def manim(self, line, cell=None, local_ns=None):
r"""Render Manim scenes contained in IPython cells.
Works as a line or cell magic.
.. note::
This line and cell magic works best when used in a JupyterLab
environment: while all of the functionality is available for
classic Jupyter notebooks as well, it is possible that videos
sometimes don't update on repeated execution of the same cell
if the scene name stays the same.
This problem does not occur when using JupyterLab.
Please refer to `<https://jupyter.org/>`_ for more information about JupyterLab
and Jupyter notebooks.
Usage in line mode::
%manim MyAwesomeScene [CLI options]
Usage in cell mode::
%%manim MyAwesomeScene [CLI options]
class MyAweseomeScene(Scene):
def construct(self):
...
Run ``%manim -h`` for possible command line interface options.
"""
if cell:
exec(cell, local_ns)
args = line.split()
if not len(
args
) or "-h" in args or "--help" in args or "--version" in args:
main(args, standalone_mode=False, prog_name="manim")
return
modified_args = ["--jupyter"] + args[:-1] + [""] + [args[-1]]
args = main(modified_args,
standalone_mode=False,
prog_name="manim")
with tempconfig(local_ns.get("config", {})):
config.digest_args(args)
exec(f"{config['scene_names'][0]}().render()", local_ns)
local_path = Path(config["output_file"]).relative_to(
Path.cwd())
tmpfile = (Path(config["media_dir"]) / "jupyter" /
f"{_video_hash(local_path)}{local_path.suffix}")
if local_path in self.rendered_files:
self.rendered_files[local_path].unlink()
self.rendered_files[local_path] = tmpfile
os.makedirs(tmpfile.parent, exist_ok=True)
shutil.copy(local_path, tmpfile)
file_type = mimetypes.guess_type(config["output_file"])[0]
if file_type.startswith("image"):
display(Image(filename=config["output_file"]))
return
# videos need to be embedded when running in google colab
video_embed = "google.colab" in str(get_ipython())
display(
Video(
tmpfile,
html_attributes=
f'controls autoplay loop style="max-width: {config["media_width"]};"',
embed=video_embed,
))
def manim(self, line, cell=None, local_ns=None):
r"""Render Manim scenes contained in IPython cells.
Works as a line or cell magic.
.. hint::
This line and cell magic works best when used in a JupyterLab
environment: while all of the functionality is available for
classic Jupyter notebooks as well, it is possible that videos
sometimes don't update on repeated execution of the same cell
if the scene name stays the same.
This problem does not occur when using JupyterLab.
Please refer to `<https://jupyter.org/>`_ for more information about JupyterLab
and Jupyter notebooks.
Usage in line mode::
%manim [CLI options] MyAwesomeScene
Usage in cell mode::
%%manim [CLI options] MyAwesomeScene
class MyAweseomeScene(Scene):
def construct(self):
...
Run ``%manim -h`` and ``%manim render -h`` for possible command line interface options.
.. note::
The maximal width of the rendered videos that are displayed in the notebook can be
configured via the ``media_width`` configuration option. The default is set to ``25vw``,
which is 25% of your current viewport width. To allow the output to become as large
as possible, set ``config.media_width = "100%"``.
Examples
--------
First make sure to put ``import manim``, or even ``from manim import *``
in a cell and evaluate it. Then, a typical Jupyter notebook cell for Manim
could look as follows::
%%manim -v WARNING --disable_caching -qm BannerExample
config.media_width = "75%"
class BannerExample(Scene):
def construct(self):
self.camera.background_color = "#ece6e2"
banner_large = ManimBanner(dark_theme=False).scale(0.7)
self.play(banner_large.create())
self.play(banner_large.expand())
Evaluating this cell will render and display the ``BannerExample`` scene defined in the body of the cell.
.. note::
In case you want to hide the red box containing the output progress bar, the ``progress_bar`` config
option should be set to ``None``. This can also be done by passing ``--progress_bar None`` as a
CLI flag.
"""
if cell:
exec(cell, local_ns)
args = line.split()
if not len(
args
) or "-h" in args or "--help" in args or "--version" in args:
main(args, standalone_mode=False, prog_name="manim")
return
modified_args = ["--jupyter"] + args[:-1] + [""] + [args[-1]]
args = main(modified_args,
standalone_mode=False,
prog_name="manim")
with tempconfig(local_ns.get("config", {})):
config.digest_args(args)
exec(f"{config['scene_names'][0]}().render()", local_ns)
local_path = Path(config["output_file"]).relative_to(
Path.cwd())
tmpfile = (Path(config["media_dir"]) / "jupyter" /
f"{_generate_file_name()}{local_path.suffix}")
if local_path in self.rendered_files:
self.rendered_files[local_path].unlink()
self.rendered_files[local_path] = tmpfile
os.makedirs(tmpfile.parent, exist_ok=True)
shutil.copy(local_path, tmpfile)
file_type = mimetypes.guess_type(config["output_file"])[0]
if file_type.startswith("image"):
display(Image(filename=config["output_file"]))
return
# videos need to be embedded when running in google colab
video_embed = "google.colab" in str(get_ipython())
display(
Video(
tmpfile,
html_attributes=
f'controls autoplay loop style="max-width: {config["media_width"]};"',
embed=video_embed,
))
def manim(
self,
line: str,
cell: str = None,
local_ns: dict[str, Any] = None,
) -> None:
r"""Render Manim scenes contained in IPython cells.
