def test_simplify_detect_negative_alias(self):
# Create model, cache it, and load the cache
compiler_options = \
{'detect_aliases': True}
casadi_model = transfer_model(TEST_DIR, 'NegativeAlias',
compiler_options)
ref_model = Model()
x = ca.MX.sym('x')
der_x = ca.MX.sym('der(x)')
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].min = 1
ref_model.states[0].max = 2
ref_model.states[0].nominal = 10
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, []))
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.equations = [der_x - x]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
self.assertEquals(casadi_model.states[0].aliases, ['-alias'])
def test_forloop(self):
with open(os.path.join(TEST_DIR, 'ForLoop.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'ForLoop')
print(casadi_model)
ref_model = Model()
x = ca.MX.sym("x", 10)
y = ca.MX.sym("y", 10)
z = ca.MX.sym("z", 10)
u = ca.MX.sym('u', 10, 2)
v = ca.MX.sym('v', 2, 10)
w = ca.MX.sym('w', 2, 10)
b = ca.MX.sym("b")
n = ca.MX.sym("n")
s = ca.MX.sym('s', 10)
Arr = ca.MX.sym('Arr', 2, 2)
der_s = ca.MX.sym('der(s)', 10)
ref_model.states = list(map(Variable, [s]))
ref_model.der_states = list(map(Variable, [der_s]))
ref_model.alg_states = list(map(Variable, [x, y, z, u, v, w, b, Arr]))
ref_model.parameters = list(map(Variable, [n]))
ref_model.parameters[0].value = 10
ref_model.equations = [
ca.horzcat(x - (np.arange(1, 11) + b), w[0, :].T - np.arange(1, 11), w[1, :].T - np.arange(2, 21, 2), u - np.ones((10, 2)), v.T - np.ones((10, 2))),
y[0:5] - np.zeros(5), y[5:] - np.ones(5),
ca.horzcat(z[0:5] - np.array([2, 2, 2, 2, 2]), z[5:10] - np.array([1, 1, 1, 1, 1])), der_s - np.ones(10), ca.horzcat(Arr[:, 1], Arr[:, 0]) - np.array([[2, 1], [2, 1]])]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_inheritance_instantiation(self):
with open(os.path.join(TEST_DIR, 'InheritanceInstantiation.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'C2')
ref_model = Model()
print(casadi_model)
bcomp1_a = ca.MX.sym('bcomp1.a')
bcomp1_b = ca.MX.sym('bcomp1.b')
bcomp2_a = ca.MX.sym('bcomp2.a')
bcomp2_b = ca.MX.sym('bcomp2.b')
bcomp3_a = ca.MX.sym('bcomp3.a')
bcomp3_b = ca.MX.sym('bcomp3.b')
bcomp1_v = ca.MX.sym('bcomp1.v', 3)
bcomp2_v = ca.MX.sym('bcomp2.v', 4)
bcomp3_v = ca.MX.sym('bcomp3.v', 2)
ref_model.states = []
ref_model.der_states = []
ref_model.alg_states = list(map(Variable, [bcomp1_v, bcomp2_v, bcomp3_v]))
ref_model.parameters = list(map(Variable, [bcomp1_a, bcomp2_a, bcomp3_a, bcomp1_b, bcomp2_b, bcomp3_b]))
ref_model.parameters[0].value = 0
ref_model.parameters[1].value = 0
ref_model.parameters[2].value = 1
ref_model.parameters[3].value = 3
ref_model.parameters[4].value = 4
ref_model.parameters[5].value = 2
ref_model.equations = []
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_simplify_all(self):
# Create model, cache it, and load the cache
compiler_options = \
{'expand_vectors': True,
'replace_constant_values': True,
'replace_constant_expressions': True,
'replace_parameter_values': True,
'replace_parameter_expressions': True,
'eliminate_constant_assignments': True,
'detect_aliases': True,
'eliminable_variable_expression': r'_\w+',
'reduce_affine_expression': True}
casadi_model = transfer_model(TEST_DIR, 'Simplify', compiler_options)
ref_model = Model()
p3 = ca.MX.sym('p3')
x = ca.MX.sym('x')
der_x = ca.MX.sym('der(x)')
y = ca.MX.sym('y')
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].min = 1
ref_model.states[0].max = 2
ref_model.states[0].nominal = 10
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [y]))
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.constants = list(map(Variable, []))
constant_values = []
for _cst, v in zip(ref_model.constants, constant_values):
_cst.value = v
