Check estimated propensity scores

[MalteKurz]

Currently we only check that predictions are finite in https://github.com/DoubleML/doubleml-for-py/blob/b3cbdb572fce435c18ec67ca323645900fc901b5/doubleml/_utils.py#L204-L208

We may additionally want to check that estimated probabilities are strictly in (0,1) (maybe with some eps threshold). Otherwise, the values of the score functions are likely infinite / missing. It may make sense to not let it directly fail but throw a warning. This way one for example would still have the option to discard these observations from the estimation of the target parameter or to choose a score function where this is accounted for, e.g., trimmed.