def test1():
"""This test ensures that the columns of the output data frame correspond to the
function output values.
"""
for _ in range(100):
constr = {"EDUC_MAX": 10, "AGENTS": 1, "PERIODS": 1}
random_init(constr)
model_params = read_init_file("test.soepy.yml")
df = simulate("test.soepy.yml")
educ_level = np.array([1.0, 0.0, 0.0])
exp_p, exp_f = 0.0, 0.0
wage_systematic = calculate_wage_systematic(
model_params, educ_level, exp_p, exp_f
)
np.testing.assert_array_equal(wage_systematic, df["Systematic Wage"])
draw_sim = draw_disturbances(
model_params.seed_sim, model_params.shocks_cov, 1, 1
)
period_wages = calculate_period_wages(
model_params, wage_systematic, draw_sim[0, 0, :]
)
np.testing.assert_array_equal(
period_wages,
np.squeeze(
df[["Period Wage N", "Period Wage P", "Period Wage F"]].values.T
),
)
consumption_utilities = calculate_consumption_utilities(
model_params, period_wages
)
np.testing.assert_array_equal(
consumption_utilities,
np.squeeze(
df[
[
"Consumption Utility N",
"Consumption Utility P",
"Consumption Utility F",
]
].values.T
),
)
total_utilities = calculate_total_utilities(model_params, consumption_utilities)
np.testing.assert_array_equal(
total_utilities,
np.squeeze(
df[["Flow Utility N", "Flow Utility P", "Flow Utility F"]].values
),
)
def test4():
"""This test ensures that the shape of the simulated data frame corresponds to the
to the random specifications of our initialization file.
"""
for _ in range(5):
constr = dict()
constr["AGENTS"] = np.random.randint(10, 100)
constr["PERIODS"] = np.random.randint(1, 6)
constr["EDUC_MAX"] = np.random.randint(10, min(10 + constr["PERIODS"], 12))
random_init(constr)
df = simulate("test.soepy.yml")
np.testing.assert_array_equal(df.shape[0], constr["AGENTS"] * constr["PERIODS"])
def check_vault(num_test):
"""This function runs another simulation for each init file in our regression vault.
"""
vault = TEST_RESOURCES_DIR / "regression_vault.soepy.pkl"
with open(vault, "rb") as file:
tests = pickle.load(file)
for test in tests[:num_test]:
init_dict, expected_df = test
calculated_df = simulate(init_dict)
for col in expected_df.columns.tolist():
expected_df[col].equals(calculated_df[col])
cleanup("regression")
def check_vault():
"""This function runs another simulation for each init file in our regression vault.
"""
file_dir = os.path.join(TEST_RESOURCES_DIR, "regression_vault.soepy.json")
tests = json.load(open(file_dir, "r"))
for test in tests:
stat, init_dict = test
print_dict(init_dict)
df = simulate("test.soepy.yml")
stat_new = np.sum(df.sum())
np.testing.assert_array_almost_equal(stat, stat_new)
cleanup("regression")
def create_vault(num_test=100, seed=123456):
"""This function creates our regression vault."""
np.random.seed(seed)
seeds = np.random.randint(0, 1000, size=num_test)
file_dir = os.path.join(TEST_RESOURCES_DIR, "regression_vault.soepy.json")
tests = []
for counter, seed in enumerate(seeds):
np.random.seed(seed)
init_dict = random_init()
df = simulate("test.soepy.yml")
stat = np.sum(df.sum())
tests += [(stat, init_dict)]
cleanup("regression")
json.dump(tests, open(file_dir, "w"))
def test1():
"""This test runs a random selection of five regression tests from
our regression test battery.
"""
fname = TEST_RESOURCES_DIR / "regression_vault.soepy.json"
tests = json.load(open(fname))
random_choice = np.random.choice(range(len(tests)), 5)
tests = [tests[i] for i in random_choice]
for test in tests:
stat, init_dict = test
print_dict(init_dict)
df = simulate("test.soepy.yml")
stat_new = np.sum(df.sum())
np.testing.assert_array_equal(stat_new, stat)
def create_vault(num_test=1000, seed=123456):
"""This function creates our regression vault."""
np.random.seed(seed)
seeds = np.random.randint(0, 1000, size=num_test)
vault = TEST_RESOURCES_DIR / "regression_vault.soepy.pkl"
tests = []
for counter, seed in enumerate(seeds):
np.random.seed(seed)
init_dict = random_init()
df = simulate("test.soepy.yml")
tests += [(init_dict, df)]
cleanup("regression")
with open(vault, "wb") as file:
pickle.dump(tests, file)
def test1(idx):
"""This test runs a random selection of five regression tests from
our regression test battery.
"""
vault = TEST_RESOURCES_DIR / "regression_vault.soepy.pkl"
with open(vault, "rb") as file:
tests = pickle.load(file)
test = tests[idx]
init_dict, expected_df = test
calculated_df = simulate(init_dict)
for col in expected_df.columns.tolist():
print(col)
np.testing.assert_array_almost_equal(
expected_df[col][expected_df[col].notna()],
calculated_df[col][calculated_df[col].notna()],
)
def test2():
"""This test ensures that the data frame contain only nan values if individuals are
still a in education.
"""
constr = {"AGENTS": 200}
random_init(constr)
df = simulate("test.soepy.yml")
for year in [11, 12]:
df2 = df[(df["Years of Education"] == year) & (df["Period"] < year - 10)]
df2 = df2[
[
col
for col in df2.columns.values
if col not in ["Identifier", "Period", "Years of Education"]
]
]
a = np.empty(df2.shape)
a[:] = np.nan
np.testing.assert_array_equal(df2.values, a)
from soepy.python.simulate.simulate_python import simulate
from soepy.test.auxiliary import cleanup
# Generate simulated dataset
data_frame = simulate("toy_model_init_file_1000.yml")
# Save data frame to csv file
data_frame.to_pickle("test.soepy.pkl")
cleanup()
def func(maxrt):
stop = datetime.datetime.now() + maxrt
while datetime.datetime.now() < stop:
random_init()
simulate("test.soepy.yml")
def test_1():
"""This test makes sure the full package works for random initialization files."""
random_init()
simulate("test.soepy.yml")
