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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
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# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
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#
import numpy as np
from iotdb.utils.IoTDBConstants import TSDataType
from iotdb.utils.NumpyTablet import NumpyTablet
from iotdb.utils.Tablet import Tablet
def test_numpy_tablet_serialization():
measurements_ = ["s_01", "s_02", "s_03", "s_04", "s_05", "s_06"]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
]
values_ = [
[False, 10, 11, 1.1, 10011.1, "test01"],
[True, 100, 11111, 1.25, 101.0, "test02"],
[False, 100, 1, 188.1, 688.25, "test03"],
[True, 0, 0, 0, 6.25, "test04"],
]
timestamps_ = [16, 17, 18, 19]
tablet_ = Tablet(
"root.sg_test_01.d_01", measurements_, data_types_, values_, timestamps_
)
np_values_ = [
np.array([False, True, False, True], np.dtype(">?")),
np.array([10, 100, 100, 0], np.dtype(">i4")),
np.array([11, 11111, 1, 0], np.dtype(">i8")),
np.array([1.1, 1.25, 188.1, 0], np.dtype(">f4")),
np.array([10011.1, 101.0, 688.25, 6.25], np.dtype(">f8")),
np.array(["test01", "test02", "test03", "test04"]),
]
np_timestamps_ = np.array([16, 17, 18, 19], np.dtype(">i8"))
np_tablet_ = NumpyTablet(
"root.sg_test_01.d_01", measurements_, data_types_, np_values_, np_timestamps_
)
assert tablet_.get_binary_timestamps() == np_tablet_.get_binary_timestamps()
assert tablet_.get_binary_values() == np_tablet_.get_binary_values()
def test_sort_numpy_tablet():
measurements_ = ["s_01", "s_02", "s_03", "s_04", "s_05", "s_06"]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
]
values_ = [
[True, 10000, 11111, 8.999, 776, "test05"],
[True, 1000, 1111, 0, 6.25, "test06"],
[False, 100, 111, 188.1, 688.25, "test07"],
[False, 10, 11, 1.25, 101.0, "test08"],
[False, 0, 1, 1.1, 10011.1, "test09"],
]
timestamps_ = [5, 6, 7, 8, 9]
tablet_ = Tablet(
"root.sg_test_01.d_01", measurements_, data_types_, values_, timestamps_
)
np_values_unsorted = [
np.array([False, False, False, True, True], np.dtype(">?")),
np.array([0, 10, 100, 1000, 10000], np.dtype(">i4")),
np.array([1, 11, 111, 1111, 11111], np.dtype(">i8")),
np.array([1.1, 1.25, 188.1, 0, 8.999], np.dtype(">f4")),
np.array([10011.1, 101.0, 688.25, 6.25, 776], np.dtype(">f8")),
np.array(["test09", "test08", "test07", "test06", "test05"]),
]
np_timestamps_unsorted = np.array([9, 8, 7, 6, 5], np.dtype(">i8"))
np_tablet_ = NumpyTablet(
"root.sg_test_01.d_01",
measurements_,
data_types_,
np_values_unsorted,
np_timestamps_unsorted,
)
assert tablet_.get_binary_timestamps() == np_tablet_.get_binary_timestamps()
assert tablet_.get_binary_values() == np_tablet_.get_binary_values()
def test_numpy_tablet_auto_correct_datatype():
measurements_ = ["s_01", "s_02", "s_03", "s_04", "s_05", "s_06"]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
]
values_ = [
[True, 10000, 11111, 8.999, 776, "test05"],
[True, 1000, 1111, 0, 6.25, "test06"],
[False, 100, 111, 188.1, 688.25, "test07"],
[False, 10, 11, 1.25, 101.0, "test08"],
[False, 0, 1, 1.1, 10011.1, "test09"],
]
timestamps_ = [5, 6, 7, 8, 9]
tablet_ = Tablet(
"root.sg_test_01.d_01", measurements_, data_types_, values_, timestamps_
)
np_values_unsorted = [
np.array([False, False, False, True, True]),
np.array([0, 10, 100, 1000, 10000]),
np.array([1, 11, 111, 1111, 11111]),
np.array([1.1, 1.25, 188.1, 0, 8.999]),
np.array([10011.1, 101.0, 688.25, 6.25, 776]),
np.array(["test09", "test08", "test07", "test06", "test05"]),
]
np_timestamps_unsorted = np.array([9, 8, 7, 6, 5])
# numpy.dtype of int and float should be little endian by default
assert np_timestamps_unsorted.dtype != np.dtype(">i8")
for i in range(1, 4):
assert np_values_unsorted[i].dtype != data_types_[i].np_dtype()
np_tablet_ = NumpyTablet(
"root.sg_test_01.d_01",
measurements_,
data_types_,
np_values_unsorted,
np_timestamps_unsorted,
)
assert tablet_.get_binary_timestamps() == np_tablet_.get_binary_timestamps()
assert tablet_.get_binary_values() == np_tablet_.get_binary_values()