def LogRun(ss, dt):
"""
LogRun adds data from current run to the RunLog table.
"""
run = ss.TrainEnv.Run.Cur # this is NOT triggered by increment yet -- use Cur
row = dt.Rows
dt.SetNumRows(row + 1)
epclog = ss.TrnEpcLog
epcix = etable.NewIdxView(epclog)
# compute mean over last N epochs for run level
nlast = 1
if nlast > epcix.Len()-1:
nlast = epcix.Len() - 1
epcix.Idxs = epcix.Idxs[epcix.Len()-nlast-1:]
params = "Std"
if ss.AvgLGain != 2.5:
params += "_AvgLGain=%s" % (ss.AvgLGain)
if ss.InputNoise != 0:
params += "_InVar=%s" % (ss.InputNoise)
dt.SetCellFloat("Run", row, float(run))
dt.SetCellString("Params", row, params)
dt.SetCellFloat("UniqPats", row, agg.Mean(epcix, "UniqPats")[0])
runix = etable.NewIdxView(dt)
spl = split.GroupBy(runix, go.Slice_string(["Params"]))
split.Desc(spl, "UniqPats")
ss.RunStats = spl.AggsToTable(etable.AddAggName)
# note: essential to use Go version of update when called from another goroutine
ss.RunPlot.GoUpdate()
def UpdateEnv(ss):
if ss.Test == TestType.MultiObjs:
ss.TestEnv.Table = etable.NewIdxView(ss.MultiObjs)
if ss.Test == TestType.StdPosner:
ss.TestEnv.Table = etable.NewIdxView(ss.StdPosner)
if ss.Test == TestType.ClosePosner:
ss.TestEnv.Table = etable.NewIdxView(ss.ClosePosner)
if ss.Test == TestType.ReversePosner:
ss.TestEnv.Table = etable.NewIdxView(ss.ReversePosner)
if ss.Test == TestType.ObjAttn:
ss.TestEnv.Table = etable.NewIdxView(ss.ObjAttn)
def SetPats(ss, partial):
"""
SetPats selects which patterns to present: full or partial faces
"""
if partial:
ss.TestEnv.Table = etable.NewIdxView(ss.PartPats)
ss.TestEnv.Validate()
ss.TestEnv.Init(0)
else:
ss.TestEnv.Table = etable.NewIdxView(ss.Pats)
ss.TestEnv.Validate()
ss.TestEnv.Init(0)
def ConfigEnv(ss):
ss.TestEnv.Nm = "TestEnv"
ss.TestEnv.Dsc = "testing params and state"
ss.TestEnv.Table = etable.NewIdxView(ss.Pats)
ss.TestEnv.Sequential = True
ss.TestEnv.Validate()
ss.TestEnv.Init(0)
def LogRun(ss, dt):
"""
LogRun adds data from current run to the RunLog table.
"""
run = ss.TrainEnv.Run.Cur
row = dt.Rows
dt.SetNumRows(row + 1)
epclog = ss.TrnEpcLog
epcix = etable.NewIdxView(epclog)
# compute mean over last N epochs for run level
nlast = 10
if nlast > epcix.Len() - 1:
nlast = epcix.Len() - 1
epcix.Idxs = epcix.Idxs[epcix.Len() - nlast - 1:]
# params := ss.Params.Name
params = "params"
dt.SetCellFloat("Run", row, float(run))
dt.SetCellString("Params", row, params)
# runix := etable.NewIdxView(dt)
# spl := split.GroupBy(runix, []string{"Params"})
# split.Desc(spl, "FirstZero")
# split.Desc(spl, "PctCor")
# ss.RunStats = spl.AggsToTable(etable.AddAggName)
# note: essential to use Go version of update when called from another goroutine
ss.RunPlot.GoUpdate()
if ss.RunFile != 0:
if row == 0:
dt.WriteCSVHeaders(ss.RunFile, etable.Tab)
dt.WriteCSVRow(ss.RunFile, row, etable.Tab)
def ConfigEnv(ss):
if ss.MaxRuns == 0:
ss.MaxRuns = 1
if ss.MaxEpcs == 0: # allow user override
ss.MaxEpcs = 100
ss.NZeroStop = -1
if ss.MaxTrls == 0: # allow user override
ss.MaxTrls = 100
ss.TrainEnv.Nm = "TrainEnv"
ss.TrainEnv.Dsc = "training params and state"
ss.TrainEnv.Defaults()
ss.TrainEnv.ImageFiles = [
"v1rf_img1.jpg", "v1rf_img2.jpg", "v1rf_img3.jpg", "v1rf_img4.jpg"
]
ss.TrainEnv.OpenImages()
ss.TrainEnv.Validate()
ss.TrainEnv.Run.Max = ss.MaxRuns # note: we are not setting epoch max -- do that manually
ss.TrainEnv.Trial.Max = ss.MaxTrls
ss.TestEnv.Nm = "TestEnv"
ss.TestEnv.Dsc = "testing (probe) params and state"
ss.TestEnv.Table = etable.NewIdxView(ss.Probes)
ss.TestEnv.Sequential = True
ss.TestEnv.Validate()
ss.TrainEnv.Init(0)
ss.TestEnv.Init(0)
def LogRun(ss, dt):
"""
LogRun adds data from current run to the RunLog table.
