file_name large_stringlengths 4 140 | prefix large_stringlengths 0 39k | suffix large_stringlengths 0 36.1k | middle large_stringlengths 0 29.4k | fim_type large_stringclasses 4
values |
|---|---|---|---|---|
main.go | package main
import (
"code.google.com/p/go.net/websocket"
"code.google.com/p/goauth2/oauth"
"code.google.com/p/google-api-go-client/mirror/v1"
"code.google.com/p/google-api-go-client/oauth2/v2"
"encoding/json"
"fmt"
picarus "github.com/bwhite/picarus/go"
"github.com/gorilla/pat"
"github.com/ugorji/go-msgpack"
"io"
"io/ioutil"
"log"
"net/http"
"strconv"
"strings"
)
const revokeEndpointFmt = "https://accounts.google.com/o/oauth2/revoke?token=%s"
func StaticServer(w http.ResponseWriter, req *http.Request) {
path := req.URL.Query().Get(":path")
if strings.ContainsAny(path, "/\\") {
return
}
http.ServeFile(w, req, "static/"+path)
}
func RootServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Got /")
content, err := ioutil.ReadFile("static/app.html")
if err != nil {
return
}
io.WriteString(w, string(content))
}
func DebugServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Debug server")
fmt.Println(req)
}
func setupUser(r *http.Request, client *http.Client, userId string) {
m, _ := mirror.New(client)
s := &mirror.Subscription{
Collection: "timeline",
UserToken: userId,
CallbackUrl: fullUrl + "/notify",
}
m.Subscriptions.Insert(s).Do()
c := &mirror.Contact{
Id: "Memento",
DisplayName: "Memento",
ImageUrls: []string{fullUrl + "/static/memento.jpg"},
}
m.Contacts.Insert(c).Do()
c = &mirror.Contact{
Id: "OpenGlass",
DisplayName: "OpenGlass",
ImageUrls: []string{fullUrl + "/static/oglogo.png"},
}
m.Contacts.Insert(c).Do()
menuItems := []*mirror.MenuItem{&mirror.MenuItem{Action: "REPLY"}, &mirror.MenuItem{Action: "TOGGLE_PINNED"}}
for _, eventName := range eventNames {
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
t := &mirror.TimelineItem{
Text: "OpenGlass",
Creator: c,
MenuItems: menuItems,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req, _ := m.Timeline.Insert(t).Do()
setUserAttribute(userId, "ogtid", req.Id)
}
// auth is the HTTP handler that redirects the user to authenticate
// with OAuth.
func authHandler(w http.ResponseWriter, r *http.Request) {
url := config(r.Host).AuthCodeURL(r.URL.RawQuery)
http.Redirect(w, r, url, http.StatusFound)
}
// oauth2callback is the handler to which Google's OAuth service redirects the
// user after they have granted the appropriate permissions.
func oauth2callbackHandler(w http.ResponseWriter, r *http.Request) {
// Create an oauth transport with a urlfetch.Transport embedded inside.
t := &oauth.Transport{Config: config(r.Host)}
// Exchange the code for access and refresh tokens.
tok, err := t.Exchange(r.FormValue("code"))
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: exchange")
return
}
o, err := oauth2.New(t.Client())
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: oauth get")
return
}
u, err := o.Userinfo.Get().Do()
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: userinfo get")
return
}
userId := fmt.Sprintf("%s_%s", strings.Split(clientId, ".")[0], u.Id)
if err = storeUserID(w, r, userId); err != nil {
w.WriteHeader(500)
LogPrintf("oauth: store userid")
return
}
userSer, err := json.Marshal(u)
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: json marshal")
return
}
storeCredential(userId, tok, string(userSer))
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func SetupHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("setup: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(401)
LogPrintf("setup: auth")
return
}
setupUser(r, t.Client(), userId)
}
// signout Revokes access for the user and removes the associated credentials from the datastore.
func signoutHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("signout: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(500)
LogPrintf("signout: auth")
return
}
req, err := http.NewRequest("GET", fmt.Sprintf(revokeEndpointFmt, t.Token.RefreshToken), nil)
response, err := http.DefaultClient.Do(req)
if err != nil {
w.WriteHeader(500)
LogPrintf("signout: revoke")
return
}
defer response.Body.Close()
storeUserID(w, r, "")
deleteCredential(userId)
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func sendImageCard(image string, text string, svc *mirror.Service) {
nt := &mirror.TimelineItem{
SpeakableText: text,
MenuItems: []*mirror.MenuItem{&mirror.MenuItem{Action: "READ_ALOUD"}, &mirror.MenuItem{Action: "DELETE"}},
Html: "<img src=\"attachment:0\" width=\"100%\" height=\"100%\">",
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(image))
_, err := req.Do()
if err != nil {
LogPrintf("sendimage: insert")
return
}
}
func getImageAttachment(conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem) ([]byte, error) {
a, err := svc.Timeline.Attachments.Get(t.Id, t.Attachments[0].Id).Do()
if err != nil {
LogPrintf("getattachment: metadata")
return nil, err
}
req, err := http.NewRequest("GET", a.ContentUrl, nil)
if err != nil |
resp, err := trans.RoundTrip(req)
if err != nil {
LogPrintf("getattachment: content")
return nil, err
}
defer resp.Body.Close()
imageData, err := ioutil.ReadAll(resp.Body)
if err != nil {
LogPrintf("getattachment: body")
return nil, err
}
return imageData, nil
}
func notifyOpenGlass(conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem, userId string) {
if !hasFlagSingle(userId, "flags", "user_openglass") {
LogPrintf("openglass: flag user_openglass")
return
}
var err error
flags, err := getUserFlags(userId, "uflags")
if err != nil {
LogPrintf("openglass: uflags")
return
}
if t.Attachments != nil && len(t.Attachments) > 0 {
imageData, err := getImageAttachment(conn, svc, trans, t)
if err != nil {
LogPrintf("openglass: attachment")
return
}
imageRow, err := PicarusApiImageUpload(conn, imageData)
if err != nil {
LogPrintf("openglass: picarus upload")
return
}
pushUserListTrim(userId, "images", imageRow, maxImages)
PicarusApiRowThumb(conn, imageRow)
if hasFlag(flags, "match_memento") {
mementoMatches, _, err := matchMementoImage(conn, imageRow, userId)
if err != nil {
LogPrintf("openglass: memento match")
} else {
for row, note := range mementoMatches {
m, err := conn.GetRow("images", row, []string{picarus.B64Dec(glassImageModel)})
if err != nil {
LogPrintf("openglass: memento get thumb")
continue
}
sendImageCard(m[picarus.B64Dec(glassImageModel)], note, svc)
}
}
}
if hasFlag(flags, "location") && hasFlag(flags, "location:streetview") {
//searchData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(locationModel))
}
if err != nil {
LogPrintf("openglass: image search")
}
// Warped image example
var imageWarped string
if hasFlag(flags, "warp") {
imageWarped, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(homographyModel))
if err != nil {
LogPrintf("openglass: image warp")
imageWarped = ""
} else {
sendImageCard(imageWarped, "", svc)
}
}
// If there is a caption, send it to the annotation task
if len(t.Text) > 0 {
if hasFlag(flags, "crowdqa") {
imageType := "full"
if strings.HasPrefix(t.Text, "augmented ") {
if len(imageWarped) > 0 {
imageWarpedData := []byte(imageWarped)
imageRowWarped, err := PicarusApiImageUpload(conn, imageWarpedData)
PicarusApiRowThumb(conn, imageRowWarped)
if err != nil {
LogPrintf("openglass: warp image upload")
} else {
imageRow = imageRowWarped
imageData = imageWarpedData
imageType = "augmented"
}
}
t.Text = t.Text[10:] // Remove "augmented "
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:question": t.Text, "meta:openglass_user": userId,
"meta:openglass_image_type": imageType}, map[string][]byte{})
if err != nil {
LogPrintf("openglass: patch image")
return
}
// TODO: Here is where we would resize the image, we can do that later
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: sync annotations")
return
}
}
} else {
if hasFlag(flags, "predict") {
confHTML := "<article><section><ul class=\"text-x-small\">"
menuItems := []*mirror.MenuItem{}
for modelName, modelRow := range predictionModels {
confMsgpack, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(modelRow))
if err != nil {
LogPrintf("openglass: predict")
return
}
var value float64
err = msgpack.Unmarshal([]byte(confMsgpack), &value, nil)
if err != nil {
LogPrintf("openglass: predict msgpack")
return
}
confHTML = confHTML + fmt.Sprintf("<li>%s: %f</li>", modelName, value)
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
menuItems = append(menuItems, &mirror.MenuItem{Action: "DELETE"})
confHTML = confHTML + "</ul></section><footer><p>Image Attributes</p></footer></article>"
nt := &mirror.TimelineItem{
Html: confHTML,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
HtmlPages: []string{"<img src=\"attachment:0\" width=\"100%\" height=\"100%\">"},
MenuItems: menuItems,
}
imageThumbData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(glassImageModel))
if err != nil {
LogPrintf("openglass: thumb")
return
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(string(imageThumbData)))
tiConf, err := req.Do()
if err != nil {
LogPrintf("openglass: predictinsert")
return
}
setUserAttribute(userId, "tid_to_row:"+tiConf.Id, imageRow)
}
}
} else {
if len(t.Text) > 0 {
if strings.HasPrefix(t.Text, "where") && hasFlag(flags, "location") {
loc, _ := svc.Locations.Get("latest").Do()
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId, "meta:latitude": strconv.FormatFloat(loc.Latitude, 'f', 16, 64),
"meta:longitude": strconv.FormatFloat(loc.Longitude, 'f', 16, 64)}, map[string][]byte{}, []picarus.Slice{})
} else {
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId}, map[string][]byte{}, []picarus.Slice{})
}
if err != nil {
LogPrintf("openglass: qa post text-only")
return
}
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: qa post text-only sync")
return
}
}
}
}
func notifyHandler(w http.ResponseWriter, r *http.Request) {
conn := picarus.Conn{Email: picarusEmail, ApiKey: picarusApiKey, Server: "https://api.picar.us"}
not := new(mirror.Notification)
if err := json.NewDecoder(r.Body).Decode(not); err != nil {
LogPrintf("notify: decode")
return
}
userId := not.UserToken
itemId := not.ItemId
fmt.Println(not)
if not.Operation == "UPDATE" {
ogTid, err := getUserAttribute(userId, "ogtid")
if err != nil {
LogPrintf("notify: ogtid")
return
}
// Annotation set by user in OpenGlass
fmt.Println(not.ItemId)
fmt.Println(ogTid)
if not.ItemId == ogTid {
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
annotationJS, err := json.Marshal(WSAnnotation{Timestamp: CurTime(), Name: vs[0], Polarity: vs[1] == "1"})
if err != nil {
LogPrintf("notify: annotationJS")
return
}
err = pushUserListTrim(userId, "annotations", string(annotationJS), 100)
if err != nil {
LogPrintf("notify: push list")
return
}
}
return
}
imageRow, err := getUserAttribute(userId, "tid_to_row:"+not.ItemId)
if err != nil {
LogPrintf("notify: tid_to_row")
return
}
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || predictionModels[vs[0]] == "" || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:userannot-" + vs[0]: vs[1]}, map[string][]byte{})
if err != nil {
LogPrintf("notify: patch annotation")
continue
}
}
return
}
if not.Operation != "INSERT" {
return
}
trans := authTransport(userId)
if trans == nil {
LogPrintf("notify: auth")
return
}
svc, err := mirror.New(trans.Client())
if err != nil {
LogPrintf("notify: mirror")
return
}
t, err := svc.Timeline.Get(itemId).Do()
if err != nil {
LogPrintf("notify: timeline item")
return
}
notifyOG := true
for _, r := range t.Recipients {
if r.Id == "Memento" {
notifyOG = false
}
}
if notifyOG {
go notifyOpenGlass(&conn, svc, trans, t, userId)
} else {
go notifyMemento(&conn, svc, trans, t, userId)
}
}
func main() {
PupilCalibrate("219250584360_109113122718379096525")
m := pat.New()
//m.Post("/", http.HandlerFunc(DebugServer))
m.Get("/map", http.HandlerFunc(MapServer))
m.Get("/search", http.HandlerFunc(MementoSearchServer))
m.Get("/static/{path}", http.HandlerFunc(StaticServer))
m.Post("/raven/{key}", http.HandlerFunc(RavenServer))
m.Post("/notify/{key}", http.HandlerFunc(NotifyServer))
m.Post("/pupil/{key}", http.HandlerFunc(PupilServer))
m.Post("/control/{action}", http.HandlerFunc(ControlServer))
m.Post("/location", http.HandlerFunc(LocationHandler))
m.Post("/setup", http.HandlerFunc(SetupHandler))
m.Post("/user/key/{type}", http.HandlerFunc(SecretKeySetupHandler))
// /auth -> google -> /oauth2callback
m.Get("/auth", http.HandlerFunc(authHandler))
m.Get("/oauth2callback", http.HandlerFunc(oauth2callbackHandler))
m.Post("/notify", http.HandlerFunc(notifyHandler))
m.Post("/signout", http.HandlerFunc(signoutHandler))
m.Post("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/flags", http.HandlerFunc(FlagsHandler))
m.Delete("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/", http.HandlerFunc(RootServer))
go pollAnnotations()
http.Handle("/ws/glass/", websocket.Handler(WSGlassHandler))
http.Handle("/ws/web", websocket.Handler(WSWebHandler))
http.Handle("/ws/web/", websocket.Handler(WSWebHandler))
http.Handle("/", m)
err := http.ListenAndServe(":16001", nil)
if err != nil {
log.Fatal("ListenAndServe: ", err)
}
}
| {
LogPrintf("getattachment: http")
return nil, err
} | conditional_block |
main.go | package main
import (
"code.google.com/p/go.net/websocket"
"code.google.com/p/goauth2/oauth"
"code.google.com/p/google-api-go-client/mirror/v1"
"code.google.com/p/google-api-go-client/oauth2/v2"
"encoding/json"
"fmt"
picarus "github.com/bwhite/picarus/go"
"github.com/gorilla/pat"
"github.com/ugorji/go-msgpack"
"io"
"io/ioutil"
"log"
"net/http"
"strconv"
"strings"
)
const revokeEndpointFmt = "https://accounts.google.com/o/oauth2/revoke?token=%s"
func StaticServer(w http.ResponseWriter, req *http.Request) {
path := req.URL.Query().Get(":path")
if strings.ContainsAny(path, "/\\") {
return
}
http.ServeFile(w, req, "static/"+path)
}
func RootServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Got /")
content, err := ioutil.ReadFile("static/app.html")
if err != nil {
return
}
io.WriteString(w, string(content))
}
func DebugServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Debug server")
fmt.Println(req)
}
func setupUser(r *http.Request, client *http.Client, userId string) {
m, _ := mirror.New(client)
s := &mirror.Subscription{
Collection: "timeline",
UserToken: userId,
CallbackUrl: fullUrl + "/notify",
}
m.Subscriptions.Insert(s).Do()
c := &mirror.Contact{
Id: "Memento",
DisplayName: "Memento",
ImageUrls: []string{fullUrl + "/static/memento.jpg"},
}
m.Contacts.Insert(c).Do()
c = &mirror.Contact{
Id: "OpenGlass",
DisplayName: "OpenGlass",
ImageUrls: []string{fullUrl + "/static/oglogo.png"},
}
m.Contacts.Insert(c).Do()
menuItems := []*mirror.MenuItem{&mirror.MenuItem{Action: "REPLY"}, &mirror.MenuItem{Action: "TOGGLE_PINNED"}}
for _, eventName := range eventNames {
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
t := &mirror.TimelineItem{
Text: "OpenGlass",
Creator: c,
MenuItems: menuItems,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req, _ := m.Timeline.Insert(t).Do()
setUserAttribute(userId, "ogtid", req.Id)
}
// auth is the HTTP handler that redirects the user to authenticate
// with OAuth.
func authHandler(w http.ResponseWriter, r *http.Request) {
url := config(r.Host).AuthCodeURL(r.URL.RawQuery)
http.Redirect(w, r, url, http.StatusFound)
}
// oauth2callback is the handler to which Google's OAuth service redirects the
// user after they have granted the appropriate permissions.
func oauth2callbackHandler(w http.ResponseWriter, r *http.Request) {
// Create an oauth transport with a urlfetch.Transport embedded inside.
t := &oauth.Transport{Config: config(r.Host)}
// Exchange the code for access and refresh tokens.
tok, err := t.Exchange(r.FormValue("code"))
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: exchange")
return
}
o, err := oauth2.New(t.Client())
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: oauth get")
return
}
u, err := o.Userinfo.Get().Do()
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: userinfo get")
return
}
userId := fmt.Sprintf("%s_%s", strings.Split(clientId, ".")[0], u.Id)
if err = storeUserID(w, r, userId); err != nil {
w.WriteHeader(500)
LogPrintf("oauth: store userid")
return | w.WriteHeader(500)
LogPrintf("oauth: json marshal")
return
}
storeCredential(userId, tok, string(userSer))
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func SetupHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("setup: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(401)
LogPrintf("setup: auth")
return
}
setupUser(r, t.Client(), userId)
}
// signout Revokes access for the user and removes the associated credentials from the datastore.
func signoutHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("signout: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(500)
LogPrintf("signout: auth")
return
}
req, err := http.NewRequest("GET", fmt.Sprintf(revokeEndpointFmt, t.Token.RefreshToken), nil)
response, err := http.DefaultClient.Do(req)
if err != nil {
w.WriteHeader(500)
LogPrintf("signout: revoke")
return
}
defer response.Body.Close()
storeUserID(w, r, "")
deleteCredential(userId)
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func sendImageCard(image string, text string, svc *mirror.Service) {
nt := &mirror.TimelineItem{
SpeakableText: text,
MenuItems: []*mirror.MenuItem{&mirror.MenuItem{Action: "READ_ALOUD"}, &mirror.MenuItem{Action: "DELETE"}},
Html: "<img src=\"attachment:0\" width=\"100%\" height=\"100%\">",
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(image))
_, err := req.Do()
if err != nil {
LogPrintf("sendimage: insert")
return
}
}
func getImageAttachment(conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem) ([]byte, error) {
a, err := svc.Timeline.Attachments.Get(t.Id, t.Attachments[0].Id).Do()
if err != nil {
LogPrintf("getattachment: metadata")
return nil, err
}
req, err := http.NewRequest("GET", a.ContentUrl, nil)
if err != nil {
LogPrintf("getattachment: http")
return nil, err
}
resp, err := trans.RoundTrip(req)
if err != nil {
LogPrintf("getattachment: content")
return nil, err
}
defer resp.Body.Close()
imageData, err := ioutil.ReadAll(resp.Body)
if err != nil {
LogPrintf("getattachment: body")
return nil, err
}
return imageData, nil
}
func notifyOpenGlass(conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem, userId string) {
if !hasFlagSingle(userId, "flags", "user_openglass") {
LogPrintf("openglass: flag user_openglass")
return
}
var err error
flags, err := getUserFlags(userId, "uflags")
if err != nil {
LogPrintf("openglass: uflags")
return
}
if t.Attachments != nil && len(t.Attachments) > 0 {
imageData, err := getImageAttachment(conn, svc, trans, t)
if err != nil {
LogPrintf("openglass: attachment")
return
}
imageRow, err := PicarusApiImageUpload(conn, imageData)
if err != nil {
LogPrintf("openglass: picarus upload")
return
}
pushUserListTrim(userId, "images", imageRow, maxImages)
PicarusApiRowThumb(conn, imageRow)
if hasFlag(flags, "match_memento") {
mementoMatches, _, err := matchMementoImage(conn, imageRow, userId)
if err != nil {
LogPrintf("openglass: memento match")
} else {
for row, note := range mementoMatches {
m, err := conn.GetRow("images", row, []string{picarus.B64Dec(glassImageModel)})
if err != nil {
LogPrintf("openglass: memento get thumb")
continue
}
sendImageCard(m[picarus.B64Dec(glassImageModel)], note, svc)
}
}
}
if hasFlag(flags, "location") && hasFlag(flags, "location:streetview") {
//searchData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(locationModel))
}
if err != nil {
LogPrintf("openglass: image search")
}
// Warped image example
var imageWarped string
if hasFlag(flags, "warp") {
imageWarped, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(homographyModel))
if err != nil {
LogPrintf("openglass: image warp")
imageWarped = ""
} else {
sendImageCard(imageWarped, "", svc)
}
}
// If there is a caption, send it to the annotation task
if len(t.Text) > 0 {
if hasFlag(flags, "crowdqa") {
imageType := "full"
if strings.HasPrefix(t.Text, "augmented ") {
if len(imageWarped) > 0 {
imageWarpedData := []byte(imageWarped)
imageRowWarped, err := PicarusApiImageUpload(conn, imageWarpedData)
PicarusApiRowThumb(conn, imageRowWarped)
if err != nil {
LogPrintf("openglass: warp image upload")
} else {
imageRow = imageRowWarped
imageData = imageWarpedData
imageType = "augmented"
}
}
t.Text = t.Text[10:] // Remove "augmented "
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:question": t.Text, "meta:openglass_user": userId,
"meta:openglass_image_type": imageType}, map[string][]byte{})
if err != nil {
LogPrintf("openglass: patch image")
return
}
// TODO: Here is where we would resize the image, we can do that later
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: sync annotations")
return
}
}
} else {
if hasFlag(flags, "predict") {
confHTML := "<article><section><ul class=\"text-x-small\">"
menuItems := []*mirror.MenuItem{}
for modelName, modelRow := range predictionModels {
confMsgpack, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(modelRow))
if err != nil {
LogPrintf("openglass: predict")
return
}
var value float64
err = msgpack.Unmarshal([]byte(confMsgpack), &value, nil)
if err != nil {
LogPrintf("openglass: predict msgpack")
return
}
confHTML = confHTML + fmt.Sprintf("<li>%s: %f</li>", modelName, value)
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
menuItems = append(menuItems, &mirror.MenuItem{Action: "DELETE"})
confHTML = confHTML + "</ul></section><footer><p>Image Attributes</p></footer></article>"
nt := &mirror.TimelineItem{
Html: confHTML,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
HtmlPages: []string{"<img src=\"attachment:0\" width=\"100%\" height=\"100%\">"},
MenuItems: menuItems,
}
imageThumbData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(glassImageModel))
if err != nil {
LogPrintf("openglass: thumb")
return
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(string(imageThumbData)))
tiConf, err := req.Do()
if err != nil {
LogPrintf("openglass: predictinsert")
return
}
setUserAttribute(userId, "tid_to_row:"+tiConf.Id, imageRow)
}
}
} else {
if len(t.Text) > 0 {
if strings.HasPrefix(t.Text, "where") && hasFlag(flags, "location") {
loc, _ := svc.Locations.Get("latest").Do()
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId, "meta:latitude": strconv.FormatFloat(loc.Latitude, 'f', 16, 64),
"meta:longitude": strconv.FormatFloat(loc.Longitude, 'f', 16, 64)}, map[string][]byte{}, []picarus.Slice{})
} else {
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId}, map[string][]byte{}, []picarus.Slice{})
}
if err != nil {
LogPrintf("openglass: qa post text-only")
return
}
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: qa post text-only sync")
return
}
}
}
}
func notifyHandler(w http.ResponseWriter, r *http.Request) {
conn := picarus.Conn{Email: picarusEmail, ApiKey: picarusApiKey, Server: "https://api.picar.us"}
not := new(mirror.Notification)
if err := json.NewDecoder(r.Body).Decode(not); err != nil {
LogPrintf("notify: decode")
return
}
userId := not.UserToken
itemId := not.ItemId
fmt.Println(not)
if not.Operation == "UPDATE" {
ogTid, err := getUserAttribute(userId, "ogtid")
if err != nil {
LogPrintf("notify: ogtid")
return
}
// Annotation set by user in OpenGlass
fmt.Println(not.ItemId)
fmt.Println(ogTid)
if not.ItemId == ogTid {
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
annotationJS, err := json.Marshal(WSAnnotation{Timestamp: CurTime(), Name: vs[0], Polarity: vs[1] == "1"})
if err != nil {
LogPrintf("notify: annotationJS")
return
}
err = pushUserListTrim(userId, "annotations", string(annotationJS), 100)
if err != nil {
LogPrintf("notify: push list")
return
}
}
return
}
imageRow, err := getUserAttribute(userId, "tid_to_row:"+not.ItemId)
if err != nil {
LogPrintf("notify: tid_to_row")
return
}
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || predictionModels[vs[0]] == "" || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:userannot-" + vs[0]: vs[1]}, map[string][]byte{})
if err != nil {
LogPrintf("notify: patch annotation")
continue
}
}
return
}
if not.Operation != "INSERT" {
return
}
trans := authTransport(userId)
if trans == nil {
LogPrintf("notify: auth")
return
}
svc, err := mirror.New(trans.Client())
if err != nil {
LogPrintf("notify: mirror")
return
}
t, err := svc.Timeline.Get(itemId).Do()
if err != nil {
LogPrintf("notify: timeline item")
return
}
notifyOG := true
for _, r := range t.Recipients {
if r.Id == "Memento" {
notifyOG = false
}
}
if notifyOG {
go notifyOpenGlass(&conn, svc, trans, t, userId)
} else {
go notifyMemento(&conn, svc, trans, t, userId)
}
}
func main() {
PupilCalibrate("219250584360_109113122718379096525")
m := pat.New()
//m.Post("/", http.HandlerFunc(DebugServer))
m.Get("/map", http.HandlerFunc(MapServer))
m.Get("/search", http.HandlerFunc(MementoSearchServer))
m.Get("/static/{path}", http.HandlerFunc(StaticServer))
m.Post("/raven/{key}", http.HandlerFunc(RavenServer))
m.Post("/notify/{key}", http.HandlerFunc(NotifyServer))
m.Post("/pupil/{key}", http.HandlerFunc(PupilServer))
m.Post("/control/{action}", http.HandlerFunc(ControlServer))
m.Post("/location", http.HandlerFunc(LocationHandler))
m.Post("/setup", http.HandlerFunc(SetupHandler))
m.Post("/user/key/{type}", http.HandlerFunc(SecretKeySetupHandler))
// /auth -> google -> /oauth2callback
m.Get("/auth", http.HandlerFunc(authHandler))
m.Get("/oauth2callback", http.HandlerFunc(oauth2callbackHandler))
m.Post("/notify", http.HandlerFunc(notifyHandler))
m.Post("/signout", http.HandlerFunc(signoutHandler))
m.Post("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/flags", http.HandlerFunc(FlagsHandler))
m.Delete("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/", http.HandlerFunc(RootServer))
go pollAnnotations()
http.Handle("/ws/glass/", websocket.Handler(WSGlassHandler))
http.Handle("/ws/web", websocket.Handler(WSWebHandler))
http.Handle("/ws/web/", websocket.Handler(WSWebHandler))
http.Handle("/", m)
err := http.ListenAndServe(":16001", nil)
if err != nil {
log.Fatal("ListenAndServe: ", err)
}
} | }
userSer, err := json.Marshal(u)
if err != nil { | random_line_split |
main.go | package main
import (
"code.google.com/p/go.net/websocket"
"code.google.com/p/goauth2/oauth"
"code.google.com/p/google-api-go-client/mirror/v1"
"code.google.com/p/google-api-go-client/oauth2/v2"
"encoding/json"
"fmt"
picarus "github.com/bwhite/picarus/go"
"github.com/gorilla/pat"
"github.com/ugorji/go-msgpack"
"io"
"io/ioutil"
"log"
"net/http"
"strconv"
"strings"
)
const revokeEndpointFmt = "https://accounts.google.com/o/oauth2/revoke?token=%s"
func StaticServer(w http.ResponseWriter, req *http.Request) {
path := req.URL.Query().Get(":path")
if strings.ContainsAny(path, "/\\") {
return
}
http.ServeFile(w, req, "static/"+path)
}
func RootServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Got /")
content, err := ioutil.ReadFile("static/app.html")
if err != nil {
return
}
io.WriteString(w, string(content))
}
func DebugServer(w http.ResponseWriter, req *http.Request) {
fmt.Println("Debug server")
fmt.Println(req)
}
func setupUser(r *http.Request, client *http.Client, userId string) {
m, _ := mirror.New(client)
s := &mirror.Subscription{
Collection: "timeline",
UserToken: userId,
CallbackUrl: fullUrl + "/notify",
}
m.Subscriptions.Insert(s).Do()
c := &mirror.Contact{
Id: "Memento",
DisplayName: "Memento",
ImageUrls: []string{fullUrl + "/static/memento.jpg"},
}
m.Contacts.Insert(c).Do()
c = &mirror.Contact{
Id: "OpenGlass",
DisplayName: "OpenGlass",
ImageUrls: []string{fullUrl + "/static/oglogo.png"},
}
m.Contacts.Insert(c).Do()
menuItems := []*mirror.MenuItem{&mirror.MenuItem{Action: "REPLY"}, &mirror.MenuItem{Action: "TOGGLE_PINNED"}}
for _, eventName := range eventNames {
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: eventName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: eventName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
t := &mirror.TimelineItem{
Text: "OpenGlass",
Creator: c,
MenuItems: menuItems,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req, _ := m.Timeline.Insert(t).Do()
setUserAttribute(userId, "ogtid", req.Id)
}
// auth is the HTTP handler that redirects the user to authenticate
// with OAuth.
func authHandler(w http.ResponseWriter, r *http.Request) {
url := config(r.Host).AuthCodeURL(r.URL.RawQuery)
http.Redirect(w, r, url, http.StatusFound)
}
// oauth2callback is the handler to which Google's OAuth service redirects the
// user after they have granted the appropriate permissions.
func oauth2callbackHandler(w http.ResponseWriter, r *http.Request) {
// Create an oauth transport with a urlfetch.Transport embedded inside.
t := &oauth.Transport{Config: config(r.Host)}
// Exchange the code for access and refresh tokens.
tok, err := t.Exchange(r.FormValue("code"))
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: exchange")
return
}
o, err := oauth2.New(t.Client())
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: oauth get")
return
}
u, err := o.Userinfo.Get().Do()
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: userinfo get")
return
}
userId := fmt.Sprintf("%s_%s", strings.Split(clientId, ".")[0], u.Id)
if err = storeUserID(w, r, userId); err != nil {
w.WriteHeader(500)
LogPrintf("oauth: store userid")
return
}
userSer, err := json.Marshal(u)
if err != nil {
w.WriteHeader(500)
LogPrintf("oauth: json marshal")
return
}
storeCredential(userId, tok, string(userSer))
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func SetupHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("setup: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(401)
LogPrintf("setup: auth")
return
}
setupUser(r, t.Client(), userId)
}
// signout Revokes access for the user and removes the associated credentials from the datastore.
func signoutHandler(w http.ResponseWriter, r *http.Request) {
userId, err := userID(r)
if err != nil || userId == "" {
w.WriteHeader(400)
LogPrintf("signout: userid")
return
}
t := authTransport(userId)
if t == nil {
w.WriteHeader(500)
LogPrintf("signout: auth")
return
}
req, err := http.NewRequest("GET", fmt.Sprintf(revokeEndpointFmt, t.Token.RefreshToken), nil)
response, err := http.DefaultClient.Do(req)
if err != nil {
w.WriteHeader(500)
LogPrintf("signout: revoke")
return
}
defer response.Body.Close()
storeUserID(w, r, "")
deleteCredential(userId)
http.Redirect(w, r, fullUrl, http.StatusFound)
}
func sendImageCard(image string, text string, svc *mirror.Service) {
nt := &mirror.TimelineItem{
SpeakableText: text,
MenuItems: []*mirror.MenuItem{&mirror.MenuItem{Action: "READ_ALOUD"}, &mirror.MenuItem{Action: "DELETE"}},
Html: "<img src=\"attachment:0\" width=\"100%\" height=\"100%\">",
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(image))
_, err := req.Do()
if err != nil {
LogPrintf("sendimage: insert")
return
}
}
func | (conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem) ([]byte, error) {
a, err := svc.Timeline.Attachments.Get(t.Id, t.Attachments[0].Id).Do()
if err != nil {
LogPrintf("getattachment: metadata")
return nil, err
}
req, err := http.NewRequest("GET", a.ContentUrl, nil)
if err != nil {
LogPrintf("getattachment: http")
return nil, err
}
resp, err := trans.RoundTrip(req)
if err != nil {
LogPrintf("getattachment: content")
return nil, err
}
defer resp.Body.Close()
imageData, err := ioutil.ReadAll(resp.Body)
if err != nil {
LogPrintf("getattachment: body")
return nil, err
}
return imageData, nil
}
func notifyOpenGlass(conn *picarus.Conn, svc *mirror.Service, trans *oauth.Transport, t *mirror.TimelineItem, userId string) {
if !hasFlagSingle(userId, "flags", "user_openglass") {
LogPrintf("openglass: flag user_openglass")
return
}
var err error
flags, err := getUserFlags(userId, "uflags")
if err != nil {
LogPrintf("openglass: uflags")
return
}
if t.Attachments != nil && len(t.Attachments) > 0 {
imageData, err := getImageAttachment(conn, svc, trans, t)
if err != nil {
LogPrintf("openglass: attachment")
return
}
imageRow, err := PicarusApiImageUpload(conn, imageData)
if err != nil {
LogPrintf("openglass: picarus upload")
return
}
pushUserListTrim(userId, "images", imageRow, maxImages)
PicarusApiRowThumb(conn, imageRow)
if hasFlag(flags, "match_memento") {
mementoMatches, _, err := matchMementoImage(conn, imageRow, userId)
if err != nil {
LogPrintf("openglass: memento match")
} else {
for row, note := range mementoMatches {
m, err := conn.GetRow("images", row, []string{picarus.B64Dec(glassImageModel)})
if err != nil {
LogPrintf("openglass: memento get thumb")
continue
}
sendImageCard(m[picarus.B64Dec(glassImageModel)], note, svc)
}
}
}
if hasFlag(flags, "location") && hasFlag(flags, "location:streetview") {
//searchData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(locationModel))
}
if err != nil {
LogPrintf("openglass: image search")
}
// Warped image example
var imageWarped string
if hasFlag(flags, "warp") {
imageWarped, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(homographyModel))
if err != nil {
LogPrintf("openglass: image warp")
imageWarped = ""
} else {
sendImageCard(imageWarped, "", svc)
}
}
// If there is a caption, send it to the annotation task
if len(t.Text) > 0 {
if hasFlag(flags, "crowdqa") {
imageType := "full"
if strings.HasPrefix(t.Text, "augmented ") {
if len(imageWarped) > 0 {
imageWarpedData := []byte(imageWarped)
imageRowWarped, err := PicarusApiImageUpload(conn, imageWarpedData)
PicarusApiRowThumb(conn, imageRowWarped)
if err != nil {
LogPrintf("openglass: warp image upload")
} else {
imageRow = imageRowWarped
imageData = imageWarpedData
imageType = "augmented"
}
}
t.Text = t.Text[10:] // Remove "augmented "
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:question": t.Text, "meta:openglass_user": userId,
"meta:openglass_image_type": imageType}, map[string][]byte{})
if err != nil {
LogPrintf("openglass: patch image")
return
}
// TODO: Here is where we would resize the image, we can do that later
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: sync annotations")
return
}
}
} else {
if hasFlag(flags, "predict") {
confHTML := "<article><section><ul class=\"text-x-small\">"
menuItems := []*mirror.MenuItem{}
for modelName, modelRow := range predictionModels {
confMsgpack, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(modelRow))
if err != nil {
LogPrintf("openglass: predict")
return
}
var value float64
err = msgpack.Unmarshal([]byte(confMsgpack), &value, nil)
if err != nil {
LogPrintf("openglass: predict msgpack")
return
}
confHTML = confHTML + fmt.Sprintf("<li>%s: %f</li>", modelName, value)
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 1", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_plus.png"}}})
menuItems = append(menuItems, &mirror.MenuItem{Action: "CUSTOM", Id: modelName + " 0", Values: []*mirror.MenuValue{&mirror.MenuValue{DisplayName: modelName, IconUrl: fullUrl + "/static/icon_minus.png"}}})
}
menuItems = append(menuItems, &mirror.MenuItem{Action: "DELETE"})
confHTML = confHTML + "</ul></section><footer><p>Image Attributes</p></footer></article>"
nt := &mirror.TimelineItem{
Html: confHTML,
Notification: &mirror.NotificationConfig{Level: "DEFAULT"},
HtmlPages: []string{"<img src=\"attachment:0\" width=\"100%\" height=\"100%\">"},
MenuItems: menuItems,
}
imageThumbData, err := PicarusApiModel(conn, imageRow, picarus.B64Dec(glassImageModel))
if err != nil {
LogPrintf("openglass: thumb")
return
}
req := svc.Timeline.Insert(nt)
req.Media(strings.NewReader(string(imageThumbData)))
tiConf, err := req.Do()
if err != nil {
LogPrintf("openglass: predictinsert")
return
}
setUserAttribute(userId, "tid_to_row:"+tiConf.Id, imageRow)
}
}
} else {
if len(t.Text) > 0 {
if strings.HasPrefix(t.Text, "where") && hasFlag(flags, "location") {
loc, _ := svc.Locations.Get("latest").Do()
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId, "meta:latitude": strconv.FormatFloat(loc.Latitude, 'f', 16, 64),
"meta:longitude": strconv.FormatFloat(loc.Longitude, 'f', 16, 64)}, map[string][]byte{}, []picarus.Slice{})
} else {
_, err = conn.PostTable("images", map[string]string{"meta:question": t.Text, "meta:openglass_user": userId}, map[string][]byte{}, []picarus.Slice{})
}
if err != nil {
LogPrintf("openglass: qa post text-only")
return
}
_, err = conn.PostRow("jobs", annotationTask, map[string]string{"action": "io/annotation/sync"})
if err != nil {
LogPrintf("openglass: qa post text-only sync")
return
}
}
}
}
func notifyHandler(w http.ResponseWriter, r *http.Request) {
conn := picarus.Conn{Email: picarusEmail, ApiKey: picarusApiKey, Server: "https://api.picar.us"}
not := new(mirror.Notification)
if err := json.NewDecoder(r.Body).Decode(not); err != nil {
LogPrintf("notify: decode")
return
}
userId := not.UserToken
itemId := not.ItemId
fmt.Println(not)
if not.Operation == "UPDATE" {
ogTid, err := getUserAttribute(userId, "ogtid")
if err != nil {
LogPrintf("notify: ogtid")
return
}
// Annotation set by user in OpenGlass
fmt.Println(not.ItemId)
fmt.Println(ogTid)
if not.ItemId == ogTid {
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
annotationJS, err := json.Marshal(WSAnnotation{Timestamp: CurTime(), Name: vs[0], Polarity: vs[1] == "1"})
if err != nil {
LogPrintf("notify: annotationJS")
return
}
err = pushUserListTrim(userId, "annotations", string(annotationJS), 100)
if err != nil {
LogPrintf("notify: push list")
return
}
}
return
}
imageRow, err := getUserAttribute(userId, "tid_to_row:"+not.ItemId)
if err != nil {
LogPrintf("notify: tid_to_row")
return
}
for _, v := range not.UserActions {
vs := strings.Split(v.Payload, " ")
if len(vs) != 2 || predictionModels[vs[0]] == "" || len(vs[1]) != 1 {
LogPrintf("notify: payload")
continue
}
_, err = conn.PatchRow("images", imageRow, map[string]string{"meta:userannot-" + vs[0]: vs[1]}, map[string][]byte{})
if err != nil {
LogPrintf("notify: patch annotation")
continue
}
}
return
}
if not.Operation != "INSERT" {
return
}
trans := authTransport(userId)
if trans == nil {
LogPrintf("notify: auth")
return
}
svc, err := mirror.New(trans.Client())
if err != nil {
LogPrintf("notify: mirror")
return
}
t, err := svc.Timeline.Get(itemId).Do()
if err != nil {
LogPrintf("notify: timeline item")
return
}
notifyOG := true
for _, r := range t.Recipients {
if r.Id == "Memento" {
notifyOG = false
}
}
if notifyOG {
go notifyOpenGlass(&conn, svc, trans, t, userId)
} else {
go notifyMemento(&conn, svc, trans, t, userId)
}
}
func main() {
PupilCalibrate("219250584360_109113122718379096525")
m := pat.New()
//m.Post("/", http.HandlerFunc(DebugServer))
m.Get("/map", http.HandlerFunc(MapServer))
m.Get("/search", http.HandlerFunc(MementoSearchServer))
m.Get("/static/{path}", http.HandlerFunc(StaticServer))
m.Post("/raven/{key}", http.HandlerFunc(RavenServer))
m.Post("/notify/{key}", http.HandlerFunc(NotifyServer))
m.Post("/pupil/{key}", http.HandlerFunc(PupilServer))
m.Post("/control/{action}", http.HandlerFunc(ControlServer))
m.Post("/location", http.HandlerFunc(LocationHandler))
m.Post("/setup", http.HandlerFunc(SetupHandler))
m.Post("/user/key/{type}", http.HandlerFunc(SecretKeySetupHandler))
// /auth -> google -> /oauth2callback
m.Get("/auth", http.HandlerFunc(authHandler))
m.Get("/oauth2callback", http.HandlerFunc(oauth2callbackHandler))
m.Post("/notify", http.HandlerFunc(notifyHandler))
m.Post("/signout", http.HandlerFunc(signoutHandler))
m.Post("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/flags", http.HandlerFunc(FlagsHandler))
m.Delete("/flags", http.HandlerFunc(FlagsHandler))
m.Get("/", http.HandlerFunc(RootServer))
go pollAnnotations()
http.Handle("/ws/glass/", websocket.Handler(WSGlassHandler))
http.Handle("/ws/web", websocket.Handler(WSWebHandler))
http.Handle("/ws/web/", websocket.Handler(WSWebHandler))
http.Handle("/", m)
err := http.ListenAndServe(":16001", nil)
if err != nil {
log.Fatal("ListenAndServe: ", err)
}
}
| getImageAttachment | identifier_name |
snapshots.go | /*
Copyright The containerd Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package snapshots
import (
gocontext "context"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"strconv"
"strings"
"text/tabwriter"
"time"
"github.com/containerd/containerd/cmd/ctr/commands"
"github.com/containerd/containerd/content"
"github.com/containerd/containerd/diff"
"github.com/containerd/containerd/log"
"github.com/containerd/containerd/mount"
"github.com/containerd/containerd/pkg/progress"
"github.com/containerd/containerd/rootfs"
"github.com/containerd/containerd/snapshots"
digest "github.com/opencontainers/go-digest"
ocispec "github.com/opencontainers/image-spec/specs-go/v1"
"github.com/urfave/cli"
)
// Command is the cli command for managing snapshots
var Command = cli.Command{
Name: "snapshots",
Aliases: []string{"snapshot"},
Usage: "Manage snapshots",
Flags: commands.SnapshotterFlags,
Subcommands: cli.Commands{
commitCommand,
diffCommand,
infoCommand,
listCommand,
mountCommand,
prepareCommand,
removeCommand,
setLabelCommand,
treeCommand,
unpackCommand,
usageCommand,
viewCommand,
},
}
var listCommand = cli.Command{
Name: "list",
Aliases: []string{"ls"},
Usage: "List snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tPARENT\tKIND\t")
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
fmt.Fprintf(tw, "%v\t%v\t%v\t\n",
info.Name,
info.Parent,
info.Kind)
return nil
}); err != nil {
return err
}
return tw.Flush()
},
}
var diffCommand = cli.Command{
Name: "diff",
Usage: "Get the diff of two snapshots. the default second snapshot is the first snapshot's parent.",
ArgsUsage: "[flags] <idA> [<idB>]",
Flags: append([]cli.Flag{
cli.StringFlag{
Name: "media-type",
Usage: "Media type to use for creating diff",
Value: ocispec.MediaTypeImageLayerGzip,
},
cli.StringFlag{
Name: "ref",
Usage: "Content upload reference to use",
},
cli.BoolFlag{
Name: "keep",
Usage: "Keep diff content. up to creator to delete it.",
},
}, commands.LabelFlag),
Action: func(context *cli.Context) error {
var (
idA = context.Args().First()
idB = context.Args().Get(1)
)
if idA == "" {
return errors.New("snapshot id must be provided")
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
ctx, done, err := client.WithLease(ctx)
if err != nil {
return err
}
defer done(ctx)
var desc ocispec.Descriptor
labels := commands.LabelArgs(context.StringSlice("label"))
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
if context.Bool("keep") {
labels["containerd.io/gc.root"] = time.Now().UTC().Format(time.RFC3339)
}
opts := []diff.Opt{
diff.WithMediaType(context.String("media-type")),
diff.WithReference(context.String("ref")),
diff.WithLabels(labels),
}
// SOURCE_DATE_EPOCH is propagated via the ctx, so no need to specify diff.WithSourceDateEpoch here
if idB == "" {
desc, err = rootfs.CreateDiff(ctx, idA, snapshotter, client.DiffService(), opts...)
if err != nil {
return err
}
} else {
desc, err = withMounts(ctx, idA, snapshotter, func(a []mount.Mount) (ocispec.Descriptor, error) {
return withMounts(ctx, idB, snapshotter, func(b []mount.Mount) (ocispec.Descriptor, error) {
return client.DiffService().Compare(ctx, a, b, opts...)
})
})
if err != nil {
return err
}
}
ra, err := client.ContentStore().ReaderAt(ctx, desc)
if err != nil {
return err
}
defer ra.Close()
_, err = io.Copy(os.Stdout, content.NewReader(ra))
return err
},
}
func withMounts(ctx gocontext.Context, id string, sn snapshots.Snapshotter, f func(mounts []mount.Mount) (ocispec.Descriptor, error)) (ocispec.Descriptor, error) {
var mounts []mount.Mount
info, err := sn.Stat(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
if info.Kind == snapshots.KindActive {
mounts, err = sn.Mounts(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
} else {
key := fmt.Sprintf("%s-view-key", id)
mounts, err = sn.View(ctx, key, id)
if err != nil {
return ocispec.Descriptor{}, err
}
defer sn.Remove(ctx, key)
}
return f(mounts)
}
var usageCommand = cli.Command{
Name: "usage",
Usage: "Usage snapshots",
ArgsUsage: "[flags] [<key>, ...]",
Flags: []cli.Flag{
cli.BoolFlag{
Name: "b",
Usage: "Display size in bytes",
},
},
Action: func(context *cli.Context) error {
var displaySize func(int64) string
if context.Bool("b") {
displaySize = func(s int64) string {
return strconv.FormatInt(s, 10)
}
} else {
displaySize = func(s int64) string {
return progress.Bytes(s).String()
}
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tSIZE\tINODES\t")
if context.NArg() == 0 {
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
usage, err := snapshotter.Usage(ctx, info.Name)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", info.Name, displaySize(usage.Size), usage.Inodes)
return nil
}); err != nil {
return err
}
} else {
for _, id := range context.Args() {
usage, err := snapshotter.Usage(ctx, id)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", id, displaySize(usage.Size), usage.Inodes)
}
}
return tw.Flush()
},
}
var removeCommand = cli.Command{
Name: "delete",
Aliases: []string{"del", "remove", "rm"},
ArgsUsage: "<key> [<key>, ...]",
Usage: "Remove snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
for _, key := range context.Args() {
err = snapshotter.Remove(ctx, key)
if err != nil {
return fmt.Errorf("failed to remove %q: %w", key, err)
}
}
return nil
},
}
var prepareCommand = cli.Command{
Name: "prepare",
Usage: "Prepare a snapshot from a committed snapshot", | Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
mounts, err := snapshotter.Prepare(ctx, key, parent, snapshots.WithLabels(labels))
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var viewCommand = cli.Command{
Name: "view",
Usage: "Create a read-only snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.View(ctx, key, parent)
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var mountCommand = cli.Command{
Name: "mounts",
Aliases: []string{"m", "mount"},
Usage: "Mount gets mount commands for the snapshots",
ArgsUsage: "<target> <key>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.Args().Get(0)
key = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.Mounts(ctx, key)
if err != nil {
return err
}
printMounts(target, mounts)
return nil
},
}
var commitCommand = cli.Command{
Name: "commit",
Usage: "Commit an active snapshot into the provided name",
ArgsUsage: "<key> <active>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
key = context.Args().Get(0)
active = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
return snapshotter.Commit(ctx, key, active, snapshots.WithLabels(labels))
},
}
var treeCommand = cli.Command{
Name: "tree",
Usage: "Display tree view of snapshot branches",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tree = newSnapshotTree()
)
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
// Get or create node and add node details
tree.add(info)
return nil
}); err != nil {
return err
}
printTree(tree)
return nil
},
}
var infoCommand = cli.Command{
Name: "info",
Usage: "Get info about a snapshot",
ArgsUsage: "<key>",
Action: func(context *cli.Context) error {
if context.NArg() != 1 {
return cli.ShowSubcommandHelp(context)
}
key := context.Args().Get(0)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info, err := snapshotter.Stat(ctx, key)
if err != nil {
return err
}
commands.PrintAsJSON(info)
return nil
},
}
var setLabelCommand = cli.Command{
Name: "label",
Usage: "Add labels to content",
ArgsUsage: "<name> [<label>=<value> ...]",
Description: "labels snapshots in the snapshotter",
Action: func(context *cli.Context) error {
key, labels := commands.ObjectWithLabelArgs(context)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info := snapshots.Info{
Name: key,
Labels: map[string]string{},
}
var paths []string
for k, v := range labels {
paths = append(paths, fmt.Sprintf("labels.%s", k))
if v != "" {
info.Labels[k] = v
}
}
// Nothing updated, do no clear
if len(paths) == 0 {
info, err = snapshotter.Stat(ctx, info.Name)
} else {
info, err = snapshotter.Update(ctx, info, paths...)
}
if err != nil {
return err
}
var labelStrings []string
for k, v := range info.Labels {
labelStrings = append(labelStrings, fmt.Sprintf("%s=%s", k, v))
}
fmt.Println(strings.Join(labelStrings, ","))
return nil
},
}
var unpackCommand = cli.Command{
Name: "unpack",
Usage: "Unpack applies layers from a manifest to a snapshot",
ArgsUsage: "[flags] <digest>",
Flags: commands.SnapshotterFlags,
Action: func(context *cli.Context) error {
dgst, err := digest.Parse(context.Args().First())
if err != nil {
return err
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
log.G(ctx).Debugf("unpacking layers from manifest %s", dgst.String())
// TODO: Support unpack by name
images, err := client.ListImages(ctx)
if err != nil {
return err
}
var unpacked bool
for _, image := range images {
if image.Target().Digest == dgst {
fmt.Printf("unpacking %s (%s)...", dgst, image.Target().MediaType)
if err := image.Unpack(ctx, context.String("snapshotter")); err != nil {
fmt.Println()
return err
}
fmt.Println("done")
unpacked = true
break
}
}
if !unpacked {
return errors.New("manifest not found")
}
// TODO: Get rootfs from Image
//log.G(ctx).Infof("chain ID: %s", chainID.String())
return nil
},
}
type snapshotTree struct {
nodes []*snapshotTreeNode
index map[string]*snapshotTreeNode
}
func newSnapshotTree() *snapshotTree {
return &snapshotTree{
index: make(map[string]*snapshotTreeNode),
}
}
type snapshotTreeNode struct {
info snapshots.Info
children []string
}
func (st *snapshotTree) add(info snapshots.Info) *snapshotTreeNode {
entry, ok := st.index[info.Name]
if !ok {
entry = &snapshotTreeNode{info: info}
st.nodes = append(st.nodes, entry)
st.index[info.Name] = entry
} else {
entry.info = info // update info if we created placeholder
}
if info.Parent != "" {
pn := st.get(info.Parent)
if pn == nil {
// create a placeholder
pn = st.add(snapshots.Info{Name: info.Parent})
}
pn.children = append(pn.children, info.Name)
}
return entry
}
func (st *snapshotTree) get(name string) *snapshotTreeNode {
return st.index[name]
}
func printTree(st *snapshotTree) {
for _, node := range st.nodes {
// Print for root(parent-less) nodes only
if node.info.Parent == "" {
printNode(node.info.Name, st, 0)
}
}
}
func printNode(name string, tree *snapshotTree, level int) {
node := tree.index[name]
prefix := strings.Repeat(" ", level)
if level > 0 {
prefix += "\\_"
}
fmt.Printf(prefix+" %s\n", node.info.Name)
level++
for _, child := range node.children {
printNode(child, tree, level)
}
}
func printMounts(target string, mounts []mount.Mount) {
// FIXME: This is specific to Unix
for _, m := range mounts {
fmt.Printf("mount -t %s %s %s -o %s\n", m.Type, m.Source, filepath.Join(target, m.Target), strings.Join(m.Options, ","))
}
} | ArgsUsage: "[flags] <key> [<parent>]", | random_line_split |
snapshots.go | /*
Copyright The containerd Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package snapshots
import (
gocontext "context"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"strconv"
"strings"
"text/tabwriter"
"time"
"github.com/containerd/containerd/cmd/ctr/commands"
"github.com/containerd/containerd/content"
"github.com/containerd/containerd/diff"
"github.com/containerd/containerd/log"
"github.com/containerd/containerd/mount"
"github.com/containerd/containerd/pkg/progress"
"github.com/containerd/containerd/rootfs"
"github.com/containerd/containerd/snapshots"
digest "github.com/opencontainers/go-digest"
ocispec "github.com/opencontainers/image-spec/specs-go/v1"
"github.com/urfave/cli"
)
// Command is the cli command for managing snapshots
var Command = cli.Command{
Name: "snapshots",
Aliases: []string{"snapshot"},
Usage: "Manage snapshots",
Flags: commands.SnapshotterFlags,
Subcommands: cli.Commands{
commitCommand,
diffCommand,
infoCommand,
listCommand,
mountCommand,
prepareCommand,
removeCommand,
setLabelCommand,
treeCommand,
unpackCommand,
usageCommand,
viewCommand,
},
}
var listCommand = cli.Command{
Name: "list",
Aliases: []string{"ls"},
Usage: "List snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tPARENT\tKIND\t")
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
fmt.Fprintf(tw, "%v\t%v\t%v\t\n",
info.Name,
info.Parent,
info.Kind)
return nil
}); err != nil {
return err
}
return tw.Flush()
},
}
var diffCommand = cli.Command{
Name: "diff",
Usage: "Get the diff of two snapshots. the default second snapshot is the first snapshot's parent.",
ArgsUsage: "[flags] <idA> [<idB>]",
Flags: append([]cli.Flag{
cli.StringFlag{
Name: "media-type",
Usage: "Media type to use for creating diff",
Value: ocispec.MediaTypeImageLayerGzip,
},
cli.StringFlag{
Name: "ref",
Usage: "Content upload reference to use",
},
cli.BoolFlag{
Name: "keep",
Usage: "Keep diff content. up to creator to delete it.",
},
}, commands.LabelFlag),
Action: func(context *cli.Context) error {
var (
idA = context.Args().First()
idB = context.Args().Get(1)
)
if idA == "" {
return errors.New("snapshot id must be provided")
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
ctx, done, err := client.WithLease(ctx)
if err != nil {
return err
}
defer done(ctx)
var desc ocispec.Descriptor
labels := commands.LabelArgs(context.StringSlice("label"))
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
if context.Bool("keep") {
labels["containerd.io/gc.root"] = time.Now().UTC().Format(time.RFC3339)
}
opts := []diff.Opt{
diff.WithMediaType(context.String("media-type")),
diff.WithReference(context.String("ref")),
diff.WithLabels(labels),
}
// SOURCE_DATE_EPOCH is propagated via the ctx, so no need to specify diff.WithSourceDateEpoch here
if idB == "" {
desc, err = rootfs.CreateDiff(ctx, idA, snapshotter, client.DiffService(), opts...)
if err != nil {
return err
}
} else {
desc, err = withMounts(ctx, idA, snapshotter, func(a []mount.Mount) (ocispec.Descriptor, error) {
return withMounts(ctx, idB, snapshotter, func(b []mount.Mount) (ocispec.Descriptor, error) {
return client.DiffService().Compare(ctx, a, b, opts...)
})
})
if err != nil {
return err
}
}
ra, err := client.ContentStore().ReaderAt(ctx, desc)
if err != nil {
return err
}
defer ra.Close()
_, err = io.Copy(os.Stdout, content.NewReader(ra))
return err
},
}
func withMounts(ctx gocontext.Context, id string, sn snapshots.Snapshotter, f func(mounts []mount.Mount) (ocispec.Descriptor, error)) (ocispec.Descriptor, error) {
var mounts []mount.Mount
info, err := sn.Stat(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
if info.Kind == snapshots.KindActive {
mounts, err = sn.Mounts(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
} else {
key := fmt.Sprintf("%s-view-key", id)
mounts, err = sn.View(ctx, key, id)
if err != nil {
return ocispec.Descriptor{}, err
}
defer sn.Remove(ctx, key)
}
return f(mounts)
}
var usageCommand = cli.Command{
Name: "usage",
Usage: "Usage snapshots",
ArgsUsage: "[flags] [<key>, ...]",
Flags: []cli.Flag{
cli.BoolFlag{
Name: "b",
Usage: "Display size in bytes",
},
},
Action: func(context *cli.Context) error {
var displaySize func(int64) string
if context.Bool("b") {
displaySize = func(s int64) string {
return strconv.FormatInt(s, 10)
}
} else {
displaySize = func(s int64) string {
return progress.Bytes(s).String()
}
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tSIZE\tINODES\t")
if context.NArg() == 0 {
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
usage, err := snapshotter.Usage(ctx, info.Name)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", info.Name, displaySize(usage.Size), usage.Inodes)
return nil
}); err != nil {
return err
}
} else {
for _, id := range context.Args() {
usage, err := snapshotter.Usage(ctx, id)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", id, displaySize(usage.Size), usage.Inodes)
}
}
return tw.Flush()
},
}
var removeCommand = cli.Command{
Name: "delete",
Aliases: []string{"del", "remove", "rm"},
ArgsUsage: "<key> [<key>, ...]",
Usage: "Remove snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
for _, key := range context.Args() {
err = snapshotter.Remove(ctx, key)
if err != nil {
return fmt.Errorf("failed to remove %q: %w", key, err)
}
}
return nil
},
}
var prepareCommand = cli.Command{
Name: "prepare",
Usage: "Prepare a snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
mounts, err := snapshotter.Prepare(ctx, key, parent, snapshots.WithLabels(labels))
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var viewCommand = cli.Command{
Name: "view",
Usage: "Create a read-only snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.View(ctx, key, parent)
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var mountCommand = cli.Command{
Name: "mounts",
Aliases: []string{"m", "mount"},
Usage: "Mount gets mount commands for the snapshots",
ArgsUsage: "<target> <key>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.Args().Get(0)
key = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.Mounts(ctx, key)
if err != nil {
return err
}
printMounts(target, mounts)
return nil
},
}
var commitCommand = cli.Command{
Name: "commit",
Usage: "Commit an active snapshot into the provided name",
ArgsUsage: "<key> <active>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
key = context.Args().Get(0)
active = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
return snapshotter.Commit(ctx, key, active, snapshots.WithLabels(labels))
},
}
var treeCommand = cli.Command{
Name: "tree",
Usage: "Display tree view of snapshot branches",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tree = newSnapshotTree()
)
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
// Get or create node and add node details
tree.add(info)
return nil
}); err != nil {
return err
}
printTree(tree)
return nil
},
}
var infoCommand = cli.Command{
Name: "info",
Usage: "Get info about a snapshot",
ArgsUsage: "<key>",
Action: func(context *cli.Context) error {
if context.NArg() != 1 {
return cli.ShowSubcommandHelp(context)
}
key := context.Args().Get(0)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info, err := snapshotter.Stat(ctx, key)
if err != nil {
return err
}
commands.PrintAsJSON(info)
return nil
},
}
var setLabelCommand = cli.Command{
Name: "label",
Usage: "Add labels to content",
ArgsUsage: "<name> [<label>=<value> ...]",
Description: "labels snapshots in the snapshotter",
Action: func(context *cli.Context) error {
key, labels := commands.ObjectWithLabelArgs(context)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info := snapshots.Info{
Name: key,
Labels: map[string]string{},
}
var paths []string
for k, v := range labels {
paths = append(paths, fmt.Sprintf("labels.%s", k))
if v != "" {
info.Labels[k] = v
}
}
// Nothing updated, do no clear
if len(paths) == 0 {
info, err = snapshotter.Stat(ctx, info.Name)
} else {
info, err = snapshotter.Update(ctx, info, paths...)
}
if err != nil {
return err
}
var labelStrings []string
for k, v := range info.Labels {
labelStrings = append(labelStrings, fmt.Sprintf("%s=%s", k, v))
}
fmt.Println(strings.Join(labelStrings, ","))
return nil
},
}
var unpackCommand = cli.Command{
Name: "unpack",
Usage: "Unpack applies layers from a manifest to a snapshot",
ArgsUsage: "[flags] <digest>",
Flags: commands.SnapshotterFlags,
Action: func(context *cli.Context) error {
dgst, err := digest.Parse(context.Args().First())
if err != nil {
return err
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
log.G(ctx).Debugf("unpacking layers from manifest %s", dgst.String())
// TODO: Support unpack by name
images, err := client.ListImages(ctx)
if err != nil {
return err
}
var unpacked bool
for _, image := range images {
if image.Target().Digest == dgst {
fmt.Printf("unpacking %s (%s)...", dgst, image.Target().MediaType)
if err := image.Unpack(ctx, context.String("snapshotter")); err != nil {
fmt.Println()
return err
}
fmt.Println("done")
unpacked = true
break
}
}
if !unpacked {
return errors.New("manifest not found")
}
// TODO: Get rootfs from Image
//log.G(ctx).Infof("chain ID: %s", chainID.String())
return nil
},
}
type snapshotTree struct {
nodes []*snapshotTreeNode
index map[string]*snapshotTreeNode
}
func newSnapshotTree() *snapshotTree {
return &snapshotTree{
index: make(map[string]*snapshotTreeNode),
}
}
type snapshotTreeNode struct {
info snapshots.Info
children []string
}
func (st *snapshotTree) add(info snapshots.Info) *snapshotTreeNode {
entry, ok := st.index[info.Name]
if !ok {
entry = &snapshotTreeNode{info: info}
st.nodes = append(st.nodes, entry)
st.index[info.Name] = entry
} else {
entry.info = info // update info if we created placeholder
}
if info.Parent != "" {
pn := st.get(info.Parent)
if pn == nil {
// create a placeholder
pn = st.add(snapshots.Info{Name: info.Parent})
}
pn.children = append(pn.children, info.Name)
}
return entry
}
func (st *snapshotTree) get(name string) *snapshotTreeNode {
return st.index[name]
}
func printTree(st *snapshotTree) {
for _, node := range st.nodes {
// Print for root(parent-less) nodes only
if node.info.Parent == "" {
printNode(node.info.Name, st, 0)
}
}
}
func printNode(name string, tree *snapshotTree, level int) {
node := tree.index[name]
prefix := strings.Repeat(" ", level)
if level > 0 {
prefix += "\\_"
}
fmt.Printf(prefix+" %s\n", node.info.Name)
level++
for _, child := range node.children {
printNode(child, tree, level)
}
}
func printMounts(target string, mounts []mount.Mount) | {
// FIXME: This is specific to Unix
for _, m := range mounts {
fmt.Printf("mount -t %s %s %s -o %s\n", m.Type, m.Source, filepath.Join(target, m.Target), strings.Join(m.Options, ","))
}
} | identifier_body | |
snapshots.go | /*
Copyright The containerd Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package snapshots
import (
gocontext "context"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"strconv"
"strings"
"text/tabwriter"
"time"
"github.com/containerd/containerd/cmd/ctr/commands"
"github.com/containerd/containerd/content"
"github.com/containerd/containerd/diff"
"github.com/containerd/containerd/log"
"github.com/containerd/containerd/mount"
"github.com/containerd/containerd/pkg/progress"
"github.com/containerd/containerd/rootfs"
"github.com/containerd/containerd/snapshots"
digest "github.com/opencontainers/go-digest"
ocispec "github.com/opencontainers/image-spec/specs-go/v1"
"github.com/urfave/cli"
)
// Command is the cli command for managing snapshots
var Command = cli.Command{
Name: "snapshots",
Aliases: []string{"snapshot"},
Usage: "Manage snapshots",
Flags: commands.SnapshotterFlags,
Subcommands: cli.Commands{
commitCommand,
diffCommand,
infoCommand,
listCommand,
mountCommand,
prepareCommand,
removeCommand,
setLabelCommand,
treeCommand,
unpackCommand,
usageCommand,
viewCommand,
},
}
var listCommand = cli.Command{
Name: "list",
Aliases: []string{"ls"},
Usage: "List snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tPARENT\tKIND\t")
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
fmt.Fprintf(tw, "%v\t%v\t%v\t\n",
info.Name,
info.Parent,
info.Kind)
return nil
}); err != nil {
return err
}
return tw.Flush()
},
}
var diffCommand = cli.Command{
Name: "diff",
Usage: "Get the diff of two snapshots. the default second snapshot is the first snapshot's parent.",
ArgsUsage: "[flags] <idA> [<idB>]",
Flags: append([]cli.Flag{
cli.StringFlag{
Name: "media-type",
Usage: "Media type to use for creating diff",
Value: ocispec.MediaTypeImageLayerGzip,
},
cli.StringFlag{
Name: "ref",
Usage: "Content upload reference to use",
},
cli.BoolFlag{
Name: "keep",
Usage: "Keep diff content. up to creator to delete it.",
},
}, commands.LabelFlag),
Action: func(context *cli.Context) error {
var (
idA = context.Args().First()
idB = context.Args().Get(1)
)
if idA == "" {
return errors.New("snapshot id must be provided")
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
ctx, done, err := client.WithLease(ctx)
if err != nil {
return err
}
defer done(ctx)
var desc ocispec.Descriptor
labels := commands.LabelArgs(context.StringSlice("label"))
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
if context.Bool("keep") {
labels["containerd.io/gc.root"] = time.Now().UTC().Format(time.RFC3339)
}
opts := []diff.Opt{
diff.WithMediaType(context.String("media-type")),
diff.WithReference(context.String("ref")),
diff.WithLabels(labels),
}
// SOURCE_DATE_EPOCH is propagated via the ctx, so no need to specify diff.WithSourceDateEpoch here
if idB == "" {
desc, err = rootfs.CreateDiff(ctx, idA, snapshotter, client.DiffService(), opts...)
if err != nil {
return err
}
} else {
desc, err = withMounts(ctx, idA, snapshotter, func(a []mount.Mount) (ocispec.Descriptor, error) {
return withMounts(ctx, idB, snapshotter, func(b []mount.Mount) (ocispec.Descriptor, error) {
return client.DiffService().Compare(ctx, a, b, opts...)
})
})
if err != nil {
return err
}
}
ra, err := client.ContentStore().ReaderAt(ctx, desc)
if err != nil {
return err
}
defer ra.Close()
_, err = io.Copy(os.Stdout, content.NewReader(ra))
return err
},
}
func withMounts(ctx gocontext.Context, id string, sn snapshots.Snapshotter, f func(mounts []mount.Mount) (ocispec.Descriptor, error)) (ocispec.Descriptor, error) {
var mounts []mount.Mount
info, err := sn.Stat(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
if info.Kind == snapshots.KindActive {
mounts, err = sn.Mounts(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
} else {
key := fmt.Sprintf("%s-view-key", id)
mounts, err = sn.View(ctx, key, id)
if err != nil {
return ocispec.Descriptor{}, err
}
defer sn.Remove(ctx, key)
}
return f(mounts)
}
var usageCommand = cli.Command{
Name: "usage",
Usage: "Usage snapshots",
ArgsUsage: "[flags] [<key>, ...]",
Flags: []cli.Flag{
cli.BoolFlag{
Name: "b",
Usage: "Display size in bytes",
},
},
Action: func(context *cli.Context) error {
var displaySize func(int64) string
if context.Bool("b") {
displaySize = func(s int64) string {
return strconv.FormatInt(s, 10)
}
} else {
displaySize = func(s int64) string {
return progress.Bytes(s).String()
}
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tSIZE\tINODES\t")
if context.NArg() == 0 {
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
usage, err := snapshotter.Usage(ctx, info.Name)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", info.Name, displaySize(usage.Size), usage.Inodes)
return nil
}); err != nil {
return err
}
} else {
for _, id := range context.Args() {
usage, err := snapshotter.Usage(ctx, id)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", id, displaySize(usage.Size), usage.Inodes)
}
}
return tw.Flush()
},
}
var removeCommand = cli.Command{
Name: "delete",
Aliases: []string{"del", "remove", "rm"},
ArgsUsage: "<key> [<key>, ...]",
Usage: "Remove snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
for _, key := range context.Args() {
err = snapshotter.Remove(ctx, key)
if err != nil {
return fmt.Errorf("failed to remove %q: %w", key, err)
}
}
return nil
},
}
var prepareCommand = cli.Command{
Name: "prepare",
Usage: "Prepare a snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
mounts, err := snapshotter.Prepare(ctx, key, parent, snapshots.WithLabels(labels))
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var viewCommand = cli.Command{
Name: "view",
Usage: "Create a read-only snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.View(ctx, key, parent)
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var mountCommand = cli.Command{
Name: "mounts",
Aliases: []string{"m", "mount"},
Usage: "Mount gets mount commands for the snapshots",
ArgsUsage: "<target> <key>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.Args().Get(0)
key = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.Mounts(ctx, key)
if err != nil {
return err
}
printMounts(target, mounts)
return nil
},
}
var commitCommand = cli.Command{
Name: "commit",
Usage: "Commit an active snapshot into the provided name",
ArgsUsage: "<key> <active>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
key = context.Args().Get(0)
active = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
return snapshotter.Commit(ctx, key, active, snapshots.WithLabels(labels))
},
}
var treeCommand = cli.Command{
Name: "tree",
Usage: "Display tree view of snapshot branches",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tree = newSnapshotTree()
)
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
// Get or create node and add node details
tree.add(info)
return nil
}); err != nil {
return err
}
printTree(tree)
return nil
},
}
var infoCommand = cli.Command{
Name: "info",
Usage: "Get info about a snapshot",
ArgsUsage: "<key>",
Action: func(context *cli.Context) error {
if context.NArg() != 1 {
return cli.ShowSubcommandHelp(context)
}
key := context.Args().Get(0)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info, err := snapshotter.Stat(ctx, key)
if err != nil {
return err
}
commands.PrintAsJSON(info)
return nil
},
}
var setLabelCommand = cli.Command{
Name: "label",
Usage: "Add labels to content",
ArgsUsage: "<name> [<label>=<value> ...]",
Description: "labels snapshots in the snapshotter",
Action: func(context *cli.Context) error {
key, labels := commands.ObjectWithLabelArgs(context)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info := snapshots.Info{
Name: key,
Labels: map[string]string{},
}
var paths []string
for k, v := range labels {
paths = append(paths, fmt.Sprintf("labels.%s", k))
if v != "" {
info.Labels[k] = v
}
}
// Nothing updated, do no clear
if len(paths) == 0 {
info, err = snapshotter.Stat(ctx, info.Name)
} else {
info, err = snapshotter.Update(ctx, info, paths...)
}
if err != nil {
return err
}
var labelStrings []string
for k, v := range info.Labels {
labelStrings = append(labelStrings, fmt.Sprintf("%s=%s", k, v))
}
fmt.Println(strings.Join(labelStrings, ","))
return nil
},
}
var unpackCommand = cli.Command{
Name: "unpack",
Usage: "Unpack applies layers from a manifest to a snapshot",
ArgsUsage: "[flags] <digest>",
Flags: commands.SnapshotterFlags,
Action: func(context *cli.Context) error {
dgst, err := digest.Parse(context.Args().First())
if err != nil {
return err
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
log.G(ctx).Debugf("unpacking layers from manifest %s", dgst.String())
// TODO: Support unpack by name
images, err := client.ListImages(ctx)
if err != nil {
return err
}
var unpacked bool
for _, image := range images {
if image.Target().Digest == dgst {
fmt.Printf("unpacking %s (%s)...", dgst, image.Target().MediaType)
if err := image.Unpack(ctx, context.String("snapshotter")); err != nil {
fmt.Println()
return err
}
fmt.Println("done")
unpacked = true
break
}
}
if !unpacked {
return errors.New("manifest not found")
}
// TODO: Get rootfs from Image
//log.G(ctx).Infof("chain ID: %s", chainID.String())
return nil
},
}
type snapshotTree struct {
nodes []*snapshotTreeNode
index map[string]*snapshotTreeNode
}
func newSnapshotTree() *snapshotTree {
return &snapshotTree{
index: make(map[string]*snapshotTreeNode),
}
}
type snapshotTreeNode struct {
info snapshots.Info
children []string
}
func (st *snapshotTree) add(info snapshots.Info) *snapshotTreeNode {
entry, ok := st.index[info.Name]
if !ok {
entry = &snapshotTreeNode{info: info}
st.nodes = append(st.nodes, entry)
st.index[info.Name] = entry
} else {
entry.info = info // update info if we created placeholder
}
if info.Parent != "" {
pn := st.get(info.Parent)
if pn == nil {
// create a placeholder
pn = st.add(snapshots.Info{Name: info.Parent})
}
pn.children = append(pn.children, info.Name)
}
return entry
}
func (st *snapshotTree) get(name string) *snapshotTreeNode {
return st.index[name]
}
func printTree(st *snapshotTree) {
for _, node := range st.nodes {
// Print for root(parent-less) nodes only
if node.info.Parent == "" {
printNode(node.info.Name, st, 0)
}
}
}
func printNode(name string, tree *snapshotTree, level int) {
node := tree.index[name]
prefix := strings.Repeat(" ", level)
if level > 0 {
prefix += "\\_"
}
fmt.Printf(prefix+" %s\n", node.info.Name)
level++
for _, child := range node.children {
printNode(child, tree, level)
}
}
func | (target string, mounts []mount.Mount) {
// FIXME: This is specific to Unix
for _, m := range mounts {
fmt.Printf("mount -t %s %s %s -o %s\n", m.Type, m.Source, filepath.Join(target, m.Target), strings.Join(m.Options, ","))
}
}
| printMounts | identifier_name |
snapshots.go | /*
Copyright The containerd Authors.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package snapshots
import (
gocontext "context"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"strconv"
"strings"
"text/tabwriter"
"time"
"github.com/containerd/containerd/cmd/ctr/commands"
"github.com/containerd/containerd/content"
"github.com/containerd/containerd/diff"
"github.com/containerd/containerd/log"
"github.com/containerd/containerd/mount"
"github.com/containerd/containerd/pkg/progress"
"github.com/containerd/containerd/rootfs"
"github.com/containerd/containerd/snapshots"
digest "github.com/opencontainers/go-digest"
ocispec "github.com/opencontainers/image-spec/specs-go/v1"
"github.com/urfave/cli"
)
// Command is the cli command for managing snapshots
var Command = cli.Command{
Name: "snapshots",
Aliases: []string{"snapshot"},
Usage: "Manage snapshots",
Flags: commands.SnapshotterFlags,
Subcommands: cli.Commands{
commitCommand,
diffCommand,
infoCommand,
listCommand,
mountCommand,
prepareCommand,
removeCommand,
setLabelCommand,
treeCommand,
unpackCommand,
usageCommand,
viewCommand,
},
}
var listCommand = cli.Command{
Name: "list",
Aliases: []string{"ls"},
Usage: "List snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tPARENT\tKIND\t")
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
fmt.Fprintf(tw, "%v\t%v\t%v\t\n",
info.Name,
info.Parent,
info.Kind)
return nil
}); err != nil {
return err
}
return tw.Flush()
},
}
var diffCommand = cli.Command{
Name: "diff",
Usage: "Get the diff of two snapshots. the default second snapshot is the first snapshot's parent.",
ArgsUsage: "[flags] <idA> [<idB>]",
Flags: append([]cli.Flag{
cli.StringFlag{
Name: "media-type",
Usage: "Media type to use for creating diff",
Value: ocispec.MediaTypeImageLayerGzip,
},
cli.StringFlag{
Name: "ref",
Usage: "Content upload reference to use",
},
cli.BoolFlag{
Name: "keep",
Usage: "Keep diff content. up to creator to delete it.",
},
}, commands.LabelFlag),
Action: func(context *cli.Context) error {
var (
idA = context.Args().First()
idB = context.Args().Get(1)
)
if idA == "" {
return errors.New("snapshot id must be provided")
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
ctx, done, err := client.WithLease(ctx)
if err != nil {
return err
}
defer done(ctx)
var desc ocispec.Descriptor
labels := commands.LabelArgs(context.StringSlice("label"))
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
if context.Bool("keep") {
labels["containerd.io/gc.root"] = time.Now().UTC().Format(time.RFC3339)
}
opts := []diff.Opt{
diff.WithMediaType(context.String("media-type")),
diff.WithReference(context.String("ref")),
diff.WithLabels(labels),
}
// SOURCE_DATE_EPOCH is propagated via the ctx, so no need to specify diff.WithSourceDateEpoch here
if idB == "" {
desc, err = rootfs.CreateDiff(ctx, idA, snapshotter, client.DiffService(), opts...)
if err != nil {
return err
}
} else {
desc, err = withMounts(ctx, idA, snapshotter, func(a []mount.Mount) (ocispec.Descriptor, error) {
return withMounts(ctx, idB, snapshotter, func(b []mount.Mount) (ocispec.Descriptor, error) {
return client.DiffService().Compare(ctx, a, b, opts...)
})
})
if err != nil {
return err
}
}
ra, err := client.ContentStore().ReaderAt(ctx, desc)
if err != nil {
return err
}
defer ra.Close()
_, err = io.Copy(os.Stdout, content.NewReader(ra))
return err
},
}
func withMounts(ctx gocontext.Context, id string, sn snapshots.Snapshotter, f func(mounts []mount.Mount) (ocispec.Descriptor, error)) (ocispec.Descriptor, error) {
var mounts []mount.Mount
info, err := sn.Stat(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
if info.Kind == snapshots.KindActive {
mounts, err = sn.Mounts(ctx, id)
if err != nil {
return ocispec.Descriptor{}, err
}
} else {
key := fmt.Sprintf("%s-view-key", id)
mounts, err = sn.View(ctx, key, id)
if err != nil {
return ocispec.Descriptor{}, err
}
defer sn.Remove(ctx, key)
}
return f(mounts)
}
var usageCommand = cli.Command{
Name: "usage",
Usage: "Usage snapshots",
ArgsUsage: "[flags] [<key>, ...]",
Flags: []cli.Flag{
cli.BoolFlag{
Name: "b",
Usage: "Display size in bytes",
},
},
Action: func(context *cli.Context) error {
var displaySize func(int64) string
if context.Bool("b") {
displaySize = func(s int64) string {
return strconv.FormatInt(s, 10)
}
} else {
displaySize = func(s int64) string {
return progress.Bytes(s).String()
}
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tw = tabwriter.NewWriter(os.Stdout, 1, 8, 1, ' ', 0)
)
fmt.Fprintln(tw, "KEY\tSIZE\tINODES\t")
if context.NArg() == 0 {
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
usage, err := snapshotter.Usage(ctx, info.Name)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", info.Name, displaySize(usage.Size), usage.Inodes)
return nil
}); err != nil {
return err
}
} else {
for _, id := range context.Args() {
usage, err := snapshotter.Usage(ctx, id)
if err != nil {
return err
}
fmt.Fprintf(tw, "%v\t%s\t%d\t\n", id, displaySize(usage.Size), usage.Inodes)
}
}
return tw.Flush()
},
}
var removeCommand = cli.Command{
Name: "delete",
Aliases: []string{"del", "remove", "rm"},
ArgsUsage: "<key> [<key>, ...]",
Usage: "Remove snapshots",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
for _, key := range context.Args() {
err = snapshotter.Remove(ctx, key)
if err != nil {
return fmt.Errorf("failed to remove %q: %w", key, err)
}
}
return nil
},
}
var prepareCommand = cli.Command{
Name: "prepare",
Usage: "Prepare a snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
mounts, err := snapshotter.Prepare(ctx, key, parent, snapshots.WithLabels(labels))
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var viewCommand = cli.Command{
Name: "view",
Usage: "Create a read-only snapshot from a committed snapshot",
ArgsUsage: "[flags] <key> [<parent>]",
Flags: []cli.Flag{
cli.StringFlag{
Name: "target, t",
Usage: "Mount target path, will print mount, if provided",
},
cli.BoolFlag{
Name: "mounts",
Usage: "Print out snapshot mounts as JSON",
},
},
Action: func(context *cli.Context) error {
if narg := context.NArg(); narg < 1 || narg > 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.String("target")
key = context.Args().Get(0)
parent = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.View(ctx, key, parent)
if err != nil {
return err
}
if target != "" {
printMounts(target, mounts)
}
if context.Bool("mounts") {
commands.PrintAsJSON(mounts)
}
return nil
},
}
var mountCommand = cli.Command{
Name: "mounts",
Aliases: []string{"m", "mount"},
Usage: "Mount gets mount commands for the snapshots",
ArgsUsage: "<target> <key>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
target = context.Args().Get(0)
key = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
mounts, err := snapshotter.Mounts(ctx, key)
if err != nil {
return err
}
printMounts(target, mounts)
return nil
},
}
var commitCommand = cli.Command{
Name: "commit",
Usage: "Commit an active snapshot into the provided name",
ArgsUsage: "<key> <active>",
Action: func(context *cli.Context) error {
if context.NArg() != 2 {
return cli.ShowSubcommandHelp(context)
}
var (
key = context.Args().Get(0)
active = context.Args().Get(1)
)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
labels := map[string]string{
"containerd.io/gc.root": time.Now().UTC().Format(time.RFC3339),
}
return snapshotter.Commit(ctx, key, active, snapshots.WithLabels(labels))
},
}
var treeCommand = cli.Command{
Name: "tree",
Usage: "Display tree view of snapshot branches",
Action: func(context *cli.Context) error {
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
var (
snapshotter = client.SnapshotService(context.GlobalString("snapshotter"))
tree = newSnapshotTree()
)
if err := snapshotter.Walk(ctx, func(ctx gocontext.Context, info snapshots.Info) error {
// Get or create node and add node details
tree.add(info)
return nil
}); err != nil {
return err
}
printTree(tree)
return nil
},
}
var infoCommand = cli.Command{
Name: "info",
Usage: "Get info about a snapshot",
ArgsUsage: "<key>",
Action: func(context *cli.Context) error {
if context.NArg() != 1 {
return cli.ShowSubcommandHelp(context)
}
key := context.Args().Get(0)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil |
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info, err := snapshotter.Stat(ctx, key)
if err != nil {
return err
}
commands.PrintAsJSON(info)
return nil
},
}
var setLabelCommand = cli.Command{
Name: "label",
Usage: "Add labels to content",
ArgsUsage: "<name> [<label>=<value> ...]",
Description: "labels snapshots in the snapshotter",
Action: func(context *cli.Context) error {
key, labels := commands.ObjectWithLabelArgs(context)
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
snapshotter := client.SnapshotService(context.GlobalString("snapshotter"))
info := snapshots.Info{
Name: key,
Labels: map[string]string{},
}
var paths []string
for k, v := range labels {
paths = append(paths, fmt.Sprintf("labels.%s", k))
if v != "" {
info.Labels[k] = v
}
}
// Nothing updated, do no clear
if len(paths) == 0 {
info, err = snapshotter.Stat(ctx, info.Name)
} else {
info, err = snapshotter.Update(ctx, info, paths...)
}
if err != nil {
return err
}
var labelStrings []string
for k, v := range info.Labels {
labelStrings = append(labelStrings, fmt.Sprintf("%s=%s", k, v))
}
fmt.Println(strings.Join(labelStrings, ","))
return nil
},
}
var unpackCommand = cli.Command{
Name: "unpack",
Usage: "Unpack applies layers from a manifest to a snapshot",
ArgsUsage: "[flags] <digest>",
Flags: commands.SnapshotterFlags,
Action: func(context *cli.Context) error {
dgst, err := digest.Parse(context.Args().First())
if err != nil {
return err
}
client, ctx, cancel, err := commands.NewClient(context)
if err != nil {
return err
}
defer cancel()
log.G(ctx).Debugf("unpacking layers from manifest %s", dgst.String())
// TODO: Support unpack by name
images, err := client.ListImages(ctx)
if err != nil {
return err
}
var unpacked bool
for _, image := range images {
if image.Target().Digest == dgst {
fmt.Printf("unpacking %s (%s)...", dgst, image.Target().MediaType)
if err := image.Unpack(ctx, context.String("snapshotter")); err != nil {
fmt.Println()
return err
}
fmt.Println("done")
unpacked = true
break
}
}
if !unpacked {
return errors.New("manifest not found")
}
// TODO: Get rootfs from Image
//log.G(ctx).Infof("chain ID: %s", chainID.String())
return nil
},
}
type snapshotTree struct {
nodes []*snapshotTreeNode
index map[string]*snapshotTreeNode
}
func newSnapshotTree() *snapshotTree {
return &snapshotTree{
index: make(map[string]*snapshotTreeNode),
}
}
type snapshotTreeNode struct {
info snapshots.Info
children []string
}
func (st *snapshotTree) add(info snapshots.Info) *snapshotTreeNode {
entry, ok := st.index[info.Name]
if !ok {
entry = &snapshotTreeNode{info: info}
st.nodes = append(st.nodes, entry)
st.index[info.Name] = entry
} else {
entry.info = info // update info if we created placeholder
}
if info.Parent != "" {
pn := st.get(info.Parent)
if pn == nil {
// create a placeholder
pn = st.add(snapshots.Info{Name: info.Parent})
}
pn.children = append(pn.children, info.Name)
}
return entry
}
func (st *snapshotTree) get(name string) *snapshotTreeNode {
return st.index[name]
}
func printTree(st *snapshotTree) {
for _, node := range st.nodes {
// Print for root(parent-less) nodes only
if node.info.Parent == "" {
printNode(node.info.Name, st, 0)
}
}
}
func printNode(name string, tree *snapshotTree, level int) {
node := tree.index[name]
prefix := strings.Repeat(" ", level)
if level > 0 {
prefix += "\\_"
}
fmt.Printf(prefix+" %s\n", node.info.Name)
level++
for _, child := range node.children {
printNode(child, tree, level)
}
}
func printMounts(target string, mounts []mount.Mount) {
// FIXME: This is specific to Unix
for _, m := range mounts {
fmt.Printf("mount -t %s %s %s -o %s\n", m.Type, m.Source, filepath.Join(target, m.Target), strings.Join(m.Options, ","))
}
}
| {
return err
} | conditional_block |
server.py | # -*- coding: utf-8 -*-
# 简易http 与 websocket 服务端
import logging
import socket
import base64
import hashlib
import struct
import os
import binascii
import json
from select import select
logging.basicConfig(level=logging.DEBUG)
def md5_for_file(f, block_size=2 ** 20):
md5 = hashlib.md5()
while True:
data = f.read(block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
class Server:
socket = None
socket_list = set()
port = 7000
buffersize = 1024*1024
timeout = 20
content = dict()
session = dict()
def __init__(self):
filelist = ['test.html', 'upload.js', 'spark-md5.min.js']
for i in filelist:
with open(i, 'r') as f:
self.content[i] = f.read()
def wshandshake( | v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept:' + key + '\r\n\r\n'
conn.send(response)
self.socket_list.add(conn)
# 超时时长， 文件名， 缓存大小
self.session[conn.fileno()] = dict(buffer='', length=0, no=0)
self.ws_send(conn, 'init')
def ws_process(self, conn, size=1024*1024):
data = conn.recv(size)
sesskey = conn.fileno()
if sesskey not in self.session or 'buffer' not in self.session[sesskey]:
self.ws_send(conn, 'session error!')
if conn in self.socket_list:
self.socket_list.remove(conn)
conn.close()
return
self.session[sesskey]['buffer'] += data
# 可能关闭连接，销毁session
while sesskey in self.session and self.session[sesskey]['buffer']:
if self.session[sesskey]['length'] == 0:
b = self.session[sesskey]['buffer']
if len(b) < 14:
break
len_flag = ord(b[1]) & 127 # 数据长度
if len_flag == 126:
self.session[sesskey]['length'] = ord(b[2]) * 256 + ord(b[3]) + 8
elif len_flag == 127:
self.session[sesskey]['length'] = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), b[2:9])) + 14
else:
self.session[sesskey]['length'] = len_flag + 6
# logging.info("length %d, buffer %d" % (self.session[sesskey]['length'], len(self.session[sesskey]['buffer'])))
if self.session[sesskey]['length'] <= len(self.session[sesskey]['buffer']) \
and self.session[sesskey]['length'] != 0:
# 处理完整包
pack_data = self.session[sesskey]['buffer'][:self.session[sesskey]['length']]
if len(self.session[sesskey]['buffer']) > self.session[sesskey]['length']:
self.session[sesskey]['buffer'] = self.session[sesskey]['buffer'][self.session[sesskey]['length']:]
else:
self.session[sesskey]['buffer'] = ''
self.session[sesskey]['length'] = 0
self.package_process(conn, pack_data)
else:
break
def package_process(self, conn, data):
# logging.info(data)
FIN = ord(data[0]) & 128 # 结束位
Opcode = ord(data[0]) & 112 # 操作码
is_mask = ord(data[1]) & 128 # 是否加掩码
len_flag = ord(data[1]) & 127 # 数据长度
if len_flag == 126:
mask = data[4:8]
length = ord(data[2]) * 256 + ord(data[3])
raw = data[8:]
elif len_flag == 127:
mask = data[10:14]
raw = data[14:]
length = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), data[2:9]))
else:
mask = data[2:6]
raw = data[6:]
length = len_flag
ret = ''
for cnt, d in enumerate(raw):
ret += chr(ord(d) ^ ord(mask[cnt % 4]))
if not ret:
pass
# logging.debug("frame info FIN %d Opcode %d mask %d length %d " % (FIN, Opcode, is_mask, length))
# hexstr = binascii.b2a_hex(data)
# bsstr = bin(int(hexstr, 16))[2:]
# logging.debug(bsstr)
sesskey = conn.fileno()
session = self.session[sesskey]
if not ret or ret is False:
# if conn in self.socket_list:
# self.socket_list.remove(conn)
logging.info("ignore empty msg")
self.ws_send(conn, 'empty:%d' % session['no'])
# conn.close()
return
try:
# logging.info(ret[:10])
msg = self.params_data(ret)
except Exception, e:
# logging.exception(e)
logging.debug("error:%d" % session['no'])
self.ws_send(conn, "error:%d" % session['no'])
return
if "a" in msg:
if msg['a'] == 'init':
self.session[sesskey]['name'] = msg['name']
# self.ws_send(conn, 'ok:0')
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['no'] = 0
self.session[sesskey]['file'] = open(
os.path.join(os.path.dirname(__file__), 'upload', msg['name']), 'ab')
elif msg['a'] == 'ping':
self.ws_send(conn, "ok:%d" % (self.session[sesskey]['no']))
elif msg['a'] == 'f':
logging.info('a %s s %d e %d n %d' % (msg['a'], msg['s'], msg['e'], msg['n']))
start, end = msg['s'], msg['e']
length = end - start
if msg['n'] != session['no']:
if msg['n'] < session['no']:
logging.info('already msg %d' % msg['n'])
self.ws_send(conn, 'already:%d' % msg['n'])
else:
logging.info("ignore msg %d %d" % (msg['n'], session['no']))
self.ws_send(conn, "retry:%d" % (session['no']))
elif length != len(msg['d']):
logging.info("error length msg %d %d" % (length, len(msg['d'])))
self.ws_send(conn, "retry:%d" % (msg['n']))
else:
self.session[sesskey]['filebuffer'].append(msg['d'])
self.session[sesskey]['no'] += 1
# logging.info('ok msg %d' % msg['n'])
# 每1M写入一次
if len(session['filebuffer']) > 128:
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.ws_send(conn, "ok:%d" % (msg['n']))
elif msg['a'] == 'over':
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['file'].close()
logging.info("over")
self.ws_send(conn, "over")
elif msg['a'] == 'check':
logging.info("check file md5 : %s" % msg['hash'])
with open(os.path.join(os.path.dirname(__file__), 'upload', session['name']), 'rb') as f:
md5 = md5_for_file(f)
logging.info(md5)
self.ws_send(conn, "check:%s" % md5)
elif msg['a'] == 'closed':
logging.info("closed")
self.ws_close(conn)
@staticmethod
def ws_send(conn, data):
head = '\x81'
if len(data) < 126:
head += struct.pack('B', len(data))
elif len(data) <= 0xFFFF:
head += struct.pack('!BH', 126, len(data))
else:
head += struct.pack('!BQ', 127, len(data))
conn.send(head + data)
def ws_close(self, conn):
msg = '\x88\x00'
conn.send(msg)
fileno = conn.fileno()
logging.info("close conn %d" % fileno)
if fileno in self.session:
self.session.pop(fileno)
if conn in self.socket_list:
self.socket_list.remove(conn)
def protocol(self, conn):
data = conn.recv(8192)
is_ws = False
query = data.split('\r\n\r\n')[0].split('\r\n')
head = query[0].split(' ')
path = '/'
if len(head) > 2:
path = head[1]
logging.info(path)
for line in query[1:]:
k, v = line.split(': ')
# 带key头，为ws连接
if k == 'Sec-WebSocket-Key':
is_ws = True
self.wshandshake(conn, v)
# 非ws连接时，采用json做接口协议
if not is_ws:
filename = 'test.html'
if len(path) > 1:
filename = path[1:]
if filename not in self.content:
filename = 'test.html'
# @TODO 404
response = 'HTTP/1.1 200 OK\r\nContent-Type:text/html\r\n' + \
'Content-Length:%d\r\n\r\n' % len(self.content[filename])
conn.send(response)
conn.send(self.content[filename])
conn.close()
@staticmethod
def params_data(raw_data):
data = raw_data.split('|')
msg = dict()
if len(data) > 0:
msg['a'] = data[0]
if msg['a'] == 'init' and len(data) == 2:
msg['name'] = data[1]
return msg
if msg['a'] == 'check' and len(data) == 2:
msg['hash'] = data[1]
return msg
if len(data) > 4:
msg['n'] = int(data[1])
msg['s'] = int(data[2])
msg['e'] = int(data[3])
msg['d'] = base64.b64decode(data[4])
return msg
return msg
def run(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
self.socket.bind(('0.0.0.0', self.port))
self.socket.listen(10)
self.socket_list.add(self.socket)
except Exception, e:
print e
exit()
while True:
r, w, e = select(self.socket_list, [], [])
for sock in r:
if sock == self.socket:
conn, addr = sock.accept()
logging.debug("accept addr %s:%d" % addr)
self.protocol(conn)
else: # 持续连接的都是ws
self.ws_process(sock)
for sock in e:
if sock in self.socket_list:
# sock.close()
self.socket_list.remove(sock)
logging.debug("remove sock %d" % sock.fileno())
# logging.info(self.session)
if __name__ == "__main__":
Server().run()
| self, conn, | identifier_name |
server.py | # -*- coding: utf-8 -*-
# 简易http 与 websocket 服务端
import logging
import socket
import base64
import hashlib
import struct
import os
import binascii
import json
from select import select
logging.basicConfig(level=logging.DEBUG)
def md5_for_file(f, block_size=2 ** 20):
md5 = hashlib.md5()
while True:
data = f.read(block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
class Server:
socket = None
socket_list = set()
port = 7000
buffersize = 1024*1024
timeout = 20
content = dict()
session = dict()
def __init__(self):
filelist = ['test.html', 'upload.js', 'spark-md5.min.js']
for i in filelist:
with open(i, 'r') as f:
self.content[i] = f.read()
def wshandshake(self, conn, v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept:' + key + '\r\n\r\n'
conn.send(response)
self.socket_list.add(conn)
# 超时时长， 文件名， 缓存大小
self.session[conn.fileno()] = dict(buffer='', length=0, no=0)
self.ws_send(conn, 'init')
def ws_process(self, conn, size=1024*1024):
data = conn.recv(size)
sesskey = conn.fileno()
if sesskey not in self.session or 'buffer' not in self.session[sesskey]:
self.ws_send(conn, 'session error!')
if conn in self.socket_list:
self.socket_list.remove(conn)
conn.close()
return
self.session[sesskey]['buffer'] += data
# 可能关闭连接，销毁session
while sesskey in self.session and self.session[sesskey]['buffer']:
if self.session[sesskey]['length'] == 0:
b = self.session[sesskey]['buffer']
if len(b) < 14:
break
len_flag = ord(b[1]) & 127 # 数据长度
if len_flag == 126:
self.session[sesskey]['length'] = ord(b[2]) * 256 + ord(b[3]) + 8
elif len_flag == 127:
self.session[sesskey]['length'] = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), b[2:9])) + 14
else:
self.session[sesskey]['length'] = len_flag + 6
# logging.info("length %d, buffer %d" % (self.session[sesskey]['length'], len(self.session[sesskey]['buffer'])))
if self.session[sesskey]['length'] <= len(self.session[sesskey]['buffer']) \
and self.session[sesskey]['length'] != 0:
# 处理完整包
pack_data = self.session[sesskey]['buffer'][:self.session[sesskey]['length']]
if len(self.session[sesskey]['buffer']) > self.session[sesskey]['length']:
self.session[sesskey]['buffer'] = self.session[sesskey]['buffer'][self.session[sesskey]['length']:]
else:
self.session[sesskey]['buffer'] = ''
self.session[sesskey]['length'] = 0
self.package_process(conn, pack_data)
else:
break
def package_process(self, conn, data):
# logging.info(data)
FIN = ord(data[0]) & 128 # 结束位
Opcode = ord(data[0]) & 112 # 操作码
is_mask = ord(data[1]) & 128 # 是否加掩码
len_flag = ord(data[1]) & 127 # 数据长度
if len_flag == 126:
mask = data[4:8]
length = ord(data[2]) * 256 + ord(data[3])
raw = data[8:]
elif len_flag == 127:
mask = data[10:14]
| length = len_flag
ret = ''
for cnt, d in enumerate(raw):
ret += chr(ord(d) ^ ord(mask[cnt % 4]))
if not ret:
pass
# logging.debug("frame info FIN %d Opcode %d mask %d length %d " % (FIN, Opcode, is_mask, length))
# hexstr = binascii.b2a_hex(data)
# bsstr = bin(int(hexstr, 16))[2:]
# logging.debug(bsstr)
sesskey = conn.fileno()
session = self.session[sesskey]
if not ret or ret is False:
# if conn in self.socket_list:
# self.socket_list.remove(conn)
logging.info("ignore empty msg")
self.ws_send(conn, 'empty:%d' % session['no'])
# conn.close()
return
try:
# logging.info(ret[:10])
msg = self.params_data(ret)
except Exception, e:
# logging.exception(e)
logging.debug("error:%d" % session['no'])
self.ws_send(conn, "error:%d" % session['no'])
return
if "a" in msg:
if msg['a'] == 'init':
self.session[sesskey]['name'] = msg['name']
# self.ws_send(conn, 'ok:0')
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['no'] = 0
self.session[sesskey]['file'] = open(
os.path.join(os.path.dirname(__file__), 'upload', msg['name']), 'ab')
elif msg['a'] == 'ping':
self.ws_send(conn, "ok:%d" % (self.session[sesskey]['no']))
elif msg['a'] == 'f':
logging.info('a %s s %d e %d n %d' % (msg['a'], msg['s'], msg['e'], msg['n']))
start, end = msg['s'], msg['e']
length = end - start
if msg['n'] != session['no']:
if msg['n'] < session['no']:
logging.info('already msg %d' % msg['n'])
self.ws_send(conn, 'already:%d' % msg['n'])
else:
logging.info("ignore msg %d %d" % (msg['n'], session['no']))
self.ws_send(conn, "retry:%d" % (session['no']))
elif length != len(msg['d']):
logging.info("error length msg %d %d" % (length, len(msg['d'])))
self.ws_send(conn, "retry:%d" % (msg['n']))
else:
self.session[sesskey]['filebuffer'].append(msg['d'])
self.session[sesskey]['no'] += 1
# logging.info('ok msg %d' % msg['n'])
# 每1M写入一次
if len(session['filebuffer']) > 128:
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.ws_send(conn, "ok:%d" % (msg['n']))
elif msg['a'] == 'over':
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['file'].close()
logging.info("over")
self.ws_send(conn, "over")
elif msg['a'] == 'check':
logging.info("check file md5 : %s" % msg['hash'])
with open(os.path.join(os.path.dirname(__file__), 'upload', session['name']), 'rb') as f:
md5 = md5_for_file(f)
logging.info(md5)
self.ws_send(conn, "check:%s" % md5)
elif msg['a'] == 'closed':
logging.info("closed")
self.ws_close(conn)
@staticmethod
def ws_send(conn, data):
head = '\x81'
if len(data) < 126:
head += struct.pack('B', len(data))
elif len(data) <= 0xFFFF:
head += struct.pack('!BH', 126, len(data))
else:
head += struct.pack('!BQ', 127, len(data))
conn.send(head + data)
def ws_close(self, conn):
msg = '\x88\x00'
conn.send(msg)
fileno = conn.fileno()
logging.info("close conn %d" % fileno)
if fileno in self.session:
self.session.pop(fileno)
if conn in self.socket_list:
self.socket_list.remove(conn)
def protocol(self, conn):
data = conn.recv(8192)
is_ws = False
query = data.split('\r\n\r\n')[0].split('\r\n')
head = query[0].split(' ')
path = '/'
if len(head) > 2:
path = head[1]
logging.info(path)
for line in query[1:]:
k, v = line.split(': ')
# 带key头，为ws连接
if k == 'Sec-WebSocket-Key':
is_ws = True
self.wshandshake(conn, v)
# 非ws连接时，采用json做接口协议
if not is_ws:
filename = 'test.html'
if len(path) > 1:
filename = path[1:]
if filename not in self.content:
filename = 'test.html'
# @TODO 404
response = 'HTTP/1.1 200 OK\r\nContent-Type:text/html\r\n' + \
'Content-Length:%d\r\n\r\n' % len(self.content[filename])
conn.send(response)
conn.send(self.content[filename])
conn.close()
@staticmethod
def params_data(raw_data):
data = raw_data.split('|')
msg = dict()
if len(data) > 0:
msg['a'] = data[0]
if msg['a'] == 'init' and len(data) == 2:
msg['name'] = data[1]
return msg
if msg['a'] == 'check' and len(data) == 2:
msg['hash'] = data[1]
return msg
if len(data) > 4:
msg['n'] = int(data[1])
msg['s'] = int(data[2])
msg['e'] = int(data[3])
msg['d'] = base64.b64decode(data[4])
return msg
return msg
def run(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
self.socket.bind(('0.0.0.0', self.port))
self.socket.listen(10)
self.socket_list.add(self.socket)
except Exception, e:
print e
exit()
while True:
r, w, e = select(self.socket_list, [], [])
for sock in r:
if sock == self.socket:
conn, addr = sock.accept()
logging.debug("accept addr %s:%d" % addr)
self.protocol(conn)
else: # 持续连接的都是ws
self.ws_process(sock)
for sock in e:
if sock in self.socket_list:
# sock.close()
self.socket_list.remove(sock)
logging.debug("remove sock %d" % sock.fileno())
# logging.info(self.session)
if __name__ == "__main__":
Server().run() | raw = data[14:]
length = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), data[2:9]))
else:
mask = data[2:6]
raw = data[6:]
| random_line_split |
server.py | # -*- coding: utf-8 -*-
# 简易http 与 websocket 服务端
import logging
import socket
import base64
import hashlib
import struct
import os
import binascii
import json
from select import select
logging.basicConfig(level=logging.DEBUG)
def md5_for_file(f, block_size=2 ** 20):
md5 = hashlib.md5()
while True:
data = f.read(block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
class Server:
socket = None
socket_list = set()
port = 7000
buffersize = 1024*1024
timeout = 20
content = dict()
session = dict()
def __init__(self):
filelist = ['test.html', 'upload.js', 'spark-md5.min.js']
for i in filelist:
with open(i, 'r') as f:
self.content[i] = f.read()
def wshandshake(self, conn, v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept:' + key + '\r\n\r\n'
conn.send(response)
self.socket_list.add(conn)
# 超时时长， 文件名， 缓存大小
self.session[conn.fileno()] = dict(buffer='', length=0, no=0)
self.ws_send(conn, 'init')
def ws_process(self, conn, size=1024*1024):
data = conn.recv(size)
sesskey = conn.fileno()
if sesskey not in self.session or 'buffer' not in self.session[sesskey]:
self.ws_send(conn, 'session error!')
if conn in self.socket_list:
self.socket_list.remove(conn)
conn.close()
return
self.session[sesskey]['buffer'] += data
# 可能关闭连接，销毁session
while sesskey in self.session and self.session[sesskey]['buffer']:
if self.session[sesskey]['length'] == 0:
b = self.session[sesskey]['buffer']
if len(b) < 14:
break
len_flag = ord(b[1]) & 127 # 数据长度
if len_flag == 126:
self.session[sesskey]['length'] = ord(b[2]) * 256 + ord(b[3]) + 8
elif len_flag == 127:
self.session[sesskey]['length'] = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), b[2:9])) + 14
else:
self.session[sesskey]['length'] = len_flag + 6
# logging.info("length %d, buffer %d" % (self.session[sesskey]['length'], len(self.session[sesskey]['buffer'])))
if self.session[sesskey]['length'] <= len(self.session[sesskey]['buffer']) \
and self.session[sesskey]['length'] != 0:
# 处理完整包
pack_data = self.session[sesskey]['buffer'][:self.session[sesskey]['length']]
if len(self.session[sesskey]['buffer']) > self.session[sesskey]['length']:
self.session[sesskey]['buffer'] = self.session[sesskey]['buffer'][self.session[sesskey]['length']:]
else:
self.session[sesskey]['buffer'] = ''
self.session[sesskey]['length'] = 0
self.package_process(conn, pack_data)
else:
break
def package_process(self, conn, data):
# logging.info(data)
FIN = ord(data[0]) & 128 # 结束位
Opcode = ord(data[0]) & 112 # 操作码
is_mask = ord(data[1]) & 128 # 是否加掩码
len_flag = ord(data[1]) & 127 # 数据长度
if len_flag == 126:
mask = data[4:8]
length = ord(data[2]) * 256 + ord(data[3])
raw = data[8:]
elif len_flag == 127:
mask = data[10:14]
raw = data[14:]
length = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), data[2:9]))
else:
mask = data[2:6]
raw = data[6:]
length = len_flag
ret = ''
for cnt, d in enumerate(raw):
ret += chr(ord(d) ^ ord(mask[cnt % 4]))
if not ret:
pass
# logging.debug("frame info FIN %d Opcode %d mask %d length %d " % (FIN, Opcode, is_mask, length))
# hexstr = binascii.b2a_hex(data)
# bsstr = bin(int(hexstr, 16))[2:]
# logging.debug(bsstr)
sesskey = conn.fileno()
session = self.session[sesskey]
if not ret or ret is False:
# if conn in self.socket_list:
# self.socket_list.remove(conn)
logging.info("ignore empty msg")
self.ws_send(conn, 'empty:%d' % session['no'])
# conn.close()
return
try:
# logging.info(ret[:10])
msg = self.params_data(ret)
except Exception, e:
# logging.exception(e)
logging.debug("error:%d" % session['no'])
self.ws_send(conn, "error:%d" % session['no'])
return
if "a" in msg:
if msg['a'] == 'init':
self.session[sesskey]['name'] = msg['name']
# self.ws_send(conn, 'ok:0')
| ey]['no']))
elif msg['a'] == 'f':
logging.info('a %s s %d e %d n %d' % (msg['a'], msg['s'], msg['e'], msg['n']))
start, end = msg['s'], msg['e']
length = end - start
if msg['n'] != session['no']:
if msg['n'] < session['no']:
logging.info('already msg %d' % msg['n'])
self.ws_send(conn, 'already:%d' % msg['n'])
else:
logging.info("ignore msg %d %d" % (msg['n'], session['no']))
self.ws_send(conn, "retry:%d" % (session['no']))
elif length != len(msg['d']):
logging.info("error length msg %d %d" % (length, len(msg['d'])))
self.ws_send(conn, "retry:%d" % (msg['n']))
else:
self.session[sesskey]['filebuffer'].append(msg['d'])
self.session[sesskey]['no'] += 1
# logging.info('ok msg %d' % msg['n'])
# 每1M写入一次
if len(session['filebuffer']) > 128:
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.ws_send(conn, "ok:%d" % (msg['n']))
elif msg['a'] == 'over':
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['file'].close()
logging.info("over")
self.ws_send(conn, "over")
elif msg['a'] == 'check':
logging.info("check file md5 : %s" % msg['hash'])
with open(os.path.join(os.path.dirname(__file__), 'upload', session['name']), 'rb') as f:
md5 = md5_for_file(f)
logging.info(md5)
self.ws_send(conn, "check:%s" % md5)
elif msg['a'] == 'closed':
logging.info("closed")
self.ws_close(conn)
@staticmethod
def ws_send(conn, data):
head = '\x81'
if len(data) < 126:
head += struct.pack('B', len(data))
elif len(data) <= 0xFFFF:
head += struct.pack('!BH', 126, len(data))
else:
head += struct.pack('!BQ', 127, len(data))
conn.send(head + data)
def ws_close(self, conn):
msg = '\x88\x00'
conn.send(msg)
fileno = conn.fileno()
logging.info("close conn %d" % fileno)
if fileno in self.session:
self.session.pop(fileno)
if conn in self.socket_list:
self.socket_list.remove(conn)
def protocol(self, conn):
data = conn.recv(8192)
is_ws = False
query = data.split('\r\n\r\n')[0].split('\r\n')
head = query[0].split(' ')
path = '/'
if len(head) > 2:
path = head[1]
logging.info(path)
for line in query[1:]:
k, v = line.split(': ')
# 带key头，为ws连接
if k == 'Sec-WebSocket-Key':
is_ws = True
self.wshandshake(conn, v)
# 非ws连接时，采用json做接口协议
if not is_ws:
filename = 'test.html'
if len(path) > 1:
filename = path[1:]
if filename not in self.content:
filename = 'test.html'
# @TODO 404
response = 'HTTP/1.1 200 OK\r\nContent-Type:text/html\r\n' + \
'Content-Length:%d\r\n\r\n' % len(self.content[filename])
conn.send(response)
conn.send(self.content[filename])
conn.close()
@staticmethod
def params_data(raw_data):
data = raw_data.split('|')
msg = dict()
if len(data) > 0:
msg['a'] = data[0]
if msg['a'] == 'init' and len(data) == 2:
msg['name'] = data[1]
return msg
if msg['a'] == 'check' and len(data) == 2:
msg['hash'] = data[1]
return msg
if len(data) > 4:
msg['n'] = int(data[1])
msg['s'] = int(data[2])
msg['e'] = int(data[3])
msg['d'] = base64.b64decode(data[4])
return msg
return msg
def run(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
self.socket.bind(('0.0.0.0', self.port))
self.socket.listen(10)
self.socket_list.add(self.socket)
except Exception, e:
print e
exit()
while True:
r, w, e = select(self.socket_list, [], [])
for sock in r:
if sock == self.socket:
conn, addr = sock.accept()
logging.debug("accept addr %s:%d" % addr)
self.protocol(conn)
else: # 持续连接的都是ws
self.ws_process(sock)
for sock in e:
if sock in self.socket_list:
# sock.close()
self.socket_list.remove(sock)
logging.debug("remove sock %d" % sock.fileno())
# logging.info(self.session)
if __name__ == "__main__":
Server().run()
| self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['no'] = 0
self.session[sesskey]['file'] = open(
os.path.join(os.path.dirname(__file__), 'upload', msg['name']), 'ab')
elif msg['a'] == 'ping':
self.ws_send(conn, "ok:%d" % (self.session[sessk | conditional_block |
server.py | # -*- coding: utf-8 -*-
# 简易http 与 websocket 服务端
import logging
import socket
import base64
import hashlib
import struct
import os
import binascii
import json
from select import select
logging.basicConfig(level=logging.DEBUG)
def md5_for_file(f, block_size=2 ** 20):
md5 = hashli | Server:
socket = None
socket_list = set()
port = 7000
buffersize = 1024*1024
timeout = 20
content = dict()
session = dict()
def __init__(self):
filelist = ['test.html', 'upload.js', 'spark-md5.min.js']
for i in filelist:
with open(i, 'r') as f:
self.content[i] = f.read()
def wshandshake(self, conn, v):
key = base64.b64encode(hashlib.sha1(v + '258EAFA5-E914-47DA-95CA-C5AB0DC85B11').digest())
response = 'HTTP/1.1 101 Switching Protocols\r\n' \
'Upgrade: websocket\r\n' \
'Connection: Upgrade\r\n' \
'Sec-WebSocket-Accept:' + key + '\r\n\r\n'
conn.send(response)
self.socket_list.add(conn)
# 超时时长， 文件名， 缓存大小
self.session[conn.fileno()] = dict(buffer='', length=0, no=0)
self.ws_send(conn, 'init')
def ws_process(self, conn, size=1024*1024):
data = conn.recv(size)
sesskey = conn.fileno()
if sesskey not in self.session or 'buffer' not in self.session[sesskey]:
self.ws_send(conn, 'session error!')
if conn in self.socket_list:
self.socket_list.remove(conn)
conn.close()
return
self.session[sesskey]['buffer'] += data
# 可能关闭连接，销毁session
while sesskey in self.session and self.session[sesskey]['buffer']:
if self.session[sesskey]['length'] == 0:
b = self.session[sesskey]['buffer']
if len(b) < 14:
break
len_flag = ord(b[1]) & 127 # 数据长度
if len_flag == 126:
self.session[sesskey]['length'] = ord(b[2]) * 256 + ord(b[3]) + 8
elif len_flag == 127:
self.session[sesskey]['length'] = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), b[2:9])) + 14
else:
self.session[sesskey]['length'] = len_flag + 6
# logging.info("length %d, buffer %d" % (self.session[sesskey]['length'], len(self.session[sesskey]['buffer'])))
if self.session[sesskey]['length'] <= len(self.session[sesskey]['buffer']) \
and self.session[sesskey]['length'] != 0:
# 处理完整包
pack_data = self.session[sesskey]['buffer'][:self.session[sesskey]['length']]
if len(self.session[sesskey]['buffer']) > self.session[sesskey]['length']:
self.session[sesskey]['buffer'] = self.session[sesskey]['buffer'][self.session[sesskey]['length']:]
else:
self.session[sesskey]['buffer'] = ''
self.session[sesskey]['length'] = 0
self.package_process(conn, pack_data)
else:
break
def package_process(self, conn, data):
# logging.info(data)
FIN = ord(data[0]) & 128 # 结束位
Opcode = ord(data[0]) & 112 # 操作码
is_mask = ord(data[1]) & 128 # 是否加掩码
len_flag = ord(data[1]) & 127 # 数据长度
if len_flag == 126:
mask = data[4:8]
length = ord(data[2]) * 256 + ord(data[3])
raw = data[8:]
elif len_flag == 127:
mask = data[10:14]
raw = data[14:]
length = reduce(lambda y, z: y * 256 + z, map(lambda x: ord(x), data[2:9]))
else:
mask = data[2:6]
raw = data[6:]
length = len_flag
ret = ''
for cnt, d in enumerate(raw):
ret += chr(ord(d) ^ ord(mask[cnt % 4]))
if not ret:
pass
# logging.debug("frame info FIN %d Opcode %d mask %d length %d " % (FIN, Opcode, is_mask, length))
# hexstr = binascii.b2a_hex(data)
# bsstr = bin(int(hexstr, 16))[2:]
# logging.debug(bsstr)
sesskey = conn.fileno()
session = self.session[sesskey]
if not ret or ret is False:
# if conn in self.socket_list:
# self.socket_list.remove(conn)
logging.info("ignore empty msg")
self.ws_send(conn, 'empty:%d' % session['no'])
# conn.close()
return
try:
# logging.info(ret[:10])
msg = self.params_data(ret)
except Exception, e:
# logging.exception(e)
logging.debug("error:%d" % session['no'])
self.ws_send(conn, "error:%d" % session['no'])
return
if "a" in msg:
if msg['a'] == 'init':
self.session[sesskey]['name'] = msg['name']
# self.ws_send(conn, 'ok:0')
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['no'] = 0
self.session[sesskey]['file'] = open(
os.path.join(os.path.dirname(__file__), 'upload', msg['name']), 'ab')
elif msg['a'] == 'ping':
self.ws_send(conn, "ok:%d" % (self.session[sesskey]['no']))
elif msg['a'] == 'f':
logging.info('a %s s %d e %d n %d' % (msg['a'], msg['s'], msg['e'], msg['n']))
start, end = msg['s'], msg['e']
length = end - start
if msg['n'] != session['no']:
if msg['n'] < session['no']:
logging.info('already msg %d' % msg['n'])
self.ws_send(conn, 'already:%d' % msg['n'])
else:
logging.info("ignore msg %d %d" % (msg['n'], session['no']))
self.ws_send(conn, "retry:%d" % (session['no']))
elif length != len(msg['d']):
logging.info("error length msg %d %d" % (length, len(msg['d'])))
self.ws_send(conn, "retry:%d" % (msg['n']))
else:
self.session[sesskey]['filebuffer'].append(msg['d'])
self.session[sesskey]['no'] += 1
# logging.info('ok msg %d' % msg['n'])
# 每1M写入一次
if len(session['filebuffer']) > 128:
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.ws_send(conn, "ok:%d" % (msg['n']))
elif msg['a'] == 'over':
for i in session['filebuffer']:
self.session[sesskey]['file'].write(i)
self.session[sesskey]['filebuffer'] = []
self.session[sesskey]['file'].close()
logging.info("over")
self.ws_send(conn, "over")
elif msg['a'] == 'check':
logging.info("check file md5 : %s" % msg['hash'])
with open(os.path.join(os.path.dirname(__file__), 'upload', session['name']), 'rb') as f:
md5 = md5_for_file(f)
logging.info(md5)
self.ws_send(conn, "check:%s" % md5)
elif msg['a'] == 'closed':
logging.info("closed")
self.ws_close(conn)
@staticmethod
def ws_send(conn, data):
head = '\x81'
if len(data) < 126:
head += struct.pack('B', len(data))
elif len(data) <= 0xFFFF:
head += struct.pack('!BH', 126, len(data))
else:
head += struct.pack('!BQ', 127, len(data))
conn.send(head + data)
def ws_close(self, conn):
msg = '\x88\x00'
conn.send(msg)
fileno = conn.fileno()
logging.info("close conn %d" % fileno)
if fileno in self.session:
self.session.pop(fileno)
if conn in self.socket_list:
self.socket_list.remove(conn)
def protocol(self, conn):
data = conn.recv(8192)
is_ws = False
query = data.split('\r\n\r\n')[0].split('\r\n')
head = query[0].split(' ')
path = '/'
if len(head) > 2:
path = head[1]
logging.info(path)
for line in query[1:]:
k, v = line.split(': ')
# 带key头，为ws连接
if k == 'Sec-WebSocket-Key':
is_ws = True
self.wshandshake(conn, v)
# 非ws连接时，采用json做接口协议
if not is_ws:
filename = 'test.html'
if len(path) > 1:
filename = path[1:]
if filename not in self.content:
filename = 'test.html'
# @TODO 404
response = 'HTTP/1.1 200 OK\r\nContent-Type:text/html\r\n' + \
'Content-Length:%d\r\n\r\n' % len(self.content[filename])
conn.send(response)
conn.send(self.content[filename])
conn.close()
@staticmethod
def params_data(raw_data):
data = raw_data.split('|')
msg = dict()
if len(data) > 0:
msg['a'] = data[0]
if msg['a'] == 'init' and len(data) == 2:
msg['name'] = data[1]
return msg
if msg['a'] == 'check' and len(data) == 2:
msg['hash'] = data[1]
return msg
if len(data) > 4:
msg['n'] = int(data[1])
msg['s'] = int(data[2])
msg['e'] = int(data[3])
msg['d'] = base64.b64decode(data[4])
return msg
return msg
def run(self):
self.socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
try:
self.socket.bind(('0.0.0.0', self.port))
self.socket.listen(10)
self.socket_list.add(self.socket)
except Exception, e:
print e
exit()
while True:
r, w, e = select(self.socket_list, [], [])
for sock in r:
if sock == self.socket:
conn, addr = sock.accept()
logging.debug("accept addr %s:%d" % addr)
self.protocol(conn)
else: # 持续连接的都是ws
self.ws_process(sock)
for sock in e:
if sock in self.socket_list:
# sock.close()
self.socket_list.remove(sock)
logging.debug("remove sock %d" % sock.fileno())
# logging.info(self.session)
if __name__ == "__main__":
Server().run()
| b.md5()
while True:
data = f.read(block_size)
if not data:
break
md5.update(data)
return md5.hexdigest()
class | identifier_body |
rol_common.js | // 防止事件冒泡
function stopBubble(e) {
// If an event object is provided, then this is a non-IE browser
if ( e && e.stopPropagation )
// and therefore it supports the W3C stopPropagation() method
e.stopPropagation();
else
// Otherwise, we need to use the Internet Explorer
// way of cancelling event bubbling
window.event.cancelBubble = true;
}
//显示更多操作菜单
function show_more_operation(btn,div_id,div_bg){
var div_obj = $("#"+div_id);
var bg_obj = null;
if(div_bg){
bg_obj = $("#"+div_bg);
}
if(div_obj.is(":hidden")){
div_obj.show();
//定位
div_obj.css("left",$(btn).offset().left);
div_obj.css("top",$(btn).offset().top+23);
div_obj.css("zIndex","1000");
if(bg_obj){
bg_obj.css("left",$(div_obj).offset().left-1);
bg_obj.css("top",$(div_obj).offset().top);
div_obj.css("zIndex","1000");
bg_obj.css("width",$(div_obj).width() +"px");
bg_obj.css("height",$(div_obj).height() +"px");
bg_obj.show();
}
}else{
div_obj.hide();
if(bg_obj!=null)
bg_obj.hide();
return;
}
//标示鼠标是否移入DIV
var flag = true;
div_obj.bind("mouseover",function(){
flag = false;
});
//鼠标移出，将DIV隐藏
div_obj.bind("mouseleave",function(){
flag = true;
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
});
//点击链接，将DIV隐藏
$('#more_operation>a').click(function(){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
});
//2秒还未进入，关闭
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
}
//事件处理函数，用户DIV层失去焦点时，隐藏out_div_hidden层
//$(document).bind("click",hidden_out_div);
function hidden_out_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("out_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".out_div_hidden").hide();
}
}
//事件处理函数，用户DIV层失去焦点时，隐藏outeditfd_div_hidden层,同时删除页面上的left_nav_infolink_high样式的样式
//$(document).bind("click",hidden_outeditfd_div);
function hidden_outeditfd_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("outeditfd_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".outeditfd_div_hidden").hide();
$(".left_nav_infolink_high").removeClass("left_nav_infolink_high");
}
}
//打开指定定位到按钮下方的层，该层需指定class:hidden_out_div
function openFloatDiv(btn,div_id){
var obj = $('#'+div_id);
if($(obj).is(":hidden")){
//失去焦点，需要隐藏带hidden_out_div class的层
// $(document).bind("click",hidden_out_div);
//显示层，需要延迟显示
setTimeout(function(){
$(obj).show();
//定位
$(obj).css("left",$(btn).offset().left);
$(obj).css("top",$(btn).offset().top+24);
$(obj).css("zIndex",1000);
$(obj).css("height",$(obj).find(".float_div_content").height()+70)
},100);
}else{
$(obj).hide();
}
}
//左菜单展开，关闭
function switch_left_nav(obj){
var div = $(obj).parent();
if($(obj).hasClass("left_nav_open"))
{
div.find(">div:not(div:first-child)").hide();
$(obj).removeClass("left_nav_open");
}else{
div.find(">div").show();
$(obj).addClass("left_nav_open");
}
}
//左边菜单展开，关闭替换图标
function replaceImg(obj){
var img = $(obj).find("img");
var src = img.attr("src");
if(src.indexOf('open')>0){
img.attr("src",src.replace("open","close"));
}else{
img.attr("src",src.replace("close","open"));
}
}
//打开左侧菜单，根据设置的.info样式
function open_left_nav(){
$("#left_nav").find(".info")
.each(function(){
$(this).parent().find(">div:first-child").trigger("click");
});
}
//左侧菜单鼠标事件
function bind_left_nav_mouse()
{
//鼠标在上面高亮显示
$("#left_nav div.infolink").mouseover(function(){
$(this).addClass("infolink_hover");
});
//鼠标移走移除高亮
$("#left_nav div.infolink").mouseout(function(){
$(this).removeClass("infolink_hover");
});
}
//左侧菜单编辑文件夹
function bind_left_nav_folder()
{
var left_nav = $("#left_nav");
left_nav.find('div.edit_folder').click(function(){
//失去焦点，需要隐藏带hidden_out_div class的层
$(document).bind("click",hidden_outeditfd_div);
var top = $(this).offset().top;
var left = $(this).offset().left;
var fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("top",top);
edit_div.css("left",left);
edit_div.find(".folder_id").val(fdid);
edit_div.find(".folder_name").val(fdname);
},100);
});
//需要编辑文件夹的，高亮显示，同时显示编辑图片
left_nav.find(".edit_folder_div").mouseover(function(){
$(this).addClass("infolink_hover");
$(this).find(".edit_folder").show();
});
//需要编辑文件夹的，移除高亮显示，同时不显示编辑图片
left_nav.find(".edit_folder_div").mouseout(function(){
$(this).find(".edit_folder").hide();
$(this).removeClass("infolink_hover");
});
}
//显示操作正确信息
function show_yes_tips(tip_id,msg,time)
{
if(!time || time < 3000){
time = 3000;
}
$.scmtips.show("success",msg,null,time);
}
//显示操作错误信息
function show_wrong_tips(tip_id,msg,time)
{
if(!time || time <3000){
time = 3000;
}
$.scmtips.show("error",msg, null,3000);
}
//杰青近五年代表性论著操作错误信息
function show_unlimit_wrong_tips(tip_id,msg)
{
$.scmtips.show("error",msg, null,3000);
} | function show_msg_tips_newdiv(type,msg,id){
if(!type || !msg)
return;
var time=3000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg,null,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg, width,time);
}
function rol_show_msg_tips(type,msg,rowCount){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg);
}
//手动关闭显示的操作消息
function close_msg_tips(){
$("#tip_msg_box").hide();
}
//替换HMTL特殊字符,注意替换顺序
function covertHmtl(str)
{
str = str.replace(/\&/gi,"&");
str = str.replace(/\>/gi,">");
str = str.replace(/\</gi,"<");
str = str.replace(/\n/gi,"<br/>");
str = str.replace(/\s/gi," ");
return str;
}
//将textarea转换成span，过滤掉特殊字符
function refreshTextArea()
{
var objs = $(".rep_textarea");
for(var i = 0; i < objs.size(); i++)
{
var tag=objs[i];
var p = tag.parentNode;
if(!p) p = document;
if(/\r(\n)?/g.test(tag.value)==true)
{
newTag = getSpan(tag.value.replace(/\r(\n)?/g,"<br>"));
}
else
{
newTag = getSpan(tag.value);
}
p.replaceChild(newTag,tag);
}
}
function getSpan(text)
{
var node = document.createElement("span");
node.innerHTML=text+" ";
return node;
}
//帮助信息
function bindHelps()
{
$(".help_prompt").bind("click",function(){
var help_prompt_left = $(this).find(".help_prompt_left");
if(help_prompt_left.is(":visible")){
help_prompt_left.hide();
$(this).find(".help_prompt_left1").show();
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
help_prompt_left.show();
$(this).find(".help_prompt_left1").hide();
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
$(".help_prompt").each(function(){
var isShow = $(this).find(".help_prompt_left1").is(":visible")? true : false;
if(isShow){
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
//链接不进行事件冒泡
$(".help_prompt").find(".help_prompt_left1 a").bind("click",function(event){
stopBubble(event);
});
}
//显示隐藏检索条件
function view_search(){
var search_block = $(".search_block");
if(!search_block.is(":hidden")){
$("#isSearchShow").val(0);
$("#view_search_block_link").show();
$("#hide_search_block_link").hide();
search_block.hide();
}else{
$("#view_search_block_link").hide();
$("#hide_search_block_link").show();
$("#isSearchShow").val(1);
search_block.show();
}
}
//验证邮件格式是否合法
function isEmail(email) {
return /^((([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+(\.([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+)*)|((\x22)((((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(([\x01-\x08\x0b\x0c\x0e-\x1f\x7f]|\x21|[\x23-\x5b]|[\x5d-\x7e]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(\\([\x01-\x09\x0b\x0c\x0d-\x7f]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]))))*(((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(\x22)))@((([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.)+(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.?$/i.test(email);
}
//产生数字下拉，例如年度等
function genNumDescOption(start,end,select_id){
if(start > end){
var tmp = start;
start = end;
end = tmp;
}
var select = $("#"+select_id);
for(;end >= start;end--){
var option = $("<option value='"+end+"' select=''>"+end+"</option>");
select.append(option);
}
}
//判断是否是不是中文
function isChinStr(s){
var regu = "[\w\W]*[\u4e00-\u9fa5][\w\W]*";
var re = new RegExp(regu);
if (s=="")
return false;
if (re.test(s)) {
return true;
}else{
return false;
}
}
//判断是否是数字
function isNumStr(s) {
var patrn=/^[0-9]{1,20}$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字母、数字、下划线
function isCharsOrNum(s) {
var patrn=/^(\w)$/;
if (!patrn.exec(s))
return false;
return true ;
}
//字母、数字
function isChrOrNum(s){
var patrn=/^[A-Za-z0-9]+$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//是否是中文或者是英文和数字
function isParamStr(s){
var flag = false;
if(isChinStr(s))
flag =true;
if(isChrOrNum(s))
flag =true;
return flag;
}
//限制textarea最多输入
function setTextareaMaxLength(maxLength){
$("textarea").keyup(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
$("textarea").blur(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
}
//判断是否是特殊字符
function isSpecial(s){
var str = '",.;[]{}+=|\*&^%$#@!~()-/?<>';
var flag = false;
if($.trim(s).length>0){
for(var i=0;i<str.length;i++){
if(s.indexOf(str.charAt(i))>=0){
flag=true;
break;
}
}
if(flag)
return true;
}
var patrn = /^[^<]*(<(.|\s)+>)[^>]*$|^#$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字符串真实的长度
function getStrRealLength(str){
return str.replace(/[^\x00-\xff]/gi, "--").replace(/[wW]/gi, "--").length;
}
//字符串缩略
function subStrBreviary(str,maxLength){
var realLength = getStrRealLength(str);
if(realLength <= maxLength){
return str;
}
//at least one half
var tmpStr = str.substring(0,maxLength/2);
var tmpLength = getStrRealLength(tmpStr);
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
//cut
for(var i = maxLength/2;i < realLength;i++){
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
tmpStr = tmpStr + str.charAt(i);
var tmpLength = getStrRealLength(tmpStr);
}
}
subByeStr = function(s, n) {
var r = /[^\x00-\xff]/g; // 其中x00-\xff代表非汉字编码
var byteLen = s.replace(r, "**").length; // 获取字符串的字节长度，其中replace(r, "**")表示讲一个中文字体换成两个英文符号
if(byteLen <= n) return s; // 如果字节长度小于或者等于要截取的字节长度，直接返回原字符串
var m = Math.floor(n/2); // 因为要截取的字符串一定大于等于字符串的长度的一半，所以从字符串长度的一半开始
for(var i=m; i<s.length; i++) {
strLen = s.substr(0, i).replace(r, "**").length;
if (strLen == n) {
return s.substr(0, i);
} else if (strLen > n) {
return s.substr(0, i-1);
}
}
return s;
}
// 格式化显示字符串
formateStr = function(name, regex, rowLen) {
var array = name;
if(regex) {
array = name.split(regex);
}
var index = 0;
var item = array[0];
for(var i = index, len = array.length; i < len; i++) {
for (var j = i + 1; j < len; j++) {
var temp2 = array[j];
var itemLen = item.replace(/[^\x00-\xff]/g, "**").length;
var temp2Len = temp2.replace(/[^\x00-\xff]/g, "**").length;
if (itemLen + temp2Len + 1 > rowLen) {
if (itemLen > rowLen) {
var temp1 = subByeStr(array[i], rowLen);
item = array[i].substring(temp1.length, array[i].length);
array[i] = temp1 + "<br />" + item;
i = i - 1;
} else {
item = array[j];
array[j - 1] = array[j - 1] + '<br />';
i = j - 1;
}
break;
} else {
item = item + ' ' + array[j];
}
}
}
return array.join(' ');
};
/**
* 转义特殊字符,如：> <转换为><
* @param str
* @return
*/
function unescapeHTML(str){
$tmp = $("<div></div>").html(str);
nodes = $tmp.contents();
nl = nodes.length;
if (nl > 0) {
var a = [];
for (var i=0, il=nl; i<il; i++) {
a.push(nodes[i].nodeValue);
}
return a.join('');
}
return '';
}
/**
* 格式化数字.
* @param num
* @param exponent
* @return
* format("12345.67","#,###.00") 12,345.67
* format("12345.67","￥#,###元0角0分") ￥12,345元6角7分
*/
function formatNumberPex(v, formatString){
v = v + "";
var parterns = formatString.split(".");
var numbers = v.split(".");
var lparterns = parterns[0].split("");
var lparternsbak = parterns[0].split("");
var lnumbers = numbers[0].split("");
var lkeep = "";
var rkeep = "";
//得到左侧要替换的部分
var lplaces = [];
for(var i=0;i<lparterns.length;i++){
var parternchar = lparterns[i];
if (parternchar == "#" || parternchar == "0"){
lplaces.push(i);
}
}
//替换左侧，左侧有数字才要替换，以避免v = .99型的数字而产生错误
if (lnumbers[0] && lnumbers[0].length>0){
var numberIndex = lnumbers.length - 1;
var replaced = 0;
for(var i=lplaces.length - 1;i>=0;i--){
replaced ++; //被替换的字符数量
var place = lplaces[i];
lparterns[place] = lnumbers[numberIndex];
if (numberIndex == 0) {
break;
}
numberIndex--;
}
//处理以#为第一个格式（#前可能有非0的其他串也在此范围）的格式串，对于以#开头的格式串，将不会截取数字串，要补齐
var lstartIdx = lplaces[0];
if (lparternsbak[lstartIdx]=="#"){
if (lnumbers.length > replaced){
var idx = lnumbers.length - replaced;
for(var i=0;i<idx;i++){
lkeep += lnumbers[i];
}
lparterns[lstartIdx] = lkeep + lparterns[lstartIdx];
}
}
}
//替换右侧
if (parterns[1] && parterns[1].length > 0){
var rparterns = parterns[1].split("");
var rparternsbak = parterns[1].split("");
if (numbers[1] && numbers[1].length>0){
var rnumbers = numbers[1].split("");
//得到右侧将要替换的部分
var rplaces = [];
for(var i=0;i<rparterns.length;i++){
var parternchar = rparterns[i];
if (parternchar == "#" || parternchar == "0"){
rplaces.push(i);
}
}
var replaced = 0;
for(var i=0;i<rplaces.length;i++){
replaced ++; //被替换的字符数量
var place = rplaces[i];
rparterns[place] = rnumbers[i];
if (i==rnumbers.length - 1){
break;
}
}
//处理以#结束的（#后有非0的串也在此范围）
var rlastIdx = rplaces[rplaces.length-1];
if (rparternsbak[rlastIdx]=="#"){
for(var i=replaced-1;i<rnumbers.length;i++){
rkeep += rnumbers[i];
}
rparterns[rlastIdx] += rkeep;
}
}
}
for(var i=0;i<lparterns.length;i++){
if (lparterns[i]=="#"){
lparterns[i] = "";
}
}
var result = lparterns.join("");
if (parterns[1]){
for(var i=0;i<rparterns.length;i++){
if (rparterns[i] == "#"){
rparterns[i] = "";
}
}
result += "." + rparterns.join("");
}
//第一位不能为,号
if (result.substring(0,1)==","){
result = result.substring(1);
}
//最后一位也不能为,号
if (result.substring(result.length-1)==","){
result = result.substring(0,result.length);
}
return result;
}
//显示操作信息（type：成功[yes或success],警告[warn或warning],失败[error或wrong]）
function show_msg_tips_batch_imp(type,msg){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
type='yes';
if('warn'==type || 'warning'==type)
type='warn';
if('error'==type || 'wrong'==type)
type='wrong';
var classs = 'tips_'+type+'_msg';
var tip = $("#tip_msg_box");
tip.find("#tips_msg").html(msg);
tip.find("#tips_msg").removeClass();
tip.find("#tips_msg").addClass(classs);
tip.show();
//tip.click(function(){$(this).hide();});
tip.find(".tips_close").click(function(){$(tip).hide();});
}
//自动匹配人员列表
function init_auhorname(){
$("#authorName,#psnName").autocomplete(ctxpath+"/ac/rolPsnUnitIns.action", {
width: 220,
highlight: function(value,term){return value;},
max:10,
dataType:'JSON',
scroll: false,
cacheLength: 0,
extraParams: {'deptId':function(){
$("#psnId").val("");
var deptId = $("#queryUnitId").attr('unitId');
if(deptId == "0"){//rol-2747 选择other部门后，控制人员只取other下的
return "-1";
}
return deptId;
}},
formatItem: function(data, i, n, value, term) {
if(data.unitName != ""){
return data.psnName + "("+data.unitName+")";
}
return data.psnName;
},
parse: function(data){// 转化数据
var rows = data;
var parsed = [];
for(var i=0;i<rows.length;i++){
var item = rows[i];
parsed.push({data:item,value:item.cpPsnId.toString(),result:item.psnName});
}
return parsed;
}
}).result(function(event, data, formatted) {// 返回result
$("#psnId").val(data.cpPsnId);
});
}
/**
* 检查用户是否已登录.
