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Don't parameterize repetitive tests
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@markcampanelli
markcampanelli committed Dec 24, 2024
1 parent 60a5d94 commit 9ab2ecf
Showing 1 changed file with 103 additions and 187 deletions.
290 changes: 103 additions & 187 deletions pvlib/tests/test_tools.py
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Original file line number Diff line number Diff line change
Expand Up @@ -149,190 +149,106 @@ def test_normalize_max2one(data_in, expected):
assert_allclose(result, expected)


@pytest.mark.parametrize(
'input,expected',
[
(
{
"time": datetime(
1974, 6, 22, 18, 30, 15, tzinfo=ZoneInfo("Etc/GMT+5"),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
datetime(1974, 6, 22, 23, 30, 15, tzinfo=ZoneInfo("UTC")),
),
(
{
"time": datetime(1974, 6, 22, 18, 30, 15),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
datetime(1974, 6, 22, 23, 30, 15, tzinfo=ZoneInfo("UTC")),
),
(
{
"time": pd.DatetimeIndex(
["1974-06-22T18:30:15"],
tz=ZoneInfo("Etc/GMT+5"),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
(
{
"time": pd.DatetimeIndex(["1974-06-22T18:30:15"]),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
(
{
"time": pd.Series(
[24.42],
index=pd.DatetimeIndex(
["1974-06-22T18:30:15"],
tz=ZoneInfo("Etc/GMT+5"),
),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.Series(
[24.42],
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
),
(
{
"time": pd.Series(
[24.42],
index=pd.DatetimeIndex(["1974-06-22T18:30:15"]),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.Series(
[24.42],
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
),
(
{
"time": pd.DataFrame(
[[24.42]],
index=pd.DatetimeIndex(
["1974-06-22T18:30:15"],
tz=ZoneInfo("Etc/GMT+5"),
),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.DataFrame(
[[24.42]],
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
),
(
{
"time": pd.DataFrame(
[[24.42]],
index=pd.DatetimeIndex(["1974-06-22T18:30:15"]),
),
"location": location.Location(
43.19262774396091, -77.58782907414867, tz="Etc/GMT+5"
)
},
pd.DataFrame(
[[24.42]],
pd.DatetimeIndex(["1974-06-22T23:30:15"], tz=ZoneInfo("UTC")),
),
),
],
ids=[
"datetime.datetime with tzinfo",
"datetime.datetime",
"pandas.DatetimeIndex with tzinfo",
"pandas.DatetimeIndex",
"pandas.Series with tzinfo",
"pandas.Series",
"pandas.DataFrame with tzinfo",
"pandas.DataFrame",
],
)
def test_localize_to_utc(input, expected):
got = tools.localize_to_utc(**input)

if isinstance(got, (pd.Series, pd.DataFrame)):
# Older pandas versions have wonky dtype equality check on timestamp
# index, so check the values as numpy.ndarray and indices one by one.
np.testing.assert_array_equal(got.to_numpy(), expected.to_numpy())

for index_got, index_expected in zip(got.index, expected.index):
assert index_got == index_expected
else:
assert got == expected


@pytest.mark.parametrize(
'input,expected',
[
(
{
"time": datetime(
1974, 6, 22, 18, 30, 15, tzinfo=ZoneInfo("Etc/GMT+5")
)
},
27201.47934027778,
),
(
{
"time": datetime(1974, 6, 22, 23, 30, 15)
},
27201.47934027778,
),
],
ids=["datetime.datetime with tzinfo", "datetime.datetime"],
)
def test_datetime_to_djd(input, expected):
assert tools.datetime_to_djd(input["time"]) == expected


@pytest.mark.parametrize(
'input,expected',
[
(
{
"djd": 27201.47934027778,
"tz": "Etc/GMT+5",
},
datetime(1974, 6, 22, 18, 30, 15, tzinfo=ZoneInfo("Etc/GMT+5")),
),
(
{
"djd": 27201.47934027778,
"tz": None,
},
datetime(1974, 6, 22, 23, 30, 15, tzinfo=ZoneInfo("UTC")),
),
],
ids=["djd with tzinfo", "djd"],
)
def test_djd_to_datetime(input, expected):
if input["tz"] is not None:
got = tools.djd_to_datetime(input["djd"])
else:
got = tools.djd_to_datetime(input["djd"], tz="Etc/GMT+5")

assert got == expected
def test_localize_to_utc():
lat, lon = 43.2, -77.6
tz = "Etc/GMT+5"
loc = location.Location(lat, lon, tz=tz)
year, month, day, hour, minute, second = 1974, 6, 22, 18, 30, 15
hour_utc = hour + 5

