data/experiments/
├── YYYYMMDD_HHMMSS_type.h5           # Experiment data
└── YYYYMMDD_HHMMSS_type_scripts/     # Scripts for this experiment
    └── analysis_name.py

#!/usr/bin/env python
"""Description of what this script does."""
import sys
import json
from pathlib import Path

# Import core storage
from core import storage

DATA_DIR = Path(__file__).parent.parent.parent  # data/experiments/

# Get experiment ID from command line
experiment_id = sys.argv[1]

# Load experiment data
exp = storage.load_experiment(experiment_id, DATA_DIR)
if exp is None:
    print(json.dumps({"error": f"Experiment {experiment_id} not found"}))
    sys.exit(1)

data = exp.to_dict()

# =============================================================================
# Your analysis code here
# =============================================================================

import numpy as np

# Available data:
#   data['params']   - input parameters dict
#   data['results']  - scalar results dict
#   data['arrays']   - numerical arrays dict (e.g., frequencies, amplitudes)
#   data['plots']    - plot data list

# Example:
# frequencies = np.array(data['arrays']['frequencies'])
# amplitudes = np.array(data['arrays']['amplitudes'])

result = {
    "status": "success",
    # your results here
}

print(json.dumps(result))

python /path/to/script.py <experiment_id>

python data/experiments/20240315_143022_qubit_spectroscopy_scripts/fit_peak.py 20240315_143022_qubit_spectroscopy

# Find experiments of same type
lab(action="history_list", filter_type="qubit_spectroscopy")

# Check each for scripts
ls data/experiments/20240315_143022_qubit_spectroscopy_scripts/

# Read a script to copy/adapt
cat data/experiments/.../fit_peak.py