def override(self, timeseries, timestep, override_val):

        val = override_val
        new_amount = timeseries.shape[0]
        misses = MissingDataFinder().find(timeseries, timestep)

        starts = {}
        for start, end, amount in misses:
            new_amount += amount
            starts[start] = [end, amount]

        # allocate new numpy array
        filled = zeros((new_amount,), dtype=[('date', int32),\
                ('corrected_score', float32),\
                ('speed', float32)])

        keys = starts.keys()
        current_index = 0

        for i in range(len(timeseries)):
            if(i in keys):
            # missing data starting
                cs = 'corrected_score'
                d = 'date'

                # add start measurement
                filled[current_index] = timeseries[i]
                current_index += 1

                end, n = starts[i]
                for j in range(1, n + 1):
                    new_timestep = timeseries[i][d] + j * timestep
                    filled[current_index] = (new_timestep, val, val)
                    current_index += 1
            else:
                filled[current_index] = timeseries[i]
                current_index += 1

        return filled
dataset/ETHPy150Open cigroup-ol/windml/windml/preprocessing/override_missing.py/OverrideMissing.override/original