* @returns {Boolean}
*/
checkUserLogin=function(){
var flag = true;
$.ajax({
async: false,
url : ctxpath+"/archiveFiles/ajaxCheckUserLogin",
type : 'post',
dataType:'json',
success : function(data) {
if(data.result == "fail" ){
flag = false;
jConfirm(project_view.noLogin, project_view.prompt,function(result){
if(result)
location.href = ctxpath+"?service=" + encodeURIComponent(location.href);
});
}
}
});
return flag;
} |
//在弹出框中显示提示信息 | random_line_split |
rol_common.js | // 防止事件冒泡
function stopBubble(e) {
// If an event object is provided, then this is a non-IE browser
if ( e && e.stopPropagation )
// and therefore it supports the W3C stopPropagation() method
e.stopPropagation();
else
// Otherwise, we need to use the Internet Explorer
// way of cancelling event bubbling
window.event.cancelBubble = true;
}
//显示更多操作菜单
function show_more_operation(btn,div_id,div_bg){
var div_obj = $("#"+div_id);
var bg_obj = null;
if(div_bg){
bg_obj = $("#"+div_bg);
}
if(div_obj.is(":hidden")){
div_obj.show();
//定位
div_obj.css("left",$(btn).offset().left);
div_obj.css("top",$(btn).offset().top+23);
div_obj.css("zIndex","1000");
if(bg_obj){
bg_obj.css("left",$(div_obj).offset().left-1);
bg_obj.css("top",$(div_obj).offset().top);
div_obj.css("zIndex","1000");
bg_obj.css("width",$(div_obj).width() +"px");
bg_obj.css("height",$(div_obj).height() +"px");
bg_obj.show();
}
}else{
div_obj.hide();
if(bg_obj!=null)
bg_obj.hide();
return;
}
//标示鼠标是否移入DIV
var flag = true;
div_obj.bind("mouseover",function(){
flag = false;
});
//鼠标移出，将DIV隐藏
div_obj.bind("mouseleave",function(){
flag = true;
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
});
//点击链接，将DIV隐藏
$('#more_operation>a').click(function(){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
});
//2秒还未进入，关闭
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
}
//事件处理函数，用户DIV层失去焦点时，隐藏out_div_hidden层
//$(document).bind("click",hidden_out_div);
function hidden_out_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("out_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".out_div_hidden").hide();
}
}
//事件处理函数，用户DIV层失去焦点时，隐藏outeditfd_div_hidden层,同时删除页面上的left_nav_infolink_high样式的样式
//$(document).bind("click",hidden_outeditfd_div);
function hidden_outeditfd_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("outeditfd_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".outeditfd_div_hidden").hide();
$(".left_nav_infolink_high").removeClass("left_nav_infolink_high");
}
}
//打开指定定位到按钮下方的层，该层需指定class:hidden_out_div
function openFloatDiv(btn,div_id){
var obj = $('#'+div_id);
if($(obj).is(":hidden")){
//失去焦点，需要隐藏带hidden_out_div class的层
// $(document).bind("click",hidden_out_div);
//显示层，需要延迟显示
setTimeout(function(){
$(obj).show();
//定位
$(obj).css("left",$(btn).offset().left);
$(obj).css("top",$(btn).offset().top+24);
| nav_open");
}
}
//左边菜单展开，关闭替换图标
function replaceImg(obj){
var img = $(obj).find("img");
var src = img.attr("src");
if(src.indexOf('open')>0){
img.attr("src",src.replace("open","close"));
}else{
img.attr("src",src.replace("close","open"));
}
}
//打开左侧菜单，根据设置的.info样式
function open_left_nav(){
$("#left_nav").find(".info")
.each(function(){
$(this).parent().find(">div:first-child").trigger("click");
});
}
//左侧菜单鼠标事件
function bind_left_nav_mouse()
{
//鼠标在上面高亮显示
$("#left_nav div.infolink").mouseover(function(){
$(this).addClass("infolink_hover");
});
//鼠标移走移除高亮
$("#left_nav div.infolink").mouseout(function(){
$(this).removeClass("infolink_hover");
});
}
//左侧菜单编辑文件夹
function bind_left_nav_folder()
{
var left_nav = $("#left_nav");
left_nav.find('div.edit_folder').click(function(){
//失去焦点，需要隐藏带hidden_out_div class的层
$(document).bind("click",hidden_outeditfd_div);
var top = $(this).offset().top;
var left = $(this).offset().left;
var fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("top",top);
edit_div.css("left",left);
edit_div.find(".folder_id").val(fdid);
edit_div.find(".folder_name").val(fdname);
},100);
});
//需要编辑文件夹的，高亮显示，同时显示编辑图片
left_nav.find(".edit_folder_div").mouseover(function(){
$(this).addClass("infolink_hover");
$(this).find(".edit_folder").show();
});
//需要编辑文件夹的，移除高亮显示，同时不显示编辑图片
left_nav.find(".edit_folder_div").mouseout(function(){
$(this).find(".edit_folder").hide();
$(this).removeClass("infolink_hover");
});
}
//显示操作正确信息
function show_yes_tips(tip_id,msg,time)
{
if(!time || time < 3000){
time = 3000;
}
$.scmtips.show("success",msg,null,time);
}
//显示操作错误信息
function show_wrong_tips(tip_id,msg,time)
{
if(!time || time <3000){
time = 3000;
}
$.scmtips.show("error",msg, null,3000);
}
//杰青近五年代表性论著操作错误信息
function show_unlimit_wrong_tips(tip_id,msg)
{
$.scmtips.show("error",msg, null,3000);
}
//在弹出框中显示提示信息
function show_msg_tips_newdiv(type,msg,id){
if(!type || !msg)
return;
var time=3000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg,null,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg, width,time);
}
function rol_show_msg_tips(type,msg,rowCount){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg);
}
//手动关闭显示的操作消息
function close_msg_tips(){
$("#tip_msg_box").hide();
}
//替换HMTL特殊字符,注意替换顺序
function covertHmtl(str)
{
str = str.replace(/\&/gi,"&");
str = str.replace(/\>/gi,">");
str = str.replace(/\</gi,"<");
str = str.replace(/\n/gi,"<br/>");
str = str.replace(/\s/gi," ");
return str;
}
//将textarea转换成span，过滤掉特殊字符
function refreshTextArea()
{
var objs = $(".rep_textarea");
for(var i = 0; i < objs.size(); i++)
{
var tag=objs[i];
var p = tag.parentNode;
if(!p) p = document;
if(/\r(\n)?/g.test(tag.value)==true)
{
newTag = getSpan(tag.value.replace(/\r(\n)?/g,"<br>"));
}
else
{
newTag = getSpan(tag.value);
}
p.replaceChild(newTag,tag);
}
}
function getSpan(text)
{
var node = document.createElement("span");
node.innerHTML=text+" ";
return node;
}
//帮助信息
function bindHelps()
{
$(".help_prompt").bind("click",function(){
var help_prompt_left = $(this).find(".help_prompt_left");
if(help_prompt_left.is(":visible")){
help_prompt_left.hide();
$(this).find(".help_prompt_left1").show();
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
help_prompt_left.show();
$(this).find(".help_prompt_left1").hide();
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
$(".help_prompt").each(function(){
var isShow = $(this).find(".help_prompt_left1").is(":visible")? true : false;
if(isShow){
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
//链接不进行事件冒泡
$(".help_prompt").find(".help_prompt_left1 a").bind("click",function(event){
stopBubble(event);
});
}
//显示隐藏检索条件
function view_search(){
var search_block = $(".search_block");
if(!search_block.is(":hidden")){
$("#isSearchShow").val(0);
$("#view_search_block_link").show();
$("#hide_search_block_link").hide();
search_block.hide();
}else{
$("#view_search_block_link").hide();
$("#hide_search_block_link").show();
$("#isSearchShow").val(1);
search_block.show();
}
}
//验证邮件格式是否合法
function isEmail(email) {
return /^((([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+(\.([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+)*)|((\x22)((((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(([\x01-\x08\x0b\x0c\x0e-\x1f\x7f]|\x21|[\x23-\x5b]|[\x5d-\x7e]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(\\([\x01-\x09\x0b\x0c\x0d-\x7f]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]))))*(((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(\x22)))@((([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.)+(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.?$/i.test(email);
}
//产生数字下拉，例如年度等
function genNumDescOption(start,end,select_id){
if(start > end){
var tmp = start;
start = end;
end = tmp;
}
var select = $("#"+select_id);
for(;end >= start;end--){
var option = $("<option value='"+end+"' select=''>"+end+"</option>");
select.append(option);
}
}
//判断是否是不是中文
function isChinStr(s){
var regu = "[\w\W]*[\u4e00-\u9fa5][\w\W]*";
var re = new RegExp(regu);
if (s=="")
return false;
if (re.test(s)) {
return true;
}else{
return false;
}
}
//判断是否是数字
function isNumStr(s) {
var patrn=/^[0-9]{1,20}$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字母、数字、下划线
function isCharsOrNum(s) {
var patrn=/^(\w)$/;
if (!patrn.exec(s))
return false;
return true ;
}
//字母、数字
function isChrOrNum(s){
var patrn=/^[A-Za-z0-9]+$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//是否是中文或者是英文和数字
function isParamStr(s){
var flag = false;
if(isChinStr(s))
flag =true;
if(isChrOrNum(s))
flag =true;
return flag;
}
//限制textarea最多输入
function setTextareaMaxLength(maxLength){
$("textarea").keyup(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
$("textarea").blur(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
}
//判断是否是特殊字符
function isSpecial(s){
var str = '",.;[]{}+=|\*&^%$#@!~()-/?<>';
var flag = false;
if($.trim(s).length>0){
for(var i=0;i<str.length;i++){
if(s.indexOf(str.charAt(i))>=0){
flag=true;
break;
}
}
if(flag)
return true;
}
var patrn = /^[^<]*(<(.|\s)+>)[^>]*$|^#$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字符串真实的长度
function getStrRealLength(str){
return str.replace(/[^\x00-\xff]/gi, "--").replace(/[wW]/gi, "--").length;
}
//字符串缩略
function subStrBreviary(str,maxLength){
var realLength = getStrRealLength(str);
if(realLength <= maxLength){
return str;
}
//at least one half
var tmpStr = str.substring(0,maxLength/2);
var tmpLength = getStrRealLength(tmpStr);
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
//cut
for(var i = maxLength/2;i < realLength;i++){
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
tmpStr = tmpStr + str.charAt(i);
var tmpLength = getStrRealLength(tmpStr);
}
}
subByeStr = function(s, n) {
var r = /[^\x00-\xff]/g; // 其中x00-\xff代表非汉字编码
var byteLen = s.replace(r, "**").length; // 获取字符串的字节长度，其中replace(r, "**")表示讲一个中文字体换成两个英文符号
if(byteLen <= n) return s; // 如果字节长度小于或者等于要截取的字节长度，直接返回原字符串
var m = Math.floor(n/2); // 因为要截取的字符串一定大于等于字符串的长度的一半，所以从字符串长度的一半开始
for(var i=m; i<s.length; i++) {
strLen = s.substr(0, i).replace(r, "**").length;
if (strLen == n) {
return s.substr(0, i);
} else if (strLen > n) {
return s.substr(0, i-1);
}
}
return s;
}
// 格式化显示字符串
formateStr = function(name, regex, rowLen) {
var array = name;
if(regex) {
array = name.split(regex);
}
var index = 0;
var item = array[0];
for(var i = index, len = array.length; i < len; i++) {
for (var j = i + 1; j < len; j++) {
var temp2 = array[j];
var itemLen = item.replace(/[^\x00-\xff]/g, "**").length;
var temp2Len = temp2.replace(/[^\x00-\xff]/g, "**").length;
if (itemLen + temp2Len + 1 > rowLen) {
if (itemLen > rowLen) {
var temp1 = subByeStr(array[i], rowLen);
item = array[i].substring(temp1.length, array[i].length);
array[i] = temp1 + "<br />" + item;
i = i - 1;
} else {
item = array[j];
array[j - 1] = array[j - 1] + '<br />';
i = j - 1;
}
break;
} else {
item = item + ' ' + array[j];
}
}
}
return array.join(' ');
};
/**
* 转义特殊字符,如：> <转换为><
* @param str
* @return
*/
function unescapeHTML(str){
$tmp = $("<div></div>").html(str);
nodes = $tmp.contents();
nl = nodes.length;
if (nl > 0) {
var a = [];
for (var i=0, il=nl; i<il; i++) {
a.push(nodes[i].nodeValue);
}
return a.join('');
}
return '';
}
/**
* 格式化数字.
* @param num
* @param exponent
* @return
* format("12345.67","#,###.00") 12,345.67
* format("12345.67","￥#,###元0角0分") ￥12,345元6角7分
*/
function formatNumberPex(v, formatString){
v = v + "";
var parterns = formatString.split(".");
var numbers = v.split(".");
var lparterns = parterns[0].split("");
var lparternsbak = parterns[0].split("");
var lnumbers = numbers[0].split("");
var lkeep = "";
var rkeep = "";
//得到左侧要替换的部分
var lplaces = [];
for(var i=0;i<lparterns.length;i++){
var parternchar = lparterns[i];
if (parternchar == "#" || parternchar == "0"){
lplaces.push(i);
}
}
//替换左侧，左侧有数字才要替换，以避免v = .99型的数字而产生错误
if (lnumbers[0] && lnumbers[0].length>0){
var numberIndex = lnumbers.length - 1;
var replaced = 0;
for(var i=lplaces.length - 1;i>=0;i--){
replaced ++; //被替换的字符数量
var place = lplaces[i];
lparterns[place] = lnumbers[numberIndex];
if (numberIndex == 0) {
break;
}
numberIndex--;
}
//处理以#为第一个格式（#前可能有非0的其他串也在此范围）的格式串，对于以#开头的格式串，将不会截取数字串，要补齐
var lstartIdx = lplaces[0];
if (lparternsbak[lstartIdx]=="#"){
if (lnumbers.length > replaced){
var idx = lnumbers.length - replaced;
for(var i=0;i<idx;i++){
lkeep += lnumbers[i];
}
lparterns[lstartIdx] = lkeep + lparterns[lstartIdx];
}
}
}
//替换右侧
if (parterns[1] && parterns[1].length > 0){
var rparterns = parterns[1].split("");
var rparternsbak = parterns[1].split("");
if (numbers[1] && numbers[1].length>0){
var rnumbers = numbers[1].split("");
//得到右侧将要替换的部分
var rplaces = [];
for(var i=0;i<rparterns.length;i++){
var parternchar = rparterns[i];
if (parternchar == "#" || parternchar == "0"){
rplaces.push(i);
}
}
var replaced = 0;
for(var i=0;i<rplaces.length;i++){
replaced ++; //被替换的字符数量
var place = rplaces[i];
rparterns[place] = rnumbers[i];
if (i==rnumbers.length - 1){
break;
}
}
//处理以#结束的（#后有非0的串也在此范围）
var rlastIdx = rplaces[rplaces.length-1];
if (rparternsbak[rlastIdx]=="#"){
for(var i=replaced-1;i<rnumbers.length;i++){
rkeep += rnumbers[i];
}
rparterns[rlastIdx] += rkeep;
}
}
}
for(var i=0;i<lparterns.length;i++){
if (lparterns[i]=="#"){
lparterns[i] = "";
}
}
var result = lparterns.join("");
if (parterns[1]){
for(var i=0;i<rparterns.length;i++){
if (rparterns[i] == "#"){
rparterns[i] = "";
}
}
result += "." + rparterns.join("");
}
//第一位不能为,号
if (result.substring(0,1)==","){
result = result.substring(1);
}
//最后一位也不能为,号
if (result.substring(result.length-1)==","){
result = result.substring(0,result.length);
}
return result;
}
//显示操作信息（type：成功[yes或success],警告[warn或warning],失败[error或wrong]）
function show_msg_tips_batch_imp(type,msg){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
type='yes';
if('warn'==type || 'warning'==type)
type='warn';
if('error'==type || 'wrong'==type)
type='wrong';
var classs = 'tips_'+type+'_msg';
var tip = $("#tip_msg_box");
tip.find("#tips_msg").html(msg);
tip.find("#tips_msg").removeClass();
tip.find("#tips_msg").addClass(classs);
tip.show();
//tip.click(function(){$(this).hide();});
tip.find(".tips_close").click(function(){$(tip).hide();});
}
//自动匹配人员列表
function init_auhorname(){
$("#authorName,#psnName").autocomplete(ctxpath+"/ac/rolPsnUnitIns.action", {
width: 220,
highlight: function(value,term){return value;},
max:10,
dataType:'JSON',
scroll: false,
cacheLength: 0,
extraParams: {'deptId':function(){
$("#psnId").val("");
var deptId = $("#queryUnitId").attr('unitId');
if(deptId == "0"){//rol-2747 选择other部门后，控制人员只取other下的
return "-1";
}
return deptId;
}},
formatItem: function(data, i, n, value, term) {
if(data.unitName != ""){
return data.psnName + "("+data.unitName+")";
}
return data.psnName;
},
parse: function(data){// 转化数据
var rows = data;
var parsed = [];
for(var i=0;i<rows.length;i++){
var item = rows[i];
parsed.push({data:item,value:item.cpPsnId.toString(),result:item.psnName});
}
return parsed;
}
}).result(function(event, data, formatted) {// 返回result
$("#psnId").val(data.cpPsnId);
});
}
/**
* 检查用户是否已登录.
* @returns {Boolean}
*/
checkUserLogin=function(){
var flag = true;
$.ajax({
async: false,
url : ctxpath+"/archiveFiles/ajaxCheckUserLogin",
type : 'post',
dataType:'json',
success : function(data) {
if(data.result == "fail" ){
flag = false;
jConfirm(project_view.noLogin, project_view.prompt,function(result){
if(result)
location.href = ctxpath+"?service=" + encodeURIComponent(location.href);
});
}
}
});
return flag;
} | $(obj).css("zIndex",1000);
$(obj).css("height",$(obj).find(".float_div_content").height()+70)
},100);
}else{
$(obj).hide();
}
}
//左菜单展开，关闭
function switch_left_nav(obj){
var div = $(obj).parent();
if($(obj).hasClass("left_nav_open"))
{
div.find(">div:not(div:first-child)").hide();
$(obj).removeClass("left_nav_open");
}else{
div.find(">div").show();
$(obj).addClass("left_ | conditional_block |
rol_common.js | // 防止事件冒泡
function stopBubble(e) {
// If an event object is provided, then this is a non-IE browser
if ( e && e.stopPropagation )
// and therefore it supports the W3C stopPropagation() method
e.stopPropagation();
else
// Otherwise, we need to use the Internet Explorer
// way of cancelling event bubbling
window.event.cancelBubble = true;
}
//显示更多操作菜单
function show_more_operation(btn,div_id,div_bg){
var div_obj = $("#"+div_id);
var bg_obj = null;
if(div_bg){
bg_obj = $("#"+div_bg);
}
if(div_obj.is(":hidden")){
div_obj.show();
//定位
div_obj.css("left",$(btn).offset().left);
div_obj.css("top",$(btn).offset().top+23);
div_obj.css("zIndex","1000");
if(bg_obj){
bg_obj.css("left",$(div_obj).offset().left-1);
bg_obj.css("top",$(div_obj).offset().top);
div_obj.css("zIndex","1000");
bg_obj.css("width",$(div_obj).width() +"px");
bg_obj.css("height",$(div_obj).height() +"px");
bg_obj.show();
}
}else{
div_obj.hide();
if(bg_obj!=null)
bg_obj.hide();
return;
}
//标示鼠标是否移入DIV
var flag = true;
div_obj.bind("mouseover",function(){
flag = false;
});
//鼠标移出，将DIV隐藏
div_obj.bind("mouseleave",function(){
flag = true;
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
});
//点击链接，将DIV隐藏
$('#more_operation>a').click(function(){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
});
//2秒还未进入，关闭
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
}
//事件处理函数，用户DIV层失去焦点时，隐藏out_div_hidden层
//$(document).bind("click",hidden_out_div);
function hidden_out_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("out_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".out_div_hidden").hide();
}
}
//事件处理函数，用户DIV层失去焦点时，隐藏outeditfd_div_hidden层,同时删除页面上的left_nav_infolink_high样式的样式
//$(document).bind("click",hidden_outeditfd_div);
function hidden_outeditfd_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("outeditfd_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".outeditfd_div_hidden").hide();
$(".left_nav_infolink_high").removeClass("left_nav_infolink_high");
}
}
//打开指定定位到按钮下方的层，该层需指定class:hidden_out_div
function openFloatDiv(btn,div_id){
var obj = $('#'+div_id);
if($(obj).is(":hidden")){
//失去焦点，需要隐藏带hidden_out_div class的层
// $(document).bind("click",hidden_out_div);
//显示层，需要延迟显示
setTimeout(function(){
$(obj).show();
//定位
$(obj).css("left",$(btn).offset().left);
$(obj).css("top",$(btn).offset().top+24);
$(obj).css("zIndex",1000);
$(obj).css("height",$(obj).find(".float_div_content").height()+70)
},100);
}else{
$(obj).hide();
}
}
//左菜单展开，关闭
function switch_left_nav(obj){
var div = $(obj).parent();
if($(obj).hasClass("left_nav_open"))
{
div.find(">div:not(div:first-child)").hide();
$(obj).removeClass("left_nav_open");
}else{
div.find(">div").show();
$(obj).addClass("left_nav_open");
}
}
//左边菜单展开，关闭替换图标
function replaceImg(obj){
var img = $(obj).find("img");
var src = img.attr("src");
if(src.indexOf('open')>0){
img.attr("src",src.replace("open","close"));
}else{
img.attr("src",src.replace("close","open"));
}
}
//打开左侧菜单，根据设置的.info样式
function open_left_nav(){
$("#left_nav").find(".info")
.each(function(){
$(this).parent().find(">div:first-child").trigger("click");
});
}
//左侧菜单鼠标事件
function bind_left_nav_mouse()
{
//鼠标在上面高亮显示
$("#left_nav div.infolink").mouseover(function(){
$(this).addClass("infolink_hover");
});
//鼠标移走移除高亮
$("#left_nav div.infolink").mouseout(function(){
$(this).removeClass("infolink_hover");
});
}
//左侧菜单编辑文件夹
function bind_left_nav_folder()
{
var left_nav = $("#left_nav");
left_nav.find('div.edit_folder').click(function(){
//失去焦点，需要隐藏带hidden_out_div class的层
$(document).bind("click",hidden_outeditfd_div);
var top = $(this).offset().top;
var left = $(this).offset().left;
var fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("top",top);
edit_div.css("left",left);
edit_div.find(".folder_id").val(fdid);
edit_div.find(".folder_name").val(fdname);
},100);
});
//需要编辑文件夹的，高亮显示，同时显示编辑图片
left_nav.find(".edit_folder_div").mouseover(function(){
$(this).addClass("infolink_hover");
$(this).find(".edit_folder").show();
});
//需要编辑文件夹的，移除高亮显示，同时不显示编辑图片
left_nav.find(".edit_folder_div").mouseout(function(){
$(this).find(".edit_folder").hide();
$(this).removeClass("infolink_hover");
});
}
//显示操作正确信息
function show_yes_tips(tip_id,msg,time)
{
if(!time || time < 3000){
time = 3000;
}
$.scmtips.show("success",msg,null,time);
}
//显示操作错误信息
function show_wrong_tips(tip_id,msg,time)
{
if(!time || time <3000){
time = 3000;
}
$.scmtips.show("error",msg, null,3000);
}
//杰青近五年代表性论著操作错误信息
function show_unlimit_wrong_tips(tip_id,msg)
{
$.scmtips.show("error",msg, null,3000);
}
//在弹出框中显示提示信息
function show_msg_tips_newdiv(type,msg,id){
if(!type || !msg)
return;
var time=3000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg,null,time);
if('warn'==type || 'warning'==type)
$.s | rror",msg,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg, width,time);
}
function rol_show_msg_tips(type,msg,rowCount){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg);
}
//手动关闭显示的操作消息
function close_msg_tips(){
$("#tip_msg_box").hide();
}
//替换HMTL特殊字符,注意替换顺序
function covertHmtl(str)
{
str = str.replace(/\&/gi,"&");
str = str.replace(/\>/gi,">");
str = str.replace(/\</gi,"<");
str = str.replace(/\n/gi,"<br/>");
str = str.replace(/\s/gi," ");
return str;
}
//将textarea转换成span，过滤掉特殊字符
function refreshTextArea()
{
var objs = $(".rep_textarea");
for(var i = 0; i < objs.size(); i++)
{
var tag=objs[i];
var p = tag.parentNode;
if(!p) p = document;
if(/\r(\n)?/g.test(tag.value)==true)
{
newTag = getSpan(tag.value.replace(/\r(\n)?/g,"<br>"));
}
else
{
newTag = getSpan(tag.value);
}
p.replaceChild(newTag,tag);
}
}
function getSpan(text)
{
var node = document.createElement("span");
node.innerHTML=text+" ";
return node;
}
//帮助信息
function bindHelps()
{
$(".help_prompt").bind("click",function(){
var help_prompt_left = $(this).find(".help_prompt_left");
if(help_prompt_left.is(":visible")){
help_prompt_left.hide();
$(this).find(".help_prompt_left1").show();
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
help_prompt_left.show();
$(this).find(".help_prompt_left1").hide();
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
$(".help_prompt").each(function(){
var isShow = $(this).find(".help_prompt_left1").is(":visible")? true : false;
if(isShow){
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
//链接不进行事件冒泡
$(".help_prompt").find(".help_prompt_left1 a").bind("click",function(event){
stopBubble(event);
});
}
//显示隐藏检索条件
function view_search(){
var search_block = $(".search_block");
if(!search_block.is(":hidden")){
$("#isSearchShow").val(0);
$("#view_search_block_link").show();
$("#hide_search_block_link").hide();
search_block.hide();
}else{
$("#view_search_block_link").hide();
$("#hide_search_block_link").show();
$("#isSearchShow").val(1);
search_block.show();
}
}
//验证邮件格式是否合法
function isEmail(email) {
return /^((([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+(\.([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+)*)|((\x22)((((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(([\x01-\x08\x0b\x0c\x0e-\x1f\x7f]|\x21|[\x23-\x5b]|[\x5d-\x7e]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(\\([\x01-\x09\x0b\x0c\x0d-\x7f]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]))))*(((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(\x22)))@((([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.)+(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.?$/i.test(email);
}
//产生数字下拉，例如年度等
function genNumDescOption(start,end,select_id){
if(start > end){
var tmp = start;
start = end;
end = tmp;
}
var select = $("#"+select_id);
for(;end >= start;end--){
var option = $("<option value='"+end+"' select=''>"+end+"</option>");
select.append(option);
}
}
//判断是否是不是中文
function isChinStr(s){
var regu = "[\w\W]*[\u4e00-\u9fa5][\w\W]*";
var re = new RegExp(regu);
if (s=="")
return false;
if (re.test(s)) {
return true;
}else{
return false;
}
}
//判断是否是数字
function isNumStr(s) {
var patrn=/^[0-9]{1,20}$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字母、数字、下划线
function isCharsOrNum(s) {
var patrn=/^(\w)$/;
if (!patrn.exec(s))
return false;
return true ;
}
//字母、数字
function isChrOrNum(s){
var patrn=/^[A-Za-z0-9]+$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//是否是中文或者是英文和数字
function isParamStr(s){
var flag = false;
if(isChinStr(s))
flag =true;
if(isChrOrNum(s))
flag =true;
return flag;
}
//限制textarea最多输入
function setTextareaMaxLength(maxLength){
$("textarea").keyup(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
$("textarea").blur(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
}
//判断是否是特殊字符
function isSpecial(s){
var str = '",.;[]{}+=|\*&^%$#@!~()-/?<>';
var flag = false;
if($.trim(s).length>0){
for(var i=0;i<str.length;i++){
if(s.indexOf(str.charAt(i))>=0){
flag=true;
break;
}
}
if(flag)
return true;
}
var patrn = /^[^<]*(<(.|\s)+>)[^>]*$|^#$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字符串真实的长度
function getStrRealLength(str){
return str.replace(/[^\x00-\xff]/gi, "--").replace(/[wW]/gi, "--").length;
}
//字符串缩略
function subStrBreviary(str,maxLength){
var realLength = getStrRealLength(str);
if(realLength <= maxLength){
return str;
}
//at least one half
var tmpStr = str.substring(0,maxLength/2);
var tmpLength = getStrRealLength(tmpStr);
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
//cut
for(var i = maxLength/2;i < realLength;i++){
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
tmpStr = tmpStr + str.charAt(i);
var tmpLength = getStrRealLength(tmpStr);
}
}
subByeStr = function(s, n) {
var r = /[^\x00-\xff]/g; // 其中x00-\xff代表非汉字编码
var byteLen = s.replace(r, "**").length; // 获取字符串的字节长度，其中replace(r, "**")表示讲一个中文字体换成两个英文符号
if(byteLen <= n) return s; // 如果字节长度小于或者等于要截取的字节长度，直接返回原字符串
var m = Math.floor(n/2); // 因为要截取的字符串一定大于等于字符串的长度的一半，所以从字符串长度的一半开始
for(var i=m; i<s.length; i++) {
strLen = s.substr(0, i).replace(r, "**").length;
if (strLen == n) {
return s.substr(0, i);
} else if (strLen > n) {
return s.substr(0, i-1);
}
}
return s;
}
// 格式化显示字符串
formateStr = function(name, regex, rowLen) {
var array = name;
if(regex) {
array = name.split(regex);
}
var index = 0;
var item = array[0];
for(var i = index, len = array.length; i < len; i++) {
for (var j = i + 1; j < len; j++) {
var temp2 = array[j];
var itemLen = item.replace(/[^\x00-\xff]/g, "**").length;
var temp2Len = temp2.replace(/[^\x00-\xff]/g, "**").length;
if (itemLen + temp2Len + 1 > rowLen) {
if (itemLen > rowLen) {
var temp1 = subByeStr(array[i], rowLen);
item = array[i].substring(temp1.length, array[i].length);
array[i] = temp1 + "<br />" + item;
i = i - 1;
} else {
item = array[j];
array[j - 1] = array[j - 1] + '<br />';
i = j - 1;
}
break;
} else {
item = item + ' ' + array[j];
}
}
}
return array.join(' ');
};
/**
* 转义特殊字符,如：> <转换为><
* @param str
* @return
*/
function unescapeHTML(str){
$tmp = $("<div></div>").html(str);
nodes = $tmp.contents();
nl = nodes.length;
if (nl > 0) {
var a = [];
for (var i=0, il=nl; i<il; i++) {
a.push(nodes[i].nodeValue);
}
return a.join('');
}
return '';
}
/**
* 格式化数字.
* @param num
* @param exponent
* @return
* format("12345.67","#,###.00") 12,345.67
* format("12345.67","￥#,###元0角0分") ￥12,345元6角7分
*/
function formatNumberPex(v, formatString){
v = v + "";
var parterns = formatString.split(".");
var numbers = v.split(".");
var lparterns = parterns[0].split("");
var lparternsbak = parterns[0].split("");
var lnumbers = numbers[0].split("");
var lkeep = "";
var rkeep = "";
//得到左侧要替换的部分
var lplaces = [];
for(var i=0;i<lparterns.length;i++){
var parternchar = lparterns[i];
if (parternchar == "#" || parternchar == "0"){
lplaces.push(i);
}
}
//替换左侧，左侧有数字才要替换，以避免v = .99型的数字而产生错误
if (lnumbers[0] && lnumbers[0].length>0){
var numberIndex = lnumbers.length - 1;
var replaced = 0;
for(var i=lplaces.length - 1;i>=0;i--){
replaced ++; //被替换的字符数量
var place = lplaces[i];
lparterns[place] = lnumbers[numberIndex];
if (numberIndex == 0) {
break;
}
numberIndex--;
}
//处理以#为第一个格式（#前可能有非0的其他串也在此范围）的格式串，对于以#开头的格式串，将不会截取数字串，要补齐
var lstartIdx = lplaces[0];
if (lparternsbak[lstartIdx]=="#"){
if (lnumbers.length > replaced){
var idx = lnumbers.length - replaced;
for(var i=0;i<idx;i++){
lkeep += lnumbers[i];
}
lparterns[lstartIdx] = lkeep + lparterns[lstartIdx];
}
}
}
//替换右侧
if (parterns[1] && parterns[1].length > 0){
var rparterns = parterns[1].split("");
var rparternsbak = parterns[1].split("");
if (numbers[1] && numbers[1].length>0){
var rnumbers = numbers[1].split("");
//得到右侧将要替换的部分
var rplaces = [];
for(var i=0;i<rparterns.length;i++){
var parternchar = rparterns[i];
if (parternchar == "#" || parternchar == "0"){
rplaces.push(i);
}
}
var replaced = 0;
for(var i=0;i<rplaces.length;i++){
replaced ++; //被替换的字符数量
var place = rplaces[i];
rparterns[place] = rnumbers[i];
if (i==rnumbers.length - 1){
break;
}
}
//处理以#结束的（#后有非0的串也在此范围）
var rlastIdx = rplaces[rplaces.length-1];
if (rparternsbak[rlastIdx]=="#"){
for(var i=replaced-1;i<rnumbers.length;i++){
rkeep += rnumbers[i];
}
rparterns[rlastIdx] += rkeep;
}
}
}
for(var i=0;i<lparterns.length;i++){
if (lparterns[i]=="#"){
lparterns[i] = "";
}
}
var result = lparterns.join("");
if (parterns[1]){
for(var i=0;i<rparterns.length;i++){
if (rparterns[i] == "#"){
rparterns[i] = "";
}
}
result += "." + rparterns.join("");
}
//第一位不能为,号
if (result.substring(0,1)==","){
result = result.substring(1);
}
//最后一位也不能为,号
if (result.substring(result.length-1)==","){
result = result.substring(0,result.length);
}
return result;
}
//显示操作信息（type：成功[yes或success],警告[warn或warning],失败[error或wrong]）
function show_msg_tips_batch_imp(type,msg){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
type='yes';
if('warn'==type || 'warning'==type)
type='warn';
if('error'==type || 'wrong'==type)
type='wrong';
var classs = 'tips_'+type+'_msg';
var tip = $("#tip_msg_box");
tip.find("#tips_msg").html(msg);
tip.find("#tips_msg").removeClass();
tip.find("#tips_msg").addClass(classs);
tip.show();
//tip.click(function(){$(this).hide();});
tip.find(".tips_close").click(function(){$(tip).hide();});
}
//自动匹配人员列表
function init_auhorname(){
$("#authorName,#psnName").autocomplete(ctxpath+"/ac/rolPsnUnitIns.action", {
width: 220,
highlight: function(value,term){return value;},
max:10,
dataType:'JSON',
scroll: false,
cacheLength: 0,
extraParams: {'deptId':function(){
$("#psnId").val("");
var deptId = $("#queryUnitId").attr('unitId');
if(deptId == "0"){//rol-2747 选择other部门后，控制人员只取other下的
return "-1";
}
return deptId;
}},
formatItem: function(data, i, n, value, term) {
if(data.unitName != ""){
return data.psnName + "("+data.unitName+")";
}
return data.psnName;
},
parse: function(data){// 转化数据
var rows = data;
var parsed = [];
for(var i=0;i<rows.length;i++){
var item = rows[i];
parsed.push({data:item,value:item.cpPsnId.toString(),result:item.psnName});
}
return parsed;
}
}).result(function(event, data, formatted) {// 返回result
$("#psnId").val(data.cpPsnId);
});
}
/**
* 检查用户是否已登录.
* @returns {Boolean}
*/
checkUserLogin=function(){
var flag = true;
$.ajax({
async: false,
url : ctxpath+"/archiveFiles/ajaxCheckUserLogin",
type : 'post',
dataType:'json',
success : function(data) {
if(data.result == "fail" ){
flag = false;
jConfirm(project_view.noLogin, project_view.prompt,function(result){
if(result)
location.href = ctxpath+"?service=" + encodeURIComponent(location.href);
});
}
}
});
return flag;
} | cmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("e | identifier_body |
rol_common.js | // 防止事件冒泡
function stopBubble(e) {
// If an event object is provided, then this is a non-IE browser
if ( e && e.stopPropagation )
// and therefore it supports the W3C stopPropagation() method
e.stopPropagation();
else
// Otherwise, we need to use the Internet Explorer
// way of cancelling event bubbling
window.event.cancelBubble = true;
}
//显示更多操作菜单
function show_more_operation(btn,div_id,div_bg){
var div_obj = $("#"+div_id);
var bg_obj = null;
if(div_bg){
bg_obj = $("#"+div_bg);
}
if(div_obj.is(":hidden")){
div_obj.show();
//定位
div_obj.css("left",$(btn).offset().left);
div_obj.css("top",$(btn).offset().top+23);
div_obj.css("zIndex","1000");
if(bg_obj){
bg_obj.css("left",$(div_obj).offset().left-1);
bg_obj.css("top",$(div_obj).offset().top);
div_obj.css("zIndex","1000");
bg_obj.css("width",$(div_obj).width() +"px");
bg_obj.css("height",$(div_obj).height() +"px");
bg_obj.show();
}
}else{
div_obj.hide();
if(bg_obj!=null)
bg_obj.hide();
return;
}
//标示鼠标是否移入DIV
var flag = true;
div_obj.bind("mouseover",function(){
flag = false;
});
//鼠标移出，将DIV隐藏
div_obj.bind("mouseleave",function(){
flag = true;
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
});
//点击链接，将DIV隐藏
$('#more_operation>a').click(function(){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
});
//2秒还未进入，关闭
setTimeout(function(){
if(flag){
div_obj.hide();
if(bg_obj){
bg_obj.hide();
}
}
},2000);
}
//事件处理函数，用户DIV层失去焦点时，隐藏out_div_hidden层
//$(document).bind("click",hidden_out_div);
function hidden_out_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("out_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".out_div_hidden").hide();
}
}
//事件处理函数，用户DIV层失去焦点时，隐藏outeditfd_div_hidden层,同时删除页面上的left_nav_infolink_high样式的样式
//$(document).bind("click",hidden_outeditfd_div);
function hidden_outeditfd_div(evt) {
var element = evt.srcElement||evt.target;
var flag = true;
while (element) {
if ($(element).hasClass("outeditfd_div_hidden")){
flag = false;
break;
}
element = element.parentNode;
}
if (flag) {
$(".outeditfd_div_hidden").hide();
$(".left_nav_infolink_high").removeClass("left_nav_infolink_high");
}
}
//打开指定定位到按钮下方的层，该层需指定class:hidden_out_div
function openFloatDiv(btn,div_id){
var obj = $('#'+div_id);
if($(obj).is(":hidden")){
//失去焦点，需要隐藏带hidden_out_div class的层
// $(document).bind("click",hidden_out_div);
//显示层，需要延迟显示
setTimeout(function(){
$(obj).show();
//定位
$(obj).css("left",$(btn).offset().left);
$(obj).css("top",$(btn).offset().top+24);
$(obj).css("zIndex",1000);
$(obj).css("height",$(obj).find(".float_div_content").height()+70)
},100);
}else{
$(obj).hide();
}
}
//左菜单展开，关闭
function switch_left_nav(obj){
var div = $(obj).parent();
if($(obj).hasClass("left_nav_open"))
{
div.find(">div:not(div:first-child)").hide();
$(obj).removeClass("left_nav_open");
}else{
div.find(">div").show();
$(obj).addClass("left_nav_open");
}
}
//左边菜单展开，关闭替换图标
function replaceImg(obj){
var img = $(obj).find("img");
var src = img.attr("src");
if(src.indexOf('open')>0){
img.attr("src",src.replace("open","close"));
}else{
img.attr("src",src.replace("close","open"));
}
}
//打开左侧菜单，根据设置的.info样式
function open_left_nav(){
$("#left_nav").find(".info")
.each(function(){
$(this).parent().find(">div:first-child").trigger("click");
});
}
//左侧菜单鼠标事件
function bind_left_nav_mouse()
{
//鼠标在上面高亮显示
$("#left_nav div.infolink").mouseover(function(){
$(this).addClass("infolink_hover");
});
//鼠标移走移除高亮
$("#left_nav div.infolink").mouseout(function(){
$(this).removeClass("infolink_hover");
});
}
//左侧菜单编辑文件夹
function bind_left_nav_folder()
{
var left_nav = $("#left_nav");
left_nav.find('div.edit_folder').click(function(){
//失去焦点，需要隐藏带hidden_out_div class的层
$(document).bind("click",hidden_outeditfd_div);
var top = $(this).offset().top;
var left = $(this).offset().left;
var fdid = $(this).parent().find(".folder_id").val();
var fdname = $(this).parent().find(".folder_name").val();
var parent = $(this).parent();
setTimeout(function(){
//添加焦点事件
parent.addClass("left_nav_infolink_high");
var edit_div = $('#float_edit');
edit_div.css("display","block");
edit_div.css("top",top);
edit_div.css("left",left);
edit_div.find(".folder_id").val(fdid);
edit_div.find(".folder_name").val(fdname);
},100);
});
//需要编辑文件夹的，高亮显示，同时显示编辑图片
left_nav.find(".edit_folder_div").mouseover(function(){
$(this).addClass("infolink_hover");
$(this).find(".edit_folder").show();
});
//需要编辑文件夹的，移除高亮显示，同时不显示编辑图片
left_nav.find(".edit_folder_div").mouseout(function(){
$(this).find(".edit_folder").hide();
$(this).removeClass("infolink_hover");
});
}
//显示操作正确信息
function show_yes_tips(tip_id,msg,time)
{
if(!time || time < 3000){
time = 3000;
}
$.scmtips.show("success",msg,null,time);
}
//显示操作错误信息
function show_wrong_tips(tip_id,msg,time)
{
if(!time || time <3000){
time = 3000;
}
$.scmtips.show("error",msg, null,3000);
}
//杰青近五年代表性论著操作错误信息
function show_unlimit_wrong_tips(tip_id,msg)
{
$.scmtips.show("error",msg, null,3000);
}
//在弹出框中显示提示信息
function show_msg_tips_newdiv(type,msg,id){
if(!type || !msg)
return;
var time=3000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg,null,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg,null,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg,null,time);
}
function show_msg_tips(type,msg,width){
if(!type || !msg)
return;
var time=1000;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg, width,time);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg, width,time);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg, width,time);
}
function rol_show_msg_tips(type,msg,rowCount){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
$.scmtips.show("success",msg);
if('warn'==type || 'warning'==type)
$.scmtips.show("warn",msg);
if('error'==type || 'wrong'==type)
$.scmtips.show("error",msg);
}
//手动关闭显示的操作消息
function close_msg_tips(){
$("#tip_msg_box").hide();
}
//替换HMTL特殊字符,注意替换顺序
function covertHmtl(str)
{
str = str.replace(/\&/gi,"&");
str = str.replace(/\>/gi,">");
str = str.replace(/\</gi,"<");
str = str.replace(/\n/gi,"<br/>");
str = str.replace(/\s/gi," ");
return str;
}
//将textarea转换成span，过滤掉特殊字符
function refreshTextArea()
{
var objs = $(".rep_textarea");
for(var i = 0; i < objs.size(); i++)
{
var tag=objs[i];
var p = tag.parentNode;
if(!p) p = document;
if(/\r(\n)?/g.test(tag.value)==true)
{
newTag = getSpan(tag.value.replace(/\r(\n)?/g,"<br>"));
}
else
{
newTag = getSpan(tag.value);
}
p.replaceChild(newTag,tag);
}
}
function getSpan(text)
{
var node = document.createElement("span");
node.innerHTML=text+" ";
return node;
}
//帮助信息
function bindHelps()
{
$(".help_prompt").bind("click",function(){
var help_prompt_left = $(this).find(".help_prompt_left");
if(help_prompt_left.is(":visible")){
help_prompt_left.hide();
$(this).find(".help_prompt_left1").show();
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
help_prompt_left.show();
$(this).find(".help_prompt_left1").hide();
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
$(".help_prompt").each(function(){
var isShow = $(this).find(".help_prompt_left1").is(":visible")? true : false;
if(isShow){
$(this).find(".shear_head-down_opt").hide();
$(this).find(".shear_head-up_opt").show();
}else{
$(this).find(".shear_head-down_opt").show();
$(this).find(".shear_head-up_opt").hide();
}
});
//链接不进行事件冒泡
$(".help_prompt").find(".help_prompt_left1 a").bind("click",function(event){
stopBubble(event);
});
}
//显示隐藏检索条件
function view_search(){
var search_block = $(".search_block");
if(!search_block.is(":hidden")){
$("#isSearchShow").val(0);
$("#view_search_block_link").show();
$("#hide_search_block_link").hide();
search_block.hide();
}else{
$("#view_search_block_link").hide();
$("#hide_search_block_link").show();
$("#isSearchShow").val(1);
search_block.show();
}
}
//验证邮件格式是否合法
function isEmail(email) {
return /^((([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+(\.([a-z]|\d|[!#\$%&'\*\+\-\/=\?\^_`{\|}~]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])+)*)|((\x22)((((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(([\x01-\x08\x0b\x0c\x0e-\x1f\x7f]|\x21|[\x23-\x5b]|[\x5d-\x7e]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(\\([\x01-\x09\x0b\x0c\x0d-\x7f]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF]))))*(((\x20|\x09)*(\x0d\x0a))?(\x20|\x09)+)?(\x22)))@((([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|\d|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.)+(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])|(([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])([a-z]|\d|-|\.|_|~|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])*([a-z]|[\u00A0-\uD7FF\uF900-\uFDCF\uFDF0-\uFFEF])))\.?$/i.test(email);
}
//产生数字下拉，例如年度等
function genNumDescOption(start,end,select_id){
if(start > end){
var tmp = start;
start = end;
end = tmp;
}
var select = $("#"+select_id);
for(;end >= start;end--){
var option = $("<option value='"+end+"' select=''>"+end+"</option>");
select.append(option);
}
}
//判断是否是不是中文
function isChinStr(s){
var regu = "[\w\W]*[\u4e00-\u9fa5][\w\W]*";
var re = new RegExp(regu);
if (s=="")
return false;
if (re.test(s)) {
return true;
}else{
return false;
}
}
//判断是否是数字
function isNumStr(s) {
var patrn=/^[0-9]{1,20}$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字母、数字、下划线
function isCharsOrNum(s) {
var patrn=/^(\w)$/;
if (!patrn.exec(s))
return false;
return true ;
}
//字母、数字
function isChrOrNum(s){
var patrn=/^[A-Za-z0-9]+$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//是否是中文或者是英文和数字
function isParamStr(s){
var flag = false;
if(isChinStr(s))
flag =true;
if(isChrOrNum(s))
flag =true;
return flag;
}
//限制textarea最多输入
function setTextareaMaxLength(maxLength){
$("textarea").keyup(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
$("textarea").blur(function(){
var area=$(this).val();
if(area.length>maxLength){
$(this).val(area.substring(0,maxLength));
}
});
}
//判断是否是特殊字符
function isSpecial(s){
var str = '",.;[]{}+=|\*&^%$#@!~()-/?<>';
var flag = false;
if($.trim(s).length>0){
for(var i=0;i<str.length;i++){
if(s.indexOf(str.charAt(i))>=0){
flag=true;
| }
}
if(flag)
return true;
}
var patrn = /^[^<]*(<(.|\s)+>)[^>]*$|^#$/;
if (!patrn.exec(s)) return false ;
return true ;
}
//字符串真实的长度
function getStrRealLength(str){
return str.replace(/[^\x00-\xff]/gi, "--").replace(/[wW]/gi, "--").length;
}
//字符串缩略
function subStrBreviary(str,maxLength){
var realLength = getStrRealLength(str);
if(realLength <= maxLength){
return str;
}
//at least one half
var tmpStr = str.substring(0,maxLength/2);
var tmpLength = getStrRealLength(tmpStr);
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
//cut
for(var i = maxLength/2;i < realLength;i++){
if(maxLength - tmpLength < 1){
return tmpStr + "..";
}
tmpStr = tmpStr + str.charAt(i);
var tmpLength = getStrRealLength(tmpStr);
}
}
subByeStr = function(s, n) {
var r = /[^\x00-\xff]/g; // 其中x00-\xff代表非汉字编码
var byteLen = s.replace(r, "**").length; // 获取字符串的字节长度，其中replace(r, "**")表示讲一个中文字体换成两个英文符号
if(byteLen <= n) return s; // 如果字节长度小于或者等于要截取的字节长度，直接返回原字符串
var m = Math.floor(n/2); // 因为要截取的字符串一定大于等于字符串的长度的一半，所以从字符串长度的一半开始
for(var i=m; i<s.length; i++) {
strLen = s.substr(0, i).replace(r, "**").length;
if (strLen == n) {
return s.substr(0, i);
} else if (strLen > n) {
return s.substr(0, i-1);
}
}
return s;
}
// 格式化显示字符串
formateStr = function(name, regex, rowLen) {
var array = name;
if(regex) {
array = name.split(regex);
}
var index = 0;
var item = array[0];
for(var i = index, len = array.length; i < len; i++) {
for (var j = i + 1; j < len; j++) {
var temp2 = array[j];
var itemLen = item.replace(/[^\x00-\xff]/g, "**").length;
var temp2Len = temp2.replace(/[^\x00-\xff]/g, "**").length;
if (itemLen + temp2Len + 1 > rowLen) {
if (itemLen > rowLen) {
var temp1 = subByeStr(array[i], rowLen);
item = array[i].substring(temp1.length, array[i].length);
array[i] = temp1 + "<br />" + item;
i = i - 1;
} else {
item = array[j];
array[j - 1] = array[j - 1] + '<br />';
i = j - 1;
}
break;
} else {
item = item + ' ' + array[j];
}
}
}
return array.join(' ');
};
/**
* 转义特殊字符,如：> <转换为><
* @param str
* @return
*/
function unescapeHTML(str){
$tmp = $("<div></div>").html(str);
nodes = $tmp.contents();
nl = nodes.length;
if (nl > 0) {
var a = [];
for (var i=0, il=nl; i<il; i++) {
a.push(nodes[i].nodeValue);
}
return a.join('');
}
return '';
}
/**
* 格式化数字.
* @param num
* @param exponent
* @return
* format("12345.67","#,###.00") 12,345.67
* format("12345.67","￥#,###元0角0分") ￥12,345元6角7分
*/
function formatNumberPex(v, formatString){
v = v + "";
var parterns = formatString.split(".");
var numbers = v.split(".");
var lparterns = parterns[0].split("");
var lparternsbak = parterns[0].split("");
var lnumbers = numbers[0].split("");
var lkeep = "";
var rkeep = "";
//得到左侧要替换的部分
var lplaces = [];
for(var i=0;i<lparterns.length;i++){
var parternchar = lparterns[i];
if (parternchar == "#" || parternchar == "0"){
lplaces.push(i);
}
}
//替换左侧，左侧有数字才要替换，以避免v = .99型的数字而产生错误
if (lnumbers[0] && lnumbers[0].length>0){
var numberIndex = lnumbers.length - 1;
var replaced = 0;
for(var i=lplaces.length - 1;i>=0;i--){
replaced ++; //被替换的字符数量
var place = lplaces[i];
lparterns[place] = lnumbers[numberIndex];
if (numberIndex == 0) {
break;
}
numberIndex--;
}
//处理以#为第一个格式（#前可能有非0的其他串也在此范围）的格式串，对于以#开头的格式串，将不会截取数字串，要补齐
var lstartIdx = lplaces[0];
if (lparternsbak[lstartIdx]=="#"){
if (lnumbers.length > replaced){
var idx = lnumbers.length - replaced;
for(var i=0;i<idx;i++){
lkeep += lnumbers[i];
}
lparterns[lstartIdx] = lkeep + lparterns[lstartIdx];
}
}
}
//替换右侧
if (parterns[1] && parterns[1].length > 0){
var rparterns = parterns[1].split("");
var rparternsbak = parterns[1].split("");
if (numbers[1] && numbers[1].length>0){
var rnumbers = numbers[1].split("");
//得到右侧将要替换的部分
var rplaces = [];
for(var i=0;i<rparterns.length;i++){
var parternchar = rparterns[i];
if (parternchar == "#" || parternchar == "0"){
rplaces.push(i);
}
}
var replaced = 0;
for(var i=0;i<rplaces.length;i++){
replaced ++; //被替换的字符数量
var place = rplaces[i];
rparterns[place] = rnumbers[i];
if (i==rnumbers.length - 1){
break;
}
}
//处理以#结束的（#后有非0的串也在此范围）
var rlastIdx = rplaces[rplaces.length-1];
if (rparternsbak[rlastIdx]=="#"){
for(var i=replaced-1;i<rnumbers.length;i++){
rkeep += rnumbers[i];
}
rparterns[rlastIdx] += rkeep;
}
}
}
for(var i=0;i<lparterns.length;i++){
if (lparterns[i]=="#"){
lparterns[i] = "";
}
}
var result = lparterns.join("");
if (parterns[1]){
for(var i=0;i<rparterns.length;i++){
if (rparterns[i] == "#"){
rparterns[i] = "";
}
}
result += "." + rparterns.join("");
}
//第一位不能为,号
if (result.substring(0,1)==","){
result = result.substring(1);
}
//最后一位也不能为,号
if (result.substring(result.length-1)==","){
result = result.substring(0,result.length);
}
return result;
}
//显示操作信息（type：成功[yes或success],警告[warn或warning],失败[error或wrong]）
function show_msg_tips_batch_imp(type,msg){
if(!type || !msg)
return;
if('success'==type || 'yes'==type)
type='yes';
if('warn'==type || 'warning'==type)
type='warn';
if('error'==type || 'wrong'==type)
type='wrong';
var classs = 'tips_'+type+'_msg';
var tip = $("#tip_msg_box");
tip.find("#tips_msg").html(msg);
tip.find("#tips_msg").removeClass();
tip.find("#tips_msg").addClass(classs);
tip.show();
//tip.click(function(){$(this).hide();});
tip.find(".tips_close").click(function(){$(tip).hide();});
}
//自动匹配人员列表
function init_auhorname(){
$("#authorName,#psnName").autocomplete(ctxpath+"/ac/rolPsnUnitIns.action", {
width: 220,
highlight: function(value,term){return value;},
max:10,
dataType:'JSON',
scroll: false,
cacheLength: 0,
extraParams: {'deptId':function(){
$("#psnId").val("");
var deptId = $("#queryUnitId").attr('unitId');
if(deptId == "0"){//rol-2747 选择other部门后，控制人员只取other下的
return "-1";
}
return deptId;
}},
formatItem: function(data, i, n, value, term) {
if(data.unitName != ""){
return data.psnName + "("+data.unitName+")";
}
return data.psnName;
},
parse: function(data){// 转化数据
var rows = data;
var parsed = [];
for(var i=0;i<rows.length;i++){
var item = rows[i];
parsed.push({data:item,value:item.cpPsnId.toString(),result:item.psnName});
}
return parsed;
}
}).result(function(event, data, formatted) {// 返回result
$("#psnId").val(data.cpPsnId);
});
}
/**
* 检查用户是否已登录.
* @returns {Boolean}
*/
checkUserLogin=function(){
var flag = true;
$.ajax({
async: false,
url : ctxpath+"/archiveFiles/ajaxCheckUserLogin",
type : 'post',
dataType:'json',
success : function(data) {
if(data.result == "fail" ){
flag = false;
jConfirm(project_view.noLogin, project_view.prompt,function(result){
if(result)
location.href = ctxpath+"?service=" + encodeURIComponent(location.href);
});
}
}
});
return flag;
} | break;
| identifier_name |
ranker_ltr.py | """
Uses Learning to Rank to rank entities
@author: Faegheh Hasibi
"""
from datetime import datetime
import pickle
from nordlys.erd.features.query_sim_feat import QuerySimFeat
from nordlys.ml.cross_validation import CrossValidation
from nordlys.erd.features.entity_feat import EntityFeat
from nordlys.erd.features.mention_feat import MentionFeat
from nordlys.erd.features.entity_mention_feat import EntityMentionFeat
from nordlys.erd import econfig
from nordlys.erd.groundtruth import erd_gt, ysqle_erd_gt, ysqle_gt
from nordlys.erd.query.query import Query
from nordlys.erd.ml.cer_instances import CERInstances, CERInstance
from nordlys.ml.ml import ML
from nordlys.retrieval.lucene_tools import Lucene
class RankerLTR(object):
"""
Attributes:
tree: int, Number of trees
depth: int, depth of the trees
alpha: float, learning rate
model: the trained model
"""
def __init__(self, commonness_th=None, sf_source=None, filter=True, model=None, config={}):
self.commonness_th = commonness_th
self.sf_source = sf_source
self.filter = filter
self.config = config
self.model = model
self.ml = ML(config) #if config is not None else None
def train(self, inss, model_file=None, feat_imp_file=None):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, the learned model
"""
config = self.config
if model_file is not None:
config['save_model'] = model_file
if feat_imp_file is not None:
config['save_feature_imp'] = feat_imp_file
self.ml.config = config
ranker = self.ml.train_model(inss)
return ranker
def cross_validate(self, inss, num_folds, folds_name=None, gen_folds=False):
"""
Performs k-fold cross validation.
:param inss: erd.ml.CERInstances
:param num_folds: int, number of folds
:param folds_name: file name for saving the folds. It adds a postfix to the file name.
e.g. "./output/res/erd-ltr" -> "./output/res/erd-ltr-f1-train.json"
:return All of instances ranked by cross validation
"""
kcv = CrossValidation(num_folds, inss, self.train, self.rank_inss)
# loads/generates folds
if gen_folds:
kcv.create_folds(group_by="session")
if folds_name is not None:
kcv.save_folds(folds_name)
else:
kcv.load_folds(folds_name)
# Cross validation
inss = kcv.run()
inss.__class__ = CERInstances
for ins in inss.get_all():
ins.__class__ = CERInstance
return inss
def rank_inss(self, inss, model=None):
"""
Ranks the instances using the given trained model.
:param inss: erd.ml.CERInstances
:return erd.ml.CERInstances, ranked instances
"""
if model is None: # Done for CV call_back_test method
|
return self.ml.apply_model(inss, model)
def rank_queries(self, queries, time_log_file=None): # commonness_th, filter=True,
"""
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instances
"""
print "Ranking queries ..."
total_time = 0.0
s_t = datetime.now() # start time
inss_list = [] # list of Instances
# Ranks queries
for q_id, q_content in queries.iteritems():
query = Query(q_id, q_content)
q_inss = self.rank_query(query)
if len(q_inss.get_all()) == 0:
print "==================================================="
print "No candidate entity for query " + q_id + ", " + q_content
print "==================================================="
inss_list.append(q_inss)
# time log
e_t = datetime.now()
diff = e_t - s_t
total_time += diff.total_seconds()
time_log = "Execution time(min):\t" + str(round(total_time/60, 4)) + "\n"
time_log += "Avg. time per query:\t" + str(round(total_time/len(queries), 4)) + "\n"
print time_log
# open(time_log_file + ".timelog", "w").write(time_log)
# print "Time log:\t" + time_log_file + ".timelog"
return CERInstances.concatenate_inss(inss_list)
def rank_query(self, query):
"""
Generates ranking score for entities related to the given query.
:param query: query.Query
:return erd.ml.CERInstances
"""
q_inss = CERInstances.gen_instances(query, self.commonness_th, sf_source=self.sf_source, filter=self.filter)
RankerLTR.add_features(q_inss, self.commonness_th, self.sf_source)
self.rank_inss(q_inss)
return q_inss
@staticmethod
def add_features(inss, commonness_th, sf_source):
print "Extracting features ..."
i = 0
for ins in inss.get_all():
ins.features = RankerLTR.get_features(ins, commonness_th, sf_source)
i += 1
if i % 1000.0 == 0:
print "Features are generated until instance " + str(ins.id)
return inss
@staticmethod
def get_features(ins, commonness_th, sf_source):
"""
Concatenate all features.
:param ins: ml.Instance
"""
all_ftrs = {}
# --- mention features ---
mention_ftr = MentionFeat(ins.mention, sf_source)
all_ftrs['len'] = mention_ftr.mention_len()
all_ftrs['ntem'] = mention_ftr.ntem()
all_ftrs['smil'] = mention_ftr.smil()
all_ftrs['matches'] = ins.matches if ins.matches is not None else mention_ftr.matches(commonness_th)
all_ftrs['len_ratio'] = mention_ftr.len_ratio(Query.preprocess(ins.q_content))
# --- entity features ---
en_ftr = EntityFeat(ins.en_id)
all_ftrs['redirects'] = en_ftr.redirects()
all_ftrs['links'] = en_ftr.links()
# --- entity-mention features ---
en_mention_ftr = EntityMentionFeat(ins.en_id, ins.mention)
all_ftrs['commonness'] = ins.commonness
all_ftrs['mct'] = en_mention_ftr.mct()
all_ftrs['tcm'] = en_mention_ftr.tcm()
all_ftrs['tem'] = en_mention_ftr.tem()
all_ftrs['pos1'] = en_mention_ftr.pos1()
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.mention, "m"))
# --- entity-query features ---
en_query_ftr = EntityMentionFeat(ins.en_id, ins.q_content)
all_ftrs['qct'] = en_query_ftr.mct()
all_ftrs['tcq'] = en_query_ftr.tcm()
all_ftrs['teq'] = en_query_ftr.tem()
mlm_tc = QuerySimFeat(ins.q_content).nllr_mlm_score(ins.en_id, {'names': 0.2, 'contents': 0.8}) # mlm_score
all_ftrs['mlm-tc'] = mlm_tc if mlm_tc is not None else 0
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.q_content, "q"))
return all_ftrs
@staticmethod
def __lm_scores(en_id, txt, prefix):
""" Calculates all LM scores. """
feat_field_dict = {'title': econfig.TITLE, 'sAbs': econfig.SHORT_ABS, 'lAbs': econfig.LONG_ABS,
'links': econfig.WIKILINKS, 'cats': econfig.CATEGORIES, 'catchall': Lucene.FIELDNAME_CONTENTS}
ftr_extractor = QuerySimFeat(txt)
scores = dict()
for feature_name, field in feat_field_dict.iteritems():
lm_score = ftr_extractor.nllr_lm_score(en_id, field) # lm_score(en_id, field)
scores[prefix + feature_name] = lm_score if lm_score is not None else 0
return scores
def main(args):
"""
Required args for training: -train -cer -t <int> -l <int> -in <train_set_name.json>
Required args for cross validation: -cv -cer -d <data_name> -c <commonness> -t <int> -l <int>
Required args for ranking: -rank -ltr -m <model_file>
Valid args for ranking: -d <data_name> -qid <str> -query <str> -c <commonness>
"""
settings_str = "-ltr-t" + str(args.tree)
model_name = ""
if args.depth is not None:
settings_str += "-d" + str(args.depth)
model_name = "gbrt"
elif args.maxfeat is not None:
settings_str += "-m" + str(args.maxfeat)
model_name = "rf"
ml_config = {'model': model_name,
'parameters': {'tree': args.tree, 'depth': args.depth, 'maxfeat': args.maxfeat}}
# ==== Train ====
if args.train:
train_inss = CERInstances.from_json(args.input)
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranker_ltr.train(train_inss, model_file=file_name + ".model", feat_imp_file=file_name + "-feat_imp.txt")
# ==== Cross Validation ====
elif args.cv:
in_file_name = args.input[:args.input.rfind(".json")]
cv_inss = CERInstances.from_json(args.input)
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranked_inss = ranker_ltr.cross_validate(cv_inss, args.folds,
folds_name=in_file_name + "-" + str(args.folds) + "f-folds.json",
gen_folds=args.genfolds)
ranked_inss.to_json(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".json")
ranked_inss.to_str(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".txt")
use_dbp = True if args.data == "ysqle" else False
ranked_inss.to_treceval(settings_str, in_file_name + "-" + str(args.folds) + "f" + settings_str + ".treceval", use_dbp)
# ==== Rank ====
elif args.rank:
# loads model
model = pickle.loads(open(args.model, 'r').read())
ranker_ltr = RankerLTR(model=model, commonness_th=args.commonness, sf_source=args.sfsource, filter=args.filter)
settings_str = "-ltr"
if args.model.rfind("-d") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-d")]
settings_str += args.model[args.model.rfind("-d"):args.model.rfind(".model")]
elif args.model.rfind("-m") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-m")]
settings_str += args.model[args.model.rfind("-m"):args.model.rfind(".model")]
# Ranks instances
if args.input is not None:
inss = CERInstances.from_json(args.input)
ranked_inss = ranker_ltr.rank_inss(inss)
# Writes instances
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranked_inss.to_json(file_name + ".json")
ranked_inss.to_str(file_name + ".txt")
ranked_inss.to_treceval(file_name, file_name + ".treceval")
# Ranks queries
else:
if args.query is not None:
queries = [Query(args.qid, args.query)]
elif args.data == "erd":
queries = erd_gt.read_queries()
elif args.data == "ysqle-erd":
queries = ysqle_erd_gt.read_queries()
elif args.data == "toy":
queries = ysqle_erd_gt.read_queries(ysqle_erd_file=econfig.DATA_DIR + "/toy.tsv")
# rank the query instances
filter_str = "" if args.filter else "-unfilter"
# sf_source_str = "-" + args.sfsource if args.sfsource is not None else ""
file_name = econfig.EVAL_DIR + "/" + args.data + "-c" + str(args.commonness) + settings_str + filter_str
ranked_inss = ranker_ltr.rank_queries(queries, time_log_file=file_name)
ranked_inss.to_json(file_name + ".json")
# ranked_inss.to_str(file_name + ".txt")
run_id = file_name[file_name.rfind("/")+1:]
ranked_inss.to_treceval(run_id, file_name + ".treceval")
| model = self.model | conditional_block |
ranker_ltr.py | """
Uses Learning to Rank to rank entities
@author: Faegheh Hasibi
"""
from datetime import datetime
import pickle
from nordlys.erd.features.query_sim_feat import QuerySimFeat
from nordlys.ml.cross_validation import CrossValidation
from nordlys.erd.features.entity_feat import EntityFeat
from nordlys.erd.features.mention_feat import MentionFeat
from nordlys.erd.features.entity_mention_feat import EntityMentionFeat
from nordlys.erd import econfig
from nordlys.erd.groundtruth import erd_gt, ysqle_erd_gt, ysqle_gt
from nordlys.erd.query.query import Query
from nordlys.erd.ml.cer_instances import CERInstances, CERInstance
from nordlys.ml.ml import ML
from nordlys.retrieval.lucene_tools import Lucene
class RankerLTR(object):
"""
Attributes:
tree: int, Number of trees
depth: int, depth of the trees
alpha: float, learning rate
model: the trained model
"""
def __init__(self, commonness_th=None, sf_source=None, filter=True, model=None, config={}):
self.commonness_th = commonness_th
self.sf_source = sf_source
self.filter = filter
self.config = config
self.model = model
self.ml = ML(config) #if config is not None else None
def train(self, inss, model_file=None, feat_imp_file=None):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, the learned model
"""
config = self.config
if model_file is not None:
config['save_model'] = model_file
if feat_imp_file is not None:
config['save_feature_imp'] = feat_imp_file
self.ml.config = config
ranker = self.ml.train_model(inss)
return ranker
def cross_validate(self, inss, num_folds, folds_name=None, gen_folds=False):
"""
Performs k-fold cross validation.
:param inss: erd.ml.CERInstances
:param num_folds: int, number of folds
:param folds_name: file name for saving the folds. It adds a postfix to the file name.
e.g. "./output/res/erd-ltr" -> "./output/res/erd-ltr-f1-train.json"
:return All of instances ranked by cross validation
"""
kcv = CrossValidation(num_folds, inss, self.train, self.rank_inss)
# loads/generates folds
if gen_folds:
kcv.create_folds(group_by="session")
if folds_name is not None:
kcv.save_folds(folds_name)
else:
kcv.load_folds(folds_name)
# Cross validation
inss = kcv.run()
inss.__class__ = CERInstances
for ins in inss.get_all():
ins.__class__ = CERInstance
return inss
def rank_inss(self, inss, model=None):
"""
Ranks the instances using the given trained model.
:param inss: erd.ml.CERInstances
:return erd.ml.CERInstances, ranked instances
"""
if model is None: # Done for CV call_back_test method
model = self.model
return self.ml.apply_model(inss, model)
def | (self, queries, time_log_file=None): # commonness_th, filter=True,
"""
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instances
"""
print "Ranking queries ..."
total_time = 0.0
s_t = datetime.now() # start time
inss_list = [] # list of Instances
# Ranks queries
for q_id, q_content in queries.iteritems():
query = Query(q_id, q_content)
q_inss = self.rank_query(query)
if len(q_inss.get_all()) == 0:
print "==================================================="
print "No candidate entity for query " + q_id + ", " + q_content
print "==================================================="
inss_list.append(q_inss)
# time log
e_t = datetime.now()
diff = e_t - s_t
total_time += diff.total_seconds()
time_log = "Execution time(min):\t" + str(round(total_time/60, 4)) + "\n"
time_log += "Avg. time per query:\t" + str(round(total_time/len(queries), 4)) + "\n"
print time_log
# open(time_log_file + ".timelog", "w").write(time_log)
# print "Time log:\t" + time_log_file + ".timelog"
return CERInstances.concatenate_inss(inss_list)
def rank_query(self, query):
"""
Generates ranking score for entities related to the given query.
:param query: query.Query
:return erd.ml.CERInstances
"""
q_inss = CERInstances.gen_instances(query, self.commonness_th, sf_source=self.sf_source, filter=self.filter)
RankerLTR.add_features(q_inss, self.commonness_th, self.sf_source)
self.rank_inss(q_inss)
return q_inss
@staticmethod
def add_features(inss, commonness_th, sf_source):
print "Extracting features ..."
i = 0
for ins in inss.get_all():
ins.features = RankerLTR.get_features(ins, commonness_th, sf_source)
i += 1
if i % 1000.0 == 0:
print "Features are generated until instance " + str(ins.id)
return inss
@staticmethod
def get_features(ins, commonness_th, sf_source):
"""
Concatenate all features.
:param ins: ml.Instance
"""
all_ftrs = {}
# --- mention features ---
mention_ftr = MentionFeat(ins.mention, sf_source)
all_ftrs['len'] = mention_ftr.mention_len()
all_ftrs['ntem'] = mention_ftr.ntem()
all_ftrs['smil'] = mention_ftr.smil()
all_ftrs['matches'] = ins.matches if ins.matches is not None else mention_ftr.matches(commonness_th)
all_ftrs['len_ratio'] = mention_ftr.len_ratio(Query.preprocess(ins.q_content))
# --- entity features ---
en_ftr = EntityFeat(ins.en_id)
all_ftrs['redirects'] = en_ftr.redirects()
all_ftrs['links'] = en_ftr.links()
# --- entity-mention features ---
en_mention_ftr = EntityMentionFeat(ins.en_id, ins.mention)
all_ftrs['commonness'] = ins.commonness
all_ftrs['mct'] = en_mention_ftr.mct()
all_ftrs['tcm'] = en_mention_ftr.tcm()
all_ftrs['tem'] = en_mention_ftr.tem()
all_ftrs['pos1'] = en_mention_ftr.pos1()
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.mention, "m"))
# --- entity-query features ---
en_query_ftr = EntityMentionFeat(ins.en_id, ins.q_content)
all_ftrs['qct'] = en_query_ftr.mct()
all_ftrs['tcq'] = en_query_ftr.tcm()
all_ftrs['teq'] = en_query_ftr.tem()
mlm_tc = QuerySimFeat(ins.q_content).nllr_mlm_score(ins.en_id, {'names': 0.2, 'contents': 0.8}) # mlm_score
all_ftrs['mlm-tc'] = mlm_tc if mlm_tc is not None else 0
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.q_content, "q"))
return all_ftrs
@staticmethod
def __lm_scores(en_id, txt, prefix):
""" Calculates all LM scores. """
feat_field_dict = {'title': econfig.TITLE, 'sAbs': econfig.SHORT_ABS, 'lAbs': econfig.LONG_ABS,
'links': econfig.WIKILINKS, 'cats': econfig.CATEGORIES, 'catchall': Lucene.FIELDNAME_CONTENTS}
ftr_extractor = QuerySimFeat(txt)
scores = dict()
for feature_name, field in feat_field_dict.iteritems():
lm_score = ftr_extractor.nllr_lm_score(en_id, field) # lm_score(en_id, field)
scores[prefix + feature_name] = lm_score if lm_score is not None else 0
return scores
def main(args):
"""
Required args for training: -train -cer -t <int> -l <int> -in <train_set_name.json>
Required args for cross validation: -cv -cer -d <data_name> -c <commonness> -t <int> -l <int>
Required args for ranking: -rank -ltr -m <model_file>
Valid args for ranking: -d <data_name> -qid <str> -query <str> -c <commonness>
"""
settings_str = "-ltr-t" + str(args.tree)
model_name = ""
if args.depth is not None:
settings_str += "-d" + str(args.depth)
model_name = "gbrt"
elif args.maxfeat is not None:
settings_str += "-m" + str(args.maxfeat)
model_name = "rf"
ml_config = {'model': model_name,
'parameters': {'tree': args.tree, 'depth': args.depth, 'maxfeat': args.maxfeat}}
# ==== Train ====
if args.train:
train_inss = CERInstances.from_json(args.input)
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranker_ltr.train(train_inss, model_file=file_name + ".model", feat_imp_file=file_name + "-feat_imp.txt")
# ==== Cross Validation ====
elif args.cv:
in_file_name = args.input[:args.input.rfind(".json")]
cv_inss = CERInstances.from_json(args.input)
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranked_inss = ranker_ltr.cross_validate(cv_inss, args.folds,
folds_name=in_file_name + "-" + str(args.folds) + "f-folds.json",
gen_folds=args.genfolds)
ranked_inss.to_json(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".json")
ranked_inss.to_str(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".txt")
use_dbp = True if args.data == "ysqle" else False
ranked_inss.to_treceval(settings_str, in_file_name + "-" + str(args.folds) + "f" + settings_str + ".treceval", use_dbp)
# ==== Rank ====
elif args.rank:
# loads model
model = pickle.loads(open(args.model, 'r').read())
ranker_ltr = RankerLTR(model=model, commonness_th=args.commonness, sf_source=args.sfsource, filter=args.filter)
settings_str = "-ltr"
if args.model.rfind("-d") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-d")]
settings_str += args.model[args.model.rfind("-d"):args.model.rfind(".model")]
elif args.model.rfind("-m") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-m")]
settings_str += args.model[args.model.rfind("-m"):args.model.rfind(".model")]
# Ranks instances
if args.input is not None:
inss = CERInstances.from_json(args.input)
ranked_inss = ranker_ltr.rank_inss(inss)
# Writes instances
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranked_inss.to_json(file_name + ".json")
ranked_inss.to_str(file_name + ".txt")
ranked_inss.to_treceval(file_name, file_name + ".treceval")
# Ranks queries
else:
if args.query is not None:
queries = [Query(args.qid, args.query)]
elif args.data == "erd":
queries = erd_gt.read_queries()
elif args.data == "ysqle-erd":
queries = ysqle_erd_gt.read_queries()
elif args.data == "toy":
queries = ysqle_erd_gt.read_queries(ysqle_erd_file=econfig.DATA_DIR + "/toy.tsv")
# rank the query instances
filter_str = "" if args.filter else "-unfilter"
# sf_source_str = "-" + args.sfsource if args.sfsource is not None else ""
file_name = econfig.EVAL_DIR + "/" + args.data + "-c" + str(args.commonness) + settings_str + filter_str
ranked_inss = ranker_ltr.rank_queries(queries, time_log_file=file_name)
ranked_inss.to_json(file_name + ".json")
# ranked_inss.to_str(file_name + ".txt")
run_id = file_name[file_name.rfind("/")+1:]
ranked_inss.to_treceval(run_id, file_name + ".treceval")
| rank_queries | identifier_name |
ranker_ltr.py | """
Uses Learning to Rank to rank entities
@author: Faegheh Hasibi
"""
from datetime import datetime
import pickle
from nordlys.erd.features.query_sim_feat import QuerySimFeat
from nordlys.ml.cross_validation import CrossValidation
from nordlys.erd.features.entity_feat import EntityFeat
from nordlys.erd.features.mention_feat import MentionFeat
from nordlys.erd.features.entity_mention_feat import EntityMentionFeat
from nordlys.erd import econfig
from nordlys.erd.groundtruth import erd_gt, ysqle_erd_gt, ysqle_gt
from nordlys.erd.query.query import Query
from nordlys.erd.ml.cer_instances import CERInstances, CERInstance
from nordlys.ml.ml import ML
from nordlys.retrieval.lucene_tools import Lucene
class RankerLTR(object):
"""
Attributes:
tree: int, Number of trees
depth: int, depth of the trees
alpha: float, learning rate
model: the trained model
"""
def __init__(self, commonness_th=None, sf_source=None, filter=True, model=None, config={}):
self.commonness_th = commonness_th
self.sf_source = sf_source
self.filter = filter
self.config = config
self.model = model
self.ml = ML(config) #if config is not None else None
def train(self, inss, model_file=None, feat_imp_file=None):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, the learned model
"""
config = self.config
if model_file is not None:
config['save_model'] = model_file
if feat_imp_file is not None:
config['save_feature_imp'] = feat_imp_file
self.ml.config = config
ranker = self.ml.train_model(inss)
return ranker
def cross_validate(self, inss, num_folds, folds_name=None, gen_folds=False):
"""
Performs k-fold cross validation.
:param inss: erd.ml.CERInstances
:param num_folds: int, number of folds
:param folds_name: file name for saving the folds. It adds a postfix to the file name.
e.g. "./output/res/erd-ltr" -> "./output/res/erd-ltr-f1-train.json"
:return All of instances ranked by cross validation
"""
kcv = CrossValidation(num_folds, inss, self.train, self.rank_inss)
# loads/generates folds
if gen_folds:
kcv.create_folds(group_by="session")
if folds_name is not None:
kcv.save_folds(folds_name)
else:
kcv.load_folds(folds_name)
# Cross validation
inss = kcv.run()
inss.__class__ = CERInstances
for ins in inss.get_all():
ins.__class__ = CERInstance
return inss
def rank_inss(self, inss, model=None):
"""
Ranks the instances using the given trained model.
:param inss: erd.ml.CERInstances
:return erd.ml.CERInstances, ranked instances
"""
if model is None: # Done for CV call_back_test method
model = self.model
return self.ml.apply_model(inss, model)
def rank_queries(self, queries, time_log_file=None): # commonness_th, filter=True,
|
def rank_query(self, query):
"""
Generates ranking score for entities related to the given query.
:param query: query.Query
:return erd.ml.CERInstances
"""
q_inss = CERInstances.gen_instances(query, self.commonness_th, sf_source=self.sf_source, filter=self.filter)
RankerLTR.add_features(q_inss, self.commonness_th, self.sf_source)
self.rank_inss(q_inss)
return q_inss
@staticmethod
def add_features(inss, commonness_th, sf_source):
print "Extracting features ..."
i = 0
for ins in inss.get_all():
ins.features = RankerLTR.get_features(ins, commonness_th, sf_source)
i += 1
if i % 1000.0 == 0:
print "Features are generated until instance " + str(ins.id)
return inss
@staticmethod
def get_features(ins, commonness_th, sf_source):
"""
Concatenate all features.
:param ins: ml.Instance
"""
all_ftrs = {}
# --- mention features ---
mention_ftr = MentionFeat(ins.mention, sf_source)
all_ftrs['len'] = mention_ftr.mention_len()
all_ftrs['ntem'] = mention_ftr.ntem()
all_ftrs['smil'] = mention_ftr.smil()
all_ftrs['matches'] = ins.matches if ins.matches is not None else mention_ftr.matches(commonness_th)
all_ftrs['len_ratio'] = mention_ftr.len_ratio(Query.preprocess(ins.q_content))
# --- entity features ---
en_ftr = EntityFeat(ins.en_id)
all_ftrs['redirects'] = en_ftr.redirects()
all_ftrs['links'] = en_ftr.links()
# --- entity-mention features ---
en_mention_ftr = EntityMentionFeat(ins.en_id, ins.mention)
all_ftrs['commonness'] = ins.commonness
all_ftrs['mct'] = en_mention_ftr.mct()
all_ftrs['tcm'] = en_mention_ftr.tcm()
all_ftrs['tem'] = en_mention_ftr.tem()
all_ftrs['pos1'] = en_mention_ftr.pos1()
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.mention, "m"))
# --- entity-query features ---
en_query_ftr = EntityMentionFeat(ins.en_id, ins.q_content)
all_ftrs['qct'] = en_query_ftr.mct()
all_ftrs['tcq'] = en_query_ftr.tcm()
all_ftrs['teq'] = en_query_ftr.tem()
mlm_tc = QuerySimFeat(ins.q_content).nllr_mlm_score(ins.en_id, {'names': 0.2, 'contents': 0.8}) # mlm_score
all_ftrs['mlm-tc'] = mlm_tc if mlm_tc is not None else 0
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.q_content, "q"))
return all_ftrs
@staticmethod
def __lm_scores(en_id, txt, prefix):
""" Calculates all LM scores. """
feat_field_dict = {'title': econfig.TITLE, 'sAbs': econfig.SHORT_ABS, 'lAbs': econfig.LONG_ABS,
'links': econfig.WIKILINKS, 'cats': econfig.CATEGORIES, 'catchall': Lucene.FIELDNAME_CONTENTS}
ftr_extractor = QuerySimFeat(txt)
scores = dict()
for feature_name, field in feat_field_dict.iteritems():
lm_score = ftr_extractor.nllr_lm_score(en_id, field) # lm_score(en_id, field)
scores[prefix + feature_name] = lm_score if lm_score is not None else 0
return scores
def main(args):
"""
Required args for training: -train -cer -t <int> -l <int> -in <train_set_name.json>
Required args for cross validation: -cv -cer -d <data_name> -c <commonness> -t <int> -l <int>
Required args for ranking: -rank -ltr -m <model_file>
Valid args for ranking: -d <data_name> -qid <str> -query <str> -c <commonness>
"""
settings_str = "-ltr-t" + str(args.tree)
model_name = ""
if args.depth is not None:
settings_str += "-d" + str(args.depth)
model_name = "gbrt"
elif args.maxfeat is not None:
settings_str += "-m" + str(args.maxfeat)
model_name = "rf"
ml_config = {'model': model_name,
'parameters': {'tree': args.tree, 'depth': args.depth, 'maxfeat': args.maxfeat}}
# ==== Train ====
if args.train:
train_inss = CERInstances.from_json(args.input)
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranker_ltr.train(train_inss, model_file=file_name + ".model", feat_imp_file=file_name + "-feat_imp.txt")
# ==== Cross Validation ====
elif args.cv:
in_file_name = args.input[:args.input.rfind(".json")]
cv_inss = CERInstances.from_json(args.input)
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranked_inss = ranker_ltr.cross_validate(cv_inss, args.folds,
folds_name=in_file_name + "-" + str(args.folds) + "f-folds.json",
gen_folds=args.genfolds)
ranked_inss.to_json(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".json")
ranked_inss.to_str(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".txt")
use_dbp = True if args.data == "ysqle" else False
ranked_inss.to_treceval(settings_str, in_file_name + "-" + str(args.folds) + "f" + settings_str + ".treceval", use_dbp)
# ==== Rank ====
elif args.rank:
# loads model
model = pickle.loads(open(args.model, 'r').read())
ranker_ltr = RankerLTR(model=model, commonness_th=args.commonness, sf_source=args.sfsource, filter=args.filter)
settings_str = "-ltr"
if args.model.rfind("-d") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-d")]
settings_str += args.model[args.model.rfind("-d"):args.model.rfind(".model")]
elif args.model.rfind("-m") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-m")]
settings_str += args.model[args.model.rfind("-m"):args.model.rfind(".model")]
# Ranks instances
if args.input is not None:
inss = CERInstances.from_json(args.input)
ranked_inss = ranker_ltr.rank_inss(inss)
# Writes instances
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranked_inss.to_json(file_name + ".json")
ranked_inss.to_str(file_name + ".txt")
ranked_inss.to_treceval(file_name, file_name + ".treceval")
# Ranks queries
else:
if args.query is not None:
queries = [Query(args.qid, args.query)]
elif args.data == "erd":
queries = erd_gt.read_queries()
elif args.data == "ysqle-erd":
queries = ysqle_erd_gt.read_queries()
elif args.data == "toy":
queries = ysqle_erd_gt.read_queries(ysqle_erd_file=econfig.DATA_DIR + "/toy.tsv")
# rank the query instances
filter_str = "" if args.filter else "-unfilter"
# sf_source_str = "-" + args.sfsource if args.sfsource is not None else ""
file_name = econfig.EVAL_DIR + "/" + args.data + "-c" + str(args.commonness) + settings_str + filter_str
ranked_inss = ranker_ltr.rank_queries(queries, time_log_file=file_name)
ranked_inss.to_json(file_name + ".json")
# ranked_inss.to_str(file_name + ".txt")
run_id = file_name[file_name.rfind("/")+1:]
ranked_inss.to_treceval(run_id, file_name + ".treceval")
| """
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instances
"""
print "Ranking queries ..."
total_time = 0.0
s_t = datetime.now() # start time
inss_list = [] # list of Instances
# Ranks queries
for q_id, q_content in queries.iteritems():
query = Query(q_id, q_content)
q_inss = self.rank_query(query)
if len(q_inss.get_all()) == 0:
print "==================================================="
print "No candidate entity for query " + q_id + ", " + q_content
print "==================================================="
inss_list.append(q_inss)
# time log
e_t = datetime.now()
diff = e_t - s_t
total_time += diff.total_seconds()
time_log = "Execution time(min):\t" + str(round(total_time/60, 4)) + "\n"
time_log += "Avg. time per query:\t" + str(round(total_time/len(queries), 4)) + "\n"
print time_log
# open(time_log_file + ".timelog", "w").write(time_log)
# print "Time log:\t" + time_log_file + ".timelog"
return CERInstances.concatenate_inss(inss_list) | identifier_body |
ranker_ltr.py | """
Uses Learning to Rank to rank entities
@author: Faegheh Hasibi
"""
from datetime import datetime
import pickle
from nordlys.erd.features.query_sim_feat import QuerySimFeat
from nordlys.ml.cross_validation import CrossValidation
from nordlys.erd.features.entity_feat import EntityFeat
from nordlys.erd.features.mention_feat import MentionFeat
from nordlys.erd.features.entity_mention_feat import EntityMentionFeat
from nordlys.erd import econfig
from nordlys.erd.groundtruth import erd_gt, ysqle_erd_gt, ysqle_gt
from nordlys.erd.query.query import Query
from nordlys.erd.ml.cer_instances import CERInstances, CERInstance
from nordlys.ml.ml import ML
from nordlys.retrieval.lucene_tools import Lucene
class RankerLTR(object):
"""
Attributes:
tree: int, Number of trees
depth: int, depth of the trees
alpha: float, learning rate | model: the trained model
"""
def __init__(self, commonness_th=None, sf_source=None, filter=True, model=None, config={}):
self.commonness_th = commonness_th
self.sf_source = sf_source
self.filter = filter
self.config = config
self.model = model
self.ml = ML(config) #if config is not None else None
def train(self, inss, model_file=None, feat_imp_file=None):
"""
Trains a model and saves it to a file.
- This function currently only supports GBRT.
Args:
inss: erd.ml.CERInstances, train instances
model_file: A file to save the model. For None value, the model will not be saved
Returns:
ranker, the learned model
"""
config = self.config
if model_file is not None:
config['save_model'] = model_file
if feat_imp_file is not None:
config['save_feature_imp'] = feat_imp_file
self.ml.config = config
ranker = self.ml.train_model(inss)
return ranker
def cross_validate(self, inss, num_folds, folds_name=None, gen_folds=False):
"""
Performs k-fold cross validation.
:param inss: erd.ml.CERInstances
:param num_folds: int, number of folds
:param folds_name: file name for saving the folds. It adds a postfix to the file name.
e.g. "./output/res/erd-ltr" -> "./output/res/erd-ltr-f1-train.json"
:return All of instances ranked by cross validation
"""
kcv = CrossValidation(num_folds, inss, self.train, self.rank_inss)
# loads/generates folds
if gen_folds:
kcv.create_folds(group_by="session")
if folds_name is not None:
kcv.save_folds(folds_name)
else:
kcv.load_folds(folds_name)
# Cross validation
inss = kcv.run()
inss.__class__ = CERInstances
for ins in inss.get_all():
ins.__class__ = CERInstance
return inss
def rank_inss(self, inss, model=None):
"""
Ranks the instances using the given trained model.
:param inss: erd.ml.CERInstances
:return erd.ml.CERInstances, ranked instances
"""
if model is None: # Done for CV call_back_test method
model = self.model
return self.ml.apply_model(inss, model)
def rank_queries(self, queries, time_log_file=None): # commonness_th, filter=True,
"""
Ranks entities for the given queries using the trained model.
:param queries: a dictionary, {q_id: q_content, ...}
:param time_log_file: file name to save time log
:return erd.ml.CERInstances, Ranked instances
"""
print "Ranking queries ..."
total_time = 0.0
s_t = datetime.now() # start time
inss_list = [] # list of Instances
# Ranks queries
for q_id, q_content in queries.iteritems():
query = Query(q_id, q_content)
q_inss = self.rank_query(query)
if len(q_inss.get_all()) == 0:
print "==================================================="
print "No candidate entity for query " + q_id + ", " + q_content
print "==================================================="
inss_list.append(q_inss)
# time log
e_t = datetime.now()
diff = e_t - s_t
total_time += diff.total_seconds()
time_log = "Execution time(min):\t" + str(round(total_time/60, 4)) + "\n"
time_log += "Avg. time per query:\t" + str(round(total_time/len(queries), 4)) + "\n"
print time_log
# open(time_log_file + ".timelog", "w").write(time_log)
# print "Time log:\t" + time_log_file + ".timelog"
return CERInstances.concatenate_inss(inss_list)
def rank_query(self, query):
"""
Generates ranking score for entities related to the given query.
:param query: query.Query
:return erd.ml.CERInstances
"""
q_inss = CERInstances.gen_instances(query, self.commonness_th, sf_source=self.sf_source, filter=self.filter)
RankerLTR.add_features(q_inss, self.commonness_th, self.sf_source)
self.rank_inss(q_inss)
return q_inss
@staticmethod
def add_features(inss, commonness_th, sf_source):
print "Extracting features ..."
i = 0
for ins in inss.get_all():
ins.features = RankerLTR.get_features(ins, commonness_th, sf_source)
i += 1
if i % 1000.0 == 0:
print "Features are generated until instance " + str(ins.id)
return inss
@staticmethod
def get_features(ins, commonness_th, sf_source):
"""
Concatenate all features.
:param ins: ml.Instance
"""
all_ftrs = {}
# --- mention features ---
mention_ftr = MentionFeat(ins.mention, sf_source)
all_ftrs['len'] = mention_ftr.mention_len()
all_ftrs['ntem'] = mention_ftr.ntem()
all_ftrs['smil'] = mention_ftr.smil()
all_ftrs['matches'] = ins.matches if ins.matches is not None else mention_ftr.matches(commonness_th)
all_ftrs['len_ratio'] = mention_ftr.len_ratio(Query.preprocess(ins.q_content))
# --- entity features ---
en_ftr = EntityFeat(ins.en_id)
all_ftrs['redirects'] = en_ftr.redirects()
all_ftrs['links'] = en_ftr.links()
# --- entity-mention features ---
en_mention_ftr = EntityMentionFeat(ins.en_id, ins.mention)
all_ftrs['commonness'] = ins.commonness
all_ftrs['mct'] = en_mention_ftr.mct()
all_ftrs['tcm'] = en_mention_ftr.tcm()
all_ftrs['tem'] = en_mention_ftr.tem()
all_ftrs['pos1'] = en_mention_ftr.pos1()
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.mention, "m"))
# --- entity-query features ---
en_query_ftr = EntityMentionFeat(ins.en_id, ins.q_content)
all_ftrs['qct'] = en_query_ftr.mct()
all_ftrs['tcq'] = en_query_ftr.tcm()
all_ftrs['teq'] = en_query_ftr.tem()
mlm_tc = QuerySimFeat(ins.q_content).nllr_mlm_score(ins.en_id, {'names': 0.2, 'contents': 0.8}) # mlm_score
all_ftrs['mlm-tc'] = mlm_tc if mlm_tc is not None else 0
all_ftrs.update(RankerLTR.__lm_scores(ins.en_id, ins.q_content, "q"))
return all_ftrs
@staticmethod
def __lm_scores(en_id, txt, prefix):
""" Calculates all LM scores. """
feat_field_dict = {'title': econfig.TITLE, 'sAbs': econfig.SHORT_ABS, 'lAbs': econfig.LONG_ABS,
'links': econfig.WIKILINKS, 'cats': econfig.CATEGORIES, 'catchall': Lucene.FIELDNAME_CONTENTS}
ftr_extractor = QuerySimFeat(txt)
scores = dict()
for feature_name, field in feat_field_dict.iteritems():
lm_score = ftr_extractor.nllr_lm_score(en_id, field) # lm_score(en_id, field)
scores[prefix + feature_name] = lm_score if lm_score is not None else 0
return scores
def main(args):
"""
Required args for training: -train -cer -t <int> -l <int> -in <train_set_name.json>
Required args for cross validation: -cv -cer -d <data_name> -c <commonness> -t <int> -l <int>
Required args for ranking: -rank -ltr -m <model_file>
Valid args for ranking: -d <data_name> -qid <str> -query <str> -c <commonness>
"""
settings_str = "-ltr-t" + str(args.tree)
model_name = ""
if args.depth is not None:
settings_str += "-d" + str(args.depth)
model_name = "gbrt"
elif args.maxfeat is not None:
settings_str += "-m" + str(args.maxfeat)
model_name = "rf"
ml_config = {'model': model_name,
'parameters': {'tree': args.tree, 'depth': args.depth, 'maxfeat': args.maxfeat}}
# ==== Train ====
if args.train:
train_inss = CERInstances.from_json(args.input)
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranker_ltr.train(train_inss, model_file=file_name + ".model", feat_imp_file=file_name + "-feat_imp.txt")
# ==== Cross Validation ====
elif args.cv:
in_file_name = args.input[:args.input.rfind(".json")]
cv_inss = CERInstances.from_json(args.input)
ranker_ltr = RankerLTR(config=ml_config) # model_name, tree=args.tree, depth=args.depth, max_features=args.maxfeat)
ranked_inss = ranker_ltr.cross_validate(cv_inss, args.folds,
folds_name=in_file_name + "-" + str(args.folds) + "f-folds.json",
gen_folds=args.genfolds)
ranked_inss.to_json(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".json")
ranked_inss.to_str(in_file_name + "-" + str(args.folds) + "f" + settings_str + ".txt")
use_dbp = True if args.data == "ysqle" else False
ranked_inss.to_treceval(settings_str, in_file_name + "-" + str(args.folds) + "f" + settings_str + ".treceval", use_dbp)
# ==== Rank ====
elif args.rank:
# loads model
model = pickle.loads(open(args.model, 'r').read())
ranker_ltr = RankerLTR(model=model, commonness_th=args.commonness, sf_source=args.sfsource, filter=args.filter)
settings_str = "-ltr"
if args.model.rfind("-d") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-d")]
settings_str += args.model[args.model.rfind("-d"):args.model.rfind(".model")]
elif args.model.rfind("-m") != -1:
settings_str += args.model[args.model.rfind("-t"):args.model.rfind("-m")]
settings_str += args.model[args.model.rfind("-m"):args.model.rfind(".model")]
# Ranks instances
if args.input is not None:
inss = CERInstances.from_json(args.input)
ranked_inss = ranker_ltr.rank_inss(inss)
# Writes instances
file_name = args.input[:args.input.rfind(".json")] + settings_str
ranked_inss.to_json(file_name + ".json")
ranked_inss.to_str(file_name + ".txt")
ranked_inss.to_treceval(file_name, file_name + ".treceval")
# Ranks queries
else:
if args.query is not None:
queries = [Query(args.qid, args.query)]
elif args.data == "erd":
queries = erd_gt.read_queries()
elif args.data == "ysqle-erd":
queries = ysqle_erd_gt.read_queries()
elif args.data == "toy":
queries = ysqle_erd_gt.read_queries(ysqle_erd_file=econfig.DATA_DIR + "/toy.tsv")
# rank the query instances
filter_str = "" if args.filter else "-unfilter"
# sf_source_str = "-" + args.sfsource if args.sfsource is not None else ""
file_name = econfig.EVAL_DIR + "/" + args.data + "-c" + str(args.commonness) + settings_str + filter_str
ranked_inss = ranker_ltr.rank_queries(queries, time_log_file=file_name)
ranked_inss.to_json(file_name + ".json")
# ranked_inss.to_str(file_name + ".txt")
run_id = file_name[file_name.rfind("/")+1:]
ranked_inss.to_treceval(run_id, file_name + ".treceval") | random_line_split | |
opentuna-stack.ts | import * as cdk from '@aws-cdk/core';
import * as cloudfront from '@aws-cdk/aws-cloudfront';
import * as route53 from '@aws-cdk/aws-route53';
import * as route53targets from '@aws-cdk/aws-route53-targets';
import * as acm from '@aws-cdk/aws-certificatemanager';
import * as cloudwatch from '@aws-cdk/aws-cloudwatch';
import * as alias from '@aws-cdk/aws-route53-targets';
import * as ec2 from '@aws-cdk/aws-ec2';
import * as sns from '@aws-cdk/aws-sns';
import * as elbv2 from '@aws-cdk/aws-elasticloadbalancingv2';
import * as ecs from '@aws-cdk/aws-ecs';
import * as s3 from '@aws-cdk/aws-s3';
import * as r53 from '@aws-cdk/aws-route53';
import { TunaManagerStack } from './tuna-manager';
import { TunaWorkerStack } from './tuna-worker';
import { ContentServerStack } from './content-server';
import { WebPortalStack } from './web-portal';
import { CloudFrontInvalidate } from './cloudfront-invalidate';
import { AnalyticsStack } from './analytics-stack';
import { MonitorStack } from './monitor-stack';
import { assert } from 'console';
export interface OpenTunaStackProps extends cdk.StackProps {
readonly vpcId: string;
readonly fileSystemId: string;
readonly fileSystemSGId: string;
readonly notifyTopic: sns.ITopic;
}
export class | extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props: OpenTunaStackProps) {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = this.node.tryGetContext('iamCertId');
let useHTTPS = false;
let domainZone: r53.IHostedZone | undefined;
// ACM or IAM certificate
let cloudfrontCert: acm.Certificate | string | null = null;
if (domainName && domainZoneName) {
domainZone = r53.HostedZone.fromLookup(this, 'HostedZone', {
domainName: domainZoneName,
});
useHTTPS = true;
if (iamCertId !== undefined) {
// Use IAM first when specified
cloudfrontCert = iamCertId;
} else if (!stack.region.startsWith('cn-')) {
// Try to use ACM certificate in us-east-1 for CloudFront
cloudfrontCert = new acm.DnsValidatedCertificate(this, 'CloudFrontCertificate', {
domainName: domainName,
hostedZone: domainZone,
validation: acm.CertificateValidation.fromDns(domainZone),
region: 'us-east-1',
});
} else {
throw new Error('You must specify iamCertId context for cn regions');
}
}
const vpc = ec2.Vpc.fromLookup(this, `VPC-${props.vpcId}`, {
vpcId: props.vpcId,
});
const assetBucket = new s3.Bucket(this, `OpenTunaAssets`, {
removalPolicy: cdk.RemovalPolicy.DESTROY,
});
// setup bucket for rubygems
const tunaRepoBucket = new s3.Bucket(this, 'TunaRepoBucket');
// CloudWatch dashboard
const dashboard = new cloudwatch.Dashboard(this, 'Dashboard', {
dashboardName: 'OpenTUNA-Dashboard',
});
const tunaManagerSG = new ec2.SecurityGroup(this, "TunaManagerSG", {
vpc,
description: "SG of Tuna Manager",
allowAllOutbound: true,
});
const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG of Tuna Worker",
allowAllOutbound: true,
});
const externalALBSG = new ec2.SecurityGroup(this, "ExternalALBSG", {
vpc,
description: "SG of External ALB",
allowAllOutbound: false,
});
const externalALB = new elbv2.ApplicationLoadBalancer(this, "ExternalALB", {
vpc,
securityGroup: externalALBSG,
internetFacing: true,
http2Enabled: useHTTPS,
});
dashboard.addWidgets(new cloudwatch.GraphWidget({
title: 'ALB Processed Data',
left: [externalALB.metricProcessedBytes({
label: 'Bytes per minute',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB Connections',
left: [externalALB.metricNewConnectionCount({
label: 'New',
period: cdk.Duration.minutes(1),
}), externalALB.metricActiveConnectionCount({
label: 'Active',
period: cdk.Duration.minutes(1),
}), externalALB.metricRejectedConnectionCount({
label: 'Rejected',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB HTTP Code from Target',
left: [externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_2XX_COUNT, {
label: '2XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_3XX_COUNT, {
label: '3XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_4XX_COUNT, {
label: '4XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_5XX_COUNT, {
label: '5XX',
period: cdk.Duration.minutes(1),
})]
}));
let cert: acm.Certificate | undefined;
if (useHTTPS) {
cert = new acm.Certificate(this, 'Certificate', {
domainName: domainName,
subjectAlternativeNames: [`${stack.region}.${domainName}`],
validation: acm.CertificateValidation.fromDns(domainZone),
});
}
const defaultALBPort: number = useHTTPS ? 443 : 80;
const defaultALBListener = externalALB.addListener(`DefaultPort-${defaultALBPort}`, {
protocol: useHTTPS ? elbv2.ApplicationProtocol.HTTPS : elbv2.ApplicationProtocol.HTTP,
port: defaultALBPort,
open: true,
certificates: cert ? [cert] : undefined,
sslPolicy: useHTTPS ? elbv2.SslPolicy.RECOMMENDED : undefined,
});
let httpOnlyALBListener: elbv2.ApplicationListener | undefined;
if (useHTTPS) {
// redirect HTTP to HTTPS
httpOnlyALBListener = externalALB.addListener(`DefaultPort-80`, {
protocol: elbv2.ApplicationProtocol.HTTP,
port: 80,
open: true,
defaultAction: elbv2.ListenerAction.redirect({
port: '443',
protocol: elbv2.ApplicationProtocol.HTTPS,
permanent: true,
}),
});
new r53.ARecord(this, 'ALBCustomDomain', {
zone: domainZone!,
recordName: `${stack.region}.${domainName}`,
ttl: cdk.Duration.minutes(5),
target: r53.RecordTarget.fromAlias(new alias.LoadBalancerTarget(externalALB)),
});
}
// Tunasync Manager stack
const tunaManagerStack = new TunaManagerStack(this, 'TunaManagerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
tunaManagerSG,
tunaManagerALBSG,
timeout: cdk.Duration.minutes(10),
assetBucket,
});
const managerUrl = `http://${tunaManagerStack.managerALB.loadBalancerDnsName}:${tunaManagerStack.managerPort}`;
// Tunasync Worker stack
const tunaWorkerStack = new TunaWorkerStack(this, 'TunaWorkerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
managerUrl,
timeout: cdk.Duration.minutes(10),
tunaWorkerSG,
assetBucket,
tunaRepoBucket,
});
tunaManagerALBSG.connections.allowFrom(tunaWorkerSG, ec2.Port.tcp(tunaManagerStack.managerPort), 'Access from tuna worker');
tunaWorkerSG.connections.allowFrom(tunaManagerSG, ec2.Port.tcp(tunaWorkerStack.workerPort), 'Access from tuna manager');
const ecsCluster = new ecs.Cluster(this, `ECSCluster`, {
vpc,
});
// Content Server stack
const contentServerStack = new ContentServerStack(this, 'ContentServerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
ecsCluster,
listener: defaultALBListener,
httpOnlyListener: httpOnlyALBListener,
dashboard,
});
// Web Portal stack
const webPortalStack = new WebPortalStack(this, 'WebPortalStack', {
vpc,
externalALBListener: defaultALBListener,
ecsCluster,
tunaManagerASG: tunaManagerStack.managerASG,
tunaManagerALBTargetGroup: tunaManagerStack.managerALBTargetGroup,
fileSystemId: props.fileSystemId,
fileSystemSGId: props.fileSystemSGId,
});
tunaManagerSG.connections.allowFrom(externalALBSG, ec2.Port.tcp(80), 'Allow external ALB to access tuna manager');
// Monitor stack
const monitorStack = new MonitorStack(this, 'MonitorStack', {
vpc,
domainName,
notifyTopic: props.notifyTopic,
tunaManagerUrl: managerUrl,
tunaManagerALBSG,
});
let commonBehaviorConfig = {
// special handling for redirections
forwardedValues: {
headers: ['Host'],
queryString: true,
},
// default 1 day cache
defaultTtl: cdk.Duration.days(1),
};
// origin access identity for s3 bucket
const oai = new cloudfront.OriginAccessIdentity(this, 'TunaRepoOAI');
tunaRepoBucket.grantRead(oai);
// CloudFront as cdn
let cloudfrontProps = {
originConfigs: [{
customOriginSource: {
domainName: useHTTPS ? `${stack.region}.${domainName}` : externalALB.loadBalancerDnsName,
originProtocolPolicy: cloudfront.OriginProtocolPolicy.MATCH_VIEWER
},
behaviors: [{
...commonBehaviorConfig,
isDefaultBehavior: true,
}, {
...commonBehaviorConfig,
pathPattern: '/debian/*',
}, {
...commonBehaviorConfig,
pathPattern: '/debian-security/*',
}, {
...commonBehaviorConfig,
pathPattern: '/ubuntu/*',
}, {
...commonBehaviorConfig,
// 5min cache for tunasync status
pathPattern: '/jobs',
defaultTtl: cdk.Duration.minutes(5),
}],
}, {
s3OriginSource: {
s3BucketSource: tunaRepoBucket,
originAccessIdentity: oai,
},
behaviors: [{
pathPattern: '/rubygems/gems/*',
// 1w cache for gem specs
defaultTtl: cdk.Duration.days(7),
}, {
pathPattern: '/rubygems/*',
// 1h cache for index files
defaultTtl: cdk.Duration.minutes(60),
}]
}],
defaultRootObject: '',
errorConfigurations: [
{
errorCode: 500,
errorCachingMinTtl: 30,
},
{
errorCode: 502,
errorCachingMinTtl: 0,
},
{
errorCode: 503,
errorCachingMinTtl: 0,
},
{
errorCode: 404,
errorCachingMinTtl: 3600,
responseCode: 404,
responsePagePath: '/404.html',
}
],
} as cloudfront.CloudFrontWebDistributionProps;
if (useHTTPS) {
// when https is enabled
cloudfrontProps = {
httpVersion: cloudfront.HttpVersion.HTTP2,
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.REDIRECT_TO_HTTPS,
...cloudfrontProps
};
if (cloudfrontCert instanceof acm.DnsValidatedCertificate) {
// ACM cert
cloudfrontProps = {
aliasConfiguration: {
acmCertRef: cloudfrontCert.certificateArn,
names: [domainName],
},
...cloudfrontProps
}
} else if (typeof cloudfrontCert === "string") {
// IAM cert
cloudfrontProps = {
viewerCertificate: cloudfront.ViewerCertificate.fromIamCertificate(
cloudfrontCert,
{
aliases: [domainName],
securityPolicy: cloudfront.SecurityPolicyProtocol.TLS_V1_2_2018,
sslMethod: cloudfront.SSLMethod.SNI, // default
}
),
...cloudfrontProps
};
}
}
// some particular options for China regions
if (stack.region.startsWith('cn-')) {
cloudfrontProps = Object.assign(cloudfrontProps, {
enableIpV6: false,
priceClass: cloudfront.PriceClass.PRICE_CLASS_ALL,
});
}
const logsBucket = new s3.Bucket(this, "OpentunaLogs");
// ALB logs
externalALB.logAccessLogs(logsBucket, 'alb-logs');
const cloudfrontLogPrefix = "new/";
// nested stack for log analysis
const OpentunaAnalyticsStack = new AnalyticsStack(this, 'OpentunaAnalyticsStack', {
resourcePrefix: "opentuna",
newKeyPrefix: cloudfrontLogPrefix,
gzKeyPrefix: "partitioned-gz/",
parquetKeyPrefix: "partitioned-parquet/",
logBucket: logsBucket,
notifyTopic: props.notifyTopic
});
cloudfrontProps = Object.assign(cloudfrontProps, {
loggingConfig: {
bucket: logsBucket,
includeCookies: true,
prefix: cloudfrontLogPrefix
}
});
const distribution = new cloudfront.CloudFrontWebDistribution(this, 'CloudFrontDist', cloudfrontProps);
// HACK: override /debian/* viewer protocol policy to allow-all
// see https://github.com/aws/aws-cdk/issues/7086
let dist = distribution.node.defaultChild as cloudfront.CfnDistribution;
let conf = dist.distributionConfig as cloudfront.CfnDistribution.DistributionConfigProperty;
let cacheBehaviors = conf.cacheBehaviors as cloudfront.CfnDistribution.CacheBehaviorProperty[];
let behavior = cacheBehaviors[0];
assert(behavior.pathPattern == '/debian/*');
for (let i = 0; i < cacheBehaviors.length; i++) {
if (['/debian/*', '/debian-security/*', '/ubuntu/*'].indexOf(cacheBehaviors[i].pathPattern) != -1) {
cacheBehaviors[i] = {
...cacheBehaviors[i],
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.ALLOW_ALL,
} as cloudfront.CfnDistribution.CacheBehaviorProperty;
}
}
if (domainZone) {
new route53.ARecord(this, 'ARecord', {
zone: domainZone!,
recordName: domainName,
target: route53.RecordTarget.fromAlias(new route53targets.CloudFrontTarget(distribution)),
ttl: cdk.Duration.minutes(5),
});
}
// invalidate cloudfront when web-portal changes
new CloudFrontInvalidate(this, 'CloudFrontInvalidate', {
distribution: distribution,
distributionPaths: ['/help*', '/news*', '/status*', '/static*', '/*.html', '/'],
updateKey: webPortalStack.dockerImageHash,
});
}
}
| OpentunaStack | identifier_name |
opentuna-stack.ts | import * as cdk from '@aws-cdk/core';
import * as cloudfront from '@aws-cdk/aws-cloudfront';
import * as route53 from '@aws-cdk/aws-route53';
import * as route53targets from '@aws-cdk/aws-route53-targets';
import * as acm from '@aws-cdk/aws-certificatemanager';
import * as cloudwatch from '@aws-cdk/aws-cloudwatch';
import * as alias from '@aws-cdk/aws-route53-targets';
import * as ec2 from '@aws-cdk/aws-ec2';
import * as sns from '@aws-cdk/aws-sns';
import * as elbv2 from '@aws-cdk/aws-elasticloadbalancingv2';
import * as ecs from '@aws-cdk/aws-ecs';
import * as s3 from '@aws-cdk/aws-s3';
import * as r53 from '@aws-cdk/aws-route53';
import { TunaManagerStack } from './tuna-manager';
import { TunaWorkerStack } from './tuna-worker';
import { ContentServerStack } from './content-server';
import { WebPortalStack } from './web-portal';
import { CloudFrontInvalidate } from './cloudfront-invalidate';
import { AnalyticsStack } from './analytics-stack';
import { MonitorStack } from './monitor-stack';
import { assert } from 'console';
export interface OpenTunaStackProps extends cdk.StackProps {
readonly vpcId: string;
readonly fileSystemId: string;
readonly fileSystemSGId: string;
readonly notifyTopic: sns.ITopic;
}
export class OpentunaStack extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props: OpenTunaStackProps) {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = this.node.tryGetContext('iamCertId');
let useHTTPS = false;
let domainZone: r53.IHostedZone | undefined;
// ACM or IAM certificate
let cloudfrontCert: acm.Certificate | string | null = null;
if (domainName && domainZoneName) {
domainZone = r53.HostedZone.fromLookup(this, 'HostedZone', {
domainName: domainZoneName,
});
useHTTPS = true;
if (iamCertId !== undefined) {
// Use IAM first when specified
cloudfrontCert = iamCertId;
} else if (!stack.region.startsWith('cn-')) {
// Try to use ACM certificate in us-east-1 for CloudFront
cloudfrontCert = new acm.DnsValidatedCertificate(this, 'CloudFrontCertificate', {
domainName: domainName,
hostedZone: domainZone,
validation: acm.CertificateValidation.fromDns(domainZone),
region: 'us-east-1',
});
} else {
throw new Error('You must specify iamCertId context for cn regions');
}
}
const vpc = ec2.Vpc.fromLookup(this, `VPC-${props.vpcId}`, {
vpcId: props.vpcId,
});
const assetBucket = new s3.Bucket(this, `OpenTunaAssets`, {
removalPolicy: cdk.RemovalPolicy.DESTROY,
});
// setup bucket for rubygems
const tunaRepoBucket = new s3.Bucket(this, 'TunaRepoBucket');
// CloudWatch dashboard
const dashboard = new cloudwatch.Dashboard(this, 'Dashboard', {
dashboardName: 'OpenTUNA-Dashboard',
});
const tunaManagerSG = new ec2.SecurityGroup(this, "TunaManagerSG", {
vpc,
description: "SG of Tuna Manager",
allowAllOutbound: true,
});
const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG of Tuna Worker",
allowAllOutbound: true,
});
const externalALBSG = new ec2.SecurityGroup(this, "ExternalALBSG", {
vpc,
description: "SG of External ALB",
allowAllOutbound: false,
});
const externalALB = new elbv2.ApplicationLoadBalancer(this, "ExternalALB", {
vpc,
securityGroup: externalALBSG,
internetFacing: true,
http2Enabled: useHTTPS,
});
dashboard.addWidgets(new cloudwatch.GraphWidget({
title: 'ALB Processed Data',
left: [externalALB.metricProcessedBytes({
label: 'Bytes per minute',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB Connections',
left: [externalALB.metricNewConnectionCount({
label: 'New',
period: cdk.Duration.minutes(1),
}), externalALB.metricActiveConnectionCount({
label: 'Active',
period: cdk.Duration.minutes(1),
}), externalALB.metricRejectedConnectionCount({
label: 'Rejected',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB HTTP Code from Target',
left: [externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_2XX_COUNT, {
label: '2XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_3XX_COUNT, {
label: '3XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_4XX_COUNT, {
label: '4XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_5XX_COUNT, {
label: '5XX',
period: cdk.Duration.minutes(1),
})]
}));
let cert: acm.Certificate | undefined;
if (useHTTPS) {
cert = new acm.Certificate(this, 'Certificate', {
domainName: domainName,
subjectAlternativeNames: [`${stack.region}.${domainName}`],
validation: acm.CertificateValidation.fromDns(domainZone),
});
}
const defaultALBPort: number = useHTTPS ? 443 : 80;
const defaultALBListener = externalALB.addListener(`DefaultPort-${defaultALBPort}`, {
protocol: useHTTPS ? elbv2.ApplicationProtocol.HTTPS : elbv2.ApplicationProtocol.HTTP,
port: defaultALBPort,
open: true,
certificates: cert ? [cert] : undefined,
sslPolicy: useHTTPS ? elbv2.SslPolicy.RECOMMENDED : undefined,
});
let httpOnlyALBListener: elbv2.ApplicationListener | undefined;
if (useHTTPS) {
// redirect HTTP to HTTPS
httpOnlyALBListener = externalALB.addListener(`DefaultPort-80`, {
protocol: elbv2.ApplicationProtocol.HTTP,
port: 80,
open: true,
defaultAction: elbv2.ListenerAction.redirect({
port: '443',
protocol: elbv2.ApplicationProtocol.HTTPS,
permanent: true,
}),
});
new r53.ARecord(this, 'ALBCustomDomain', {
zone: domainZone!,
recordName: `${stack.region}.${domainName}`,
ttl: cdk.Duration.minutes(5),
target: r53.RecordTarget.fromAlias(new alias.LoadBalancerTarget(externalALB)),
});
}
// Tunasync Manager stack
const tunaManagerStack = new TunaManagerStack(this, 'TunaManagerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
tunaManagerSG,
tunaManagerALBSG,
timeout: cdk.Duration.minutes(10),
assetBucket,
});
const managerUrl = `http://${tunaManagerStack.managerALB.loadBalancerDnsName}:${tunaManagerStack.managerPort}`;
// Tunasync Worker stack
const tunaWorkerStack = new TunaWorkerStack(this, 'TunaWorkerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
managerUrl,
timeout: cdk.Duration.minutes(10),
tunaWorkerSG,
assetBucket,
tunaRepoBucket,
});
tunaManagerALBSG.connections.allowFrom(tunaWorkerSG, ec2.Port.tcp(tunaManagerStack.managerPort), 'Access from tuna worker');
tunaWorkerSG.connections.allowFrom(tunaManagerSG, ec2.Port.tcp(tunaWorkerStack.workerPort), 'Access from tuna manager');
const ecsCluster = new ecs.Cluster(this, `ECSCluster`, {
vpc,
});
// Content Server stack
const contentServerStack = new ContentServerStack(this, 'ContentServerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
ecsCluster,
listener: defaultALBListener,
httpOnlyListener: httpOnlyALBListener,
dashboard,
});
// Web Portal stack
const webPortalStack = new WebPortalStack(this, 'WebPortalStack', {
vpc,
externalALBListener: defaultALBListener,
ecsCluster,
tunaManagerASG: tunaManagerStack.managerASG,
tunaManagerALBTargetGroup: tunaManagerStack.managerALBTargetGroup,
fileSystemId: props.fileSystemId,
fileSystemSGId: props.fileSystemSGId,
});
tunaManagerSG.connections.allowFrom(externalALBSG, ec2.Port.tcp(80), 'Allow external ALB to access tuna manager');
// Monitor stack
const monitorStack = new MonitorStack(this, 'MonitorStack', {
vpc,
domainName,
notifyTopic: props.notifyTopic,
tunaManagerUrl: managerUrl,
tunaManagerALBSG,
});
let commonBehaviorConfig = {
// special handling for redirections
forwardedValues: {
headers: ['Host'],
queryString: true,
},
// default 1 day cache
defaultTtl: cdk.Duration.days(1),
};
// origin access identity for s3 bucket
const oai = new cloudfront.OriginAccessIdentity(this, 'TunaRepoOAI');
tunaRepoBucket.grantRead(oai);
// CloudFront as cdn
let cloudfrontProps = {
originConfigs: [{
customOriginSource: {
domainName: useHTTPS ? `${stack.region}.${domainName}` : externalALB.loadBalancerDnsName,
originProtocolPolicy: cloudfront.OriginProtocolPolicy.MATCH_VIEWER
},
behaviors: [{
...commonBehaviorConfig,
isDefaultBehavior: true,
}, {
...commonBehaviorConfig,
pathPattern: '/debian/*',
}, {
...commonBehaviorConfig,
pathPattern: '/debian-security/*',
}, {
...commonBehaviorConfig,
pathPattern: '/ubuntu/*',
}, {
...commonBehaviorConfig,
// 5min cache for tunasync status
pathPattern: '/jobs',
defaultTtl: cdk.Duration.minutes(5),
}],
}, {
s3OriginSource: {
s3BucketSource: tunaRepoBucket,
originAccessIdentity: oai,
},
behaviors: [{
pathPattern: '/rubygems/gems/*',
// 1w cache for gem specs
defaultTtl: cdk.Duration.days(7),
}, {
pathPattern: '/rubygems/*',
// 1h cache for index files
defaultTtl: cdk.Duration.minutes(60),
}]
}],
defaultRootObject: '',
errorConfigurations: [
{
errorCode: 500,
errorCachingMinTtl: 30,
},
{
errorCode: 502,
errorCachingMinTtl: 0,
},
{
errorCode: 503,
errorCachingMinTtl: 0,
},
{
errorCode: 404,
errorCachingMinTtl: 3600,
responseCode: 404,
responsePagePath: '/404.html',
}
],
} as cloudfront.CloudFrontWebDistributionProps;
if (useHTTPS) {
// when https is enabled
cloudfrontProps = {
httpVersion: cloudfront.HttpVersion.HTTP2,
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.REDIRECT_TO_HTTPS,
...cloudfrontProps
};
if (cloudfrontCert instanceof acm.DnsValidatedCertificate) | else if (typeof cloudfrontCert === "string") {
// IAM cert
cloudfrontProps = {
viewerCertificate: cloudfront.ViewerCertificate.fromIamCertificate(
cloudfrontCert,
{
aliases: [domainName],
securityPolicy: cloudfront.SecurityPolicyProtocol.TLS_V1_2_2018,
sslMethod: cloudfront.SSLMethod.SNI, // default
}
),
...cloudfrontProps
};
}
}
// some particular options for China regions
if (stack.region.startsWith('cn-')) {
cloudfrontProps = Object.assign(cloudfrontProps, {
enableIpV6: false,
priceClass: cloudfront.PriceClass.PRICE_CLASS_ALL,
});
}
const logsBucket = new s3.Bucket(this, "OpentunaLogs");
// ALB logs
externalALB.logAccessLogs(logsBucket, 'alb-logs');
const cloudfrontLogPrefix = "new/";
// nested stack for log analysis
const OpentunaAnalyticsStack = new AnalyticsStack(this, 'OpentunaAnalyticsStack', {
resourcePrefix: "opentuna",
newKeyPrefix: cloudfrontLogPrefix,
gzKeyPrefix: "partitioned-gz/",
parquetKeyPrefix: "partitioned-parquet/",
logBucket: logsBucket,
notifyTopic: props.notifyTopic
});
cloudfrontProps = Object.assign(cloudfrontProps, {
loggingConfig: {
bucket: logsBucket,
includeCookies: true,
prefix: cloudfrontLogPrefix
}
});
const distribution = new cloudfront.CloudFrontWebDistribution(this, 'CloudFrontDist', cloudfrontProps);
// HACK: override /debian/* viewer protocol policy to allow-all
// see https://github.com/aws/aws-cdk/issues/7086
let dist = distribution.node.defaultChild as cloudfront.CfnDistribution;
let conf = dist.distributionConfig as cloudfront.CfnDistribution.DistributionConfigProperty;
let cacheBehaviors = conf.cacheBehaviors as cloudfront.CfnDistribution.CacheBehaviorProperty[];
let behavior = cacheBehaviors[0];
assert(behavior.pathPattern == '/debian/*');
for (let i = 0; i < cacheBehaviors.length; i++) {
if (['/debian/*', '/debian-security/*', '/ubuntu/*'].indexOf(cacheBehaviors[i].pathPattern) != -1) {
cacheBehaviors[i] = {
...cacheBehaviors[i],
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.ALLOW_ALL,
} as cloudfront.CfnDistribution.CacheBehaviorProperty;
}
}
if (domainZone) {
new route53.ARecord(this, 'ARecord', {
zone: domainZone!,
recordName: domainName,
target: route53.RecordTarget.fromAlias(new route53targets.CloudFrontTarget(distribution)),
ttl: cdk.Duration.minutes(5),
});
}
// invalidate cloudfront when web-portal changes
new CloudFrontInvalidate(this, 'CloudFrontInvalidate', {
distribution: distribution,
distributionPaths: ['/help*', '/news*', '/status*', '/static*', '/*.html', '/'],
updateKey: webPortalStack.dockerImageHash,
});
}
}
| {
// ACM cert
cloudfrontProps = {
aliasConfiguration: {
acmCertRef: cloudfrontCert.certificateArn,
names: [domainName],
},
...cloudfrontProps
}
} | conditional_block |
opentuna-stack.ts | import * as cdk from '@aws-cdk/core';
import * as cloudfront from '@aws-cdk/aws-cloudfront';
import * as route53 from '@aws-cdk/aws-route53';
import * as route53targets from '@aws-cdk/aws-route53-targets';
import * as acm from '@aws-cdk/aws-certificatemanager';
import * as cloudwatch from '@aws-cdk/aws-cloudwatch';
import * as alias from '@aws-cdk/aws-route53-targets';
import * as ec2 from '@aws-cdk/aws-ec2';
import * as sns from '@aws-cdk/aws-sns';
import * as elbv2 from '@aws-cdk/aws-elasticloadbalancingv2';
import * as ecs from '@aws-cdk/aws-ecs';
import * as s3 from '@aws-cdk/aws-s3';
import * as r53 from '@aws-cdk/aws-route53';
import { TunaManagerStack } from './tuna-manager';
import { TunaWorkerStack } from './tuna-worker';
import { ContentServerStack } from './content-server';
import { WebPortalStack } from './web-portal';
import { CloudFrontInvalidate } from './cloudfront-invalidate';
import { AnalyticsStack } from './analytics-stack';
import { MonitorStack } from './monitor-stack';
import { assert } from 'console';
export interface OpenTunaStackProps extends cdk.StackProps {
readonly vpcId: string;
readonly fileSystemId: string;
readonly fileSystemSGId: string;
readonly notifyTopic: sns.ITopic;
}
export class OpentunaStack extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props: OpenTunaStackProps) |
}
| {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = this.node.tryGetContext('iamCertId');
let useHTTPS = false;
let domainZone: r53.IHostedZone | undefined;
// ACM or IAM certificate
let cloudfrontCert: acm.Certificate | string | null = null;
if (domainName && domainZoneName) {
domainZone = r53.HostedZone.fromLookup(this, 'HostedZone', {
domainName: domainZoneName,
});
useHTTPS = true;
if (iamCertId !== undefined) {
// Use IAM first when specified
cloudfrontCert = iamCertId;
} else if (!stack.region.startsWith('cn-')) {
// Try to use ACM certificate in us-east-1 for CloudFront
cloudfrontCert = new acm.DnsValidatedCertificate(this, 'CloudFrontCertificate', {
domainName: domainName,
hostedZone: domainZone,
validation: acm.CertificateValidation.fromDns(domainZone),
region: 'us-east-1',
});
} else {
throw new Error('You must specify iamCertId context for cn regions');
}
}
const vpc = ec2.Vpc.fromLookup(this, `VPC-${props.vpcId}`, {
vpcId: props.vpcId,
});
const assetBucket = new s3.Bucket(this, `OpenTunaAssets`, {
removalPolicy: cdk.RemovalPolicy.DESTROY,
});
// setup bucket for rubygems
const tunaRepoBucket = new s3.Bucket(this, 'TunaRepoBucket');
// CloudWatch dashboard
const dashboard = new cloudwatch.Dashboard(this, 'Dashboard', {
dashboardName: 'OpenTUNA-Dashboard',
});
const tunaManagerSG = new ec2.SecurityGroup(this, "TunaManagerSG", {
vpc,
description: "SG of Tuna Manager",
allowAllOutbound: true,
});
const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG of Tuna Worker",
allowAllOutbound: true,
});
const externalALBSG = new ec2.SecurityGroup(this, "ExternalALBSG", {
vpc,
description: "SG of External ALB",
allowAllOutbound: false,
});
const externalALB = new elbv2.ApplicationLoadBalancer(this, "ExternalALB", {
vpc,
securityGroup: externalALBSG,
internetFacing: true,
http2Enabled: useHTTPS,
});
dashboard.addWidgets(new cloudwatch.GraphWidget({
title: 'ALB Processed Data',
left: [externalALB.metricProcessedBytes({
label: 'Bytes per minute',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB Connections',
left: [externalALB.metricNewConnectionCount({
label: 'New',
period: cdk.Duration.minutes(1),
}), externalALB.metricActiveConnectionCount({
label: 'Active',
period: cdk.Duration.minutes(1),
}), externalALB.metricRejectedConnectionCount({
label: 'Rejected',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB HTTP Code from Target',
left: [externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_2XX_COUNT, {
label: '2XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_3XX_COUNT, {
label: '3XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_4XX_COUNT, {
label: '4XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_5XX_COUNT, {
label: '5XX',
period: cdk.Duration.minutes(1),
})]
}));
let cert: acm.Certificate | undefined;
if (useHTTPS) {
cert = new acm.Certificate(this, 'Certificate', {
domainName: domainName,
subjectAlternativeNames: [`${stack.region}.${domainName}`],
validation: acm.CertificateValidation.fromDns(domainZone),
});
}
const defaultALBPort: number = useHTTPS ? 443 : 80;
const defaultALBListener = externalALB.addListener(`DefaultPort-${defaultALBPort}`, {
protocol: useHTTPS ? elbv2.ApplicationProtocol.HTTPS : elbv2.ApplicationProtocol.HTTP,
port: defaultALBPort,
open: true,
certificates: cert ? [cert] : undefined,
sslPolicy: useHTTPS ? elbv2.SslPolicy.RECOMMENDED : undefined,
});
let httpOnlyALBListener: elbv2.ApplicationListener | undefined;
if (useHTTPS) {
// redirect HTTP to HTTPS
httpOnlyALBListener = externalALB.addListener(`DefaultPort-80`, {
protocol: elbv2.ApplicationProtocol.HTTP,
port: 80,
open: true,
defaultAction: elbv2.ListenerAction.redirect({
port: '443',
protocol: elbv2.ApplicationProtocol.HTTPS,
permanent: true,
}),
});
new r53.ARecord(this, 'ALBCustomDomain', {
zone: domainZone!,
recordName: `${stack.region}.${domainName}`,
ttl: cdk.Duration.minutes(5),
target: r53.RecordTarget.fromAlias(new alias.LoadBalancerTarget(externalALB)),
});
}
// Tunasync Manager stack
const tunaManagerStack = new TunaManagerStack(this, 'TunaManagerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
tunaManagerSG,
tunaManagerALBSG,
timeout: cdk.Duration.minutes(10),
assetBucket,
});
const managerUrl = `http://${tunaManagerStack.managerALB.loadBalancerDnsName}:${tunaManagerStack.managerPort}`;
// Tunasync Worker stack
const tunaWorkerStack = new TunaWorkerStack(this, 'TunaWorkerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
managerUrl,
timeout: cdk.Duration.minutes(10),
tunaWorkerSG,
assetBucket,
tunaRepoBucket,
});
tunaManagerALBSG.connections.allowFrom(tunaWorkerSG, ec2.Port.tcp(tunaManagerStack.managerPort), 'Access from tuna worker');
tunaWorkerSG.connections.allowFrom(tunaManagerSG, ec2.Port.tcp(tunaWorkerStack.workerPort), 'Access from tuna manager');
const ecsCluster = new ecs.Cluster(this, `ECSCluster`, {
vpc,
});
// Content Server stack
const contentServerStack = new ContentServerStack(this, 'ContentServerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
ecsCluster,
listener: defaultALBListener,
httpOnlyListener: httpOnlyALBListener,
dashboard,
});
// Web Portal stack
const webPortalStack = new WebPortalStack(this, 'WebPortalStack', {
vpc,
externalALBListener: defaultALBListener,
ecsCluster,
tunaManagerASG: tunaManagerStack.managerASG,
tunaManagerALBTargetGroup: tunaManagerStack.managerALBTargetGroup,
fileSystemId: props.fileSystemId,
fileSystemSGId: props.fileSystemSGId,
});
tunaManagerSG.connections.allowFrom(externalALBSG, ec2.Port.tcp(80), 'Allow external ALB to access tuna manager');
// Monitor stack
const monitorStack = new MonitorStack(this, 'MonitorStack', {
vpc,
domainName,
notifyTopic: props.notifyTopic,
tunaManagerUrl: managerUrl,
tunaManagerALBSG,
});
let commonBehaviorConfig = {
// special handling for redirections
forwardedValues: {
headers: ['Host'],
queryString: true,
},
// default 1 day cache
defaultTtl: cdk.Duration.days(1),
};
// origin access identity for s3 bucket
const oai = new cloudfront.OriginAccessIdentity(this, 'TunaRepoOAI');
tunaRepoBucket.grantRead(oai);
// CloudFront as cdn
let cloudfrontProps = {
originConfigs: [{
customOriginSource: {
domainName: useHTTPS ? `${stack.region}.${domainName}` : externalALB.loadBalancerDnsName,
originProtocolPolicy: cloudfront.OriginProtocolPolicy.MATCH_VIEWER
},
behaviors: [{
...commonBehaviorConfig,
isDefaultBehavior: true,
}, {
...commonBehaviorConfig,
pathPattern: '/debian/*',
}, {
...commonBehaviorConfig,
pathPattern: '/debian-security/*',
}, {
...commonBehaviorConfig,
pathPattern: '/ubuntu/*',
}, {
...commonBehaviorConfig,
// 5min cache for tunasync status
pathPattern: '/jobs',
defaultTtl: cdk.Duration.minutes(5),
}],
}, {
s3OriginSource: {
s3BucketSource: tunaRepoBucket,
originAccessIdentity: oai,
},
behaviors: [{
pathPattern: '/rubygems/gems/*',
// 1w cache for gem specs
defaultTtl: cdk.Duration.days(7),
}, {
pathPattern: '/rubygems/*',
// 1h cache for index files
defaultTtl: cdk.Duration.minutes(60),
}]
}],
defaultRootObject: '',
errorConfigurations: [
{
errorCode: 500,
errorCachingMinTtl: 30,
},
{
errorCode: 502,
errorCachingMinTtl: 0,
},
{
errorCode: 503,
errorCachingMinTtl: 0,
},
{
errorCode: 404,
errorCachingMinTtl: 3600,
responseCode: 404,
responsePagePath: '/404.html',
}
],
} as cloudfront.CloudFrontWebDistributionProps;
if (useHTTPS) {
// when https is enabled
cloudfrontProps = {
httpVersion: cloudfront.HttpVersion.HTTP2,
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.REDIRECT_TO_HTTPS,
...cloudfrontProps
};
if (cloudfrontCert instanceof acm.DnsValidatedCertificate) {
// ACM cert
cloudfrontProps = {
aliasConfiguration: {
acmCertRef: cloudfrontCert.certificateArn,
names: [domainName],
},
...cloudfrontProps
}
} else if (typeof cloudfrontCert === "string") {
// IAM cert
cloudfrontProps = {
viewerCertificate: cloudfront.ViewerCertificate.fromIamCertificate(
cloudfrontCert,
{
aliases: [domainName],
securityPolicy: cloudfront.SecurityPolicyProtocol.TLS_V1_2_2018,
sslMethod: cloudfront.SSLMethod.SNI, // default
}
),
...cloudfrontProps
};
}
}
// some particular options for China regions
if (stack.region.startsWith('cn-')) {
cloudfrontProps = Object.assign(cloudfrontProps, {
enableIpV6: false,
priceClass: cloudfront.PriceClass.PRICE_CLASS_ALL,
});
}
const logsBucket = new s3.Bucket(this, "OpentunaLogs");
// ALB logs
externalALB.logAccessLogs(logsBucket, 'alb-logs');
const cloudfrontLogPrefix = "new/";
// nested stack for log analysis
const OpentunaAnalyticsStack = new AnalyticsStack(this, 'OpentunaAnalyticsStack', {
resourcePrefix: "opentuna",
newKeyPrefix: cloudfrontLogPrefix,
gzKeyPrefix: "partitioned-gz/",
parquetKeyPrefix: "partitioned-parquet/",
logBucket: logsBucket,
notifyTopic: props.notifyTopic
});
cloudfrontProps = Object.assign(cloudfrontProps, {
loggingConfig: {
bucket: logsBucket,
includeCookies: true,
prefix: cloudfrontLogPrefix
}
});
const distribution = new cloudfront.CloudFrontWebDistribution(this, 'CloudFrontDist', cloudfrontProps);
// HACK: override /debian/* viewer protocol policy to allow-all
// see https://github.com/aws/aws-cdk/issues/7086
let dist = distribution.node.defaultChild as cloudfront.CfnDistribution;
let conf = dist.distributionConfig as cloudfront.CfnDistribution.DistributionConfigProperty;
let cacheBehaviors = conf.cacheBehaviors as cloudfront.CfnDistribution.CacheBehaviorProperty[];
let behavior = cacheBehaviors[0];
assert(behavior.pathPattern == '/debian/*');
for (let i = 0; i < cacheBehaviors.length; i++) {
if (['/debian/*', '/debian-security/*', '/ubuntu/*'].indexOf(cacheBehaviors[i].pathPattern) != -1) {
cacheBehaviors[i] = {
...cacheBehaviors[i],
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.ALLOW_ALL,
} as cloudfront.CfnDistribution.CacheBehaviorProperty;
}
}
if (domainZone) {
new route53.ARecord(this, 'ARecord', {
zone: domainZone!,
recordName: domainName,
target: route53.RecordTarget.fromAlias(new route53targets.CloudFrontTarget(distribution)),
ttl: cdk.Duration.minutes(5),
});
}
// invalidate cloudfront when web-portal changes
new CloudFrontInvalidate(this, 'CloudFrontInvalidate', {
distribution: distribution,
distributionPaths: ['/help*', '/news*', '/status*', '/static*', '/*.html', '/'],
updateKey: webPortalStack.dockerImageHash,
});
} | identifier_body |
opentuna-stack.ts | import * as cdk from '@aws-cdk/core';
import * as cloudfront from '@aws-cdk/aws-cloudfront';
import * as route53 from '@aws-cdk/aws-route53';
import * as route53targets from '@aws-cdk/aws-route53-targets';
import * as acm from '@aws-cdk/aws-certificatemanager';
import * as cloudwatch from '@aws-cdk/aws-cloudwatch';
import * as alias from '@aws-cdk/aws-route53-targets';
import * as ec2 from '@aws-cdk/aws-ec2';
import * as sns from '@aws-cdk/aws-sns';
import * as elbv2 from '@aws-cdk/aws-elasticloadbalancingv2';
import * as ecs from '@aws-cdk/aws-ecs';
import * as s3 from '@aws-cdk/aws-s3';
import * as r53 from '@aws-cdk/aws-route53';
import { TunaManagerStack } from './tuna-manager';
import { TunaWorkerStack } from './tuna-worker';
import { ContentServerStack } from './content-server';
import { WebPortalStack } from './web-portal';
import { CloudFrontInvalidate } from './cloudfront-invalidate';
import { AnalyticsStack } from './analytics-stack';
import { MonitorStack } from './monitor-stack';
import { assert } from 'console';
export interface OpenTunaStackProps extends cdk.StackProps {
readonly vpcId: string;
readonly fileSystemId: string;
readonly fileSystemSGId: string;
readonly notifyTopic: sns.ITopic;
}
export class OpentunaStack extends cdk.Stack {
constructor(scope: cdk.Construct, id: string, props: OpenTunaStackProps) {
super(scope, id, props);
const stack = cdk.Stack.of(this);
const domainName = this.node.tryGetContext('domainName');
const domainZoneName = this.node.tryGetContext('domainZone');
const iamCertId = this.node.tryGetContext('iamCertId');
let useHTTPS = false;
let domainZone: r53.IHostedZone | undefined;
// ACM or IAM certificate
let cloudfrontCert: acm.Certificate | string | null = null;
if (domainName && domainZoneName) {
domainZone = r53.HostedZone.fromLookup(this, 'HostedZone', {
domainName: domainZoneName,
});
useHTTPS = true;
if (iamCertId !== undefined) {
// Use IAM first when specified
cloudfrontCert = iamCertId;
} else if (!stack.region.startsWith('cn-')) {
// Try to use ACM certificate in us-east-1 for CloudFront
cloudfrontCert = new acm.DnsValidatedCertificate(this, 'CloudFrontCertificate', {
domainName: domainName,
hostedZone: domainZone,
validation: acm.CertificateValidation.fromDns(domainZone),
region: 'us-east-1',
});
} else {
throw new Error('You must specify iamCertId context for cn regions');
}
}
const vpc = ec2.Vpc.fromLookup(this, `VPC-${props.vpcId}`, {
vpcId: props.vpcId,
});
const assetBucket = new s3.Bucket(this, `OpenTunaAssets`, {
removalPolicy: cdk.RemovalPolicy.DESTROY,
});
// setup bucket for rubygems
const tunaRepoBucket = new s3.Bucket(this, 'TunaRepoBucket');
// CloudWatch dashboard
const dashboard = new cloudwatch.Dashboard(this, 'Dashboard', {
dashboardName: 'OpenTUNA-Dashboard',
}); | allowAllOutbound: true,
});
const tunaManagerALBSG = new ec2.SecurityGroup(this, "TunaManagerALBSG", {
vpc,
description: "SG of ALB of Tuna Manager",
allowAllOutbound: false,
});
const tunaWorkerSG = new ec2.SecurityGroup(this, "TunaWorkerSG", {
vpc,
description: "SG of Tuna Worker",
allowAllOutbound: true,
});
const externalALBSG = new ec2.SecurityGroup(this, "ExternalALBSG", {
vpc,
description: "SG of External ALB",
allowAllOutbound: false,
});
const externalALB = new elbv2.ApplicationLoadBalancer(this, "ExternalALB", {
vpc,
securityGroup: externalALBSG,
internetFacing: true,
http2Enabled: useHTTPS,
});
dashboard.addWidgets(new cloudwatch.GraphWidget({
title: 'ALB Processed Data',
left: [externalALB.metricProcessedBytes({
label: 'Bytes per minute',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB Connections',
left: [externalALB.metricNewConnectionCount({
label: 'New',
period: cdk.Duration.minutes(1),
}), externalALB.metricActiveConnectionCount({
label: 'Active',
period: cdk.Duration.minutes(1),
}), externalALB.metricRejectedConnectionCount({
label: 'Rejected',
period: cdk.Duration.minutes(1),
})]
}), new cloudwatch.GraphWidget({
title: 'ALB HTTP Code from Target',
left: [externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_2XX_COUNT, {
label: '2XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_3XX_COUNT, {
label: '3XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_4XX_COUNT, {
label: '4XX',
period: cdk.Duration.minutes(1),
}), externalALB.metricHttpCodeTarget(elbv2.HttpCodeTarget.TARGET_5XX_COUNT, {
label: '5XX',
period: cdk.Duration.minutes(1),
})]
}));
let cert: acm.Certificate | undefined;
if (useHTTPS) {
cert = new acm.Certificate(this, 'Certificate', {
domainName: domainName,
subjectAlternativeNames: [`${stack.region}.${domainName}`],
validation: acm.CertificateValidation.fromDns(domainZone),
});
}
const defaultALBPort: number = useHTTPS ? 443 : 80;
const defaultALBListener = externalALB.addListener(`DefaultPort-${defaultALBPort}`, {
protocol: useHTTPS ? elbv2.ApplicationProtocol.HTTPS : elbv2.ApplicationProtocol.HTTP,
port: defaultALBPort,
open: true,
certificates: cert ? [cert] : undefined,
sslPolicy: useHTTPS ? elbv2.SslPolicy.RECOMMENDED : undefined,
});
let httpOnlyALBListener: elbv2.ApplicationListener | undefined;
if (useHTTPS) {
// redirect HTTP to HTTPS
httpOnlyALBListener = externalALB.addListener(`DefaultPort-80`, {
protocol: elbv2.ApplicationProtocol.HTTP,
port: 80,
open: true,
defaultAction: elbv2.ListenerAction.redirect({
port: '443',
protocol: elbv2.ApplicationProtocol.HTTPS,
permanent: true,
}),
});
new r53.ARecord(this, 'ALBCustomDomain', {
zone: domainZone!,
recordName: `${stack.region}.${domainName}`,
ttl: cdk.Duration.minutes(5),
target: r53.RecordTarget.fromAlias(new alias.LoadBalancerTarget(externalALB)),
});
}
// Tunasync Manager stack
const tunaManagerStack = new TunaManagerStack(this, 'TunaManagerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
tunaManagerSG,
tunaManagerALBSG,
timeout: cdk.Duration.minutes(10),
assetBucket,
});
const managerUrl = `http://${tunaManagerStack.managerALB.loadBalancerDnsName}:${tunaManagerStack.managerPort}`;
// Tunasync Worker stack
const tunaWorkerStack = new TunaWorkerStack(this, 'TunaWorkerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
managerUrl,
timeout: cdk.Duration.minutes(10),
tunaWorkerSG,
assetBucket,
tunaRepoBucket,
});
tunaManagerALBSG.connections.allowFrom(tunaWorkerSG, ec2.Port.tcp(tunaManagerStack.managerPort), 'Access from tuna worker');
tunaWorkerSG.connections.allowFrom(tunaManagerSG, ec2.Port.tcp(tunaWorkerStack.workerPort), 'Access from tuna manager');
const ecsCluster = new ecs.Cluster(this, `ECSCluster`, {
vpc,
});
// Content Server stack
const contentServerStack = new ContentServerStack(this, 'ContentServerStack', {
vpc,
fileSystemId: props.fileSystemId,
notifyTopic: props.notifyTopic,
ecsCluster,
listener: defaultALBListener,
httpOnlyListener: httpOnlyALBListener,
dashboard,
});
// Web Portal stack
const webPortalStack = new WebPortalStack(this, 'WebPortalStack', {
vpc,
externalALBListener: defaultALBListener,
ecsCluster,
tunaManagerASG: tunaManagerStack.managerASG,
tunaManagerALBTargetGroup: tunaManagerStack.managerALBTargetGroup,
fileSystemId: props.fileSystemId,
fileSystemSGId: props.fileSystemSGId,
});
tunaManagerSG.connections.allowFrom(externalALBSG, ec2.Port.tcp(80), 'Allow external ALB to access tuna manager');
// Monitor stack
const monitorStack = new MonitorStack(this, 'MonitorStack', {
vpc,
domainName,
notifyTopic: props.notifyTopic,
tunaManagerUrl: managerUrl,
tunaManagerALBSG,
});
let commonBehaviorConfig = {
// special handling for redirections
forwardedValues: {
headers: ['Host'],
queryString: true,
},
// default 1 day cache
defaultTtl: cdk.Duration.days(1),
};
// origin access identity for s3 bucket
const oai = new cloudfront.OriginAccessIdentity(this, 'TunaRepoOAI');
tunaRepoBucket.grantRead(oai);
// CloudFront as cdn
let cloudfrontProps = {
originConfigs: [{
customOriginSource: {
domainName: useHTTPS ? `${stack.region}.${domainName}` : externalALB.loadBalancerDnsName,
originProtocolPolicy: cloudfront.OriginProtocolPolicy.MATCH_VIEWER
},
behaviors: [{
...commonBehaviorConfig,
isDefaultBehavior: true,
}, {
...commonBehaviorConfig,
pathPattern: '/debian/*',
}, {
...commonBehaviorConfig,
pathPattern: '/debian-security/*',
}, {
...commonBehaviorConfig,
pathPattern: '/ubuntu/*',
}, {
...commonBehaviorConfig,
// 5min cache for tunasync status
pathPattern: '/jobs',
defaultTtl: cdk.Duration.minutes(5),
}],
}, {
s3OriginSource: {
s3BucketSource: tunaRepoBucket,
originAccessIdentity: oai,
},
behaviors: [{
pathPattern: '/rubygems/gems/*',
// 1w cache for gem specs
defaultTtl: cdk.Duration.days(7),
}, {
pathPattern: '/rubygems/*',
// 1h cache for index files
defaultTtl: cdk.Duration.minutes(60),
}]
}],
defaultRootObject: '',
errorConfigurations: [
{
errorCode: 500,
errorCachingMinTtl: 30,
},
{
errorCode: 502,
errorCachingMinTtl: 0,
},
{
errorCode: 503,
errorCachingMinTtl: 0,
},
{
errorCode: 404,
errorCachingMinTtl: 3600,
responseCode: 404,
responsePagePath: '/404.html',
}
],
} as cloudfront.CloudFrontWebDistributionProps;
if (useHTTPS) {
// when https is enabled
cloudfrontProps = {
httpVersion: cloudfront.HttpVersion.HTTP2,
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.REDIRECT_TO_HTTPS,
...cloudfrontProps
};
if (cloudfrontCert instanceof acm.DnsValidatedCertificate) {
// ACM cert
cloudfrontProps = {
aliasConfiguration: {
acmCertRef: cloudfrontCert.certificateArn,
names: [domainName],
},
...cloudfrontProps
}
} else if (typeof cloudfrontCert === "string") {
// IAM cert
cloudfrontProps = {
viewerCertificate: cloudfront.ViewerCertificate.fromIamCertificate(
cloudfrontCert,
{
aliases: [domainName],
securityPolicy: cloudfront.SecurityPolicyProtocol.TLS_V1_2_2018,
sslMethod: cloudfront.SSLMethod.SNI, // default
}
),
...cloudfrontProps
};
}
}
// some particular options for China regions
if (stack.region.startsWith('cn-')) {
cloudfrontProps = Object.assign(cloudfrontProps, {
enableIpV6: false,
priceClass: cloudfront.PriceClass.PRICE_CLASS_ALL,
});
}
const logsBucket = new s3.Bucket(this, "OpentunaLogs");
// ALB logs
externalALB.logAccessLogs(logsBucket, 'alb-logs');
const cloudfrontLogPrefix = "new/";
// nested stack for log analysis
const OpentunaAnalyticsStack = new AnalyticsStack(this, 'OpentunaAnalyticsStack', {
resourcePrefix: "opentuna",
newKeyPrefix: cloudfrontLogPrefix,
gzKeyPrefix: "partitioned-gz/",
parquetKeyPrefix: "partitioned-parquet/",
logBucket: logsBucket,
notifyTopic: props.notifyTopic
});
cloudfrontProps = Object.assign(cloudfrontProps, {
loggingConfig: {
bucket: logsBucket,
includeCookies: true,
prefix: cloudfrontLogPrefix
}
});
const distribution = new cloudfront.CloudFrontWebDistribution(this, 'CloudFrontDist', cloudfrontProps);
// HACK: override /debian/* viewer protocol policy to allow-all
// see https://github.com/aws/aws-cdk/issues/7086
let dist = distribution.node.defaultChild as cloudfront.CfnDistribution;
let conf = dist.distributionConfig as cloudfront.CfnDistribution.DistributionConfigProperty;
let cacheBehaviors = conf.cacheBehaviors as cloudfront.CfnDistribution.CacheBehaviorProperty[];
let behavior = cacheBehaviors[0];
assert(behavior.pathPattern == '/debian/*');
for (let i = 0; i < cacheBehaviors.length; i++) {
if (['/debian/*', '/debian-security/*', '/ubuntu/*'].indexOf(cacheBehaviors[i].pathPattern) != -1) {
cacheBehaviors[i] = {
...cacheBehaviors[i],
viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.ALLOW_ALL,
} as cloudfront.CfnDistribution.CacheBehaviorProperty;
}
}
if (domainZone) {
new route53.ARecord(this, 'ARecord', {
zone: domainZone!,
recordName: domainName,
target: route53.RecordTarget.fromAlias(new route53targets.CloudFrontTarget(distribution)),
ttl: cdk.Duration.minutes(5),
});
}
// invalidate cloudfront when web-portal changes
new CloudFrontInvalidate(this, 'CloudFrontInvalidate', {
distribution: distribution,
distributionPaths: ['/help*', '/news*', '/status*', '/static*', '/*.html', '/'],
updateKey: webPortalStack.dockerImageHash,
});
}
} |
const tunaManagerSG = new ec2.SecurityGroup(this, "TunaManagerSG", {
vpc,
description: "SG of Tuna Manager", | random_line_split |
L.IM_RoutingControl.js | /**
* L.Control.RoutingControl control de routing basado en el leaflet-routing-machine
*/
L.Control.RoutingControl = L.Control.extend({
includes: L.Mixin.Events,
options: {
position: 'topleft',
lang: 'ca',
id: 'dv_bt_Routing',
className: 'leaflet-bar btn btn-default btn-sm grisfort',
title: 'Routing',
langTitle: 'Routing',
html: '<span id="span_bt_Routing" class="t" style="font-size:16px; margin-top:-2px;">'+
'<i class="t-square-rounded" style="-webkit-transform:scale(1.25) scale(0.65) rotate(45deg);-moz-transform:scale(1.25) scale(0.65) rotate(45deg);transform:scale(1.25) scale(0.65) rotate(45deg)"></i>'+
'<i class="t-turn-90-l t-c-white" style="-webkit-transform:scale(-1.3, 1.3);-moz-transform:scale(-1.3, 1.3);transform:scale(-1.3, 1.3)"></i>'+
'</span>',
tooltip: 'right',
marker_style_origen: {
icon : '',
markerColor : 'green',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
marker_style_desti: {
icon : '',
markerColor : 'red',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
marker_style_intermig: {
icon : '',
markerColor : 'orange',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
originTexts: {
title: "Càlcul de rutes",
btnStart: "Defineix com a origen",
btnEnd: "Defineix com a destí",
btnReverse: "Ruta inversa",
btnAdd: "Afegir punts",
start: "Inici",
end: "Destí"
},
texts: {
title: "Càlcul de rutes",
btnStart: "Defineix com a origen",
btnEnd: "Defineix com a destí",
btnReverse: "Ruta inversa",
btnAdd: "Afegir punts",
start: "Inici",
end: "Destí"
}
},
//TODO ver el tema del lang para poder cambiar el idioma del control
initialize: function(options) {
L.setOptions(this, options);
var self = this,
options = this.options,
lang = options.lang,
puntIntermig = L.AwesomeMarkers.icon(options.marker_style_intermig),
puntDesti = L.AwesomeMarkers.icon(options.marker_style_desti),
puntOrigen = L.AwesomeMarkers.icon(options.marker_style_origen);
this._reversablePlan = L.Routing.Plan.extend({
createGeocoders: function() {
var container = L.Routing.Plan.prototype.createGeocoders.call(this),
title = (window.lang) ? window.lang.translate(options.originTexts.btnReverse) : options.texts.btnReverse,
reverseButton = self._createButton('<span class="glyphicon glyphicon-sort" style="font-size:14px;"></span>', container, title, lang);
L.DomEvent.on(reverseButton, 'click', function() {
var waypoints = this.getWaypoints();
this.setWaypoints(waypoints.reverse());
}, this);
return container;
}
});
var createMarker = function(i, wp) {
var numWp = this._route.getWaypoints().length;
if(i == 0){
return L.marker(wp.latLng, {
draggable: true,
icon: puntOrigen
});
}
else if (i === (numWp - 1)){
| else {
return L.marker(wp.latLng, {
draggable: true,
icon: puntIntermig
});
}
};
this._plan = new this._reversablePlan([], {
geocoder: L.Control.Geocoder.icgc(),
routeWhileDragging: true,
language: lang,
createMarker: createMarker.bind(self)
});
//console.debug(lang);
this._route = L.Routing.control({
router: L.Routing.mapzen('mapzen-aMHsmLA', {
language: lang,
costing:'auto',
directions_options: {
language: lang
}
}),
formatter: new L.Routing.mapzenFormatter(),
routeWhileDragging: true,
plan: this._plan,
position: 'topleft',
language: lang,
showAlternatives: true,
lineOptions: {
styles: [
{color: '#00B3FD', opacity: 1, weight: 4},
]
},
altLineOptions:{
styles: [
{color: 'black', opacity: 1, weight: 2},
]
}
});
},
onAdd: function(map){
var self = this,
options = self.options,
stop = L.DomEvent.stopPropagation,
container = L.DomUtil.create('div', options.className);
container.id = options.id;
container.innerHTML = options.html;
container.title = options.title;
container.dataset.toggle = 'tooltip';
container.dataset.placement = options.tooltip;
container.dataset.langTitle = options.langTitle;
self._div = container;
self._map = map;
L.DomEvent
.on(container, 'click', stop)
.on(container, 'mousedown', stop)
.on(container, 'dblclick', stop)
.on(container, 'click', L.DomEvent.preventDefault)
.on(container, 'click', self._toggle, self);
return container;
},
hideBtn: function(){
var self = this;
$(self._div).hide();
},
showBtn: function(){
var self = this;
$(self._div).show();
},
show: function() {
L.DomUtil.removeClass(this._div, 'grisfort');
L.DomUtil.addClass(this._div, 'greenfort');
var _map = this._map,
options = this.options,
_texts = options.texts,
_route = this._route;
_map.fire('showRouting'); //to track ga events
_map.on('click', this._routingPopup, this);
_route.addTo(_map);
if(window.lang){
_texts.title = window.lang.translate(options.originTexts.title);
_texts.btnReverse = window.lang.translate(options.originTexts.btnReverse);
_texts.btnAdd = window.lang.translate(options.originTexts.btnAdd);
_texts.start = window.lang.translate(options.originTexts.start);
_texts.end = window.lang.translate(options.originTexts.end);
}
$('.leaflet-routing-geocoders').before( '<div class="div-routing-title"><span lang="ca" class="routing-title">'+_texts.title+'</span> <a href="http://www.liedman.net/leaflet-routing-machine/" target="_blank" class="div-routing-title" style="display:inline;"><span class="glyphicon glyphicon-info-sign white" style="font-size:14px;"></a></div>' );
$('.leaflet-routing-add-waypoint').attr('title',_texts.btnAdd);
$('.leaflet-routing-add-waypoint').attr('lang',options.lang);
$('.leaflet-routing-geocoder').first().find('input').attr('placeholder',_texts.start);
$('.leaflet-routing-geocoder').last().find('input').attr('placeholder',_texts.end);
var offset = $(this._div).offset();
jQuery('.leaflet-routing-container').css('top', (offset.top-60)+'px');
jQuery('.leaflet-routing-container').css('left', (offset.left + 35)+'px');
jQuery('.leaflet-routing-container').css('position','absolute');
jQuery('.leaflet-routing-container').css('z-index','100');
},
hide: function() {
var self = this,
_map = self._map,
_route = self._route;
L.DomUtil.removeClass(self._div, 'greenfort');
L.DomUtil.addClass(self._div, 'grisfort');
console.debug("AQUI");
try{
_route.removeFrom.call(_route,_map);
}catch(e){
console.debug(e);
}finally{
_map.off('click',self._routingPopup, self);
}
},
_toggle: function(e){
var collapsed = L.DomUtil.hasClass(this._div, 'grisfort');
this[collapsed ? 'show' : 'hide']();
},
_routingPopup: function(e) {
console.debug("routing");
var options = this.options,
_texts = options.texts;
if(window.lang){
_texts.title = window.lang.translate(options.originTexts.title);
_texts.btnStart = window.lang.translate(options.originTexts.btnStart);
_texts.btnEnd = window.lang.translate(options.originTexts.btnEnd);
}
var container ='<div id="contentRoutingPopup" class="contentRoutingPopup">';
container +='<h4 style="border-bottom:0px;" lang="ca">'+_texts.title+'</h4>';
container +='<button class="btn startBtn" lang="ca" type="button" id="startBtn">'+_texts.btnStart+'</button>'+
'<span class="awesome-marker-icon-green awesome-marker leaflet-zoom-hide leaflet-clickable leaflet-marker-draggable icona icona-origen" id="icona-origen"></span>'+
'<button class="btn endBtn" lang="ca" type="button" id="destBtn">'+_texts.btnEnd+'</button>'+
'<span class="awesome-marker-icon-red awesome-marker leaflet-zoom-hide leaflet-clickable leaflet-marker-draggable icona icona-desti" id="icona-desti"></span>';
container += "</div>";
var _map = this._map,
_route = this._route;
L.popup().setContent(container).setLatLng(e.latlng).openOn(_map);
jQuery(".leaflet-popup-content").css('width','184px');
jQuery(".leaflet-popup-content").css('margin','5px 15px');
jQuery('#startBtn').on('click', function() {
_route.spliceWaypoints(0, 1, e.latlng);
_map.closePopup();
});
jQuery('#destBtn').on('click', function() {
_route.spliceWaypoints(_route.getWaypoints().length - 1, 1, e.latlng);
_map.closePopup();
});
jQuery('#icona-origen').on('click', function() {
_route.spliceWaypoints(0, 1, e.latlng);
_map.closePopup();
});
jQuery('#icona-desti').on('click', function() {
_route.spliceWaypoints(_route.getWaypoints().length - 1, 1, e.latlng);
_map.closePopup();
});
},
_createButton: function(label, container, title, lang) {
var btn = L.DomUtil.create('button', '', container);
btn.setAttribute('type', 'button');
btn.setAttribute('lang', lang);
btn.setAttribute('title', title);
btn.innerHTML = label;
return btn;
},
_createSpan: function(label, container) {
var span = L.DomUtil.create('span', '', container);
span.innerHTML = label;
return span;
}
});
L.control.routingControl = function(options){
return new L.Control.RoutingControl(options);
}; | return L.marker(wp.latLng, {
draggable: true,
icon: puntDesti
});
}
| conditional_block |
L.IM_RoutingControl.js | /**
* L.Control.RoutingControl control de routing basado en el leaflet-routing-machine
*/
L.Control.RoutingControl = L.Control.extend({
includes: L.Mixin.Events,
options: {
position: 'topleft',
lang: 'ca',
id: 'dv_bt_Routing',
className: 'leaflet-bar btn btn-default btn-sm grisfort',
title: 'Routing',
langTitle: 'Routing',
html: '<span id="span_bt_Routing" class="t" style="font-size:16px; margin-top:-2px;">'+ | '<i class="t-square-rounded" style="-webkit-transform:scale(1.25) scale(0.65) rotate(45deg);-moz-transform:scale(1.25) scale(0.65) rotate(45deg);transform:scale(1.25) scale(0.65) rotate(45deg)"></i>'+
'<i class="t-turn-90-l t-c-white" style="-webkit-transform:scale(-1.3, 1.3);-moz-transform:scale(-1.3, 1.3);transform:scale(-1.3, 1.3)"></i>'+
'</span>',
tooltip: 'right',
marker_style_origen: {
icon : '',
markerColor : 'green',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
marker_style_desti: {
icon : '',
markerColor : 'red',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
marker_style_intermig: {
icon : '',
markerColor : 'orange',
divColor:'transparent',
iconAnchor : new L.Point(14, 42),
iconSize : new L.Point(28, 42),
iconColor : '#000000',
prefix : 'fa',
isCanvas:false,
radius:6,
opacity:1,
weight : 2,
fillOpacity : 0.9,
color : "#ffffff",
fillColor :"transparent"
},
originTexts: {
title: "Càlcul de rutes",
btnStart: "Defineix com a origen",
btnEnd: "Defineix com a destí",
btnReverse: "Ruta inversa",
btnAdd: "Afegir punts",
start: "Inici",
end: "Destí"
},
texts: {
title: "Càlcul de rutes",
btnStart: "Defineix com a origen",
btnEnd: "Defineix com a destí",
btnReverse: "Ruta inversa",
btnAdd: "Afegir punts",
start: "Inici",
end: "Destí"
}
},
//TODO ver el tema del lang para poder cambiar el idioma del control
initialize: function(options) {
L.setOptions(this, options);
var self = this,
options = this.options,
lang = options.lang,
puntIntermig = L.AwesomeMarkers.icon(options.marker_style_intermig),
puntDesti = L.AwesomeMarkers.icon(options.marker_style_desti),
puntOrigen = L.AwesomeMarkers.icon(options.marker_style_origen);
this._reversablePlan = L.Routing.Plan.extend({
createGeocoders: function() {
var container = L.Routing.Plan.prototype.createGeocoders.call(this),
title = (window.lang) ? window.lang.translate(options.originTexts.btnReverse) : options.texts.btnReverse,
reverseButton = self._createButton('<span class="glyphicon glyphicon-sort" style="font-size:14px;"></span>', container, title, lang);
L.DomEvent.on(reverseButton, 'click', function() {
var waypoints = this.getWaypoints();
this.setWaypoints(waypoints.reverse());
}, this);
return container;
}
});
var createMarker = function(i, wp) {
var numWp = this._route.getWaypoints().length;
if(i == 0){
return L.marker(wp.latLng, {
draggable: true,
icon: puntOrigen
});
}
else if (i === (numWp - 1)){
return L.marker(wp.latLng, {
draggable: true,
icon: puntDesti
});
}
else {
return L.marker(wp.latLng, {
draggable: true,
icon: puntIntermig
});
}
};
this._plan = new this._reversablePlan([], {
geocoder: L.Control.Geocoder.icgc(),
routeWhileDragging: true,
language: lang,
createMarker: createMarker.bind(self)
});
//console.debug(lang);
this._route = L.Routing.control({
router: L.Routing.mapzen('mapzen-aMHsmLA', {
language: lang,
costing:'auto',
directions_options: {
language: lang
}
}),
formatter: new L.Routing.mapzenFormatter(),
routeWhileDragging: true,
plan: this._plan,
position: 'topleft',
language: lang,
showAlternatives: true,
lineOptions: {
styles: [
{color: '#00B3FD', opacity: 1, weight: 4},
]
},
altLineOptions:{
styles: [
{color: 'black', opacity: 1, weight: 2},
]
}
});
},
onAdd: function(map){
var self = this,
options = self.options,
stop = L.DomEvent.stopPropagation,
container = L.DomUtil.create('div', options.className);
container.id = options.id;
container.innerHTML = options.html;
container.title = options.title;
container.dataset.toggle = 'tooltip';
container.dataset.placement = options.tooltip;
container.dataset.langTitle = options.langTitle;
self._div = container;
self._map = map;
L.DomEvent
.on(container, 'click', stop)
.on(container, 'mousedown', stop)
.on(container, 'dblclick', stop)
.on(container, 'click', L.DomEvent.preventDefault)
.on(container, 'click', self._toggle, self);
return container;
},
hideBtn: function(){
var self = this;
$(self._div).hide();
},
showBtn: function(){
var self = this;
$(self._div).show();
},
show: function() {
L.DomUtil.removeClass(this._div, 'grisfort');
L.DomUtil.addClass(this._div, 'greenfort');
var _map = this._map,
options = this.options,
_texts = options.texts,
_route = this._route;
_map.fire('showRouting'); //to track ga events
_map.on('click', this._routingPopup, this);
_route.addTo(_map);
if(window.lang){
_texts.title = window.lang.translate(options.originTexts.title);
_texts.btnReverse = window.lang.translate(options.originTexts.btnReverse);
_texts.btnAdd = window.lang.translate(options.originTexts.btnAdd);
_texts.start = window.lang.translate(options.originTexts.start);
_texts.end = window.lang.translate(options.originTexts.end);
}
$('.leaflet-routing-geocoders').before( '<div class="div-routing-title"><span lang="ca" class="routing-title">'+_texts.title+'</span> <a href="http://www.liedman.net/leaflet-routing-machine/" target="_blank" class="div-routing-title" style="display:inline;"><span class="glyphicon glyphicon-info-sign white" style="font-size:14px;"></a></div>' );
$('.leaflet-routing-add-waypoint').attr('title',_texts.btnAdd);
$('.leaflet-routing-add-waypoint').attr('lang',options.lang);
$('.leaflet-routing-geocoder').first().find('input').attr('placeholder',_texts.start);
$('.leaflet-routing-geocoder').last().find('input').attr('placeholder',_texts.end);
var offset = $(this._div).offset();
jQuery('.leaflet-routing-container').css('top', (offset.top-60)+'px');
jQuery('.leaflet-routing-container').css('left', (offset.left + 35)+'px');
jQuery('.leaflet-routing-container').css('position','absolute');
jQuery('.leaflet-routing-container').css('z-index','100');
},
hide: function() {
var self = this,
_map = self._map,
_route = self._route;
L.DomUtil.removeClass(self._div, 'greenfort');
L.DomUtil.addClass(self._div, 'grisfort');
console.debug("AQUI");
try{
_route.removeFrom.call(_route,_map);
}catch(e){
console.debug(e);
}finally{
_map.off('click',self._routingPopup, self);
}
},
_toggle: function(e){
var collapsed = L.DomUtil.hasClass(this._div, 'grisfort');
this[collapsed ? 'show' : 'hide']();
},
_routingPopup: function(e) {
console.debug("routing");
var options = this.options,
_texts = options.texts;
if(window.lang){
_texts.title = window.lang.translate(options.originTexts.title);
_texts.btnStart = window.lang.translate(options.originTexts.btnStart);
_texts.btnEnd = window.lang.translate(options.originTexts.btnEnd);
}
var container ='<div id="contentRoutingPopup" class="contentRoutingPopup">';
container +='<h4 style="border-bottom:0px;" lang="ca">'+_texts.title+'</h4>';
container +='<button class="btn startBtn" lang="ca" type="button" id="startBtn">'+_texts.btnStart+'</button>'+
'<span class="awesome-marker-icon-green awesome-marker leaflet-zoom-hide leaflet-clickable leaflet-marker-draggable icona icona-origen" id="icona-origen"></span>'+
'<button class="btn endBtn" lang="ca" type="button" id="destBtn">'+_texts.btnEnd+'</button>'+
'<span class="awesome-marker-icon-red awesome-marker leaflet-zoom-hide leaflet-clickable leaflet-marker-draggable icona icona-desti" id="icona-desti"></span>';
container += "</div>";
var _map = this._map,
_route = this._route;
L.popup().setContent(container).setLatLng(e.latlng).openOn(_map);
jQuery(".leaflet-popup-content").css('width','184px');
jQuery(".leaflet-popup-content").css('margin','5px 15px');
jQuery('#startBtn').on('click', function() {
_route.spliceWaypoints(0, 1, e.latlng);
_map.closePopup();
});
jQuery('#destBtn').on('click', function() {
_route.spliceWaypoints(_route.getWaypoints().length - 1, 1, e.latlng);
_map.closePopup();
});
jQuery('#icona-origen').on('click', function() {
_route.spliceWaypoints(0, 1, e.latlng);
_map.closePopup();
});
jQuery('#icona-desti').on('click', function() {
_route.spliceWaypoints(_route.getWaypoints().length - 1, 1, e.latlng);
_map.closePopup();
});
},
_createButton: function(label, container, title, lang) {
var btn = L.DomUtil.create('button', '', container);
btn.setAttribute('type', 'button');
btn.setAttribute('lang', lang);
btn.setAttribute('title', title);
btn.innerHTML = label;
return btn;
},
_createSpan: function(label, container) {
var span = L.DomUtil.create('span', '', container);
span.innerHTML = label;
return span;
}
});
L.control.routingControl = function(options){
return new L.Control.RoutingControl(options);
}; | random_line_split | |
views.py | from django.shortcuts import render, redirect, get_object_or_404
from django.core.urlresolvers import reverse_lazy
from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.base import TemplateResponseMixin, View
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.db.models import Count
# для django1.9 вместо braces можно использовать миксины из django.contrib.auth.mixins
from braces.views import LoginRequiredMixin, PermissionRequiredMixin,\
CsrfExemptMixin, JsonRequestResponseMixin
# ------------------------------------------------------------------
from django.forms.models import modelform_factory
from django.apps import apps
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def get_queryset(self):
"""
вернуть объекты созданные только текущим пользователем
"""
queryset = super(OwnerMixin, self).get_queryset()
return queryset.filter(owner=self.request.user)
class OwnerEditMixin(object):
"""
Миксин переопределяющий метод form_valid
во всех дочерних классах.
