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from tempfile import NamedTemporaryFile
import numpy.testing
import pandas
import pytest
from conftest import ODC_VERSION, codc, odc_modules
SAMPLE_DATA = {
"col1": [1, 2, 3, 4, 5, 6, 7],
"col2": [0, 0, 0, 0, 0, 0, 0],
"col3": [73] * 7,
"col4": [1.432] * 7,
"col5": [-17, -7, -7, None, 1, 4, 4],
"col6": ["aoeu", "aoeu", "aaaaaaaooooooo", "None", "boo", "squiggle", "a"],
"col7": ["abcd"] * 7,
"col8": [2.345] * 7,
"col9": [999.99, 888.88, 777.77, 666.66, 555.55, 444.44, 333.33],
"col10": [999.99, 888.88, 777.77, 666.66, 555.55, 444.44, 333.33],
"col11": [1, None, 3, 4, 5, None, 7],
"col12": [-512, None, 3, 7623, -22000, None, 7],
"col13": [-1234567, 8765432, None, 22, 22222222, -81222323, None],
"col14": [0b0000, 0b1001, 0b0110, 0b0101, 0b1010, 0b1111, 0b0000],
"col15": [0b0000, 0b1001, None, 0b0101, 0b1010, 0b1111, 0b0000],
"constant_bitfield": [0b1100] * 7,
}
SAMPLE_PROPERTIES = {
"property1": "this is a string ....",
"property2": ".......and another .......",
}
SAMPLE_BITFIELDS = {
"col14": ["bf1", ("bfextended", 2), ("bf3", 1)],
"col15": ["bf1", ("bfextended", 2), ("bf3", 1)],
"constant_bitfield": ["bf1", ("bfextended", 2), ("bf3", 1)],
}
def assert_dataframe_equal(df1, df2):
"""
Assert that two dataframes are equal, but ignoring column order
"""
pandas.testing.assert_frame_equal(
df1.sort_index(axis=1),
df2.sort_index(axis=1),
)
def encode_sample(odyssey, f):
df = pandas.DataFrame(SAMPLE_DATA)
types = {
"col8": odyssey.REAL,
"col10": odyssey.REAL,
"col14": odyssey.BITFIELD,
"col15": odyssey.BITFIELD,
"constant_bitfield": odyssey.BITFIELD,
# 'col21': odyssey.REAL
}
properties = SAMPLE_PROPERTIES
bitfields = SAMPLE_BITFIELDS
odyssey.encode_odb(df, f, types=types, rows_per_frame=4, properties=properties, bitfields=bitfields)
if not isinstance(f, str):
f.flush()
return df
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_filename(odyssey):
with NamedTemporaryFile() as fencode:
df = encode_sample(odyssey, fencode)
df2 = odyssey.read_odb(fencode.name, single=True)
assert isinstance(df2, pandas.DataFrame)
for col in df.keys():
s1 = df[col]
s2 = df2[col]
if col in ("col8", "col10"):
numpy.testing.assert_array_almost_equal(s1, s2, decimal=2)
else:
numpy.testing.assert_array_equal(s1, s2)
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_file_object(odyssey):
with NamedTemporaryFile() as fencode:
df = encode_sample(odyssey, fencode)
with open(fencode.name, "rb") as fread:
df2 = odyssey.read_odb(fread, single=True)
assert isinstance(df2, pandas.DataFrame)
for col in df.keys():
s1 = df[col]
s2 = df2[col]
if col in ("col8", "col10"):
numpy.testing.assert_array_almost_equal(s1, s2, decimal=2)
else:
numpy.testing.assert_array_equal(s1, s2)
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_simple_columns(odyssey):
with NamedTemporaryFile() as fencode:
df = encode_sample(odyssey, fencode)
cols = ("col6", "col7")
df2 = odyssey.read_odb(fencode.name, columns=cols, single=True)
assert isinstance(df2, pandas.DataFrame)
assert df2.shape[1] == len(cols)
for col in cols:
numpy.testing.assert_array_equal(df[col], df2[col])
@pytest.mark.parametrize("odyssey", odc_modules)
def test_aggregate_non_matching(odyssey):
"""
Where we aggregate tables with non-matching columns, ensure that the infilled
missing values are type appropriate
"""
sample1 = {"col1": [111, 222, 333]}
sample2 = {"col2": ["aaa", "bbb", "ccc"]}
with NamedTemporaryFile() as fencode:
odyssey.encode_odb(pandas.DataFrame(sample1), fencode)
odyssey.encode_odb(pandas.DataFrame(sample2), fencode)
fencode.flush()
df = odyssey.read_odb(fencode.name, single=True)
assert isinstance(df, pandas.DataFrame)
assert df["col1"].dtype == "float64"
assert df["col2"].dtype == "object"
assert df["col2"][0] is None
numpy.testing.assert_array_equal(df["col1"], [111.0, 222.0, 333.0, numpy.nan, numpy.nan, numpy.nan])
numpy.testing.assert_array_equal(df["col2"], [None, None, None, "aaa", "bbb", "ccc"])
@pytest.mark.parametrize("odyssey", odc_modules)
def test_unqualified_names(odyssey):
