def newToQImage(array):
    """Converts a numpy array to a QImage 
    A Python version of PyQt4.Qwt5.toQImage(array) in PyQwt >= 5.2.
    Function written by Gerard Vermeulen
    """
    if array.ndim != 2:
        raise RuntimeError('array must be 2-D')
    height, width = array.shape
    if array.dtype == numpy.uint8:
        # image = QImage(array, width, height, QImage.Format_Indexed8)
        # The next statement shows that QImage does not increase the
        # reference count of the buffer object to keep the data valid.
        image = Qt.QImage(
            array.tostring(), width, height, Qt.QImage.Format_Indexed8)
        image.setNumColors(256)
        for i in range(256):
            image.setColor(i, qRgb(i, i, i))
        return image
    elif array.dtype == numpy.uint32:
        image = Qt.QImage(
            array.tostring(), width, height, Qt.QImage.Format_ARGB32)
        return image
    else:
        raise RuntimeError('array.dtype must be uint8 or uint32')
def oldToQImage(array):
    """Converts a numpy array to a QImage 
    A Python version of PyQt4.Qwt5.toQImage(array) in PyQwt < 5.2.
    Function written by Gerard Vermeulen 
    """
    if array.ndim != 2:
        raise RuntimeError('array must be 2-D')
    nx, ny = array.shape # width, height
    xstride, ystride = array.strides
    if array.dtype == numpy.uint8:
        image = QImage(nx, ny, QImage.Format_Indexed8)
        f_array = numpy.reshape(array,(nx*ny,),order='F')
        for j in range(ny):
            pointer = image.scanLine(j)
            pointer.setsize(nx*array.itemsize)
            memory = numpy.frombuffer(pointer, numpy.uint8)
            first_value = j*nx
            last_value = (j+1)*nx 
            memory[:] = f_array[first_value:last_value]
        image.setColorCount(256)
        for i in range(256):
            image.setColor(i, qRgb(i, i, i))
        return image
    elif array.dtype == numpy.uint32:
        image = Qt.QImage(
            array.tostring(), width, height, Qt.QImage.Format_ARGB32)
        f_array = numpy.reshape(array,(nx*ny,),order='F')
        for j in xrange(ny):
            pointer = image.scanLine(j)
            pointer.setsize(nx*array.itemsize)
            memory = numpy.frombuffer(pointer, numpy.uint32)
            first_value = j*nx
            last_value = (j+1)*nx 
            memory[:] = f_array[first_value:last_value]
        return image
    else:
        raise RuntimeError('array.dtype must be uint8 or uint32')