Source code for yt.visualization.volume_rendering.scene

import builtins
import functools
from collections import OrderedDict
from typing import Optional, Union

import numpy as np

from yt.config import ytcfg
from yt.funcs import mylog
from yt.units.dimensions import length  # type: ignore
from yt.units.unit_registry import UnitRegistry  # type: ignore
from yt.units.yt_array import YTArray, YTQuantity
from yt.utilities.exceptions import YTNotInsideNotebook
from yt.visualization._commons import get_canvas, validate_image_name

from .camera import Camera
from .render_source import (
    BoxSource,
    CoordinateVectorSource,
    GridSource,
    LineSource,
    MeshSource,
    OpaqueSource,
    PointSource,
    RenderSource,
    VolumeSource,
)
from .zbuffer_array import ZBuffer


[docs] class Scene: """A virtual landscape for a volume rendering. The Scene class is meant to be the primary container for the new volume rendering framework. A single scene may contain several Camera and RenderSource instances, and is the primary driver behind creating a volume rendering. This sets up the basics needed to add sources and cameras. This does very little setup, and requires additional input to do anything useful. Examples -------- This example shows how to create an empty scene and add a VolumeSource and a Camera. >>> import yt >>> from yt.visualization.volume_rendering.api import ( ... Camera, Scene, create_volume_source) >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = Scene() >>> source = create_volume_source(ds.all_data(), "density") >>> sc.add_source(source) >>> cam = sc.add_camera() >>> im = sc.render() Alternatively, you can use the create_scene function to set up defaults and then modify the Scene later: >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # Modify camera, sources, etc... >>> im = sc.render() """ _current = None _camera = None _unit_registry = None def __init__(self): r"""Create a new Scene instance""" super().__init__() self.sources = OrderedDict() self._last_render = None # A non-public attribute used to get around the fact that we can't # pass kwargs into _repr_png_() self._sigma_clip = None
[docs] def get_source(self, source_num=0): """Returns the volume rendering source indexed by ``source_num``""" return list(self.sources.values())[source_num]
def __getitem__(self, item): if item in self.sources: return self.sources[item] return self.get_source(item) @property def opaque_sources(self): """ Iterate over opaque RenderSource objects, returning a tuple of (key, source) """ for k, source in self.sources.items(): if isinstance(source, OpaqueSource) or issubclass( OpaqueSource, type(source) ): yield k, source @property def transparent_sources(self): """ Iterate over transparent RenderSource objects, returning a tuple of (key, source) """ for k, source in self.sources.items(): if not isinstance(source, OpaqueSource): yield k, source
[docs] def add_source(self, render_source, keyname=None): """Add a render source to the scene. This will autodetect the type of source. Parameters ---------- render_source: :class:`yt.visualization.volume_rendering.render_source.RenderSource` A source to contribute to the volume rendering scene. keyname: string (optional) The dictionary key used to reference the source in the sources dictionary. """ if keyname is None: keyname = "source_%02i" % len(self.sources) data_sources = (VolumeSource, MeshSource, GridSource) if isinstance(render_source, data_sources): self._set_new_unit_registry(render_source.data_source.ds.unit_registry) line_annotation_sources = (GridSource, BoxSource, CoordinateVectorSource) if isinstance(render_source, line_annotation_sources): lens_str = str(self.camera.lens) if "fisheye" in lens_str or "spherical" in lens_str: raise NotImplementedError( "Line annotation sources are not supported for %s." % (type(self.camera.lens).__name__), ) if isinstance(render_source, (LineSource, PointSource)): if isinstance(render_source.positions, YTArray): render_source.positions = ( self.arr(render_source.positions).in_units("code_length").d ) self.sources[keyname] = render_source return self
