def test_convert_units(self):
a = tstoolbox.read("tests/data_gainesville_daily_precip.csv",
target_units="in")
b = tstoolbox.equation(
"x1/25.4",
input_ts="tests/data_gainesville_daily_precip.csv").astype(
"float64")
b.columns = ["ADaymet-prcp:in"]
assert_frame_equal(a, b)
a = tstoolbox.read("tests/data_gainesville_daily_precip.csv",
target_units="km")
b = tstoolbox.equation(
"x1/(1000*1000)",
input_ts="tests/data_gainesville_daily_precip.csv").astype(
"float64")
b.columns = ["ADaymet-prcp:km"]
assert_frame_equal(a, b)
with pytest.raises(ValueError) as e_info:
_ = tstoolbox.read("tests/data_gainesville_daily_precip.csv",
source_units="ft3/s")
assert (
r" You specified 'source_units' as ft3/s, but column units are mm."
in str(e_info.value))
with pytest.raises(ValueError) as e_info:
_ = tstoolbox.read("tests/data_gainesville_daily_precip.csv",
target_units="ft3/s")
def test_extract(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=5,
base_year=1870)
wdmtoolbox.csvtowdm(self.wdmname, 101,
input_ts='tests/sunspot_area.csv')
ret1 = wdmtoolbox.extract(self.wdmname, 101).astype('f')
ret2 = wdmtoolbox.extract('{0},101'.format(self.wdmname)).astype('f')
assert_frame_equal(ret1, ret2)
ret3 = tstoolbox.read('tests/sunspot_area.csv').astype('f')
ret1.columns = ['Area']
assert_frame_equal(ret1, ret3)
ret4 = tstoolbox.read('tests/sunspot_area_with_missing.csv',
dropna='no').astype('f')
wdmtoolbox.createnewdsn(self.wdmname,
500,
tcode=5,
base_year=1870)
wdmtoolbox.csvtowdm(self.wdmname,
500,
input_ts='tests/sunspot_area_with_missing.csv')
ret5 = wdmtoolbox.extract(self.wdmname, 500).astype('f')
ret5.columns = ['Area']
assert_frame_equal(ret5, ret4)
def setUp(self):
self.data_0_to_1 = tstoolbox.read(
'tests/data_sunspot_normalized_0_to_1.csv')
self.data_10_to_20 = tstoolbox.read(
'tests/data_sunspot_normalized_10_to_20.csv')
self.data_zscore = tstoolbox.read(
'tests/data_sunspot_normalized_zscore.csv')
self.data_zscore = tsutils.memory_optimize(self.data_zscore)
self.data_pct_rank = tstoolbox.read(
'tests/data_sunspot_normalized_pct_rank.csv')
self.data_pct_rank = tsutils.memory_optimize(self.data_pct_rank)
def setUp(self):
self.data_0_to_1 = tstoolbox.read(
"tests/data_sunspot_normalized_0_to_1.csv")
self.data_0_to_1.columns = ["Area::minmax"]
self.data_10_to_20 = tstoolbox.read(
"tests/data_sunspot_normalized_10_to_20.csv")
self.data_10_to_20.columns = ["Area::minmax"]
self.data_zscore = tstoolbox.read(
"tests/data_sunspot_normalized_zscore.csv")
self.data_zscore.columns = ["Area::zscore"]
self.data_zscore = tsutils.memory_optimize(self.data_zscore)
self.data_pct_rank = tstoolbox.read(
"tests/data_sunspot_normalized_pct_rank.csv")
self.data_pct_rank.columns = ["Area::pct_rank"]
self.data_pct_rank = tsutils.memory_optimize(self.data_pct_rank)
def test_small_window_len(self):
out = tstoolbox.filter("flat",
input_ts="tests/data_sine.csv",
window_len=2)
out1 = tstoolbox.read("tests/data_sine.csv")
out1.columns = ["Value::filter"]
# NOp
assert_frame_equal(out, out1)
def test_small_window_len(self):
out = tstoolbox.filter('flat',
input_ts='tests/data_sine.csv',
window_len=2)
out1 = tstoolbox.read('tests/data_sine.csv')
out1.columns = ['Value_filter']
# NOp
assert_frame_equal(out, out1)
def test_round_index_mulitple_direct(self):
"""Test round_index API for multiple columns - daily."""