Works as a line or cell magic.
.. hint::
This line and cell magic works best when used in a JupyterLab
environment: while all of the functionality is available for
classic Jupyter notebooks as well, it is possible that videos
sometimes don't update on repeated execution of the same cell
if the scene name stays the same.
This problem does not occur when using JupyterLab.
Please refer to `<https://jupyter.org/>`_ for more information about JupyterLab
and Jupyter notebooks.
Usage in line mode::
%manim [CLI options] MyAwesomeScene
Usage in cell mode::
%%manim [CLI options] MyAwesomeScene
class MyAweseomeScene(Scene):
def construct(self):
...
Run ``%manim --help`` and ``%manim render --help`` for possible command line interface options.
.. note::
The maximal width of the rendered videos that are displayed in the notebook can be
configured via the ``media_width`` configuration option. The default is set to ``25vw``,
which is 25% of your current viewport width. To allow the output to become as large
as possible, set ``config.media_width = "100%"``.
Examples
--------
First make sure to put ``import manim``, or even ``from manim import *``
in a cell and evaluate it. Then, a typical Jupyter notebook cell for Manim
could look as follows::
%%manim -v WARNING --disable_caching -qm BannerExample
config.media_width = "75%"
class BannerExample(Scene):
def construct(self):
self.camera.background_color = "#ece6e2"
banner_large = ManimBanner(dark_theme=False).scale(0.7)
self.play(banner_large.create())
self.play(banner_large.expand())
Evaluating this cell will render and display the ``BannerExample`` scene defined in the body of the cell.
.. note::
In case you want to hide the red box containing the output progress bar, the ``progress_bar`` config
option should be set to ``None``. This can also be done by passing ``--progress_bar None`` as a
CLI flag.
"""
if cell:
exec(cell, local_ns)
args = line.split()
if not len(args) or "-h" in args or "--help" in args or "--version" in args:
main(args, standalone_mode=False, prog_name="manim")
return
modified_args = self.add_additional_args(args)
args = main(modified_args, standalone_mode=False, prog_name="manim")
with tempconfig(local_ns.get("config", {})):
config.digest_args(args)
renderer = None
if config.renderer == "opengl":
# Check if the imported mobjects extend the OpenGLMobject class
# meaning ConvertToOpenGL did its job
if "OpenGLMobject" in map(lambda cls: cls.__name__, Group.mro()):
from manim.renderer.opengl_renderer import OpenGLRenderer
renderer = OpenGLRenderer()
else:
logger.warning(
"Renderer must be set to OpenGL in the configuration file "
"before importing Manim! Using cairo renderer instead.",
)
config.renderer = "cairo"
try:
SceneClass = local_ns[config["scene_names"][0]]
scene = SceneClass(renderer=renderer)
scene.render()
finally:
# Shader cache becomes invalid as the context is destroyed
shader_program_cache.clear()
# Close OpenGL window here instead of waiting for the main thread to
# finish causing the window to stay open and freeze
if renderer is not None and renderer.window is not None:
renderer.window.close()
if config["output_file"] is None:
logger.info("No output file produced")
return
local_path = Path(config["output_file"]).relative_to(Path.cwd())
tmpfile = (
Path(config["media_dir"])
/ "jupyter"
/ f"{_generate_file_name()}{local_path.suffix}"
)
if local_path in self.rendered_files:
self.rendered_files[local_path].unlink()
self.rendered_files[local_path] = tmpfile
os.makedirs(tmpfile.parent, exist_ok=True)
shutil.copy(local_path, tmpfile)
file_type = mimetypes.guess_type(config["output_file"])[0]
if file_type.startswith("image"):
display(Image(filename=config["output_file"]))
return
# videos need to be embedded when running in google colab
video_embed = "google.colab" in str(get_ipython())
display(
Video(
tmpfile,
html_attributes=f'controls autoplay loop style="max-width: {config["media_width"]};"',
embed=video_embed,
),
)
class LargeDepthFirstSearchMazeGenerationScene(
DepthFirstSearchMazeGenerationScene, LargeMazeGenerationScene):
pass
class LargeKruskalsMazeGenerationScene(KruskalsMazeGenerationScene,
LargeMazeGenerationScene):
pass
class LargePrimsMazeGenerationScene(PrimsMazeGenerationScene,
LargeMazeGenerationScene):
pass
class LargeWilsonsMazeGenerationScene(WilsonsMazeGenerationScene,
LargeMazeGenerationScene):
pass
if __name__ == '__main__':
scene_name = sys.argv[1] if len(sys.argv) > 1 else GraphToGrid.__name__
sys.argv[1:] = ['-p', '-ql', __file__, scene_name]
main()