def testEqual1(self) -> None:
df0 = pd.DataFrame([[0, 1, 0], [2, 3, 60], [4, 5, 120]],
columns=['A', 'B', 'C'])
ds0 = SimpleSeries.fromDataFrame(df0)
ds1 = SimpleSeries.fromDataFrame(df0)
self.assertTrue(ds0 == ds1)
buf = ds1.iat[0, 0]
ds1.iat[0, 0] = -1
self.assertFalse(ds0 == ds1)
ds1.iat[0, 0] = buf
self.assertFalse(ds0 != ds1)
def testCreateNumericIndex0(self) -> None:
r0 = SimpleSeries.createNumericIndex(0.9, 40, 0.1)
r1 = SimpleSeries.createNumericIndex(10, 40, 1)
r2 = SimpleSeries.createNumericIndex(10, 40, 10)
r3 = SimpleSeries.createNumericIndex(10, 40, 100)
self.assertEqual(len(r0), 392)
self.assertAlmostEqual(r0[-2], 39.9, 1)
self.assertEqual(len(r1), 31)
self.assertEqual(r1[-2], 39)
self.assertEqual(len(r2), 4)
self.assertEqual(r2[-2], 30)
self.assertEqual(len(r3), 1)
self.assertEqual(r3[0], 10)
def testRandom0(self) -> None:
#tests also __setitem__
min = 0.000001
max = 0.000005
ds = SimpleSeries.random(min, max, 10, ['A', 'B', 'Cr'])
ds[1, 1] = 1
self.assertFalse(ds.bounded(min, max))
def testColumnNames0(self) -> None:
columnsNames = ['A', 'B', 'C']
numColumnsNames = ['A']
df0 = pd.DataFrame([[0, 1, 'A'], [2, 3, 'B'], [4, 'x', 'C']],
columns=columnsNames)
ds0 = SimpleSeries.fromDataFrame(df0)
self.assertTrue(all(ds0.columnNames() == columnsNames))
self.assertTrue(all(ds0.numericColumnNames() == numColumnsNames))
def testBounded0(self) -> None:
df0 = pd.DataFrame([[0, 1, 10.23], [2, 3, -23.1], [4, 5, 9]],
columns=['A', 'B', 'C'])
ds0 = SimpleSeries.fromDataFrame(df0)
self.assertTrue(ds0.bounded(-23.1, 10.23))
self.assertFalse(ds0.bounded(-23.0, 10.23))
self.assertFalse(ds0.bounded(-23.2, 10.0))
self.assertFalse(ds0.bounded(-22, 10.0))
def testFindExpectedSamples0(self) -> Any:
df0 = pd.DataFrame(
[[10, 1, 0], [20, 3, 60], [30, 5, 120], [40, 8, 20], [50, 5, 10]],
columns=['i', 'A', 'B'])
df0 = df0.set_index('i')
ds0 = SimpleSeries.fromDataFrame(df0)
self.assertEqual(ds0.findExpectedSamples(0.1), 401)
self.assertEqual(ds0.findExpectedSamples(1), 41)
self.assertEqual(ds0.findExpectedSamples(10), 5)
self.assertEqual(ds0.findExpectedSamples(100), 1)
ds1 = ds0.reversed()
self.assertEqual(ds1.findExpectedSamples(0.1), 401)
def testInterpolate0(self) -> None:
resolution = 0.1
ds0 = SimpleSeries.random(0.1, 0.3, 5, ['A', 'B'])
expectedSamples, existingSamples = ds0.findMissing(resolution)
self.assertTrue(ds0.hasMissing(resolution))
self.assertEqual(existingSamples, 5)
self.assertEqual(expectedSamples, 41)
self.assertEqual(expectedSamples - existingSamples, 36)
ds1 = ds0.copy()
ds1.interpolate(resolution)
expectedSamples, existingSamples = ds1.findMissing(resolution)
self.assertFalse(ds1.hasMissing(resolution))
self.assertEqual(existingSamples, 41)
self.assertEqual(expectedSamples, 41)
if plot:
plt.subplot(1, 2, 1)
plt.plot(ds0.toDataFrame())
plt.subplot(1, 2, 2)
plt.plot(ds1.toDataFrame())
plt.show()
def setUpClass(cls) -> None:
#code to be executed only once before all tests start
#Get market data
cls.marketDataSS = SimpleSeries.fromCSV(seriesFN, allColumNames)
def testRandom1(self) -> None:
min = -10.000001
max = 0.000005
ds = SimpleSeries.random(min, max, 10, ['A', 'B', 'Cr'])
self.assertTrue(ds.bounded(min, max))