out = tstoolbox.read(
"tests/data_simple.csv,tests/data_simple.csv",
append="columns",
round_index="D",
)
assert_frame_equal(out, self.round_index_multiple_direct)
def test_small_window_len(self):
out = tstoolbox.filter('flat',
input_ts='tests/data_sine.csv',
window_len=2)
out1 = tstoolbox.read('tests/data_sine.csv')
out1.columns = ['Value::filter']
# NOp
assert_frame_equal(out, out1)
def test_kde_time_multiple_traces():
ndf = tstoolbox.read(['tests/daily.csv',
'tests/02325000_flow.csv'])
return tstoolbox.plot(type='kde_time',
columns=[2, 3],
clean=True,
input_ts=ndf,
ytitle='Flow',
ofilename=None)
def setUp(self):
self.ats = tstoolbox.read(os.path.join('tests', 'data_sine.csv'))
self.ats.index.name = 'Datetime'
self.ats.columns = ['Value']
self.flat_3 = self.ats.join(
tstoolbox.read(os.path.join('tests', 'data_filter_flat.csv')))
self.hanning = self.ats.join(
tstoolbox.read(os.path.join('tests', 'data_filter_hanning.csv')))
self.fft_lowpass = self.ats.join(
tstoolbox.read(os.path.join('tests',
'data_filter_fft_lowpass.csv')))
self.fft_highpass = self.ats.copy()
self.fft_highpass.columns = ['Value_filter']
self.fft_highpass = self.ats.join(self.fft_highpass)
def test_boxplot():
ndf = tstoolbox.read(['tests/02234500_65_65.csv',
'tests/02325000_flow.csv'],
clean=True,
append='combine')
return tstoolbox.plot(input_ts=ndf,
clean=True,
columns=[2, 3],
type='boxplot',
ofilename=None)
def test_equation_cols_over_nine(self):
"""Test of using equation API with columns over 9."""
input_ts = tstoolbox.read('tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv', append='columns')
out = tstoolbox.equation('x10*10', input_ts=input_ts)
self.maxDiff = None
assert_frame_equal(out, self.equation_result)
def test_kde_time_multiple_traces():
plt.close("all")
ndf = tstoolbox.read(["tests/daily.csv", "tests/02325000_flow.csv"])
return tstoolbox.plot(
type="kde_time",
columns=[2, 3],
clean=True,
input_ts=ndf,
ytitle="Flow",
ofilename=None,
)
def setUp(self):
self.ats = tstoolbox.read(os.path.join('tests', 'data_sine.csv'))
self.ats.index.name = 'Datetime'
self.ats.columns = ['Value']
self.flat_3 = self.ats.join(tstoolbox.read(os.path.join('tests',
'data_filter_flat.csv')))
self.flat_3.columns = ['Value', 'Value::filter']
self.hanning = self.ats.join(tstoolbox.read(os.path.join('tests',
'data_filter_hanning.csv')))
self.hanning.columns = ['Value', 'Value::filter']
self.fft_lowpass = self.ats.join(tstoolbox.read(os.path.join('tests',
'data_filter_fft_lowpass.csv')))
self.fft_lowpass.columns = ['Value', 'Value::filter']
self.fft_highpass = self.ats.copy()
self.fft_highpass.columns = ['Value::filter']
self.fft_highpass = self.ats.join(self.fft_highpass)
def test_start_date(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=2,
base_year=1970, tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname, 101,
input_ts='tests/nwisiv_02246000.csv')
ret1 = wdmtoolbox.extract(self.wdmname, 101, start_date='2014-02-21 16:00:00')
ret3 = tstoolbox.read('tests/nwisiv_02246000.csv', start_date='2014-02-21 16:00:00').astype('float64')
ret1.columns = ['02246000_iv_00060']
assert_frame_equal(ret1, ret3)
def test_boxplot():
