def _test_df_binary_operations(self,
pyfunc,
name,
total_data_length,
test_name=None,
input_data=test_global_input_data_float64):
np.random.seed(0)
hpat_func = sdc.jit(pyfunc)
for data_length in total_data_length:
# TODO: replace with generic function to generate random sequence of floats
data1 = np.random.ranf(data_length)
data2 = np.random.ranf(data_length)
A = pandas.DataFrame({f"f{i}": data1 for i in range(3)})
B = pandas.DataFrame({f"f{i}": data2 for i in range(3)})
compile_results = calc_compilation(pyfunc,
A,
B,
iter_number=self.iter_number)
# Warming up
hpat_func(A, B)
exec_times, boxing_times = get_times(hpat_func,
A,
B,
iter_number=self.iter_number)
self.test_results.add(name,
'JIT',
A.size,
exec_times,
boxing_times,
compile_results=compile_results,
num_threads=self.num_threads)
exec_times, _ = get_times(pyfunc,
A,
B,
iter_number=self.iter_number)
self.test_results.add(name,
'Reference',
A.size,
exec_times,
num_threads=self.num_threads)
def _test_jitted(self, pyfunc, record, *args, **kwargs):
# compilation time
record["compile_results"] = calc_compilation(pyfunc, *args, **kwargs)
cfunc = numba.njit(pyfunc)
# Warming up
cfunc(*args, **kwargs)
# execution and boxing time
record["test_results"], record["boxing_results"] = \
get_times(cfunc, *args, **kwargs)
def _test_python(self, pyfunc, record, *args, **kwargs):
record["test_results"], _ = \
get_times(pyfunc, *args, **kwargs)