Baruch Tabanpour
6cfea71985
PiperOrigin-RevId: 755935704 Change-Id: Ic135cd00137c2857c73c683ed9fdc5ac4418715d
748 lines
24 KiB
Python
748 lines
24 KiB
Python
# Copyright 2023 DeepMind Technologies Limited
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Tests for support."""
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from absl.testing import absltest
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from absl.testing import parameterized
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import jax
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from jax import numpy as jp
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import mujoco
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from mujoco import mjx
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from mujoco.mjx._src import support
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from mujoco.mjx._src import test_util
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import numpy as np
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class SupportTest(parameterized.TestCase):
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def test_mul_m(self):
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m = test_util.load_test_file('pendula.xml')
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# first test sparse
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m.opt.jacobian = mujoco.mjtJacobian.mjJAC_SPARSE
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d = mujoco.MjData(m)
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# give the system a little kick to ensure we have non-identity rotations
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d.qvel = np.random.random(m.nv)
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mujoco.mj_step(m, d, 10) # let dynamics get state significantly non-zero
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mujoco.mj_forward(m, d)
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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vec = np.random.random(m.nv)
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mjx_vec = jax.jit(mjx.mul_m)(mx, dx, jp.array(vec))
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mj_vec = np.zeros(m.nv)
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mujoco.mj_mulM(m, d, mj_vec, vec)
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np.testing.assert_allclose(mjx_vec, mj_vec, atol=5e-5, rtol=5e-5)
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# also check dense
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m.opt.jacobian = mujoco.mjtJacobian.mjJAC_DENSE
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mujoco.mj_forward(m, d)
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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mjx_vec = jax.jit(mjx.mul_m)(mx, dx, jp.array(vec))
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np.testing.assert_allclose(mjx_vec, mj_vec, atol=5e-5, rtol=5e-5)
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def test_full_m(self):
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m = test_util.load_test_file('pendula.xml')
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# for the model to be sparse to exercise MJX full_M
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m.opt.jacobian = mujoco.mjtJacobian.mjJAC_SPARSE
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d = mujoco.MjData(m)
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# give the system a little kick to ensure we have non-identity rotations
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d.qvel = np.random.random(m.nv)
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mujoco.mj_step(m, d, 10) # let dynamics get state significantly non-zero
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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mjx_full_m = jax.jit(support.full_m)(mx, dx)
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mj_full_m = np.zeros((m.nv, m.nv), dtype=np.float64)
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mujoco.mj_fullM(m, mj_full_m, d.qM)
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np.testing.assert_allclose(mjx_full_m, mj_full_m, atol=5e-5, rtol=5e-5)
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@parameterized.parameters('constraints.xml', 'pendula.xml')
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def test_jac(self, fname):
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np.random.seed(0)
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m = test_util.load_test_file(fname)
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d = mujoco.MjData(m)
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mujoco.mj_step(m, d)
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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point = np.random.randn(3)
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body = np.random.choice(m.nbody)
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jacp, jacr = jax.jit(support.jac)(mx, dx, point, body)
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jacp_expected, jacr_expected = np.zeros((3, m.nv)), np.zeros((3, m.nv))
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mujoco.mj_jac(m, d, jacp_expected, jacr_expected, point, body)
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np.testing.assert_almost_equal(jacp, jacp_expected.T, 6)
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np.testing.assert_almost_equal(jacr, jacr_expected.T, 6)
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def test_xfrc_accumulate(self):
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"""Tests that xfrc_accumulate ouput matches mj_xfrcAccumulate."""