"""
def form_valid(self, form):
"""
С помощью этого метода при создании объекта(подтверждение формы)
задается владелец этого объекта.
"""
form.instance.owner = self.request.user
return super(OwnerEditMixin, self).form_valid(form)
class OwnerCourseMixin(OwnerMixin, LoginRequiredMixin):
"""
Указание модели для queryset во всех дочерних классах
"""
model = Course
class OwnerCourseEditMixin(OwnerCourseMixin, OwnerEditMixin):
"""
Миксин который должен использоватся в классах изменяющиюх
или создающих объекты модели Course
"""
# указание полей для форм дочерних классов
fields = ['subject', 'title', 'slug', 'overview']
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('man | lass CourseUpdateView(PermissionRequiredMixin, OwnerCourseEditMixin, UpdateView):
"""
Используется для изменения Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.change_course"
class CourseDeleteView(PermissionRequiredMixin, OwnerCourseMixin, DeleteView):
"""
Используется для удаления Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.delete_course"
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/delete.html"
class CourseModuleUpdateView(TemplateResponseMixin, View):
"""
Класс используется для добавления, обновления и удаления модулей
определенного курса.
--------------------
TemplateResponseMixin используется для отображения templates, для него
обязательно нужно указывать template_name или реализовать
метод get_template_names; имеет метод render_to_response
для отображения context в template
--------------------
View реализует метод dispatch, который анализирует response на метод запроса
и в зависимости от его типа отправляет его нужному методу (get(), post()...)
"""
template_name = "courses/manage/module/formset.html"
course = None
def get_formset(self, data=None):
return ModuleFormSet(instance=self.course, data=data)
def dispatch(self, request, pk):
# ищем определенный курс текущего пользователя
self.course = get_object_or_404(Course, id=pk, owner=request.user)
return super(CourseModuleUpdateView, self).dispatch(request, pk)
def get(self, request, *args, **kwargs):
# создаем пустой formset
formset = self.get_formset()
return self.render_to_response({'course': self.course,
'formset': formset})
def post(self, request, *args, **kwargs):
# создаем formset с данными
formset = self.get_formset(data=request.POST)
if formset.is_valid():
formset.save()
return redirect('manage_course_list')
return self.render_to_response({'course': self.course,
'formset': formset})
class ContentCreateUpdateView(TemplateResponseMixin, View):
module = None
model = None
obj = None
template_name = "courses/manage/content/form.html"
def get_model(self, model_name):
# если имя модели соответствует одному из имен моделей контента
# вернуть модель для app_label и model_name
if model_name in ['text', 'file', 'image', 'video']:
return apps.get_model(app_label="courses", model_name=model_name)
# если модель нам не подходит
return None
def get_form(self, model, *args, **kwargs):
# возвращает ModelForm для указаной model
# со всеми полями кроме тех что указаны в exclude
Form = modelform_factory(model, exclude=['owner'
'created',
'updated',
'order', 'owner'])
return Form(*args, **kwargs)
def dispatch(self, request, module_id, model_name, id=None):
# получаем модуль с которым будет асоциирован объект
self.module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
# получаем модель которая будет соответсвотать типу контента
self.model = self.get_model(model_name)
# если не None, то объект будет обновлен, иначе будет создан новый
if id:
self.obj = get_object_or_404(self.model,
id=id,
owner=request.user)
# вызываем метод родителя
return super(ContentCreateUpdateView, self).dispatch(request,
module_id,
model_name,
id)
def get(self, request, module_id, model_name, id=None):
# возвращаем форму для изменения экземпляра контента при self.obj!=None.
# при None, будт возвращена форма для создания экземпляра контента.
form = self.get_form(self.model, instance=self.obj)
return self.render_to_response({'form': form,
'object': self.obj})
def post(self, request, module_id, model_name, id=None):
# возвращаем форму с данными и файлами
form = self.get_form(self.model,
instance=self.obj,
data=request.POST,
files=request.FILES)
if form.is_valid():
# задаем владельцем контента текущего пользователя
obj = form.save(commit=False)
obj.owner = request.user
obj.save()
if not id:
# если id объекта не указан, создаем новый экземпляр
Content.objects.create(module=self.module, content_object=obj)
return redirect('module_content_list', self.module.id)
return self.render_to_response({'form': form, 'object': self.obj})
class ContentDeleteView(View):
def post(self, request, id):
content = get_object_or_404(Content,
id=id,
module__course__owner=request.user)
module = content.module
content.content_object.delete()
content.delete()
# возвращаемся к списку контента модуля
return redirect('module_content_list', module.id)
class ModuleContentListView(TemplateResponseMixin, View):
template_name = "courses/manage/module/content_list.html"
def get(self, request, module_id):
module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
return self.render_to_response({'module': module})
class ModuleOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
Module.objects.filter(id=id,
course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class ContentOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
print('id', id, ' -- ', order)
for id, order in self.request_json.items():
Content.objects.filter(id=id, module__course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class CourseListView(TemplateResponseMixin, View):
"""
Список всех курсов
"""
model = Course
template_name = "courses/course/list.html"
def get(self, request, subject=None):
# возвращаем все subjects с количеством курсов для subject
subjects = Subject.objects.annotate(total_courses=Count('courses'))
# возвращаем все courses с количеством модулей для курса
courses = Course.objects.annotate(total_modules=Count('modules'))
if subject:
# если указан subject, фильтруем по нему все курсы
subject = get_object_or_404(Subject, slug=subject)
courses = courses.filter(subject=subject)
return self.render_to_response({'subjects': subjects,
'subject': subject,
'courses': courses})
class CourseDetailView(DetailView):
"""
Отображает единственный объект по его PK или по slug.
Этот объект присваивается к self.object
"""
model = Course
template_name = "courses/course/detail.html"
def get_context_data(self, **kwargs):
context = super(CourseDetailView, self).get_context_data(**kwargs)
# довавляем в контект форму подписки на текущий объект курса
context['enroll_form'] = CourseEnrollForm(initial={'course': self.object})
return context
| age_course_list')
template_name = "courses/manage/course/form.html"
class ManageCourseListView(OwnerCourseMixin, ListView):
"""
Используя наследование от OwnerCourseMixin, ListView
этот класс также будет содержать все поля и методы из
OwnerCourseMixin, ListView, OwnerMixin
"""
template_name = "courses/manage/course/list.html"
class CourseCreateView(PermissionRequiredMixin, OwnerCourseEditMixin, CreateView):
"""
Используется для создания нового Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.add_course"
c | identifier_body |
views.py | from django.shortcuts import render, redirect, get_object_or_404
from django.core.urlresolvers import reverse_lazy
from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.base import TemplateResponseMixin, View
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.db.models import Count
# для django1.9 вместо braces можно использовать миксины из django.contrib.auth.mixins
from braces.views import LoginRequiredMixin, PermissionRequiredMixin,\
CsrfExemptMixin, JsonRequestResponseMixin
# ------------------------------------------------------------------
from django.forms.models import modelform_factory
from django.apps import apps
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def get_queryset(self):
"""
вернуть объекты созданные только текущим пользователем
"""
queryset = super(OwnerMixin, self).get_queryset()
return queryset.filter(owner=self.request.user)
class OwnerEditMixin(object):
"""
Миксин переопределяющий метод form_valid
во всех дочерних классах.
"""
def form_valid(self, form):
"""
С помощью этого метода при создании объекта(подтверждение формы)
задается владелец этого объекта.
"""
form.instance.owner = self.request.user
return super(OwnerEditMixin, self).form_valid(form)
class OwnerCourseMixin(OwnerMixin, LoginRequiredMixin):
"""
Указание модели для queryset во всех дочерних классах
"""
model = Course
class OwnerCourseEditMixin(OwnerCourseMixin, OwnerEditMixin):
"""
Миксин который должен использоватся в классах изменяющиюх
или создающих объекты модели Course
"""
# указание полей для форм дочерних классов
fields = ['subject', 'title', 'slug', 'overview']
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/form.html"
class ManageCourseListView(OwnerCourseMixin, ListView):
"""
Используя наследование от OwnerCourseMixin, ListView
этот класс также будет содержать все поля и методы из
OwnerCourseMixin, ListView, OwnerMixin
"""
template_name = "courses/manage/course/list.html"
class CourseCreateView(PermissionRequiredMixin, OwnerCourseEditMixin, CreateView):
"""
Используется для создания нового Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.add_course"
class CourseUpdateView(PermissionRequiredMixin, OwnerCourseEditMixin, UpdateView):
"""
Используется для изменения Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.change_course"
class CourseDeleteView(PermissionRequiredMixin, OwnerCourseMixin, DeleteView):
"""
Используется для удаления Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.delete_course"
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/delete.html"
class CourseModuleUpdateView(TemplateResponseMixin, View):
"""
Класс используется для добавления, обновления и удаления модулей
определенного курса.
--------------------
TemplateResponseMixin используется для отображения templates, для него
обязательно нужно указывать template_name или реализовать
метод get_template_names; имеет метод render_to_response
для отображения context в template
--------------------
View реализует метод dispatch, который анализирует response на метод запроса
и в зависимости от его типа отправляет его нужному методу (get(), post()...)
"""
template_name = "courses/manage/module/formset.html"
course = None
def get_formset(self, data=None):
return ModuleFormSet(instance=self.course, data=data)
def dispatch(self, request, pk):
# ищем определенный курс текущего пользователя
self.course = get_object_or_404(Course, id=pk, owner=request.user)
return super(CourseModuleUpdateView, self).dispatch(request, pk)
def get(self, request, *args, **kwargs):
# создаем пустой formset
formset = self.get_formset()
return self.render_to_response({'course': self.course,
'formset': formset})
def post(self, request, *args, **kwargs):
# создаем formset с данными
formset = self.get_formset(data=request.POST)
if formset.is_valid():
formset.save()
return redirect('manage_course_list')
return self.render_to_response({'course': self.course,
'formset': formset})
class ContentCreateUpdateView(TemplateResponseMixin, View):
module = None
model = None
obj = None
template_name = "courses/manage/content/form.html"
def get_model(self, model_name):
# если имя модели соответствует одному из имен моделей контента
# вернуть модель для app_label и model_name
if model_name in ['text', 'file', 'image', 'video']:
return apps.get_model(app_label="courses", model_name=model_name)
# если модель нам не подходит
return None
def get_form(self, model, *args, **kwargs):
# возвращает ModelForm для указаной model
# со всеми полями кроме тех что указаны в exclude
Form = modelform_factory(model, exclude=['owner'
'created',
'updated',
'order', 'owner'])
return Form(*args, **kwargs)
def dispatch(self, request, module_id, model_name, id=None):
# получаем модуль с которым будет асоциирован объект
self.module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
# получаем модель которая будет соответсвотать типу контента
self.model = self.get_model(model_name)
# если не None, то объект будет обновлен, иначе будет создан новый
if id:
self.obj = get_object_or_404(self.model,
id=id,
owner=request.user)
# вызываем метод родителя
return super(ContentCreateUpdateView, self).dispatch(request,
module_id,
model_name,
id)
def get(self, request, module_id, model_name, id=None):
# возвращаем форму для изменения экземпляра контента при self.obj!=None.
# при None, будт возвращена форма для создания экземпляра контента.
form = self.get_form(self.model, instance=self.obj)
return self.render_to_response({'form': form,
'object': self.obj})
def post(self, request, module_id, model_name, id=None):
# возвращаем форму с данными и файлами
form = self.get_form(self.model,
instance=self.obj,
data=request.POST,
files=request.FILES)
if form.is_valid():
# задаем владельцем контента текущего пользователя
obj = form.save(commit=False)
obj.owner = request.user
obj.save()
if not id:
# если id объекта не указан, создаем новый экземпляр
Content.objects.create(module=self.module, content_object=obj)
return redirect('module_content_list', self.module.id)
return self.render_to_response({'form': form, 'object': self.obj})
class ContentDeleteView(View):
def post(self, request, id):
content = get_object_or_404(Content,
id=id,
module__course__owner=request.user)
module = content.module
content.content_object.delete()
content.delete()
# возвращаемся к списку контента модуля
return redirect('module_content_list', module.id)
class ModuleContentListView(TemplateResponseMixin, View):
template_name = "courses/manage/module/content_list.html"
def get(self, request, module_id):
module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
return self.render_to_response({'module': module})
class ModuleOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
Module.objects.filter(id=id,
course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class ContentOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также с | ved': 'OK'})
class CourseListView(TemplateResponseMixin, View):
"""
Список всех курсов
"""
model = Course
template_name = "courses/course/list.html"
def get(self, request, subject=None):
# возвращаем все subjects с количеством курсов для subject
subjects = Subject.objects.annotate(total_courses=Count('courses'))
# возвращаем все courses с количеством модулей для курса
courses = Course.objects.annotate(total_modules=Count('modules'))
if subject:
# если указан subject, фильтруем по нему все курсы
subject = get_object_or_404(Subject, slug=subject)
courses = courses.filter(subject=subject)
return self.render_to_response({'subjects': subjects,
'subject': subject,
'courses': courses})
class CourseDetailView(DetailView):
"""
Отображает единственный объект по его PK или по slug.
Этот объект присваивается к self.object
"""
model = Course
template_name = "courses/course/detail.html"
def get_context_data(self, **kwargs):
context = super(CourseDetailView, self).get_context_data(**kwargs)
# довавляем в контект форму подписки на текущий объект курса
context['enroll_form'] = CourseEnrollForm(initial={'course': self.object})
return context
| ериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
print('id', id, ' -- ', order)
for id, order in self.request_json.items():
Content.objects.filter(id=id, module__course__owner=request.user).update(order=order)
return self.render_json_response({'sa | conditional_block |
views.py | from django.shortcuts import render, redirect, get_object_or_404
from django.core.urlresolvers import reverse_lazy
from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.base import TemplateResponseMixin, View
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.db.models import Count
# для django1.9 вместо braces можно использовать миксины из django.contrib.auth.mixins
from braces.views import LoginRequiredMixin, PermissionRequiredMixin,\
CsrfExemptMixin, JsonRequestResponseMixin
# ------------------------------------------------------------------
from django.forms.models import modelform_factory
from django.apps import apps
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def get_queryset(self):
"""
вернуть объекты созданные только текущим пользователем
"""
queryset = super(OwnerMixin, self).get_queryset()
return queryset.filter(owner=self.request.user)
class OwnerEditMixin(object):
"""
Миксин переопределяющий метод form_valid
во всех дочерних классах.
"""
def form_valid(self, form):
"""
С помощью этого метода при создании объекта(подтверждение формы)
задается владелец этого объекта.
"""
form.instance.owner = self.request.user
return super(OwnerEditMixin, self).form_valid(form)
class OwnerCourseMixin(OwnerMixin, LoginRequiredMixin):
"""
Указание модели для queryset во всех дочерних классах
"""
model = Course
class OwnerCourseEditMixin(OwnerCourseMixin, OwnerEditMixin):
"""
Миксин который должен использоватся в классах изменяющиюх
или создающих объекты модели Course
"""
# указание полей для форм дочерних классов
fields = ['subject', 'title', 'slug', 'overview']
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/form.html"
class ManageCourseListView(OwnerCourseMixin, ListView):
"""
Используя наследование от OwnerCourseMixin, ListView
этот класс также будет содержать все поля и методы из
OwnerCourseMixin, ListView, OwnerMixin
"""
template_name = "courses/manage/course/list.html"
class CourseCreateView(PermissionRequiredMixin, OwnerCourseEditMixin, CreateView):
"""
Используется для создания нового Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.add_course"
class CourseUpdateView(PermissionRequiredMixin, OwnerCourseEditMixin, UpdateView):
"""
Используется для изменения Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.change_course"
class CourseDeleteView(PermissionRequiredMixin, OwnerCourseMixin, DeleteView):
"""
Используется для удаления Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.delete_course"
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/delete.html"
class CourseModuleUpdateView(TemplateResponseMixin, View):
"""
Класс используется для добавления, обновления и удаления модулей
определенного курса.
--------------------
TemplateResponseMixin используется для отображения templates, для него
обязательно нужно указывать template_name или реализовать
метод get_template_names; имеет метод render_to_response
для отображения context в template
--------------------
View реализует метод dispatch, который анализирует response на метод запроса
и в зависимости от его типа отправляет его нужному методу (get(), post()...)
"""
template_name = "courses/manage/module/formset.html"
course = None
def get_formset(self, data=None):
return ModuleFormSet(instance=self.course, data=data)
def dispatch(self, request, pk):
# ищем определенный курс текущего пользователя
self.course = get_object_or_404(Course, id=pk, owner=request.user)
return super(CourseModuleUpdateView, self).dispatch(request, pk)
def get(self, request, *args, **kwargs):
# создаем пустой formset
formset = self.get_formset()
return self.render_to_response({'course': self.course,
'formset': formset})
def post(self, request, *args, **kwargs):
# создаем formset с данными
formset = self.get_formset(data=request.POST)
if formset.is_valid():
formset.save()
return redirect('manage_course_list')
return self.render_to_response({'course': self.course,
'formset': formset})
class ContentCreateUpdateView(TemplateResponseMixin, View):
module = None
model = None
obj = None
template_name = "courses/manage/content/form.html"
def get_model(self, model_name):
# если имя модели соответствует одному из имен моделей контента
# вернуть модель для app_label и model_name
if model_name in ['text', 'file', 'image', 'video']:
return apps.get_model(app_label="courses", model_name=model_name)
# если модель нам не подходит
return None
def get_form(self, model, *args, **kwargs):
# возвращает ModelForm для указаной model
# со всеми полями кроме тех что указаны в exclude
Form = modelform_factory(model, exclude=['owner'
'created',
'updated',
'order', 'owner'])
return Form(*args, **kwargs)
def dispatch(self, request, module_id, model_name, id=None):
# получаем модуль с которым будет асоциирован объект
self.module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
# получаем модель которая будет соответсвотать типу контента
self.model = self.get_model(model_name)
# если не None, то объект будет обновлен, иначе будет создан новый
if id:
self.obj = get_object_or_404(self.model,
id=id,
owner=request.user)
# вызываем метод родителя
return super(ContentCreateUpdateView, self).dispatch(request,
module_id,
model_name,
id)
def get(self, request, module_id, model_name, id=None):
# возвращаем форму для изменения экземпляра контента при self.obj!=None.
# при None, будт возвращена форма для создания экземпляра контента.
form = self.get_form(self.model, instance=self.obj)
return self.render_to_response({'form': form,
'object': self.obj})
def post(self, request, module_id, model_name, id=None):
# возвращаем форму с данными и файлами
form = self.get_form(self.model,
instance=self.obj,
data=request.POST,
files=request.FILES)
if form.is_valid():
# задаем владельцем контента текущего пользователя
obj = form.save(commit=False)
obj.owner = request.user
obj.save()
if not id:
# если id объекта не указан, создаем новый экземпляр
Content.objects.create(module=self.module, content_object=obj)
return redirect('module_content_list', self.module.id)
return self.render_to_response({'form': form, 'object': self.obj})
class ContentDeleteView(View):
def post(self, request, id):
content = get_object_or_404(Content, | content.content_object.delete()
content.delete()
# возвращаемся к списку контента модуля
return redirect('module_content_list', module.id)
class ModuleContentListView(TemplateResponseMixin, View):
template_name = "courses/manage/module/content_list.html"
def get(self, request, module_id):
module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
return self.render_to_response({'module': module})
class ModuleOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
Module.objects.filter(id=id,
course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class ContentOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
print('id', id, ' -- ', order)
for id, order in self.request_json.items():
Content.objects.filter(id=id, module__course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class CourseListView(TemplateResponseMixin, View):
"""
Список всех курсов
"""
model = Course
template_name = "courses/course/list.html"
def get(self, request, subject=None):
# возвращаем все subjects с количеством курсов для subject
subjects = Subject.objects.annotate(total_courses=Count('courses'))
# возвращаем все courses с количеством модулей для курса
courses = Course.objects.annotate(total_modules=Count('modules'))
if subject:
# если указан subject, фильтруем по нему все курсы
subject = get_object_or_404(Subject, slug=subject)
courses = courses.filter(subject=subject)
return self.render_to_response({'subjects': subjects,
'subject': subject,
'courses': courses})
class CourseDetailView(DetailView):
"""
Отображает единственный объект по его PK или по slug.
Этот объект присваивается к self.object
"""
model = Course
template_name = "courses/course/detail.html"
def get_context_data(self, **kwargs):
context = super(CourseDetailView, self).get_context_data(**kwargs)
# довавляем в контект форму подписки на текущий объект курса
context['enroll_form'] = CourseEnrollForm(initial={'course': self.object})
return context | id=id,
module__course__owner=request.user)
module = content.module | random_line_split |
views.py | from django.shortcuts import render, redirect, get_object_or_404
from django.core.urlresolvers import reverse_lazy
from django.views.generic.list import ListView
from django.views.generic.detail import DetailView
from django.views.generic.base import TemplateResponseMixin, View
from django.views.generic.edit import CreateView, UpdateView, DeleteView
from django.db.models import Count
# для django1.9 вместо braces можно использовать миксины из django.contrib.auth.mixins
from braces.views import LoginRequiredMixin, PermissionRequiredMixin,\
CsrfExemptMixin, JsonRequestResponseMixin
# ------------------------------------------------------------------
from django.forms.models import modelform_factory
from django.apps import apps
from students.forms import CourseEnrollForm
from .models import Course, Module, Content, Subject
from .forms import ModuleFormSet
class OwnerMixin(object):
"""
Миксин переопределяющий метод get_queryset
во всех дочерних классах.
Может взаимодействовать со всеми моделями
у которых есть атрибут owner.
"""
def get_queryset(self):
"""
вернуть объекты созданные только текущим пользователем
"""
queryset = super(OwnerMixin, self).get_queryset()
return queryset.filter(owner=self.request.user)
class OwnerEditMixin(object):
"""
Миксин переопределяющий метод form_valid
во всех дочерних классах.
"""
def form_valid(self, form):
"""
С помощью этого метода при создании объекта(подт | ы)
задается владелец этого объекта.
"""
form.instance.owner = self.request.user
return super(OwnerEditMixin, self).form_valid(form)
class OwnerCourseMixin(OwnerMixin, LoginRequiredMixin):
"""
Указание модели для queryset во всех дочерних классах
"""
model = Course
class OwnerCourseEditMixin(OwnerCourseMixin, OwnerEditMixin):
"""
Миксин который должен использоватся в классах изменяющиюх
или создающих объекты модели Course
"""
# указание полей для форм дочерних классов
fields = ['subject', 'title', 'slug', 'overview']
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/form.html"
class ManageCourseListView(OwnerCourseMixin, ListView):
"""
Используя наследование от OwnerCourseMixin, ListView
этот класс также будет содержать все поля и методы из
OwnerCourseMixin, ListView, OwnerMixin
"""
template_name = "courses/manage/course/list.html"
class CourseCreateView(PermissionRequiredMixin, OwnerCourseEditMixin, CreateView):
"""
Используется для создания нового Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.add_course"
class CourseUpdateView(PermissionRequiredMixin, OwnerCourseEditMixin, UpdateView):
"""
Используется для изменения Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.change_course"
class CourseDeleteView(PermissionRequiredMixin, OwnerCourseMixin, DeleteView):
"""
Используется для удаления Course
"""
# PermissionRequiredMixin проверяет если у пользователя указанный permission_required
permission_required = "courses.delete_course"
# указание, куда будет перенаправлен пользователь
# после подтверждения формы.
# manage_course_list это имя URL в url.py
success_url = reverse_lazy('manage_course_list')
template_name = "courses/manage/course/delete.html"
class CourseModuleUpdateView(TemplateResponseMixin, View):
"""
Класс используется для добавления, обновления и удаления модулей
определенного курса.
--------------------
TemplateResponseMixin используется для отображения templates, для него
обязательно нужно указывать template_name или реализовать
метод get_template_names; имеет метод render_to_response
для отображения context в template
--------------------
View реализует метод dispatch, который анализирует response на метод запроса
и в зависимости от его типа отправляет его нужному методу (get(), post()...)
"""
template_name = "courses/manage/module/formset.html"
course = None
def get_formset(self, data=None):
return ModuleFormSet(instance=self.course, data=data)
def dispatch(self, request, pk):
# ищем определенный курс текущего пользователя
self.course = get_object_or_404(Course, id=pk, owner=request.user)
return super(CourseModuleUpdateView, self).dispatch(request, pk)
def get(self, request, *args, **kwargs):
# создаем пустой formset
formset = self.get_formset()
return self.render_to_response({'course': self.course,
'formset': formset})
def post(self, request, *args, **kwargs):
# создаем formset с данными
formset = self.get_formset(data=request.POST)
if formset.is_valid():
formset.save()
return redirect('manage_course_list')
return self.render_to_response({'course': self.course,
'formset': formset})
class ContentCreateUpdateView(TemplateResponseMixin, View):
module = None
model = None
obj = None
template_name = "courses/manage/content/form.html"
def get_model(self, model_name):
# если имя модели соответствует одному из имен моделей контента
# вернуть модель для app_label и model_name
if model_name in ['text', 'file', 'image', 'video']:
return apps.get_model(app_label="courses", model_name=model_name)
# если модель нам не подходит
return None
def get_form(self, model, *args, **kwargs):
# возвращает ModelForm для указаной model
# со всеми полями кроме тех что указаны в exclude
Form = modelform_factory(model, exclude=['owner'
'created',
'updated',
'order', 'owner'])
return Form(*args, **kwargs)
def dispatch(self, request, module_id, model_name, id=None):
# получаем модуль с которым будет асоциирован объект
self.module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
# получаем модель которая будет соответсвотать типу контента
self.model = self.get_model(model_name)
# если не None, то объект будет обновлен, иначе будет создан новый
if id:
self.obj = get_object_or_404(self.model,
id=id,
owner=request.user)
# вызываем метод родителя
return super(ContentCreateUpdateView, self).dispatch(request,
module_id,
model_name,
id)
def get(self, request, module_id, model_name, id=None):
# возвращаем форму для изменения экземпляра контента при self.obj!=None.
# при None, будт возвращена форма для создания экземпляра контента.
form = self.get_form(self.model, instance=self.obj)
return self.render_to_response({'form': form,
'object': self.obj})
def post(self, request, module_id, model_name, id=None):
# возвращаем форму с данными и файлами
form = self.get_form(self.model,
instance=self.obj,
data=request.POST,
files=request.FILES)
if form.is_valid():
# задаем владельцем контента текущего пользователя
obj = form.save(commit=False)
obj.owner = request.user
obj.save()
if not id:
# если id объекта не указан, создаем новый экземпляр
Content.objects.create(module=self.module, content_object=obj)
return redirect('module_content_list', self.module.id)
return self.render_to_response({'form': form, 'object': self.obj})
class ContentDeleteView(View):
def post(self, request, id):
content = get_object_or_404(Content,
id=id,
module__course__owner=request.user)
module = content.module
content.content_object.delete()
content.delete()
# возвращаемся к списку контента модуля
return redirect('module_content_list', module.id)
class ModuleContentListView(TemplateResponseMixin, View):
template_name = "courses/manage/module/content_list.html"
def get(self, request, module_id):
module = get_object_or_404(Module,
id=module_id,
course__owner=request.user)
return self.render_to_response({'module': module})
class ModuleOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
Module.objects.filter(id=id,
course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class ContentOrderView(CsrfExemptMixin, JsonRequestResponseMixin, View):
"""
CsrfExemptMixin освобождает запрос от csrf token'а.
JsonRequestResponseMixin - помещает правильно отформатированый
json запрос в request_json; также сериализирует response
"""
def post(self, request):
for id, order in self.request_json.items():
print('id', id, ' -- ', order)
for id, order in self.request_json.items():
Content.objects.filter(id=id, module__course__owner=request.user).update(order=order)
return self.render_json_response({'saved': 'OK'})
class CourseListView(TemplateResponseMixin, View):
"""
Список всех курсов
"""
model = Course
template_name = "courses/course/list.html"
def get(self, request, subject=None):
# возвращаем все subjects с количеством курсов для subject
subjects = Subject.objects.annotate(total_courses=Count('courses'))
# возвращаем все courses с количеством модулей для курса
courses = Course.objects.annotate(total_modules=Count('modules'))
if subject:
# если указан subject, фильтруем по нему все курсы
subject = get_object_or_404(Subject, slug=subject)
courses = courses.filter(subject=subject)
return self.render_to_response({'subjects': subjects,
'subject': subject,
'courses': courses})
class CourseDetailView(DetailView):
"""
Отображает единственный объект по его PK или по slug.
Этот объект присваивается к self.object
"""
model = Course
template_name = "courses/course/detail.html"
def get_context_data(self, **kwargs):
context = super(CourseDetailView, self).get_context_data(**kwargs)
# довавляем в контект форму подписки на текущий объект курса
context['enroll_form'] = CourseEnrollForm(initial={'course': self.object})
return context
| верждение форм | identifier_name |
CKEditor_media_tab.js | /**
* Add a media tab to the image properties dialog.
*
* This process as to be executed in a precise time frame;
* After CKEditor is loaded, but before it's executed.
*
* It tooks me some time to find out a stable way to define this.
* There is how I understand the loading process:
*
* Drupal Page:
* * Drupal Module A JS
* * Drupal Module B JS
* * ...
* * Drupal Module eatlas_media_frame_filter JS (CKEditor do not exists yet)
* * ...
* * Drupal Module N JS
* (some inconsistant loading delay)
* * CKEditor is created (*)
*
* (*) Wysiwyg JS (the javascript related to the wysiwyg module, the one
* that trigger the loading of CKEditor) is inserted somewhere in this
* process, maybe before, maybe after eatlas_media_frame_filter JS, so I
* can't rely on the existance of that module. I suppose the module
* dependencies defined in eatlas_media_frame_filter info file help to
* define the loading order, but this is not THE issue we are dealing
* with.
* Wysiwyg PHP module read the config and determine that the page will
* need CKEditor, so it add CKEditor to the page. At this point, maybe
* CKEditor is executed, maybe not, but at lease the variable CKEditor
* exists so I can listen to the instanceReady event.
*
* Since my JS as already been load, I have to defer it's execution to be
* able to listen to CKEditor events (I can't listen to those events
* before the CKEditor variable has been created). Defering it after the
* page load seems to be enough to push it's execution after CKEditor get
* created, changing the workflow to:
*
* Page:
* * Module A JS
* * Module B JS
* * ...
* * eatlas_media_frame_filter JS loaded but execution defered
* * ...
* * Module N JS
* (some inconsistant loading delay)
* * CKEditor is loaded, but maybe not executed yet (that's why I listen to instanceReady)
* (page load event is fired)
* * eatlas_media_frame_filter JS is executed
*
* Pseudo code:
* when all JS are in place (page load event):
* if CKEditor exists:
* When 'instanceReady' event is called:
* Add media tab to CKEditor's image properties dialog
* else
* Assume that the page do not have an instance of CKEditor => nothing to do.
*/
/**
* Waiting for the page load event to execute the script.
* Using JQuery to enforce compatibilities across browsers JS API.
* NOTE: This script use variables from Drupal, passed to JavaScript by
* the variable Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles
* defined in eatlas_media_frame_filter.module.
*/
(function ($) {
$(document).ready(function(){
if (typeof(CKEDITOR) !== 'undefined') {
// Example: http://docs.cksource.com/CKEditor_3.x/Developers_Guide/Dialog_Customization
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definitionObject.html
CKEDITOR.on('dialogDefinition', function(ev) {
// Take the dialog name and its definition from the event data.
var dialogName = ev.data.name;
var dialogDefinition = ev.data.definition;
if (dialogName == 'image') {
dialogDefinition.addContents(
_eatlas_media_frame_ckeditor_create_media_tab(), // Tab Definition
'Link' // Next element
);
}
});
}
});
/**
* Return the definition of the media tab.
* See - ckeditor/plugins/image/dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = function() {
// This = input element.
var value = this.getValue(),
dialog = this.getDialog();
var enable = value && value != 'enlarge';
toggleInput(dialog, 'chkHideDesc', enable);
toggleInput(dialog, 'chkHideLicense', enable);
toggleInput(dialog, 'txtMediaTitle', enable);
toggleInput(dialog, 'txtMediaDescPrefix', enable);
toggleInput(dialog, 'txtMediaDescription', enable);
};
var onImageStyleChange = function() {
var newMediaStyle = this.getValue(),
dialog = this.getDialog();
if (!newMediaStyle) {
newMediaStyle = 'media_original'
}
// The media styles are inconsistent with image styles. It's okay
// with most of them, but a mapping has to be done for the
// 'hardcoded' one.
var newImageStyle = newMediaStyle;
if (newImageStyle === 'media_preview') {
newImageStyle = 'square_thumbnail';
} else if (newImageStyle === 'media_large') {
newImageStyle = 'large';
} else if (newImageStyle === 'media_original') {
newImageStyle = '';
}
// API http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.html
//
// pageId: 'info', 'media', 'Link', 'Upload', 'advanced'
// elementId:
// info:
// 'txtUrl' (cke_75_uiElement),
// 'browse' (cke_77_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'txtAlt' (cke_82_uiElement),
// 'txtWidth' (cke_85_uiElement),
// 'txtHeight' (cke_88_uiElement),
// undefined (cke_89_uiElement) (container for Width and Height),
// 'ratioLock' (cke_90_uiElement) (both lock and reset),
// 'txtBorder' (cke_94_uiElement),
// 'txtHSpace' (cke_97_uiElement),
// 'txtVSpace' (cke_100_uiElement),
// 'cmbAlign' (cke_103_uiElement),
// 'basic' (cke_105_uiElement) (container for Width, Height, Border, HSpace, VSpace and Alignment),
// 'htmlPreview' (cke_106_uiElement)
// media:
// 'lstImageStyle' (cke_113_uiElement),
// 'lstMediaStyle' (cke_116_uiElement),
// 'lstMediaLink' (...),
// 'txtMediaTitle' (...),
// 'txtMediaDescPrefix' (...),
// 'txtMediaDescription' (cke_119_uiElement),
// undefined (cke_120_uiElement) (metadata info),
// Link:
// 'txtUrl' (cke_125_uiElement),
// 'browse' (cke_127_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'cmbTarget' (cke_130_uiElement)
// Upload:
// 'upload' (cke_135_uiElement),
// 'uploadButton' (cke_137_uiElement)
// advanced:
// 'linkId' (cke_142_uiElement),
// 'cmbLangDir' (cke_145_uiElement),
// 'txtLangCode' (cke_148_uiElement),
// 'txtGenLongDescr' (cke_152_uiElement),
// 'txtGenClass' (cke_155_uiElement),
// 'txtGenTitle' (cke_158_uiElement),
// undefined (cke_159_uiElement) (container for Stylesheet Classes and Advisory Title),
// 'txtdlgGenStyle' (cke_162_uiElement)
//
// Snipet to display the mapping DOM ID => CKEditor element ID:
// dialog.foreach(function(el) {
// console.log('DOM ID: ' + el.domId + ' ID: ' + el.id);
// });
// *** CSS Classes ***
// Get actual image CSS Classes, as defined in the dialog field
// API: dialog.getValueOf(pageId, elementId);
var classes = dialog.getValueOf('advanced', 'txtGenClass');
classes = classes ? classes.split(/\s+/) : [];
// Remove previous 'image style' class and find the image ID
var newClasses = [];
for (var i=0, len=classes.length; i<len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) !== IMAGESTYLE_CLASS_PREFIX) {
newClasses.push(classes[i]);
}
}
// Add new 'image style' class
newClasses.push(IMAGESTYLE_CLASS_PREFIX + newMediaStyle);
// Set the new image CSS Classes in the dialog field
// API: dialog.setValueOf(pageId, elementId, value);
dialog.setValueOf('advanced', 'txtGenClass', newClasses.join(' '));
// *** Image URL ***
// Async request to the file URL service (only works when logged)
// IMPORTANT: The Drupal API must be used to get the image URL
// because it need to add the "itok" token to the URL.
// That token has been added to avoid an easy DDoS.
// See: http://berk.es/2013/03/04/drupal-imagecache-security-vulnarability-with-ddos-attack-explained/
if (typeof this.fid !== 'undefined') {
$.getJSON("/eatlas_mediaframe_fileurl/" + this.fid + "/" + newImageStyle, function(json){
if (typeof json.url !== 'undefined') {
// Set the new image URL in the dialog field
var currentUrl = dialog.getValueOf('info', 'txtUrl');
if (currentUrl != json.url) {
dialog.setValueOf('info', 'txtUrl', json.url);
}
}
});
}
};
var getImageStyle = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) === IMAGESTYLE_CLASS_PREFIX) {
return classes[i].substring(IMAGESTYLE_CLASS_PREFIX.length);
}
}
};
var getMediaFileId = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGEID_CLASS_PREFIX.length) === IMAGEID_CLASS_PREFIX) {
return classes[i].substring(IMAGEID_CLASS_PREFIX.length);
}
}
};
var toggleInput = function(dialog, inputID, active) {
var inputEl = dialog.getContentElement('media', inputID).getInputElement();
if (active) | else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
['Link', 'media_link'],
['Preview', 'media_preview'],
['Large', 'media_large']
];
// NOTE: Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles is defined in eatlas_media_frame_filter.module
if (typeof Drupal.settings.eatlas_media_frame_filter === 'object' && typeof Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles === 'object') {
var customStyles = Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles;
for (customStyleId in customStyles) {
if (customStyles.hasOwnProperty(customStyleId)) {
imageStyles.push([customStyles[customStyleId], customStyleId]);
}
}
}
// CKEditor API: http://docs.ckeditor.com/#!/api/CKEDITOR.dialog.definition.checkbox
return {
id: 'media',
label: 'Frame info',
padding: 0,
elements: [
{
id: 'lstImageStyle',
type: 'select',
label: 'Image style',
// NOTE: This CSS class hide the field when it's disabled.
className: 'eatlas-media-frame-filter-image-style-select',
items: imageStyles,
onChange: onImageStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var currentImageStyle = getImageStyle(element);
this.fid = getMediaFileId(element);
this.setValue(currentImageStyle);
// Disable the field when it's set to "Original"
// We don't want users to be able to choose something else
// but still give the ability to fix broken images.
if (currentImageStyle === 'media_original') {
this.disable();
}
}
},
commit: function(type, element) {}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaStyle',
type: 'select',
label: 'Frame style',
items: [
['- No frame -', ''],
['Wikipedia style', 'wikipedia'],
['Info on image', 'onImage'],
['Tile', 'tile']
],
'default': '', // The default must match the default in "eatlas_media_frame_filter.module"
onChange: onMediaStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var frameStyle = element.getAttribute('media_style');
if (frameStyle !== null) {
this.setValue(frameStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var frameStyle = this.getValue();
element.setAttribute('media_style', frameStyle);
}
}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaLink',
type: 'select',
label: 'Link to media page',
items: [
['- No link to media page -', 'none'],
['Magnifier', 'magnifier'],
['Image linked to media page', 'direct']
],
'default': 'none',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var mediaLinkStyle = element.getAttribute('media_link');
if (mediaLinkStyle !== null) {
this.setValue(mediaLinkStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var mediaLinkStyle = this.getValue();
element.setAttribute('media_link', mediaLinkStyle);
}
}
}, {
id: 'chkHideDesc',
type: 'checkbox',
label: 'Hide description',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidedesc = element.getAttribute('media_hidedesc');
if (hidedesc) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidedesc = this.getValue();
if (hidedesc) {
element.setAttribute('media_hidedesc', true);
} else {
element.removeAttribute('media_hidedesc');
}
}
}
}, {
id: 'chkHideLicense',
type: 'checkbox',
label: 'Hide license',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidelicense = element.getAttribute('media_hidelicense');
if (hidelicense) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidelicense = this.getValue();
if (hidelicense) {
element.setAttribute('media_hidelicense', true);
} else {
element.removeAttribute('media_hidelicense');
}
}
}
}, {
id: 'txtMediaTitle',
type: 'text',
label: 'Title overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var title = _decode(element.getAttribute('media_title'));
if (title) {
this.setValue(title);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var title = _encode(this.getValue());
if (title) {
element.setAttribute('media_title', title);
} else {
element.removeAttribute('media_title');
}
}
}
}, {
id: 'txtMediaDescPrefix',
type: 'text',
label: 'Description prefix',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var prefix = _decode(element.getAttribute('media_descprefix'));
if (prefix) {
this.setValue(prefix);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var prefix = _encode(this.getValue());
if (prefix) {
element.setAttribute('media_descprefix', prefix);
} else {
element.removeAttribute('media_descprefix');
}
}
}
}, {
id: 'txtMediaDescription',
type: 'textarea',
label: 'Description overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var description = _decode(element.getAttribute('media_description'));
if (description) {
this.setValue(description);
}
}
},
commit: function( type, element ) {
if (type == IMAGE) {
var description = _encode(this.getValue());
if (description) {
element.setAttribute('media_description', description);
} else {
element.removeAttribute('media_description');
}
}
}
}, {
type: 'html',
html: '<div role="presentation">' +
'<label>Metadata</label>' +
'<div id="eatlas_media_frame_info"><span class="loading">Loading...</span></div>' +
'</div>',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var domElement = document.getElementById('eatlas_media_frame_info');
var fid = _eatlas_media_frame_ckeditor_get_fid(element);
if (fid !== null) {
domElement.innerHTML = '<iframe class="iframe-mediaframe-fileinfo" src="/?q=eatlas_mediaframe_fileinfo/' + fid + '"/>';
} else {
domElement.innerHTML = '<span class="noinfo">No information available</span>';
}
}
}
}
]
};
function _encode(htmlStr) {
// Create a in-memory div, set it's inner text (which jQuery automatically encodes)
// then grab the encoded contents back out. The div never exists on the page.
return $('<div/>').text(htmlStr).html();
}
function _decode(str) {
return $('<div/>').html(str).text();
}
/**
* element: CKEDITOR.dom.element
* The file ID is store in the class of the element:
* class="... img__fid__12 ...";
*/
function _eatlas_media_frame_ckeditor_get_fid(element) {
var classesStr = element.getAttribute('class');
var fidClassPrefix = 'img__fid__';
if (classesStr) {
var classes = classesStr.split(" ");
var _class = null;
for (var i=0, len=classes.length; i<len; i++) {
_class = classes[i];
if (_class && _class.indexOf(fidClassPrefix) === 0) {
return parseInt(_class.substring(fidClassPrefix.length));
}
}
}
return null;
}
}
})(jQuery);
| {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} | conditional_block |
CKEditor_media_tab.js | /**
* Add a media tab to the image properties dialog.
*
* This process as to be executed in a precise time frame;
* After CKEditor is loaded, but before it's executed.
*
* It tooks me some time to find out a stable way to define this.
* There is how I understand the loading process:
*
* Drupal Page:
* * Drupal Module A JS
* * Drupal Module B JS
* * ...
* * Drupal Module eatlas_media_frame_filter JS (CKEditor do not exists yet)
* * ...
* * Drupal Module N JS
* (some inconsistant loading delay)
* * CKEditor is created (*)
*
* (*) Wysiwyg JS (the javascript related to the wysiwyg module, the one
* that trigger the loading of CKEditor) is inserted somewhere in this
* process, maybe before, maybe after eatlas_media_frame_filter JS, so I
* can't rely on the existance of that module. I suppose the module
* dependencies defined in eatlas_media_frame_filter info file help to
* define the loading order, but this is not THE issue we are dealing
* with.
* Wysiwyg PHP module read the config and determine that the page will
* need CKEditor, so it add CKEditor to the page. At this point, maybe
* CKEditor is executed, maybe not, but at lease the variable CKEditor
* exists so I can listen to the instanceReady event.
*
* Since my JS as already been load, I have to defer it's execution to be
* able to listen to CKEditor events (I can't listen to those events
* before the CKEditor variable has been created). Defering it after the
* page load seems to be enough to push it's execution after CKEditor get
* created, changing the workflow to:
*
* Page:
* * Module A JS
* * Module B JS
* * ...
* * eatlas_media_frame_filter JS loaded but execution defered
* * ...
* * Module N JS
* (some inconsistant loading delay)
* * CKEditor is loaded, but maybe not executed yet (that's why I listen to instanceReady)
* (page load event is fired)
* * eatlas_media_frame_filter JS is executed
*
* Pseudo code:
* when all JS are in place (page load event):
* if CKEditor exists:
* When 'instanceReady' event is called:
* Add media tab to CKEditor's image properties dialog
* else
* Assume that the page do not have an instance of CKEditor => nothing to do.
*/
/**
* Waiting for the page load event to execute the script.
* Using JQuery to enforce compatibilities across browsers JS API.
* NOTE: This script use variables from Drupal, passed to JavaScript by
* the variable Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles
* defined in eatlas_media_frame_filter.module.
*/
(function ($) {
$(document).ready(function(){
if (typeof(CKEDITOR) !== 'undefined') {
// Example: http://docs.cksource.com/CKEditor_3.x/Developers_Guide/Dialog_Customization
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definitionObject.html
CKEDITOR.on('dialogDefinition', function(ev) {
// Take the dialog name and its definition from the event data.
var dialogName = ev.data.name;
var dialogDefinition = ev.data.definition;
if (dialogName == 'image') {
dialogDefinition.addContents(
_eatlas_media_frame_ckeditor_create_media_tab(), // Tab Definition
'Link' // Next element
);
}
});
}
});
/**
* Return the definition of the media tab.
* See - ckeditor/plugins/image/dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = function() {
// This = input element.
var value = this.getValue(),
dialog = this.getDialog();
var enable = value && value != 'enlarge';
toggleInput(dialog, 'chkHideDesc', enable);
toggleInput(dialog, 'chkHideLicense', enable);
toggleInput(dialog, 'txtMediaTitle', enable);
toggleInput(dialog, 'txtMediaDescPrefix', enable);
toggleInput(dialog, 'txtMediaDescription', enable);
};
var onImageStyleChange = function() {
var newMediaStyle = this.getValue(),
dialog = this.getDialog();
if (!newMediaStyle) {
newMediaStyle = 'media_original'
}
// The media styles are inconsistent with image styles. It's okay
// with most of them, but a mapping has to be done for the
// 'hardcoded' one.
var newImageStyle = newMediaStyle;
if (newImageStyle === 'media_preview') {
newImageStyle = 'square_thumbnail';
} else if (newImageStyle === 'media_large') {
newImageStyle = 'large';
} else if (newImageStyle === 'media_original') {
newImageStyle = '';
}
// API http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.html
//
// pageId: 'info', 'media', 'Link', 'Upload', 'advanced'
// elementId:
// info:
// 'txtUrl' (cke_75_uiElement),
// 'browse' (cke_77_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'txtAlt' (cke_82_uiElement),
// 'txtWidth' (cke_85_uiElement),
// 'txtHeight' (cke_88_uiElement),
// undefined (cke_89_uiElement) (container for Width and Height),
// 'ratioLock' (cke_90_uiElement) (both lock and reset),
// 'txtBorder' (cke_94_uiElement),
// 'txtHSpace' (cke_97_uiElement),
// 'txtVSpace' (cke_100_uiElement),
// 'cmbAlign' (cke_103_uiElement),
// 'basic' (cke_105_uiElement) (container for Width, Height, Border, HSpace, VSpace and Alignment),
// 'htmlPreview' (cke_106_uiElement)
// media:
// 'lstImageStyle' (cke_113_uiElement),
// 'lstMediaStyle' (cke_116_uiElement),
// 'lstMediaLink' (...),
// 'txtMediaTitle' (...),
// 'txtMediaDescPrefix' (...),
// 'txtMediaDescription' (cke_119_uiElement),
// undefined (cke_120_uiElement) (metadata info),
// Link:
// 'txtUrl' (cke_125_uiElement),
// 'browse' (cke_127_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'cmbTarget' (cke_130_uiElement)
// Upload:
// 'upload' (cke_135_uiElement),
// 'uploadButton' (cke_137_uiElement)
// advanced:
// 'linkId' (cke_142_uiElement),
// 'cmbLangDir' (cke_145_uiElement),
// 'txtLangCode' (cke_148_uiElement),
// 'txtGenLongDescr' (cke_152_uiElement),
// 'txtGenClass' (cke_155_uiElement),
// 'txtGenTitle' (cke_158_uiElement),
// undefined (cke_159_uiElement) (container for Stylesheet Classes and Advisory Title),
// 'txtdlgGenStyle' (cke_162_uiElement)
//
// Snipet to display the mapping DOM ID => CKEditor element ID:
// dialog.foreach(function(el) {
// console.log('DOM ID: ' + el.domId + ' ID: ' + el.id);
// });
// *** CSS Classes ***
// Get actual image CSS Classes, as defined in the dialog field |
// Remove previous 'image style' class and find the image ID
var newClasses = [];
for (var i=0, len=classes.length; i<len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) !== IMAGESTYLE_CLASS_PREFIX) {
newClasses.push(classes[i]);
}
}
// Add new 'image style' class
newClasses.push(IMAGESTYLE_CLASS_PREFIX + newMediaStyle);
// Set the new image CSS Classes in the dialog field
// API: dialog.setValueOf(pageId, elementId, value);
dialog.setValueOf('advanced', 'txtGenClass', newClasses.join(' '));
// *** Image URL ***
// Async request to the file URL service (only works when logged)
// IMPORTANT: The Drupal API must be used to get the image URL
// because it need to add the "itok" token to the URL.
// That token has been added to avoid an easy DDoS.
// See: http://berk.es/2013/03/04/drupal-imagecache-security-vulnarability-with-ddos-attack-explained/
if (typeof this.fid !== 'undefined') {
$.getJSON("/eatlas_mediaframe_fileurl/" + this.fid + "/" + newImageStyle, function(json){
if (typeof json.url !== 'undefined') {
// Set the new image URL in the dialog field
var currentUrl = dialog.getValueOf('info', 'txtUrl');
if (currentUrl != json.url) {
dialog.setValueOf('info', 'txtUrl', json.url);
}
}
});
}
};
var getImageStyle = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) === IMAGESTYLE_CLASS_PREFIX) {
return classes[i].substring(IMAGESTYLE_CLASS_PREFIX.length);
}
}
};
var getMediaFileId = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGEID_CLASS_PREFIX.length) === IMAGEID_CLASS_PREFIX) {
return classes[i].substring(IMAGEID_CLASS_PREFIX.length);
}
}
};
var toggleInput = function(dialog, inputID, active) {
var inputEl = dialog.getContentElement('media', inputID).getInputElement();
if (active) {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
['Link', 'media_link'],
['Preview', 'media_preview'],
['Large', 'media_large']
];
// NOTE: Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles is defined in eatlas_media_frame_filter.module
if (typeof Drupal.settings.eatlas_media_frame_filter === 'object' && typeof Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles === 'object') {
var customStyles = Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles;
for (customStyleId in customStyles) {
if (customStyles.hasOwnProperty(customStyleId)) {
imageStyles.push([customStyles[customStyleId], customStyleId]);
}
}
}
// CKEditor API: http://docs.ckeditor.com/#!/api/CKEDITOR.dialog.definition.checkbox
return {
id: 'media',
label: 'Frame info',
padding: 0,
elements: [
{
id: 'lstImageStyle',
type: 'select',
label: 'Image style',
// NOTE: This CSS class hide the field when it's disabled.
className: 'eatlas-media-frame-filter-image-style-select',
items: imageStyles,
onChange: onImageStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var currentImageStyle = getImageStyle(element);
this.fid = getMediaFileId(element);
this.setValue(currentImageStyle);
// Disable the field when it's set to "Original"
// We don't want users to be able to choose something else
// but still give the ability to fix broken images.
if (currentImageStyle === 'media_original') {
this.disable();
}
}
},
commit: function(type, element) {}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaStyle',
type: 'select',
label: 'Frame style',
items: [
['- No frame -', ''],
['Wikipedia style', 'wikipedia'],
['Info on image', 'onImage'],
['Tile', 'tile']
],
'default': '', // The default must match the default in "eatlas_media_frame_filter.module"
onChange: onMediaStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var frameStyle = element.getAttribute('media_style');
if (frameStyle !== null) {
this.setValue(frameStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var frameStyle = this.getValue();
element.setAttribute('media_style', frameStyle);
}
}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaLink',
type: 'select',
label: 'Link to media page',
items: [
['- No link to media page -', 'none'],
['Magnifier', 'magnifier'],
['Image linked to media page', 'direct']
],
'default': 'none',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var mediaLinkStyle = element.getAttribute('media_link');
if (mediaLinkStyle !== null) {
this.setValue(mediaLinkStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var mediaLinkStyle = this.getValue();
element.setAttribute('media_link', mediaLinkStyle);
}
}
}, {
id: 'chkHideDesc',
type: 'checkbox',
label: 'Hide description',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidedesc = element.getAttribute('media_hidedesc');
if (hidedesc) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidedesc = this.getValue();
if (hidedesc) {
element.setAttribute('media_hidedesc', true);
} else {
element.removeAttribute('media_hidedesc');
}
}
}
}, {
id: 'chkHideLicense',
type: 'checkbox',
label: 'Hide license',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidelicense = element.getAttribute('media_hidelicense');
if (hidelicense) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidelicense = this.getValue();
if (hidelicense) {
element.setAttribute('media_hidelicense', true);
} else {
element.removeAttribute('media_hidelicense');
}
}
}
}, {
id: 'txtMediaTitle',
type: 'text',
label: 'Title overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var title = _decode(element.getAttribute('media_title'));
if (title) {
this.setValue(title);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var title = _encode(this.getValue());
if (title) {
element.setAttribute('media_title', title);
} else {
element.removeAttribute('media_title');
}
}
}
}, {
id: 'txtMediaDescPrefix',
type: 'text',
label: 'Description prefix',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var prefix = _decode(element.getAttribute('media_descprefix'));
if (prefix) {
this.setValue(prefix);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var prefix = _encode(this.getValue());
if (prefix) {
element.setAttribute('media_descprefix', prefix);
} else {
element.removeAttribute('media_descprefix');
}
}
}
}, {
id: 'txtMediaDescription',
type: 'textarea',
label: 'Description overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var description = _decode(element.getAttribute('media_description'));
if (description) {
this.setValue(description);
}
}
},
commit: function( type, element ) {
if (type == IMAGE) {
var description = _encode(this.getValue());
if (description) {
element.setAttribute('media_description', description);
} else {
element.removeAttribute('media_description');
}
}
}
}, {
type: 'html',
html: '<div role="presentation">' +
'<label>Metadata</label>' +
'<div id="eatlas_media_frame_info"><span class="loading">Loading...</span></div>' +
'</div>',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var domElement = document.getElementById('eatlas_media_frame_info');
var fid = _eatlas_media_frame_ckeditor_get_fid(element);
if (fid !== null) {
domElement.innerHTML = '<iframe class="iframe-mediaframe-fileinfo" src="/?q=eatlas_mediaframe_fileinfo/' + fid + '"/>';
} else {
domElement.innerHTML = '<span class="noinfo">No information available</span>';
}
}
}
}
]
};
function _encode(htmlStr) {
// Create a in-memory div, set it's inner text (which jQuery automatically encodes)
// then grab the encoded contents back out. The div never exists on the page.
return $('<div/>').text(htmlStr).html();
}
function _decode(str) {
return $('<div/>').html(str).text();
}
/**
* element: CKEDITOR.dom.element
* The file ID is store in the class of the element:
* class="... img__fid__12 ...";
*/
function _eatlas_media_frame_ckeditor_get_fid(element) {
var classesStr = element.getAttribute('class');
var fidClassPrefix = 'img__fid__';
if (classesStr) {
var classes = classesStr.split(" ");
var _class = null;
for (var i=0, len=classes.length; i<len; i++) {
_class = classes[i];
if (_class && _class.indexOf(fidClassPrefix) === 0) {
return parseInt(_class.substring(fidClassPrefix.length));
}
}
}
return null;
}
}
})(jQuery); | // API: dialog.getValueOf(pageId, elementId);
var classes = dialog.getValueOf('advanced', 'txtGenClass');
classes = classes ? classes.split(/\s+/) : []; | random_line_split |
CKEditor_media_tab.js | /**
* Add a media tab to the image properties dialog.
*
* This process as to be executed in a precise time frame;
* After CKEditor is loaded, but before it's executed.
*
* It tooks me some time to find out a stable way to define this.
* There is how I understand the loading process:
*
* Drupal Page:
* * Drupal Module A JS
* * Drupal Module B JS
* * ...
* * Drupal Module eatlas_media_frame_filter JS (CKEditor do not exists yet)
* * ...
* * Drupal Module N JS
* (some inconsistant loading delay)
* * CKEditor is created (*)
*
* (*) Wysiwyg JS (the javascript related to the wysiwyg module, the one
* that trigger the loading of CKEditor) is inserted somewhere in this
* process, maybe before, maybe after eatlas_media_frame_filter JS, so I
* can't rely on the existance of that module. I suppose the module
* dependencies defined in eatlas_media_frame_filter info file help to
* define the loading order, but this is not THE issue we are dealing
* with.
* Wysiwyg PHP module read the config and determine that the page will
* need CKEditor, so it add CKEditor to the page. At this point, maybe
* CKEditor is executed, maybe not, but at lease the variable CKEditor
* exists so I can listen to the instanceReady event.
*
* Since my JS as already been load, I have to defer it's execution to be
* able to listen to CKEditor events (I can't listen to those events
* before the CKEditor variable has been created). Defering it after the
* page load seems to be enough to push it's execution after CKEditor get
* created, changing the workflow to:
*
* Page:
* * Module A JS
* * Module B JS
* * ...
* * eatlas_media_frame_filter JS loaded but execution defered
* * ...
* * Module N JS
* (some inconsistant loading delay)
* * CKEditor is loaded, but maybe not executed yet (that's why I listen to instanceReady)
* (page load event is fired)
* * eatlas_media_frame_filter JS is executed
*
* Pseudo code:
* when all JS are in place (page load event):
* if CKEditor exists:
* When 'instanceReady' event is called:
* Add media tab to CKEditor's image properties dialog
* else
* Assume that the page do not have an instance of CKEditor => nothing to do.
*/
/**
* Waiting for the page load event to execute the script.
* Using JQuery to enforce compatibilities across browsers JS API.
* NOTE: This script use variables from Drupal, passed to JavaScript by
* the variable Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles
* defined in eatlas_media_frame_filter.module.
*/
(function ($) {
$(document).ready(function(){
if (typeof(CKEDITOR) !== 'undefined') {
// Example: http://docs.cksource.com/CKEditor_3.x/Developers_Guide/Dialog_Customization
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definitionObject.html
CKEDITOR.on('dialogDefinition', function(ev) {
// Take the dialog name and its definition from the event data.
var dialogName = ev.data.name;
var dialogDefinition = ev.data.definition;
if (dialogName == 'image') {
dialogDefinition.addContents(
_eatlas_media_frame_ckeditor_create_media_tab(), // Tab Definition
'Link' // Next element
);
}
});
}
});
/**
* Return the definition of the media tab.
* See - ckeditor/plugins/image/dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = function() {
// This = input element.
var value = this.getValue(),
dialog = this.getDialog();
var enable = value && value != 'enlarge';
toggleInput(dialog, 'chkHideDesc', enable);
toggleInput(dialog, 'chkHideLicense', enable);
toggleInput(dialog, 'txtMediaTitle', enable);
toggleInput(dialog, 'txtMediaDescPrefix', enable);
toggleInput(dialog, 'txtMediaDescription', enable);
};
var onImageStyleChange = function() {
var newMediaStyle = this.getValue(),
dialog = this.getDialog();
if (!newMediaStyle) {
newMediaStyle = 'media_original'
}
// The media styles are inconsistent with image styles. It's okay
// with most of them, but a mapping has to be done for the
// 'hardcoded' one.
var newImageStyle = newMediaStyle;
if (newImageStyle === 'media_preview') {
newImageStyle = 'square_thumbnail';
} else if (newImageStyle === 'media_large') {
newImageStyle = 'large';
} else if (newImageStyle === 'media_original') {
newImageStyle = '';
}
// API http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.html
//
// pageId: 'info', 'media', 'Link', 'Upload', 'advanced'
// elementId:
// info:
// 'txtUrl' (cke_75_uiElement),
// 'browse' (cke_77_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'txtAlt' (cke_82_uiElement),
// 'txtWidth' (cke_85_uiElement),
// 'txtHeight' (cke_88_uiElement),
// undefined (cke_89_uiElement) (container for Width and Height),
// 'ratioLock' (cke_90_uiElement) (both lock and reset),
// 'txtBorder' (cke_94_uiElement),
// 'txtHSpace' (cke_97_uiElement),
// 'txtVSpace' (cke_100_uiElement),
// 'cmbAlign' (cke_103_uiElement),
// 'basic' (cke_105_uiElement) (container for Width, Height, Border, HSpace, VSpace and Alignment),
// 'htmlPreview' (cke_106_uiElement)
// media:
// 'lstImageStyle' (cke_113_uiElement),
// 'lstMediaStyle' (cke_116_uiElement),
// 'lstMediaLink' (...),
// 'txtMediaTitle' (...),
// 'txtMediaDescPrefix' (...),
// 'txtMediaDescription' (cke_119_uiElement),
// undefined (cke_120_uiElement) (metadata info),
// Link:
// 'txtUrl' (cke_125_uiElement),
// 'browse' (cke_127_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'cmbTarget' (cke_130_uiElement)
// Upload:
// 'upload' (cke_135_uiElement),
// 'uploadButton' (cke_137_uiElement)
// advanced:
// 'linkId' (cke_142_uiElement),
// 'cmbLangDir' (cke_145_uiElement),
// 'txtLangCode' (cke_148_uiElement),
// 'txtGenLongDescr' (cke_152_uiElement),
// 'txtGenClass' (cke_155_uiElement),
// 'txtGenTitle' (cke_158_uiElement),
// undefined (cke_159_uiElement) (container for Stylesheet Classes and Advisory Title),
// 'txtdlgGenStyle' (cke_162_uiElement)
//
// Snipet to display the mapping DOM ID => CKEditor element ID:
// dialog.foreach(function(el) {
// console.log('DOM ID: ' + el.domId + ' ID: ' + el.id);
// });
// *** CSS Classes ***
// Get actual image CSS Classes, as defined in the dialog field
// API: dialog.getValueOf(pageId, elementId);
var classes = dialog.getValueOf('advanced', 'txtGenClass');
classes = classes ? classes.split(/\s+/) : [];
// Remove previous 'image style' class and find the image ID
var newClasses = [];
for (var i=0, len=classes.length; i<len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) !== IMAGESTYLE_CLASS_PREFIX) {
newClasses.push(classes[i]);
}
}
// Add new 'image style' class
newClasses.push(IMAGESTYLE_CLASS_PREFIX + newMediaStyle);
// Set the new image CSS Classes in the dialog field
// API: dialog.setValueOf(pageId, elementId, value);
dialog.setValueOf('advanced', 'txtGenClass', newClasses.join(' '));
// *** Image URL ***
// Async request to the file URL service (only works when logged)
// IMPORTANT: The Drupal API must be used to get the image URL
// because it need to add the "itok" token to the URL.
// That token has been added to avoid an easy DDoS.
// See: http://berk.es/2013/03/04/drupal-imagecache-security-vulnarability-with-ddos-attack-explained/
if (typeof this.fid !== 'undefined') {
$.getJSON("/eatlas_mediaframe_fileurl/" + this.fid + "/" + newImageStyle, function(json){
if (typeof json.url !== 'undefined') {
// Set the new image URL in the dialog field
var currentUrl = dialog.getValueOf('info', 'txtUrl');
if (currentUrl != json.url) {
dialog.setValueOf('info', 'txtUrl', json.url);
}
}
});
}
};
var getImageStyle = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) === IMAGESTYLE_CLASS_PREFIX) {
return classes[i].substring(IMAGESTYLE_CLASS_PREFIX.length);
}
}
};
var getMediaFileId = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGEID_CLASS_PREFIX.length) === IMAGEID_CLASS_PREFIX) {
return classes[i].substring(IMAGEID_CLASS_PREFIX.length);
}
}
};
var toggleInput = function(dialog, inputID, active) {
var inputEl = dialog.getContentElement('media', inputID).getInputElement();
if (active) {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
['Link', 'media_link'],
['Preview', 'media_preview'],
['Large', 'media_large']
];
// NOTE: Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles is defined in eatlas_media_frame_filter.module
if (typeof Drupal.settings.eatlas_media_frame_filter === 'object' && typeof Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles === 'object') {
var customStyles = Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles;
for (customStyleId in customStyles) {
if (customStyles.hasOwnProperty(customStyleId)) {
imageStyles.push([customStyles[customStyleId], customStyleId]);
}
}
}
// CKEditor API: http://docs.ckeditor.com/#!/api/CKEDITOR.dialog.definition.checkbox
return {
id: 'media',
label: 'Frame info',
padding: 0,
elements: [
{
id: 'lstImageStyle',
type: 'select',
label: 'Image style',
// NOTE: This CSS class hide the field when it's disabled.
className: 'eatlas-media-frame-filter-image-style-select',
items: imageStyles,
onChange: onImageStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var currentImageStyle = getImageStyle(element);
this.fid = getMediaFileId(element);
this.setValue(currentImageStyle);
// Disable the field when it's set to "Original"
// We don't want users to be able to choose something else
// but still give the ability to fix broken images.
if (currentImageStyle === 'media_original') {
this.disable();
}
}
},
commit: function(type, element) {}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaStyle',
type: 'select',
label: 'Frame style',
items: [
['- No frame -', ''],
['Wikipedia style', 'wikipedia'],
['Info on image', 'onImage'],
['Tile', 'tile']
],
'default': '', // The default must match the default in "eatlas_media_frame_filter.module"
onChange: onMediaStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var frameStyle = element.getAttribute('media_style');
if (frameStyle !== null) {
this.setValue(frameStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var frameStyle = this.getValue();
element.setAttribute('media_style', frameStyle);
}
}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaLink',
type: 'select',
label: 'Link to media page',
items: [
['- No link to media page -', 'none'],
['Magnifier', 'magnifier'],
['Image linked to media page', 'direct']
],
'default': 'none',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var mediaLinkStyle = element.getAttribute('media_link');
if (mediaLinkStyle !== null) {
this.setValue(mediaLinkStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var mediaLinkStyle = this.getValue();
element.setAttribute('media_link', mediaLinkStyle);
}
}
}, {
id: 'chkHideDesc',
type: 'checkbox',
label: 'Hide description',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidedesc = element.getAttribute('media_hidedesc');
if (hidedesc) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidedesc = this.getValue();
if (hidedesc) {
element.setAttribute('media_hidedesc', true);
} else {
element.removeAttribute('media_hidedesc');
}
}
}
}, {
id: 'chkHideLicense',
type: 'checkbox',
label: 'Hide license',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidelicense = element.getAttribute('media_hidelicense');
if (hidelicense) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidelicense = this.getValue();
if (hidelicense) {
element.setAttribute('media_hidelicense', true);
} else {
element.removeAttribute('media_hidelicense');
}
}
}
}, {
id: 'txtMediaTitle',
type: 'text',
label: 'Title overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var title = _decode(element.getAttribute('media_title'));
if (title) {
this.setValue(title);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var title = _encode(this.getValue());
if (title) {
element.setAttribute('media_title', title);
} else {
element.removeAttribute('media_title');
}
}
}
}, {
id: 'txtMediaDescPrefix',
type: 'text',
label: 'Description prefix',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var prefix = _decode(element.getAttribute('media_descprefix'));
if (prefix) {
this.setValue(prefix);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var prefix = _encode(this.getValue());
if (prefix) {
element.setAttribute('media_descprefix', prefix);
} else {
element.removeAttribute('media_descprefix');
}
}
}
}, {
id: 'txtMediaDescription',
type: 'textarea',
label: 'Description overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var description = _decode(element.getAttribute('media_description'));
if (description) {
this.setValue(description);
}
}
},
commit: function( type, element ) {
if (type == IMAGE) {
var description = _encode(this.getValue());
if (description) {
element.setAttribute('media_description', description);
} else {
element.removeAttribute('media_description');
}
}
}
}, {
type: 'html',
html: '<div role="presentation">' +
'<label>Metadata</label>' +
'<div id="eatlas_media_frame_info"><span class="loading">Loading...</span></div>' +
'</div>',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var domElement = document.getElementById('eatlas_media_frame_info');
var fid = _eatlas_media_frame_ckeditor_get_fid(element);
if (fid !== null) {
domElement.innerHTML = '<iframe class="iframe-mediaframe-fileinfo" src="/?q=eatlas_mediaframe_fileinfo/' + fid + '"/>';
} else {
domElement.innerHTML = '<span class="noinfo">No information available</span>';
}
}
}
}
]
};
function _encode(htmlStr) {
// Create a in-memory div, set it's inner text (which jQuery automatically encodes)
// then grab the encoded contents back out. The div never exists on the page.
return $('<div/>').text(htmlStr).html();
}
function _decode(str) |
/**
* element: CKEDITOR.dom.element
* The file ID is store in the class of the element:
* class="... img__fid__12 ...";
*/
function _eatlas_media_frame_ckeditor_get_fid(element) {
var classesStr = element.getAttribute('class');
var fidClassPrefix = 'img__fid__';
if (classesStr) {
var classes = classesStr.split(" ");
var _class = null;
for (var i=0, len=classes.length; i<len; i++) {
_class = classes[i];
if (_class && _class.indexOf(fidClassPrefix) === 0) {
return parseInt(_class.substring(fidClassPrefix.length));
}
}
}
return null;
}
}
})(jQuery);
| {
return $('<div/>').html(str).text();
} | identifier_body |
CKEditor_media_tab.js | /**
* Add a media tab to the image properties dialog.
*
* This process as to be executed in a precise time frame;
* After CKEditor is loaded, but before it's executed.
*
* It tooks me some time to find out a stable way to define this.
* There is how I understand the loading process:
*
* Drupal Page:
* * Drupal Module A JS
* * Drupal Module B JS
* * ...
* * Drupal Module eatlas_media_frame_filter JS (CKEditor do not exists yet)
* * ...
* * Drupal Module N JS
* (some inconsistant loading delay)
* * CKEditor is created (*)
*
* (*) Wysiwyg JS (the javascript related to the wysiwyg module, the one
* that trigger the loading of CKEditor) is inserted somewhere in this
* process, maybe before, maybe after eatlas_media_frame_filter JS, so I
* can't rely on the existance of that module. I suppose the module
* dependencies defined in eatlas_media_frame_filter info file help to
* define the loading order, but this is not THE issue we are dealing
* with.
* Wysiwyg PHP module read the config and determine that the page will
* need CKEditor, so it add CKEditor to the page. At this point, maybe
* CKEditor is executed, maybe not, but at lease the variable CKEditor
* exists so I can listen to the instanceReady event.
*
* Since my JS as already been load, I have to defer it's execution to be
* able to listen to CKEditor events (I can't listen to those events
* before the CKEditor variable has been created). Defering it after the
* page load seems to be enough to push it's execution after CKEditor get
* created, changing the workflow to:
*
* Page:
* * Module A JS
* * Module B JS
* * ...
* * eatlas_media_frame_filter JS loaded but execution defered
* * ...
* * Module N JS
* (some inconsistant loading delay)
* * CKEditor is loaded, but maybe not executed yet (that's why I listen to instanceReady)
* (page load event is fired)
* * eatlas_media_frame_filter JS is executed
*
* Pseudo code:
* when all JS are in place (page load event):
* if CKEditor exists:
* When 'instanceReady' event is called:
* Add media tab to CKEditor's image properties dialog
* else
* Assume that the page do not have an instance of CKEditor => nothing to do.
*/
/**
* Waiting for the page load event to execute the script.
* Using JQuery to enforce compatibilities across browsers JS API.
* NOTE: This script use variables from Drupal, passed to JavaScript by
* the variable Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles
* defined in eatlas_media_frame_filter.module.
*/
(function ($) {
$(document).ready(function(){
if (typeof(CKEDITOR) !== 'undefined') {
// Example: http://docs.cksource.com/CKEditor_3.x/Developers_Guide/Dialog_Customization
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definitionObject.html
CKEDITOR.on('dialogDefinition', function(ev) {
// Take the dialog name and its definition from the event data.
var dialogName = ev.data.name;
var dialogDefinition = ev.data.definition;
if (dialogName == 'image') {
dialogDefinition.addContents(
_eatlas_media_frame_ckeditor_create_media_tab(), // Tab Definition
'Link' // Next element
);
}
});
}
});
/**
* Return the definition of the media tab.
* See - ckeditor/plugins/image/dialogs/image.js
*/
function _eatlas_media_frame_ckeditor_create_media_tab() {
// As defined in imageDialog function
var IMAGE = 1,
LINK = 2,
PREVIEW = 4,
CLEANUP = 8;
var IMAGESTYLE_CLASS_PREFIX = 'img__view_mode__';
var IMAGEID_CLASS_PREFIX = 'img__fid__';
var onMediaStyleChange = function() {
// This = input element.
var value = this.getValue(),
dialog = this.getDialog();
var enable = value && value != 'enlarge';
toggleInput(dialog, 'chkHideDesc', enable);
toggleInput(dialog, 'chkHideLicense', enable);
toggleInput(dialog, 'txtMediaTitle', enable);
toggleInput(dialog, 'txtMediaDescPrefix', enable);
toggleInput(dialog, 'txtMediaDescription', enable);
};
var onImageStyleChange = function() {
var newMediaStyle = this.getValue(),
dialog = this.getDialog();
if (!newMediaStyle) {
newMediaStyle = 'media_original'
}
// The media styles are inconsistent with image styles. It's okay
// with most of them, but a mapping has to be done for the
// 'hardcoded' one.
var newImageStyle = newMediaStyle;
if (newImageStyle === 'media_preview') {
newImageStyle = 'square_thumbnail';
} else if (newImageStyle === 'media_large') {
newImageStyle = 'large';
} else if (newImageStyle === 'media_original') {
newImageStyle = '';
}
// API http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.html
//
// pageId: 'info', 'media', 'Link', 'Upload', 'advanced'
// elementId:
// info:
// 'txtUrl' (cke_75_uiElement),
// 'browse' (cke_77_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'txtAlt' (cke_82_uiElement),
// 'txtWidth' (cke_85_uiElement),
// 'txtHeight' (cke_88_uiElement),
// undefined (cke_89_uiElement) (container for Width and Height),
// 'ratioLock' (cke_90_uiElement) (both lock and reset),
// 'txtBorder' (cke_94_uiElement),
// 'txtHSpace' (cke_97_uiElement),
// 'txtVSpace' (cke_100_uiElement),
// 'cmbAlign' (cke_103_uiElement),
// 'basic' (cke_105_uiElement) (container for Width, Height, Border, HSpace, VSpace and Alignment),
// 'htmlPreview' (cke_106_uiElement)
// media:
// 'lstImageStyle' (cke_113_uiElement),
// 'lstMediaStyle' (cke_116_uiElement),
// 'lstMediaLink' (...),
// 'txtMediaTitle' (...),
// 'txtMediaDescPrefix' (...),
// 'txtMediaDescription' (cke_119_uiElement),
// undefined (cke_120_uiElement) (metadata info),
// Link:
// 'txtUrl' (cke_125_uiElement),
// 'browse' (cke_127_uiElement) (disabled 'Browse Server' button to the right of URL field),
// 'cmbTarget' (cke_130_uiElement)
// Upload:
// 'upload' (cke_135_uiElement),
// 'uploadButton' (cke_137_uiElement)
// advanced:
// 'linkId' (cke_142_uiElement),
// 'cmbLangDir' (cke_145_uiElement),
// 'txtLangCode' (cke_148_uiElement),
// 'txtGenLongDescr' (cke_152_uiElement),
// 'txtGenClass' (cke_155_uiElement),
// 'txtGenTitle' (cke_158_uiElement),
// undefined (cke_159_uiElement) (container for Stylesheet Classes and Advisory Title),
// 'txtdlgGenStyle' (cke_162_uiElement)
//
// Snipet to display the mapping DOM ID => CKEditor element ID:
// dialog.foreach(function(el) {
// console.log('DOM ID: ' + el.domId + ' ID: ' + el.id);
// });
// *** CSS Classes ***
// Get actual image CSS Classes, as defined in the dialog field
// API: dialog.getValueOf(pageId, elementId);
var classes = dialog.getValueOf('advanced', 'txtGenClass');
classes = classes ? classes.split(/\s+/) : [];
// Remove previous 'image style' class and find the image ID
var newClasses = [];
for (var i=0, len=classes.length; i<len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) !== IMAGESTYLE_CLASS_PREFIX) {
newClasses.push(classes[i]);
}
}
// Add new 'image style' class
newClasses.push(IMAGESTYLE_CLASS_PREFIX + newMediaStyle);
// Set the new image CSS Classes in the dialog field
// API: dialog.setValueOf(pageId, elementId, value);
dialog.setValueOf('advanced', 'txtGenClass', newClasses.join(' '));
// *** Image URL ***
// Async request to the file URL service (only works when logged)
// IMPORTANT: The Drupal API must be used to get the image URL
// because it need to add the "itok" token to the URL.
// That token has been added to avoid an easy DDoS.
// See: http://berk.es/2013/03/04/drupal-imagecache-security-vulnarability-with-ddos-attack-explained/
if (typeof this.fid !== 'undefined') {
$.getJSON("/eatlas_mediaframe_fileurl/" + this.fid + "/" + newImageStyle, function(json){
if (typeof json.url !== 'undefined') {
// Set the new image URL in the dialog field
var currentUrl = dialog.getValueOf('info', 'txtUrl');
if (currentUrl != json.url) {
dialog.setValueOf('info', 'txtUrl', json.url);
}
}
});
}
};
var getImageStyle = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGESTYLE_CLASS_PREFIX.length) === IMAGESTYLE_CLASS_PREFIX) {
return classes[i].substring(IMAGESTYLE_CLASS_PREFIX.length);
}
}
};
var getMediaFileId = function(element) {
var classes = element.getAttribute('class');
if (!classes) {
return null;
}
classes = classes.split(/\s+/);
for (var i=0, len=classes.length; i < len; i++) {
if (classes[i].substring(0, IMAGEID_CLASS_PREFIX.length) === IMAGEID_CLASS_PREFIX) {
return classes[i].substring(IMAGEID_CLASS_PREFIX.length);
}
}
};
var toggleInput = function(dialog, inputID, active) {
var inputEl = dialog.getContentElement('media', inputID).getInputElement();
if (active) {
inputEl.removeAttribute('readonly');
inputEl.removeClass('disabled');
} else {
inputEl.setAttribute('readonly', true);
inputEl.addClass('disabled');
}
};
var imageStyles = [
['Original', 'media_original'],
['Link', 'media_link'],
['Preview', 'media_preview'],
['Large', 'media_large']
];
// NOTE: Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles is defined in eatlas_media_frame_filter.module
if (typeof Drupal.settings.eatlas_media_frame_filter === 'object' && typeof Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles === 'object') {
var customStyles = Drupal.settings.eatlas_media_frame_filter.drupal_custom_image_styles;
for (customStyleId in customStyles) {
if (customStyles.hasOwnProperty(customStyleId)) {
imageStyles.push([customStyles[customStyleId], customStyleId]);
}
}
}
// CKEditor API: http://docs.ckeditor.com/#!/api/CKEDITOR.dialog.definition.checkbox
return {
id: 'media',
label: 'Frame info',
padding: 0,
elements: [
{
id: 'lstImageStyle',
type: 'select',
label: 'Image style',
// NOTE: This CSS class hide the field when it's disabled.
className: 'eatlas-media-frame-filter-image-style-select',
items: imageStyles,
onChange: onImageStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var currentImageStyle = getImageStyle(element);
this.fid = getMediaFileId(element);
this.setValue(currentImageStyle);
// Disable the field when it's set to "Original"
// We don't want users to be able to choose something else
// but still give the ability to fix broken images.
if (currentImageStyle === 'media_original') {
this.disable();
}
}
},
commit: function(type, element) {}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaStyle',
type: 'select',
label: 'Frame style',
items: [
['- No frame -', ''],
['Wikipedia style', 'wikipedia'],
['Info on image', 'onImage'],
['Tile', 'tile']
],
'default': '', // The default must match the default in "eatlas_media_frame_filter.module"
onChange: onMediaStyleChange,
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var frameStyle = element.getAttribute('media_style');
if (frameStyle !== null) {
this.setValue(frameStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var frameStyle = this.getValue();
element.setAttribute('media_style', frameStyle);
}
}
}, {
// API: http://docs.cksource.com/ckeditor_api/symbols/CKEDITOR.dialog.definition.select.html
id: 'lstMediaLink',
type: 'select',
label: 'Link to media page',
items: [
['- No link to media page -', 'none'],
['Magnifier', 'magnifier'],
['Image linked to media page', 'direct']
],
'default': 'none',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
// noframe, with default true
var mediaLinkStyle = element.getAttribute('media_link');
if (mediaLinkStyle !== null) {
this.setValue(mediaLinkStyle);
}
}
},
commit: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var mediaLinkStyle = this.getValue();
element.setAttribute('media_link', mediaLinkStyle);
}
}
}, {
id: 'chkHideDesc',
type: 'checkbox',
label: 'Hide description',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidedesc = element.getAttribute('media_hidedesc');
if (hidedesc) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidedesc = this.getValue();
if (hidedesc) {
element.setAttribute('media_hidedesc', true);
} else {
element.removeAttribute('media_hidedesc');
}
}
}
}, {
id: 'chkHideLicense',
type: 'checkbox',
label: 'Hide license',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var hidelicense = element.getAttribute('media_hidelicense');
if (hidelicense) {
this.setValue(true);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var hidelicense = this.getValue();
if (hidelicense) {
element.setAttribute('media_hidelicense', true);
} else {
element.removeAttribute('media_hidelicense');
}
}
}
}, {
id: 'txtMediaTitle',
type: 'text',
label: 'Title overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var title = _decode(element.getAttribute('media_title'));
if (title) {
this.setValue(title);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var title = _encode(this.getValue());
if (title) {
element.setAttribute('media_title', title);
} else {
element.removeAttribute('media_title');
}
}
}
}, {
id: 'txtMediaDescPrefix',
type: 'text',
label: 'Description prefix',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var prefix = _decode(element.getAttribute('media_descprefix'));
if (prefix) {
this.setValue(prefix);
}
}
},
commit: function(type, element) {
if (type == IMAGE) {
var prefix = _encode(this.getValue());
if (prefix) {
element.setAttribute('media_descprefix', prefix);
} else {
element.removeAttribute('media_descprefix');
}
}
}
}, {
id: 'txtMediaDescription',
type: 'textarea',
label: 'Description overwrite',
style: 'width: 100%',
'default': '',
readonly: true,
setup: function(type, element) {
if (type == IMAGE) {
var description = _decode(element.getAttribute('media_description'));
if (description) {
this.setValue(description);
}
}
},
commit: function( type, element ) {
if (type == IMAGE) {
var description = _encode(this.getValue());
if (description) {
element.setAttribute('media_description', description);
} else {
element.removeAttribute('media_description');
}
}
}
}, {
type: 'html',
html: '<div role="presentation">' +
'<label>Metadata</label>' +
'<div id="eatlas_media_frame_info"><span class="loading">Loading...</span></div>' +
'</div>',
setup: function(type, element) {
// element => CKEDITOR.dom.element
if (type == IMAGE) {
var domElement = document.getElementById('eatlas_media_frame_info');
var fid = _eatlas_media_frame_ckeditor_get_fid(element);
if (fid !== null) {
domElement.innerHTML = '<iframe class="iframe-mediaframe-fileinfo" src="/?q=eatlas_mediaframe_fileinfo/' + fid + '"/>';
} else {
domElement.innerHTML = '<span class="noinfo">No information available</span>';
}
}
}
}
]
};
function _encode(htmlStr) {
// Create a in-memory div, set it's inner text (which jQuery automatically encodes)
// then grab the encoded contents back out. The div never exists on the page.
return $('<div/>').text(htmlStr).html();
}
function | (str) {
return $('<div/>').html(str).text();
}
/**
* element: CKEDITOR.dom.element
* The file ID is store in the class of the element:
* class="... img__fid__12 ...";
*/
function _eatlas_media_frame_ckeditor_get_fid(element) {
var classesStr = element.getAttribute('class');
var fidClassPrefix = 'img__fid__';
if (classesStr) {
var classes = classesStr.split(" ");
var _class = null;
for (var i=0, len=classes.length; i<len; i++) {
_class = classes[i];
if (_class && _class.indexOf(fidClassPrefix) === 0) {
return parseInt(_class.substring(fidClassPrefix.length));
}
}
}
return null;
}
}
})(jQuery);
| _decode | identifier_name |
lib.rs | // This file is part of Substrate.
// Copyright (C) Parity Technologies (UK) Ltd.
// SPDX-License-Identifier: Apache-2.0
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! # Utility Pallet
//! A stateless pallet with helpers for dispatch management which does no re-authentication.
//!
//! - [`Config`]
//! - [`Call`]
//!
//! ## Overview
//!
//! This pallet contains two basic pieces of functionality:
//! - Batch dispatch: A stateless operation, allowing any origin to execute multiple calls in a
//! single dispatch. This can be useful to amalgamate proposals, combining `set_code` with
//! corresponding `set_storage`s, for efficient multiple payouts with just a single signature
//! verify, or in combination with one of the other two dispatch functionality.
//! - Pseudonymal dispatch: A stateless operation, allowing a signed origin to execute a call from
//! an alternative signed origin. Each account has 2 * 2**16 possible "pseudonyms" (alternative
//! account IDs) and these can be stacked. This can be useful as a key management tool, where you
//! need multiple distinct accounts (e.g. as controllers for many staking accounts), but where
//! it's perfectly fine to have each of them controlled by the same underlying keypair. Derivative
//! accounts are, for the purposes of proxy filtering considered exactly the same as the origin
//! and are thus hampered with the origin's filters.
//!
//! Since proxy filters are respected in all dispatches of this pallet, it should never need to be
//! filtered by any proxy.
//!
//! ## Interface
//!
//! ### Dispatchable Functions
//!
//! #### For batch dispatch
//! * `batch` - Dispatch multiple calls from the sender's origin.
//!
//! #### For pseudonymal dispatch
//! * `as_derivative` - Dispatch a call from a derivative signed origin.
// Ensure we're `no_std` when compiling for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
mod benchmarking;
mod tests;
pub mod weights;
use codec::{Decode, Encode};
use frame_support::{
dispatch::{extract_actual_weight, GetDispatchInfo, PostDispatchInfo},
traits::{IsSubType, OriginTrait, UnfilteredDispatchable},
};
use sp_core::TypeId;
use sp_io::hashing::blake2_256;
use sp_runtime::traits::{BadOrigin, Dispatchable, TrailingZeroInput};
use sp_std::prelude::*;
pub use weights::WeightInfo;
pub use pallet::*;
#[frame_support::pallet]
pub mod pallet {
use super::*;
use frame_support::pallet_prelude::*;
use frame_system::pallet_prelude::*;
#[pallet::pallet]
pub struct Pallet<T>(_);
/// Configuration trait.
#[pallet::config]
pub trait Config: frame_system::Config {
/// The overarching event type.
type RuntimeEvent: From<Event> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
/// The overarching call type.
type RuntimeCall: Parameter
+ Dispatchable<RuntimeOrigin = Self::RuntimeOrigin, PostInfo = PostDispatchInfo>
+ GetDispatchInfo
+ From<frame_system::Call<Self>>
+ UnfilteredDispatchable<RuntimeOrigin = Self::RuntimeOrigin>
+ IsSubType<Call<Self>>
+ IsType<<Self as frame_system::Config>::RuntimeCall>;
/// The caller origin, overarching type of all pallets origins.
type PalletsOrigin: Parameter +
Into<<Self as frame_system::Config>::RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
/// Batch of dispatches did not complete fully. Index of first failing dispatch given, as
/// well as the error.
BatchInterrupted { index: u32, error: DispatchError },
/// Batch of dispatches completed fully with no error.
BatchCompleted,
/// Batch of dispatches completed but has errors.
BatchCompletedWithErrors,
/// A single item within a Batch of dispatches has completed with no error.
ItemCompleted,
/// A single item within a Batch of dispatches has completed with error.
ItemFailed { error: DispatchError },
/// A call was dispatched.
DispatchedAs { result: DispatchResult },
}
// Align the call size to 1KB. As we are currently compiling the runtime for native/wasm
// the `size_of` of the `Call` can be different. To ensure that this don't leads to
// mismatches between native/wasm or to different metadata for the same runtime, we
// algin the call size. The value is chosen big enough to hopefully never reach it.
const CALL_ALIGN: u32 = 1024;
#[pallet::extra_constants]
impl<T: Config> Pallet<T> {
/// The limit on the number of batched calls.
fn batched_calls_limit() -> u32 |
}
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
fn integrity_test() {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller than {} bytes.",
CALL_ALIGN,
);
}
}
#[pallet::error]
pub enum Error<T> {
/// Too many calls batched.
TooManyCalls,
}
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Send a batch of dispatch calls.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
///
/// This will return `Ok` in all circumstances. To determine the success of the batch, an
/// event is deposited. If a call failed and the batch was interrupted, then the
/// `BatchInterrupted` event is deposited, along with the number of successful calls made
/// and the error of the failed call. If all were successful, then the `BatchCompleted`
/// event is deposited.
#[pallet::call_index(0)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
Self::deposit_event(Event::BatchInterrupted {
index: index as u32,
error: e.error,
});
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
return Ok(Some(base_weight + weight).into())
}
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight + weight).into())
}
/// Send a call through an indexed pseudonym of the sender.
///
/// Filter from origin are passed along. The call will be dispatched with an origin which
/// use the same filter as the origin of this call.
///
/// NOTE: If you need to ensure that any account-based filtering is not honored (i.e.
/// because you expect `proxy` to have been used prior in the call stack and you do not want
/// the call restrictions to apply to any sub-accounts), then use `as_multi_threshold_1`
/// in the Multisig pallet instead.
///
/// NOTE: Prior to version *12, this was called `as_limited_sub`.
///
/// The dispatch origin for this call must be _Signed_.
#[pallet::call_index(1)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::as_derivative()
// AccountData for inner call origin accountdata.
.saturating_add(T::DbWeight::get().reads_writes(1, 1))
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn as_derivative(
origin: OriginFor<T>,
index: u16,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
let mut origin = origin;
let who = ensure_signed(origin.clone())?;
let pseudonym = Self::derivative_account_id(who, index);
origin.set_caller_from(frame_system::RawOrigin::Signed(pseudonym));
let info = call.get_dispatch_info();
let result = call.dispatch(origin);
// Always take into account the base weight of this call.
let mut weight = T::WeightInfo::as_derivative()
.saturating_add(T::DbWeight::get().reads_writes(1, 1));
// Add the real weight of the dispatch.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result
.map_err(|mut err| {
err.post_info = Some(weight).into();
err
})
.map(|_| Some(weight).into())
}
/// Send a batch of dispatch calls and atomically execute them.
/// The whole transaction will rollback and fail if any of the calls failed.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(2)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch_all(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch_all(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, bypass any dispatch filter; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
let mut filtered_origin = origin.clone();
// Don't allow users to nest `batch_all` calls.
filtered_origin.add_filter(
move |c: &<T as frame_system::Config>::RuntimeCall| {
let c = <T as Config>::RuntimeCall::from_ref(c);
!matches!(c.is_sub_type(), Some(Call::batch_all { .. }))
},
);
call.dispatch(filtered_origin)
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result.map_err(|mut err| {
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch_all(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
err.post_info = Some(base_weight + weight).into();
err
})?;
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch_all(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatches a function call with a provided origin.
///
/// The dispatch origin for this call must be _Root_.
///
/// ## Complexity
/// - O(1).
#[pallet::call_index(3)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::dispatch_as()
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn dispatch_as(
origin: OriginFor<T>,
as_origin: Box<T::PalletsOrigin>,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter((*as_origin).into());
Self::deposit_event(Event::DispatchedAs {
result: res.map(|_| ()).map_err(|e| e.error),
});
Ok(())
}
/// Send a batch of dispatch calls.
/// Unlike `batch`, it allows errors and won't interrupt.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatch without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(4)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::force_batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn force_batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
// Track failed dispatch occur.
let mut has_error: bool = false;
for call in calls.into_iter() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
has_error = true;
Self::deposit_event(Event::ItemFailed { error: e.error });
} else {
Self::deposit_event(Event::ItemCompleted);
}
}
if has_error {
Self::deposit_event(Event::BatchCompletedWithErrors);
} else {
Self::deposit_event(Event::BatchCompleted);
}
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatch a function call with a specified weight.
///
/// This function does not check the weight of the call, and instead allows the
/// Root origin to specify the weight of the call.
///
/// The dispatch origin for this call must be _Root_.
#[pallet::call_index(5)]
#[pallet::weight((*_weight, call.get_dispatch_info().class))]
pub fn with_weight(
origin: OriginFor<T>,
call: Box<<T as Config>::RuntimeCall>,
_weight: Weight,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
res.map(|_| ()).map_err(|e| e.error)
}
}
}
/// A pallet identifier. These are per pallet and should be stored in a registry somewhere.
#[derive(Clone, Copy, Eq, PartialEq, Encode, Decode)]
struct IndexedUtilityPalletId(u16);
impl TypeId for IndexedUtilityPalletId {
const TYPE_ID: [u8; 4] = *b"suba";
}
impl<T: Config> Pallet<T> {
/// Derive a derivative account ID from the owner account and the sub-account index.
pub fn derivative_account_id(who: T::AccountId, index: u16) -> T::AccountId {
let entropy = (b"modlpy/utilisuba", who, index).using_encoded(blake2_256);
Decode::decode(&mut TrailingZeroInput::new(entropy.as_ref()))
.expect("infinite length input; no invalid inputs for type; qed")
}
}
| {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
// The margin to take into account vec doubling capacity.
let margin_factor = 3;
allocator_limit / margin_factor / call_size
} | identifier_body |
lib.rs | // This file is part of Substrate.
// Copyright (C) Parity Technologies (UK) Ltd.
// SPDX-License-Identifier: Apache-2.0
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! # Utility Pallet
//! A stateless pallet with helpers for dispatch management which does no re-authentication.
//!
//! - [`Config`]
//! - [`Call`]
//!
//! ## Overview
//!
//! This pallet contains two basic pieces of functionality:
//! - Batch dispatch: A stateless operation, allowing any origin to execute multiple calls in a
//! single dispatch. This can be useful to amalgamate proposals, combining `set_code` with
//! corresponding `set_storage`s, for efficient multiple payouts with just a single signature
//! verify, or in combination with one of the other two dispatch functionality.
//! - Pseudonymal dispatch: A stateless operation, allowing a signed origin to execute a call from
//! an alternative signed origin. Each account has 2 * 2**16 possible "pseudonyms" (alternative
//! account IDs) and these can be stacked. This can be useful as a key management tool, where you
//! need multiple distinct accounts (e.g. as controllers for many staking accounts), but where
//! it's perfectly fine to have each of them controlled by the same underlying keypair. Derivative
//! accounts are, for the purposes of proxy filtering considered exactly the same as the origin
//! and are thus hampered with the origin's filters.
//!
//! Since proxy filters are respected in all dispatches of this pallet, it should never need to be
//! filtered by any proxy.
//!
//! ## Interface
//!
//! ### Dispatchable Functions
//!
//! #### For batch dispatch
//! * `batch` - Dispatch multiple calls from the sender's origin.
//!
//! #### For pseudonymal dispatch
//! * `as_derivative` - Dispatch a call from a derivative signed origin.
// Ensure we're `no_std` when compiling for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
mod benchmarking;
mod tests;
pub mod weights;
use codec::{Decode, Encode};
use frame_support::{
dispatch::{extract_actual_weight, GetDispatchInfo, PostDispatchInfo},
traits::{IsSubType, OriginTrait, UnfilteredDispatchable},
};
use sp_core::TypeId;
use sp_io::hashing::blake2_256;
use sp_runtime::traits::{BadOrigin, Dispatchable, TrailingZeroInput};
use sp_std::prelude::*;
pub use weights::WeightInfo;
pub use pallet::*;
#[frame_support::pallet]
pub mod pallet {
use super::*;
use frame_support::pallet_prelude::*;
use frame_system::pallet_prelude::*;
#[pallet::pallet]
pub struct Pallet<T>(_);
/// Configuration trait.
#[pallet::config]
pub trait Config: frame_system::Config {
/// The overarching event type.
type RuntimeEvent: From<Event> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
/// The overarching call type.
type RuntimeCall: Parameter
+ Dispatchable<RuntimeOrigin = Self::RuntimeOrigin, PostInfo = PostDispatchInfo>
+ GetDispatchInfo
+ From<frame_system::Call<Self>>
+ UnfilteredDispatchable<RuntimeOrigin = Self::RuntimeOrigin>
+ IsSubType<Call<Self>>
+ IsType<<Self as frame_system::Config>::RuntimeCall>;
/// The caller origin, overarching type of all pallets origins.
type PalletsOrigin: Parameter +
Into<<Self as frame_system::Config>::RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
/// Batch of dispatches did not complete fully. Index of first failing dispatch given, as
/// well as the error.
BatchInterrupted { index: u32, error: DispatchError },
/// Batch of dispatches completed fully with no error.
BatchCompleted,
/// Batch of dispatches completed but has errors.
BatchCompletedWithErrors,
/// A single item within a Batch of dispatches has completed with no error.
ItemCompleted,
/// A single item within a Batch of dispatches has completed with error.
ItemFailed { error: DispatchError },
/// A call was dispatched.
DispatchedAs { result: DispatchResult },
}
// Align the call size to 1KB. As we are currently compiling the runtime for native/wasm
// the `size_of` of the `Call` can be different. To ensure that this don't leads to
// mismatches between native/wasm or to different metadata for the same runtime, we
// algin the call size. The value is chosen big enough to hopefully never reach it.
const CALL_ALIGN: u32 = 1024;
#[pallet::extra_constants]
impl<T: Config> Pallet<T> {
/// The limit on the number of batched calls.
fn batched_calls_limit() -> u32 {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
// The margin to take into account vec doubling capacity.
let margin_factor = 3;
allocator_limit / margin_factor / call_size
}
}
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
fn | () {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller than {} bytes.",
CALL_ALIGN,
);
}
}
#[pallet::error]
pub enum Error<T> {
/// Too many calls batched.
TooManyCalls,
}
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Send a batch of dispatch calls.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
///
/// This will return `Ok` in all circumstances. To determine the success of the batch, an
/// event is deposited. If a call failed and the batch was interrupted, then the
/// `BatchInterrupted` event is deposited, along with the number of successful calls made
/// and the error of the failed call. If all were successful, then the `BatchCompleted`
/// event is deposited.
#[pallet::call_index(0)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
Self::deposit_event(Event::BatchInterrupted {
index: index as u32,
error: e.error,
});
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
return Ok(Some(base_weight + weight).into())
}
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight + weight).into())
}
/// Send a call through an indexed pseudonym of the sender.
///
/// Filter from origin are passed along. The call will be dispatched with an origin which
/// use the same filter as the origin of this call.
///
/// NOTE: If you need to ensure that any account-based filtering is not honored (i.e.
/// because you expect `proxy` to have been used prior in the call stack and you do not want
/// the call restrictions to apply to any sub-accounts), then use `as_multi_threshold_1`
/// in the Multisig pallet instead.
///
/// NOTE: Prior to version *12, this was called `as_limited_sub`.
///
/// The dispatch origin for this call must be _Signed_.
#[pallet::call_index(1)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::as_derivative()
// AccountData for inner call origin accountdata.
.saturating_add(T::DbWeight::get().reads_writes(1, 1))
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn as_derivative(
origin: OriginFor<T>,
index: u16,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
let mut origin = origin;
let who = ensure_signed(origin.clone())?;
let pseudonym = Self::derivative_account_id(who, index);
origin.set_caller_from(frame_system::RawOrigin::Signed(pseudonym));
let info = call.get_dispatch_info();
let result = call.dispatch(origin);
// Always take into account the base weight of this call.
let mut weight = T::WeightInfo::as_derivative()
.saturating_add(T::DbWeight::get().reads_writes(1, 1));
// Add the real weight of the dispatch.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result
.map_err(|mut err| {
err.post_info = Some(weight).into();
err
})
.map(|_| Some(weight).into())
}
/// Send a batch of dispatch calls and atomically execute them.