# Test all combinations of supported inputs.
dt_time_aware_utc = datetime(
year, month, day, hour_utc, minute, second, tzinfo=ZoneInfo("UTC")
)
dt_time_aware = datetime(
year, month, day, hour, minute, second, tzinfo=ZoneInfo(tz)
)
assert tools.localize_to_utc(dt_time_aware, None) == dt_time_aware_utc
dt_time_naive = datetime(year, month, day, hour, minute, second)
assert tools.localize_to_utc(dt_time_naive, loc) == dt_time_aware_utc

# FIXME Derive timestamp strings from above variables.
dt_index_aware_utc = pd.DatetimeIndex(
[dt_time_aware_utc.strftime("%Y-%m-%dT%H:%M:%S")], tz=ZoneInfo("UTC")
)
dt_index_aware = pd.DatetimeIndex(
[dt_time_aware.strftime("%Y-%m-%dT%H:%M:%S")], tz=ZoneInfo(tz)
)
assert tools.localize_to_utc(dt_index_aware, None) == dt_index_aware_utc
dt_index_naive = pd.DatetimeIndex(
[dt_time_naive.strftime("%Y-%m-%dT%H:%M:%S")]
)
assert tools.localize_to_utc(dt_index_naive, loc) == dt_index_aware_utc

# Older pandas versions have wonky dtype equality check on timestamp
# index, so check the values as numpy.ndarray and indices one by one.
series_time_aware_utc_expected = pd.Series([24.42], dt_index_aware_utc)
series_time_aware = pd.Series([24.42], index=dt_index_aware)
series_time_aware_utc_got = tools.localize_to_utc(series_time_aware, None)
np.testing.assert_array_equal(
series_time_aware_utc_got.to_numpy(),
series_time_aware_utc_expected.to_numpy(),
)

for index_got, index_expected in zip(
series_time_aware_utc_got.index, series_time_aware_utc_expected.index
):
assert index_got == index_expected

series_time_naive = pd.Series([24.42], index=dt_index_naive)
series_time_naive_utc_got = tools.localize_to_utc(series_time_naive, loc)
np.testing.assert_array_equal(
series_time_naive_utc_got.to_numpy(),
series_time_aware_utc_expected.to_numpy(),
)

for index_got, index_expected in zip(
series_time_naive_utc_got.index, series_time_aware_utc_expected.index
):
assert index_got == index_expected

# Older pandas versions have wonky dtype equality check on timestamp
# index, so check the values as numpy.ndarray and indices one by one.
df_time_aware_utc_expected = pd.DataFrame([[24.42]], dt_index_aware)
df_time_naive = pd.DataFrame([[24.42]], index=dt_index_naive)
df_time_naive_utc_got = tools.localize_to_utc(df_time_naive, loc)
np.testing.assert_array_equal(
df_time_naive_utc_got.to_numpy(),
df_time_aware_utc_expected.to_numpy(),
)

for index_got, index_expected in zip(
df_time_naive_utc_got.index, df_time_aware_utc_expected.index
):
assert index_got == index_expected

df_time_aware = pd.DataFrame([[24.42]], index=dt_index_aware)
df_time_aware_utc_got = tools.localize_to_utc(df_time_aware, None)
np.testing.assert_array_equal(
df_time_aware_utc_got.to_numpy(),
df_time_aware_utc_expected.to_numpy(),
)

for index_got, index_expected in zip(
df_time_aware_utc_got.index, df_time_aware_utc_expected.index
):
assert index_got == index_expected


def test_datetime_to_djd():
expected = 27201.47934027778
dt_aware = datetime(1974, 6, 22, 18, 30, 15, tzinfo=ZoneInfo("Etc/GMT+5"))
assert tools.datetime_to_djd(dt_aware) == expected
dt_naive_utc = datetime(1974, 6, 22, 23, 30, 15)
assert tools.datetime_to_djd(dt_naive_utc) == expected


def test_djd_to_datetime():
djd = 27201.47934027778
tz = "Etc/GMT+5"

expected = datetime(1974, 6, 22, 18, 30, 15, tzinfo=ZoneInfo(tz))
assert tools.djd_to_datetime(djd, tz) == expected

expected = datetime(1974, 6, 22, 23, 30, 15, tzinfo=ZoneInfo("UTC"))
assert tools.djd_to_datetime(djd) == expected

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