"""
Experiment Designer Agent

Designs rigorous scientific experiments including experimental protocols,
control groups, randomization strategies, and statistical power analysis.
"""

from typing import Any, Dict, List
from agents.base import BaseAgent


class ExperimentDesignerAgent(BaseAgent):
    """
    Scientific experiment design and methodology agent.

    Capabilities:
    - Experimental design (RCT, factorial, crossover, etc.)
    - Sample size and power calculations
    - Randomization and blinding strategies
    - Control group design
    - Variable selection and operationalization
    - Confounding factor identification
    - Statistical analysis planning
    """

    def __init__(self):
        super().__init__(
            name='experiment-designer',
            description='Design scientific experiments and protocols',
            category='research',
            version='1.0.0',
            tags=['experiment', 'design', 'methodology', 'research', 'scientific', 'protocol']
        )

    async def execute(self, params: Dict[str, Any]) -> Dict[str, Any]:
        """
        Design a scientific experiment.

        Args:
            params: {
                'research_question': str,
                'hypothesis': str,
                'study_type': 'RCT|factorial|crossover|observational|quasi-experimental',
                'variables': {
                    'independent': List[Dict],
                    'dependent': List[Dict],
                    'control': List[Dict],
                    'confounding': List[Dict]
                },
                'population': {
                    'target_population': str,
                    'inclusion_criteria': List[str],
                    'exclusion_criteria': List[str]
                },
                'sample_size': {
                    'effect_size': float,
                    'power': float,
                    'alpha': float,
                    'tails': int
                },
                'design_parameters': {
                    'randomization': 'simple|stratified|block|cluster',
                    'blinding': 'single|double|triple|none',
                    'controls': List[str],
                    'replication': int
                },
                'options': {
                    'include_pilot': bool,
                    'calculate_power': bool,
                    'identify_threats': bool,
                    'generate_protocol': bool
                }
            }

        Returns:
            {
                'status': 'success|failed',
                'experiment_id': str,
                'design': Dict,
                'sample_size_calculation': Dict,
                'methodology': Dict,
                'timeline': Dict,
                'threats_to_validity': List[Dict],
                'recommendations': List[str]
            }
        """
        research_question = params.get('research_question')
        hypothesis = params.get('hypothesis')
        study_type = params.get('study_type', 'RCT')
        variables = params.get('variables', {})
        options = params.get('options', {})

        self.logger.info(
            f"Designing {study_type} experiment: {research_question}"
        )

        # Mock experiment design
        experimental_design = {
            'study_type': study_type,
            'design_notation': 'R O X O',  # Randomized, Observe, Treatment, Observe
            'groups': [
                {
                    'group_id': 'experimental',
                    'name': 'Treatment Group',
                    'intervention': 'Novel AI-based teaching method',
                    'sample_size': 120,
                    'characteristics': 'Receives experimental intervention'
                },
                {
                    'group_id': 'control',
                    'name': 'Control Group',
                    'intervention': 'Traditional teaching method',
                    'sample_size': 120,
                    'characteristics': 'Standard practice comparison'
                },
                {
                    'group_id': 'placebo',
                    'name': 'Placebo Control',
                    'intervention': 'Attention-matched control',
                    'sample_size': 120,
                    'characteristics': 'Controls for attention effects'
                }
            ],
            'total_participants': 360,
            'allocation_ratio': '1:1:1',
            'randomization': {
                'method': 'Stratified block randomization',
                'stratification_factors': ['age_group', 'baseline_performance'],
                'block_size': 6,
                'concealment': 'Central allocation via web system',
                'sequence_generation': 'Computer-generated random numbers'
            },
            'blinding': {
                'level': 'Double-blind',
                'participants_blinded': True,
                'assessors_blinded': True,
                'analysts_blinded': True,
                'blinding_maintenance': [
                    'Identical intervention materials',
                    'Separate data collection team',
                    'Coded treatment assignments'
                ]
            }
        }

        sample_size_calculation = {
            'method': 'Two-sample t-test power analysis',
            'parameters': {
                'effect_size': params.get('sample_size', {}).get('effect_size', 0.5),
                'alpha': 0.05,
                'power': 0.80,
                'tails': 2
            },
            'minimum_per_group': 64,
            'recommended_per_group': 120,
            'total_recommended': 360,
            'attrition_assumption': 0.15,
            'adjusted_sample_size': 424,
            'power_achieved': 0.85,
            'detectable_effect_size': 0.45,
            'sensitivity_analysis': {
                'power_0.70': {'n_per_group': 88},
                'power_0.80': {'n_per_group': 120},
                'power_0.90': {'n_per_group': 156}
            },
            'assumptions': [
                'Normal distribution of outcomes',
                'Equal variances between groups',
                'Independence of observations',
                '15% attrition rate expected'
            ]
        }