"""
run = ss.TrainEnv.Run.Cur
row = dt.Rows
dt.SetNumRows(row + 1)
epclog = ss.TrnEpcLog
epcix = etable.NewIdxView(epclog)
# compute mean over last N epochs for run level
nlast = 1
if nlast > epcix.Len() - 1:
nlast = epcix.Len() - 1
epcix.Idxs = epcix.Idxs[epcix.Len() - nlast:]
params = "Std"
# if ss.AvgLGain != 2.5 {
# params += "_AvgLGain=%s" % (ss.AvgLGain)
# }
# if ss.InputNoise != 0 {
# params += "_InVar=%v" % (ss.InputNoise)
# }
dt.SetCellFloat("Run", row, float(run))
dt.SetCellString("Params", row, params)
# runix := etable.NewIdxView(dt)
# spl := split.GroupBy(runix, []string{"Params"})
# split.Desc(spl, "UniqPats")
# ss.RunStats = spl.AggsToTable(etable.AddAggName)
# note: essential to use Go version of update when called from another goroutine
ss.RunPlot.GoUpdate()
def ConfigEnv(ss):
if ss.MaxRuns == 0: # allow user override
ss.MaxRuns = 1
if ss.MaxEpcs == 0: # allow user override
ss.MaxEpcs = 1
ss.TrainEnv.Nm = "TrainEnv"
ss.TrainEnv.Dsc = "training params and state"
if ss.Delay == Delays.Delay3:
ss.TrainEnv.Table = etable.NewIdxView(ss.Delay3Pats)
if ss.Delay == Delays.Delay5:
ss.TrainEnv.Table = etable.NewIdxView(ss.Delay5Pats)
if ss.Delay == Delays.Delay1:
ss.TrainEnv.Table = etable.NewIdxView(ss.Delay1Pats)
ss.TrainEnv.Sequential = True
ss.TrainEnv.Validate()
ss.TrainEnv.Run.Max = ss.MaxRuns # note: we are not setting epoch max -- do that manually
ss.TrainEnv.Init(0)
def ConfigEnv(ss):
if ss.MaxRuns == 0:
ss.MaxRuns = 8
if ss.MaxEpcs == 0: # allow user override
ss.MaxEpcs = 30
ss.TrainEnv.Nm = "TrainEnv"
ss.TrainEnv.Dsc = "training params and state"
ss.TrainEnv.Table = etable.NewIdxView(ss.Lines2)
ss.TrainEnv.Validate()
ss.TrainEnv.Run.Max = ss.MaxRuns # note: we are not setting epoch max -- do that manually
ss.TestEnv.Nm = "TestEnv"
ss.TestEnv.Dsc = "testing params and state"
ss.TestEnv.Table = etable.NewIdxView(ss.Lines1)
ss.TestEnv.Sequential = True
ss.TestEnv.Validate()
ss.TrainEnv.Init(0)
ss.TestEnv.Init(0)
def LogRun(ss, dt):
"""
LogRun adds data from current run to the RunLog table.
"""
run = ss.TrainEnv.Run.Cur # this is NOT triggered by increment yet -- use Cur
row = dt.Rows
dt.SetNumRows(row + 1)
epclog = ss.TstEpcLog
epcix = etable.NewIdxView(epclog)
# compute mean over last N epochs for run level
nlast = 5
if nlast > epcix.Len()-1:
nlast = epcix.Len() - 1
epcix.Idxs = go.Slice_int(epcix.Idxs[epcix.Len()-nlast:])
params = ss.Learn.name + "_" + ss.Pats.name
dt.SetCellFloat("Run", row, float(run))
dt.SetCellString("Params", row, params)
dt.SetCellFloat("FirstZero", row, float(ss.FirstZero))
dt.SetCellFloat("SSE", row, agg.Mean(epcix, "SSE")[0])
dt.SetCellFloat("AvgSSE", row, agg.Mean(epcix, "AvgSSE")[0])
dt.SetCellFloat("PctErr", row, agg.Mean(epcix, "PctErr")[0])
dt.SetCellFloat("PctCor", row, agg.Mean(epcix, "PctCor")[0])
dt.SetCellFloat("CosDiff", row, agg.Mean(epcix, "CosDiff")[0])
runix = etable.NewIdxView(dt)
spl = split.GroupBy(runix, go.Slice_string(["Params"]))
split.Desc(spl, "FirstZero")
split.Desc(spl, "PctCor")
split.Desc(spl, "SSE")
ss.RunStats = spl.AggsToTable(etable.AddAggName)
# note: essential to use Go version of update when called from another goroutine
if ss.RunPlot != 0:
ss.RunPlot.GoUpdate()
if ss.RunFile != 0:
if row == 0:
dt.WriteCSVHeaders(ss.RunFile, etable.Tab)
dt.WriteCSVRow(ss.RunFile, row, etable.Tab)