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np.random.seed(0)
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m = test_util.load_test_file('pendula.xml')
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d = mujoco.MjData(m)
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mujoco.mj_step(m, d)
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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self.assertFalse((dx.xipos == 0.0).all())
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xfrc = np.random.rand(*dx.xfrc_applied.shape)
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d.xfrc_applied[:] = xfrc
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dx = dx.replace(xfrc_applied=jp.array(xfrc))
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qfrc = jax.jit(support.xfrc_accumulate)(mx, dx)
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qfrc_expected = np.zeros(m.nv)
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for i in range(1, m.nbody):
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mujoco.mj_applyFT(
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m,
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d,
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d.xfrc_applied[i, :3],
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d.xfrc_applied[i, 3:],
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d.xipos[i],
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i,
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qfrc_expected,
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)
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np.testing.assert_almost_equal(qfrc, qfrc_expected, 6)
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def test_custom(self):
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xml = """
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<mujoco model="right_shadow_hand">
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<custom>
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<numeric data="15" name="max_contact_points"/>
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<numeric data="42" name="max_geom_pairs"/>
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</custom>
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</mujoco>
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"""
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m = mujoco.MjModel.from_xml_string(xml)
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def _get_numeric(m, name):
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id_ = support.name2id(m, mujoco.mjtObj.mjOBJ_NUMERIC, name)
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return int(m.numeric_data[id_]) if id_ >= 0 else -1
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self.assertEqual(_get_numeric(m, 'something'), -1)
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self.assertEqual(_get_numeric(m, 'max_contact_points'), 15)
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self.assertEqual(_get_numeric(m, 'max_geom_pairs'), 42)
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mx = mjx.put_model(m)
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self.assertEqual(_get_numeric(mx, 'something'), -1)
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self.assertEqual(_get_numeric(mx, 'max_contact_points'), 15)
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self.assertEqual(_get_numeric(mx, 'max_geom_pairs'), 42)
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def test_names_and_ids(self):
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m = test_util.load_test_file('pendula.xml')
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mx = mjx.put_model(m)
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nums = {
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mujoco.mjtObj.mjOBJ_JOINT: m.njnt,
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mujoco.mjtObj.mjOBJ_GEOM: m.ngeom,
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mujoco.mjtObj.mjOBJ_BODY: m.nbody,
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}
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for obj in nums:
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names = [mujoco.mj_id2name(m, obj.value, i) for i in range(nums[obj])]
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for i, n in enumerate(names):
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self.assertEqual(support.id2name(mx, obj, i), n)
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i = i if n is not None else -1
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self.assertEqual(support.name2id(mx, obj, n), i)
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def test_bind(self):
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xml = """
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<mujoco model="test_bind_model">
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<worldbody>
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<body pos="10 20 30" name="body1">
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<joint axis="1 0 0" type="ball" name="joint1"/>
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<geom size="1 2 3" type="box" name="geom1" pos="0 1 0"/>
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</body>
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<body pos="40 50 60" name="body2">
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<joint axis="0 1 0" type="slide" name="joint2"/>
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<geom size="4 5 6" type="box" name="geom2"/>
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</body>
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<body pos="70 80 90" name="body3">
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<joint axis="0 0 1" type="slide" name="joint3"/>
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<geom size="7 8 9" type="box" name="geom3"/>
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</body>
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</worldbody>
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<actuator>
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<motor joint="joint1"/>
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<motor joint="joint2"/>
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<motor joint="joint3"/>
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</actuator>
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<sensor>
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<framepos objtype="body" objname="body1"/>
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<framepos objtype="body" objname="body2"/>
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<framepos objtype="body" objname="body3"/>
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</sensor>
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</mujoco>
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"""
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s = mujoco.MjSpec.from_string(xml)
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m = s.compile()
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d = mujoco.MjData(m)
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mx = mjx.put_model(m)
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dx = mjx.put_data(m, d)
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mujoco.mj_step(m, d)
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dx = mjx.step(mx, dx)
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# test getting
