[0.4.1] - 2026-06-13

Fixed

• split_by_date(): observation_days=N now produces an N-unit observation window
  [target_date - N + 1, target_date], restoring symmetry with evaluation_days=N
  (which produces the N-unit window [target_date + 1, target_date + N]).
  Previously observation_days=N produced an N+1-unit window
  [target_date - N, target_date] due to an off-by-one in the inclusive start
  boundary. Migration: if you previously called
  split_by_date(df, target_date, observation_days=N) and want the same
  observation window, pass observation_days=N+1.
• normalize_ref(): invalid string dates (e.g., "not a date") now consistently
  raise ValueError("time value could not be normalized: ..."). Previously the
  str-path bypassed the friendly error and surfaced a raw pandas error.
• Documentation: numerous accuracy fixes across docs/ (glossary, functional-design,
  product-requirements, architecture, repository-structure, development-guidelines)
  including terminology unification (閲覧, 累積対象イベント発生数), _plotting.py
  reference in the module / repository layout, Python 3.11 minimum requirement,
  and kind enum corrections for plot_probability_surface() /
  plot_marginal_probability().

Changed

• Internal refactor: extracted plot_probability_surface() and
  plot_marginal_probability() to a new private module src/rfscorer/_plotting.py
  as PlottingMixin. RecencyFrequencyScorer now inherits from PlottingMixin,
  so the public API (scorer.plot_*()) is preserved with no caller-visible change.
• Internal refactor: reorganized RecencyFrequencyScorer methods by typical
  workflow (Initialization → Fitting → Optimization → Inference → Evaluation →
  Export → Inspection → Internal helpers) and added section divider comments.
  No behavior change.