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Trail Recommender Module
------------------------
Translates trail questionnaire responses into a numerical vector.
Unified with the road module's dictionary-based mapping style for consistency.
"""
from .content_based import get_priority_val, run_recommendation_pipeline
from typing import List, Dict, Any, Tuple
def preprocess_trail_input(user_input: Dict[str, Any],
binary_cols: List[str],
continuous_cols: List[str]) -> Tuple[List[float], List[int]]:
"""
Translates trail running preferences into a standardized numerical vector.
Standardized to match the road recommender's look-up table style.
Args:
user_input (Dict[str, Any]): Raw user preferences.
binary_cols (List[str]): List of binary feature names.
continuous_cols (List[str]): List of continuous feature names.
Returns:
Tuple[List[float], List[int]]:
- The full numerical vector.
- A list of indices for active features.
"""
all_cols = binary_cols + continuous_cols
feats = {col: 0.0 for col in all_cols}
# 1. Unified Mappings
feats['terrain_light'] = get_priority_val(user_input, ['terrain'], {'terrain': {'Light': 1.0, 'Mixed': 0.5, 'Rocky': 0.0, 'Muddy': 0.0}})
feats['terrain_moderate'] = get_priority_val(user_input, ['terrain'], {'terrain': {'Light': 0.5, 'Mixed': 1.0, 'Rocky': 0.5, 'Muddy': 0.5}})
feats['terrain_technical'] = get_priority_val(user_input, ['terrain'], {'terrain': {'Light': 0.0, 'Mixed': 0.5, 'Rocky': 1.0, 'Muddy': 1.0}})
feats['lug_dept_mm'] = get_priority_val(user_input, ['terrain'], {'terrain': {'Light': 0.5, 'Mixed': 1.0, 'Rocky': 0.5, 'Muddy': 1.0}})
feats['traction_scaled'] = get_priority_val(user_input, ['terrain'], {'terrain': {'Light': 0.5, 'Mixed': 1.0, 'Rocky': 0.5, 'Muddy': 1.0}})
feats['shock_absorption'] = get_priority_val(user_input, ['rock_sensitive', 'terrain'], {'rock_sensitive': {'Yes': 1.0, 'No': 0.0}, 'terrain': {'Light': 0.2, 'Mixed': 0.6, 'Rocky': 1.0, 'Muddy': 0.0}})
feats['energy_return'] = 1.0
feats['arch_neutral'] = get_priority_val(user_input, ['arch_type'], {'arch_type': {'Flat': 0.0, 'Normal': 0.8, 'High': 1.0}})
feats['arch_stability'] = get_priority_val(user_input, ['arch_type'], {'arch_type': {'Flat': 1.0, 'Normal': 0.2, 'High': 0.0}})
feats['drop_lab_mm'] = get_priority_val(user_input, ['pace'], {'pace': {'Easy': 1.0, 'Steady': 0.5, 'Fast': 0.0}})
prio_strike = ['strike_pattern', 'pace']
feats['strike_heel'] = get_priority_val(user_input, prio_strike, {'strike_pattern': {'Heel': 1.0, 'Mid': 0.5, 'Forefoot': 0.0}, 'pace': {'Easy': 1.0, 'Steady': 0.5, 'Fast': 0.0}})
feats['strike_mid'] = get_priority_val(user_input, prio_strike, {'strike_pattern': {'Heel': 0.5, 'Mid': 1.0, 'Forefoot': 0.5}, 'pace': {'Easy': 0.5, 'Steady': 1.0, 'Fast': 0.5}})
feats['strike_forefoot'] = get_priority_val(user_input, prio_strike, {'strike_pattern': {'Heel': 0.0, 'Mid': 0.0, 'Forefoot': 1.0}, 'pace': {'Easy': 0.0, 'Steady': 0.5, 'Fast': 1.0}})
feats['midsole_softness'] = get_priority_val(user_input, ['pace'], {'pace': {'Easy': 1.0, 'Steady': 0.6, 'Fast': 0.2}})
feats['plate_rock_plate'] = get_priority_val(user_input, ['pace', 'terrain'], {'pace': {'Easy': 0.5, 'Steady': 0.5, 'Fast': 0.5}, 'terrain': {'Light': 0.5, 'Mixed': 1.0, 'Rocky': 1.0, 'Muddy': 1.0}})
feats['plate_carbon_plate'] = get_priority_val(user_input, ['pace', 'terrain'], {'pace': {'Easy': 0.5, 'Steady': 0.5, 'Fast': 1.0}, 'terrain': {'Light': 0.5, 'Mixed': 0.5, 'Rocky': 0.5, 'Muddy': 0.5}})
feats['width_fit'] = get_priority_val(user_input, ['foot_width'], {'foot_width': {'Narrow': 0.2, 'Regular': 0.6, 'Wide': 1.0}})
