def load_test_csv(path):
inputSeq = []
expectedSeq = []
csvFile = open(path, "r")
reader = csv.DictReader(csvFile)
for row in reader:
inputSeq.append(float(row["Input"]))
expected = row["Expected"]
if not expected:
expected = None
else:
expected = float(expected)
expectedSeq.append(expected)
return (dataseries.SequenceDataSeries(inputSeq),
dataseries.SequenceDataSeries(expectedSeq))
def testSeqLikeOps(self):
seq = range(10)
ds = dataseries.SequenceDataSeries(seq)
# Test length and every item.
self.assertEqual(len(ds), len(seq))
for i in xrange(len(seq)):
self.assertEqual(ds[i], seq[i])
# Test negative indices
self.assertEqual(ds[-1], seq[-1])
self.assertEqual(ds[-2], seq[-2])
self.assertEqual(ds[-9], seq[-9])
# Test slices
sl = slice(0, 1, 2)
self.assertEqual(ds[sl], seq[sl])
sl = slice(0, 9, 2)
self.assertEqual(ds[sl], seq[sl])
sl = slice(0, -1, 1)
self.assertEqual(ds[sl], seq[sl])
for i in xrange(-100, 100):
self.assertEqual(ds[i:], seq[i:])
for step in xrange(1, 10):
for i in xrange(-100, 100):
self.assertEqual(ds[i::step], seq[i::step])
def testEmpty(self):
ds = dataseries.SequenceDataSeries([])
self.assertTrue(ds.get_first_valid_index() == 0)
self.assertTrue(ds.get_length() == 0)
with self.assertRaises(IndexError):
ds[-1]
with self.assertRaises(IndexError):
ds[-2]
with self.assertRaises(IndexError):
ds[0]
with self.assertRaises(IndexError):
ds[1]
def testNonEmpty(self):
ds = dataseries.SequenceDataSeries(range(10))
self.assertTrue(ds.get_first_valid_index() == 0)
self.assertTrue(ds.get_length() == 10)
self.assertTrue(ds[-1] == 9)
self.assertTrue(ds[-2] == 8)
self.assertTrue(ds[0] == 0)
self.assertTrue(ds[1] == 1)
self.assertTrue(ds.get_values(1) == [9])
self.assertTrue(ds.get_values(2) == [8, 9])
self.assertTrue(ds.get_values(1, 1) == [8])
self.assertTrue(ds.get_values(2, 1) == [7, 8])
self.assertTrue(ds.get_values_absolute(1, 3) == [1, 2, 3])
self.assertTrue(ds.get_values_absolute(9, 9) == [9])
self.assertTrue(ds.get_values_absolute(9, 10) == None)
self.assertTrue(ds.get_values_absolute(9, 10, True) == [9, None])
def testInvalidPosNotCached(self):
values = []
ds = dataseries.SequenceDataSeries(values)
for i in range(10):
values.append(i)
values.append(None) # Interleave Nones.
testFilter = DataSeriesFilterTest.TestFilter(ds)
self.assertTrue(testFilter[-1] == None)
self.assertTrue(testFilter[-2] == 9)
self.assertTrue(
testFilter[-4] == 8
) # We go 3 instead of 2 because we need to skip the interleaved None values.
self.assertTrue(testFilter[18] == 9)
self.assertTrue(testFilter[19] == None)
# Absolut pos 20 should have the next value once we insert it, but right now it should be invalid.
with self.assertRaises(IndexError):
testFilter[20]
values.append(10)
self.assertTrue(testFilter[20] == 10)
def __init__(self):
self.__net_returns = dataseries.SequenceDataSeries()
self.__cumulative_returns = dataseries.SequenceDataSeries()
class Accumulator(technical.DataSeriesFilter):
def __init__(self, dataSeries, windowSize):
technical.DataSeriesFilter.__init__(self, dataSeries, windowSize)
def calculateValue(self, first_idx, last_idx):
accum = 0
for value in self.get_data_series()[first_idx:last_idx + 1]:
# If any value from the wrapped DataSeries is None then we abort calculation and return None.
if value is None:
return None
accum += value
return accum
# Build a sequence based DataSeries.
ds = dataseries.SequenceDataSeries(range(0, 50))
# Wrap it with a 3 element Accumulator filter.
ds = Accumulator(ds, 3)
# Get some values.
print ds[0] # Not enough values yet.
print ds[1] # Not enough values yet.
print ds[2] # Ok, now we should have at least 3 values.
print ds[3]
# Get the last value, which should equals 49 + 48 + 47.
print ds[-1]
def __loadMedPriceDS(self):
ret = dataseries.SequenceDataSeries()
for i in xrange(len(OPEN_VALUES)):
ret.append_value(LOW_VALUES[i] +
(HIGH_VALUES[i] - LOW_VALUES[i]) / 2.0)
return ret