def test_astype(self): def test_impl(N): return np.ones(N).astype(np.int32).sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_df_values_parallel1(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n), 'B': np.arange(n)}) return df.values.sum() hpat_func = sdc.jit(test_impl) n = 11 np.testing.assert_array_equal(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_quantile_parallel_int(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(0, n, 1, np.int32)}) return df.A.quantile(.25) hpat_func = sdc.jit(test_impl) n = 1001 np.testing.assert_almost_equal(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_agg_parallel_str(self): def test_impl(): df = pq.read_table("groupby3.pq").to_pandas() A = df.groupby('A')['B'].agg(lambda x: x.max() - x.min()) return A.sum() hpat_func = self.jit(test_impl) self.assertEqual(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pq_read_global_str1(self): def test_impl(): df = pd.read_parquet(kde_file) X = df['points'] return X.sum() hpat_func = self.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_np_io2(self): # parallel version def test_impl(): A = np.fromfile("np_file1.dat", np.float64) return A.sum() hpat_func = self.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pq_str_with_nan_par_multigroup(self): def test_impl(): df = pq.read_table('example2.parquet').to_pandas() A = df.five.values == 'foo' return A.sum() hpat_func = self.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pq_str(self): def test_impl(): df = pq.read_table('example.parquet').to_pandas() A = df.two.values == 'foo' return A.sum() hpat_func = sdc.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pd_read_parquet(self): def test_impl(): df = pd.read_parquet('kde.parquet') X = df['points'] return X.sum() hpat_func = sdc.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_whole_slice(self): def test_impl(N): X = np.ones((N, 4)) X[:, 3] = (X[:, 3]) / (np.max(X[:, 3]) - np.min(X[:, 3])) return X.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_agg_parallel_as_index(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) df2 = df.groupby('A', as_index=False).max() return df2.A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_agg_parallel_std(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n, np.int64), 'B': np.arange(n)}) A = df.groupby('A')['B'].std() return A.sum() hpat_func = self.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pq_read(self): def test_impl(): t = pq.read_table('kde.parquet') df = t.to_pandas() X = df['points'] return X.sum() hpat_func = self.jit(test_impl) np.testing.assert_almost_equal(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_shift2(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(n) + 1.0, 'B': np.random.ranf(n)}) Ac = df.A.pct_change(1) return Ac.sum() hpat_func = self.jit(test_impl) n = 11 np.testing.assert_almost_equal(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_rolling3(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)}) Ac = df.A.rolling(3, center=True).apply(lambda a: a[0] + 2 * a[1] + a[2]) return Ac.sum() hpat_func = self.jit(test_impl) n = 121 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_concat_series_str(self): def test_impl(): df1 = pq.read_table('example.parquet').to_pandas() df2 = pq.read_table('example.parquet').to_pandas() A3 = pd.concat([df1.two, df2.two]) return (A3 == 'foo').sum() hpat_func = sdc.jit(test_impl) self.assertEqual(hpat_func(), test_impl()) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_strided_getitem(self): def test_impl(N): A = np.ones(N) B = A[::7] return B.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_1D_Var_len(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(n), 'B': np.arange(n) + 1.0}) df1 = df[df.A > 5] return len(df1.B) hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_rolling2(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)}) df['moving average'] = df.A.rolling(window=5, center=True).mean() return df['moving average'].sum() hpat_func = sdc.jit(test_impl) n = 121 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_filter3(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(n) + n, 'B': np.arange(n)**2}) df1 = df.iloc[(df.A > .5).values] return np.sum(df1.B) hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_describe(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(0, n, 1, np.float64)}) return df.A.describe() hpat_func = sdc.jit(test_impl) n = 1001 hpat_func(n) # XXX: test actual output self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_setitem1(self): def test_impl(N): A = np.arange(10) + 1.0 A[0] = 30 return A.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_inplace_binop(self): def test_impl(N): A = np.ones(N) B = np.ones(N) B += A return B.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_quantile_parallel_float_nan(self): def test_impl(n): df = pd.DataFrame({'A': np.arange(0, n, 1, np.float32)}) df.A[0:100] = np.nan df.A[200:331] = np.nan return df.A.quantile(.25) hpat_func = sdc.jit(test_impl) n = 1001 np.testing.assert_almost_equal(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_getitem_multidim(self): def test_impl(N): A = np.ones((N, 3)) B = np.ones(N) > .5 C = A[B, 2] return C.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_column_getitem1(self): def test_impl(n): df = pd.DataFrame({'A': np.ones(n), 'B': np.random.ranf(n)}) Ac = df['A'].values return Ac.sum() hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) self.assertEqual(count_parfor_OneDs(), 1)
def test_transpose(self): def test_impl(n): A = np.ones((30, 40, 50)) B = A.transpose((0, 2, 1)) C = A.transpose(0, 2, 1) return B.sum() + C.sum() hpat_func = self.jit(test_impl) n = 128 np.testing.assert_allclose(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_pd_DataFrame_from_series_par(self): def test_impl(n): S1 = pd.Series(np.ones(n)) S2 = pd.Series(np.random.ranf(n)) df = pd.DataFrame({'A': S1, 'B': S2}) return df.A.sum() hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0) self.assertEqual(count_parfor_OneDs(), 1)
def test_shape1(self): def test_impl(n): df = pd.DataFrame({ 'A': np.ones(n, np.int64), 'B': np.random.ranf(n) }) return df.shape hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)
def test_shift1(self): def test_impl(n): df = pd.DataFrame({ 'A': np.arange(n) + 1.0, 'B': np.random.ranf(n) }) Ac = df.A.shift(1) return Ac.sum() hpat_func = sdc.jit(test_impl) n = 11 self.assertEqual(hpat_func(n), test_impl(n)) self.assertEqual(count_array_REPs(), 0) self.assertEqual(count_parfor_REPs(), 0)