def test_to_numpy(self):
for col in self.test_table.columns:
with self.subTest(f"test single column to numpy- {col.name}"):
np_array = to_numpy(self.test_table, [col.name])
self.assertEqual((2, 1), np_array.shape)
np.array_equal(np_array, self.np_array_dict[col.name])
try:
to_numpy(self.test_table,
[col.name for col in self.test_table.columns])
except DHError as e:
self.assertIn("same data type", e.root_cause)
with self.subTest("test multi-columns to numpy"):
input_cols = [
float_col(name="Float", data=[1.01, -1.01]),
float_col(name="Float1", data=[11.011, -11.011]),
float_col(name="Float2", data=[111.0111, -111.0111]),
float_col(name="Float3", data=[1111.01111, -1111.01111]),
float_col(name="Float4", data=[11111.011111, -11111.011111])
]
tmp_table = new_table(cols=input_cols)
np_array = to_numpy(tmp_table,
[col.name for col in tmp_table.columns])
self.assertEqual((2, 5), np_array.shape)
def test_to_table(self):
for col in self.test_table.columns:
with self.subTest(f"test single column to numpy- {col.name}"):
np_array = to_numpy(self.test_table, [col.name])
test_table = to_table(np_array, [col.name])
self.assertEqual(test_table.size, self.test_table.size)
with self.subTest("test multi-columns to numpy"):
input_cols = [
float_col(name="Float", data=[1.01, -1.01]),
float_col(name="Float1", data=[11.011, -11.011]),
float_col(name="Float2", data=[111.0111, -111.0111]),
float_col(name="Float3", data=[1111.01111, -1111.01111]),
float_col(name="Float4", data=[11111.011111, -11111.011111])
]
tmp_table = new_table(cols=input_cols)
np_array = to_numpy(tmp_table,
[col.name for col in tmp_table.columns])
tmp_table2 = to_table(np_array,
[col.name for col in tmp_table.columns])
self.assert_table_equals(tmp_table2, tmp_table)
with self.assertRaises(DHError) as cm:
tmp_table3 = to_table(np_array[:, [0, 1, 3]],
[col.name for col in tmp_table.columns])
self.assertIn("doesn't match", cm.exception.root_cause)
def setUp(self):
j_array_list1 = j_array_list([1, -1])
j_array_list2 = j_array_list([2, -2])
input_cols = [
bool_col(name="Boolean", data=[True, False]),
byte_col(name="Byte", data=(1, -1)),
char_col(name="Char", data='-1'),
short_col(name="Short", data=[1, -1]),
int_col(name="Int_", data=[1, -1]),
long_col(name="Long_", data=[1, NULL_LONG]),
long_col(name="NPLong", data=np.array([1, -1], dtype=np.int8)),
float_col(name="Float_", data=[1.01, -1.01]),
double_col(name="Double_", data=[1.01, -1.01]),
string_col(name="String", data=["foo", "bar"]),
datetime_col(name="Datetime",
data=[dtypes.DateTime(1),
dtypes.DateTime(-1)]),
pyobj_col(name="PyObj",
data=[CustomClass(1, "1"),
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj1", data=[[1, 2, 3],
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj2", data=[False, 'False']),
jobj_col(name="JObj", data=[j_array_list1, j_array_list2]),
]
self.test_table = new_table(cols=input_cols)
def setUp(self):
j_array_list1 = j_array_list([1, -1])
j_array_list2 = j_array_list([2, -2])
input_cols = [
bool_col(name="Boolean", data=[True, False]),
byte_col(name="Byte", data=(1, -1)),
char_col(name="Char", data='-1'),
short_col(name="Short", data=[1, -1]),
int_col(name="Int", data=[1, -1]),
long_col(name="Long", data=[1, NULL_LONG]),
long_col(name="NPLong", data=np.array([1, -1], dtype=np.int8)),
float_col(name="Float", data=[1.01, -1.01]),
double_col(name="Double", data=[1.01, -1.01]),
string_col(name="String", data=["foo", "bar"]),
datetime_col(name="Datetime",
data=[dtypes.DateTime(1),
dtypes.DateTime(-1)]),
pyobj_col(name="PyObj",
data=[CustomClass(1, "1"),
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj1", data=[[1, 2, 3],
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj2", data=[False, 'False']),
jobj_col(name="JObj", data=[j_array_list1, j_array_list2]),
]
self.test_table = new_table(cols=input_cols)
self.np_array_dict = {
'Boolean':
np.array([True, False]),
'Byte':
np.array([1, -1], dtype=np.int8),
'Char':
np.array('-1', dtype=np.int16),
'Short':
np.array([1, -1], dtype=np.int16),
'Int':
np.array([1, -1], dtype=np.int32),
'Long':
np.array([1, NULL_LONG], dtype=np.int64),
"NPLong":
