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"""Tests for the ``sympy.physics.biomechanics.activation.py`` module."""
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import pytest
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from sympy import Symbol
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from sympy.core.numbers import Float, Integer, Rational
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from sympy.functions.elementary.hyperbolic import tanh
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from sympy.matrices import Matrix
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from sympy.matrices.dense import zeros
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from sympy.physics.mechanics import dynamicsymbols
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from sympy.physics.biomechanics import (
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ActivationBase,
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FirstOrderActivationDeGroote2016,
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ZerothOrderActivation,
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)
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from sympy.physics.biomechanics._mixin import _NamedMixin
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from sympy.simplify.simplify import simplify
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class TestZerothOrderActivation:
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@staticmethod
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def test_class():
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assert issubclass(ZerothOrderActivation, ActivationBase)
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assert issubclass(ZerothOrderActivation, _NamedMixin)
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assert ZerothOrderActivation.__name__ == 'ZerothOrderActivation'
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@pytest.fixture(autouse=True)
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def _zeroth_order_activation_fixture(self):
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self.name = 'name'
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self.e = dynamicsymbols('e_name')
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self.instance = ZerothOrderActivation(self.name)
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def test_instance(self):
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instance = ZerothOrderActivation(self.name)
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assert isinstance(instance, ZerothOrderActivation)
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def test_with_defaults(self):
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instance = ZerothOrderActivation.with_defaults(self.name)
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assert isinstance(instance, ZerothOrderActivation)
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assert instance == ZerothOrderActivation(self.name)
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def test_name(self):
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assert hasattr(self.instance, 'name')
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assert self.instance.name == self.name
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def test_order(self):
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assert hasattr(self.instance, 'order')
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assert self.instance.order == 0
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def test_excitation_attribute(self):
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assert hasattr(self.instance, 'e')
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assert hasattr(self.instance, 'excitation')
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e_expected = dynamicsymbols('e_name')
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assert self.instance.e == e_expected
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assert self.instance.excitation == e_expected
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assert self.instance.e is self.instance.excitation
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def test_activation_attribute(self):
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assert hasattr(self.instance, 'a')
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assert hasattr(self.instance, 'activation')
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a_expected = dynamicsymbols('e_name')
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assert self.instance.a == a_expected
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assert self.instance.activation == a_expected
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assert self.instance.a is self.instance.activation is self.instance.e
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def test_state_vars_attribute(self):
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assert hasattr(self.instance, 'x')
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assert hasattr(self.instance, 'state_vars')
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assert self.instance.x == self.instance.state_vars
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x_expected = zeros(0, 1)
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assert self.instance.x == x_expected
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assert self.instance.state_vars == x_expected
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assert isinstance(self.instance.x, Matrix)
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assert isinstance(self.instance.state_vars, Matrix)
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assert self.instance.x.shape == (0, 1)
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assert self.instance.state_vars.shape == (0, 1)
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def test_input_vars_attribute(self):
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assert hasattr(self.instance, 'r')
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assert hasattr(self.instance, 'input_vars')
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assert self.instance.r == self.instance.input_vars
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r_expected = Matrix([self.e])
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assert self.instance.r == r_expected
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assert self.instance.input_vars == r_expected
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assert isinstance(self.instance.r, Matrix)
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assert isinstance(self.instance.input_vars, Matrix)
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assert self.instance.r.shape == (1, 1)
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assert self.instance.input_vars.shape == (1, 1)
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def test_constants_attribute(self):
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assert hasattr(self.instance, 'p')
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assert hasattr(self.instance, 'constants')
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assert self.instance.p == self.instance.constants
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p_expected = zeros(0, 1)
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assert self.instance.p == p_expected
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assert self.instance.constants == p_expected
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assert isinstance(self.instance.p, Matrix)
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assert isinstance(self.instance.constants, Matrix)
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assert self.instance.p.shape == (0, 1)
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assert self.instance.constants.shape == (0, 1)
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def test_M_attribute(self):
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assert hasattr(self.instance, 'M')
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M_expected = Matrix([])
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assert self.instance.M == M_expected
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assert isinstance(self.instance.M, Matrix)
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assert self.instance.M.shape == (0, 0)
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def test_F(self):
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assert hasattr(self.instance, 'F')
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F_expected = zeros(0, 1)
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assert self.instance.F == F_expected
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assert isinstance(self.instance.F, Matrix)
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assert self.instance.F.shape == (0, 1)
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def test_rhs(self):
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assert hasattr(self.instance, 'rhs')
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rhs_expected = zeros(0, 1)
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rhs = self.instance.rhs()
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assert rhs == rhs_expected
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assert isinstance(rhs, Matrix)
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assert rhs.shape == (0, 1)
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def test_repr(self):
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expected = 'ZerothOrderActivation(\'name\')'
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assert repr(self.instance) == expected
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class TestFirstOrderActivationDeGroote2016:
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@staticmethod
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def test_class():
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assert issubclass(FirstOrderActivationDeGroote2016, ActivationBase)
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assert issubclass(FirstOrderActivationDeGroote2016, _NamedMixin)
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assert FirstOrderActivationDeGroote2016.__name__ == 'FirstOrderActivationDeGroote2016'
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@pytest.fixture(autouse=True)
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def _first_order_activation_de_groote_2016_fixture(self):
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self.name = 'name'
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self.e = dynamicsymbols('e_name')
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self.a = dynamicsymbols('a_name')
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self.tau_a = Symbol('tau_a')
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self.tau_d = Symbol('tau_d')
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self.b = Symbol('b')
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self.instance = FirstOrderActivationDeGroote2016(
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self.name,
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self.tau_a,
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self.tau_d,
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self.b,
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)
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def test_instance(self):
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instance = FirstOrderActivationDeGroote2016(self.name)
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assert isinstance(instance, FirstOrderActivationDeGroote2016)
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def test_with_defaults(self):
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instance = FirstOrderActivationDeGroote2016.with_defaults(self.name)
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assert isinstance(instance, FirstOrderActivationDeGroote2016)
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assert instance.tau_a == Float('0.015')
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assert instance.activation_time_constant == Float('0.015')
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assert instance.tau_d == Float('0.060')
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assert instance.deactivation_time_constant == Float('0.060')
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assert instance.b == Float('10.0')
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assert instance.smoothing_rate == Float('10.0')
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def test_name(self):
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assert hasattr(self.instance, 'name')
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assert self.instance.name == self.name
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def test_order(self):
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assert hasattr(self.instance, 'order')
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assert self.instance.order == 1
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def test_excitation(self):
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assert hasattr(self.instance, 'e')
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assert hasattr(self.instance, 'excitation')
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e_expected = dynamicsymbols('e_name')
