def test_tssdict_min_date(self):
"""Tests min date """
# First add a timeseries that is earlier than the others
tmp_ts0 = Timeseries()
tmp_ts0.key = "First"
tmp_ts0.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts0.tseries = np.arange(10)
tmp_ts0.make_arrays()
self.tssdict[tmp_ts0.key] = tmp_ts0
self.assertTupleEqual(
self.tssdict.min_date(), (date(2014, 12, 22), "First")
)
tmp_nodata = Timeseries()
tmp_nodata.key = "nothing"
tssdict = TssDict()
tssdict[tmp_nodata.key] = tmp_nodata
self.assertTupleEqual(tssdict.min_date(), (None, "nothing"))
tssdict = TssDict()
# none timeseries list
tssdict["test"] = [
date(2014, 12, 31) + timedelta(days=i) for i in range(10)
]
tssdict["test1"] = [
date(2013, 12, 31) + timedelta(days=i) for i in range(10)
]
self.assertRaises(ValueError, tssdict.min_date)
def setUp(self):
# three timeseries
self.ts = Timeseries()
self.ts.key = "Main"
self.ts.columns = ["F1"]
start_date = datetime(2015, 12, 31).toordinal()
self.ts.dseries = start_date + np.arange(10)
self.ts.tseries = np.arange(10)
self.ts.make_arrays()
# longer timeseries
self.ts_long = Timeseries()
self.ts_long.key = "Long"
start_date = datetime(2015, 12, 31).toordinal()
self.ts_long.dseries = start_date + np.arange(20)
self.ts_long.tseries = np.arange(20)
self.ts_long.make_arrays()
# shorter timeseries
self.ts_short = Timeseries()
self.ts_short.key = "Short"
start_date = datetime(2015, 12, 31).toordinal()
self.ts_short.dseries = start_date + np.arange(5)
self.ts_short.tseries = np.arange(5)
self.ts_short.make_arrays()
self.tssdict = TssDict([self.ts, self.ts_long, self.ts_short])
def test_class_init_(self):
"""Test class initialization."""
self.assertEqual(len(self.tssdict), 3)
tmp_ts0 = Timeseries()
tmp_ts1 = Timeseries()
tmp_ts2 = Timeseries()
tmp_ts0.key = "ts0"
tmp_ts1.key = "ts1"
tmp_ts2.key = "ts2"
tssdict = TssDict([tmp_ts0, tmp_ts1, tmp_ts2])
self.assertEqual(len(tssdict), 3)
tssdict = TssDict()
tssdict["ts0"] = tmp_ts0
tssdict["ts1"] = tmp_ts1
tssdict["ts2"] = tmp_ts2
self.assertEqual(len(tssdict), 3)
tssdict = TssDict(
{
tmp_ts0.key: tmp_ts0,
tmp_ts1.key: tmp_ts1,
tmp_ts2.key: tmp_ts2,
}
)
self.assertEqual(len(tssdict), 3)
def test_from_json(self):
"""
This function tests building back a tsslist from json fmt string.
This relies heavily on the test for Timeseries.from_json.
"""
json_str = self.tssdict.to_json()
tssdict = TssDict()
tssdict.from_json(json_str)
self.assertEqual(len(tssdict), 3)
self.assertTupleEqual(tssdict["Main"].shape(), self.ts.shape())
self.assertTupleEqual(tssdict["Long"].shape(), self.ts_long.shape())
self.assertTupleEqual(tssdict["Short"].shape(), self.ts_short.shape())
test = json.dumps(["test"])
self.assertRaises(ValueError, tssdict.from_json, json.dumps(["test"]))
def test_tssdict_combine(self):
"""
A batch of tests combining columns to one timeseries.
Tests check to see whether the parameters are passed down properly to
each timeseries.
"""
# combine(self, discard=True, pad=None)
ts_new, _ = self.tssdict.combine(discard=True, pad=None)
# shape corresponds to the shortest length
self.assertEqual(
ts_new.tseries.shape[0], self.ts_short.tseries.shape[0]
)
self.assertEqual(ts_new.tseries.shape[1], 3)
# combine(self, discard=False, pad=0)
ts_new, _ = self.tssdict.combine(discard=False, pad=0)
# shape corresponds to the longest length
self.assertEqual(
ts_new.tseries.shape[0], self.ts_long.tseries.shape[0]
)
self.assertEqual(ts_new.tseries.shape[1], 3)
# test with TssList
tmp_ts0 = Timeseries()
tmp_ts0.key = "First"
tmp_ts0.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts0.tseries = np.arange(10)
tmp_ts0.make_arrays()
tmp_ts1 = Timeseries()
tmp_ts1.key = "Second"
tmp_ts1.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts1.tseries = np.arange(10)
tmp_ts1.make_arrays()
tssdict = TssDict(TssList([tmp_ts0, tmp_ts1]))
ts, _ = tssdict.combine()
self.assertTupleEqual(ts.tseries.shape, (10, 2))
# test with TssDict
tssdict = TssDict(TssDict([tmp_ts0, tmp_ts1]))
ts, _ = tssdict.combine()
self.assertTupleEqual(ts.tseries.shape, (10, 2))
def test_from_dict(self):
"""
This function tests creating a TssDict instance from a dict of timeseries.