/// The whole transaction will rollback and fail if any of the calls failed.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(2)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch_all(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch_all(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, bypass any dispatch filter; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
let mut filtered_origin = origin.clone();
// Don't allow users to nest `batch_all` calls.
filtered_origin.add_filter(
move |c: &<T as frame_system::Config>::RuntimeCall| {
let c = <T as Config>::RuntimeCall::from_ref(c);
!matches!(c.is_sub_type(), Some(Call::batch_all { .. }))
},
);
call.dispatch(filtered_origin)
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result.map_err(|mut err| {
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch_all(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
err.post_info = Some(base_weight + weight).into();
err
})?;
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch_all(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatches a function call with a provided origin.
///
/// The dispatch origin for this call must be _Root_.
///
/// ## Complexity
/// - O(1).
#[pallet::call_index(3)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::dispatch_as()
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn dispatch_as(
origin: OriginFor<T>,
as_origin: Box<T::PalletsOrigin>,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter((*as_origin).into());
Self::deposit_event(Event::DispatchedAs {
result: res.map(|_| ()).map_err(|e| e.error),
});
Ok(())
}
/// Send a batch of dispatch calls.
/// Unlike `batch`, it allows errors and won't interrupt.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatch without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(4)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::force_batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn force_batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
// Track failed dispatch occur.
let mut has_error: bool = false;
for call in calls.into_iter() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
has_error = true;
Self::deposit_event(Event::ItemFailed { error: e.error });
} else {
Self::deposit_event(Event::ItemCompleted);
}
}
if has_error {
Self::deposit_event(Event::BatchCompletedWithErrors);
} else {
Self::deposit_event(Event::BatchCompleted);
}
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatch a function call with a specified weight.
///
/// This function does not check the weight of the call, and instead allows the
/// Root origin to specify the weight of the call.
///
/// The dispatch origin for this call must be _Root_.
#[pallet::call_index(5)]
#[pallet::weight((*_weight, call.get_dispatch_info().class))]
pub fn with_weight(
origin: OriginFor<T>,
call: Box<<T as Config>::RuntimeCall>,
_weight: Weight,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
res.map(|_| ()).map_err(|e| e.error)
}
}
}
/// A pallet identifier. These are per pallet and should be stored in a registry somewhere.
#[derive(Clone, Copy, Eq, PartialEq, Encode, Decode)]
struct IndexedUtilityPalletId(u16);
impl TypeId for IndexedUtilityPalletId {
const TYPE_ID: [u8; 4] = *b"suba";
}
impl<T: Config> Pallet<T> {
/// Derive a derivative account ID from the owner account and the sub-account index.
pub fn derivative_account_id(who: T::AccountId, index: u16) -> T::AccountId {
let entropy = (b"modlpy/utilisuba", who, index).using_encoded(blake2_256);
Decode::decode(&mut TrailingZeroInput::new(entropy.as_ref()))
.expect("infinite length input; no invalid inputs for type; qed")
}
}
| integrity_test | identifier_name |
lib.rs | // This file is part of Substrate.
// Copyright (C) Parity Technologies (UK) Ltd.
// SPDX-License-Identifier: Apache-2.0
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! # Utility Pallet
//! A stateless pallet with helpers for dispatch management which does no re-authentication.
//!
//! - [`Config`]
//! - [`Call`]
//!
//! ## Overview
//!
//! This pallet contains two basic pieces of functionality:
//! - Batch dispatch: A stateless operation, allowing any origin to execute multiple calls in a
//! single dispatch. This can be useful to amalgamate proposals, combining `set_code` with
//! corresponding `set_storage`s, for efficient multiple payouts with just a single signature
//! verify, or in combination with one of the other two dispatch functionality.
//! - Pseudonymal dispatch: A stateless operation, allowing a signed origin to execute a call from
//! an alternative signed origin. Each account has 2 * 2**16 possible "pseudonyms" (alternative
//! account IDs) and these can be stacked. This can be useful as a key management tool, where you
//! need multiple distinct accounts (e.g. as controllers for many staking accounts), but where
//! it's perfectly fine to have each of them controlled by the same underlying keypair. Derivative
//! accounts are, for the purposes of proxy filtering considered exactly the same as the origin
//! and are thus hampered with the origin's filters.
//!
//! Since proxy filters are respected in all dispatches of this pallet, it should never need to be
//! filtered by any proxy.
//!
//! ## Interface
//!
//! ### Dispatchable Functions
//!
//! #### For batch dispatch
//! * `batch` - Dispatch multiple calls from the sender's origin.
//!
//! #### For pseudonymal dispatch
//! * `as_derivative` - Dispatch a call from a derivative signed origin.
// Ensure we're `no_std` when compiling for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
mod benchmarking;
mod tests;
pub mod weights;
use codec::{Decode, Encode};
use frame_support::{
dispatch::{extract_actual_weight, GetDispatchInfo, PostDispatchInfo},
traits::{IsSubType, OriginTrait, UnfilteredDispatchable},
};
use sp_core::TypeId;
use sp_io::hashing::blake2_256;
use sp_runtime::traits::{BadOrigin, Dispatchable, TrailingZeroInput};
use sp_std::prelude::*;
pub use weights::WeightInfo;
pub use pallet::*;
#[frame_support::pallet]
pub mod pallet {
use super::*;
use frame_support::pallet_prelude::*;
use frame_system::pallet_prelude::*;
#[pallet::pallet]
pub struct Pallet<T>(_);
/// Configuration trait.
#[pallet::config]
pub trait Config: frame_system::Config {
/// The overarching event type.
type RuntimeEvent: From<Event> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
/// The overarching call type.
type RuntimeCall: Parameter
+ Dispatchable<RuntimeOrigin = Self::RuntimeOrigin, PostInfo = PostDispatchInfo>
+ GetDispatchInfo
+ From<frame_system::Call<Self>>
+ UnfilteredDispatchable<RuntimeOrigin = Self::RuntimeOrigin>
+ IsSubType<Call<Self>>
+ IsType<<Self as frame_system::Config>::RuntimeCall>;
/// The caller origin, overarching type of all pallets origins.
type PalletsOrigin: Parameter +
Into<<Self as frame_system::Config>::RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
/// Batch of dispatches did not complete fully. Index of first failing dispatch given, as
/// well as the error.
BatchInterrupted { index: u32, error: DispatchError },
/// Batch of dispatches completed fully with no error.
BatchCompleted,
/// Batch of dispatches completed but has errors.
BatchCompletedWithErrors,
/// A single item within a Batch of dispatches has completed with no error.
ItemCompleted,
/// A single item within a Batch of dispatches has completed with error.
ItemFailed { error: DispatchError },
/// A call was dispatched.
DispatchedAs { result: DispatchResult },
}
// Align the call size to 1KB. As we are currently compiling the runtime for native/wasm
// the `size_of` of the `Call` can be different. To ensure that this don't leads to
// mismatches between native/wasm or to different metadata for the same runtime, we
// algin the call size. The value is chosen big enough to hopefully never reach it.
const CALL_ALIGN: u32 = 1024;
#[pallet::extra_constants]
impl<T: Config> Pallet<T> {
/// The limit on the number of batched calls.
fn batched_calls_limit() -> u32 {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
// The margin to take into account vec doubling capacity.
let margin_factor = 3;
allocator_limit / margin_factor / call_size
}
}
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
fn integrity_test() {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller than {} bytes.",
CALL_ALIGN,
);
}
}
#[pallet::error]
pub enum Error<T> {
/// Too many calls batched.
TooManyCalls,
}
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Send a batch of dispatch calls.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
///
/// This will return `Ok` in all circumstances. To determine the success of the batch, an
/// event is deposited. If a call failed and the batch was interrupted, then the
/// `BatchInterrupted` event is deposited, along with the number of successful calls made
/// and the error of the failed call. If all were successful, then the `BatchCompleted`
/// event is deposited.
#[pallet::call_index(0)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
Self::deposit_event(Event::BatchInterrupted {
index: index as u32,
error: e.error,
});
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
return Ok(Some(base_weight + weight).into())
}
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight + weight).into())
}
/// Send a call through an indexed pseudonym of the sender.
///
/// Filter from origin are passed along. The call will be dispatched with an origin which
/// use the same filter as the origin of this call.
///
/// NOTE: If you need to ensure that any account-based filtering is not honored (i.e.
/// because you expect `proxy` to have been used prior in the call stack and you do not want
/// the call restrictions to apply to any sub-accounts), then use `as_multi_threshold_1`
/// in the Multisig pallet instead.
///
/// NOTE: Prior to version *12, this was called `as_limited_sub`.
///
/// The dispatch origin for this call must be _Signed_.
#[pallet::call_index(1)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::as_derivative()
// AccountData for inner call origin accountdata.
.saturating_add(T::DbWeight::get().reads_writes(1, 1))
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn as_derivative(
origin: OriginFor<T>,
index: u16,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
let mut origin = origin;
let who = ensure_signed(origin.clone())?;
let pseudonym = Self::derivative_account_id(who, index);
origin.set_caller_from(frame_system::RawOrigin::Signed(pseudonym));
let info = call.get_dispatch_info();
let result = call.dispatch(origin);
// Always take into account the base weight of this call.
let mut weight = T::WeightInfo::as_derivative()
.saturating_add(T::DbWeight::get().reads_writes(1, 1));
// Add the real weight of the dispatch.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result
.map_err(|mut err| {
err.post_info = Some(weight).into();
err
})
.map(|_| Some(weight).into())
}
/// Send a batch of dispatch calls and atomically execute them.
/// The whole transaction will rollback and fail if any of the calls failed.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(2)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch_all(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch_all(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() |
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, bypass any dispatch filter; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
let mut filtered_origin = origin.clone();
// Don't allow users to nest `batch_all` calls.
filtered_origin.add_filter(
move |c: &<T as frame_system::Config>::RuntimeCall| {
let c = <T as Config>::RuntimeCall::from_ref(c);
!matches!(c.is_sub_type(), Some(Call::batch_all { .. }))
},
);
call.dispatch(filtered_origin)
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result.map_err(|mut err| {
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch_all(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
err.post_info = Some(base_weight + weight).into();
err
})?;
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch_all(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatches a function call with a provided origin.
///
/// The dispatch origin for this call must be _Root_.
///
/// ## Complexity
/// - O(1).
#[pallet::call_index(3)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::dispatch_as()
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn dispatch_as(
origin: OriginFor<T>,
as_origin: Box<T::PalletsOrigin>,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter((*as_origin).into());
Self::deposit_event(Event::DispatchedAs {
result: res.map(|_| ()).map_err(|e| e.error),
});
Ok(())
}
/// Send a batch of dispatch calls.
/// Unlike `batch`, it allows errors and won't interrupt.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatch without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(4)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::force_batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn force_batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
// Track failed dispatch occur.
let mut has_error: bool = false;
for call in calls.into_iter() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
has_error = true;
Self::deposit_event(Event::ItemFailed { error: e.error });
} else {
Self::deposit_event(Event::ItemCompleted);
}
}
if has_error {
Self::deposit_event(Event::BatchCompletedWithErrors);
} else {
Self::deposit_event(Event::BatchCompleted);
}
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatch a function call with a specified weight.
///
/// This function does not check the weight of the call, and instead allows the
/// Root origin to specify the weight of the call.
///
/// The dispatch origin for this call must be _Root_.
#[pallet::call_index(5)]
#[pallet::weight((*_weight, call.get_dispatch_info().class))]
pub fn with_weight(
origin: OriginFor<T>,
call: Box<<T as Config>::RuntimeCall>,
_weight: Weight,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
res.map(|_| ()).map_err(|e| e.error)
}
}
}
/// A pallet identifier. These are per pallet and should be stored in a registry somewhere.
#[derive(Clone, Copy, Eq, PartialEq, Encode, Decode)]
struct IndexedUtilityPalletId(u16);
impl TypeId for IndexedUtilityPalletId {
const TYPE_ID: [u8; 4] = *b"suba";
}
impl<T: Config> Pallet<T> {
/// Derive a derivative account ID from the owner account and the sub-account index.
pub fn derivative_account_id(who: T::AccountId, index: u16) -> T::AccountId {
let entropy = (b"modlpy/utilisuba", who, index).using_encoded(blake2_256);
Decode::decode(&mut TrailingZeroInput::new(entropy.as_ref()))
.expect("infinite length input; no invalid inputs for type; qed")
}
}
| {
return Err(BadOrigin.into())
} | conditional_block |
lib.rs | // This file is part of Substrate.
// Copyright (C) Parity Technologies (UK) Ltd.
// SPDX-License-Identifier: Apache-2.0
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//! # Utility Pallet
//! A stateless pallet with helpers for dispatch management which does no re-authentication.
//!
//! - [`Config`]
//! - [`Call`]
//!
//! ## Overview
//!
//! This pallet contains two basic pieces of functionality:
//! - Batch dispatch: A stateless operation, allowing any origin to execute multiple calls in a
//! single dispatch. This can be useful to amalgamate proposals, combining `set_code` with
//! corresponding `set_storage`s, for efficient multiple payouts with just a single signature
//! verify, or in combination with one of the other two dispatch functionality.
//! - Pseudonymal dispatch: A stateless operation, allowing a signed origin to execute a call from
//! an alternative signed origin. Each account has 2 * 2**16 possible "pseudonyms" (alternative
//! account IDs) and these can be stacked. This can be useful as a key management tool, where you
//! need multiple distinct accounts (e.g. as controllers for many staking accounts), but where
//! it's perfectly fine to have each of them controlled by the same underlying keypair. Derivative
//! accounts are, for the purposes of proxy filtering considered exactly the same as the origin
//! and are thus hampered with the origin's filters.
//!
//! Since proxy filters are respected in all dispatches of this pallet, it should never need to be
//! filtered by any proxy.
//!
//! ## Interface
//!
//! ### Dispatchable Functions
//!
//! #### For batch dispatch
//! * `batch` - Dispatch multiple calls from the sender's origin.
//!
//! #### For pseudonymal dispatch
//! * `as_derivative` - Dispatch a call from a derivative signed origin.
// Ensure we're `no_std` when compiling for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
mod benchmarking;
mod tests;
pub mod weights;
use codec::{Decode, Encode};
use frame_support::{
dispatch::{extract_actual_weight, GetDispatchInfo, PostDispatchInfo},
traits::{IsSubType, OriginTrait, UnfilteredDispatchable},
};
use sp_core::TypeId;
use sp_io::hashing::blake2_256;
use sp_runtime::traits::{BadOrigin, Dispatchable, TrailingZeroInput};
use sp_std::prelude::*;
pub use weights::WeightInfo;
pub use pallet::*;
#[frame_support::pallet]
pub mod pallet {
use super::*;
use frame_support::pallet_prelude::*;
use frame_system::pallet_prelude::*;
#[pallet::pallet]
pub struct Pallet<T>(_);
/// Configuration trait.
#[pallet::config]
pub trait Config: frame_system::Config {
/// The overarching event type.
type RuntimeEvent: From<Event> + IsType<<Self as frame_system::Config>::RuntimeEvent>;
/// The overarching call type.
type RuntimeCall: Parameter
+ Dispatchable<RuntimeOrigin = Self::RuntimeOrigin, PostInfo = PostDispatchInfo>
+ GetDispatchInfo
+ From<frame_system::Call<Self>>
+ UnfilteredDispatchable<RuntimeOrigin = Self::RuntimeOrigin>
+ IsSubType<Call<Self>>
+ IsType<<Self as frame_system::Config>::RuntimeCall>;
/// The caller origin, overarching type of all pallets origins.
type PalletsOrigin: Parameter +
Into<<Self as frame_system::Config>::RuntimeOrigin> +
IsType<<<Self as frame_system::Config>::RuntimeOrigin as frame_support::traits::OriginTrait>::PalletsOrigin>;
/// Weight information for extrinsics in this pallet.
type WeightInfo: WeightInfo;
}
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event {
/// Batch of dispatches did not complete fully. Index of first failing dispatch given, as
/// well as the error.
BatchInterrupted { index: u32, error: DispatchError },
/// Batch of dispatches completed fully with no error.
BatchCompleted,
/// Batch of dispatches completed but has errors.
BatchCompletedWithErrors,
/// A single item within a Batch of dispatches has completed with no error.
ItemCompleted,
/// A single item within a Batch of dispatches has completed with error.
ItemFailed { error: DispatchError },
/// A call was dispatched.
DispatchedAs { result: DispatchResult },
}
// Align the call size to 1KB. As we are currently compiling the runtime for native/wasm
// the `size_of` of the `Call` can be different. To ensure that this don't leads to
// mismatches between native/wasm or to different metadata for the same runtime, we
// algin the call size. The value is chosen big enough to hopefully never reach it.
const CALL_ALIGN: u32 = 1024;
#[pallet::extra_constants]
impl<T: Config> Pallet<T> {
/// The limit on the number of batched calls.
fn batched_calls_limit() -> u32 {
let allocator_limit = sp_core::MAX_POSSIBLE_ALLOCATION;
let call_size = ((sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 +
CALL_ALIGN - 1) / CALL_ALIGN) *
CALL_ALIGN;
// The margin to take into account vec doubling capacity.
let margin_factor = 3;
allocator_limit / margin_factor / call_size
}
}
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
fn integrity_test() {
// If you hit this error, you need to try to `Box` big dispatchable parameters.
assert!(
sp_std::mem::size_of::<<T as Config>::RuntimeCall>() as u32 <= CALL_ALIGN,
"Call enum size should be smaller than {} bytes.",
CALL_ALIGN,
);
}
}
#[pallet::error]
pub enum Error<T> {
/// Too many calls batched.
TooManyCalls,
}
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Send a batch of dispatch calls.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity | /// event is deposited. If a call failed and the batch was interrupted, then the
/// `BatchInterrupted` event is deposited, along with the number of successful calls made
/// and the error of the failed call. If all were successful, then the `BatchCompleted`
/// event is deposited.
#[pallet::call_index(0)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
Self::deposit_event(Event::BatchInterrupted {
index: index as u32,
error: e.error,
});
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
return Ok(Some(base_weight + weight).into())
}
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight + weight).into())
}
/// Send a call through an indexed pseudonym of the sender.
///
/// Filter from origin are passed along. The call will be dispatched with an origin which
/// use the same filter as the origin of this call.
///
/// NOTE: If you need to ensure that any account-based filtering is not honored (i.e.
/// because you expect `proxy` to have been used prior in the call stack and you do not want
/// the call restrictions to apply to any sub-accounts), then use `as_multi_threshold_1`
/// in the Multisig pallet instead.
///
/// NOTE: Prior to version *12, this was called `as_limited_sub`.
///
/// The dispatch origin for this call must be _Signed_.
#[pallet::call_index(1)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::as_derivative()
// AccountData for inner call origin accountdata.
.saturating_add(T::DbWeight::get().reads_writes(1, 1))
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn as_derivative(
origin: OriginFor<T>,
index: u16,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
let mut origin = origin;
let who = ensure_signed(origin.clone())?;
let pseudonym = Self::derivative_account_id(who, index);
origin.set_caller_from(frame_system::RawOrigin::Signed(pseudonym));
let info = call.get_dispatch_info();
let result = call.dispatch(origin);
// Always take into account the base weight of this call.
let mut weight = T::WeightInfo::as_derivative()
.saturating_add(T::DbWeight::get().reads_writes(1, 1));
// Add the real weight of the dispatch.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result
.map_err(|mut err| {
err.post_info = Some(weight).into();
err
})
.map(|_| Some(weight).into())
}
/// Send a batch of dispatch calls and atomically execute them.
/// The whole transaction will rollback and fail if any of the calls failed.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatched without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(2)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::batch_all(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn batch_all(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
for (index, call) in calls.into_iter().enumerate() {
let info = call.get_dispatch_info();
// If origin is root, bypass any dispatch filter; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
let mut filtered_origin = origin.clone();
// Don't allow users to nest `batch_all` calls.
filtered_origin.add_filter(
move |c: &<T as frame_system::Config>::RuntimeCall| {
let c = <T as Config>::RuntimeCall::from_ref(c);
!matches!(c.is_sub_type(), Some(Call::batch_all { .. }))
},
);
call.dispatch(filtered_origin)
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
result.map_err(|mut err| {
// Take the weight of this function itself into account.
let base_weight = T::WeightInfo::batch_all(index.saturating_add(1) as u32);
// Return the actual used weight + base_weight of this call.
err.post_info = Some(base_weight + weight).into();
err
})?;
Self::deposit_event(Event::ItemCompleted);
}
Self::deposit_event(Event::BatchCompleted);
let base_weight = T::WeightInfo::batch_all(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatches a function call with a provided origin.
///
/// The dispatch origin for this call must be _Root_.
///
/// ## Complexity
/// - O(1).
#[pallet::call_index(3)]
#[pallet::weight({
let dispatch_info = call.get_dispatch_info();
(
T::WeightInfo::dispatch_as()
.saturating_add(dispatch_info.weight),
dispatch_info.class,
)
})]
pub fn dispatch_as(
origin: OriginFor<T>,
as_origin: Box<T::PalletsOrigin>,
call: Box<<T as Config>::RuntimeCall>,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter((*as_origin).into());
Self::deposit_event(Event::DispatchedAs {
result: res.map(|_| ()).map_err(|e| e.error),
});
Ok(())
}
/// Send a batch of dispatch calls.
/// Unlike `batch`, it allows errors and won't interrupt.
///
/// May be called from any origin except `None`.
///
/// - `calls`: The calls to be dispatched from the same origin. The number of call must not
/// exceed the constant: `batched_calls_limit` (available in constant metadata).
///
/// If origin is root then the calls are dispatch without checking origin filter. (This
/// includes bypassing `frame_system::Config::BaseCallFilter`).
///
/// ## Complexity
/// - O(C) where C is the number of calls to be batched.
#[pallet::call_index(4)]
#[pallet::weight({
let dispatch_infos = calls.iter().map(|call| call.get_dispatch_info()).collect::<Vec<_>>();
let dispatch_weight = dispatch_infos.iter()
.map(|di| di.weight)
.fold(Weight::zero(), |total: Weight, weight: Weight| total.saturating_add(weight))
.saturating_add(T::WeightInfo::force_batch(calls.len() as u32));
let dispatch_class = {
let all_operational = dispatch_infos.iter()
.map(|di| di.class)
.all(|class| class == DispatchClass::Operational);
if all_operational {
DispatchClass::Operational
} else {
DispatchClass::Normal
}
};
(dispatch_weight, dispatch_class)
})]
pub fn force_batch(
origin: OriginFor<T>,
calls: Vec<<T as Config>::RuntimeCall>,
) -> DispatchResultWithPostInfo {
// Do not allow the `None` origin.
if ensure_none(origin.clone()).is_ok() {
return Err(BadOrigin.into())
}
let is_root = ensure_root(origin.clone()).is_ok();
let calls_len = calls.len();
ensure!(calls_len <= Self::batched_calls_limit() as usize, Error::<T>::TooManyCalls);
// Track the actual weight of each of the batch calls.
let mut weight = Weight::zero();
// Track failed dispatch occur.
let mut has_error: bool = false;
for call in calls.into_iter() {
let info = call.get_dispatch_info();
// If origin is root, don't apply any dispatch filters; root can call anything.
let result = if is_root {
call.dispatch_bypass_filter(origin.clone())
} else {
call.dispatch(origin.clone())
};
// Add the weight of this call.
weight = weight.saturating_add(extract_actual_weight(&result, &info));
if let Err(e) = result {
has_error = true;
Self::deposit_event(Event::ItemFailed { error: e.error });
} else {
Self::deposit_event(Event::ItemCompleted);
}
}
if has_error {
Self::deposit_event(Event::BatchCompletedWithErrors);
} else {
Self::deposit_event(Event::BatchCompleted);
}
let base_weight = T::WeightInfo::batch(calls_len as u32);
Ok(Some(base_weight.saturating_add(weight)).into())
}
/// Dispatch a function call with a specified weight.
///
/// This function does not check the weight of the call, and instead allows the
/// Root origin to specify the weight of the call.
///
/// The dispatch origin for this call must be _Root_.
#[pallet::call_index(5)]
#[pallet::weight((*_weight, call.get_dispatch_info().class))]
pub fn with_weight(
origin: OriginFor<T>,
call: Box<<T as Config>::RuntimeCall>,
_weight: Weight,
) -> DispatchResult {
ensure_root(origin)?;
let res = call.dispatch_bypass_filter(frame_system::RawOrigin::Root.into());
res.map(|_| ()).map_err(|e| e.error)
}
}
}
/// A pallet identifier. These are per pallet and should be stored in a registry somewhere.
#[derive(Clone, Copy, Eq, PartialEq, Encode, Decode)]
struct IndexedUtilityPalletId(u16);
impl TypeId for IndexedUtilityPalletId {
const TYPE_ID: [u8; 4] = *b"suba";
}
impl<T: Config> Pallet<T> {
/// Derive a derivative account ID from the owner account and the sub-account index.
pub fn derivative_account_id(who: T::AccountId, index: u16) -> T::AccountId {
let entropy = (b"modlpy/utilisuba", who, index).using_encoded(blake2_256);
Decode::decode(&mut TrailingZeroInput::new(entropy.as_ref()))
.expect("infinite length input; no invalid inputs for type; qed")
}
} | /// - O(C) where C is the number of calls to be batched.
///
/// This will return `Ok` in all circumstances. To determine the success of the batch, an | random_line_split |
main.py | import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
from torchvision import datasets
from functions import *
from imagepreprocess import *
from model_init import *
from src.representation import *
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
parser = argparse.ArgumentParser(description='PyTorch ImageNet Training')
parser.add_argument('data', metavar='DIR',
help='path to dataset')
parser.add_argument('--arch', '-a', metavar='ARCH', default='resnet18',
help='model architecture: ')
parser.add_argument('-j', '--workers', default=8, type=int, metavar='N',
help='number of data loading workers (default: 4)')
parser.add_argument('--epochs', default=100, type=int, metavar='N',
help='number of total epochs to run')
parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
help='manual epoch number (useful on restarts)')
parser.add_argument('-b', '--batch-size', default=256, type=int,
metavar='N', help='mini-batch size (default: 256)')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
metavar='LR', help='initial learning rate')
parser.add_argument('--lr-method', default='step', type=str,
help='method of learning rate')
parser.add_argument('--lr-params', default=[], dest='lr_params',
action='append', help='params of lr method')
parser.add_argument('--momentum', default=0.9, type=float, metavar='M',
help='momentum')
parser.add_argument('--weight-decay', '--wd', default=1e-4, type=float,
metavar='W', help='weight decay (default: 1e-4)')
parser.add_argument('--print-freq', '-p', default=10, type=int,
metavar='N', help='print frequency (default: 10)')
parser.add_argument('--resume', default='', type=str, metavar='PATH',
help='path to latest checkpoint (default: none)')
parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true',
help='evaluate model on validation set')
parser.add_argument('--pretrained', dest='pretrained', action='store_true',
help='use pre-trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes')
parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='gloo', type=str,
help='distributed backend')
parser.add_argument('--seed', default=None, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--modeldir', default=None, type=str,
help='director of checkpoint')
parser.add_argument('--representation', default=None, type=str,
help='define the representation method')
parser.add_argument('--num-classes', default=None, type=int,
help='define the number of classes')
parser.add_argument('--freezed-layer', default=None, type=int,
help='define the end of freezed layer')
parser.add_argument('--store-model-everyepoch', dest='store_model_everyepoch', action='store_true',
help='store checkpoint in every epoch')
parser.add_argument('--classifier-factor', default=None, type=int,
help='define the multiply factor of classifier')
parser.add_argument('--benchmark', default=None, type=str,
help='name of dataset')
best_prec1 = 0
def main():
global args, best_prec1
args = parser.parse_args()
print(args)
if args.seed is not None:
random.seed(args.seed)
torch.manual_seed(args.seed)
cudnn.deterministic = True
warnings.warn('You have chosen to seed training. '
'This will turn on the CUDNN deterministic setting, '
'which can slow down your training considerably! '
'You may see unexpected behavior when restarting '
'from checkpoints.')
if args.gpu is not None:
warnings.warn('You have chosen a specific GPU. This will completely '
'disable data parallelism.')
args.distributed = args.world_size > 1
if args.distributed:
dist.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
world_size=args.world_size)
# create model
if args.representation == 'GAvP':
representation = {'function':GAvP,
'input_dim':2048}
elif args.representation == 'MPNCOV':
representation = {'function':MPNCOV,
'iterNum':5,
'is_sqrt':True,
'is_vec':True,
'input_dim':2048,
'dimension_reduction':None if args.pretrained else 256}
elif args.representation == 'BCNN':
representation = {'function':BCNN,
'is_vec':True,
'input_dim':2048}
else:
warnings.warn('=> You did not choose a global image representation method!')
representation = None # which for original vgg or alexnet
model = get_model(args.arch,
representation,
args.num_classes,
args.freezed_layer,
pretrained=args.pretrained)
# plot network
vizNet(model, args.modeldir)
# obtain learning rate
LR = Learning_rate_generater(args.lr_method, args.lr_params, args.epochs)
if args.pretrained:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay': 0. if args.arch.startswith('vgg') else args.weight_decay})
else:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay':args.weight_decay})
optimizer = torch.optim.SGD(params_list, lr=args.lr,
momentum=args.momentum,
weight_decay=args.weight_decay)
if args.gpu is not None:
model = model.cuda(args.gpu)
elif args.distributed:
model.cuda()
model = torch.nn.parallel.DistributedDataParallel(model)
else:
if args.arch.startswith('alexnet') or args.arch.startswith('vgg'):
model.features = torch.nn.DataParallel(model.features)
model.cuda()
else:
model = torch.nn.DataParallel(model).cuda()
# define loss function (criterion) and optimizer
criterion = nn.CrossEntropyLoss().cuda(args.gpu)
# optionally resume from a checkpoint
if args.resume:
if os.path.isfile(args.resume):
print("=> loading checkpoint '{}'".format(args.resume))
checkpoint = torch.load(args.resume)
args.start_epoch = checkpoint['epoch']
best_prec1 = checkpoint['best_prec1']
model.load_state_dict(checkpoint['state_dict'])
optimizer.load_state_dict(checkpoint['optimizer'])
print("=> loaded checkpoint '{}' (epoch {})"
.format(args.resume, checkpoint['epoch']))
else:
print("=> no checkpoint found at '{}'".format(args.resume))
cudnn.benchmark = True
# Data loading code
traindir = os.path.join(args.data, 'train')
valdir = os.path.join(args.data, 'val')
train_transforms, val_transforms = preprocess_strategy(args.benchmark)
train_dataset = datasets.ImageFolder(
traindir,
train_transforms)
if args.distributed:
train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
train_sampler = None
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=args.batch_size, shuffle=(train_sampler is None),
num_workers=args.workers, pin_memory=True, sampler=train_sampler)
val_loader = torch.utils.data.DataLoader(
datasets.ImageFolder(valdir, val_transforms),
batch_size=args.batch_size, shuffle=False,
num_workers=args.workers, pin_memory=True)
if args.evaluate:
validate(val_loader, model, criterion)
return
# make directory for storing checkpoint files
if os.path.exists(args.modeldir) is not True:
os.mkdir(args.modeldir)
stats_ = stats(args.modeldir, args.start_epoch)
for epoch in range(args.start_epoch, args.epochs):
if args.distributed:
train_sampler.set_epoch(epoch)
adjust_learning_rate(optimizer, LR.lr_factor, epoch)
# train for one epoch
trainObj, top1, top5 = train(train_loader, model, criterion, optimizer, epoch)
# evaluate on validation set
valObj, prec1, prec5 = validate(val_loader, model, criterion)
# update stats
stats_._update(trainObj, top1, top5, valObj, prec1, prec5)
# remember best prec@1 and save checkpoint
is_best = prec1 > best_prec1
best_prec1 = max(prec1, best_prec1)
filename = []
if args.store_model_everyepoch:
filename.append(os.path.join(args.modeldir, 'net-epoch-%s.pth.tar' % (epoch + 1)))
else:
filename.append(os.path.join(args.modeldir, 'checkpoint.pth.tar'))
filename.append(os.path.join(args.modeldir, 'model_best.pth.tar'))
save_checkpoint({
'epoch': epoch + 1,
'arch': args.arch,
'state_dict': model.state_dict(),
'best_prec1': best_prec1,
'optimizer' : optimizer.state_dict(),
}, is_best, filename)
plot_curve(stats_, args.modeldir, True)
data = stats_
sio.savemat(os.path.join(args.modeldir,'stats.mat'), {'data':data})
def train(train_loader, model, criterion, optimizer, epoch):
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to train mode
model.train()
end = time.time()
for i, (input, target) in enumerate(train_loader):
# measure data loading time
data_time.update(time.time() - end)
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Epoch: [{0}][{1}/{2}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Data {data_time.val:.3f} ({data_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top5.val:.3f} ({top5.avg:.3f})'.format(
epoch, i, len(train_loader), batch_time=batch_time,
data_time=data_time, loss=losses, top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def validate(val_loader, model, criterion):
batch_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to evaluate mode
model.eval()
with torch.no_grad():
end = time.time()
for i, (input, target) in enumerate(val_loader):
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Test: [{0}/{1}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top1.val:.3f} ({top5.avg:.3f})'.format(
i, len(val_loader), batch_time=batch_time, loss=losses,
top1=top1, top5=top5))
print(' * Prec@1 {top1.avg:.3f} Prec@5 {top5.avg:.3f}'
.format(top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
torch.save(state, filename[0])
if is_best:
shutil.copyfile(filename[0], filename[1])
class AverageMeter(object):
"""Computes and stores the average and current value"""
def | (self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
class Learning_rate_generater(object):
"""Generates a list of learning rate for each training epoch"""
def __init__(self, method, params, total_epoch):
if method == 'step':
lr_factor, lr = self.step(params, total_epoch)
elif method == 'log':
lr_factor, lr = self.log(params, total_epoch)
else:
raise KeyError("=> undefined learning rate method '{}'" .format(method))
self.lr_factor = lr_factor
self.lr = lr
def step(self, params, total_epoch):
decrease_until = decode_params(params)
decrease_num = len(decrease_until)
base_factor = 0.1
lr_factor = []
lr = []
flag = 0
for epoch in range(total_epoch):
if flag < decrease_num:
if epoch >= decrease_until[flag]:
flag+=1
lr_factor.append(np.power(base_factor,flag))
lr.append(args.lr*lr_factor[epoch])
return lr_factor, lr
def log(self, params, total_epoch):
params = decode(params)
left_range = params[0]
right_range = params[1]
np_lr = np.logspace(left_range, right_range, total_epoch)
lr_factor = []
lr = []
for epoch in range(total_epoch):
lr.append(np_lr[epoch])
lr_factor.append(np_lr[epoch]/np_lr[0])
if lr[0] != args.lr:
args.lr = lr[0]
return lr_factor, lr
def adjust_learning_rate(optimizer, lr_factor, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
#lr = args.lr * (0.1 ** (epoch // 30))
print('the learning rate is set to {0:.5f}'.format(lr_factor[epoch]*args.lr))
for param_group in optimizer.param_groups:
param_group['lr'] = lr_factor[epoch]*args.lr
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, -1).expand_as(pred))
res = []
for k in topk:
correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
res.append(correct_k.mul_(100.0 / batch_size))
return res
if __name__ == '__main__':
main()
| __init__ | identifier_name |
main.py | import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
from torchvision import datasets
from functions import *
from imagepreprocess import *
from model_init import *
from src.representation import *
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
parser = argparse.ArgumentParser(description='PyTorch ImageNet Training')
parser.add_argument('data', metavar='DIR',
help='path to dataset')
parser.add_argument('--arch', '-a', metavar='ARCH', default='resnet18',
help='model architecture: ')
parser.add_argument('-j', '--workers', default=8, type=int, metavar='N',
help='number of data loading workers (default: 4)')
parser.add_argument('--epochs', default=100, type=int, metavar='N',
help='number of total epochs to run')
parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
help='manual epoch number (useful on restarts)')
parser.add_argument('-b', '--batch-size', default=256, type=int,
metavar='N', help='mini-batch size (default: 256)')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
metavar='LR', help='initial learning rate')
parser.add_argument('--lr-method', default='step', type=str,
help='method of learning rate')
parser.add_argument('--lr-params', default=[], dest='lr_params',
action='append', help='params of lr method')
parser.add_argument('--momentum', default=0.9, type=float, metavar='M',
help='momentum')
parser.add_argument('--weight-decay', '--wd', default=1e-4, type=float,
metavar='W', help='weight decay (default: 1e-4)')
parser.add_argument('--print-freq', '-p', default=10, type=int,
metavar='N', help='print frequency (default: 10)')
parser.add_argument('--resume', default='', type=str, metavar='PATH',
help='path to latest checkpoint (default: none)')
parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true',
help='evaluate model on validation set')
parser.add_argument('--pretrained', dest='pretrained', action='store_true',
help='use pre-trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes')
parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='gloo', type=str,
help='distributed backend')
parser.add_argument('--seed', default=None, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--modeldir', default=None, type=str,
help='director of checkpoint')
parser.add_argument('--representation', default=None, type=str,
help='define the representation method')
parser.add_argument('--num-classes', default=None, type=int,
help='define the number of classes')
parser.add_argument('--freezed-layer', default=None, type=int,
help='define the end of freezed layer')
parser.add_argument('--store-model-everyepoch', dest='store_model_everyepoch', action='store_true',
help='store checkpoint in every epoch')
parser.add_argument('--classifier-factor', default=None, type=int,
help='define the multiply factor of classifier')
parser.add_argument('--benchmark', default=None, type=str,
help='name of dataset')
best_prec1 = 0
def main():
global args, best_prec1
args = parser.parse_args()
print(args)
if args.seed is not None:
random.seed(args.seed)
torch.manual_seed(args.seed)
cudnn.deterministic = True
warnings.warn('You have chosen to seed training. '
'This will turn on the CUDNN deterministic setting, '
'which can slow down your training considerably! '
'You may see unexpected behavior when restarting '
'from checkpoints.')
if args.gpu is not None:
warnings.warn('You have chosen a specific GPU. This will completely '
'disable data parallelism.')
args.distributed = args.world_size > 1
if args.distributed:
dist.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
world_size=args.world_size)
# create model
if args.representation == 'GAvP':
representation = {'function':GAvP,
'input_dim':2048}
elif args.representation == 'MPNCOV':
representation = {'function':MPNCOV,
'iterNum':5,
'is_sqrt':True,
'is_vec':True,
'input_dim':2048,
'dimension_reduction':None if args.pretrained else 256}
elif args.representation == 'BCNN':
representation = {'function':BCNN,
'is_vec':True,
'input_dim':2048}
else:
warnings.warn('=> You did not choose a global image representation method!')
representation = None # which for original vgg or alexnet
model = get_model(args.arch,
representation,
args.num_classes,
args.freezed_layer,
pretrained=args.pretrained)
# plot network
vizNet(model, args.modeldir)
# obtain learning rate
LR = Learning_rate_generater(args.lr_method, args.lr_params, args.epochs)
if args.pretrained:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay': 0. if args.arch.startswith('vgg') else args.weight_decay})
else:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay':args.weight_decay})
optimizer = torch.optim.SGD(params_list, lr=args.lr,
momentum=args.momentum,
weight_decay=args.weight_decay)
if args.gpu is not None:
model = model.cuda(args.gpu)
elif args.distributed:
model.cuda()
model = torch.nn.parallel.DistributedDataParallel(model)
else:
if args.arch.startswith('alexnet') or args.arch.startswith('vgg'):
model.features = torch.nn.DataParallel(model.features)
model.cuda()
else:
model = torch.nn.DataParallel(model).cuda()
# define loss function (criterion) and optimizer
criterion = nn.CrossEntropyLoss().cuda(args.gpu)
# optionally resume from a checkpoint
if args.resume:
if os.path.isfile(args.resume):
print("=> loading checkpoint '{}'".format(args.resume))
checkpoint = torch.load(args.resume)
args.start_epoch = checkpoint['epoch']
best_prec1 = checkpoint['best_prec1']
model.load_state_dict(checkpoint['state_dict'])
optimizer.load_state_dict(checkpoint['optimizer'])
print("=> loaded checkpoint '{}' (epoch {})"
.format(args.resume, checkpoint['epoch']))
else:
print("=> no checkpoint found at '{}'".format(args.resume))
cudnn.benchmark = True
# Data loading code
traindir = os.path.join(args.data, 'train')
valdir = os.path.join(args.data, 'val')
train_transforms, val_transforms = preprocess_strategy(args.benchmark)
train_dataset = datasets.ImageFolder(
traindir,
train_transforms)
if args.distributed:
train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
train_sampler = None
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=args.batch_size, shuffle=(train_sampler is None),
num_workers=args.workers, pin_memory=True, sampler=train_sampler)
val_loader = torch.utils.data.DataLoader(
datasets.ImageFolder(valdir, val_transforms),
batch_size=args.batch_size, shuffle=False,
num_workers=args.workers, pin_memory=True)
if args.evaluate:
validate(val_loader, model, criterion)
return
# make directory for storing checkpoint files
if os.path.exists(args.modeldir) is not True:
os.mkdir(args.modeldir)
stats_ = stats(args.modeldir, args.start_epoch)
for epoch in range(args.start_epoch, args.epochs):
if args.distributed:
train_sampler.set_epoch(epoch)
adjust_learning_rate(optimizer, LR.lr_factor, epoch)
# train for one epoch
trainObj, top1, top5 = train(train_loader, model, criterion, optimizer, epoch)
# evaluate on validation set
valObj, prec1, prec5 = validate(val_loader, model, criterion)
# update stats
stats_._update(trainObj, top1, top5, valObj, prec1, prec5)
# remember best prec@1 and save checkpoint
is_best = prec1 > best_prec1
best_prec1 = max(prec1, best_prec1)
filename = []
if args.store_model_everyepoch:
filename.append(os.path.join(args.modeldir, 'net-epoch-%s.pth.tar' % (epoch + 1)))
else:
filename.append(os.path.join(args.modeldir, 'checkpoint.pth.tar'))
filename.append(os.path.join(args.modeldir, 'model_best.pth.tar'))
save_checkpoint({
'epoch': epoch + 1,
'arch': args.arch,
'state_dict': model.state_dict(),
'best_prec1': best_prec1,
'optimizer' : optimizer.state_dict(),
}, is_best, filename)
plot_curve(stats_, args.modeldir, True)
data = stats_
sio.savemat(os.path.join(args.modeldir,'stats.mat'), {'data':data})
def train(train_loader, model, criterion, optimizer, epoch):
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to train mode
model.train()
end = time.time()
for i, (input, target) in enumerate(train_loader):
# measure data loading time
data_time.update(time.time() - end)
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Epoch: [{0}][{1}/{2}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Data {data_time.val:.3f} ({data_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top5.val:.3f} ({top5.avg:.3f})'.format(
epoch, i, len(train_loader), batch_time=batch_time,
data_time=data_time, loss=losses, top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def validate(val_loader, model, criterion):
batch_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to evaluate mode
model.eval()
with torch.no_grad():
end = time.time()
for i, (input, target) in enumerate(val_loader):
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Test: [{0}/{1}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top1.val:.3f} ({top5.avg:.3f})'.format(
i, len(val_loader), batch_time=batch_time, loss=losses,
top1=top1, top5=top5))
print(' * Prec@1 {top1.avg:.3f} Prec@5 {top5.avg:.3f}'
.format(top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
torch.save(state, filename[0])
if is_best:
shutil.copyfile(filename[0], filename[1])
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
class Learning_rate_generater(object):
"""Generates a list of learning rate for each training epoch"""
def __init__(self, method, params, total_epoch):
if method == 'step':
lr_factor, lr = self.step(params, total_epoch)
elif method == 'log':
|
else:
raise KeyError("=> undefined learning rate method '{}'" .format(method))
self.lr_factor = lr_factor
self.lr = lr
def step(self, params, total_epoch):
decrease_until = decode_params(params)
decrease_num = len(decrease_until)
base_factor = 0.1
lr_factor = []
lr = []
flag = 0
for epoch in range(total_epoch):
if flag < decrease_num:
if epoch >= decrease_until[flag]:
flag+=1
lr_factor.append(np.power(base_factor,flag))
lr.append(args.lr*lr_factor[epoch])
return lr_factor, lr
def log(self, params, total_epoch):
params = decode(params)
left_range = params[0]
right_range = params[1]
np_lr = np.logspace(left_range, right_range, total_epoch)
lr_factor = []
lr = []
for epoch in range(total_epoch):
lr.append(np_lr[epoch])
lr_factor.append(np_lr[epoch]/np_lr[0])
if lr[0] != args.lr:
args.lr = lr[0]
return lr_factor, lr
def adjust_learning_rate(optimizer, lr_factor, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
#lr = args.lr * (0.1 ** (epoch // 30))
print('the learning rate is set to {0:.5f}'.format(lr_factor[epoch]*args.lr))
for param_group in optimizer.param_groups:
param_group['lr'] = lr_factor[epoch]*args.lr
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, -1).expand_as(pred))
res = []
for k in topk:
correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
res.append(correct_k.mul_(100.0 / batch_size))
return res
if __name__ == '__main__':
main()
| lr_factor, lr = self.log(params, total_epoch) | conditional_block |
main.py | import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
from torchvision import datasets
from functions import *
from imagepreprocess import *
from model_init import *
from src.representation import *
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
parser = argparse.ArgumentParser(description='PyTorch ImageNet Training')
parser.add_argument('data', metavar='DIR',
help='path to dataset')
parser.add_argument('--arch', '-a', metavar='ARCH', default='resnet18',
help='model architecture: ')
parser.add_argument('-j', '--workers', default=8, type=int, metavar='N',
help='number of data loading workers (default: 4)')
parser.add_argument('--epochs', default=100, type=int, metavar='N',
help='number of total epochs to run')
parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
help='manual epoch number (useful on restarts)')
parser.add_argument('-b', '--batch-size', default=256, type=int,
metavar='N', help='mini-batch size (default: 256)')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
metavar='LR', help='initial learning rate')
parser.add_argument('--lr-method', default='step', type=str,
help='method of learning rate')
parser.add_argument('--lr-params', default=[], dest='lr_params',
action='append', help='params of lr method')
parser.add_argument('--momentum', default=0.9, type=float, metavar='M',
help='momentum')
parser.add_argument('--weight-decay', '--wd', default=1e-4, type=float,
metavar='W', help='weight decay (default: 1e-4)')
parser.add_argument('--print-freq', '-p', default=10, type=int,
metavar='N', help='print frequency (default: 10)')
parser.add_argument('--resume', default='', type=str, metavar='PATH',
help='path to latest checkpoint (default: none)')
parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true',
help='evaluate model on validation set')
parser.add_argument('--pretrained', dest='pretrained', action='store_true',
help='use pre-trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes')
parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str,
help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='gloo', type=str,
help='distributed backend')
parser.add_argument('--seed', default=None, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--modeldir', default=None, type=str,
help='director of checkpoint')
parser.add_argument('--representation', default=None, type=str,
help='define the representation method')
parser.add_argument('--num-classes', default=None, type=int,
help='define the number of classes')
parser.add_argument('--freezed-layer', default=None, type=int,
help='define the end of freezed layer')
parser.add_argument('--store-model-everyepoch', dest='store_model_everyepoch', action='store_true',
help='store checkpoint in every epoch')
parser.add_argument('--classifier-factor', default=None, type=int,
help='define the multiply factor of classifier')
parser.add_argument('--benchmark', default=None, type=str,
help='name of dataset')
best_prec1 = 0
def main():
global args, best_prec1
args = parser.parse_args()
print(args)
if args.seed is not None:
random.seed(args.seed)
torch.manual_seed(args.seed)
cudnn.deterministic = True
warnings.warn('You have chosen to seed training. '
'This will turn on the CUDNN deterministic setting, '
'which can slow down your training considerably! '
'You may see unexpected behavior when restarting '
'from checkpoints.')
if args.gpu is not None:
warnings.warn('You have chosen a specific GPU. This will completely '
'disable data parallelism.')
args.distributed = args.world_size > 1
if args.distributed:
dist.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
world_size=args.world_size)
# create model
if args.representation == 'GAvP':
representation = {'function':GAvP,
'input_dim':2048}
elif args.representation == 'MPNCOV':
representation = {'function':MPNCOV,
'iterNum':5,
'is_sqrt':True,
'is_vec':True,
'input_dim':2048,
'dimension_reduction':None if args.pretrained else 256}
elif args.representation == 'BCNN':
representation = {'function':BCNN,
'is_vec':True,
'input_dim':2048}
else:
warnings.warn('=> You did not choose a global image representation method!')
representation = None # which for original vgg or alexnet
model = get_model(args.arch,
representation,
args.num_classes,
args.freezed_layer,
pretrained=args.pretrained)
# plot network
vizNet(model, args.modeldir)
# obtain learning rate
LR = Learning_rate_generater(args.lr_method, args.lr_params, args.epochs)
if args.pretrained:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay': 0. if args.arch.startswith('vgg') else args.weight_decay})
else:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay':args.weight_decay})
optimizer = torch.optim.SGD(params_list, lr=args.lr,
momentum=args.momentum,
weight_decay=args.weight_decay)
if args.gpu is not None:
model = model.cuda(args.gpu)
elif args.distributed:
model.cuda()
model = torch.nn.parallel.DistributedDataParallel(model)
else:
if args.arch.startswith('alexnet') or args.arch.startswith('vgg'):
model.features = torch.nn.DataParallel(model.features)
model.cuda()
else:
model = torch.nn.DataParallel(model).cuda()
# define loss function (criterion) and optimizer
criterion = nn.CrossEntropyLoss().cuda(args.gpu)
# optionally resume from a checkpoint
if args.resume:
if os.path.isfile(args.resume):
print("=> loading checkpoint '{}'".format(args.resume))
checkpoint = torch.load(args.resume)
args.start_epoch = checkpoint['epoch']
best_prec1 = checkpoint['best_prec1']
model.load_state_dict(checkpoint['state_dict'])
optimizer.load_state_dict(checkpoint['optimizer'])
print("=> loaded checkpoint '{}' (epoch {})"
.format(args.resume, checkpoint['epoch']))
else:
print("=> no checkpoint found at '{}'".format(args.resume))
cudnn.benchmark = True
# Data loading code
traindir = os.path.join(args.data, 'train')
valdir = os.path.join(args.data, 'val')
train_transforms, val_transforms = preprocess_strategy(args.benchmark)
train_dataset = datasets.ImageFolder(
traindir,
train_transforms)
if args.distributed:
train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
train_sampler = None
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=args.batch_size, shuffle=(train_sampler is None),
num_workers=args.workers, pin_memory=True, sampler=train_sampler)
val_loader = torch.utils.data.DataLoader(
datasets.ImageFolder(valdir, val_transforms),
batch_size=args.batch_size, shuffle=False,
num_workers=args.workers, pin_memory=True)
if args.evaluate:
validate(val_loader, model, criterion)
return
# make directory for storing checkpoint files
if os.path.exists(args.modeldir) is not True:
os.mkdir(args.modeldir)
stats_ = stats(args.modeldir, args.start_epoch)
for epoch in range(args.start_epoch, args.epochs):
if args.distributed:
train_sampler.set_epoch(epoch)
adjust_learning_rate(optimizer, LR.lr_factor, epoch)
# train for one epoch
trainObj, top1, top5 = train(train_loader, model, criterion, optimizer, epoch)
# evaluate on validation set
valObj, prec1, prec5 = validate(val_loader, model, criterion)
# update stats
stats_._update(trainObj, top1, top5, valObj, prec1, prec5)
# remember best prec@1 and save checkpoint
is_best = prec1 > best_prec1
best_prec1 = max(prec1, best_prec1)
filename = []
if args.store_model_everyepoch:
filename.append(os.path.join(args.modeldir, 'net-epoch-%s.pth.tar' % (epoch + 1)))
else:
filename.append(os.path.join(args.modeldir, 'checkpoint.pth.tar'))
filename.append(os.path.join(args.modeldir, 'model_best.pth.tar'))
save_checkpoint({
'epoch': epoch + 1,
'arch': args.arch,
'state_dict': model.state_dict(),
'best_prec1': best_prec1,
'optimizer' : optimizer.state_dict(),
}, is_best, filename)
plot_curve(stats_, args.modeldir, True)
data = stats_
sio.savemat(os.path.join(args.modeldir,'stats.mat'), {'data':data})
def train(train_loader, model, criterion, optimizer, epoch):
|
def validate(val_loader, model, criterion):
batch_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to evaluate mode
model.eval()
with torch.no_grad():
end = time.time()
for i, (input, target) in enumerate(val_loader):
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Test: [{0}/{1}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top1.val:.3f} ({top5.avg:.3f})'.format(
i, len(val_loader), batch_time=batch_time, loss=losses,
top1=top1, top5=top5))
print(' * Prec@1 {top1.avg:.3f} Prec@5 {top5.avg:.3f}'
.format(top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
torch.save(state, filename[0])
if is_best:
shutil.copyfile(filename[0], filename[1])
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
class Learning_rate_generater(object):
"""Generates a list of learning rate for each training epoch"""
def __init__(self, method, params, total_epoch):
if method == 'step':
lr_factor, lr = self.step(params, total_epoch)
elif method == 'log':
lr_factor, lr = self.log(params, total_epoch)
else:
raise KeyError("=> undefined learning rate method '{}'" .format(method))
self.lr_factor = lr_factor
self.lr = lr
def step(self, params, total_epoch):
decrease_until = decode_params(params)
decrease_num = len(decrease_until)
base_factor = 0.1
lr_factor = []
lr = []
flag = 0
for epoch in range(total_epoch):
if flag < decrease_num:
if epoch >= decrease_until[flag]:
flag+=1
lr_factor.append(np.power(base_factor,flag))
lr.append(args.lr*lr_factor[epoch])
return lr_factor, lr
def log(self, params, total_epoch):
params = decode(params)
left_range = params[0]
right_range = params[1]
np_lr = np.logspace(left_range, right_range, total_epoch)
lr_factor = []
lr = []
for epoch in range(total_epoch):
lr.append(np_lr[epoch])
lr_factor.append(np_lr[epoch]/np_lr[0])
if lr[0] != args.lr:
args.lr = lr[0]
return lr_factor, lr
def adjust_learning_rate(optimizer, lr_factor, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
#lr = args.lr * (0.1 ** (epoch // 30))
print('the learning rate is set to {0:.5f}'.format(lr_factor[epoch]*args.lr))
for param_group in optimizer.param_groups:
param_group['lr'] = lr_factor[epoch]*args.lr
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, -1).expand_as(pred))
res = []
for k in topk:
correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
res.append(correct_k.mul_(100.0 / batch_size))
return res
if __name__ == '__main__':
main()
| batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to train mode
model.train()
end = time.time()
for i, (input, target) in enumerate(train_loader):
# measure data loading time
data_time.update(time.time() - end)
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Epoch: [{0}][{1}/{2}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Data {data_time.val:.3f} ({data_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top5.val:.3f} ({top5.avg:.3f})'.format(
epoch, i, len(train_loader), batch_time=batch_time,
data_time=data_time, loss=losses, top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg | identifier_body |
main.py | import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
from torchvision import datasets
from functions import *
from imagepreprocess import *
from model_init import *
from src.representation import *
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
parser = argparse.ArgumentParser(description='PyTorch ImageNet Training')
parser.add_argument('data', metavar='DIR',
help='path to dataset')
parser.add_argument('--arch', '-a', metavar='ARCH', default='resnet18',
help='model architecture: ')
parser.add_argument('-j', '--workers', default=8, type=int, metavar='N',
help='number of data loading workers (default: 4)')
parser.add_argument('--epochs', default=100, type=int, metavar='N',
help='number of total epochs to run')
parser.add_argument('--start-epoch', default=0, type=int, metavar='N',
help='manual epoch number (useful on restarts)')
parser.add_argument('-b', '--batch-size', default=256, type=int,
metavar='N', help='mini-batch size (default: 256)')
parser.add_argument('--lr', '--learning-rate', default=0.1, type=float,
metavar='LR', help='initial learning rate')
parser.add_argument('--lr-method', default='step', type=str,
help='method of learning rate')
parser.add_argument('--lr-params', default=[], dest='lr_params',
action='append', help='params of lr method')
parser.add_argument('--momentum', default=0.9, type=float, metavar='M',
help='momentum')
parser.add_argument('--weight-decay', '--wd', default=1e-4, type=float,
metavar='W', help='weight decay (default: 1e-4)')
parser.add_argument('--print-freq', '-p', default=10, type=int,
metavar='N', help='print frequency (default: 10)')
parser.add_argument('--resume', default='', type=str, metavar='PATH',
help='path to latest checkpoint (default: none)')
parser.add_argument('-e', '--evaluate', dest='evaluate', action='store_true',
help='evaluate model on validation set')
parser.add_argument('--pretrained', dest='pretrained', action='store_true',
help='use pre-trained model')
parser.add_argument('--world-size', default=1, type=int,
help='number of distributed processes') | help='url used to set up distributed training')
parser.add_argument('--dist-backend', default='gloo', type=str,
help='distributed backend')
parser.add_argument('--seed', default=None, type=int,
help='seed for initializing training. ')
parser.add_argument('--gpu', default=None, type=int,
help='GPU id to use.')
parser.add_argument('--modeldir', default=None, type=str,
help='director of checkpoint')
parser.add_argument('--representation', default=None, type=str,
help='define the representation method')
parser.add_argument('--num-classes', default=None, type=int,
help='define the number of classes')
parser.add_argument('--freezed-layer', default=None, type=int,
help='define the end of freezed layer')
parser.add_argument('--store-model-everyepoch', dest='store_model_everyepoch', action='store_true',
help='store checkpoint in every epoch')
parser.add_argument('--classifier-factor', default=None, type=int,
help='define the multiply factor of classifier')
parser.add_argument('--benchmark', default=None, type=str,
help='name of dataset')
best_prec1 = 0
def main():
global args, best_prec1
args = parser.parse_args()
print(args)
if args.seed is not None:
random.seed(args.seed)
torch.manual_seed(args.seed)
cudnn.deterministic = True
warnings.warn('You have chosen to seed training. '
'This will turn on the CUDNN deterministic setting, '
'which can slow down your training considerably! '
'You may see unexpected behavior when restarting '
'from checkpoints.')
if args.gpu is not None:
warnings.warn('You have chosen a specific GPU. This will completely '
'disable data parallelism.')
args.distributed = args.world_size > 1
if args.distributed:
dist.init_process_group(backend=args.dist_backend, init_method=args.dist_url,
world_size=args.world_size)
# create model
if args.representation == 'GAvP':
representation = {'function':GAvP,
'input_dim':2048}
elif args.representation == 'MPNCOV':
representation = {'function':MPNCOV,
'iterNum':5,
'is_sqrt':True,
'is_vec':True,
'input_dim':2048,
'dimension_reduction':None if args.pretrained else 256}
elif args.representation == 'BCNN':
representation = {'function':BCNN,
'is_vec':True,
'input_dim':2048}
else:
warnings.warn('=> You did not choose a global image representation method!')
representation = None # which for original vgg or alexnet
model = get_model(args.arch,
representation,
args.num_classes,
args.freezed_layer,
pretrained=args.pretrained)
# plot network
vizNet(model, args.modeldir)
# obtain learning rate
LR = Learning_rate_generater(args.lr_method, args.lr_params, args.epochs)
if args.pretrained:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay': 0. if args.arch.startswith('vgg') else args.weight_decay})
else:
params_list = [{'params': model.features.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay},]
params_list.append({'params': model.representation.parameters(), 'lr': args.lr,
'weight_decay': args.weight_decay})
params_list.append({'params': model.classifier.parameters(),
'lr': args.lr*args.classifier_factor,
'weight_decay':args.weight_decay})
optimizer = torch.optim.SGD(params_list, lr=args.lr,
momentum=args.momentum,
weight_decay=args.weight_decay)
if args.gpu is not None:
model = model.cuda(args.gpu)
elif args.distributed:
model.cuda()
model = torch.nn.parallel.DistributedDataParallel(model)
else:
if args.arch.startswith('alexnet') or args.arch.startswith('vgg'):
model.features = torch.nn.DataParallel(model.features)
model.cuda()
else:
model = torch.nn.DataParallel(model).cuda()
# define loss function (criterion) and optimizer
criterion = nn.CrossEntropyLoss().cuda(args.gpu)
# optionally resume from a checkpoint
if args.resume:
if os.path.isfile(args.resume):
print("=> loading checkpoint '{}'".format(args.resume))
checkpoint = torch.load(args.resume)
args.start_epoch = checkpoint['epoch']
best_prec1 = checkpoint['best_prec1']
model.load_state_dict(checkpoint['state_dict'])
optimizer.load_state_dict(checkpoint['optimizer'])
print("=> loaded checkpoint '{}' (epoch {})"
.format(args.resume, checkpoint['epoch']))
else:
print("=> no checkpoint found at '{}'".format(args.resume))
cudnn.benchmark = True
# Data loading code
traindir = os.path.join(args.data, 'train')
valdir = os.path.join(args.data, 'val')
train_transforms, val_transforms = preprocess_strategy(args.benchmark)
train_dataset = datasets.ImageFolder(
traindir,
train_transforms)
if args.distributed:
train_sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
else:
train_sampler = None
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=args.batch_size, shuffle=(train_sampler is None),
num_workers=args.workers, pin_memory=True, sampler=train_sampler)
val_loader = torch.utils.data.DataLoader(
datasets.ImageFolder(valdir, val_transforms),
batch_size=args.batch_size, shuffle=False,
num_workers=args.workers, pin_memory=True)
if args.evaluate:
validate(val_loader, model, criterion)
return
# make directory for storing checkpoint files
if os.path.exists(args.modeldir) is not True:
os.mkdir(args.modeldir)
stats_ = stats(args.modeldir, args.start_epoch)
for epoch in range(args.start_epoch, args.epochs):
if args.distributed:
train_sampler.set_epoch(epoch)
adjust_learning_rate(optimizer, LR.lr_factor, epoch)
# train for one epoch
trainObj, top1, top5 = train(train_loader, model, criterion, optimizer, epoch)
# evaluate on validation set
valObj, prec1, prec5 = validate(val_loader, model, criterion)
# update stats
stats_._update(trainObj, top1, top5, valObj, prec1, prec5)
# remember best prec@1 and save checkpoint
is_best = prec1 > best_prec1
best_prec1 = max(prec1, best_prec1)
filename = []
if args.store_model_everyepoch:
filename.append(os.path.join(args.modeldir, 'net-epoch-%s.pth.tar' % (epoch + 1)))
else:
filename.append(os.path.join(args.modeldir, 'checkpoint.pth.tar'))
filename.append(os.path.join(args.modeldir, 'model_best.pth.tar'))
save_checkpoint({
'epoch': epoch + 1,
'arch': args.arch,
'state_dict': model.state_dict(),
'best_prec1': best_prec1,
'optimizer' : optimizer.state_dict(),
}, is_best, filename)
plot_curve(stats_, args.modeldir, True)
data = stats_
sio.savemat(os.path.join(args.modeldir,'stats.mat'), {'data':data})
def train(train_loader, model, criterion, optimizer, epoch):
batch_time = AverageMeter()
data_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to train mode
model.train()
end = time.time()
for i, (input, target) in enumerate(train_loader):
# measure data loading time
data_time.update(time.time() - end)
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# compute gradient and do SGD step
optimizer.zero_grad()
loss.backward()
optimizer.step()
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Epoch: [{0}][{1}/{2}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Data {data_time.val:.3f} ({data_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top5.val:.3f} ({top5.avg:.3f})'.format(
epoch, i, len(train_loader), batch_time=batch_time,
data_time=data_time, loss=losses, top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def validate(val_loader, model, criterion):
batch_time = AverageMeter()
losses = AverageMeter()
top1 = AverageMeter()
top5 = AverageMeter()
# switch to evaluate mode
model.eval()
with torch.no_grad():
end = time.time()
for i, (input, target) in enumerate(val_loader):
if args.gpu is not None:
input = input.cuda(args.gpu, non_blocking=True)
target = target.cuda(args.gpu, non_blocking=True)
# compute output
output = model(input)
loss = criterion(output, target)
# measure accuracy and record loss
prec1, prec5 = accuracy(output, target, topk=(1, 5))
losses.update(loss.item(), input.size(0))
top1.update(prec1[0], input.size(0))
top5.update(prec5[0], input.size(0))
# measure elapsed time
batch_time.update(time.time() - end)
end = time.time()
if i % args.print_freq == 0:
print('Test: [{0}/{1}]\t'
'Time {batch_time.val:.3f} ({batch_time.avg:.3f})\t'
'Loss {loss.val:.4f} ({loss.avg:.4f})\t'
'Prec@1 {top1.val:.3f} ({top1.avg:.3f})\t'
'Prec@5 {top1.val:.3f} ({top5.avg:.3f})'.format(
i, len(val_loader), batch_time=batch_time, loss=losses,
top1=top1, top5=top5))
print(' * Prec@1 {top1.avg:.3f} Prec@5 {top5.avg:.3f}'
.format(top1=top1, top5=top5))
return losses.avg, top1.avg, top5.avg
def save_checkpoint(state, is_best, filename='checkpoint.pth.tar'):
torch.save(state, filename[0])
if is_best:
shutil.copyfile(filename[0], filename[1])
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.count = 0
def update(self, val, n=1):
self.val = val
self.sum += val * n
self.count += n
self.avg = self.sum / self.count
class Learning_rate_generater(object):
"""Generates a list of learning rate for each training epoch"""
def __init__(self, method, params, total_epoch):
if method == 'step':
lr_factor, lr = self.step(params, total_epoch)
elif method == 'log':
lr_factor, lr = self.log(params, total_epoch)
else:
raise KeyError("=> undefined learning rate method '{}'" .format(method))
self.lr_factor = lr_factor
self.lr = lr
def step(self, params, total_epoch):
decrease_until = decode_params(params)
decrease_num = len(decrease_until)
base_factor = 0.1
lr_factor = []
lr = []
flag = 0
for epoch in range(total_epoch):
if flag < decrease_num:
if epoch >= decrease_until[flag]:
flag+=1
lr_factor.append(np.power(base_factor,flag))
lr.append(args.lr*lr_factor[epoch])
return lr_factor, lr
def log(self, params, total_epoch):
params = decode(params)
left_range = params[0]
right_range = params[1]
np_lr = np.logspace(left_range, right_range, total_epoch)
lr_factor = []
lr = []
for epoch in range(total_epoch):
lr.append(np_lr[epoch])
lr_factor.append(np_lr[epoch]/np_lr[0])
if lr[0] != args.lr:
args.lr = lr[0]
return lr_factor, lr
def adjust_learning_rate(optimizer, lr_factor, epoch):
"""Sets the learning rate to the initial LR decayed by 10 every 30 epochs"""
#lr = args.lr * (0.1 ** (epoch // 30))
print('the learning rate is set to {0:.5f}'.format(lr_factor[epoch]*args.lr))
for param_group in optimizer.param_groups:
param_group['lr'] = lr_factor[epoch]*args.lr
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
with torch.no_grad():
maxk = max(topk)
batch_size = target.size(0)
_, pred = output.topk(maxk, 1, True, True)
pred = pred.t()
correct = pred.eq(target.view(1, -1).expand_as(pred))
res = []
for k in topk:
correct_k = correct[:k].view(-1).float().sum(0, keepdim=True)
res.append(correct_k.mul_(100.0 / batch_size))
return res
if __name__ == '__main__':
main() | parser.add_argument('--dist-url', default='tcp://224.66.41.62:23456', type=str, | random_line_split |
shlex.go | /*
Copyright 2012 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package shlex
/*
Package shlex implements a simple lexer which splits input in to tokens using
shell-style rules for quoting and commenting.
*/
import (
"bufio"
"errors"
"fmt"
"io"
"strings"
)
/*
A TokenType is a top-level token; a word, space, comment, unknown.
*/
type TokenType int
/*
A RuneTokenType is the type of a UTF-8 character; a character, quote, space, escape.
*/
type RuneTokenType int
type lexerState int
type Token struct {
tokenType TokenType
value string
}
/*
Two tokens are equal if both their types and values are equal. A nil token can
never equal another token.
*/
func (a *Token) Equal(b *Token) bool {
if a == nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE string = "\""
RUNE_NONESCAPING_QUOTE string = "'"
RUNE_ESCAPE = "\\"
RUNE_COMMENT = "#"
RUNETOKEN_UNKNOWN RuneTokenType = 0
RUNETOKEN_CHAR RuneTokenType = 1
RUNETOKEN_SPACE RuneTokenType = 2
RUNETOKEN_ESCAPING_QUOTE RuneTokenType = 3
RUNETOKEN_NONESCAPING_QUOTE RuneTokenType = 4
RUNETOKEN_ESCAPE RuneTokenType = 5
RUNETOKEN_COMMENT RuneTokenType = 6
RUNETOKEN_EOF RuneTokenType = 7
TOKEN_UNKNOWN TokenType = 0
TOKEN_WORD TokenType = 1
TOKEN_SPACE TokenType = 2
TOKEN_COMMENT TokenType = 3
STATE_START lexerState = 0
STATE_INWORD lexerState = 1
STATE_ESCAPING lexerState = 2
STATE_ESCAPING_QUOTED lexerState = 3
STATE_QUOTED_ESCAPING lexerState = 4
STATE_QUOTED lexerState = 5
STATE_COMMENT lexerState = 6
INITIAL_TOKEN_CAPACITY int = 100
)
/*
A type for classifying characters. This allows for different sorts of
classifiers - those accepting extended non-ascii chars, or strict posix
compatibility, for example.
*/
type TokenClassifier struct {
typeMap map[int32]RuneTokenType
}
func addRuneClass(typeMap *map[int32]RuneTokenType, runes string, tokenType RuneTokenType) {
for _, rune := range runes {
(*typeMap)[int32(rune)] = tokenType
}
}
/*
Create a new classifier for basic ASCII characters.
*/
func NewDefaultClassifier() *TokenClassifier |
func (classifier *TokenClassifier) ClassifyRune(rune int32) RuneTokenType {
return classifier.typeMap[rune]
}
/*
A type for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func NewLexer(r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: tokenizer}
return lexer, nil
}
/*
Return the next word, and an error value. If there are no more words, the error
will be io.EOF.
*/
func (l *Lexer) NextWord() (string, error) {
var token *Token
var err error
for {
token, err = l.tokenizer.NextToken()
if err != nil {
return "", err
}
switch token.tokenType {
case TOKEN_WORD:
{
return token.value, nil
}
case TOKEN_COMMENT:
{
// skip comments
}
default:
{
panic(fmt.Sprintf("Unknown token type: %v", token.tokenType))
}
}
}
return "", io.EOF
}
/*
A type for turning an input stream in to a sequence of typed tokens.
*/
type Tokenizer struct {
input *bufio.Reader
classifier *TokenClassifier
}
/*
Create a new tokenizer.
*/
func NewTokenizer(r io.Reader) (*Tokenizer, error) {
input := bufio.NewReader(r)
classifier := NewDefaultClassifier()
tokenizer := &Tokenizer{
input: input,
classifier: classifier}
return tokenizer, nil
}
/*
Scan the stream for the next token.
This uses an internal state machine. It will panic if it encounters a character
which it does not know how to handle.
*/
func (t *Tokenizer) scanStream() (*Token, error) {
state := STATE_START
var tokenType TokenType
value := make([]int32, 0, INITIAL_TOKEN_CAPACITY)
var (
nextRune int32
nextRuneType RuneTokenType
err error
)
SCAN:
for {
nextRune, _, err = t.input.ReadRune()
nextRuneType = t.classifier.ClassifyRune(nextRune)
if err != nil {
if err == io.EOF {
nextRuneType = RUNETOKEN_EOF
err = nil
} else {
return nil, err
}
}
switch state {
case STATE_START: // no runes read yet
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
return nil, io.EOF
}
case RUNETOKEN_CHAR:
{
tokenType = TOKEN_WORD
value = append(value, nextRune)
state = STATE_INWORD
}
case RUNETOKEN_SPACE:
{
}
case RUNETOKEN_ESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
tokenType = TOKEN_WORD
state = STATE_ESCAPING
}
case RUNETOKEN_COMMENT:
{
tokenType = TOKEN_COMMENT
state = STATE_COMMENT
}
default:
{
return nil, errors.New(fmt.Sprintf("Unknown rune: %v", nextRune))
}
}
}
case STATE_INWORD: // in a regular word
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
t.input.UnreadRune()
break SCAN
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING: // the next rune after an escape character
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_INWORD
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING_QUOTED: // the next rune after an escape character, in double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_QUOTED_ESCAPING
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED_ESCAPING: // in escaping double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_INWORD
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING_QUOTED
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED: // in non-escaping single quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_INWORD
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_COMMENT:
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT, RUNETOKEN_NONESCAPING_QUOTE:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
if nextRune == '\n' {
state = STATE_START
break SCAN
} else {
value = append(value, nextRune)
}
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
default:
{
panic(fmt.Sprintf("Unexpected state: %v", state))
}
}
}
token := &Token{
tokenType: tokenType,
value: string(value)}
return token, err
}
/*
Return the next token in the stream, and an error value. If there are no more
tokens available, the error value will be io.EOF.
*/
func (t *Tokenizer) NextToken() (*Token, error) {
return t.scanStream()
}
/*
Split a string in to a slice of strings, based upon shell-style rules for
quoting, escaping, and spaces.
*/
func Split(s string) ([]string, error) {
l, err := NewLexer(strings.NewReader(s))
if err != nil {
return nil, err
}
subStrings := []string{}
for {
word, err := l.NextWord()
if err != nil {
if err == io.EOF {
return subStrings, nil
}
return subStrings, err
}
subStrings = append(subStrings, word)
}
return subStrings, nil
}
| {
typeMap := map[int32]RuneTokenType{}
addRuneClass(&typeMap, RUNE_CHAR, RUNETOKEN_CHAR)
addRuneClass(&typeMap, RUNE_SPACE, RUNETOKEN_SPACE)
addRuneClass(&typeMap, RUNE_ESCAPING_QUOTE, RUNETOKEN_ESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_NONESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_ESCAPE, RUNETOKEN_ESCAPE)
addRuneClass(&typeMap, RUNE_COMMENT, RUNETOKEN_COMMENT)
return &TokenClassifier{
typeMap: typeMap}
} | identifier_body |
shlex.go | /*
Copyright 2012 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package shlex
/*
Package shlex implements a simple lexer which splits input in to tokens using
shell-style rules for quoting and commenting.
*/
import (
"bufio"
"errors"
"fmt"
"io"
"strings"
)
/*
A TokenType is a top-level token; a word, space, comment, unknown.
*/
type TokenType int
/*
A RuneTokenType is the type of a UTF-8 character; a character, quote, space, escape.
*/
type RuneTokenType int
type lexerState int
type Token struct {
tokenType TokenType
value string
}
/*
Two tokens are equal if both their types and values are equal. A nil token can | never equal another token.
*/
func (a *Token) Equal(b *Token) bool {
if a == nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE string = "\""
RUNE_NONESCAPING_QUOTE string = "'"
RUNE_ESCAPE = "\\"
RUNE_COMMENT = "#"
RUNETOKEN_UNKNOWN RuneTokenType = 0
RUNETOKEN_CHAR RuneTokenType = 1
RUNETOKEN_SPACE RuneTokenType = 2
RUNETOKEN_ESCAPING_QUOTE RuneTokenType = 3
RUNETOKEN_NONESCAPING_QUOTE RuneTokenType = 4
RUNETOKEN_ESCAPE RuneTokenType = 5
RUNETOKEN_COMMENT RuneTokenType = 6
RUNETOKEN_EOF RuneTokenType = 7
TOKEN_UNKNOWN TokenType = 0
TOKEN_WORD TokenType = 1
TOKEN_SPACE TokenType = 2
TOKEN_COMMENT TokenType = 3
STATE_START lexerState = 0
STATE_INWORD lexerState = 1
STATE_ESCAPING lexerState = 2
STATE_ESCAPING_QUOTED lexerState = 3
STATE_QUOTED_ESCAPING lexerState = 4
STATE_QUOTED lexerState = 5
STATE_COMMENT lexerState = 6
INITIAL_TOKEN_CAPACITY int = 100
)
/*
A type for classifying characters. This allows for different sorts of
classifiers - those accepting extended non-ascii chars, or strict posix
compatibility, for example.
*/
type TokenClassifier struct {
typeMap map[int32]RuneTokenType
}
func addRuneClass(typeMap *map[int32]RuneTokenType, runes string, tokenType RuneTokenType) {
for _, rune := range runes {
(*typeMap)[int32(rune)] = tokenType
}
}
/*
Create a new classifier for basic ASCII characters.
*/
func NewDefaultClassifier() *TokenClassifier {
typeMap := map[int32]RuneTokenType{}
addRuneClass(&typeMap, RUNE_CHAR, RUNETOKEN_CHAR)
addRuneClass(&typeMap, RUNE_SPACE, RUNETOKEN_SPACE)
addRuneClass(&typeMap, RUNE_ESCAPING_QUOTE, RUNETOKEN_ESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_NONESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_ESCAPE, RUNETOKEN_ESCAPE)
addRuneClass(&typeMap, RUNE_COMMENT, RUNETOKEN_COMMENT)
return &TokenClassifier{
typeMap: typeMap}
}
func (classifier *TokenClassifier) ClassifyRune(rune int32) RuneTokenType {
return classifier.typeMap[rune]
}
/*
A type for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func NewLexer(r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: tokenizer}
return lexer, nil
}
/*
Return the next word, and an error value. If there are no more words, the error
will be io.EOF.
*/
func (l *Lexer) NextWord() (string, error) {
var token *Token
var err error
for {
token, err = l.tokenizer.NextToken()
if err != nil {
return "", err
}
switch token.tokenType {
case TOKEN_WORD:
{
return token.value, nil
}
case TOKEN_COMMENT:
{
// skip comments
}
default:
{
panic(fmt.Sprintf("Unknown token type: %v", token.tokenType))
}
}
}
return "", io.EOF
}
/*
A type for turning an input stream in to a sequence of typed tokens.
*/
type Tokenizer struct {
input *bufio.Reader
classifier *TokenClassifier
}
/*
Create a new tokenizer.
*/
func NewTokenizer(r io.Reader) (*Tokenizer, error) {
input := bufio.NewReader(r)
classifier := NewDefaultClassifier()
tokenizer := &Tokenizer{
input: input,
classifier: classifier}
return tokenizer, nil
}
/*
Scan the stream for the next token.
This uses an internal state machine. It will panic if it encounters a character
which it does not know how to handle.
*/
func (t *Tokenizer) scanStream() (*Token, error) {
state := STATE_START
var tokenType TokenType
value := make([]int32, 0, INITIAL_TOKEN_CAPACITY)
var (
nextRune int32
nextRuneType RuneTokenType
err error
)
SCAN:
for {
nextRune, _, err = t.input.ReadRune()
nextRuneType = t.classifier.ClassifyRune(nextRune)
if err != nil {
if err == io.EOF {
nextRuneType = RUNETOKEN_EOF
err = nil
} else {
return nil, err
}
}
switch state {
case STATE_START: // no runes read yet
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
return nil, io.EOF
}
case RUNETOKEN_CHAR:
{
tokenType = TOKEN_WORD
value = append(value, nextRune)
state = STATE_INWORD
}
case RUNETOKEN_SPACE:
{
}
case RUNETOKEN_ESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
tokenType = TOKEN_WORD
state = STATE_ESCAPING
}
case RUNETOKEN_COMMENT:
{
tokenType = TOKEN_COMMENT
state = STATE_COMMENT
}
default:
{
return nil, errors.New(fmt.Sprintf("Unknown rune: %v", nextRune))
}
}
}
case STATE_INWORD: // in a regular word
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
t.input.UnreadRune()
break SCAN
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING: // the next rune after an escape character
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_INWORD
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING_QUOTED: // the next rune after an escape character, in double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_QUOTED_ESCAPING
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED_ESCAPING: // in escaping double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_INWORD
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING_QUOTED
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED: // in non-escaping single quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_INWORD
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_COMMENT:
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT, RUNETOKEN_NONESCAPING_QUOTE:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
if nextRune == '\n' {
state = STATE_START
break SCAN
} else {
value = append(value, nextRune)
}
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
default:
{
panic(fmt.Sprintf("Unexpected state: %v", state))
}
}
}
token := &Token{
tokenType: tokenType,
value: string(value)}
return token, err
}
/*
Return the next token in the stream, and an error value. If there are no more
tokens available, the error value will be io.EOF.
*/
func (t *Tokenizer) NextToken() (*Token, error) {
return t.scanStream()
}
/*
Split a string in to a slice of strings, based upon shell-style rules for
quoting, escaping, and spaces.
*/
func Split(s string) ([]string, error) {
l, err := NewLexer(strings.NewReader(s))
if err != nil {
return nil, err
}
subStrings := []string{}
for {
word, err := l.NextWord()
if err != nil {
if err == io.EOF {
return subStrings, nil
}
return subStrings, err
}
subStrings = append(subStrings, word)
}
return subStrings, nil
} | random_line_split | |
shlex.go | /*
Copyright 2012 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package shlex
/*
Package shlex implements a simple lexer which splits input in to tokens using
shell-style rules for quoting and commenting.
*/
import (
"bufio"
"errors"
"fmt"
"io"
"strings"
)
/*
A TokenType is a top-level token; a word, space, comment, unknown.
*/
type TokenType int
/*
A RuneTokenType is the type of a UTF-8 character; a character, quote, space, escape.
*/
type RuneTokenType int
type lexerState int
type Token struct {
tokenType TokenType
value string
}
/*
Two tokens are equal if both their types and values are equal. A nil token can
never equal another token.
*/
func (a *Token) Equal(b *Token) bool {
if a == nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE string = "\""
RUNE_NONESCAPING_QUOTE string = "'"
RUNE_ESCAPE = "\\"
RUNE_COMMENT = "#"
RUNETOKEN_UNKNOWN RuneTokenType = 0
RUNETOKEN_CHAR RuneTokenType = 1
RUNETOKEN_SPACE RuneTokenType = 2
RUNETOKEN_ESCAPING_QUOTE RuneTokenType = 3
RUNETOKEN_NONESCAPING_QUOTE RuneTokenType = 4
RUNETOKEN_ESCAPE RuneTokenType = 5
RUNETOKEN_COMMENT RuneTokenType = 6
RUNETOKEN_EOF RuneTokenType = 7
TOKEN_UNKNOWN TokenType = 0
TOKEN_WORD TokenType = 1
TOKEN_SPACE TokenType = 2
TOKEN_COMMENT TokenType = 3
STATE_START lexerState = 0
STATE_INWORD lexerState = 1
STATE_ESCAPING lexerState = 2
STATE_ESCAPING_QUOTED lexerState = 3
STATE_QUOTED_ESCAPING lexerState = 4
STATE_QUOTED lexerState = 5
STATE_COMMENT lexerState = 6
INITIAL_TOKEN_CAPACITY int = 100
)
/*
A type for classifying characters. This allows for different sorts of
classifiers - those accepting extended non-ascii chars, or strict posix
compatibility, for example.
*/
type TokenClassifier struct {
typeMap map[int32]RuneTokenType
}
func addRuneClass(typeMap *map[int32]RuneTokenType, runes string, tokenType RuneTokenType) {
for _, rune := range runes {
(*typeMap)[int32(rune)] = tokenType
}
}
/*
Create a new classifier for basic ASCII characters.
*/
func NewDefaultClassifier() *TokenClassifier {
typeMap := map[int32]RuneTokenType{}
addRuneClass(&typeMap, RUNE_CHAR, RUNETOKEN_CHAR)
addRuneClass(&typeMap, RUNE_SPACE, RUNETOKEN_SPACE)
addRuneClass(&typeMap, RUNE_ESCAPING_QUOTE, RUNETOKEN_ESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_NONESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_ESCAPE, RUNETOKEN_ESCAPE)
addRuneClass(&typeMap, RUNE_COMMENT, RUNETOKEN_COMMENT)
return &TokenClassifier{
typeMap: typeMap}
}
func (classifier *TokenClassifier) ClassifyRune(rune int32) RuneTokenType {
return classifier.typeMap[rune]
}
/*
A type for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func | (r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: tokenizer}
return lexer, nil
}
/*
Return the next word, and an error value. If there are no more words, the error
will be io.EOF.
*/
func (l *Lexer) NextWord() (string, error) {
var token *Token
var err error
for {
token, err = l.tokenizer.NextToken()
if err != nil {
return "", err
}
switch token.tokenType {
case TOKEN_WORD:
{
return token.value, nil
}
case TOKEN_COMMENT:
{
// skip comments
}
default:
{
panic(fmt.Sprintf("Unknown token type: %v", token.tokenType))
}
}
}
return "", io.EOF
}
/*
A type for turning an input stream in to a sequence of typed tokens.
*/
type Tokenizer struct {
input *bufio.Reader
classifier *TokenClassifier
}
/*
Create a new tokenizer.
*/
func NewTokenizer(r io.Reader) (*Tokenizer, error) {
input := bufio.NewReader(r)
classifier := NewDefaultClassifier()
tokenizer := &Tokenizer{
input: input,
classifier: classifier}
return tokenizer, nil
}
/*
Scan the stream for the next token.
This uses an internal state machine. It will panic if it encounters a character
which it does not know how to handle.
*/
func (t *Tokenizer) scanStream() (*Token, error) {
state := STATE_START
var tokenType TokenType
value := make([]int32, 0, INITIAL_TOKEN_CAPACITY)
var (
nextRune int32
nextRuneType RuneTokenType
err error
)
SCAN:
for {
nextRune, _, err = t.input.ReadRune()
nextRuneType = t.classifier.ClassifyRune(nextRune)
if err != nil {
if err == io.EOF {
nextRuneType = RUNETOKEN_EOF
err = nil
} else {
return nil, err
}
}
switch state {
case STATE_START: // no runes read yet
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
return nil, io.EOF
}
case RUNETOKEN_CHAR:
{
tokenType = TOKEN_WORD
value = append(value, nextRune)
state = STATE_INWORD
}
case RUNETOKEN_SPACE:
{
}
case RUNETOKEN_ESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
tokenType = TOKEN_WORD
state = STATE_ESCAPING
}
case RUNETOKEN_COMMENT:
{
tokenType = TOKEN_COMMENT
state = STATE_COMMENT
}
default:
{
return nil, errors.New(fmt.Sprintf("Unknown rune: %v", nextRune))
}
}
}
case STATE_INWORD: // in a regular word
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
t.input.UnreadRune()
break SCAN
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING: // the next rune after an escape character
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_INWORD
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING_QUOTED: // the next rune after an escape character, in double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_QUOTED_ESCAPING
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED_ESCAPING: // in escaping double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_INWORD
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING_QUOTED
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED: // in non-escaping single quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_INWORD
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_COMMENT:
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT, RUNETOKEN_NONESCAPING_QUOTE:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
if nextRune == '\n' {
state = STATE_START
break SCAN
} else {
value = append(value, nextRune)
}
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
default:
{
panic(fmt.Sprintf("Unexpected state: %v", state))
}
}
}
token := &Token{
tokenType: tokenType,
value: string(value)}
return token, err
}
/*
Return the next token in the stream, and an error value. If there are no more
tokens available, the error value will be io.EOF.
*/
func (t *Tokenizer) NextToken() (*Token, error) {
return t.scanStream()
}
/*
Split a string in to a slice of strings, based upon shell-style rules for
quoting, escaping, and spaces.
*/
func Split(s string) ([]string, error) {
l, err := NewLexer(strings.NewReader(s))
if err != nil {
return nil, err
}
subStrings := []string{}
for {
word, err := l.NextWord()
if err != nil {
if err == io.EOF {
return subStrings, nil
}
return subStrings, err
}
subStrings = append(subStrings, word)
}
return subStrings, nil
}
| NewLexer | identifier_name |
shlex.go | /*
Copyright 2012 Google Inc. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
*/
package shlex
/*
Package shlex implements a simple lexer which splits input in to tokens using
shell-style rules for quoting and commenting.
*/
import (
"bufio"
"errors"
"fmt"
"io"
"strings"
)
/*
A TokenType is a top-level token; a word, space, comment, unknown.
*/
type TokenType int
/*
A RuneTokenType is the type of a UTF-8 character; a character, quote, space, escape.
*/
type RuneTokenType int
type lexerState int
type Token struct {
tokenType TokenType
value string
}
/*
Two tokens are equal if both their types and values are equal. A nil token can
never equal another token.
*/
func (a *Token) Equal(b *Token) bool {
if a == nil || b == nil {
return false
}
if a.tokenType != b.tokenType {
return false
}
return a.value == b.value
}
const (
RUNE_CHAR string = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789._-,/@$*()+=><:;&^%~|!?[]{}"
RUNE_SPACE string = " \t\r\n"
RUNE_ESCAPING_QUOTE string = "\""
RUNE_NONESCAPING_QUOTE string = "'"
RUNE_ESCAPE = "\\"
RUNE_COMMENT = "#"
RUNETOKEN_UNKNOWN RuneTokenType = 0
RUNETOKEN_CHAR RuneTokenType = 1
RUNETOKEN_SPACE RuneTokenType = 2
RUNETOKEN_ESCAPING_QUOTE RuneTokenType = 3
RUNETOKEN_NONESCAPING_QUOTE RuneTokenType = 4
RUNETOKEN_ESCAPE RuneTokenType = 5
RUNETOKEN_COMMENT RuneTokenType = 6
RUNETOKEN_EOF RuneTokenType = 7
TOKEN_UNKNOWN TokenType = 0
TOKEN_WORD TokenType = 1
TOKEN_SPACE TokenType = 2
TOKEN_COMMENT TokenType = 3
STATE_START lexerState = 0
STATE_INWORD lexerState = 1
STATE_ESCAPING lexerState = 2
STATE_ESCAPING_QUOTED lexerState = 3
STATE_QUOTED_ESCAPING lexerState = 4
STATE_QUOTED lexerState = 5
STATE_COMMENT lexerState = 6
INITIAL_TOKEN_CAPACITY int = 100
)
/*
A type for classifying characters. This allows for different sorts of
classifiers - those accepting extended non-ascii chars, or strict posix
compatibility, for example.
*/
type TokenClassifier struct {
typeMap map[int32]RuneTokenType
}
func addRuneClass(typeMap *map[int32]RuneTokenType, runes string, tokenType RuneTokenType) {
for _, rune := range runes {
(*typeMap)[int32(rune)] = tokenType
}
}
/*
Create a new classifier for basic ASCII characters.
*/
func NewDefaultClassifier() *TokenClassifier {
typeMap := map[int32]RuneTokenType{}
addRuneClass(&typeMap, RUNE_CHAR, RUNETOKEN_CHAR)
addRuneClass(&typeMap, RUNE_SPACE, RUNETOKEN_SPACE)
addRuneClass(&typeMap, RUNE_ESCAPING_QUOTE, RUNETOKEN_ESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_NONESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE)
addRuneClass(&typeMap, RUNE_ESCAPE, RUNETOKEN_ESCAPE)
addRuneClass(&typeMap, RUNE_COMMENT, RUNETOKEN_COMMENT)
return &TokenClassifier{
typeMap: typeMap}
}
func (classifier *TokenClassifier) ClassifyRune(rune int32) RuneTokenType {
return classifier.typeMap[rune]
}
/*
A type for turning an input stream in to a sequence of strings. Whitespace and
comments are skipped.
*/
type Lexer struct {
tokenizer *Tokenizer
}
/*
Create a new lexer.
*/
func NewLexer(r io.Reader) (*Lexer, error) {
tokenizer, err := NewTokenizer(r)
if err != nil {
return nil, err
}
lexer := &Lexer{tokenizer: tokenizer}
return lexer, nil
}
/*
Return the next word, and an error value. If there are no more words, the error
will be io.EOF.
*/
func (l *Lexer) NextWord() (string, error) {
var token *Token
var err error
for {
token, err = l.tokenizer.NextToken()
if err != nil {
return "", err
}
switch token.tokenType {
case TOKEN_WORD:
{
return token.value, nil
}
case TOKEN_COMMENT:
{
// skip comments
}
default:
{
panic(fmt.Sprintf("Unknown token type: %v", token.tokenType))
}
}
}
return "", io.EOF
}
/*
A type for turning an input stream in to a sequence of typed tokens.
*/
type Tokenizer struct {
input *bufio.Reader
classifier *TokenClassifier
}
/*
Create a new tokenizer.
*/
func NewTokenizer(r io.Reader) (*Tokenizer, error) {
input := bufio.NewReader(r)
classifier := NewDefaultClassifier()
tokenizer := &Tokenizer{
input: input,
classifier: classifier}
return tokenizer, nil
}
/*
Scan the stream for the next token.
This uses an internal state machine. It will panic if it encounters a character
which it does not know how to handle.
*/
func (t *Tokenizer) scanStream() (*Token, error) {
state := STATE_START
var tokenType TokenType
value := make([]int32, 0, INITIAL_TOKEN_CAPACITY)
var (
nextRune int32
nextRuneType RuneTokenType
err error
)
SCAN:
for {
nextRune, _, err = t.input.ReadRune()
nextRuneType = t.classifier.ClassifyRune(nextRune)
if err != nil {
if err == io.EOF {
nextRuneType = RUNETOKEN_EOF
err = nil
} else {
return nil, err
}
}
switch state {
case STATE_START: // no runes read yet
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
return nil, io.EOF
}
case RUNETOKEN_CHAR:
{
tokenType = TOKEN_WORD
value = append(value, nextRune)
state = STATE_INWORD
}
case RUNETOKEN_SPACE:
{
}
case RUNETOKEN_ESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
tokenType = TOKEN_WORD
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
tokenType = TOKEN_WORD
state = STATE_ESCAPING
}
case RUNETOKEN_COMMENT:
{
tokenType = TOKEN_COMMENT
state = STATE_COMMENT
}
default:
{
return nil, errors.New(fmt.Sprintf("Unknown rune: %v", nextRune))
}
}
}
case STATE_INWORD: // in a regular word
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
t.input.UnreadRune()
break SCAN
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_QUOTED_ESCAPING
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_QUOTED
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING: // the next rune after an escape character
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_INWORD
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_ESCAPING_QUOTED: // the next rune after an escape character, in double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found after escape character")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
state = STATE_QUOTED_ESCAPING
value = append(value, nextRune)
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED_ESCAPING: // in escaping double quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_NONESCAPING_QUOTE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_ESCAPING_QUOTE:
{
state = STATE_INWORD
}
case RUNETOKEN_ESCAPE:
{
state = STATE_ESCAPING_QUOTED
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_QUOTED: // in non-escaping single quotes
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
err = errors.New("EOF found when expecting closing quote.")
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_SPACE, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT:
{
value = append(value, nextRune)
}
case RUNETOKEN_NONESCAPING_QUOTE:
{
state = STATE_INWORD
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
case STATE_COMMENT:
{
switch nextRuneType {
case RUNETOKEN_EOF:
{
break SCAN
}
case RUNETOKEN_CHAR, RUNETOKEN_UNKNOWN, RUNETOKEN_ESCAPING_QUOTE, RUNETOKEN_ESCAPE, RUNETOKEN_COMMENT, RUNETOKEN_NONESCAPING_QUOTE:
{
value = append(value, nextRune)
}
case RUNETOKEN_SPACE:
{
if nextRune == '\n' {
state = STATE_START
break SCAN
} else {
value = append(value, nextRune)
}
}
default:
{
return nil, errors.New(fmt.Sprintf("Uknown rune: %v", nextRune))
}
}
}
default:
{
panic(fmt.Sprintf("Unexpected state: %v", state))
}
}
}
token := &Token{
tokenType: tokenType,
value: string(value)}
return token, err
}
/*
Return the next token in the stream, and an error value. If there are no more
tokens available, the error value will be io.EOF.
*/
func (t *Tokenizer) NextToken() (*Token, error) {
return t.scanStream()
}
/*
Split a string in to a slice of strings, based upon shell-style rules for
quoting, escaping, and spaces.
*/
func Split(s string) ([]string, error) {
l, err := NewLexer(strings.NewReader(s))
if err != nil {
return nil, err
}
subStrings := []string{}
for |
return subStrings, nil
}
| {
word, err := l.NextWord()
if err != nil {
if err == io.EOF {
return subStrings, nil
}
return subStrings, err
}
subStrings = append(subStrings, word)
} | conditional_block |
mod.rs | mod console_tests;
mod iterator;
use std::borrow::Cow;
use ansi_term::Style;
use itertools::Itertools;
use unicode_segmentation::UnicodeSegmentation;
use unicode_width::UnicodeWidthStr;
use iterator::{AnsiElementIterator, Element};
pub const ANSI_CSI_CLEAR_TO_EOL: &str = "\x1b[0K";
pub const ANSI_CSI_CLEAR_TO_BOL: &str = "\x1b[1K";
pub const ANSI_SGR_RESET: &str = "\x1b[0m";
pub const ANSI_SGR_REVERSE: &str = "\x1b[7m";
pub fn strip_ansi_codes(s: &str) -> String {
strip_ansi_codes_from_strings_iterator(ansi_strings_iterator(s))
}
pub fn measure_text_width(s: &str) -> usize {
ansi_strings_iterator(s).fold(0, |acc, (element, is_ansi)| {
acc + if is_ansi { 0 } else { element.width() }
})
}
/// Truncate string such that `tail` is present as a suffix, preceded by as much of `s` as can be
/// displayed in the requested width.
// Return string constructed as follows:
// 1. `display_width` characters are available. If the string fits, return it.
//
// 2. Contribute graphemes and ANSI escape sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_str<'a>(s: &'a str, display_width: usize, tail: &str) -> Cow<'a, str> {
let items = ansi_strings_iterator(s).collect::<Vec<(&str, bool)>>();
let width = strip_ansi_codes_from_strings_iterator(items.iter().copied()).width();
if width <= display_width {
return Cow::from(s);
}
let result_tail = if !tail.is_empty() {
truncate_str(tail, display_width, "").to_string()
} else {
String::new()
};
let mut used = measure_text_width(&result_tail);
let mut result = String::new();
for (t, is_ansi) in items {
if !is_ansi {
for g in t.graphemes(true) {
let w = g.width();
if used + w > display_width {
result.push_str(&" ".repeat(display_width.saturating_sub(used)));
break;
}
result.push_str(g);
used += w;
}
} else {
result.push_str(t);
}
}
Cow::from(format!("{result}{result_tail}"))
}
pub fn parse_style_sections(s: &str) -> Vec<(ansi_term::Style, &str)> {
let mut sections = Vec::new();
let mut curr_style = Style::default();
for element in AnsiElementIterator::new(s) {
match element {
Element::Text(start, end) => sections.push((curr_style, &s[start..end])),
Element::Sgr(style, _, _) => curr_style = style,
_ => {}
}
}
sections
}
// Return the first CSI element, if any, as an `ansi_term::Style`.
pub fn parse_first_style(s: &str) -> Option<ansi_term::Style> {
AnsiElementIterator::new(s).find_map(|el| match el {
Element::Sgr(style, _, _) => Some(style),
_ => None,
})
}
pub fn string_starts_with_ansi_style_sequence(s: &str) -> bool {
AnsiElementIterator::new(s)
.next()
.map(|el| matches!(el, Element::Sgr(_, _, _)))
.unwrap_or(false)
}
/// Return string formed from a byte slice starting at byte position `start`, where the index
/// counts bytes in non-ANSI-escape-sequence content only. All ANSI escape sequences in the
/// original string are preserved.
pub fn ansi_preserving_slice(s: &str, start: usize) -> String {
AnsiElementIterator::new(s)
.scan(0, |index, element| {
// `index` is the index in non-ANSI-escape-sequence content.
Some(match element {
Element::Sgr(_, a, b) => &s[a..b],
Element::Csi(a, b) => &s[a..b],
Element::Esc(a, b) => &s[a..b],
Element::Osc(a, b) => &s[a..b],
Element::Text(a, b) => {
let i = *index;
*index += b - a;
if *index <= start {
// This text segment ends before start, so contributes no bytes.
""
} else if i > start {
// This section starts after `start`, so contributes all its bytes.
&s[a..b]
} else {
// This section contributes those bytes that are >= start
&s[(a + start - i)..b]
}
}
})
})
.join("")
}
/// Return the byte index in `s` of the i-th text byte in `s`. I.e. `i` counts
/// bytes in non-ANSI-escape-sequence content only.
pub fn ansi_preserving_index(s: &str, i: usize) -> Option<usize> {
let mut index = 0;
for element in AnsiElementIterator::new(s) {
if let Element::Text(a, b) = element {
index += b - a;
if index > i {
return Some(b - (index - i));
}
}
}
None
}
fn ansi_strings_iterator(s: &str) -> impl Iterator<Item = (&str, bool)> {
AnsiElementIterator::new(s).map(move |el| match el {
Element::Sgr(_, i, j) => (&s[i..j], true),
Element::Csi(i, j) => (&s[i..j], true),
Element::Esc(i, j) => (&s[i..j], true),
Element::Osc(i, j) => (&s[i..j], true),
Element::Text(i, j) => (&s[i..j], false),
})
}
fn strip_ansi_codes_from_strings_iterator<'a>(
strings: impl Iterator<Item = (&'a str, bool)>,
) -> String {
strings
.filter_map(|(el, is_ansi)| if !is_ansi { Some(el) } else { None })
.join("")
}
pub fn explain_ansi(line: &str, colorful: bool) -> String {
use crate::style::Style;
parse_style_sections(line)
.into_iter()
.map(|(ansi_term_style, s)| {
let style = Style {
ansi_term_style,
..Style::default()
};
if colorful {
format!("({}){}", style.to_painted_string(), style.paint(s))
} else {
format!("({style}){s}")
}
})
.collect()
}
#[cfg(test)]
mod tests {
use crate::ansi::ansi_preserving_index;
// Note that src/ansi/console_tests.rs contains additional test coverage for this module.
use super::{
ansi_preserving_slice, measure_text_width, parse_first_style,
string_starts_with_ansi_style_sequence, strip_ansi_codes, truncate_str,
};
#[test]
fn test_strip_ansi_codes() {
for s in &["src/ansi/mod.rs", "バー", "src/ansi/modバー.rs"] {
assert_eq!(strip_ansi_codes(s), *s);
}
assert_eq!(strip_ansi_codes("\x1b[31mバー\x1b[0m"), "バー");
}
#[test]
fn test_measure_text_width() {
assert_eq!(measure_text_width("src/ansi/mod.rs"), 15);
assert_eq!(measure_text_width("バー"), 4);
assert_eq!(measure_text_width("src/ansi/modバー.rs"), 19);
assert_eq!(measure_text_width("\x1b[31mバー\x1b[0m"), 4);
assert_eq!(measure_text_width("a\nb\n"), 2);
}
#[test]
fn test_strip_ansi_codes_osc_hyperlink() {
assert_eq!(strip_ansi_codes("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m\n"),
"src/ansi/mod.rs\n");
}
#[test]
fn test_measure_text_width_osc_hyperlink() {
assert_eq!(measure | asure_text_width_osc_hyperlink_non_ascii() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let minus_line_from_unconfigured_git = "\x1b[31m-____\x1b[m\n";
let style = parse_first_style(minus_line_from_unconfigured_git);
let expected_style = ansi_term::Style {
foreground: Some(ansi_term::Color::Red),
..ansi_term::Style::default()
};
assert_eq!(Some(expected_style), style);
}
#[test]
fn test_string_starts_with_ansi_escape_sequence() {
assert!(!string_starts_with_ansi_style_sequence(""));
assert!(!string_starts_with_ansi_style_sequence("-"));
assert!(string_starts_with_ansi_style_sequence(
"\x1b[31m-XXX\x1b[m\n"
));
assert!(string_starts_with_ansi_style_sequence("\x1b[32m+XXX"));
}
#[test]
fn test_ansi_preserving_slice_and_index() {
assert_eq!(ansi_preserving_slice("", 0), "");
assert_eq!(ansi_preserving_index("", 0), None);
assert_eq!(ansi_preserving_slice("0", 0), "0");
assert_eq!(ansi_preserving_index("0", 0), Some(0));
assert_eq!(ansi_preserving_slice("0", 1), "");
assert_eq!(ansi_preserving_index("0", 1), None);
let raw_string = "\x1b[1;35m0123456789\x1b[0m";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;35m123456789\x1b[0m"
);
assert_eq!(ansi_preserving_slice(raw_string, 7), "\x1b[1;35m789\x1b[0m");
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(14));
let raw_string = "\x1b[1;36m0\x1b[m\x1b[1;36m123456789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;36m\x1b[m\x1b[1;36m123456789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(18));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
let raw_string = "\x1b[1;36m012345\x1b[m\x1b[1;36m6789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 3),
"\x1b[1;36m345\x1b[m\x1b[1;36m6789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
}
#[test]
fn test_truncate_str() {
assert_eq!(truncate_str("1", 1, ""), "1");
assert_eq!(truncate_str("12", 1, ""), "1");
assert_eq!(truncate_str("123", 2, "s"), "1s");
assert_eq!(truncate_str("123", 2, "→"), "1→");
assert_eq!(truncate_str("12ݶ", 1, "ݶ"), "ݶ");
}
}
| _text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_me | identifier_body |
mod.rs | mod console_tests;
mod iterator;
use std::borrow::Cow;
use ansi_term::Style;
use itertools::Itertools;
use unicode_segmentation::UnicodeSegmentation;
use unicode_width::UnicodeWidthStr;
use iterator::{AnsiElementIterator, Element};
pub const ANSI_CSI_CLEAR_TO_EOL: &str = "\x1b[0K";
pub const ANSI_CSI_CLEAR_TO_BOL: &str = "\x1b[1K";
pub const ANSI_SGR_RESET: &str = "\x1b[0m";
pub const ANSI_SGR_REVERSE: &str = "\x1b[7m";
pub fn strip_ansi_codes(s: &str) -> String {
strip_ansi_codes_from_strings_iterator(ansi_strings_iterator(s))
}
pub fn measure_text_width(s: &str) -> usize {
ansi_strings_iterator(s).fold(0, |acc, (element, is_ansi)| {
acc + if is_ansi { 0 } else { element.width() }
})
}
/// Truncate string such that `tail` is present as a suffix, preceded by as much of `s` as can be
/// displayed in the requested width.
// Return string constructed as follows:
// 1. `display_width` characters are available. If the string fits, return it.
//
// 2. Contribute graphemes and ANSI escape sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_str<'a>(s: &'a str, display_width: usize, tail: &str) -> Cow<'a, str> {
let items = ansi_strings_iterator(s).collect::<Vec<(&str, bool)>>();
let width = strip_ansi_codes_from_strings_iterator(items.iter().copied()).width();
if width <= display_width {
return Cow::from(s);
}
let result_tail = if !tail.is_empty() {
truncate_str(tail, display_width, "").to_string()
} else {
String::new()
};
let mut used = measure_text_width(&result_tail);
let mut result = String::new();
for (t, is_ansi) in items {
if !is_ansi {
for g in t.graphemes(true) {
let w = g.width();
if used + w > display_width {
result.push_str(&" ".repeat(display_width.saturating_sub(used)));
break;
}
result.push_str(g);
used += w;
}
} else {
result.push_str(t);
}
}
Cow::from(format!("{result}{result_tail}"))
}
pub fn parse_style_sections(s: &str) -> Vec<(ansi_term::Style, &str)> {
let mut sections = Vec::new();
let mut curr_style = Style::default();
for element in AnsiElementIterator::new(s) {
match element {
Element::Text(start, end) => sections.push((curr_style, &s[start..end])),
Element::Sgr(style, _, _) => curr_style = style,
_ => {}
}
}
sections
}
// Return the first CSI element, if any, as an `ansi_term::Style`.
pub fn parse_first_style(s: &str) -> Option<ansi_term::Style> {
AnsiElementIterator::new(s).find_map(|el| match el {
Element::Sgr(style, _, _) => Some(style),
_ => None,
})
}
pub fn string_starts_with_ansi_style_sequence(s: &str) -> bool {
AnsiElementIterator::new(s)
.next()
.map(|el| matches!(el, Element::Sgr(_, _, _)))
.unwrap_or(false)
}
/// Return string formed from a byte slice starting at byte position `start`, where the index
/// counts bytes in non-ANSI-escape-sequence content only. All ANSI escape sequences in the
/// original string are preserved.
pub fn ansi_preserving_slice(s: &str, start: usize) -> String {
AnsiElementIterator::new(s)
.scan(0, |index, element| {
// `index` is the index in non-ANSI-escape-sequence content.
Some(match element {
Element::Sgr(_, a, b) => &s[a..b],
Element::Csi(a, b) => &s[a..b],
Element::Esc(a, b) => &s[a..b],
Element::Osc(a, b) => &s[a..b],
Element::Text(a, b) => {
let i = *index;
*index += b - a;
if *index <= start {
// This text segment ends before start, so contributes no bytes.
""
} else if i > start {
// This section starts after `start`, so contributes all its bytes.
&s[a..b]
} else {
// This section contributes those bytes that are >= start
&s[(a + start - i)..b]
}
}
})
})
.join("")
}
/// Return the byte index in `s` of the i-th text byte in `s`. I.e. `i` counts
/// bytes in non-ANSI-escape-sequence content only.
pub fn ansi_preserving_index(s: &str, i: usize) -> Option<usize> {
let mut index = 0;
for element in AnsiElementIterator::new(s) {
if let Element::Text(a, b) = element {
index += b - a;
if index > i {
return Some(b - (index - i));
}
}
}
None
}
fn ansi_strings_iterator(s: &str) -> impl Iterator<Item = (&str, bool)> {
AnsiElementIterator::new(s).map(move |el| match el {
Element::Sgr(_, i, j) => (&s[i..j], true),
Element::Csi(i, j) => (&s[i..j], true),
Element::Esc(i, j) => (&s[i..j], true),
Element::Osc(i, j) => (&s[i..j], true),
Element::Text(i, j) => (&s[i..j], false),
})
}
fn strip_ansi_codes_from_strings_iterator<'a>(
strings: impl Iterator<Item = (&'a str, bool)>,
) -> String {
strings
.filter_map(|(el, is_ansi)| if !is_ansi { Some(el) } else { None })
.join("")
}
pub fn explain_ansi(line: &str, colorful: bool) -> String {
use crate::style::Style;
parse_style_sections(line)
.into_iter()
.map(|(ansi_term_style, s)| {
let style = Style {
ansi_term_style,
..Style::default()
};
if colorful {
format!("({}){}", style.to_painted_string(), style.paint(s))
} else {
format!("({style}){s}")
}
})
.collect()
}
#[cfg(test)]
mod tests {
use crate::ansi::ansi_preserving_index;
// Note that src/ansi/console_tests.rs contains additional test coverage for this module.
use super::{
ansi_preserving_slice, measure_text_width, parse_first_style,
string_starts_with_ansi_style_sequence, strip_ansi_codes, truncate_str,
};
#[test]
fn test_strip_ansi_codes() {
for s in &["src/ansi/mod.rs", "バー", "src/ansi/modバー.rs"] {
assert_eq!(strip_ansi_codes(s), *s);
}
assert_eq!(strip_ansi_codes("\x1b[31mバー\x1b[0m"), "バー");
}
#[test]
fn test_measure_text_width() {
assert_eq!(measure_text_width("src/ansi/mod.rs"), 15);
assert_eq!(measure_text_width("バー"), 4);
assert_eq!(measure_text_width("src/ansi/modバー.rs"), 19);
assert_eq!(measure_text_width("\x1b[31mバー\x1b[0m"), 4);
assert_eq!(measure_text_width("a\nb\n"), 2);
}
#[test]
fn test_strip_ansi_codes_osc_hyperlink() {
assert_eq!(strip_ansi_codes("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m\n"),
"src/ansi/mod.rs\n");
}
#[test]
fn test_measure_text_width_osc_hyperlink() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_measure_text_width_osc_ | ure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let minus_line_from_unconfigured_git = "\x1b[31m-____\x1b[m\n";
let style = parse_first_style(minus_line_from_unconfigured_git);
let expected_style = ansi_term::Style {
foreground: Some(ansi_term::Color::Red),
..ansi_term::Style::default()
};
assert_eq!(Some(expected_style), style);
}
#[test]
fn test_string_starts_with_ansi_escape_sequence() {
assert!(!string_starts_with_ansi_style_sequence(""));
assert!(!string_starts_with_ansi_style_sequence("-"));
assert!(string_starts_with_ansi_style_sequence(
"\x1b[31m-XXX\x1b[m\n"
));
assert!(string_starts_with_ansi_style_sequence("\x1b[32m+XXX"));
}
#[test]
fn test_ansi_preserving_slice_and_index() {
assert_eq!(ansi_preserving_slice("", 0), "");
assert_eq!(ansi_preserving_index("", 0), None);
assert_eq!(ansi_preserving_slice("0", 0), "0");
assert_eq!(ansi_preserving_index("0", 0), Some(0));
assert_eq!(ansi_preserving_slice("0", 1), "");
assert_eq!(ansi_preserving_index("0", 1), None);
let raw_string = "\x1b[1;35m0123456789\x1b[0m";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;35m123456789\x1b[0m"
);
assert_eq!(ansi_preserving_slice(raw_string, 7), "\x1b[1;35m789\x1b[0m");
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(14));
let raw_string = "\x1b[1;36m0\x1b[m\x1b[1;36m123456789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;36m\x1b[m\x1b[1;36m123456789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(18));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
let raw_string = "\x1b[1;36m012345\x1b[m\x1b[1;36m6789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 3),
"\x1b[1;36m345\x1b[m\x1b[1;36m6789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
}
#[test]
fn test_truncate_str() {
assert_eq!(truncate_str("1", 1, ""), "1");
assert_eq!(truncate_str("12", 1, ""), "1");
assert_eq!(truncate_str("123", 2, "s"), "1s");
assert_eq!(truncate_str("123", 2, "→"), "1→");
assert_eq!(truncate_str("12ݶ", 1, "ݶ"), "ݶ");
}
}
| hyperlink_non_ascii() {
assert_eq!(meas | identifier_name |
mod.rs | mod console_tests;
mod iterator;
use std::borrow::Cow;
use ansi_term::Style;
use itertools::Itertools;
use unicode_segmentation::UnicodeSegmentation;
use unicode_width::UnicodeWidthStr;
use iterator::{AnsiElementIterator, Element};
pub const ANSI_CSI_CLEAR_TO_EOL: &str = "\x1b[0K";
pub const ANSI_CSI_CLEAR_TO_BOL: &str = "\x1b[1K";
pub const ANSI_SGR_RESET: &str = "\x1b[0m";
pub const ANSI_SGR_REVERSE: &str = "\x1b[7m";
pub fn strip_ansi_codes(s: &str) -> String {
strip_ansi_codes_from_strings_iterator(ansi_strings_iterator(s))
}
pub fn measure_text_width(s: &str) -> usize {
ansi_strings_iterator(s).fold(0, |acc, (element, is_ansi)| {
acc + if is_ansi { 0 } else { element.width() }
})
}
/// Truncate string such that `tail` is present as a suffix, preceded by as much of `s` as can be
/// displayed in the requested width.
// Return string constructed as follows:
// 1. `display_width` characters are available. If the string fits, return it.
//
// 2. Contribute graphemes and ANSI escape sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_str<'a>(s: &'a str, display_width: usize, tail: &str) -> Cow<'a, str> {
let items = ansi_strings_iterator(s).collect::<Vec<(&str, bool)>>();
let width = strip_ansi_codes_from_strings_iterator(items.iter().copied()).width();
if width <= display_width {
return Cow::from(s);
}
let result_tail = if !tail.is_empty() {
truncate_str(tail, display_width, "").to_string()
} else {
String::new()
};
let mut used = measure_text_width(&result_tail);
let mut result = String::new();
for (t, is_ansi) in items {
if !is_ansi {
for g in t.graphemes(true) {
let w = g.width();
if used + w > display_width {
result.push_str(&" ".repeat(display_width.saturating_sub(used)));
break;
}
result.push_str(g);
used += w;
}
} else |
}
Cow::from(format!("{result}{result_tail}"))
}
pub fn parse_style_sections(s: &str) -> Vec<(ansi_term::Style, &str)> {
let mut sections = Vec::new();
let mut curr_style = Style::default();
for element in AnsiElementIterator::new(s) {
match element {
Element::Text(start, end) => sections.push((curr_style, &s[start..end])),
Element::Sgr(style, _, _) => curr_style = style,
_ => {}
}
}
sections
}
// Return the first CSI element, if any, as an `ansi_term::Style`.
pub fn parse_first_style(s: &str) -> Option<ansi_term::Style> {
AnsiElementIterator::new(s).find_map(|el| match el {
Element::Sgr(style, _, _) => Some(style),
_ => None,
})
}
pub fn string_starts_with_ansi_style_sequence(s: &str) -> bool {
AnsiElementIterator::new(s)
.next()
.map(|el| matches!(el, Element::Sgr(_, _, _)))
.unwrap_or(false)
}
/// Return string formed from a byte slice starting at byte position `start`, where the index
/// counts bytes in non-ANSI-escape-sequence content only. All ANSI escape sequences in the
/// original string are preserved.
pub fn ansi_preserving_slice(s: &str, start: usize) -> String {
AnsiElementIterator::new(s)
.scan(0, |index, element| {
// `index` is the index in non-ANSI-escape-sequence content.
Some(match element {
Element::Sgr(_, a, b) => &s[a..b],
Element::Csi(a, b) => &s[a..b],
Element::Esc(a, b) => &s[a..b],
Element::Osc(a, b) => &s[a..b],
Element::Text(a, b) => {
let i = *index;
*index += b - a;
if *index <= start {
// This text segment ends before start, so contributes no bytes.
""
} else if i > start {
// This section starts after `start`, so contributes all its bytes.
&s[a..b]
} else {
// This section contributes those bytes that are >= start
&s[(a + start - i)..b]
}
}
})
})
.join("")
}
/// Return the byte index in `s` of the i-th text byte in `s`. I.e. `i` counts
/// bytes in non-ANSI-escape-sequence content only.
pub fn ansi_preserving_index(s: &str, i: usize) -> Option<usize> {
let mut index = 0;
for element in AnsiElementIterator::new(s) {
if let Element::Text(a, b) = element {
index += b - a;
if index > i {
return Some(b - (index - i));
}
}
}
None
}
fn ansi_strings_iterator(s: &str) -> impl Iterator<Item = (&str, bool)> {
AnsiElementIterator::new(s).map(move |el| match el {
Element::Sgr(_, i, j) => (&s[i..j], true),
Element::Csi(i, j) => (&s[i..j], true),
Element::Esc(i, j) => (&s[i..j], true),
Element::Osc(i, j) => (&s[i..j], true),
Element::Text(i, j) => (&s[i..j], false),
})
}
fn strip_ansi_codes_from_strings_iterator<'a>(
strings: impl Iterator<Item = (&'a str, bool)>,
) -> String {
strings
.filter_map(|(el, is_ansi)| if !is_ansi { Some(el) } else { None })
.join("")
}
pub fn explain_ansi(line: &str, colorful: bool) -> String {
use crate::style::Style;
parse_style_sections(line)
.into_iter()
.map(|(ansi_term_style, s)| {
let style = Style {
ansi_term_style,
..Style::default()
};
if colorful {
format!("({}){}", style.to_painted_string(), style.paint(s))
} else {
format!("({style}){s}")
}
})
.collect()
}
#[cfg(test)]
mod tests {
use crate::ansi::ansi_preserving_index;
// Note that src/ansi/console_tests.rs contains additional test coverage for this module.
use super::{
ansi_preserving_slice, measure_text_width, parse_first_style,
string_starts_with_ansi_style_sequence, strip_ansi_codes, truncate_str,
};
#[test]
fn test_strip_ansi_codes() {
for s in &["src/ansi/mod.rs", "バー", "src/ansi/modバー.rs"] {
assert_eq!(strip_ansi_codes(s), *s);
}
assert_eq!(strip_ansi_codes("\x1b[31mバー\x1b[0m"), "バー");
}
#[test]
fn test_measure_text_width() {
assert_eq!(measure_text_width("src/ansi/mod.rs"), 15);
assert_eq!(measure_text_width("バー"), 4);
assert_eq!(measure_text_width("src/ansi/modバー.rs"), 19);
assert_eq!(measure_text_width("\x1b[31mバー\x1b[0m"), 4);
assert_eq!(measure_text_width("a\nb\n"), 2);
}
#[test]
fn test_strip_ansi_codes_osc_hyperlink() {
assert_eq!(strip_ansi_codes("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m\n"),
"src/ansi/mod.rs\n");
}
#[test]
fn test_measure_text_width_osc_hyperlink() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_measure_text_width_osc_hyperlink_non_ascii() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let minus_line_from_unconfigured_git = "\x1b[31m-____\x1b[m\n";
let style = parse_first_style(minus_line_from_unconfigured_git);
let expected_style = ansi_term::Style {
foreground: Some(ansi_term::Color::Red),
..ansi_term::Style::default()
};
assert_eq!(Some(expected_style), style);
}
#[test]
fn test_string_starts_with_ansi_escape_sequence() {
assert!(!string_starts_with_ansi_style_sequence(""));
assert!(!string_starts_with_ansi_style_sequence("-"));
assert!(string_starts_with_ansi_style_sequence(
"\x1b[31m-XXX\x1b[m\n"
));
assert!(string_starts_with_ansi_style_sequence("\x1b[32m+XXX"));
}
#[test]
fn test_ansi_preserving_slice_and_index() {
assert_eq!(ansi_preserving_slice("", 0), "");
assert_eq!(ansi_preserving_index("", 0), None);
assert_eq!(ansi_preserving_slice("0", 0), "0");
assert_eq!(ansi_preserving_index("0", 0), Some(0));
assert_eq!(ansi_preserving_slice("0", 1), "");
assert_eq!(ansi_preserving_index("0", 1), None);
let raw_string = "\x1b[1;35m0123456789\x1b[0m";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;35m123456789\x1b[0m"
);
assert_eq!(ansi_preserving_slice(raw_string, 7), "\x1b[1;35m789\x1b[0m");
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(14));
let raw_string = "\x1b[1;36m0\x1b[m\x1b[1;36m123456789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;36m\x1b[m\x1b[1;36m123456789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(18));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
let raw_string = "\x1b[1;36m012345\x1b[m\x1b[1;36m6789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 3),
"\x1b[1;36m345\x1b[m\x1b[1;36m6789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
}
#[test]
fn test_truncate_str() {
assert_eq!(truncate_str("1", 1, ""), "1");
assert_eq!(truncate_str("12", 1, ""), "1");
assert_eq!(truncate_str("123", 2, "s"), "1s");
assert_eq!(truncate_str("123", 2, "→"), "1→");
assert_eq!(truncate_str("12ݶ", 1, "ݶ"), "ݶ");
}
}
| {
result.push_str(t);
} | conditional_block |
mod.rs | mod console_tests;
mod iterator;
use std::borrow::Cow;
use ansi_term::Style;
use itertools::Itertools;
use unicode_segmentation::UnicodeSegmentation;
use unicode_width::UnicodeWidthStr;
use iterator::{AnsiElementIterator, Element};
pub const ANSI_CSI_CLEAR_TO_EOL: &str = "\x1b[0K";
pub const ANSI_CSI_CLEAR_TO_BOL: &str = "\x1b[1K";
pub const ANSI_SGR_RESET: &str = "\x1b[0m";
pub const ANSI_SGR_REVERSE: &str = "\x1b[7m";
pub fn strip_ansi_codes(s: &str) -> String {
strip_ansi_codes_from_strings_iterator(ansi_strings_iterator(s))
}
pub fn measure_text_width(s: &str) -> usize {
ansi_strings_iterator(s).fold(0, |acc, (element, is_ansi)| {
acc + if is_ansi { 0 } else { element.width() }
})
}
/// Truncate string such that `tail` is present as a suffix, preceded by as much of `s` as can be
/// displayed in the requested width.
// Return string constructed as follows:
// 1. `display_width` characters are available. If the string fits, return it.
//
// 2. Contribute graphemes and ANSI escape sequences from `tail` until either (1) `tail` is
// exhausted, or (2) the display width of the result would exceed `display_width`.
//
// 3. If tail was exhausted, then contribute graphemes and ANSI escape sequences from `s` until the
// display_width of the result would exceed `display_width`.
pub fn truncate_str<'a>(s: &'a str, display_width: usize, tail: &str) -> Cow<'a, str> {
let items = ansi_strings_iterator(s).collect::<Vec<(&str, bool)>>();
let width = strip_ansi_codes_from_strings_iterator(items.iter().copied()).width();
if width <= display_width {
return Cow::from(s);
}
let result_tail = if !tail.is_empty() {
truncate_str(tail, display_width, "").to_string()
} else {
String::new()
};
let mut used = measure_text_width(&result_tail);
let mut result = String::new();
for (t, is_ansi) in items {
if !is_ansi {
for g in t.graphemes(true) {
let w = g.width();
if used + w > display_width {
result.push_str(&" ".repeat(display_width.saturating_sub(used)));
break;
}
result.push_str(g);
used += w;
}
} else {
result.push_str(t);
}
}
Cow::from(format!("{result}{result_tail}"))
}
pub fn parse_style_sections(s: &str) -> Vec<(ansi_term::Style, &str)> {
let mut sections = Vec::new();
let mut curr_style = Style::default();
for element in AnsiElementIterator::new(s) {
match element {
Element::Text(start, end) => sections.push((curr_style, &s[start..end])),
Element::Sgr(style, _, _) => curr_style = style,
_ => {}
}
}
sections
}
// Return the first CSI element, if any, as an `ansi_term::Style`.
pub fn parse_first_style(s: &str) -> Option<ansi_term::Style> {
AnsiElementIterator::new(s).find_map(|el| match el {
Element::Sgr(style, _, _) => Some(style),
_ => None,
})
}
pub fn string_starts_with_ansi_style_sequence(s: &str) -> bool {
AnsiElementIterator::new(s)
.next()
.map(|el| matches!(el, Element::Sgr(_, _, _)))
.unwrap_or(false)
}
/// Return string formed from a byte slice starting at byte position `start`, where the index
/// counts bytes in non-ANSI-escape-sequence content only. All ANSI escape sequences in the
/// original string are preserved.
pub fn ansi_preserving_slice(s: &str, start: usize) -> String {
AnsiElementIterator::new(s)
.scan(0, |index, element| {
// `index` is the index in non-ANSI-escape-sequence content.
Some(match element {
Element::Sgr(_, a, b) => &s[a..b],
Element::Csi(a, b) => &s[a..b],
Element::Esc(a, b) => &s[a..b],
Element::Osc(a, b) => &s[a..b],
Element::Text(a, b) => {
let i = *index;
*index += b - a;
if *index <= start {
// This text segment ends before start, so contributes no bytes.
""
} else if i > start {
// This section starts after `start`, so contributes all its bytes.
&s[a..b]
} else {
// This section contributes those bytes that are >= start
&s[(a + start - i)..b]
}
}
})
})
.join("")
}
/// Return the byte index in `s` of the i-th text byte in `s`. I.e. `i` counts
/// bytes in non-ANSI-escape-sequence content only.
pub fn ansi_preserving_index(s: &str, i: usize) -> Option<usize> {
let mut index = 0;
for element in AnsiElementIterator::new(s) {
if let Element::Text(a, b) = element {
index += b - a;
if index > i {
return Some(b - (index - i));
}
}
}
None
}
fn ansi_strings_iterator(s: &str) -> impl Iterator<Item = (&str, bool)> {
AnsiElementIterator::new(s).map(move |el| match el {
Element::Sgr(_, i, j) => (&s[i..j], true),
Element::Csi(i, j) => (&s[i..j], true),
Element::Esc(i, j) => (&s[i..j], true),
Element::Osc(i, j) => (&s[i..j], true),
Element::Text(i, j) => (&s[i..j], false),
})
}
fn strip_ansi_codes_from_strings_iterator<'a>(
strings: impl Iterator<Item = (&'a str, bool)>,
) -> String {
strings
.filter_map(|(el, is_ansi)| if !is_ansi { Some(el) } else { None })
.join("")
}
pub fn explain_ansi(line: &str, colorful: bool) -> String {
use crate::style::Style;
parse_style_sections(line)
.into_iter()
.map(|(ansi_term_style, s)| {
let style = Style {
ansi_term_style,
..Style::default()
};
if colorful {
format!("({}){}", style.to_painted_string(), style.paint(s))
} else {
format!("({style}){s}")
}
})
.collect()
}
#[cfg(test)]
mod tests {
use crate::ansi::ansi_preserving_index;
// Note that src/ansi/console_tests.rs contains additional test coverage for this module.
use super::{
ansi_preserving_slice, measure_text_width, parse_first_style,
string_starts_with_ansi_style_sequence, strip_ansi_codes, truncate_str,
};
#[test]
fn test_strip_ansi_codes() {
for s in &["src/ansi/mod.rs", "バー", "src/ansi/modバー.rs"] {
assert_eq!(strip_ansi_codes(s), *s);
}
assert_eq!(strip_ansi_codes("\x1b[31mバー\x1b[0m"), "バー");
}
#[test]
fn test_measure_text_width() {
assert_eq!(measure_text_width("src/ansi/mod.rs"), 15);
assert_eq!(measure_text_width("バー"), 4);
assert_eq!(measure_text_width("src/ansi/modバー.rs"), 19);
assert_eq!(measure_text_width("\x1b[31mバー\x1b[0m"), 4);
assert_eq!(measure_text_width("a\nb\n"), 2);
}
#[test]
fn test_strip_ansi_codes_osc_hyperlink() {
assert_eq!(strip_ansi_codes("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m\n"),
"src/ansi/mod.rs\n");
}
#[test]
fn test_measure_text_width_osc_hyperlink() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/mod.rs\x1b]8;;\x1b\\\x1b[0m"), | measure_text_width("src/ansi/mod.rs"));
}
#[test]
fn test_measure_text_width_osc_hyperlink_non_ascii() {
assert_eq!(measure_text_width("\x1b[38;5;4m\x1b]8;;file:///Users/dan/src/delta/src/ansi/mod.rs\x1b\\src/ansi/modバー.rs\x1b]8;;\x1b\\\x1b[0m"),
measure_text_width("src/ansi/modバー.rs"));
}
#[test]
fn test_parse_first_style() {
let minus_line_from_unconfigured_git = "\x1b[31m-____\x1b[m\n";
let style = parse_first_style(minus_line_from_unconfigured_git);
let expected_style = ansi_term::Style {
foreground: Some(ansi_term::Color::Red),
..ansi_term::Style::default()
};
assert_eq!(Some(expected_style), style);
}
#[test]
fn test_string_starts_with_ansi_escape_sequence() {
assert!(!string_starts_with_ansi_style_sequence(""));
assert!(!string_starts_with_ansi_style_sequence("-"));
assert!(string_starts_with_ansi_style_sequence(
"\x1b[31m-XXX\x1b[m\n"
));
assert!(string_starts_with_ansi_style_sequence("\x1b[32m+XXX"));
}
#[test]
fn test_ansi_preserving_slice_and_index() {
assert_eq!(ansi_preserving_slice("", 0), "");
assert_eq!(ansi_preserving_index("", 0), None);
assert_eq!(ansi_preserving_slice("0", 0), "0");
assert_eq!(ansi_preserving_index("0", 0), Some(0));
assert_eq!(ansi_preserving_slice("0", 1), "");
assert_eq!(ansi_preserving_index("0", 1), None);
let raw_string = "\x1b[1;35m0123456789\x1b[0m";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;35m123456789\x1b[0m"
);
assert_eq!(ansi_preserving_slice(raw_string, 7), "\x1b[1;35m789\x1b[0m");
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(14));
let raw_string = "\x1b[1;36m0\x1b[m\x1b[1;36m123456789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 1),
"\x1b[1;36m\x1b[m\x1b[1;36m123456789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(18));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
let raw_string = "\x1b[1;36m012345\x1b[m\x1b[1;36m6789\x1b[m\n";
assert_eq!(
ansi_preserving_slice(raw_string, 3),
"\x1b[1;36m345\x1b[m\x1b[1;36m6789\x1b[m\n"
);
assert_eq!(ansi_preserving_index(raw_string, 0), Some(7));
assert_eq!(ansi_preserving_index(raw_string, 1), Some(8));
assert_eq!(ansi_preserving_index(raw_string, 7), Some(24));
}
#[test]
fn test_truncate_str() {
assert_eq!(truncate_str("1", 1, ""), "1");
assert_eq!(truncate_str("12", 1, ""), "1");
assert_eq!(truncate_str("123", 2, "s"), "1s");
assert_eq!(truncate_str("123", 2, "→"), "1→");
assert_eq!(truncate_str("12ݶ", 1, "ݶ"), "ݶ");
}
} | random_line_split | |
main.rs | #![no_std]
#![no_main]
#![feature(asm)]
#![feature(collections)]
extern crate stm32f7_discovery as stm32f7;
extern crate collections;
extern crate r0;
pub mod plot;
pub mod model;
pub mod temp_sensor;
pub mod time;
pub mod util;
pub mod pid;
pub mod ramp;
pub mod state_button;
mod leak;
use stm32f7::{system_clock,board,embedded,sdram,lcd,touch,i2c};
use stm32f7::lcd::*;
use embedded::interfaces::gpio;
use embedded::interfaces::gpio::{Gpio};
use board::spi::Spi;
use time::*;
use util::*;
use plot::DragDirection;
use embedded::util::delay;
use model::TouchEvent::*;
use collections::*;
use collections::boxed::Box;
use leak::Leak;
use self::temp_sensor::{TemperatureSensor,Max6675};
use state_button::State;
static TTF: &[u8] = include_bytes!("RobotoMono-Bold.ttf");
#[no_mangle]
pub unsafe extern "C" fn reset() {
extern "C" {
static __DATA_LOAD: u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_start = &mut __BSS_START;
let bss_end = &__BSS_END;
r0::init_data(data_start, data_end, data_load);
r0::zero_bss(bss_start, bss_end);
stm32f7::heap::init();
// enable floating point unit
let scb = stm32f7::cortex_m::peripheral::scb_mut();
scb.cpacr.modify(|v| v | 0b1111 << 20);
asm!("DSB; ISB;"::::"volatile"); // pipeline flush
main(board::hw());
}
// WORKAROUND: rust compiler will inline & reorder fp instructions into
#[inline(never)] // reset() before the FPU is initialized
fn main(hw: board::Hardware) -> ! {
let board::Hardware {
rcc,
pwr,
flash,
fmc,
ltdc,
gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k,
spi_2,
i2c_3,
..