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assert self.instance.e == e_expected
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assert self.instance.excitation == e_expected
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assert self.instance.e is self.instance.excitation
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def test_excitation_is_immutable(self):
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with pytest.raises(AttributeError):
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self.instance.e = None
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with pytest.raises(AttributeError):
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self.instance.excitation = None
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def test_activation(self):
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assert hasattr(self.instance, 'a')
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assert hasattr(self.instance, 'activation')
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a_expected = dynamicsymbols('a_name')
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assert self.instance.a == a_expected
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assert self.instance.activation == a_expected
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def test_activation_is_immutable(self):
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with pytest.raises(AttributeError):
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self.instance.a = None
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with pytest.raises(AttributeError):
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self.instance.activation = None
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@pytest.mark.parametrize(
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'tau_a, expected',
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[
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(None, Symbol('tau_a_name')),
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(Symbol('tau_a'), Symbol('tau_a')),
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(Float('0.015'), Float('0.015')),
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]
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)
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def test_activation_time_constant(self, tau_a, expected):
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instance = FirstOrderActivationDeGroote2016(
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'name', activation_time_constant=tau_a,
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)
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assert instance.tau_a == expected
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assert instance.activation_time_constant == expected
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assert instance.tau_a is instance.activation_time_constant
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def test_activation_time_constant_is_immutable(self):
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with pytest.raises(AttributeError):
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self.instance.tau_a = None
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with pytest.raises(AttributeError):
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self.instance.activation_time_constant = None
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@pytest.mark.parametrize(
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'tau_d, expected',
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[
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(None, Symbol('tau_d_name')),
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(Symbol('tau_d'), Symbol('tau_d')),
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(Float('0.060'), Float('0.060')),
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]
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)
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def test_deactivation_time_constant(self, tau_d, expected):
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instance = FirstOrderActivationDeGroote2016(
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'name', deactivation_time_constant=tau_d,
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)
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assert instance.tau_d == expected
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assert instance.deactivation_time_constant == expected
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assert instance.tau_d is instance.deactivation_time_constant
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def test_deactivation_time_constant_is_immutable(self):
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with pytest.raises(AttributeError):
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self.instance.tau_d = None
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with pytest.raises(AttributeError):
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self.instance.deactivation_time_constant = None
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@pytest.mark.parametrize(
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'b, expected',
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[
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(None, Symbol('b_name')),
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(Symbol('b'), Symbol('b')),
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(Integer('10'), Integer('10')),
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]
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)
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def test_smoothing_rate(self, b, expected):
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instance = FirstOrderActivationDeGroote2016(
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'name', smoothing_rate=b,
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)
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assert instance.b == expected
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assert instance.smoothing_rate == expected
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assert instance.b is instance.smoothing_rate
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def test_smoothing_rate_is_immutable(self):
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with pytest.raises(AttributeError):
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self.instance.b = None
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with pytest.raises(AttributeError):
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self.instance.smoothing_rate = None
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def test_state_vars(self):
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assert hasattr(self.instance, 'x')
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assert hasattr(self.instance, 'state_vars')
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assert self.instance.x == self.instance.state_vars
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x_expected = Matrix([self.a])
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assert self.instance.x == x_expected
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assert self.instance.state_vars == x_expected
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assert isinstance(self.instance.x, Matrix)
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assert isinstance(self.instance.state_vars, Matrix)
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assert self.instance.x.shape == (1, 1)
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assert self.instance.state_vars.shape == (1, 1)
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def test_input_vars(self):
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assert hasattr(self.instance, 'r')
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assert hasattr(self.instance, 'input_vars')
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assert self.instance.r == self.instance.input_vars
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r_expected = Matrix([self.e])
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assert self.instance.r == r_expected
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assert self.instance.input_vars == r_expected
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assert isinstance(self.instance.r, Matrix)
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assert isinstance(self.instance.input_vars, Matrix)
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assert self.instance.r.shape == (1, 1)
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assert self.instance.input_vars.shape == (1, 1)
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def test_constants(self):
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assert hasattr(self.instance, 'p')
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assert hasattr(self.instance, 'constants')
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assert self.instance.p == self.instance.constants
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p_expected = Matrix([self.tau_a, self.tau_d, self.b])
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assert self.instance.p == p_expected
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assert self.instance.constants == p_expected
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assert isinstance(self.instance.p, Matrix)
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assert isinstance(self.instance.constants, Matrix)
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assert self.instance.p.shape == (3, 1)
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assert self.instance.constants.shape == (3, 1)
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def test_M(self):
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assert hasattr(self.instance, 'M')
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M_expected = Matrix([1])
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assert self.instance.M == M_expected
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assert isinstance(self.instance.M, Matrix)
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assert self.instance.M.shape == (1, 1)
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def test_F(self):
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assert hasattr(self.instance, 'F')
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da_expr = (
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((1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
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*(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
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+ ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
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*(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a))))
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*(self.e - self.a)
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)
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F_expected = Matrix([da_expr])
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assert self.instance.F == F_expected
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assert isinstance(self.instance.F, Matrix)
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assert self.instance.F.shape == (1, 1)
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def test_rhs(self):
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assert hasattr(self.instance, 'rhs')
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da_expr = (
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((1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
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*(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
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+ ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
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*(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a))))
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*(self.e - self.a)
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)
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rhs_expected = Matrix([da_expr])
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rhs = self.instance.rhs()
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assert rhs == rhs_expected
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assert isinstance(rhs, Matrix)
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assert rhs.shape == (1, 1)
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assert simplify(self.instance.M.solve(self.instance.F) - rhs) == zeros(1)
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def test_repr(self):
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expected = (
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'FirstOrderActivationDeGroote2016(\'name\', '
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'activation_time_constant=tau_a, '
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'deactivation_time_constant=tau_d, '
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'smoothing_rate=b)'
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)
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assert repr(self.instance) == expected
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File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,48 @@
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"""Tests for the ``sympy.physics.biomechanics._mixin.py`` module."""
