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Mujoco_WASM/python/mujoco/sysid/tests/test_model_modifier.py
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Copybara-Service 3ec09f7296 Merge pull request #3079 from aftersomemath:sysid-pr
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Change-Id: I790bc08fc8b0745583a2f92d9ee2c5a19ba558ea
2026-02-10 11:04:12 -08:00

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Python

# Copyright 2026 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for the model_modifier module."""
import mujoco
from mujoco.sysid._src import model_modifier
import numpy as np
def test_apply_pgain(arm_spec):
"""Setting a P gain correctly configures the underlying actuator parameters."""
actuator_name = "actuator5"
pgain_value = 74
modified_spec = model_modifier.apply_pgain(
arm_spec, actuator_name, pgain_value
)
model = modified_spec.compile()
assert model.actuator(actuator_name).gainprm[0] == pgain_value
assert model.actuator(actuator_name).biasprm[1] == -pgain_value
def test_apply_dgain(arm_spec):
"""Setting a D gain correctly configures the underlying actuator parameters."""
actuator_name = "actuator5"
dgain_value = 1.2
modified_spec = model_modifier.apply_dgain(
arm_spec, actuator_name, dgain_value
)
model = modified_spec.compile()
assert model.actuator(actuator_name).biasprm[2] == -dgain_value
def test_apply_pdgain(arm_spec):
"""Setting P and D gains together from a single array configures both correctly."""
actuator_name = "actuator5"
pdgain_value = np.array([74, 1.2])
modified_spec = model_modifier.apply_pdgain(
arm_spec, actuator_name, pdgain_value
)
model = modified_spec.compile()
assert model.actuator(actuator_name).gainprm[0] == pdgain_value[0]
assert model.actuator(actuator_name).biasprm[1] == -pdgain_value[0]
assert model.actuator(actuator_name).biasprm[2] == -pdgain_value[1]
def test_apply_body_mass_explicit(arm_spec):
"""Bodies with inertia defined in XML: changing mass proportionally scales inertia."""
body_name = "link1"
model = arm_spec.compile()
original_mass = model.body(body_name).mass[0]
original_inertia = model.body(body_name).inertia
del model
scale = 3.3
new_mass = scale * original_mass
modified_spec = model_modifier.apply_body_mass_ipos(
arm_spec, body_name, mass=new_mass, rot_inertia_scale=True
)
model = modified_spec.compile()
assert model.body(body_name).mass == new_mass
np.testing.assert_allclose(
model.body(body_name).inertia, original_inertia * scale
)
def test_apply_body_mass_implicit(oscillator_spec):
"""Bodies with inertia inferred from geoms: changing mass proportionally scales inertia."""
body_name = "mass"
model = oscillator_spec.compile()
original_mass = model.body(body_name).mass[0]
original_inertia = model.body(body_name).inertia
del model
scale = 0.077
new_mass = scale * original_mass
modified_spec = model_modifier.apply_body_mass_ipos(
oscillator_spec, body_name, mass=new_mass, rot_inertia_scale=True
)
model = modified_spec.compile()
assert model.body(body_name).mass == new_mass
np.testing.assert_allclose(
model.body(body_name).inertia, original_inertia * scale
)
def test_remove_visuals(arm_spec):
"""Stripping visuals removes all textures and materials for faster compilation."""
cleaned_spec = model_modifier.remove_visuals(arm_spec)
assert not cleaned_spec.textures
assert not cleaned_spec.materials
def test_apply_param_modifiers(box_spec, box_params):
"""The full modifier pipeline applies parameter callbacks and produces an updated model."""
spec = box_spec.copy()
original_model = spec.compile()
original_mass = original_model.body("box").mass[0]
# Change box_mass parameter.
box_params["box_mass"].update_from_vector(np.array([5.3]))
modified_model = model_modifier.apply_param_modifiers(box_params, spec)
assert modified_model.body("box").mass[0] != original_mass
np.testing.assert_allclose(modified_model.body("box").mass[0], 5.3, atol=1e-6)
# Also verify apply_param_modifiers_spec returns MjSpec.
spec2 = box_spec.copy()
result = model_modifier.apply_param_modifiers_spec(box_params, spec2)
assert isinstance(result, mujoco.MjSpec)