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- include stats
- proc clean(x: float): float =
- result = round(1.0e8*x).float * 1.0e-8
- var rs: RunningStat
- rs.push(@[1.0, 2.0, 1.0, 4.0, 1.0, 4.0, 1.0, 2.0])
- doAssert(rs.n == 8)
- doAssert(clean(rs.mean) == 2.0)
- doAssert(clean(rs.variance()) == 1.5)
- doAssert(clean(rs.varianceS()) == 1.71428571)
- doAssert(clean(rs.skewness()) == 0.81649658)
- doAssert(clean(rs.skewnessS()) == 1.01835015)
- doAssert(clean(rs.kurtosis()) == -1.0)
- doAssert(clean(rs.kurtosisS()) == -0.7000000000000001)
- var rs1, rs2: RunningStat
- rs1.push(@[1.0, 2.0, 1.0, 4.0])
- rs2.push(@[1.0, 4.0, 1.0, 2.0])
- let rs3 = rs1 + rs2
- doAssert(clean(rs3.mom2) == clean(rs.mom2))
- doAssert(clean(rs3.mom3) == clean(rs.mom3))
- doAssert(clean(rs3.mom4) == clean(rs.mom4))
- rs1 += rs2
- doAssert(clean(rs1.mom2) == clean(rs.mom2))
- doAssert(clean(rs1.mom3) == clean(rs.mom3))
- doAssert(clean(rs1.mom4) == clean(rs.mom4))
- rs1.clear()
- rs1.push(@[1.0, 2.2, 1.4, 4.9])
- doAssert(rs1.sum == 9.5)
- doAssert(rs1.mean() == 2.375)
- when not defined(cpu32):
- # XXX For some reason on 32bit CPUs these results differ
- var rr: RunningRegress
- rr.push(@[0.0, 1.0, 2.8, 3.0, 4.0], @[0.0, 1.0, 2.3, 3.0, 4.0])
- doAssert(rr.slope() == 0.9695585996955861)
- doAssert(rr.intercept() == -0.03424657534246611)
- doAssert(rr.correlation() == 0.9905100362239381)
- var rr1, rr2: RunningRegress
- rr1.push(@[0.0, 1.0], @[0.0, 1.0])
- rr2.push(@[2.8, 3.0, 4.0], @[2.3, 3.0, 4.0])
- let rr3 = rr1 + rr2
- doAssert(rr3.correlation() == rr.correlation())
- doAssert(clean(rr3.slope()) == clean(rr.slope()))
- doAssert(clean(rr3.intercept()) == clean(rr.intercept()))
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