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np.testing.assert_array_equal(mx.bind(s.bodies).pos, m.body_pos)
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np.testing.assert_array_equal(dx.bind(mx, s.bodies).xpos, d.xpos)
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np.testing.assert_array_equal(m.bind(s.bodies[0]).mass, m.body_mass[0])
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np.testing.assert_array_equal(m.bind(s.bodies[0:1]).mass, [m.body_mass[0]])
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np.testing.assert_array_equal(mx.bind(s.bodies[0]).mass, m.body_mass[0])
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np.testing.assert_array_equal(mx.bind(s.bodies[0:1]).mass, [m.body_mass[0]])
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for i in range(m.nbody):
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np.testing.assert_array_equal(m.bind(s.bodies[i]).pos, m.body_pos[i, :])
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np.testing.assert_array_equal(mx.bind(s.bodies[i]).pos, m.body_pos[i, :])
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np.testing.assert_array_equal(d.bind(s.bodies[i]).xpos, d.xpos[i, :])
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np.testing.assert_array_equal(
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dx.bind(mx, s.bodies[i]).xpos, d.xpos[i, :]
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)
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np.testing.assert_array_equal(
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dx.bind(mx, s.bodies[i]).xfrc_applied, d.xfrc_applied[i, :]
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)
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np.testing.assert_array_equal(mx.bind(s.geoms).size, m.geom_size)
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np.testing.assert_array_equal(dx.bind(mx, s.geoms).xpos, d.geom_xpos)
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for i in range(m.ngeom):
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np.testing.assert_array_equal(m.bind(s.geoms[i]).size, m.geom_size[i, :])
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np.testing.assert_array_equal(mx.bind(s.geoms[i]).size, m.geom_size[i, :])
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np.testing.assert_array_equal(d.bind(s.geoms[i]).xpos, d.geom_xpos[i, :])
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np.testing.assert_array_equal(
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dx.bind(mx, s.geoms[i]).xpos, d.geom_xpos[i, :]
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)
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np.testing.assert_array_equal(mx.bind(s.joints).axis, m.jnt_axis)
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np.testing.assert_array_equal(mx.bind(s.joints).qposadr, m.jnt_qposadr)
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np.testing.assert_array_equal(mx.bind(s.joints).dofadr, m.jnt_dofadr)
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np.testing.assert_array_equal(dx.bind(mx, s.joints[1]).id, 1)
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np.testing.assert_array_equal(dx.bind(mx, s.joints[1:2]).id, [1])
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qposnum = [4, 1, 1] # one ball joint (4) and two slide joints (1)
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dofnum = [3, 1, 1] # one ball joint (3) and two slide joints (1)
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for i in range(m.njnt):
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np.testing.assert_array_equal(m.bind(s.joints[i]).axis, m.jnt_axis[i, :])
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np.testing.assert_array_equal(mx.bind(s.joints[i]).axis, m.jnt_axis[i, :])
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np.testing.assert_array_almost_equal(
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dx.bind(mx, s.joints[i]).qpos,
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d.qpos[m.jnt_qposadr[i]:m.jnt_qposadr[i] + qposnum[i]], decimal=6
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)
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np.testing.assert_array_almost_equal(
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dx.bind(mx, s.joints[i]).qvel,
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d.qvel[m.jnt_dofadr[i]:m.jnt_dofadr[i] + dofnum[i]], decimal=6
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)
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np.testing.assert_array_almost_equal(
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dx.bind(mx, s.joints[i]).qacc,
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d.qacc[m.jnt_dofadr[i]:m.jnt_dofadr[i] + dofnum[i]], decimal=6
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)
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, d.ctrl)
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for i in range(m.nu):
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np.testing.assert_array_equal(d.bind(s.actuators[i]).ctrl, d.ctrl[i])
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np.testing.assert_array_equal(
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dx.bind(mx, s.actuators[i]).ctrl, d.ctrl[i]
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)
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np.testing.assert_array_equal(
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dx.bind(mx, s.sensors).sensordata, d.sensordata
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)
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for i in range(m.nsensor):
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np.testing.assert_array_equal(
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dx.bind(mx, s.sensors[i]).sensordata,
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d.sensordata[m.sensor_adr[i] : m.sensor_adr[i] + m.sensor_dim[i]],
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)
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# test setting
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np.testing.assert_array_equal(d.ctrl, [0, 0, 0])
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, d.ctrl)
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dx2 = dx.bind(mx, s.actuators).set('ctrl', [1, 2, 3])
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np.testing.assert_array_equal(dx2.bind(mx, s.actuators).ctrl, [1, 2, 3])
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, [0, 0, 0])
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dx3 = dx.bind(mx, s.actuators[1:]).set('ctrl', [4, 5])
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np.testing.assert_array_equal(dx3.bind(mx, s.actuators).ctrl, [0, 4, 5])
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, [0, 0, 0])
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dx4 = dx.bind(mx, s.actuators[1]).set('ctrl', [6])
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np.testing.assert_array_equal(dx4.bind(mx, s.actuators).ctrl, [0, 6, 0])
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, [0, 0, 0])
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dx5 = dx.bind(mx, s.actuators[1]).set('ctrl', 7)
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np.testing.assert_array_equal(dx5.bind(mx, s.actuators).ctrl, [0, 7, 0])
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, [0, 0, 0])
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qpos_1step = [1.00000e00, -3.67875e-06, 0, 0, 0, -3.924e-05]