ref_model.parameters = list(map(Variable, [p3]))
parameter_values = [np.nan]
for par, v in zip(ref_model.parameters, parameter_values):
par.value = v
A = ca.MX(2, 3)
A[0, 0] = -1.0
A[0, 1] = 1.0
A[1, 0] = -1.1
A[1, 2] = 1.0
b = ca.MX(2, 1)
b[0] = -6 - 3 * p3
b[1] = -7
x = ca.vertcat(x, der_x, y)
ref_model.equations = [ca.mtimes(A, x) + b]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
def test_attributes(self):
with open(os.path.join(TEST_DIR, 'Attributes.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'Attributes')
print(casadi_model)
ref_model = Model()
nested_p1 = ca.MX.sym('nested.p1')
nested_p = ca.MX.sym('nested.p')
nested_s = ca.MX.sym('nested.s')
i = ca.MX.sym("int")
b = ca.MX.sym("bool")
r = ca.MX.sym("real")
der_r = ca.MX.sym("der(real)")
test_state = ca.MX.sym("test_state")
i1 = ca.MX.sym("i1")
i2 = ca.MX.sym("i2")
i3 = ca.MX.sym("i3")
i4 = ca.MX.sym("i4")
cst = ca.MX.sym("cst")
prm = ca.MX.sym("prm")
protected_variable = ca.MX.sym("protected_variable")
ref_model.states = list(map(Variable, [r]))
ref_model.states[0].start = 20
ref_model.der_states = list(map(Variable, [der_r]))
ref_model.alg_states = list(
map(Variable,
[nested_s, i, b, i4, test_state, protected_variable]))
ref_model.alg_states[1].min = -5
ref_model.alg_states[1].max = 10
ref_model.inputs = list(map(Variable, [i1, i2, i3]))
ref_model.inputs[0].fixed = True
ref_model.outputs = list(map(Variable, [i4, protected_variable]))
ref_model.constants = list(map(Variable, [cst]))
constant_values = [1]
for c, v in zip(ref_model.constants, constant_values):
c.value = v
ref_model.parameters = list(map(Variable, [nested_p1, nested_p, prm]))
parameter_values = [1, 2 * nested_p1, 2]
for c, v in zip(ref_model.parameters, parameter_values):
c.value = v
ref_model.equations = [
i4 - ((i1 + i2) + i3),
der_r - (i1 + ca.if_else(b, 1, 0, True) * i),
protected_variable - (i1 + i2), nested_s - 3 * nested_p,
test_state - r
]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_simplify_eliminate_constant_assignments(self):
# Create model, cache it, and load the cache
compiler_options = \
{'eliminate_constant_assignments': True}
casadi_model = transfer_model(TEST_DIR, 'Simplify', compiler_options)
ref_model = Model()
c = ca.MX.sym('c')
p1 = ca.MX.sym('p1')
p2 = ca.MX.sym('p2')
p3 = ca.MX.sym('p3')
p4 = ca.MX.sym('p4')
x = ca.MX.sym('x')
der_x = ca.MX.sym('der(x)')
alias = ca.MX.sym('alias')
y = ca.MX.sym('y')
_tmp = ca.MX.sym('_tmp')
cst = ca.MX.sym('cst')
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].min = 0
ref_model.states[0].max = 3
ref_model.states[0].nominal = 10
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [alias, y, _tmp]))
ref_model.alg_states[0].min = 1
ref_model.alg_states[0].max = 2
ref_model.alg_states[0].nominal = 1
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.constants = list(map(Variable, [c, cst]))
constant_values = [3, 4]
for _cst, v in zip(ref_model.constants, constant_values):
_cst.value = v
ref_model.parameters = list(map(Variable, [p1, p2, p3, p4]))
parameter_values = [2.0, 2 * p1, np.nan, 2 * p3]
for par, v in zip(ref_model.parameters, parameter_values):
par.value = v
ref_model.equations = [
der_x - x - p1 - p2 - p3 - p4, alias - x, y - x - c - _tmp - cst,
_tmp - 0.1 * x
]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
def test_simplify_replace_parameter_values_and_expressions(self):
# Create model, cache it, and load the cache
compiler_options = \
{'replace_parameter_values': True,
'replace_parameter_expressions': True}
casadi_model = transfer_model(TEST_DIR, 'Simplify', compiler_options)
ref_model = Model()
c = ca.MX.sym('c')
p3 = ca.MX.sym('p3')
x = ca.MX.sym('x')
der_x = ca.MX.sym('der(x)')
alias = ca.MX.sym('alias')
y = ca.MX.sym('y')
_tmp = ca.MX.sym('_tmp')
cst = ca.MX.sym('cst')