def __setitem__(self, key, value): return self.add_source(value, key) def _set_new_unit_registry(self, input_registry): self.unit_registry = UnitRegistry( add_default_symbols=False, lut=input_registry.lut ) # Validate that the new unit registry makes sense current_scaling = self.unit_registry["unitary"][0] if current_scaling != input_registry["unitary"][0]: for source in self.sources.items(): data_source = getattr(source, "data_source", None) if data_source is None: continue scaling = data_source.ds.unit_registry["unitary"][0] if scaling != current_scaling: raise NotImplementedError( "Simultaneously rendering data from datasets with " "different units is not supported" )
[docs] def render(self, camera=None): r"""Render all sources in the Scene. Use the current state of the Scene object to render all sources currently in the scene. Returns the image array. If you want to save the output to a file, call the save() function. Parameters ---------- camera: :class:`Camera`, optional If specified, use a different :class:`Camera` to render the scene. Returns ------- A :class:`yt.data_objects.image_array.ImageArray` instance containing the current rendering image. Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # Modify camera, sources, etc... >>> im = sc.render() >>> sc.save(sigma_clip=4.0, render=False) Altneratively, if you do not need the image array, you can just call ``save`` as follows. >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # Modify camera, sources, etc... >>> sc.save(sigma_clip=4.0) """ mylog.info("Rendering scene (Can take a while).") if camera is None: camera = self.camera assert camera is not None self._validate() bmp = self.composite(camera=camera) self._last_render = bmp return bmp
def _render_on_demand(self, render): # checks for existing render before rendering, in most cases we want to # render every time, but in some cases pulling the previous render is # desirable (e.g., if only changing sigma_clip or # saving after a call to sc.show()). if self._last_render is not None and not render: mylog.info("Found previously rendered image to save.") return if self._last_render is None: mylog.warning("No previously rendered image found, rendering now.") elif render: mylog.warning( "Previously rendered image exists, but rendering anyway. " "Supply 'render=False' to save previously rendered image directly." ) self.render() def _get_render_sources(self): return [s for s in self.sources.values() if isinstance(s, RenderSource)] def _setup_save(self, fname, render) -> str: self._render_on_demand(render) rensources = self._get_render_sources() if fname is None: # if a volume source present, use its affiliated ds for fname if len(rensources) > 0: rs = rensources[0] basename = rs.data_source.ds.basename if isinstance(rs.field, str): field = rs.field else: field = rs.field[-1] fname = f"{basename}_Render_{field}" # if no volume source present, use a default filename else: fname = "Render_opaque" fname = validate_image_name(fname) mylog.info("Saving rendered image to %s", fname) return fname
[docs] def save( self, fname: Optional[str] = None, sigma_clip: Optional[float] = None, render: bool = True, ): r"""Saves a rendered image of the Scene to disk. Once you have created a scene, this saves an image array to disk with an optional filename. This function calls render() to generate an image array, unless the render parameter is set to False, in which case the most recently rendered scene is used if it exists. Parameters ---------- fname: string, optional If specified, save the rendering as to the file "fname". If unspecified, it creates a default based on the dataset filename. The file format is inferred from the filename's suffix. Supported formats depend on which version of matplotlib is installed. Default: None sigma_clip: float, optional Image values greater than this number times the standard deviation plus the mean of the image will be clipped before saving. Useful for enhancing images as it gets rid of rare high pixel values. Default: None floor(vals > std_dev*sigma_clip + mean) render: boolean, optional If True, will always render the scene before saving. If False, will use results of previous render if it exists. Default: True Returns ------- Nothing Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # Modify camera, sources, etc... >>> sc.save("test.png", sigma_clip=4) When saving multiple images without modifying the scene (camera, sources,etc.), render=False can be used to avoid re-rendering. This is useful for generating images at a range of sigma_clip values: >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # save with different sigma clipping values >>> sc.save("raw.png") # The