<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def make_image(imagesize, voxval=0, spacing=None, origin=None, direction=None, has_components=False, pixeltype='float'):
 """ Make an image with given size and voxel value or given a mask and vector ANTsR function: `makeImage` Arguments --------- shape : tuple/ANTsImage input image size or mask voxval : scalar input image value or vector, size of mask spacing : tuple/list image spatial resolution origin : tuple/list image spatial origin direction : list/ndarray direction matrix to convert from index to physical space components : boolean whether there are components per pixel or not pixeltype : float data type of image values Returns ------- ANTsImage """

    if isinstance(imagesize, iio.ANTsImage):
        img = imagesize.clone()
        sel = imagesize > 0
        if voxval.ndim > 1:
                voxval = voxval.flatten()
        if (len(voxval) == int((sel>0).sum())) or (len(voxval) == 0):
            img[sel] = voxval
        else:
            raise ValueError('Num given voxels %i not same as num positive values %i in `imagesize`' % (len(voxval), int((sel>0).sum())))
        return img
    else:
        if isinstance(voxval, (tuple,list,np.ndarray)):
            array = np.asarray(voxval).astype('float32').reshape(imagesize)
        else:
            array = np.full(imagesize,voxval,dtype='float32')
        image = from_numpy(array, origin=origin, spacing=spacing,
                            direction=direction, has_components=has_components)
        return image.clone(pixeltype)