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import pytest
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from sympy.physics.biomechanics._mixin import _NamedMixin
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class TestNamedMixin:
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@staticmethod
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def test_subclass():
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class Subclass(_NamedMixin):
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def __init__(self, name):
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self.name = name
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instance = Subclass('name')
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assert instance.name == 'name'
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@pytest.fixture(autouse=True)
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def _named_mixin_fixture(self):
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class Subclass(_NamedMixin):
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def __init__(self, name):
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self.name = name
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self.Subclass = Subclass
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@pytest.mark.parametrize('name', ['a', 'name', 'long_name'])
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def test_valid_name_argument(self, name):
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instance = self.Subclass(name)
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assert instance.name == name
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@pytest.mark.parametrize('invalid_name', [0, 0.0, None, False])
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def test_invalid_name_argument_not_str(self, invalid_name):
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with pytest.raises(TypeError):
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_ = self.Subclass(invalid_name)
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def test_invalid_name_argument_zero_length_str(self):
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with pytest.raises(ValueError):
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_ = self.Subclass('')
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def test_name_attribute_is_immutable(self):
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instance = self.Subclass('name')
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with pytest.raises(AttributeError):
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instance.name = 'new_name'
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@@ -0,0 +1,837 @@
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"""Tests for the ``sympy.physics.biomechanics.musculotendon.py`` module."""
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import abc
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import pytest
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from sympy.core.expr import UnevaluatedExpr
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from sympy.core.numbers import Float, Integer, Rational
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from sympy.core.symbol import Symbol
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from sympy.functions.elementary.exponential import exp
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from sympy.functions.elementary.hyperbolic import tanh
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from sympy.functions.elementary.miscellaneous import sqrt
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from sympy.functions.elementary.trigonometric import sin
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from sympy.matrices.dense import MutableDenseMatrix as Matrix, eye, zeros
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from sympy.physics.biomechanics.activation import (
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FirstOrderActivationDeGroote2016
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)
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from sympy.physics.biomechanics.curve import (
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CharacteristicCurveCollection,
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FiberForceLengthActiveDeGroote2016,
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FiberForceLengthPassiveDeGroote2016,
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FiberForceLengthPassiveInverseDeGroote2016,
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FiberForceVelocityDeGroote2016,
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FiberForceVelocityInverseDeGroote2016,
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TendonForceLengthDeGroote2016,
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TendonForceLengthInverseDeGroote2016,
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)
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from sympy.physics.biomechanics.musculotendon import (
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MusculotendonBase,
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MusculotendonDeGroote2016,
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MusculotendonFormulation,
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||||
)
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from sympy.physics.biomechanics._mixin import _NamedMixin