"""
Check that we can extract columns by unqualified name, and by fully qualified name
(that is, where the name contains an '@', we can extract by short name
"""
sample = {
"col1@tbl1": [11, 12, 13, 14, 15, 16],
"col2@tbl1": [21, 22, 23, 24, 25, 26],
"col1@tbl2": [31, 32, 33, 34, 35, 36],
"col3@tbl2": [41, 42, 43, 44, 45, 46],
"col4": [51, 52, 53, 54, 55, 56],
}
input_df = pandas.DataFrame(sample)
with NamedTemporaryFile() as fencode:
odyssey.encode_odb(input_df, fencode)
fencode.flush()
# Check fully-qualified naming
cols = ["col1@tbl1", "col3@tbl2", "col4"]
df = odyssey.read_odb(fencode.name, single=True, columns=cols)
expected_df = input_df[cols]
assert_dataframe_equal(df, expected_df)
# Check quick-access naming
cols = ["col2", "col3", "col4"]
df = odyssey.read_odb(fencode.name, single=True, columns=cols)
assert len(df.keys()) == 3
assert set(df.keys()) == set(cols)
expected_df = pandas.DataFrame(
{
"col2": sample["col2@tbl1"],
"col3": sample["col3@tbl2"],
"col4": sample["col4"],
}
)
assert_dataframe_equal(df, expected_df)
# What happens if we try and access an ambiguous columns?
with pytest.raises(KeyError):
odyssey.read_odb(fencode.name, single=True, columns=["col1"])
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_properties(odyssey):
"""Check that additional properties are encoded and decoded properly."""
with NamedTemporaryFile() as fencode:
# Test both by passing file handle and name to the encoding function.
# Please see ODB-523 for more information.
for f in [fencode, fencode.name]:
encode_sample(odyssey, f)
reader = odyssey.Reader(fencode.name)
for frame in reader.frames:
expected_properties = SAMPLE_PROPERTIES
# C library adds an implicit `encoder` property to each frame
if odyssey == codc:
expected_properties["encoder"] = "odc version " + ODC_VERSION
assert frame.properties == expected_properties
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_bitfields(odyssey):
"""
Check that bitfields are appropriately encoded with all the details
"""
EXPECTED_ALL = [0b0000, 0b1001, 0b0110, 0b0101, 0b1010, 0b1111, 0b0000]
EXPECTED1 = [False, True, False, True, False, True, False]
EXPECTED2 = [0, 0, 3, 2, 1, 3, 0]
EXPECTED3 = [False, True, False, False, True, True, False]
EXPECTED_ALLb = [0b0000, 0b1001, None, 0b0101, 0b1010, 0b1111, 0b0000]
EXPECTED1b = [False, True, None, True, False, True, False]
EXPECTED2b = [0, 0, None, 2, 1, 3, 0]
EXPECTED3b = [False, True, None, False, True, True, False]
with NamedTemporaryFile() as fencode:
encode_sample(odyssey, fencode)
reader = odyssey.Reader(fencode.name)
# Check that the frame contains the correct bitfield info
for frame in reader.frames:
for colname in ("col14", "col15"):
col = frame.column_dict[colname]
assert col.dtype == odyssey.BITFIELD
assert len(col.bitfields) == 3
assert col.bitfields[0].name == "bf1"
assert col.bitfields[0].size == 1
assert col.bitfields[0].offset == 0
assert col.bitfields[1].name == "bfextended"
assert col.bitfields[1].size == 2
assert col.bitfields[1].offset == 1
assert col.bitfields[2].name == "bf3"
assert col.bitfields[2].size == 1
assert col.bitfields[2].offset == 3
# Check that the decoded columns look right
df = odyssey.read_odb(fencode.name, single=True)
data = df["col14"]
expected = pandas.Series(EXPECTED_ALL, name="col14")
pandas.testing.assert_series_equal(data, expected)
data = df["col15"]
expected = pandas.Series(EXPECTED_ALLb, name="col15")
pandas.testing.assert_series_equal(data, expected)
# Check that we can decode specific bitfield colmuns
df = odyssey.read_odb(fencode.name, columns=["col14.bf3", "col14.bfextended", "col14.bf1"], single=True)
expected_df = pandas.DataFrame({"col14.bf1": EXPECTED1, "col14.bfextended": EXPECTED2, "col14.bf3": EXPECTED3})
assert_dataframe_equal(df, expected_df)
df = odyssey.read_odb(fencode.name, columns=["col15.bf3", "col15.bfextended", "col15.bf1"], single=True)
expected_df = pandas.DataFrame(
{"col15.bf1": EXPECTED1b, "col15.bfextended": EXPECTED2b, "col15.bf3": EXPECTED3b}
)
assert_dataframe_equal(df, expected_df)
