From c21b771c1b5350528080cbc78b48a9cb5127a932 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Sun, 4 Jan 2026 16:55:57 +0100 Subject: [PATCH] docs(quickadapter): use markdown escape MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- README.md | 2 +- quickadapter/user_data/strategies/Utils.py | 7 +++---- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 03f480b..e29e0dc 100644 --- a/README.md +++ b/README.md @@ -71,7 +71,7 @@ docker compose up -d --build | freqai.extrema_weighting.standardization | `none` | enum {`none`,`zscore`,`robust`,`mmad`,`power_yj`} | Standardization method applied to smoothed weighted extrema before normalization. `none`=w, `zscore`=(w-μ)/σ, `robust`=(w-median)/IQR, `mmad`=(w-median)/(MAD·k), `power_yj`=YJ(w). | | freqai.extrema_weighting.robust_quantiles | [0.25, 0.75] | list[float] where 0 <= Q1 < Q3 <= 1 | Quantile range for robust standardization, Q1 and Q3. | | freqai.extrema_weighting.mmad_scaling_factor | 1.4826 | float > 0 | Scaling factor for MMAD standardization. | -| freqai.extrema_weighting.normalization | `maxabs` | enum {`maxabs`,`minmax`,`sigmoid`,`none`} | Normalization method applied to smoothed weighted extrema. `maxabs`=w/max(|w|), `minmax`=low+(w-min)/(max-min)·(high-low), `sigmoid`=2·σ(scale·w)-1, `none`=w. | +| freqai.extrema_weighting.normalization | `maxabs` | enum {`maxabs`,`minmax`,`sigmoid`,`none`} | Normalization method applied to smoothed weighted extrema. `maxabs`=w/max(\|w\|), `minmax`=low+(w-min)/(max-min)·(high-low), `sigmoid`=2·σ(scale·w)-1, `none`=w. | | freqai.extrema_weighting.minmax_range | [-1.0, 1.0] | list[float] | Target range for `minmax` normalization, min and max. | | freqai.extrema_weighting.sigmoid_scale | 1.0 | float > 0 | Scale parameter for `sigmoid` normalization, controls steepness. | | freqai.extrema_weighting.gamma | 1.0 | float (0,10] | Contrast exponent applied to smoothed weighted extrema after normalization: >1 emphasizes extrema, values between 0 and 1 soften. | diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index 9695b9a..845161c 100644 --- a/quickadapter/user_data/strategies/Utils.py +++ b/quickadapter/user_data/strategies/Utils.py @@ -166,12 +166,11 @@ def get_extrema_weighting_config( if ( strategy != WEIGHT_STRATEGIES[0] # "none" and standardization != STANDARDIZATION_TYPES[0] # "none" - and normalization == NORMALIZATION_TYPES[2] # "none" + and normalization == NORMALIZATION_TYPES[3] # "none" ): logger.warning( - f"extrema_weighting standardization={standardization!r} with normalization={normalization!r} " - "can produce negative weights and flip ternary extrema labels. " - f"Consider using normalization in {{{NORMALIZATION_TYPES[0]!r},{NORMALIZATION_TYPES[1]!r}}} " + f"extrema_weighting standardization={standardization!r} with normalization={normalization!r} can shift/flip ternary extrema labels. " + f"Consider using normalization in {{{NORMALIZATION_TYPES[0]!r},{NORMALIZATION_TYPES[1]!r},{NORMALIZATION_TYPES[2]!r}}} " f"or set standardization={STANDARDIZATION_TYPES[0]!r}" ) -- 2.43.0