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].min = 0
ref_model.states[0].max = 3
ref_model.states[0].nominal = 10
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [alias, y, _tmp, cst]))
ref_model.alg_states[0].min = 1
ref_model.alg_states[0].max = 2
ref_model.alg_states[0].nominal = 1
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.constants = list(map(Variable, [c]))
constant_values = [3]
for _cst, v in zip(ref_model.constants, constant_values):
_cst.value = v
ref_model.parameters = list(map(Variable, [p3]))
parameter_values = [np.nan]
for par, v in zip(ref_model.parameters, parameter_values):
par.value = v
ref_model.equations = [
der_x - x - 6 - 3 * p3, alias - x, y - x - c - _tmp - cst,
_tmp - 0.1 * x, cst - 4
]
print(casadi_model)
print(ref_model)
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
def test_duplicate(self):
with open(os.path.join(TEST_DIR, 'DuplicateState.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'DuplicateState')
print(casadi_model)
ref_model = Model()
x = ca.MX.sym("x")
der_x = ca.MX.sym("der(x)")
y = ca.MX.sym("y")
der_y = ca.MX.sym("der(y)")
ref_model.states = list(map(Variable, [x, y]))
ref_model.der_states = list(map(Variable, [der_x, der_y]))
ref_model.equations = [der_x + der_y - 1, der_x - 2]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_nested_classes(self):
with open(os.path.join(TEST_DIR, 'NestedClasses.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'C2')
ref_model = Model()
print(casadi_model)
v1 = ca.MX.sym('v1')
v2 = ca.MX.sym('v2')
ref_model.states = []
ref_model.der_states = []
ref_model.alg_states = list(map(Variable, [v1, v2]))
ref_model.equations = []
ref_model.alg_states[0].nominal = 1000.0
ref_model.alg_states[1].nominal = 1000.0
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_estimator(self):
with open(os.path.join(TEST_DIR, 'Estimator.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'Estimator')
ref_model = Model()
print(casadi_model)
x = ca.MX.sym("x")
der_x = ca.MX.sym("der(x)")
y = ca.MX.sym("y")
ref_model.states = list(map(Variable, [x]))
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [y]))
ref_model.outputs = list(map(Variable, [y]))
ref_model.equations = [der_x + x, y - x]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_state_annotator(self):
with open(os.path.join(TEST_DIR, 'StateAnnotator.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'StateAnnotator')
print(casadi_model)
ref_model = Model()
x = ca.MX.sym('x')
y = ca.MX.sym('y')
z = ca.MX.sym('z')
der_x = ca.MX.sym('der(x)')
der_y = ca.MX.sym('der(y)')
der_z = ca.MX.sym('der(z)')
ref_model.states = list(map(Variable, [x, y, z]))
ref_model.der_states = list(map(Variable, [der_x, der_y, der_z]))
ref_model.equations = [der_x + der_y - 1, der_x * y + x * der_y - 2, (der_x * y - x * der_y) / (y**2) - 3, 2 * x * der_x - 4, der_z - 5, der_x * z + x * der_z + der_y * z + y * der_z - 4, 0]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_simplify_reduce_affine_expression_loop(self):
# Create model, cache it, and load the cache
compiler_options = \
{'expand_vectors': True,
'detect_aliases': True,
'reduce_affine_expression': True,
'replace_constant_expressions': True,
'replace_constant_values': True,
'replace_parameter_expressions': True,
'replace_parameter_values': True}
casadi_model = transfer_model(TEST_DIR, 'SimplifyLoop',
compiler_options)
ref_model = Model()
x = ca.MX.sym('x')
y0 = ca.MX.sym('y[0]')
y1 = ca.MX.sym('y[1]')
A = ca.MX(2, 3)
A[0, 0] = -1
A[0, 1] = 1
A[0, 2] = 0
A[1, 0] = -2
A[1, 1] = 0
A[1, 2] = 1
b = ca.MX(2, 1)
b[0, 0] = 0
b[1, 0] = 0
ref_model.states = list(map(Variable, []))
ref_model.der_states = list(map(Variable, []))
ref_model.alg_states = list(map(Variable, [x, y0, y1]))
