cogentcore · kkoreilly · Jun 30, 2025 · Jun 24, 2025 · Jun 24, 2025 · Jun 24, 2025
diff --git a/cmd/tablecat/tablecat.go b/cmd/tablecat/tablecat.go
@@ -126,10 +126,9 @@ func AvgCat(files []string) {
 		fmt.Println("No files or files are empty, exiting")
 		return
 	}
-	// todo: need meantables
-	// avgdt := stats.MeanTables(dts)
-	// tensor.SetPrecision(avgdt, LogPrec)
-	// avgdt.SaveCSV(core.Filename(Output), tensor.Tab, table.Headers)
+	avgdt := stats.MeanTables(dts)
+	tensor.SetPrecision(avgdt, LogPrec)
+	avgdt.SaveCSV(core.Filename(Output), tensor.Tab, table.Headers)
 }
 
 // AvgByColumn computes average by given column for given files

diff --git a/docs/content/tensorfs.md b/docs/content/tensorfs.md
@@ -32,7 +32,7 @@ There are also a few other variants of the `Value` functionality:
 * `ValueType` takes a `reflect.Kind` arg for the data type, which can then be a variable.
 * `SetTensor` sets a tensor to a node of given name, creating the node if needed. This is also available as the `Set` method on a directory node.
 
-`DirTable` returns a [[table]] with all the tensors under a given directory node, which can then be used for making plots or doing other forms of data analysis. This works best when each tensor has the same outer-most row dimension. The table is persistent and very efficient, using direct pointers to the underlying tensor values.
+`tensorfs.DirTable` returns a [[table]] with all the tensors under a given directory node, which can then be used for making plots or doing other forms of data analysis. This works best when each tensor has the same outer-most row dimension. The table is persistent and very efficient, using direct pointers to the underlying tensor values.
 
 ## Directories
 

diff --git a/examples/simmer/config.go b/examples/simmer/config.go
diff --git a/examples/simmer/config.goal b/examples/simmer/config.goal
@@ -17,13 +17,17 @@ type FilterResults struct {
 	// File name contains this string, e.g., "_epoch" or "_run"
 	FileContains string `width:"60"`
 
-	//	extension of files, e.g., .tsv
+	// extension of files, e.g., .tsv
 	Ext string
+
+	// if true, fetch results before opening.
+	Fetch bool
 }
 
 func (fp *FilterResults) Defaults() {
 	fp.FileContains = "_epc"
 	fp.Ext = ".tsv"
+	fp.Fetch = true
 }
 
 // SubmitParams specifies the parameters for submitting a job.
@@ -136,7 +140,11 @@ type Configuration struct {
 
 	// Server has server parameters.
 	Server ServerParams
-
+
+	// GroupColumns are the column(s) to use for grouping result data, for PlotMean.
+	// e.g., Epoch for epoch-level results.
+	GroupColumns []string
+
 	// FetchFiles is a glob expression for files to fetch from server,
 	// for Fetch command. Is *.tsv by default.
 	FetchFiles string
@@ -199,6 +207,7 @@ func (cf *Configuration) Defaults() {
 	cf.FetchFiles = "*.tsv"
 	cf.Filter.Defaults()
 	cf.TimeFormat = "2006-01-02 15:04:05 MST"
+	cf.GroupColumns = []string{"Epoch"}
 }
 
 func (cf *Configuration) Update() {

diff --git a/examples/simmer/results.go b/examples/simmer/results.go
diff --git a/examples/simmer/results.goal b/examples/simmer/results.goal
@@ -7,15 +7,18 @@ package main
 import (
 	"fmt"
 	"path/filepath"
+	"reflect"
 	"strings"
 
 	"cogentcore.org/core/base/fsx"
 	"cogentcore.org/core/core"
 	"cogentcore.org/core/styles"
 	"cogentcore.org/lab/lab"
 	"cogentcore.org/lab/plot"
+	"cogentcore.org/lab/stats/stats"
 	"cogentcore.org/lab/table"
 	"cogentcore.org/lab/tensor"
+	"cogentcore.org/lab/tensorfs"
 )
 
 // FindResult finds an existing result record for given job id and path,
@@ -86,6 +89,14 @@ func (sr *Simmer) Results() { //types:add
 		sr.Config.Filter.Ext = ".tsv"
 	}
 	lab.PromptStruct(sr, &sr.Config.Filter, "Open results data for files", func() {
+		if sr.Config.Filter.Fetch  {
+			core.MessageSnackbar(sr, "Fetching jobs..")
+			for _, jid := range jobs {
+				sr.FetchJob(jid, false)
+			}
+			core.MessageSnackbar(sr, "Fetch Jobs completed")
+			sr.UpdateSims()
+		}
 		sr.OpenResultFiles(jobs, sr.Config.Filter)
 	})
 }
@@ -140,6 +151,51 @@ func (sr *Simmer) Plot() { //types:add
 	ts.PlotTable("Plot", AggTable)
 }
 
+// PlotMean concatenates selected Results data files and generates a plot
+// of the resulting data, computing the mean over the values in 
+// [Config.GroupColumns] to group values (e.g., across Epochs).
+func (sr *Simmer) PlotMean() { //types:add
+	ts := sr.Tabs.AsLab()
+	tv := sr.ResultsTableView
+	jis := tv.SelectedIndexesList(false)
+	if len(jis) == 0 {
+		fmt.Println("No Results rows selected")
+		return
+	}
+	nc := len(sr.Config.GroupColumns)
+	rdir := "Stats/" + sr.Config.GroupColumns[nc-1] // results dir
+	var AggTable *table.Table
+	for _, i := range jis {
+		res := sr.ResultsList[i]
+		jid := res.JobID
+		label := res.Label
+		dir, _ := tensorfs.NewDir("root")
+		rdt := res.Table
+		stats.TableGroups(dir, rdt, sr.Config.GroupColumns...)
+		var fcols []string
+		for ci, cl := range rdt.Columns.Values {
+			if cl.DataType() != reflect.Float32 && cl.DataType() != reflect.Float64 {
+				continue
+			}
+			fcols = append(fcols, rdt.Columns.Keys[ci])
+		}
+		stats.TableGroupStats(dir, stats.StatMean, rdt, fcols...)
+		edir := dir.Dir(rdir)
+		sdt := tensorfs.DirTable(edir, nil)
+		dt := sdt.InsertKeyColumns("JobID", jid, "JobLabel", label) // this clones the table
+		if AggTable == nil {
+			AggTable = dt
+			plot.SetFirstStyler(dt.Columns.Values[0], func(s *plot.Style) {
+				s.Role = plot.Split
+				s.On = true
+			})
+		} else {
+			AggTable.AppendRows(dt)
+		}
+	}
+	ts.PlotTable("Plot", AggTable)
+}
+
 func (sr *Simmer) styleResults() {
 	tv := sr.ResultsTableView
 	tv.ShowIndexes = true

diff --git a/examples/simmer/simmer.go b/examples/simmer/simmer.go
@@ -246,6 +246,9 @@ func (sr *Simmer) MakeToolbar(p *tree.Plan) {
 	tree.Add(p, func(w *core.FuncButton) {
 		w.SetFunc(sr.Plot).SetIcon(icons.ShowChart)
 	})
+	tree.Add(p, func(w *core.FuncButton) {
+		w.SetFunc(sr.PlotMean).SetIcon(icons.ShowChart)
+	})
 	tree.Add(p, func(w *core.FuncButton) {
 		w.SetFunc(sr.Cancel).SetIcon(icons.Refresh)
 	})