} = hw;
let mut gpio = Gpio::new(gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k);
system_clock::init(rcc, pwr, flash);
// Peripheral clock configuration
{
// enable all gpio ports
rcc.ahb1enr.update(|r| {
r.set_gpioaen(true);
r.set_gpioben(true);
r.set_gpiocen(true);
r.set_gpioden(true);
r.set_gpioeen(true);
r.set_gpiofen(true);
r.set_gpiogen(true);
r.set_gpiohen(true);
r.set_gpioien(true);
r.set_gpiojen(true);
r.set_gpioken(true);
});
// Enable SPI_2
rcc.apb1enr.update(|apb1enr| {
apb1enr.set_spi2en(true);
});
delay(1);
}
// i2c configuration
i2c::init_pins_and_clocks(rcc, &mut gpio);
let mut i2c_3 = i2c::init(i2c_3);
i2c_3.test_1();
i2c_3.test_2();
let mut temp_sensor = temp_sensor_init_spi2(&mut gpio, spi_2);
// init sdram (needed for display buffer)
sdram::init(rcc, fmc, &mut gpio);
let pwm_pin = (gpio::Port::PortI, gpio::Pin::Pin2);
let mut pwm_gpio = gpio.to_output(pwm_pin,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High, | let drag_color = Color::from_hex(0x000000);
let grid_color = Color::from_hex(0x444444);
// lcd controller
let mut lcd = lcd::init(ltdc, rcc, &mut gpio);
touch::check_family_id(&mut i2c_3).unwrap();
loop {
SYSCLOCK.reset();
lcd.clear_screen();
lcd.set_background_color(Color::from_hex(0x000000));
let plot_font = Box::new(Font::new(TTF, 11).unwrap()).leak();
let rtval_font = Box::new(Font::new(TTF, 14).unwrap()).leak();
let mut plot = plot::Plot::new(model::Range::new(0f32, (20*60) as f32),
model::Range::new(0f32, 200f32),
plot_font,
rtval_font,
axis_color,
grid_color,
drag_color,
80, // drag timeout
);
plot.draw_axis(&mut lcd);
//let mut pid_controller = pid::PIDController::new(0.3f32, 0.0f32, 0.0f32);
//let mut pid_controller = pid::PIDController::new(0.1f32, 0.0f32, 0.3f32); // Definitely better than first, but overshooting
//let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.3f32); // Not much different
let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.6f32); // Not much different
let mut smoother = pid::Smoother::new(10);
let mut measurement_start_system_time = SYSCLOCK.get_ticks();
let mut last_measurement_system_time = SYSCLOCK.get_ticks();
let mut duty_cycle: usize = 0;
let mut temp = 20f32;
let mut state_button = state_button::StateButton::new(
Color::from_hex(0x222222),
Rect{origin: Point{x: 440, y: 0}, width: 40, height: 40}
);
state_button.render(&mut lcd);
let mut last_touch_event = None;
'mainloop: loop {
let ticks = SYSCLOCK.get_ticks();
let delta_measurement = time::delta_checked(&last_measurement_system_time, &ticks);
if delta_measurement.to_msecs() >= 500 {
let val = temp_sensor.read();
let measurement_time = time::delta_checked(&measurement_start_system_time, &ticks).to_secs();
let measurement = model::TimeTemp{
time: measurement_time, // TODO just integer divide here?
temp: val as f32,
};
match state_button.state() {
State::RUNNING => plot.add_measurement(measurement, &mut lcd),
State::RESETTED => {
plot.set_measurement(model::TimeTemp{time: 0f32, temp: measurement.temp}, &mut lcd);
plot.update_ramp_start(&mut lcd);
},
State::STOPPED => {},
}
if let State::RUNNING = state_button.state() {
smoother.push_value(val);
let smooth_temp = smoother.get_average();
let ramp_target_temp = plot.ramp().evaluate(measurement_time);
let error = ramp_target_temp - smooth_temp;
let pid_value = pid_controller.cycle(error, &delta_measurement);
duty_cycle = (util::clamp(pid_value, 0f32, 1f32) * 1000f32) as usize;
lcd.draw_point_color(
Point{
x: plot.transform_time(measurement_time),
y: plot::Plot::transform_ranges(model::Range{from: 0f32, to: 1f32}, plot::Y_PX_RANGE, pid_value)
}, Layer::Layer2, Color::from_hex(0x0000ff).to_argb1555());
//let pid_clamped = util::clamp(pid_value, 0f32, 1f32);
//temp += (pid_clamped - 0.3) * delta_measurement.to_secs() * 1.0;
} else {
duty_cycle = 0;
}
last_measurement_system_time = ticks;
}
pwm_gpio.set(ticks.to_msecs() % 1000 < duty_cycle);
// poll for new touch data
let mut touches = false;
for touch in &touch::touches(&mut i2c_3).unwrap() {
touches = true;
let touch = model::Touch{
location: Point{
x: touch.x,
y: touch.y
},
time: ticks
};
let touch_event = match last_touch_event {
Some(TouchDown(_)) | Some(TouchMove(_)) => TouchMove(touch),
None | Some(TouchUp(_)) => TouchDown(touch),
};
//Do not allow changing ramp in stopped state
match state_button.state() {
State::RUNNING | State::RESETTED =>
plot.handle_touch(touch_event, &mut lcd),
_ => {},
}
last_touch_event = Some(touch_event);
}
// Deliver touch-up events
if !touches && last_touch_event.is_some() {
let touch_event = match last_touch_event.unwrap() {
TouchDown(t) | TouchMove(t) if time::delta(&ticks,&t.time).to_msecs() > 200 => {
if let Some(new_state) = state_button.handle_touch(TouchUp(t), &mut lcd) {
match new_state {
State::RESETTED => {
break 'mainloop;
},
State::RUNNING => {
measurement_start_system_time = SYSCLOCK.get_ticks();
last_measurement_system_time = measurement_start_system_time;
},
_ => {},
}
}
plot.handle_touch(TouchUp(t), &mut lcd);
None
},
x => Some(x),
};
last_touch_event = touch_event;
}
}
}
}
/// Initialize temperature sensor on SPI_2 port (GPIO pins)
/// IMPORTANT: "Table 3. Arduino connectors" in the discovery board datasheet
// states SPI2_NSS is pin D10. This is wrong.AsMut
// SPI2_NSS is D5, as seen in "Figure 25: Arduino Uno connectors"
fn temp_sensor_init_spi2(gpio: &mut Gpio, spi_2: &'static mut Spi) -> Max6675 {
let sck_pin = (gpio::Port::PortI, gpio::Pin::Pin1);
let miso_pin = (gpio::Port::PortB, gpio::Pin::Pin14);
let mosi_pin = (gpio::Port::PortB, gpio::Pin::Pin15);
let nss_pin = (gpio::Port::PortI, gpio::Pin::Pin0);
gpio.to_alternate_function(sck_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure sck");
// TODO the MOSI pin is not necessarily necessary for MAX6675
gpio.to_alternate_function(mosi_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure mosi");
gpio.to_alternate_function(miso_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure MISO pin");
gpio.to_alternate_function(nss_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure NSS ");
return Max6675::init(spi_2);
} | gpio::Resistor::NoPull)
.expect("Could not configure pwm pin");
let axis_color = Color::from_hex(0xffffff); | random_line_split |
main.rs | #![no_std]
#![no_main]
#![feature(asm)]
#![feature(collections)]
extern crate stm32f7_discovery as stm32f7;
extern crate collections;
extern crate r0;
pub mod plot;
pub mod model;
pub mod temp_sensor;
pub mod time;
pub mod util;
pub mod pid;
pub mod ramp;
pub mod state_button;
mod leak;
use stm32f7::{system_clock,board,embedded,sdram,lcd,touch,i2c};
use stm32f7::lcd::*;
use embedded::interfaces::gpio;
use embedded::interfaces::gpio::{Gpio};
use board::spi::Spi;
use time::*;
use util::*;
use plot::DragDirection;
use embedded::util::delay;
use model::TouchEvent::*;
use collections::*;
use collections::boxed::Box;
use leak::Leak;
use self::temp_sensor::{TemperatureSensor,Max6675};
use state_button::State;
static TTF: &[u8] = include_bytes!("RobotoMono-Bold.ttf");
#[no_mangle]
pub unsafe extern "C" fn reset() {
extern "C" {
static __DATA_LOAD: u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_start = &mut __BSS_START;
let bss_end = &__BSS_END;
r0::init_data(data_start, data_end, data_load);
r0::zero_bss(bss_start, bss_end);
stm32f7::heap::init();
// enable floating point unit
let scb = stm32f7::cortex_m::peripheral::scb_mut();
scb.cpacr.modify(|v| v | 0b1111 << 20);
asm!("DSB; ISB;"::::"volatile"); // pipeline flush
main(board::hw());
}
// WORKAROUND: rust compiler will inline & reorder fp instructions into
#[inline(never)] // reset() before the FPU is initialized
fn | (hw: board::Hardware) -> ! {
let board::Hardware {
rcc,
pwr,
flash,
fmc,
ltdc,
gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k,
spi_2,
i2c_3,
..
} = hw;
let mut gpio = Gpio::new(gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k);
system_clock::init(rcc, pwr, flash);
// Peripheral clock configuration
{
// enable all gpio ports
rcc.ahb1enr.update(|r| {
r.set_gpioaen(true);
r.set_gpioben(true);
r.set_gpiocen(true);
r.set_gpioden(true);
r.set_gpioeen(true);
r.set_gpiofen(true);
r.set_gpiogen(true);
r.set_gpiohen(true);
r.set_gpioien(true);
r.set_gpiojen(true);
r.set_gpioken(true);
});
// Enable SPI_2
rcc.apb1enr.update(|apb1enr| {
apb1enr.set_spi2en(true);
});
delay(1);
}
// i2c configuration
i2c::init_pins_and_clocks(rcc, &mut gpio);
let mut i2c_3 = i2c::init(i2c_3);
i2c_3.test_1();
i2c_3.test_2();
let mut temp_sensor = temp_sensor_init_spi2(&mut gpio, spi_2);
// init sdram (needed for display buffer)
sdram::init(rcc, fmc, &mut gpio);
let pwm_pin = (gpio::Port::PortI, gpio::Pin::Pin2);
let mut pwm_gpio = gpio.to_output(pwm_pin,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure pwm pin");
let axis_color = Color::from_hex(0xffffff);
let drag_color = Color::from_hex(0x000000);
let grid_color = Color::from_hex(0x444444);
// lcd controller
let mut lcd = lcd::init(ltdc, rcc, &mut gpio);
touch::check_family_id(&mut i2c_3).unwrap();
loop {
SYSCLOCK.reset();
lcd.clear_screen();
lcd.set_background_color(Color::from_hex(0x000000));
let plot_font = Box::new(Font::new(TTF, 11).unwrap()).leak();
let rtval_font = Box::new(Font::new(TTF, 14).unwrap()).leak();
let mut plot = plot::Plot::new(model::Range::new(0f32, (20*60) as f32),
model::Range::new(0f32, 200f32),
plot_font,
rtval_font,
axis_color,
grid_color,
drag_color,
80, // drag timeout
);
plot.draw_axis(&mut lcd);
//let mut pid_controller = pid::PIDController::new(0.3f32, 0.0f32, 0.0f32);
//let mut pid_controller = pid::PIDController::new(0.1f32, 0.0f32, 0.3f32); // Definitely better than first, but overshooting
//let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.3f32); // Not much different
let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.6f32); // Not much different
let mut smoother = pid::Smoother::new(10);
let mut measurement_start_system_time = SYSCLOCK.get_ticks();
let mut last_measurement_system_time = SYSCLOCK.get_ticks();
let mut duty_cycle: usize = 0;
let mut temp = 20f32;
let mut state_button = state_button::StateButton::new(
Color::from_hex(0x222222),
Rect{origin: Point{x: 440, y: 0}, width: 40, height: 40}
);
state_button.render(&mut lcd);
let mut last_touch_event = None;
'mainloop: loop {
let ticks = SYSCLOCK.get_ticks();
let delta_measurement = time::delta_checked(&last_measurement_system_time, &ticks);
if delta_measurement.to_msecs() >= 500 {
let val = temp_sensor.read();
let measurement_time = time::delta_checked(&measurement_start_system_time, &ticks).to_secs();
let measurement = model::TimeTemp{
time: measurement_time, // TODO just integer divide here?
temp: val as f32,
};
match state_button.state() {
State::RUNNING => plot.add_measurement(measurement, &mut lcd),
State::RESETTED => {
plot.set_measurement(model::TimeTemp{time: 0f32, temp: measurement.temp}, &mut lcd);
plot.update_ramp_start(&mut lcd);
},
State::STOPPED => {},
}
if let State::RUNNING = state_button.state() {
smoother.push_value(val);
let smooth_temp = smoother.get_average();
let ramp_target_temp = plot.ramp().evaluate(measurement_time);
let error = ramp_target_temp - smooth_temp;
let pid_value = pid_controller.cycle(error, &delta_measurement);
duty_cycle = (util::clamp(pid_value, 0f32, 1f32) * 1000f32) as usize;
lcd.draw_point_color(
Point{
x: plot.transform_time(measurement_time),
y: plot::Plot::transform_ranges(model::Range{from: 0f32, to: 1f32}, plot::Y_PX_RANGE, pid_value)
}, Layer::Layer2, Color::from_hex(0x0000ff).to_argb1555());
//let pid_clamped = util::clamp(pid_value, 0f32, 1f32);
//temp += (pid_clamped - 0.3) * delta_measurement.to_secs() * 1.0;
} else {
duty_cycle = 0;
}
last_measurement_system_time = ticks;
}
pwm_gpio.set(ticks.to_msecs() % 1000 < duty_cycle);
// poll for new touch data
let mut touches = false;
for touch in &touch::touches(&mut i2c_3).unwrap() {
touches = true;
let touch = model::Touch{
location: Point{
x: touch.x,
y: touch.y
},
time: ticks
};
let touch_event = match last_touch_event {
Some(TouchDown(_)) | Some(TouchMove(_)) => TouchMove(touch),
None | Some(TouchUp(_)) => TouchDown(touch),
};
//Do not allow changing ramp in stopped state
match state_button.state() {
State::RUNNING | State::RESETTED =>
plot.handle_touch(touch_event, &mut lcd),
_ => {},
}
last_touch_event = Some(touch_event);
}
// Deliver touch-up events
if !touches && last_touch_event.is_some() {
let touch_event = match last_touch_event.unwrap() {
TouchDown(t) | TouchMove(t) if time::delta(&ticks,&t.time).to_msecs() > 200 => {
if let Some(new_state) = state_button.handle_touch(TouchUp(t), &mut lcd) {
match new_state {
State::RESETTED => {
break 'mainloop;
},
State::RUNNING => {
measurement_start_system_time = SYSCLOCK.get_ticks();
last_measurement_system_time = measurement_start_system_time;
},
_ => {},
}
}
plot.handle_touch(TouchUp(t), &mut lcd);
None
},
x => Some(x),
};
last_touch_event = touch_event;
}
}
}
}
/// Initialize temperature sensor on SPI_2 port (GPIO pins)
/// IMPORTANT: "Table 3. Arduino connectors" in the discovery board datasheet
// states SPI2_NSS is pin D10. This is wrong.AsMut
// SPI2_NSS is D5, as seen in "Figure 25: Arduino Uno connectors"
fn temp_sensor_init_spi2(gpio: &mut Gpio, spi_2: &'static mut Spi) -> Max6675 {
let sck_pin = (gpio::Port::PortI, gpio::Pin::Pin1);
let miso_pin = (gpio::Port::PortB, gpio::Pin::Pin14);
let mosi_pin = (gpio::Port::PortB, gpio::Pin::Pin15);
let nss_pin = (gpio::Port::PortI, gpio::Pin::Pin0);
gpio.to_alternate_function(sck_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure sck");
// TODO the MOSI pin is not necessarily necessary for MAX6675
gpio.to_alternate_function(mosi_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure mosi");
gpio.to_alternate_function(miso_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure MISO pin");
gpio.to_alternate_function(nss_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure NSS ");
return Max6675::init(spi_2);
}
| main | identifier_name |
main.rs | #![no_std]
#![no_main]
#![feature(asm)]
#![feature(collections)]
extern crate stm32f7_discovery as stm32f7;
extern crate collections;
extern crate r0;
pub mod plot;
pub mod model;
pub mod temp_sensor;
pub mod time;
pub mod util;
pub mod pid;
pub mod ramp;
pub mod state_button;
mod leak;
use stm32f7::{system_clock,board,embedded,sdram,lcd,touch,i2c};
use stm32f7::lcd::*;
use embedded::interfaces::gpio;
use embedded::interfaces::gpio::{Gpio};
use board::spi::Spi;
use time::*;
use util::*;
use plot::DragDirection;
use embedded::util::delay;
use model::TouchEvent::*;
use collections::*;
use collections::boxed::Box;
use leak::Leak;
use self::temp_sensor::{TemperatureSensor,Max6675};
use state_button::State;
static TTF: &[u8] = include_bytes!("RobotoMono-Bold.ttf");
#[no_mangle]
pub unsafe extern "C" fn reset() |
// WORKAROUND: rust compiler will inline & reorder fp instructions into
#[inline(never)] // reset() before the FPU is initialized
fn main(hw: board::Hardware) -> ! {
let board::Hardware {
rcc,
pwr,
flash,
fmc,
ltdc,
gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k,
spi_2,
i2c_3,
..
} = hw;
let mut gpio = Gpio::new(gpio_a,
gpio_b,
gpio_c,
gpio_d,
gpio_e,
gpio_f,
gpio_g,
gpio_h,
gpio_i,
gpio_j,
gpio_k);
system_clock::init(rcc, pwr, flash);
// Peripheral clock configuration
{
// enable all gpio ports
rcc.ahb1enr.update(|r| {
r.set_gpioaen(true);
r.set_gpioben(true);
r.set_gpiocen(true);
r.set_gpioden(true);
r.set_gpioeen(true);
r.set_gpiofen(true);
r.set_gpiogen(true);
r.set_gpiohen(true);
r.set_gpioien(true);
r.set_gpiojen(true);
r.set_gpioken(true);
});
// Enable SPI_2
rcc.apb1enr.update(|apb1enr| {
apb1enr.set_spi2en(true);
});
delay(1);
}
// i2c configuration
i2c::init_pins_and_clocks(rcc, &mut gpio);
let mut i2c_3 = i2c::init(i2c_3);
i2c_3.test_1();
i2c_3.test_2();
let mut temp_sensor = temp_sensor_init_spi2(&mut gpio, spi_2);
// init sdram (needed for display buffer)
sdram::init(rcc, fmc, &mut gpio);
let pwm_pin = (gpio::Port::PortI, gpio::Pin::Pin2);
let mut pwm_gpio = gpio.to_output(pwm_pin,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure pwm pin");
let axis_color = Color::from_hex(0xffffff);
let drag_color = Color::from_hex(0x000000);
let grid_color = Color::from_hex(0x444444);
// lcd controller
let mut lcd = lcd::init(ltdc, rcc, &mut gpio);
touch::check_family_id(&mut i2c_3).unwrap();
loop {
SYSCLOCK.reset();
lcd.clear_screen();
lcd.set_background_color(Color::from_hex(0x000000));
let plot_font = Box::new(Font::new(TTF, 11).unwrap()).leak();
let rtval_font = Box::new(Font::new(TTF, 14).unwrap()).leak();
let mut plot = plot::Plot::new(model::Range::new(0f32, (20*60) as f32),
model::Range::new(0f32, 200f32),
plot_font,
rtval_font,
axis_color,
grid_color,
drag_color,
80, // drag timeout
);
plot.draw_axis(&mut lcd);
//let mut pid_controller = pid::PIDController::new(0.3f32, 0.0f32, 0.0f32);
//let mut pid_controller = pid::PIDController::new(0.1f32, 0.0f32, 0.3f32); // Definitely better than first, but overshooting
//let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.3f32); // Not much different
let mut pid_controller = pid::PIDController::new(0.2f32, 0.0f32, 0.6f32); // Not much different
let mut smoother = pid::Smoother::new(10);
let mut measurement_start_system_time = SYSCLOCK.get_ticks();
let mut last_measurement_system_time = SYSCLOCK.get_ticks();
let mut duty_cycle: usize = 0;
let mut temp = 20f32;
let mut state_button = state_button::StateButton::new(
Color::from_hex(0x222222),
Rect{origin: Point{x: 440, y: 0}, width: 40, height: 40}
);
state_button.render(&mut lcd);
let mut last_touch_event = None;
'mainloop: loop {
let ticks = SYSCLOCK.get_ticks();
let delta_measurement = time::delta_checked(&last_measurement_system_time, &ticks);
if delta_measurement.to_msecs() >= 500 {
let val = temp_sensor.read();
let measurement_time = time::delta_checked(&measurement_start_system_time, &ticks).to_secs();
let measurement = model::TimeTemp{
time: measurement_time, // TODO just integer divide here?
temp: val as f32,
};
match state_button.state() {
State::RUNNING => plot.add_measurement(measurement, &mut lcd),
State::RESETTED => {
plot.set_measurement(model::TimeTemp{time: 0f32, temp: measurement.temp}, &mut lcd);
plot.update_ramp_start(&mut lcd);
},
State::STOPPED => {},
}
if let State::RUNNING = state_button.state() {
smoother.push_value(val);
let smooth_temp = smoother.get_average();
let ramp_target_temp = plot.ramp().evaluate(measurement_time);
let error = ramp_target_temp - smooth_temp;
let pid_value = pid_controller.cycle(error, &delta_measurement);
duty_cycle = (util::clamp(pid_value, 0f32, 1f32) * 1000f32) as usize;
lcd.draw_point_color(
Point{
x: plot.transform_time(measurement_time),
y: plot::Plot::transform_ranges(model::Range{from: 0f32, to: 1f32}, plot::Y_PX_RANGE, pid_value)
}, Layer::Layer2, Color::from_hex(0x0000ff).to_argb1555());
//let pid_clamped = util::clamp(pid_value, 0f32, 1f32);
//temp += (pid_clamped - 0.3) * delta_measurement.to_secs() * 1.0;
} else {
duty_cycle = 0;
}
last_measurement_system_time = ticks;
}
pwm_gpio.set(ticks.to_msecs() % 1000 < duty_cycle);
// poll for new touch data
let mut touches = false;
for touch in &touch::touches(&mut i2c_3).unwrap() {
touches = true;
let touch = model::Touch{
location: Point{
x: touch.x,
y: touch.y
},
time: ticks
};
let touch_event = match last_touch_event {
Some(TouchDown(_)) | Some(TouchMove(_)) => TouchMove(touch),
None | Some(TouchUp(_)) => TouchDown(touch),
};
//Do not allow changing ramp in stopped state
match state_button.state() {
State::RUNNING | State::RESETTED =>
plot.handle_touch(touch_event, &mut lcd),
_ => {},
}
last_touch_event = Some(touch_event);
}
// Deliver touch-up events
if !touches && last_touch_event.is_some() {
let touch_event = match last_touch_event.unwrap() {
TouchDown(t) | TouchMove(t) if time::delta(&ticks,&t.time).to_msecs() > 200 => {
if let Some(new_state) = state_button.handle_touch(TouchUp(t), &mut lcd) {
match new_state {
State::RESETTED => {
break 'mainloop;
},
State::RUNNING => {
measurement_start_system_time = SYSCLOCK.get_ticks();
last_measurement_system_time = measurement_start_system_time;
},
_ => {},
}
}
plot.handle_touch(TouchUp(t), &mut lcd);
None
},
x => Some(x),
};
last_touch_event = touch_event;
}
}
}
}
/// Initialize temperature sensor on SPI_2 port (GPIO pins)
/// IMPORTANT: "Table 3. Arduino connectors" in the discovery board datasheet
// states SPI2_NSS is pin D10. This is wrong.AsMut
// SPI2_NSS is D5, as seen in "Figure 25: Arduino Uno connectors"
fn temp_sensor_init_spi2(gpio: &mut Gpio, spi_2: &'static mut Spi) -> Max6675 {
let sck_pin = (gpio::Port::PortI, gpio::Pin::Pin1);
let miso_pin = (gpio::Port::PortB, gpio::Pin::Pin14);
let mosi_pin = (gpio::Port::PortB, gpio::Pin::Pin15);
let nss_pin = (gpio::Port::PortI, gpio::Pin::Pin0);
gpio.to_alternate_function(sck_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure sck");
// TODO the MOSI pin is not necessarily necessary for MAX6675
gpio.to_alternate_function(mosi_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure mosi");
gpio.to_alternate_function(miso_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure MISO pin");
gpio.to_alternate_function(nss_pin,
gpio::AlternateFunction::AF5,
gpio::OutputType::PushPull,
gpio::OutputSpeed::High,
gpio::Resistor::NoPull)
.expect("Could not configure NSS ");
return Max6675::init(spi_2);
}
| {
extern "C" {
static __DATA_LOAD: u32;
static __DATA_END: u32;
static mut __DATA_START: u32;
static mut __BSS_START: u32;
static mut __BSS_END: u32;
}
let data_load = &__DATA_LOAD;
let data_start = &mut __DATA_START;
let data_end = &__DATA_END;
let bss_start = &mut __BSS_START;
let bss_end = &__BSS_END;
r0::init_data(data_start, data_end, data_load);
r0::zero_bss(bss_start, bss_end);
stm32f7::heap::init();
// enable floating point unit
let scb = stm32f7::cortex_m::peripheral::scb_mut();
scb.cpacr.modify(|v| v | 0b1111 << 20);
asm!("DSB; ISB;"::::"volatile"); // pipeline flush
main(board::hw());
} | identifier_body |
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index.ts | import Chunk from '../Chunk';
import { optimizeChunks } from '../chunk-optimization';
import Graph from '../Graph';
import { createAddons } from '../utils/addons';
import { createAssetPluginHooks, finaliseAsset } from '../utils/assetHooks';
import commondir from '../utils/commondir';
import { Deprecation } from '../utils/deprecateOptions';
import error from '../utils/error';
import { writeFile } from '../utils/fs';
import getExportMode from '../utils/getExportMode';
import mergeOptions, { GenericConfigObject } from '../utils/mergeOptions';
import { basename, dirname, isAbsolute, resolve } from '../utils/path';
import { SOURCEMAPPING_URL } from '../utils/sourceMappingURL';
import { getTimings, initialiseTimers, timeEnd, timeStart } from '../utils/timers';
import { Watcher } from '../watch';
import {
InputOptions,
OutputBundle,
OutputChunk,
OutputFile,
OutputOptions,
Plugin,
RollupBuild,
RollupSingleFileBuild,
WarningHandler
} from './types';
function addDeprecations(deprecations: Deprecation[], warn: WarningHandler) {
const message = `The following options have been renamed — please update your config: ${deprecations
.map(option => `${option.old} -> ${option.new}`)
.join(', ')}`;
warn({
code: 'DEPRECATED_OPTIONS',
message,
deprecations
});
}
function checkInputOptions(options: InputOptions) {
if (options.transform || options.load || options.resolveId || options.resolveExternal) {
throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plugins'
);
}
}
function checkOutputOptions(options: OutputOptions) {
if (<string>options.format === 'es6') {
error({
message: 'The `es6` output format is deprecated – use `es` instead',
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (!options.format) {
error({
message: `You must specify output.format, which can be one of 'amd', 'cjs', 'system', 'esm', 'iife' or 'umd'`,
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (options.moduleId) {
if (options.amd) throw new Error('Cannot have both output.amd and output.moduleId');
}
}
const throwAsyncGenerateError = {
get() {
throw new Error(`bundle.generate(...) now returns a Promise instead of a { code, map } object`);
}
};
function appl | utOptions: InputOptions, plugin: Plugin) {
if (plugin.options) return plugin.options(inputOptions) || inputOptions;
return inputOptions;
}
function getInputOptions(rawInputOptions: GenericConfigObject): any {
if (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOptions: input 从命令行或配置文件与默认配置合并
// deprecations: 过时的参数列表，过时的参数，仍然会写入正确的地方
// optionError: 错误信息
let { inputOptions, deprecations, optionError } = mergeOptions({
config: rawInputOptions,
deprecateConfig: { input: true }
});
// 如果存在错误信息，直接输出到终端
if (optionError) inputOptions.onwarn({ message: optionError, code: 'UNKNOWN_OPTION' });
// 如果存在过时参数，直接输出到终端
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
// 检查是否存在一些 属性 如 transform 应放到插件里。（应该不会出现这种情况，因为inputOptions不可能会有）
checkInputOptions(inputOptions);
// 整理插件列表，过滤掉null,undefined等无效的插件，并确保是数组
const plugins = inputOptions.plugins;
inputOptions.plugins = Array.isArray(plugins)
? plugins.filter(Boolean)
: plugins
? [plugins]
: [];
// 依次调用每个插件的options方法
inputOptions = inputOptions.plugins.reduce(applyOptionHook, inputOptions);
// 实验代码分割,
if (!inputOptions.experimentalCodeSplitting) {
inputOptions.inlineDynamicImports = true; // 内联动态导入
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are only supported for experimentalCodeSplitting.'
});
}
// 内联动态导入
if (inputOptions.inlineDynamicImports) {
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are not supported for inlineDynamicImports.'
});
} else if (inputOptions.experimentalPreserveModules) {
// 实验保存模块
if (inputOptions.inlineDynamicImports)
error({
code: 'INVALID_OPTION',
message: `experimentalPreserveModules does not support the inlineDynamicImports option.`
});
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the manualChunks option.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the optimizeChunks option.'
});
}
return inputOptions;
}
let curWatcher: Watcher;
export function setWatcher(watcher: Watcher) {
curWatcher = watcher;
}
export default function rollup(
rawInputOptions: GenericConfigObject
): Promise<RollupSingleFileBuild | RollupBuild> {
try {
// 从命令行，配置文件，默认配置中获取配置信息，并调用每个插件的options方法
const inputOptions = getInputOptions(rawInputOptions);
// 当perf为true时，给插件的指定方法注入打印开始时间，结束时间
initialiseTimers(inputOptions);
const graph = new Graph(inputOptions, curWatcher);
curWatcher = undefined;
// remove the cache option from the memory after graph creation (cache is not used anymore)
const useCache = rawInputOptions.cache !== false;
delete inputOptions.cache;
delete rawInputOptions.cache;
timeStart('BUILD', 1);
return graph.pluginDriver
.hookParallel('buildStart')
.then(() =>
graph.build(
inputOptions.input,
inputOptions.manualChunks,
inputOptions.inlineDynamicImports,
inputOptions.experimentalPreserveModules
)
)
.then(
chunks =>
graph.pluginDriver.hookParallel('buildEnd').then(() => {
return chunks;
}),
err =>
graph.pluginDriver.hookParallel('buildEnd', [err]).then(() => {
throw err;
})
)
.then(chunks => {
timeEnd('BUILD', 1);
// TODO: deprecate legacy single chunk return
let singleChunk: Chunk | void;
const singleInput =
typeof inputOptions.input === 'string' ||
(inputOptions.input instanceof Array && inputOptions.input.length === 1);
//let imports: string[], exports: string[];
if (!inputOptions.experimentalPreserveModules) {
if (singleInput) {
for (const chunk of chunks) {
if (chunk.entryModule === undefined) continue;
if (singleChunk) {
singleChunk = undefined;
break;
}
singleChunk = chunk;
}
}
}
// ensure we only do one optimization pass per build
let optimized = false;
function generate(rawOutputOptions: GenericConfigObject, isWrite: boolean) {
const outputOptions = normalizeOutputOptions(inputOptions, rawOutputOptions);
if (inputOptions.experimentalCodeSplitting) {
if (typeof outputOptions.file === 'string' && typeof outputOptions.dir === 'string')
error({
code: 'INVALID_OPTION',
message:
'Build must set either output.file for a single-file build or output.dir when generating multiple chunks.'
});
if (chunks.length > 1) {
if (outputOptions.format === 'umd' || outputOptions.format === 'iife')
error({
code: 'INVALID_OPTION',
message:
'UMD and IIFE output formats are not supported with the experimentalCodeSplitting option.'
});
if (outputOptions.sourcemapFile)
error({
code: 'INVALID_OPTION',
message: '"sourcemapFile" is only supported for single-file builds.'
});
}
if (!singleChunk && typeof outputOptions.file === 'string')
error({
code: 'INVALID_OPTION',
message: singleInput
? 'When building a bundle using dynamic imports, the output.dir option must be used, not output.file. Alternatively set inlineDynamicImports: true to output a single file.'
: 'When building multiple entry point inputs, the output.dir option must be used, not output.file.'
});
}
if (!outputOptions.file && inputOptions.experimentalCodeSplitting)
singleChunk = undefined;
timeStart('GENERATE', 1);
// populate asset files into output
const assetFileNames = outputOptions.assetFileNames || 'assets/[name]-[hash][extname]';
const outputBundle: OutputBundle = graph.finaliseAssets(assetFileNames);
const inputBase = commondir(
chunks
.filter(chunk => chunk.entryModule && isAbsolute(chunk.entryModule.id))
.map(chunk => chunk.entryModule.id)
);
return graph.pluginDriver
.hookParallel('renderStart')
.then(() => createAddons(graph, outputOptions))
.then(addons => {
// pre-render all chunks
for (const chunk of chunks) {
if (!inputOptions.experimentalPreserveModules)
chunk.generateInternalExports(outputOptions);
if (chunk.isEntryModuleFacade)
chunk.exportMode = getExportMode(chunk, outputOptions);
}
for (const chunk of chunks) {
chunk.preRender(outputOptions, inputBase);
}
if (!optimized && inputOptions.optimizeChunks) {
optimizeChunks(chunks, outputOptions, inputOptions.chunkGroupingSize, inputBase);
optimized = true;
}
// name all chunks
const usedIds: Record<string, true> = {};
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk === singleChunk) {
singleChunk.id = basename(
outputOptions.file ||
(inputOptions.input instanceof Array
? inputOptions.input[0]
: <string>inputOptions.input)
);
} else if (inputOptions.experimentalPreserveModules) {
chunk.generateIdPreserveModules(inputBase, usedIds);
} else {
let pattern, patternName;
if (chunk.isEntryModuleFacade) {
pattern = outputOptions.entryFileNames || '[name].js';
patternName = 'output.entryFileNames';
} else {
pattern = outputOptions.chunkFileNames || '[name]-[hash].js';
patternName = 'output.chunkFileNames';
}
chunk.generateId(pattern, patternName, addons, outputOptions, usedIds);
}
usedIds[chunk.id] = true;
}
// assign to outputBundle
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
outputBundle[chunk.id] = {
fileName: chunk.id,
isEntry: chunk.entryModule !== undefined,
imports: chunk.getImportIds(),
exports: chunk.getExportNames(),
modules: chunk.renderedModules,
code: undefined,
map: undefined
};
}
return Promise.all(
chunks.map(chunk => {
const outputChunk = <OutputChunk>outputBundle[chunk.id];
return chunk.render(outputOptions, addons, outputChunk).then(rendered => {
outputChunk.code = rendered.code;
outputChunk.map = rendered.map;
return graph.pluginDriver.hookParallel('ongenerate', [
{ bundle: outputChunk, ...outputOptions },
outputChunk
]);
});
})
).then(() => {});
})
.catch(error =>
graph.pluginDriver.hookParallel('renderError', [error]).then(() => {
throw error;
})
)
.then(() => {
// run generateBundle hook
// assets emitted during generateBundle are unique to that specific generate call
const assets = new Map(graph.assetsById);
const generateAssetPluginHooks = createAssetPluginHooks(
assets,
outputBundle,
assetFileNames
);
return graph.pluginDriver
.hookSeq('generateBundle', [outputOptions, outputBundle, isWrite], context => ({
...context,
...generateAssetPluginHooks
}))
.then(() => {
// throw errors for assets not finalised with a source
assets.forEach(asset => {
if (asset.fileName === undefined)
finaliseAsset(asset, outputBundle, assetFileNames);
});
});
})
.then(() => {
timeEnd('GENERATE', 1);
return outputBundle;
});
}
const cache = useCache ? graph.getCache() : undefined;
const result: RollupSingleFileBuild | RollupBuild = {
cache,
watchFiles: Object.keys(graph.watchFiles),
generate: <any>((rawOutputOptions: GenericConfigObject) => {
const promise = generate(rawOutputOptions, false).then(
result =>
inputOptions.experimentalCodeSplitting
? { output: result }
: <OutputChunk>result[chunks[0].id]
);
Object.defineProperty(promise, 'code', throwAsyncGenerateError);
Object.defineProperty(promise, 'map', throwAsyncGenerateError);
return promise;
}),
write: <any>((outputOptions: OutputOptions) => {
if (
inputOptions.experimentalCodeSplitting &&
(!outputOptions || (!outputOptions.dir && !outputOptions.file))
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file or output.dir for the build.'
});
} else if (
!inputOptions.experimentalCodeSplitting &&
(!outputOptions || !outputOptions.file)
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file.'
});
}
return generate(outputOptions, true).then(outputBundle =>
Promise.all(
Object.keys(outputBundle).map(chunkId => {
return writeOutputFile(
graph,
result,
chunkId,
outputBundle[chunkId],
outputOptions
);
})
).then(
() =>
inputOptions.experimentalCodeSplitting
? { output: outputBundle }
: <OutputChunk>outputBundle[chunks[0].id]
)
);
})
};
if (!inputOptions.experimentalCodeSplitting) {
(<any>result).imports = (<Chunk>singleChunk).getImportIds();
(<any>result).exports = (<Chunk>singleChunk).getExportNames();
(<any>result).modules = (cache || graph.getCache()).modules;
}
if (inputOptions.perf === true) result.getTimings = getTimings;
return result;
});
} catch (err) {
return Promise.reject(err);
}
}
function isOutputChunk(file: OutputFile): file is OutputChunk {
return typeof (<OutputChunk>file).code === 'string';
}
function writeOutputFile(
graph: Graph,
build: RollupBuild | RollupSingleFileBuild,
outputFileName: string,
outputFile: OutputFile,
outputOptions: OutputOptions
): Promise<void> {
const filename = resolve(outputOptions.dir || dirname(outputOptions.file), outputFileName);
let writeSourceMapPromise: Promise<void>;
let source: string | Buffer;
if (isOutputChunk(outputFile)) {
source = outputFile.code;
if (outputOptions.sourcemap && outputFile.map) {
let url: string;
if (outputOptions.sourcemap === 'inline') {
url = outputFile.map.toUrl();
} else {
url = `${basename(outputFileName)}.map`;
writeSourceMapPromise = writeFile(`${filename}.map`, outputFile.map.toString());
}
source += `//# ${SOURCEMAPPING_URL}=${url}\n`;
}
} else {
source = outputFile;
}
return writeFile(filename, source)
.then(() => writeSourceMapPromise)
.then(
() =>
isOutputChunk(outputFile) &&
graph.pluginDriver.hookSeq('onwrite', [
{
bundle: build,
...outputOptions
},
outputFile
])
)
.then(() => {});
}
function normalizeOutputOptions(
inputOptions: GenericConfigObject,
rawOutputOptions: GenericConfigObject
): OutputOptions {
if (!rawOutputOptions) {
throw new Error('You must supply an options object');
}
// since deprecateOptions, adds the output properties
// to `inputOptions` so adding that lastly
const consolidatedOutputOptions = {
output: { ...rawOutputOptions, ...rawOutputOptions.output, ...inputOptions.output }
};
const mergedOptions = mergeOptions({
// just for backward compatiblity to fallback on root
// if the option isn't present in `output`
config: consolidatedOutputOptions,
deprecateConfig: { output: true }
});
if (mergedOptions.optionError) throw new Error(mergedOptions.optionError);
// now outputOptions is an array, but rollup.rollup API doesn't support arrays
const outputOptions = mergedOptions.outputOptions[0];
const deprecations = mergedOptions.deprecations;
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
checkOutputOptions(outputOptions);
return outputOptions;
}
| yOptionHook(inp | identifier_name |
index.ts | import Chunk from '../Chunk';
import { optimizeChunks } from '../chunk-optimization';
import Graph from '../Graph';
import { createAddons } from '../utils/addons';
import { createAssetPluginHooks, finaliseAsset } from '../utils/assetHooks';
import commondir from '../utils/commondir';
import { Deprecation } from '../utils/deprecateOptions';
import error from '../utils/error';
import { writeFile } from '../utils/fs';
import getExportMode from '../utils/getExportMode';
import mergeOptions, { GenericConfigObject } from '../utils/mergeOptions';
import { basename, dirname, isAbsolute, resolve } from '../utils/path';
import { SOURCEMAPPING_URL } from '../utils/sourceMappingURL';
import { getTimings, initialiseTimers, timeEnd, timeStart } from '../utils/timers';
import { Watcher } from '../watch';
import {
InputOptions,
OutputBundle,
OutputChunk,
OutputFile,
OutputOptions,
Plugin,
RollupBuild,
RollupSingleFileBuild,
WarningHandler
} from './types';
function addDeprecations(deprecations: Deprecation[], warn: WarningHandler) {
const message = `The following options have been renamed — please update your config: ${deprecations
.map(option => `${option.old} -> ${option.new}`)
.join(', ')}`;
warn({
code: 'DEPRECATED_OPTIONS',
message,
deprecations
});
}
function checkInputOptions(options: InputOptions) {
if (options.transform || options.load || options.resolveId || options.resolveExternal) {
throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plugins'
);
}
}
function checkOutputOptions(options: OutputOptions) {
if (<string>options.format === 'es6') {
error({
message: 'The `es6` output format is deprecated – use `es` instead',
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (!options.format) {
error({
message: `You must specify output.format, which can be one of 'amd', 'cjs', 'system', 'esm', 'iife' or 'umd'`,
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (options.moduleId) {
if (options.amd) throw new Error('Cannot have both output.amd and output.moduleId');
}
}
const throwAsyncGenerateError = {
get() {
throw new Error(`bundle.generate(...) now returns a Promise instead of a { code, map } object`);
}
};
function applyOptionHook(inputOptions: InputOptions, plugin: Plugin) {
if (plugin.options) return plugin.options(inputOptions) || inputOptions;
return inputOptions;
}
function getInputOptions(rawInputOptions: GenericConfigObject): any {
if (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOptions: input 从命令行或配置文件与默认配置合并
// deprecations: 过时的参数列表，过时的参数，仍然会写入正确的地方
// optionError: 错误信息
let { inputOptions, deprecations, optionError } = mergeOptions({
config: rawInputOptions,
deprecateConfig: { input: true }
});
// 如果存在错误信息，直接输出到终端
if (optionError) inputOptions.onwarn({ message: optionError, code: 'UNKNOWN_OPTION' });
// 如果存在过时参数，直接输出到终端
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
// 检查是否存在一些 属性 如 transform 应放到插件里。（应该不会出现这种情况，因为inputOptions不可能会有）
checkInputOptions(inputOptions);
// 整理插件列表，过滤掉null,undefined等无效的插件，并确保是数组
const plugins = inputOptions.plugins;
inputOptions.plugins = Array.isArray(plugins)
? plugins.filter(Boolean)
: plugins
? [plugins]
: [];
// 依次调用每个插件的options方法
inputOptions = inputOptions.plugins.reduce(applyOptionHook, inputOptions);
// 实验代码分割,
if (!inputOptions.experimentalCodeSplitting) {
inputOptions.inlineDynamicImports = true; // 内联动态导入
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are only supported for experimentalCodeSplitting.'
});
}
// 内联动态导入
if (inputOptions.inlineDynamicImports) {
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are not supported for inlineDynamicImports.'
});
} else if (inputOptions.experimentalPreserveModules) {
// 实验保存模块
if (inputOptions.inlineDynamicImports)
error({
code: 'INVALID_OPTION',
message: `experimentalPreserveModules does not support the inlineDynamicImports option.`
});
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the manualChunks option.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the optimizeChunks option.'
});
}
return inputOptions;
}
let curWatcher: Watcher;
export function setWatcher(watcher: Watcher) {
curWatcher = watcher;
}
export default function rollup(
rawInputOptions: GenericConfigObject
): Promise<RollupSingleFileBuild | RollupBuild> {
try {
// 从命令行，配置文件，默认配置中获取配置信息，并调用每个插件的options方法
const inputOptions = getInputOptions(rawInputOptions);
// 当perf为true时，给插件的指定方法注入打印开始时间，结束时间
initialiseTimers(inputOptions);
const graph = new Graph(inputOptions, curWatcher);
curWatcher = undefined;
// remove the cache option from the memory after graph creation (cache is not used anymore)
const useCache = rawInputOptions.cache !== false;
delete inputOptions.cache;
delete rawInputOptions.cache;
timeStart('BUILD', 1);
return graph.pluginDriver
.hookParallel('buildStart')
.then(() =>
graph.build(
inputOptions.input,
inputOptions.manualChunks,
inputOptions.inlineDynamicImports,
inputOptions.experimentalPreserveModules
)
)
.then(
chunks =>
graph.pluginDriver.hookParallel('buildEnd').then(() => {
return chunks;
}),
err =>
graph.pluginDriver.hookParallel('buildEnd', [err]).then(() => {
throw err;
})
)
.then(chunks => {
timeEnd('BUILD', 1);
// TODO: deprecate legacy single chunk return
let singleChunk: Chunk | void;
const singleInput =
typeof inputOptions.input === 'string' ||
(inputOptions.input instanceof Array && inputOptions.input.length === 1);
//let imports: string[], exports: string[];
if (!inputOptions.experimentalPreserveModules) {
if (singleInput) {
for (const chunk of chunks) {
if (chunk.entryModule === undefined) continue;
if (singleChunk) {
singleChunk = undefined;
break;
}
singleChunk = chunk;
}
}
}
// ensure we only do one optimization pass per build
let optimized = false;
function generate(rawOutputOptions: GenericConfigObject, isWrite: boolean) {
const outputOptions = normalizeOutputOptions(inputOptions, rawOutputOptions);
if (inputOptions.experimentalCodeSplitting) {
if (typeof outputOptions.file === 'string' && typeof outputOptions.dir === 'string')
error({
code: 'INVALID_OPTION',
message:
'Build must set either output.file for a single-file build or output.dir when generating multiple chunks.'
});
if (chunks.length > 1) {
if (outputOptions.format === 'umd' || outputOptions.format === 'iife')
error({
code: 'INVALID_OPTION',
message:
'UMD and IIFE output formats are not supported with the experimentalCodeSplitting option.'
});
if (outputOptions.sourcemapFile)
error({
code: 'INVALID_OPTION',
message: '"sourcemapFile" is only supported for single-file builds.'
});
}
if (!singleChunk && typeof outputOptions.file === 'string')
error({
code: 'INVALID_OPTION',
message: singleInput
? 'When building a bundle using dynamic imports, the output.dir option must be used, not output.file. Alternatively set inlineDynamicImports: true to output a single file.'
: 'When building multiple entry point inputs, the output.dir option must be used, not output.file.'
});
}
if (!outputOptions.file && inputOptions.experimentalCodeSplitting)
singleChunk = undefined;
timeStart('GENERATE', 1);
// populate asset files into output
const assetFileNames = outputOptions.assetFileNames || 'assets/[name]-[hash][extname]';
const outputBundle: OutputBundle = graph.finaliseAssets(assetFileNames);
const inputBase = commondir(
chunks
.filter(chunk => chunk.entryModule && isAbsolute(chunk.entryModule.id))
.map(chunk => chunk.entryModule.id)
);
return graph.pluginDriver
.hookParallel('renderStart')
.then(() => createAddons(graph, outputOptions)) | .then(addons => {
// pre-render all chunks
for (const chunk of chunks) {
if (!inputOptions.experimentalPreserveModules)
chunk.generateInternalExports(outputOptions);
if (chunk.isEntryModuleFacade)
chunk.exportMode = getExportMode(chunk, outputOptions);
}
for (const chunk of chunks) {
chunk.preRender(outputOptions, inputBase);
}
if (!optimized && inputOptions.optimizeChunks) {
optimizeChunks(chunks, outputOptions, inputOptions.chunkGroupingSize, inputBase);
optimized = true;
}
// name all chunks
const usedIds: Record<string, true> = {};
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk === singleChunk) {
singleChunk.id = basename(
outputOptions.file ||
(inputOptions.input instanceof Array
? inputOptions.input[0]
: <string>inputOptions.input)
);
} else if (inputOptions.experimentalPreserveModules) {
chunk.generateIdPreserveModules(inputBase, usedIds);
} else {
let pattern, patternName;
if (chunk.isEntryModuleFacade) {
pattern = outputOptions.entryFileNames || '[name].js';
patternName = 'output.entryFileNames';
} else {
pattern = outputOptions.chunkFileNames || '[name]-[hash].js';
patternName = 'output.chunkFileNames';
}
chunk.generateId(pattern, patternName, addons, outputOptions, usedIds);
}
usedIds[chunk.id] = true;
}
// assign to outputBundle
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
outputBundle[chunk.id] = {
fileName: chunk.id,
isEntry: chunk.entryModule !== undefined,
imports: chunk.getImportIds(),
exports: chunk.getExportNames(),
modules: chunk.renderedModules,
code: undefined,
map: undefined
};
}
return Promise.all(
chunks.map(chunk => {
const outputChunk = <OutputChunk>outputBundle[chunk.id];
return chunk.render(outputOptions, addons, outputChunk).then(rendered => {
outputChunk.code = rendered.code;
outputChunk.map = rendered.map;
return graph.pluginDriver.hookParallel('ongenerate', [
{ bundle: outputChunk, ...outputOptions },
outputChunk
]);
});
})
).then(() => {});
})
.catch(error =>
graph.pluginDriver.hookParallel('renderError', [error]).then(() => {
throw error;
})
)
.then(() => {
// run generateBundle hook
// assets emitted during generateBundle are unique to that specific generate call
const assets = new Map(graph.assetsById);
const generateAssetPluginHooks = createAssetPluginHooks(
assets,
outputBundle,
assetFileNames
);
return graph.pluginDriver
.hookSeq('generateBundle', [outputOptions, outputBundle, isWrite], context => ({
...context,
...generateAssetPluginHooks
}))
.then(() => {
// throw errors for assets not finalised with a source
assets.forEach(asset => {
if (asset.fileName === undefined)
finaliseAsset(asset, outputBundle, assetFileNames);
});
});
})
.then(() => {
timeEnd('GENERATE', 1);
return outputBundle;
});
}
const cache = useCache ? graph.getCache() : undefined;
const result: RollupSingleFileBuild | RollupBuild = {
cache,
watchFiles: Object.keys(graph.watchFiles),
generate: <any>((rawOutputOptions: GenericConfigObject) => {
const promise = generate(rawOutputOptions, false).then(
result =>
inputOptions.experimentalCodeSplitting
? { output: result }
: <OutputChunk>result[chunks[0].id]
);
Object.defineProperty(promise, 'code', throwAsyncGenerateError);
Object.defineProperty(promise, 'map', throwAsyncGenerateError);
return promise;
}),
write: <any>((outputOptions: OutputOptions) => {
if (
inputOptions.experimentalCodeSplitting &&
(!outputOptions || (!outputOptions.dir && !outputOptions.file))
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file or output.dir for the build.'
});
} else if (
!inputOptions.experimentalCodeSplitting &&
(!outputOptions || !outputOptions.file)
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file.'
});
}
return generate(outputOptions, true).then(outputBundle =>
Promise.all(
Object.keys(outputBundle).map(chunkId => {
return writeOutputFile(
graph,
result,
chunkId,
outputBundle[chunkId],
outputOptions
);
})
).then(
() =>
inputOptions.experimentalCodeSplitting
? { output: outputBundle }
: <OutputChunk>outputBundle[chunks[0].id]
)
);
})
};
if (!inputOptions.experimentalCodeSplitting) {
(<any>result).imports = (<Chunk>singleChunk).getImportIds();
(<any>result).exports = (<Chunk>singleChunk).getExportNames();
(<any>result).modules = (cache || graph.getCache()).modules;
}
if (inputOptions.perf === true) result.getTimings = getTimings;
return result;
});
} catch (err) {
return Promise.reject(err);
}
}
function isOutputChunk(file: OutputFile): file is OutputChunk {
return typeof (<OutputChunk>file).code === 'string';
}
function writeOutputFile(
graph: Graph,
build: RollupBuild | RollupSingleFileBuild,
outputFileName: string,
outputFile: OutputFile,
outputOptions: OutputOptions
): Promise<void> {
const filename = resolve(outputOptions.dir || dirname(outputOptions.file), outputFileName);
let writeSourceMapPromise: Promise<void>;
let source: string | Buffer;
if (isOutputChunk(outputFile)) {
source = outputFile.code;
if (outputOptions.sourcemap && outputFile.map) {
let url: string;
if (outputOptions.sourcemap === 'inline') {
url = outputFile.map.toUrl();
} else {
url = `${basename(outputFileName)}.map`;
writeSourceMapPromise = writeFile(`${filename}.map`, outputFile.map.toString());
}
source += `//# ${SOURCEMAPPING_URL}=${url}\n`;
}
} else {
source = outputFile;
}
return writeFile(filename, source)
.then(() => writeSourceMapPromise)
.then(
() =>
isOutputChunk(outputFile) &&
graph.pluginDriver.hookSeq('onwrite', [
{
bundle: build,
...outputOptions
},
outputFile
])
)
.then(() => {});
}
function normalizeOutputOptions(
inputOptions: GenericConfigObject,
rawOutputOptions: GenericConfigObject
): OutputOptions {
if (!rawOutputOptions) {
throw new Error('You must supply an options object');
}
// since deprecateOptions, adds the output properties
// to `inputOptions` so adding that lastly
const consolidatedOutputOptions = {
output: { ...rawOutputOptions, ...rawOutputOptions.output, ...inputOptions.output }
};
const mergedOptions = mergeOptions({
// just for backward compatiblity to fallback on root
// if the option isn't present in `output`
config: consolidatedOutputOptions,
deprecateConfig: { output: true }
});
if (mergedOptions.optionError) throw new Error(mergedOptions.optionError);
// now outputOptions is an array, but rollup.rollup API doesn't support arrays
const outputOptions = mergedOptions.outputOptions[0];
const deprecations = mergedOptions.deprecations;
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
checkOutputOptions(outputOptions);
return outputOptions;
} | random_line_split | |
index.ts | import Chunk from '../Chunk';
import { optimizeChunks } from '../chunk-optimization';
import Graph from '../Graph';
import { createAddons } from '../utils/addons';
import { createAssetPluginHooks, finaliseAsset } from '../utils/assetHooks';
import commondir from '../utils/commondir';
import { Deprecation } from '../utils/deprecateOptions';
import error from '../utils/error';
import { writeFile } from '../utils/fs';
import getExportMode from '../utils/getExportMode';
import mergeOptions, { GenericConfigObject } from '../utils/mergeOptions';
import { basename, dirname, isAbsolute, resolve } from '../utils/path';
import { SOURCEMAPPING_URL } from '../utils/sourceMappingURL';
import { getTimings, initialiseTimers, timeEnd, timeStart } from '../utils/timers';
import { Watcher } from '../watch';
import {
InputOptions,
OutputBundle,
OutputChunk,
OutputFile,
OutputOptions,
Plugin,
RollupBuild,
RollupSingleFileBuild,
WarningHandler
} from './types';
function addDeprecations(deprecations: Deprecation[], warn: WarningHandler) | function checkInputOptions(options: InputOptions) {
if (options.transform || options.load || options.resolveId || options.resolveExternal) {
throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plugins'
);
}
}
function checkOutputOptions(options: OutputOptions) {
if (<string>options.format === 'es6') {
error({
message: 'The `es6` output format is deprecated – use `es` instead',
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (!options.format) {
error({
message: `You must specify output.format, which can be one of 'amd', 'cjs', 'system', 'esm', 'iife' or 'umd'`,
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (options.moduleId) {
if (options.amd) throw new Error('Cannot have both output.amd and output.moduleId');
}
}
const throwAsyncGenerateError = {
get() {
throw new Error(`bundle.generate(...) now returns a Promise instead of a { code, map } object`);
}
};
function applyOptionHook(inputOptions: InputOptions, plugin: Plugin) {
if (plugin.options) return plugin.options(inputOptions) || inputOptions;
return inputOptions;
}
function getInputOptions(rawInputOptions: GenericConfigObject): any {
if (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOptions: input 从命令行或配置文件与默认配置合并
// deprecations: 过时的参数列表，过时的参数，仍然会写入正确的地方
// optionError: 错误信息
let { inputOptions, deprecations, optionError } = mergeOptions({
config: rawInputOptions,
deprecateConfig: { input: true }
});
// 如果存在错误信息，直接输出到终端
if (optionError) inputOptions.onwarn({ message: optionError, code: 'UNKNOWN_OPTION' });
// 如果存在过时参数，直接输出到终端
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
// 检查是否存在一些 属性 如 transform 应放到插件里。（应该不会出现这种情况，因为inputOptions不可能会有）
checkInputOptions(inputOptions);
// 整理插件列表，过滤掉null,undefined等无效的插件，并确保是数组
const plugins = inputOptions.plugins;
inputOptions.plugins = Array.isArray(plugins)
? plugins.filter(Boolean)
: plugins
? [plugins]
: [];
// 依次调用每个插件的options方法
inputOptions = inputOptions.plugins.reduce(applyOptionHook, inputOptions);
// 实验代码分割,
if (!inputOptions.experimentalCodeSplitting) {
inputOptions.inlineDynamicImports = true; // 内联动态导入
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are only supported for experimentalCodeSplitting.'
});
}
// 内联动态导入
if (inputOptions.inlineDynamicImports) {
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are not supported for inlineDynamicImports.'
});
} else if (inputOptions.experimentalPreserveModules) {
// 实验保存模块
if (inputOptions.inlineDynamicImports)
error({
code: 'INVALID_OPTION',
message: `experimentalPreserveModules does not support the inlineDynamicImports option.`
});
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the manualChunks option.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the optimizeChunks option.'
});
}
return inputOptions;
}
let curWatcher: Watcher;
export function setWatcher(watcher: Watcher) {
curWatcher = watcher;
}
export default function rollup(
rawInputOptions: GenericConfigObject
): Promise<RollupSingleFileBuild | RollupBuild> {
try {
// 从命令行，配置文件，默认配置中获取配置信息，并调用每个插件的options方法
const inputOptions = getInputOptions(rawInputOptions);
// 当perf为true时，给插件的指定方法注入打印开始时间，结束时间
initialiseTimers(inputOptions);
const graph = new Graph(inputOptions, curWatcher);
curWatcher = undefined;
// remove the cache option from the memory after graph creation (cache is not used anymore)
const useCache = rawInputOptions.cache !== false;
delete inputOptions.cache;
delete rawInputOptions.cache;
timeStart('BUILD', 1);
return graph.pluginDriver
.hookParallel('buildStart')
.then(() =>
graph.build(
inputOptions.input,
inputOptions.manualChunks,
inputOptions.inlineDynamicImports,
inputOptions.experimentalPreserveModules
)
)
.then(
chunks =>
graph.pluginDriver.hookParallel('buildEnd').then(() => {
return chunks;
}),
err =>
graph.pluginDriver.hookParallel('buildEnd', [err]).then(() => {
throw err;
})
)
.then(chunks => {
timeEnd('BUILD', 1);
// TODO: deprecate legacy single chunk return
let singleChunk: Chunk | void;
const singleInput =
typeof inputOptions.input === 'string' ||
(inputOptions.input instanceof Array && inputOptions.input.length === 1);
//let imports: string[], exports: string[];
if (!inputOptions.experimentalPreserveModules) {
if (singleInput) {
for (const chunk of chunks) {
if (chunk.entryModule === undefined) continue;
if (singleChunk) {
singleChunk = undefined;
break;
}
singleChunk = chunk;
}
}
}
// ensure we only do one optimization pass per build
let optimized = false;
function generate(rawOutputOptions: GenericConfigObject, isWrite: boolean) {
const outputOptions = normalizeOutputOptions(inputOptions, rawOutputOptions);
if (inputOptions.experimentalCodeSplitting) {
if (typeof outputOptions.file === 'string' && typeof outputOptions.dir === 'string')
error({
code: 'INVALID_OPTION',
message:
'Build must set either output.file for a single-file build or output.dir when generating multiple chunks.'
});
if (chunks.length > 1) {
if (outputOptions.format === 'umd' || outputOptions.format === 'iife')
error({
code: 'INVALID_OPTION',
message:
'UMD and IIFE output formats are not supported with the experimentalCodeSplitting option.'
});
if (outputOptions.sourcemapFile)
error({
code: 'INVALID_OPTION',
message: '"sourcemapFile" is only supported for single-file builds.'
});
}
if (!singleChunk && typeof outputOptions.file === 'string')
error({
code: 'INVALID_OPTION',
message: singleInput
? 'When building a bundle using dynamic imports, the output.dir option must be used, not output.file. Alternatively set inlineDynamicImports: true to output a single file.'
: 'When building multiple entry point inputs, the output.dir option must be used, not output.file.'
});
}
if (!outputOptions.file && inputOptions.experimentalCodeSplitting)
singleChunk = undefined;
timeStart('GENERATE', 1);
// populate asset files into output
const assetFileNames = outputOptions.assetFileNames || 'assets/[name]-[hash][extname]';
const outputBundle: OutputBundle = graph.finaliseAssets(assetFileNames);
const inputBase = commondir(
chunks
.filter(chunk => chunk.entryModule && isAbsolute(chunk.entryModule.id))
.map(chunk => chunk.entryModule.id)
);
return graph.pluginDriver
.hookParallel('renderStart')
.then(() => createAddons(graph, outputOptions))
.then(addons => {
// pre-render all chunks
for (const chunk of chunks) {
if (!inputOptions.experimentalPreserveModules)
chunk.generateInternalExports(outputOptions);
if (chunk.isEntryModuleFacade)
chunk.exportMode = getExportMode(chunk, outputOptions);
}
for (const chunk of chunks) {
chunk.preRender(outputOptions, inputBase);
}
if (!optimized && inputOptions.optimizeChunks) {
optimizeChunks(chunks, outputOptions, inputOptions.chunkGroupingSize, inputBase);
optimized = true;
}
// name all chunks
const usedIds: Record<string, true> = {};
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk === singleChunk) {
singleChunk.id = basename(
outputOptions.file ||
(inputOptions.input instanceof Array
? inputOptions.input[0]
: <string>inputOptions.input)
);
} else if (inputOptions.experimentalPreserveModules) {
chunk.generateIdPreserveModules(inputBase, usedIds);
} else {
let pattern, patternName;
if (chunk.isEntryModuleFacade) {
pattern = outputOptions.entryFileNames || '[name].js';
patternName = 'output.entryFileNames';
} else {
pattern = outputOptions.chunkFileNames || '[name]-[hash].js';
patternName = 'output.chunkFileNames';
}
chunk.generateId(pattern, patternName, addons, outputOptions, usedIds);
}
usedIds[chunk.id] = true;
}
// assign to outputBundle
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
outputBundle[chunk.id] = {
fileName: chunk.id,
isEntry: chunk.entryModule !== undefined,
imports: chunk.getImportIds(),
exports: chunk.getExportNames(),
modules: chunk.renderedModules,
code: undefined,
map: undefined
};
}
return Promise.all(
chunks.map(chunk => {
const outputChunk = <OutputChunk>outputBundle[chunk.id];
return chunk.render(outputOptions, addons, outputChunk).then(rendered => {
outputChunk.code = rendered.code;
outputChunk.map = rendered.map;
return graph.pluginDriver.hookParallel('ongenerate', [
{ bundle: outputChunk, ...outputOptions },
outputChunk
]);
});
})
).then(() => {});
})
.catch(error =>
graph.pluginDriver.hookParallel('renderError', [error]).then(() => {
throw error;
})
)
.then(() => {
// run generateBundle hook
// assets emitted during generateBundle are unique to that specific generate call
const assets = new Map(graph.assetsById);
const generateAssetPluginHooks = createAssetPluginHooks(
assets,
outputBundle,
assetFileNames
);
return graph.pluginDriver
.hookSeq('generateBundle', [outputOptions, outputBundle, isWrite], context => ({
...context,
...generateAssetPluginHooks
}))
.then(() => {
// throw errors for assets not finalised with a source
assets.forEach(asset => {
if (asset.fileName === undefined)
finaliseAsset(asset, outputBundle, assetFileNames);
});
});
})
.then(() => {
timeEnd('GENERATE', 1);
return outputBundle;
});
}
const cache = useCache ? graph.getCache() : undefined;
const result: RollupSingleFileBuild | RollupBuild = {
cache,
watchFiles: Object.keys(graph.watchFiles),
generate: <any>((rawOutputOptions: GenericConfigObject) => {
const promise = generate(rawOutputOptions, false).then(
result =>
inputOptions.experimentalCodeSplitting
? { output: result }
: <OutputChunk>result[chunks[0].id]
);
Object.defineProperty(promise, 'code', throwAsyncGenerateError);
Object.defineProperty(promise, 'map', throwAsyncGenerateError);
return promise;
}),
write: <any>((outputOptions: OutputOptions) => {
if (
inputOptions.experimentalCodeSplitting &&
(!outputOptions || (!outputOptions.dir && !outputOptions.file))
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file or output.dir for the build.'
});
} else if (
!inputOptions.experimentalCodeSplitting &&
(!outputOptions || !outputOptions.file)
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file.'
});
}
return generate(outputOptions, true).then(outputBundle =>
Promise.all(
Object.keys(outputBundle).map(chunkId => {
return writeOutputFile(
graph,
result,
chunkId,
outputBundle[chunkId],
outputOptions
);
})
).then(
() =>
inputOptions.experimentalCodeSplitting
? { output: outputBundle }
: <OutputChunk>outputBundle[chunks[0].id]
)
);
})
};
if (!inputOptions.experimentalCodeSplitting) {
(<any>result).imports = (<Chunk>singleChunk).getImportIds();
(<any>result).exports = (<Chunk>singleChunk).getExportNames();
(<any>result).modules = (cache || graph.getCache()).modules;
}
if (inputOptions.perf === true) result.getTimings = getTimings;
return result;
});
} catch (err) {
return Promise.reject(err);
}
}
function isOutputChunk(file: OutputFile): file is OutputChunk {
return typeof (<OutputChunk>file).code === 'string';
}
function writeOutputFile(
graph: Graph,
build: RollupBuild | RollupSingleFileBuild,
outputFileName: string,
outputFile: OutputFile,
outputOptions: OutputOptions
): Promise<void> {
const filename = resolve(outputOptions.dir || dirname(outputOptions.file), outputFileName);
let writeSourceMapPromise: Promise<void>;
let source: string | Buffer;
if (isOutputChunk(outputFile)) {
source = outputFile.code;
if (outputOptions.sourcemap && outputFile.map) {
let url: string;
if (outputOptions.sourcemap === 'inline') {
url = outputFile.map.toUrl();
} else {
url = `${basename(outputFileName)}.map`;
writeSourceMapPromise = writeFile(`${filename}.map`, outputFile.map.toString());
}
source += `//# ${SOURCEMAPPING_URL}=${url}\n`;
}
} else {
source = outputFile;
}
return writeFile(filename, source)
.then(() => writeSourceMapPromise)
.then(
() =>
isOutputChunk(outputFile) &&
graph.pluginDriver.hookSeq('onwrite', [
{
bundle: build,
...outputOptions
},
outputFile
])
)
.then(() => {});
}
function normalizeOutputOptions(
inputOptions: GenericConfigObject,
rawOutputOptions: GenericConfigObject
): OutputOptions {
if (!rawOutputOptions) {
throw new Error('You must supply an options object');
}
// since deprecateOptions, adds the output properties
// to `inputOptions` so adding that lastly
const consolidatedOutputOptions = {
output: { ...rawOutputOptions, ...rawOutputOptions.output, ...inputOptions.output }
};
const mergedOptions = mergeOptions({
// just for backward compatiblity to fallback on root
// if the option isn't present in `output`
config: consolidatedOutputOptions,
deprecateConfig: { output: true }
});
if (mergedOptions.optionError) throw new Error(mergedOptions.optionError);
// now outputOptions is an array, but rollup.rollup API doesn't support arrays
const outputOptions = mergedOptions.outputOptions[0];
const deprecations = mergedOptions.deprecations;
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
checkOutputOptions(outputOptions);
return outputOptions;
}
| {
const message = `The following options have been renamed — please update your config: ${deprecations
.map(option => `${option.old} -> ${option.new}`)
.join(', ')}`;
warn({
code: 'DEPRECATED_OPTIONS',
message,
deprecations
});
}
| identifier_body |
index.ts | import Chunk from '../Chunk';
import { optimizeChunks } from '../chunk-optimization';
import Graph from '../Graph';
import { createAddons } from '../utils/addons';
import { createAssetPluginHooks, finaliseAsset } from '../utils/assetHooks';
import commondir from '../utils/commondir';
import { Deprecation } from '../utils/deprecateOptions';
import error from '../utils/error';
import { writeFile } from '../utils/fs';
import getExportMode from '../utils/getExportMode';
import mergeOptions, { GenericConfigObject } from '../utils/mergeOptions';
import { basename, dirname, isAbsolute, resolve } from '../utils/path';
import { SOURCEMAPPING_URL } from '../utils/sourceMappingURL';
import { getTimings, initialiseTimers, timeEnd, timeStart } from '../utils/timers';
import { Watcher } from '../watch';
import {
InputOptions,
OutputBundle,
OutputChunk,
OutputFile,
OutputOptions,
Plugin,
RollupBuild,
RollupSingleFileBuild,
WarningHandler
} from './types';
function addDeprecations(deprecations: Deprecation[], warn: WarningHandler) {
const message = `The following options have been renamed — please update your config: ${deprecations
.map(option => `${option.old} -> ${option.new}`)
.join(', ')}`;
warn({
code: 'DEPRECATED_OPTIONS',
message,
deprecations
});
}
function checkInputOptions(options: InputOptions) {
if (options.transform || options.load || options.resolveId || options.resolveExternal) {
|
function checkOutputOptions(options: OutputOptions) {
if (<string>options.format === 'es6') {
error({
message: 'The `es6` output format is deprecated – use `es` instead',
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (!options.format) {
error({
message: `You must specify output.format, which can be one of 'amd', 'cjs', 'system', 'esm', 'iife' or 'umd'`,
url: `https://rollupjs.org/guide/en#output-format-f-format`
});
}
if (options.moduleId) {
if (options.amd) throw new Error('Cannot have both output.amd and output.moduleId');
}
}
const throwAsyncGenerateError = {
get() {
throw new Error(`bundle.generate(...) now returns a Promise instead of a { code, map } object`);
}
};
function applyOptionHook(inputOptions: InputOptions, plugin: Plugin) {
if (plugin.options) return plugin.options(inputOptions) || inputOptions;
return inputOptions;
}
function getInputOptions(rawInputOptions: GenericConfigObject): any {
if (!rawInputOptions) {
throw new Error('You must supply an options object to rollup');
}
// inputOptions: input 从命令行或配置文件与默认配置合并
// deprecations: 过时的参数列表，过时的参数，仍然会写入正确的地方
// optionError: 错误信息
let { inputOptions, deprecations, optionError } = mergeOptions({
config: rawInputOptions,
deprecateConfig: { input: true }
});
// 如果存在错误信息，直接输出到终端
if (optionError) inputOptions.onwarn({ message: optionError, code: 'UNKNOWN_OPTION' });
// 如果存在过时参数，直接输出到终端
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
// 检查是否存在一些 属性 如 transform 应放到插件里。（应该不会出现这种情况，因为inputOptions不可能会有）
checkInputOptions(inputOptions);
// 整理插件列表，过滤掉null,undefined等无效的插件，并确保是数组
const plugins = inputOptions.plugins;
inputOptions.plugins = Array.isArray(plugins)
? plugins.filter(Boolean)
: plugins
? [plugins]
: [];
// 依次调用每个插件的options方法
inputOptions = inputOptions.plugins.reduce(applyOptionHook, inputOptions);
// 实验代码分割,
if (!inputOptions.experimentalCodeSplitting) {
inputOptions.inlineDynamicImports = true; // 内联动态导入
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is only supported for experimentalCodeSplitting.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are only supported for experimentalCodeSplitting.'
});
}
// 内联动态导入
if (inputOptions.inlineDynamicImports) {
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: '"manualChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: '"optimizeChunks" option is not supported for inlineDynamicImports.'
});
if (inputOptions.input instanceof Array || typeof inputOptions.input === 'object')
error({
code: 'INVALID_OPTION',
message: 'Multiple inputs are not supported for inlineDynamicImports.'
});
} else if (inputOptions.experimentalPreserveModules) {
// 实验保存模块
if (inputOptions.inlineDynamicImports)
error({
code: 'INVALID_OPTION',
message: `experimentalPreserveModules does not support the inlineDynamicImports option.`
});
if (inputOptions.manualChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the manualChunks option.'
});
if (inputOptions.optimizeChunks)
error({
code: 'INVALID_OPTION',
message: 'experimentalPreserveModules does not support the optimizeChunks option.'
});
}
return inputOptions;
}
let curWatcher: Watcher;
export function setWatcher(watcher: Watcher) {
curWatcher = watcher;
}
export default function rollup(
rawInputOptions: GenericConfigObject
): Promise<RollupSingleFileBuild | RollupBuild> {
try {
// 从命令行，配置文件，默认配置中获取配置信息，并调用每个插件的options方法
const inputOptions = getInputOptions(rawInputOptions);
// 当perf为true时，给插件的指定方法注入打印开始时间，结束时间
initialiseTimers(inputOptions);
const graph = new Graph(inputOptions, curWatcher);
curWatcher = undefined;
// remove the cache option from the memory after graph creation (cache is not used anymore)
const useCache = rawInputOptions.cache !== false;
delete inputOptions.cache;
delete rawInputOptions.cache;
timeStart('BUILD', 1);
return graph.pluginDriver
.hookParallel('buildStart')
.then(() =>
graph.build(
inputOptions.input,
inputOptions.manualChunks,
inputOptions.inlineDynamicImports,
inputOptions.experimentalPreserveModules
)
)
.then(
chunks =>
graph.pluginDriver.hookParallel('buildEnd').then(() => {
return chunks;
}),
err =>
graph.pluginDriver.hookParallel('buildEnd', [err]).then(() => {
throw err;
})
)
.then(chunks => {
timeEnd('BUILD', 1);
// TODO: deprecate legacy single chunk return
let singleChunk: Chunk | void;
const singleInput =
typeof inputOptions.input === 'string' ||
(inputOptions.input instanceof Array && inputOptions.input.length === 1);
//let imports: string[], exports: string[];
if (!inputOptions.experimentalPreserveModules) {
if (singleInput) {
for (const chunk of chunks) {
if (chunk.entryModule === undefined) continue;
if (singleChunk) {
singleChunk = undefined;
break;
}
singleChunk = chunk;
}
}
}
// ensure we only do one optimization pass per build
let optimized = false;
function generate(rawOutputOptions: GenericConfigObject, isWrite: boolean) {
const outputOptions = normalizeOutputOptions(inputOptions, rawOutputOptions);
if (inputOptions.experimentalCodeSplitting) {
if (typeof outputOptions.file === 'string' && typeof outputOptions.dir === 'string')
error({
code: 'INVALID_OPTION',
message:
'Build must set either output.file for a single-file build or output.dir when generating multiple chunks.'
});
if (chunks.length > 1) {
if (outputOptions.format === 'umd' || outputOptions.format === 'iife')
error({
code: 'INVALID_OPTION',
message:
'UMD and IIFE output formats are not supported with the experimentalCodeSplitting option.'
});
if (outputOptions.sourcemapFile)
error({
code: 'INVALID_OPTION',
message: '"sourcemapFile" is only supported for single-file builds.'
});
}
if (!singleChunk && typeof outputOptions.file === 'string')
error({
code: 'INVALID_OPTION',
message: singleInput
? 'When building a bundle using dynamic imports, the output.dir option must be used, not output.file. Alternatively set inlineDynamicImports: true to output a single file.'
: 'When building multiple entry point inputs, the output.dir option must be used, not output.file.'
});
}
if (!outputOptions.file && inputOptions.experimentalCodeSplitting)
singleChunk = undefined;
timeStart('GENERATE', 1);
// populate asset files into output
const assetFileNames = outputOptions.assetFileNames || 'assets/[name]-[hash][extname]';
const outputBundle: OutputBundle = graph.finaliseAssets(assetFileNames);
const inputBase = commondir(
chunks
.filter(chunk => chunk.entryModule && isAbsolute(chunk.entryModule.id))
.map(chunk => chunk.entryModule.id)
);
return graph.pluginDriver
.hookParallel('renderStart')
.then(() => createAddons(graph, outputOptions))
.then(addons => {
// pre-render all chunks
for (const chunk of chunks) {
if (!inputOptions.experimentalPreserveModules)
chunk.generateInternalExports(outputOptions);
if (chunk.isEntryModuleFacade)
chunk.exportMode = getExportMode(chunk, outputOptions);
}
for (const chunk of chunks) {
chunk.preRender(outputOptions, inputBase);
}
if (!optimized && inputOptions.optimizeChunks) {
optimizeChunks(chunks, outputOptions, inputOptions.chunkGroupingSize, inputBase);
optimized = true;
}
// name all chunks
const usedIds: Record<string, true> = {};
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
if (chunk === singleChunk) {
singleChunk.id = basename(
outputOptions.file ||
(inputOptions.input instanceof Array
? inputOptions.input[0]
: <string>inputOptions.input)
);
} else if (inputOptions.experimentalPreserveModules) {
chunk.generateIdPreserveModules(inputBase, usedIds);
} else {
let pattern, patternName;
if (chunk.isEntryModuleFacade) {
pattern = outputOptions.entryFileNames || '[name].js';
patternName = 'output.entryFileNames';
} else {
pattern = outputOptions.chunkFileNames || '[name]-[hash].js';
patternName = 'output.chunkFileNames';
}
chunk.generateId(pattern, patternName, addons, outputOptions, usedIds);
}
usedIds[chunk.id] = true;
}
// assign to outputBundle
for (let i = 0; i < chunks.length; i++) {
const chunk = chunks[i];
outputBundle[chunk.id] = {
fileName: chunk.id,
isEntry: chunk.entryModule !== undefined,
imports: chunk.getImportIds(),
exports: chunk.getExportNames(),
modules: chunk.renderedModules,
code: undefined,
map: undefined
};
}
return Promise.all(
chunks.map(chunk => {
const outputChunk = <OutputChunk>outputBundle[chunk.id];
return chunk.render(outputOptions, addons, outputChunk).then(rendered => {
outputChunk.code = rendered.code;
outputChunk.map = rendered.map;
return graph.pluginDriver.hookParallel('ongenerate', [
{ bundle: outputChunk, ...outputOptions },
outputChunk
]);
});
})
).then(() => {});
})
.catch(error =>
graph.pluginDriver.hookParallel('renderError', [error]).then(() => {
throw error;
})
)
.then(() => {
// run generateBundle hook
// assets emitted during generateBundle are unique to that specific generate call
const assets = new Map(graph.assetsById);
const generateAssetPluginHooks = createAssetPluginHooks(
assets,
outputBundle,
assetFileNames
);
return graph.pluginDriver
.hookSeq('generateBundle', [outputOptions, outputBundle, isWrite], context => ({
...context,
...generateAssetPluginHooks
}))
.then(() => {
// throw errors for assets not finalised with a source
assets.forEach(asset => {
if (asset.fileName === undefined)
finaliseAsset(asset, outputBundle, assetFileNames);
});
});
})
.then(() => {
timeEnd('GENERATE', 1);
return outputBundle;
});
}
const cache = useCache ? graph.getCache() : undefined;
const result: RollupSingleFileBuild | RollupBuild = {
cache,
watchFiles: Object.keys(graph.watchFiles),
generate: <any>((rawOutputOptions: GenericConfigObject) => {
const promise = generate(rawOutputOptions, false).then(
result =>
inputOptions.experimentalCodeSplitting
? { output: result }
: <OutputChunk>result[chunks[0].id]
);
Object.defineProperty(promise, 'code', throwAsyncGenerateError);
Object.defineProperty(promise, 'map', throwAsyncGenerateError);
return promise;
}),
write: <any>((outputOptions: OutputOptions) => {
if (
inputOptions.experimentalCodeSplitting &&
(!outputOptions || (!outputOptions.dir && !outputOptions.file))
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file or output.dir for the build.'
});
} else if (
!inputOptions.experimentalCodeSplitting &&
(!outputOptions || !outputOptions.file)
) {
error({
code: 'MISSING_OPTION',
message: 'You must specify output.file.'
});
}
return generate(outputOptions, true).then(outputBundle =>
Promise.all(
Object.keys(outputBundle).map(chunkId => {
return writeOutputFile(
graph,
result,
chunkId,
outputBundle[chunkId],
outputOptions
);
})
).then(
() =>
inputOptions.experimentalCodeSplitting
? { output: outputBundle }
: <OutputChunk>outputBundle[chunks[0].id]
)
);
})
};
if (!inputOptions.experimentalCodeSplitting) {
(<any>result).imports = (<Chunk>singleChunk).getImportIds();
(<any>result).exports = (<Chunk>singleChunk).getExportNames();
(<any>result).modules = (cache || graph.getCache()).modules;
}
if (inputOptions.perf === true) result.getTimings = getTimings;
return result;
});
} catch (err) {
return Promise.reject(err);
}
}
function isOutputChunk(file: OutputFile): file is OutputChunk {
return typeof (<OutputChunk>file).code === 'string';
}
function writeOutputFile(
graph: Graph,
build: RollupBuild | RollupSingleFileBuild,
outputFileName: string,
outputFile: OutputFile,
outputOptions: OutputOptions
): Promise<void> {
const filename = resolve(outputOptions.dir || dirname(outputOptions.file), outputFileName);
let writeSourceMapPromise: Promise<void>;
let source: string | Buffer;
if (isOutputChunk(outputFile)) {
source = outputFile.code;
if (outputOptions.sourcemap && outputFile.map) {
let url: string;
if (outputOptions.sourcemap === 'inline') {
url = outputFile.map.toUrl();
} else {
url = `${basename(outputFileName)}.map`;
writeSourceMapPromise = writeFile(`${filename}.map`, outputFile.map.toString());
}
source += `//# ${SOURCEMAPPING_URL}=${url}\n`;
}
} else {
source = outputFile;
}
return writeFile(filename, source)
.then(() => writeSourceMapPromise)
.then(
() =>
isOutputChunk(outputFile) &&
graph.pluginDriver.hookSeq('onwrite', [
{
bundle: build,
...outputOptions
},
outputFile
])
)
.then(() => {});
}
function normalizeOutputOptions(
inputOptions: GenericConfigObject,
rawOutputOptions: GenericConfigObject
): OutputOptions {
if (!rawOutputOptions) {
throw new Error('You must supply an options object');
}
// since deprecateOptions, adds the output properties
// to `inputOptions` so adding that lastly
const consolidatedOutputOptions = {
output: { ...rawOutputOptions, ...rawOutputOptions.output, ...inputOptions.output }
};
const mergedOptions = mergeOptions({
// just for backward compatiblity to fallback on root
// if the option isn't present in `output`
config: consolidatedOutputOptions,
deprecateConfig: { output: true }
});
if (mergedOptions.optionError) throw new Error(mergedOptions.optionError);
// now outputOptions is an array, but rollup.rollup API doesn't support arrays
const outputOptions = mergedOptions.outputOptions[0];
const deprecations = mergedOptions.deprecations;
if (deprecations.length) addDeprecations(deprecations, inputOptions.onwarn);
checkOutputOptions(outputOptions);
return outputOptions;
}
| throw new Error(
'The `transform`, `load`, `resolveId` and `resolveExternal` options are deprecated in favour of a unified plugin API. See https://rollupjs.org/guide/en#plugins'
);
}
} | conditional_block |
model_probabilistic.py | #!/usr/bin/env python
import os
import pickle
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
tf_bijs = tfp.bijectors
tf_dist = tfp.distributions
tf_mean_field = tfp.layers.default_mean_field_normal_fn
#==============================================================
class RegressionModel(object):
NUM_SAMPLES = 1
ACT_FUNC = 'leaky_relu'
ACT_FUNC_OUT = 'linear'
LEARNING_RATE = 0.75 * 10**-3
MLP_SIZE = 48
REG = 1e-3
DROP = 0.1
def __init__(self, graph, dataset_details, config, scope, batch_size, max_iter = 10**8):
self.graph = graph
self.scope = scope
self.config = config
self.batch_size = batch_size
self.dataset_details = dataset_details
self.max_iter = max_iter
self.is_graph_constructed = False
self._read_scaling_details()
def _generator(self, features, targets, batch_size):
indices = np.arange(len(features))
while True:
np.random.shuffle(indices)
batch_features = features[indices[:batch_size]]
batch_targets = targets[indices[:batch_size]]
yield (batch_features, batch_targets)
def _read_scaling_details(self):
with open(self.dataset_details, 'rb') as content:
details = pickle.load(content)
self.scaling = {key: details[key] for key in details}
self.features_shape = self.scaling['features_shape']
self.targets_shape = self.scaling['targets_shape']
def get_scaled_features(self, features):
if self.config['feature_rescaling'] == 'standardization':
scaled = (features - self.scaling['mean_features']) / self.scaling['std_features']
elif self.config['feature_rescaling'] == 'unit_cube':
scaled = (features - self.scaling['min_features']) / (self.scaling['max_features'] - self.scaling['min_features'])
return scaled
def get_scaled_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
scaled = (targets - self.scaling['mean_targets']) / self.scaling['std_targets']
elif self.config['target_rescaling'] == 'unit_cube':
scaled = (targets - self.scaling['min_targets']) / (self.scaling['max_targets'] - self.scaling['min_targets'])
elif self.config['target_rescaling'] == 'mean':
scaled = targets / self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
scaled = targets
return scaled
def get_raw_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
raw = targets * self.scaling['std_targets'] + self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'unit_cube':
raw = (self.scaling['max_targets'] - self.scaling['min_targets']) * targets + self.scaling['min_targets']
elif self.config['target_rescaling'] == 'mean':
raw = targets * self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
raw = targets
return raw
def set_hyperparameters(self, hyperparam_dict):
for key, value in hyperparam_dict.items():
setattr(self, key, value)
def construct_graph(self):
act_funcs = {
'linear': lambda y: y,
'leaky_relu': lambda y: tf.nn.leaky_relu(y, 0.2),
'relu': lambda y: tf.nn.relu(y),
'softmax': lambda y: tf.nn.softmax(y),
'softplus': lambda y: tf.nn.softplus(y),
'softsign': lambda y: tf.nn.softsign(y),
'sigmoid': lambda y: tf.nn.sigmoid(y),
}
mlp_activation = act_funcs[self.ACT_FUNC]
out_activation = act_funcs[self.ACT_FUNC_OUT]
with self.graph.as_default():
with tf.name_scope(self.scope):
self.is_training = tf.compat.v1.placeholder(tf.bool, shape = ())
self.x_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.features_shape[1]])
self.y_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.targets_shape[1]])
self.layer_0 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_1_act = self.layer_1(layer_0_out)
layer_1_out = tf.layers.dropout(layer_1_act, rate = self.DROP, training = self.is_training)
self.layer_2 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_2_act = self.layer_2(layer_1_out)
layer_2_out = layer_2_act
self.layer_3 = tfp.layers.DenseLocalReparameterization(
self.targets_shape[1],
activation = out_activation,
)
layer_3_out = self.layer_3(layer_2_out)
self.net_out = layer_3_out
self.scales = tf.nn.softplus(tf.Variable(tf.zeros(1)))
self.y_pred = tf_dist.Normal(self.net_out, scale = self.scales)
def construct_inference(self):
self.is_graph_constructed = True
with self.graph.as_default():
self.kl = sum(self.layer_0.losses) / float(self.batch_size)
self.kl += sum(self.layer_1.losses) / float(self.batch_size)
self.kl += sum(self.layer_2.losses) / float(self.batch_size)
self.kl += sum(self.layer_3.losses) / float(self.batch_size)
self.reg_loss = - tf.reduce_mean( self.y_pred.log_prob(self.y_ph) )
self.loss = self.reg_loss + self.REG * self.kl
self.optimizer = tf.compat.v1.train.AdamOptimizer(self.LEARNING_RATE)
self.train_op = self.optimizer.minimize(self.loss)
self.init_op = tf.group(tf.compat.v1.global_variables_initializer(), tf.compat.v1.local_variables_initializer())
self.sess = tf.compat.v1.Session(graph = self.graph)
with self.sess.as_default():
self.sess.run(self.init_op)
def train(self, train_features, train_targets, valid_features, valid_targets, model_path, plot = False, targets = 'same'):
from sklearn.metrics import r2_score
if not os.path.isdir(model_path): os.mkdir(model_path)
logfile = open('%s/logfile.dat' % model_path, 'w')
logfile.close()
if not self.is_graph_constructed: self.construct_inference()
train_feat_scaled = self.get_scaled_features(train_features)
train_targ_scaled = self.get_scaled_targets(train_targets)
valid_feat_scaled = self.get_scaled_features(valid_features)
valid_targ_scaled = self.get_scaled_targets(valid_targets)
min_target, max_target = np.minimum(np.amin(train_targets, axis = 0), np.amin(valid_targets, axis = 0)), np.maximum(np.amax(train_targets, axis = 0), np.amax(valid_targets, axis = 0))
if targets == 'probs':
min_target = 1. / (1. + np.exp( - min_target))
max_target = 1. / (1. + np.exp( - max_target))
batch_train_gen = self._generator(train_feat_scaled, train_targ_scaled, self.batch_size)
batch_valid_gen = self._generator(valid_feat_scaled, valid_targ_scaled, self.batch_size)
train_errors, valid_errors = [], []
with self.graph.as_default():
with self.sess.as_default():
self.saver = tf.compat.v1.train.Saver()
if plot:
import matplotlib.pyplot as plt
import seaborn as sns
colors = sns.color_palette('RdYlGn', 4)
plt.ion()
plt.style.use('dark_background')
fig = plt.figure(figsize = (14, 5))
ax0 = plt.subplot2grid((1, 3), (0, 0))
ax1 = plt.subplot2grid((1, 3), (0, 1))
ax2 = plt.subplot2grid((1, 3), (0, 2))
for epoch in range(self.max_iter):
train_x, train_y = next(batch_train_gen)
valid_x, valid_y = next(batch_valid_gen)
self.sess.run(self.train_op, feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: True})
if epoch % 200 == 0:
valid_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: valid_x, self.is_training: False})
valid_y = self.get_raw_targets(valid_y)
valid_preds = self.get_raw_targets(valid_preds)
if targets == 'probs':
valid_y = 1. / (1. + np.exp( - valid_y))
valid_preds = 1. / (1. + np.exp( - valid_preds))
try:
valid_r2 = r2_score(valid_y, valid_preds)
except:
valid_r2 = np.nan
valid_errors.append(valid_r2)
_1_, _2_ = self.sess.run([self.reg_loss, self.kl], feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: False})
print('...', _1_, _2_)
train_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: train_x, self.is_training: False})
train_y = self.get_raw_targets(train_y)
train_preds = self.get_raw_targets(train_preds)
try:
train_r2 = r2_score(train_y, train_preds)
except:
train_r2 = np.nan
train_errors.append(train_r2)
if targets == 'probs':
train_y = 1. / (1. + np.exp( - train_y))
train_preds = 1. / (1. + np.exp( - train_preds))
logfile = open('%s/logfile.dat' % model_path, 'a')
logfile.write('%d\t%.5f\t%.5f\n' % (epoch, train_r2, valid_r2))
logfile.close()
# define break condition --> last improvement happened more than 100 epochs ago
max_r2_index = np.argmax(valid_errors)
if len(valid_errors) - max_r2_index > 100: break
if max_r2_index == len(valid_errors) - 1:
self.saver.save(self.sess, '%s/model.ckpt' % model_path)
new_line = 'EVALUATION: %d (%d)\t%.5f\t%.5f' % ( len(valid_errors) - max_r2_index, len(valid_errors), train_errors[-1], valid_errors[-1])
print(new_line)
if plot:
train_preds_scaled = train_preds
train_trues_scaled = train_y
valid_preds_scaled = valid_preds
valid_trues_scaled = valid_y
ax0.cla()
ax1.cla()
ax2.cla()
ax0.plot([min_target[0], max_target[0]], [min_target[0], max_target[0]], lw = 3, color = 'w', alpha = 0.5)
ax0.plot(train_trues_scaled[:, 0], train_preds_scaled[:, 0], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax0.plot(valid_trues_scaled[:, 0], valid_preds_scaled[:, 0], marker = '.', ls = '', color = colors[0], alpha = 0.5)
if len(min_target) > 1:
ax1.plot([min_target[1], max_target[1]], [min_target[1], max_target[1]], lw = 3, color = 'w', alpha = 0.5)
ax1.plot(train_trues_scaled[:, 1], train_preds_scaled[:, 1], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax1.plot(valid_trues_scaled[:, 1], valid_preds_scaled[:, 1], marker = '.', ls = '', color = colors[0], alpha = 0.5)
RANGE = 50
ax2.plot(np.arange(len(train_errors[-RANGE:])) + len(train_errors[-RANGE:]), train_errors[-RANGE:], lw = 3, color = colors[-1])
ax2.plot(np.arange(len(valid_errors[-RANGE:])) + len(valid_errors[-RANGE:]), valid_errors[-RANGE:], lw = 3, color = colors[0])
plt.pause(0.05)
def restore(self, model_path):
if not self.is_graph_constructed: self.construct_inference()
self.sess = tf.compat.v1.Session(graph = self.graph)
self.saver = tf.compat.v1.train.Saver()
try:
self.saver.restore(self.sess, model_path)
return True
except AttributeError:
return False
def predict(self, input_raw): | with self.sess.as_default():
output_scaled = []
for _ in range(self.NUM_SAMPLES):
output_scaled.append(self.sess.run(self.net_out, feed_dict = {self.x_ph: input_scaled, self.is_training: False}))
output_scaled = np.array(output_scaled)
output_raw = self.get_raw_targets(output_scaled)
output_raw_mean = np.mean(output_raw, axis = 0)
output_raw_std = np.std(output_raw, axis = 0)
return {'samples': output_raw, 'averages': output_raw_mean, 'uncertainties': output_raw_std}
#============================================================== |
input_scaled = self.get_scaled_features(input_raw)
| random_line_split |
model_probabilistic.py | #!/usr/bin/env python
import os
import pickle
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
tf_bijs = tfp.bijectors
tf_dist = tfp.distributions
tf_mean_field = tfp.layers.default_mean_field_normal_fn
#==============================================================
class RegressionModel(object):
NUM_SAMPLES = 1
ACT_FUNC = 'leaky_relu'
ACT_FUNC_OUT = 'linear'
LEARNING_RATE = 0.75 * 10**-3
MLP_SIZE = 48
REG = 1e-3
DROP = 0.1
def __init__(self, graph, dataset_details, config, scope, batch_size, max_iter = 10**8):
self.graph = graph
self.scope = scope
self.config = config
self.batch_size = batch_size
self.dataset_details = dataset_details
self.max_iter = max_iter
self.is_graph_constructed = False
self._read_scaling_details()
def _generator(self, features, targets, batch_size):
indices = np.arange(len(features))
while True:
np.random.shuffle(indices)
batch_features = features[indices[:batch_size]]
batch_targets = targets[indices[:batch_size]]
yield (batch_features, batch_targets)
def _read_scaling_details(self):
with open(self.dataset_details, 'rb') as content:
details = pickle.load(content)
self.scaling = {key: details[key] for key in details}
self.features_shape = self.scaling['features_shape']
self.targets_shape = self.scaling['targets_shape']
def get_scaled_features(self, features):
if self.config['feature_rescaling'] == 'standardization':
scaled = (features - self.scaling['mean_features']) / self.scaling['std_features']
elif self.config['feature_rescaling'] == 'unit_cube':
scaled = (features - self.scaling['min_features']) / (self.scaling['max_features'] - self.scaling['min_features'])
return scaled
def get_scaled_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
scaled = (targets - self.scaling['mean_targets']) / self.scaling['std_targets']
elif self.config['target_rescaling'] == 'unit_cube':
scaled = (targets - self.scaling['min_targets']) / (self.scaling['max_targets'] - self.scaling['min_targets'])
elif self.config['target_rescaling'] == 'mean':
scaled = targets / self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
scaled = targets
return scaled
def get_raw_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
raw = targets * self.scaling['std_targets'] + self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'unit_cube':
raw = (self.scaling['max_targets'] - self.scaling['min_targets']) * targets + self.scaling['min_targets']
elif self.config['target_rescaling'] == 'mean':
raw = targets * self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
|
return raw
def set_hyperparameters(self, hyperparam_dict):
for key, value in hyperparam_dict.items():
setattr(self, key, value)
def construct_graph(self):
act_funcs = {
'linear': lambda y: y,
'leaky_relu': lambda y: tf.nn.leaky_relu(y, 0.2),
'relu': lambda y: tf.nn.relu(y),
'softmax': lambda y: tf.nn.softmax(y),
'softplus': lambda y: tf.nn.softplus(y),
'softsign': lambda y: tf.nn.softsign(y),
'sigmoid': lambda y: tf.nn.sigmoid(y),
}
mlp_activation = act_funcs[self.ACT_FUNC]
out_activation = act_funcs[self.ACT_FUNC_OUT]
with self.graph.as_default():
with tf.name_scope(self.scope):
self.is_training = tf.compat.v1.placeholder(tf.bool, shape = ())
self.x_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.features_shape[1]])
self.y_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.targets_shape[1]])
self.layer_0 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_1_act = self.layer_1(layer_0_out)
layer_1_out = tf.layers.dropout(layer_1_act, rate = self.DROP, training = self.is_training)
self.layer_2 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_2_act = self.layer_2(layer_1_out)
layer_2_out = layer_2_act
self.layer_3 = tfp.layers.DenseLocalReparameterization(
self.targets_shape[1],
activation = out_activation,
)
layer_3_out = self.layer_3(layer_2_out)
self.net_out = layer_3_out
self.scales = tf.nn.softplus(tf.Variable(tf.zeros(1)))
self.y_pred = tf_dist.Normal(self.net_out, scale = self.scales)
def construct_inference(self):
self.is_graph_constructed = True
with self.graph.as_default():
self.kl = sum(self.layer_0.losses) / float(self.batch_size)
self.kl += sum(self.layer_1.losses) / float(self.batch_size)
self.kl += sum(self.layer_2.losses) / float(self.batch_size)
self.kl += sum(self.layer_3.losses) / float(self.batch_size)
self.reg_loss = - tf.reduce_mean( self.y_pred.log_prob(self.y_ph) )
self.loss = self.reg_loss + self.REG * self.kl
self.optimizer = tf.compat.v1.train.AdamOptimizer(self.LEARNING_RATE)
self.train_op = self.optimizer.minimize(self.loss)
self.init_op = tf.group(tf.compat.v1.global_variables_initializer(), tf.compat.v1.local_variables_initializer())
self.sess = tf.compat.v1.Session(graph = self.graph)
with self.sess.as_default():
self.sess.run(self.init_op)
def train(self, train_features, train_targets, valid_features, valid_targets, model_path, plot = False, targets = 'same'):
from sklearn.metrics import r2_score
if not os.path.isdir(model_path): os.mkdir(model_path)
logfile = open('%s/logfile.dat' % model_path, 'w')
logfile.close()
if not self.is_graph_constructed: self.construct_inference()
train_feat_scaled = self.get_scaled_features(train_features)
train_targ_scaled = self.get_scaled_targets(train_targets)
valid_feat_scaled = self.get_scaled_features(valid_features)
valid_targ_scaled = self.get_scaled_targets(valid_targets)
min_target, max_target = np.minimum(np.amin(train_targets, axis = 0), np.amin(valid_targets, axis = 0)), np.maximum(np.amax(train_targets, axis = 0), np.amax(valid_targets, axis = 0))
if targets == 'probs':
min_target = 1. / (1. + np.exp( - min_target))
max_target = 1. / (1. + np.exp( - max_target))
batch_train_gen = self._generator(train_feat_scaled, train_targ_scaled, self.batch_size)
batch_valid_gen = self._generator(valid_feat_scaled, valid_targ_scaled, self.batch_size)
train_errors, valid_errors = [], []
with self.graph.as_default():
with self.sess.as_default():
self.saver = tf.compat.v1.train.Saver()
if plot:
import matplotlib.pyplot as plt
import seaborn as sns
colors = sns.color_palette('RdYlGn', 4)
plt.ion()
plt.style.use('dark_background')
fig = plt.figure(figsize = (14, 5))
ax0 = plt.subplot2grid((1, 3), (0, 0))
ax1 = plt.subplot2grid((1, 3), (0, 1))
ax2 = plt.subplot2grid((1, 3), (0, 2))
for epoch in range(self.max_iter):
train_x, train_y = next(batch_train_gen)
valid_x, valid_y = next(batch_valid_gen)
self.sess.run(self.train_op, feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: True})
if epoch % 200 == 0:
valid_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: valid_x, self.is_training: False})
valid_y = self.get_raw_targets(valid_y)
valid_preds = self.get_raw_targets(valid_preds)
if targets == 'probs':
valid_y = 1. / (1. + np.exp( - valid_y))
valid_preds = 1. / (1. + np.exp( - valid_preds))
try:
valid_r2 = r2_score(valid_y, valid_preds)
except:
valid_r2 = np.nan
valid_errors.append(valid_r2)
_1_, _2_ = self.sess.run([self.reg_loss, self.kl], feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: False})
print('...', _1_, _2_)
train_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: train_x, self.is_training: False})
train_y = self.get_raw_targets(train_y)
train_preds = self.get_raw_targets(train_preds)
try:
train_r2 = r2_score(train_y, train_preds)
except:
train_r2 = np.nan
train_errors.append(train_r2)
if targets == 'probs':
train_y = 1. / (1. + np.exp( - train_y))
train_preds = 1. / (1. + np.exp( - train_preds))
logfile = open('%s/logfile.dat' % model_path, 'a')
logfile.write('%d\t%.5f\t%.5f\n' % (epoch, train_r2, valid_r2))
logfile.close()
# define break condition --> last improvement happened more than 100 epochs ago
max_r2_index = np.argmax(valid_errors)
if len(valid_errors) - max_r2_index > 100: break
if max_r2_index == len(valid_errors) - 1:
self.saver.save(self.sess, '%s/model.ckpt' % model_path)
new_line = 'EVALUATION: %d (%d)\t%.5f\t%.5f' % ( len(valid_errors) - max_r2_index, len(valid_errors), train_errors[-1], valid_errors[-1])
print(new_line)
if plot:
train_preds_scaled = train_preds
train_trues_scaled = train_y
valid_preds_scaled = valid_preds
valid_trues_scaled = valid_y
ax0.cla()
ax1.cla()
ax2.cla()
ax0.plot([min_target[0], max_target[0]], [min_target[0], max_target[0]], lw = 3, color = 'w', alpha = 0.5)
ax0.plot(train_trues_scaled[:, 0], train_preds_scaled[:, 0], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax0.plot(valid_trues_scaled[:, 0], valid_preds_scaled[:, 0], marker = '.', ls = '', color = colors[0], alpha = 0.5)
if len(min_target) > 1:
ax1.plot([min_target[1], max_target[1]], [min_target[1], max_target[1]], lw = 3, color = 'w', alpha = 0.5)
ax1.plot(train_trues_scaled[:, 1], train_preds_scaled[:, 1], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax1.plot(valid_trues_scaled[:, 1], valid_preds_scaled[:, 1], marker = '.', ls = '', color = colors[0], alpha = 0.5)
RANGE = 50
ax2.plot(np.arange(len(train_errors[-RANGE:])) + len(train_errors[-RANGE:]), train_errors[-RANGE:], lw = 3, color = colors[-1])
ax2.plot(np.arange(len(valid_errors[-RANGE:])) + len(valid_errors[-RANGE:]), valid_errors[-RANGE:], lw = 3, color = colors[0])
plt.pause(0.05)
def restore(self, model_path):
if not self.is_graph_constructed: self.construct_inference()
self.sess = tf.compat.v1.Session(graph = self.graph)
self.saver = tf.compat.v1.train.Saver()
try:
self.saver.restore(self.sess, model_path)
return True
except AttributeError:
return False
def predict(self, input_raw):
input_scaled = self.get_scaled_features(input_raw)
with self.sess.as_default():
output_scaled = []
for _ in range(self.NUM_SAMPLES):
output_scaled.append(self.sess.run(self.net_out, feed_dict = {self.x_ph: input_scaled, self.is_training: False}))
output_scaled = np.array(output_scaled)
output_raw = self.get_raw_targets(output_scaled)
output_raw_mean = np.mean(output_raw, axis = 0)
output_raw_std = np.std(output_raw, axis = 0)
return {'samples': output_raw, 'averages': output_raw_mean, 'uncertainties': output_raw_std}
#==============================================================
| raw = targets | conditional_block |
model_probabilistic.py | #!/usr/bin/env python
import os
import pickle
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
tf_bijs = tfp.bijectors
tf_dist = tfp.distributions
tf_mean_field = tfp.layers.default_mean_field_normal_fn
#==============================================================
class RegressionModel(object):
NUM_SAMPLES = 1
ACT_FUNC = 'leaky_relu'
ACT_FUNC_OUT = 'linear'
LEARNING_RATE = 0.75 * 10**-3
MLP_SIZE = 48
REG = 1e-3
DROP = 0.1
def __init__(self, graph, dataset_details, config, scope, batch_size, max_iter = 10**8):
self.graph = graph
self.scope = scope
self.config = config
self.batch_size = batch_size
self.dataset_details = dataset_details
self.max_iter = max_iter
self.is_graph_constructed = False
self._read_scaling_details()
def _generator(self, features, targets, batch_size):
indices = np.arange(len(features))
while True:
np.random.shuffle(indices)
batch_features = features[indices[:batch_size]]
batch_targets = targets[indices[:batch_size]]
yield (batch_features, batch_targets)
def _read_scaling_details(self):
with open(self.dataset_details, 'rb') as content:
details = pickle.load(content)
self.scaling = {key: details[key] for key in details}
self.features_shape = self.scaling['features_shape']
self.targets_shape = self.scaling['targets_shape']
def get_scaled_features(self, features):
if self.config['feature_rescaling'] == 'standardization':
scaled = (features - self.scaling['mean_features']) / self.scaling['std_features']
elif self.config['feature_rescaling'] == 'unit_cube':
scaled = (features - self.scaling['min_features']) / (self.scaling['max_features'] - self.scaling['min_features'])
return scaled
def get_scaled_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
scaled = (targets - self.scaling['mean_targets']) / self.scaling['std_targets']
elif self.config['target_rescaling'] == 'unit_cube':
scaled = (targets - self.scaling['min_targets']) / (self.scaling['max_targets'] - self.scaling['min_targets'])
elif self.config['target_rescaling'] == 'mean':
scaled = targets / self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
scaled = targets
return scaled
def get_raw_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
raw = targets * self.scaling['std_targets'] + self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'unit_cube':
raw = (self.scaling['max_targets'] - self.scaling['min_targets']) * targets + self.scaling['min_targets']
elif self.config['target_rescaling'] == 'mean':
raw = targets * self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
raw = targets
return raw
def set_hyperparameters(self, hyperparam_dict):
for key, value in hyperparam_dict.items():
setattr(self, key, value)
def construct_graph(self):
act_funcs = {
'linear': lambda y: y,
'leaky_relu': lambda y: tf.nn.leaky_relu(y, 0.2),
'relu': lambda y: tf.nn.relu(y),
'softmax': lambda y: tf.nn.softmax(y),
'softplus': lambda y: tf.nn.softplus(y),
'softsign': lambda y: tf.nn.softsign(y),
'sigmoid': lambda y: tf.nn.sigmoid(y),
}
mlp_activation = act_funcs[self.ACT_FUNC]
out_activation = act_funcs[self.ACT_FUNC_OUT]
with self.graph.as_default():
with tf.name_scope(self.scope):
self.is_training = tf.compat.v1.placeholder(tf.bool, shape = ())
self.x_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.features_shape[1]])
self.y_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.targets_shape[1]])
self.layer_0 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_1_act = self.layer_1(layer_0_out)
layer_1_out = tf.layers.dropout(layer_1_act, rate = self.DROP, training = self.is_training)
self.layer_2 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_2_act = self.layer_2(layer_1_out)
layer_2_out = layer_2_act
self.layer_3 = tfp.layers.DenseLocalReparameterization(
self.targets_shape[1],
activation = out_activation,
)
layer_3_out = self.layer_3(layer_2_out)
self.net_out = layer_3_out
self.scales = tf.nn.softplus(tf.Variable(tf.zeros(1)))
self.y_pred = tf_dist.Normal(self.net_out, scale = self.scales)
def construct_inference(self):
self.is_graph_constructed = True
with self.graph.as_default():
self.kl = sum(self.layer_0.losses) / float(self.batch_size)
self.kl += sum(self.layer_1.losses) / float(self.batch_size)
self.kl += sum(self.layer_2.losses) / float(self.batch_size)
self.kl += sum(self.layer_3.losses) / float(self.batch_size)
self.reg_loss = - tf.reduce_mean( self.y_pred.log_prob(self.y_ph) )
self.loss = self.reg_loss + self.REG * self.kl
self.optimizer = tf.compat.v1.train.AdamOptimizer(self.LEARNING_RATE)
self.train_op = self.optimizer.minimize(self.loss)
self.init_op = tf.group(tf.compat.v1.global_variables_initializer(), tf.compat.v1.local_variables_initializer())
self.sess = tf.compat.v1.Session(graph = self.graph)
with self.sess.as_default():
self.sess.run(self.init_op)
def train(self, train_features, train_targets, valid_features, valid_targets, model_path, plot = False, targets = 'same'):
from sklearn.metrics import r2_score
if not os.path.isdir(model_path): os.mkdir(model_path)
logfile = open('%s/logfile.dat' % model_path, 'w')
logfile.close()
if not self.is_graph_constructed: self.construct_inference()
train_feat_scaled = self.get_scaled_features(train_features)
train_targ_scaled = self.get_scaled_targets(train_targets)
valid_feat_scaled = self.get_scaled_features(valid_features)
valid_targ_scaled = self.get_scaled_targets(valid_targets)
min_target, max_target = np.minimum(np.amin(train_targets, axis = 0), np.amin(valid_targets, axis = 0)), np.maximum(np.amax(train_targets, axis = 0), np.amax(valid_targets, axis = 0))
if targets == 'probs':
min_target = 1. / (1. + np.exp( - min_target))
max_target = 1. / (1. + np.exp( - max_target))
batch_train_gen = self._generator(train_feat_scaled, train_targ_scaled, self.batch_size)
batch_valid_gen = self._generator(valid_feat_scaled, valid_targ_scaled, self.batch_size)
train_errors, valid_errors = [], []
with self.graph.as_default():
with self.sess.as_default():
self.saver = tf.compat.v1.train.Saver()
if plot:
import matplotlib.pyplot as plt
import seaborn as sns
colors = sns.color_palette('RdYlGn', 4)
plt.ion()
plt.style.use('dark_background')
fig = plt.figure(figsize = (14, 5))
ax0 = plt.subplot2grid((1, 3), (0, 0))
ax1 = plt.subplot2grid((1, 3), (0, 1))
ax2 = plt.subplot2grid((1, 3), (0, 2))
for epoch in range(self.max_iter):
train_x, train_y = next(batch_train_gen)
valid_x, valid_y = next(batch_valid_gen)
self.sess.run(self.train_op, feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: True})
if epoch % 200 == 0:
valid_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: valid_x, self.is_training: False})
valid_y = self.get_raw_targets(valid_y)
valid_preds = self.get_raw_targets(valid_preds)
if targets == 'probs':
valid_y = 1. / (1. + np.exp( - valid_y))
valid_preds = 1. / (1. + np.exp( - valid_preds))
try:
valid_r2 = r2_score(valid_y, valid_preds)
except:
valid_r2 = np.nan
valid_errors.append(valid_r2)
_1_, _2_ = self.sess.run([self.reg_loss, self.kl], feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: False})
print('...', _1_, _2_)
train_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: train_x, self.is_training: False})
train_y = self.get_raw_targets(train_y)
train_preds = self.get_raw_targets(train_preds)
try:
train_r2 = r2_score(train_y, train_preds)
except:
train_r2 = np.nan
train_errors.append(train_r2)
if targets == 'probs':
train_y = 1. / (1. + np.exp( - train_y))
train_preds = 1. / (1. + np.exp( - train_preds))
logfile = open('%s/logfile.dat' % model_path, 'a')
logfile.write('%d\t%.5f\t%.5f\n' % (epoch, train_r2, valid_r2))
logfile.close()
# define break condition --> last improvement happened more than 100 epochs ago
max_r2_index = np.argmax(valid_errors)
if len(valid_errors) - max_r2_index > 100: break
if max_r2_index == len(valid_errors) - 1:
self.saver.save(self.sess, '%s/model.ckpt' % model_path)
new_line = 'EVALUATION: %d (%d)\t%.5f\t%.5f' % ( len(valid_errors) - max_r2_index, len(valid_errors), train_errors[-1], valid_errors[-1])
print(new_line)
if plot:
train_preds_scaled = train_preds
train_trues_scaled = train_y
valid_preds_scaled = valid_preds
valid_trues_scaled = valid_y
ax0.cla()
ax1.cla()
ax2.cla()
ax0.plot([min_target[0], max_target[0]], [min_target[0], max_target[0]], lw = 3, color = 'w', alpha = 0.5)
ax0.plot(train_trues_scaled[:, 0], train_preds_scaled[:, 0], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax0.plot(valid_trues_scaled[:, 0], valid_preds_scaled[:, 0], marker = '.', ls = '', color = colors[0], alpha = 0.5)
if len(min_target) > 1:
ax1.plot([min_target[1], max_target[1]], [min_target[1], max_target[1]], lw = 3, color = 'w', alpha = 0.5)
ax1.plot(train_trues_scaled[:, 1], train_preds_scaled[:, 1], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax1.plot(valid_trues_scaled[:, 1], valid_preds_scaled[:, 1], marker = '.', ls = '', color = colors[0], alpha = 0.5)
RANGE = 50
ax2.plot(np.arange(len(train_errors[-RANGE:])) + len(train_errors[-RANGE:]), train_errors[-RANGE:], lw = 3, color = colors[-1])
ax2.plot(np.arange(len(valid_errors[-RANGE:])) + len(valid_errors[-RANGE:]), valid_errors[-RANGE:], lw = 3, color = colors[0])
plt.pause(0.05)
def restore(self, model_path):
|
def predict(self, input_raw):
input_scaled = self.get_scaled_features(input_raw)
with self.sess.as_default():
output_scaled = []
for _ in range(self.NUM_SAMPLES):
output_scaled.append(self.sess.run(self.net_out, feed_dict = {self.x_ph: input_scaled, self.is_training: False}))
output_scaled = np.array(output_scaled)
output_raw = self.get_raw_targets(output_scaled)
output_raw_mean = np.mean(output_raw, axis = 0)
output_raw_std = np.std(output_raw, axis = 0)
return {'samples': output_raw, 'averages': output_raw_mean, 'uncertainties': output_raw_std}
#==============================================================
| if not self.is_graph_constructed: self.construct_inference()
self.sess = tf.compat.v1.Session(graph = self.graph)
self.saver = tf.compat.v1.train.Saver()
try:
self.saver.restore(self.sess, model_path)
return True
except AttributeError:
return False | identifier_body |
model_probabilistic.py | #!/usr/bin/env python
import os
import pickle
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
tf_bijs = tfp.bijectors
tf_dist = tfp.distributions
tf_mean_field = tfp.layers.default_mean_field_normal_fn
#==============================================================
class RegressionModel(object):
NUM_SAMPLES = 1
ACT_FUNC = 'leaky_relu'
ACT_FUNC_OUT = 'linear'
LEARNING_RATE = 0.75 * 10**-3
MLP_SIZE = 48
REG = 1e-3
DROP = 0.1
def | (self, graph, dataset_details, config, scope, batch_size, max_iter = 10**8):
self.graph = graph
self.scope = scope
self.config = config
self.batch_size = batch_size
self.dataset_details = dataset_details
self.max_iter = max_iter
self.is_graph_constructed = False
self._read_scaling_details()
def _generator(self, features, targets, batch_size):
indices = np.arange(len(features))
while True:
np.random.shuffle(indices)
batch_features = features[indices[:batch_size]]
batch_targets = targets[indices[:batch_size]]
yield (batch_features, batch_targets)
def _read_scaling_details(self):
with open(self.dataset_details, 'rb') as content:
details = pickle.load(content)
self.scaling = {key: details[key] for key in details}
self.features_shape = self.scaling['features_shape']
self.targets_shape = self.scaling['targets_shape']
def get_scaled_features(self, features):
if self.config['feature_rescaling'] == 'standardization':
scaled = (features - self.scaling['mean_features']) / self.scaling['std_features']
elif self.config['feature_rescaling'] == 'unit_cube':
scaled = (features - self.scaling['min_features']) / (self.scaling['max_features'] - self.scaling['min_features'])
return scaled
def get_scaled_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
scaled = (targets - self.scaling['mean_targets']) / self.scaling['std_targets']
elif self.config['target_rescaling'] == 'unit_cube':
scaled = (targets - self.scaling['min_targets']) / (self.scaling['max_targets'] - self.scaling['min_targets'])
elif self.config['target_rescaling'] == 'mean':
scaled = targets / self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
scaled = targets
return scaled
def get_raw_targets(self, targets):
if self.config['target_rescaling'] == 'standardization':
raw = targets * self.scaling['std_targets'] + self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'unit_cube':
raw = (self.scaling['max_targets'] - self.scaling['min_targets']) * targets + self.scaling['min_targets']
elif self.config['target_rescaling'] == 'mean':
raw = targets * self.scaling['mean_targets']
elif self.config['target_rescaling'] == 'same':
raw = targets
return raw
def set_hyperparameters(self, hyperparam_dict):
for key, value in hyperparam_dict.items():
setattr(self, key, value)
def construct_graph(self):
act_funcs = {
'linear': lambda y: y,
'leaky_relu': lambda y: tf.nn.leaky_relu(y, 0.2),
'relu': lambda y: tf.nn.relu(y),
'softmax': lambda y: tf.nn.softmax(y),
'softplus': lambda y: tf.nn.softplus(y),
'softsign': lambda y: tf.nn.softsign(y),
'sigmoid': lambda y: tf.nn.sigmoid(y),
}
mlp_activation = act_funcs[self.ACT_FUNC]
out_activation = act_funcs[self.ACT_FUNC_OUT]
with self.graph.as_default():
with tf.name_scope(self.scope):
self.is_training = tf.compat.v1.placeholder(tf.bool, shape = ())
self.x_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.features_shape[1]])
self.y_ph = tf.compat.v1.placeholder(tf.float32, [self.batch_size, self.targets_shape[1]])
self.layer_0 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_0_act = self.layer_0(self.x_ph)
layer_0_out = tf.layers.dropout(layer_0_act, rate = self.DROP, training = self.is_training)
self.layer_1 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_1_act = self.layer_1(layer_0_out)
layer_1_out = tf.layers.dropout(layer_1_act, rate = self.DROP, training = self.is_training)
self.layer_2 = tfp.layers.DenseLocalReparameterization(
self.MLP_SIZE,
activation = mlp_activation,
)
layer_2_act = self.layer_2(layer_1_out)
layer_2_out = layer_2_act
self.layer_3 = tfp.layers.DenseLocalReparameterization(
self.targets_shape[1],
activation = out_activation,
)
layer_3_out = self.layer_3(layer_2_out)
self.net_out = layer_3_out
self.scales = tf.nn.softplus(tf.Variable(tf.zeros(1)))
self.y_pred = tf_dist.Normal(self.net_out, scale = self.scales)
def construct_inference(self):
self.is_graph_constructed = True
with self.graph.as_default():
self.kl = sum(self.layer_0.losses) / float(self.batch_size)
self.kl += sum(self.layer_1.losses) / float(self.batch_size)
self.kl += sum(self.layer_2.losses) / float(self.batch_size)
self.kl += sum(self.layer_3.losses) / float(self.batch_size)
self.reg_loss = - tf.reduce_mean( self.y_pred.log_prob(self.y_ph) )
self.loss = self.reg_loss + self.REG * self.kl
self.optimizer = tf.compat.v1.train.AdamOptimizer(self.LEARNING_RATE)
self.train_op = self.optimizer.minimize(self.loss)
self.init_op = tf.group(tf.compat.v1.global_variables_initializer(), tf.compat.v1.local_variables_initializer())
self.sess = tf.compat.v1.Session(graph = self.graph)
with self.sess.as_default():
self.sess.run(self.init_op)
def train(self, train_features, train_targets, valid_features, valid_targets, model_path, plot = False, targets = 'same'):
from sklearn.metrics import r2_score
if not os.path.isdir(model_path): os.mkdir(model_path)
logfile = open('%s/logfile.dat' % model_path, 'w')
logfile.close()
if not self.is_graph_constructed: self.construct_inference()
train_feat_scaled = self.get_scaled_features(train_features)
train_targ_scaled = self.get_scaled_targets(train_targets)
valid_feat_scaled = self.get_scaled_features(valid_features)
valid_targ_scaled = self.get_scaled_targets(valid_targets)
min_target, max_target = np.minimum(np.amin(train_targets, axis = 0), np.amin(valid_targets, axis = 0)), np.maximum(np.amax(train_targets, axis = 0), np.amax(valid_targets, axis = 0))
if targets == 'probs':
min_target = 1. / (1. + np.exp( - min_target))
max_target = 1. / (1. + np.exp( - max_target))
batch_train_gen = self._generator(train_feat_scaled, train_targ_scaled, self.batch_size)
batch_valid_gen = self._generator(valid_feat_scaled, valid_targ_scaled, self.batch_size)
train_errors, valid_errors = [], []
with self.graph.as_default():
with self.sess.as_default():
self.saver = tf.compat.v1.train.Saver()
if plot:
import matplotlib.pyplot as plt
import seaborn as sns
colors = sns.color_palette('RdYlGn', 4)
plt.ion()
plt.style.use('dark_background')
fig = plt.figure(figsize = (14, 5))
ax0 = plt.subplot2grid((1, 3), (0, 0))
ax1 = plt.subplot2grid((1, 3), (0, 1))
ax2 = plt.subplot2grid((1, 3), (0, 2))
for epoch in range(self.max_iter):
train_x, train_y = next(batch_train_gen)
valid_x, valid_y = next(batch_valid_gen)
self.sess.run(self.train_op, feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: True})
if epoch % 200 == 0:
valid_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: valid_x, self.is_training: False})
valid_y = self.get_raw_targets(valid_y)
valid_preds = self.get_raw_targets(valid_preds)
if targets == 'probs':
valid_y = 1. / (1. + np.exp( - valid_y))
valid_preds = 1. / (1. + np.exp( - valid_preds))
try:
valid_r2 = r2_score(valid_y, valid_preds)
except:
valid_r2 = np.nan
valid_errors.append(valid_r2)
_1_, _2_ = self.sess.run([self.reg_loss, self.kl], feed_dict = {self.x_ph: train_x, self.y_ph: train_y, self.is_training: False})
print('...', _1_, _2_)
train_preds = self.sess.run(self.net_out, feed_dict = {self.x_ph: train_x, self.is_training: False})
train_y = self.get_raw_targets(train_y)
train_preds = self.get_raw_targets(train_preds)
try:
train_r2 = r2_score(train_y, train_preds)
except:
train_r2 = np.nan
train_errors.append(train_r2)
if targets == 'probs':
train_y = 1. / (1. + np.exp( - train_y))
train_preds = 1. / (1. + np.exp( - train_preds))
logfile = open('%s/logfile.dat' % model_path, 'a')
logfile.write('%d\t%.5f\t%.5f\n' % (epoch, train_r2, valid_r2))
logfile.close()
# define break condition --> last improvement happened more than 100 epochs ago
max_r2_index = np.argmax(valid_errors)
if len(valid_errors) - max_r2_index > 100: break
if max_r2_index == len(valid_errors) - 1:
self.saver.save(self.sess, '%s/model.ckpt' % model_path)
new_line = 'EVALUATION: %d (%d)\t%.5f\t%.5f' % ( len(valid_errors) - max_r2_index, len(valid_errors), train_errors[-1], valid_errors[-1])
print(new_line)
if plot:
train_preds_scaled = train_preds
train_trues_scaled = train_y
valid_preds_scaled = valid_preds
valid_trues_scaled = valid_y
ax0.cla()
ax1.cla()
ax2.cla()
ax0.plot([min_target[0], max_target[0]], [min_target[0], max_target[0]], lw = 3, color = 'w', alpha = 0.5)
ax0.plot(train_trues_scaled[:, 0], train_preds_scaled[:, 0], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax0.plot(valid_trues_scaled[:, 0], valid_preds_scaled[:, 0], marker = '.', ls = '', color = colors[0], alpha = 0.5)
if len(min_target) > 1:
ax1.plot([min_target[1], max_target[1]], [min_target[1], max_target[1]], lw = 3, color = 'w', alpha = 0.5)
ax1.plot(train_trues_scaled[:, 1], train_preds_scaled[:, 1], marker = '.', ls = '', color = colors[-1], alpha = 0.5)
ax1.plot(valid_trues_scaled[:, 1], valid_preds_scaled[:, 1], marker = '.', ls = '', color = colors[0], alpha = 0.5)
RANGE = 50
ax2.plot(np.arange(len(train_errors[-RANGE:])) + len(train_errors[-RANGE:]), train_errors[-RANGE:], lw = 3, color = colors[-1])
ax2.plot(np.arange(len(valid_errors[-RANGE:])) + len(valid_errors[-RANGE:]), valid_errors[-RANGE:], lw = 3, color = colors[0])
plt.pause(0.05)
def restore(self, model_path):
if not self.is_graph_constructed: self.construct_inference()
self.sess = tf.compat.v1.Session(graph = self.graph)
self.saver = tf.compat.v1.train.Saver()
try:
self.saver.restore(self.sess, model_path)
return True
except AttributeError:
return False
def predict(self, input_raw):
input_scaled = self.get_scaled_features(input_raw)
with self.sess.as_default():
output_scaled = []
for _ in range(self.NUM_SAMPLES):
output_scaled.append(self.sess.run(self.net_out, feed_dict = {self.x_ph: input_scaled, self.is_training: False}))
output_scaled = np.array(output_scaled)
output_raw = self.get_raw_targets(output_scaled)
output_raw_mean = np.mean(output_raw, axis = 0)
output_raw_std = np.std(output_raw, axis = 0)
return {'samples': output_raw, 'averages': output_raw_mean, 'uncertainties': output_raw_std}
#==============================================================
| __init__ | identifier_name |
walk.py | import os
import platform
import shutil
from datetime import datetime
from functools import reduce
from hashlib import md5
from math import inf
from multiprocessing import cpu_count
from multiprocessing.pool import Pool
from operator import itemgetter
from pathlib import Path
from looptools import Timer
from dirutility.walk.filter import PathFilters
from dirutility.walk.multiprocess import Sprinter
from dirutility.walk.sequential import Crawler
class Printer:
def __init__(self, console_output, console_stream):
"""Printer function initialized with classes. Used for optional printing"""
self.console_output = console_output
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process_name='Pool processing', cpus=cpu_count()):
"""
Apply a function to each element in an iterable and return a result list.
:param func: A function that returns a value
:param iterable: A list or set of elements to be passed to the func as the singular parameter
:param process_name: Name of the process, for printing purposes only
:param cpus: Number of CPUs
:return: Result list
"""
with Timer('\t{0} ({1}) completed in'.format(process_name, str(func))):
pool = Pool(cpus)
vals = pool.map(func, iterable)
pool.close()
return vals
def md5_hash(file_path):
"""Open a file path and hash the contents."""
with open(file_path, 'rb') as fp:
return md5(fp.read()).hexdigest()
def md5_tuple(file_path):
"""Returns a file_path, hash tuple."""
return file_path, md5_hash(file_path)
def | (path_list):
"""Pool process file hashing."""
return pool_process(md5_tuple, path_list, 'MD5 hashing')
def remover(file_path):
"""Delete a file or directory path only if it exists."""
if os.path.isfile(file_path):
os.remove(file_path)
return True
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
return True
else:
return False
def creation_date(path_to_file, return_datetime=True):
"""
Retrieve a file's creation date.
Try to get the date that a file was created, falling back to when it was
last modified if that isn't possible.
See http://stackoverflow.com/a/39501288/1709587 for explanation.
:param path_to_file: File path
:param return_datetime: Bool, returns value in Datetime format
:return: Creation date
"""
if platform.system() == 'Windows':
created_at = os.path.getctime(path_to_file)
else:
stat = os.stat(path_to_file)
try:
created_at = stat.st_birthtime
except AttributeError:
# We're probably on Linux. No easy way to get creation dates here,
# so we'll settle for when its content was last modified.
created_at = stat.st_mtime
if return_datetime:
return datetime.fromtimestamp(created_at)
else:
return created_at
def creation_date_tuple(file_path):
"""Returns a (file_path, creation_date) tuple."""
return file_path, creation_date(file_path)
def pool_creation_date(path_list):
"""Pool process file creation dates."""
return pool_process(creation_date_tuple, path_list, 'File creation dates')
class DirPaths:
def __init__(self,
directory,
full_paths=False,
topdown=True,
to_include=None,
to_exclude=None,
min_level=0,
max_level=inf,
filters=None,
non_empty_folders=False,
parallelize=False,
pool_size=cpu_count(),
console_output=False,
console_stream=False,
hash_files=False):
"""
This class generates a list of either files and or folders within a root directory.
The walk method generates a directory list of files by walking the file tree top down or bottom up. The
files and folders method generate a list of files or folders in the top level of the tree.
:param directory: Starting directory file path
:param full_paths: Bool, when true full paths are concatenated to file paths list
:param topdown: Bool, when true walk method walks tree from the topdwon. When false tree is walked bottom up
:param to_include: None by default. List of filters acceptable to find within file path string return
:param to_exclude: None by default. List of filters NOT acceptable to return
:param min_level: 0 by default. Minimum directory level to save paths from
:param max_level: Infinity by default. Maximum directory level to save paths from
:param parallelize: Bool, when true pool processing is enabled within walk method
:param pool_size: Number of CPUs for pool processing, default is number of processors
:param console_output: Bool, when true console output is printed
:param console_stream: Bool, when true loops print live results
:param hash_files: Bool, when true walk() method return a dictionary file_paths and hashes
"""
self.timer = Timer()
self.full_paths = full_paths
self.topdown = topdown
# Exclude .DS_Store by default, set to_exclude to False to include .DS_Store
to_exclude = ['.DS_Store'] if to_exclude is None else to_exclude
if any(i for i in [to_include, to_exclude, filters]) or min_level != 0 or max_level != inf:
self.filters = PathFilters(to_include, to_exclude, min_level, max_level, filters, non_empty_folders)
else:
self.filters = False
self.console_output = console_output
self.console_stream = console_stream
self._hash_files = hash_files
self._printer = Printer(console_output, console_stream).printer
self._printer('DIRPATHS')
# Check that parallelization is enabled
if parallelize:
self.pool_size = pool_size
self.parallelize = parallelize
self.filepaths = []
# Check if directory is a singular (1) string or if it is a list of strings (multiple)
try:
self.directory = [str(directory)]
except TypeError:
self.directory = [str(dirs) for dirs in directory]
def __iter__(self):
return iter(list(self.filepaths))
def __str__(self):
return str(self.filepaths)
def __len__(self):
return len(self.filepaths)
def _get_filepaths(self):
"""Filters list of file paths to remove non-included, remove excluded files and concatenate full paths."""
self._printer(str(self.__len__()) + " file paths have been parsed in " + str(self.timer.end))
if self._hash_files:
return pool_hash(self.filepaths)
else:
return self.filepaths
def creation_dates(self, sort=True):
"""
Return a list of (file_path, creation_date) tuples created from list of walked paths.
:param sort: Bool, sorts file_paths on created_date from newest to oldest.
:return: List of (file_path, created_date) tuples.
"""
if not sort:
return pool_creation_date(self.filepaths)
else:
pcd = pool_creation_date(self.filepaths)
pcd.sort(key=itemgetter(1), reverse=True)
return pcd
def walk(self):
"""
Default file path retrieval function.
sprinter() - Generates file path list using pool processing and Queues
crawler() - Generates file path list using os.walk() in sequence
"""
if self.parallelize:
self.filepaths = Sprinter(self.directory, self.filters, self.full_paths, self.pool_size,
self._printer).sprinter()
else:
self.filepaths = Crawler(self.directory, self.filters, self.full_paths, self.topdown,
self._printer).crawler()
return self._get_filepaths()
def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
def folders(self):
"""Return list of folders in root directory"""
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isdir(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
class DirTree:
def __init__(self, root, branches=None):
"""
Generate a tree dictionary of the contents of a root directory.
:param root: Starting directory
:param branches: List of function tuples used for filtering
"""
self.tree_dict = {}
self.directory = Path(root)
self.start = str(self.directory).rfind(os.sep) + 1
self.branches = branches
self.get()
def __iter__(self):
return iter(self.tree_dict.items())
def __str__(self):
return str(self.tree_dict)
@property
def dict(self):
return self.tree_dict
def _filter(self, folders, folder_or_file):
for index in range(0, len(folders)):
filters = self.branches[index][folder_or_file]
if filters:
exclude = filters.get
include = filters.get
if exclude and folders[index] in exclude:
return False
if include and folders[index] not in include:
return False
return True
def get(self):
"""
Generate path, dirs, files tuple for each path in directory. Executes filters if branches are not None
:return:
"""
for path, dirs, files in os.walk(self.directory):
folders = path[self.start:].split(os.sep)
if self.branches:
if self._filter(folders, 'folders'):
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
else:
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
return self.tree_dict
def gui():
from dirutility.gui import WalkGUI
gui = WalkGUI()
params = gui.parsing()
parse = params['parse']
paths = DirPaths(parse['directory'],
console_stream=parse['console_stream'],
parallelize=parse['parallelize'],
max_level=parse['max_level'],
non_empty_folders=parse['non_empty_folders']).walk()
if params['save']:
from databasetools import CSVExport, DictTools
save = params['save']
if save['csv']:
CSVExport(list(paths),
cols=['files'],
file_path=save['directory'],
file_name=os.path.basename(parse['directory']))
if save['json']:
DictTools(save['directory'], os.path.basename(parse['directory'])).save(list(paths))
print('Done!')
if __name__ == "__main__":
gui()
| pool_hash | identifier_name |
walk.py | import os
import platform
import shutil
from datetime import datetime
from functools import reduce
from hashlib import md5
from math import inf
from multiprocessing import cpu_count
from multiprocessing.pool import Pool
from operator import itemgetter
from pathlib import Path
from looptools import Timer
from dirutility.walk.filter import PathFilters
from dirutility.walk.multiprocess import Sprinter
from dirutility.walk.sequential import Crawler
class Printer:
def __init__(self, console_output, console_stream):
"""Printer function initialized with classes. Used for optional printing"""
self.console_output = console_output
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process_name='Pool processing', cpus=cpu_count()):
"""
Apply a function to each element in an iterable and return a result list.
:param func: A function that returns a value
:param iterable: A list or set of elements to be passed to the func as the singular parameter
:param process_name: Name of the process, for printing purposes only
:param cpus: Number of CPUs
:return: Result list
"""
with Timer('\t{0} ({1}) completed in'.format(process_name, str(func))):
pool = Pool(cpus)
vals = pool.map(func, iterable)
pool.close()
return vals
def md5_hash(file_path):
"""Open a file path and hash the contents."""
with open(file_path, 'rb') as fp:
return md5(fp.read()).hexdigest()
def md5_tuple(file_path):
"""Returns a file_path, hash tuple."""
return file_path, md5_hash(file_path)
def pool_hash(path_list):
"""Pool process file hashing."""
return pool_process(md5_tuple, path_list, 'MD5 hashing')
def remover(file_path):
"""Delete a file or directory path only if it exists."""
if os.path.isfile(file_path):
os.remove(file_path)
return True
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
return True
else:
return False
def creation_date(path_to_file, return_datetime=True):
"""
Retrieve a file's creation date.
Try to get the date that a file was created, falling back to when it was
last modified if that isn't possible.
See http://stackoverflow.com/a/39501288/1709587 for explanation.
:param path_to_file: File path
:param return_datetime: Bool, returns value in Datetime format
:return: Creation date
"""
if platform.system() == 'Windows':
created_at = os.path.getctime(path_to_file)
else:
stat = os.stat(path_to_file)
try:
created_at = stat.st_birthtime
except AttributeError:
# We're probably on Linux. No easy way to get creation dates here,
# so we'll settle for when its content was last modified.
created_at = stat.st_mtime
if return_datetime:
return datetime.fromtimestamp(created_at)
else:
return created_at
def creation_date_tuple(file_path):
"""Returns a (file_path, creation_date) tuple."""
return file_path, creation_date(file_path)
def pool_creation_date(path_list):
|
class DirPaths:
def __init__(self,
directory,
full_paths=False,
topdown=True,
to_include=None,
to_exclude=None,
min_level=0,
max_level=inf,
filters=None,
non_empty_folders=False,
parallelize=False,
pool_size=cpu_count(),
console_output=False,
console_stream=False,
hash_files=False):
"""
This class generates a list of either files and or folders within a root directory.
The walk method generates a directory list of files by walking the file tree top down or bottom up. The
files and folders method generate a list of files or folders in the top level of the tree.