feats['toebox_width'] = get_priority_val(user_input, ['foot_width'], {'foot_width': {'Narrow': 0.2, 'Regular': 0.6, 'Wide': 1.0}})
feats['stiffness_scaled'] = get_priority_val(user_input, ['pace'], {'pace': {'Easy': 0.2, 'Steady': 0.6, 'Fast': 1.0}})
feats['torsional_rigidity'] = get_priority_val(user_input, ['arch_type', 'pace'], {'arch_type': {'Flat': 1.0, 'Normal': 0.5, 'High': 0.5}, 'pace': {'Easy': 0.2, 'Steady': 0.6, 'Fast': 1.0}})
feats['heel_stiff'] = get_priority_val(user_input, ['arch_type'], {'arch_type': {'Flat': 1.0, 'Normal': 0.6, 'High': 0.2}})
feats['heel_lab_mm'] = get_priority_val(user_input, ['strike_pattern', 'pace', 'terrain'], {'strike_pattern': {'Heel': 1.0, 'Mid': 0.5, 'Forefoot': 0.0}, 'pace': {'Easy': 1.0, 'Steady': 0.5, 'Fast': 0.0}, 'terrain': {'Light': 0.5, 'Mixed': 1.0, 'Rocky': 1.0, 'Muddy': 1.0}})
feats['forefoot_lab_mm'] = get_priority_val(user_input, ['strike_pattern', 'pace', 'terrain'], {'strike_pattern': {'Heel': 0.0, 'Mid': 0.5, 'Forefoot': 1.0}, 'pace': {'Easy': 0.0, 'Steady': 0.5, 'Fast': 1.0}, 'terrain': {'Light': 0.5, 'Mixed': 0.5, 'Rocky': 0.5, 'Muddy': 0.5}})
feats['waterproof'] = get_priority_val(user_input, ['water_resistance', 'terrain'], {'water_resistance': {'Waterproof': 1.0, 'Water Repellent': 0.5}, 'terrain': {'Muddy': 1.0}})
feats['water_repellent'] = get_priority_val(user_input, ['water_resistance', 'terrain'], {'water_resistance': {'Waterproof': 1.0, 'Water Repellent': 1.0}, 'terrain': {'Mixed': 1.0, 'Muddy': 1.0}})
feats['lightweight'] = get_priority_val(user_input, ['pace'], {'pace': {'Easy': 0.5, 'Steady': 0.5, 'Fast': 1.0}})
feats['removable_insole'] = get_priority_val(user_input, ['orthotic_usage'], {'orthotic_usage': {'Yes': 1.0, 'No': 0.5}})
# Static Column Assignment
for col in ['toebox_durability', 'heel_durability', 'outsole_durability', 'breathability_scaled']:
feats[col] = 1.0
# 2. Vector and Masking Setup
binary_set = set(binary_cols)
full_vector_raw = [feats.get(c, 0.0 if c in binary_set else 0.5) for c in all_cols]
provided_inputs = {k for k, v in user_input.items() if v}
feature_sources = {
'terrain_light': ['terrain'], 'terrain_moderate': ['terrain'], 'terrain_technical': ['terrain'],
'shock_absorption': ['rock_sensitive', 'terrain'], 'traction_scaled': ['terrain'],
'arch_neutral': ['arch_type'], 'arch_stability': ['arch_type'],
'drop_lab_mm': ['pace'], 'midsole_softness': ['pace'],
'strike_heel': ['strike_pattern', 'pace'], 'strike_mid': ['strike_pattern', 'pace'], 'strike_forefoot': ['strike_pattern', 'pace'],
'plate_rock_plate': ['pace', 'terrain'], 'plate_carbon_plate': ['pace', 'terrain'],
'width_fit': ['foot_width'], 'toebox_width': ['foot_width'],
'stiffness_scaled': ['pace'], 'torsional_rigidity': ['arch_type', 'pace'],
'heel_stiff': ['arch_type'], 'lug_dept_mm': ['terrain'],
'heel_lab_mm': ['strike_pattern', 'pace', 'terrain'], 'forefoot_lab_mm': ['strike_pattern', 'pace', 'terrain'],
'removable_insole': ['orthotic_usage'], 'lightweight': ['pace'],
'waterproof': ['water_resistance', 'terrain'], 'water_repellent': ['water_resistance', 'terrain']
}
valid_indices = [
i for i, col in enumerate(all_cols)
if not feature_sources.get(col) or not set(feature_sources[col]).isdisjoint(provided_inputs)
]
return full_vector_raw, valid_indices or list(range(len(all_cols)))
def get_recommendations(user_input: Dict[str, Any], artifacts: Dict[str, Any]) -> List[Any]:
"""Wrapper entry point for trail recommendation."""
full_vector, valid_idx = preprocess_trail_input(user_input, artifacts['binary_cols'], artifacts['continuous_cols'])
return run_recommendation_pipeline(full_vector, valid_idx, artifacts) |