WGAN: Why 1-d_loss?

So i plotted the loss of the critic during training. It starts off negative and then converges to zero as the generated samples improve. The way i see it, this means the Wasserstein distance between the Real and generated samples is getting smaller. Now my question is, why is d_loss starting at a negative value? and why is the code printing d_loss as 1-d_loss?

In other words, can someone explain to me how -d_loss and the wasserstein estimate are related? Why are these two things the same?