comparison COBRAxy/flux_simulation_beta.py @ 479:a036b8d3642f draft

Uploaded

478:78b28b2ee1f0

        optgp = OptGPSampler(model, thinning, seed)
        samples = optgp.sample(n_samples)
        
        # Save as numpy array (more memory efficient)
        batch_filename = f"{ARGS.output_path}/{model_name}_{i}_OPTGP.npy"
        np.save(batch_filename, samples.values)
        
        seed += 1
    
    # Merge all batches into a single DataFrame
    all_samples = []

            )
        
        # Save as numpy array (more memory efficient)
        batch_filename = f"{ARGS.output_path}/{model_name}_{i}_CBS.npy"
        utils.logWarning(batch_filename, ARGS.out_log)
        np.save(batch_filename, samples.values)
    
    # Merge all batches into a single DataFrame
    all_samples = []
    
    for i in range(n_batches):

479:a036b8d3642f

        optgp = OptGPSampler(model, thinning, seed)
        samples = optgp.sample(n_samples)
        
        # Save as numpy array (more memory efficient)
        batch_filename = f"{ARGS.output_path}/{model_name}_{i}_OPTGP.npy"
        np.save(batch_filename, samples.to_numpy())
        
        seed += 1
    
    # Merge all batches into a single DataFrame
    all_samples = []

            )
        
        # Save as numpy array (more memory efficient)
        batch_filename = f"{ARGS.output_path}/{model_name}_{i}_CBS.npy"
        utils.logWarning(batch_filename, ARGS.out_log)
        np.save(batch_filename, samples.to_numpy())
    
    # Merge all batches into a single DataFrame
    all_samples = []
    
    for i in range(n_batches):