def _fromdata(self, data, maxval=None):
        data = numpy.array(data, ndmin=2, copy=True)
        if data.dtype.kind not in "uib":
            raise ValueError("not an integer type: %s" % data.dtype)
        if data.dtype.kind == 'i' and numpy.min(data) < 0:
            raise ValueError("data out of range: %i" % numpy.min(data))
        if maxval is None:
            maxval = numpy.max(data)
            maxval = 255 if maxval < 256 else 65535
        if maxval < 0 or maxval > 65535:
            raise ValueError("data out of range: %i" % maxval)
        data = data.astype('u1' if maxval < 256 else '>u2')
        self._data = data
        if data.ndim > 2 and data.shape[-1] in (3, 4):
            self.depth = data.shape[-1]
            self.width = data.shape[-2]
            self.height = data.shape[-3]
            self.magicnum = b'P7' if self.depth == 4 else b'P6'
        else:
            self.depth = 1
            self.width = data.shape[-1]
            self.height = data.shape[-2]
            self.magicnum = b'P5' if maxval > 1 else b'P4'
        self.maxval = maxval
        self.tupltypes = [self._types[self.magicnum]]
        self.header = self._header()
Initialize instance from numpy array.
dataset/ETHPy150Open SheffieldML/GPy/GPy/util/netpbmfile.py/NetpbmFile._fromdata