Merge pull request #100 from NeLy-EPFL/develop

Merge v0.2.4

Author: sibocw

doc/source/changelog.rst

@@ -1,6 +1,10 @@
 Change Log
 ==========
 
+* **0.2.4:** Set MuJoCo version to 2.3.7. Documentation updates.
+* **0.2.3:** Various bug fixes. Improved placement of the spherical treadmill in the tethered environment.
+* **0.2.2:** Changed default joint kp and adhesion forces to those used in the controller comparison task. Various minor bug fixes. Documentation updates.
+* **0.2.1:** Simplified class names: ``NeuroMechFlyMuJoCo`` → ``NeuroMechFly``, ``MuJoCoParameters`` → ``Parameters``. Minor documentation updates.
 * **0.2.0:** The current base version — major API change from 0.1.x.
 * **0.1.x** The version used during the development of NeuroMechFly 2.0.
-* **Unversioned:** Version used for the Spring 2023 offering of BIOENG-456 Controlling Behavior in Animals and Robots course at EPFL.
+* **Unversioned:** Version used for the Spring 2023 offering of BIOENG-456 Controlling Behavior in Animals and Robots course at EPFL.

doc/source/index.rst

@@ -25,11 +25,6 @@ Simulating embodied sensorimotor control with NeuroMechFly 2.0
    :width: 400
    :alt: Overview video
 
-.. note::
-   
-   FlyGym is still in beta; the API is subject to change.
-   We will add further examples and documentation in the coming weeks. Stay tuned!
-   --- 21 September 2023
 
 FlyGym is the Python library for NeuroMechFly 2.0, a digital twin of the adult fruit fly *Drosophila melanogaster* that can see, smell, walk over challenging terrain, and interact with the environment (see our `NeuroMechFly 2.0 paper <https://www.biorxiv.org/content/10.1101/2023.09.18.556649>`_).
 
@@ -56,15 +51,8 @@ If you use FlyGym or NeuroMechFly in your research, please cite the following tw
 
 .. code-block:: bibtex
    
-   @article{WangChen2023,
-      author = {Sibo Wang-Chen and Victor Alfred Stimpfling and Pembe Gizem \"{O}zdil and Louise Genoud and Femke Hurtak and Pavan Ramdya},
-      title = {NeuroMechFly 2.0, a framework for simulating embodied sensorimotor control in adult Drosophila},
-      year = {2023},
-      doi = {10.1101/2023.09.18.556649},
-      URL = {https://www.biorxiv.org/content/10.1101/2023.09.18.556649},
-      journal = {bioRxiv}
-   }
-
+   % Original NeuroMechFly: Original biomechanical model, kinematic replay, CPG-based
+   % neural controller, PyBullet version, DoF analysis, perturbation tests
    @article{LobatoRios2022,
       doi = {10.1038/s41592-022-01466-7},
       url = {https://doi.org/10.1038/s41592-022-01466-7},
@@ -77,3 +65,15 @@ If you use FlyGym or NeuroMechFly in your research, please cite the following tw
       title = {{NeuroMechFly}, a neuromechanical model of adult {Drosophila} melanogaster},
       journal = {Nature Methods}
    }
+   
+   % NeuroMechFly 2.0: This library, MuJoCo version, leg adhesion, rule-based controller,
+   % hybrid controller, complex terrain, preprogrammed steps, leg adhesion, vision,
+   % olfaction, RL-based navigation, Gym environment, updated biomechanical model
+   @article{WangChen2023,
+      author = {Sibo Wang-Chen and Victor Alfred Stimpfling and Pembe Gizem \"{O}zdil and Louise Genoud and Femke Hurtak and Pavan Ramdya},
+      title = {NeuroMechFly 2.0, a framework for simulating embodied sensorimotor control in adult Drosophila},
+      year = {2023},
+      doi = {10.1101/2023.09.18.556649},
+      URL = {https://www.biorxiv.org/content/10.1101/2023.09.18.556649},
+      journal = {bioRxiv}
+   }

doc/source/tutorials/index.rst

@@ -1,9 +1,6 @@
 Tutorials
 =========
 
-.. note::
-   We will add more tutorials soon. In the meantime, please refer to the `API reference <../api_ref/index.html>`_ and our `paper  <https://www.biorxiv.org/content/10.1101/2023.09.18.556649>`_, which describes in detail the experiments that we have performed.
-
 .. toctree::
    :maxdepth: 2
 
@@ -13,4 +10,4 @@ Tutorials
    hybrid_controller
    turning
    vision
-   olfaction
+   olfaction

doc/source/tutorials/rule_based_controller.rst

@@ -11,7 +11,7 @@ mechanism like the CPG.
 
     .. code:: bash
 
-       pip install -e "flygym[tutorials]"
+       pip install networkx
     
 
 Previously, we have covered how a centralized network of oscillators

flygym/mujoco/arena/sensory_environment.py

@@ -43,7 +43,7 @@ class OdorArena(BaseArena):
     Parameters
     ----------
     size : Tuple[float, float], optional
-        The size of the arena in mm, by default (50, 50).
+        The size of the arena in mm, by default (300, 300).
     friction : Tuple[float, float, float], optional
         The sliding, torsional, and rolling friction coefficients of the
         ground, by default (1, 0.005, 0.0001).

setup.py

@@ -3,7 +3,7 @@
 
 setup(
     name="flygym",
-    version="0.2.3",
+    version="0.2.4",
     author="Neuroengineering Laboratory, EPFL",
     author_email="[email protected]",
     description="Gym environments for NeuroMechFly in various physics simulators",
@@ -28,7 +28,7 @@
         "tqdm",
     ],
     extras_require={
-        "mujoco": ["mujoco", "dm_control", "numba", "opencv-python"],
+        "mujoco": ["mujoco>=2.3.0,<3.0.0", "dm_control", "numba", "opencv-python"],
         "pybullet": ["pybullet"],
         "dev": [
             "sphinx",
@@ -42,7 +42,6 @@
             "rasterio",
             "requests",
         ],
-        "tutorials": ["networkx"],
     },
     url="https://neuromechfly.org/",
     long_description=open("README.md").read(),