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from sympy.physics.mechanics.actuator import ForceActuator
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from sympy.physics.mechanics.pathway import LinearPathway
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from sympy.physics.vector.frame import ReferenceFrame
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from sympy.physics.vector.functions import dynamicsymbols
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from sympy.physics.vector.point import Point
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from sympy.simplify.simplify import simplify
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||||
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||||
class TestMusculotendonFormulation:
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@staticmethod
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def test_rigid_tendon_member():
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assert MusculotendonFormulation(0) == 0
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assert MusculotendonFormulation.RIGID_TENDON == 0
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||||
@staticmethod
|
||||
def test_fiber_length_explicit_member():
|
||||
assert MusculotendonFormulation(1) == 1
|
||||
assert MusculotendonFormulation.FIBER_LENGTH_EXPLICIT == 1
|
||||
|
||||
@staticmethod
|
||||
def test_tendon_force_explicit_member():
|
||||
assert MusculotendonFormulation(2) == 2
|
||||
assert MusculotendonFormulation.TENDON_FORCE_EXPLICIT == 2
|
||||
|
||||
@staticmethod
|
||||
def test_fiber_length_implicit_member():
|
||||
assert MusculotendonFormulation(3) == 3
|
||||
assert MusculotendonFormulation.FIBER_LENGTH_IMPLICIT == 3
|
||||
|
||||
@staticmethod
|
||||
def test_tendon_force_implicit_member():
|
||||
assert MusculotendonFormulation(4) == 4
|
||||
assert MusculotendonFormulation.TENDON_FORCE_IMPLICIT == 4
|
||||
|
||||
|
||||
class TestMusculotendonBase:
|
||||
|
||||
@staticmethod
|
||||
def test_is_abstract_base_class():
|
||||
assert issubclass(MusculotendonBase, abc.ABC)
|
||||
|
||||
@staticmethod
|
||||
def test_class():
|
||||
assert issubclass(MusculotendonBase, ForceActuator)
|
||||
assert issubclass(MusculotendonBase, _NamedMixin)
|
||||
assert MusculotendonBase.__name__ == 'MusculotendonBase'
|
||||
|
||||
@staticmethod
|
||||
def test_cannot_instantiate_directly():
|
||||
with pytest.raises(TypeError):
|
||||
_ = MusculotendonBase()
|
||||
|
||||
|
||||
@pytest.mark.parametrize('musculotendon_concrete', [MusculotendonDeGroote2016])
|
||||
class TestMusculotendonRigidTendon:
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _musculotendon_rigid_tendon_fixture(self, musculotendon_concrete):
|
||||
self.name = 'name'
|
||||
self.N = ReferenceFrame('N')
|
||||
self.q = dynamicsymbols('q')
|
||||
self.origin = Point('pO')
|
||||
self.insertion = Point('pI')
|
||||
self.insertion.set_pos(self.origin, self.q*self.N.x)
|
||||
self.pathway = LinearPathway(self.origin, self.insertion)
|
||||
self.activation = FirstOrderActivationDeGroote2016(self.name)
|
||||
self.e = self.activation.excitation
|
||||
self.a = self.activation.activation
|
||||
self.tau_a = self.activation.activation_time_constant
|
||||
self.tau_d = self.activation.deactivation_time_constant
|
||||
self.b = self.activation.smoothing_rate
|
||||
self.formulation = MusculotendonFormulation.RIGID_TENDON
|
||||
self.l_T_slack = Symbol('l_T_slack')
|
||||
self.F_M_max = Symbol('F_M_max')
|
||||
self.l_M_opt = Symbol('l_M_opt')
|
||||
self.v_M_max = Symbol('v_M_max')
|
||||
self.alpha_opt = Symbol('alpha_opt')
|
||||
self.beta = Symbol('beta')
|
||||
self.instance = musculotendon_concrete(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=self.formulation,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
self.da_expr = (
|
||||
(1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
|
||||
*(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
+ ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
|
||||
*(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
)*(self.e - self.a)
|
||||
|
||||
def test_state_vars(self):
|
||||
assert hasattr(self.instance, 'x')
|
||||
assert hasattr(self.instance, 'state_vars')
|
||||
assert self.instance.x == self.instance.state_vars
|
||||
x_expected = Matrix([self.a])
|
||||
assert self.instance.x == x_expected
|
||||
assert self.instance.state_vars == x_expected
|
||||
assert isinstance(self.instance.x, Matrix)
|
||||
assert isinstance(self.instance.state_vars, Matrix)
|
||||
assert self.instance.x.shape == (1, 1)
|
||||
assert self.instance.state_vars.shape == (1, 1)
|
||||
|
||||
def test_input_vars(self):
|
||||
assert hasattr(self.instance, 'r')
|
||||
assert hasattr(self.instance, 'input_vars')
|
||||
assert self.instance.r == self.instance.input_vars
|
||||
r_expected = Matrix([self.e])
|
||||
assert self.instance.r == r_expected
|
||||
assert self.instance.input_vars == r_expected
|
||||
assert isinstance(self.instance.r, Matrix)
|
||||
assert isinstance(self.instance.input_vars, Matrix)
|
||||
assert self.instance.r.shape == (1, 1)
|
||||
assert self.instance.input_vars.shape == (1, 1)
|
||||
|
||||
def test_constants(self):
|
||||
assert hasattr(self.instance, 'p')
|
||||
assert hasattr(self.instance, 'constants')
|
||||
assert self.instance.p == self.instance.constants
|
||||
p_expected = Matrix(
|
||||
[
|
||||
self.l_T_slack,
|
||||
self.F_M_max,
|
||||
self.l_M_opt,