initial render call happens here >>> sc.save("clipped_2.png", sigma_clip=2, render=False) >>> sc.save("clipped_4.png", sigma_clip=4, render=False) """ fname = self._setup_save(fname, render) # We can render pngs natively but for other formats we defer to # matplotlib. if fname.endswith(".png"): self._last_render.write_png(fname, sigma_clip=sigma_clip) else: from matplotlib.figure import Figure shape = self._last_render.shape fig = Figure((shape[0] / 100.0, shape[1] / 100.0)) canvas = get_canvas(fig, fname) ax = fig.add_axes((0, 0, 1, 1)) ax.set_axis_off() out = self._last_render if sigma_clip is not None: max_val = out._clipping_value(sigma_clip) else: max_val = out[:, :, :3].max() alpha = 255 * out[:, :, 3].astype("uint8") out = np.clip(out[:, :, :3] / max_val, 0.0, 1.0) * 255 out = np.concatenate([out.astype("uint8"), alpha[..., None]], axis=-1) # not sure why we need rot90, but this makes the orientation # match the png writer ax.imshow(np.rot90(out), origin="lower") canvas.print_figure(fname, dpi=100)
[docs] def save_annotated( self, fname: Optional[str] = None, label_fmt: Optional[str] = None, text_annotate=None, dpi: int = 100, sigma_clip: Optional[float] = None, render: bool = True, tf_rect: Optional[list[float]] = None, *, label_fontsize: Union[float, str] = 10, ): r"""Saves the most recently rendered image of the Scene to disk, including an image of the transfer function and and user-defined text. Once you have created a scene and rendered that scene to an image array, this saves that image array to disk with an optional filename. If an image has not yet been rendered for the current scene object, it forces one and writes it out. Parameters ---------- fname: string, optional If specified, save the rendering as a bitmap to the file "fname". If unspecified, it creates a default based on the dataset filename. Default: None sigma_clip: float, optional Image values greater than this number times the standard deviation plus the mean of the image will be clipped before saving. Useful for enhancing images as it gets rid of rare high pixel values. Default: None floor(vals > std_dev*sigma_clip + mean) dpi: integer, optional By default, the resulting image will be the same size as the camera parameters. If you supply a dpi, then the image will be scaled accordingly (from the default 100 dpi) label_fmt : str, optional A format specifier (e.g., label_fmt="%.2g") to use in formatting the data values that label the transfer function colorbar. label_fontsize : float or string, optional The fontsize used to display the numbers on the transfer function colorbar. This can be any matplotlib font size specification, e.g., "large" or 12. (default: 10) text_annotate : list of iterables Any text that you wish to display on the image. This should be an list containing a tuple of coordinates (in normalized figure coordinates), the text to display, and, optionally, a dictionary of keyword/value pairs to pass through to the matplotlib text() function. Each item in the main list is a separate string to write. render: boolean, optional If True, will render the scene before saving. If False, will use results of previous render if it exists. Default: True tf_rect : sequence of floats, optional A rectangle that defines the location of the transfer function legend. This is only used for the case where there are multiple volume sources with associated transfer functions. tf_rect is of the form [x0, y0, width, height], in figure coordinates. Returns ------- Nothing Examples -------- >>> sc.save_annotated( ... "fig.png", ... text_annotate=[ ... [ ... (0.05, 0.05), ... f"t = {ds.current_time.d}", ... dict(horizontalalignment="left"), ... ], ... [ ... (0.5, 0.95), ... "simulation title", ... dict(color="y", fontsize="24", horizontalalignment="center"), ... ], ... ], ... ) """ fname = self._setup_save(fname, render) ax = self._show_mpl( self._last_render.swapaxes(0, 1), sigma_clip=sigma_clip, dpi=dpi ) # number of transfer functions? num_trans_func = 0 for rs in self._get_render_sources(): if hasattr(rs, "transfer_function"): num_trans_func += 1 # which transfer function? if num_trans_func == 1: rs = self._get_render_sources()[0] tf = rs.transfer_function label = rs.data_source.ds._get_field_info(rs.field).get_label() self._annotate( ax.axes, tf, rs, label=label, label_fmt=label_fmt, label_fontsize=label_fontsize, ) else: # set the origin and width