:param directory: Starting directory file path
:param full_paths: Bool, when true full paths are concatenated to file paths list
:param topdown: Bool, when true walk method walks tree from the topdwon. When false tree is walked bottom up
:param to_include: None by default. List of filters acceptable to find within file path string return
:param to_exclude: None by default. List of filters NOT acceptable to return
:param min_level: 0 by default. Minimum directory level to save paths from
:param max_level: Infinity by default. Maximum directory level to save paths from
:param parallelize: Bool, when true pool processing is enabled within walk method
:param pool_size: Number of CPUs for pool processing, default is number of processors
:param console_output: Bool, when true console output is printed
:param console_stream: Bool, when true loops print live results
:param hash_files: Bool, when true walk() method return a dictionary file_paths and hashes
"""
self.timer = Timer()
self.full_paths = full_paths
self.topdown = topdown
# Exclude .DS_Store by default, set to_exclude to False to include .DS_Store
to_exclude = ['.DS_Store'] if to_exclude is None else to_exclude
if any(i for i in [to_include, to_exclude, filters]) or min_level != 0 or max_level != inf:
self.filters = PathFilters(to_include, to_exclude, min_level, max_level, filters, non_empty_folders)
else:
self.filters = False
self.console_output = console_output
self.console_stream = console_stream
self._hash_files = hash_files
self._printer = Printer(console_output, console_stream).printer
self._printer('DIRPATHS')
# Check that parallelization is enabled
if parallelize:
self.pool_size = pool_size
self.parallelize = parallelize
self.filepaths = []
# Check if directory is a singular (1) string or if it is a list of strings (multiple)
try:
self.directory = [str(directory)]
except TypeError:
self.directory = [str(dirs) for dirs in directory]
def __iter__(self):
return iter(list(self.filepaths))
def __str__(self):
return str(self.filepaths)
def __len__(self):
return len(self.filepaths)
def _get_filepaths(self):
"""Filters list of file paths to remove non-included, remove excluded files and concatenate full paths."""
self._printer(str(self.__len__()) + " file paths have been parsed in " + str(self.timer.end))
if self._hash_files:
return pool_hash(self.filepaths)
else:
return self.filepaths
def creation_dates(self, sort=True):
"""
Return a list of (file_path, creation_date) tuples created from list of walked paths.
:param sort: Bool, sorts file_paths on created_date from newest to oldest.
:return: List of (file_path, created_date) tuples.
"""
if not sort:
return pool_creation_date(self.filepaths)
else:
pcd = pool_creation_date(self.filepaths)
pcd.sort(key=itemgetter(1), reverse=True)
return pcd
def walk(self):
"""
Default file path retrieval function.
sprinter() - Generates file path list using pool processing and Queues
crawler() - Generates file path list using os.walk() in sequence
"""
if self.parallelize:
self.filepaths = Sprinter(self.directory, self.filters, self.full_paths, self.pool_size,
self._printer).sprinter()
else:
self.filepaths = Crawler(self.directory, self.filters, self.full_paths, self.topdown,
self._printer).crawler()
return self._get_filepaths()
def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
def folders(self):
"""Return list of folders in root directory"""
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isdir(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
class DirTree:
def __init__(self, root, branches=None):
"""
Generate a tree dictionary of the contents of a root directory.
:param root: Starting directory
:param branches: List of function tuples used for filtering
"""
self.tree_dict = {}
self.directory = Path(root)
self.start = str(self.directory).rfind(os.sep) + 1
self.branches = branches
self.get()
def __iter__(self):
return iter(self.tree_dict.items())
def __str__(self):
return str(self.tree_dict)
@property
def dict(self):
return self.tree_dict
def _filter(self, folders, folder_or_file):
for index in range(0, len(folders)):
filters = self.branches[index][folder_or_file]
if filters:
exclude = filters.get
include = filters.get
if exclude and folders[index] in exclude:
return False
if include and folders[index] not in include:
return False
return True
def get(self):
"""
Generate path, dirs, files tuple for each path in directory. Executes filters if branches are not None
:return:
"""
for path, dirs, files in os.walk(self.directory):
folders = path[self.start:].split(os.sep)
if self.branches:
if self._filter(folders, 'folders'):
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
else:
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
return self.tree_dict
def gui():
from dirutility.gui import WalkGUI
gui = WalkGUI()
params = gui.parsing()
parse = params['parse']
paths = DirPaths(parse['directory'],
console_stream=parse['console_stream'],
parallelize=parse['parallelize'],
max_level=parse['max_level'],
non_empty_folders=parse['non_empty_folders']).walk()
if params['save']:
from databasetools import CSVExport, DictTools
save = params['save']
if save['csv']:
CSVExport(list(paths),
cols=['files'],
file_path=save['directory'],
file_name=os.path.basename(parse['directory']))
if save['json']:
DictTools(save['directory'], os.path.basename(parse['directory'])).save(list(paths))
print('Done!')
if __name__ == "__main__":
gui()
| """Pool process file creation dates."""
return pool_process(creation_date_tuple, path_list, 'File creation dates') | identifier_body |
walk.py | import os
import platform
import shutil
from datetime import datetime
from functools import reduce
from hashlib import md5
from math import inf
from multiprocessing import cpu_count
from multiprocessing.pool import Pool
from operator import itemgetter
from pathlib import Path
from looptools import Timer
from dirutility.walk.filter import PathFilters
from dirutility.walk.multiprocess import Sprinter
from dirutility.walk.sequential import Crawler
class Printer:
def __init__(self, console_output, console_stream):
"""Printer function initialized with classes. Used for optional printing"""
self.console_output = console_output
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process_name='Pool processing', cpus=cpu_count()):
"""
Apply a function to each element in an iterable and return a result list.
:param func: A function that returns a value
:param iterable: A list or set of elements to be passed to the func as the singular parameter
:param process_name: Name of the process, for printing purposes only
:param cpus: Number of CPUs
:return: Result list
"""
with Timer('\t{0} ({1}) completed in'.format(process_name, str(func))):
pool = Pool(cpus)
vals = pool.map(func, iterable)
pool.close()
return vals
def md5_hash(file_path):
"""Open a file path and hash the contents."""
with open(file_path, 'rb') as fp:
return md5(fp.read()).hexdigest()
def md5_tuple(file_path):
"""Returns a file_path, hash tuple."""
return file_path, md5_hash(file_path)
def pool_hash(path_list):
"""Pool process file hashing."""
return pool_process(md5_tuple, path_list, 'MD5 hashing')
def remover(file_path):
"""Delete a file or directory path only if it exists."""
if os.path.isfile(file_path):
os.remove(file_path)
return True
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
return True
else:
return False
def creation_date(path_to_file, return_datetime=True):
"""
Retrieve a file's creation date.
Try to get the date that a file was created, falling back to when it was
last modified if that isn't possible.
See http://stackoverflow.com/a/39501288/1709587 for explanation.
:param path_to_file: File path
:param return_datetime: Bool, returns value in Datetime format
:return: Creation date
"""
if platform.system() == 'Windows':
created_at = os.path.getctime(path_to_file)
else:
stat = os.stat(path_to_file)
try:
created_at = stat.st_birthtime
except AttributeError:
# We're probably on Linux. No easy way to get creation dates here,
# so we'll settle for when its content was last modified.
created_at = stat.st_mtime
if return_datetime:
return datetime.fromtimestamp(created_at)
else:
return created_at
def creation_date_tuple(file_path):
"""Returns a (file_path, creation_date) tuple."""
return file_path, creation_date(file_path)
def pool_creation_date(path_list):
"""Pool process file creation dates."""
return pool_process(creation_date_tuple, path_list, 'File creation dates')
class DirPaths:
def __init__(self,
directory,
full_paths=False,
topdown=True,
to_include=None,
to_exclude=None,
min_level=0,
max_level=inf,
filters=None,
non_empty_folders=False,
parallelize=False,
pool_size=cpu_count(),
console_output=False,
console_stream=False,
hash_files=False):
"""
This class generates a list of either files and or folders within a root directory.
The walk method generates a directory list of files by walking the file tree top down or bottom up. The
files and folders method generate a list of files or folders in the top level of the tree.
:param directory: Starting directory file path
:param full_paths: Bool, when true full paths are concatenated to file paths list
:param topdown: Bool, when true walk method walks tree from the topdwon. When false tree is walked bottom up
:param to_include: None by default. List of filters acceptable to find within file path string return
:param to_exclude: None by default. List of filters NOT acceptable to return
:param min_level: 0 by default. Minimum directory level to save paths from
:param max_level: Infinity by default. Maximum directory level to save paths from
:param parallelize: Bool, when true pool processing is enabled within walk method
:param pool_size: Number of CPUs for pool processing, default is number of processors
:param console_output: Bool, when true console output is printed
:param console_stream: Bool, when true loops print live results
:param hash_files: Bool, when true walk() method return a dictionary file_paths and hashes
"""
self.timer = Timer()
self.full_paths = full_paths
self.topdown = topdown
# Exclude .DS_Store by default, set to_exclude to False to include .DS_Store
to_exclude = ['.DS_Store'] if to_exclude is None else to_exclude
if any(i for i in [to_include, to_exclude, filters]) or min_level != 0 or max_level != inf:
|
else:
self.filters = False
self.console_output = console_output
self.console_stream = console_stream
self._hash_files = hash_files
self._printer = Printer(console_output, console_stream).printer
self._printer('DIRPATHS')
# Check that parallelization is enabled
if parallelize:
self.pool_size = pool_size
self.parallelize = parallelize
self.filepaths = []
# Check if directory is a singular (1) string or if it is a list of strings (multiple)
try:
self.directory = [str(directory)]
except TypeError:
self.directory = [str(dirs) for dirs in directory]
def __iter__(self):
return iter(list(self.filepaths))
def __str__(self):
return str(self.filepaths)
def __len__(self):
return len(self.filepaths)
def _get_filepaths(self):
"""Filters list of file paths to remove non-included, remove excluded files and concatenate full paths."""
self._printer(str(self.__len__()) + " file paths have been parsed in " + str(self.timer.end))
if self._hash_files:
return pool_hash(self.filepaths)
else:
return self.filepaths
def creation_dates(self, sort=True):
"""
Return a list of (file_path, creation_date) tuples created from list of walked paths.
:param sort: Bool, sorts file_paths on created_date from newest to oldest.
:return: List of (file_path, created_date) tuples.
"""
if not sort:
return pool_creation_date(self.filepaths)
else:
pcd = pool_creation_date(self.filepaths)
pcd.sort(key=itemgetter(1), reverse=True)
return pcd
def walk(self):
"""
Default file path retrieval function.
sprinter() - Generates file path list using pool processing and Queues
crawler() - Generates file path list using os.walk() in sequence
"""
if self.parallelize:
self.filepaths = Sprinter(self.directory, self.filters, self.full_paths, self.pool_size,
self._printer).sprinter()
else:
self.filepaths = Crawler(self.directory, self.filters, self.full_paths, self.topdown,
self._printer).crawler()
return self._get_filepaths()
def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
def folders(self):
"""Return list of folders in root directory"""
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isdir(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
class DirTree:
def __init__(self, root, branches=None):
"""
Generate a tree dictionary of the contents of a root directory.
:param root: Starting directory
:param branches: List of function tuples used for filtering
"""
self.tree_dict = {}
self.directory = Path(root)
self.start = str(self.directory).rfind(os.sep) + 1
self.branches = branches
self.get()
def __iter__(self):
return iter(self.tree_dict.items())
def __str__(self):
return str(self.tree_dict)
@property
def dict(self):
return self.tree_dict
def _filter(self, folders, folder_or_file):
for index in range(0, len(folders)):
filters = self.branches[index][folder_or_file]
if filters:
exclude = filters.get
include = filters.get
if exclude and folders[index] in exclude:
return False
if include and folders[index] not in include:
return False
return True
def get(self):
"""
Generate path, dirs, files tuple for each path in directory. Executes filters if branches are not None
:return:
"""
for path, dirs, files in os.walk(self.directory):
folders = path[self.start:].split(os.sep)
if self.branches:
if self._filter(folders, 'folders'):
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
else:
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
return self.tree_dict
def gui():
from dirutility.gui import WalkGUI
gui = WalkGUI()
params = gui.parsing()
parse = params['parse']
paths = DirPaths(parse['directory'],
console_stream=parse['console_stream'],
parallelize=parse['parallelize'],
max_level=parse['max_level'],
non_empty_folders=parse['non_empty_folders']).walk()
if params['save']:
from databasetools import CSVExport, DictTools
save = params['save']
if save['csv']:
CSVExport(list(paths),
cols=['files'],
file_path=save['directory'],
file_name=os.path.basename(parse['directory']))
if save['json']:
DictTools(save['directory'], os.path.basename(parse['directory'])).save(list(paths))
print('Done!')
if __name__ == "__main__":
gui()
| self.filters = PathFilters(to_include, to_exclude, min_level, max_level, filters, non_empty_folders) | conditional_block |
walk.py | import os
import platform
import shutil
from datetime import datetime
from functools import reduce
from hashlib import md5
from math import inf
from multiprocessing import cpu_count
from multiprocessing.pool import Pool
from operator import itemgetter
from pathlib import Path
from looptools import Timer
from dirutility.walk.filter import PathFilters
from dirutility.walk.multiprocess import Sprinter
from dirutility.walk.sequential import Crawler
class Printer:
def __init__(self, console_output, console_stream):
"""Printer function initialized with classes. Used for optional printing"""
self.console_output = console_output
self.console_stream = console_stream
def printer(self, message, stream=False):
if not stream:
if self.console_output:
print('\t' + message)
else:
if self.console_stream:
print('\t' + message)
def pool_process(func, iterable, process_name='Pool processing', cpus=cpu_count()):
"""
Apply a function to each element in an iterable and return a result list.
:param func: A function that returns a value
:param iterable: A list or set of elements to be passed to the func as the singular parameter
:param process_name: Name of the process, for printing purposes only
:param cpus: Number of CPUs
:return: Result list
"""
with Timer('\t{0} ({1}) completed in'.format(process_name, str(func))):
pool = Pool(cpus)
vals = pool.map(func, iterable)
pool.close()
return vals
def md5_hash(file_path):
"""Open a file path and hash the contents."""
with open(file_path, 'rb') as fp:
return md5(fp.read()).hexdigest()
def md5_tuple(file_path):
"""Returns a file_path, hash tuple."""
return file_path, md5_hash(file_path)
def pool_hash(path_list):
"""Pool process file hashing."""
return pool_process(md5_tuple, path_list, 'MD5 hashing')
def remover(file_path):
"""Delete a file or directory path only if it exists."""
if os.path.isfile(file_path):
os.remove(file_path)
return True
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
return True
else:
return False
def creation_date(path_to_file, return_datetime=True):
"""
Retrieve a file's creation date.
Try to get the date that a file was created, falling back to when it was
last modified if that isn't possible.
See http://stackoverflow.com/a/39501288/1709587 for explanation.
:param path_to_file: File path
:param return_datetime: Bool, returns value in Datetime format
:return: Creation date
"""
if platform.system() == 'Windows':
created_at = os.path.getctime(path_to_file)
else:
stat = os.stat(path_to_file)
try:
created_at = stat.st_birthtime
except AttributeError:
# We're probably on Linux. No easy way to get creation dates here,
# so we'll settle for when its content was last modified.
created_at = stat.st_mtime
if return_datetime:
return datetime.fromtimestamp(created_at)
else:
return created_at
def creation_date_tuple(file_path):
"""Returns a (file_path, creation_date) tuple."""
return file_path, creation_date(file_path)
def pool_creation_date(path_list):
"""Pool process file creation dates."""
return pool_process(creation_date_tuple, path_list, 'File creation dates')
class DirPaths:
def __init__(self,
directory,
full_paths=False,
topdown=True,
to_include=None,
to_exclude=None,
min_level=0,
max_level=inf,
filters=None,
non_empty_folders=False,
parallelize=False,
pool_size=cpu_count(),
console_output=False,
console_stream=False,
hash_files=False):
"""
This class generates a list of either files and or folders within a root directory.
The walk method generates a directory list of files by walking the file tree top down or bottom up. The
files and folders method generate a list of files or folders in the top level of the tree.
:param directory: Starting directory file path
:param full_paths: Bool, when true full paths are concatenated to file paths list
:param topdown: Bool, when true walk method walks tree from the topdwon. When false tree is walked bottom up
:param to_include: None by default. List of filters acceptable to find within file path string return
:param to_exclude: None by default. List of filters NOT acceptable to return
:param min_level: 0 by default. Minimum directory level to save paths from
:param max_level: Infinity by default. Maximum directory level to save paths from
:param parallelize: Bool, when true pool processing is enabled within walk method
:param pool_size: Number of CPUs for pool processing, default is number of processors
:param console_output: Bool, when true console output is printed
:param console_stream: Bool, when true loops print live results
:param hash_files: Bool, when true walk() method return a dictionary file_paths and hashes
"""
self.timer = Timer()
self.full_paths = full_paths
self.topdown = topdown
# Exclude .DS_Store by default, set to_exclude to False to include .DS_Store
to_exclude = ['.DS_Store'] if to_exclude is None else to_exclude
if any(i for i in [to_include, to_exclude, filters]) or min_level != 0 or max_level != inf:
self.filters = PathFilters(to_include, to_exclude, min_level, max_level, filters, non_empty_folders)
else:
self.filters = False
self.console_output = console_output
self.console_stream = console_stream
self._hash_files = hash_files
self._printer = Printer(console_output, console_stream).printer
self._printer('DIRPATHS')
# Check that parallelization is enabled
if parallelize:
self.pool_size = pool_size
self.parallelize = parallelize
self.filepaths = []
# Check if directory is a singular (1) string or if it is a list of strings (multiple)
try:
self.directory = [str(directory)]
except TypeError:
self.directory = [str(dirs) for dirs in directory]
def __iter__(self):
return iter(list(self.filepaths))
def __str__(self):
return str(self.filepaths)
def __len__(self):
return len(self.filepaths)
def _get_filepaths(self):
"""Filters list of file paths to remove non-included, remove excluded files and concatenate full paths."""
self._printer(str(self.__len__()) + " file paths have been parsed in " + str(self.timer.end))
if self._hash_files:
return pool_hash(self.filepaths)
else:
return self.filepaths
def creation_dates(self, sort=True):
"""
Return a list of (file_path, creation_date) tuples created from list of walked paths.
:param sort: Bool, sorts file_paths on created_date from newest to oldest.
:return: List of (file_path, created_date) tuples.
"""
if not sort:
return pool_creation_date(self.filepaths)
else:
pcd = pool_creation_date(self.filepaths)
pcd.sort(key=itemgetter(1), reverse=True)
return pcd
def walk(self):
"""
Default file path retrieval function.
sprinter() - Generates file path list using pool processing and Queues
crawler() - Generates file path list using os.walk() in sequence
"""
if self.parallelize:
self.filepaths = Sprinter(self.directory, self.filters, self.full_paths, self.pool_size,
self._printer).sprinter()
else:
self.filepaths = Crawler(self.directory, self.filters, self.full_paths, self.topdown,
self._printer).crawler()
return self._get_filepaths()
def files(self):
"""Return list of files in root directory"""
self._printer('\tFiles Walk')
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isfile(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
def folders(self):
"""Return list of folders in root directory"""
for directory in self.directory:
for path in os.listdir(directory):
full_path = os.path.join(directory, path)
if os.path.isdir(full_path):
if not path.startswith('.'):
self.filepaths.append(full_path)
return self._get_filepaths()
class DirTree:
def __init__(self, root, branches=None):
"""
Generate a tree dictionary of the contents of a root directory.
:param root: Starting directory
:param branches: List of function tuples used for filtering
"""
self.tree_dict = {}
self.directory = Path(root)
self.start = str(self.directory).rfind(os.sep) + 1
self.branches = branches
self.get()
| return str(self.tree_dict)
@property
def dict(self):
return self.tree_dict
def _filter(self, folders, folder_or_file):
for index in range(0, len(folders)):
filters = self.branches[index][folder_or_file]
if filters:
exclude = filters.get
include = filters.get
if exclude and folders[index] in exclude:
return False
if include and folders[index] not in include:
return False
return True
def get(self):
"""
Generate path, dirs, files tuple for each path in directory. Executes filters if branches are not None
:return:
"""
for path, dirs, files in os.walk(self.directory):
folders = path[self.start:].split(os.sep)
if self.branches:
if self._filter(folders, 'folders'):
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
else:
files = dict.fromkeys(files)
parent = reduce(dict.get, folders[:-1], self.tree_dict)
parent[folders[-1]] = files
return self.tree_dict
def gui():
from dirutility.gui import WalkGUI
gui = WalkGUI()
params = gui.parsing()
parse = params['parse']
paths = DirPaths(parse['directory'],
console_stream=parse['console_stream'],
parallelize=parse['parallelize'],
max_level=parse['max_level'],
non_empty_folders=parse['non_empty_folders']).walk()
if params['save']:
from databasetools import CSVExport, DictTools
save = params['save']
if save['csv']:
CSVExport(list(paths),
cols=['files'],
file_path=save['directory'],
file_name=os.path.basename(parse['directory']))
if save['json']:
DictTools(save['directory'], os.path.basename(parse['directory'])).save(list(paths))
print('Done!')
if __name__ == "__main__":
gui() | def __iter__(self):
return iter(self.tree_dict.items())
def __str__(self): | random_line_split |
utils.py | import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import rankdata
import time
import logging
logger = logging.getLogger(__name__)
def plot_learning_curves(bnn, plotsize=4):
total_epochs = len(bnn.fit_history.history["loss"])
fig, axes = plt.subplots(
1, len(bnn.metrics_names),
figsize=(len(bnn.metrics_names)*plotsize, plotsize))
axes[0].plot(range(total_epochs), bnn.fit_history.history["loss"], '-o', label="training")
if 'val_loss' in bnn.fit_history.history:
axes[0].plot(range(total_epochs), bnn.fit_history.history["val_loss"], '-o', label="validation")
axes[0].legend()
axes[0].set_ylabel("ELBO")
axes[0].set_xlabel("epoch")
for i in range(len(bnn.metrics_names)-1):
this_metric = bnn.metrics_names[i+1]
axes[i+1].plot(range(total_epochs), bnn.fit_history.history[this_metric], '-o', label="training")
if "val_{}".format(this_metric) in bnn.fit_history.history:
axes[i+1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)
def onehot_encode_labels(y):
"""
One-hot encode integer labels y. The number of classes is assumed to be
the largest value in y
Args:
y: array with shape (n_examples,)
Returns:
array with shape (n_examples, n_classes)
"""
return OneHotEncoder(categories="auto", sparse=False).fit_transform(y.reshape(y.shape[0],1))
def get_roc_curves(variable_importances):
"""
Calculate ROC curves
# TODO: set row idx as variable
Args:
variable_importances: A dataframe with the following columns:
- method
- n
- p
- repeat_idx
- variable
"""
roc_curve_df = pd.DataFrame()
base_fpr = np.linspace(0, 1, 101) # Interpolate tpr (y-axis) at these fpr (x-axis) values
for method in variable_importances["method"].unique():
for n in variable_importances["n"].unique():
for p in variable_importances["p"].unique():
for repeat_idx in range(np.amax(variable_importances["repeat_idx"].unique()+1)):
df = variable_importances.loc[
(variable_importances["method"]==method) &
(variable_importances["repeat_idx"]==repeat_idx) &
(variable_importances["n"]==n) &
(variable_importances["p"]==p)
]
if len(df)==0:
continue
preds, labels = df["value"].values, df["causal"].values.astype(float)
fpr, tpr, _ = roc_curve(labels, np.abs(preds))
interp_tpr = np.interp(base_fpr, fpr, tpr)
auroc = auc(fpr, tpr)
roc_curve_df = pd.concat([
roc_curve_df,
pd.DataFrame({
"fpr" : base_fpr, "tpr" : interp_tpr, "auc" : auroc,
"method" : method, "n" : n, "p" : p
})
])
return roc_curve_df
def load_mnist(fashion, onehot_encode=True, flatten_x=False, crop_x=0, classes=None):
"""
Load the MNIST dataset
Args:
onehot_encode: Boolean indicating whether to one-hot encode training
and test labels (default True)
flatten_x: Boolean indicating whether to flatten the training and
test inputs to 2D arrays with shape (n_examples, image_size**2).
If False, returned inputs have shape (n_examples, image_size, image_size
(default False)
crop_x: Integer controlling the size of the border to be removed from the input
images (default 0, meaning no cropping).
classes: None to include all classes (default). Otherwise include a list of two
integers that will be encoded as 0, 1 in the order they appear.
Returns:
x_train, y_train, x_test, y_test: train and test inputs and labels.
First dimension is always the number of examples
"""
if not fashion:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
else:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
def crop(X, crop_size):
assert crop_x < X.shape[1]/2
assert crop_x < X.shape[2]/2
return X[:,crop_size:-crop_size,crop_size:-crop_size]
if crop_x > 0:
x_train = crop(x_train, crop_x)
x_test = crop(x_test, crop_x)
# Flatten to 2d arrays (each example 1d)
def flatten_image(X):
return X.reshape(X.shape[0], X.shape[1]*X.shape[1])
if flatten_x:
x_train = flatten_image(x_train)
x_test = flatten_image(x_test)
if onehot_encode:
y_train = onehot_encode_labels(y_train)
y_test = onehot_encode_labels(y_test)
if classes is not None:
assert len(classes) == 2
c0, c1 = classes
train_idxs_to_keep = np.logical_or(y_train==c0, y_train==c1)
x_train, y_train = x_train[train_idxs_to_keep,:], y_train[train_idxs_to_keep]
test_idxs_to_keep = np.logical_or(y_test==c0, y_test==c1)
x_test, y_test = x_test[test_idxs_to_keep,:], y_test[test_idxs_to_keep]
y_train = (y_train==c1).astype(int)[:,np.newaxis]
y_test = (y_test==c1).astype(int)[:,np.newaxis]
return x_train, y_train, x_test, y_test
def make_square(arr):
"""
Reshape a 1D array (or 2D array with .shape[2]==1) into a square 2D array
"""
assert arr.ndim==1 or arr.ndim==2, "array must be 1 or 2-D"
if arr.ndim==2:
assert arr.shape[1]==1, "If array is 2d then second dimension must be 1"
arr = arr.reshape(arr.shape[0])
assert arr.shape[0]**0.5 == int(arr.shape[0]**0.5), "array shape must be square (it is {})".format(arr.shape[0])
return arr.reshape(int(arr.shape[0]**0.5), int(arr.shape[0]**0.5))
def accuracy_onehot(labels, preds):
"""
Compute the accuracy of predictions using one-hot encoded labels
Args:
labels: array of labels with shape (n_examples, n_classes). Must be one-hot encoded
or result may be nonsense (this is not checked)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(np.argmax(preds, axis=1) == np.argmax(labels, axis=1))/float(labels.shape[0])
def accuracy(labels, preds):
"""
Compute the accuracy of predictions using integer labels
Args:
labels: array of labels with shape (n_examples,)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(preds==labels)/float(labels.shape[0])
def get_nullify_idxs(original_size, border_size):
"""
Get the indices of a flattened image that lie within border_size of the
edge of an image (use to pass to nullify argument in RATE function)
Args:
original size: Integer giving the size of the image
border_size: Integer giving the size of the border to be removed.
Returns:
Array of (integer) indices that lie in the border.
"""
assert border_size < original_size/2, "Border too large to be removed from image of this size"
tmp = np.zeros((original_size, original_size), dtype=int)
tmp[:border_size,:] = 1
tmp[-border_size:,:] = 1
tmp[:,-border_size:] = 1
tmp[:,:border_size] = 1
tmp = tmp.reshape(tmp.shape[0]*tmp.shape[1])
return np.where(tmp==1)[0]
def idx2pixel(idx, image_size):
"""
Get the 2D pixel location corresponding to the index of its flattened array
Args:
idx: integer index to be converted to pixel location
image_size: integer giving size of the image
Returns:
i, j: the location of the pixel corresponding to idx
"""
assert idx < image_size**2, "index {} too large for image size {}".format(idx, image_size)
tmp = np.zeros(image_size**2)
tmp[idx] = 1
tmp = tmp.reshape(image_size, image_size)
i, j = np.where(tmp==1)
return i[0], j[0]
def sampled_accuracies(pred_proba_samples, labels):
""" | pred_proba_samples: array of predicted probability samples with shape
(n_mc_samples, n_examples, n_classes)/(n_mc_samples, n_examples)
for multiclass/binary classification. (This is the shape returned by BNN_Classifier.predict).
labels: array of one-hot encoded labels with shape (n_examples, n_classes) for non-binary clasification
or (n_examples,1) for binary classification.
Returns:
Array of test accuracies for each round of MC samples with shape (n_mc_samples,)
"""
binary_labels = labels.shape[1]==1
assert pred_proba_samples.shape[1]==labels.shape[0], "Different number of examples in logit samples and labels"
if not binary_labels:
assert pred_proba_samples.shape[2]==labels.shape[1], "Different number of classes in logit samples and labels"
sampled_test_accuracies = np.sum(
np.argmax(pred_proba_samples, axis=2) == np.argmax(labels, axis=1)[:,np.newaxis], axis=1)/float(labels.shape[0])
else:
sampled_test_accuracies = np.sum((pred_proba_samples[:,:]>0.5) == labels[:,0], axis=1)/float(labels.shape[0])
return sampled_test_accuracies
def accuracy_hist(pred_proba_samples, labels):
"""
Plot a histogram showing test accuracies.
Just calls sampled_accuracies then plots the result.
"""
sampled_acc = sampled_accuracies(pred_proba_samples, labels)
avg_accuracy = round(np.mean(sampled_acc) * 100, 3)
print("average accuracy across " + str(pred_proba_samples.shape[0]) + " samples: " + str(avg_accuracy) + "%\n")
fig, ax = plt.subplots(figsize=(10,5))
sns.distplot(100*sampled_acc, ax=ax, rug=True, kde=False)
ax.set_xlabel("Test set accuracy (%)", fontsize=30)
ax.set_ylabel("Frequency density", fontsize=30);
ax.tick_params("both", labelsize=15)
return sampled_acc
def rank_array(arr):
assert arr.ndim==1
return (arr.shape[0] - rankdata(arr)).astype(int)
def reverse_ranks(rankarr):
return rankarr.shape[0] - rankarr - 1
def compute_power(pvals, SNPs):
"""
Compute the power for identifying causal predictors.
Args:
Ps: list of causal predictors
Output: matrix with dimension (num. predictors, 2), where columns are FPR, TPR
"""
nsnps = len(pvals)
all_snps = np.arange(0, nsnps)
pos = SNPs
negs = list(set(all_snps) - set(SNPs))
pvals_rank = rank_array(pvals)
rocr = np.zeros((nsnps, 2))
for i in all_snps:
v = pvals_rank[0:i] # test positives
z = list(set(all_snps) - set(v)) # test negatives
TP = len(set(v) & set(pos))
FP = len(set(v) & set(negs))
TN = len(set(z) & set(negs))
FN = len(set(z) & set(pos))
TPR = 1.0*TP/(TP+FN); FPR = 1.0*FP/(FP+TN); #FDR = 1.0*FP/(FP+TP)
rocr[i, :] = [FPR, TPR]
return rocr | Get the sampled accuracies over the entire test set from logit samples.
Args: | random_line_split |
utils.py | import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import rankdata
import time
import logging
logger = logging.getLogger(__name__)
def plot_learning_curves(bnn, plotsize=4):
total_epochs = len(bnn.fit_history.history["loss"])
fig, axes = plt.subplots(
1, len(bnn.metrics_names),
figsize=(len(bnn.metrics_names)*plotsize, plotsize))
axes[0].plot(range(total_epochs), bnn.fit_history.history["loss"], '-o', label="training")
if 'val_loss' in bnn.fit_history.history:
axes[0].plot(range(total_epochs), bnn.fit_history.history["val_loss"], '-o', label="validation")
axes[0].legend()
axes[0].set_ylabel("ELBO")
axes[0].set_xlabel("epoch")
for i in range(len(bnn.metrics_names)-1):
this_metric = bnn.metrics_names[i+1]
axes[i+1].plot(range(total_epochs), bnn.fit_history.history[this_metric], '-o', label="training")
if "val_{}".format(this_metric) in bnn.fit_history.history:
axes[i+1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)
def onehot_encode_labels(y):
"""
One-hot encode integer labels y. The number of classes is assumed to be
the largest value in y
Args:
y: array with shape (n_examples,)
Returns:
array with shape (n_examples, n_classes)
"""
return OneHotEncoder(categories="auto", sparse=False).fit_transform(y.reshape(y.shape[0],1))
def get_roc_curves(variable_importances):
"""
Calculate ROC curves
# TODO: set row idx as variable
Args:
variable_importances: A dataframe with the following columns:
- method
- n
- p
- repeat_idx
- variable
"""
roc_curve_df = pd.DataFrame()
base_fpr = np.linspace(0, 1, 101) # Interpolate tpr (y-axis) at these fpr (x-axis) values
for method in variable_importances["method"].unique():
for n in variable_importances["n"].unique():
for p in variable_importances["p"].unique():
|
return roc_curve_df
def load_mnist(fashion, onehot_encode=True, flatten_x=False, crop_x=0, classes=None):
"""
Load the MNIST dataset
Args:
onehot_encode: Boolean indicating whether to one-hot encode training
and test labels (default True)
flatten_x: Boolean indicating whether to flatten the training and
test inputs to 2D arrays with shape (n_examples, image_size**2).
If False, returned inputs have shape (n_examples, image_size, image_size
(default False)
crop_x: Integer controlling the size of the border to be removed from the input
images (default 0, meaning no cropping).
classes: None to include all classes (default). Otherwise include a list of two
integers that will be encoded as 0, 1 in the order they appear.
Returns:
x_train, y_train, x_test, y_test: train and test inputs and labels.
First dimension is always the number of examples
"""
if not fashion:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
else:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
def crop(X, crop_size):
assert crop_x < X.shape[1]/2
assert crop_x < X.shape[2]/2
return X[:,crop_size:-crop_size,crop_size:-crop_size]
if crop_x > 0:
x_train = crop(x_train, crop_x)
x_test = crop(x_test, crop_x)
# Flatten to 2d arrays (each example 1d)
def flatten_image(X):
return X.reshape(X.shape[0], X.shape[1]*X.shape[1])
if flatten_x:
x_train = flatten_image(x_train)
x_test = flatten_image(x_test)
if onehot_encode:
y_train = onehot_encode_labels(y_train)
y_test = onehot_encode_labels(y_test)
if classes is not None:
assert len(classes) == 2
c0, c1 = classes
train_idxs_to_keep = np.logical_or(y_train==c0, y_train==c1)
x_train, y_train = x_train[train_idxs_to_keep,:], y_train[train_idxs_to_keep]
test_idxs_to_keep = np.logical_or(y_test==c0, y_test==c1)
x_test, y_test = x_test[test_idxs_to_keep,:], y_test[test_idxs_to_keep]
y_train = (y_train==c1).astype(int)[:,np.newaxis]
y_test = (y_test==c1).astype(int)[:,np.newaxis]
return x_train, y_train, x_test, y_test
def make_square(arr):
"""
Reshape a 1D array (or 2D array with .shape[2]==1) into a square 2D array
"""
assert arr.ndim==1 or arr.ndim==2, "array must be 1 or 2-D"
if arr.ndim==2:
assert arr.shape[1]==1, "If array is 2d then second dimension must be 1"
arr = arr.reshape(arr.shape[0])
assert arr.shape[0]**0.5 == int(arr.shape[0]**0.5), "array shape must be square (it is {})".format(arr.shape[0])
return arr.reshape(int(arr.shape[0]**0.5), int(arr.shape[0]**0.5))
def accuracy_onehot(labels, preds):
"""
Compute the accuracy of predictions using one-hot encoded labels
Args:
labels: array of labels with shape (n_examples, n_classes). Must be one-hot encoded
or result may be nonsense (this is not checked)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(np.argmax(preds, axis=1) == np.argmax(labels, axis=1))/float(labels.shape[0])
def accuracy(labels, preds):
"""
Compute the accuracy of predictions using integer labels
Args:
labels: array of labels with shape (n_examples,)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(preds==labels)/float(labels.shape[0])
def get_nullify_idxs(original_size, border_size):
"""
Get the indices of a flattened image that lie within border_size of the
edge of an image (use to pass to nullify argument in RATE function)
Args:
original size: Integer giving the size of the image
border_size: Integer giving the size of the border to be removed.
Returns:
Array of (integer) indices that lie in the border.
"""
assert border_size < original_size/2, "Border too large to be removed from image of this size"
tmp = np.zeros((original_size, original_size), dtype=int)
tmp[:border_size,:] = 1
tmp[-border_size:,:] = 1
tmp[:,-border_size:] = 1
tmp[:,:border_size] = 1
tmp = tmp.reshape(tmp.shape[0]*tmp.shape[1])
return np.where(tmp==1)[0]
def idx2pixel(idx, image_size):
"""
Get the 2D pixel location corresponding to the index of its flattened array
Args:
idx: integer index to be converted to pixel location
image_size: integer giving size of the image
Returns:
i, j: the location of the pixel corresponding to idx
"""
assert idx < image_size**2, "index {} too large for image size {}".format(idx, image_size)
tmp = np.zeros(image_size**2)
tmp[idx] = 1
tmp = tmp.reshape(image_size, image_size)
i, j = np.where(tmp==1)
return i[0], j[0]
def sampled_accuracies(pred_proba_samples, labels):
"""
Get the sampled accuracies over the entire test set from logit samples.
Args:
pred_proba_samples: array of predicted probability samples with shape
(n_mc_samples, n_examples, n_classes)/(n_mc_samples, n_examples)
for multiclass/binary classification. (This is the shape returned by BNN_Classifier.predict).
labels: array of one-hot encoded labels with shape (n_examples, n_classes) for non-binary clasification
or (n_examples,1) for binary classification.
Returns:
Array of test accuracies for each round of MC samples with shape (n_mc_samples,)
"""
binary_labels = labels.shape[1]==1
assert pred_proba_samples.shape[1]==labels.shape[0], "Different number of examples in logit samples and labels"
if not binary_labels:
assert pred_proba_samples.shape[2]==labels.shape[1], "Different number of classes in logit samples and labels"
sampled_test_accuracies = np.sum(
np.argmax(pred_proba_samples, axis=2) == np.argmax(labels, axis=1)[:,np.newaxis], axis=1)/float(labels.shape[0])
else:
sampled_test_accuracies = np.sum((pred_proba_samples[:,:]>0.5) == labels[:,0], axis=1)/float(labels.shape[0])
return sampled_test_accuracies
def accuracy_hist(pred_proba_samples, labels):
"""
Plot a histogram showing test accuracies.
Just calls sampled_accuracies then plots the result.
"""
sampled_acc = sampled_accuracies(pred_proba_samples, labels)
avg_accuracy = round(np.mean(sampled_acc) * 100, 3)
print("average accuracy across " + str(pred_proba_samples.shape[0]) + " samples: " + str(avg_accuracy) + "%\n")
fig, ax = plt.subplots(figsize=(10,5))
sns.distplot(100*sampled_acc, ax=ax, rug=True, kde=False)
ax.set_xlabel("Test set accuracy (%)", fontsize=30)
ax.set_ylabel("Frequency density", fontsize=30);
ax.tick_params("both", labelsize=15)
return sampled_acc
def rank_array(arr):
assert arr.ndim==1
return (arr.shape[0] - rankdata(arr)).astype(int)
def reverse_ranks(rankarr):
return rankarr.shape[0] - rankarr - 1
def compute_power(pvals, SNPs):
"""
Compute the power for identifying causal predictors.
Args:
Ps: list of causal predictors
Output: matrix with dimension (num. predictors, 2), where columns are FPR, TPR
"""
nsnps = len(pvals)
all_snps = np.arange(0, nsnps)
pos = SNPs
negs = list(set(all_snps) - set(SNPs))
pvals_rank = rank_array(pvals)
rocr = np.zeros((nsnps, 2))
for i in all_snps:
v = pvals_rank[0:i] # test positives
z = list(set(all_snps) - set(v)) # test negatives
TP = len(set(v) & set(pos))
FP = len(set(v) & set(negs))
TN = len(set(z) & set(negs))
FN = len(set(z) & set(pos))
TPR = 1.0*TP/(TP+FN); FPR = 1.0*FP/(FP+TN); #FDR = 1.0*FP/(FP+TP)
rocr[i, :] = [FPR, TPR]
return rocr | for repeat_idx in range(np.amax(variable_importances["repeat_idx"].unique()+1)):
df = variable_importances.loc[
(variable_importances["method"]==method) &
(variable_importances["repeat_idx"]==repeat_idx) &
(variable_importances["n"]==n) &
(variable_importances["p"]==p)
]
if len(df)==0:
continue
preds, labels = df["value"].values, df["causal"].values.astype(float)
fpr, tpr, _ = roc_curve(labels, np.abs(preds))
interp_tpr = np.interp(base_fpr, fpr, tpr)
auroc = auc(fpr, tpr)
roc_curve_df = pd.concat([
roc_curve_df,
pd.DataFrame({
"fpr" : base_fpr, "tpr" : interp_tpr, "auc" : auroc,
"method" : method, "n" : n, "p" : p
})
]) | conditional_block |
utils.py | import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import rankdata
import time
import logging
logger = logging.getLogger(__name__)
def plot_learning_curves(bnn, plotsize=4):
total_epochs = len(bnn.fit_history.history["loss"])
fig, axes = plt.subplots(
1, len(bnn.metrics_names),
figsize=(len(bnn.metrics_names)*plotsize, plotsize))
axes[0].plot(range(total_epochs), bnn.fit_history.history["loss"], '-o', label="training")
if 'val_loss' in bnn.fit_history.history:
axes[0].plot(range(total_epochs), bnn.fit_history.history["val_loss"], '-o', label="validation")
axes[0].legend()
axes[0].set_ylabel("ELBO")
axes[0].set_xlabel("epoch")
for i in range(len(bnn.metrics_names)-1):
this_metric = bnn.metrics_names[i+1]
axes[i+1].plot(range(total_epochs), bnn.fit_history.history[this_metric], '-o', label="training")
if "val_{}".format(this_metric) in bnn.fit_history.history:
axes[i+1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)
def onehot_encode_labels(y):
"""
One-hot encode integer labels y. The number of classes is assumed to be
the largest value in y
Args:
y: array with shape (n_examples,)
Returns:
array with shape (n_examples, n_classes)
"""
return OneHotEncoder(categories="auto", sparse=False).fit_transform(y.reshape(y.shape[0],1))
def get_roc_curves(variable_importances):
"""
Calculate ROC curves
# TODO: set row idx as variable
Args:
variable_importances: A dataframe with the following columns:
- method
- n
- p
- repeat_idx
- variable
"""
roc_curve_df = pd.DataFrame()
base_fpr = np.linspace(0, 1, 101) # Interpolate tpr (y-axis) at these fpr (x-axis) values
for method in variable_importances["method"].unique():
for n in variable_importances["n"].unique():
for p in variable_importances["p"].unique():
for repeat_idx in range(np.amax(variable_importances["repeat_idx"].unique()+1)):
df = variable_importances.loc[
(variable_importances["method"]==method) &
(variable_importances["repeat_idx"]==repeat_idx) &
(variable_importances["n"]==n) &
(variable_importances["p"]==p)
]
if len(df)==0:
continue
preds, labels = df["value"].values, df["causal"].values.astype(float)
fpr, tpr, _ = roc_curve(labels, np.abs(preds))
interp_tpr = np.interp(base_fpr, fpr, tpr)
auroc = auc(fpr, tpr)
roc_curve_df = pd.concat([
roc_curve_df,
pd.DataFrame({
"fpr" : base_fpr, "tpr" : interp_tpr, "auc" : auroc,
"method" : method, "n" : n, "p" : p
})
])
return roc_curve_df
def load_mnist(fashion, onehot_encode=True, flatten_x=False, crop_x=0, classes=None):
"""
Load the MNIST dataset
Args:
onehot_encode: Boolean indicating whether to one-hot encode training
and test labels (default True)
flatten_x: Boolean indicating whether to flatten the training and
test inputs to 2D arrays with shape (n_examples, image_size**2).
If False, returned inputs have shape (n_examples, image_size, image_size
(default False)
crop_x: Integer controlling the size of the border to be removed from the input
images (default 0, meaning no cropping).
classes: None to include all classes (default). Otherwise include a list of two
integers that will be encoded as 0, 1 in the order they appear.
Returns:
x_train, y_train, x_test, y_test: train and test inputs and labels.
First dimension is always the number of examples
"""
if not fashion:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
else:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
def crop(X, crop_size):
assert crop_x < X.shape[1]/2
assert crop_x < X.shape[2]/2
return X[:,crop_size:-crop_size,crop_size:-crop_size]
if crop_x > 0:
x_train = crop(x_train, crop_x)
x_test = crop(x_test, crop_x)
# Flatten to 2d arrays (each example 1d)
def flatten_image(X):
return X.reshape(X.shape[0], X.shape[1]*X.shape[1])
if flatten_x:
x_train = flatten_image(x_train)
x_test = flatten_image(x_test)
if onehot_encode:
y_train = onehot_encode_labels(y_train)
y_test = onehot_encode_labels(y_test)
if classes is not None:
assert len(classes) == 2
c0, c1 = classes
train_idxs_to_keep = np.logical_or(y_train==c0, y_train==c1)
x_train, y_train = x_train[train_idxs_to_keep,:], y_train[train_idxs_to_keep]
test_idxs_to_keep = np.logical_or(y_test==c0, y_test==c1)
x_test, y_test = x_test[test_idxs_to_keep,:], y_test[test_idxs_to_keep]
y_train = (y_train==c1).astype(int)[:,np.newaxis]
y_test = (y_test==c1).astype(int)[:,np.newaxis]
return x_train, y_train, x_test, y_test
def make_square(arr):
"""
Reshape a 1D array (or 2D array with .shape[2]==1) into a square 2D array
"""
assert arr.ndim==1 or arr.ndim==2, "array must be 1 or 2-D"
if arr.ndim==2:
assert arr.shape[1]==1, "If array is 2d then second dimension must be 1"
arr = arr.reshape(arr.shape[0])
assert arr.shape[0]**0.5 == int(arr.shape[0]**0.5), "array shape must be square (it is {})".format(arr.shape[0])
return arr.reshape(int(arr.shape[0]**0.5), int(arr.shape[0]**0.5))
def accuracy_onehot(labels, preds):
"""
Compute the accuracy of predictions using one-hot encoded labels
Args:
labels: array of labels with shape (n_examples, n_classes). Must be one-hot encoded
or result may be nonsense (this is not checked)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(np.argmax(preds, axis=1) == np.argmax(labels, axis=1))/float(labels.shape[0])
def accuracy(labels, preds):
"""
Compute the accuracy of predictions using integer labels
Args:
labels: array of labels with shape (n_examples,)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(preds==labels)/float(labels.shape[0])
def get_nullify_idxs(original_size, border_size):
"""
Get the indices of a flattened image that lie within border_size of the
edge of an image (use to pass to nullify argument in RATE function)
Args:
original size: Integer giving the size of the image
border_size: Integer giving the size of the border to be removed.
Returns:
Array of (integer) indices that lie in the border.
"""
assert border_size < original_size/2, "Border too large to be removed from image of this size"
tmp = np.zeros((original_size, original_size), dtype=int)
tmp[:border_size,:] = 1
tmp[-border_size:,:] = 1
tmp[:,-border_size:] = 1
tmp[:,:border_size] = 1
tmp = tmp.reshape(tmp.shape[0]*tmp.shape[1])
return np.where(tmp==1)[0]
def idx2pixel(idx, image_size):
"""
Get the 2D pixel location corresponding to the index of its flattened array
Args:
idx: integer index to be converted to pixel location
image_size: integer giving size of the image
Returns:
i, j: the location of the pixel corresponding to idx
"""
assert idx < image_size**2, "index {} too large for image size {}".format(idx, image_size)
tmp = np.zeros(image_size**2)
tmp[idx] = 1
tmp = tmp.reshape(image_size, image_size)
i, j = np.where(tmp==1)
return i[0], j[0]
def sampled_accuracies(pred_proba_samples, labels):
"""
Get the sampled accuracies over the entire test set from logit samples.
Args:
pred_proba_samples: array of predicted probability samples with shape
(n_mc_samples, n_examples, n_classes)/(n_mc_samples, n_examples)
for multiclass/binary classification. (This is the shape returned by BNN_Classifier.predict).
labels: array of one-hot encoded labels with shape (n_examples, n_classes) for non-binary clasification
or (n_examples,1) for binary classification.
Returns:
Array of test accuracies for each round of MC samples with shape (n_mc_samples,)
"""
binary_labels = labels.shape[1]==1
assert pred_proba_samples.shape[1]==labels.shape[0], "Different number of examples in logit samples and labels"
if not binary_labels:
assert pred_proba_samples.shape[2]==labels.shape[1], "Different number of classes in logit samples and labels"
sampled_test_accuracies = np.sum(
np.argmax(pred_proba_samples, axis=2) == np.argmax(labels, axis=1)[:,np.newaxis], axis=1)/float(labels.shape[0])
else:
sampled_test_accuracies = np.sum((pred_proba_samples[:,:]>0.5) == labels[:,0], axis=1)/float(labels.shape[0])
return sampled_test_accuracies
def accuracy_hist(pred_proba_samples, labels):
"""
Plot a histogram showing test accuracies.
Just calls sampled_accuracies then plots the result.
"""
sampled_acc = sampled_accuracies(pred_proba_samples, labels)
avg_accuracy = round(np.mean(sampled_acc) * 100, 3)
print("average accuracy across " + str(pred_proba_samples.shape[0]) + " samples: " + str(avg_accuracy) + "%\n")
fig, ax = plt.subplots(figsize=(10,5))
sns.distplot(100*sampled_acc, ax=ax, rug=True, kde=False)
ax.set_xlabel("Test set accuracy (%)", fontsize=30)
ax.set_ylabel("Frequency density", fontsize=30);
ax.tick_params("both", labelsize=15)
return sampled_acc
def rank_array(arr):
assert arr.ndim==1
return (arr.shape[0] - rankdata(arr)).astype(int)
def reverse_ranks(rankarr):
return rankarr.shape[0] - rankarr - 1
def | (pvals, SNPs):
"""
Compute the power for identifying causal predictors.
Args:
Ps: list of causal predictors
Output: matrix with dimension (num. predictors, 2), where columns are FPR, TPR
"""
nsnps = len(pvals)
all_snps = np.arange(0, nsnps)
pos = SNPs
negs = list(set(all_snps) - set(SNPs))
pvals_rank = rank_array(pvals)
rocr = np.zeros((nsnps, 2))
for i in all_snps:
v = pvals_rank[0:i] # test positives
z = list(set(all_snps) - set(v)) # test negatives
TP = len(set(v) & set(pos))
FP = len(set(v) & set(negs))
TN = len(set(z) & set(negs))
FN = len(set(z) & set(pos))
TPR = 1.0*TP/(TP+FN); FPR = 1.0*FP/(FP+TN); #FDR = 1.0*FP/(FP+TP)
rocr[i, :] = [FPR, TPR]
return rocr | compute_power | identifier_name |
utils.py | import numpy as np
import pandas as pd
import tensorflow as tf
from sklearn.preprocessing import OneHotEncoder
from sklearn.metrics import roc_curve, auc
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.stats import rankdata
import time
import logging
logger = logging.getLogger(__name__)
def plot_learning_curves(bnn, plotsize=4):
total_epochs = len(bnn.fit_history.history["loss"])
fig, axes = plt.subplots(
1, len(bnn.metrics_names),
figsize=(len(bnn.metrics_names)*plotsize, plotsize))
axes[0].plot(range(total_epochs), bnn.fit_history.history["loss"], '-o', label="training")
if 'val_loss' in bnn.fit_history.history:
axes[0].plot(range(total_epochs), bnn.fit_history.history["val_loss"], '-o', label="validation")
axes[0].legend()
axes[0].set_ylabel("ELBO")
axes[0].set_xlabel("epoch")
for i in range(len(bnn.metrics_names)-1):
this_metric = bnn.metrics_names[i+1]
axes[i+1].plot(range(total_epochs), bnn.fit_history.history[this_metric], '-o', label="training")
if "val_{}".format(this_metric) in bnn.fit_history.history:
axes[i+1].plot(range(total_epochs), bnn.fit_history.history["val_{}".format(this_metric)], '-o', label="validation")
axes[i+1].legend()
axes[i+1].set_ylabel(this_metric)
axes[i+1].set_xlabel("epoch")
plt.tight_layout()
return fig, axes
def make_1d2d(arr):
assert arr.ndim == 1
return arr.reshape(arr.shape[0], 1)
def onehot_encode_labels(y):
"""
One-hot encode integer labels y. The number of classes is assumed to be
the largest value in y
Args:
y: array with shape (n_examples,)
Returns:
array with shape (n_examples, n_classes)
"""
return OneHotEncoder(categories="auto", sparse=False).fit_transform(y.reshape(y.shape[0],1))
def get_roc_curves(variable_importances):
"""
Calculate ROC curves
# TODO: set row idx as variable
Args:
variable_importances: A dataframe with the following columns:
- method
- n
- p
- repeat_idx
- variable
"""
roc_curve_df = pd.DataFrame()
base_fpr = np.linspace(0, 1, 101) # Interpolate tpr (y-axis) at these fpr (x-axis) values
for method in variable_importances["method"].unique():
for n in variable_importances["n"].unique():
for p in variable_importances["p"].unique():
for repeat_idx in range(np.amax(variable_importances["repeat_idx"].unique()+1)):
df = variable_importances.loc[
(variable_importances["method"]==method) &
(variable_importances["repeat_idx"]==repeat_idx) &
(variable_importances["n"]==n) &
(variable_importances["p"]==p)
]
if len(df)==0:
continue
preds, labels = df["value"].values, df["causal"].values.astype(float)
fpr, tpr, _ = roc_curve(labels, np.abs(preds))
interp_tpr = np.interp(base_fpr, fpr, tpr)
auroc = auc(fpr, tpr)
roc_curve_df = pd.concat([
roc_curve_df,
pd.DataFrame({
"fpr" : base_fpr, "tpr" : interp_tpr, "auc" : auroc,
"method" : method, "n" : n, "p" : p
})
])
return roc_curve_df
def load_mnist(fashion, onehot_encode=True, flatten_x=False, crop_x=0, classes=None):
"""
Load the MNIST dataset
Args:
onehot_encode: Boolean indicating whether to one-hot encode training
and test labels (default True)
flatten_x: Boolean indicating whether to flatten the training and
test inputs to 2D arrays with shape (n_examples, image_size**2).
If False, returned inputs have shape (n_examples, image_size, image_size
(default False)
crop_x: Integer controlling the size of the border to be removed from the input
images (default 0, meaning no cropping).
classes: None to include all classes (default). Otherwise include a list of two
integers that will be encoded as 0, 1 in the order they appear.
Returns:
x_train, y_train, x_test, y_test: train and test inputs and labels.
First dimension is always the number of examples
"""
if not fashion:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
else:
(x_train, y_train),(x_test, y_test) = tf.keras.datasets.fashion_mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
def crop(X, crop_size):
|
if crop_x > 0:
x_train = crop(x_train, crop_x)
x_test = crop(x_test, crop_x)
# Flatten to 2d arrays (each example 1d)
def flatten_image(X):
return X.reshape(X.shape[0], X.shape[1]*X.shape[1])
if flatten_x:
x_train = flatten_image(x_train)
x_test = flatten_image(x_test)
if onehot_encode:
y_train = onehot_encode_labels(y_train)
y_test = onehot_encode_labels(y_test)
if classes is not None:
assert len(classes) == 2
c0, c1 = classes
train_idxs_to_keep = np.logical_or(y_train==c0, y_train==c1)
x_train, y_train = x_train[train_idxs_to_keep,:], y_train[train_idxs_to_keep]
test_idxs_to_keep = np.logical_or(y_test==c0, y_test==c1)
x_test, y_test = x_test[test_idxs_to_keep,:], y_test[test_idxs_to_keep]
y_train = (y_train==c1).astype(int)[:,np.newaxis]
y_test = (y_test==c1).astype(int)[:,np.newaxis]
return x_train, y_train, x_test, y_test
def make_square(arr):
"""
Reshape a 1D array (or 2D array with .shape[2]==1) into a square 2D array
"""
assert arr.ndim==1 or arr.ndim==2, "array must be 1 or 2-D"
if arr.ndim==2:
assert arr.shape[1]==1, "If array is 2d then second dimension must be 1"
arr = arr.reshape(arr.shape[0])
assert arr.shape[0]**0.5 == int(arr.shape[0]**0.5), "array shape must be square (it is {})".format(arr.shape[0])
return arr.reshape(int(arr.shape[0]**0.5), int(arr.shape[0]**0.5))
def accuracy_onehot(labels, preds):
"""
Compute the accuracy of predictions using one-hot encoded labels
Args:
labels: array of labels with shape (n_examples, n_classes). Must be one-hot encoded
or result may be nonsense (this is not checked)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(np.argmax(preds, axis=1) == np.argmax(labels, axis=1))/float(labels.shape[0])
def accuracy(labels, preds):
"""
Compute the accuracy of predictions using integer labels
Args:
labels: array of labels with shape (n_examples,)
preds: array of predictions with shape (n_examples, n_classes)
Returns:
Accuracy as float. Result is in [0,1]
"""
assert labels.shape[0]==preds.shape[0]
return np.sum(preds==labels)/float(labels.shape[0])
def get_nullify_idxs(original_size, border_size):
"""
Get the indices of a flattened image that lie within border_size of the
edge of an image (use to pass to nullify argument in RATE function)
Args:
original size: Integer giving the size of the image
border_size: Integer giving the size of the border to be removed.
Returns:
Array of (integer) indices that lie in the border.
"""
assert border_size < original_size/2, "Border too large to be removed from image of this size"
tmp = np.zeros((original_size, original_size), dtype=int)
tmp[:border_size,:] = 1
tmp[-border_size:,:] = 1
tmp[:,-border_size:] = 1
tmp[:,:border_size] = 1
tmp = tmp.reshape(tmp.shape[0]*tmp.shape[1])
return np.where(tmp==1)[0]
def idx2pixel(idx, image_size):
"""
Get the 2D pixel location corresponding to the index of its flattened array
Args:
idx: integer index to be converted to pixel location
image_size: integer giving size of the image
Returns:
i, j: the location of the pixel corresponding to idx
"""
assert idx < image_size**2, "index {} too large for image size {}".format(idx, image_size)
tmp = np.zeros(image_size**2)
tmp[idx] = 1
tmp = tmp.reshape(image_size, image_size)
i, j = np.where(tmp==1)
return i[0], j[0]
def sampled_accuracies(pred_proba_samples, labels):
"""
Get the sampled accuracies over the entire test set from logit samples.
Args:
pred_proba_samples: array of predicted probability samples with shape
(n_mc_samples, n_examples, n_classes)/(n_mc_samples, n_examples)
for multiclass/binary classification. (This is the shape returned by BNN_Classifier.predict).
labels: array of one-hot encoded labels with shape (n_examples, n_classes) for non-binary clasification
or (n_examples,1) for binary classification.
Returns:
Array of test accuracies for each round of MC samples with shape (n_mc_samples,)
"""
binary_labels = labels.shape[1]==1
assert pred_proba_samples.shape[1]==labels.shape[0], "Different number of examples in logit samples and labels"
if not binary_labels:
assert pred_proba_samples.shape[2]==labels.shape[1], "Different number of classes in logit samples and labels"
sampled_test_accuracies = np.sum(
np.argmax(pred_proba_samples, axis=2) == np.argmax(labels, axis=1)[:,np.newaxis], axis=1)/float(labels.shape[0])
else:
sampled_test_accuracies = np.sum((pred_proba_samples[:,:]>0.5) == labels[:,0], axis=1)/float(labels.shape[0])
return sampled_test_accuracies
def accuracy_hist(pred_proba_samples, labels):
"""
Plot a histogram showing test accuracies.
Just calls sampled_accuracies then plots the result.
"""
sampled_acc = sampled_accuracies(pred_proba_samples, labels)
avg_accuracy = round(np.mean(sampled_acc) * 100, 3)
print("average accuracy across " + str(pred_proba_samples.shape[0]) + " samples: " + str(avg_accuracy) + "%\n")
fig, ax = plt.subplots(figsize=(10,5))
sns.distplot(100*sampled_acc, ax=ax, rug=True, kde=False)
ax.set_xlabel("Test set accuracy (%)", fontsize=30)
ax.set_ylabel("Frequency density", fontsize=30);
ax.tick_params("both", labelsize=15)
return sampled_acc
def rank_array(arr):
assert arr.ndim==1
return (arr.shape[0] - rankdata(arr)).astype(int)
def reverse_ranks(rankarr):
return rankarr.shape[0] - rankarr - 1
def compute_power(pvals, SNPs):
"""
Compute the power for identifying causal predictors.
Args:
Ps: list of causal predictors
Output: matrix with dimension (num. predictors, 2), where columns are FPR, TPR
"""
nsnps = len(pvals)
all_snps = np.arange(0, nsnps)
pos = SNPs
negs = list(set(all_snps) - set(SNPs))
pvals_rank = rank_array(pvals)
rocr = np.zeros((nsnps, 2))
for i in all_snps:
v = pvals_rank[0:i] # test positives
z = list(set(all_snps) - set(v)) # test negatives
TP = len(set(v) & set(pos))
FP = len(set(v) & set(negs))
TN = len(set(z) & set(negs))
FN = len(set(z) & set(pos))
TPR = 1.0*TP/(TP+FN); FPR = 1.0*FP/(FP+TN); #FDR = 1.0*FP/(FP+TP)
rocr[i, :] = [FPR, TPR]
return rocr | assert crop_x < X.shape[1]/2
assert crop_x < X.shape[2]/2
return X[:,crop_size:-crop_size,crop_size:-crop_size] | identifier_body |
analysis.py | import itertools
import pandas as pd
import pingouin as pg
import numpy as np
from scipy.stats import wilcoxon
from sklearn.decomposition import PCA
from sklearn.covariance import EllipticEnvelope
def preprocess_data(users, blocks, trials):
""" Clean data.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:returns: Joined and recoded DataFrame. Number of erroneous blocks. Number of sessions removed as a consequence.
Number of removed trials.
:rtype: tuple[pandas.DataFrame, int, int, int]
"""
blocks, n_errors, invalid_sessions = remove_erroneous_blocks(blocks)
# Merge to 1 table.
df = join_data(users, blocks, trials)
# Remove invalid trials.
cleaned, n_trials_removed = get_valid_trials(df)
return cleaned, n_errors, len(invalid_sessions), n_trials_removed
def remove_erroneous_blocks(blocks):
""" Remove sessions with erroneous data due to a NeuroPsy Research App malfunction.
The error causes block data to be duplicated and the values for df1 & df2 multiplied again by 100.
The duplicated blocks are identified by comparing their time stamps to the previous block (less than 2 seconds
difference). If the error caused the session to end early, the whole session is removed.
NeuroPsyResearchApp issue #1.
:param pandas.DataFrame blocks: Data about blocks.
:returns: Cleaned block data. Number of errors found. List of sessions that were removed as a consequence.
:rtype: tuple[pandas.DataFrame, int, list]
"""
# Identify duplicated blocks. Consecutive time stamps are usually less than 2 seconds apart.
mask = blocks.groupby(['session_uid'])['time'].diff() < 2.0
try:
n_errors = mask.value_counts()[True]
except KeyError:
n_errors = 0
blocks = blocks.loc[~mask, :]
# Now, after removal of erroneous data a session might not have all 3 blocks we expect. Exclude whole session.
invalid_sessions = blocks['session_uid'].value_counts() != 3
invalid_sessions = invalid_sessions.loc[invalid_sessions].index.to_list()
blocks = blocks.loc[~blocks['session_uid'].isin(invalid_sessions), :]
return blocks, n_errors, invalid_sessions
def join_data(users, blocks, trials):
""" Take data from different database tables and join them to a single DataFrame. Some variables are renamed and
recoded in the process, some are dropped.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:return: Joined and recoded DataFrame.
:rtype: pandas.DataFrame
"""
# Use users' index instead of id for obfuscation and shorter display.
users_inv_map = pd.Series(users.index, index=users.id)
# Remove trials that don't belong to any block. Those have been excluded.
trials = trials.loc[trials['block_id'].isin(blocks.index), :]
# Start a new table for trials and augment with data from other tables.
df = pd.DataFrame(index=trials.index)
df['user'] = trials.user_id.map(users_inv_map).astype('category')
df['session'] = trials['block_id'].map(blocks['nth_session']).astype('category')
# Map whole sessions to the constraint in the treatment block as a condition for easier grouping during analysis.
df['condition'] = trials['block_id'].map(blocks[['session_uid', 'treatment']].replace(
{'treatment': {'': np.nan}}).groupby('session_uid')['treatment'].ffill().bfill()).astype('category')
df['block'] = trials['block_id'].map(blocks['nth_block']).astype('category')
# Add pre and post labels to trials for each block. Name it task instead of treatment.
# Theoretically, one could have changed number of blocks and order of treatment, but we assume default order here.
df['task'] = trials['block_id'].map(blocks['treatment'].where(blocks['treatment'] != '',
blocks.nth_block.map({1: 'pre', 3: 'post'}))
).astype('category')
#df['task'] = trials['block_id'].map(blocks['treatment'].replace(to_replace={r'\w+': 1, r'^\s*$': 0}, regex=True)
# ).astype('category')
df = pd.concat((df, trials), axis='columns')
# Add columns for easier filtering.
df['grab_diff'] = (df['df2_grab'] - df['df1_grab']).abs()
df['duration_diff'] = (df['df2_duration'] - df['df1_duration']).abs()
# Exclude columns.
df.drop(columns=['user_id', 'block_id'], inplace=True)
return df
def get_valid_trials(dataframe):
""" Remove trials where sliders where not grabbed concurrently or grabbed at all.
:param dataframe: Trial data.
:type dataframe: pandas.DataFrame
:returns: Filtered trials. Number of removed trials.
:rtype: tuple[pandas.DataFrame, int]
"""
# Remove trials with missing values. This means at least one slider wasn't grabbed.
df = dataframe.dropna(axis='index', how='any')
# Remove trials where sliders where not grabbed concurrently.
mask = ~((df['df1_release'] <= df['df2_grab']) | (df['df2_release'] <= df['df1_grab']))
df = df.loc[mask, :]
n_removed = len(dataframe) - len(df)
return df, n_removed
def get_outlyingness(data, contamination=0.1):
""" Outlier detection from covariance estimation in a Gaussian distributed dataset.
:param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Decision on each row if it's an outlier. And contour array for drawing ellipse in graph.
:rtype: tuple[numpy.ndarray, numpy.ndarray]
"""
robust_cov = EllipticEnvelope(support_fraction=1., contamination=contamination)
outlyingness = robust_cov.fit_predict(data)
decision = (outlyingness-1).astype(bool)
# Visualisation.
xx, yy = np.meshgrid(np.linspace(0, 100, 101),
np.linspace(0, 100, 101))
z = robust_cov.predict(np.c_[xx.ravel(), yy.ravel()])
z = z.reshape(xx.shape)
return decision, z
#ToDo: remove blocks/sessions with sum mean way off.
#ToDo: remove sessions with less than 10 trials in any block.
def get_pca_data(dataframe):
""" Conduct Principal Component Analysis on 2D dataset.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:return: Explained variance, components and means.
:rtype: pandas.DataFrame
"""
# We don't reduce dimensionality, but overlay the 2 principal components in 2D.
pca = PCA(n_components=2)
x = dataframe[['df1', 'df2']].values
try:
# df1 and df2 have the same scale. No need to standardize. Standardizing might actually distort PCA here.
pca.fit(x)
except ValueError:
# Return empty.
df = pd.DataFrame(columns=['var_expl', 'var_expl_ratio', 'x', 'y', 'meanx', 'meany'])
else:
df = pd.DataFrame({'var_expl': pca.explained_variance_.T,
'var_expl_ratio': pca.explained_variance_ratio_.T * 100, # In percent
'x': pca.components_[:, 0],
'y': pca.components_[:, 1],
'meanx': pca.mean_[0],
'meany': pca.mean_[1],
},
index=[1, 2] # For designating principal components.
)
df.index.rename('PC', inplace=True)
return df
def get_pca_vectors(dataframe):
""" Get principal components as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Tabular PCA data.
:type dataframe: pandas.DataFrame
:return: Principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vectors = list()
# Use the "components" to define the direction of the vectors,
# and the "explained variance" to define the squared-length of the vectors.
for idx, row in dataframe.iterrows():
|
return vectors
def get_pca_vectors_by(dataframe, by=None):
""" Get principal components for each group as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:param by: Column to group data by and return 2 vectors for each group.
:type by: str|list
:return: list of principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vector_pairs = list()
if by is None:
pca_df = get_pca_data(dataframe)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
else:
grouped = dataframe.groupby(by)
for group, data in grouped:
pca_df = get_pca_data(data)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
# ToDo: Augment by groupby criteria.
return vector_pairs
def get_interior_angle(vec0, vec1):
""" Get the smaller angle between vec0 and vec1 in degrees.
:param vec0: Vector 0
:type vec0: numpy.ndarray
:param vec1: Vector 1
:type vec1: numpy.ndarray
:return: Interior angle between vector0 and vector1 in degrees.
:rtype: float
"""
angle = np.math.atan2(np.linalg.det([vec0, vec1]), np.dot(vec0, vec1))
degrees = abs(np.degrees(angle))
# Min and max should be between 0° an 90°.
degrees = min(degrees, 180.0 - degrees)
return degrees
def get_ucm_vec(p0=None, p1=None):
""" Returns 2D unit vector in direction of uncontrolled manifold. """
if p0 is None:
p0 = np.array([25, 100])
if p1 is None:
p1 = np.array([100, 25])
parallel = p1 - p0
parallel = parallel / np.linalg.norm(parallel) # Normalize.
return parallel
def get_orthogonal_vec2d(vec):
""" Get a vector that is orthogonal to vec and has same length.
:param vec: 2D Vector
:return: 2D Vector orthogonal to vec.
:rtype: numpy.ndarray
"""
ortho = np.array([-vec[1], vec[0]])
return ortho
def get_pc_ucm_angles(dataframe, vec_ucm):
""" Computes the interior angles between pca vectors and ucm parallel/orthogonal vectors.
:param dataframe: PCA data .
:type dataframe: pandas.DataFrame
:param vec_ucm: Vector parallel to UCM.
:type vec_ucm: numpy.ndarray
:return: Each angle between principal components and UCM parallel and orthogonal vector.
:rtype: pandas.DataFrame
"""
vec_ucm_ortho = get_orthogonal_vec2d(vec_ucm)
df_angles = pd.DataFrame(columns=['parallel', 'orthogonal'])
for idx, row in dataframe.iterrows():
angle_parallel = get_interior_angle(vec_ucm, row[['x', 'y']])
angle_ortho = get_interior_angle(vec_ucm_ortho, row[['x', 'y']])
df_angles.loc[idx] = [angle_parallel, angle_ortho]
df_angles[['parallel', 'orthogonal']] = df_angles[['parallel', 'orthogonal']].astype(float)
df_angles.insert(0, 'PC', dataframe['PC'])
return df_angles
def get_projections(points, vec_ucm):
""" Returns coefficients a and b in x = a*vec_ucm + b*vec_ortho with x being the difference of a data point and
the mean.
Projection is computed using a transformation matrix with ucm parallel and orthogonal vectors as basis.
:param points: Data of 2D points.
:type points: pandas.Dataframe
:param vec_ucm: Unit vector parallel to uncontrolled manifold.
:type vec_ucm: numpy.ndarray
:return: Array with projected lengths onto vector parallel to UCM as 'a', onto vector orthogonal to UCM as 'b'.
:rtype: pandas.Dataframe
"""
# Get the vector orthogonal to the UCM.
vec_ortho = get_orthogonal_vec2d(vec_ucm)
# Build a transformation matrix with vec_ucm and vec_ortho as new basis vectors.
A = np.vstack((vec_ucm, vec_ortho)).T # A is not an orthogonal projection matrix (A=A.T), but this works.
# Centralize the data. Analogous to calculating across trials deviation from average for each time step.
diffs = points - points.mean()
# For computational efficiency we shortcut the projection calculation with matrix multiplication.
# The actual math behind it:
# coeffs = vec_ucm.T@diff/np.sqrt(vec_ucm.T@vec_ucm), vec_ortho.T@diff/np.sqrt(vec_ortho.T@vec_ortho)
# Biased variance (normalized by (n-1)) of projection onto UCM vector:
# var_ucm = vec_ucm.T@np.cov(diffs, bias=True, rowvar=False)@vec_ucm/(vec_ucm.T@vec_ucm) # Rayleigh fraction.
coeffs = diffs@A
coeffs.columns = ['parallel', 'orthogonal']
return coeffs
def get_synergy_indices(variances, n=2, d=1):
"""
n: Number of degrees of freedom. In our case 2.
d: Dimensionality of performance variable. In our case a scalar (1).
Vucm = 1/N * 1/(n - d) * sum(ProjUCM**2)
Vort = 1/N * 1/(d) * sum(ProjORT**2)
Vtotal = 1/n * (d * Vort + (n-d) * Vucm) # Anull the weights on Vucm and Vort for the sum.
dV = (Vucm - Vort) / Vtotal
dV = n*(Vucm - Vort) / ((n - d)*Vucm + d*Vort)
Zhang (2008) without weighting Vucm, Vort and Vtotal first:
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
dVz = 0.5*ln((n / d + dV) / (n / ((n - d) - dV))
dVz = 0.5*ln((2 + dV) / (2 - dV))
Reference: https://www.frontiersin.org/articles/10.3389/fnagi.2019.00032/full#supplementary-material
:param variances: Unweighted variances of parallel and orthogonal projections to the UCM.
:type variances: pandas.DataFrame
:param n: Number of degrees of freedom. Defaults to 2.
:type: int
:param d: Dimensionality of performance variable. Defaults to 1.
:type d: int
:returns: Synergy index, Fisher's z-transformed synergy index.
:rtype: pandas.DataFrame
"""
try:
dV = n * (variances['parallel']/(n-d) - variances['orthogonal']/d) \
/ variances[['parallel', 'orthogonal']].sum(axis='columns')
except KeyError:
synergy_indices = pd.DataFrame(columns=["dV", "dVz"])
else:
dVz = 0.5 * np.log((n/d + dV)/(n/(n-d) - dV))
synergy_indices = pd.DataFrame({"dV": dV, "dVz": dVz})
return synergy_indices
def get_synergy_idx_bounds(n=2, d=1):
""" Get lower and upper bounds of the synergy index.
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
If all variance lies within the UCM, then Vort=0 and it follows for the upper bound: dV = n/(n-d)
If all variance lies within Vort, then Vucm=0 and it follows for the lower bound: dV = -n/d
:param n: Number of degrees of freedom.
:type: int
:param d: Dimensionality of performance variable.
:type d: int
:returns: Lower and upper bounds of synergy index.
:rtype: tuple
"""
dV_lower = -n/d
dV_upper = n/(n-d)
return dV_lower, dV_upper
def get_mean(dataframe, column, by=None):
""" Return mean values of column x (optionally grouped)
:param dataframe: Data
:type dataframe: pandas.Dataframe
:param column: Column name
:type column: str
:param by: Column names by which to group.
:type by: str|list
:return: mean value, optionally for each group.
:rtype: numpy.float64|pandas.Series
"""
if by is None:
means = dataframe[column].mean()
else:
means = dataframe.groupby(by)[column].mean()
return means
def get_descriptive_stats(data, by=None):
""" Return mean and variance statistics for data.
:param data: numerical data.
:type data: pandas.Dataframe
:param by: groupby column name(s)
:type by: str|List
:return: Dataframe with columns mean, var, count and column names of data as rows.
:rtype: pandas.Dataframe
"""
# There's a bug in pandas 1.0.4 where you can't use custom numpy functions in agg anymore (ValueError).
# Note that the variance of projections is usually divided by (n-d) for Vucm and d for Vort. Both are 1 in our case.
# Pandas default var returns unbiased population variance /(n-1). Doesn't make a difference for synergy indices.
f_var = lambda series: series.var(ddof=0)
f_var.__name__ = 'variance' # Column name gets function name.
f_avg = lambda series: series.abs().mean()
f_avg.__name__ = 'absolute average'
# When there're no data, return empty DataFrame with columns.
if data.empty:
if by:
data.set_index(by, drop=True, inplace=True)
col_idx = pd.MultiIndex.from_product([data.columns, [f_avg.__name__, 'mean', f_var.__name__]])
stats = pd.DataFrame(None, index=data.index, columns=col_idx)
stats['count'] = None
return stats
if not by:
stats = data.agg([f_avg, 'mean', f_var, 'count']).T
stats['count'] = stats['count'].astype(int)
else:
grouped = data.groupby(by)
stats = grouped.agg([f_avg, 'mean', f_var])
stats['count'] = grouped.size()
stats.dropna(inplace=True)
return stats
def get_statistics(df_trials, df_proj):
""" Calculate descriptive statistics for key values of the anaylsis.
:param df_trials: Data from joined table on trials.
:type df_trials: pandas.DataFrame
:param df_proj: Projections onto UCM and its orthogonal space.
:type df_proj: pandas.DataFrame
:return: Descriptive statistics and synergy indices.
:rtype: pandas.DataFrame
"""
groupers = ['user', 'session', 'condition', 'block', 'task']
try:
# Get only those trials we have the projections for, in the same order.
df_trials = df_trials.iloc[df_proj.index]
df_trials[groupers] = df_trials[groupers].astype('category')
except (KeyError, ValueError):
df_proj_stats = get_descriptive_stats(pd.DataFrame(columns=df_proj.columns))
df_dof_stats = get_descriptive_stats(pd.DataFrame(columns=df_trials.columns))
cov = pd.DataFrame(columns=[('df1,df2 covariance', '')])
else:
df_proj[groupers] = df_trials[groupers]
# Get statistic characteristics of absolute lengths.
df_proj_stats = get_descriptive_stats(df_proj, by=groupers)
# Clean-up to match data on degrees of freedom.
df_proj_stats.dropna(inplace=True)
df_dof_stats = get_descriptive_stats(df_trials[groupers + ['df1', 'df2', 'sum']], by=groupers)
# For degrees of freedom absolute average is the same as the mean, since there are no negative values.
df_dof_stats.drop('absolute average', axis='columns', level=1, inplace=True)
# Get covariance between degrees of freedom.
cov = df_trials.groupby(groupers).apply(lambda x: np.cov(x[['df1', 'df2']].T, ddof=0)[0, 1])
try:
cov = cov.to_frame(('df1,df2 covariance', '')) # MultiIndex.
except AttributeError: # In case cov is an empty Dataframe.
cov = pd.DataFrame(columns=pd.MultiIndex.from_tuples([('df1,df2 covariance', '')]))
# We now have 1 count column too many, since the projection statistics already has the identical column.
df_dof_stats.drop('count', axis='columns', level=0, inplace=True)
# For projections the mean is 0, since projections are from deviations from the mean. So we don't need to show it.
df_proj_stats.drop('mean', axis='columns', level=1, inplace=True)
# Get synergy indices based on projection variances we just calculated.
df_synergies = get_synergy_indices(df_proj_stats.xs('variance', level=1, axis='columns'))
# Before we merge dataframes, give this one a Multiindex, too.
df_synergies.columns = pd.MultiIndex.from_product([df_synergies.columns, ['']])
# Join the 3 statistics to be displayed in a single table.
df = pd.concat((df_dof_stats, cov, df_proj_stats, df_synergies), axis='columns')
return df
def wilcoxon_rank_test(data):
w, p = wilcoxon(data['parallel'], data['orthogonal'], alternative='greater')
return p < 0.05, w, p
def wide_to_long(df, stubs, suffixes, j):
""" Transforms a dataframe to long format, where the stubs are melted into a single column with name j and suffixes
into value columns. Filters for all columns that are a stubs+suffixes combination.
Keeps 'user', 'task' as id_vars. When an error is encountered an emtpy dataframe is returned.
:param df: Data in wide/mixed format.
:type df: pandas.DataFrame
:param stubs: First part of a column name. These names will be the values of the new column j.
:type stubs: list[str]
:param suffixes: Second part of a column name. These will be the new columns holding the respective values.
:type suffixes: str|list[str]
:param j: Name for new column containing stubs.
:type j: str
:return: Filtered Dataframe in long format.
:rtype: pandas.Dataframe
"""
if isinstance(suffixes, str):
suffixes = [suffixes]
# We want all stubs+suffix combinations as columns.
val_cols = [" ".join(x) for x in itertools.product(stubs, suffixes)]
try:
# Filter for data we want to plot.
df = df[['user', 'condition', 'block', 'task', *val_cols]]
# Reverse stub and suffix for long format. We want the measurements as columns, not the categories.
df.columns = [" ".join(x.split(" ")[::-1]) for x in df.columns]
long_df = pd.wide_to_long(df=df, stubnames=suffixes, i=['user', 'condition', 'block', 'task'],
j=j, sep=" ", suffix=f'(!?{"|".join(stubs)})')
long_df.reset_index(inplace=True)
except (KeyError, ValueError):
long_df = pd.DataFrame(columns=['user', 'condition', 'block', 'task', j, *suffixes])
long_df[['user', 'condition', 'block', 'task']] = long_df[['user', 'condition', 'block', 'task']].astype('category')
return long_df
def normality_test(df, columns, multivariate=False):
""" Tests whether there is considerable deviation from a normal distribution.
If no deviation could be detected, we don't know much about the distribution.
Independent normality tests use the Shapiro-Wilk method. Multivariate tests use the Henze-Zirkler multivariate
normality test.
:param df: Aggregated data containing Fisher-z-transformed synergy index.
:type df: pandas.DataFrame
:param columns: Which columns to test for normality deviation.
:type columns: list[str]
:param multivariate: Do multivariate normality testing?
:type multivariate: bool
:return: Normality test results.
:rtype: pandas.DataFrame
"""
if multivariate:
# Multivariate testing.
is_normal, p = df.groupby(['user', 'block'])[columns].apply(pg.multivariate_normality)
res = df.groupby(['user', 'block'])[['df1', 'df2']].apply(pg.multivariate_normality).apply(pd.Series)\
.rename(columns={0: 'normal', 1: 'p'})
else:
# We would want to minimize type II error rate, risk of not rejecting the null when it's false.
res = df.groupby(['user', 'block'])[columns].apply(pg.normality).unstack(level=2) # Shapiro-Wilk tests.
return res
def mixed_anova_synergy_index_z(dataframe):
""" 3 x (3) Two-way split-plot ANOVA with between-factor condition and within-factor block.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index.
:type dataframe: pandas.DataFrame
:return: mixed-design ANOVA results.
:rtype: pandas.DataFrame
"""
if dataframe['condition'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 condition, run ANOVA with one within factor instead.
if dataframe['block'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 block, run ANOVA with one between factor instead.
aov = pg.mixed_anova(data=dataframe, dv='dVz', within='block', subject='user', between='condition', correction=True)
return aov
def posthoc_ttests(dataframe, var_='dVz'):
""" Pairwise posthoc t-tests on a variable in a mixed design. Between factor is 'condition', within factor is
'block'.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index in long format.
:type dataframe: pandas.DataFrame
:param var_: The variable which to test. One of the column names in dataframe.
:type var_: str
:return: Pairwise T-tests results.
:rtype: pandas.DataFrame
"""
posthocs = pg.pairwise_ttests(data=dataframe, dv=var_, within='block', subject='user', between='condition',
alpha=0.05, within_first=False,
padjust='fdr_by', marginal=True, return_desc=True, tail='one-sided', parametric=True)
return posthocs
| v = row[['x', 'y']].values * np.sqrt(row['var_expl']) * 3 # Scale up for better visibility.
mean = row[['meanx', 'meany']].values
mean_offset = (mean, mean + v)
vectors.append(mean_offset) | conditional_block |
analysis.py | import itertools
import pandas as pd
import pingouin as pg
import numpy as np
from scipy.stats import wilcoxon
from sklearn.decomposition import PCA
from sklearn.covariance import EllipticEnvelope
def preprocess_data(users, blocks, trials):
""" Clean data.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:returns: Joined and recoded DataFrame. Number of erroneous blocks. Number of sessions removed as a consequence.
Number of removed trials.
:rtype: tuple[pandas.DataFrame, int, int, int]
"""
blocks, n_errors, invalid_sessions = remove_erroneous_blocks(blocks)
# Merge to 1 table.
df = join_data(users, blocks, trials)
# Remove invalid trials.
cleaned, n_trials_removed = get_valid_trials(df)
return cleaned, n_errors, len(invalid_sessions), n_trials_removed
def remove_erroneous_blocks(blocks):
""" Remove sessions with erroneous data due to a NeuroPsy Research App malfunction.
The error causes block data to be duplicated and the values for df1 & df2 multiplied again by 100.
The duplicated blocks are identified by comparing their time stamps to the previous block (less than 2 seconds
difference). If the error caused the session to end early, the whole session is removed.
NeuroPsyResearchApp issue #1.
:param pandas.DataFrame blocks: Data about blocks.
:returns: Cleaned block data. Number of errors found. List of sessions that were removed as a consequence.
:rtype: tuple[pandas.DataFrame, int, list]
"""
# Identify duplicated blocks. Consecutive time stamps are usually less than 2 seconds apart.
mask = blocks.groupby(['session_uid'])['time'].diff() < 2.0
try:
n_errors = mask.value_counts()[True]
except KeyError:
n_errors = 0
blocks = blocks.loc[~mask, :]
# Now, after removal of erroneous data a session might not have all 3 blocks we expect. Exclude whole session.
invalid_sessions = blocks['session_uid'].value_counts() != 3
invalid_sessions = invalid_sessions.loc[invalid_sessions].index.to_list()
blocks = blocks.loc[~blocks['session_uid'].isin(invalid_sessions), :]
return blocks, n_errors, invalid_sessions
def join_data(users, blocks, trials):
""" Take data from different database tables and join them to a single DataFrame. Some variables are renamed and
recoded in the process, some are dropped.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:return: Joined and recoded DataFrame.
:rtype: pandas.DataFrame
"""
# Use users' index instead of id for obfuscation and shorter display.
users_inv_map = pd.Series(users.index, index=users.id)
# Remove trials that don't belong to any block. Those have been excluded.
trials = trials.loc[trials['block_id'].isin(blocks.index), :]
# Start a new table for trials and augment with data from other tables.
df = pd.DataFrame(index=trials.index)
df['user'] = trials.user_id.map(users_inv_map).astype('category')
df['session'] = trials['block_id'].map(blocks['nth_session']).astype('category')
# Map whole sessions to the constraint in the treatment block as a condition for easier grouping during analysis.
df['condition'] = trials['block_id'].map(blocks[['session_uid', 'treatment']].replace(
{'treatment': {'': np.nan}}).groupby('session_uid')['treatment'].ffill().bfill()).astype('category')
df['block'] = trials['block_id'].map(blocks['nth_block']).astype('category')
# Add pre and post labels to trials for each block. Name it task instead of treatment.
# Theoretically, one could have changed number of blocks and order of treatment, but we assume default order here.
df['task'] = trials['block_id'].map(blocks['treatment'].where(blocks['treatment'] != '',
blocks.nth_block.map({1: 'pre', 3: 'post'}))
).astype('category')
#df['task'] = trials['block_id'].map(blocks['treatment'].replace(to_replace={r'\w+': 1, r'^\s*$': 0}, regex=True)
# ).astype('category')
df = pd.concat((df, trials), axis='columns')
# Add columns for easier filtering.
df['grab_diff'] = (df['df2_grab'] - df['df1_grab']).abs()
df['duration_diff'] = (df['df2_duration'] - df['df1_duration']).abs()
# Exclude columns.
df.drop(columns=['user_id', 'block_id'], inplace=True)
return df
def get_valid_trials(dataframe):
""" Remove trials where sliders where not grabbed concurrently or grabbed at all.
:param dataframe: Trial data.
:type dataframe: pandas.DataFrame
:returns: Filtered trials. Number of removed trials.
:rtype: tuple[pandas.DataFrame, int]
"""
# Remove trials with missing values. This means at least one slider wasn't grabbed.
df = dataframe.dropna(axis='index', how='any')
# Remove trials where sliders where not grabbed concurrently.
mask = ~((df['df1_release'] <= df['df2_grab']) | (df['df2_release'] <= df['df1_grab']))
df = df.loc[mask, :]
n_removed = len(dataframe) - len(df)
return df, n_removed
def get_outlyingness(data, contamination=0.1):
""" Outlier detection from covariance estimation in a Gaussian distributed dataset.
:param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Decision on each row if it's an outlier. And contour array for drawing ellipse in graph.
:rtype: tuple[numpy.ndarray, numpy.ndarray]
"""
robust_cov = EllipticEnvelope(support_fraction=1., contamination=contamination)
outlyingness = robust_cov.fit_predict(data)
decision = (outlyingness-1).astype(bool)
# Visualisation.
xx, yy = np.meshgrid(np.linspace(0, 100, 101),
np.linspace(0, 100, 101))
z = robust_cov.predict(np.c_[xx.ravel(), yy.ravel()])
z = z.reshape(xx.shape)
return decision, z
#ToDo: remove blocks/sessions with sum mean way off.
#ToDo: remove sessions with less than 10 trials in any block.
def get_pca_data(dataframe):
""" Conduct Principal Component Analysis on 2D dataset.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:return: Explained variance, components and means.
:rtype: pandas.DataFrame
"""
# We don't reduce dimensionality, but overlay the 2 principal components in 2D.
pca = PCA(n_components=2)
x = dataframe[['df1', 'df2']].values
try:
# df1 and df2 have the same scale. No need to standardize. Standardizing might actually distort PCA here.
pca.fit(x)
except ValueError:
# Return empty.
df = pd.DataFrame(columns=['var_expl', 'var_expl_ratio', 'x', 'y', 'meanx', 'meany'])
else:
df = pd.DataFrame({'var_expl': pca.explained_variance_.T,
'var_expl_ratio': pca.explained_variance_ratio_.T * 100, # In percent
'x': pca.components_[:, 0],
'y': pca.components_[:, 1],
'meanx': pca.mean_[0],
'meany': pca.mean_[1],
},
index=[1, 2] # For designating principal components.
)
df.index.rename('PC', inplace=True)
return df
def get_pca_vectors(dataframe):
""" Get principal components as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Tabular PCA data.
:type dataframe: pandas.DataFrame
:return: Principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vectors = list()
# Use the "components" to define the direction of the vectors,
# and the "explained variance" to define the squared-length of the vectors.
for idx, row in dataframe.iterrows():
v = row[['x', 'y']].values * np.sqrt(row['var_expl']) * 3 # Scale up for better visibility.
mean = row[['meanx', 'meany']].values
mean_offset = (mean, mean + v)
vectors.append(mean_offset)
return vectors
def get_pca_vectors_by(dataframe, by=None):
""" Get principal components for each group as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:param by: Column to group data by and return 2 vectors for each group.
:type by: str|list
:return: list of principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vector_pairs = list()
if by is None:
pca_df = get_pca_data(dataframe)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
else:
grouped = dataframe.groupby(by)
for group, data in grouped:
pca_df = get_pca_data(data)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
# ToDo: Augment by groupby criteria.
return vector_pairs
def get_interior_angle(vec0, vec1):
""" Get the smaller angle between vec0 and vec1 in degrees.
:param vec0: Vector 0
:type vec0: numpy.ndarray
:param vec1: Vector 1
:type vec1: numpy.ndarray
:return: Interior angle between vector0 and vector1 in degrees.
:rtype: float
"""
angle = np.math.atan2(np.linalg.det([vec0, vec1]), np.dot(vec0, vec1))
degrees = abs(np.degrees(angle))
# Min and max should be between 0° an 90°.
degrees = min(degrees, 180.0 - degrees)
return degrees
def get_ucm_vec(p0=None, p1=None):
""" Returns 2D unit vector in direction of uncontrolled manifold. """
if p0 is None:
p0 = np.array([25, 100])
if p1 is None:
p1 = np.array([100, 25])
parallel = p1 - p0
parallel = parallel / np.linalg.norm(parallel) # Normalize.
return parallel
def get_orthogonal_vec2d(vec):
""" Get a vector that is orthogonal to vec and has same length.
:param vec: 2D Vector
:return: 2D Vector orthogonal to vec.
:rtype: numpy.ndarray
"""
ortho = np.array([-vec[1], vec[0]])
return ortho
def get_pc_ucm_angles(dataframe, vec_ucm):
""" Computes the interior angles between pca vectors and ucm parallel/orthogonal vectors.
:param dataframe: PCA data .
:type dataframe: pandas.DataFrame
:param vec_ucm: Vector parallel to UCM.
:type vec_ucm: numpy.ndarray
:return: Each angle between principal components and UCM parallel and orthogonal vector.
:rtype: pandas.DataFrame
"""
vec_ucm_ortho = get_orthogonal_vec2d(vec_ucm)
df_angles = pd.DataFrame(columns=['parallel', 'orthogonal'])
for idx, row in dataframe.iterrows():
angle_parallel = get_interior_angle(vec_ucm, row[['x', 'y']])
angle_ortho = get_interior_angle(vec_ucm_ortho, row[['x', 'y']])
df_angles.loc[idx] = [angle_parallel, angle_ortho]
df_angles[['parallel', 'orthogonal']] = df_angles[['parallel', 'orthogonal']].astype(float)
df_angles.insert(0, 'PC', dataframe['PC'])
return df_angles
def get_projections(points, vec_ucm):
""" Returns coefficients a and b in x = a*vec_ucm + b*vec_ortho with x being the difference of a data point and
the mean.
Projection is computed using a transformation matrix with ucm parallel and orthogonal vectors as basis.
:param points: Data of 2D points.
:type points: pandas.Dataframe
:param vec_ucm: Unit vector parallel to uncontrolled manifold.
:type vec_ucm: numpy.ndarray
:return: Array with projected lengths onto vector parallel to UCM as 'a', onto vector orthogonal to UCM as 'b'.
:rtype: pandas.Dataframe
"""
# Get the vector orthogonal to the UCM.
vec_ortho = get_orthogonal_vec2d(vec_ucm)
# Build a transformation matrix with vec_ucm and vec_ortho as new basis vectors.
A = np.vstack((vec_ucm, vec_ortho)).T # A is not an orthogonal projection matrix (A=A.T), but this works.
# Centralize the data. Analogous to calculating across trials deviation from average for each time step.
diffs = points - points.mean()
# For computational efficiency we shortcut the projection calculation with matrix multiplication.
# The actual math behind it:
# coeffs = vec_ucm.T@diff/np.sqrt(vec_ucm.T@vec_ucm), vec_ortho.T@diff/np.sqrt(vec_ortho.T@vec_ortho)
# Biased variance (normalized by (n-1)) of projection onto UCM vector:
# var_ucm = vec_ucm.T@np.cov(diffs, bias=True, rowvar=False)@vec_ucm/(vec_ucm.T@vec_ucm) # Rayleigh fraction.
coeffs = diffs@A
coeffs.columns = ['parallel', 'orthogonal']
return coeffs
def get_synergy_indices(variances, n=2, d=1):
"""
n: Number of degrees of freedom. In our case 2.
d: Dimensionality of performance variable. In our case a scalar (1).
Vucm = 1/N * 1/(n - d) * sum(ProjUCM**2)
Vort = 1/N * 1/(d) * sum(ProjORT**2)
Vtotal = 1/n * (d * Vort + (n-d) * Vucm) # Anull the weights on Vucm and Vort for the sum.
dV = (Vucm - Vort) / Vtotal
dV = n*(Vucm - Vort) / ((n - d)*Vucm + d*Vort)
Zhang (2008) without weighting Vucm, Vort and Vtotal first:
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
dVz = 0.5*ln((n / d + dV) / (n / ((n - d) - dV))
dVz = 0.5*ln((2 + dV) / (2 - dV))
Reference: https://www.frontiersin.org/articles/10.3389/fnagi.2019.00032/full#supplementary-material
:param variances: Unweighted variances of parallel and orthogonal projections to the UCM.
:type variances: pandas.DataFrame
:param n: Number of degrees of freedom. Defaults to 2.
:type: int
:param d: Dimensionality of performance variable. Defaults to 1.
:type d: int
:returns: Synergy index, Fisher's z-transformed synergy index.
:rtype: pandas.DataFrame
"""
try:
dV = n * (variances['parallel']/(n-d) - variances['orthogonal']/d) \
/ variances[['parallel', 'orthogonal']].sum(axis='columns')
except KeyError:
synergy_indices = pd.DataFrame(columns=["dV", "dVz"])
else:
dVz = 0.5 * np.log((n/d + dV)/(n/(n-d) - dV))
synergy_indices = pd.DataFrame({"dV": dV, "dVz": dVz})
return synergy_indices
def get_synergy_idx_bounds(n=2, d=1):
""" Get lower and upper bounds of the synergy index.
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
If all variance lies within the UCM, then Vort=0 and it follows for the upper bound: dV = n/(n-d)
If all variance lies within Vort, then Vucm=0 and it follows for the lower bound: dV = -n/d
:param n: Number of degrees of freedom.
:type: int
:param d: Dimensionality of performance variable.
:type d: int
:returns: Lower and upper bounds of synergy index.
:rtype: tuple
"""
dV_lower = -n/d
dV_upper = n/(n-d)
return dV_lower, dV_upper
def get_mean(dataframe, column, by=None):
""" Return mean values of column x (optionally grouped)
:param dataframe: Data
:type dataframe: pandas.Dataframe
:param column: Column name
:type column: str
:param by: Column names by which to group.
:type by: str|list
:return: mean value, optionally for each group.
:rtype: numpy.float64|pandas.Series
"""
if by is None:
means = dataframe[column].mean()
else:
means = dataframe.groupby(by)[column].mean()
return means
def get_descriptive_stats(data, by=None):
""" Return mean and variance statistics for data.
:param data: numerical data.
:type data: pandas.Dataframe
:param by: groupby column name(s)
:type by: str|List
:return: Dataframe with columns mean, var, count and column names of data as rows.
:rtype: pandas.Dataframe
"""
# There's a bug in pandas 1.0.4 where you can't use custom numpy functions in agg anymore (ValueError).
# Note that the variance of projections is usually divided by (n-d) for Vucm and d for Vort. Both are 1 in our case.
# Pandas default var returns unbiased population variance /(n-1). Doesn't make a difference for synergy indices.
f_var = lambda series: series.var(ddof=0)
f_var.__name__ = 'variance' # Column name gets function name.
f_avg = lambda series: series.abs().mean()
f_avg.__name__ = 'absolute average'
# When there're no data, return empty DataFrame with columns.
if data.empty:
if by:
data.set_index(by, drop=True, inplace=True)
col_idx = pd.MultiIndex.from_product([data.columns, [f_avg.__name__, 'mean', f_var.__name__]])
stats = pd.DataFrame(None, index=data.index, columns=col_idx)
stats['count'] = None
return stats
if not by:
stats = data.agg([f_avg, 'mean', f_var, 'count']).T
stats['count'] = stats['count'].astype(int)
else:
grouped = data.groupby(by)
stats = grouped.agg([f_avg, 'mean', f_var])
stats['count'] = grouped.size()
stats.dropna(inplace=True)
return stats
def get_statistics(df_trials, df_proj):
""" Calculate descriptive statistics for key values of the anaylsis.
:param df_trials: Data from joined table on trials.
:type df_trials: pandas.DataFrame
:param df_proj: Projections onto UCM and its orthogonal space.
:type df_proj: pandas.DataFrame
:return: Descriptive statistics and synergy indices.
:rtype: pandas.DataFrame
"""
groupers = ['user', 'session', 'condition', 'block', 'task']
try:
# Get only those trials we have the projections for, in the same order.
df_trials = df_trials.iloc[df_proj.index]
df_trials[groupers] = df_trials[groupers].astype('category')
except (KeyError, ValueError):
df_proj_stats = get_descriptive_stats(pd.DataFrame(columns=df_proj.columns))
df_dof_stats = get_descriptive_stats(pd.DataFrame(columns=df_trials.columns))
cov = pd.DataFrame(columns=[('df1,df2 covariance', '')])
else:
df_proj[groupers] = df_trials[groupers]
# Get statistic characteristics of absolute lengths.
df_proj_stats = get_descriptive_stats(df_proj, by=groupers)
# Clean-up to match data on degrees of freedom.
df_proj_stats.dropna(inplace=True)
df_dof_stats = get_descriptive_stats(df_trials[groupers + ['df1', 'df2', 'sum']], by=groupers)
# For degrees of freedom absolute average is the same as the mean, since there are no negative values.
df_dof_stats.drop('absolute average', axis='columns', level=1, inplace=True)
# Get covariance between degrees of freedom.
cov = df_trials.groupby(groupers).apply(lambda x: np.cov(x[['df1', 'df2']].T, ddof=0)[0, 1])
try:
cov = cov.to_frame(('df1,df2 covariance', '')) # MultiIndex.
except AttributeError: # In case cov is an empty Dataframe.
cov = pd.DataFrame(columns=pd.MultiIndex.from_tuples([('df1,df2 covariance', '')]))
# We now have 1 count column too many, since the projection statistics already has the identical column.
df_dof_stats.drop('count', axis='columns', level=0, inplace=True)
# For projections the mean is 0, since projections are from deviations from the mean. So we don't need to show it.
df_proj_stats.drop('mean', axis='columns', level=1, inplace=True)
# Get synergy indices based on projection variances we just calculated.
df_synergies = get_synergy_indices(df_proj_stats.xs('variance', level=1, axis='columns'))
# Before we merge dataframes, give this one a Multiindex, too.
df_synergies.columns = pd.MultiIndex.from_product([df_synergies.columns, ['']])
# Join the 3 statistics to be displayed in a single table.
df = pd.concat((df_dof_stats, cov, df_proj_stats, df_synergies), axis='columns')
return df
def wilcoxon_rank_test(data):
w, p = wilcoxon(data['parallel'], data['orthogonal'], alternative='greater')
return p < 0.05, w, p
def wide_to_long(df, stubs, suffixes, j):
""" Transforms a dataframe to long format, where the stubs are melted into a single column with name j and suffixes
into value columns. Filters for all columns that are a stubs+suffixes combination.
Keeps 'user', 'task' as id_vars. When an error is encountered an emtpy dataframe is returned.
:param df: Data in wide/mixed format.
:type df: pandas.DataFrame
:param stubs: First part of a column name. These names will be the values of the new column j.
:type stubs: list[str]
:param suffixes: Second part of a column name. These will be the new columns holding the respective values.
:type suffixes: str|list[str]
:param j: Name for new column containing stubs.
:type j: str
:return: Filtered Dataframe in long format.
:rtype: pandas.Dataframe
"""
if isinstance(suffixes, str):
suffixes = [suffixes]
# We want all stubs+suffix combinations as columns.
val_cols = [" ".join(x) for x in itertools.product(stubs, suffixes)]
try:
# Filter for data we want to plot.
df = df[['user', 'condition', 'block', 'task', *val_cols]]
# Reverse stub and suffix for long format. We want the measurements as columns, not the categories.
df.columns = [" ".join(x.split(" ")[::-1]) for x in df.columns]
long_df = pd.wide_to_long(df=df, stubnames=suffixes, i=['user', 'condition', 'block', 'task'],
j=j, sep=" ", suffix=f'(!?{"|".join(stubs)})')
long_df.reset_index(inplace=True)
except (KeyError, ValueError):
long_df = pd.DataFrame(columns=['user', 'condition', 'block', 'task', j, *suffixes])
long_df[['user', 'condition', 'block', 'task']] = long_df[['user', 'condition', 'block', 'task']].astype('category')
return long_df
def normality_test(df, columns, multivariate=False):
""" Tests whether there is considerable deviation from a normal distribution.
If no deviation could be detected, we don't know much about the distribution.
Independent normality tests use the Shapiro-Wilk method. Multivariate tests use the Henze-Zirkler multivariate
normality test.
:param df: Aggregated data containing Fisher-z-transformed synergy index.
:type df: pandas.DataFrame
:param columns: Which columns to test for normality deviation.
:type columns: list[str]
:param multivariate: Do multivariate normality testing?
:type multivariate: bool
:return: Normality test results.
:rtype: pandas.DataFrame
"""
if multivariate:
# Multivariate testing.
is_normal, p = df.groupby(['user', 'block'])[columns].apply(pg.multivariate_normality)
res = df.groupby(['user', 'block'])[['df1', 'df2']].apply(pg.multivariate_normality).apply(pd.Series)\
.rename(columns={0: 'normal', 1: 'p'})
else:
# We would want to minimize type II error rate, risk of not rejecting the null when it's false.
res = df.groupby(['user', 'block'])[columns].apply(pg.normality).unstack(level=2) # Shapiro-Wilk tests.
return res
def mixed_anova_synergy_index_z(dataframe):
"" |
def posthoc_ttests(dataframe, var_='dVz'):
""" Pairwise posthoc t-tests on a variable in a mixed design. Between factor is 'condition', within factor is
'block'.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index in long format.
:type dataframe: pandas.DataFrame
:param var_: The variable which to test. One of the column names in dataframe.
:type var_: str
:return: Pairwise T-tests results.
:rtype: pandas.DataFrame
"""
posthocs = pg.pairwise_ttests(data=dataframe, dv=var_, within='block', subject='user', between='condition',
alpha=0.05, within_first=False,
padjust='fdr_by', marginal=True, return_desc=True, tail='one-sided', parametric=True)
return posthocs
| " 3 x (3) Two-way split-plot ANOVA with between-factor condition and within-factor block.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index.
:type dataframe: pandas.DataFrame
:return: mixed-design ANOVA results.
:rtype: pandas.DataFrame
"""
if dataframe['condition'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 condition, run ANOVA with one within factor instead.
if dataframe['block'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 block, run ANOVA with one between factor instead.
aov = pg.mixed_anova(data=dataframe, dv='dVz', within='block', subject='user', between='condition', correction=True)
return aov
| identifier_body |
analysis.py | import itertools
import pandas as pd
import pingouin as pg
import numpy as np
from scipy.stats import wilcoxon
from sklearn.decomposition import PCA
from sklearn.covariance import EllipticEnvelope
def preprocess_data(users, blocks, trials):
""" Clean data.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:returns: Joined and recoded DataFrame. Number of erroneous blocks. Number of sessions removed as a consequence.
Number of removed trials.
:rtype: tuple[pandas.DataFrame, int, int, int]
"""
blocks, n_errors, invalid_sessions = remove_erroneous_blocks(blocks)
# Merge to 1 table.
df = join_data(users, blocks, trials)
# Remove invalid trials.
cleaned, n_trials_removed = get_valid_trials(df)
return cleaned, n_errors, len(invalid_sessions), n_trials_removed
def remove_erroneous_blocks(blocks):
""" Remove sessions with erroneous data due to a NeuroPsy Research App malfunction.
The error causes block data to be duplicated and the values for df1 & df2 multiplied again by 100.
The duplicated blocks are identified by comparing their time stamps to the previous block (less than 2 seconds
difference). If the error caused the session to end early, the whole session is removed.
NeuroPsyResearchApp issue #1.
:param pandas.DataFrame blocks: Data about blocks.
:returns: Cleaned block data. Number of errors found. List of sessions that were removed as a consequence.
:rtype: tuple[pandas.DataFrame, int, list]
"""
# Identify duplicated blocks. Consecutive time stamps are usually less than 2 seconds apart.
mask = blocks.groupby(['session_uid'])['time'].diff() < 2.0
try:
n_errors = mask.value_counts()[True]
except KeyError:
n_errors = 0
blocks = blocks.loc[~mask, :]
# Now, after removal of erroneous data a session might not have all 3 blocks we expect. Exclude whole session.
invalid_sessions = blocks['session_uid'].value_counts() != 3
invalid_sessions = invalid_sessions.loc[invalid_sessions].index.to_list()
blocks = blocks.loc[~blocks['session_uid'].isin(invalid_sessions), :]
return blocks, n_errors, invalid_sessions
def join_data(users, blocks, trials):
""" Take data from different database tables and join them to a single DataFrame. Some variables are renamed and
recoded in the process, some are dropped.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:return: Joined and recoded DataFrame.
:rtype: pandas.DataFrame
"""
# Use users' index instead of id for obfuscation and shorter display.
users_inv_map = pd.Series(users.index, index=users.id)
# Remove trials that don't belong to any block. Those have been excluded.
trials = trials.loc[trials['block_id'].isin(blocks.index), :]
# Start a new table for trials and augment with data from other tables.
df = pd.DataFrame(index=trials.index)
df['user'] = trials.user_id.map(users_inv_map).astype('category')
df['session'] = trials['block_id'].map(blocks['nth_session']).astype('category')
# Map whole sessions to the constraint in the treatment block as a condition for easier grouping during analysis.
df['condition'] = trials['block_id'].map(blocks[['session_uid', 'treatment']].replace(
{'treatment': {'': np.nan}}).groupby('session_uid')['treatment'].ffill().bfill()).astype('category')
df['block'] = trials['block_id'].map(blocks['nth_block']).astype('category')
# Add pre and post labels to trials for each block. Name it task instead of treatment.
# Theoretically, one could have changed number of blocks and order of treatment, but we assume default order here.
df['task'] = trials['block_id'].map(blocks['treatment'].where(blocks['treatment'] != '',
blocks.nth_block.map({1: 'pre', 3: 'post'}))
).astype('category')
#df['task'] = trials['block_id'].map(blocks['treatment'].replace(to_replace={r'\w+': 1, r'^\s*$': 0}, regex=True)
# ).astype('category')
df = pd.concat((df, trials), axis='columns')
# Add columns for easier filtering.
df['grab_diff'] = (df['df2_grab'] - df['df1_grab']).abs()
df['duration_diff'] = (df['df2_duration'] - df['df1_duration']).abs()
# Exclude columns.
df.drop(columns=['user_id', 'block_id'], inplace=True)
return df
def get_valid_trials(dataframe):
""" Remove trials where sliders where not grabbed concurrently or grabbed at all.
:param dataframe: Trial data.
:type dataframe: pandas.DataFrame
:returns: Filtered trials. Number of removed trials.
:rtype: tuple[pandas.DataFrame, int]
"""
# Remove trials with missing values. This means at least one slider wasn't grabbed.
df = dataframe.dropna(axis='index', how='any')
# Remove trials where sliders where not grabbed concurrently.
mask = ~((df['df1_release'] <= df['df2_grab']) | (df['df2_release'] <= df['df1_grab']))
df = df.loc[mask, :]
n_removed = len(dataframe) - len(df)
return df, n_removed
def get_outlyingness(data, contamination=0.1):
""" Outlier detection from covariance estimation in a Gaussian distributed dataset.
:param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Decision on each row if it's an outlier. And contour array for drawing ellipse in graph.
:rtype: tuple[numpy.ndarray, numpy.ndarray]
"""
robust_cov = EllipticEnvelope(support_fraction=1., contamination=contamination)
outlyingness = robust_cov.fit_predict(data)
decision = (outlyingness-1).astype(bool)
# Visualisation.
xx, yy = np.meshgrid(np.linspace(0, 100, 101),
np.linspace(0, 100, 101))
z = robust_cov.predict(np.c_[xx.ravel(), yy.ravel()])
z = z.reshape(xx.shape)
return decision, z
#ToDo: remove blocks/sessions with sum mean way off.
#ToDo: remove sessions with less than 10 trials in any block.
def get_pca_data(dataframe):
""" Conduct Principal Component Analysis on 2D dataset.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:return: Explained variance, components and means.
:rtype: pandas.DataFrame
"""
# We don't reduce dimensionality, but overlay the 2 principal components in 2D.
pca = PCA(n_components=2)
x = dataframe[['df1', 'df2']].values
try:
# df1 and df2 have the same scale. No need to standardize. Standardizing might actually distort PCA here.
pca.fit(x)
except ValueError:
# Return empty.
df = pd.DataFrame(columns=['var_expl', 'var_expl_ratio', 'x', 'y', 'meanx', 'meany'])
else:
df = pd.DataFrame({'var_expl': pca.explained_variance_.T,
'var_expl_ratio': pca.explained_variance_ratio_.T * 100, # In percent
'x': pca.components_[:, 0],
'y': pca.components_[:, 1],
'meanx': pca.mean_[0],
'meany': pca.mean_[1],
},
index=[1, 2] # For designating principal components.
)
df.index.rename('PC', inplace=True)
return df
def get_pca_vectors(dataframe):
""" Get principal components as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Tabular PCA data.
:type dataframe: pandas.DataFrame
:return: Principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vectors = list()
# Use the "components" to define the direction of the vectors,
# and the "explained variance" to define the squared-length of the vectors.
for idx, row in dataframe.iterrows():
v = row[['x', 'y']].values * np.sqrt(row['var_expl']) * 3 # Scale up for better visibility.
mean = row[['meanx', 'meany']].values
mean_offset = (mean, mean + v)
vectors.append(mean_offset)
return vectors
def get_pca_vectors_by(dataframe, by=None):
""" Get principal components for each group as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:param by: Column to group data by and return 2 vectors for each group.
:type by: str|list
:return: list of principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vector_pairs = list()
if by is None:
pca_df = get_pca_data(dataframe)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
else:
grouped = dataframe.groupby(by)
for group, data in grouped:
pca_df = get_pca_data(data)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
# ToDo: Augment by groupby criteria.
return vector_pairs
def get_interior_angle(vec0, vec1):
""" Get the smaller angle between vec0 and vec1 in degrees.
:param vec0: Vector 0
:type vec0: numpy.ndarray
:param vec1: Vector 1
:type vec1: numpy.ndarray
:return: Interior angle between vector0 and vector1 in degrees.
:rtype: float
"""
angle = np.math.atan2(np.linalg.det([vec0, vec1]), np.dot(vec0, vec1))
degrees = abs(np.degrees(angle))
# Min and max should be between 0° an 90°.
degrees = min(degrees, 180.0 - degrees)
return degrees
def get_ucm_vec(p0=None, p1=None):
""" Returns 2D unit vector in direction of uncontrolled manifold. """
if p0 is None:
p0 = np.array([25, 100])
if p1 is None:
p1 = np.array([100, 25])
parallel = p1 - p0
parallel = parallel / np.linalg.norm(parallel) # Normalize.
return parallel
def get_orthogonal_vec2d(vec):
""" Get a vector that is orthogonal to vec and has same length.
:param vec: 2D Vector
:return: 2D Vector orthogonal to vec.
:rtype: numpy.ndarray
"""
ortho = np.array([-vec[1], vec[0]])
return ortho
def get_pc_ucm_angles(dataframe, vec_ucm):
""" Computes the interior angles between pca vectors and ucm parallel/orthogonal vectors.
:param dataframe: PCA data .
:type dataframe: pandas.DataFrame
:param vec_ucm: Vector parallel to UCM.
:type vec_ucm: numpy.ndarray
:return: Each angle between principal components and UCM parallel and orthogonal vector.
:rtype: pandas.DataFrame
"""
vec_ucm_ortho = get_orthogonal_vec2d(vec_ucm)
df_angles = pd.DataFrame(columns=['parallel', 'orthogonal'])
for idx, row in dataframe.iterrows():
angle_parallel = get_interior_angle(vec_ucm, row[['x', 'y']])
angle_ortho = get_interior_angle(vec_ucm_ortho, row[['x', 'y']])
df_angles.loc[idx] = [angle_parallel, angle_ortho]
df_angles[['parallel', 'orthogonal']] = df_angles[['parallel', 'orthogonal']].astype(float)
df_angles.insert(0, 'PC', dataframe['PC'])
return df_angles
def get_projections(points, vec_ucm):
""" Returns coefficients a and b in x = a*vec_ucm + b*vec_ortho with x being the difference of a data point and
the mean.
Projection is computed using a transformation matrix with ucm parallel and orthogonal vectors as basis.
:param points: Data of 2D points.
:type points: pandas.Dataframe
:param vec_ucm: Unit vector parallel to uncontrolled manifold.
:type vec_ucm: numpy.ndarray
:return: Array with projected lengths onto vector parallel to UCM as 'a', onto vector orthogonal to UCM as 'b'.
:rtype: pandas.Dataframe
"""
# Get the vector orthogonal to the UCM.
vec_ortho = get_orthogonal_vec2d(vec_ucm)
# Build a transformation matrix with vec_ucm and vec_ortho as new basis vectors.
A = np.vstack((vec_ucm, vec_ortho)).T # A is not an orthogonal projection matrix (A=A.T), but this works.
# Centralize the data. Analogous to calculating across trials deviation from average for each time step.
diffs = points - points.mean()
# For computational efficiency we shortcut the projection calculation with matrix multiplication.
# The actual math behind it:
# coeffs = vec_ucm.T@diff/np.sqrt(vec_ucm.T@vec_ucm), vec_ortho.T@diff/np.sqrt(vec_ortho.T@vec_ortho)
# Biased variance (normalized by (n-1)) of projection onto UCM vector:
# var_ucm = vec_ucm.T@np.cov(diffs, bias=True, rowvar=False)@vec_ucm/(vec_ucm.T@vec_ucm) # Rayleigh fraction.
coeffs = diffs@A
coeffs.columns = ['parallel', 'orthogonal']
return coeffs
def get_synergy_indices(variances, n=2, d=1):
"""
n: Number of degrees of freedom. In our case 2.
d: Dimensionality of performance variable. In our case a scalar (1).
Vucm = 1/N * 1/(n - d) * sum(ProjUCM**2)
Vort = 1/N * 1/(d) * sum(ProjORT**2)
Vtotal = 1/n * (d * Vort + (n-d) * Vucm) # Anull the weights on Vucm and Vort for the sum.
dV = (Vucm - Vort) / Vtotal
dV = n*(Vucm - Vort) / ((n - d)*Vucm + d*Vort)
Zhang (2008) without weighting Vucm, Vort and Vtotal first:
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
dVz = 0.5*ln((n / d + dV) / (n / ((n - d) - dV))
dVz = 0.5*ln((2 + dV) / (2 - dV))
Reference: https://www.frontiersin.org/articles/10.3389/fnagi.2019.00032/full#supplementary-material
:param variances: Unweighted variances of parallel and orthogonal projections to the UCM.
:type variances: pandas.DataFrame
:param n: Number of degrees of freedom. Defaults to 2.
:type: int
:param d: Dimensionality of performance variable. Defaults to 1.
:type d: int
:returns: Synergy index, Fisher's z-transformed synergy index.
:rtype: pandas.DataFrame
""" | / variances[['parallel', 'orthogonal']].sum(axis='columns')
except KeyError:
synergy_indices = pd.DataFrame(columns=["dV", "dVz"])
else:
dVz = 0.5 * np.log((n/d + dV)/(n/(n-d) - dV))
synergy_indices = pd.DataFrame({"dV": dV, "dVz": dVz})
return synergy_indices
def get_synergy_idx_bounds(n=2, d=1):
""" Get lower and upper bounds of the synergy index.
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
If all variance lies within the UCM, then Vort=0 and it follows for the upper bound: dV = n/(n-d)
If all variance lies within Vort, then Vucm=0 and it follows for the lower bound: dV = -n/d
:param n: Number of degrees of freedom.
:type: int
:param d: Dimensionality of performance variable.
:type d: int
:returns: Lower and upper bounds of synergy index.
:rtype: tuple
"""
dV_lower = -n/d
dV_upper = n/(n-d)
return dV_lower, dV_upper
def get_mean(dataframe, column, by=None):
""" Return mean values of column x (optionally grouped)
:param dataframe: Data
:type dataframe: pandas.Dataframe
:param column: Column name
:type column: str
:param by: Column names by which to group.
:type by: str|list
:return: mean value, optionally for each group.
:rtype: numpy.float64|pandas.Series
"""
if by is None:
means = dataframe[column].mean()
else:
means = dataframe.groupby(by)[column].mean()
return means
def get_descriptive_stats(data, by=None):
""" Return mean and variance statistics for data.
:param data: numerical data.
:type data: pandas.Dataframe
:param by: groupby column name(s)
:type by: str|List
:return: Dataframe with columns mean, var, count and column names of data as rows.
:rtype: pandas.Dataframe
"""
# There's a bug in pandas 1.0.4 where you can't use custom numpy functions in agg anymore (ValueError).
# Note that the variance of projections is usually divided by (n-d) for Vucm and d for Vort. Both are 1 in our case.
# Pandas default var returns unbiased population variance /(n-1). Doesn't make a difference for synergy indices.
f_var = lambda series: series.var(ddof=0)
f_var.__name__ = 'variance' # Column name gets function name.
f_avg = lambda series: series.abs().mean()
f_avg.__name__ = 'absolute average'
# When there're no data, return empty DataFrame with columns.
if data.empty:
if by:
data.set_index(by, drop=True, inplace=True)
col_idx = pd.MultiIndex.from_product([data.columns, [f_avg.__name__, 'mean', f_var.__name__]])
stats = pd.DataFrame(None, index=data.index, columns=col_idx)
stats['count'] = None
return stats
if not by:
stats = data.agg([f_avg, 'mean', f_var, 'count']).T
stats['count'] = stats['count'].astype(int)
else:
grouped = data.groupby(by)
stats = grouped.agg([f_avg, 'mean', f_var])
stats['count'] = grouped.size()
stats.dropna(inplace=True)
return stats
def get_statistics(df_trials, df_proj):
""" Calculate descriptive statistics for key values of the anaylsis.
:param df_trials: Data from joined table on trials.
:type df_trials: pandas.DataFrame
:param df_proj: Projections onto UCM and its orthogonal space.
:type df_proj: pandas.DataFrame
:return: Descriptive statistics and synergy indices.
:rtype: pandas.DataFrame
"""
groupers = ['user', 'session', 'condition', 'block', 'task']
try:
# Get only those trials we have the projections for, in the same order.
df_trials = df_trials.iloc[df_proj.index]
df_trials[groupers] = df_trials[groupers].astype('category')
except (KeyError, ValueError):
df_proj_stats = get_descriptive_stats(pd.DataFrame(columns=df_proj.columns))
df_dof_stats = get_descriptive_stats(pd.DataFrame(columns=df_trials.columns))
cov = pd.DataFrame(columns=[('df1,df2 covariance', '')])
else:
df_proj[groupers] = df_trials[groupers]
# Get statistic characteristics of absolute lengths.
df_proj_stats = get_descriptive_stats(df_proj, by=groupers)
# Clean-up to match data on degrees of freedom.
df_proj_stats.dropna(inplace=True)
df_dof_stats = get_descriptive_stats(df_trials[groupers + ['df1', 'df2', 'sum']], by=groupers)
# For degrees of freedom absolute average is the same as the mean, since there are no negative values.
df_dof_stats.drop('absolute average', axis='columns', level=1, inplace=True)
# Get covariance between degrees of freedom.
cov = df_trials.groupby(groupers).apply(lambda x: np.cov(x[['df1', 'df2']].T, ddof=0)[0, 1])
try:
cov = cov.to_frame(('df1,df2 covariance', '')) # MultiIndex.
except AttributeError: # In case cov is an empty Dataframe.
cov = pd.DataFrame(columns=pd.MultiIndex.from_tuples([('df1,df2 covariance', '')]))
# We now have 1 count column too many, since the projection statistics already has the identical column.
df_dof_stats.drop('count', axis='columns', level=0, inplace=True)
# For projections the mean is 0, since projections are from deviations from the mean. So we don't need to show it.
df_proj_stats.drop('mean', axis='columns', level=1, inplace=True)
# Get synergy indices based on projection variances we just calculated.
df_synergies = get_synergy_indices(df_proj_stats.xs('variance', level=1, axis='columns'))
# Before we merge dataframes, give this one a Multiindex, too.
df_synergies.columns = pd.MultiIndex.from_product([df_synergies.columns, ['']])
# Join the 3 statistics to be displayed in a single table.
df = pd.concat((df_dof_stats, cov, df_proj_stats, df_synergies), axis='columns')
return df
def wilcoxon_rank_test(data):
w, p = wilcoxon(data['parallel'], data['orthogonal'], alternative='greater')
return p < 0.05, w, p
def wide_to_long(df, stubs, suffixes, j):
""" Transforms a dataframe to long format, where the stubs are melted into a single column with name j and suffixes
into value columns. Filters for all columns that are a stubs+suffixes combination.
Keeps 'user', 'task' as id_vars. When an error is encountered an emtpy dataframe is returned.
:param df: Data in wide/mixed format.
:type df: pandas.DataFrame
:param stubs: First part of a column name. These names will be the values of the new column j.
:type stubs: list[str]
:param suffixes: Second part of a column name. These will be the new columns holding the respective values.
:type suffixes: str|list[str]
:param j: Name for new column containing stubs.
:type j: str
:return: Filtered Dataframe in long format.
:rtype: pandas.Dataframe
"""
if isinstance(suffixes, str):
suffixes = [suffixes]
# We want all stubs+suffix combinations as columns.
val_cols = [" ".join(x) for x in itertools.product(stubs, suffixes)]
try:
# Filter for data we want to plot.
df = df[['user', 'condition', 'block', 'task', *val_cols]]
# Reverse stub and suffix for long format. We want the measurements as columns, not the categories.
df.columns = [" ".join(x.split(" ")[::-1]) for x in df.columns]
long_df = pd.wide_to_long(df=df, stubnames=suffixes, i=['user', 'condition', 'block', 'task'],
j=j, sep=" ", suffix=f'(!?{"|".join(stubs)})')
long_df.reset_index(inplace=True)
except (KeyError, ValueError):
long_df = pd.DataFrame(columns=['user', 'condition', 'block', 'task', j, *suffixes])
long_df[['user', 'condition', 'block', 'task']] = long_df[['user', 'condition', 'block', 'task']].astype('category')
return long_df
def normality_test(df, columns, multivariate=False):
""" Tests whether there is considerable deviation from a normal distribution.
If no deviation could be detected, we don't know much about the distribution.
Independent normality tests use the Shapiro-Wilk method. Multivariate tests use the Henze-Zirkler multivariate
normality test.
:param df: Aggregated data containing Fisher-z-transformed synergy index.
:type df: pandas.DataFrame
:param columns: Which columns to test for normality deviation.
:type columns: list[str]
:param multivariate: Do multivariate normality testing?
:type multivariate: bool
:return: Normality test results.
:rtype: pandas.DataFrame
"""
if multivariate:
# Multivariate testing.
is_normal, p = df.groupby(['user', 'block'])[columns].apply(pg.multivariate_normality)
res = df.groupby(['user', 'block'])[['df1', 'df2']].apply(pg.multivariate_normality).apply(pd.Series)\
.rename(columns={0: 'normal', 1: 'p'})
else:
# We would want to minimize type II error rate, risk of not rejecting the null when it's false.
res = df.groupby(['user', 'block'])[columns].apply(pg.normality).unstack(level=2) # Shapiro-Wilk tests.
return res
def mixed_anova_synergy_index_z(dataframe):
""" 3 x (3) Two-way split-plot ANOVA with between-factor condition and within-factor block.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index.
:type dataframe: pandas.DataFrame
:return: mixed-design ANOVA results.
:rtype: pandas.DataFrame
"""
if dataframe['condition'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 condition, run ANOVA with one within factor instead.
if dataframe['block'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 block, run ANOVA with one between factor instead.
aov = pg.mixed_anova(data=dataframe, dv='dVz', within='block', subject='user', between='condition', correction=True)
return aov
def posthoc_ttests(dataframe, var_='dVz'):
""" Pairwise posthoc t-tests on a variable in a mixed design. Between factor is 'condition', within factor is
'block'.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index in long format.
:type dataframe: pandas.DataFrame
:param var_: The variable which to test. One of the column names in dataframe.
:type var_: str
:return: Pairwise T-tests results.
:rtype: pandas.DataFrame
"""
posthocs = pg.pairwise_ttests(data=dataframe, dv=var_, within='block', subject='user', between='condition',
alpha=0.05, within_first=False,
padjust='fdr_by', marginal=True, return_desc=True, tail='one-sided', parametric=True)
return posthocs | try:
dV = n * (variances['parallel']/(n-d) - variances['orthogonal']/d) \ | random_line_split |
analysis.py | import itertools
import pandas as pd
import pingouin as pg
import numpy as np
from scipy.stats import wilcoxon
from sklearn.decomposition import PCA
from sklearn.covariance import EllipticEnvelope
def preprocess_data(users, blocks, trials):
""" Clean data.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:returns: Joined and recoded DataFrame. Number of erroneous blocks. Number of sessions removed as a consequence.
Number of removed trials.
:rtype: tuple[pandas.DataFrame, int, int, int]
"""
blocks, n_errors, invalid_sessions = remove_erroneous_blocks(blocks)
# Merge to 1 table.
df = join_data(users, blocks, trials)
# Remove invalid trials.
cleaned, n_trials_removed = get_valid_trials(df)
return cleaned, n_errors, len(invalid_sessions), n_trials_removed
def remove_erroneous_blocks(blocks):
""" Remove sessions with erroneous data due to a NeuroPsy Research App malfunction.
The error causes block data to be duplicated and the values for df1 & df2 multiplied again by 100.
The duplicated blocks are identified by comparing their time stamps to the previous block (less than 2 seconds
difference). If the error caused the session to end early, the whole session is removed.
NeuroPsyResearchApp issue #1.
:param pandas.DataFrame blocks: Data about blocks.
:returns: Cleaned block data. Number of errors found. List of sessions that were removed as a consequence.
:rtype: tuple[pandas.DataFrame, int, list]
"""
# Identify duplicated blocks. Consecutive time stamps are usually less than 2 seconds apart.
mask = blocks.groupby(['session_uid'])['time'].diff() < 2.0
try:
n_errors = mask.value_counts()[True]
except KeyError:
n_errors = 0
blocks = blocks.loc[~mask, :]
# Now, after removal of erroneous data a session might not have all 3 blocks we expect. Exclude whole session.
invalid_sessions = blocks['session_uid'].value_counts() != 3
invalid_sessions = invalid_sessions.loc[invalid_sessions].index.to_list()
blocks = blocks.loc[~blocks['session_uid'].isin(invalid_sessions), :]
return blocks, n_errors, invalid_sessions
def join_data(users, blocks, trials):
""" Take data from different database tables and join them to a single DataFrame. Some variables are renamed and
recoded in the process, some are dropped.
:param users: Data from users table
:type users: pandas.DataFrame
:param blocks: Data from circletask_blocks table.
:type blocks: pandas.DataFrame
:param trials: Data from circletask_trials table.
:type trials: pandas.DataFrame
:return: Joined and recoded DataFrame.
:rtype: pandas.DataFrame
"""
# Use users' index instead of id for obfuscation and shorter display.
users_inv_map = pd.Series(users.index, index=users.id)
# Remove trials that don't belong to any block. Those have been excluded.
trials = trials.loc[trials['block_id'].isin(blocks.index), :]
# Start a new table for trials and augment with data from other tables.
df = pd.DataFrame(index=trials.index)
df['user'] = trials.user_id.map(users_inv_map).astype('category')
df['session'] = trials['block_id'].map(blocks['nth_session']).astype('category')
# Map whole sessions to the constraint in the treatment block as a condition for easier grouping during analysis.
df['condition'] = trials['block_id'].map(blocks[['session_uid', 'treatment']].replace(
{'treatment': {'': np.nan}}).groupby('session_uid')['treatment'].ffill().bfill()).astype('category')
df['block'] = trials['block_id'].map(blocks['nth_block']).astype('category')
# Add pre and post labels to trials for each block. Name it task instead of treatment.
# Theoretically, one could have changed number of blocks and order of treatment, but we assume default order here.
df['task'] = trials['block_id'].map(blocks['treatment'].where(blocks['treatment'] != '',
blocks.nth_block.map({1: 'pre', 3: 'post'}))
).astype('category')
#df['task'] = trials['block_id'].map(blocks['treatment'].replace(to_replace={r'\w+': 1, r'^\s*$': 0}, regex=True)
# ).astype('category')
df = pd.concat((df, trials), axis='columns')
# Add columns for easier filtering.
df['grab_diff'] = (df['df2_grab'] - df['df1_grab']).abs()
df['duration_diff'] = (df['df2_duration'] - df['df1_duration']).abs()
# Exclude columns.
df.drop(columns=['user_id', 'block_id'], inplace=True)
return df
def get_valid_trials(dataframe):
""" Remove trials where sliders where not grabbed concurrently or grabbed at all.
:param dataframe: Trial data.
:type dataframe: pandas.DataFrame
:returns: Filtered trials. Number of removed trials.
:rtype: tuple[pandas.DataFrame, int]
"""
# Remove trials with missing values. This means at least one slider wasn't grabbed.
df = dataframe.dropna(axis='index', how='any')
# Remove trials where sliders where not grabbed concurrently.
mask = ~((df['df1_release'] <= df['df2_grab']) | (df['df2_release'] <= df['df1_grab']))
df = df.loc[mask, :]
n_removed = len(dataframe) - len(df)
return df, n_removed
def get_outlyingness(data, contamination=0.1):
""" Outlier detection from covariance estimation in a Gaussian distributed dataset.
:param data: Data in which to detect outliers. Take care that n_samples > n_features ** 2 .
:type data: pandas.DataFrame
:param contamination: The amount of contamination of the data set, i.e. the proportion of outliers in the data set.
Range is (0, 0.5).
:type contamination: float
:returns: Decision on each row if it's an outlier. And contour array for drawing ellipse in graph.
:rtype: tuple[numpy.ndarray, numpy.ndarray]
"""
robust_cov = EllipticEnvelope(support_fraction=1., contamination=contamination)
outlyingness = robust_cov.fit_predict(data)
decision = (outlyingness-1).astype(bool)
# Visualisation.
xx, yy = np.meshgrid(np.linspace(0, 100, 101),
np.linspace(0, 100, 101))
z = robust_cov.predict(np.c_[xx.ravel(), yy.ravel()])
z = z.reshape(xx.shape)
return decision, z
#ToDo: remove blocks/sessions with sum mean way off.
#ToDo: remove sessions with less than 10 trials in any block.
def get_pca_data(dataframe):
""" Conduct Principal Component Analysis on 2D dataset.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:return: Explained variance, components and means.
:rtype: pandas.DataFrame
"""
# We don't reduce dimensionality, but overlay the 2 principal components in 2D.
pca = PCA(n_components=2)
x = dataframe[['df1', 'df2']].values
try:
# df1 and df2 have the same scale. No need to standardize. Standardizing might actually distort PCA here.
pca.fit(x)
except ValueError:
# Return empty.
df = pd.DataFrame(columns=['var_expl', 'var_expl_ratio', 'x', 'y', 'meanx', 'meany'])
else:
df = pd.DataFrame({'var_expl': pca.explained_variance_.T,
'var_expl_ratio': pca.explained_variance_ratio_.T * 100, # In percent
'x': pca.components_[:, 0],
'y': pca.components_[:, 1],
'meanx': pca.mean_[0],
'meany': pca.mean_[1],
},
index=[1, 2] # For designating principal components.
)
df.index.rename('PC', inplace=True)
return df
def | (dataframe):
""" Get principal components as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Tabular PCA data.
:type dataframe: pandas.DataFrame
:return: Principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vectors = list()
# Use the "components" to define the direction of the vectors,
# and the "explained variance" to define the squared-length of the vectors.
for idx, row in dataframe.iterrows():
v = row[['x', 'y']].values * np.sqrt(row['var_expl']) * 3 # Scale up for better visibility.
mean = row[['meanx', 'meany']].values
mean_offset = (mean, mean + v)
vectors.append(mean_offset)
return vectors
def get_pca_vectors_by(dataframe, by=None):
""" Get principal components for each group as vectors. Vectors can then be used to annotate graphs.
:param dataframe: Data holding 'df1' and 'df2' values as columns.
:type dataframe: pandas.DataFrame
:param by: Column to group data by and return 2 vectors for each group.
:type by: str|list
:return: list of principal components as vector pairs in input space with mean as origin first and offset second.
:rtype: list
"""
vector_pairs = list()
if by is None:
pca_df = get_pca_data(dataframe)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
else:
grouped = dataframe.groupby(by)
for group, data in grouped:
pca_df = get_pca_data(data)
v = get_pca_vectors(pca_df)
vector_pairs.append(v)
# ToDo: Augment by groupby criteria.
return vector_pairs
def get_interior_angle(vec0, vec1):
""" Get the smaller angle between vec0 and vec1 in degrees.
:param vec0: Vector 0
:type vec0: numpy.ndarray
:param vec1: Vector 1
:type vec1: numpy.ndarray
:return: Interior angle between vector0 and vector1 in degrees.
