def test_categorize_columns():
csvdata = StringIO(
dedent("""\
parameter,units,season,lower,NSQD Median,upper
Cadmium (Cd),ug/L,autumn,0.117,0.361,0.52
Cadmium (Cd),ug/L,spring,0.172,0.352,0.53
Cadmium (Cd),ug/L,summer,0.304,0.411,0.476
Cadmium (Cd),ug/L,winter,0.355,0.559,1.125
Dissolved Chloride (Cl),mg/L,autumn,0.342,2.3,5.8
Dissolved Chloride (Cl),mg/L,spring,2.5,2.5,2.5
Dissolved Chloride (Cl),mg/L,summer,0.308,0.762,1.24
Escherichia coli,MPN/100 mL,autumn,1200.0,15500.0,24000.0
Escherichia coli,MPN/100 mL,spring,10.0,630.0,810.0
Escherichia coli,MPN/100 mL,summer,21000.0,27000.0,35000.0
Escherichia coli,MPN/100 mL,winter,20.0,200.0,800.0
"""))
df = pandas.read_csv(csvdata)
df2 = misc.categorize_columns(df, "parameter", "units", "season")
# check pandas API that the first df has object columns
assert object in df.dtypes.values
# confirm that all of those objects are gone
assert object not in df2.dtypes.values
with helpers.raises(ValueError):
misc.categorize_columns(df, "parameter", "upper")
def test_getStormFromTimestamp_(hr_simple_fixture, value, smallstorms, error):
with helpers.raises(error):
sn, storm = hr_simple_fixture.getStormFromTimestamp(
value, smallstorms=smallstorms)
assert sn == 2
if not smallstorms:
assert storm is None
else:
assert isinstance(storm, hydro.Storm)
def test__find_by_name(value, expected, error):
source = [
{"name": "MPN/100 mL", "factor": 1},
{"name": "MPN/100 mL", "factor": 1},
{"name": "ug/L", "factor": 1},
]
with helpers.raises(error):
result = info._find_by_name(value, source)
assert result == expected
def test_add_column_level(basic_data):
known_cols = pandas.MultiIndex.from_tuples([
(u"test", u"A"), (u"test", u"B"), (u"test", u"C"), (u"test", u"D")
])
newdata = misc.add_column_level(basic_data, "test", "testlevel")
assert known_cols.tolist() == newdata.columns.tolist()
# can only add levels to non-MultiIndex columns
with helpers.raises(ValueError):
misc.add_column_level(newdata, "test2", "testlevel2")
def test_getStormFromTimestamp_lookback(hr_simple_fixture, lbh, expected,
error):
with helpers.raises(error):
ts = pandas.Timestamp("2013-05-19 14:42")
sn, storm = hr_simple_fixture.getStormFromTimestamp(ts,
lookback_hours=lbh)
if expected:
assert sn == expected
else:
assert sn is None
def test_makeTimestamp_basic(row, expected, error):
with warnings.catch_warnings(), helpers.raises(error):
warnings.simplefilter("always")
tstamp = dateutils.makeTimestamp(row)
assert tstamp == pandas.Timestamp(expected)
def test_ds_scatterplot_useros(ds_NDs):
with helpers.raises(ValueError):
ds_NDs.scatterplot(useros=True)
def test_theilslopes(dc):
with helpers.raises(NotImplementedError):
_ = dc.theilslopes
def test_anderson_darling_log(dc):
with helpers.raises(NotImplementedError):
_ = dc.anderson_darling_log
def test__detection_limit_index_out_of_bounds(basic_cohn):
with helpers.raises(IndexError):
ros._detection_limit_index(0, basic_cohn)
