def test_print_overloading_estimator():
"""Check that printing a fitted estimator results in 'pretty' output"""
random_state = check_random_state(415)
X = np.reshape(random_state.uniform(size=50), (5, 10))
y = random_state.uniform(size=5)
# Check the regressor
est = SymbolicRegressor(generations=2, random_state=0)
# Unfitted
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_unfitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
# Fitted
est.fit(X, y)
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_fitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est._program)
output_program = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
assert_true(output_unfitted != output_fitted)
assert_true(output_unfitted == est.__repr__())
assert_true(output_fitted == output_program)
# Check the transformer
est = SymbolicTransformer(generations=2, random_state=0)
# Unfitted
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_unfitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
# Fitted
est.fit(X, y)
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_fitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
output = str([gp.__str__() for gp in est])
print(output.replace("',", ",\n").replace("'", ""))
output_program = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
assert_true(output_unfitted != output_fitted)
assert_true(output_unfitted == est.__repr__())
assert_true(output_fitted == output_program)
def test_print_overloading_estimator():
"""Check that printing a fitted estimator results in 'pretty' output"""
random_state = check_random_state(415)
X = np.reshape(random_state.uniform(size=50), (5, 10))
y = random_state.uniform(size=5)
# Check the regressor
est = SymbolicRegressor(generations=2, random_state=0)
# Unfitted
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_unfitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
# Fitted
est.fit(X, y)
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_fitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est._program)
output_program = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
assert_true(output_unfitted != output_fitted)
assert_true(output_unfitted == est.__repr__())
assert_true(output_fitted == output_program)
# Check the transformer
est = SymbolicTransformer(generations=2, random_state=0)
# Unfitted
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_unfitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
# Fitted
est.fit(X, y)
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
print(est)
output_fitted = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
orig_stdout = sys.stdout
try:
out = StringIO()
sys.stdout = out
output = str([gp.__str__() for gp in est])
print(output.replace("',", ",\n").replace("'", ""))
output_program = out.getvalue().strip()
finally:
sys.stdout = orig_stdout
assert_true(output_unfitted != output_fitted)
assert_true(output_unfitted == est.__repr__())
assert_true(output_fitted == output_program)
