def test_crs_compat():
from patsy.test_state import check_stateful
from patsy.test_splines_crs_data import (R_crs_test_x,
R_crs_test_data,
R_crs_num_tests)
lines = R_crs_test_data.split("\n")
tests_ran = 0
start_idx = lines.index("--BEGIN TEST CASE--")
while True:
if not lines[start_idx] == "--BEGIN TEST CASE--":
break
start_idx += 1
stop_idx = lines.index("--END TEST CASE--", start_idx)
block = lines[start_idx:stop_idx]
test_data = {}
for line in block:
key, value = line.split("=", 1)
test_data[key] = value
# Translate the R output into Python calling conventions
adjust_df = 0
if test_data["spline_type"] == "cr" or test_data["spline_type"] == "cs":
spline_type = CR
elif test_data["spline_type"] == "cc":
spline_type = CC
adjust_df += 1
else:
raise ValueError("Unrecognized spline type %r"
% (test_data["spline_type"],))
kwargs = {}
if test_data["absorb_cons"] == "TRUE":
kwargs["constraints"] = "center"
adjust_df += 1
if test_data["knots"] != "None":
all_knots = np.asarray(eval(test_data["knots"]))
all_knots.sort()
kwargs["knots"] = all_knots[1:-1]
kwargs["lower_bound"] = all_knots[0]
kwargs["upper_bound"] = all_knots[-1]
else:
kwargs["df"] = eval(test_data["nb_knots"]) - adjust_df
output = np.asarray(eval(test_data["output"]))
# Do the actual test
check_stateful(spline_type, False, R_crs_test_x, output, **kwargs)
tests_ran += 1
# Set up for the next one
start_idx = stop_idx + 1
assert tests_ran == R_crs_num_tests
def test_crs_compat():
from patsy.test_state import check_stateful
from patsy.test_splines_crs_data import (R_crs_test_x,
R_crs_test_data,
R_crs_num_tests)
lines = R_crs_test_data.split("\n")
tests_ran = 0
start_idx = lines.index("--BEGIN TEST CASE--")
while True:
if not lines[start_idx] == "--BEGIN TEST CASE--":
break
start_idx += 1
stop_idx = lines.index("--END TEST CASE--", start_idx)
block = lines[start_idx:stop_idx]
test_data = {}
for line in block:
key, value = line.split("=", 1)
test_data[key] = value
# Translate the R output into Python calling conventions
adjust_df = 0
if test_data["spline_type"] == "cr" or test_data["spline_type"] == "cs":
spline_type = CR
elif test_data["spline_type"] == "cc":
spline_type = CC
adjust_df += 1
else:
raise ValueError("Unrecognized spline type %r"
% (test_data["spline_type"],))
kwargs = {}
if test_data["absorb_cons"] == "TRUE":
kwargs["constraints"] = "center"
adjust_df += 1
if test_data["knots"] != "None":
all_knots = np.asarray(eval(test_data["knots"]))
all_knots.sort()
kwargs["knots"] = all_knots[1:-1]
kwargs["lower_bound"] = all_knots[0]
kwargs["upper_bound"] = all_knots[-1]
else:
kwargs["df"] = eval(test_data["nb_knots"]) - adjust_df
output = np.asarray(eval(test_data["output"]))
# Do the actual test
check_stateful(spline_type, False, R_crs_test_x, output, **kwargs)
tests_ran += 1
# Set up for the next one
start_idx = stop_idx + 1
assert tests_ran == R_crs_num_tests
def test_bs_compat():
from patsy.test_state import check_stateful
from patsy.test_splines_bs_data import (R_bs_test_x,
R_bs_test_data,
R_bs_num_tests)
lines = R_bs_test_data.split("\n")
tests_ran = 0
start_idx = lines.index("--BEGIN TEST CASE--")
while True:
if not lines[start_idx] == "--BEGIN TEST CASE--":
break
start_idx += 1
stop_idx = lines.index("--END TEST CASE--", start_idx)
block = lines[start_idx:stop_idx]
test_data = {}
for line in block:
key, value = line.split("=", 1)
test_data[key] = value
# Translate the R output into Python calling conventions
kwargs = {
"degree": int(test_data["degree"]),
# integer, or None
"df": eval(test_data["df"]),
# np.array() call, or None
"knots": eval(test_data["knots"]),
}
if test_data["Boundary.knots"] != "None":
lower, upper = eval(test_data["Boundary.knots"])
kwargs["lower_bound"] = lower
kwargs["upper_bound"] = upper
kwargs["include_intercept"] = (test_data["intercept"] == "TRUE")
# Special case: in R, setting intercept=TRUE increases the effective
# dof by 1. Adjust our arguments to match.
# if kwargs["df"] is not None and kwargs["include_intercept"]:
# kwargs["df"] += 1
output = np.asarray(eval(test_data["output"]))
if kwargs["df"] is not None:
assert output.shape[1] == kwargs["df"]
# Do the actual test
check_stateful(BS, False, R_bs_test_x, output, **kwargs)
tests_ran += 1
# Set up for the next one
start_idx = stop_idx + 1
assert tests_ran == R_bs_num_tests
def test_bs_compat():
from patsy.test_state import check_stateful
from patsy.test_splines_bs_data import (R_bs_test_x,
R_bs_test_data,
R_bs_num_tests)
lines = R_bs_test_data.split("\n")
tests_ran = 0
start_idx = lines.index("--BEGIN TEST CASE--")
while True:
if not lines[start_idx] == "--BEGIN TEST CASE--":
break
start_idx += 1
stop_idx = lines.index("--END TEST CASE--", start_idx)
block = lines[start_idx:stop_idx]
test_data = {}
for line in block:
key, value = line.split("=", 1)
test_data[key] = value
# Translate the R output into Python calling conventions
kwargs = {
"degree": int(test_data["degree"]),
# integer, or None
"df": eval(test_data["df"]),
# np.array() call, or None
"knots": eval(test_data["knots"]),
}
if test_data["Boundary.knots"] != "None":
lower, upper = eval(test_data["Boundary.knots"])
kwargs["lower_bound"] = lower
kwargs["upper_bound"] = upper
kwargs["include_intercept"] = (test_data["intercept"] == "TRUE")
# Special case: in R, setting intercept=TRUE increases the effective
# dof by 1. Adjust our arguments to match.
# if kwargs["df"] is not None and kwargs["include_intercept"]:
# kwargs["df"] += 1
output = np.asarray(eval(test_data["output"]))
if kwargs["df"] is not None:
assert output.shape[1] == kwargs["df"]
# Do the actual test
check_stateful(BS, False, R_bs_test_x, output, **kwargs)
tests_ran += 1
# Set up for the next one
start_idx = stop_idx + 1
assert tests_ran == R_bs_num_tests