plt.close("all")
xdf = tstoolbox.read(
["tests/02234500_65_65.csv", "tests/02325000_flow.csv"],
clean=True,
append="combine",
)
return tstoolbox.plot(input_ts=xdf,
clean=True,
columns=[2, 3],
type="boxplot",
ofilename=None)
def setUp(self):
self.ats = tstoolbox.read(os.path.join("tests", "data_sine.csv"))
self.ats.index.name = "Datetime"
self.ats.columns = ["Value"]
self.flat_3 = self.ats.join(
tstoolbox.read(os.path.join("tests", "data_filter_flat.csv")))
self.flat_3.columns = ["Value", "Value::filter"]
self.hanning = self.ats.join(
tstoolbox.read(os.path.join("tests", "data_filter_hanning.csv")))
self.hanning.columns = ["Value", "Value::filter"]
self.fft_lowpass = self.ats.join(
tstoolbox.read(os.path.join("tests",
"data_filter_fft_lowpass.csv")))
self.fft_lowpass.columns = ["Value", "Value::filter"]
self.fft_highpass = self.ats.copy()
self.fft_highpass.columns = ["Value::filter"]
self.fft_highpass = self.ats.join(self.fft_highpass)
def test_start_date(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=2, base_year=1970, tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname, 101, input_ts="tests/nwisiv_02246000.csv")
ret1 = wdmtoolbox.extract(self.wdmname, 101, start_date="2014-02-21 16:00:00")
ret3 = tstoolbox.read(
"tests/nwisiv_02246000.csv", start_date="2014-02-21 16:00:00"
).astype("float64")
ret3.index = ret3.index.tz_localize(None)
ret1.columns = ["02246000_iv_00060"]
assert_frame_equal(ret1, ret3, check_index_type=False)
def test_tstep(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=2,
base_year=1970, tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname, 101,
input_ts='tests/nwisiv_02246000.csv')
ret1 = wdmtoolbox.extract(self.wdmname, 101)
ret2 = wdmtoolbox.extract('{0},101'.format(self.wdmname))
assert_frame_equal(ret1, ret2)
ret3 = tstoolbox.read('tests/nwisiv_02246000.csv').astype('float64')
ret1.columns = ['02246000_iv_00060']
assert_frame_equal(ret1, ret3)
def test_equation_cols_over_nine(self):
"""Test of using equation API with columns over 9."""
input_ts = tstoolbox.read(
"tests/data_multiple_cols.csv,"
"tests/data_multiple_cols.csv,"
"tests/data_multiple_cols.csv,"
"tests/data_multiple_cols.csv,"
"tests/data_multiple_cols.csv",
append="columns",
)
out = tstoolbox.equation("x10*10", input_ts=input_ts)
self.maxDiff = None
assert_frame_equal(out, self.equation_result)
def test_equation_cols_over_nine(self):
''' Test of using equation API with columns over 9.
'''
input_ts = tstoolbox.read(
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv,'
'tests/data_multiple_cols.csv',
append='columns')
out = tstoolbox.equation('x10*10', input_ts=input_ts)
self.maxDiff = None
assert_frame_equal(out, self.equation_result)
def setUp(self):
self.df = tstoolbox.read(
["tests/data_sunspot.csv", "tests/data_sunspot.csv"])
self.gof = [
["Bias", 0.0],
["Root-mean-square Deviation (RMSD)", 0.0],
["Centered RMSD (CRMSD)", 0.0],
["Correlation coefficient (r)", 1.0],
["Skill score (Murphy)", 1.0],
["Nash-Sutcliffe Efficiency", 1.0],
["Common count observed and simulated", 1672],
["Count of NaNs", "", 0, 0],
]
def test_fill_from(self):
"""Test fill with from API."""
