Missing Value

There are the parameters default_value and out_of_bounds_value, but both are designed for return statements. The extract functions expect to have a numpy.array with nans for missing data. But if a data set has a different missing value (e.g. -200 for GHS data) this is not working. It is very likely, that this wasn't a problem up to now, because if the missing value is lower than the set min_valid value (in views.py), this value was anyway treated as missing resp. invalid. But maybe it would be better to explicitly name the missing_value in the view setup.