- Refactor label processing into 4 orthogonal phases:
1. Weighting: apply weights to raw label values per column
2. Smoothing: smooth weighted values per column
3. Pipeline: LabelTransformer standardization per column
4. Prediction: threshold calculation per column
- Loop over LABEL_COLUMNS for weighting and smoothing in set_freqai_targets()
- Loop over dk.label_list for thresholds in fit_live_predictions()
- All config helpers return {default, columns} structure with glob pattern support
- Rename ExtremaWeightingTransformer to LabelTransformer
- Harmonize namespace: label_weighting, label_smoothing, label_prediction
- Backward compatible with flat configs and legacy column names
* refactor: remove deprecated internal APIs
Remove unused deprecated functions that were replaced by the orthogonal
label processing architecture:
- get_label_transformer_config() from Utils.py
- get_label_transformer_config import from QuickAdapterV3.py
- extrema_smoothing property from QuickAdapterV3.py
* refactor: use DEFAULTS_LABEL_PREDICTION for outlier_quantile fallback
* refactor: make label weighting generic with metrics dict
- compute_label_weights() takes generic metrics dict instead of hardcoded params
- _compute_combined_weights() takes generic metrics dict
- apply_label_weighting() takes generic metrics dict
- Caller builds metrics dict, making weighting truly transverse to any label
* refactor: centralize deprecation handling with PARAM_DEPRECATIONS table
* refactor: call resolve_deprecated_params once at startup
- Change resolve_deprecated_params to modify dict in-place (returns None)
- Centralize all deprecation calls in bot_start() and __init__()
- Remove calls from properties and utility functions that run multiple times
- This ensures deprecation warnings are logged once, not repeatedly
* fix: resolve deprecations in __init__ before regressor loads
- Move deprecation resolution from bot_start() to Strategy.__init__()
so it runs before FreqaiModel.__init__() (which reads same config)
- Remove label_transformer legacy support (never released)
- Simplify label_weighting/label_pipeline properties
- Keep regressor-specific deprecations in regressor __init__
* fix: address PR review comments
- Fix label_weighting['strategy'] KeyError by using ['default']['strategy']
- Respect label_prediction.method='none' in min_max_pred()
- Use float('inf') specificity for exact matches in get_column_config
- Reuse Utils.get_column_config in LabelTransformer
- Default label_smoothing method to 'gaussian'
* refactor: unify threshold column naming and soft_extremum_alpha
- Remove MINIMA_THRESHOLD_COLUMN/MAXIMA_THRESHOLD_COLUMN constants
- Use uniform {label}_minima_threshold/{label}_maxima_threshold for all labels
- Rename internal soft_alpha to soft_extremum_alpha for consistency with config
- Remove redundant docstrings from LabelTransformer (code is self-documenting)
* refactor: cleanup docstrings and rename internal functions
* refactor: make label_pipeline orthogonal from label_weighting
* refactor: rename get_column_config to get_label_column_config
* fix: add missing method field to label_prediction logging
* refactor: per-column logging and deprecate label_smoothing.window
- Update logging in QuickAdapterV3 and QuickAdapterRegressorV3 to show
resolved per-column configs instead of just defaults with override keys
- Move get_label_column_config() to LabelTransformer.py (re-export from Utils)
- Add deprecation mapping for label_smoothing.window -> window_candles
- Fix extrema_direction undefined variable bug in populate_any_indicators
* fix: correct deprecation mappings for label_prediction params
* refactor: move label_pipeline property and logging to regressor
- Move label_pipeline property from QuickAdapterV3 strategy to QuickAdapterRegressorV3
- Move Pipeline configuration logging from _log_strategy_configuration() to
_log_model_configuration()
- Simplify define_label_pipeline() to use self.label_pipeline property
- Remove unused get_label_pipeline_config import from strategy
- Rename local variable label_weighting to label_weighting_raw for consistency
* fix: import get_label_column_config from LabelTransformer
Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>
* refactor(quickadapter): replace string literals with constant references in LabelTransformer
* refactor(quickadapter): use per-column prediction config in regressor and strategy
* fix: reference correct config paths for label processing
Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>
* fix(quickadapter): warn when column doesn't match any config pattern
* feat(deprecation): support cross-section parameter moves
Extend PARAM_DEPRECATIONS to handle parameters that moved between
config sections, not just renames within the same section.
- Add tuple[str, str] value type for (old_section, old_key) moves
- Add root_config parameter to resolve_deprecated_params()
- Add deprecation entries for 7 params moved from label_weighting
to label_pipeline: standardization, robust_quantiles,
mmad_scaling_factor, normalization, minmax_range, sigmoid_scale,
gamma
- Add call sites in QuickAdapterV3 and QuickAdapterRegressorV3
* refactor(quickadapter): replace imperative deprecation handling with declarative path-based migrations
- Replace PARAM_DEPRECATIONS dict and resolve_deprecated_params() with
CONFIG_MIGRATIONS tuple and migrate_config()
- Single migrate_config() call in __init__ replaces 6+ resolve_deprecated_params() calls
- Fix bug in set_freqai_targets: move maxima/minima column creation after weighting
- Fix DI_value_param assignment to only occur when Weibull fit succeeds
* refactor(validation): replace imperative validation with declarative system
- Add dataclass-based validators (_EnumValidator, _NumericValidator, etc.)
- Replace ~240 lines of repetitive validation code with _validate_params()
- Consolidate type aliases in LabelTransformer.py (avoid duplicates)
- Fix pyright errors: float() casts, np.asarray() for pmean returns
- Use np.nan as default for optuna .get() (proper 'no value' sentinel)
- Add pyright to requirements-dev.txt
* chore(ReforceXY): add pyright to dev dependencies
- Move DI_value stats computation before label loop
- Unify warmed_up conditional to single if/else block
- Always set threshold values (defaults when not warmed up)
* refactor(quickadapter): add OPTUNA_*_DEFAULT constants and fix static member access
- Add OPTUNA_*_DEFAULT class constants for n_jobs, n_trials, timeout,
n_startup_trials, min_resource, label_candles_step, space_reduction,
space_fraction, and seed
- Update _optuna_config property to use constants instead of hardcoded values
- Update all .get() calls to use constants as defaults for type safety
- Fix static method/property access: use QuickAdapterRegressorV3.method()
instead of self.method() for static members
- Add assertions for narrowing Optional types (weights)
- Fix min_max_pred signature to accept Optional[int] for label_period_candles
Reduces pyright errors from 174 to 158 (-16)
* fix(quickadapter): default label_prediction method to 'thresholding' for backward compatibility
DEFAULTS_LABEL_PREDICTION['method'] was 'none' which broke backward
compatibility - legacy configs without explicit method would skip
threshold computation. Changed to 'thresholding' to preserve historical
behavior where thresholds were always computed by default.
repositories / freqai-strategies.git / commit
