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# This tests a specific case of optimisation from the old encoder, WriteBufferingIterator.
#
# This pre-initialised the rows buffer with missing values. As such, for the first row of
# data, if these contained missing values, it did not differ from the previous row.
#
# If the first values in the row to be encoded (i.e. the slowest varying column) contained
# a missing value, then according to this metric, it did not need to be encoded, and the
# starting row marker would be non-zero.
#
# We need to ensure that these get correctly decoded!
# See ODB-533
import os
import numpy
import pandas
import pytest
from conftest import odc_modules
@pytest.mark.parametrize("odyssey", odc_modules)
def test_initial_missing1(odyssey):
check_data = {
"stringval": ["", "testing"],
"intval": [None, 12345678],
"realval": [None, 1234.56],
"doubleval": [None, 9876.54],
}
check_df = pandas.DataFrame(check_data)
data_file = os.path.join(os.path.dirname(__file__), "data/odb_533_1.odb")
df = odyssey.read_odb(data_file, single=True)
assert set(check_df.columns) == set(df.columns)
for col in df.columns:
numpy.testing.assert_array_equal(df[col], check_df[col])
@pytest.mark.parametrize("odyssey", odc_modules)
def test_initial_missing2(odyssey):
check_data = {
"stringval": ["", "testing"],
"intval": [None, 12345678],
"realval": [None, 1234.56],
"doubleval": [None, 9876.54],
"changing": [1234, 5678],
}
check_df = pandas.DataFrame(check_data)
data_file = os.path.join(os.path.dirname(__file__), "data/odb_533_2.odb")
df = odyssey.read_odb(data_file, single=True)
assert set(check_df.columns) == set(df.columns)
for col in df.columns:
numpy.testing.assert_array_equal(df[col], check_df[col])
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