Avoid C update with negative weights for (bad) injected solutions

[nikohansen]

Injecting always the same arbitrary bad solution twice or more often leads to a failure, similar to the one observe here

es = cma.CMAEvolutionStrategy(8 * [5], 10, {'ftarget': 1e-9,
                                           #'CMA_active': 0,
                                          })
fit = cma.ff.sphere
while not es.stop():
    X = es.ask()
    F = [fit(x) for x in X]
    es.tell(X, F)
    es.inject(2 * [es.N * [100]])
    es.disp(300)
    es.logger.add()
cma.plot(xsemilog=True);

A simple fix is to turn off 'CMA_active'. A (much) better fix would be to catch the points that don't comply with the sample distribution (as is already done) and ignore them in the update of the covariance matrix if they are bad (needs to be done).

[nikohansen]

Fixed in the upcoming release.