package affectors;

import java.io.PrintWriter;
import java.util.Enumeration;
import java.util.Vector;
import main.Node;
import main.Cell;
import main.Globals;

/** This is a meta-affector which sums together transcriptional activation terms while keeping
	the total transcription rate less than or equal to 1. Each sub-affector is assumed
	to be giving a probability per some unit time of the transcription machinery binding
	to the promoter and starting transcription. MultiEnhancerAff figures out the total probability
	of the transcription machinery based on the individual probabilities.

<p> <b>Formula</b>
<br>dnodex/dt = 1 - (1 - alpha_T1/max_alpha * T1)(1 - alpha_T2/max_alpha * T2) ... (1 - alpha_Tn/max_alpha * Tn)
<br>where T1 ... Tn are the sub-affector values and max_alpha is the max of all the alpha's

<p> <b>Parameters</b>
<br>There needs to be one alpha parameter per subaffector. The alphas give the relative weights
of each subaffectors contribution to the total value.

<p> <b>Usage</b>
<code><font size = "3"><br>&nodex
<blockquote> &EnhancerRegionAff
<blockquote>    	&MultiEnhancerAff	alpha_AC	alpha_SC
<blockquote>		&TxnSiteActivatorAff	AC	K_ACsc	nu_ACsc
					<br>&TxnSiteActivatorAff	SC	K_SCsc	nu_SCsc </blockquote>
	&endMultiEnhancerAff</blockquote>
&endEnhancerRegionAff	
</blockquote>
&endnodex</code></font>

*/
public class MultiEnhancerAff extends EnhancerRegionAff implements Cloneable	{

	int			[]	alphas;
	
	static final String		desc = "Probabilistic sum of several other affectors";
	static final int	[]	whichSides = { -1 };

	public MultiEnhancerAff() {	}

	protected void setLabelsAndTypes()	{
		setDescriptions(this.desc, null, null);
		setSided(true, whichSides);

		this.Type[GUI_CAPABLE] = 0;
		this.Type[CERTIFICATION] = Affector.RETURNS_DERIV;
		this.Type[MATHTYPE] = Affector.FF;	// ???? None really fit
		this.Type[TERMTYPE] = Affector.PRODUCTION;
	}

	public void setParameterNumbers(int [] param_nums)
	{
		if(param_nums.length != numAffectors)
		{
			System.out.println("Error: Number of alpha parameters does not match number of affectors in MultiEnhancer meta-affector");
			return;
		}
		
		alphas = new int[param_nums.length];
		
		for(int i = 0; i < param_nums.length; i++)
			alphas[i] = param_nums[i];
	}

	/** Overrides Affector.getValue() to multiply together the values from
		all the subsidiary affectors. */
	public float getValue(Node which_node)	 {
		float	value = 1f;
		int		i;
		
		// Find scaling for alphas
		float max_alpha = 0.0000001f;
		for(i = 0; i < numAffectors; i++) {
			if(params[alphas[i]] > max_alpha) max_alpha = params[alphas[i]];
		}

		for(i = 0; i < numAffectors; i++) {
			float	aff_val = affectors[i].getValue(which_node) * params[alphas[i]] / max_alpha;
			if(aff_val > 1.0) aff_val = 1f;
			value *= (1f - aff_val);
		}
		return (1f - value);
	}
	
	/** Overrides Affector.getNCValue() to multiply together the values from
		all the subsidiary affectors. */
	public float getNCValue(Node which_node)  {
		if(containsTarget) {
			float	value = 1f;
			int		i;
			
			// Find scaling for alphas
			float max_alpha = 0.0000001f;
			for(i = 0; i < numAffectors; i++) {
				if(params[alphas[i]] > max_alpha) max_alpha = params[alphas[i]];
			}
			
			for(i = 0; i < numAffectors; i++) {
				float	aff_val = affectors[i].getNCValue(which_node) * params[alphas[i]] / max_alpha;
				if(aff_val > 1.0) aff_val = 1f;
				value *= (1f - aff_val);
			}
			return (1f - value);
		}
		
		else return super.getNCValue(which_node);
	}



/* The rest of these functions are overrides of Affector functions so that they
	work right for this class. */
	
	public Affector copy()	{
		MultiEnhancerAff element = null;
		try { element = (MultiEnhancerAff)this.clone(); }
		catch(CloneNotSupportedException e) { System.out.println("Error cloning MultiEnhancerAff: " + e.toString()); }
		element.affectors = new Affector[3];
		element.numAffectors = 0;
		for(int i = 0; i < numAffectors; i++) {
			element.addAffector(affectors[i].copy());
		}
		element.this_debug_num = debug_num++;
		return element;
	}

	
}