out = tstoolbox.fill(
method="from",
input_ts="tests/data_fill_from.csv",
from_columns=[2, 3],
to_columns=1,
)
compare = tstoolbox.read("tests/data_fill_from.csv")
compare.columns = ["Value::fill", "Value1::fill", "Value2::fill"]
compare.loc["2000-01-02", "Value::fill"] = 2.5
compare.loc["2000-01-04", "Value::fill"] = 23.1
self.conDiff = None
assert_frame_equal(out, compare)
def test_extract(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=5, base_year=1870)
wdmtoolbox.csvtowdm(self.wdmname, 101, input_ts="tests/sunspot_area.csv")
ret1 = wdmtoolbox.extract(self.wdmname, 101).astype("f")
ret2 = wdmtoolbox.extract("{0},101".format(self.wdmname)).astype("f")
assert_frame_equal(ret1, ret2)
ret3 = tstoolbox.read("tests/sunspot_area.csv").astype("f")
ret1.columns = ["Area"]
assert_frame_equal(ret1, ret3)
ret4 = tstoolbox.read(
"tests/sunspot_area_with_missing.csv", dropna="no"
).astype("f")
wdmtoolbox.createnewdsn(self.wdmname, 500, tcode=5, base_year=1870)
wdmtoolbox.csvtowdm(
self.wdmname, 500, input_ts="tests/sunspot_area_with_missing.csv"
)
ret5 = wdmtoolbox.extract(self.wdmname, 500).astype("f")
ret5.columns = ["Area"]
assert_frame_equal(ret5, ret4)
def test_copy_to_self(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=2,
base_year=1970, tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname, 101,
input_ts='tests/nwisiv_02246000.csv')
ret1 = wdmtoolbox.extract(self.wdmname, 101)
ret2 = wdmtoolbox.extract('{0},101'.format(self.wdmname))
assert_frame_equal(ret1, ret2)
ret3 = tstoolbox.read('tests/nwisiv_02246000.csv').astype('float64')
ret1.columns = ['02246000_iv_00060']
assert_frame_equal(ret1, ret3)
wdmtoolbox.copydsn(self.wdmname, 101, self.wdmname, 1101)
def test_extract(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=5, base_year=1870)
wdmtoolbox.csvtowdm(self.wdmname,
101,
input_ts='tests/sunspot_area.csv')
ret1 = wdmtoolbox.extract(self.wdmname, 101)
ret2 = wdmtoolbox.extract('{0},101'.format(self.wdmname))
assert_frame_equal(ret1, ret2)
ret3 = tstoolbox.read('tests/sunspot_area.csv')
ret1.columns = ['Area']
assert_frame_equal(ret1, ret3)
ret4 = tstoolbox.read('tests/sunspot_area_with_missing.csv',
dropna='no')
wdmtoolbox.createnewdsn(self.wdmname, 500, tcode=5, base_year=1870)
wdmtoolbox.csvtowdm(self.wdmname,
500,
input_ts='tests/sunspot_area_with_missing.csv')
ret5 = wdmtoolbox.extract(self.wdmname, 500)
ret5.columns = ['Area']
assert_frame_equal(ret5, ret4)
def test_end_date(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname, 101, tcode=2,
base_year=1970, tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname, 101,
input_ts='tests/nwisiv_02246000.csv')
ret1 = wdmtoolbox.extract(self.wdmname,
101,
end_date='2014-02-22 11:00:00')
ret3 = tstoolbox.read('tests/nwisiv_02246000.csv',
end_date='2014-02-22 11:00:00').astype('float64')
ret3.index = ret3.index.tz_localize(None)
ret1.columns = ['02246000_iv_00060']
assert_frame_equal(ret1, ret3, check_index_type=False)
def test_end_date(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname,
101,
tcode=2,
base_year=1970,
tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname,
101,
input_ts='tests/nwisiv_02246000.csv')
ret1 = wdmtoolbox.extract(self.wdmname,
101,
end_date='2014-02-22 11:00:00')
ret3 = tstoolbox.read('tests/nwisiv_02246000.csv',
end_date='2014-02-22 11:00:00').astype('float64')
ret1.columns = ['02246000_iv_00060']
assert_frame_equal(ret1, ret3)
def test_copy_to_self(self):
wdmtoolbox.createnewwdm(self.wdmname, overwrite=True)
wdmtoolbox.createnewdsn(self.wdmname,
101,
tcode=2,
base_year=1970,
tsstep=15)
wdmtoolbox.csvtowdm(self.wdmname,
101,
input_ts="tests/nwisiv_02246000.csv")
ret1 = wdmtoolbox.extract(self.wdmname, 101)
ret2 = wdmtoolbox.extract("{0},101".format(self.wdmname))
assert_frame_equal(ret1, ret2, check_index_type=False)
ret3 = tstoolbox.read("tests/nwisiv_02246000.csv").astype("float64")
ret3.index = ret3.index.tz_localize(None)
ret1.columns = ["02246000_iv_00060"]
assert_frame_equal(ret1, ret3, check_index_type=False)
wdmtoolbox.copydsn(self.wdmname, 101, self.wdmname, 1101)
def setUp(self):
"""Prepare in-memory versions of the files ./data_flat.csv."""
