refactor(quickadapter): harmonize error messages

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index ab19b3c27a19ad9e5085681d326558a90cee6026..e6a9da1cc8ca80f196d2090a9d51e468676054c2 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -297,8 +297,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
                 label_frequency_candles = default_label_frequency_candles
             else:
                 logger.warning(
-                    f"Invalid string value for label_frequency_candles {label_frequency_candles!r}, "
-                    f"only 'auto' is supported, using default {default_label_frequency_candles!r}"
+                    f"Invalid label_frequency_candles {label_frequency_candles!r}: only 'auto' is supported for string values. Using default {default_label_frequency_candles!r}"
                 )
                 label_frequency_candles = default_label_frequency_candles
         elif isinstance(label_frequency_candles, (int, float)):
@@ -306,14 +305,12 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
                 label_frequency_candles = int(label_frequency_candles)
             else:
                 logger.warning(
-                    f"Invalid numeric value for label_frequency_candles: {label_frequency_candles!r}, "
-                    f"must be between 2 and 10000, using default {default_label_frequency_candles!r}"
+                    f"Invalid label_frequency_candles {label_frequency_candles!r}: must be in range [2, 10000]. Using default {default_label_frequency_candles!r}"
                 )
                 label_frequency_candles = default_label_frequency_candles
         else:
             logger.warning(
-                f"Invalid type for label_frequency_candles {type(label_frequency_candles).__name__!r}, "
-                f"expected int, float, or 'auto', using default {default_label_frequency_candles!r}"
+                f"Invalid label_frequency_candles {label_frequency_candles!r}: expected int, float, or 'auto'. Using default {default_label_frequency_candles!r}"
             )
             label_frequency_candles = default_label_frequency_candles
 
@@ -1436,7 +1433,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
         extrema_fraction: float = 1.0,
     ) -> tuple[float, float]:
         if alpha < 0:
-            raise ValueError(f"Invalid alpha {alpha}: must be >= 0")
+            raise ValueError(f"Invalid alpha {alpha!r}: must be >= 0")
         pred_minima, pred_maxima = QuickAdapterRegressorV3.get_pred_min_max(
             pred_extrema, extrema_selection, extrema_fraction
         )
@@ -1693,7 +1690,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
 
         if not np.all(np.isfinite(normalized_matrix)):
             raise ValueError(
-                "normalized_matrix must contain only finite values after normalization"
+                "Invalid normalized_matrix: must contain only finite values after normalization"
             )
 
         return normalized_matrix

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 63fdd5d0d0b93cc5b5e9af1e989fdc248a4237f0..4054808ab1e66d0203f0353e4e3a542f2a6624dc 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -495,7 +495,7 @@ class QuickAdapterV3(IStrategy):
 
         if not isinstance(lookback_period, int) or lookback_period < 0:
             logger.warning(
-                f"Invalid reversal_confirmation lookback_period {lookback_period!r}, using default {QuickAdapterV3.default_reversal_confirmation['lookback_period']}"
+                f"Invalid reversal_confirmation lookback_period {lookback_period!r}: must be >= 0. Using default {QuickAdapterV3.default_reversal_confirmation['lookback_period']!r}"
             )
             lookback_period = QuickAdapterV3.default_reversal_confirmation[
                 "lookback_period"
@@ -503,7 +503,7 @@ class QuickAdapterV3(IStrategy):
 
         if not isinstance(decay_ratio, (int, float)) or not (0.0 < decay_ratio <= 1.0):
             logger.warning(
-                f"Invalid reversal_confirmation decay_ratio {decay_ratio!r}, using default {QuickAdapterV3.default_reversal_confirmation['decay_ratio']}"
+                f"Invalid reversal_confirmation decay_ratio {decay_ratio!r}: must be in range (0, 1]. Using default {QuickAdapterV3.default_reversal_confirmation['decay_ratio']!r}"
             )
             decay_ratio = QuickAdapterV3.default_reversal_confirmation["decay_ratio"]
 
@@ -742,7 +742,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_strategy not in set(WEIGHT_STRATEGIES):
             logger.warning(
-                f"Invalid extrema_weighting strategy {weighting_strategy!r}, must be one of {WEIGHT_STRATEGIES}, using default {WEIGHT_STRATEGIES[0]!r}"
+                f"Invalid extrema_weighting strategy {weighting_strategy!r}. Supported: {', '.join(WEIGHT_STRATEGIES)}. Using default {WEIGHT_STRATEGIES[0]!r}"
             )
             weighting_strategy = WEIGHT_STRATEGIES[0]
 