np.array([1, -1], dtype=np.int8),
"Float":
np.array([1.01, -1.01], dtype=np.float32),
"Double":
np.array([1.01, -1.01]),
"String":
np.array(["foo", "bar"], dtype=np.string_),
"Datetime":
np.array([1, -1], dtype=np.dtype("datetime64[ns]")),
"PyObj":
np.array([CustomClass(1, "1"),
CustomClass(-1, "-1")]),
"PyObj1":
np.array([[1, 2, 3], CustomClass(-1, "-1")], dtype=np.object_),
"PyObj2":
np.array([False, 'False'], dtype=np.object_),
"JObj":
np.array([j_array_list1, j_array_list2]),
}
def test_new_table(self):
jobj1 = JArrayList()
jobj1.add(1)
jobj1.add(-1)
jobj2 = JArrayList()
jobj2.add(2)
jobj2.add(-2)
cols = [
bool_col(name="Boolean", data=[True, False]),
byte_col(name="Byte", data=(1, -1)),
char_col(name="Char", data='-1'),
short_col(name="Short", data=[1, -1]),
int_col(name="Int", data=[1, -1]),
long_col(name="Long", data=[1, -1]),
long_col(name="NPLong", data=np.array([1, -1], dtype=np.int8)),
float_col(name="Float", data=[1.01, -1.01]),
double_col(name="Double", data=[1.01, -1.01]),
string_col(name="String", data=["foo", "bar"]),
datetime_col(name="Datetime",
data=[dtypes.DateTime(1),
dtypes.DateTime(-1)]),
pyobj_col(name="PyObj",
data=[CustomClass(1, "1"),
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj1", data=[[1, 2, 3],
CustomClass(-1, "-1")]),
pyobj_col(name="PyObj2", data=[False, 'False']),
jobj_col(name="JObj", data=[jobj1, jobj2]),
]
t = new_table(cols=cols)
self.assertEqual(t.size, 2)
def test_to_table(self):
input_cols = [
bool_col(name="Boolean", data=[True, False]),
byte_col(name="Byte", data=(1, -1)),
char_col(name="Char", data='-1'),
short_col(name="Short", data=[1, -1]),
int_col(name="Int", data=[1, -1]),
long_col(name="Long", data=[1, NULL_LONG]),
long_col(name="NPLong", data=np.array([1, -1], dtype=np.int8)),
float_col(name="Float", data=[1.01, -1.01]),
double_col(name="Double", data=[1.01, -1.01]),
]
test_table = new_table(cols=input_cols)
df = to_pandas(test_table)
table_from_df = to_table(df)
self.assert_table_equals(table_from_df, test_table)
def test_round_trip_with_nulls(self):
# Note that no two-way conversion for those types
# j_array_list = dtypes.ArrayList([1, -1])
# bool_col(name="Boolean", data=[True, None])]
# string_col(name="String", data=["foo", None]),
# jobj_col(name="JObj", data=[j_array_list, None]),
input_cols = [
byte_col(name="Byte", data=(1, NULL_BYTE)),
char_col(name="Char", data='-1'),
short_col(name="Short", data=[1, NULL_SHORT]),
int_col(name="Int_", data=[1, NULL_INT]),
long_col(name="Long_", data=[1, NULL_LONG]),
float_col(name="Float_", data=[1.01, np.nan]),
double_col(name="Double_", data=[1.01, np.nan]),
datetime_col(name="Datetime", data=[dtypes.DateTime(1), None]),
pyobj_col(name="PyObj", data=[CustomClass(1, "1"), None]),
]
test_table = new_table(cols=input_cols)
df = to_pandas(test_table)
self.assertEqual(len(df.columns), len(test_table.columns))
self.assertEqual(df.size, 2 * len(test_table.columns))
test_table2 = to_table(df)
self.assert_table_equals(test_table2, test_table)
def test_column_error(self):
jobj = j_array_list([1, -1])
with self.assertRaises(DHError) as cm:
bool_input_col = bool_col(name="Boolean", data=[True, 'abc'])
self.assertNotIn("bool_input_col", dir())
with self.assertRaises(DHError) as cm:
_ = byte_col(name="Byte", data=[1, 'abc'])
with self.assertRaises(DHError) as cm:
_ = char_col(name="Char", data=[jobj])
with self.assertRaises(DHError) as cm:
_ = short_col(name="Short", data=[1, 'abc'])
with self.assertRaises(DHError) as cm:
_ = int_col(name="Int", data=[1, [1, 2]])
with self.assertRaises(DHError) as cm:
_ = long_col(name="Long", data=[1, float('inf')])
with self.assertRaises(DHError) as cm:
_ = float_col(name="Float", data=[1.01, 'NaN'])
with self.assertRaises(DHError) as cm:
_ = double_col(name="Double", data=[1.01, jobj])
with self.assertRaises(DHError) as cm:
_ = string_col(name="String", data=[1, -1.01])
with self.assertRaises(DHError) as cm:
_ = datetime_col(name="Datetime",
data=[dtypes.DateTime(round(time.time())), False])
with self.assertRaises(DHError) as cm:
_ = jobj_col(name="JObj", data=[jobj, CustomClass(-1, "-1")])