self.fdata = tstoolbox.read("tests/data_flat.csv,tests/data_sunspot.csv")
self.fdata.index.name = "Datetime"
def test_createts_from_input(self):
"""Create a ts of data_flat.csv."""
out = tstoolbox.createts(input_ts=self.data).index
out1 = tstoolbox.read('tests/data_flat.csv').index
assert_index_equal(out, out1)
def test_read_direct_dropna(self):
"""Test read dropna for single column - daily."""
out = tstoolbox.read('tests/data_missing.csv', dropna='all')
assert_frame_equal(out, self.read_direct)
def test_ts_intervals(self):
"""Test many intervals to make sure tstoolbox makes a good guess."""
# 'matches' lists out things that should match but tstoolbox will give
# the simpler answer. For example 4 quarters is equal to a 1 year
# interval. Also difficult for tstoolbox to figure out that a 2 month
# interval isn't a 1 month interval with gaps.
matches = {
'4Q': '1A',
'8Q': '2A',
'4BQS': '1BAS',
'8BQS': '2BAS',
'4BQ': '1BA',
'8BQ': '2BA',
'4QS': '1AS',
'8QS': '2AS',
# '2M': '1M',
'3M': '1Q',
# '4M': '1M',
# '5M': '1M',
'6M': '2Q',
# '7M': '1M',
# '8M': '1M',
'9M': '3Q',
# '10M': '1M',
# '11M': '1M',
# '2BMS': '1BMS',
'3BMS': '1BQS',
# '4BMS': '1BMS',
# '5BMS': '1BMS',
'6BMS': '2BQS',
# '7BMS': '1BMS',
# '8BMS': '1BMS',
'9BMS': '3BQS',
# '10BMS': '1BMS',
# '11BMS': '1BMS',
# '2BM': '1BM',
'3BM': '1BQ',
# '4BM': '1BM',
# '5BM': '1BM',
'6BM': '2BQ',
# '7BM': '1BM',
# '8BM': '1BM',
'9BM': '3BQ',
# '10BM': '1BM',
# '11BM': '1BM',
# '2MS': '1MS',
'3MS': '1QS',
# '4MS': '1MS',
# '5MS': '1MS',
'6MS': '2QS',
# '7MS': '1MS',
# '8MS': '1MS',
'9MS': '3QS',
# '10MS': '1MS',
# '11MS': '1MS',
'5B': '1W',
'7D': '1W',
# BUG!!!
'2B': '2D',
'3B': '1D',
'4B': '2D',
'6B': '2D',
'7B': '1D',
'8B': '2D',
'9B': '1D',
}
for key in self.fps:
df = tstoolbox.read(self.fps[key][1])
inferred_code = df.index.inferred_freq
if inferred_code is None:
continue
testcode = '{0}{1}'.format(*key)
if inferred_code[0] not in '123456789':
inferred_code = '1' + inferred_code
if testcode in matches:
testcode = matches[testcode]
try:
self.assertEqual(testcode, inferred_code.split('-')[0])
except AssertionError:
self.assertEqual([i for i in testcode if not i.isdigit()],
[i for i in inferred_code.split('-')[0] if not i.isdigit()])
def setUp(self):
self.disaggregate_temperature = tstoolbox.read(
"tests/data_temperature_gainesville_disaggregate_sine_mean.csv")
def test_read_bi_monthly(self):
"""Test read API for bi monthly time series."""
