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#!/usr/bin/env python3
#
# Copyright 2018, The Android Open Source Project
#
# Licensed 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 "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""Unit tests for the data_frame.py script."""
from data_frame import DataFrame
def test_data_frame():
# trivial empty data frame
df = DataFrame()
assert df.headers == []
assert df.data_table == []
assert df.data_table_transposed == []
# common case, same number of values in each place.
df = DataFrame({'TotalTime_ms': [1, 2, 3], 'Displayed_ms': [4, 5, 6]})
assert df.headers == ['TotalTime_ms', 'Displayed_ms']
assert df.data_table == [[1, 4], [2, 5], [3, 6]]
assert df.data_table_transposed == [(1, 2, 3), (4, 5, 6)]
# varying num values.
df = DataFrame({'many': [1, 2], 'none': []})
assert df.headers == ['many', 'none']
assert df.data_table == [[1, None], [2, None]]
assert df.data_table_transposed == [(1, 2), (None, None)]
df = DataFrame({'many': [], 'none': [1, 2]})
assert df.headers == ['many', 'none']
assert df.data_table == [[None, 1], [None, 2]]
assert df.data_table_transposed == [(None, None), (1, 2)]
# merge multiple data frames
df = DataFrame()
df.concat_rows(DataFrame())
assert df.headers == []
assert df.data_table == []
assert df.data_table_transposed == []
df = DataFrame()
df2 = DataFrame({'TotalTime_ms': [1, 2, 3], 'Displayed_ms': [4, 5, 6]})
df.concat_rows(df2)
assert df.headers == ['TotalTime_ms', 'Displayed_ms']
assert df.data_table == [[1, 4], [2, 5], [3, 6]]
assert df.data_table_transposed == [(1, 2, 3), (4, 5, 6)]
df = DataFrame({'TotalTime_ms': [1, 2]})
df2 = DataFrame({'Displayed_ms': [4, 5]})
df.concat_rows(df2)
assert df.headers == ['TotalTime_ms', 'Displayed_ms']
assert df.data_table == [[1, None], [2, None], [None, 4], [None, 5]]
df = DataFrame({'TotalTime_ms': [1, 2]})
df2 = DataFrame({'TotalTime_ms': [3, 4], 'Displayed_ms': [5, 6]})
df.concat_rows(df2)
assert df.headers == ['TotalTime_ms', 'Displayed_ms']
assert df.data_table == [[1, None], [2, None], [3, 5], [4, 6]]
# data_row_at
df = DataFrame({'TotalTime_ms': [1, 2, 3], 'Displayed_ms': [4, 5, 6]})
assert df.data_row_at(-1) == [3, 6]
assert df.data_row_at(2) == [3, 6]
assert df.data_row_at(1) == [2, 5]
# repeat
df = DataFrame({'TotalTime_ms': [1], 'Displayed_ms': [4]})
df2 = DataFrame({'TotalTime_ms': [1, 1, 1], 'Displayed_ms': [4, 4, 4]})
assert df.repeat(3) == df2
# repeat
df = DataFrame({'TotalTime_ms': [1, 1, 1], 'Displayed_ms': [4, 4, 4]})
assert df.data_row_len == 3
df = DataFrame({'TotalTime_ms': [1, 1]})
assert df.data_row_len == 2
# repeat
df = DataFrame({'TotalTime_ms': [1, 1, 1], 'Displayed_ms': [4, 4, 4]})
assert df.data_row_len == 3
df = DataFrame({'TotalTime_ms': [1, 1]})
assert df.data_row_len == 2
# data_row_reduce
df = DataFrame({'TotalTime_ms': [1, 1, 1], 'Displayed_ms': [4, 4, 4]})
df_sum = DataFrame({'TotalTime_ms': [3], 'Displayed_ms': [12]})
assert df.data_row_reduce(sum) == df_sum
# merge_data_columns
df = DataFrame({'TotalTime_ms': [1, 2, 3]})
df2 = DataFrame({'Displayed_ms': [3, 4, 5, 6]})
df.merge_data_columns(df2)
assert df == DataFrame(
{'TotalTime_ms': [1, 2, 3], 'Displayed_ms': [3, 4, 5, 6]})
df = DataFrame({'TotalTime_ms': [1, 2, 3]})
df2 = DataFrame({'Displayed_ms': [3, 4]})
df.merge_data_columns(df2)
assert df == DataFrame(
{'TotalTime_ms': [1, 2, 3], 'Displayed_ms': [3, 4]})
df = DataFrame({'TotalTime_ms': [1, 2, 3]})
df2 = DataFrame({'TotalTime_ms': [10, 11]})
df.merge_data_columns(df2)
assert df == DataFrame({'TotalTime_ms': [10, 11, 3]})
df = DataFrame({'TotalTime_ms': []})
df2 = DataFrame({'TotalTime_ms': [10, 11]})
df.merge_data_columns(df2)
assert df == DataFrame({'TotalTime_ms': [10, 11]})
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