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Diffstat (limited to 'artifact_analysis.py')
| -rw-r--r-- | artifact_analysis.py | 249 |
1 files changed, 249 insertions, 0 deletions
diff --git a/artifact_analysis.py b/artifact_analysis.py new file mode 100644 index 0000000..dab4693 --- /dev/null +++ b/artifact_analysis.py @@ -0,0 +1,249 @@ +import json +from collections import defaultdict, Counter +from typing import Dict, List + +class ArtifactAnalyzer: + def __init__(self): + self.artifacts = [] + self.characters = {} + + def load_data(self): + """Load artifact and character data""" + with open('data.json', 'r') as f: + data = json.load(f) + self.artifacts = data['artifacts'] + + with open('characters.json', 'r') as f: + self.characters = json.load(f) + + def analyze_artifact_distribution(self): + """Analyze artifact set and slot distribution""" + print("="*60) + print("š¦ ARTIFACT INVENTORY ANALYSIS") + print("="*60) + + # Basic counts + total_artifacts = len(self.artifacts) + five_star_count = sum(1 for art in self.artifacts if art['rarity'] == 5) + four_star_count = sum(1 for art in self.artifacts if art['rarity'] == 4) + + print(f"Total Artifacts: {total_artifacts}") + print(f"5ā Artifacts: {five_star_count} ({five_star_count/total_artifacts*100:.1f}%)") + print(f"4ā Artifacts: {four_star_count} ({four_star_count/total_artifacts*100:.1f}%)") + + # Set distribution + set_counts = Counter(art['setKey'] for art in self.artifacts) + print(f"\nš Artifact Sets ({len(set_counts)} unique sets):") + for set_name, count in set_counts.most_common(): + print(f" {set_name}: {count} pieces") + + # Slot distribution + slot_counts = Counter(art['slotKey'] for art in self.artifacts) + print(f"\nšÆ Slot Distribution:") + slot_names = {'flower': 'Flower', 'plume': 'Feather', 'sands': 'Sands', + 'goblet': 'Goblet', 'circlet': 'Circlet'} + for slot, count in slot_counts.items(): + print(f" {slot_names.get(slot, slot)}: {count} pieces") + + def analyze_main_stats(self): + """Analyze main stat distribution by slot""" + print(f"\nš MAIN STAT ANALYSIS") + print("="*60) + + # Group by slot + slot_main_stats = defaultdict(Counter) + for art in self.artifacts: + slot_main_stats[art['slotKey']][art['mainStatKey']] += 1 + + slot_names = {'flower': 'Flower', 'plume': 'Feather', 'sands': 'Sands', + 'goblet': 'Goblet', 'circlet': 'Circlet'} + + for slot, main_stats in slot_main_stats.items(): + print(f"\n{slot_names.get(slot, slot)}:") + total_slot = sum(main_stats.values()) + for main_stat, count in main_stats.most_common(): + percentage = count / total_slot * 100 + print(f" {main_stat}: {count} ({percentage:.1f}%)") + + def analyze_levels_and_quality(self): + """Analyze artifact levels and upgrade status""" + print(f"\nš ARTIFACT QUALITY ANALYSIS") + print("="*60) + + # Level distribution + level_counts = Counter(art['level'] for art in self.artifacts) + print(f"Level Distribution:") + for level in sorted(level_counts.keys(), reverse=True): + count = level_counts[level] + percentage = count / len(self.artifacts) * 100 + print(f" Level {level}: {count} ({percentage:.1f}%)") + + # Maxed artifacts + maxed_5star = sum(1 for art in self.artifacts if art['level'] == 20 and art['rarity'] == 5) + maxed_4star = sum(1 for art in self.artifacts if art['level'] >= 16 and art['rarity'] == 4) + + print(f"\nMaxed Artifacts:") + print(f" 5ā Level 20: {maxed_5star}") + print(f" 4ā Level 16+: {maxed_4star}") + + # Average level by rarity + five_star_levels = [art['level'] for art in self.artifacts if art['rarity'] == 5] + four_star_levels = [art['level'] for art in self.artifacts if art['rarity'] == 4] + + if five_star_levels: + avg_5star = sum(five_star_levels) / len(five_star_levels) + print(f"\nAverage Levels:") + print(f" 5ā Average: {avg_5star:.1f}") + + if four_star_levels: + avg_4star = sum(four_star_levels) / len(four_star_levels) + print(f" 4ā Average: {avg_4star:.1f}") + + def analyze_character_assignments(self): + """Analyze which characters have artifacts assigned""" + print(f"\nš„ CHARACTER ASSIGNMENT ANALYSIS") + print("="*60) + + # Count assignments + assignments = Counter() + unassigned_count = 0 + + for art in self.artifacts: + location = art.get('location', '') + if location and location.strip(): + assignments[location] += 1 + else: + unassigned_count += 1 + + print(f"Assigned Artifacts: {sum(assignments.values())}") + print(f"Unassigned Artifacts: {unassigned_count}") + print(f"Assignment Rate: {sum(assignments.values())/len(self.artifacts)*100:.1f}%") + + if assignments: + print(f"\nCharacter Assignments:") + for char, count in assignments.most_common(): + print(f" {char}: {count} pieces") + + # Show set composition for each character + char_artifacts = [art for art in self.artifacts if art.get('location') == char] + char_sets = Counter(art['setKey'] for art in char_artifacts) + set_summary = ", ".join(f"{set_name}({count})" for set_name, count in char_sets.items()) + print(f" Sets: {set_summary}") + + def analyze_substats(self): + """Analyze substat distribution and quality""" + print(f"\nā” SUBSTAT ANALYSIS") + print("="*60) + + # Count substat occurrences + substat_counts = Counter() + substat_values = defaultdict(list) + + for art in self.artifacts: + for substat in art.get('substats', []): + key = substat['key'] + value = substat['value'] + substat_counts[key] += 1 + substat_values[key].append(value) + + print(f"Substat Frequency (across all artifacts):") + for stat, count in substat_counts.most_common(): + avg_value = sum(substat_values[stat]) / len(substat_values[stat]) + max_value = max(substat_values[stat]) + print(f" {stat}: {count} rolls (avg: {avg_value:.1f}, max: {max_value:.1f})") + + # High-value substats + print(f"\nHigh-Value Substat Instances:") + high_value_thresholds = { + 'critRate_': 10.0, + 'critDMG_': 20.0, + 'atk_': 15.0, + 'hp_': 15.0, + 'def_': 18.0, + 'enerRech_': 20.0, + 'eleMas': 60.0 + } + + for art in self.artifacts: + high_value_substats = [] + for substat in art.get('substats', []): + key = substat['key'] + value = substat['value'] + threshold = high_value_thresholds.get(key, float('inf')) + if value >= threshold: + high_value_substats.append(f"{key}:{value}") + + if high_value_substats: + set_name = art['setKey'] + slot = art['slotKey'] + level = art['level'] + print(f" {set_name} {slot} L{level}: {', '.join(high_value_substats)}") + + def analyze_optimization_potential(self): + """Analyze potential for optimization""" + print(f"\nšÆ OPTIMIZATION POTENTIAL") + print("="*60) + + # Unassigned high-level artifacts + unassigned_maxed = [art for art in self.artifacts + if not art.get('location', '').strip() + and ((art['rarity'] == 5 and art['level'] == 20) or + (art['rarity'] == 4 and art['level'] >= 16))] + + print(f"Unassigned High-Level Artifacts: {len(unassigned_maxed)}") + + if unassigned_maxed: + print("Available for optimization:") + slot_counts = Counter(art['slotKey'] for art in unassigned_maxed) + for slot, count in slot_counts.items(): + print(f" {slot}: {count} pieces") + + # Character coverage + known_chars = set(self.characters.keys()) + assigned_chars = set(art.get('location', '') for art in self.artifacts + if art.get('location', '').strip()) + + print(f"\nCharacter Coverage:") + print(f" Known characters: {len(known_chars)}") + print(f" Characters with artifacts: {len(assigned_chars)}") + + unoptimized_chars = known_chars - assigned_chars + if unoptimized_chars: + print(f" Unoptimized characters: {', '.join(unoptimized_chars)}") + + # Set bonus potential + print(f"\nSet Bonus Analysis:") + for set_name, count in Counter(art['setKey'] for art in self.artifacts).items(): + if count >= 4: + bonus_type = "4-piece" if count >= 4 else "2-piece" + print(f" {set_name}: {count} pieces (can form {bonus_type} set)") + + def run_full_analysis(self): + """Run complete artifact analysis""" + print("š GENSHIN IMPACT ARTIFACT ANALYSIS") + print("="*80) + + self.load_data() + + self.analyze_artifact_distribution() + self.analyze_main_stats() + self.analyze_levels_and_quality() + self.analyze_character_assignments() + self.analyze_substats() + self.analyze_optimization_potential() + + print(f"\n{'='*80}") + print("š ANALYSIS COMPLETE") + print("="*80) + print("Use this information to:") + print("ā¢ Identify which artifacts need upgrading") + print("ā¢ Find optimization opportunities") + print("ā¢ Plan future artifact farming") + print("ā¢ Optimize character builds") + +def main(): + analyzer = ArtifactAnalyzer() + analyzer.run_full_analysis() + +if __name__ == "__main__": + main()
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