        methodology = {
            'phase_1_pilot': {
                'duration': '2 months',
                'sample_size': 30,
                'objectives': [
                    'Test feasibility of recruitment',
                    'Refine intervention protocols',
                    'Validate measurement instruments',
                    'Estimate effect sizes for power calculation'
                ]
            },
            'phase_2_main': {
                'duration': '12 months',
                'phases': [
                    {
                        'phase': 'Baseline Assessment',
                        'duration': '1 month',
                        'activities': [
                            'Screen participants',
                            'Obtain informed consent',
                            'Collect baseline measurements',
                            'Randomize participants'
                        ]
                    },
                    {
                        'phase': 'Intervention Period',
                        'duration': '6 months',
                        'activities': [
                            'Deliver interventions',
                            'Monitor adherence',
                            'Collect interim data',
                            'Manage adverse events'
                        ]
                    },
                    {
                        'phase': 'Post-Intervention Assessment',
                        'duration': '1 month',
                        'activities': [
                            'Collect primary outcomes',
                            'Collect secondary outcomes',
                            'Conduct exit interviews',
                            'Debrief participants'
                        ]
                    },
                    {
                        'phase': 'Follow-up',
                        'duration': '3 months',
                        'activities': [
                            'Long-term outcome assessment',
                            'Measure sustainability',
                            'Final data collection'
                        ]
                    }
                ]
            },
            'data_collection': {
                'primary_outcome': {
                    'measure': 'Academic Performance Score',
                    'instrument': 'Standardized test battery',
                    'timepoints': ['baseline', '3-months', '6-months', '9-months'],
                    'reliability': 0.92,
                    'validity': 'Validated in previous studies'
                },
                'secondary_outcomes': [
                    {'measure': 'Student Engagement', 'instrument': 'Engagement Scale'},
                    {'measure': 'Self-efficacy', 'instrument': 'Self-Efficacy Questionnaire'},
                    {'measure': 'Motivation', 'instrument': 'Motivation Inventory'}
                ],
                'process_measures': [
                    'Intervention adherence',
                    'Fidelity of implementation',
                    'Participant satisfaction'
                ]
            },
            'quality_control': {
                'data_quality': [
                    'Real-time data validation',
                    'Missing data monitoring',
                    'Outlier detection',
                    'Regular data audits'
                ],
                'protocol_adherence': [
                    'Weekly team meetings',
                    'Intervention checklists',
                    'Fidelity observations',
                    'Deviation tracking'
                ],
                'participant_safety': [
                    'Adverse event monitoring',
                    'Data Safety Monitoring Board',
                    'Stopping rules defined',
                    'Emergency protocols'
                ]
            }
        }

        threats_to_validity = [
            {
                'type': 'Internal Validity',
                'threats': [
                    {
                        'threat': 'Selection bias',
                        'risk': 'Low',
                        'mitigation': 'Random allocation with concealment'
                    },
                    {
                        'threat': 'Attrition bias',
                        'risk': 'Medium',
                        'mitigation': 'Intention-to-treat analysis, retention strategies'
                    },
                    {
                        'threat': 'Testing effects',
                        'risk': 'Low',
                        'mitigation': 'Alternate forms, sufficient time between assessments'
                    },
                    {
                        'threat': 'Maturation',
                        'risk': 'Medium',
                        'mitigation': 'Control group comparison, limited duration'
                    }
                ]
            },
            {
                'type': 'External Validity',
                'threats': [
                    {
                        'threat': 'Population generalizability',
                        'risk': 'Medium',
                        'mitigation': 'Diverse sampling, clear inclusion criteria'
                    },
                    {
                        'threat': 'Ecological validity',
                        'risk': 'Low',
                        'mitigation': 'Real-world setting, authentic tasks'
                    },
                    {
                        'threat': 'Temporal validity',
                        'risk': 'Medium',
                        'mitigation': 'Follow-up assessments, longitudinal design'
                    }
                ]
            },
            {
                'type': 'Construct Validity',
                'threats': [
                    {
                        'threat': 'Measurement error',
                        'risk': 'Low',
                        'mitigation': 'Validated instruments, trained assessors'
                    },
                    {
                        'threat': 'Hawthorne effect',
                        'risk': 'Medium',
                        'mitigation': 'Blinding, natural observation periods'
                    }
                ]
            },
            {
                'type': 'Statistical Conclusion Validity',
                'threats': [
                    {
                        'threat': 'Low statistical power',
                        'risk': 'Low',
                        'mitigation': 'Adequate sample size calculation'
                    },
                    {
                        'threat': 'Violation of assumptions',
                        'risk': 'Medium',
                        'mitigation': 'Assumption testing, robust methods'
                    }
                ]
            }
        ]