# Check that we can decode all the things at the same time...
df = odyssey.read_odb(fencode.name, columns=["col14.bf3", "col14", "col14.bf1"], single=True)
expected_df = pandas.DataFrame({"col14.bf1": EXPECTED1, "col14": EXPECTED_ALL, "col14.bf3": EXPECTED3})
assert_dataframe_equal(df, expected_df)
df = odyssey.read_odb(fencode.name, columns=["col15.bf3", "col15", "col15.bf1"], single=True)
expected_df = pandas.DataFrame({"col15.bf1": EXPECTED1b, "col15": EXPECTED_ALLb, "col15.bf3": EXPECTED3b})
assert_dataframe_equal(df, expected_df)
# Check that we get a sensible error if we request a bitfield that doesn't exist
with pytest.raises(KeyError):
odyssey.read_odb(fencode.name, columns=["col14.badbf"], single=True)
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_bitfield_like(odyssey):
sample = {
"col1.bf1": [1, 0, 1, 0, 1, 0, 1],
"col1.bf2": [1, 3, 2, 1, 3, 1, 2],
"col1.bf3": [0, 1, 0, 1, 0, 1, 0],
}
input_df = pandas.DataFrame(sample)
with NamedTemporaryFile() as fencode:
odyssey.encode_odb(input_df, fencode)
fencode.flush()
# We can extract columns with more complex names
df = odyssey.read_odb(fencode.name, single=True)
assert isinstance(df, pandas.DataFrame)
assert_dataframe_equal(df, input_df)
assert "col1.bf1" in df
assert "col1.bf2" in df
assert "col1.bf3" in df
# We can extract a subset of these columns
df = odyssey.read_odb(fencode.name, single=True, columns=("col1.bf2",))
assert "col1.bf1" not in df
assert "col1.bf2" in df
assert "col1.bf3" not in df
numpy.testing.assert_array_equal(df["col1.bf2"], input_df["col1.bf2"])
@pytest.mark.parametrize("odyssey", odc_modules)
def test_encode_decode_bitfield_like_fully_qualified(odyssey):
sample = {
"col1.bf1@tbl": [1, 0, 1, 0, 1, 0, 1],
"col1.bf2@tbl": [1, 3, 2, 1, 3, 1, 2],
"col1.bf3@tbl": [0, 1, 0, 1, 0, 1, 0],
"col1@tbl": [0, 0, 0, 0, 0, 0, 0],
}
input_df = pandas.DataFrame(sample)
with NamedTemporaryFile() as fencode:
odyssey.encode_odb(input_df, fencode)
fencode.flush()
# We can extract columns with more complex names
df = odyssey.read_odb(fencode.name, single=True)
assert isinstance(df, pandas.DataFrame)
assert_dataframe_equal(df, input_df)
assert "col1.bf1@tbl" in df
assert "col1.bf2@tbl" in df
assert "col1.bf3@tbl" in df
# We can extract a subset of these columns
df = odyssey.read_odb(fencode.name, single=True, columns=("col1.bf2", "col1"))
assert "col1" in df
assert "col1.bf1" not in df
assert "col1.bf2" in df
assert "col1.bf3" not in df
assert "col1@tbl" not in df
assert "col1.bf1@tbl" not in df
assert "col1.bf2@tbl" not in df
assert "col1.bf3@tbl" not in df
numpy.testing.assert_array_equal(df["col1.bf2"], input_df["col1.bf2@tbl"])
numpy.testing.assert_array_equal(df["col1"], input_df["col1@tbl"])
# And by fully qualified name
df = odyssey.read_odb(fencode.name, single=True, columns=("col1.bf2@tbl", "col1@tbl"))
assert "col1" not in df
assert "col1.bf1" not in df
assert "col1.bf2" not in df
assert "col1.bf3" not in df
assert "col1@tbl" in df
assert "col1.bf1@tbl" not in df
assert "col1.bf2@tbl" in df
assert "col1.bf3@tbl" not in df
numpy.testing.assert_array_equal(df["col1.bf2@tbl"], input_df["col1.bf2@tbl"])
numpy.testing.assert_array_equal(df["col1@tbl"], input_df["col1@tbl"])
@pytest.mark.parametrize("encode_odc, decode_odc", [(e, d) for e in odc_modules for d in odc_modules])
def test_cross_library_encode_decode(encode_odc, decode_odc):
"Check that all the four (encoder, decoder) pairs work across pyodc and codc, (if codc is present)."
SAMPLE_TYPES = {
"col14": encode_odc.BITFIELD,
"col15": encode_odc.BITFIELD,
"constant_bitfield": encode_odc.BITFIELD,
}
with NamedTemporaryFile() as f:
df1 = pandas.DataFrame(SAMPLE_DATA)
encode_odc.encode_odb(df1, f, types=SAMPLE_TYPES, bitfields=SAMPLE_BITFIELDS)
f.flush()
df2 = decode_odc.read_odb(f.name, single=True)
assert_dataframe_equal(df1, df2)
|