def UpdateEnv(ss):
if ss.Pats == PatsType.Easy:
ss.TrainEnv.Table = etable.NewIdxView(ss.Easy)
ss.TestEnv.Table = etable.NewIdxView(ss.Easy)
elif ss.Pats == PatsType.Hard:
ss.TrainEnv.Table = etable.NewIdxView(ss.Hard)
ss.TestEnv.Table = etable.NewIdxView(ss.Hard)
elif ss.Pats == PatsType.Impossible:
ss.TrainEnv.Table = etable.NewIdxView(ss.Impossible)
ss.TestEnv.Table = etable.NewIdxView(ss.Impossible)
def ClustPlot(ss, plt, dt, colNm):
"""
ClustPlot does one cluster plot on given table column
"""
ix = etable.NewIdxView(dt)
smat = simat.SimMat()
smat.TableColStd(ix, colNm, "Name", False, metric.Euclidean)
pt = etable.Table()
clust.Plot(pt, clust.GlomStd(smat, clust.Min), smat)
plt.InitName(plt, colNm)
plt.Params.Title = "Cluster Plot of Faces " + colNm
plt.Params.XAxisCol = "X"
plt.SetTable(pt)
plt.SetColParams("X", eplot.Off, eplot.FixMin, 0, eplot.FloatMax, 0)
plt.SetColParams("Y", eplot.On, eplot.FixMin, 0, eplot.FloatMax, 0)
plt.SetColParams("Label", eplot.On, eplot.FixMin, 0, eplot.FloatMax, 0)
def UpdateEnv(ss):
if ss.Pats == PatsType.Easy:
ss.TrainEnv.Table = etable.NewIdxView(ss.Easy)
ss.TestEnv.Table = etable.NewIdxView(ss.Easy)
elif ss.Pats == PatsType.Hard:
ss.TrainEnv.Table = etable.NewIdxView(ss.Hard)
ss.TestEnv.Table = etable.NewIdxView(ss.Hard)
elif ss.Pats == PatsType.Impossible:
ss.TrainEnv.Table = etable.NewIdxView(ss.Impossible)
ss.TestEnv.Table = etable.NewIdxView(ss.Impossible)
elif ss.Pats == PatsType.Lines2:
all = etable.NewIdxView(ss.Lines2)
splits = split.Permuted(all, go.Slice_float64([.9, .1]), go.Slice_string(["Train", "Test"]))
ss.TrainEnv.Table = splits.Splits[0]
ss.TestEnv.Table = splits.Splits[1]
def LogTstEpc(ss, dt):
row = dt.Rows
dt.SetNumRows(row + 1)
trl = ss.TstTrlLog
tix = etable.NewIdxView(trl)
epc = ss.TrainEnv.Epoch.Prv # ?
# note: this shows how to use agg methods to compute summary data from another
# data table, instead of incrementing on the Sim
dt.SetCellFloat("Run", row, float(ss.TrainEnv.Run.Cur))
dt.SetCellFloat("Epoch", row, float(epc))
dt.SetCellFloat("SSE", row, agg.Sum(tix, "SSE")[0])
dt.SetCellFloat("AvgSSE", row, agg.Mean(tix, "AvgSSE")[0])
dt.SetCellFloat("PctErr", row, agg.Mean(tix, "Err")[0])
dt.SetCellFloat("PctCor", row, 1 - agg.Mean(tix, "Err")[0])
dt.SetCellFloat("CosDiff", row, agg.Mean(tix, "CosDiff")[0])
# note: essential to use Go version of update when called from another goroutine
if ss.TstEpcPlot != 0:
ss.TstEpcPlot.GoUpdate()
def UniquePatStat(ss, dt):
"""
UniquePatStat analyzes the hidden activity patterns for the single-line test inputs
to determine how many such lines have a distinct hidden pattern, as computed
from the similarity matrix across patterns
"""
hc = etensor.Float64(dt.ColByName("Hidden"))
norm.Binarize64(hc.Values, .5, 1, 0)
ix = etable.NewIdxView(dt)
ss.SimMat.TableColStd(ix, "Hidden", "TrialName", False, metric.SumSquares)
dm = ss.SimMat.Mat
nrow = dm.Dim(0)
uniq = 0
for row in range(nrow):
tsr = etensor.Float64(dm.SubSpace(go.Slice_int([row])))
nzero = 0
for vl in tsr.Values:
if vl == 0:
nzero += 1
if nzero == 1:
uniq += 1
return float(uniq)
def TestStats(ss):
dt = ss.TstTrlLog
runix = etable.NewIdxView(dt)
spl = split.GroupBy(runix, go.Slice_string(["TrialName"]))
split.Desc(spl, "Cycle")
ss.TstStats = spl.AggsToTable(etable.AddAggName)
