jplephem/daf.py
def map_array(self, start, end):
        """Return floats from `start` to `end` inclusive, indexed from 1.

        Instead of pausing to load all of the floats into RAM, this
        routine creates a memory map which will load data from the file
        only as it is accessed, and then will let it expire back out to
        disk later.  This is very efficient for large data sets to which
        you need random access.

        """
        if self._array is None:
            self._map, skip = self.map_words(1, self.free - 1)
            assert skip == 0
            self._array = ndarray(self.free - 1, self.endian + 'd', self._map)
        return self._array[start - 1 : end]
def map_array(self, start, end):
        """Return floats from `start` to `end` inclusive, indexed from 1.

        Instead of pausing to load all of the floats into RAM, this
        routine creates a memory map which will load data from the file
        only as it is accessed, and then will let it expire back out to
        disk later.  This is very efficient for large data sets to which
        you need random access.

        """
        if self._array is None:
            self._map, skip = self.map_words(1, self.free - 1)
            assert skip == 0
            self._array = ndarray(self.free - 1, self.endian + 'd', self._map)
        return self._array[start - 1 : end]
Return floats from `start` to `end` inclusive, indexed from 1.

        Instead of pausing to load all of the floats into RAM, this
        routine creates a memory map which will load data from the file
        only as it is accessed, and then will let it expire back out to
        disk later.  This is very efficient for large data sets to which
        you need random access.