out = tstoolbox.read("tests/data_bi_daily.csv")
assert_frame_equal(out, self.read_tsstep_2_daily)
def test_read_mulitple_direct_list(self):
"""Test read API for multiple columns - daily."""
out = tstoolbox.read(
["tests/data_simple.csv", "tests/data_simple.csv"],
append=r"columns")
assert_frame_equal(out, self.read_multiple_direct)
def test_read_direct(self):
"""Test read API for single column - daily."""
out = tstoolbox.read("tests/data_simple.csv")
assert_frame_equal(out, self.read_direct)
def test_createts_from_input(self):
"""Create a ts of data_flat.csv."""
out = tstoolbox.createts(input_ts=self.data).index
out1 = tstoolbox.read("tests/data_flat.csv").index
assert_index_equal(out, out1)
def setUp(self):
self.ats = tstoolbox.read(os.path.join('tests', 'data_sine.csv'))
self.ats.index.name = 'Datetime'
self.ats.columns = ['Value::clip']
self.ats.loc[self.ats['Value::clip'] < -0.75, 'Value::clip'] = -0.75
self.ats.loc[self.ats['Value::clip'] > 0.75, 'Value::clip'] = 0.75
def test_round_index_mulitple_direct(self):
"""Test round_index API for multiple columns - daily."""
out = tstoolbox.read('tests/data_simple.csv,tests/data_simple.csv',
append='columns',
round_index='D')
assert_frame_equal(out, self.round_index_multiple_direct)
def test_read_direct_sparse(self):
"""Test read API for single column - daily."""
out = tstoolbox.read('tests/data_simple_extra_rows_sparse.csv', skiprows=[4, 6])
assert_frame_equal(out, self.read_direct_sparse)
def test_read_direct_sparse(self):
"""Test read API for single column - daily."""
out = tstoolbox.read("tests/data_simple_extra_rows_sparse.csv", skiprows=[4, 6])
assert_frame_equal(out, self.read_direct_sparse)
def test_round_index_bi_monthly(self):
"""Test round_index API for bi monthly time series."""
out = tstoolbox.read('tests/data_bi_daily.csv',
round_index='D')
assert_frame_equal(out, self.round_index_tsstep_2_daily)
def setUp(self):
self.ats = tstoolbox.read(os.path.join("tests", "data_sine.csv"))
self.ats.index.name = "Datetime"
self.ats.columns = ["Value::clip"]
self.ats.loc[self.ats["Value::clip"] < -0.75, "Value::clip"] = -0.75
self.ats.loc[self.ats["Value::clip"] > 0.75, "Value::clip"] = 0.75
def test_ts_intervals(self):
''' Test many intervals to make sure tstoolbox makes a good guess.
'''
# 'matches' lists out things that should match but tstoolbox will give
# the simpler answer. For example 4 quarters is equal to a 1 year
# interval. Also difficult for tstoolbox to figure out that a 2 month
# interval isn't a 1 month interval with gaps.
matches = {
'4Q': '1A',
'8Q': '2A',
'4BQS': '1BAS',
'8BQS': '2BAS',
'4BQ': '1BA',
'8BQ': '2BA',
'4QS': '1AS',
'8QS': '2AS',
#'2M': '1M',
'3M': '1Q',
#'4M': '1M',
#'5M': '1M',
'6M': '2Q',
#'7M': '1M',
#'8M': '1M',
'9M': '3Q',
#'10M': '1M',
#'11M': '1M',
#'2BMS': '1BMS',
'3BMS': '1BQS',
#'4BMS': '1BMS',
#'5BMS': '1BMS',
'6BMS': '2BQS',
#'7BMS': '1BMS',
#'8BMS': '1BMS',
'9BMS': '3BQS',
#'10BMS': '1BMS',
#'11BMS': '1BMS',
#'2BM': '1BM',
'3BM': '1BQ',
#'4BM': '1BM',
#'5BM': '1BM',
'6BM': '2BQ',
#'7BM': '1BM',
#'8BM': '1BM',
'9BM': '3BQ',
#'10BM': '1BM',
#'11BM': '1BM',
#'2MS': '1MS',
'3MS': '1QS',
#'4MS': '1MS',
#'5MS': '1MS',
'6MS': '2QS',
#'7MS': '1MS',
#'8MS': '1MS',
'9MS': '3QS',
#'10MS': '1MS',
#'11MS': '1MS',
'5B': '1W',
'7D': '1W',
#BUG!!!