@@ -754,7 +754,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_standardization not in set(STANDARDIZATION_TYPES):
             logger.warning(
-                f"Invalid extrema_weighting standardization {weighting_standardization!r}, must be one of {STANDARDIZATION_TYPES}, using default {STANDARDIZATION_TYPES[0]!r}"
+                f"Invalid extrema_weighting standardization {weighting_standardization!r}. Supported: {', '.join(STANDARDIZATION_TYPES)}. Using default {STANDARDIZATION_TYPES[0]!r}"
             )
             weighting_standardization = STANDARDIZATION_TYPES[0]
 
@@ -771,7 +771,7 @@ class QuickAdapterV3(IStrategy):
             or weighting_robust_quantiles[0] >= weighting_robust_quantiles[1]
         ):
             logger.warning(
-                f"Invalid extrema_weighting robust_quantiles {weighting_robust_quantiles!r}, must be (q1, q3) with 0 <= q1 < q3 <= 1, using default {DEFAULTS_EXTREMA_WEIGHTING['robust_quantiles']!r}"
+                f"Invalid extrema_weighting robust_quantiles {weighting_robust_quantiles!r}: must be (q1, q3) with 0 <= q1 < q3 <= 1. Using default {DEFAULTS_EXTREMA_WEIGHTING['robust_quantiles']!r}"
             )
             weighting_robust_quantiles = DEFAULTS_EXTREMA_WEIGHTING["robust_quantiles"]
         else:
@@ -789,7 +789,7 @@ class QuickAdapterV3(IStrategy):
             or weighting_mmad_scaling_factor <= 0
         ):
             logger.warning(
-                f"Invalid extrema_weighting mmad_scaling_factor {weighting_mmad_scaling_factor!r}, must be a finite number > 0, using default {DEFAULTS_EXTREMA_WEIGHTING['mmad_scaling_factor']!r}"
+                f"Invalid extrema_weighting mmad_scaling_factor {weighting_mmad_scaling_factor!r}: must be a finite number > 0. Using default {DEFAULTS_EXTREMA_WEIGHTING['mmad_scaling_factor']!r}"
             )
             weighting_mmad_scaling_factor = DEFAULTS_EXTREMA_WEIGHTING[
                 "mmad_scaling_factor"
@@ -803,7 +803,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_normalization not in set(NORMALIZATION_TYPES):
             logger.warning(
-                f"Invalid extrema_weighting normalization {weighting_normalization!r}, must be one of {NORMALIZATION_TYPES}, using default {NORMALIZATION_TYPES[0]!r}"
+                f"Invalid extrema_weighting normalization {weighting_normalization!r}. Supported: {', '.join(NORMALIZATION_TYPES)}. Using default {NORMALIZATION_TYPES[0]!r}"
             )
             weighting_normalization = NORMALIZATION_TYPES[0]
 
@@ -838,7 +838,7 @@ class QuickAdapterV3(IStrategy):
             or weighting_minmax_range[0] >= weighting_minmax_range[1]
         ):
             logger.warning(
-                f"Invalid extrema_weighting minmax_range {weighting_minmax_range!r}, must be (min, max) with min < max, using default {DEFAULTS_EXTREMA_WEIGHTING['minmax_range']!r}"
+                f"Invalid extrema_weighting minmax_range {weighting_minmax_range!r}: must be (min, max) with min < max. Using default {DEFAULTS_EXTREMA_WEIGHTING['minmax_range']!r}"
             )
             weighting_minmax_range = DEFAULTS_EXTREMA_WEIGHTING["minmax_range"]
         else:
@@ -856,7 +856,7 @@ class QuickAdapterV3(IStrategy):
             or weighting_sigmoid_scale <= 0
         ):
             logger.warning(
-                f"Invalid extrema_weighting sigmoid_scale {weighting_sigmoid_scale!r}, must be a finite number > 0, using default {DEFAULTS_EXTREMA_WEIGHTING['sigmoid_scale']!r}"
+                f"Invalid extrema_weighting sigmoid_scale {weighting_sigmoid_scale!r}: must be a finite number > 0. Using default {DEFAULTS_EXTREMA_WEIGHTING['sigmoid_scale']!r}"
             )
             weighting_sigmoid_scale = DEFAULTS_EXTREMA_WEIGHTING["sigmoid_scale"]
 
