def test_dot_function_e_Cat(self):
""" CONTINUOUS states and outcomes, but add a final (fourth) hidden state factor
Now, when arguments themselves are instances of Categorical """
array_path = os.path.join(os.getcwd(), "tests/data/dot_e.mat")
mat_contents = loadmat(file_name=array_path)
A = mat_contents["A"]
obs = Categorical(values=mat_contents["o"])
states = mat_contents["s"]
states_array_version = np.empty(states.shape[1], dtype=object)
for i in range(states.shape[1]):
states_array_version[i] = states[0][i][0]
states_array_version = Categorical(values=states_array_version)
result_1 = mat_contents["result1"]
result_2 = mat_contents["result2"]
result_3 = mat_contents["result3"]
A = Categorical(values=A)
result_1_py = A.dot(obs, return_numpy=True)
self.assertTrue(np.isclose(result_1, result_1_py).all())
result_2_py = A.dot(states_array_version, return_numpy=True)
result_2_py = result_2_py.astype("float64")[:, np.newaxis]
self.assertTrue(np.isclose(result_2, result_2_py).all())
result_3_py = A.dot(states_array_version,
dims_to_omit=[0],
return_numpy=True)
self.assertTrue(np.isclose(result_3, result_3_py).all())
def test_dot_function_c(self):
""" DISCRETE states and outcomes, but also a third hidden state factor """
array_path = os.path.join(os.getcwd(), "tests/data/dot_c.mat")
mat_contents = loadmat(file_name=array_path)
A = mat_contents["A"]
obs = mat_contents["o"]
states = mat_contents["s"]
states_array_version = np.empty(states.shape[1], dtype=object)
for i in range(states.shape[1]):
states_array_version[i] = states[0][i][0]
result_1 = mat_contents["result1"]
result_2 = mat_contents["result2"]
result_3 = mat_contents["result3"]
A = Categorical(values=A)
result_1_py = A.dot(obs, return_numpy=True)
self.assertTrue(np.isclose(result_1, result_1_py).all())
result_2_py = A.dot(states_array_version, return_numpy=True)
result_2_py = result_2_py.astype("float64")[:, np.newaxis]
self.assertTrue(np.isclose(result_2, result_2_py).all())
result_3_py = A.dot(states_array_version,
dims_to_omit=[0],
return_numpy=True)
self.assertTrue(np.isclose(result_3, result_3_py).all())
def test_dot_function_a_Cat(self):
""" test with vectors and matrices, discrete state / outcomes
Now, when arguments themselves are instances of Categorical
"""
array_path = os.path.join(os.getcwd(), "tests/data/dot_a.mat")
mat_contents = loadmat(file_name=array_path)
A = mat_contents["A"]
obs = Categorical(values=mat_contents["o"])
states = Categorical(values=mat_contents["s"][0])
result_1 = mat_contents["result1"]
result_2 = mat_contents["result2"]
result_3 = mat_contents["result3"]
A = Categorical(values=A)
result_1_py = A.dot(obs, return_numpy=True)
self.assertTrue(np.isclose(result_1, result_1_py).all())
result_2_py = A.dot(states, return_numpy=True)
result_2_py = result_2_py.astype("float64")[:, np.newaxis]
self.assertTrue(np.isclose(result_2, result_2_py).all())
result_3_py = A.dot(states, dims_to_omit=[0], return_numpy=True)
self.assertTrue(np.isclose(result_3, result_3_py).all())
def test_dot_function_b(self):
""" continuous states and outcomes """
array_path = os.path.join(os.getcwd(), "tests/data/dot_b.mat")
mat_contents = loadmat(file_name=array_path)
A = mat_contents["A"]
obs = mat_contents["o"]
states = mat_contents["s"]
states = np.array(states, dtype=object)
result_1 = mat_contents["result1"]
result_2 = mat_contents["result2"]
result_3 = mat_contents["result3"]
A = Categorical(values=A)
result_1_py = A.dot(obs, return_numpy=True)
self.assertTrue(np.isclose(result_1, result_1_py).all())
result_2_py = A.dot(states, return_numpy=True)
result_2_py = result_2_py.astype("float64")[:, np.newaxis]
self.assertTrue(np.isclose(result_2, result_2_py).all())
result_3_py = A.dot(states, dims_to_omit=[0], return_numpy=True)
self.assertTrue(np.isclose(result_3, result_3_py).all())
# %% Debugging for Categorical.dot()
array_path = os.path.join(os.getcwd(), "tests/data/dot_a.mat")
mat_contents = loadmat(file_name=array_path)
A = mat_contents["A"]
obs = mat_contents["o"]
states = mat_contents["s"]
states = np.array(states, dtype=object)
result_1 = mat_contents["result1"]
result_2 = mat_contents["result2"]
result_3 = mat_contents["result3"]
A = Categorical(values=A)
result_1_py = A.dot(obs, return_numpy=True)
print(np.isclose(result_1, result_1_py).all())
result_2_py = A.dot(states, return_numpy=True)
result_2_py = result_2_py.astype("float64")[:, np.newaxis]
print(np.isclose(result_2, result_2_py).all())
result_3_py = A.dot(states, dims_to_omit=[0], return_numpy=True)
print(np.isclose(result_3, result_3_py).all())
# now try by putting obs and states into Categoricals themselves
obs = Categorical(values=mat_contents["o"])
states = Categorical(values=mat_contents["s"][0])
result_1_py_cat = A.dot(obs, return_numpy=True)
print(np.isclose(result_1, result_1_py_cat).all())