Yuval Tassa
f9a00bd5b5
The new spotlight attribute softness (real in [0, 1], default 0) is the fraction of the cone, measured inward from the cutoff, over which intensity falls to zero. It is used by physically-based lighting models; the Phong model's corresponding knob remains exponent. The filament renderer previously hardcoded the inner cone angle to 0, making the entire beam penumbra: the shader attenuates by the squared smoothstep ((cos(theta) - cos(outer)) / (cos(inner) - cos(outer)))^2, so a cutoff-25 spot delivered its rated candela only exactly on-axis and about a third of it averaged over the light pool, with the deficit shrinking as the cutoff widens. The inner angle is now (1 - softness) * cutoff, so at the default the light delivers its full intensity everywhere inside the cone and illuminance follows E = I/d^2 independent of the cutoff. Setting softness to 1 reproduces the previous appearance exactly (verified bit-identical), which is the migration path for models tuned against the old behavior. The filament light type also changes from FOCUSED_SPOT to SPOT. With intensity given in candela and the cone set at build time the two types produce identical output (FOCUSED_SPOT's power-conserving rescale only applies when the cone changes after the intensity is set), but SPOT guarantees that candela never rescales with cone angle should the cone ever become runtime-editable. Verified with headless renders under a linear tone mapper against an equal-candela point light at cutoffs 25/45/80: softness 0 gives spot/point luminance ratio 1.000 at all sampled angles inside the cone; softness 0.2 is flat over the inner 80% of the cone; softness 1 matches the previous renderer with zero linear-pixel difference. XML round-trip and the [0, 1] compile-time check verified. Introspect and wasm bindings regenerated. PiperOrigin-RevId: 959334706 Change-Id: I0f0729781899880de1729ea9b3d8c055d715a025
MuJoCo Python Bindings
This package is the canonical Python bindings for the MuJoCo physics engine. These bindings are developed and maintained by Google DeepMind, and is kept up-to-date with the latest developments in MuJoCo itself.
The mujoco package provides direct access to raw MuJoCo C API functions,
structs, constants, and enumerations. Structs are provided as Python classes,
with Pythonic initialization and deletion semantics.
It is not the aim of this package to provide fully fledged
scene/environment/game authoring API, as there are already a number of existing
packages that do this well. However, this package does provide a number of
lower-level components outside of MuJoCo itself that are likely to be useful to
most users who access MuJoCo through Python. For example, the egl, glfw, and
osmesa subpackages contain utilities for setting up OpenGL rendering contexts.
Installation
The recommended way to install this package is via PyPI:
pip install mujoco
A copy of the MuJoCo library is provided as part of the package and does not need to be downloaded or installed separately.
Source
IMPORTANT: Building from source is only necessary if you are modifying the Python bindings (or are trying to run on exceptionally old Linux systems). If that's not the case, then we recommend installing the prebuilt binaries from PyPI.
If you need to build the Python bindings from source, please consult the documentation.
Usage
Once installed, the package can be imported via import mujoco. Please consult
our documentation for
further detail on the package's API.
We recommend going through the tutorial notebook which covers the basics of
MuJoCo using Python:
Versioning
The major.minor.micro portion of the version number matches the version of
MuJoCo that the bindings provide. Optionally, if we release updates to the
Python bindings themselves that target the same version of MuJoCo, a .postN
suffix is added, for example 2.1.2.post2 represents the second update to the
bindings for MuJoCo 2.1.2.
License and Disclaimer
Copyright 2022 DeepMind Technologies Limited
MuJoCo and its Python bindings are licensed under the Apache License, Version 2.0. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.
This is not an officially supported Google product.