@@ -869,7 +869,7 @@ class QuickAdapterV3(IStrategy):
             or weighting_softmax_temperature <= 0
         ):
             logger.warning(
-                f"Invalid extrema_weighting softmax_temperature {weighting_softmax_temperature!r}, must be a finite number > 0, using default {DEFAULTS_EXTREMA_WEIGHTING['softmax_temperature']!r}"
+                f"Invalid extrema_weighting softmax_temperature {weighting_softmax_temperature!r}: must be a finite number > 0. Using default {DEFAULTS_EXTREMA_WEIGHTING['softmax_temperature']!r}"
             )
             weighting_softmax_temperature = DEFAULTS_EXTREMA_WEIGHTING[
                 "softmax_temperature"
@@ -882,7 +882,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_rank_method not in set(RANK_METHODS):
             logger.warning(
-                f"Invalid extrema_weighting rank_method {weighting_rank_method!r}, must be one of {RANK_METHODS}, using default {RANK_METHODS[0]!r}"
+                f"Invalid extrema_weighting rank_method {weighting_rank_method!r}. Supported: {', '.join(RANK_METHODS)}. Using default {RANK_METHODS[0]!r}"
             )
             weighting_rank_method = RANK_METHODS[0]
 
@@ -896,7 +896,7 @@ class QuickAdapterV3(IStrategy):
             or not (0 < weighting_gamma <= 10.0)
         ):
             logger.warning(
-                f"Invalid extrema_weighting gamma {weighting_gamma!r}, must be a finite number in (0, 10], using default {DEFAULTS_EXTREMA_WEIGHTING['gamma']!r}"
+                f"Invalid extrema_weighting gamma {weighting_gamma!r}: must be in range (0, 10]. Using default {DEFAULTS_EXTREMA_WEIGHTING['gamma']!r}"
             )
             weighting_gamma = DEFAULTS_EXTREMA_WEIGHTING["gamma"]
 
@@ -905,7 +905,7 @@ class QuickAdapterV3(IStrategy):
         )
         if not isinstance(weighting_source_weights, dict):
             logger.warning(
-                f"Invalid extrema_weighting source_weights {weighting_source_weights!r}, must be a dict of source name to weight, using default {DEFAULTS_EXTREMA_WEIGHTING['source_weights']!r}"
+                f"Invalid extrema_weighting source_weights {weighting_source_weights!r}: must be a dict of source name to weight. Using default {DEFAULTS_EXTREMA_WEIGHTING['source_weights']!r}"
             )
             weighting_source_weights = DEFAULTS_EXTREMA_WEIGHTING["source_weights"]
         else:
@@ -922,7 +922,7 @@ class QuickAdapterV3(IStrategy):
                 sanitized_source_weights[str(source)] = float(weight)
             if not sanitized_source_weights:
                 logger.warning(
-                    f"Invalid/empty extrema_weighting source_weights {weighting_source_weights!r}, using default {DEFAULTS_EXTREMA_WEIGHTING['source_weights']!r}"
+                    f"Invalid extrema_weighting source_weights {weighting_source_weights!r}: empty after sanitization. Using default {DEFAULTS_EXTREMA_WEIGHTING['source_weights']!r}"
                 )
                 weighting_source_weights = DEFAULTS_EXTREMA_WEIGHTING["source_weights"]
             else:
@@ -935,7 +935,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_aggregation not in set(HYBRID_AGGREGATIONS):
             logger.warning(
-                f"Invalid extrema_weighting aggregation {weighting_aggregation!r}, must be one of {HYBRID_AGGREGATIONS}, using default {HYBRID_AGGREGATIONS[0]!r}"
+                f"Invalid extrema_weighting aggregation {weighting_aggregation!r}. Supported: {', '.join(HYBRID_AGGREGATIONS)}. Using default {HYBRID_AGGREGATIONS[0]!r}"
             )
             weighting_aggregation = DEFAULTS_EXTREMA_WEIGHTING["aggregation"]
         weighting_aggregation_normalization = str(
@@ -946,7 +946,7 @@ class QuickAdapterV3(IStrategy):
         )
         if weighting_aggregation_normalization not in set(NORMALIZATION_TYPES):
             logger.warning(
-                f"Invalid extrema_weighting aggregation_normalization {weighting_aggregation_normalization!r}, must be one of {NORMALIZATION_TYPES}, using default {NORMALIZATION_TYPES[6]!r}"
+                f"Invalid extrema_weighting aggregation_normalization {weighting_aggregation_normalization!r}. Supported: {', '.join(NORMALIZATION_TYPES)}. Using default {NORMALIZATION_TYPES[6]!r}"
             )
             weighting_aggregation_normalization = DEFAULTS_EXTREMA_WEIGHTING[
                 "aggregation_normalization"
@@ -992,7 +992,7 @@ class QuickAdapterV3(IStrategy):
         )
         if smoothing_method not in set(SMOOTHING_METHODS):
             logger.warning(
-                f"Invalid extrema_smoothing method {smoothing_method!r}, must be one of {SMOOTHING_METHODS}, using default {SMOOTHING_METHODS[0]!r}"
+                f"Invalid extrema_smoothing method {smoothing_method!r}. Supported: {', '.join(SMOOTHING_METHODS)}. Using default {SMOOTHING_METHODS[0]!r}"
             )
             smoothing_method = SMOOTHING_METHODS[0]
 
