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- Enhanced the skill scoring formula to incorporate intensity and level range factors, improving the accuracy of skill contributions. - Removed the use of `is_primary` and `development_contribution` from calculations, streamlining the scoring process. - Updated documentation to reflect changes in the scoring logic and versioning. - Adjusted frontend components to align with the new scoring criteria, ensuring consistent user experience across the application.
81 lines
2.6 KiB
Python
81 lines
2.6 KiB
Python
"""Unit-Tests für gewichtetes Fähigkeiten-Scoring (Phase 3)."""
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from skill_scoring import (
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ExerciseOccurrence,
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compute_skill_profile,
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match_score_for_skill_ids,
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_level_range_multiplier,
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_skill_link_multiplier,
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)
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def test_skill_link_multiplier_intensity_and_levels():
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assert _skill_link_multiplier(intensity="hoch") == 1.2
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assert _skill_link_multiplier(intensity="niedrig") == 0.85
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wide = _skill_link_multiplier(
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intensity="mittel",
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required_level="basis",
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target_level="optimierung",
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)
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narrow = _skill_link_multiplier(
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intensity="mittel",
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required_level="grundlagen",
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target_level="grundlagen",
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)
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assert wide > narrow
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def test_level_range_multiplier_span():
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assert _level_range_multiplier(None, None) == 1.0
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assert _level_range_multiplier("aufbau", "fortgeschritten") > _level_range_multiplier("basis", "basis")
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def test_compute_skill_profile_aggregates_weights():
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occurrences = [
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ExerciseOccurrence(exercise_id=1, planned_duration_min=60),
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ExerciseOccurrence(exercise_id=1, planned_duration_min=30),
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]
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skills_map = {
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1: [
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{
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"skill_id": 10,
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"skill_name": "Distanz",
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"category": "kihon",
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"intensity": "hoch",
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"required_level": "grundlagen",
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"target_level": "aufbau",
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"exercise_title": "Übung A",
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},
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{
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"skill_id": 11,
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"skill_name": "Balance",
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"category": "kihon",
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"intensity": "niedrig",
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"required_level": "basis",
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"target_level": "basis",
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"exercise_title": "Übung A",
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},
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],
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}
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profile = compute_skill_profile(occurrences, skills_map)
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assert profile["scoring_version"] == "1.1"
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assert profile["exercise_occurrence_count"] == 2
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assert profile["distinct_exercise_count"] == 1
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assert len(profile["skills"]) == 2
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assert profile["skills"][0]["skill_id"] == 10
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assert profile["total_weight"] > profile["skills"][1]["weight"]
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assert abs(sum(s["share_percent"] for s in profile["skills"]) - 100.0) < 0.1
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def test_match_score_for_skill_ids():
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profile = {
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"total_weight": 100.0,
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"skills": [
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{"skill_id": 1, "skill_name": "A", "weight": 40.0},
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{"skill_id": 2, "skill_name": "B", "weight": 60.0},
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],
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}
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m = match_score_for_skill_ids(profile, [1])
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assert m["match_weight"] == 40.0
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assert m["match_percent"] == 40.0
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assert m["matched_skill_ids"] == [1]
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