Use tilelib to load for export and pca.

[lightning.git] / pca.go

diff --git a/pca.go b/pca.go
index bebd6765b7f06517a7e4d4131b94553c1703b4b3..67e11fc92e4905385e47ea9cb308cc86c78f5971 100644 (file)
--- a/pca.go
+++ b/pca.go
@@ -2,6 +2,7 @@ package main
 
 import (
        "bufio"
+       "context"
        "errors"
        "flag"
        "fmt"
@@ -10,7 +11,6 @@ import (
        "net/http"
        _ "net/http/pprof"
        "os"
-       "sort"
 
        "git.arvados.org/arvados.git/sdk/go/arvados"
        "github.com/james-bowman/nlp"
@@ -138,7 +138,11 @@ func (cmd *goPCA) RunCommand(prog string, args []string, stdin io.Reader, stdout
                defer input.Close()
        }
        log.Print("reading")
-       cgs, err := ReadCompactGenomes(input)
+       tilelib := tileLibrary{
+               includeNoCalls: true,
+               compactGenomes: map[string][]tileVariantID{},
+       }
+       err = tilelib.LoadGob(context.Background(), input, nil)
        if err != nil {
                return 1
        }
@@ -146,16 +150,13 @@ func (cmd *goPCA) RunCommand(prog string, args []string, stdin io.Reader, stdout
        if err != nil {
                return 1
        }
-       log.Print("sorting")
-       sort.Slice(cgs, func(i, j int) bool { return cgs[i].Name < cgs[j].Name })
 
        log.Print("converting cgs to array")
-       data, rows, cols := cgs2array(cgs)
+       data, rows, cols := cgs2array(tilelib.compactGenomes)
        if *onehot {
                log.Printf("recode one-hot: %d rows, %d cols", rows, cols)
                data, cols = recodeOnehot(data, cols)
        }
-       cgs = nil
 
        log.Printf("creating matrix backed by array: %d rows, %d cols", rows, cols)
        mtx := array2matrix(rows, cols, data).T()