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add sum back in, fix min inital value, tidy up spaces in

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code and comment wording, add a sum test assertion
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JamesP 2015-11-07 18:00:21 +10:00
commit 7d62b9fc1a
1 changed files with 20 additions and 11 deletions
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lib/pure/stats.nim
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@ -15,6 +15,7 @@
## - n (data count) ## - n (data count)
## - min (smallest value) ## - min (smallest value)
## - max (largest value) ## - max (largest value)
## - sum
## - mean ## - mean
## - variance ## - variance
## - varianceS (sample var) ## - varianceS (sample var)
@ -38,7 +39,7 @@ from math import FloatClass, sqrt, pow, round
type type
RunningStat* = object ## an accumulator for statistical data RunningStat* = object ## an accumulator for statistical data
n*: int ## number of pushed data n*: int ## number of pushed data
min*, max*: float ## self-explaining min*, max*, sum*: float ## self-explaining
mom1, mom2, mom3, mom4: float ## statistical moments, mom1 is mean mom1, mom2, mom3, mom4: float ## statistical moments, mom1 is mean
@ -46,15 +47,16 @@ type
n*: int ## number of pushed data n*: int ## number of pushed data
x_stats*: RunningStat ## stats for first set of data x_stats*: RunningStat ## stats for first set of data
y_stats*: RunningStat ## stats for second set of data y_stats*: RunningStat ## stats for second set of data
s_xy: float ## acculated data for combined xy s_xy: float ## accumulated data for combined xy
{.deprecated: [TFloatClass: FloatClass, TRunningStat: RunningStat].} {.deprecated: [TFloatClass: FloatClass, TRunningStat: RunningStat].}
proc clear(s: var RunningStat) = proc clear*(s: var RunningStat) =
## reset `s` ## reset `s`
s.n = 0 s.n = 0
s.min = 0.0 s.min = toBiggestFloat(int.high)
s.max = 0.0 s.max = 0.0
s.sum = 0.0
s.mom1 = 0.0 s.mom1 = 0.0
s.mom2 = 0.0 s.mom2 = 0.0
s.mom3 = 0.0 s.mom3 = 0.0
@ -62,10 +64,12 @@ proc clear(s: var RunningStat) =
proc push*(s: var RunningStat, x: float) = proc push*(s: var RunningStat, x: float) =
## pushes a value `x` for processing ## pushes a value `x` for processing
if s.n == 0: s.min = x
inc(s.n) inc(s.n)
# See Knuth TAOCP vol 2, 3rd edition, page 232 # See Knuth TAOCP vol 2, 3rd edition, page 232
if s.min > x: s.min = x if s.min > x: s.min = x
if s.max < x: s.max = x if s.max < x: s.max = x
s.sum += x
let n = toFloat(s.n) let n = toFloat(s.n)
let delta = x - s.mom1 let delta = x - s.mom1
let delta_n = delta / toFloat(s.n) let delta_n = delta / toFloat(s.n)
@ -92,8 +96,9 @@ proc push*(s: var RunningStat, x: openarray[float|int]) =
for val in x: for val in x:
s.push(val) s.push(val)
proc mean*(s: RunningStat): float = result = s.mom1 proc mean*(s: RunningStat): float =
## computes the current mean of `s` ## computes the current mean of `s`
result = s.mom1
proc variance*(s: RunningStat): float = proc variance*(s: RunningStat): float =
## computes the current population variance of `s` ## computes the current population variance of `s`
@ -172,8 +177,8 @@ proc clear*(r: var RunningRegress) =
proc push*(r: var RunningRegress, x, y: float) = proc push*(r: var RunningRegress, x, y: float) =
## pushes two values `x` and `y` for processing ## pushes two values `x` and `y` for processing
r.s_xy += (r.x_stats.mean() -x)*(r.y_stats.mean() - y)*toFloat(r.n)/toFloat(r.n+1) r.s_xy += (r.x_stats.mean() - x)*(r.y_stats.mean() - y)*
toFloat(r.n) / toFloat(r.n + 1)
r.x_stats.push(x) r.x_stats.push(x)
r.y_stats.push(y) r.y_stats.push(y)
inc(r.n) inc(r.n)
@ -254,6 +259,10 @@ when isMainModule:
doAssert(clean(rs1.mom2) == clean(rs.mom2)) doAssert(clean(rs1.mom2) == clean(rs.mom2))
doAssert(clean(rs1.mom3) == clean(rs.mom3)) doAssert(clean(rs1.mom3) == clean(rs.mom3))
doAssert(clean(rs1.mom4) == clean(rs.mom4)) 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)
var rr: RunningRegress 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]) rr.push(@[0.0,1.0,2.8,3.0,4.0], @[0.0,1.0,2.3,3.0,4.0])