and height of the colorbar region if tf_rect is None: tf_rect = [0.80, 0.12, 0.12, 0.9] cbx0, cby0, cbw, cbh = tf_rect cbh_each = cbh / num_trans_func for i, rs in enumerate(self._get_render_sources()): ax = self._render_figure.add_axes( [cbx0, cby0 + i * cbh_each, 0.8 * cbw, 0.8 * cbh_each] ) try: tf = rs.transfer_function except AttributeError: pass else: label = rs.data_source.ds._get_field_info(rs.field).get_label() self._annotate_multi( ax, tf, rs, label=label, label_fmt=label_fmt, label_fontsize=label_fontsize, ) # any text? if text_annotate is not None: f = self._render_figure for t in text_annotate: xy = t[0] string = t[1] if len(t) == 3: opt = t[2] else: opt = {} # sane default if "color" not in opt: opt["color"] = "w" ax.axes.text(xy[0], xy[1], string, transform=f.transFigure, **opt) self._render_figure.canvas = get_canvas(self._render_figure, fname) self._render_figure.tight_layout() self._render_figure.savefig(fname, facecolor="black", pad_inches=0)
def _show_mpl(self, im, sigma_clip=None, dpi=100): from matplotlib.figure import Figure s = im.shape self._render_figure = Figure(figsize=(s[1] / float(dpi), s[0] / float(dpi))) self._render_figure.clf() ax = self._render_figure.add_subplot(111) ax.set_position([0, 0, 1, 1]) if sigma_clip is not None: nim = im / im._clipping_value(sigma_clip) nim[nim > 1.0] = 1.0 nim[nim < 0.0] = 0.0 else: nim = im axim = ax.imshow(nim[:, :, :3] / nim[:, :, :3].max(), interpolation="bilinear") return axim def _annotate(self, ax, tf, source, label="", label_fmt=None, label_fontsize=10): ax.get_xaxis().set_visible(False) ax.get_xaxis().set_ticks([]) ax.get_yaxis().set_visible(False) ax.get_yaxis().set_ticks([]) cb = self._render_figure.colorbar( ax.images[0], pad=0.0, fraction=0.05, drawedges=True ) tf.vert_cbar( ax=cb.ax, label=label, label_fmt=label_fmt, label_fontsize=label_fontsize, resolution=self.camera.resolution[0], log_scale=source.log_field, ) def _annotate_multi(self, ax, tf, source, label, label_fmt, label_fontsize=10): ax.yaxis.set_label_position("right") ax.yaxis.tick_right() tf.vert_cbar( ax=ax, label=label, label_fmt=label_fmt, label_fontsize=label_fontsize, resolution=self.camera.resolution[0], log_scale=source.log_field, size=6, ) def _validate(self): r"""Validate the current state of the scene.""" for source in self.sources.values(): source._validate() return
[docs] def composite(self, camera=None): r"""Create a composite image of the current scene. First iterate over the opaque sources and set the ZBuffer. Then iterate over the transparent sources, rendering from the value of the zbuffer to the front of the box. Typically this function is accessed through the .render() command. Parameters ---------- camera: :class:`Camera`, optional If specified, use a specific :class:`Camera` to render the scene. Returns ------- im: :class:`ImageArray` ImageArray instance of the current rendering image. Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> # Modify camera, sources, etc... >>> im = sc.composite() """ if camera is None: camera = self.camera empty = camera.lens.new_image(camera) opaque = ZBuffer(empty, np.full(empty.shape[:2], np.inf)) for _, source in self.opaque_sources: source.render(camera, zbuffer=opaque) im = source.zbuffer.rgba for _, source in self.transparent_sources: im = source.render(camera, zbuffer=opaque) opaque.rgba = im # rotate image 180 degrees so orientation agrees with e.g. # a PlotWindow plot return np.rot90(im, k=2)
[docs] def add_camera(self, data_source=None, lens_type="plane-parallel", auto=False): r"""Add a new camera to the Scene. The camera is defined by a position (the location of the camera in the simulation domain,), a focus (the point at which the camera is pointed), a width (the width of the snapshot that will be taken, a resolution (the number of pixels in the image), and a north_vector (the "up" direction in the resulting image). A camera can use a variety of different Lens objects. If the scene already has a camera associated with it, this function will create a new camera and discard the old one. Parameters ---------- data_source: :class:`AMR3DData` or :class:`Dataset`, optional This is the source to be rendered, which can be any arbitrary yt data object or dataset. lens_type: string, optional This specifies the type of lens to use for rendering. Current options are 'plane-parallel', 'perspective', and 'fisheye'. See :class:`yt.visualization.volume_rendering.lens.Lens` for details. Default: 'plane-parallel' auto: boolean If True, build smart defaults using the data source extent. This can be time-consuming to iterate over the entire dataset to find the positional bounds. Default: False Examples -------- In this example, the camera is set using defaults that are chosen to be reasonable for the argument Dataset. >>> import yt >>> from yt.visualization.volume_rendering.api import Camera, Scene >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = Scene() >>> sc.add_camera() Here, we set the camera properties manually: >>> import yt >>> from yt.visualization.volume_rendering.api import Camera, Scene >>> sc = Scene() >>> cam = sc.add_camera() >>> cam.position = np.array([0.5, 0.5, -1.0]) >>> cam.focus = np.array([0.5, 0.5, 0.0]) >>> cam.north_vector = np.array([1.0, 0.0, 0.0]) Finally, we create a camera with a non-default lens: >>> import yt >>> from yt.visualization.volume_rendering.api import Camera >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = Scene() >>> sc.add_camera(ds, lens_type="perspective") """ self._camera = Camera(self, data_source, lens_type, auto) return self.camera
@property def camera(self): r"""The camera property. This is the default camera that will be used when rendering. Can be set manually, but Camera type will be checked for validity. """ return self._camera @camera.setter def camera(self, value): value.width = self.arr(value.width) value.focus = self.arr(value.focus) value.position = self.arr(value.position) self._camera = value @camera.deleter def camera(self): del self._camera self._camera = None @property def unit_registry(self): ur = self._unit_registry if ur is None: ur = UnitRegistry() # This will be updated when we add a volume source ur.add("unitary", 1.0, length) self._unit_registry = ur return self._unit_registry @unit_registry.setter def unit_registry(self, value): self._unit_registry = value if self.camera is not None: self.camera.width = YTArray( self.camera.width.in_units("unitary"), registry=value ) self.camera.focus = YTArray( self.camera.focus.in_units("unitary"), registry=value ) self.camera.position = YTArray( self.camera.position.in_units("unitary"), registry=value ) @unit_registry.deleter def unit_registry(self): del self._unit_registry self._unit_registry = None
[docs] def set_camera(self, camera): r""" Set the camera to be used by this scene. """ self.camera = camera
[docs] def get_camera(self): r""" Get the camera currently used by this scene. """ return self.camera
[docs] def annotate_domain(self, ds, color=None): r""" Modifies this scene by drawing the edges of the computational domain. This adds a new BoxSource to the scene corresponding to the domain boundaries and returns the modified scene object. Parameters ---------- ds : :class:`yt.data_objects.static_output.Dataset` This is the dataset object corresponding to the simulation being rendered. Used to get the domain bounds. color : array_like of shape (4,), optional The RGBA value to use to draw the domain boundaries. Default is black with an alpha of 1.0. Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> sc.annotate_domain(ds) >>> im = sc.render() """ box_source = BoxSource(ds.domain_left_edge, ds.domain_right_edge, color=color) self.add_source(box_source) return self
[docs] def annotate_grids( self, data_source, alpha=0.3, cmap=None, min_level=None, max_level=None ): r""" Modifies this scene by drawing the edges of the AMR grids. This adds a new GridSource to the scene that represents the AMR grid and returns the resulting Scene object. Parameters ---------- data_source: :class:`~yt.data_objects.api.DataContainer` The data container that will be used to identify grids to draw. alpha : float The opacity of the grids to draw. cmap : color map name The color map to use to map resolution levels to color. min_level : int, optional Minimum level to draw max_level : int, optional Maximum level to draw Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> sc.annotate_grids(ds.all_data()) >>> im = sc.render() """ if cmap is None: cmap = ytcfg.get("yt", "default_colormap") grids = GridSource( data_source, alpha=alpha, cmap=cmap, min_level=min_level, max_level=max_level, ) self.add_source(grids) return self