The format of the incoming timeseries is to_dict(dt_fmt='str')
"""
tssdict = TssDict().from_dict(
{
self.ts.key: self.ts.to_dict(dt_fmt="str"),
self.ts_long.key: self.ts_long.to_dict(dt_fmt="str"),
self.ts_short.key: self.ts_short.to_dict(dt_fmt="str"),
}
)
self.assertListEqual(
list(self.tssdict.keys()),
[self.ts.key, self.ts_long.key, self.ts_short.key],
)
def test_tssdict_max_date(self):
"""Tests max date """
self.assertTupleEqual(
self.tssdict.max_date(), (date(2016, 1, 19), "Long")
)
tssdict = TssDict()
# none timeseries list
tssdict["test"] = [
date(2014, 12, 31) + timedelta(days=i) for i in range(10)
]
tssdict["test1"] = [
date(2013, 12, 31) + timedelta(days=i) for i in range(10)
]
self.assertRaises(ValueError, tssdict.max_date)
class TestTssDict(unittest.TestCase):
""" This class tests the class TssDict. """
def setUp(self):
# three timeseries
self.ts = Timeseries()
self.ts.key = "Main"
self.ts.columns = ["F1"]
start_date = datetime(2015, 12, 31).toordinal()
self.ts.dseries = start_date + np.arange(10)
self.ts.tseries = np.arange(10)
self.ts.make_arrays()
# longer timeseries
self.ts_long = Timeseries()
self.ts_long.key = "Long"
start_date = datetime(2015, 12, 31).toordinal()
self.ts_long.dseries = start_date + np.arange(20)
self.ts_long.tseries = np.arange(20)
self.ts_long.make_arrays()
# shorter timeseries
self.ts_short = Timeseries()
self.ts_short.key = "Short"
start_date = datetime(2015, 12, 31).toordinal()
self.ts_short.dseries = start_date + np.arange(5)
self.ts_short.tseries = np.arange(5)
self.ts_short.make_arrays()
self.tssdict = TssDict([self.ts, self.ts_long, self.ts_short])
def test_class_init_(self):
"""Test class initialization."""
self.assertEqual(len(self.tssdict), 3)
tmp_ts0 = Timeseries()
tmp_ts1 = Timeseries()
tmp_ts2 = Timeseries()
tmp_ts0.key = "ts0"
tmp_ts1.key = "ts1"
tmp_ts2.key = "ts2"
tssdict = TssDict([tmp_ts0, tmp_ts1, tmp_ts2])
self.assertEqual(len(tssdict), 3)
tssdict = TssDict()
tssdict["ts0"] = tmp_ts0
tssdict["ts1"] = tmp_ts1
tssdict["ts2"] = tmp_ts2
self.assertEqual(len(tssdict), 3)
tssdict = TssDict(
{
tmp_ts0.key: tmp_ts0,
tmp_ts1.key: tmp_ts1,
tmp_ts2.key: tmp_ts2,
}
)
self.assertEqual(len(tssdict), 3)
def test_tssdict_min_date(self):
"""Tests min date """
# First add a timeseries that is earlier than the others
tmp_ts0 = Timeseries()
tmp_ts0.key = "First"
tmp_ts0.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts0.tseries = np.arange(10)
tmp_ts0.make_arrays()
self.tssdict[tmp_ts0.key] = tmp_ts0
self.assertTupleEqual(
self.tssdict.min_date(), (date(2014, 12, 22), "First")
)
tmp_nodata = Timeseries()
tmp_nodata.key = "nothing"
tssdict = TssDict()
tssdict[tmp_nodata.key] = tmp_nodata
self.assertTupleEqual(tssdict.min_date(), (None, "nothing"))
tssdict = TssDict()
# none timeseries list
tssdict["test"] = [
date(2014, 12, 31) + timedelta(days=i) for i in range(10)
]
tssdict["test1"] = [
date(2013, 12, 31) + timedelta(days=i) for i in range(10)
]
self.assertRaises(ValueError, tssdict.min_date)
def test_tssdict_max_date(self):
"""Tests max date """
self.assertTupleEqual(
self.tssdict.max_date(), (date(2016, 1, 19), "Long")
)
tssdict = TssDict()
# none timeseries list
tssdict["test"] = [
date(2014, 12, 31) + timedelta(days=i) for i in range(10)
]
tssdict["test1"] = [
date(2013, 12, 31) + timedelta(days=i) for i in range(10)
]
self.assertRaises(ValueError, tssdict.max_date)
def test_tssdict_longest_ts(self):
"""
This test tests for the longest timeseries.
"""
length, key = self.tssdict.longest_ts()
self.assertTupleEqual(
(length, key), (self.ts_long.tseries.shape[0], "Long")
)
self.tssdict["test"] = "something else"
self.assertRaises(ValueError, self.tssdict.longest_ts)
def test_tssdict_shortest_ts(self):
"""
This test tests for the shortest timeseries.
