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Mujoco_WASM/mjx/mujoco/mjx/_src/support_test.py
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Erik Frey b3ccf67ebf Cleanup MJX tests and migrate them to put_model/put_data.
PiperOrigin-RevId: 588304729
Change-Id: I58075383e6eed64ae00cea305a568eba6465b0b0
2023-12-05 23:08:05 -08:00

82 lines
2.5 KiB
Python

# Copyright 2023 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 support."""
from absl.testing import absltest
from absl.testing import parameterized
import jax
from jax import numpy as jp
import mujoco
from mujoco import mjx
from mujoco.mjx._src import support
from mujoco.mjx._src import test_util
import numpy as np
class SupportTest(parameterized.TestCase):
@parameterized.parameters(set(test_util.TEST_FILES) - {'convex.xml'})
def test_jac(self, fname):
np.random.seed(0)
m = test_util.load_test_file(fname)
d = mujoco.MjData(m)
mujoco.mj_step(m, d)
mx = mjx.put_model(m)
dx = mjx.put_data(m, d)
point = np.random.randn(3)
body = np.random.choice(m.nbody)
jacp, jacr = jax.jit(support.jac)(mx, dx, point, body)
jacp_expected, jacr_expected = np.zeros((3, m.nv)), np.zeros((3, m.nv))
mujoco.mj_jac(m, d, jacp_expected, jacr_expected, point, body)
np.testing.assert_almost_equal(jacp, jacp_expected.T, 6)
np.testing.assert_almost_equal(jacr, jacr_expected.T, 6)
def test_xfrc_accumulate(self):
"""Tests that xfrc_accumulate ouput matches mj_xfrcAccumulate."""
np.random.seed(0)
m = test_util.load_test_file('pendula.xml')
d = mujoco.MjData(m)
mujoco.mj_step(m, d)
mx = mjx.put_model(m)
dx = mjx.put_data(m, d)
self.assertFalse((dx.xipos == 0.0).all())
xfrc = np.random.rand(*dx.xfrc_applied.shape)
d.xfrc_applied[:] = xfrc
dx = dx.replace(xfrc_applied=jp.array(xfrc))
qfrc = jax.jit(support.xfrc_accumulate)(mx, dx)
qfrc_expected = np.zeros(m.nv)
for i in range(1, m.nbody):
mujoco.mj_applyFT(
m,
d,
d.xfrc_applied[i, :3],
d.xfrc_applied[i, 3:],
d.xipos[i],
i,
qfrc_expected,
)
np.testing.assert_almost_equal(qfrc, qfrc_expected, 6)
if __name__ == '__main__':
absltest.main()