[docs] def annotate_mesh_lines(self, color=None, alpha=1.0): """ Modifies this Scene by drawing the mesh line boundaries on all MeshSources. Parameters ---------- color : array_like of shape (4,), optional The RGBA value to use to draw the mesh lines. Default is black with an alpha of 1.0. alpha : float, optional The opacity of the mesh lines. Default is 255 (solid). """ for _, source in self.opaque_sources: if isinstance(source, MeshSource): source.annotate_mesh_lines(color=color, alpha=alpha) return self
[docs] def annotate_axes(self, colors=None, alpha=1.0, *, thickness=1): r""" Modifies this scene by drawing the coordinate axes. This adds a new CoordinateVectorSource to the scene and returns the modified scene object. Parameters ---------- colors: array-like of shape (3,4), optional The RGBA values to use to draw the x, y, and z vectors. The default is [[1, 0, 0, alpha], [0, 1, 0, alpha], [0, 0, 1, alpha]] where ``alpha`` is set by the parameter below. If ``colors`` is set then ``alpha`` is ignored. alpha : float, optional The opacity of the vectors. thickness : int, optional The line thickness Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> sc.annotate_axes(alpha=0.5) >>> im = sc.render() """ coords = CoordinateVectorSource(colors, alpha, thickness=thickness) self.add_source(coords) return self
[docs] def show(self, sigma_clip=None): r"""This will send the most recently rendered image to the IPython notebook. If yt is being run from within an IPython session, and it is able to determine this, this function will send the current image of this Scene to the notebook for display. If there is no current image, it will run the render() method on this Scene before sending the result to the notebook. If yt can't determine if it's inside an IPython session, this will raise YTNotInsideNotebook. Examples -------- >>> import yt >>> ds = yt.load("IsolatedGalaxy/galaxy0030/galaxy0030") >>> sc = yt.create_scene(ds) >>> sc.show() """ if "__IPYTHON__" in dir(builtins): from IPython.display import display self._sigma_clip = sigma_clip display(self) else: raise YTNotInsideNotebook
_arr = None @property def arr(self): """Converts an array into a :class:`yt.units.yt_array.YTArray` The returned YTArray will be dimensionless by default, but can be cast to arbitrary units using the ``units`` keyword argument. Parameters ---------- input_array : Iterable A tuple, list, or array to attach units to units: String unit specification, unit symbol object, or astropy units object The units of the array. Powers must be specified using python syntax (cm**3, not cm^3). dtype : string or NumPy dtype object The dtype of the returned array data Examples -------- >>> a = sc.arr([1, 2, 3], "cm") >>> b = sc.arr([4, 5, 6], "m") >>> a + b YTArray([ 401., 502., 603.]) cm >>> b + a YTArray([ 4.01, 5.02, 6.03]) m Arrays returned by this function know about the scene's unit system >>> a = sc.arr(np.ones(5), "unitary") >>> a.in_units("Mpc") YTArray([ 1.00010449, 1.00010449, 1.00010449, 1.00010449, 1.00010449]) Mpc """ if self._arr is not None: return self._arr self._arr = functools.partial(YTArray, registry=self.unit_registry) return self._arr _quan = None @property def quan(self): """Converts an scalar into a :class:`yt.units.yt_array.YTQuantity` The returned YTQuantity will be dimensionless by default, but can be cast to arbitrary units using the ``units`` keyword argument. Parameters ---------- input_scalar : an integer or floating point scalar The scalar to attach units to units : String unit specification, unit symbol object, or astropy units input_units : deprecated in favor of 'units' The units of the quantity. Powers must be specified using python syntax (cm**3, not cm^3). dtype : string or NumPy dtype object The dtype of the array data. Examples -------- >>> a = sc.quan(1, "cm") >>> b = sc.quan(2, "m") >>> a + b 201.0 cm >>> b + a 2.01 m Quantities created this way automatically know about the unit system of the scene >>> a = ds.quan(5, "unitary") >>> a.in_cgs() 1.543e+25 cm """ if self._quan is not None: return self._quan self._quan = functools.partial(YTQuantity, registry=self.unit_registry) return self._quan def _repr_png_(self): if self._last_render is None: self.render() png = self._last_render.write_png( filename=None, sigma_clip=self._sigma_clip, background="black" ) self._sigma_clip = None return png def __repr__(self): disp = "<Scene Object>:" disp += "\nSources: \n" for k, v in self.sources.items(): disp += f" {k}: {v}\n" disp += "Camera: \n" disp += f" {self.camera}" return disp