|
||||
self.v_M_max,
|
||||
self.alpha_opt,
|
||||
self.beta,
|
||||
self.tau_a,
|
||||
self.tau_d,
|
||||
self.b,
|
||||
Symbol('c_0_fl_T_name'),
|
||||
Symbol('c_1_fl_T_name'),
|
||||
Symbol('c_2_fl_T_name'),
|
||||
Symbol('c_3_fl_T_name'),
|
||||
Symbol('c_0_fl_M_pas_name'),
|
||||
Symbol('c_1_fl_M_pas_name'),
|
||||
Symbol('c_0_fl_M_act_name'),
|
||||
Symbol('c_1_fl_M_act_name'),
|
||||
Symbol('c_2_fl_M_act_name'),
|
||||
Symbol('c_3_fl_M_act_name'),
|
||||
Symbol('c_4_fl_M_act_name'),
|
||||
Symbol('c_5_fl_M_act_name'),
|
||||
Symbol('c_6_fl_M_act_name'),
|
||||
Symbol('c_7_fl_M_act_name'),
|
||||
Symbol('c_8_fl_M_act_name'),
|
||||
Symbol('c_9_fl_M_act_name'),
|
||||
Symbol('c_10_fl_M_act_name'),
|
||||
Symbol('c_11_fl_M_act_name'),
|
||||
Symbol('c_0_fv_M_name'),
|
||||
Symbol('c_1_fv_M_name'),
|
||||
Symbol('c_2_fv_M_name'),
|
||||
Symbol('c_3_fv_M_name'),
|
||||
]
|
||||
)
|
||||
assert self.instance.p == p_expected
|
||||
assert self.instance.constants == p_expected
|
||||
assert isinstance(self.instance.p, Matrix)
|
||||
assert isinstance(self.instance.constants, Matrix)
|
||||
assert self.instance.p.shape == (31, 1)
|
||||
assert self.instance.constants.shape == (31, 1)
|
||||
|
||||
def test_M(self):
|
||||
assert hasattr(self.instance, 'M')
|
||||
M_expected = Matrix([1])
|
||||
assert self.instance.M == M_expected
|
||||
assert isinstance(self.instance.M, Matrix)
|
||||
assert self.instance.M.shape == (1, 1)
|
||||
|
||||
def test_F(self):
|
||||
assert hasattr(self.instance, 'F')
|
||||
F_expected = Matrix([self.da_expr])
|
||||
assert self.instance.F == F_expected
|
||||
assert isinstance(self.instance.F, Matrix)
|
||||
assert self.instance.F.shape == (1, 1)
|
||||
|
||||
def test_rhs(self):
|
||||
assert hasattr(self.instance, 'rhs')
|
||||
rhs_expected = Matrix([self.da_expr])
|
||||
rhs = self.instance.rhs()
|
||||
assert isinstance(rhs, Matrix)
|
||||
assert rhs.shape == (1, 1)
|
||||
assert simplify(rhs - rhs_expected) == zeros(1)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'musculotendon_concrete, curve',
|
||||
[
|
||||
(
|
||||
MusculotendonDeGroote2016,
|
||||
CharacteristicCurveCollection(
|
||||
tendon_force_length=TendonForceLengthDeGroote2016,
|
||||
tendon_force_length_inverse=TendonForceLengthInverseDeGroote2016,
|
||||
fiber_force_length_passive=FiberForceLengthPassiveDeGroote2016,
|
||||
fiber_force_length_passive_inverse=FiberForceLengthPassiveInverseDeGroote2016,
|
||||
fiber_force_length_active=FiberForceLengthActiveDeGroote2016,
|
||||
fiber_force_velocity=FiberForceVelocityDeGroote2016,
|
||||
fiber_force_velocity_inverse=FiberForceVelocityInverseDeGroote2016,
|
||||
),
|
||||
)
|
||||
],
|
||||
)
|
||||
class TestFiberLengthExplicit:
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _musculotendon_fiber_length_explicit_fixture(
|
||||
self,
|
||||
musculotendon_concrete,
|
||||
curve,
|
||||
):
|
||||
self.name = 'name'
|
||||
self.N = ReferenceFrame('N')
|
||||
self.q = dynamicsymbols('q')
|
||||
self.origin = Point('pO')
|
||||
self.insertion = Point('pI')
|
||||
self.insertion.set_pos(self.origin, self.q*self.N.x)
|
||||
self.pathway = LinearPathway(self.origin, self.insertion)
|
||||
self.activation = FirstOrderActivationDeGroote2016(self.name)
|
||||
self.e = self.activation.excitation
|
||||
self.a = self.activation.activation
|
||||
self.tau_a = self.activation.activation_time_constant
|
||||
self.tau_d = self.activation.deactivation_time_constant
|
||||
self.b = self.activation.smoothing_rate
|
||||
self.formulation = MusculotendonFormulation.FIBER_LENGTH_EXPLICIT
|
||||
self.l_T_slack = Symbol('l_T_slack')
|
||||
self.F_M_max = Symbol('F_M_max')
|
||||
self.l_M_opt = Symbol('l_M_opt')
|
||||
self.v_M_max = Symbol('v_M_max')
|
||||
self.alpha_opt = Symbol('alpha_opt')
|
||||
self.beta = Symbol('beta')
|
||||
self.instance = musculotendon_concrete(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=self.formulation,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
with_defaults=True,
|
||||
)
|
||||
self.l_M_tilde = dynamicsymbols('l_M_tilde_name')
|
||||
l_MT = self.pathway.length
|
||||
l_M = self.l_M_tilde*self.l_M_opt
|
||||
l_T = l_MT - sqrt(l_M**2 - (self.l_M_opt*sin(self.alpha_opt))**2)
|
||||
fl_T = curve.tendon_force_length.with_defaults(l_T/self.l_T_slack)
|
||||
fl_M_pas = curve.fiber_force_length_passive.with_defaults(self.l_M_tilde)
|
||||
fl_M_act = curve.fiber_force_length_active.with_defaults(self.l_M_tilde)
|
||||
v_M_tilde = curve.fiber_force_velocity_inverse.with_defaults(
|
||||
((((fl_T*self.F_M_max)/((l_MT - l_T)/l_M))/self.F_M_max) - fl_M_pas)
|
||||
/(self.a*fl_M_act)
|
||||
)
|
||||
self.dl_M_tilde_expr = (self.v_M_max/self.l_M_opt)*v_M_tilde
|
||||
self.da_expr = (
|
||||
(1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
|
||||
*(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
+ ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
|
||||
*(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
)*(self.e - self.a)
|
||||
|
||||
def test_state_vars(self):
|
||||
assert hasattr(self.instance, 'x')
|
||||
assert hasattr(self.instance, 'state_vars')
|
||||
assert self.instance.x == self.instance.state_vars
|
||||
x_expected = Matrix([self.l_M_tilde, self.a])
|
||||
assert self.instance.x == x_expected
|
||||
assert self.instance.state_vars == x_expected
|
||||
assert isinstance(self.instance.x, Matrix)
|
||||
assert isinstance(self.instance.state_vars, Matrix)
|
||||