'2B': '2D',
'3B': '1D',
'4B': '2D',
'6B': '2D',
'7B': '1D',
'8B': '2D',
'9B': '1D',
}
for key in self.fps:
df = tstoolbox.read(self.fps[key][1])
inferred_code = df.index.inferred_freq
if inferred_code is None:
continue
testcode = '{0}{1}'.format(*key)
if inferred_code[0] not in '123456789':
inferred_code = '1' + inferred_code
if testcode in matches:
testcode = matches[testcode]
try:
self.assertEqual(testcode, inferred_code.split('-')[0])
except AssertionError:
self.assertEqual([i for i in testcode if not i.isdigit()], [
i for i in inferred_code.split('-')[0] if not i.isdigit()
])
def test_ts_intervals(self):
"""Test many intervals to make sure tstoolbox makes a good guess."""
# 'matches' lists out things that should match but tstoolbox will give
# the simpler answer. For example 4 quarters is equal to a 1 year
# interval. Also difficult for tstoolbox to figure out that a 2 month
# interval isn't a 1 month interval with gaps.
matches = {
"4Q": "1A",
"8Q": "2A",
"4BQS": "1BAS",
"8BQS": "2BAS",
"4BQ": "1BA",
"8BQ": "2BA",
"4QS": "1AS",
"8QS": "2AS",
# '2M': '1M',
"3M": "1Q",
# '4M': '1M',
# '5M': '1M',
"6M": "2Q",
# '7M': '1M',
# '8M': '1M',
"9M": "3Q",
# '10M': '1M',
# '11M': '1M',
# '2BMS': '1BMS',
"3BMS": "1BQS",
# '4BMS': '1BMS',
# '5BMS': '1BMS',
"6BMS": "2BQS",
# '7BMS': '1BMS',
# '8BMS': '1BMS',
"9BMS": "3BQS",
# '10BMS': '1BMS',
# '11BMS': '1BMS',
# '2BM': '1BM',
"3BM": "1BQ",
# '4BM': '1BM',
# '5BM': '1BM',
"6BM": "2BQ",
# '7BM': '1BM',
# '8BM': '1BM',
"9BM": "3BQ",
# '10BM': '1BM',
# '11BM': '1BM',
# '2MS': '1MS',
"3MS": "1QS",
# '4MS': '1MS',
# '5MS': '1MS',
"6MS": "2QS",
# '7MS': '1MS',
# '8MS': '1MS',
"9MS": "3QS",
# '10MS': '1MS',
# '11MS': '1MS',
"5B": "1W",
"7D": "1W",
# BUG!!!
"2B": "2D",
"3B": "1D",
"4B": "2D",
"6B": "2D",
"7B": "1D",
"8B": "2D",
"9B": "1D",
}
for key in self.fps:
df = tstoolbox.read(self.fps[key][1])
inferred_code = df.index.inferred_freq
if inferred_code is None:
continue
testcode = "{0}{1}".format(*key)
if inferred_code[0] not in "123456789":
inferred_code = "1" + inferred_code
if testcode in matches:
testcode = matches[testcode]
try:
self.assertEqual(testcode, inferred_code.split("-")[0])
except AssertionError:
self.assertEqual(
[i for i in testcode if not i.isdigit()],
[
i for i in inferred_code.split("-")[0]
if not i.isdigit()
],
)
def test_round_index_direct(self):
"""Test round_index API for single column - daily."""
out = tstoolbox.read('tests/data_simple.csv', round_index='D')
assert_frame_equal(out, self.round_index_direct)
