Function for Calculating Pignistic Probability in DS Evidence Theory

This function implements the Pignistic probability transformation for Dempster-Shafer (DS) evidence theory. The algorithm efficiently converts basic probability assignments (BPAs) into probability distributions over singleton propositions, enabling more intuitive decision-making analysis. Key implementation features include handling of focal elements, normalization procedures, and belief mass redistribution across hypothesis space. Users can reference the comprehensive help documentation within the file to understand input parameter requirements (evidence matrix structure), output formats (probability vectors), and computational rules including conflict management between evidence sources. This tool facilitates rapid and accurate probability calculations for DS theory applications, supporting advanced research in uncertainty reasoning and evidence fusion. The function employs vectorized operations for optimal performance with large evidence sets, and includes error checking for evidence normalization and proposition consistency.