired the R KWF path to
those accelerators.
Added a first-class clustered KWF workflow with thermosensitivity
classification, wavelet-feature clustering helpers, cluster assignment,
and a dedicated elcf4r_fit_kwf_clustered() model path.
Generalized dataset ingestion around a common normalized panel
schema and added dataset adapters for iFlex, StoreNet, Low Carbon London
and REFIT.
Implemented elcf4r_download_storenet() with figshare
API resolution for known household article IDs and an archive fallback
for broader StoreNet retrieval.
Added a generic rolling-origin benchmark API through
elcf4r_build_benchmark_index() and
elcf4r_benchmark(), with saved predictions, backend
metadata and support for gam, mars,
kwf, kwf_clustered and lstm.
Completed benchmark metric coverage so shipped benchmark artifacts
now carry populated NMAE, NRMSE, sMAPE and MASE values for all shipped
result rows.
Added shipped example panels and saved benchmark-result datasets for
StoreNet, Low Carbon London and REFIT, complementing the existing iFlex
example and benchmark artifacts.
Expanded the shipped benchmark cohorts to stronger rolling windows:
iFlex now uses 15 households with 28 train days and 7 test days; the
shipped LCL and REFIT benchmark cohorts are now filtered to
thermosensitive seasonal windows so kwf_clustered rows are
benchmarked rather than skipped.
Reworked dataset-facing documentation to describe the supported
reader surface, shipped artifacts and reproducible
data-raw/ rebuild scripts.
Clarified the dataset roadmap around IDEAL and GX: IDEAL is a future
candidate dataset with a currently verified CC BY 4.0 source record,
while GX is treated as a secondary transformer-level benchmark candidate
that requires explicit licence re-verification before any shipped subset
is added.
elcf4R 0.2.0
Added an iFlex preprocessing pipeline with normalized panel readers,
daily-segment builders, compact shipped example data, and saved
benchmark result datasets.
Added package documentation and vignettes for the shipped iFlex
workflows and benchmark outputs, and documented the bundled
elcf4r_elmas_toy dataset.
Replaced the placeholder KWF/LSTM paths with working model wrappers,
unified predict.elcf4r_model(), and migrated the LSTM
implementation to keras3 with automatic detection of the
r-tensorflow virtualenv.
Cleaned up package metadata, namespace declarations, tests, and
examples so package checks now pass apart from environment-specific CRAN
notes.
elcf4R 0.1.0
Package creation and initial release containing estimators, autoplot
helpers, and reliability utilities.