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qpos_desired = [1, 0, 0, 0, 0, 8]
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np.testing.assert_array_almost_equal(d.qpos, qpos_1step)
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np.testing.assert_array_almost_equal(dx.bind(mx, s.joints).qpos, d.qpos)
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dx6 = dx.bind(mx, s.joints[::2]).set('qpos', [1, 0, 0, 0, 8])
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np.testing.assert_array_equal(dx6.bind(mx, s.joints).qpos, qpos_desired)
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np.testing.assert_array_almost_equal(dx.bind(mx, s.joints).qpos, d.qpos)
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dx6a = dx.bind(mx, s.joints[0]).set('qpos', qpos_desired[:4])
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np.testing.assert_array_equal(
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dx6a.bind(mx, s.joints[0]).qpos, qpos_desired[:4]
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)
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dx7 = dx.bind(mx, s.joints[::2]).set('qvel', [2.0, -1.2, 0.5, 0.3])
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np.testing.assert_array_almost_equal(
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dx7.bind(mx, s.joints).qvel, [2.0, -1.2, 0.5, 0.0, 0.3], decimal=6
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)
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dx8 = dx.bind(mx, s.joints[::2]).set('qacc', [3.0, -2.1, 0.6, 0.4])
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np.testing.assert_array_almost_equal(
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dx8.bind(mx, s.joints).qacc, [3.0, -2.1, 0.6, 0.0, 0.4], decimal=6
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)
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dx9 = dx.bind(mx, s.bodies[1]).set('xfrc_applied', [1, 2, 3, 4, 5, 6])
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np.testing.assert_array_equal(
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dx9.bind(mx, s.bodies[1]).xfrc_applied, [1, 2, 3, 4, 5, 6]
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)
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for body in s.bodies[:1] + s.bodies[2:]:
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np.testing.assert_array_equal(
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dx7.bind(mx, body).xfrc_applied, [0, 0, 0, 0, 0, 0]
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)
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# test attribute and type mismatches
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with self.assertRaisesRegex(
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AttributeError, 'ctrl is not available for this type'
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):
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print(dx.bind(mx, s.geoms).ctrl)
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with self.assertRaises(KeyError):
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print(dx.bind(mx, s.actuators).actuator_ctrl)
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with self.assertRaisesRegex(
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AttributeError,
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"'Data' object has no attribute 'actuator_actuator_ctrl'",
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):
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print(dx.bind(mx, s.actuators).set('actuator_ctrl', [1, 2, 3]))
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with self.assertRaisesRegex(
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AttributeError, 'qpos, qvel, qacc are not available for this type'
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):
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print(dx.bind(mx, s.geoms).qpos)
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# test that modified names do not raise an error
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s.actuators[0].name = 'modified_actuator_name'
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np.testing.assert_array_equal(dx.bind(mx, s.actuators).ctrl, d.ctrl)
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s.geoms[0].name = 'modified_geom_name'
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np.testing.assert_array_equal(mx.bind(s.geoms[0]).pos, m.geom_pos[0, :])
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# test batched data
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batch_size = 16
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ds = [d for _ in range(batch_size)]
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vdx = jax.vmap(lambda xpos: dx.replace(xpos=xpos))(
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jp.array([d.xpos for d in ds], device=jax.devices('cpu')[0]))
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for i in range(m.nbody):
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np.testing.assert_array_equal(
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vdx.bind(mx, s.bodies[i]).xpos, [d.xpos[i, :]] * batch_size
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)
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# test that adding a body requires recompilation
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s.worldbody.add_body()
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with self.assertRaises(ValueError) as e:
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mx.bind(s.bodies)
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self.assertEqual(
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str(e.exception),
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'mjSpec signature does not match mjx.Model signature:'
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' 17856615236057737915 != 12517827274439268436',
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)
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_CONTACTS = """
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<mujoco>
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<worldbody>
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<body pos="0 0 0.55" euler="1 0 0">
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<joint axis="1 0 0" type="free"/>
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<geom fromto="-0.4 0 0 0.4 0 0" size="0.05" type="capsule" condim="6"/>
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</body>
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<body pos="0 0 0.5" euler="0 1 0">
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<joint axis="1 0 0" type="free"/>
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<geom fromto="-0.4 0 0 0.4 0 0" size="0.05" type="capsule" condim="3"/>
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</body>
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<body pos="0 0 0.445" euler="0 90 0">
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<joint axis="1 0 0" type="free"/>
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<geom fromto="-0.4 0 0 0.4 0 0" size="0.05" type="capsule" condim="1"/>
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</body>
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</worldbody>
|
|
</mujoco>
|
|
"""
|
|
|
|
def test_contact_force(self):
|
|
m = mujoco.MjModel.from_xml_string(self._CONTACTS)
|
|
d = mujoco.MjData(m)
|
|
mujoco.mj_step(m, d)
|
|
assert (
|
|
np.unique(d.contact.geom).shape[0] == 3
|
|
), 'This test assumes all capsule are in contact.'
