Adding univariate calls for cross CMI

java/source/infodynamics/measures/continuous/ConditionalMutualInfoCalculatorMultiVariate.java

@@ -623,6 +623,38 @@ public interface ConditionalMutualInfoCalculatorMultiVariate
 	public double[] computeLocalUsingPreviousObservations(double states1[][], double states2[][], double[][] condStates)
 		throws Exception;
 
+	/**
+	 * <p>As per {@link #computeLocalUsingPreviousObservations(double[][], double[][], double[][])}
+	 * but can only be used where dimensions of
+	 * states1 and states2 have been set to 1.</p>
+	 * 
+	 * @param states1 series of univariate observations for variable 1
+	 * @param states2 series of univariate observations for variable 2
+	 *  Length must match <code>states1</code>, and their indices must correspond.
+	 * @param condStates series of multivariate observations for the conditional
+	 *  (first index is time or observation index, second is variable number).
+	 *  Length must match <code>states1</code>, and their indices must correspond.
+	 * @return the series of local conditional MI values.
+	 * @throws Exception
+	 */
+	public double[] computeLocalUsingPreviousObservations(double states1[], double states2[], double[][] condStates)
+		throws Exception;
+
+	/**
+	 * <p>As per {@link #computeLocalUsingPreviousObservations(double[][], double[][], double[][])}
+	 * but can only be used all dimensions have been set to 1.</p>
+	 * 
+	 * @param states1 series of univariate observations for variable 1
+	 * @param states2 series of univariate observations for variable 2.
+	 *  Length must match <code>states1</code>, and their indices must correspond.
+	 * @param condStates series of univariate observations for the conditional.
+	 *  Length must match <code>states1</code>, and their indices must correspond.
+	 * @return the series of local conditional MI values.
+	 * @throws Exception
+	 */
+	public double[] computeLocalUsingPreviousObservations(double states1[], double states2[], double[] condStates)
+		throws Exception;
+
 	/**
 	 * @throws Exception if the implementing class computes MI without
 	 * explicit observations (e.g. see

java/source/infodynamics/measures/continuous/ConditionalMutualInfoMultiVariateCommon.java

@@ -934,6 +934,34 @@ public abstract class ConditionalMutualInfoMultiVariateCommon implements
 		// Compute the MI
 		return miSurrogateCalculator.computeAverageLocalOfObservations();
 	}
+	
+	@Override
+	public double[] computeLocalUsingPreviousObservations(double[] states1, double[] states2, double[][] condStates)
+			throws Exception {
+		if ((dimensionsVar1 != 1) || (dimensionsVar2 != 1)) {
+			throw new Exception("The number of source and dest dimensions (having been initialised to " +
+					dimensionsVar1 + " and " + dimensionsVar2 + ") can only be 1 when " +
+					"the univariate computeLocalUsingPreviousObservations(double[],double[],double[][]) " + 
+					"method is called");
+		}
+		return computeLocalUsingPreviousObservations(MatrixUtils.reshape(states1, states1.length, 1),
+						MatrixUtils.reshape(states2, states2.length, 1),
+						condStates);
+	}
+
+	@Override
+	public double[] computeLocalUsingPreviousObservations(double[] states1, double[] states2, double[] condStates)
+			throws Exception {
+		if ((dimensionsVar1 != 1) || (dimensionsVar2 != 1) || (dimensionsCond != 1)) {
+			throw new Exception("The number of source, dest and conditional dimensions (having been initialised to " +
+					dimensionsVar1 + ", " + dimensionsVar2 + " and " + dimensionsCond + ") can only be 1 when " +
+					"the univariate computeLocalUsingPreviousObservations(double[],double[],double[]) " + 
+					"method is called");
+		}
+		return computeLocalUsingPreviousObservations(MatrixUtils.reshape(states1, states1.length, 1),
+						MatrixUtils.reshape(states2, states2.length, 1),
+						MatrixUtils.reshape(condStates, condStates.length, 1));
+	}
 
 	@Override
 	public void setDebug(boolean debug) {