@@ -1001,7 +1001,7 @@ class QuickAdapterV3(IStrategy):
         )
         if not isinstance(smoothing_window, int) or smoothing_window < 3:
             logger.warning(
-                f"Invalid extrema_smoothing window {smoothing_window!r}, must be an integer >= 3, using default {DEFAULTS_EXTREMA_SMOOTHING['window']!r}"
+                f"Invalid extrema_smoothing window {smoothing_window!r}: must be an integer >= 3. Using default {DEFAULTS_EXTREMA_SMOOTHING['window']!r}"
             )
             smoothing_window = DEFAULTS_EXTREMA_SMOOTHING["window"]
 
@@ -1014,7 +1014,7 @@ class QuickAdapterV3(IStrategy):
             or smoothing_beta <= 0
         ):
             logger.warning(
-                f"Invalid extrema_smoothing beta {smoothing_beta!r}, must be a finite number > 0, using default {DEFAULTS_EXTREMA_SMOOTHING['beta']!r}"
+                f"Invalid extrema_smoothing beta {smoothing_beta!r}: must be a finite number > 0. Using default {DEFAULTS_EXTREMA_SMOOTHING['beta']!r}"
             )
             smoothing_beta = DEFAULTS_EXTREMA_SMOOTHING["beta"]
 
@@ -1023,7 +1023,7 @@ class QuickAdapterV3(IStrategy):
         )
         if not isinstance(smoothing_polyorder, int) or smoothing_polyorder < 1:
             logger.warning(
-                f"Invalid extrema_smoothing polyorder {smoothing_polyorder!r}, must be an integer >= 1, using default {DEFAULTS_EXTREMA_SMOOTHING['polyorder']!r}"
+                f"Invalid extrema_smoothing polyorder {smoothing_polyorder!r}: must be an integer >= 1. Using default {DEFAULTS_EXTREMA_SMOOTHING['polyorder']!r}"
             )
             smoothing_polyorder = DEFAULTS_EXTREMA_SMOOTHING["polyorder"]
 
@@ -1032,7 +1032,7 @@ class QuickAdapterV3(IStrategy):
         )
         if smoothing_mode not in set(SMOOTHING_MODES):
             logger.warning(
-                f"Invalid extrema_smoothing mode {smoothing_mode!r}, must be one of {SMOOTHING_MODES}, using default {SMOOTHING_MODES[0]!r}"
+                f"Invalid extrema_smoothing mode {smoothing_mode!r}. Supported: {', '.join(SMOOTHING_MODES)}. Using default {SMOOTHING_MODES[0]!r}"
             )
             smoothing_mode = SMOOTHING_MODES[0]
 
@@ -1045,7 +1045,7 @@ class QuickAdapterV3(IStrategy):
             or not np.isfinite(smoothing_sigma)
         ):
             logger.warning(
-                f"Invalid extrema_smoothing sigma {smoothing_sigma!r}, must be a finite number > 0, using default {DEFAULTS_EXTREMA_SMOOTHING['sigma']!r}"
+                f"Invalid extrema_smoothing sigma {smoothing_sigma!r}: must be a finite number > 0. Using default {DEFAULTS_EXTREMA_SMOOTHING['sigma']!r}"
             )
             smoothing_sigma = DEFAULTS_EXTREMA_SMOOTHING["sigma"]
 

diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py
index 3652ccc659b155e2d8f7a31dd17a9a1696eb7f82..b216cf92f05219f395eb4bc1b9975d55863e6ba3 100644 (file)
--- a/quickadapter/user_data/strategies/Utils.py
+++ b/quickadapter/user_data/strategies/Utils.py
@@ -2367,7 +2367,7 @@ def validate_range(
             or (non_negative and value < 0)
         ):
             logger.warning(
-                f"Invalid {name} {value!r}, must be {constraint_str}, using default {default_value!r}"
+                f"Invalid {name} {value!r}: must be {constraint_str}. Using default {default_value!r}"
             )
             return default_value
         return value