|
|
mx = mjx.put_model(m)
|
|
dx = mjx.put_data(m, d)
|
|
mujoco.mj_step(m, d)
|
|
dx = mjx.step(mx, dx)
|
|
|
|
# map MJX contacts to MJ ones
|
|
def _find(g):
|
|
val = (g == dx._impl.contact.geom).sum(axis=1)
|
|
return np.where(val == 2)[0][0]
|
|
|
|
contact_id_map = {i: _find(d.contact.geom[i]) for i in range(d.ncon)}
|
|
|
|
for i in range(d.ncon):
|
|
result = np.zeros(6, dtype=float)
|
|
mujoco.mj_contactForce(m, d, i, result)
|
|
|
|
j = contact_id_map[i]
|
|
force = jax.jit(support.contact_force, static_argnums=(2,))(mx, dx, j)
|
|
np.testing.assert_allclose(result, force, rtol=1e-5, atol=2)
|
|
|
|
# check for zeros after first condim elements
|
|
condim = dx._impl.contact.dim[j]
|
|
if condim < 6:
|
|
np.testing.assert_allclose(force[condim:], 0, rtol=1e-5, atol=1e-5)
|
|
|
|
# test world conversion
|
|
force = jax.jit(
|
|
support.contact_force,
|
|
static_argnums=(
|
|
2,
|
|
3,
|
|
),
|
|
)(mx, dx, j, True)
|
|
# back to contact frame
|
|
force = force.at[:3].set(dx._impl.contact.frame[j] @ force[:3])
|
|
force = force.at[3:].set(dx._impl.contact.frame[j] @ force[3:])
|
|
np.testing.assert_allclose(result, force, rtol=1e-5, atol=2)
|
|
|
|
def test_wrap_inside(self):
|
|
maxiter = 5
|
|
tolerance = 1.0e-4
|
|
z_init = 1.0 - 1.0e-5
|
|
|
|
# len0 <= radius
|
|
np.testing.assert_equal(
|
|
support.wrap_inside(
|
|
jp.array([1.0, 0, 0, 0]),
|
|
jp.array([1.0]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)[0],
|
|
jp.array([-1]),
|
|
)
|
|
|
|
# len1 <= radius
|
|
np.testing.assert_equal(
|
|
support.wrap_inside(
|
|
jp.array([0, 0, 1.0, 0]),
|
|
jp.array([1.0]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)[0],
|
|
jp.array([-1]),
|
|
)
|
|
|
|
# radius < mjMINVAL
|
|
np.testing.assert_equal(
|
|
support.wrap_inside(
|
|
jp.array([1, 0, 0, 1]), jp.array([0.1 * mujoco.mjMINVAL]), maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)[0],
|
|
jp.array([-1]),
|
|
)
|
|
|
|
# len0 < mjMINVAL and radius < mjMINVAL
|
|
np.testing.assert_equal(
|
|
support.wrap_inside(
|
|
jp.array([0.1 * mujoco.mjMINVAL, 0, 0, 0]),
|
|
jp.array([0.1 * mujoco.mjMINVAL]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)[0],
|
|
jp.array([-1]),
|
|
)
|
|
|
|
# len1 < mjMINVAL and radius < mjMINVAL
|
|
np.testing.assert_equal(
|
|
support.wrap_inside(
|
|
jp.array([0, 0, 0.1 * mujoco.mjMINVAL, 0]),
|
|
jp.array([0.1 * mujoco.mjMINVAL]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)[0],
|
|
jp.array([-1]),
|
|
)
|
|
|
|
# wrap: p0 = [1, 0], p1 = [0, 1]
|
|
status, pnt = support.wrap_inside(
|
|
jp.array([1, 0, 0, 1]), jp.array([0.5]), maxiter, tolerance, z_init
|
|
)
|
|
np.testing.assert_allclose(
|
|
pnt,
|
|
jp.array([0.353553, 0.353553, 0.353553, 0.353553]),
|
|
atol=1e-3,
|
|
rtol=1e-3,
|
|
)
|
|
np.testing.assert_equal(status, jp.array([0]))
|
|
|
|
# no wrap, point on circle: p0 = [1, 0], p1 = [0, 0.5]
|
|
status, pnt = support.wrap_inside(
|
|
jp.array([1, 0, 0, 0.5]), jp.array([0.5]), maxiter, tolerance, z_init
