def render_nlpgraphics(renderer,
filtered,
filepath: str = None,
output_type: str = 'SVG'):
"""Render an NLPInstance into the supported formats.
Args:
renderer (SingleSentenceRenderer or AlignmentRenderer): The renderer object.
filtered (NLPInstance): The filtered NLPInstane to be rendered.
filepath (str): The path of the outputfile.
output_type (str): The type of the output format.
Returns: The bytesting of the rendered object if needed.
"""
svg_scene = Drawing(size=('100%', '100%')) # default: '100%', '100%'
dim = renderer.render(filtered, svg_scene)
# Set the actual computed dimension without rerendering
svg_scene.attribs['width'] = dim[0]
svg_scene.attribs['height'] = dim[1]
svg_bytes = svg_scene.tostring().encode('UTF-8')
if filepath is not None and output_type == 'SVG':
svg_scene.saveas(filepath)
elif filepath is None and output_type == 'SVG':
return svg_bytes
elif output_type == 'PS':
cairosvg.svg2ps(bytestring=svg_bytes, write_to=filepath)
elif output_type == 'PDF':
cairosvg.svg2pdf(bytestring=svg_bytes, write_to=filepath)
else:
raise ValueError(
'{0} not a supported filetype!'.format(output_type))
def test_save_as(self):
fn = 'test_drawing.svg'
if os.path.exists(fn):
os.remove(fn)
dwg = Drawing()
dwg.saveas(fn)
self.assertTrue(os.path.exists(fn))
os.remove(fn)
def test_save_as(self):
fn = 'test_drawing.svg'
if os.path.exists(fn):
os.remove(fn)
dwg = Drawing()
dwg.saveas(fn)
self.assertTrue(os.path.exists(fn))
os.remove(fn)
def test_save_as(self):
fn = Path('test_drawing.svg')
if fn.exists():
fn.unlink()
dwg = Drawing()
dwg.saveas(str(fn))
self.assertTrue(fn.exists())
fn.unlink()