assert self.instance.x.shape == (2, 1)
|
||||
assert self.instance.state_vars.shape == (2, 1)
|
||||
|
||||
def test_input_vars(self):
|
||||
assert hasattr(self.instance, 'r')
|
||||
assert hasattr(self.instance, 'input_vars')
|
||||
assert self.instance.r == self.instance.input_vars
|
||||
r_expected = Matrix([self.e])
|
||||
assert self.instance.r == r_expected
|
||||
assert self.instance.input_vars == r_expected
|
||||
assert isinstance(self.instance.r, Matrix)
|
||||
assert isinstance(self.instance.input_vars, Matrix)
|
||||
assert self.instance.r.shape == (1, 1)
|
||||
assert self.instance.input_vars.shape == (1, 1)
|
||||
|
||||
def test_constants(self):
|
||||
assert hasattr(self.instance, 'p')
|
||||
assert hasattr(self.instance, 'constants')
|
||||
assert self.instance.p == self.instance.constants
|
||||
p_expected = Matrix(
|
||||
[
|
||||
self.l_T_slack,
|
||||
self.F_M_max,
|
||||
self.l_M_opt,
|
||||
self.v_M_max,
|
||||
self.alpha_opt,
|
||||
self.beta,
|
||||
self.tau_a,
|
||||
self.tau_d,
|
||||
self.b,
|
||||
]
|
||||
)
|
||||
assert self.instance.p == p_expected
|
||||
assert self.instance.constants == p_expected
|
||||
assert isinstance(self.instance.p, Matrix)
|
||||
assert isinstance(self.instance.constants, Matrix)
|
||||
assert self.instance.p.shape == (9, 1)
|
||||
assert self.instance.constants.shape == (9, 1)
|
||||
|
||||
def test_M(self):
|
||||
assert hasattr(self.instance, 'M')
|
||||
M_expected = eye(2)
|
||||
assert self.instance.M == M_expected
|
||||
assert isinstance(self.instance.M, Matrix)
|
||||
assert self.instance.M.shape == (2, 2)
|
||||
|
||||
def test_F(self):
|
||||
assert hasattr(self.instance, 'F')
|
||||
F_expected = Matrix([self.dl_M_tilde_expr, self.da_expr])
|
||||
assert self.instance.F == F_expected
|
||||
assert isinstance(self.instance.F, Matrix)
|
||||
assert self.instance.F.shape == (2, 1)
|
||||
|
||||
def test_rhs(self):
|
||||
assert hasattr(self.instance, 'rhs')
|
||||
rhs_expected = Matrix([self.dl_M_tilde_expr, self.da_expr])
|
||||
rhs = self.instance.rhs()
|
||||
assert isinstance(rhs, Matrix)
|
||||
assert rhs.shape == (2, 1)
|
||||
assert simplify(rhs - rhs_expected) == zeros(2, 1)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'musculotendon_concrete, curve',
|
||||
[
|
||||
(
|
||||
MusculotendonDeGroote2016,
|
||||
CharacteristicCurveCollection(
|
||||
tendon_force_length=TendonForceLengthDeGroote2016,
|
||||
tendon_force_length_inverse=TendonForceLengthInverseDeGroote2016,
|
||||
fiber_force_length_passive=FiberForceLengthPassiveDeGroote2016,
|
||||
fiber_force_length_passive_inverse=FiberForceLengthPassiveInverseDeGroote2016,
|
||||
fiber_force_length_active=FiberForceLengthActiveDeGroote2016,
|
||||
fiber_force_velocity=FiberForceVelocityDeGroote2016,
|
||||
fiber_force_velocity_inverse=FiberForceVelocityInverseDeGroote2016,
|
||||
),
|
||||
)
|
||||
],
|
||||
)
|
||||
class TestTendonForceExplicit:
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _musculotendon_tendon_force_explicit_fixture(
|
||||
self,
|
||||
musculotendon_concrete,
|
||||
curve,
|
||||
):
|
||||
self.name = 'name'
|
||||
self.N = ReferenceFrame('N')
|
||||
self.q = dynamicsymbols('q')
|
||||
self.origin = Point('pO')
|
||||
self.insertion = Point('pI')
|
||||
self.insertion.set_pos(self.origin, self.q*self.N.x)
|
||||
self.pathway = LinearPathway(self.origin, self.insertion)
|
||||
self.activation = FirstOrderActivationDeGroote2016(self.name)
|
||||
self.e = self.activation.excitation
|
||||
self.a = self.activation.activation
|
||||
self.tau_a = self.activation.activation_time_constant
|
||||
self.tau_d = self.activation.deactivation_time_constant
|
||||
self.b = self.activation.smoothing_rate
|
||||
self.formulation = MusculotendonFormulation.TENDON_FORCE_EXPLICIT
|
||||
self.l_T_slack = Symbol('l_T_slack')
|
||||
self.F_M_max = Symbol('F_M_max')
|
||||
self.l_M_opt = Symbol('l_M_opt')
|
||||
self.v_M_max = Symbol('v_M_max')
|
||||
self.alpha_opt = Symbol('alpha_opt')
|
||||
self.beta = Symbol('beta')
|
||||
self.instance = musculotendon_concrete(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=self.formulation,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
with_defaults=True,
|
||||
)
|
||||
self.F_T_tilde = dynamicsymbols('F_T_tilde_name')
|
||||
l_T_tilde = curve.tendon_force_length_inverse.with_defaults(self.F_T_tilde)
|
||||
l_MT = self.pathway.length
|
||||
v_MT = self.pathway.extension_velocity
|
||||
l_T = l_T_tilde*self.l_T_slack
|
||||
l_M = sqrt((l_MT - l_T)**2 + (self.l_M_opt*sin(self.alpha_opt))**2)
|
||||
l_M_tilde = l_M/self.l_M_opt
|
||||
cos_alpha = (l_MT - l_T)/l_M
|
||||
F_T = self.F_T_tilde*self.F_M_max
|
||||
F_M = F_T/cos_alpha
|
||||
F_M_tilde = F_M/self.F_M_max
|
||||
fl_M_pas = curve.fiber_force_length_passive.with_defaults(l_M_tilde)
|
||||
fl_M_act = curve.fiber_force_length_active.with_defaults(l_M_tilde)
|
||||
fv_M = (F_M_tilde - fl_M_pas)/(self.a*fl_M_act)
|
||||
v_M_tilde = curve.fiber_force_velocity_inverse.with_defaults(fv_M)
|
||||
v_M = v_M_tilde*self.v_M_max
|
||||
v_T = v_MT - v_M/cos_alpha
|
||||
v_T_tilde = v_T/self.l_T_slack
|
||||
self.dF_T_tilde_expr = (
|
||||
Float('0.2')*Float('33.93669377311689')*exp(
|
||||
Float('33.93669377311689')*UnevaluatedExpr(l_T_tilde - Float('0.995'))
|
||||
)*v_T_tilde
|
||||
)
|
||||
self.da_expr = (
|
||||
(1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
|
||||
*(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
+ ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
|
||||
*(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a)))
|
||||
)*(self.e - self.a)
|
||||
|
||||
def test_state_vars(self):
|
||||
assert hasattr(self.instance, 'x')
|
||||
assert hasattr(self.instance, 'state_vars')
|
||||
assert self.instance.x == self.instance.state_vars
|
||||
x_expected = Matrix([self.F_T_tilde, self.a])
|
||||
assert self.instance.x == x_expected
|
||||
assert self.instance.state_vars == x_expected
|
||||
assert isinstance(self.instance.x, Matrix)
|
||||
assert isinstance(self.instance.state_vars, Matrix)
|
||||
assert self.instance.x.shape == (2, 1)
|
||||
assert self.instance.state_vars.shape == (2, 1)
|
||||
|
||||
def test_input_vars(self):
|
||||
assert hasattr(self.instance, 'r')
|
||||
assert hasattr(self.instance, 'input_vars')
|
||||
assert self.instance.r == self.instance.input_vars
|
||||
r_expected = Matrix([self.e])
|
||||
assert self.instance.r == r_expected
|
||||
assert self.instance.input_vars == r_expected
|
||||
assert isinstance(self.instance.r, Matrix)
|
||||
assert isinstance(self.instance.input_vars, Matrix)
|
||||
assert self.instance.r.shape == (1, 1)
|
||||
assert self.instance.input_vars.shape == (1, 1)
|
||||
|
||||
def test_constants(self):
|
||||
assert hasattr(self.instance, 'p')
|
||||
assert hasattr(self.instance, 'constants')
|
||||
assert self.instance.p == self.instance.constants
|
||||
p_expected = Matrix(
|
||||
[
|
||||
self.l_T_slack,
|
||||
self.F_M_max,
|
||||
self.l_M_opt,
|
||||
self.v_M_max,
|
||||
self.alpha_opt,
|
||||
self.beta,
|
||||
self.tau_a,
|
||||
self.tau_d,
|
||||
self.b,
|
||||
]
|
||||
)
|
||||
assert self.instance.p == p_expected
|
||||
assert self.instance.constants == p_expected
|
||||
assert isinstance(self.instance.p, Matrix)
|
||||
assert isinstance(self.instance.constants, Matrix)
|
||||
assert self.instance.p.shape == (9, 1)
|
||||
assert self.instance.constants.shape == (9, 1)
|
||||
|
||||
def test_M(self):
|
||||
assert hasattr(self.instance, 'M')
|
||||
M_expected = eye(2)
|
||||
assert self.instance.M == M_expected
|
||||
assert isinstance(self.instance.M, Matrix)
|
||||
assert self.instance.M.shape == (2, 2)
|
||||
|
||||
def test_F(self):
|
||||
assert hasattr(self.instance, 'F')
|
||||
F_expected = Matrix([self.dF_T_tilde_expr, self.da_expr])
|
||||
assert self.instance.F == F_expected
|
||||
assert isinstance(self.instance.F, Matrix)
|
||||
assert self.instance.F.shape == (2, 1)
|
||||
|
||||
def test_rhs(self):
|
||||
assert hasattr(self.instance, 'rhs')
|
||||
rhs_expected = Matrix([self.dF_T_tilde_expr, self.da_expr])
|
||||
rhs = self.instance.rhs()
|
||||
assert isinstance(rhs, Matrix)
|
||||
assert rhs.shape == (2, 1)
|
||||
assert simplify(rhs - rhs_expected) == zeros(2, 1)
|
||||
|
||||
|
||||
class TestMusculotendonDeGroote2016:
|
||||
|
||||
@staticmethod
|
||||
def test_class():
|
||||
assert issubclass(MusculotendonDeGroote2016, ForceActuator)
|
||||
assert issubclass(MusculotendonDeGroote2016, _NamedMixin)
|
||||
assert MusculotendonDeGroote2016.__name__ == 'MusculotendonDeGroote2016'
|
||||
|
||||
@staticmethod
|
||||
def test_instance():
|
||||
origin = Point('pO')
|
||||
insertion = Point('pI')
|
||||
insertion.set_pos(origin, dynamicsymbols('q')*ReferenceFrame('N').x)
|
||||
pathway = LinearPathway(origin, insertion)
|
||||
activation = FirstOrderActivationDeGroote2016('name')
|
||||
l_T_slack = Symbol('l_T_slack')
|
||||
F_M_max = Symbol('F_M_max')
|
||||
l_M_opt = Symbol('l_M_opt')
|
||||
v_M_max = Symbol('v_M_max')
|
||||
alpha_opt = Symbol('alpha_opt')
|
||||
beta = Symbol('beta')
|
||||
instance = MusculotendonDeGroote2016(
|
||||
'name',
|
||||
pathway,
|
||||
activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=l_T_slack,
|
||||
peak_isometric_force=F_M_max,
|
||||
optimal_fiber_length=l_M_opt,
|
||||
maximal_fiber_velocity=v_M_max,
|
||||
optimal_pennation_angle=alpha_opt,
|
||||
fiber_damping_coefficient=beta,
|
||||
)
|
||||
assert isinstance(instance, MusculotendonDeGroote2016)
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _musculotendon_fixture(self):
|
||||
self.name = 'name'
|
||||
self.N = ReferenceFrame('N')
|
||||
self.q = dynamicsymbols('q')
|
||||
self.origin = Point('pO')
|
||||
self.insertion = Point('pI')
|
||||
self.insertion.set_pos(self.origin, self.q*self.N.x)
|
||||
self.pathway = LinearPathway(self.origin, self.insertion)
|
||||
self.activation = FirstOrderActivationDeGroote2016(self.name)
|
||||
self.l_T_slack = Symbol('l_T_slack')
|
||||
self.F_M_max = Symbol('F_M_max')
|
||||
self.l_M_opt = Symbol('l_M_opt')
|
||||
self.v_M_max = Symbol('v_M_max')
|
||||
self.alpha_opt = Symbol('alpha_opt')
|
||||
self.beta = Symbol('beta')
|
||||
|
||||
def test_with_defaults(self):
|
||||
origin = Point('pO')
|
||||
insertion = Point('pI')
|
||||
insertion.set_pos(origin, dynamicsymbols('q')*ReferenceFrame('N').x)
|
||||
pathway = LinearPathway(origin, insertion)
|
||||
activation = FirstOrderActivationDeGroote2016('name')
|
||||
l_T_slack = Symbol('l_T_slack')
|
||||
F_M_max = Symbol('F_M_max')
|
||||
l_M_opt = Symbol('l_M_opt')
|
||||
v_M_max = Float('10.0')
|
||||
alpha_opt = Float('0.0')
|
||||
beta = Float('0.1')
|
||||
instance = MusculotendonDeGroote2016.with_defaults(
|
||||
'name',
|
||||
pathway,
|
||||
activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=l_T_slack,
|
||||
peak_isometric_force=F_M_max,
|
||||
optimal_fiber_length=l_M_opt,
|
||||
)
|
||||