|
|
)
|
|
np.testing.assert_allclose(
|
|
pnt,
|
|
jp.zeros(4),
|
|
atol=1e-3,
|
|
rtol=1e-3,
|
|
)
|
|
np.testing.assert_equal(status, jp.array([-1]))
|
|
|
|
# no wrap, segment-circle intersection: p0 = [0.75, 0], p1 = [0, 0.51]
|
|
status, pnt = support.wrap_inside(
|
|
jp.array([0.75, 0, 0, 0.51]),
|
|
jp.array([0.5]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)
|
|
np.testing.assert_allclose(
|
|
pnt,
|
|
jp.zeros(4),
|
|
atol=1e-3,
|
|
rtol=1e-3,
|
|
)
|
|
np.testing.assert_equal(status, jp.array([-1]))
|
|
|
|
# wrap: p0 = [-0.5, 1], p1 = [0.5, 1]
|
|
status, pnt = support.wrap_inside(
|
|
jp.array([-0.5, 1, 0.5, 1]),
|
|
jp.array([0.5]),
|
|
maxiter,
|
|
tolerance,
|
|
z_init,
|
|
)
|
|
np.testing.assert_allclose(
|
|
pnt,
|
|
jp.array([0, 0.5, 0, 0.5]),
|
|
atol=1e-3,
|
|
rtol=1e-3,
|
|
)
|
|
np.testing.assert_equal(status, jp.array([0]))
|
|
|
|
# TODO(taylorhowell): improve wrap_inside testing with additional test cases
|
|
|
|
def test_muscle_gain_length(self):
|
|
lmin = 0.5
|
|
lmax = 1.5
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(0, lmin, lmax),
|
|
jp.zeros(1),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(0.5, lmin, lmax),
|
|
jp.zeros(1),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(0.6, lmin, lmax),
|
|
jp.array([0.08]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(0.75, lmin, lmax),
|
|
jp.array([0.5]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(1.0, lmin, lmax),
|
|
jp.ones(1),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(1.25, lmin, lmax),
|
|
jp.array([0.5]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(1.5, lmin, lmax),
|
|
jp.zeros(1),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain_length(2.0, lmin, lmax),
|
|
jp.zeros(1),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
def test_muscle_gain(self):
|
|
length = jp.array([1.0])
|
|
lengthrange = jp.array([0.0, 1.0])
|
|
acc0 = jp.array([1.0])
|
|
prm = jp.array([0.0, 1.0, 1.0, 200.0, 0.5, 3.0, 1.0, 0.0, 2.0, 0.0])
|
|
|
|
# V <= -1
|
|
vel = jp.array([-1.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain(length, vel, lengthrange, acc0, prm),
|
|
jp.array([-0.0]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# V <= 0
|
|
vel = jp.array([-0.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain(length, vel, lengthrange, acc0, prm),
|
|
jp.array([-0.25]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# V <= y
|
|
vel = jp.array([0.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain(length, vel, lengthrange, acc0, prm),
|
|
jp.array([-1.75]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# V > y
|
|
vel = jp.array([1.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain(length, vel, lengthrange, acc0, prm),
|
|
jp.array([-2.0]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# force < 0
|
|
prm = prm.at[2].set(-1.0)
|
|
np.testing.assert_allclose(
|
|
support.muscle_gain(length, vel, lengthrange, acc0, prm),
|
|
jp.array([-400.0]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