:rtype: float
"""
angle = np.math.atan2(np.linalg.det([vec0, vec1]), np.dot(vec0, vec1))
degrees = abs(np.degrees(angle))
# Min and max should be between 0° an 90°.
degrees = min(degrees, 180.0 - degrees)
return degrees
def get_ucm_vec(p0=None, p1=None):
""" Returns 2D unit vector in direction of uncontrolled manifold. """
if p0 is None:
p0 = np.array([25, 100])
if p1 is None:
p1 = np.array([100, 25])
parallel = p1 - p0
parallel = parallel / np.linalg.norm(parallel) # Normalize.
return parallel
def get_orthogonal_vec2d(vec):
""" Get a vector that is orthogonal to vec and has same length.
:param vec: 2D Vector
:return: 2D Vector orthogonal to vec.
:rtype: numpy.ndarray
"""
ortho = np.array([-vec[1], vec[0]])
return ortho
def get_pc_ucm_angles(dataframe, vec_ucm):
""" Computes the interior angles between pca vectors and ucm parallel/orthogonal vectors.
:param dataframe: PCA data .
:type dataframe: pandas.DataFrame
:param vec_ucm: Vector parallel to UCM.
:type vec_ucm: numpy.ndarray
:return: Each angle between principal components and UCM parallel and orthogonal vector.
:rtype: pandas.DataFrame
"""
vec_ucm_ortho = get_orthogonal_vec2d(vec_ucm)
df_angles = pd.DataFrame(columns=['parallel', 'orthogonal'])
for idx, row in dataframe.iterrows():
angle_parallel = get_interior_angle(vec_ucm, row[['x', 'y']])
angle_ortho = get_interior_angle(vec_ucm_ortho, row[['x', 'y']])
df_angles.loc[idx] = [angle_parallel, angle_ortho]
df_angles[['parallel', 'orthogonal']] = df_angles[['parallel', 'orthogonal']].astype(float)
df_angles.insert(0, 'PC', dataframe['PC'])
return df_angles
def get_projections(points, vec_ucm):
""" Returns coefficients a and b in x = a*vec_ucm + b*vec_ortho with x being the difference of a data point and
the mean.
Projection is computed using a transformation matrix with ucm parallel and orthogonal vectors as basis.
:param points: Data of 2D points.
:type points: pandas.Dataframe
:param vec_ucm: Unit vector parallel to uncontrolled manifold.
:type vec_ucm: numpy.ndarray
:return: Array with projected lengths onto vector parallel to UCM as 'a', onto vector orthogonal to UCM as 'b'.
:rtype: pandas.Dataframe
"""
# Get the vector orthogonal to the UCM.
vec_ortho = get_orthogonal_vec2d(vec_ucm)
# Build a transformation matrix with vec_ucm and vec_ortho as new basis vectors.
A = np.vstack((vec_ucm, vec_ortho)).T # A is not an orthogonal projection matrix (A=A.T), but this works.
# Centralize the data. Analogous to calculating across trials deviation from average for each time step.
diffs = points - points.mean()
# For computational efficiency we shortcut the projection calculation with matrix multiplication.
# The actual math behind it:
# coeffs = vec_ucm.T@diff/np.sqrt(vec_ucm.T@vec_ucm), vec_ortho.T@diff/np.sqrt(vec_ortho.T@vec_ortho)
# Biased variance (normalized by (n-1)) of projection onto UCM vector:
# var_ucm = vec_ucm.T@np.cov(diffs, bias=True, rowvar=False)@vec_ucm/(vec_ucm.T@vec_ucm) # Rayleigh fraction.
coeffs = diffs@A
coeffs.columns = ['parallel', 'orthogonal']
return coeffs
def get_synergy_indices(variances, n=2, d=1):
"""
n: Number of degrees of freedom. In our case 2.
d: Dimensionality of performance variable. In our case a scalar (1).
Vucm = 1/N * 1/(n - d) * sum(ProjUCM**2)
Vort = 1/N * 1/(d) * sum(ProjORT**2)
Vtotal = 1/n * (d * Vort + (n-d) * Vucm) # Anull the weights on Vucm and Vort for the sum.
dV = (Vucm - Vort) / Vtotal
dV = n*(Vucm - Vort) / ((n - d)*Vucm + d*Vort)
Zhang (2008) without weighting Vucm, Vort and Vtotal first:
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
dVz = 0.5*ln((n / d + dV) / (n / ((n - d) - dV))
dVz = 0.5*ln((2 + dV) / (2 - dV))
Reference: https://www.frontiersin.org/articles/10.3389/fnagi.2019.00032/full#supplementary-material
:param variances: Unweighted variances of parallel and orthogonal projections to the UCM.
:type variances: pandas.DataFrame
:param n: Number of degrees of freedom. Defaults to 2.
:type: int
:param d: Dimensionality of performance variable. Defaults to 1.
:type d: int
:returns: Synergy index, Fisher's z-transformed synergy index.
:rtype: pandas.DataFrame
"""
try:
dV = n * (variances['parallel']/(n-d) - variances['orthogonal']/d) \
/ variances[['parallel', 'orthogonal']].sum(axis='columns')
except KeyError:
synergy_indices = pd.DataFrame(columns=["dV", "dVz"])
else:
dVz = 0.5 * np.log((n/d + dV)/(n/(n-d) - dV))
synergy_indices = pd.DataFrame({"dV": dV, "dVz": dVz})
return synergy_indices
def get_synergy_idx_bounds(n=2, d=1):
""" Get lower and upper bounds of the synergy index.
dV = n * (Vucm/(n - d) - Vort/d) / (Vucm + Vort)
If all variance lies within the UCM, then Vort=0 and it follows for the upper bound: dV = n/(n-d)
If all variance lies within Vort, then Vucm=0 and it follows for the lower bound: dV = -n/d
:param n: Number of degrees of freedom.
:type: int
:param d: Dimensionality of performance variable.
:type d: int
:returns: Lower and upper bounds of synergy index.
:rtype: tuple
"""
dV_lower = -n/d
dV_upper = n/(n-d)
return dV_lower, dV_upper
def get_mean(dataframe, column, by=None):
""" Return mean values of column x (optionally grouped)
:param dataframe: Data
:type dataframe: pandas.Dataframe
:param column: Column name
:type column: str
:param by: Column names by which to group.
:type by: str|list
:return: mean value, optionally for each group.
:rtype: numpy.float64|pandas.Series
"""
if by is None:
means = dataframe[column].mean()
else:
means = dataframe.groupby(by)[column].mean()
return means
def get_descriptive_stats(data, by=None):
""" Return mean and variance statistics for data.
:param data: numerical data.
:type data: pandas.Dataframe
:param by: groupby column name(s)
:type by: str|List
:return: Dataframe with columns mean, var, count and column names of data as rows.
:rtype: pandas.Dataframe
"""
# There's a bug in pandas 1.0.4 where you can't use custom numpy functions in agg anymore (ValueError).
# Note that the variance of projections is usually divided by (n-d) for Vucm and d for Vort. Both are 1 in our case.
# Pandas default var returns unbiased population variance /(n-1). Doesn't make a difference for synergy indices.
f_var = lambda series: series.var(ddof=0)
f_var.__name__ = 'variance' # Column name gets function name.
f_avg = lambda series: series.abs().mean()
f_avg.__name__ = 'absolute average'
# When there're no data, return empty DataFrame with columns.
if data.empty:
if by:
data.set_index(by, drop=True, inplace=True)
col_idx = pd.MultiIndex.from_product([data.columns, [f_avg.__name__, 'mean', f_var.__name__]])
stats = pd.DataFrame(None, index=data.index, columns=col_idx)
stats['count'] = None
return stats
if not by:
stats = data.agg([f_avg, 'mean', f_var, 'count']).T
stats['count'] = stats['count'].astype(int)
else:
grouped = data.groupby(by)
stats = grouped.agg([f_avg, 'mean', f_var])
stats['count'] = grouped.size()
stats.dropna(inplace=True)
return stats
def get_statistics(df_trials, df_proj):
""" Calculate descriptive statistics for key values of the anaylsis.
:param df_trials: Data from joined table on trials.
:type df_trials: pandas.DataFrame
:param df_proj: Projections onto UCM and its orthogonal space.
:type df_proj: pandas.DataFrame
:return: Descriptive statistics and synergy indices.
:rtype: pandas.DataFrame
"""
groupers = ['user', 'session', 'condition', 'block', 'task']
try:
# Get only those trials we have the projections for, in the same order.
df_trials = df_trials.iloc[df_proj.index]
df_trials[groupers] = df_trials[groupers].astype('category')
except (KeyError, ValueError):
df_proj_stats = get_descriptive_stats(pd.DataFrame(columns=df_proj.columns))
df_dof_stats = get_descriptive_stats(pd.DataFrame(columns=df_trials.columns))
cov = pd.DataFrame(columns=[('df1,df2 covariance', '')])
else:
df_proj[groupers] = df_trials[groupers]
# Get statistic characteristics of absolute lengths.
df_proj_stats = get_descriptive_stats(df_proj, by=groupers)
# Clean-up to match data on degrees of freedom.
df_proj_stats.dropna(inplace=True)
df_dof_stats = get_descriptive_stats(df_trials[groupers + ['df1', 'df2', 'sum']], by=groupers)
# For degrees of freedom absolute average is the same as the mean, since there are no negative values.
df_dof_stats.drop('absolute average', axis='columns', level=1, inplace=True)
# Get covariance between degrees of freedom.
cov = df_trials.groupby(groupers).apply(lambda x: np.cov(x[['df1', 'df2']].T, ddof=0)[0, 1])
try:
cov = cov.to_frame(('df1,df2 covariance', '')) # MultiIndex.
except AttributeError: # In case cov is an empty Dataframe.
cov = pd.DataFrame(columns=pd.MultiIndex.from_tuples([('df1,df2 covariance', '')]))
# We now have 1 count column too many, since the projection statistics already has the identical column.
df_dof_stats.drop('count', axis='columns', level=0, inplace=True)
# For projections the mean is 0, since projections are from deviations from the mean. So we don't need to show it.
df_proj_stats.drop('mean', axis='columns', level=1, inplace=True)
# Get synergy indices based on projection variances we just calculated.
df_synergies = get_synergy_indices(df_proj_stats.xs('variance', level=1, axis='columns'))
# Before we merge dataframes, give this one a Multiindex, too.
df_synergies.columns = pd.MultiIndex.from_product([df_synergies.columns, ['']])
# Join the 3 statistics to be displayed in a single table.
df = pd.concat((df_dof_stats, cov, df_proj_stats, df_synergies), axis='columns')
return df
def wilcoxon_rank_test(data):
w, p = wilcoxon(data['parallel'], data['orthogonal'], alternative='greater')
return p < 0.05, w, p
def wide_to_long(df, stubs, suffixes, j):
""" Transforms a dataframe to long format, where the stubs are melted into a single column with name j and suffixes
into value columns. Filters for all columns that are a stubs+suffixes combination.
Keeps 'user', 'task' as id_vars. When an error is encountered an emtpy dataframe is returned.
:param df: Data in wide/mixed format.
:type df: pandas.DataFrame
:param stubs: First part of a column name. These names will be the values of the new column j.
:type stubs: list[str]
:param suffixes: Second part of a column name. These will be the new columns holding the respective values.
:type suffixes: str|list[str]
:param j: Name for new column containing stubs.
:type j: str
:return: Filtered Dataframe in long format.
:rtype: pandas.Dataframe
"""
if isinstance(suffixes, str):
suffixes = [suffixes]
# We want all stubs+suffix combinations as columns.
val_cols = [" ".join(x) for x in itertools.product(stubs, suffixes)]
try:
# Filter for data we want to plot.
df = df[['user', 'condition', 'block', 'task', *val_cols]]
# Reverse stub and suffix for long format. We want the measurements as columns, not the categories.
df.columns = [" ".join(x.split(" ")[::-1]) for x in df.columns]
long_df = pd.wide_to_long(df=df, stubnames=suffixes, i=['user', 'condition', 'block', 'task'],
j=j, sep=" ", suffix=f'(!?{"|".join(stubs)})')
long_df.reset_index(inplace=True)
except (KeyError, ValueError):
long_df = pd.DataFrame(columns=['user', 'condition', 'block', 'task', j, *suffixes])
long_df[['user', 'condition', 'block', 'task']] = long_df[['user', 'condition', 'block', 'task']].astype('category')
return long_df
def normality_test(df, columns, multivariate=False):
""" Tests whether there is considerable deviation from a normal distribution.
If no deviation could be detected, we don't know much about the distribution.
Independent normality tests use the Shapiro-Wilk method. Multivariate tests use the Henze-Zirkler multivariate
normality test.
:param df: Aggregated data containing Fisher-z-transformed synergy index.
:type df: pandas.DataFrame
:param columns: Which columns to test for normality deviation.
:type columns: list[str]
:param multivariate: Do multivariate normality testing?
:type multivariate: bool
:return: Normality test results.
:rtype: pandas.DataFrame
"""
if multivariate:
# Multivariate testing.
is_normal, p = df.groupby(['user', 'block'])[columns].apply(pg.multivariate_normality)
res = df.groupby(['user', 'block'])[['df1', 'df2']].apply(pg.multivariate_normality).apply(pd.Series)\
.rename(columns={0: 'normal', 1: 'p'})
else:
# We would want to minimize type II error rate, risk of not rejecting the null when it's false.
res = df.groupby(['user', 'block'])[columns].apply(pg.normality).unstack(level=2) # Shapiro-Wilk tests.
return res
def mixed_anova_synergy_index_z(dataframe):
""" 3 x (3) Two-way split-plot ANOVA with between-factor condition and within-factor block.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index.
:type dataframe: pandas.DataFrame
:return: mixed-design ANOVA results.
:rtype: pandas.DataFrame
"""
if dataframe['condition'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 condition, run ANOVA with one within factor instead.
if dataframe['block'].nunique() <= 1:
raise ValueError("ERROR: Between factor has insufficient number of levels.")
#ToDo: If there's only 1 block, run ANOVA with one between factor instead.
aov = pg.mixed_anova(data=dataframe, dv='dVz', within='block', subject='user', between='condition', correction=True)
return aov
def posthoc_ttests(dataframe, var_='dVz'):
""" Pairwise posthoc t-tests on a variable in a mixed design. Between factor is 'condition', within factor is
'block'.
:param dataframe: Aggregated data containing Fisher-z-transformed synergy index in long format.
:type dataframe: pandas.DataFrame
:param var_: The variable which to test. One of the column names in dataframe.
:type var_: str
:return: Pairwise T-tests results.
:rtype: pandas.DataFrame
"""
posthocs = pg.pairwise_ttests(data=dataframe, dv=var_, within='block', subject='user', between='condition',
alpha=0.05, within_first=False,
padjust='fdr_by', marginal=True, return_desc=True, tail='one-sided', parametric=True)
return posthocs
| get_pca_vectors | identifier_name |
system_information.rs | use crate::{SMBiosStruct, UndefinedStruct};
use serde::{ser::SerializeStruct, Serialize, Serializer};
use core::{
array::TryFromSliceError,
convert::{TryFrom, TryInto},
fmt,
ops::Deref,
any
};
#[cfg(feature = "no_std")]
use alloc::{string::String, format};
/// # System Information (Type 1)
///
/// The information in this structure defines attributes of the overall system and is intended to be associated
/// with the Component ID group of the system’s MIF. An SMBIOS implementation is associated with a single
/// system instance and contains one and only one System Information (Type 1) structure.
///
/// Compliant with:
/// DMTF SMBIOS Reference Specification 3.4.0 (DSP0134)
/// Document Date: 2020-07-17
pub struct SMBiosSystemInformation<'a> {
parts: &'a UndefinedStruct,
}
impl<'a> SMBiosStruct<'a> for SMBiosSystemInformation<'a> {
const STRUCT_TYPE: u8 = 1u8;
fn new(parts: &'a UndefinedStruct) -> Self {
| fn parts(&self) -> &'a UndefinedStruct {
self.parts
}
}
impl<'a> SMBiosSystemInformation<'a> {
/// Manufacturer
pub fn manufacturer(&self) -> Option<String> {
self.parts.get_field_string(0x04)
}
/// Product name
pub fn product_name(&self) -> Option<String> {
self.parts.get_field_string(0x05)
}
/// Version
pub fn version(&self) -> Option<String> {
self.parts.get_field_string(0x06)
}
/// Serial number
pub fn serial_number(&self) -> Option<String> {
self.parts.get_field_string(0x07)
}
/// System UUID
pub fn uuid(&self) -> Option<SystemUuidData> {
self.parts
.get_field_data(0x08, 0x18)
.map(|raw| SystemUuidData::try_from(raw).expect("A GUID is 0x10 bytes"))
}
/// Wake-up type
///
/// Identifies the event that caused the system to power up.
pub fn wakeup_type(&self) -> Option<SystemWakeUpTypeData> {
self.parts
.get_field_byte(0x18)
.map(|raw| SystemWakeUpTypeData::from(raw))
}
/// SKU Number
///
/// This text string identifies a particular computer
/// configuration for sale. It is sometimes also
/// called a product ID or purchase order number.
/// This number is frequently found in existing
/// fields, but there is no standard format.
/// Typically for a given system board from a
/// given OEM, there are tens of unique
/// processor, memory, hard drive, and optical
/// drive configurations.
pub fn sku_number(&self) -> Option<String> {
self.parts.get_field_string(0x19)
}
/// Family
///
/// This text string identifies the family to which a
/// particular computer belongs. A family refers to
/// a set of computers that are similar but not
/// identical from a hardware or software point of
/// view. Typically, a family is composed of
/// different computer models, which have
/// different configurations and pricing points.
/// Computers in the same family often have
/// similar branding and cosmetic features.
pub fn family(&self) -> Option<String> {
self.parts.get_field_string(0x1A)
}
}
impl fmt::Debug for SMBiosSystemInformation<'_> {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SMBiosSystemInformation<'_>>())
.field("header", &self.parts.header)
.field("manufacturer", &self.manufacturer())
.field("product_name", &self.product_name())
.field("version", &self.version())
.field("serial_number", &self.serial_number())
.field("uuid", &self.uuid())
.field("wakeup_type", &self.wakeup_type())
.field("sku_number", &self.sku_number())
.field("family", &self.family())
.finish()
}
}
impl Serialize for SMBiosSystemInformation<'_> {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SMBiosSystemInformation", 9)?;
state.serialize_field("header", &self.parts.header)?;
state.serialize_field("manufacturer", &self.manufacturer())?;
state.serialize_field("product_name", &self.product_name())?;
state.serialize_field("version", &self.version())?;
state.serialize_field("serial_number", &self.serial_number())?;
state.serialize_field("uuid", &self.uuid())?;
state.serialize_field("wakeup_type", &self.wakeup_type())?;
state.serialize_field("sku_number", &self.sku_number())?;
state.serialize_field("family", &self.family())?;
state.end()
}
}
/// # System - UUID Data
#[derive(Serialize, Debug)]
pub enum SystemUuidData {
/// The ID is not currently present in the system, but it can be set
IdNotPresentButSettable,
/// The ID is not present in the system
IdNotPresent,
/// System UUID
Uuid(SystemUuid),
}
impl SystemUuidData {
fn new<'a>(array: &'a [u8; 0x10]) -> SystemUuidData {
if array.iter().all(|&x| x == 0) {
SystemUuidData::IdNotPresentButSettable
} else if array.iter().all(|&x| x == 0xFF) {
SystemUuidData::IdNotPresent
} else {
SystemUuidData::Uuid(SystemUuid::from(array))
}
}
}
impl<'a> TryFrom<&'a [u8]> for SystemUuidData {
type Error = TryFromSliceError;
fn try_from(raw: &'a [u8]) -> Result<Self, Self::Error> {
<&[u8; 0x10]>::try_from(raw).and_then(|array| Ok(SystemUuidData::new(array)))
}
}
impl fmt::Display for SystemUuidData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &*self {
SystemUuidData::IdNotPresent => write!(f, "IdNotPresent"),
SystemUuidData::IdNotPresentButSettable => write!(f, "IdNotPresentButSettable"),
SystemUuidData::Uuid(_system_uuid) => write!(f, "{}", &_system_uuid),
}
}
}
/// # System - UUID
#[derive(PartialEq, Eq)]
pub struct SystemUuid {
/// Raw byte array for this UUID
pub raw: [u8; 0x10],
}
impl SystemUuid {
/// Low field of the timestamp
pub fn time_low(&self) -> u32 {
u32::from_le_bytes(self.raw[..0x4].try_into().expect("incorrect size"))
}
/// Middle field of the timestamp
pub fn time_mid(&self) -> u16 {
u16::from_le_bytes(self.raw[0x4..0x6].try_into().expect("incorrect size"))
}
/// High field of the timestamp multiplexed with the version number
pub fn time_high_and_version(&self) -> u16 {
u16::from_le_bytes(self.raw[0x6..0x8].try_into().expect("incorrect size"))
}
/// High field of the clock sequence multiplexed with the variant
pub fn clock_seq_high_and_reserved(&self) -> u8 {
self.raw[0x8]
}
/// Low field of the clock sequence
pub fn clock_seq_low(&self) -> u8 {
self.raw[0x9]
}
/// Spatially unique node identifier
pub fn node(&self) -> &[u8; 6] {
self.raw[0xA..0x10].try_into().expect("incorrect size")
}
}
impl<'a> From<&'a [u8; 0x10]> for SystemUuid {
fn from(raw: &'a [u8; 0x10]) -> Self {
SystemUuid { raw: raw.clone() }
}
}
impl fmt::Display for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
// Example output:
// "00360FE7-D4D5-11E5-9C43-BC0000F00000"
// <TimeLow>-<TimeMid>-<TimeHiAndVersion>-<ClockSeqHiAndReserved><ClockSeqLow>-<Node[6]>
write!(
f,
"{:08X}-{:04X}-{:04X}-{:02X}{:02X}-",
self.time_low(),
self.time_mid(),
self.time_high_and_version(),
self.clock_seq_high_and_reserved(),
self.clock_seq_low()
)?;
self.node().iter().fold(Ok(()), |result, node_byte| {
result.and_then(|_| write!(f, "{:02X}", node_byte))
})
}
}
impl fmt::Debug for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "{}", &self)
}
}
impl Serialize for SystemUuid {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
serializer.serialize_str(format!("{}", self).as_str())
}
}
/// # System - Wake-up Type Data
pub struct SystemWakeUpTypeData {
/// Raw value
///
/// _raw_ is most useful when _value_ is None.
/// This is most likely to occur when the standard was updated but
/// this library code has not been updated to match the current
/// standard.
pub raw: u8,
/// The contained [SystemWakeUpType] value
pub value: SystemWakeUpType,
}
impl fmt::Debug for SystemWakeUpTypeData {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SystemWakeUpTypeData>())
.field("raw", &self.raw)
.field("value", &self.value)
.finish()
}
}
impl Serialize for SystemWakeUpTypeData {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SystemWakeUpTypeData", 2)?;
state.serialize_field("raw", &self.raw)?;
state.serialize_field("value", &self.value)?;
state.end()
}
}
impl fmt::Display for SystemWakeUpTypeData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &self.value {
SystemWakeUpType::None => write!(f, "{}", &self.raw),
_ => write!(f, "{:?}", &self.value),
}
}
}
impl Deref for SystemWakeUpTypeData {
type Target = SystemWakeUpType;
fn deref(&self) -> &Self::Target {
&self.value
}
}
/// # System - Wake-up Type
#[derive(Serialize, Debug, PartialEq, Eq)]
pub enum SystemWakeUpType {
/// Other
Other,
/// Unknown
Unknown,
/// APM Timer
ApmTimer,
/// Modem Ring
ModernRing,
/// LAN Remote
LanRemote,
/// Power Switch
PowerSwitch,
/// PCI PME#
PciPme,
/// AC Power Restored
ACPowerRestored,
/// A value unknown to this standard, check the raw value
None,
}
impl From<u8> for SystemWakeUpTypeData {
fn from(raw: u8) -> Self {
SystemWakeUpTypeData {
value: match raw {
0x01 => SystemWakeUpType::Other,
0x02 => SystemWakeUpType::Unknown,
0x03 => SystemWakeUpType::ApmTimer,
0x04 => SystemWakeUpType::ModernRing,
0x05 => SystemWakeUpType::LanRemote,
0x06 => SystemWakeUpType::PowerSwitch,
0x07 => SystemWakeUpType::PciPme,
0x08 => SystemWakeUpType::ACPowerRestored,
_ => SystemWakeUpType::None,
},
raw,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn unit_test() {
let struct_type1 = vec![
0x01, 0x1B, 0x01, 0x00, 0x01, 0x02, 0x03, 0x04, 0xD2, 0x01, 0x25, 0x3E, 0x48, 0xE6,
0x11, 0xE8, 0xBA, 0xD3, 0x70, 0x20, 0x84, 0x0F, 0x9D, 0x47, 0x06, 0x05, 0x06, b'L',
b'E', b'N', b'O', b'V', b'O', 0x00, b'3', b'0', b'B', b'F', b'S', b'0', b'7', b'5',
b'0', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o',
b'n', b' ', b'P', b'5', b'2', b'0', 0x00, b'M', b'N', b'0', b'6', b'P', b'Q', b'R',
b'S', 0x00, b'L', b'E', b'N', b'O', b'V', b'O', b'_', b'M', b'T', b'_', b'3', b'0',
b'B', b'F', b'_', b'B', b'U', b'_', b'T', b'h', b'i', b'n', b'k', b'_', b'F', b'M',
b'_', b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o', b'n', b' ',
b'P', b'5', b'2', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't',
b'i', b'o', b'n', b' ', b'P', b'5', b'2', b'0', 0x00, 0x00,
];
let parts = UndefinedStruct::new(&struct_type1);
let test_struct = SMBiosSystemInformation::new(&parts);
assert_eq!(test_struct.manufacturer(), Some("LENOVO".to_string()));
assert_eq!(test_struct.product_name(), Some("30BFS07500".to_string()));
assert_eq!(test_struct.version(), Some("ThinkStation P520".to_string()));
assert_eq!(test_struct.serial_number(), Some("MN06PQRS".to_string()));
assert_eq!(
format!("{:?}", test_struct.uuid()),
"Some(Uuid(3E2501D2-E648-E811-BAD3-7020840F9D47))".to_string()
);
assert_eq!(
*test_struct.wakeup_type().unwrap(),
SystemWakeUpType::PowerSwitch
);
assert_eq!(
test_struct.sku_number(),
Some("LENOVO_MT_30BF_BU_Think_FM_ThinkStation P520".to_string())
);
assert_eq!(test_struct.family(), Some("ThinkStation P520".to_string()));
}
}
| Self { parts }
}
| identifier_body |
system_information.rs | use crate::{SMBiosStruct, UndefinedStruct};
use serde::{ser::SerializeStruct, Serialize, Serializer};
use core::{
array::TryFromSliceError,
convert::{TryFrom, TryInto},
fmt,
ops::Deref,
any
};
#[cfg(feature = "no_std")]
use alloc::{string::String, format};
/// # System Information (Type 1)
///
/// The information in this structure defines attributes of the overall system and is intended to be associated
/// with the Component ID group of the system’s MIF. An SMBIOS implementation is associated with a single
/// system instance and contains one and only one System Information (Type 1) structure.
///
/// Compliant with:
/// DMTF SMBIOS Reference Specification 3.4.0 (DSP0134)
/// Document Date: 2020-07-17
pub struct SMBiosSystemInformation<'a> {
parts: &'a UndefinedStruct,
}
impl<'a> SMBiosStruct<'a> for SMBiosSystemInformation<'a> {
const STRUCT_TYPE: u8 = 1u8;
fn new(parts: &'a UndefinedStruct) -> Self {
Self { parts }
}
fn parts(&self) -> &'a UndefinedStruct {
self.parts
}
}
impl<'a> SMBiosSystemInformation<'a> {
/// Manufacturer
pub fn manufacturer(&self) -> Option<String> {
self.parts.get_field_string(0x04)
}
/// Product name
pub fn product_name(&self) -> Option<String> {
self.parts.get_field_string(0x05)
}
/// Version
pub fn version(&self) -> Option<String> {
self.parts.get_field_string(0x06)
}
/// Serial number
pub fn serial_number(&self) -> Option<String> {
self.parts.get_field_string(0x07)
}
/// System UUID
pub fn uuid(&self) -> Option<SystemUuidData> {
self.parts
.get_field_data(0x08, 0x18)
.map(|raw| SystemUuidData::try_from(raw).expect("A GUID is 0x10 bytes"))
}
/// Wake-up type
///
/// Identifies the event that caused the system to power up.
pub fn wakeup_type(&self) -> Option<SystemWakeUpTypeData> {
self.parts
.get_field_byte(0x18)
.map(|raw| SystemWakeUpTypeData::from(raw))
}
/// SKU Number
///
/// This text string identifies a particular computer
/// configuration for sale. It is sometimes also
/// called a product ID or purchase order number.
/// This number is frequently found in existing
/// fields, but there is no standard format.
/// Typically for a given system board from a
/// given OEM, there are tens of unique
/// processor, memory, hard drive, and optical
/// drive configurations.
pub fn sku_number(&self) -> Option<String> {
self.parts.get_field_string(0x19)
}
/// Family
///
/// This text string identifies the family to which a
/// particular computer belongs. A family refers to
/// a set of computers that are similar but not
/// identical from a hardware or software point of
/// view. Typically, a family is composed of
/// different computer models, which have
/// different configurations and pricing points.
/// Computers in the same family often have
/// similar branding and cosmetic features.
pub fn family(&self) -> Option<String> {
self.parts.get_field_string(0x1A)
}
}
impl fmt::Debug for SMBiosSystemInformation<'_> {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SMBiosSystemInformation<'_>>())
.field("header", &self.parts.header)
.field("manufacturer", &self.manufacturer())
.field("product_name", &self.product_name())
.field("version", &self.version())
.field("serial_number", &self.serial_number())
.field("uuid", &self.uuid())
.field("wakeup_type", &self.wakeup_type())
.field("sku_number", &self.sku_number())
.field("family", &self.family())
.finish()
}
}
impl Serialize for SMBiosSystemInformation<'_> {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SMBiosSystemInformation", 9)?;
state.serialize_field("header", &self.parts.header)?;
state.serialize_field("manufacturer", &self.manufacturer())?;
state.serialize_field("product_name", &self.product_name())?;
state.serialize_field("version", &self.version())?;
state.serialize_field("serial_number", &self.serial_number())?;
state.serialize_field("uuid", &self.uuid())?;
state.serialize_field("wakeup_type", &self.wakeup_type())?;
state.serialize_field("sku_number", &self.sku_number())?;
state.serialize_field("family", &self.family())?;
state.end()
}
}
/// # System - UUID Data
#[derive(Serialize, Debug)]
pub enum SystemUuidData {
/// The ID is not currently present in the system, but it can be set
IdNotPresentButSettable,
/// The ID is not present in the system
IdNotPresent,
/// System UUID
Uuid(SystemUuid),
}
impl SystemUuidData {
fn new<'a>(array: &'a [u8; 0x10]) -> SystemUuidData {
if array.iter().all(|&x| x == 0) {
SystemUuidData::IdNotPresentButSettable
} else if array.iter().all(|&x| x == 0xFF) {
SystemUuidData::IdNotPresent
} else {
SystemUuidData::Uuid(SystemUuid::from(array))
}
}
}
impl<'a> TryFrom<&'a [u8]> for SystemUuidData {
type Error = TryFromSliceError;
fn try_from(raw: &'a [u8]) -> Result<Self, Self::Error> {
<&[u8; 0x10]>::try_from(raw).and_then(|array| Ok(SystemUuidData::new(array)))
}
}
impl fmt::Display for SystemUuidData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &*self {
SystemUuidData::IdNotPresent => write!(f, "IdNotPresent"),
SystemUuidData::IdNotPresentButSettable => write!(f, "IdNotPresentButSettable"),
SystemUuidData::Uuid(_system_uuid) => write!(f, "{}", &_system_uuid),
}
}
}
/// # System - UUID
#[derive(PartialEq, Eq)]
pub struct SystemUuid {
/// Raw byte array for this UUID
pub raw: [u8; 0x10],
}
impl SystemUuid {
/// Low field of the timestamp
pub fn time_low(&self) -> u32 {
u32::from_le_bytes(self.raw[..0x4].try_into().expect("incorrect size"))
}
/// Middle field of the timestamp
pub fn time_mid(&self) -> u16 {
u16::from_le_bytes(self.raw[0x4..0x6].try_into().expect("incorrect size"))
}
/// High field of the timestamp multiplexed with the version number
pub fn time_high_and_version(&self) -> u16 {
u16::from_le_bytes(self.raw[0x6..0x8].try_into().expect("incorrect size"))
}
/// High field of the clock sequence multiplexed with the variant
pub fn clock_seq_high_and_reserved(&self) -> u8 {
self.raw[0x8]
}
/// Low field of the clock sequence
pub fn clock_seq_low(&self) -> u8 {
self.raw[0x9]
}
/// Spatially unique node identifier
pub fn node(&self) -> &[u8; 6] {
self.raw[0xA..0x10].try_into().expect("incorrect size")
}
}
impl<'a> From<&'a [u8; 0x10]> for SystemUuid {
fn from(raw: &'a [u8; 0x10]) -> Self {
SystemUuid { raw: raw.clone() }
}
}
impl fmt::Display for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
// Example output:
// "00360FE7-D4D5-11E5-9C43-BC0000F00000"
// <TimeLow>-<TimeMid>-<TimeHiAndVersion>-<ClockSeqHiAndReserved><ClockSeqLow>-<Node[6]>
write!(
f,
"{:08X}-{:04X}-{:04X}-{:02X}{:02X}-",
self.time_low(),
self.time_mid(),
self.time_high_and_version(),
self.clock_seq_high_and_reserved(),
self.clock_seq_low()
)?;
self.node().iter().fold(Ok(()), |result, node_byte| {
result.and_then(|_| write!(f, "{:02X}", node_byte))
})
}
}
impl fmt::Debug for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "{}", &self)
}
}
impl Serialize for SystemUuid {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
serializer.serialize_str(format!("{}", self).as_str())
}
} | /// Raw value
///
/// _raw_ is most useful when _value_ is None.
/// This is most likely to occur when the standard was updated but
/// this library code has not been updated to match the current
/// standard.
pub raw: u8,
/// The contained [SystemWakeUpType] value
pub value: SystemWakeUpType,
}
impl fmt::Debug for SystemWakeUpTypeData {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SystemWakeUpTypeData>())
.field("raw", &self.raw)
.field("value", &self.value)
.finish()
}
}
impl Serialize for SystemWakeUpTypeData {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SystemWakeUpTypeData", 2)?;
state.serialize_field("raw", &self.raw)?;
state.serialize_field("value", &self.value)?;
state.end()
}
}
impl fmt::Display for SystemWakeUpTypeData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &self.value {
SystemWakeUpType::None => write!(f, "{}", &self.raw),
_ => write!(f, "{:?}", &self.value),
}
}
}
impl Deref for SystemWakeUpTypeData {
type Target = SystemWakeUpType;
fn deref(&self) -> &Self::Target {
&self.value
}
}
/// # System - Wake-up Type
#[derive(Serialize, Debug, PartialEq, Eq)]
pub enum SystemWakeUpType {
/// Other
Other,
/// Unknown
Unknown,
/// APM Timer
ApmTimer,
/// Modem Ring
ModernRing,
/// LAN Remote
LanRemote,
/// Power Switch
PowerSwitch,
/// PCI PME#
PciPme,
/// AC Power Restored
ACPowerRestored,
/// A value unknown to this standard, check the raw value
None,
}
impl From<u8> for SystemWakeUpTypeData {
fn from(raw: u8) -> Self {
SystemWakeUpTypeData {
value: match raw {
0x01 => SystemWakeUpType::Other,
0x02 => SystemWakeUpType::Unknown,
0x03 => SystemWakeUpType::ApmTimer,
0x04 => SystemWakeUpType::ModernRing,
0x05 => SystemWakeUpType::LanRemote,
0x06 => SystemWakeUpType::PowerSwitch,
0x07 => SystemWakeUpType::PciPme,
0x08 => SystemWakeUpType::ACPowerRestored,
_ => SystemWakeUpType::None,
},
raw,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn unit_test() {
let struct_type1 = vec![
0x01, 0x1B, 0x01, 0x00, 0x01, 0x02, 0x03, 0x04, 0xD2, 0x01, 0x25, 0x3E, 0x48, 0xE6,
0x11, 0xE8, 0xBA, 0xD3, 0x70, 0x20, 0x84, 0x0F, 0x9D, 0x47, 0x06, 0x05, 0x06, b'L',
b'E', b'N', b'O', b'V', b'O', 0x00, b'3', b'0', b'B', b'F', b'S', b'0', b'7', b'5',
b'0', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o',
b'n', b' ', b'P', b'5', b'2', b'0', 0x00, b'M', b'N', b'0', b'6', b'P', b'Q', b'R',
b'S', 0x00, b'L', b'E', b'N', b'O', b'V', b'O', b'_', b'M', b'T', b'_', b'3', b'0',
b'B', b'F', b'_', b'B', b'U', b'_', b'T', b'h', b'i', b'n', b'k', b'_', b'F', b'M',
b'_', b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o', b'n', b' ',
b'P', b'5', b'2', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't',
b'i', b'o', b'n', b' ', b'P', b'5', b'2', b'0', 0x00, 0x00,
];
let parts = UndefinedStruct::new(&struct_type1);
let test_struct = SMBiosSystemInformation::new(&parts);
assert_eq!(test_struct.manufacturer(), Some("LENOVO".to_string()));
assert_eq!(test_struct.product_name(), Some("30BFS07500".to_string()));
assert_eq!(test_struct.version(), Some("ThinkStation P520".to_string()));
assert_eq!(test_struct.serial_number(), Some("MN06PQRS".to_string()));
assert_eq!(
format!("{:?}", test_struct.uuid()),
"Some(Uuid(3E2501D2-E648-E811-BAD3-7020840F9D47))".to_string()
);
assert_eq!(
*test_struct.wakeup_type().unwrap(),
SystemWakeUpType::PowerSwitch
);
assert_eq!(
test_struct.sku_number(),
Some("LENOVO_MT_30BF_BU_Think_FM_ThinkStation P520".to_string())
);
assert_eq!(test_struct.family(), Some("ThinkStation P520".to_string()));
}
} |
/// # System - Wake-up Type Data
pub struct SystemWakeUpTypeData { | random_line_split |
system_information.rs | use crate::{SMBiosStruct, UndefinedStruct};
use serde::{ser::SerializeStruct, Serialize, Serializer};
use core::{
array::TryFromSliceError,
convert::{TryFrom, TryInto},
fmt,
ops::Deref,
any
};
#[cfg(feature = "no_std")]
use alloc::{string::String, format};
/// # System Information (Type 1)
///
/// The information in this structure defines attributes of the overall system and is intended to be associated
/// with the Component ID group of the system’s MIF. An SMBIOS implementation is associated with a single
/// system instance and contains one and only one System Information (Type 1) structure.
///
/// Compliant with:
/// DMTF SMBIOS Reference Specification 3.4.0 (DSP0134)
/// Document Date: 2020-07-17
pub struct SMBiosSystemInformation<'a> {
parts: &'a UndefinedStruct,
}
impl<'a> SMBiosStruct<'a> for SMBiosSystemInformation<'a> {
const STRUCT_TYPE: u8 = 1u8;
fn new(parts: &'a UndefinedStruct) -> Self {
Self { parts }
}
fn parts(&self) -> &'a UndefinedStruct {
self.parts
}
}
impl<'a> SMBiosSystemInformation<'a> {
/// Manufacturer
pub fn manufacturer(&self) -> Option<String> {
self.parts.get_field_string(0x04)
}
/// Product name
pub fn product_name(&self) -> Option<String> {
self.parts.get_field_string(0x05)
}
/// Version
pub fn version(&self) -> Option<String> {
self.parts.get_field_string(0x06)
}
/// Serial number
pub fn serial_number(&self) -> Option<String> {
self.parts.get_field_string(0x07)
}
/// System UUID
pub fn uuid(&self) -> Option<SystemUuidData> {
self.parts
.get_field_data(0x08, 0x18)
.map(|raw| SystemUuidData::try_from(raw).expect("A GUID is 0x10 bytes"))
}
/// Wake-up type
///
/// Identifies the event that caused the system to power up.
pub fn wakeup_type(&self) -> Option<SystemWakeUpTypeData> {
self.parts
.get_field_byte(0x18)
.map(|raw| SystemWakeUpTypeData::from(raw))
}
/// SKU Number
///
/// This text string identifies a particular computer
/// configuration for sale. It is sometimes also
/// called a product ID or purchase order number.
/// This number is frequently found in existing
/// fields, but there is no standard format.
/// Typically for a given system board from a
/// given OEM, there are tens of unique
/// processor, memory, hard drive, and optical
/// drive configurations.
pub fn sku_number(&self) -> Option<String> {
self.parts.get_field_string(0x19)
}
/// Family
///
/// This text string identifies the family to which a
/// particular computer belongs. A family refers to
/// a set of computers that are similar but not
/// identical from a hardware or software point of
/// view. Typically, a family is composed of
/// different computer models, which have
/// different configurations and pricing points.
/// Computers in the same family often have
/// similar branding and cosmetic features.
pub fn family(&self) -> Option<String> {
self.parts.get_field_string(0x1A)
}
}
impl fmt::Debug for SMBiosSystemInformation<'_> {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SMBiosSystemInformation<'_>>())
.field("header", &self.parts.header)
.field("manufacturer", &self.manufacturer())
.field("product_name", &self.product_name())
.field("version", &self.version())
.field("serial_number", &self.serial_number())
.field("uuid", &self.uuid())
.field("wakeup_type", &self.wakeup_type())
.field("sku_number", &self.sku_number())
.field("family", &self.family())
.finish()
}
}
impl Serialize for SMBiosSystemInformation<'_> {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SMBiosSystemInformation", 9)?;
state.serialize_field("header", &self.parts.header)?;
state.serialize_field("manufacturer", &self.manufacturer())?;
state.serialize_field("product_name", &self.product_name())?;
state.serialize_field("version", &self.version())?;
state.serialize_field("serial_number", &self.serial_number())?;
state.serialize_field("uuid", &self.uuid())?;
state.serialize_field("wakeup_type", &self.wakeup_type())?;
state.serialize_field("sku_number", &self.sku_number())?;
state.serialize_field("family", &self.family())?;
state.end()
}
}
/// # System - UUID Data
#[derive(Serialize, Debug)]
pub enum SystemUuidData {
/// The ID is not currently present in the system, but it can be set
IdNotPresentButSettable,
/// The ID is not present in the system
IdNotPresent,
/// System UUID
Uuid(SystemUuid),
}
impl SystemUuidData {
fn new<'a>(array: &'a [u8; 0x10]) -> SystemUuidData {
if array.iter().all(|&x| x == 0) {
SystemUuidData::IdNotPresentButSettable
} else if array.iter().all(|&x| x == 0xFF) {
SystemUuidData::IdNotPresent
} else {
SystemUuidData::Uuid(SystemUuid::from(array))
}
}
}
impl<'a> TryFrom<&'a [u8]> for SystemUuidData {
type Error = TryFromSliceError;
fn try_from(raw: &'a [u8]) -> Result<Self, Self::Error> {
<&[u8; 0x10]>::try_from(raw).and_then(|array| Ok(SystemUuidData::new(array)))
}
}
impl fmt::Display for SystemUuidData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &*self {
SystemUuidData::IdNotPresent => write!(f, "IdNotPresent"),
SystemUuidData::IdNotPresentButSettable => write!(f, "IdNotPresentButSettable"),
SystemUuidData::Uuid(_system_uuid) => write!(f, "{}", &_system_uuid),
}
}
}
/// # System - UUID
#[derive(PartialEq, Eq)]
pub struct SystemUuid {
/// Raw byte array for this UUID
pub raw: [u8; 0x10],
}
impl SystemUuid {
/// Low field of the timestamp
pub fn time_low(&self) -> u32 {
u32::from_le_bytes(self.raw[..0x4].try_into().expect("incorrect size"))
}
/// Middle field of the timestamp
pub fn time_mid(&self) -> u16 {
u16::from_le_bytes(self.raw[0x4..0x6].try_into().expect("incorrect size"))
}
/// High field of the timestamp multiplexed with the version number
pub fn time_high_and_version(&self) -> u16 {
u16::from_le_bytes(self.raw[0x6..0x8].try_into().expect("incorrect size"))
}
/// High field of the clock sequence multiplexed with the variant
pub fn clock_seq_high_and_reserved(&self) -> u8 {
self.raw[0x8]
}
/// Low field of the clock sequence
pub fn clock_seq_low(&self) -> u8 {
self.raw[0x9]
}
/// Spatially unique node identifier
pub fn node(&self) -> &[u8; 6] {
self.raw[0xA..0x10].try_into().expect("incorrect size")
}
}
impl<'a> From<&'a [u8; 0x10]> for SystemUuid {
fn from(raw: &'a [u8; 0x10]) -> Self {
SystemUuid { raw: raw.clone() }
}
}
impl fmt::Display for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
// Example output:
// "00360FE7-D4D5-11E5-9C43-BC0000F00000"
// <TimeLow>-<TimeMid>-<TimeHiAndVersion>-<ClockSeqHiAndReserved><ClockSeqLow>-<Node[6]>
write!(
f,
"{:08X}-{:04X}-{:04X}-{:02X}{:02X}-",
self.time_low(),
self.time_mid(),
self.time_high_and_version(),
self.clock_seq_high_and_reserved(),
self.clock_seq_low()
)?;
self.node().iter().fold(Ok(()), |result, node_byte| {
result.and_then(|_| write!(f, "{:02X}", node_byte))
})
}
}
impl fmt::Debug for SystemUuid {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
write!(f, "{}", &self)
}
}
impl Serialize for SystemUuid {
fn se | >(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
serializer.serialize_str(format!("{}", self).as_str())
}
}
/// # System - Wake-up Type Data
pub struct SystemWakeUpTypeData {
/// Raw value
///
/// _raw_ is most useful when _value_ is None.
/// This is most likely to occur when the standard was updated but
/// this library code has not been updated to match the current
/// standard.
pub raw: u8,
/// The contained [SystemWakeUpType] value
pub value: SystemWakeUpType,
}
impl fmt::Debug for SystemWakeUpTypeData {
fn fmt(&self, fmt: &mut fmt::Formatter<'_>) -> fmt::Result {
fmt.debug_struct(any::type_name::<SystemWakeUpTypeData>())
.field("raw", &self.raw)
.field("value", &self.value)
.finish()
}
}
impl Serialize for SystemWakeUpTypeData {
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
{
let mut state = serializer.serialize_struct("SystemWakeUpTypeData", 2)?;
state.serialize_field("raw", &self.raw)?;
state.serialize_field("value", &self.value)?;
state.end()
}
}
impl fmt::Display for SystemWakeUpTypeData {
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
match &self.value {
SystemWakeUpType::None => write!(f, "{}", &self.raw),
_ => write!(f, "{:?}", &self.value),
}
}
}
impl Deref for SystemWakeUpTypeData {
type Target = SystemWakeUpType;
fn deref(&self) -> &Self::Target {
&self.value
}
}
/// # System - Wake-up Type
#[derive(Serialize, Debug, PartialEq, Eq)]
pub enum SystemWakeUpType {
/// Other
Other,
/// Unknown
Unknown,
/// APM Timer
ApmTimer,
/// Modem Ring
ModernRing,
/// LAN Remote
LanRemote,
/// Power Switch
PowerSwitch,
/// PCI PME#
PciPme,
/// AC Power Restored
ACPowerRestored,
/// A value unknown to this standard, check the raw value
None,
}
impl From<u8> for SystemWakeUpTypeData {
fn from(raw: u8) -> Self {
SystemWakeUpTypeData {
value: match raw {
0x01 => SystemWakeUpType::Other,
0x02 => SystemWakeUpType::Unknown,
0x03 => SystemWakeUpType::ApmTimer,
0x04 => SystemWakeUpType::ModernRing,
0x05 => SystemWakeUpType::LanRemote,
0x06 => SystemWakeUpType::PowerSwitch,
0x07 => SystemWakeUpType::PciPme,
0x08 => SystemWakeUpType::ACPowerRestored,
_ => SystemWakeUpType::None,
},
raw,
}
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn unit_test() {
let struct_type1 = vec![
0x01, 0x1B, 0x01, 0x00, 0x01, 0x02, 0x03, 0x04, 0xD2, 0x01, 0x25, 0x3E, 0x48, 0xE6,
0x11, 0xE8, 0xBA, 0xD3, 0x70, 0x20, 0x84, 0x0F, 0x9D, 0x47, 0x06, 0x05, 0x06, b'L',
b'E', b'N', b'O', b'V', b'O', 0x00, b'3', b'0', b'B', b'F', b'S', b'0', b'7', b'5',
b'0', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o',
b'n', b' ', b'P', b'5', b'2', b'0', 0x00, b'M', b'N', b'0', b'6', b'P', b'Q', b'R',
b'S', 0x00, b'L', b'E', b'N', b'O', b'V', b'O', b'_', b'M', b'T', b'_', b'3', b'0',
b'B', b'F', b'_', b'B', b'U', b'_', b'T', b'h', b'i', b'n', b'k', b'_', b'F', b'M',
b'_', b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't', b'i', b'o', b'n', b' ',
b'P', b'5', b'2', b'0', 0x00, b'T', b'h', b'i', b'n', b'k', b'S', b't', b'a', b't',
b'i', b'o', b'n', b' ', b'P', b'5', b'2', b'0', 0x00, 0x00,
];
let parts = UndefinedStruct::new(&struct_type1);
let test_struct = SMBiosSystemInformation::new(&parts);
assert_eq!(test_struct.manufacturer(), Some("LENOVO".to_string()));
assert_eq!(test_struct.product_name(), Some("30BFS07500".to_string()));
assert_eq!(test_struct.version(), Some("ThinkStation P520".to_string()));
assert_eq!(test_struct.serial_number(), Some("MN06PQRS".to_string()));
assert_eq!(
format!("{:?}", test_struct.uuid()),
"Some(Uuid(3E2501D2-E648-E811-BAD3-7020840F9D47))".to_string()
);
assert_eq!(
*test_struct.wakeup_type().unwrap(),
SystemWakeUpType::PowerSwitch
);
assert_eq!(
test_struct.sku_number(),
Some("LENOVO_MT_30BF_BU_Think_FM_ThinkStation P520".to_string())
);
assert_eq!(test_struct.family(), Some("ThinkStation P520".to_string()));
}
}
| rialize<S | identifier_name |
loader.rs | extern crate xml;
use std;
use std::fs::File;
use std::path::{Path, PathBuf};
use std::ffi::OsStr;
use std::io::{BufReader, Cursor, Read};
use std::sync::mpsc::Sender;
use std::collections::HashMap;
use zip::read::{ZipArchive, ZipFile};
use loader::xml::reader::{EventReader, XmlEvent};
use rodio::source::Source;
use sdl2::rwops::RWops;
use sdl2::image::ImageRWops;
//use sdl2::surface::SurfaceContext;
use mp3::Mp3Decoder;
use songs::Song;
use surface::Surface;
use Result;
pub enum LoadStatus {
TotalSize(u64),
LoadSize(u64),
Done(ResPack),
}
// SDL2-rust implementation of surface isn't threadsafe for some reason
pub struct ResPack {
pub info: PackInfo,
pub images: Vec<ImageLoader>,
pub songs: Vec<Song>,
}
pub struct ImageLoader {
//data: SurfaceContext
pub name: String,
pub fullname: Option<String>,
pub data: Surface,
pub source: Option<String>,
pub source_other: Option<String>,
}
pub struct SongData {
pub name: String,
pub title: String,
pub source: Option<String>,
pub rhythm: Vec<char>,
pub buildup: Option<String>,
pub buildup_rhythm: Vec<char>,
}
impl ImageLoader {
fn new(name: &str, buffer: Surface) -> Self {
ImageLoader {
name: name.to_owned(),
data: buffer,
fullname: None,
source: None,
source_other: None,
}
}
fn add_data(&mut self, data: ImageData) {
self.fullname = data.fullname;
self.source = data.source;
self.source_other = data.source_other;
}
}
struct ImageData {
filename: String,
fullname: Option<String>,
source: Option<String>,
source_other: Option<String>,
// align
// frameDuration
}
#[derive(Debug, Default)]
pub struct PackInfo {
name: String,
author: Option<String>,
description: Option<String>,
link: Option<String>
}
impl PackInfo {
fn new(name: &str) -> Self {
PackInfo {
name: name.to_owned(),
..Default::default()
}
}
}
pub fn load_respack<T: AsRef<Path>>(path: T, tx: Sender<LoadStatus>) -> Result<()> {
let path = path.as_ref();
let f = File::open(path)?;
let total_size = f.metadata()?.len();
tx.send(LoadStatus::TotalSize(total_size))?;
let mut archive = ZipArchive::new(f)?;
let mut images: HashMap<String, ImageLoader> = HashMap::new();
let mut audio: HashMap<String, _> = HashMap::new();
let mut song_data = Vec::new();
let mut image_data = Vec::new();
let mut pack_info = PackInfo::new(path.file_stem().and_then(OsStr::to_str).unwrap_or("???"));
let mut loaded_size = 0;
for i in 0..archive.len() {
let mut file = archive.by_index(i)?;
let path: PathBuf = file.name().into();
let size = file.compressed_size();
let name: &str = path.file_stem().and_then(OsStr::to_str).ok_or_else(|| "Bad path")?;
match path.extension().and_then(OsStr::to_str) {
Some("png") => {
let surface = {
let mut buffer = Vec::with_capacity(file.size() as usize);
file.read_to_end(&mut buffer)?;
let rwops = RWops::from_bytes(&buffer[..])?;
let surface = rwops.load_png()?;
Surface::from_surface(surface)?
};
let image = ImageLoader::new(name, surface);
images.insert(name.to_owned(), image);
}
Some("mp3") => {
let mut data = Vec::with_capacity(file.size() as usize);
file.read_to_end(&mut data)?;
let decoder = Mp3Decoder::new(Cursor::new(data));
let source = (Box::new(decoder) as Box<Source<Item = i16> + Send>).buffered();
audio.insert(name.to_owned(), source);
}
Some("xml") => {
parse_xml(file, &mut song_data, &mut image_data, &mut pack_info);
}
Some("") => {},
_ => println!("{:?}", path),
}
tx.send(LoadStatus::LoadSize(size))?;
loaded_size += size;
}
// Leftovers
tx.send(LoadStatus::LoadSize(total_size - loaded_size))?;
// Process songs
let songs: Vec<Song> = song_data
.into_iter()
.filter_map(|data| Song::new(data, &mut audio).ok())
.collect();
if !audio.is_empty() {
println!("Warning: Unused audio data {:?}", audio.keys());
}
// Process images
for image in image_data.into_iter() {
if let Some(loader) = images.get_mut(&image.filename) {
loader.add_data(image);
} else {
println!("Warning: Could not find image {}", image.filename);
}
}
tx.send(LoadStatus::Done(ResPack {
info: pack_info,
images: images.into_iter().map(|(_k, v)| v).collect(),
songs,
}))?;
Ok(())
}
// XML
// tempted to try and write a macro to handle this
// maybe if it grows some more
enum State {
Document,
Songs,
Song(Option<SongField>),
Images,
Image(Option<ImageField>),
Info(Option<InfoField>),
}
#[derive(Copy, Clone, Debug)]
enum SongField {
Title,
Source,
Rhythm,
Buildup,
BuildupRhythm,
}
#[derive(Copy, Clone, Debug)]
enum ImageField {
Source,
SourceOther,
FullName,
Align,
FrameDuration, // TODO: handle animations
}
#[derive(Copy, Clone, Debug)]
enum InfoField {
Name,
Author,
Description,
Link,
}
// based off code from stebalien on rust-lang
// ok this got ugly, clean it up
fn parse_xml(file: ZipFile, songs: &mut Vec<SongData>, images: &mut Vec<ImageData>, pack_info: &mut PackInfo) {
let mut reader = EventReader::new(BufReader::new(file));
let mut state = State::Document;
let mut song_name = None;
let mut song_title = None;
let mut song_source = None;
let mut song_rhythm = Vec::new();
let mut song_buildup = None;
let mut song_buildup_rhythm = Vec::new();
let mut image_filename = None;
let mut image_name = None;
let mut image_source = None;
let mut image_source_other = None;
// TODO: handle smart align
//let mut image_align = None;
while let Ok(event) = reader.next() {
state = match state {
State::Document => match event {
XmlEvent::StartDocument { .. } => State::Document,
XmlEvent::StartElement { name, .. } => match name.local_name.as_ref() {
"info" => State::Info(None),
"songs" => State::Songs,
"images" => State::Images,
_ => {
println!("Unknown xml tag {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Document
}
},
XmlEvent::EndDocument => break,
_ => {
println!("Unexpected");
State::Document
}
},
State::Songs => match event {
XmlEvent::StartElement {
name, attributes, ..
} => {
if name.local_name != "song" {
panic!("Expected a song tag - got {}", name.local_name);
}
for attr in attributes.into_iter() {
if attr.name.local_name == "name" {
song_name = Some(attr.value);
break;
}
}
if song_name.is_none() {
panic!("Expected a song name");
}
State::Song(None)
}
XmlEvent::EndElement { .. } => State::Document,
XmlEvent::Whitespace(_) => State::Songs,
_ => {
println!("Expected a song tag - got {:?}", event);
State::Songs
}
},
State::Song(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"title" => State::Song(Some(SongField::Title)),
"source" => State::Song(Some(SongField::Source)),
"rhythm" => State::Song(Some(SongField::Rhythm)), | println!("Unknown song field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Song(None)
}
},
XmlEvent::EndElement { .. } => {
if song_rhythm.is_empty() {
// TODO: be graceful
panic!("Empty rhythm");
}
let song = SongData {
name: song_name.take().unwrap(),
title: song_title.take().unwrap(),
source: song_source.take(),
rhythm: std::mem::replace(&mut song_rhythm, Vec::new()),
buildup: song_buildup.take(),
buildup_rhythm: std::mem::replace(&mut song_buildup_rhythm, Vec::new()),
};
songs.push(song);
State::Songs
}
_ => State::Song(None),
},
State::Song(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
SongField::Title => song_title = Some(data),
SongField::Source => song_source = Some(data),
SongField::Rhythm => {
if !data.is_ascii() {
panic!("Expected ascii characters in rhythm");
}
song_rhythm = data.chars().collect();
}
SongField::Buildup => song_buildup = Some(data),
SongField::BuildupRhythm => {
if !data.is_ascii() {
panic!("Expected ascii characters in rhythm");
}
if data.is_empty() {
panic!("Buildup rhythm empty!");
}
song_buildup_rhythm = data.chars().collect();
}
}
State::Song(Some(field))
}
XmlEvent::EndElement { .. } => State::Song(None),
_ => panic!("Expected data for tag {:?}", field),
},
State::Images => match event {
XmlEvent::StartElement {
name, attributes, ..
} => {
if name.local_name != "image" {
panic!("Expected an image tag - got {}", name.local_name);
}
for attr in attributes.into_iter() {
if attr.name.local_name == "name" {
image_filename = Some(attr.value);
break;
}
}
if image_filename.is_none() {
panic!("Expected an image name");
}
State::Image(None)
}
XmlEvent::EndElement { .. } => State::Document,
XmlEvent::Whitespace(_) => State::Images,
_ => panic!("Expected an image tag - got {:?}", event),
},
State::Image(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"source" => State::Image(Some(ImageField::Source)),
"source_other" => State::Image(Some(ImageField::SourceOther)),
"fullname" => State::Image(Some(ImageField::FullName)),
"align" => State::Image(Some(ImageField::Align)),
"frameDuration" => State::Image(Some(ImageField::FrameDuration)),
_ => {
println!("Unknown image field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Image(None)
}
},
XmlEvent::EndElement { .. } => {
let image = ImageData {
filename: image_filename.take().unwrap(),
fullname: image_name.take(),
source: image_source.take(),
source_other: image_source_other.take(),
};
images.push(image);
State::Images
}
_ => State::Image(None),
},
State::Image(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
ImageField::Source => image_source = Some(data),
ImageField::SourceOther => image_source_other = Some(data),
ImageField::FullName => image_name = Some(data),
ImageField::Align => {}
ImageField::FrameDuration => {}
}
State::Image(Some(field))
}
XmlEvent::EndElement { .. } => State::Image(None),
_ => panic!("Expected data for tag {:?}", field),
},
State::Info(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"name" => State::Info(Some(InfoField::Name)),
"author" => State::Info(Some(InfoField::Author)),
"description" => State::Info(Some(InfoField::Description)),
"link" => State::Info(Some(InfoField::Link)),
_ => {
println!("Unknown info field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Info(None)
}
},
XmlEvent::EndElement { .. } => State::Document,
_ => State::Info(None),
},
State::Info(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
InfoField::Name => pack_info.name = data,
InfoField::Author => pack_info.author = Some(data),
InfoField::Description => pack_info.description = Some(data),
InfoField::Link => pack_info.link = Some(data),
}
State::Info(Some(field))
}
XmlEvent::EndElement { .. } => State::Info(None),
_ => {
println!("Expected data for tag {:?}", field);
State::Info(Some(field))
}
}
}
}
}
fn xml_skip_tag<R: Read>(reader: &mut EventReader<R>) -> Result<()> {
let mut depth = 1;
while depth > 0 {
match reader.next() {
Ok(XmlEvent::StartElement { .. }) => depth += 1,
Ok(XmlEvent::EndElement { .. }) => depth -= 1,
Ok(_event) => {}
_ => return Err("Unexpected event error".into()),
}
}
Ok(())
} | "buildup" => State::Song(Some(SongField::Buildup)),
"buildupRhythm" => State::Song(Some(SongField::BuildupRhythm)),
_ => { | random_line_split |
loader.rs | extern crate xml;
use std;
use std::fs::File;
use std::path::{Path, PathBuf};
use std::ffi::OsStr;
use std::io::{BufReader, Cursor, Read};
use std::sync::mpsc::Sender;
use std::collections::HashMap;
use zip::read::{ZipArchive, ZipFile};
use loader::xml::reader::{EventReader, XmlEvent};
use rodio::source::Source;
use sdl2::rwops::RWops;
use sdl2::image::ImageRWops;
//use sdl2::surface::SurfaceContext;
use mp3::Mp3Decoder;
use songs::Song;
use surface::Surface;
use Result;
pub enum LoadStatus {
TotalSize(u64),
LoadSize(u64),
Done(ResPack),
}
// SDL2-rust implementation of surface isn't threadsafe for some reason
pub struct | {
pub info: PackInfo,
pub images: Vec<ImageLoader>,
pub songs: Vec<Song>,
}
pub struct ImageLoader {
//data: SurfaceContext
pub name: String,
pub fullname: Option<String>,
pub data: Surface,
pub source: Option<String>,
pub source_other: Option<String>,
}
pub struct SongData {
pub name: String,
pub title: String,
pub source: Option<String>,
pub rhythm: Vec<char>,
pub buildup: Option<String>,
pub buildup_rhythm: Vec<char>,
}
impl ImageLoader {
fn new(name: &str, buffer: Surface) -> Self {
ImageLoader {
name: name.to_owned(),
data: buffer,
fullname: None,
source: None,
source_other: None,
}
}
fn add_data(&mut self, data: ImageData) {
self.fullname = data.fullname;
self.source = data.source;
self.source_other = data.source_other;
}
}
struct ImageData {
filename: String,
fullname: Option<String>,
source: Option<String>,
source_other: Option<String>,
// align
// frameDuration
}
#[derive(Debug, Default)]
pub struct PackInfo {
name: String,
author: Option<String>,
description: Option<String>,
link: Option<String>
}
impl PackInfo {
fn new(name: &str) -> Self {
PackInfo {
name: name.to_owned(),
..Default::default()
}
}
}
pub fn load_respack<T: AsRef<Path>>(path: T, tx: Sender<LoadStatus>) -> Result<()> {
let path = path.as_ref();
let f = File::open(path)?;
let total_size = f.metadata()?.len();
tx.send(LoadStatus::TotalSize(total_size))?;
let mut archive = ZipArchive::new(f)?;
let mut images: HashMap<String, ImageLoader> = HashMap::new();
let mut audio: HashMap<String, _> = HashMap::new();
let mut song_data = Vec::new();
let mut image_data = Vec::new();
let mut pack_info = PackInfo::new(path.file_stem().and_then(OsStr::to_str).unwrap_or("???"));
let mut loaded_size = 0;
for i in 0..archive.len() {
let mut file = archive.by_index(i)?;
let path: PathBuf = file.name().into();
let size = file.compressed_size();
let name: &str = path.file_stem().and_then(OsStr::to_str).ok_or_else(|| "Bad path")?;
match path.extension().and_then(OsStr::to_str) {
Some("png") => {
let surface = {
let mut buffer = Vec::with_capacity(file.size() as usize);
file.read_to_end(&mut buffer)?;
let rwops = RWops::from_bytes(&buffer[..])?;
let surface = rwops.load_png()?;
Surface::from_surface(surface)?
};
let image = ImageLoader::new(name, surface);
images.insert(name.to_owned(), image);
}
Some("mp3") => {
let mut data = Vec::with_capacity(file.size() as usize);
file.read_to_end(&mut data)?;
let decoder = Mp3Decoder::new(Cursor::new(data));
let source = (Box::new(decoder) as Box<Source<Item = i16> + Send>).buffered();
audio.insert(name.to_owned(), source);
}
Some("xml") => {
parse_xml(file, &mut song_data, &mut image_data, &mut pack_info);
}
Some("") => {},
_ => println!("{:?}", path),
}
tx.send(LoadStatus::LoadSize(size))?;
loaded_size += size;
}
// Leftovers
tx.send(LoadStatus::LoadSize(total_size - loaded_size))?;
// Process songs
let songs: Vec<Song> = song_data
.into_iter()
.filter_map(|data| Song::new(data, &mut audio).ok())
.collect();
if !audio.is_empty() {
println!("Warning: Unused audio data {:?}", audio.keys());
}
// Process images
for image in image_data.into_iter() {
if let Some(loader) = images.get_mut(&image.filename) {
loader.add_data(image);
} else {
println!("Warning: Could not find image {}", image.filename);
}
}
tx.send(LoadStatus::Done(ResPack {
info: pack_info,
images: images.into_iter().map(|(_k, v)| v).collect(),
songs,
}))?;
Ok(())
}
// XML
// tempted to try and write a macro to handle this
// maybe if it grows some more
enum State {
Document,
Songs,
Song(Option<SongField>),
Images,
Image(Option<ImageField>),
Info(Option<InfoField>),
}
#[derive(Copy, Clone, Debug)]
enum SongField {
Title,
Source,
Rhythm,
Buildup,
BuildupRhythm,
}
#[derive(Copy, Clone, Debug)]
enum ImageField {
Source,
SourceOther,
FullName,
Align,
FrameDuration, // TODO: handle animations
}
#[derive(Copy, Clone, Debug)]
enum InfoField {
Name,
Author,
Description,
Link,
}
// based off code from stebalien on rust-lang
// ok this got ugly, clean it up
fn parse_xml(file: ZipFile, songs: &mut Vec<SongData>, images: &mut Vec<ImageData>, pack_info: &mut PackInfo) {
let mut reader = EventReader::new(BufReader::new(file));
let mut state = State::Document;
let mut song_name = None;
let mut song_title = None;
let mut song_source = None;
let mut song_rhythm = Vec::new();
let mut song_buildup = None;
let mut song_buildup_rhythm = Vec::new();
let mut image_filename = None;
let mut image_name = None;
let mut image_source = None;
let mut image_source_other = None;
// TODO: handle smart align
//let mut image_align = None;
while let Ok(event) = reader.next() {
state = match state {
State::Document => match event {
XmlEvent::StartDocument { .. } => State::Document,
XmlEvent::StartElement { name, .. } => match name.local_name.as_ref() {
"info" => State::Info(None),
"songs" => State::Songs,
"images" => State::Images,
_ => {
println!("Unknown xml tag {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Document
}
},
XmlEvent::EndDocument => break,
_ => {
println!("Unexpected");
State::Document
}
},
State::Songs => match event {
XmlEvent::StartElement {
name, attributes, ..
} => {
if name.local_name != "song" {
panic!("Expected a song tag - got {}", name.local_name);
}
for attr in attributes.into_iter() {
if attr.name.local_name == "name" {
song_name = Some(attr.value);
break;
}
}
if song_name.is_none() {
panic!("Expected a song name");
}
State::Song(None)
}
XmlEvent::EndElement { .. } => State::Document,
XmlEvent::Whitespace(_) => State::Songs,
_ => {
println!("Expected a song tag - got {:?}", event);
State::Songs
}
},
State::Song(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"title" => State::Song(Some(SongField::Title)),
"source" => State::Song(Some(SongField::Source)),
"rhythm" => State::Song(Some(SongField::Rhythm)),
"buildup" => State::Song(Some(SongField::Buildup)),
"buildupRhythm" => State::Song(Some(SongField::BuildupRhythm)),
_ => {
println!("Unknown song field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Song(None)
}
},
XmlEvent::EndElement { .. } => {
if song_rhythm.is_empty() {
// TODO: be graceful
panic!("Empty rhythm");
}
let song = SongData {
name: song_name.take().unwrap(),
title: song_title.take().unwrap(),
source: song_source.take(),
rhythm: std::mem::replace(&mut song_rhythm, Vec::new()),
buildup: song_buildup.take(),
buildup_rhythm: std::mem::replace(&mut song_buildup_rhythm, Vec::new()),
};
songs.push(song);
State::Songs
}
_ => State::Song(None),
},
State::Song(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
SongField::Title => song_title = Some(data),
SongField::Source => song_source = Some(data),
SongField::Rhythm => {
if !data.is_ascii() {
panic!("Expected ascii characters in rhythm");
}
song_rhythm = data.chars().collect();
}
SongField::Buildup => song_buildup = Some(data),
SongField::BuildupRhythm => {
if !data.is_ascii() {
panic!("Expected ascii characters in rhythm");
}
if data.is_empty() {
panic!("Buildup rhythm empty!");
}
song_buildup_rhythm = data.chars().collect();
}
}
State::Song(Some(field))
}
XmlEvent::EndElement { .. } => State::Song(None),
_ => panic!("Expected data for tag {:?}", field),
},
State::Images => match event {
XmlEvent::StartElement {
name, attributes, ..
} => {
if name.local_name != "image" {
panic!("Expected an image tag - got {}", name.local_name);
}
for attr in attributes.into_iter() {
if attr.name.local_name == "name" {
image_filename = Some(attr.value);
break;
}
}
if image_filename.is_none() {
panic!("Expected an image name");
}
State::Image(None)
}
XmlEvent::EndElement { .. } => State::Document,
XmlEvent::Whitespace(_) => State::Images,
_ => panic!("Expected an image tag - got {:?}", event),
},
State::Image(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"source" => State::Image(Some(ImageField::Source)),
"source_other" => State::Image(Some(ImageField::SourceOther)),
"fullname" => State::Image(Some(ImageField::FullName)),
"align" => State::Image(Some(ImageField::Align)),
"frameDuration" => State::Image(Some(ImageField::FrameDuration)),
_ => {
println!("Unknown image field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Image(None)
}
},
XmlEvent::EndElement { .. } => {
let image = ImageData {
filename: image_filename.take().unwrap(),
fullname: image_name.take(),
source: image_source.take(),
source_other: image_source_other.take(),
};
images.push(image);
State::Images
}
_ => State::Image(None),
},
State::Image(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
ImageField::Source => image_source = Some(data),
ImageField::SourceOther => image_source_other = Some(data),
ImageField::FullName => image_name = Some(data),
ImageField::Align => {}
ImageField::FrameDuration => {}
}
State::Image(Some(field))
}
XmlEvent::EndElement { .. } => State::Image(None),
_ => panic!("Expected data for tag {:?}", field),
},
State::Info(None) => match event {
XmlEvent::StartElement { ref name, .. } => match name.local_name.as_ref() {
"name" => State::Info(Some(InfoField::Name)),
"author" => State::Info(Some(InfoField::Author)),
"description" => State::Info(Some(InfoField::Description)),
"link" => State::Info(Some(InfoField::Link)),
_ => {
println!("Unknown info field {}", name.local_name);
xml_skip_tag(&mut reader).unwrap();
State::Info(None)
}
},
XmlEvent::EndElement { .. } => State::Document,
_ => State::Info(None),
},
State::Info(Some(field)) => match event {
XmlEvent::Characters(data) => {
match field {
InfoField::Name => pack_info.name = data,
InfoField::Author => pack_info.author = Some(data),
InfoField::Description => pack_info.description = Some(data),
InfoField::Link => pack_info.link = Some(data),
}
State::Info(Some(field))
}
XmlEvent::EndElement { .. } => State::Info(None),
_ => {
println!("Expected data for tag {:?}", field);
State::Info(Some(field))
}
}
}
}
}
fn xml_skip_tag<R: Read>(reader: &mut EventReader<R>) -> Result<()> {
let mut depth = 1;
while depth > 0 {
match reader.next() {
Ok(XmlEvent::StartElement { .. }) => depth += 1,
Ok(XmlEvent::EndElement { .. }) => depth -= 1,
Ok(_event) => {}
_ => return Err("Unexpected event error".into()),
}
}
Ok(())
}
| ResPack | identifier_name |
lib.rs | ///////////////////////////////////////////////////////////////////////////////
//
// Copyright 2018-2021 Robonomics Network <research@robonomics.network>
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////////////
//! The Robonomics runtime module. This can be compiled with `#[no_std]`, ready for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
pub mod economics;
pub mod signed;
pub mod technics;
pub mod traits;
pub use pallet::*;
pub use signed::*;
pub use traits::*;
#[frame_support::pallet]
pub mod pallet {
use super::traits::*;
use frame_support::{dispatch, pallet_prelude::*};
use frame_system::pallet_prelude::*;
use sp_std::prelude::*;
#[pallet::config]
pub trait Config: frame_system::Config {
/// How to make and process agreement between two parties.
type Agreement: dispatch::Parameter + Processing + Agreement<Self::AccountId>;
/// How to report of agreement execution.
type Report: dispatch::Parameter + Report<Self::Index, Self::AccountId>;
/// The overarching event type.
type Event: From<Event<Self>> + IsType<<Self as frame_system::Config>::Event>;
}
pub type TechnicsFor<T> =
<<T as Config>::Agreement as Agreement<<T as frame_system::Config>::AccountId>>::Technical;
pub type EconomicsFor<T> =
<<T as Config>::Agreement as Agreement<<T as frame_system::Config>::AccountId>>::Economical;
pub type ReportFor<T> = <T as Config>::Report;
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event<T: Config> {
/// Yay! New liability created.
NewLiability(
T::Index,
TechnicsFor<T>,
EconomicsFor<T>,
T::AccountId,
T::AccountId,
),
/// Liability report published.
NewReport(T::Index, ReportFor<T>),
}
#[pallet::error]
pub enum Error<T> {
/// Agreement proof verification failed.
BadAgreementProof,
/// Report proof verification failed.
BadReportProof,
/// Wrong report sender account.
BadReportSender,
/// Liability already finalized.
AlreadyFinalized,
/// Real world oracle is not ready for this report.
OracleIsNotReady,
/// Unable to load agreement from storage.
AgreementNotFound,
}
#[pallet::storage]
#[pallet::getter(fn latest_index)]
/// [DEPRECATED] Latest liability index.
/// TODO: remove after mainnet upgrade
pub(super) type LatestIndex<T: Config> = StorageValue<_, T::Index>;
#[pallet::storage]
#[pallet::getter(fn next_index)]
/// Next liability index.
pub(super) type NextIndex<T: Config> = StorageValue<_, T::Index>;
#[pallet::storage]
#[pallet::getter(fn agreement_of)]
/// Technical and economical parameters of liability.
pub(super) type AgreementOf<T: Config> = StorageMap<_, Twox64Concat, T::Index, T::Agreement>;
#[pallet::storage]
#[pallet::getter(fn report_of)]
/// Result of liability execution.
pub(super) type ReportOf<T: Config> = StorageMap<_, Twox64Concat, T::Index, ReportFor<T>>;
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
// TODO: remove after mainnet upgrade
fn on_runtime_upgrade() -> Weight {
if <NextIndex<T>>::get().is_none() {
if let Some(index) = <LatestIndex<T>>::take() {
<NextIndex<T>>::put(index)
}
}
1
}
}
#[pallet::pallet]
#[pallet::generate_store(pub(super) trait Store)]
#[pallet::without_storage_info]
pub struct Pallet<T>(PhantomData<T>);
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Create agreement between two parties.
#[pallet::weight(200_000)]
pub fn create(origin: OriginFor<T>, agreement: T::Agreement) -> DispatchResultWithPostInfo {
let _ = ensure_signed(origin)?;
ensure!(agreement.verify(), Error::<T>::BadAgreementProof);
// Start agreement processing
agreement.on_start()?;
// Store agreement on storage
let next_index = <NextIndex<T>>::get().unwrap_or(Default::default());
<AgreementOf<T>>::insert(next_index, agreement.clone());
<NextIndex<T>>::put(next_index + 1u32.into());
// Emit event
Self::deposit_event(Event::NewLiability(
next_index,
agreement.technical(),
agreement.economical(),
agreement.promisee(),
agreement.promisor(),
));
Ok(().into())
}
/// Publish technical report of complite works.
#[pallet::weight(200_000)]
pub fn finalize(origin: OriginFor<T>, report: ReportFor<T>) -> DispatchResultWithPostInfo {
let _ = ensure_signed(origin)?;
// Check report proof
ensure!(report.verify(), Error::<T>::BadReportProof);
let index = report.index();
// Is liability already finalized?
ensure!(
<ReportOf<T>>::get(index) == None,
Error::<T>::AlreadyFinalized
);
// Decode agreement from storage
if let Some(agreement) = <AgreementOf<T>>::get(index) {
// Check report sender
ensure!(
report.sender() == agreement.promisor(),
Error::<T>::BadReportSender
);
// Run agreement final processing
match report.is_confirmed() {
None => Err(Error::<T>::OracleIsNotReady)?,
Some(x) => agreement.on_finish(x)?,
}
// Store report on storage
<ReportOf<T>>::insert(index, report.clone());
// Emit event
Self::deposit_event(Event::NewReport(index, report));
Ok(().into())
} else {
Err(Error::<T>::AgreementNotFound.into())
}
}
}
}
#[cfg(test)]
mod tests {
use crate::economics::SimpleMarket;
use crate::signed::*;
use crate::technics::IPFS;
use crate::traits::*;
use crate::{self as liability, *};
use frame_support::{assert_err, assert_ok, parameter_types};
use hex_literal::hex;
use sp_core::{crypto::Pair, sr25519, H256};
use sp_keyring::AccountKeyring;
use sp_runtime::{
testing::Header,
traits::{IdentifyAccount, IdentityLookup, Verify},
AccountId32, MultiSignature,
};
type UncheckedExtrinsic = frame_system::mocking::MockUncheckedExtrinsic<Runtime>;
type Block = frame_system::mocking::MockBlock<Runtime>;
type Balance = u128;
const XRT: Balance = 1_000_000_000;
frame_support::construct_runtime!(
pub enum Runtime where
Block = Block,
NodeBlock = Block,
UncheckedExtrinsic = UncheckedExtrinsic,
{
System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
Balances: pallet_balances::{Pallet, Call, Storage, Config<T>, Event<T>},
Liability: liability::{Pallet, Call, Storage, Event<T>},
}
);
parameter_types! {
pub const BlockHashCount: u64 = 250;
}
impl frame_system::Config for Runtime {
type Origin = Origin;
type Index = u64;
type BlockNumber = u64;
type Call = Call;
type Hash = H256;
type Hashing = ::sp_runtime::traits::BlakeTwo256;
type AccountId = AccountId32;
type Lookup = IdentityLookup<Self::AccountId>;
type Header = Header;
type Event = Event;
type BlockHashCount = BlockHashCount;
type Version = ();
type PalletInfo = PalletInfo;
type AccountData = pallet_balances::AccountData<Balance>;
type OnNewAccount = ();
type OnKilledAccount = ();
type DbWeight = ();
type BaseCallFilter = frame_support::traits::Everything;
type SystemWeightInfo = ();
type BlockWeights = ();
type BlockLength = ();
type SS58Prefix = ();
type OnSetCode = ();
type MaxConsumers = frame_support::traits::ConstU32<16>;
}
parameter_types! {
pub const MaxLocks: u32 = 50;
pub const MaxReserves: u32 = 50;
pub const ExistentialDeposit: Balance = 10;
}
impl pallet_balances::Config for Runtime {
type MaxLocks = MaxLocks;
type MaxReserves = MaxReserves;
type ReserveIdentifier = [u8; 8];
type Balance = Balance;
type Event = Event;
type DustRemoval = ();
type ExistentialDeposit = ExistentialDeposit;
type AccountStore = System;
type WeightInfo = ();
}
impl Config for Runtime {
type Event = Event;
type Agreement = SignedAgreement<
// Provide task in IPFS
IPFS,
// Liability has a price
SimpleMarket<Self::AccountId, Balances>,
// Use standard accounts
Self::AccountId,
// Use standard signatures
MultiSignature,
>;
type Report = SignedReport<
// Indexing liabilities using system index
Self::Index,
// Use standard accounts
Self::AccountId,
// Use standard signatures
MultiSignature,
// Provide report in IPFS
IPFS,
>;
}
// IPFS raw hash (sha256)
const IPFS_HASH: [u8; 32] =
hex!["30f3d649b3d140a6601e11a2cfbe3560e60dc5434f62d702ac8ceff4e1890015"];
fn new_test_ext() -> sp_io::TestExternalities {
let mut storage = frame_system::GenesisConfig::default()
.build_storage::<Runtime>()
.unwrap();
let _ = pallet_balances::GenesisConfig::<Runtime> {
balances: vec![
(AccountKeyring::Alice.into(), 100 * XRT),
(AccountKeyring::Bob.into(), 100 * XRT),
],
}
.assimilate_storage(&mut storage);
storage.into()
}
#[test]
fn test_initial_setup() {
new_test_ext().execute_with(|| {
assert_eq!(Liability::next_index(), None);
});
}
fn | (
uri: &str,
technics: &TechnicsFor<Runtime>,
economics: &EconomicsFor<Runtime>,
) -> (AccountId32, MultiSignature) {
let pair = sr25519::Pair::from_string(uri, None).unwrap();
let sender = <MultiSignature as Verify>::Signer::from(pair.public()).into_account();
let signature = <ProofSigner<_> as AgreementProofBuilder<_, _, _, _>>::proof(
technics, economics, &pair,
)
.into();
(sender, signature)
}
fn get_report_proof(uri: &str, index: &u64, message: &IPFS) -> (AccountId32, MultiSignature) {
let pair = sr25519::Pair::from_string(uri, None).unwrap();
let sender = <MultiSignature as Verify>::Signer::from(pair.public()).into_account();
let signature =
<ProofSigner<_> as ReportProofBuilder<_, _, _, _>>::proof(index, message, &pair).into();
(sender, signature)
}
#[test]
fn test_liability_proofs() {
let technics = IPFS {
hash: IPFS_HASH.into(),
};
let economics = SimpleMarket { price: 10 };
let (sender, signature) = get_params_proof("//Alice", &technics, &economics);
let agreement: <Runtime as Config>::Agreement = SignedAgreement {
technics,
economics,
promisee: sender.clone(),
promisor: sender.clone(),
promisee_signature: signature.clone(),
promisor_signature: signature.clone(),
};
assert_eq!(agreement.verify(), true);
let index = 1;
let payload = IPFS {
hash: IPFS_HASH.into(),
};
let (sender, signature) = get_report_proof("//Alice", &index, &payload);
let report = SignedReport {
index,
sender,
payload,
signature,
};
assert_eq!(report.verify(), true);
}
#[test]
fn test_liability_lifecycle() {
new_test_ext().execute_with(|| {
assert_eq!(Liability::next_index(), None);
let technics = IPFS {
hash: IPFS_HASH.into(),
};
let economics = SimpleMarket { price: 10 * XRT };
let (alice, promisee_signature) = get_params_proof("//Alice", &technics, &economics);
let (bob, promisor_signature) = get_params_proof("//Bob", &technics, &economics);
assert_eq!(System::account(&alice).data.free, 100 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let agreement = SignedAgreement {
technics,
economics,
promisee: alice.clone(),
promisor: bob.clone(),
promisee_signature: promisor_signature.clone(),
promisor_signature,
};
assert_err!(
Liability::create(
Origin::signed(agreement.promisor.clone()),
agreement.clone()
),
Error::<Runtime>::BadAgreementProof,
);
assert_eq!(Liability::next_index(), None);
assert_eq!(System::account(&alice).data.free, 100 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let agreement = SignedAgreement {
promisee_signature,
..agreement
};
assert_ok!(Liability::create(
Origin::signed(agreement.promisor.clone()),
agreement.clone()
),);
assert_eq!(Liability::next_index(), Some(1));
assert_eq!(Liability::report_of(0), None);
assert_eq!(Liability::agreement_of(0), Some(agreement));
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let index = 0;
let payload = IPFS {
hash: IPFS_HASH.into(),
};
let (_, bad_signature) = get_report_proof("//Alice", &index, &payload);
let (sender, signature) = get_report_proof("//Bob", &index, &payload);
let report = SignedReport {
index,
sender,
payload,
signature: bad_signature,
};
assert_err!(
Liability::finalize(Origin::signed(report.sender.clone()), report.clone()),
Error::<Runtime>::BadReportProof,
);
assert_eq!(Liability::report_of(0), None);
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let report = SignedReport {
signature,
..report.clone()
};
assert_ok!(Liability::finalize(
Origin::signed(report.sender.clone()),
report.clone()
));
assert_eq!(Liability::report_of(0), Some(report));
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 110 * XRT);
})
}
}
| get_params_proof | identifier_name |
lib.rs | ///////////////////////////////////////////////////////////////////////////////
//
// Copyright 2018-2021 Robonomics Network <research@robonomics.network>
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
///////////////////////////////////////////////////////////////////////////////
//! The Robonomics runtime module. This can be compiled with `#[no_std]`, ready for Wasm.
#![cfg_attr(not(feature = "std"), no_std)]
pub mod economics;
pub mod signed;
pub mod technics;
pub mod traits;
pub use pallet::*;
pub use signed::*;
pub use traits::*;
#[frame_support::pallet]
pub mod pallet {
use super::traits::*;
use frame_support::{dispatch, pallet_prelude::*};
use frame_system::pallet_prelude::*;
use sp_std::prelude::*;
#[pallet::config]
pub trait Config: frame_system::Config { |
/// How to report of agreement execution.
type Report: dispatch::Parameter + Report<Self::Index, Self::AccountId>;
/// The overarching event type.
type Event: From<Event<Self>> + IsType<<Self as frame_system::Config>::Event>;
}
pub type TechnicsFor<T> =
<<T as Config>::Agreement as Agreement<<T as frame_system::Config>::AccountId>>::Technical;
pub type EconomicsFor<T> =
<<T as Config>::Agreement as Agreement<<T as frame_system::Config>::AccountId>>::Economical;
pub type ReportFor<T> = <T as Config>::Report;
#[pallet::event]
#[pallet::generate_deposit(pub(super) fn deposit_event)]
pub enum Event<T: Config> {
/// Yay! New liability created.
NewLiability(
T::Index,
TechnicsFor<T>,
EconomicsFor<T>,
T::AccountId,
T::AccountId,
),
/// Liability report published.
NewReport(T::Index, ReportFor<T>),
}
#[pallet::error]
pub enum Error<T> {
/// Agreement proof verification failed.
BadAgreementProof,
/// Report proof verification failed.
BadReportProof,
/// Wrong report sender account.
BadReportSender,
/// Liability already finalized.
AlreadyFinalized,
/// Real world oracle is not ready for this report.
OracleIsNotReady,
/// Unable to load agreement from storage.
AgreementNotFound,
}
#[pallet::storage]
#[pallet::getter(fn latest_index)]
/// [DEPRECATED] Latest liability index.
/// TODO: remove after mainnet upgrade
pub(super) type LatestIndex<T: Config> = StorageValue<_, T::Index>;
#[pallet::storage]
#[pallet::getter(fn next_index)]
/// Next liability index.
pub(super) type NextIndex<T: Config> = StorageValue<_, T::Index>;
#[pallet::storage]
#[pallet::getter(fn agreement_of)]
/// Technical and economical parameters of liability.
pub(super) type AgreementOf<T: Config> = StorageMap<_, Twox64Concat, T::Index, T::Agreement>;
#[pallet::storage]
#[pallet::getter(fn report_of)]
/// Result of liability execution.
pub(super) type ReportOf<T: Config> = StorageMap<_, Twox64Concat, T::Index, ReportFor<T>>;
#[pallet::hooks]
impl<T: Config> Hooks<BlockNumberFor<T>> for Pallet<T> {
// TODO: remove after mainnet upgrade
fn on_runtime_upgrade() -> Weight {
if <NextIndex<T>>::get().is_none() {
if let Some(index) = <LatestIndex<T>>::take() {
<NextIndex<T>>::put(index)
}
}
1
}
}
#[pallet::pallet]
#[pallet::generate_store(pub(super) trait Store)]
#[pallet::without_storage_info]
pub struct Pallet<T>(PhantomData<T>);
#[pallet::call]
impl<T: Config> Pallet<T> {
/// Create agreement between two parties.
#[pallet::weight(200_000)]
pub fn create(origin: OriginFor<T>, agreement: T::Agreement) -> DispatchResultWithPostInfo {
let _ = ensure_signed(origin)?;
ensure!(agreement.verify(), Error::<T>::BadAgreementProof);
// Start agreement processing
agreement.on_start()?;
// Store agreement on storage
let next_index = <NextIndex<T>>::get().unwrap_or(Default::default());
<AgreementOf<T>>::insert(next_index, agreement.clone());
<NextIndex<T>>::put(next_index + 1u32.into());
// Emit event
Self::deposit_event(Event::NewLiability(
next_index,
agreement.technical(),
agreement.economical(),
agreement.promisee(),
agreement.promisor(),
));
Ok(().into())
}
/// Publish technical report of complite works.
#[pallet::weight(200_000)]
pub fn finalize(origin: OriginFor<T>, report: ReportFor<T>) -> DispatchResultWithPostInfo {
let _ = ensure_signed(origin)?;
// Check report proof
ensure!(report.verify(), Error::<T>::BadReportProof);
let index = report.index();
// Is liability already finalized?
ensure!(
<ReportOf<T>>::get(index) == None,
Error::<T>::AlreadyFinalized
);
// Decode agreement from storage
if let Some(agreement) = <AgreementOf<T>>::get(index) {
// Check report sender
ensure!(
report.sender() == agreement.promisor(),
Error::<T>::BadReportSender
);
// Run agreement final processing
match report.is_confirmed() {
None => Err(Error::<T>::OracleIsNotReady)?,
Some(x) => agreement.on_finish(x)?,
}
// Store report on storage
<ReportOf<T>>::insert(index, report.clone());
// Emit event
Self::deposit_event(Event::NewReport(index, report));
Ok(().into())
} else {
Err(Error::<T>::AgreementNotFound.into())
}
}
}
}
#[cfg(test)]
mod tests {
use crate::economics::SimpleMarket;
use crate::signed::*;
use crate::technics::IPFS;
use crate::traits::*;
use crate::{self as liability, *};
use frame_support::{assert_err, assert_ok, parameter_types};
use hex_literal::hex;
use sp_core::{crypto::Pair, sr25519, H256};
use sp_keyring::AccountKeyring;
use sp_runtime::{
testing::Header,
traits::{IdentifyAccount, IdentityLookup, Verify},
AccountId32, MultiSignature,
};
type UncheckedExtrinsic = frame_system::mocking::MockUncheckedExtrinsic<Runtime>;
type Block = frame_system::mocking::MockBlock<Runtime>;
type Balance = u128;
const XRT: Balance = 1_000_000_000;
frame_support::construct_runtime!(
pub enum Runtime where
Block = Block,
NodeBlock = Block,
UncheckedExtrinsic = UncheckedExtrinsic,
{
System: frame_system::{Pallet, Call, Config, Storage, Event<T>},
Balances: pallet_balances::{Pallet, Call, Storage, Config<T>, Event<T>},
Liability: liability::{Pallet, Call, Storage, Event<T>},
}
);
parameter_types! {
pub const BlockHashCount: u64 = 250;
}
impl frame_system::Config for Runtime {
type Origin = Origin;
type Index = u64;
type BlockNumber = u64;
type Call = Call;
type Hash = H256;
type Hashing = ::sp_runtime::traits::BlakeTwo256;
type AccountId = AccountId32;
type Lookup = IdentityLookup<Self::AccountId>;
type Header = Header;
type Event = Event;
type BlockHashCount = BlockHashCount;
type Version = ();
type PalletInfo = PalletInfo;
type AccountData = pallet_balances::AccountData<Balance>;
type OnNewAccount = ();
type OnKilledAccount = ();
type DbWeight = ();
type BaseCallFilter = frame_support::traits::Everything;
type SystemWeightInfo = ();
type BlockWeights = ();
type BlockLength = ();
type SS58Prefix = ();
type OnSetCode = ();
type MaxConsumers = frame_support::traits::ConstU32<16>;
}
parameter_types! {
pub const MaxLocks: u32 = 50;
pub const MaxReserves: u32 = 50;
pub const ExistentialDeposit: Balance = 10;
}
impl pallet_balances::Config for Runtime {
type MaxLocks = MaxLocks;
type MaxReserves = MaxReserves;
type ReserveIdentifier = [u8; 8];
type Balance = Balance;
type Event = Event;
type DustRemoval = ();
type ExistentialDeposit = ExistentialDeposit;
type AccountStore = System;
type WeightInfo = ();
}
impl Config for Runtime {
type Event = Event;
type Agreement = SignedAgreement<
// Provide task in IPFS
IPFS,
// Liability has a price
SimpleMarket<Self::AccountId, Balances>,
// Use standard accounts
Self::AccountId,
// Use standard signatures
MultiSignature,
>;
type Report = SignedReport<
// Indexing liabilities using system index
Self::Index,
// Use standard accounts
Self::AccountId,
// Use standard signatures
MultiSignature,
// Provide report in IPFS
IPFS,
>;
}
// IPFS raw hash (sha256)
const IPFS_HASH: [u8; 32] =
hex!["30f3d649b3d140a6601e11a2cfbe3560e60dc5434f62d702ac8ceff4e1890015"];
fn new_test_ext() -> sp_io::TestExternalities {
let mut storage = frame_system::GenesisConfig::default()
.build_storage::<Runtime>()
.unwrap();
let _ = pallet_balances::GenesisConfig::<Runtime> {
balances: vec![
(AccountKeyring::Alice.into(), 100 * XRT),
(AccountKeyring::Bob.into(), 100 * XRT),
],
}
.assimilate_storage(&mut storage);
storage.into()
}
#[test]
fn test_initial_setup() {
new_test_ext().execute_with(|| {
assert_eq!(Liability::next_index(), None);
});
}
fn get_params_proof(
uri: &str,
technics: &TechnicsFor<Runtime>,
economics: &EconomicsFor<Runtime>,
) -> (AccountId32, MultiSignature) {
let pair = sr25519::Pair::from_string(uri, None).unwrap();
let sender = <MultiSignature as Verify>::Signer::from(pair.public()).into_account();
let signature = <ProofSigner<_> as AgreementProofBuilder<_, _, _, _>>::proof(
technics, economics, &pair,
)
.into();
(sender, signature)
}
fn get_report_proof(uri: &str, index: &u64, message: &IPFS) -> (AccountId32, MultiSignature) {
let pair = sr25519::Pair::from_string(uri, None).unwrap();
let sender = <MultiSignature as Verify>::Signer::from(pair.public()).into_account();
let signature =
<ProofSigner<_> as ReportProofBuilder<_, _, _, _>>::proof(index, message, &pair).into();
(sender, signature)
}
#[test]
fn test_liability_proofs() {
let technics = IPFS {
hash: IPFS_HASH.into(),
};
let economics = SimpleMarket { price: 10 };
let (sender, signature) = get_params_proof("//Alice", &technics, &economics);
let agreement: <Runtime as Config>::Agreement = SignedAgreement {
technics,
economics,
promisee: sender.clone(),
promisor: sender.clone(),
promisee_signature: signature.clone(),
promisor_signature: signature.clone(),
};
assert_eq!(agreement.verify(), true);
let index = 1;
let payload = IPFS {
hash: IPFS_HASH.into(),
};
let (sender, signature) = get_report_proof("//Alice", &index, &payload);
let report = SignedReport {
index,
sender,
payload,
signature,
};
assert_eq!(report.verify(), true);
}
#[test]
fn test_liability_lifecycle() {
new_test_ext().execute_with(|| {
assert_eq!(Liability::next_index(), None);
let technics = IPFS {
hash: IPFS_HASH.into(),
};
let economics = SimpleMarket { price: 10 * XRT };
let (alice, promisee_signature) = get_params_proof("//Alice", &technics, &economics);
let (bob, promisor_signature) = get_params_proof("//Bob", &technics, &economics);
assert_eq!(System::account(&alice).data.free, 100 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let agreement = SignedAgreement {
technics,
economics,
promisee: alice.clone(),
promisor: bob.clone(),
promisee_signature: promisor_signature.clone(),
promisor_signature,
};
assert_err!(
Liability::create(
Origin::signed(agreement.promisor.clone()),
agreement.clone()
),
Error::<Runtime>::BadAgreementProof,
);
assert_eq!(Liability::next_index(), None);
assert_eq!(System::account(&alice).data.free, 100 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let agreement = SignedAgreement {
promisee_signature,
..agreement
};
assert_ok!(Liability::create(
Origin::signed(agreement.promisor.clone()),
agreement.clone()
),);
assert_eq!(Liability::next_index(), Some(1));
assert_eq!(Liability::report_of(0), None);
assert_eq!(Liability::agreement_of(0), Some(agreement));
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let index = 0;
let payload = IPFS {
hash: IPFS_HASH.into(),
};
let (_, bad_signature) = get_report_proof("//Alice", &index, &payload);
let (sender, signature) = get_report_proof("//Bob", &index, &payload);
let report = SignedReport {
index,
sender,
payload,
signature: bad_signature,
};
assert_err!(
Liability::finalize(Origin::signed(report.sender.clone()), report.clone()),
Error::<Runtime>::BadReportProof,
);
assert_eq!(Liability::report_of(0), None);
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 100 * XRT);
let report = SignedReport {
signature,
..report.clone()
};
assert_ok!(Liability::finalize(
Origin::signed(report.sender.clone()),
report.clone()
));
assert_eq!(Liability::report_of(0), Some(report));
assert_eq!(System::account(&alice).data.free, 90 * XRT);
assert_eq!(System::account(&bob).data.free, 110 * XRT);
})
}
} | /// How to make and process agreement between two parties.
type Agreement: dispatch::Parameter + Processing + Agreement<Self::AccountId>; | random_line_split |
vrf.go | //
// Copyright 2017-2019 Nippon Telegraph and Telephone Corporation.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
package vswitch
import (
"errors"
"fmt"
"net"
"regexp"
"sync"
"github.com/lagopus/vsw/dpdk"
"github.com/lagopus/vsw/utils/notifier"
)
const (
tapModule = "tap"
hostifModule = "hostif"
)
// VRF represents Virtual Routing & Forwarding instance.
type VRF struct {
name string
devs map[VIFIndex]OutputDevice
router *router
tap *BaseInstance
hostif *BaseInstance
enabled bool
index VRFIndex
vifIndex VIFIndex
rd uint64 // XXX: Do we need this?
sadb *SADatabases
sadbOnce sync.Once
*RoutingTable
*PBR
vrrpref uint
vrrpMutex sync.Mutex
}
type vrfManager struct {
mutex sync.Mutex
byName map[string]*VRF
byIndex [MaxVRF]*VRF
nextIndex int
rds map[uint64]struct{}
re *regexp.Regexp
}
var vrfMgr = &vrfManager{
byName: make(map[string]*VRF),
rds: make(map[uint64]struct{}),
re: regexp.MustCompile(`^vrf\d+$`),
}
// should be called via assignIndex only
func (vm *vrfManager) findSlot(vrf *VRF, from, to int) bool {
for i := from; i < to; i++ {
if vm.byIndex[i] == nil {
vrf.index = VRFIndex(i)
vm.byIndex[i] = vrf
vm.nextIndex = (i + 1) % len(vm.byIndex)
return true
}
}
return false
}
// should be called with lock held
func (vm *vrfManager) assignIndex(vrf *VRF) bool {
// try from the nextIndex to the end
if vm.findSlot(vrf, vm.nextIndex, len(vm.byIndex)) {
return true
}
// try from the head to the nextIndex
return vm.findSlot(vrf, 0, vm.nextIndex)
}
// should be called with lock held
func (vm *vrfManager) releaseIndex(vrf *VRF) {
vm.byIndex[int(vrf.index)] = nil
}
// NewVRF creates a VRF instance.
func NewVRF(name string) (*VRF, error) {
if !vrfMgr.re.MatchString(name) {
return nil, fmt.Errorf("Invalid VRF name: '%v'", name)
}
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
if _, exists := vrfMgr.byName[name]; exists {
return nil, fmt.Errorf("VRF %s already exists", name)
}
vrf := &VRF{
name: name,
enabled: false,
}
if !vrfMgr.assignIndex(vrf) {
return nil, fmt.Errorf("No space left for new VRF")
}
vifIndex, err := vifIdxMgr.allocVIFIndex(vrf)
if err != nil {
vrfMgr.releaseIndex(vrf)
return nil, fmt.Errorf("Can't assign VIFIndex: %v", err)
}
vrf.vifIndex = vifIndex
// Create an ICMP processor
var errMsg error
tapName := name + "-tap"
if tap, err := newInstance(tapModule, tapName, name); err != nil {
errMsg = fmt.Errorf("ICMP handler instance creation failed: %v", err)
goto error1
} else {
vrf.tap = tap
}
// Craete a router
if router, err := newRouter(vrf, name); err != nil {
errMsg = fmt.Errorf("Router instance creation failed: %v", err)
goto error2
} else {
vrf.router = router
}
// Forward all IP packets to the ICMP processor
if err := vrf.router.connect(vrf.tap.Input(), MatchIPv4DstSelf, nil); err != nil {
errMsg = errors.New("Can't connect a router and an tap modules")
goto error3
}
vrf.RoutingTable = newRoutingTable(vrf)
vrf.devs = make(map[VIFIndex]OutputDevice)
vrf.PBR = newPBR(vrf)
vrfMgr.byName[name] = vrf
noti.Notify(notifier.Add, vrf, nil)
return vrf, nil
error3:
vrf.router.free()
error2:
vrf.tap.free()
error1:
vrfMgr.releaseIndex(vrf)
return nil, errMsg
}
func (v *VRF) Free() {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
v.DeleteVIF(vif)
}
}
v.router.disconnect(MatchIPv4DstSelf, nil)
v.tap.free()
v.router.free()
delete(vrfMgr.byName, v.name)
vrfMgr.releaseIndex(v)
if err := vifIdxMgr.freeVIFIndex(v.vifIndex); err != nil {
logger.Err("Freeing VIFIndex for %v failed: %v", v.name, err)
}
if v.rd != 0 {
delete(vrfMgr.rds, v.rd)
}
noti.Notify(notifier.Delete, v, nil)
}
func (v *VRF) baseInstance() *BaseInstance {
return v.router.base
}
func (v *VRF) IsEnabled() bool {
return v.enabled
}
func (v *VRF) Enable() error {
if v.enabled {
return nil
}
if err := v.tap.enable(); err != nil {
return err
}
// Even if vrf is enabled, hostif may not be enabled.
if v.hostif != nil {
if err := v.hostif.enable(); err != nil {
// If activation of hostif fails,
// disable other functions.
v.tap.disable()
return err
}
}
if err := v.router.enable(); err != nil {
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
return err
}
v.enabled = true
return nil
}
func (v *VRF) Disable() {
if v.enabled {
v.router.disable()
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
v.enabled = false
}
}
// Name returns the name of the VRF.
func (v *VRF) Name() string {
return v.name
}
func (v *VRF) String() string {
return v.name
}
// Index returns a unique identifier of the VRF.
func (v *VRF) Index() VRFIndex {
return v.index
}
// VRFIndex returns a unique VIFIndex of the VRF.
// VIFIndex is used for inter-VRF routing.
func (v *VRF) VIFIndex() VIFIndex {
return v.vifIndex
}
// Input returns an input ring for the VRF
// which is the input ring for the underlying interface.
func (v *VRF) Input() *dpdk.Ring {
return v.router.base.Input()
}
// SetRD sets the route distinguisher of thr VRF.
func (v *VRF) SetRD(rd uint64) error {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
oldrd := v.rd
if _, exists := vrfMgr.rds[rd]; exists {
return fmt.Errorf("VRF RD %d already exists", rd)
}
v.rd = rd
vrfMgr.rds[rd] = struct{}{}
if oldrd != 0 {
delete(vrfMgr.rds, oldrd)
}
return nil
}
// RD returns the route distinguisher of the VRF.
func (v *VRF) RD() uint64 {
return v.rd
}
// AddVIF adds VIF to the VRF.
// If the same VIF is added more than once to the VRF,
// it sliently ignores.
func (v *VRF) AddVIF(vif *VIF) error {
var err error
if _, exists := v.devs[vif.VIFIndex()]; exists {
return nil
}
if err = vif.setVRF(v); err != nil {
return err
}
// router -> VIF
if err = v.router.addVIF(vif); err != nil {
goto error1
}
// ICMP -> VIF
if err = v.tap.connect(vif.Outbound(), MatchOutVIF, vif); err != nil {
goto error2
}
// VIF -> router (DST_SELF)
if err = vif.connect(v.router.input(), MatchEthDstSelf, nil); err != nil {
goto error3
}
// VIF -> router (broadcast)
if err = vif.connect(v.router.input(), MatchEthDstBC, nil); err != nil {
goto error4
}
// VIF -> router (multicast)
if err = vif.connect(v.router.input(), MatchEthDstMC, nil); err != nil {
goto error5
}
// Enable NAPT if needed
if vif.isNAPTEnabled() {
if err = v.enableNAPT(vif); err != nil {
goto error6
}
}
v.devs[vif.VIFIndex()] = vif
// TUN/TAP for the VIF will be created
noti.Notify(notifier.Add, v, vif)
return nil
error6:
vif.disconnect(MatchEthDstMC, nil)
error5:
vif.disconnect(MatchEthDstBC, nil)
error4:
vif.disconnect(MatchEthDstSelf, nil)
error3:
v.tap.disconnect(MatchOutVIF, vif)
error2:
v.router.deleteVIF(vif)
error1:
vif.setVRF(nil)
return err
}
func (v *VRF) DeleteVIF(vif *VIF) error {
if _, ok := v.devs[vif.VIFIndex()]; !ok {
return fmt.Errorf("Can't find %v in the VRF.", vif)
}
// Delete routes related a vif as notifications about deletion of the routes
// is not notified from netlink when the vif is deleted from a vrf.
for _, route := range v.ListEntries() {
if route.Dev.VIFIndex() == vif.VIFIndex() {
v.DeleteEntry(route)
}
}
v.tap.disconnect(MatchOutVIF, vif)
vif.disconnect(MatchEthDstSelf, nil)
vif.disconnect(MatchEthDstBC, nil)
vif.disconnect(MatchEthDstMC, nil)
vif.setVRF(nil)
v.router.deleteVIF(vif)
delete(v.devs, vif.VIFIndex())
// TUN/TAP for the VIF will be deleted
noti.Notify(notifier.Delete, v, vif)
return nil
}
// Called only when VRRP is added to VIF
func (v *VRF) vrrpEnabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
var ipv4dst *ScopedAddress
var err error
if ipv4dst, err = NewScopedAddress(VRRPMcastAddr.IP, vif); err != nil {
return
}
// Create only one hostif for vrf
if v.hostif == nil {
hostifName := v.name + "-hostif"
if v.hostif, err = newInstance(hostifModule, hostifName, v.name); err != nil {
return
} else {
if v.enabled {
if err = v.hostif.enable(); err != nil {
goto error
}
}
}
}
// Add packet forwarding rule
// router -> hostif
// VRRP advertisement multicast address.
if err = v.router.connect(v.hostif.Input(), MatchIPv4DstInVIF, ipv4dst); err != nil {
goto error
}
v.vrrpref++
return
error:
if v.vrrpref == 0 {
v.hostif.free()
v.hostif = nil
}
}
// Called only when VRRP is deleted from VIF
func (v *VRF) vrrpDisabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
ipv4dst, err := NewScopedAddress(VRRPMcastAddr.IP, vif)
if err != nil {
return
}
v.router.disconnect(MatchIPv4DstInVIF, ipv4dst)
if v.hostif != nil && v.vrrpref == 1 {
v.hostif.free()
v.hostif = nil
}
v.vrrpref--
}
// VIF returns a slice of Vif Indices in the VRF.
func (v *VRF) VIF() []*VIF {
var vifs []*VIF
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
vifs = append(vifs, vif)
}
}
return vifs
}
// Dump returns descriptive information about the VRF
func (v *VRF) Dump() string {
str := fmt.Sprintf("%s: RD=%d. %d DEV(s):", v.name, v.rd, len(v.devs))
for _, dev := range v.devs {
str += fmt.Sprintf(" %v", dev)
}
if v.sadb != nil {
sad := v.sadb.SAD()
str += fmt.Sprintf("\n%d SAD", len(sad))
for _, sa := range sad {
str += fmt.Sprintf("\n\t%v", sa)
}
spd := v.sadb.SPD()
str += fmt.Sprintf("\n%d SPD", len(spd))
for _, sp := range spd {
str += fmt.Sprintf("\n\t%v", sp)
}
}
return str
}
// SADatabases returns SADatabases associated with the VRF.
func (v *VRF) SADatabases() *SADatabases {
v.sadbOnce.Do(func() {
v.sadb = newSADatabases(v)
})
return v.sadb
}
// HasSADatabases returns true if the VRF has associated SADatbases.
// Returns false otherwise.
func (v *VRF) HasSADatabases() bool {
return v.sadb != nil
}
func createFiveTuples(remotes []net.IP, local net.IP, proto IPProto, dstPort PortRange) []*FiveTuple {
fiveTuples := make([]*FiveTuple, len(remotes))
for i, remote := range remotes {
ft := NewFiveTuple()
ft.SrcIP = CreateIPAddr(remote)
ft.DstIP = CreateIPAddr(local)
ft.DstPort = dstPort
ft.Proto = proto
fiveTuples[i] = ft
}
return fiveTuples
}
func (v *VRF) addL3Tunnel(vif *VIF) error {
t := vif.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", vif)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := vif.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil |
// Forward inbound packets to L3 Tunnel
fts := createFiveTuples(ra, t.local, t.IPProto(), PortRange{})
for i, ft := range fts {
if err := v.router.connect(vif.Inbound(), Match5Tuple, ft); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:i] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Adding a rule to router for L3 tunnel failed: %v", err)
}
}
// Add a rule for NAT Traversal, if the tunnel is IPSec.
if t.Security() == SecurityIPSec {
nats := createFiveTuples(ra, t.local, IPP_UDP, PortRange{Start: 4500})
for i, nat := range nats {
if err := v.router.connect(vif.Inbound(), Match5Tuple, nat); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, ft := range fts {
v.router.disconnect(Match5Tuple, ft)
}
for _, addedNat := range nats[0:i] {
v.router.disconnect(Match5Tuple, addedNat)
}
return fmt.Errorf("Adding a rule for IPSec NAT traversal failed: %v", err)
}
}
}
return nil
}
func (v *VRF) deleteL3Tunnel(vif *VIF) {
t := vif.Tunnel()
for _, ft := range createFiveTuples(t.remotes, t.local, t.IPProto(), PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
if t.Security() == SecurityIPSec {
for _, nat := range createFiveTuples(t.remotes, t.local, IPP_UDP, PortRange{Start: 4500}) {
v.router.disconnect(Match5Tuple, nat)
}
}
vif.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func createVxLANs(remotes []net.IP, local net.IP, dstPort uint16, vni uint32) []*VxLAN {
vxlans := make([]*VxLAN, len(remotes))
for i, remote := range remotes {
vxlan := &VxLAN{
Src: remote,
Dst: local,
DstPort: dstPort,
VNI: vni,
}
vxlans[i] = vxlan
}
return vxlans
}
func (v *VRF) addL2Tunnel(i *Interface) error {
t := i.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", i)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := i.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L2 tunnel: %v", i, err)
}
// Forward inbound packets to L2 Tunnel
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
fts := createFiveTuples(ra, t.local, IPP_GRE, PortRange{})
for idx, ft := range fts {
if err := v.router.connect(i.Inbound(), Match5Tuple, ft); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:idx] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
case EncapsMethodVxLAN:
vxlans := createVxLANs(ra, t.local, t.vxlanPort, t.vni)
for idx, vxlan := range vxlans {
if err := v.router.connect(i.Inbound(), MatchVxLAN, vxlan); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedVxLAN := range vxlans[0:idx] {
v.router.disconnect(Match5Tuple, addedVxLAN)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
default:
return fmt.Errorf("Unsupported L2 Tunnel encaps method: %v", e)
}
return nil
}
func (v *VRF) deleteL2Tunnel(i *Interface) {
t := i.Tunnel()
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
for _, ft := range createFiveTuples(t.remotes, t.local, IPP_GRE, PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
case EncapsMethodVxLAN:
for _, vxlan := range createVxLANs(t.remotes, t.local, t.vxlanPort, t.vni) {
v.router.disconnect(MatchVxLAN, vxlan)
}
}
i.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func (v *VRF) enableNAPT(vif *VIF) error {
return v.router.enableNAPT(vif)
}
func (v *VRF) disableNAPT(vif *VIF) error {
return v.router.disableNAPT(vif)
}
func (v *VRF) MarshalJSON() ([]byte, error) {
return []byte(`"` + v.name + `"`), nil
}
func (v *VRF) registerOutputDevice(dev OutputDevice) error {
// If OutputDevice is already in devs, it means the OutputDevice
// is either VIF, or VRF that has already been added.
if _, exists := v.devs[dev.VIFIndex()]; exists {
return nil
}
// OutputDevice to be added shall be VRF.
// If OutputDevice is VIF, it should have been added via AddVIF already.
if _, ok := dev.(*VRF); !ok {
return fmt.Errorf("OutputDevice is not VRF: %v", dev)
}
// Add VRF to router instance
if err := v.router.addOutputDevice(dev); err != nil {
return fmt.Errorf("Adding OutputDevice %v failed.", dev)
}
v.devs[dev.VIFIndex()] = dev
return nil
}
func (v *VRF) routeEntryAdded(entry Route) {
// Check if all OutputDevice that appears in Route has already
// been registered to the router instance.
if len(entry.Nexthops) == 0 {
if err := v.registerOutputDevice(entry.Dev); err != nil {
logger.Err("%v", err)
return
}
} else {
for _, nh := range entry.Nexthops {
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) routeEntryDeleted(entry Route) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
func (v *VRF) pbrEntryAdded(entry *PBREntry) {
for _, nh := range entry.NextHops {
if nh.Dev == nil {
continue
}
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) pbrEntryDeleted(entry *PBREntry) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
// GetAllVRF returns a slice of available VRF.
func GetAllVRF() []*VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
v := make([]*VRF, len(vrfMgr.byName))
n := 0
for _, vrf := range vrfMgr.byName {
v[n] = vrf
n++
}
return v
}
// GetVRFByName returns a VRF with the given name.
func GetVRFByName(name string) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byName[name]
}
// GetVRFByIndex returns a VRF with the given index.
func GetVRFByIndex(index VRFIndex) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byIndex[int(index)]
}
| {
return fmt.Errorf("Adding a rule to %v failed for L3 tunnel: %v", vif, err)
} | conditional_block |
vrf.go | //
// Copyright 2017-2019 Nippon Telegraph and Telephone Corporation.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
package vswitch
import (
"errors"
"fmt"
"net"
"regexp"
"sync"
"github.com/lagopus/vsw/dpdk"
"github.com/lagopus/vsw/utils/notifier"
)
const (
tapModule = "tap"
hostifModule = "hostif"
)
// VRF represents Virtual Routing & Forwarding instance.
type VRF struct {
name string
devs map[VIFIndex]OutputDevice
router *router
tap *BaseInstance
hostif *BaseInstance
enabled bool
index VRFIndex
vifIndex VIFIndex
rd uint64 // XXX: Do we need this?
sadb *SADatabases
sadbOnce sync.Once
*RoutingTable
*PBR
vrrpref uint
vrrpMutex sync.Mutex
}
type vrfManager struct {
mutex sync.Mutex
byName map[string]*VRF
byIndex [MaxVRF]*VRF
nextIndex int
rds map[uint64]struct{}
re *regexp.Regexp
}
var vrfMgr = &vrfManager{
byName: make(map[string]*VRF),
rds: make(map[uint64]struct{}),
re: regexp.MustCompile(`^vrf\d+$`),
}
// should be called via assignIndex only
func (vm *vrfManager) findSlot(vrf *VRF, from, to int) bool {
for i := from; i < to; i++ {
if vm.byIndex[i] == nil {
vrf.index = VRFIndex(i)
vm.byIndex[i] = vrf
vm.nextIndex = (i + 1) % len(vm.byIndex)
return true
}
}
return false
}
// should be called with lock held
func (vm *vrfManager) assignIndex(vrf *VRF) bool {
// try from the nextIndex to the end
if vm.findSlot(vrf, vm.nextIndex, len(vm.byIndex)) {
return true
}
// try from the head to the nextIndex
return vm.findSlot(vrf, 0, vm.nextIndex)
}
// should be called with lock held
func (vm *vrfManager) releaseIndex(vrf *VRF) {
vm.byIndex[int(vrf.index)] = nil
}
// NewVRF creates a VRF instance.
func NewVRF(name string) (*VRF, error) {
if !vrfMgr.re.MatchString(name) {
return nil, fmt.Errorf("Invalid VRF name: '%v'", name)
}
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
if _, exists := vrfMgr.byName[name]; exists {
return nil, fmt.Errorf("VRF %s already exists", name)
}
vrf := &VRF{
name: name,
enabled: false,
}
if !vrfMgr.assignIndex(vrf) {
return nil, fmt.Errorf("No space left for new VRF")
}
vifIndex, err := vifIdxMgr.allocVIFIndex(vrf)
if err != nil {
vrfMgr.releaseIndex(vrf)
return nil, fmt.Errorf("Can't assign VIFIndex: %v", err)
}
vrf.vifIndex = vifIndex
// Create an ICMP processor
var errMsg error
tapName := name + "-tap"
if tap, err := newInstance(tapModule, tapName, name); err != nil {
errMsg = fmt.Errorf("ICMP handler instance creation failed: %v", err)
goto error1
} else {
vrf.tap = tap
}
// Craete a router
if router, err := newRouter(vrf, name); err != nil {
errMsg = fmt.Errorf("Router instance creation failed: %v", err)
goto error2
} else {
vrf.router = router
}
// Forward all IP packets to the ICMP processor
if err := vrf.router.connect(vrf.tap.Input(), MatchIPv4DstSelf, nil); err != nil {
errMsg = errors.New("Can't connect a router and an tap modules")
goto error3
}
vrf.RoutingTable = newRoutingTable(vrf)
vrf.devs = make(map[VIFIndex]OutputDevice)
vrf.PBR = newPBR(vrf)
vrfMgr.byName[name] = vrf
noti.Notify(notifier.Add, vrf, nil)
return vrf, nil
error3:
vrf.router.free()
error2:
vrf.tap.free()
error1:
vrfMgr.releaseIndex(vrf)
return nil, errMsg
}
func (v *VRF) Free() {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
v.DeleteVIF(vif)
}
}
v.router.disconnect(MatchIPv4DstSelf, nil)
v.tap.free()
v.router.free()
delete(vrfMgr.byName, v.name)
vrfMgr.releaseIndex(v)
if err := vifIdxMgr.freeVIFIndex(v.vifIndex); err != nil {
logger.Err("Freeing VIFIndex for %v failed: %v", v.name, err)
}
if v.rd != 0 {
delete(vrfMgr.rds, v.rd)
}
noti.Notify(notifier.Delete, v, nil)
}
func (v *VRF) baseInstance() *BaseInstance {
return v.router.base
}
func (v *VRF) IsEnabled() bool {
return v.enabled
}
func (v *VRF) Enable() error {
if v.enabled {
return nil
}
if err := v.tap.enable(); err != nil {
return err
}
// Even if vrf is enabled, hostif may not be enabled.
if v.hostif != nil {
if err := v.hostif.enable(); err != nil {
// If activation of hostif fails,
// disable other functions.
v.tap.disable()
return err
}
}
if err := v.router.enable(); err != nil {
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
return err
}
v.enabled = true
return nil
}
func (v *VRF) Disable() {
if v.enabled {
v.router.disable()
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
v.enabled = false
}
}
// Name returns the name of the VRF.
func (v *VRF) Name() string {
return v.name
}
func (v *VRF) String() string {
return v.name
}
// Index returns a unique identifier of the VRF.
func (v *VRF) Index() VRFIndex {
return v.index
}
// VRFIndex returns a unique VIFIndex of the VRF.
// VIFIndex is used for inter-VRF routing.
func (v *VRF) VIFIndex() VIFIndex {
return v.vifIndex
}
// Input returns an input ring for the VRF
// which is the input ring for the underlying interface.
func (v *VRF) Input() *dpdk.Ring {
return v.router.base.Input()
}
// SetRD sets the route distinguisher of thr VRF.
func (v *VRF) SetRD(rd uint64) error {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
oldrd := v.rd
if _, exists := vrfMgr.rds[rd]; exists {
return fmt.Errorf("VRF RD %d already exists", rd)
}
v.rd = rd
vrfMgr.rds[rd] = struct{}{}
if oldrd != 0 {
delete(vrfMgr.rds, oldrd)
}
return nil
}
// RD returns the route distinguisher of the VRF.
func (v *VRF) RD() uint64 {
return v.rd
}
// AddVIF adds VIF to the VRF.
// If the same VIF is added more than once to the VRF,
// it sliently ignores.
func (v *VRF) AddVIF(vif *VIF) error {
var err error
if _, exists := v.devs[vif.VIFIndex()]; exists {
return nil
}
if err = vif.setVRF(v); err != nil {
return err
}
// router -> VIF
if err = v.router.addVIF(vif); err != nil {
goto error1
}
// ICMP -> VIF
if err = v.tap.connect(vif.Outbound(), MatchOutVIF, vif); err != nil {
goto error2
}
// VIF -> router (DST_SELF)
if err = vif.connect(v.router.input(), MatchEthDstSelf, nil); err != nil {
goto error3
}
// VIF -> router (broadcast)
if err = vif.connect(v.router.input(), MatchEthDstBC, nil); err != nil {
goto error4
}
// VIF -> router (multicast)
if err = vif.connect(v.router.input(), MatchEthDstMC, nil); err != nil {
goto error5
}
// Enable NAPT if needed
if vif.isNAPTEnabled() {
if err = v.enableNAPT(vif); err != nil {
goto error6
}
}
v.devs[vif.VIFIndex()] = vif
// TUN/TAP for the VIF will be created
noti.Notify(notifier.Add, v, vif)
return nil
error6:
vif.disconnect(MatchEthDstMC, nil)
error5:
vif.disconnect(MatchEthDstBC, nil)
error4:
vif.disconnect(MatchEthDstSelf, nil)
error3:
v.tap.disconnect(MatchOutVIF, vif)
error2:
v.router.deleteVIF(vif)
error1:
vif.setVRF(nil)
return err
}
func (v *VRF) DeleteVIF(vif *VIF) error {
if _, ok := v.devs[vif.VIFIndex()]; !ok {
return fmt.Errorf("Can't find %v in the VRF.", vif)
}
// Delete routes related a vif as notifications about deletion of the routes
// is not notified from netlink when the vif is deleted from a vrf.
for _, route := range v.ListEntries() {
if route.Dev.VIFIndex() == vif.VIFIndex() {
v.DeleteEntry(route)
}
}
v.tap.disconnect(MatchOutVIF, vif)
vif.disconnect(MatchEthDstSelf, nil)
vif.disconnect(MatchEthDstBC, nil)
vif.disconnect(MatchEthDstMC, nil)
vif.setVRF(nil)
v.router.deleteVIF(vif)
delete(v.devs, vif.VIFIndex())
// TUN/TAP for the VIF will be deleted
noti.Notify(notifier.Delete, v, vif)
return nil
}
// Called only when VRRP is added to VIF
func (v *VRF) vrrpEnabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
var ipv4dst *ScopedAddress
var err error
if ipv4dst, err = NewScopedAddress(VRRPMcastAddr.IP, vif); err != nil {
return
}
// Create only one hostif for vrf
if v.hostif == nil {
hostifName := v.name + "-hostif"
if v.hostif, err = newInstance(hostifModule, hostifName, v.name); err != nil {
return
} else {
if v.enabled {
if err = v.hostif.enable(); err != nil {
goto error
}
}
}
}
// Add packet forwarding rule
// router -> hostif
// VRRP advertisement multicast address.
if err = v.router.connect(v.hostif.Input(), MatchIPv4DstInVIF, ipv4dst); err != nil {
goto error
}
v.vrrpref++
return
error:
if v.vrrpref == 0 {
v.hostif.free()
v.hostif = nil
}
}
// Called only when VRRP is deleted from VIF
func (v *VRF) vrrpDisabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
ipv4dst, err := NewScopedAddress(VRRPMcastAddr.IP, vif)
if err != nil {
return
}
v.router.disconnect(MatchIPv4DstInVIF, ipv4dst)
if v.hostif != nil && v.vrrpref == 1 {
v.hostif.free()
v.hostif = nil
}
v.vrrpref--
}
// VIF returns a slice of Vif Indices in the VRF.
func (v *VRF) VIF() []*VIF {
var vifs []*VIF
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
vifs = append(vifs, vif)
}
}
return vifs
}
// Dump returns descriptive information about the VRF
func (v *VRF) Dump() string {
str := fmt.Sprintf("%s: RD=%d. %d DEV(s):", v.name, v.rd, len(v.devs))
for _, dev := range v.devs {
str += fmt.Sprintf(" %v", dev)
}
if v.sadb != nil {
sad := v.sadb.SAD()
str += fmt.Sprintf("\n%d SAD", len(sad))
for _, sa := range sad {
str += fmt.Sprintf("\n\t%v", sa)
}
spd := v.sadb.SPD()
str += fmt.Sprintf("\n%d SPD", len(spd))
for _, sp := range spd {
str += fmt.Sprintf("\n\t%v", sp)
}
}
return str
}
// SADatabases returns SADatabases associated with the VRF.
func (v *VRF) SADatabases() *SADatabases {
v.sadbOnce.Do(func() {
v.sadb = newSADatabases(v)
})
return v.sadb
}
// HasSADatabases returns true if the VRF has associated SADatbases.
// Returns false otherwise.
func (v *VRF) HasSADatabases() bool {
return v.sadb != nil
}
func createFiveTuples(remotes []net.IP, local net.IP, proto IPProto, dstPort PortRange) []*FiveTuple {
fiveTuples := make([]*FiveTuple, len(remotes))
for i, remote := range remotes {
ft := NewFiveTuple()
ft.SrcIP = CreateIPAddr(remote)
ft.DstIP = CreateIPAddr(local)
ft.DstPort = dstPort
ft.Proto = proto
fiveTuples[i] = ft
}
return fiveTuples
}
func (v *VRF) addL3Tunnel(vif *VIF) error {
t := vif.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", vif)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := vif.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L3 tunnel: %v", vif, err)
}
// Forward inbound packets to L3 Tunnel
fts := createFiveTuples(ra, t.local, t.IPProto(), PortRange{})
for i, ft := range fts {
if err := v.router.connect(vif.Inbound(), Match5Tuple, ft); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:i] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Adding a rule to router for L3 tunnel failed: %v", err)
}
}
// Add a rule for NAT Traversal, if the tunnel is IPSec.
if t.Security() == SecurityIPSec {
nats := createFiveTuples(ra, t.local, IPP_UDP, PortRange{Start: 4500})
for i, nat := range nats {
if err := v.router.connect(vif.Inbound(), Match5Tuple, nat); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, ft := range fts {
v.router.disconnect(Match5Tuple, ft)
}
for _, addedNat := range nats[0:i] {
v.router.disconnect(Match5Tuple, addedNat)
}
return fmt.Errorf("Adding a rule for IPSec NAT traversal failed: %v", err)
}
}
}
return nil
}
func (v *VRF) deleteL3Tunnel(vif *VIF) {
t := vif.Tunnel()
for _, ft := range createFiveTuples(t.remotes, t.local, t.IPProto(), PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
if t.Security() == SecurityIPSec {
for _, nat := range createFiveTuples(t.remotes, t.local, IPP_UDP, PortRange{Start: 4500}) {
v.router.disconnect(Match5Tuple, nat)
}
}
vif.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func createVxLANs(remotes []net.IP, local net.IP, dstPort uint16, vni uint32) []*VxLAN {
vxlans := make([]*VxLAN, len(remotes))
for i, remote := range remotes {
vxlan := &VxLAN{
Src: remote,
Dst: local,
DstPort: dstPort,
VNI: vni,
}
vxlans[i] = vxlan
}
return vxlans
}
func (v *VRF) addL2Tunnel(i *Interface) error {
t := i.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", i)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := i.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L2 tunnel: %v", i, err)
}
// Forward inbound packets to L2 Tunnel
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
fts := createFiveTuples(ra, t.local, IPP_GRE, PortRange{})
for idx, ft := range fts {
if err := v.router.connect(i.Inbound(), Match5Tuple, ft); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:idx] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
case EncapsMethodVxLAN:
vxlans := createVxLANs(ra, t.local, t.vxlanPort, t.vni)
for idx, vxlan := range vxlans {
if err := v.router.connect(i.Inbound(), MatchVxLAN, vxlan); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedVxLAN := range vxlans[0:idx] {
v.router.disconnect(Match5Tuple, addedVxLAN)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
default:
return fmt.Errorf("Unsupported L2 Tunnel encaps method: %v", e)
}
return nil
}
func (v *VRF) deleteL2Tunnel(i *Interface) {
t := i.Tunnel()
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
for _, ft := range createFiveTuples(t.remotes, t.local, IPP_GRE, PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
case EncapsMethodVxLAN:
for _, vxlan := range createVxLANs(t.remotes, t.local, t.vxlanPort, t.vni) {
v.router.disconnect(MatchVxLAN, vxlan)
}
}
i.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func (v *VRF) enableNAPT(vif *VIF) error {
return v.router.enableNAPT(vif)
}
func (v *VRF) disableNAPT(vif *VIF) error {
return v.router.disableNAPT(vif)
}
func (v *VRF) MarshalJSON() ([]byte, error) {
return []byte(`"` + v.name + `"`), nil
}
func (v *VRF) registerOutputDevice(dev OutputDevice) error {
// If OutputDevice is already in devs, it means the OutputDevice
// is either VIF, or VRF that has already been added.
if _, exists := v.devs[dev.VIFIndex()]; exists {
return nil
}
// OutputDevice to be added shall be VRF.
// If OutputDevice is VIF, it should have been added via AddVIF already.
if _, ok := dev.(*VRF); !ok {
return fmt.Errorf("OutputDevice is not VRF: %v", dev)
}
// Add VRF to router instance
if err := v.router.addOutputDevice(dev); err != nil {
return fmt.Errorf("Adding OutputDevice %v failed.", dev)
}
v.devs[dev.VIFIndex()] = dev
return nil
}
func (v *VRF) routeEntryAdded(entry Route) {
// Check if all OutputDevice that appears in Route has already
// been registered to the router instance.
if len(entry.Nexthops) == 0 {
if err := v.registerOutputDevice(entry.Dev); err != nil {
logger.Err("%v", err)
return
}
} else {
for _, nh := range entry.Nexthops {
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) routeEntryDeleted(entry Route) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
func (v *VRF) pbrEntryAdded(entry *PBREntry) {
for _, nh := range entry.NextHops {
if nh.Dev == nil {
continue
}
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) pbrEntryDeleted(entry *PBREntry) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
// GetAllVRF returns a slice of available VRF.
func GetAllVRF() []*VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
v := make([]*VRF, len(vrfMgr.byName))
n := 0
for _, vrf := range vrfMgr.byName {
v[n] = vrf
n++
}
return v
}
// GetVRFByName returns a VRF with the given name.
func | (name string) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byName[name]
}
// GetVRFByIndex returns a VRF with the given index.
func GetVRFByIndex(index VRFIndex) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byIndex[int(index)]
}
| GetVRFByName | identifier_name |
vrf.go | //
// Copyright 2017-2019 Nippon Telegraph and Telephone Corporation.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
package vswitch
import (
"errors"
"fmt"
"net"
"regexp"
"sync"
"github.com/lagopus/vsw/dpdk"
"github.com/lagopus/vsw/utils/notifier"
)
const (
tapModule = "tap"
hostifModule = "hostif"
)
// VRF represents Virtual Routing & Forwarding instance.
type VRF struct {
name string
devs map[VIFIndex]OutputDevice
router *router
tap *BaseInstance
hostif *BaseInstance
enabled bool
index VRFIndex
vifIndex VIFIndex
rd uint64 // XXX: Do we need this?
sadb *SADatabases
sadbOnce sync.Once
*RoutingTable
*PBR
vrrpref uint
vrrpMutex sync.Mutex
}
type vrfManager struct {
mutex sync.Mutex
byName map[string]*VRF
byIndex [MaxVRF]*VRF
nextIndex int
rds map[uint64]struct{}
re *regexp.Regexp
}
var vrfMgr = &vrfManager{
byName: make(map[string]*VRF),
rds: make(map[uint64]struct{}),
re: regexp.MustCompile(`^vrf\d+$`),
}
// should be called via assignIndex only
func (vm *vrfManager) findSlot(vrf *VRF, from, to int) bool {
for i := from; i < to; i++ {
if vm.byIndex[i] == nil {
vrf.index = VRFIndex(i)
vm.byIndex[i] = vrf
vm.nextIndex = (i + 1) % len(vm.byIndex)
return true
}
}
return false
}
// should be called with lock held
func (vm *vrfManager) assignIndex(vrf *VRF) bool |
// should be called with lock held
func (vm *vrfManager) releaseIndex(vrf *VRF) {
vm.byIndex[int(vrf.index)] = nil
}
// NewVRF creates a VRF instance.
func NewVRF(name string) (*VRF, error) {
if !vrfMgr.re.MatchString(name) {
return nil, fmt.Errorf("Invalid VRF name: '%v'", name)
}
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
if _, exists := vrfMgr.byName[name]; exists {
return nil, fmt.Errorf("VRF %s already exists", name)
}
vrf := &VRF{
name: name,
enabled: false,
}
if !vrfMgr.assignIndex(vrf) {
return nil, fmt.Errorf("No space left for new VRF")
}
vifIndex, err := vifIdxMgr.allocVIFIndex(vrf)
if err != nil {
vrfMgr.releaseIndex(vrf)
return nil, fmt.Errorf("Can't assign VIFIndex: %v", err)
}
vrf.vifIndex = vifIndex
// Create an ICMP processor
var errMsg error
tapName := name + "-tap"
if tap, err := newInstance(tapModule, tapName, name); err != nil {
errMsg = fmt.Errorf("ICMP handler instance creation failed: %v", err)
goto error1
} else {
vrf.tap = tap
}
// Craete a router
if router, err := newRouter(vrf, name); err != nil {
errMsg = fmt.Errorf("Router instance creation failed: %v", err)
goto error2
} else {
vrf.router = router
}
// Forward all IP packets to the ICMP processor
if err := vrf.router.connect(vrf.tap.Input(), MatchIPv4DstSelf, nil); err != nil {
errMsg = errors.New("Can't connect a router and an tap modules")
goto error3
}
vrf.RoutingTable = newRoutingTable(vrf)
vrf.devs = make(map[VIFIndex]OutputDevice)
vrf.PBR = newPBR(vrf)
vrfMgr.byName[name] = vrf
noti.Notify(notifier.Add, vrf, nil)
return vrf, nil
error3:
vrf.router.free()
error2:
vrf.tap.free()
error1:
vrfMgr.releaseIndex(vrf)
return nil, errMsg
}
func (v *VRF) Free() {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
v.DeleteVIF(vif)
}
}
v.router.disconnect(MatchIPv4DstSelf, nil)
v.tap.free()
v.router.free()
delete(vrfMgr.byName, v.name)
vrfMgr.releaseIndex(v)
if err := vifIdxMgr.freeVIFIndex(v.vifIndex); err != nil {
logger.Err("Freeing VIFIndex for %v failed: %v", v.name, err)
}
if v.rd != 0 {
delete(vrfMgr.rds, v.rd)
}
noti.Notify(notifier.Delete, v, nil)
}
func (v *VRF) baseInstance() *BaseInstance {
return v.router.base
}
func (v *VRF) IsEnabled() bool {
return v.enabled
}
func (v *VRF) Enable() error {
if v.enabled {
return nil
}
if err := v.tap.enable(); err != nil {
return err
}
// Even if vrf is enabled, hostif may not be enabled.
if v.hostif != nil {
if err := v.hostif.enable(); err != nil {
// If activation of hostif fails,
// disable other functions.
v.tap.disable()
return err
}
}
if err := v.router.enable(); err != nil {
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
return err
}
v.enabled = true
return nil
}
func (v *VRF) Disable() {
if v.enabled {
v.router.disable()
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
v.enabled = false
}
}
// Name returns the name of the VRF.
func (v *VRF) Name() string {
return v.name
}
func (v *VRF) String() string {
return v.name
}
// Index returns a unique identifier of the VRF.
func (v *VRF) Index() VRFIndex {
return v.index
}
// VRFIndex returns a unique VIFIndex of the VRF.