        statistical_analysis_plan = {
            'primary_analysis': {
                'method': 'Mixed-effects ANOVA',
                'factors': ['time', 'group', 'time*group'],
                'covariates': ['baseline_score', 'age', 'prior_achievement'],
                'significance_level': 0.05,
                'multiple_comparison_correction': 'Bonferroni'
            },
            'secondary_analyses': [
                'Subgroup analysis by baseline performance',
                'Mediation analysis for engagement',
                'Moderation analysis for demographic factors'
            ],
            'missing_data': {
                'strategy': 'Multiple imputation',
                'method': 'Multivariate imputation by chained equations (MICE)',
                'imputations': 20,
                'sensitivity_analysis': 'Complete case analysis'
            },
            'interim_analysis': {
                'scheduled': True,
                'timepoints': ['50% enrollment', '75% enrollment'],
                'alpha_spending': 'O\'Brien-Fleming boundary',
                'stopping_rules': 'Defined by DSMB charter'
            }
        }

        timeline = {
            'phase_1_preparation': {
                'duration': '3 months',
                'tasks': [
                    'Ethics approval',
                    'Protocol finalization',
                    'Staff training',
                    'Materials preparation'
                ]
            },
            'phase_2_pilot': {
                'duration': '2 months',
                'tasks': [
                    'Pilot recruitment',
                    'Pilot intervention',
                    'Protocol refinement'
                ]
            },
            'phase_3_main_study': {
                'duration': '12 months',
                'tasks': [
                    'Main recruitment',
                    'Intervention delivery',
                    'Data collection'
                ]
            },
            'phase_4_analysis': {
                'duration': '3 months',
                'tasks': [
                    'Data cleaning',
                    'Statistical analysis',
                    'Report writing'
                ]
            },
            'total_duration': '20 months',
            'key_milestones': [
                {'milestone': 'Ethics approval', 'month': 3},
                {'milestone': 'Pilot complete', 'month': 5},
                {'milestone': '50% enrollment', 'month': 10},
                {'milestone': 'Intervention complete', 'month': 17},
                {'milestone': 'Analysis complete', 'month': 20}
            ]
        }

        return {
            'status': 'success',
            'experiment_id': 'EXP-20251116-001',
            'research_question': research_question,
            'hypothesis': hypothesis,
            'design': experimental_design,
            'sample_size_calculation': sample_size_calculation,
            'methodology': methodology,
            'statistical_analysis_plan': statistical_analysis_plan,
            'timeline': timeline,
            'threats_to_validity': threats_to_validity,
            'ethical_considerations': {
                'required_approvals': ['Institutional Review Board', 'Data Protection'],
                'informed_consent': 'Written informed consent required',
                'risk_level': 'Minimal risk',
                'participant_protections': [
                    'Voluntary participation',
                    'Right to withdraw',
                    'Confidentiality assured',
                    'Adverse event monitoring'
                ],
                'data_security': 'Encrypted storage, de-identified data'
            },
            'resources_required': {
                'personnel': {
                    'Principal Investigator': 1,
                    'Research Coordinators': 2,
                    'Data Collectors': 4,
                    'Interventionists': 6,
                    'Data Analyst': 1
                },
                'estimated_budget': {
                    'personnel': 250000,
                    'equipment': 30000,
                    'materials': 20000,
                    'participant_incentives': 18000,
                    'overhead': 95000,
                    'total': 413000,
                    'currency': 'USD'
                },
                'facilities': [
                    'Testing rooms (3)',
                    'Intervention space',
                    'Data storage server'
                ]
            },
            'deliverables': [
                'Detailed protocol document',
                'Standard Operating Procedures (SOPs)',
                'Case Report Forms (CRFs)',
                'Data management plan',
                'Statistical analysis plan',
                'Ethics application materials',
                'Training materials',
                'Recruitment materials'
            ],
            'recommendations': [
                'Conduct thorough pilot study before main trial',
                'Establish Data Safety Monitoring Board early',
                'Implement robust data quality procedures',
                'Plan for 15-20% attrition in sample size',
                'Pre-register study protocol (e.g., ClinicalTrials.gov)',
                'Ensure adequate training for all personnel',
                'Build in flexibility for protocol amendments',
                'Establish clear communication channels'
            ],
            'success_criteria': {
                'primary': 'Detect significant group difference in primary outcome',
                'secondary': [
                    'Achieve 85% participant retention',
                    'Maintain 90% intervention fidelity',
                    'Complete data collection on schedule',
                    'Stay within budget'
                ]
            }
        }

    def validate_params(self, params: Dict[str, Any]) -> bool:
        """Validate experiment design parameters."""
        if 'research_question' not in params:
            self.logger.error("Missing required field: research_question")
            return False

        valid_study_types = ['RCT', 'factorial', 'crossover', 'observational', 'quasi-experimental']
        study_type = params.get('study_type', 'RCT')
        if study_type not in valid_study_types:
            self.logger.error(f"Invalid study_type: {study_type}")
            return False

        return True