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
x = ca.vertcat(x, y0, y1)
ref_model.equations = [ca.mtimes(A, x) + b]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
def test_spring(self):
with open(os.path.join(TEST_DIR, 'Spring.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'Spring')
ref_model = Model()
print(casadi_model)
x = ca.MX.sym("x")
v_x = ca.MX.sym("v_x")
der_x = ca.MX.sym("der(x)")
der_v_x = ca.MX.sym("der(v_x)")
k = ca.MX.sym("k")
c = ca.MX.sym("c")
ref_model.states = list(map(Variable, [x, v_x]))
ref_model.der_states = list(map(Variable, [der_x, der_v_x]))
ref_model.parameters = list(map(Variable, [c, k]))
ref_model.parameters[0].value = 0.1
ref_model.parameters[1].value = 2
ref_model.equations = [der_x - v_x, der_v_x - (-k * x - c * v_x)]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_inheritance(self):
with open(os.path.join(TEST_DIR, 'Inheritance.mo'), 'r') as f:
txt = f.read()
ast_tree = parser.parse(txt)
casadi_model = gen_casadi.generate(ast_tree, 'Sub')
ref_model = Model()
x = ca.MX.sym("x")
der_x = ca.MX.sym("der(x)")
y = ca.MX.sym("y")
# noinspection PyUnusedLocal
der_y = ca.MX.sym("y")
k = ca.MX.sym("k")
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].max = 30.0
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [y]))
ref_model.parameters = list(map(Variable, [k]))
ref_model.parameters[0].value = -1.0
ref_model.equations = [der_x - k * x, x + y - 3]
self.assert_model_equivalent_numeric(ref_model, casadi_model)
def test_simplify_expand_vectors(self):
# Create model, cache it, and load the cache
compiler_options = \
{'expand_vectors': True}
casadi_model = transfer_model(TEST_DIR, 'SimplifyVector', compiler_options)
ref_model = Model()
x0 = ca.MX.sym('x[0]')
x1 = ca.MX.sym('x[1]')
der_x0 = ca.MX.sym('der(x)[0]')
der_x1 = ca.MX.sym('der(x)[1]')
ref_model.states = list(map(Variable, [x0, x1]))
ref_model.der_states = list(map(Variable, [der_x0, der_x1]))
ref_model.alg_states = list(map(Variable, []))
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.equations = [der_x0 - x0, der_x1 - x1]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)
def test_simplify_reduce_affine_expression(self):
# Create model, cache it, and load the cache
compiler_options = \
{'reduce_affine_expression': True}
casadi_model = transfer_model(TEST_DIR, 'Simplify', compiler_options)
ref_model = Model()
c = ca.MX.sym('c')
p1 = ca.MX.sym('p1')
p2 = ca.MX.sym('p2')
p3 = ca.MX.sym('p3')
p4 = ca.MX.sym('p4')
x = ca.MX.sym('x')
der_x = ca.MX.sym('der(x)')
alias = ca.MX.sym('alias')
y = ca.MX.sym('y')
_tmp = ca.MX.sym('_tmp')
cst = ca.MX.sym('cst')
ref_model.states = list(map(Variable, [x]))
ref_model.states[0].min = 0
ref_model.states[0].max = 3
ref_model.states[0].nominal = 10
ref_model.der_states = list(map(Variable, [der_x]))
ref_model.alg_states = list(map(Variable, [alias, y, _tmp, cst]))
ref_model.alg_states[0].min = 1
ref_model.alg_states[0].max = 2
ref_model.alg_states[0].nominal = 1
ref_model.inputs = list(map(Variable, []))
ref_model.outputs = list(map(Variable, []))
ref_model.constants = list(map(Variable, [c]))
constant_values = [3]
for _cst, v in zip(ref_model.constants, constant_values):
_cst.value = v
ref_model.parameters = list(map(Variable, [p1, p2, p3, p4]))
parameter_values = [2.0, 2 * p1, np.nan, 2 * p3]
for par, v in zip(ref_model.parameters, parameter_values):
par.value = v
A = ca.MX(5, 6)
A[0, 0] = -1.0
A[0, 1] = 1.0
A[1, 2] = 1.0
A[1, 0] = -1.0
A[2, 0] = -1.0
A[2, 3] = 1.0
A[2, 4] = -1.0
A[2, 5] = -1.0
A[3, 0] = -0.1
A[3, 4] = 1.0
A[4, 5] = 1.0
b = ca.MX(5, 1)
b[0] = -p1 - p2 - p3 - p4
b[2] = -c
b[4] = -4
x = ca.vertcat(x, der_x, alias, y, _tmp, cst)
ref_model.equations = [ca.mtimes(A, x) + b]
# Compare
self.assert_model_equivalent_numeric(casadi_model, ref_model)