def METHOD_NAME():
    # Test saving a 16384 x 16384 image
    OpenDatabase(silo_data_path("curv2d.silo"))
    AddPlot("Pseudocolor", "d")
    DrawPlots()
    view2=GetView2D()
    view2.fullFrameActivationMode=view2.Off
    SetView2D(view2)
    swa=SaveWindowAttributes()
    # ensure the image is written to the run_dir by providing full path
    imgOutName=pjoin(TestEnv.params["run_dir"], "image_16384x16384.png")
    swa.width = 16384
    swa.height = 16384
    swa.fileName = imgOutName
    swa.family = 0
    SetSaveWindowAttributes(swa)
    SaveWindow()
    # Comparing md5 sum instead of image, since the image is large.
    md5_hash = hashlib.md5()
    with open(imgOutName, "rb") as f:
        # Read and update hash in chunks of 4K
        for byte_block in iter(lambda: f.read(4096),b""):
            md5_hash.update(byte_block)
    TestValueEQ("md5 hash for 16384x16384 image", md5_hash.hexdigest(), "9196b516c25ecbeac1fab4cd54ee0c59")