assert instance.tendon_slack_length == l_T_slack
|
||||
assert instance.peak_isometric_force == F_M_max
|
||||
assert instance.optimal_fiber_length == l_M_opt
|
||||
assert instance.maximal_fiber_velocity == v_M_max
|
||||
assert instance.optimal_pennation_angle == alpha_opt
|
||||
assert instance.fiber_damping_coefficient == beta
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'l_T_slack, expected',
|
||||
[
|
||||
(None, Symbol('l_T_slack_name')),
|
||||
(Symbol('l_T_slack'), Symbol('l_T_slack')),
|
||||
(Rational(1, 2), Rational(1, 2)),
|
||||
(Float('0.5'), Float('0.5')),
|
||||
],
|
||||
)
|
||||
def test_tendon_slack_length(self, l_T_slack, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
assert instance.l_T_slack == expected
|
||||
assert instance.tendon_slack_length == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'F_M_max, expected',
|
||||
[
|
||||
(None, Symbol('F_M_max_name')),
|
||||
(Symbol('F_M_max'), Symbol('F_M_max')),
|
||||
(Integer(1000), Integer(1000)),
|
||||
(Float('1000.0'), Float('1000.0')),
|
||||
],
|
||||
)
|
||||
def test_peak_isometric_force(self, F_M_max, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
assert instance.F_M_max == expected
|
||||
assert instance.peak_isometric_force == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'l_M_opt, expected',
|
||||
[
|
||||
(None, Symbol('l_M_opt_name')),
|
||||
(Symbol('l_M_opt'), Symbol('l_M_opt')),
|
||||
(Rational(1, 2), Rational(1, 2)),
|
||||
(Float('0.5'), Float('0.5')),
|
||||
],
|
||||
)
|
||||
def test_optimal_fiber_length(self, l_M_opt, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
assert instance.l_M_opt == expected
|
||||
assert instance.optimal_fiber_length == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'v_M_max, expected',
|
||||
[
|
||||
(None, Symbol('v_M_max_name')),
|
||||
(Symbol('v_M_max'), Symbol('v_M_max')),
|
||||
(Integer(10), Integer(10)),
|
||||
(Float('10.0'), Float('10.0')),
|
||||
],
|
||||
)
|
||||
def test_maximal_fiber_velocity(self, v_M_max, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
assert instance.v_M_max == expected
|
||||
assert instance.maximal_fiber_velocity == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'alpha_opt, expected',
|
||||
[
|
||||
(None, Symbol('alpha_opt_name')),
|
||||
(Symbol('alpha_opt'), Symbol('alpha_opt')),
|
||||
(Integer(0), Integer(0)),
|
||||
(Float('0.1'), Float('0.1')),
|
||||
],
|
||||
)
|
||||
def test_optimal_pennation_angle(self, alpha_opt, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
assert instance.alpha_opt == expected
|
||||
assert instance.optimal_pennation_angle == expected
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
'beta, expected',
|
||||
[
|
||||
(None, Symbol('beta_name')),
|
||||
(Symbol('beta'), Symbol('beta')),
|
||||
(Integer(0), Integer(0)),
|
||||
(Rational(1, 10), Rational(1, 10)),
|
||||
(Float('0.1'), Float('0.1')),
|
||||
],
|
||||
)
|
||||
def test_fiber_damping_coefficient(self, beta, expected):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=beta,
|
||||
)
|
||||
assert instance.beta == expected
|
||||
assert instance.fiber_damping_coefficient == expected
|
||||
|
||||
def test_excitation(self):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
)
|
||||
assert hasattr(instance, 'e')
|
||||
assert hasattr(instance, 'excitation')
|
||||
e_expected = dynamicsymbols('e_name')
|
||||
assert instance.e == e_expected
|
||||
assert instance.excitation == e_expected
|
||||
assert instance.e is instance.excitation
|
||||
|
||||
def test_excitation_is_immutable(self):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
)
|
||||
with pytest.raises(AttributeError):
|
||||
instance.e = None
|
||||
with pytest.raises(AttributeError):
|
||||
instance.excitation = None
|
||||
|
||||
def test_activation(self):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
)
|
||||
assert hasattr(instance, 'a')
|
||||
assert hasattr(instance, 'activation')
|
||||
a_expected = dynamicsymbols('a_name')
|
||||
assert instance.a == a_expected
|
||||
assert instance.activation == a_expected
|
||||
|
||||
def test_activation_is_immutable(self):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
)
|
||||
with pytest.raises(AttributeError):
|
||||
instance.a = None
|
||||
with pytest.raises(AttributeError):
|
||||
instance.activation = None
|
||||
|
||||
def test_repr(self):
|
||||
instance = MusculotendonDeGroote2016(
|
||||
self.name,
|
||||
self.pathway,
|
||||
self.activation,
|
||||
musculotendon_dynamics=MusculotendonFormulation.RIGID_TENDON,
|
||||
tendon_slack_length=self.l_T_slack,
|
||||
peak_isometric_force=self.F_M_max,
|
||||
optimal_fiber_length=self.l_M_opt,
|
||||
maximal_fiber_velocity=self.v_M_max,
|
||||
optimal_pennation_angle=self.alpha_opt,
|
||||
fiber_damping_coefficient=self.beta,
|
||||
)
|
||||
expected = (
|
||||
'MusculotendonDeGroote2016(\'name\', '
|
||||
'pathway=LinearPathway(pO, pI), '
|
||||
'activation_dynamics=FirstOrderActivationDeGroote2016(\'name\', '
|
||||
'activation_time_constant=tau_a_name, '
|
||||
'deactivation_time_constant=tau_d_name, '
|
||||
'smoothing_rate=b_name), '
|
||||
'musculotendon_dynamics=0, '
|
||||
'tendon_slack_length=l_T_slack, '
|
||||
'peak_isometric_force=F_M_max, '
|
||||
'optimal_fiber_length=l_M_opt, '
|
||||
'maximal_fiber_velocity=v_M_max, '
|
||||
'optimal_pennation_angle=alpha_opt, '
|
||||
'fiber_damping_coefficient=beta)'
|
||||
)
|
||||
assert repr(instance) == expected
|
||||
Reference in New Issue
Block a user