****************************************
Short helpfile for action TD_EXPONENTIALLY_MODIFIED_GAUSSIAN
****************************************

The following options are available

          SHIFT_TO_ZERO - ( default=off ) Shift the minimum value of the target 
                          distribution to zero. This can for example be used to avoid negative 
                          values in the target distribution. If this option is active the 
                          distribution will be automatically normalized. 
              NORMALIZE - ( default=off ) Renormalized the target distribution over 
                          the intervals on which it is defined to make sure that it is 
                          properly normalized to 1. In most cases this should not be needed as 
                          the target distributions should be normalized. The code will 
                          issue a warning (but still run) if this is needed for some 
                          reason. 
                 CENTER - The center of each exponentially modified Gaussian 
                          distributions.. You can use multiple instances of this keyword i.e. 
                          CENTER1, CENTER2, CENTER3... 
                  SIGMA - The sigma parameters for each exponentially modified 
                          Gaussian distributions.. You can use multiple instances of this 
                          keyword i.e. SIGMA1, SIGMA2, SIGMA3... 
                 LAMBDA - The lambda parameters for each exponentially modified 
                          Gaussian distributions. You can use multiple instances of this 
                          keyword i.e. LAMBDA1, LAMBDA2, LAMBDA3... 
                WEIGHTS - The weights of the distributions. By default all are 
                          weighted equally. 
    WELLTEMPERED_FACTOR - Broaden the target distribution such that it is taken as 
                          [p(s)]^(1/gamma) where gamma is the well tempered factor given here. If this 
                          option is active the distribution will be automatically 
                          normalized. 