def test_muscle_bias(self):
|
|
lengthrange = jp.array([0.0, 1.0])
|
|
acc0 = jp.array([1.0])
|
|
prm = jp.array([0.0, 1.0, 1.0, 200.0, 0.5, 3.0, 1.5, 1.3, 1.2, 0.0])
|
|
|
|
# L <= 1
|
|
length = jp.array([0.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_bias(length, lengthrange, acc0, prm),
|
|
jp.array([0.0]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# L <= b
|
|
length = jp.array([1.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_bias(length, lengthrange, acc0, prm),
|
|
jp.array([-0.1625]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# L > b
|
|
length = jp.array([2.5])
|
|
np.testing.assert_allclose(
|
|
support.muscle_bias(length, lengthrange, acc0, prm),
|
|
jp.array([-1.3]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# force < 0
|
|
prm = prm.at[2].set(-1.0)
|
|
np.testing.assert_allclose(
|
|
support.muscle_bias(length, lengthrange, acc0, prm),
|
|
jp.array([-260.0]),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
def test_smooth_muscle_dynamics(self):
|
|
# compute time constant as in Millard et al. (2013)
|
|
# https://doi.org/10.1115/1.4023390
|
|
def _muscle_dynamics_millard(ctrl, act, prm):
|
|
ctrlclamp = jp.clip(ctrl, 0, 1)
|
|
actclamp = jp.clip(act, 0, 1)
|
|
|
|
tau0 = prm[0] * (0.5 + 1.5 * actclamp)
|
|
tau1 = prm[1] / (0.5 + 1.5 * actclamp)
|
|
tau = jp.where(ctrlclamp > act, tau0, tau1)
|
|
|
|
return (ctrlclamp - act) / jp.maximum(mujoco.mjMINVAL, tau)
|
|
|
|
prm = jp.array([0.01, 0.04, 0.0])
|
|
|
|
# exact equality if tau_smooth = 0
|
|
for ctrl in [-0.1, 0.0, 0.4, 0.5, 1.0, 1.0]:
|
|
for act in [-0.1, 0.0, 0.4, 0.5, 1.0, 1.1]:
|
|
actdot_old = _muscle_dynamics_millard(ctrl, act, prm)
|
|
actdot_new = support.muscle_dynamics(ctrl, act, prm)
|
|
np.testing.assert_allclose(actdot_old, actdot_new, rtol=1e-5, atol=1e-5)
|
|
|
|
# positive tau_smooth
|
|
tau_smooth = 0.2
|
|
prm = prm.at[2].set(tau_smooth)
|
|
act = 0.5
|
|
eps = 1.0e-6
|
|
|
|
ctrl = 0.4 - eps # smaller than act by just over 0.5 * tau_smooth
|
|
np.testing.assert_allclose(
|
|
_muscle_dynamics_millard(ctrl, act, prm),
|
|
support.muscle_dynamics(ctrl, act, prm),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
ctrl = 0.6 + eps # larger than act by just over 0.5 * tau_smooth
|
|
np.testing.assert_allclose(
|
|
_muscle_dynamics_millard(ctrl, act, prm),
|
|
support.muscle_dynamics(ctrl, act, prm),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
# right in the middle should give average of time constants
|
|
tau_act = 0.2
|
|
tau_deact = 0.3
|
|
for dctrl in [0.0, 0.1, 0.2, 1.0, 1.1]:
|
|
lower = support.muscle_dynamics_timescale(
|
|
-dctrl, tau_act, tau_deact, tau_smooth
|
|
)
|
|
upper = support.muscle_dynamics_timescale(
|
|
dctrl, tau_act, tau_deact, tau_smooth
|
|
)
|
|
np.testing.assert_allclose(
|
|
0.5 * (upper + lower),
|
|
0.5 * (tau_act + tau_deact),
|
|
rtol=1e-5,
|
|
atol=1e-5,
|
|
)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
absltest.main()
|