"""
length, key = self.tssdict.shortest_ts()
self.assertTupleEqual(
(length, key), (self.ts_short.tseries.shape[0], "Short")
)
# zero length
self.tssdict["nothing"] = Timeseries()
self.assertIsNone(self.tssdict.shortest_ts())
del self.tssdict["nothing"]
# bad data
self.tssdict["bad"] = "something else"
self.assertRaises(ValueError, self.tssdict.shortest_ts)
def test_tssdict_combine(self):
"""
A batch of tests combining columns to one timeseries.
Tests check to see whether the parameters are passed down properly to
each timeseries.
"""
# combine(self, discard=True, pad=None)
ts_new, _ = self.tssdict.combine(discard=True, pad=None)
# shape corresponds to the shortest length
self.assertEqual(
ts_new.tseries.shape[0], self.ts_short.tseries.shape[0]
)
self.assertEqual(ts_new.tseries.shape[1], 3)
# combine(self, discard=False, pad=0)
ts_new, _ = self.tssdict.combine(discard=False, pad=0)
# shape corresponds to the longest length
self.assertEqual(
ts_new.tseries.shape[0], self.ts_long.tseries.shape[0]
)
self.assertEqual(ts_new.tseries.shape[1], 3)
# test with TssList
tmp_ts0 = Timeseries()
tmp_ts0.key = "First"
tmp_ts0.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts0.tseries = np.arange(10)
tmp_ts0.make_arrays()
tmp_ts1 = Timeseries()
tmp_ts1.key = "Second"
tmp_ts1.dseries = datetime(2014, 12, 31).toordinal() - np.arange(10)
tmp_ts1.tseries = np.arange(10)
tmp_ts1.make_arrays()
tssdict = TssDict(TssList([tmp_ts0, tmp_ts1]))
ts, _ = tssdict.combine()
self.assertTupleEqual(ts.tseries.shape, (10, 2))
# test with TssDict
tssdict = TssDict(TssDict([tmp_ts0, tmp_ts1]))
ts, _ = tssdict.combine()
self.assertTupleEqual(ts.tseries.shape, (10, 2))
def test_tssdict_get_values(self):
""" Tests the ability to locate the correct row of data. """
date1 = datetime(2016, 1, 4) # existing date within date series
date2 = datetime(2016, 1, 16) # date falling on a weekend
# get data from existing date
self.assertTupleEqual(
self.tssdict.get_values(
date=date1, keys=["Main", "Long", "Short"]
),
((4.0, 4.0, 4.0), ("Main", "Long", "Short")),
)
# attempt to get data from date not present, with notify
self.assertRaises(
ValueError, self.tssdict.get_values, date2, notify=True
)
# attempt to get data from date not present, no notify
self.assertTupleEqual(
self.tssdict.get_values(
date=date2, keys=["Main", "Long", "Short"]
),
((None, 16.0, None), ("Main", "Long", "Short")),
)
def test_clone(self):
"""Verifies that a copy is made."""
tssdict = self.tssdict.clone()
# is it a separate object
for key, ts_new in tssdict.items():
ts_orig = self.tssdict[key]
self.assertNotEqual(ts_new, ts_orig)
# do the characteristics match up?
self.assertEqual(len(tssdict), 3)
def test_to_json(self):
"""
This function tests sending a TssList to a json format.
Using a cheap assumption that since it is simply a dict, that as long
as the timeseries are converted, the list is what is needed to check.
More needs to be checked.
"""
json_str = self.tssdict.to_json()
self.assertIsInstance(json.loads(json_str), dict)
def test_from_dict(self):
"""
This function tests creating a TssDict instance from a dict of timeseries.
The format of the incoming timeseries is to_dict(dt_fmt='str')
"""
tssdict = TssDict().from_dict(
{
self.ts.key: self.ts.to_dict(dt_fmt="str"),
self.ts_long.key: self.ts_long.to_dict(dt_fmt="str"),
self.ts_short.key: self.ts_short.to_dict(dt_fmt="str"),
}
)
self.assertListEqual(
list(self.tssdict.keys()),
[self.ts.key, self.ts_long.key, self.ts_short.key],
)
def test_from_json(self):
"""
This function tests building back a tsslist from json fmt string.
This relies heavily on the test for Timeseries.from_json.
"""
json_str = self.tssdict.to_json()
tssdict = TssDict()
tssdict.from_json(json_str)
self.assertEqual(len(tssdict), 3)
self.assertTupleEqual(tssdict["Main"].shape(), self.ts.shape())
self.assertTupleEqual(tssdict["Long"].shape(), self.ts_long.shape())
self.assertTupleEqual(tssdict["Short"].shape(), self.ts_short.shape())
test = json.dumps(["test"])
self.assertRaises(ValueError, tssdict.from_json, json.dumps(["test"]))
def test_tssdict_do_func(self):
"""Placeholder for future function."""
pass