// VIFIndex is used for inter-VRF routing.
func (v *VRF) VIFIndex() VIFIndex {
return v.vifIndex
}
// Input returns an input ring for the VRF
// which is the input ring for the underlying interface.
func (v *VRF) Input() *dpdk.Ring {
return v.router.base.Input()
}
// SetRD sets the route distinguisher of thr VRF.
func (v *VRF) SetRD(rd uint64) error {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
oldrd := v.rd
if _, exists := vrfMgr.rds[rd]; exists {
return fmt.Errorf("VRF RD %d already exists", rd)
}
v.rd = rd
vrfMgr.rds[rd] = struct{}{}
if oldrd != 0 {
delete(vrfMgr.rds, oldrd)
}
return nil
}
// RD returns the route distinguisher of the VRF.
func (v *VRF) RD() uint64 {
return v.rd
}
// AddVIF adds VIF to the VRF.
// If the same VIF is added more than once to the VRF,
// it sliently ignores.
func (v *VRF) AddVIF(vif *VIF) error {
var err error
if _, exists := v.devs[vif.VIFIndex()]; exists {
return nil
}
if err = vif.setVRF(v); err != nil {
return err
}
// router -> VIF
if err = v.router.addVIF(vif); err != nil {
goto error1
}
// ICMP -> VIF
if err = v.tap.connect(vif.Outbound(), MatchOutVIF, vif); err != nil {
goto error2
}
// VIF -> router (DST_SELF)
if err = vif.connect(v.router.input(), MatchEthDstSelf, nil); err != nil {
goto error3
}
// VIF -> router (broadcast)
if err = vif.connect(v.router.input(), MatchEthDstBC, nil); err != nil {
goto error4
}
// VIF -> router (multicast)
if err = vif.connect(v.router.input(), MatchEthDstMC, nil); err != nil {
goto error5
}
// Enable NAPT if needed
if vif.isNAPTEnabled() {
if err = v.enableNAPT(vif); err != nil {
goto error6
}
}
v.devs[vif.VIFIndex()] = vif
// TUN/TAP for the VIF will be created
noti.Notify(notifier.Add, v, vif)
return nil
error6:
vif.disconnect(MatchEthDstMC, nil)
error5:
vif.disconnect(MatchEthDstBC, nil)
error4:
vif.disconnect(MatchEthDstSelf, nil)
error3:
v.tap.disconnect(MatchOutVIF, vif)
error2:
v.router.deleteVIF(vif)
error1:
vif.setVRF(nil)
return err
}
func (v *VRF) DeleteVIF(vif *VIF) error {
if _, ok := v.devs[vif.VIFIndex()]; !ok {
return fmt.Errorf("Can't find %v in the VRF.", vif)
}
// Delete routes related a vif as notifications about deletion of the routes
// is not notified from netlink when the vif is deleted from a vrf.
for _, route := range v.ListEntries() {
if route.Dev.VIFIndex() == vif.VIFIndex() {
v.DeleteEntry(route)
}
}
v.tap.disconnect(MatchOutVIF, vif)
vif.disconnect(MatchEthDstSelf, nil)
vif.disconnect(MatchEthDstBC, nil)
vif.disconnect(MatchEthDstMC, nil)
vif.setVRF(nil)
v.router.deleteVIF(vif)
delete(v.devs, vif.VIFIndex())
// TUN/TAP for the VIF will be deleted
noti.Notify(notifier.Delete, v, vif)
return nil
}
// Called only when VRRP is added to VIF
func (v *VRF) vrrpEnabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
var ipv4dst *ScopedAddress
var err error
if ipv4dst, err = NewScopedAddress(VRRPMcastAddr.IP, vif); err != nil {
return
}
// Create only one hostif for vrf
if v.hostif == nil {
hostifName := v.name + "-hostif"
if v.hostif, err = newInstance(hostifModule, hostifName, v.name); err != nil {
return
} else {
if v.enabled {
if err = v.hostif.enable(); err != nil {
goto error
}
}
}
}
// Add packet forwarding rule
// router -> hostif
// VRRP advertisement multicast address.
if err = v.router.connect(v.hostif.Input(), MatchIPv4DstInVIF, ipv4dst); err != nil {
goto error
}
v.vrrpref++
return
error:
if v.vrrpref == 0 {
v.hostif.free()
v.hostif = nil
}
}
// Called only when VRRP is deleted from VIF
func (v *VRF) vrrpDisabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
ipv4dst, err := NewScopedAddress(VRRPMcastAddr.IP, vif)
if err != nil {
return
}
v.router.disconnect(MatchIPv4DstInVIF, ipv4dst)
if v.hostif != nil && v.vrrpref == 1 {
v.hostif.free()
v.hostif = nil
}
v.vrrpref--
}
// VIF returns a slice of Vif Indices in the VRF.
func (v *VRF) VIF() []*VIF {
var vifs []*VIF
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
vifs = append(vifs, vif)
}
}
return vifs
}
// Dump returns descriptive information about the VRF
func (v *VRF) Dump() string {
str := fmt.Sprintf("%s: RD=%d. %d DEV(s):", v.name, v.rd, len(v.devs))
for _, dev := range v.devs {
str += fmt.Sprintf(" %v", dev)
}
if v.sadb != nil {
sad := v.sadb.SAD()
str += fmt.Sprintf("\n%d SAD", len(sad))
for _, sa := range sad {
str += fmt.Sprintf("\n\t%v", sa)
}
spd := v.sadb.SPD()
str += fmt.Sprintf("\n%d SPD", len(spd))
for _, sp := range spd {
str += fmt.Sprintf("\n\t%v", sp)
}
}
return str
}
// SADatabases returns SADatabases associated with the VRF.
func (v *VRF) SADatabases() *SADatabases {
v.sadbOnce.Do(func() {
v.sadb = newSADatabases(v)
})
return v.sadb
}
// HasSADatabases returns true if the VRF has associated SADatbases.
// Returns false otherwise.
func (v *VRF) HasSADatabases() bool {
return v.sadb != nil
}
func createFiveTuples(remotes []net.IP, local net.IP, proto IPProto, dstPort PortRange) []*FiveTuple {
fiveTuples := make([]*FiveTuple, len(remotes))
for i, remote := range remotes {
ft := NewFiveTuple()
ft.SrcIP = CreateIPAddr(remote)
ft.DstIP = CreateIPAddr(local)
ft.DstPort = dstPort
ft.Proto = proto
fiveTuples[i] = ft
}
return fiveTuples
}
func (v *VRF) addL3Tunnel(vif *VIF) error {
t := vif.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", vif)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := vif.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L3 tunnel: %v", vif, err)
}
// Forward inbound packets to L3 Tunnel
fts := createFiveTuples(ra, t.local, t.IPProto(), PortRange{})
for i, ft := range fts {
if err := v.router.connect(vif.Inbound(), Match5Tuple, ft); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:i] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Adding a rule to router for L3 tunnel failed: %v", err)
}
}
// Add a rule for NAT Traversal, if the tunnel is IPSec.
if t.Security() == SecurityIPSec {
nats := createFiveTuples(ra, t.local, IPP_UDP, PortRange{Start: 4500})
for i, nat := range nats {
if err := v.router.connect(vif.Inbound(), Match5Tuple, nat); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, ft := range fts {
v.router.disconnect(Match5Tuple, ft)
}
for _, addedNat := range nats[0:i] {
v.router.disconnect(Match5Tuple, addedNat)
}
return fmt.Errorf("Adding a rule for IPSec NAT traversal failed: %v", err)
}
}
}
return nil
}
func (v *VRF) deleteL3Tunnel(vif *VIF) {
t := vif.Tunnel()
for _, ft := range createFiveTuples(t.remotes, t.local, t.IPProto(), PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
if t.Security() == SecurityIPSec {
for _, nat := range createFiveTuples(t.remotes, t.local, IPP_UDP, PortRange{Start: 4500}) {
v.router.disconnect(Match5Tuple, nat)
}
}
vif.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func createVxLANs(remotes []net.IP, local net.IP, dstPort uint16, vni uint32) []*VxLAN {
vxlans := make([]*VxLAN, len(remotes))
for i, remote := range remotes {
vxlan := &VxLAN{
Src: remote,
Dst: local,
DstPort: dstPort,
VNI: vni,
}
vxlans[i] = vxlan
}
return vxlans
}
func (v *VRF) addL2Tunnel(i *Interface) error {
t := i.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", i)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := i.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L2 tunnel: %v", i, err)
}
// Forward inbound packets to L2 Tunnel
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
fts := createFiveTuples(ra, t.local, IPP_GRE, PortRange{})
for idx, ft := range fts {
if err := v.router.connect(i.Inbound(), Match5Tuple, ft); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:idx] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
case EncapsMethodVxLAN:
vxlans := createVxLANs(ra, t.local, t.vxlanPort, t.vni)
for idx, vxlan := range vxlans {
if err := v.router.connect(i.Inbound(), MatchVxLAN, vxlan); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedVxLAN := range vxlans[0:idx] {
v.router.disconnect(Match5Tuple, addedVxLAN)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
default:
return fmt.Errorf("Unsupported L2 Tunnel encaps method: %v", e)
}
return nil
}
func (v *VRF) deleteL2Tunnel(i *Interface) {
t := i.Tunnel()
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
for _, ft := range createFiveTuples(t.remotes, t.local, IPP_GRE, PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
case EncapsMethodVxLAN:
for _, vxlan := range createVxLANs(t.remotes, t.local, t.vxlanPort, t.vni) {
v.router.disconnect(MatchVxLAN, vxlan)
}
}
i.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func (v *VRF) enableNAPT(vif *VIF) error {
return v.router.enableNAPT(vif)
}
func (v *VRF) disableNAPT(vif *VIF) error {
return v.router.disableNAPT(vif)
}
func (v *VRF) MarshalJSON() ([]byte, error) {
return []byte(`"` + v.name + `"`), nil
}
func (v *VRF) registerOutputDevice(dev OutputDevice) error {
// If OutputDevice is already in devs, it means the OutputDevice
// is either VIF, or VRF that has already been added.
if _, exists := v.devs[dev.VIFIndex()]; exists {
return nil
}
// OutputDevice to be added shall be VRF.
// If OutputDevice is VIF, it should have been added via AddVIF already.
if _, ok := dev.(*VRF); !ok {
return fmt.Errorf("OutputDevice is not VRF: %v", dev)
}
// Add VRF to router instance
if err := v.router.addOutputDevice(dev); err != nil {
return fmt.Errorf("Adding OutputDevice %v failed.", dev)
}
v.devs[dev.VIFIndex()] = dev
return nil
}
func (v *VRF) routeEntryAdded(entry Route) {
// Check if all OutputDevice that appears in Route has already
// been registered to the router instance.
if len(entry.Nexthops) == 0 {
if err := v.registerOutputDevice(entry.Dev); err != nil {
logger.Err("%v", err)
return
}
} else {
for _, nh := range entry.Nexthops {
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) routeEntryDeleted(entry Route) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
func (v *VRF) pbrEntryAdded(entry *PBREntry) {
for _, nh := range entry.NextHops {
if nh.Dev == nil {
continue
}
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) pbrEntryDeleted(entry *PBREntry) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
// GetAllVRF returns a slice of available VRF.
func GetAllVRF() []*VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
v := make([]*VRF, len(vrfMgr.byName))
n := 0
for _, vrf := range vrfMgr.byName {
v[n] = vrf
n++
}
return v
}
// GetVRFByName returns a VRF with the given name.
func GetVRFByName(name string) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byName[name]
}
// GetVRFByIndex returns a VRF with the given index.
func GetVRFByIndex(index VRFIndex) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byIndex[int(index)]
}
| {
// try from the nextIndex to the end
if vm.findSlot(vrf, vm.nextIndex, len(vm.byIndex)) {
return true
}
// try from the head to the nextIndex
return vm.findSlot(vrf, 0, vm.nextIndex)
} | identifier_body |
vrf.go | //
// Copyright 2017-2019 Nippon Telegraph and Telephone Corporation.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
package vswitch
import (
"errors"
"fmt"
"net"
"regexp"
"sync"
"github.com/lagopus/vsw/dpdk"
"github.com/lagopus/vsw/utils/notifier"
)
const (
tapModule = "tap"
hostifModule = "hostif"
)
// VRF represents Virtual Routing & Forwarding instance.
type VRF struct {
name string
devs map[VIFIndex]OutputDevice
router *router
tap *BaseInstance
hostif *BaseInstance
enabled bool
index VRFIndex
vifIndex VIFIndex
rd uint64 // XXX: Do we need this?
sadb *SADatabases
sadbOnce sync.Once
*RoutingTable
*PBR
vrrpref uint
vrrpMutex sync.Mutex
}
type vrfManager struct {
mutex sync.Mutex
byName map[string]*VRF
byIndex [MaxVRF]*VRF
nextIndex int
rds map[uint64]struct{}
re *regexp.Regexp
}
var vrfMgr = &vrfManager{
byName: make(map[string]*VRF),
rds: make(map[uint64]struct{}),
re: regexp.MustCompile(`^vrf\d+$`),
}
// should be called via assignIndex only
func (vm *vrfManager) findSlot(vrf *VRF, from, to int) bool {
for i := from; i < to; i++ {
if vm.byIndex[i] == nil {
vrf.index = VRFIndex(i)
vm.byIndex[i] = vrf
vm.nextIndex = (i + 1) % len(vm.byIndex)
return true
}
}
return false
}
// should be called with lock held
func (vm *vrfManager) assignIndex(vrf *VRF) bool {
// try from the nextIndex to the end
if vm.findSlot(vrf, vm.nextIndex, len(vm.byIndex)) {
return true
}
// try from the head to the nextIndex
return vm.findSlot(vrf, 0, vm.nextIndex)
}
// should be called with lock held
func (vm *vrfManager) releaseIndex(vrf *VRF) {
vm.byIndex[int(vrf.index)] = nil
}
// NewVRF creates a VRF instance.
func NewVRF(name string) (*VRF, error) {
if !vrfMgr.re.MatchString(name) {
return nil, fmt.Errorf("Invalid VRF name: '%v'", name)
}
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
if _, exists := vrfMgr.byName[name]; exists {
return nil, fmt.Errorf("VRF %s already exists", name)
}
vrf := &VRF{
name: name,
enabled: false,
}
if !vrfMgr.assignIndex(vrf) {
return nil, fmt.Errorf("No space left for new VRF")
}
vifIndex, err := vifIdxMgr.allocVIFIndex(vrf)
if err != nil {
vrfMgr.releaseIndex(vrf)
return nil, fmt.Errorf("Can't assign VIFIndex: %v", err)
}
vrf.vifIndex = vifIndex
// Create an ICMP processor
var errMsg error
tapName := name + "-tap"
if tap, err := newInstance(tapModule, tapName, name); err != nil {
errMsg = fmt.Errorf("ICMP handler instance creation failed: %v", err)
goto error1
} else {
vrf.tap = tap
}
// Craete a router
if router, err := newRouter(vrf, name); err != nil {
errMsg = fmt.Errorf("Router instance creation failed: %v", err)
goto error2
} else {
vrf.router = router
}
// Forward all IP packets to the ICMP processor
if err := vrf.router.connect(vrf.tap.Input(), MatchIPv4DstSelf, nil); err != nil {
errMsg = errors.New("Can't connect a router and an tap modules")
goto error3
}
vrf.RoutingTable = newRoutingTable(vrf)
vrf.devs = make(map[VIFIndex]OutputDevice)
vrf.PBR = newPBR(vrf)
vrfMgr.byName[name] = vrf
noti.Notify(notifier.Add, vrf, nil)
return vrf, nil
error3:
vrf.router.free()
error2:
vrf.tap.free()
error1:
vrfMgr.releaseIndex(vrf)
return nil, errMsg
}
func (v *VRF) Free() {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
v.DeleteVIF(vif)
}
}
v.router.disconnect(MatchIPv4DstSelf, nil)
v.tap.free()
v.router.free()
delete(vrfMgr.byName, v.name)
vrfMgr.releaseIndex(v)
if err := vifIdxMgr.freeVIFIndex(v.vifIndex); err != nil {
logger.Err("Freeing VIFIndex for %v failed: %v", v.name, err)
}
if v.rd != 0 {
delete(vrfMgr.rds, v.rd)
}
noti.Notify(notifier.Delete, v, nil)
}
func (v *VRF) baseInstance() *BaseInstance {
return v.router.base
}
func (v *VRF) IsEnabled() bool {
return v.enabled
}
func (v *VRF) Enable() error {
if v.enabled {
return nil
}
if err := v.tap.enable(); err != nil {
return err
}
// Even if vrf is enabled, hostif may not be enabled.
if v.hostif != nil {
if err := v.hostif.enable(); err != nil {
// If activation of hostif fails,
// disable other functions.
v.tap.disable()
return err
}
}
if err := v.router.enable(); err != nil {
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
return err
}
v.enabled = true
return nil
}
func (v *VRF) Disable() {
if v.enabled {
v.router.disable()
v.tap.disable()
if v.hostif != nil {
v.hostif.disable()
}
v.enabled = false
}
}
// Name returns the name of the VRF.
func (v *VRF) Name() string {
return v.name
}
func (v *VRF) String() string {
return v.name
}
// Index returns a unique identifier of the VRF.
func (v *VRF) Index() VRFIndex {
return v.index
}
// VRFIndex returns a unique VIFIndex of the VRF.
// VIFIndex is used for inter-VRF routing.
func (v *VRF) VIFIndex() VIFIndex {
return v.vifIndex
}
// Input returns an input ring for the VRF
// which is the input ring for the underlying interface.
func (v *VRF) Input() *dpdk.Ring {
return v.router.base.Input()
}
// SetRD sets the route distinguisher of thr VRF.
func (v *VRF) SetRD(rd uint64) error {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
oldrd := v.rd
if _, exists := vrfMgr.rds[rd]; exists {
return fmt.Errorf("VRF RD %d already exists", rd)
}
v.rd = rd
vrfMgr.rds[rd] = struct{}{}
if oldrd != 0 {
delete(vrfMgr.rds, oldrd)
}
return nil
}
// RD returns the route distinguisher of the VRF.
func (v *VRF) RD() uint64 {
return v.rd
}
// AddVIF adds VIF to the VRF.
// If the same VIF is added more than once to the VRF,
// it sliently ignores.
func (v *VRF) AddVIF(vif *VIF) error {
var err error
if _, exists := v.devs[vif.VIFIndex()]; exists {
return nil
}
if err = vif.setVRF(v); err != nil {
return err
}
// router -> VIF
if err = v.router.addVIF(vif); err != nil {
goto error1
}
// ICMP -> VIF
if err = v.tap.connect(vif.Outbound(), MatchOutVIF, vif); err != nil {
goto error2
}
// VIF -> router (DST_SELF)
if err = vif.connect(v.router.input(), MatchEthDstSelf, nil); err != nil {
goto error3
}
// VIF -> router (broadcast)
if err = vif.connect(v.router.input(), MatchEthDstBC, nil); err != nil {
goto error4
}
// VIF -> router (multicast)
if err = vif.connect(v.router.input(), MatchEthDstMC, nil); err != nil {
goto error5
}
// Enable NAPT if needed
if vif.isNAPTEnabled() {
if err = v.enableNAPT(vif); err != nil {
goto error6
}
}
v.devs[vif.VIFIndex()] = vif
// TUN/TAP for the VIF will be created
noti.Notify(notifier.Add, v, vif)
return nil
error6:
vif.disconnect(MatchEthDstMC, nil)
error5:
vif.disconnect(MatchEthDstBC, nil)
error4:
vif.disconnect(MatchEthDstSelf, nil)
error3:
v.tap.disconnect(MatchOutVIF, vif)
error2:
v.router.deleteVIF(vif)
error1:
vif.setVRF(nil)
return err
}
func (v *VRF) DeleteVIF(vif *VIF) error {
if _, ok := v.devs[vif.VIFIndex()]; !ok {
return fmt.Errorf("Can't find %v in the VRF.", vif)
}
// Delete routes related a vif as notifications about deletion of the routes
// is not notified from netlink when the vif is deleted from a vrf.
for _, route := range v.ListEntries() {
if route.Dev.VIFIndex() == vif.VIFIndex() {
v.DeleteEntry(route)
}
}
v.tap.disconnect(MatchOutVIF, vif)
vif.disconnect(MatchEthDstSelf, nil)
vif.disconnect(MatchEthDstBC, nil)
vif.disconnect(MatchEthDstMC, nil)
vif.setVRF(nil)
v.router.deleteVIF(vif)
delete(v.devs, vif.VIFIndex())
// TUN/TAP for the VIF will be deleted
noti.Notify(notifier.Delete, v, vif)
return nil
}
// Called only when VRRP is added to VIF
func (v *VRF) vrrpEnabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
var ipv4dst *ScopedAddress
var err error
if ipv4dst, err = NewScopedAddress(VRRPMcastAddr.IP, vif); err != nil {
return
}
// Create only one hostif for vrf
if v.hostif == nil {
hostifName := v.name + "-hostif"
if v.hostif, err = newInstance(hostifModule, hostifName, v.name); err != nil {
return
} else {
if v.enabled {
if err = v.hostif.enable(); err != nil {
goto error
}
}
}
}
// Add packet forwarding rule
// router -> hostif
// VRRP advertisement multicast address.
if err = v.router.connect(v.hostif.Input(), MatchIPv4DstInVIF, ipv4dst); err != nil {
goto error
}
v.vrrpref++
return
error:
if v.vrrpref == 0 {
v.hostif.free()
v.hostif = nil
}
}
// Called only when VRRP is deleted from VIF
func (v *VRF) vrrpDisabled(vif *VIF) {
v.vrrpMutex.Lock()
defer v.vrrpMutex.Unlock()
ipv4dst, err := NewScopedAddress(VRRPMcastAddr.IP, vif)
if err != nil {
return
}
v.router.disconnect(MatchIPv4DstInVIF, ipv4dst)
if v.hostif != nil && v.vrrpref == 1 {
v.hostif.free()
v.hostif = nil
}
v.vrrpref--
}
// VIF returns a slice of Vif Indices in the VRF.
func (v *VRF) VIF() []*VIF {
var vifs []*VIF
for _, dev := range v.devs {
if vif, ok := dev.(*VIF); ok {
vifs = append(vifs, vif)
}
}
return vifs
}
// Dump returns descriptive information about the VRF
func (v *VRF) Dump() string {
str := fmt.Sprintf("%s: RD=%d. %d DEV(s):", v.name, v.rd, len(v.devs))
for _, dev := range v.devs {
str += fmt.Sprintf(" %v", dev)
}
if v.sadb != nil {
sad := v.sadb.SAD()
str += fmt.Sprintf("\n%d SAD", len(sad))
for _, sa := range sad {
str += fmt.Sprintf("\n\t%v", sa)
}
spd := v.sadb.SPD()
str += fmt.Sprintf("\n%d SPD", len(spd))
for _, sp := range spd {
str += fmt.Sprintf("\n\t%v", sp)
}
}
return str
}
// SADatabases returns SADatabases associated with the VRF.
func (v *VRF) SADatabases() *SADatabases {
v.sadbOnce.Do(func() {
v.sadb = newSADatabases(v)
})
return v.sadb
}
// HasSADatabases returns true if the VRF has associated SADatbases.
// Returns false otherwise.
func (v *VRF) HasSADatabases() bool {
return v.sadb != nil
}
func createFiveTuples(remotes []net.IP, local net.IP, proto IPProto, dstPort PortRange) []*FiveTuple {
fiveTuples := make([]*FiveTuple, len(remotes))
for i, remote := range remotes {
ft := NewFiveTuple()
ft.SrcIP = CreateIPAddr(remote)
ft.DstIP = CreateIPAddr(local)
ft.DstPort = dstPort
ft.Proto = proto
fiveTuples[i] = ft
}
return fiveTuples
}
func (v *VRF) addL3Tunnel(vif *VIF) error {
t := vif.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", vif)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := vif.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L3 tunnel: %v", vif, err)
}
// Forward inbound packets to L3 Tunnel
fts := createFiveTuples(ra, t.local, t.IPProto(), PortRange{})
for i, ft := range fts {
if err := v.router.connect(vif.Inbound(), Match5Tuple, ft); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:i] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Adding a rule to router for L3 tunnel failed: %v", err)
}
}
// Add a rule for NAT Traversal, if the tunnel is IPSec.
if t.Security() == SecurityIPSec {
nats := createFiveTuples(ra, t.local, IPP_UDP, PortRange{Start: 4500})
for i, nat := range nats {
if err := v.router.connect(vif.Inbound(), Match5Tuple, nat); err != nil {
vif.disconnect(MatchIPv4Dst, &ra[0])
for _, ft := range fts {
v.router.disconnect(Match5Tuple, ft)
}
for _, addedNat := range nats[0:i] {
v.router.disconnect(Match5Tuple, addedNat)
}
return fmt.Errorf("Adding a rule for IPSec NAT traversal failed: %v", err)
}
}
}
return nil
}
func (v *VRF) deleteL3Tunnel(vif *VIF) {
t := vif.Tunnel()
for _, ft := range createFiveTuples(t.remotes, t.local, t.IPProto(), PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
|
vif.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func createVxLANs(remotes []net.IP, local net.IP, dstPort uint16, vni uint32) []*VxLAN {
vxlans := make([]*VxLAN, len(remotes))
for i, remote := range remotes {
vxlan := &VxLAN{
Src: remote,
Dst: local,
DstPort: dstPort,
VNI: vni,
}
vxlans[i] = vxlan
}
return vxlans
}
func (v *VRF) addL2Tunnel(i *Interface) error {
t := i.Tunnel()
if t == nil {
return fmt.Errorf("%v is not tunnel.", i)
}
ra := t.RemoteAddresses()
if len(ra) == 0 {
return fmt.Errorf("No remote address(es) specified: %v.", t)
}
if err := i.connect(v.router.input(), MatchIPv4Dst, &ra[0]); err != nil {
return fmt.Errorf("Adding a rule to %v failed for L2 tunnel: %v", i, err)
}
// Forward inbound packets to L2 Tunnel
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
fts := createFiveTuples(ra, t.local, IPP_GRE, PortRange{})
for idx, ft := range fts {
if err := v.router.connect(i.Inbound(), Match5Tuple, ft); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedFt := range fts[0:idx] {
v.router.disconnect(Match5Tuple, addedFt)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
case EncapsMethodVxLAN:
vxlans := createVxLANs(ra, t.local, t.vxlanPort, t.vni)
for idx, vxlan := range vxlans {
if err := v.router.connect(i.Inbound(), MatchVxLAN, vxlan); err != nil {
i.disconnect(MatchIPv4Dst, &ra[0])
for _, addedVxLAN := range vxlans[0:idx] {
v.router.disconnect(Match5Tuple, addedVxLAN)
}
return fmt.Errorf("Can't connect L2 tunnel to the router: %v", err)
}
}
default:
return fmt.Errorf("Unsupported L2 Tunnel encaps method: %v", e)
}
return nil
}
func (v *VRF) deleteL2Tunnel(i *Interface) {
t := i.Tunnel()
switch e := t.EncapsMethod(); e {
case EncapsMethodGRE:
for _, ft := range createFiveTuples(t.remotes, t.local, IPP_GRE, PortRange{}) {
v.router.disconnect(Match5Tuple, ft)
}
case EncapsMethodVxLAN:
for _, vxlan := range createVxLANs(t.remotes, t.local, t.vxlanPort, t.vni) {
v.router.disconnect(MatchVxLAN, vxlan)
}
}
i.disconnect(MatchIPv4Dst, &(t.RemoteAddresses()[0]))
}
func (v *VRF) enableNAPT(vif *VIF) error {
return v.router.enableNAPT(vif)
}
func (v *VRF) disableNAPT(vif *VIF) error {
return v.router.disableNAPT(vif)
}
func (v *VRF) MarshalJSON() ([]byte, error) {
return []byte(`"` + v.name + `"`), nil
}
func (v *VRF) registerOutputDevice(dev OutputDevice) error {
// If OutputDevice is already in devs, it means the OutputDevice
// is either VIF, or VRF that has already been added.
if _, exists := v.devs[dev.VIFIndex()]; exists {
return nil
}
// OutputDevice to be added shall be VRF.
// If OutputDevice is VIF, it should have been added via AddVIF already.
if _, ok := dev.(*VRF); !ok {
return fmt.Errorf("OutputDevice is not VRF: %v", dev)
}
// Add VRF to router instance
if err := v.router.addOutputDevice(dev); err != nil {
return fmt.Errorf("Adding OutputDevice %v failed.", dev)
}
v.devs[dev.VIFIndex()] = dev
return nil
}
func (v *VRF) routeEntryAdded(entry Route) {
// Check if all OutputDevice that appears in Route has already
// been registered to the router instance.
if len(entry.Nexthops) == 0 {
if err := v.registerOutputDevice(entry.Dev); err != nil {
logger.Err("%v", err)
return
}
} else {
for _, nh := range entry.Nexthops {
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) routeEntryDeleted(entry Route) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
func (v *VRF) pbrEntryAdded(entry *PBREntry) {
for _, nh := range entry.NextHops {
if nh.Dev == nil {
continue
}
if err := v.registerOutputDevice(nh.Dev); err != nil {
logger.Err("%v", err)
return
}
}
noti.Notify(notifier.Add, v, entry)
}
func (v *VRF) pbrEntryDeleted(entry *PBREntry) {
// TODO: Remove unused VRF from the router instance
noti.Notify(notifier.Delete, v, entry)
}
// GetAllVRF returns a slice of available VRF.
func GetAllVRF() []*VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
v := make([]*VRF, len(vrfMgr.byName))
n := 0
for _, vrf := range vrfMgr.byName {
v[n] = vrf
n++
}
return v
}
// GetVRFByName returns a VRF with the given name.
func GetVRFByName(name string) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byName[name]
}
// GetVRFByIndex returns a VRF with the given index.
func GetVRFByIndex(index VRFIndex) *VRF {
vrfMgr.mutex.Lock()
defer vrfMgr.mutex.Unlock()
return vrfMgr.byIndex[int(index)]
} | if t.Security() == SecurityIPSec {
for _, nat := range createFiveTuples(t.remotes, t.local, IPP_UDP, PortRange{Start: 4500}) {
v.router.disconnect(Match5Tuple, nat)
}
} | random_line_split |
brush.rs | // Copyright © 2020 Cormac O'Brien.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
use std::{
borrow::Cow,
cell::{Cell, RefCell},
collections::HashMap,
mem::size_of,
num::NonZeroU32,
ops::Range,
rc::Rc,
};
use crate::{
client::render::{
pipeline::PushConstantUpdate,
warp,
world::{BindGroupLayoutId, WorldPipelineBase},
Camera, GraphicsState, LightmapData, Pipeline, TextureData,
},
common::{
bsp::{
self, BspData, BspFace, BspLeaf, BspModel, BspTexInfo, BspTexture, BspTextureKind,
BspTextureMipmap,
},
math,
util::any_slice_as_bytes,
},
};
use bumpalo::Bump;
use cgmath::{InnerSpace as _, Matrix4, Vector3};
use chrono::Duration;
use failure::Error;
pub struct BrushPipeline {
pipeline: wgpu::RenderPipeline,
bind_group_layouts: Vec<wgpu::BindGroupLayout>,
}
impl BrushPipeline {
pub fn new(
device: &wgpu::Device,
queue: &wgpu::Queue,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) -> BrushPipeline {
let (pipeline, bind_group_layouts) =
BrushPipeline::create(device, compiler, world_bind_group_layouts, sample_count);
BrushPipeline {
pipeline,
// TODO: pick a starting capacity
bind_group_layouts,
}
}
pub fn rebuild(
&mut self,
device: &wgpu::Device,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) {
let layout_refs: Vec<_> = world_bind_group_layouts
.iter()
.chain(self.bind_group_layouts.iter())
.collect();
self.pipeline = BrushPipeline::recreate(device, compiler, &layout_refs, sample_count);
}
pub fn pipeline(&self) -> &wgpu::RenderPipeline {
&self.pipeline
}
pub fn bind_group_layouts(&self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupLayoutId::PerTexture as usize);
&self.bind_group_layouts[id as usize - BindGroupLayoutId::PerTexture as usize]
}
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct VertexPushConstants {
pub transform: Matrix4<f32>,
pub model_view: Matrix4<f32>,
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct SharedPushConstants {
pub texture_kind: u32,
}
const BIND_GROUP_LAYOUT_ENTRIES: &[&[wgpu::BindGroupLayoutEntry]] = &[
&[
// diffuse texture, updated once per face
wgpu::BindGroupLayoutEntry {
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
// fullbright texture
wgpu::BindGroupLayoutEntry {
binding: 1,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
],
&[
// lightmap texture array
wgpu::BindGroupLayoutEntry {
count: NonZeroU32::new(4),
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
},
],
];
lazy_static! {
static ref VERTEX_ATTRIBUTES: [wgpu::VertexAttribute; 5] =
wgpu::vertex_attr_array![
// position
0 => Float32x3,
// normal
1 => Float32x3,
// diffuse texcoord
2 => Float32x2,
// lightmap texcoord
3 => Float32x2,
// lightmap animation ids
4 => Uint8x4,
];
}
impl Pipeline for BrushPipeline {
type VertexPushConstants = VertexPushConstants;
type SharedPushConstants = SharedPushConstants;
type FragmentPushConstants = ();
fn name() -> &'static str {
"brush"
}
fn vertex_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.vert"))
}
fn fragment_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.frag"))
}
// NOTE: if any of the binding indices are changed, they must also be changed in
// the corresponding shaders and the BindGroupLayout generation functions.
fn bind_group_layout_descriptors() -> Vec<wgpu::BindGroupLayoutDescriptor<'static>> {
vec![
// group 2: updated per-texture
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-texture bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[0],
},
// group 3: updated per-face
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-face bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[1],
},
]
}
fn primitive_state() -> wgpu::PrimitiveState {
WorldPipelineBase::primitive_state()
}
fn color_target_states() -> Vec<wgpu::ColorTargetState> {
WorldPipelineBase::color_target_states()
}
fn depth_stencil_state() -> Option<wgpu::DepthStencilState> {
WorldPipelineBase::depth_stencil_state()
}
// NOTE: if the vertex format is changed, this descriptor must also be changed accordingly.
fn vertex_buffer_layouts() -> Vec<wgpu::VertexBufferLayout<'static>> {
vec![wgpu::VertexBufferLayout {
array_stride: size_of::<BrushVertex>() as u64,
step_mode: wgpu::InputStepMode::Vertex,
attributes: &VERTEX_ATTRIBUTES[..],
}]
}
}
fn calculate_lightmap_texcoords(
position: Vector3<f32>,
face: &BspFace,
texinfo: &BspTexInfo,
) -> [f32; 2] {
let mut s = texinfo.s_vector.dot(position) + texinfo.s_offset;
s -= (face.texture_mins[0] as f32 / 16.0).floor() * 16.0;
s += 0.5;
s /= face.extents[0] as f32;
let mut t = texinfo.t_vector.dot(position) + texinfo.t_offset;
t -= (face.texture_mins[1] as f32 / 16.0).floor() * 16.0;
t += 0.5;
t /= face.extents[1] as f32;
[s, t]
}
type Position = [f32; 3];
type Normal = [f32; 3];
type DiffuseTexcoord = [f32; 2];
type LightmapTexcoord = [f32; 2];
type LightmapAnim = [u8; 4];
#[repr(C)]
#[derive(Clone, Copy, Debug)]
struct BrushVertex {
position: Position,
normal: Normal,
diffuse_texcoord: DiffuseTexcoord,
lightmap_texcoord: LightmapTexcoord,
lightmap_anim: LightmapAnim,
}
#[repr(u32)]
#[derive(Clone, Copy, Debug)]
pub enum TextureKind {
Normal = 0,
Warp = 1,
Sky = 2,
}
/// A single frame of a brush texture.
pub struct BrushTextureFrame {
bind_group_id: usize,
diffuse: wgpu::Texture,
fullbright: wgpu::Texture,
diffuse_view: wgpu::TextureView,
fullbright_view: wgpu::TextureView,
kind: TextureKind,
}
/// A brush texture.
pub enum BrushTexture {
/// A brush texture with a single frame.
Static(BrushTextureFrame),
/// A brush texture with multiple frames.
///
/// Animated brush textures advance one frame every 200 milliseconds, i.e.,
/// they have a framerate of 5 fps.
Animated {
primary: Vec<BrushTextureFrame>,
alternate: Option<Vec<BrushTextureFrame>>,
},
}
impl BrushTexture {
fn kind(&self) -> TextureKind {
match self {
BrushTexture::Static(ref frame) => frame.kind,
BrushTexture::Animated { ref primary, .. } => primary[0].kind,
}
}
}
#[derive(Debug)]
struct BrushFace {
vertices: Range<u32>,
min: Vector3<f32>,
max: Vector3<f32>,
texture_id: usize,
lightmap_ids: Vec<usize>,
light_styles: [u8; 4],
/// Indicates whether the face should be drawn this frame.
///
/// This is set to false by default, and will be set to true if the model is
/// a worldmodel and the containing leaf is in the PVS. If the model is not
/// a worldmodel, this flag is ignored.
draw_flag: Cell<bool>,
}
struct BrushLeaf {
facelist_ids: Range<usize>,
}
impl<B> std::convert::From<B> for BrushLeaf
where
B: std::borrow::Borrow<BspLeaf>,
{
fn from(bsp_leaf: B) -> Self {
let bsp_leaf = bsp_leaf.borrow();
BrushLeaf {
facelist_ids: bsp_leaf.facelist_id..bsp_leaf.facelist_id + bsp_leaf.facelist_count,
}
}
}
pub struct BrushRendererBuilder {
bsp_data: Rc<BspData>,
face_range: Range<usize>,
leaves: Option<Vec<BrushLeaf>>,
per_texture_bind_groups: RefCell<Vec<wgpu::BindGroup>>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
vertices: Vec<BrushVertex>,
faces: Vec<BrushFace>,
texture_chains: HashMap<usize, Vec<usize>>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRendererBuilder {
pub fn new(bsp_model: &BspModel, worldmodel: bool) -> BrushRendererBuilder {
BrushRendererBuilder {
bsp_data: bsp_model.bsp_data().clone(),
face_range: bsp_model.face_id..bsp_model.face_id + bsp_model.face_count,
leaves: if worldmodel {
Some(
bsp_model
.iter_leaves()
.map(|leaf| BrushLeaf::from(leaf))
.collect(),
)
} else {
None
},
per_texture_bind_groups: RefCell::new(Vec::new()),
per_face_bind_groups: Vec::new(),
vertices: Vec::new(),
faces: Vec::new(),
texture_chains: HashMap::new(),
textures: Vec::new(),
lightmaps: Vec::new(),
//lightmap_views: Vec::new(),
}
}
fn create_face(&mut self, state: &GraphicsState, face_id: usize) -> BrushFace {
let face = &self.bsp_data.faces()[face_id];
let face_vert_id = self.vertices.len();
let texinfo = &self.bsp_data.texinfo()[face.texinfo_id];
let tex = &self.bsp_data.textures()[texinfo.tex_id];
let mut min = Vector3::new(f32::INFINITY, f32::INFINITY, f32::INFINITY);
let mut max = Vector3::new(f32::NEG_INFINITY, f32::NEG_INFINITY, f32::NEG_INFINITY);
let no_collinear =
math::remove_collinear(self.bsp_data.face_iter_vertices(face_id).collect());
for vert in no_collinear.iter() {
for component in 0..3 {
min[component] = min[component].min(vert[component]);
max[component] = max[component].max(vert[component]);
}
}
if tex.name().starts_with("*") {
// tessellate the surface so we can do texcoord warping
let verts = warp::subdivide(no_collinear);
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
for vert in verts.into_iter() {
self.vertices.push(BrushVertex {
position: vert.into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(vert.into(), face, texinfo),
lightmap_anim: face.light_styles,
})
}
} else {
// expand the vertices into a triangle list.
// the vertices are guaranteed to be in valid triangle fan order (that's
// how GLQuake renders them) so we expand from triangle fan to triangle
// list order.
//
// v1 is the base vertex, so it remains constant.
// v2 takes the previous value of v3.
// v3 is the newest vertex.
let verts = no_collinear;
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
let mut vert_iter = verts.into_iter();
let v1 = vert_iter.next().unwrap();
let mut v2 = vert_iter.next().unwrap();
for v3 in vert_iter {
let tri = &[v1, v2, v3];
// skip collinear points
for vert in tri.iter() {
self.vertices.push(BrushVertex {
position: (*vert).into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(
(*vert).into(),
face,
texinfo,
),
lightmap_anim: face.light_styles,
});
}
v2 = v3;
}
}
// build the lightmaps
let lightmaps = if !texinfo.special {
self.bsp_data.face_lightmaps(face_id)
} else {
Vec::new()
};
let mut lightmap_ids = Vec::new();
for lightmap in lightmaps {
let lightmap_data = TextureData::Lightmap(LightmapData { | let texture =
state.create_texture(None, lightmap.width(), lightmap.height(), &lightmap_data);
let id = self.lightmaps.len();
self.lightmaps.push(texture);
//self.lightmap_views
//.push(self.lightmaps[id].create_view(&Default::default()));
lightmap_ids.push(id);
}
BrushFace {
vertices: face_vert_id as u32..self.vertices.len() as u32,
min,
max,
texture_id: texinfo.tex_id as usize,
lightmap_ids,
light_styles: face.light_styles,
draw_flag: Cell::new(true),
}
}
fn create_per_texture_bind_group(
&self,
state: &GraphicsState,
tex: &BrushTextureFrame,
) -> wgpu::BindGroup {
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerTexture);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-texture bind group"),
layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureView(&tex.diffuse_view),
},
wgpu::BindGroupEntry {
binding: 1,
resource: wgpu::BindingResource::TextureView(&tex.fullbright_view),
},
],
};
state.device().create_bind_group(&desc)
}
fn create_per_face_bind_group(&self, state: &GraphicsState, face_id: usize) -> wgpu::BindGroup {
let mut lightmap_views: Vec<_> = self.faces[face_id]
.lightmap_ids
.iter()
.map(|id| self.lightmaps[*id].create_view(&Default::default()))
.collect();
lightmap_views.resize_with(4, || {
state.default_lightmap().create_view(&Default::default())
});
let lightmap_view_refs = lightmap_views.iter().collect::<Vec<_>>();
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerFace);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-face bind group"),
layout,
entries: &[wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureViewArray(&lightmap_view_refs[..]),
}],
};
state.device().create_bind_group(&desc)
}
fn create_brush_texture_frame<S>(
&self,
state: &GraphicsState,
mipmap: &[u8],
width: u32,
height: u32,
name: S,
) -> BrushTextureFrame
where
S: AsRef<str>,
{
let name = name.as_ref();
let (diffuse_data, fullbright_data) = state.palette().translate(mipmap);
let diffuse =
state.create_texture(None, width, height, &TextureData::Diffuse(diffuse_data));
let fullbright = state.create_texture(
None,
width,
height,
&TextureData::Fullbright(fullbright_data),
);
let diffuse_view = diffuse.create_view(&Default::default());
let fullbright_view = fullbright.create_view(&Default::default());
let kind = if name.starts_with("sky") {
TextureKind::Sky
} else if name.starts_with("*") {
TextureKind::Warp
} else {
TextureKind::Normal
};
let mut frame = BrushTextureFrame {
bind_group_id: 0,
diffuse,
fullbright,
diffuse_view,
fullbright_view,
kind,
};
// generate texture bind group
let per_texture_bind_group = self.create_per_texture_bind_group(state, &frame);
let bind_group_id = self.per_texture_bind_groups.borrow().len();
self.per_texture_bind_groups
.borrow_mut()
.push(per_texture_bind_group);
frame.bind_group_id = bind_group_id;
frame
}
pub fn create_brush_texture(&self, state: &GraphicsState, tex: &BspTexture) -> BrushTexture {
// TODO: upload mipmaps
let (width, height) = tex.dimensions();
match tex.kind() {
// sequence animated textures
BspTextureKind::Animated { primary, alternate } => {
let primary_frames: Vec<_> = primary
.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect();
let alternate_frames: Option<Vec<_>> = alternate.as_ref().map(|a| {
a.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect()
});
BrushTexture::Animated {
primary: primary_frames,
alternate: alternate_frames,
}
}
BspTextureKind::Static(bsp_tex) => {
BrushTexture::Static(self.create_brush_texture_frame(
state,
bsp_tex.mipmap(BspTextureMipmap::Full),
tex.width(),
tex.height(),
tex.name(),
))
}
}
}
pub fn build(mut self, state: &GraphicsState) -> Result<BrushRenderer, Error> {
// create the diffuse and fullbright textures
for tex in self.bsp_data.textures().iter() {
self.textures.push(self.create_brush_texture(state, tex));
}
// generate faces, vertices and lightmaps
// bsp_face_id is the id of the face in the bsp data
// face_id is the new id of the face in the renderer
for bsp_face_id in self.face_range.start..self.face_range.end {
let face_id = self.faces.len();
let face = self.create_face(state, bsp_face_id);
self.faces.push(face);
let face_tex_id = self.faces[face_id].texture_id;
// update the corresponding texture chain
self.texture_chains
.entry(face_tex_id)
.or_insert(Vec::new())
.push(face_id);
// generate face bind group
let per_face_bind_group = self.create_per_face_bind_group(state, face_id);
self.per_face_bind_groups.push(per_face_bind_group);
}
use wgpu::util::DeviceExt as _;
let vertex_buffer = state
.device()
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: None,
contents: unsafe { any_slice_as_bytes(self.vertices.as_slice()) },
usage: wgpu::BufferUsage::VERTEX,
});
Ok(BrushRenderer {
bsp_data: self.bsp_data,
vertex_buffer,
leaves: self.leaves,
per_texture_bind_groups: self.per_texture_bind_groups.into_inner(),
per_face_bind_groups: self.per_face_bind_groups,
texture_chains: self.texture_chains,
faces: self.faces,
textures: self.textures,
lightmaps: self.lightmaps,
//lightmap_views: self.lightmap_views,
})
}
}
pub struct BrushRenderer {
bsp_data: Rc<BspData>,
leaves: Option<Vec<BrushLeaf>>,
vertex_buffer: wgpu::Buffer,
per_texture_bind_groups: Vec<wgpu::BindGroup>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
// faces are grouped by texture to reduce the number of texture rebinds
// texture_chains maps texture ids to face ids
texture_chains: HashMap<usize, Vec<usize>>,
faces: Vec<BrushFace>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRenderer {
/// Record the draw commands for this brush model to the given `wgpu::RenderPass`.
pub fn record_draw<'a>(
&'a self,
state: &'a GraphicsState,
pass: &mut wgpu::RenderPass<'a>,
bump: &'a Bump,
time: Duration,
camera: &Camera,
frame_id: usize,
) {
pass.set_pipeline(state.brush_pipeline().pipeline());
pass.set_vertex_buffer(0, self.vertex_buffer.slice(..));
// if this is a worldmodel, mark faces to be drawn
if let Some(ref leaves) = self.leaves {
let pvs = self
.bsp_data
.get_pvs(self.bsp_data.find_leaf(camera.origin), leaves.len());
// only draw faces in pvs
for leaf_id in pvs {
for facelist_id in leaves[leaf_id].facelist_ids.clone() {
let face = &self.faces[self.bsp_data.facelist()[facelist_id]];
// TODO: frustum culling
face.draw_flag.set(true);
}
}
}
for (tex_id, face_ids) in self.texture_chains.iter() {
use PushConstantUpdate::*;
BrushPipeline::set_push_constants(
pass,
Retain,
Update(bump.alloc(SharedPushConstants {
texture_kind: self.textures[*tex_id].kind() as u32,
})),
Retain,
);
let bind_group_id = match &self.textures[*tex_id] {
BrushTexture::Static(ref frame) => frame.bind_group_id,
BrushTexture::Animated { primary, alternate } => {
// if frame is not zero and this texture has an alternate
// animation, use it
let anim = if frame_id == 0 {
primary
} else if let Some(a) = alternate {
a
} else {
primary
};
let time_ms = time.num_milliseconds();
let total_ms = (bsp::frame_duration() * anim.len() as i32).num_milliseconds();
let anim_ms = if total_ms == 0 { 0 } else { time_ms % total_ms };
anim[(anim_ms / bsp::frame_duration().num_milliseconds()) as usize]
.bind_group_id
}
};
pass.set_bind_group(
BindGroupLayoutId::PerTexture as u32,
&self.per_texture_bind_groups[bind_group_id],
&[],
);
for face_id in face_ids.iter() {
let face = &self.faces[*face_id];
// only skip the face if we have visibility data but it's not marked
if self.leaves.is_some() && !face.draw_flag.replace(false) {
continue;
}
pass.set_bind_group(
BindGroupLayoutId::PerFace as u32,
&self.per_face_bind_groups[*face_id],
&[],
);
pass.draw(face.vertices.clone(), 0..1);
}
}
}
} | lightmap: Cow::Borrowed(lightmap.data()),
});
| random_line_split |
brush.rs | // Copyright © 2020 Cormac O'Brien.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
use std::{
borrow::Cow,
cell::{Cell, RefCell},
collections::HashMap,
mem::size_of,
num::NonZeroU32,
ops::Range,
rc::Rc,
};
use crate::{
client::render::{
pipeline::PushConstantUpdate,
warp,
world::{BindGroupLayoutId, WorldPipelineBase},
Camera, GraphicsState, LightmapData, Pipeline, TextureData,
},
common::{
bsp::{
self, BspData, BspFace, BspLeaf, BspModel, BspTexInfo, BspTexture, BspTextureKind,
BspTextureMipmap,
},
math,
util::any_slice_as_bytes,
},
};
use bumpalo::Bump;
use cgmath::{InnerSpace as _, Matrix4, Vector3};
use chrono::Duration;
use failure::Error;
pub struct BrushPipeline {
pipeline: wgpu::RenderPipeline,
bind_group_layouts: Vec<wgpu::BindGroupLayout>,
}
impl BrushPipeline {
pub fn new(
device: &wgpu::Device,
queue: &wgpu::Queue,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) -> BrushPipeline {
let (pipeline, bind_group_layouts) =
BrushPipeline::create(device, compiler, world_bind_group_layouts, sample_count);
BrushPipeline {
pipeline,
// TODO: pick a starting capacity
bind_group_layouts,
}
}
pub fn rebuild(
&mut self,
device: &wgpu::Device,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) { |
pub fn pipeline(&self) -> &wgpu::RenderPipeline {
&self.pipeline
}
pub fn bind_group_layouts(&self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupLayoutId::PerTexture as usize);
&self.bind_group_layouts[id as usize - BindGroupLayoutId::PerTexture as usize]
}
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct VertexPushConstants {
pub transform: Matrix4<f32>,
pub model_view: Matrix4<f32>,
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct SharedPushConstants {
pub texture_kind: u32,
}
const BIND_GROUP_LAYOUT_ENTRIES: &[&[wgpu::BindGroupLayoutEntry]] = &[
&[
// diffuse texture, updated once per face
wgpu::BindGroupLayoutEntry {
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
// fullbright texture
wgpu::BindGroupLayoutEntry {
binding: 1,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
],
&[
// lightmap texture array
wgpu::BindGroupLayoutEntry {
count: NonZeroU32::new(4),
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
},
],
];
lazy_static! {
static ref VERTEX_ATTRIBUTES: [wgpu::VertexAttribute; 5] =
wgpu::vertex_attr_array![
// position
0 => Float32x3,
// normal
1 => Float32x3,
// diffuse texcoord
2 => Float32x2,
// lightmap texcoord
3 => Float32x2,
// lightmap animation ids
4 => Uint8x4,
];
}
impl Pipeline for BrushPipeline {
type VertexPushConstants = VertexPushConstants;
type SharedPushConstants = SharedPushConstants;
type FragmentPushConstants = ();
fn name() -> &'static str {
"brush"
}
fn vertex_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.vert"))
}
fn fragment_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.frag"))
}
// NOTE: if any of the binding indices are changed, they must also be changed in
// the corresponding shaders and the BindGroupLayout generation functions.
fn bind_group_layout_descriptors() -> Vec<wgpu::BindGroupLayoutDescriptor<'static>> {
vec![
// group 2: updated per-texture
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-texture bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[0],
},
// group 3: updated per-face
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-face bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[1],
},
]
}
fn primitive_state() -> wgpu::PrimitiveState {
WorldPipelineBase::primitive_state()
}
fn color_target_states() -> Vec<wgpu::ColorTargetState> {
WorldPipelineBase::color_target_states()
}
fn depth_stencil_state() -> Option<wgpu::DepthStencilState> {
WorldPipelineBase::depth_stencil_state()
}
// NOTE: if the vertex format is changed, this descriptor must also be changed accordingly.
fn vertex_buffer_layouts() -> Vec<wgpu::VertexBufferLayout<'static>> {
vec![wgpu::VertexBufferLayout {
array_stride: size_of::<BrushVertex>() as u64,
step_mode: wgpu::InputStepMode::Vertex,
attributes: &VERTEX_ATTRIBUTES[..],
}]
}
}
fn calculate_lightmap_texcoords(
position: Vector3<f32>,
face: &BspFace,
texinfo: &BspTexInfo,
) -> [f32; 2] {
let mut s = texinfo.s_vector.dot(position) + texinfo.s_offset;
s -= (face.texture_mins[0] as f32 / 16.0).floor() * 16.0;
s += 0.5;
s /= face.extents[0] as f32;
let mut t = texinfo.t_vector.dot(position) + texinfo.t_offset;
t -= (face.texture_mins[1] as f32 / 16.0).floor() * 16.0;
t += 0.5;
t /= face.extents[1] as f32;
[s, t]
}
type Position = [f32; 3];
type Normal = [f32; 3];
type DiffuseTexcoord = [f32; 2];
type LightmapTexcoord = [f32; 2];
type LightmapAnim = [u8; 4];
#[repr(C)]
#[derive(Clone, Copy, Debug)]
struct BrushVertex {
position: Position,
normal: Normal,
diffuse_texcoord: DiffuseTexcoord,
lightmap_texcoord: LightmapTexcoord,
lightmap_anim: LightmapAnim,
}
#[repr(u32)]
#[derive(Clone, Copy, Debug)]
pub enum TextureKind {
Normal = 0,
Warp = 1,
Sky = 2,
}
/// A single frame of a brush texture.
pub struct BrushTextureFrame {
bind_group_id: usize,
diffuse: wgpu::Texture,
fullbright: wgpu::Texture,
diffuse_view: wgpu::TextureView,
fullbright_view: wgpu::TextureView,
kind: TextureKind,
}
/// A brush texture.
pub enum BrushTexture {
/// A brush texture with a single frame.
Static(BrushTextureFrame),
/// A brush texture with multiple frames.
///
/// Animated brush textures advance one frame every 200 milliseconds, i.e.,
/// they have a framerate of 5 fps.
Animated {
primary: Vec<BrushTextureFrame>,
alternate: Option<Vec<BrushTextureFrame>>,
},
}
impl BrushTexture {
fn kind(&self) -> TextureKind {
match self {
BrushTexture::Static(ref frame) => frame.kind,
BrushTexture::Animated { ref primary, .. } => primary[0].kind,
}
}
}
#[derive(Debug)]
struct BrushFace {
vertices: Range<u32>,
min: Vector3<f32>,
max: Vector3<f32>,
texture_id: usize,
lightmap_ids: Vec<usize>,
light_styles: [u8; 4],
/// Indicates whether the face should be drawn this frame.
///
/// This is set to false by default, and will be set to true if the model is
/// a worldmodel and the containing leaf is in the PVS. If the model is not
/// a worldmodel, this flag is ignored.
draw_flag: Cell<bool>,
}
struct BrushLeaf {
facelist_ids: Range<usize>,
}
impl<B> std::convert::From<B> for BrushLeaf
where
B: std::borrow::Borrow<BspLeaf>,
{
fn from(bsp_leaf: B) -> Self {
let bsp_leaf = bsp_leaf.borrow();
BrushLeaf {
facelist_ids: bsp_leaf.facelist_id..bsp_leaf.facelist_id + bsp_leaf.facelist_count,
}
}
}
pub struct BrushRendererBuilder {
bsp_data: Rc<BspData>,
face_range: Range<usize>,
leaves: Option<Vec<BrushLeaf>>,
per_texture_bind_groups: RefCell<Vec<wgpu::BindGroup>>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
vertices: Vec<BrushVertex>,
faces: Vec<BrushFace>,
texture_chains: HashMap<usize, Vec<usize>>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRendererBuilder {
pub fn new(bsp_model: &BspModel, worldmodel: bool) -> BrushRendererBuilder {
BrushRendererBuilder {
bsp_data: bsp_model.bsp_data().clone(),
face_range: bsp_model.face_id..bsp_model.face_id + bsp_model.face_count,
leaves: if worldmodel {
Some(
bsp_model
.iter_leaves()
.map(|leaf| BrushLeaf::from(leaf))
.collect(),
)
} else {
None
},
per_texture_bind_groups: RefCell::new(Vec::new()),
per_face_bind_groups: Vec::new(),
vertices: Vec::new(),
faces: Vec::new(),
texture_chains: HashMap::new(),
textures: Vec::new(),
lightmaps: Vec::new(),
//lightmap_views: Vec::new(),
}
}
fn create_face(&mut self, state: &GraphicsState, face_id: usize) -> BrushFace {
let face = &self.bsp_data.faces()[face_id];
let face_vert_id = self.vertices.len();
let texinfo = &self.bsp_data.texinfo()[face.texinfo_id];
let tex = &self.bsp_data.textures()[texinfo.tex_id];
let mut min = Vector3::new(f32::INFINITY, f32::INFINITY, f32::INFINITY);
let mut max = Vector3::new(f32::NEG_INFINITY, f32::NEG_INFINITY, f32::NEG_INFINITY);
let no_collinear =
math::remove_collinear(self.bsp_data.face_iter_vertices(face_id).collect());
for vert in no_collinear.iter() {
for component in 0..3 {
min[component] = min[component].min(vert[component]);
max[component] = max[component].max(vert[component]);
}
}
if tex.name().starts_with("*") {
// tessellate the surface so we can do texcoord warping
let verts = warp::subdivide(no_collinear);
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
for vert in verts.into_iter() {
self.vertices.push(BrushVertex {
position: vert.into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(vert.into(), face, texinfo),
lightmap_anim: face.light_styles,
})
}
} else {
// expand the vertices into a triangle list.
// the vertices are guaranteed to be in valid triangle fan order (that's
// how GLQuake renders them) so we expand from triangle fan to triangle
// list order.
//
// v1 is the base vertex, so it remains constant.
// v2 takes the previous value of v3.
// v3 is the newest vertex.
let verts = no_collinear;
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
let mut vert_iter = verts.into_iter();
let v1 = vert_iter.next().unwrap();
let mut v2 = vert_iter.next().unwrap();
for v3 in vert_iter {
let tri = &[v1, v2, v3];
// skip collinear points
for vert in tri.iter() {
self.vertices.push(BrushVertex {
position: (*vert).into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(
(*vert).into(),
face,
texinfo,
),
lightmap_anim: face.light_styles,
});
}
v2 = v3;
}
}
// build the lightmaps
let lightmaps = if !texinfo.special {
self.bsp_data.face_lightmaps(face_id)
} else {
Vec::new()
};
let mut lightmap_ids = Vec::new();
for lightmap in lightmaps {
let lightmap_data = TextureData::Lightmap(LightmapData {
lightmap: Cow::Borrowed(lightmap.data()),
});
let texture =
state.create_texture(None, lightmap.width(), lightmap.height(), &lightmap_data);
let id = self.lightmaps.len();
self.lightmaps.push(texture);
//self.lightmap_views
//.push(self.lightmaps[id].create_view(&Default::default()));
lightmap_ids.push(id);
}
BrushFace {
vertices: face_vert_id as u32..self.vertices.len() as u32,
min,
max,
texture_id: texinfo.tex_id as usize,
lightmap_ids,
light_styles: face.light_styles,
draw_flag: Cell::new(true),
}
}
fn create_per_texture_bind_group(
&self,
state: &GraphicsState,
tex: &BrushTextureFrame,
) -> wgpu::BindGroup {
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerTexture);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-texture bind group"),
layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureView(&tex.diffuse_view),
},
wgpu::BindGroupEntry {
binding: 1,
resource: wgpu::BindingResource::TextureView(&tex.fullbright_view),
},
],
};
state.device().create_bind_group(&desc)
}
fn create_per_face_bind_group(&self, state: &GraphicsState, face_id: usize) -> wgpu::BindGroup {
let mut lightmap_views: Vec<_> = self.faces[face_id]
.lightmap_ids
.iter()
.map(|id| self.lightmaps[*id].create_view(&Default::default()))
.collect();
lightmap_views.resize_with(4, || {
state.default_lightmap().create_view(&Default::default())
});
let lightmap_view_refs = lightmap_views.iter().collect::<Vec<_>>();
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerFace);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-face bind group"),
layout,
entries: &[wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureViewArray(&lightmap_view_refs[..]),
}],
};
state.device().create_bind_group(&desc)
}
fn create_brush_texture_frame<S>(
&self,
state: &GraphicsState,
mipmap: &[u8],
width: u32,
height: u32,
name: S,
) -> BrushTextureFrame
where
S: AsRef<str>,
{
let name = name.as_ref();
let (diffuse_data, fullbright_data) = state.palette().translate(mipmap);
let diffuse =
state.create_texture(None, width, height, &TextureData::Diffuse(diffuse_data));
let fullbright = state.create_texture(
None,
width,
height,
&TextureData::Fullbright(fullbright_data),
);
let diffuse_view = diffuse.create_view(&Default::default());
let fullbright_view = fullbright.create_view(&Default::default());
let kind = if name.starts_with("sky") {
TextureKind::Sky
} else if name.starts_with("*") {
TextureKind::Warp
} else {
TextureKind::Normal
};
let mut frame = BrushTextureFrame {
bind_group_id: 0,
diffuse,
fullbright,
diffuse_view,
fullbright_view,
kind,
};
// generate texture bind group
let per_texture_bind_group = self.create_per_texture_bind_group(state, &frame);
let bind_group_id = self.per_texture_bind_groups.borrow().len();
self.per_texture_bind_groups
.borrow_mut()
.push(per_texture_bind_group);
frame.bind_group_id = bind_group_id;
frame
}
pub fn create_brush_texture(&self, state: &GraphicsState, tex: &BspTexture) -> BrushTexture {
// TODO: upload mipmaps
let (width, height) = tex.dimensions();
match tex.kind() {
// sequence animated textures
BspTextureKind::Animated { primary, alternate } => {
let primary_frames: Vec<_> = primary
.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect();
let alternate_frames: Option<Vec<_>> = alternate.as_ref().map(|a| {
a.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect()
});
BrushTexture::Animated {
primary: primary_frames,
alternate: alternate_frames,
}
}
BspTextureKind::Static(bsp_tex) => {
BrushTexture::Static(self.create_brush_texture_frame(
state,
bsp_tex.mipmap(BspTextureMipmap::Full),
tex.width(),
tex.height(),
tex.name(),
))
}
}
}
pub fn build(mut self, state: &GraphicsState) -> Result<BrushRenderer, Error> {
// create the diffuse and fullbright textures
for tex in self.bsp_data.textures().iter() {
self.textures.push(self.create_brush_texture(state, tex));
}
// generate faces, vertices and lightmaps
// bsp_face_id is the id of the face in the bsp data
// face_id is the new id of the face in the renderer
for bsp_face_id in self.face_range.start..self.face_range.end {
let face_id = self.faces.len();
let face = self.create_face(state, bsp_face_id);
self.faces.push(face);
let face_tex_id = self.faces[face_id].texture_id;
// update the corresponding texture chain
self.texture_chains
.entry(face_tex_id)
.or_insert(Vec::new())
.push(face_id);
// generate face bind group
let per_face_bind_group = self.create_per_face_bind_group(state, face_id);
self.per_face_bind_groups.push(per_face_bind_group);
}
use wgpu::util::DeviceExt as _;
let vertex_buffer = state
.device()
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: None,
contents: unsafe { any_slice_as_bytes(self.vertices.as_slice()) },
usage: wgpu::BufferUsage::VERTEX,
});
Ok(BrushRenderer {
bsp_data: self.bsp_data,
vertex_buffer,
leaves: self.leaves,
per_texture_bind_groups: self.per_texture_bind_groups.into_inner(),
per_face_bind_groups: self.per_face_bind_groups,
texture_chains: self.texture_chains,
faces: self.faces,
textures: self.textures,
lightmaps: self.lightmaps,
//lightmap_views: self.lightmap_views,
})
}
}
pub struct BrushRenderer {
bsp_data: Rc<BspData>,
leaves: Option<Vec<BrushLeaf>>,
vertex_buffer: wgpu::Buffer,
per_texture_bind_groups: Vec<wgpu::BindGroup>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
// faces are grouped by texture to reduce the number of texture rebinds
// texture_chains maps texture ids to face ids
texture_chains: HashMap<usize, Vec<usize>>,
faces: Vec<BrushFace>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRenderer {
/// Record the draw commands for this brush model to the given `wgpu::RenderPass`.
pub fn record_draw<'a>(
&'a self,
state: &'a GraphicsState,
pass: &mut wgpu::RenderPass<'a>,
bump: &'a Bump,
time: Duration,
camera: &Camera,
frame_id: usize,
) {
pass.set_pipeline(state.brush_pipeline().pipeline());
pass.set_vertex_buffer(0, self.vertex_buffer.slice(..));
// if this is a worldmodel, mark faces to be drawn
if let Some(ref leaves) = self.leaves {
let pvs = self
.bsp_data
.get_pvs(self.bsp_data.find_leaf(camera.origin), leaves.len());
// only draw faces in pvs
for leaf_id in pvs {
for facelist_id in leaves[leaf_id].facelist_ids.clone() {
let face = &self.faces[self.bsp_data.facelist()[facelist_id]];
// TODO: frustum culling
face.draw_flag.set(true);
}
}
}
for (tex_id, face_ids) in self.texture_chains.iter() {
use PushConstantUpdate::*;
BrushPipeline::set_push_constants(
pass,
Retain,
Update(bump.alloc(SharedPushConstants {
texture_kind: self.textures[*tex_id].kind() as u32,
})),
Retain,
);
let bind_group_id = match &self.textures[*tex_id] {
BrushTexture::Static(ref frame) => frame.bind_group_id,
BrushTexture::Animated { primary, alternate } => {
// if frame is not zero and this texture has an alternate
// animation, use it
let anim = if frame_id == 0 {
primary
} else if let Some(a) = alternate {
a
} else {
primary
};
let time_ms = time.num_milliseconds();
let total_ms = (bsp::frame_duration() * anim.len() as i32).num_milliseconds();
let anim_ms = if total_ms == 0 { 0 } else { time_ms % total_ms };
anim[(anim_ms / bsp::frame_duration().num_milliseconds()) as usize]
.bind_group_id
}
};
pass.set_bind_group(
BindGroupLayoutId::PerTexture as u32,
&self.per_texture_bind_groups[bind_group_id],
&[],
);
for face_id in face_ids.iter() {
let face = &self.faces[*face_id];
// only skip the face if we have visibility data but it's not marked
if self.leaves.is_some() && !face.draw_flag.replace(false) {
continue;
}
pass.set_bind_group(
BindGroupLayoutId::PerFace as u32,
&self.per_face_bind_groups[*face_id],
&[],
);
pass.draw(face.vertices.clone(), 0..1);
}
}
}
}
|
let layout_refs: Vec<_> = world_bind_group_layouts
.iter()
.chain(self.bind_group_layouts.iter())
.collect();
self.pipeline = BrushPipeline::recreate(device, compiler, &layout_refs, sample_count);
}
| identifier_body |
brush.rs | // Copyright © 2020 Cormac O'Brien.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
use std::{
borrow::Cow,
cell::{Cell, RefCell},
collections::HashMap,
mem::size_of,
num::NonZeroU32,
ops::Range,
rc::Rc,
};
use crate::{
client::render::{
pipeline::PushConstantUpdate,
warp,
world::{BindGroupLayoutId, WorldPipelineBase},
Camera, GraphicsState, LightmapData, Pipeline, TextureData,
},
common::{
bsp::{
self, BspData, BspFace, BspLeaf, BspModel, BspTexInfo, BspTexture, BspTextureKind,
BspTextureMipmap,
},
math,
util::any_slice_as_bytes,
},
};
use bumpalo::Bump;
use cgmath::{InnerSpace as _, Matrix4, Vector3};
use chrono::Duration;
use failure::Error;
pub struct BrushPipeline {
pipeline: wgpu::RenderPipeline,
bind_group_layouts: Vec<wgpu::BindGroupLayout>,
}
impl BrushPipeline {
pub fn new(
device: &wgpu::Device,
queue: &wgpu::Queue,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) -> BrushPipeline {
let (pipeline, bind_group_layouts) =
BrushPipeline::create(device, compiler, world_bind_group_layouts, sample_count);
BrushPipeline {
pipeline,
// TODO: pick a starting capacity
bind_group_layouts,
}
}
pub fn rebuild(
&mut self,
device: &wgpu::Device,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) {
let layout_refs: Vec<_> = world_bind_group_layouts
.iter()
.chain(self.bind_group_layouts.iter())
.collect();
self.pipeline = BrushPipeline::recreate(device, compiler, &layout_refs, sample_count);
}
pub fn pipeline(&self) -> &wgpu::RenderPipeline {
&self.pipeline
}
pub fn bind_group_layouts(&self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupLayoutId::PerTexture as usize);
&self.bind_group_layouts[id as usize - BindGroupLayoutId::PerTexture as usize]
}
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct VertexPushConstants {
pub transform: Matrix4<f32>,
pub model_view: Matrix4<f32>,
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct SharedPushConstants {
pub texture_kind: u32,
}
const BIND_GROUP_LAYOUT_ENTRIES: &[&[wgpu::BindGroupLayoutEntry]] = &[
&[
// diffuse texture, updated once per face
wgpu::BindGroupLayoutEntry {
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
// fullbright texture
wgpu::BindGroupLayoutEntry {
binding: 1,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
],
&[
// lightmap texture array
wgpu::BindGroupLayoutEntry {
count: NonZeroU32::new(4),
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
},
],
];
lazy_static! {
static ref VERTEX_ATTRIBUTES: [wgpu::VertexAttribute; 5] =
wgpu::vertex_attr_array![
// position
0 => Float32x3,
// normal
1 => Float32x3,
// diffuse texcoord
2 => Float32x2,
// lightmap texcoord
3 => Float32x2,
// lightmap animation ids
4 => Uint8x4,
];
}
impl Pipeline for BrushPipeline {
type VertexPushConstants = VertexPushConstants;
type SharedPushConstants = SharedPushConstants;
type FragmentPushConstants = ();
fn name() -> &'static str {
"brush"
}
fn vertex_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.vert"))
}
fn fragment_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.frag"))
}
// NOTE: if any of the binding indices are changed, they must also be changed in
// the corresponding shaders and the BindGroupLayout generation functions.
fn bind_group_layout_descriptors() -> Vec<wgpu::BindGroupLayoutDescriptor<'static>> {
vec![
// group 2: updated per-texture
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-texture bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[0],
},
// group 3: updated per-face
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-face bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[1],
},
]
}
fn primitive_state() -> wgpu::PrimitiveState {
WorldPipelineBase::primitive_state()
}
fn color_target_states() -> Vec<wgpu::ColorTargetState> {
WorldPipelineBase::color_target_states()
}
fn depth_stencil_state() -> Option<wgpu::DepthStencilState> {
WorldPipelineBase::depth_stencil_state()
}
// NOTE: if the vertex format is changed, this descriptor must also be changed accordingly.
fn vertex_buffer_layouts() -> Vec<wgpu::VertexBufferLayout<'static>> {
vec![wgpu::VertexBufferLayout {
array_stride: size_of::<BrushVertex>() as u64,
step_mode: wgpu::InputStepMode::Vertex,
attributes: &VERTEX_ATTRIBUTES[..],
}]
}
}
fn calculate_lightmap_texcoords(
position: Vector3<f32>,
face: &BspFace,
texinfo: &BspTexInfo,
) -> [f32; 2] {
let mut s = texinfo.s_vector.dot(position) + texinfo.s_offset;
s -= (face.texture_mins[0] as f32 / 16.0).floor() * 16.0;
s += 0.5;
s /= face.extents[0] as f32;
let mut t = texinfo.t_vector.dot(position) + texinfo.t_offset;
t -= (face.texture_mins[1] as f32 / 16.0).floor() * 16.0;
t += 0.5;
t /= face.extents[1] as f32;
[s, t]
}
type Position = [f32; 3];
type Normal = [f32; 3];
type DiffuseTexcoord = [f32; 2];
type LightmapTexcoord = [f32; 2];
type LightmapAnim = [u8; 4];
#[repr(C)]
#[derive(Clone, Copy, Debug)]
struct BrushVertex {
position: Position,
normal: Normal,
diffuse_texcoord: DiffuseTexcoord,
lightmap_texcoord: LightmapTexcoord,
lightmap_anim: LightmapAnim,
}
#[repr(u32)]
#[derive(Clone, Copy, Debug)]
pub enum TextureKind {
Normal = 0,
Warp = 1,
Sky = 2,
}
/// A single frame of a brush texture.
pub struct BrushTextureFrame {
bind_group_id: usize,
diffuse: wgpu::Texture,
fullbright: wgpu::Texture,
diffuse_view: wgpu::TextureView,
fullbright_view: wgpu::TextureView,
kind: TextureKind,
}
/// A brush texture.
pub enum BrushTexture {
/// A brush texture with a single frame.
Static(BrushTextureFrame),
/// A brush texture with multiple frames.
///
/// Animated brush textures advance one frame every 200 milliseconds, i.e.,
/// they have a framerate of 5 fps.
Animated {
primary: Vec<BrushTextureFrame>,
alternate: Option<Vec<BrushTextureFrame>>,
},
}
impl BrushTexture {
fn kind(&self) -> TextureKind {
match self {
BrushTexture::Static(ref frame) => frame.kind,
BrushTexture::Animated { ref primary, .. } => primary[0].kind,
}
}
}
#[derive(Debug)]
struct BrushFace {
vertices: Range<u32>,
min: Vector3<f32>,
max: Vector3<f32>,
texture_id: usize,
lightmap_ids: Vec<usize>,
light_styles: [u8; 4],
/// Indicates whether the face should be drawn this frame.
///
/// This is set to false by default, and will be set to true if the model is
/// a worldmodel and the containing leaf is in the PVS. If the model is not
/// a worldmodel, this flag is ignored.
draw_flag: Cell<bool>,
}
struct BrushLeaf {
facelist_ids: Range<usize>,
}
impl<B> std::convert::From<B> for BrushLeaf
where
B: std::borrow::Borrow<BspLeaf>,
{
fn from(bsp_leaf: B) -> Self {
let bsp_leaf = bsp_leaf.borrow();
BrushLeaf {
facelist_ids: bsp_leaf.facelist_id..bsp_leaf.facelist_id + bsp_leaf.facelist_count,
}
}
}
pub struct BrushRendererBuilder {
bsp_data: Rc<BspData>,
face_range: Range<usize>,
leaves: Option<Vec<BrushLeaf>>,
per_texture_bind_groups: RefCell<Vec<wgpu::BindGroup>>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
vertices: Vec<BrushVertex>,
faces: Vec<BrushFace>,
texture_chains: HashMap<usize, Vec<usize>>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRendererBuilder {
pub fn new(bsp_model: &BspModel, worldmodel: bool) -> BrushRendererBuilder {
BrushRendererBuilder {
bsp_data: bsp_model.bsp_data().clone(),
face_range: bsp_model.face_id..bsp_model.face_id + bsp_model.face_count,
leaves: if worldmodel {
Some(
bsp_model
.iter_leaves()
.map(|leaf| BrushLeaf::from(leaf))
.collect(),
)
} else {
None
},
per_texture_bind_groups: RefCell::new(Vec::new()),
per_face_bind_groups: Vec::new(),
vertices: Vec::new(),
faces: Vec::new(),
texture_chains: HashMap::new(),
textures: Vec::new(),
lightmaps: Vec::new(),
//lightmap_views: Vec::new(),
}
}
fn create_face(&mut self, state: &GraphicsState, face_id: usize) -> BrushFace {
let face = &self.bsp_data.faces()[face_id];
let face_vert_id = self.vertices.len();
let texinfo = &self.bsp_data.texinfo()[face.texinfo_id];
let tex = &self.bsp_data.textures()[texinfo.tex_id];
let mut min = Vector3::new(f32::INFINITY, f32::INFINITY, f32::INFINITY);
let mut max = Vector3::new(f32::NEG_INFINITY, f32::NEG_INFINITY, f32::NEG_INFINITY);
let no_collinear =
math::remove_collinear(self.bsp_data.face_iter_vertices(face_id).collect());
for vert in no_collinear.iter() {
for component in 0..3 {
min[component] = min[component].min(vert[component]);
max[component] = max[component].max(vert[component]);
}
}
if tex.name().starts_with("*") {
// tessellate the surface so we can do texcoord warping
let verts = warp::subdivide(no_collinear);
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
for vert in verts.into_iter() {
self.vertices.push(BrushVertex {
position: vert.into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(vert.into(), face, texinfo),
lightmap_anim: face.light_styles,
})
}
} else {
// expand the vertices into a triangle list.
// the vertices are guaranteed to be in valid triangle fan order (that's
// how GLQuake renders them) so we expand from triangle fan to triangle
// list order.
//
// v1 is the base vertex, so it remains constant.
// v2 takes the previous value of v3.
// v3 is the newest vertex.
let verts = no_collinear;
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
let mut vert_iter = verts.into_iter();
let v1 = vert_iter.next().unwrap();
let mut v2 = vert_iter.next().unwrap();
for v3 in vert_iter {
let tri = &[v1, v2, v3];
// skip collinear points
for vert in tri.iter() {
self.vertices.push(BrushVertex {
position: (*vert).into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(
(*vert).into(),
face,
texinfo,
),
lightmap_anim: face.light_styles,
});
}
v2 = v3;
}
}
// build the lightmaps
let lightmaps = if !texinfo.special {
self.bsp_data.face_lightmaps(face_id)
} else {
Vec::new()
};
let mut lightmap_ids = Vec::new();
for lightmap in lightmaps {
let lightmap_data = TextureData::Lightmap(LightmapData {
lightmap: Cow::Borrowed(lightmap.data()),
});
let texture =
state.create_texture(None, lightmap.width(), lightmap.height(), &lightmap_data);
let id = self.lightmaps.len();
self.lightmaps.push(texture);
//self.lightmap_views
//.push(self.lightmaps[id].create_view(&Default::default()));
lightmap_ids.push(id);
}
BrushFace {
vertices: face_vert_id as u32..self.vertices.len() as u32,
min,
max,
texture_id: texinfo.tex_id as usize,
lightmap_ids,
light_styles: face.light_styles,
draw_flag: Cell::new(true),
}
}
fn create_per_texture_bind_group(
&self,
state: &GraphicsState,
tex: &BrushTextureFrame,
) -> wgpu::BindGroup {
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerTexture);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-texture bind group"),
layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureView(&tex.diffuse_view),
},
wgpu::BindGroupEntry {
binding: 1,
resource: wgpu::BindingResource::TextureView(&tex.fullbright_view),
},
],
};
state.device().create_bind_group(&desc)
}
fn create_per_face_bind_group(&self, state: &GraphicsState, face_id: usize) -> wgpu::BindGroup {
let mut lightmap_views: Vec<_> = self.faces[face_id]
.lightmap_ids
.iter()
.map(|id| self.lightmaps[*id].create_view(&Default::default()))
.collect();
lightmap_views.resize_with(4, || {
state.default_lightmap().create_view(&Default::default())
});
let lightmap_view_refs = lightmap_views.iter().collect::<Vec<_>>();
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerFace);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-face bind group"),
layout,
entries: &[wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureViewArray(&lightmap_view_refs[..]),
}],
};
state.device().create_bind_group(&desc)
}
fn create_brush_texture_frame<S>(
&self,
state: &GraphicsState,
mipmap: &[u8],
width: u32,
height: u32,
name: S,
) -> BrushTextureFrame
where
S: AsRef<str>,
{
let name = name.as_ref();
let (diffuse_data, fullbright_data) = state.palette().translate(mipmap);
let diffuse =
state.create_texture(None, width, height, &TextureData::Diffuse(diffuse_data));
let fullbright = state.create_texture(
None,
width,
height,
&TextureData::Fullbright(fullbright_data),
);
let diffuse_view = diffuse.create_view(&Default::default());
let fullbright_view = fullbright.create_view(&Default::default());
let kind = if name.starts_with("sky") {
TextureKind::Sky
} else if name.starts_with("*") {
TextureKind::Warp
} else {
TextureKind::Normal
};
let mut frame = BrushTextureFrame {
bind_group_id: 0,
diffuse,
fullbright,
diffuse_view,
fullbright_view,
kind,
};
// generate texture bind group
let per_texture_bind_group = self.create_per_texture_bind_group(state, &frame);
let bind_group_id = self.per_texture_bind_groups.borrow().len();
self.per_texture_bind_groups
.borrow_mut()
.push(per_texture_bind_group);
frame.bind_group_id = bind_group_id;
frame
}
pub fn create_brush_texture(&self, state: &GraphicsState, tex: &BspTexture) -> BrushTexture {
// TODO: upload mipmaps
let (width, height) = tex.dimensions();
match tex.kind() {
// sequence animated textures
BspTextureKind::Animated { primary, alternate } => { |
BspTextureKind::Static(bsp_tex) => {
BrushTexture::Static(self.create_brush_texture_frame(
state,
bsp_tex.mipmap(BspTextureMipmap::Full),
tex.width(),
tex.height(),
tex.name(),
))
}
}
}
pub fn build(mut self, state: &GraphicsState) -> Result<BrushRenderer, Error> {
// create the diffuse and fullbright textures
for tex in self.bsp_data.textures().iter() {
self.textures.push(self.create_brush_texture(state, tex));
}
// generate faces, vertices and lightmaps
// bsp_face_id is the id of the face in the bsp data
// face_id is the new id of the face in the renderer
for bsp_face_id in self.face_range.start..self.face_range.end {
let face_id = self.faces.len();
let face = self.create_face(state, bsp_face_id);
self.faces.push(face);
let face_tex_id = self.faces[face_id].texture_id;
// update the corresponding texture chain
self.texture_chains
.entry(face_tex_id)
.or_insert(Vec::new())
.push(face_id);
// generate face bind group
let per_face_bind_group = self.create_per_face_bind_group(state, face_id);
self.per_face_bind_groups.push(per_face_bind_group);
}
use wgpu::util::DeviceExt as _;
let vertex_buffer = state
.device()
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: None,
contents: unsafe { any_slice_as_bytes(self.vertices.as_slice()) },
usage: wgpu::BufferUsage::VERTEX,
});
Ok(BrushRenderer {
bsp_data: self.bsp_data,
vertex_buffer,
leaves: self.leaves,
per_texture_bind_groups: self.per_texture_bind_groups.into_inner(),
per_face_bind_groups: self.per_face_bind_groups,
texture_chains: self.texture_chains,
faces: self.faces,
textures: self.textures,
lightmaps: self.lightmaps,
//lightmap_views: self.lightmap_views,
})
}
}
pub struct BrushRenderer {
bsp_data: Rc<BspData>,
leaves: Option<Vec<BrushLeaf>>,
vertex_buffer: wgpu::Buffer,
per_texture_bind_groups: Vec<wgpu::BindGroup>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
// faces are grouped by texture to reduce the number of texture rebinds
// texture_chains maps texture ids to face ids
texture_chains: HashMap<usize, Vec<usize>>,
faces: Vec<BrushFace>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRenderer {
/// Record the draw commands for this brush model to the given `wgpu::RenderPass`.
pub fn record_draw<'a>(
&'a self,
state: &'a GraphicsState,
pass: &mut wgpu::RenderPass<'a>,
bump: &'a Bump,
time: Duration,
camera: &Camera,
frame_id: usize,
) {
pass.set_pipeline(state.brush_pipeline().pipeline());
pass.set_vertex_buffer(0, self.vertex_buffer.slice(..));
// if this is a worldmodel, mark faces to be drawn
if let Some(ref leaves) = self.leaves {
let pvs = self
.bsp_data
.get_pvs(self.bsp_data.find_leaf(camera.origin), leaves.len());
// only draw faces in pvs
for leaf_id in pvs {
for facelist_id in leaves[leaf_id].facelist_ids.clone() {
let face = &self.faces[self.bsp_data.facelist()[facelist_id]];
// TODO: frustum culling
face.draw_flag.set(true);
}
}
}
for (tex_id, face_ids) in self.texture_chains.iter() {
use PushConstantUpdate::*;
BrushPipeline::set_push_constants(
pass,
Retain,
Update(bump.alloc(SharedPushConstants {
texture_kind: self.textures[*tex_id].kind() as u32,
})),
Retain,
);
let bind_group_id = match &self.textures[*tex_id] {
BrushTexture::Static(ref frame) => frame.bind_group_id,
BrushTexture::Animated { primary, alternate } => {
// if frame is not zero and this texture has an alternate
// animation, use it
let anim = if frame_id == 0 {
primary
} else if let Some(a) = alternate {
a
} else {
primary
};
let time_ms = time.num_milliseconds();
let total_ms = (bsp::frame_duration() * anim.len() as i32).num_milliseconds();
let anim_ms = if total_ms == 0 { 0 } else { time_ms % total_ms };
anim[(anim_ms / bsp::frame_duration().num_milliseconds()) as usize]
.bind_group_id
}
};
pass.set_bind_group(
BindGroupLayoutId::PerTexture as u32,
&self.per_texture_bind_groups[bind_group_id],
&[],
);
for face_id in face_ids.iter() {
let face = &self.faces[*face_id];
// only skip the face if we have visibility data but it's not marked
if self.leaves.is_some() && !face.draw_flag.replace(false) {
continue;
}
pass.set_bind_group(
BindGroupLayoutId::PerFace as u32,
&self.per_face_bind_groups[*face_id],
&[],
);
pass.draw(face.vertices.clone(), 0..1);
}
}
}
}
|
let primary_frames: Vec<_> = primary
.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect();
let alternate_frames: Option<Vec<_>> = alternate.as_ref().map(|a| {
a.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect()
});
BrushTexture::Animated {
primary: primary_frames,
alternate: alternate_frames,
}
}
| conditional_block |
brush.rs | // Copyright © 2020 Cormac O'Brien.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
use std::{
borrow::Cow,
cell::{Cell, RefCell},
collections::HashMap,
mem::size_of,
num::NonZeroU32,
ops::Range,
rc::Rc,
};
use crate::{
client::render::{
pipeline::PushConstantUpdate,
warp,
world::{BindGroupLayoutId, WorldPipelineBase},
Camera, GraphicsState, LightmapData, Pipeline, TextureData,
},
common::{
bsp::{
self, BspData, BspFace, BspLeaf, BspModel, BspTexInfo, BspTexture, BspTextureKind,
BspTextureMipmap,
},
math,
util::any_slice_as_bytes,
},
};
use bumpalo::Bump;
use cgmath::{InnerSpace as _, Matrix4, Vector3};
use chrono::Duration;
use failure::Error;
pub struct BrushPipeline {
pipeline: wgpu::RenderPipeline,
bind_group_layouts: Vec<wgpu::BindGroupLayout>,
}
impl BrushPipeline {
pub fn new(
device: &wgpu::Device,
queue: &wgpu::Queue,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) -> BrushPipeline {
let (pipeline, bind_group_layouts) =
BrushPipeline::create(device, compiler, world_bind_group_layouts, sample_count);
BrushPipeline {
pipeline,
// TODO: pick a starting capacity
bind_group_layouts,
}
}
pub fn rebuild(
&mut self,
device: &wgpu::Device,
compiler: &mut shaderc::Compiler,
world_bind_group_layouts: &[wgpu::BindGroupLayout],
sample_count: u32,
) {
let layout_refs: Vec<_> = world_bind_group_layouts
.iter()
.chain(self.bind_group_layouts.iter())
.collect();
self.pipeline = BrushPipeline::recreate(device, compiler, &layout_refs, sample_count);
}
pub fn pipeline(&self) -> &wgpu::RenderPipeline {
&self.pipeline
}
pub fn b | &self) -> &[wgpu::BindGroupLayout] {
&self.bind_group_layouts
}
pub fn bind_group_layout(&self, id: BindGroupLayoutId) -> &wgpu::BindGroupLayout {
assert!(id as usize >= BindGroupLayoutId::PerTexture as usize);
&self.bind_group_layouts[id as usize - BindGroupLayoutId::PerTexture as usize]
}
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct VertexPushConstants {
pub transform: Matrix4<f32>,
pub model_view: Matrix4<f32>,
}
#[repr(C)]
#[derive(Copy, Clone, Debug)]
pub struct SharedPushConstants {
pub texture_kind: u32,
}
const BIND_GROUP_LAYOUT_ENTRIES: &[&[wgpu::BindGroupLayoutEntry]] = &[
&[
// diffuse texture, updated once per face
wgpu::BindGroupLayoutEntry {
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
// fullbright texture
wgpu::BindGroupLayoutEntry {
binding: 1,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
count: None,
},
],
&[
// lightmap texture array
wgpu::BindGroupLayoutEntry {
count: NonZeroU32::new(4),
binding: 0,
visibility: wgpu::ShaderStage::FRAGMENT,
ty: wgpu::BindingType::Texture {
view_dimension: wgpu::TextureViewDimension::D2,
sample_type: wgpu::TextureSampleType::Float { filterable: true },
multisampled: false,
},
},
],
];
lazy_static! {
static ref VERTEX_ATTRIBUTES: [wgpu::VertexAttribute; 5] =
wgpu::vertex_attr_array![
// position
0 => Float32x3,
// normal
1 => Float32x3,
// diffuse texcoord
2 => Float32x2,
// lightmap texcoord
3 => Float32x2,
// lightmap animation ids
4 => Uint8x4,
];
}
impl Pipeline for BrushPipeline {
type VertexPushConstants = VertexPushConstants;
type SharedPushConstants = SharedPushConstants;
type FragmentPushConstants = ();
fn name() -> &'static str {
"brush"
}
fn vertex_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.vert"))
}
fn fragment_shader() -> &'static str {
include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/shaders/brush.frag"))
}
// NOTE: if any of the binding indices are changed, they must also be changed in
// the corresponding shaders and the BindGroupLayout generation functions.
fn bind_group_layout_descriptors() -> Vec<wgpu::BindGroupLayoutDescriptor<'static>> {
vec![
// group 2: updated per-texture
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-texture bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[0],
},
// group 3: updated per-face
wgpu::BindGroupLayoutDescriptor {
label: Some("brush per-face bind group"),
entries: BIND_GROUP_LAYOUT_ENTRIES[1],
},
]
}
fn primitive_state() -> wgpu::PrimitiveState {
WorldPipelineBase::primitive_state()
}
fn color_target_states() -> Vec<wgpu::ColorTargetState> {
WorldPipelineBase::color_target_states()
}
fn depth_stencil_state() -> Option<wgpu::DepthStencilState> {
WorldPipelineBase::depth_stencil_state()
}
// NOTE: if the vertex format is changed, this descriptor must also be changed accordingly.
fn vertex_buffer_layouts() -> Vec<wgpu::VertexBufferLayout<'static>> {
vec![wgpu::VertexBufferLayout {
array_stride: size_of::<BrushVertex>() as u64,
step_mode: wgpu::InputStepMode::Vertex,
attributes: &VERTEX_ATTRIBUTES[..],
}]
}
}
fn calculate_lightmap_texcoords(
position: Vector3<f32>,
face: &BspFace,
texinfo: &BspTexInfo,
) -> [f32; 2] {
let mut s = texinfo.s_vector.dot(position) + texinfo.s_offset;
s -= (face.texture_mins[0] as f32 / 16.0).floor() * 16.0;
s += 0.5;
s /= face.extents[0] as f32;
let mut t = texinfo.t_vector.dot(position) + texinfo.t_offset;
t -= (face.texture_mins[1] as f32 / 16.0).floor() * 16.0;
t += 0.5;
t /= face.extents[1] as f32;
[s, t]
}
type Position = [f32; 3];
type Normal = [f32; 3];
type DiffuseTexcoord = [f32; 2];
type LightmapTexcoord = [f32; 2];
type LightmapAnim = [u8; 4];
#[repr(C)]
#[derive(Clone, Copy, Debug)]
struct BrushVertex {
position: Position,
normal: Normal,
diffuse_texcoord: DiffuseTexcoord,
lightmap_texcoord: LightmapTexcoord,
lightmap_anim: LightmapAnim,
}
#[repr(u32)]
#[derive(Clone, Copy, Debug)]
pub enum TextureKind {
Normal = 0,
Warp = 1,
Sky = 2,
}
/// A single frame of a brush texture.
pub struct BrushTextureFrame {
bind_group_id: usize,
diffuse: wgpu::Texture,
fullbright: wgpu::Texture,
diffuse_view: wgpu::TextureView,
fullbright_view: wgpu::TextureView,
kind: TextureKind,
}
/// A brush texture.
pub enum BrushTexture {
/// A brush texture with a single frame.
Static(BrushTextureFrame),
/// A brush texture with multiple frames.
///
/// Animated brush textures advance one frame every 200 milliseconds, i.e.,
/// they have a framerate of 5 fps.
Animated {
primary: Vec<BrushTextureFrame>,
alternate: Option<Vec<BrushTextureFrame>>,
},
}
impl BrushTexture {
fn kind(&self) -> TextureKind {
match self {
BrushTexture::Static(ref frame) => frame.kind,
BrushTexture::Animated { ref primary, .. } => primary[0].kind,
}
}
}
#[derive(Debug)]
struct BrushFace {
vertices: Range<u32>,
min: Vector3<f32>,
max: Vector3<f32>,
texture_id: usize,
lightmap_ids: Vec<usize>,
light_styles: [u8; 4],
/// Indicates whether the face should be drawn this frame.
///
/// This is set to false by default, and will be set to true if the model is
/// a worldmodel and the containing leaf is in the PVS. If the model is not
/// a worldmodel, this flag is ignored.
draw_flag: Cell<bool>,
}
struct BrushLeaf {
facelist_ids: Range<usize>,
}
impl<B> std::convert::From<B> for BrushLeaf
where
B: std::borrow::Borrow<BspLeaf>,
{
fn from(bsp_leaf: B) -> Self {
let bsp_leaf = bsp_leaf.borrow();
BrushLeaf {
facelist_ids: bsp_leaf.facelist_id..bsp_leaf.facelist_id + bsp_leaf.facelist_count,
}
}
}
pub struct BrushRendererBuilder {
bsp_data: Rc<BspData>,
face_range: Range<usize>,
leaves: Option<Vec<BrushLeaf>>,
per_texture_bind_groups: RefCell<Vec<wgpu::BindGroup>>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
vertices: Vec<BrushVertex>,
faces: Vec<BrushFace>,
texture_chains: HashMap<usize, Vec<usize>>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRendererBuilder {
pub fn new(bsp_model: &BspModel, worldmodel: bool) -> BrushRendererBuilder {
BrushRendererBuilder {
bsp_data: bsp_model.bsp_data().clone(),
face_range: bsp_model.face_id..bsp_model.face_id + bsp_model.face_count,
leaves: if worldmodel {
Some(
bsp_model
.iter_leaves()
.map(|leaf| BrushLeaf::from(leaf))
.collect(),
)
} else {
None
},
per_texture_bind_groups: RefCell::new(Vec::new()),
per_face_bind_groups: Vec::new(),
vertices: Vec::new(),
faces: Vec::new(),
texture_chains: HashMap::new(),
textures: Vec::new(),
lightmaps: Vec::new(),
//lightmap_views: Vec::new(),
}
}
fn create_face(&mut self, state: &GraphicsState, face_id: usize) -> BrushFace {
let face = &self.bsp_data.faces()[face_id];
let face_vert_id = self.vertices.len();
let texinfo = &self.bsp_data.texinfo()[face.texinfo_id];
let tex = &self.bsp_data.textures()[texinfo.tex_id];
let mut min = Vector3::new(f32::INFINITY, f32::INFINITY, f32::INFINITY);
let mut max = Vector3::new(f32::NEG_INFINITY, f32::NEG_INFINITY, f32::NEG_INFINITY);
let no_collinear =
math::remove_collinear(self.bsp_data.face_iter_vertices(face_id).collect());
for vert in no_collinear.iter() {
for component in 0..3 {
min[component] = min[component].min(vert[component]);
max[component] = max[component].max(vert[component]);
}
}
if tex.name().starts_with("*") {
// tessellate the surface so we can do texcoord warping
let verts = warp::subdivide(no_collinear);
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
for vert in verts.into_iter() {
self.vertices.push(BrushVertex {
position: vert.into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(vert.into(), face, texinfo),
lightmap_anim: face.light_styles,
})
}
} else {
// expand the vertices into a triangle list.
// the vertices are guaranteed to be in valid triangle fan order (that's
// how GLQuake renders them) so we expand from triangle fan to triangle
// list order.
//
// v1 is the base vertex, so it remains constant.
// v2 takes the previous value of v3.
// v3 is the newest vertex.
let verts = no_collinear;
let normal = (verts[0] - verts[1]).cross(verts[2] - verts[1]).normalize();
let mut vert_iter = verts.into_iter();
let v1 = vert_iter.next().unwrap();
let mut v2 = vert_iter.next().unwrap();
for v3 in vert_iter {
let tri = &[v1, v2, v3];
// skip collinear points
for vert in tri.iter() {
self.vertices.push(BrushVertex {
position: (*vert).into(),
normal: normal.into(),
diffuse_texcoord: [
((vert.dot(texinfo.s_vector) + texinfo.s_offset) / tex.width() as f32),
((vert.dot(texinfo.t_vector) + texinfo.t_offset) / tex.height() as f32),
],
lightmap_texcoord: calculate_lightmap_texcoords(
(*vert).into(),
face,
texinfo,
),
lightmap_anim: face.light_styles,
});
}
v2 = v3;
}
}
// build the lightmaps
let lightmaps = if !texinfo.special {
self.bsp_data.face_lightmaps(face_id)
} else {
Vec::new()
};
let mut lightmap_ids = Vec::new();
for lightmap in lightmaps {
let lightmap_data = TextureData::Lightmap(LightmapData {
lightmap: Cow::Borrowed(lightmap.data()),
});
let texture =
state.create_texture(None, lightmap.width(), lightmap.height(), &lightmap_data);
let id = self.lightmaps.len();
self.lightmaps.push(texture);
//self.lightmap_views
//.push(self.lightmaps[id].create_view(&Default::default()));
lightmap_ids.push(id);
}
BrushFace {
vertices: face_vert_id as u32..self.vertices.len() as u32,
min,
max,
texture_id: texinfo.tex_id as usize,
lightmap_ids,
light_styles: face.light_styles,
draw_flag: Cell::new(true),
}
}
fn create_per_texture_bind_group(
&self,
state: &GraphicsState,
tex: &BrushTextureFrame,
) -> wgpu::BindGroup {
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerTexture);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-texture bind group"),
layout,
entries: &[
wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureView(&tex.diffuse_view),
},
wgpu::BindGroupEntry {
binding: 1,
resource: wgpu::BindingResource::TextureView(&tex.fullbright_view),
},
],
};
state.device().create_bind_group(&desc)
}
fn create_per_face_bind_group(&self, state: &GraphicsState, face_id: usize) -> wgpu::BindGroup {
let mut lightmap_views: Vec<_> = self.faces[face_id]
.lightmap_ids
.iter()
.map(|id| self.lightmaps[*id].create_view(&Default::default()))
.collect();
lightmap_views.resize_with(4, || {
state.default_lightmap().create_view(&Default::default())
});
let lightmap_view_refs = lightmap_views.iter().collect::<Vec<_>>();
let layout = &state
.brush_pipeline()
.bind_group_layout(BindGroupLayoutId::PerFace);
let desc = wgpu::BindGroupDescriptor {
label: Some("per-face bind group"),
layout,
entries: &[wgpu::BindGroupEntry {
binding: 0,
resource: wgpu::BindingResource::TextureViewArray(&lightmap_view_refs[..]),
}],
};
state.device().create_bind_group(&desc)
}
fn create_brush_texture_frame<S>(
&self,
state: &GraphicsState,
mipmap: &[u8],
width: u32,
height: u32,
name: S,
) -> BrushTextureFrame
where
S: AsRef<str>,
{
let name = name.as_ref();
let (diffuse_data, fullbright_data) = state.palette().translate(mipmap);
let diffuse =
state.create_texture(None, width, height, &TextureData::Diffuse(diffuse_data));
let fullbright = state.create_texture(
None,
width,
height,
&TextureData::Fullbright(fullbright_data),
);
let diffuse_view = diffuse.create_view(&Default::default());
let fullbright_view = fullbright.create_view(&Default::default());
let kind = if name.starts_with("sky") {
TextureKind::Sky
} else if name.starts_with("*") {
TextureKind::Warp
} else {
TextureKind::Normal
};
let mut frame = BrushTextureFrame {
bind_group_id: 0,
diffuse,
fullbright,
diffuse_view,
fullbright_view,
kind,
};
// generate texture bind group
let per_texture_bind_group = self.create_per_texture_bind_group(state, &frame);
let bind_group_id = self.per_texture_bind_groups.borrow().len();
self.per_texture_bind_groups
.borrow_mut()
.push(per_texture_bind_group);
frame.bind_group_id = bind_group_id;
frame
}
pub fn create_brush_texture(&self, state: &GraphicsState, tex: &BspTexture) -> BrushTexture {
// TODO: upload mipmaps
let (width, height) = tex.dimensions();
match tex.kind() {
// sequence animated textures
BspTextureKind::Animated { primary, alternate } => {
let primary_frames: Vec<_> = primary
.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect();
let alternate_frames: Option<Vec<_>> = alternate.as_ref().map(|a| {
a.iter()
.map(|f| {
self.create_brush_texture_frame(
state,
f.mipmap(BspTextureMipmap::Full),
width,
height,
tex.name(),
)
})
.collect()
});
BrushTexture::Animated {
primary: primary_frames,
alternate: alternate_frames,
}
}
BspTextureKind::Static(bsp_tex) => {
BrushTexture::Static(self.create_brush_texture_frame(
state,
bsp_tex.mipmap(BspTextureMipmap::Full),
tex.width(),
tex.height(),
tex.name(),
))
}
}
}
pub fn build(mut self, state: &GraphicsState) -> Result<BrushRenderer, Error> {
// create the diffuse and fullbright textures
for tex in self.bsp_data.textures().iter() {
self.textures.push(self.create_brush_texture(state, tex));
}
// generate faces, vertices and lightmaps
// bsp_face_id is the id of the face in the bsp data
// face_id is the new id of the face in the renderer
for bsp_face_id in self.face_range.start..self.face_range.end {
let face_id = self.faces.len();
let face = self.create_face(state, bsp_face_id);
self.faces.push(face);
let face_tex_id = self.faces[face_id].texture_id;
// update the corresponding texture chain
self.texture_chains
.entry(face_tex_id)
.or_insert(Vec::new())
.push(face_id);
// generate face bind group
let per_face_bind_group = self.create_per_face_bind_group(state, face_id);
self.per_face_bind_groups.push(per_face_bind_group);
}
use wgpu::util::DeviceExt as _;
let vertex_buffer = state
.device()
.create_buffer_init(&wgpu::util::BufferInitDescriptor {
label: None,
contents: unsafe { any_slice_as_bytes(self.vertices.as_slice()) },
usage: wgpu::BufferUsage::VERTEX,
});
Ok(BrushRenderer {
bsp_data: self.bsp_data,
vertex_buffer,
leaves: self.leaves,
per_texture_bind_groups: self.per_texture_bind_groups.into_inner(),
per_face_bind_groups: self.per_face_bind_groups,
texture_chains: self.texture_chains,
faces: self.faces,
textures: self.textures,
lightmaps: self.lightmaps,
//lightmap_views: self.lightmap_views,
})
}
}
pub struct BrushRenderer {
bsp_data: Rc<BspData>,
leaves: Option<Vec<BrushLeaf>>,
vertex_buffer: wgpu::Buffer,
per_texture_bind_groups: Vec<wgpu::BindGroup>,
per_face_bind_groups: Vec<wgpu::BindGroup>,
// faces are grouped by texture to reduce the number of texture rebinds
// texture_chains maps texture ids to face ids
texture_chains: HashMap<usize, Vec<usize>>,
faces: Vec<BrushFace>,
textures: Vec<BrushTexture>,
lightmaps: Vec<wgpu::Texture>,
//lightmap_views: Vec<wgpu::TextureView>,
}
impl BrushRenderer {
/// Record the draw commands for this brush model to the given `wgpu::RenderPass`.
pub fn record_draw<'a>(
&'a self,
state: &'a GraphicsState,
pass: &mut wgpu::RenderPass<'a>,
bump: &'a Bump,
time: Duration,
camera: &Camera,
frame_id: usize,
) {
pass.set_pipeline(state.brush_pipeline().pipeline());
pass.set_vertex_buffer(0, self.vertex_buffer.slice(..));
// if this is a worldmodel, mark faces to be drawn
if let Some(ref leaves) = self.leaves {
let pvs = self
.bsp_data
.get_pvs(self.bsp_data.find_leaf(camera.origin), leaves.len());
// only draw faces in pvs
for leaf_id in pvs {
for facelist_id in leaves[leaf_id].facelist_ids.clone() {
let face = &self.faces[self.bsp_data.facelist()[facelist_id]];
// TODO: frustum culling
face.draw_flag.set(true);
}
}
}
for (tex_id, face_ids) in self.texture_chains.iter() {
use PushConstantUpdate::*;
BrushPipeline::set_push_constants(
pass,
Retain,
Update(bump.alloc(SharedPushConstants {
texture_kind: self.textures[*tex_id].kind() as u32,
})),
Retain,
);
let bind_group_id = match &self.textures[*tex_id] {
BrushTexture::Static(ref frame) => frame.bind_group_id,
BrushTexture::Animated { primary, alternate } => {
// if frame is not zero and this texture has an alternate
// animation, use it
let anim = if frame_id == 0 {
primary
} else if let Some(a) = alternate {
a
} else {
primary
};
let time_ms = time.num_milliseconds();
let total_ms = (bsp::frame_duration() * anim.len() as i32).num_milliseconds();
let anim_ms = if total_ms == 0 { 0 } else { time_ms % total_ms };
anim[(anim_ms / bsp::frame_duration().num_milliseconds()) as usize]
.bind_group_id
}
};
pass.set_bind_group(
BindGroupLayoutId::PerTexture as u32,
&self.per_texture_bind_groups[bind_group_id],
&[],
);
for face_id in face_ids.iter() {
let face = &self.faces[*face_id];
// only skip the face if we have visibility data but it's not marked
if self.leaves.is_some() && !face.draw_flag.replace(false) {
continue;
}
pass.set_bind_group(
BindGroupLayoutId::PerFace as u32,
&self.per_face_bind_groups[*face_id],
&[],
);
pass.draw(face.vertices.clone(), 0..1);
}
}
}
}
| ind_group_layouts( | identifier_name |
glsl3.rs | use std::mem::size_of;
use std::ptr;
use crossfont::RasterizedGlyph;
use log::info;
use alacritty_terminal::term::cell::Flags;
use crate::display::content::RenderableCell;
use crate::display::SizeInfo;
use crate::gl;
use crate::gl::types::*;
use crate::renderer::shader::{ShaderProgram, ShaderVersion};
use crate::renderer::{cstr, Error};
use super::atlas::{Atlas, ATLAS_SIZE};
use super::{
Glyph, LoadGlyph, LoaderApi, RenderingGlyphFlags, RenderingPass, TextRenderApi,
TextRenderBatch, TextRenderer, TextShader,
};
// Shader source.
pub static TEXT_SHADER_F: &str = include_str!("../../../res/glsl3/text.f.glsl");
static TEXT_SHADER_V: &str = include_str!("../../../res/glsl3/text.v.glsl");
/// Maximum items to be drawn in a batch.
const BATCH_MAX: usize = 0x1_0000;
#[derive(Debug)]
pub struct Glsl3Renderer {
program: TextShaderProgram,
vao: GLuint,
ebo: GLuint,
vbo_instance: GLuint,
atlas: Vec<Atlas>,
current_atlas: usize,
active_tex: GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
unsafe {
gl::Enable(gl::BLEND);
gl::BlendFunc(gl::SRC1_COLOR, gl::ONE_MINUS_SRC1_COLOR);
// Disable depth mask, as the renderer never uses depth tests.
gl::DepthMask(gl::FALSE);
gl::GenVertexArrays(1, &mut vao);
gl::GenBuffers(1, &mut ebo);
gl::GenBuffers(1, &mut vbo_instance);
gl::BindVertexArray(vao);
// ---------------------
// Set up element buffer
// ---------------------
let indices: [u32; 6] = [0, 1, 3, 1, 2, 3];
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, ebo);
gl::BufferData(
gl::ELEMENT_ARRAY_BUFFER,
(6 * size_of::<u32>()) as isize,
indices.as_ptr() as *const _,
gl::STATIC_DRAW,
);
// ----------------------------
// Setup vertex instance buffer
// ----------------------------
gl::BindBuffer(gl::ARRAY_BUFFER, vbo_instance);
gl::BufferData(
gl::ARRAY_BUFFER,
(BATCH_MAX * size_of::<InstanceData>()) as isize,
ptr::null(),
gl::STREAM_DRAW,
);
let mut index = 0;
let mut size = 0;
macro_rules! add_attr {
($count:expr, $gl_type:expr, $type:ty) => {
gl::VertexAttribPointer(
index,
$count,
$gl_type,
gl::FALSE,
size_of::<InstanceData>() as i32,
size as *const _,
);
gl::EnableVertexAttribArray(index);
gl::VertexAttribDivisor(index, 1);
#[allow(unused_assignments)]
{
size += $count * size_of::<$type>();
index += 1;
}
};
}
// Coords.
add_attr!(2, gl::UNSIGNED_SHORT, u16);
// Glyph offset and size.
add_attr!(4, gl::SHORT, i16);
// UV offset.
add_attr!(4, gl::FLOAT, f32);
// Color and cell flags.
//
// These are packed together because of an OpenGL driver issue on macOS, which caused a
// `vec3(u8)` text color and a `u8` cell flags to increase the rendering time by a
// huge margin.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Background color.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Cleanup.
gl::BindVertexArray(0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
}
Ok(Self {
program,
vao,
ebo,
vbo_instance,
atlas: vec![Atlas::new(ATLAS_SIZE, false)],
current_atlas: 0,
active_tex: 0,
batch: Batch::new(),
})
}
}
impl<'a> TextRenderer<'a> for Glsl3Renderer {
type RenderApi = RenderApi<'a>;
type RenderBatch = Batch;
type Shader = TextShaderProgram;
fn with_api<'b: 'a, F, T>(&'b mut self, size_info: &'b SizeInfo, func: F) -> T
where
F: FnOnce(Self::RenderApi) -> T,
{
unsafe {
gl::UseProgram(self.program.id());
self.program.set_term_uniforms(size_info);
gl::BindVertexArray(self.vao);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, self.ebo);
gl::BindBuffer(gl::ARRAY_BUFFER, self.vbo_instance);
gl::ActiveTexture(gl::TEXTURE0);
}
let res = func(RenderApi {
active_tex: &mut self.active_tex,
batch: &mut self.batch,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
program: &mut self.program,
});
unsafe {
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindVertexArray(0);
gl::UseProgram(0);
}
res
}
fn program(&self) -> &Self::Shader {
&self.program
}
fn loader_api(&mut self) -> LoaderApi<'_> {
LoaderApi {
active_tex: &mut self.active_tex,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
}
}
}
impl Drop for Glsl3Renderer {
fn drop(&mut self) {
unsafe {
gl::DeleteBuffers(1, &self.vbo_instance);
gl::DeleteBuffers(1, &self.ebo);
gl::DeleteVertexArrays(1, &self.vao);
}
}
}
#[derive(Debug)]
pub struct RenderApi<'a> {
active_tex: &'a mut GLuint,
batch: &'a mut Batch,
atlas: &'a mut Vec<Atlas>,
current_atlas: &'a mut usize,
program: &'a mut TextShaderProgram,
}
impl<'a> TextRenderApi<Batch> for RenderApi<'a> {
fn batch(&mut self) -> &mut Batch {
self.batch
}
fn render_batch(&mut self) {
unsafe {
gl::BufferSubData(
gl::ARRAY_BUFFER,
0,
self.batch.size() as isize,
self.batch.instances.as_ptr() as *const _,
);
}
// Bind texture if necessary.
if *self.active_tex != self.batch.tex() |
unsafe {
self.program.set_rendering_pass(RenderingPass::Background);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
self.program.set_rendering_pass(RenderingPass::SubpixelPass1);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
}
self.batch.clear();
}
}
impl<'a> LoadGlyph for RenderApi<'a> {
fn load_glyph(&mut self, rasterized: &RasterizedGlyph) -> Glyph {
Atlas::load_glyph(self.active_tex, self.atlas, self.current_atlas, rasterized)
}
fn clear(&mut self) {
Atlas::clear_atlas(self.atlas, self.current_atlas)
}
}
impl<'a> Drop for RenderApi<'a> {
fn drop(&mut self) {
if !self.batch.is_empty() {
self.render_batch();
}
}
}
#[derive(Debug)]
#[repr(C)]
struct InstanceData {
// Coords.
col: u16,
row: u16,
// Glyph offset.
left: i16,
top: i16,
// Glyph size.
width: i16,
height: i16,
// UV offset.
uv_left: f32,
uv_bot: f32,
// uv scale.
uv_width: f32,
uv_height: f32,
// Color.
r: u8,
g: u8,
b: u8,
// Cell flags like multicolor or fullwidth character.
cell_flags: RenderingGlyphFlags,
// Background color.
bg_r: u8,
bg_g: u8,
bg_b: u8,
bg_a: u8,
}
#[derive(Debug, Default)]
pub struct Batch {
tex: GLuint,
instances: Vec<InstanceData>,
}
impl TextRenderBatch for Batch {
#[inline]
fn tex(&self) -> GLuint {
self.tex
}
#[inline]
fn full(&self) -> bool {
self.capacity() == self.len()
}
#[inline]
fn is_empty(&self) -> bool {
self.len() == 0
}
fn add_item(&mut self, cell: &RenderableCell, glyph: &Glyph, _: &SizeInfo) {
if self.is_empty() {
self.tex = glyph.tex_id;
}
let mut cell_flags = RenderingGlyphFlags::empty();
cell_flags.set(RenderingGlyphFlags::COLORED, glyph.multicolor);
cell_flags.set(RenderingGlyphFlags::WIDE_CHAR, cell.flags.contains(Flags::WIDE_CHAR));
self.instances.push(InstanceData {
col: cell.point.column.0 as u16,
row: cell.point.line as u16,
top: glyph.top,
left: glyph.left,
width: glyph.width,
height: glyph.height,
uv_bot: glyph.uv_bot,
uv_left: glyph.uv_left,
uv_width: glyph.uv_width,
uv_height: glyph.uv_height,
r: cell.fg.r,
g: cell.fg.g,
b: cell.fg.b,
cell_flags,
bg_r: cell.bg.r,
bg_g: cell.bg.g,
bg_b: cell.bg.b,
bg_a: (cell.bg_alpha * 255.0) as u8,
});
}
}
impl Batch {
#[inline]
pub fn new() -> Self {
Self { tex: 0, instances: Vec::with_capacity(BATCH_MAX) }
}
#[inline]
pub fn len(&self) -> usize {
self.instances.len()
}
#[inline]
pub fn capacity(&self) -> usize {
BATCH_MAX
}
#[inline]
pub fn size(&self) -> usize {
self.len() * size_of::<InstanceData>()
}
pub fn clear(&mut self) {
self.tex = 0;
self.instances.clear();
}
}
/// Text drawing program.
///
/// Uniforms are prefixed with "u", and vertex attributes are prefixed with "a".
#[derive(Debug)]
pub struct TextShaderProgram {
/// Shader program.
program: ShaderProgram,
/// Projection scale and offset uniform.
u_projection: GLint,
/// Cell dimensions (pixels).
u_cell_dim: GLint,
/// Background pass flag.
///
/// Rendering is split into two passes; one for backgrounds, and one for text.
u_rendering_pass: GLint,
}
impl TextShaderProgram {
pub fn new(shader_version: ShaderVersion) -> Result<TextShaderProgram, Error> {
let program = ShaderProgram::new(shader_version, None, TEXT_SHADER_V, TEXT_SHADER_F)?;
Ok(Self {
u_projection: program.get_uniform_location(cstr!("projection"))?,
u_cell_dim: program.get_uniform_location(cstr!("cellDim"))?,
u_rendering_pass: program.get_uniform_location(cstr!("renderingPass"))?,
program,
})
}
fn set_term_uniforms(&self, props: &SizeInfo) {
unsafe {
gl::Uniform2f(self.u_cell_dim, props.cell_width(), props.cell_height());
}
}
fn set_rendering_pass(&self, rendering_pass: RenderingPass) {
let value = match rendering_pass {
RenderingPass::Background | RenderingPass::SubpixelPass1 => rendering_pass as i32,
_ => unreachable!("provided pass is not supported in GLSL3 renderer"),
};
unsafe {
gl::Uniform1i(self.u_rendering_pass, value);
}
}
}
impl TextShader for TextShaderProgram {
fn id(&self) -> GLuint {
self.program.id()
}
fn projection_uniform(&self) -> GLint {
self.u_projection
}
}
| {
unsafe {
gl::BindTexture(gl::TEXTURE_2D, self.batch.tex());
}
*self.active_tex = self.batch.tex();
} | conditional_block |
glsl3.rs | use std::mem::size_of;
use std::ptr;
use crossfont::RasterizedGlyph;
use log::info;
use alacritty_terminal::term::cell::Flags;
use crate::display::content::RenderableCell;
use crate::display::SizeInfo;
use crate::gl;
use crate::gl::types::*;
use crate::renderer::shader::{ShaderProgram, ShaderVersion};
use crate::renderer::{cstr, Error};
use super::atlas::{Atlas, ATLAS_SIZE};
use super::{
Glyph, LoadGlyph, LoaderApi, RenderingGlyphFlags, RenderingPass, TextRenderApi,
TextRenderBatch, TextRenderer, TextShader,
};
// Shader source.
pub static TEXT_SHADER_F: &str = include_str!("../../../res/glsl3/text.f.glsl");
static TEXT_SHADER_V: &str = include_str!("../../../res/glsl3/text.v.glsl");
/// Maximum items to be drawn in a batch.
const BATCH_MAX: usize = 0x1_0000;
#[derive(Debug)]
pub struct Glsl3Renderer {
program: TextShaderProgram,
vao: GLuint,
ebo: GLuint,
vbo_instance: GLuint,
atlas: Vec<Atlas>,
current_atlas: usize,
active_tex: GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
unsafe {
gl::Enable(gl::BLEND);
gl::BlendFunc(gl::SRC1_COLOR, gl::ONE_MINUS_SRC1_COLOR);
// Disable depth mask, as the renderer never uses depth tests.
gl::DepthMask(gl::FALSE);
gl::GenVertexArrays(1, &mut vao);
gl::GenBuffers(1, &mut ebo);
gl::GenBuffers(1, &mut vbo_instance);
gl::BindVertexArray(vao);
// ---------------------
// Set up element buffer
// ---------------------
let indices: [u32; 6] = [0, 1, 3, 1, 2, 3];
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, ebo);
gl::BufferData(
gl::ELEMENT_ARRAY_BUFFER,
(6 * size_of::<u32>()) as isize,
indices.as_ptr() as *const _,
gl::STATIC_DRAW,
);
// ----------------------------
// Setup vertex instance buffer
// ----------------------------
gl::BindBuffer(gl::ARRAY_BUFFER, vbo_instance);
gl::BufferData(
gl::ARRAY_BUFFER,
(BATCH_MAX * size_of::<InstanceData>()) as isize,
ptr::null(),
gl::STREAM_DRAW,
);
let mut index = 0;
let mut size = 0;
macro_rules! add_attr {
($count:expr, $gl_type:expr, $type:ty) => {
gl::VertexAttribPointer(
index,
$count,
$gl_type,
gl::FALSE,
size_of::<InstanceData>() as i32,
size as *const _,
);
gl::EnableVertexAttribArray(index);
gl::VertexAttribDivisor(index, 1);
#[allow(unused_assignments)]
{
size += $count * size_of::<$type>();
index += 1;
}
};
}
// Coords.
add_attr!(2, gl::UNSIGNED_SHORT, u16);
// Glyph offset and size.
add_attr!(4, gl::SHORT, i16);
// UV offset.
add_attr!(4, gl::FLOAT, f32);
// Color and cell flags.
//
// These are packed together because of an OpenGL driver issue on macOS, which caused a
// `vec3(u8)` text color and a `u8` cell flags to increase the rendering time by a
// huge margin.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Background color.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Cleanup.
gl::BindVertexArray(0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
}
Ok(Self {
program,
vao,
ebo,
vbo_instance,
atlas: vec![Atlas::new(ATLAS_SIZE, false)],
current_atlas: 0,
active_tex: 0,
batch: Batch::new(),
})
}
}
impl<'a> TextRenderer<'a> for Glsl3Renderer {
type RenderApi = RenderApi<'a>;
type RenderBatch = Batch;
type Shader = TextShaderProgram;
fn with_api<'b: 'a, F, T>(&'b mut self, size_info: &'b SizeInfo, func: F) -> T
where
F: FnOnce(Self::RenderApi) -> T,
{
unsafe {
gl::UseProgram(self.program.id());
self.program.set_term_uniforms(size_info);
gl::BindVertexArray(self.vao);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, self.ebo);
gl::BindBuffer(gl::ARRAY_BUFFER, self.vbo_instance);
gl::ActiveTexture(gl::TEXTURE0);
}
let res = func(RenderApi {
active_tex: &mut self.active_tex,
batch: &mut self.batch,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
program: &mut self.program,
});
unsafe {
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindVertexArray(0);
gl::UseProgram(0);
}
res
}
fn program(&self) -> &Self::Shader {
&self.program
}
fn loader_api(&mut self) -> LoaderApi<'_> {
LoaderApi {
active_tex: &mut self.active_tex,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
}
}
}
impl Drop for Glsl3Renderer {
fn drop(&mut self) {
unsafe {
gl::DeleteBuffers(1, &self.vbo_instance);
gl::DeleteBuffers(1, &self.ebo);
gl::DeleteVertexArrays(1, &self.vao);
}
}
}
#[derive(Debug)]
pub struct RenderApi<'a> {
active_tex: &'a mut GLuint,
batch: &'a mut Batch,
atlas: &'a mut Vec<Atlas>,
current_atlas: &'a mut usize,
program: &'a mut TextShaderProgram,
}
impl<'a> TextRenderApi<Batch> for RenderApi<'a> {
fn batch(&mut self) -> &mut Batch {
self.batch
}
fn render_batch(&mut self) {
unsafe {
gl::BufferSubData(
gl::ARRAY_BUFFER,
0,
self.batch.size() as isize,
self.batch.instances.as_ptr() as *const _,
);
}
// Bind texture if necessary.
if *self.active_tex != self.batch.tex() {
unsafe {
gl::BindTexture(gl::TEXTURE_2D, self.batch.tex());
}
*self.active_tex = self.batch.tex();
}
unsafe {
self.program.set_rendering_pass(RenderingPass::Background);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
self.program.set_rendering_pass(RenderingPass::SubpixelPass1);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
}
self.batch.clear();
}
}
impl<'a> LoadGlyph for RenderApi<'a> {
fn load_glyph(&mut self, rasterized: &RasterizedGlyph) -> Glyph {
Atlas::load_glyph(self.active_tex, self.atlas, self.current_atlas, rasterized)
}
fn clear(&mut self) {
Atlas::clear_atlas(self.atlas, self.current_atlas)
}
}
impl<'a> Drop for RenderApi<'a> {
fn drop(&mut self) {
if !self.batch.is_empty() {
self.render_batch();
}
}
}
#[derive(Debug)]
#[repr(C)]
struct InstanceData {
// Coords.
col: u16,
row: u16,
// Glyph offset.
left: i16,
top: i16,
// Glyph size.
width: i16,
height: i16,
// UV offset.
uv_left: f32,
uv_bot: f32,
// uv scale.
uv_width: f32,
uv_height: f32,
// Color.
r: u8,
g: u8,
b: u8,
// Cell flags like multicolor or fullwidth character.
cell_flags: RenderingGlyphFlags,
// Background color.
bg_r: u8,
bg_g: u8,
bg_b: u8,
bg_a: u8,
}
#[derive(Debug, Default)]
pub struct Batch {
tex: GLuint,
instances: Vec<InstanceData>,
}
impl TextRenderBatch for Batch {
#[inline]
fn tex(&self) -> GLuint {
self.tex
}
#[inline]
fn full(&self) -> bool {
self.capacity() == self.len()
}
#[inline]
fn is_empty(&self) -> bool {
self.len() == 0
}
fn add_item(&mut self, cell: &RenderableCell, glyph: &Glyph, _: &SizeInfo) {
if self.is_empty() {
self.tex = glyph.tex_id;
}
let mut cell_flags = RenderingGlyphFlags::empty();
cell_flags.set(RenderingGlyphFlags::COLORED, glyph.multicolor);
cell_flags.set(RenderingGlyphFlags::WIDE_CHAR, cell.flags.contains(Flags::WIDE_CHAR));
self.instances.push(InstanceData {
col: cell.point.column.0 as u16,
row: cell.point.line as u16,
top: glyph.top,
left: glyph.left,
width: glyph.width,
height: glyph.height,
uv_bot: glyph.uv_bot,
uv_left: glyph.uv_left,
uv_width: glyph.uv_width,
uv_height: glyph.uv_height,
r: cell.fg.r,
g: cell.fg.g,
b: cell.fg.b,
cell_flags,
bg_r: cell.bg.r,
bg_g: cell.bg.g,
bg_b: cell.bg.b,
bg_a: (cell.bg_alpha * 255.0) as u8,
});
}
}
impl Batch {
#[inline]
pub fn new() -> Self {
Self { tex: 0, instances: Vec::with_capacity(BATCH_MAX) }
}
#[inline]
pub fn len(&self) -> usize {
self.instances.len()
}
#[inline]
pub fn capacity(&self) -> usize {
BATCH_MAX
}
#[inline]
pub fn size(&self) -> usize {
self.len() * size_of::<InstanceData>()
}
pub fn clear(&mut self) {
self.tex = 0;
self.instances.clear();
}
}
/// Text drawing program.
///
/// Uniforms are prefixed with "u", and vertex attributes are prefixed with "a".
#[derive(Debug)]
pub struct TextShaderProgram {
/// Shader program.
program: ShaderProgram,
/// Projection scale and offset uniform.
u_projection: GLint,
/// Cell dimensions (pixels).
u_cell_dim: GLint,
/// Background pass flag.
/// |
impl TextShaderProgram {
pub fn new(shader_version: ShaderVersion) -> Result<TextShaderProgram, Error> {
let program = ShaderProgram::new(shader_version, None, TEXT_SHADER_V, TEXT_SHADER_F)?;
Ok(Self {
u_projection: program.get_uniform_location(cstr!("projection"))?,
u_cell_dim: program.get_uniform_location(cstr!("cellDim"))?,
u_rendering_pass: program.get_uniform_location(cstr!("renderingPass"))?,
program,
})
}
fn set_term_uniforms(&self, props: &SizeInfo) {
unsafe {
gl::Uniform2f(self.u_cell_dim, props.cell_width(), props.cell_height());
}
}
fn set_rendering_pass(&self, rendering_pass: RenderingPass) {
let value = match rendering_pass {
RenderingPass::Background | RenderingPass::SubpixelPass1 => rendering_pass as i32,
_ => unreachable!("provided pass is not supported in GLSL3 renderer"),
};
unsafe {
gl::Uniform1i(self.u_rendering_pass, value);
}
}
}
impl TextShader for TextShaderProgram {
fn id(&self) -> GLuint {
self.program.id()
}
fn projection_uniform(&self) -> GLint {
self.u_projection
}
} | /// Rendering is split into two passes; one for backgrounds, and one for text.
u_rendering_pass: GLint,
} | random_line_split |
glsl3.rs | use std::mem::size_of;
use std::ptr;
use crossfont::RasterizedGlyph;
use log::info;
use alacritty_terminal::term::cell::Flags;
use crate::display::content::RenderableCell;
use crate::display::SizeInfo;
use crate::gl;
use crate::gl::types::*;
use crate::renderer::shader::{ShaderProgram, ShaderVersion};
use crate::renderer::{cstr, Error};
use super::atlas::{Atlas, ATLAS_SIZE};
use super::{
Glyph, LoadGlyph, LoaderApi, RenderingGlyphFlags, RenderingPass, TextRenderApi,
TextRenderBatch, TextRenderer, TextShader,
};
// Shader source.
pub static TEXT_SHADER_F: &str = include_str!("../../../res/glsl3/text.f.glsl");
static TEXT_SHADER_V: &str = include_str!("../../../res/glsl3/text.v.glsl");
/// Maximum items to be drawn in a batch.
const BATCH_MAX: usize = 0x1_0000;
#[derive(Debug)]
pub struct Glsl3Renderer {
program: TextShaderProgram,
vao: GLuint,
ebo: GLuint,
vbo_instance: GLuint,
atlas: Vec<Atlas>,
current_atlas: usize,
active_tex: GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
unsafe {
gl::Enable(gl::BLEND);
gl::BlendFunc(gl::SRC1_COLOR, gl::ONE_MINUS_SRC1_COLOR);
// Disable depth mask, as the renderer never uses depth tests.
gl::DepthMask(gl::FALSE);
gl::GenVertexArrays(1, &mut vao);
gl::GenBuffers(1, &mut ebo);
gl::GenBuffers(1, &mut vbo_instance);
gl::BindVertexArray(vao);
// ---------------------
// Set up element buffer
// ---------------------
let indices: [u32; 6] = [0, 1, 3, 1, 2, 3];
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, ebo);
gl::BufferData(
gl::ELEMENT_ARRAY_BUFFER,
(6 * size_of::<u32>()) as isize,
indices.as_ptr() as *const _,
gl::STATIC_DRAW,
);
// ----------------------------
// Setup vertex instance buffer
// ----------------------------
gl::BindBuffer(gl::ARRAY_BUFFER, vbo_instance);
gl::BufferData(
gl::ARRAY_BUFFER,
(BATCH_MAX * size_of::<InstanceData>()) as isize,
ptr::null(),
gl::STREAM_DRAW,
);
let mut index = 0;
let mut size = 0;
macro_rules! add_attr {
($count:expr, $gl_type:expr, $type:ty) => {
gl::VertexAttribPointer(
index,
$count,
$gl_type,
gl::FALSE,
size_of::<InstanceData>() as i32,
size as *const _,
);
gl::EnableVertexAttribArray(index);
gl::VertexAttribDivisor(index, 1);
#[allow(unused_assignments)]
{
size += $count * size_of::<$type>();
index += 1;
}
};
}
// Coords.
add_attr!(2, gl::UNSIGNED_SHORT, u16);
// Glyph offset and size.
add_attr!(4, gl::SHORT, i16);
// UV offset.
add_attr!(4, gl::FLOAT, f32);
// Color and cell flags.
//
// These are packed together because of an OpenGL driver issue on macOS, which caused a
// `vec3(u8)` text color and a `u8` cell flags to increase the rendering time by a
// huge margin.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Background color.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Cleanup.
gl::BindVertexArray(0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
}
Ok(Self {
program,
vao,
ebo,
vbo_instance,
atlas: vec![Atlas::new(ATLAS_SIZE, false)],
current_atlas: 0,
active_tex: 0,
batch: Batch::new(),
})
}
}
impl<'a> TextRenderer<'a> for Glsl3Renderer {
type RenderApi = RenderApi<'a>;
type RenderBatch = Batch;
type Shader = TextShaderProgram;
fn with_api<'b: 'a, F, T>(&'b mut self, size_info: &'b SizeInfo, func: F) -> T
where
F: FnOnce(Self::RenderApi) -> T,
{
unsafe {
gl::UseProgram(self.program.id());
self.program.set_term_uniforms(size_info);
gl::BindVertexArray(self.vao);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, self.ebo);
gl::BindBuffer(gl::ARRAY_BUFFER, self.vbo_instance);
gl::ActiveTexture(gl::TEXTURE0);
}
let res = func(RenderApi {
active_tex: &mut self.active_tex,
batch: &mut self.batch,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
program: &mut self.program,
});
unsafe {
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindVertexArray(0);
gl::UseProgram(0);
}
res
}
fn program(&self) -> &Self::Shader {
&self.program
}
fn loader_api(&mut self) -> LoaderApi<'_> {
LoaderApi {
active_tex: &mut self.active_tex,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
}
}
}
impl Drop for Glsl3Renderer {
fn drop(&mut self) {
unsafe {
gl::DeleteBuffers(1, &self.vbo_instance);
gl::DeleteBuffers(1, &self.ebo);
gl::DeleteVertexArrays(1, &self.vao);
}
}
}
#[derive(Debug)]
pub struct | <'a> {
active_tex: &'a mut GLuint,
batch: &'a mut Batch,
atlas: &'a mut Vec<Atlas>,
current_atlas: &'a mut usize,
program: &'a mut TextShaderProgram,
}
impl<'a> TextRenderApi<Batch> for RenderApi<'a> {
fn batch(&mut self) -> &mut Batch {
self.batch
}
fn render_batch(&mut self) {
unsafe {
gl::BufferSubData(
gl::ARRAY_BUFFER,
0,
self.batch.size() as isize,
self.batch.instances.as_ptr() as *const _,
);
}
// Bind texture if necessary.
if *self.active_tex != self.batch.tex() {
unsafe {
gl::BindTexture(gl::TEXTURE_2D, self.batch.tex());
}
*self.active_tex = self.batch.tex();
}
unsafe {
self.program.set_rendering_pass(RenderingPass::Background);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
self.program.set_rendering_pass(RenderingPass::SubpixelPass1);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
}
self.batch.clear();
}
}
impl<'a> LoadGlyph for RenderApi<'a> {
fn load_glyph(&mut self, rasterized: &RasterizedGlyph) -> Glyph {
Atlas::load_glyph(self.active_tex, self.atlas, self.current_atlas, rasterized)
}
fn clear(&mut self) {
Atlas::clear_atlas(self.atlas, self.current_atlas)
}
}
impl<'a> Drop for RenderApi<'a> {
fn drop(&mut self) {
if !self.batch.is_empty() {
self.render_batch();
}
}
}
#[derive(Debug)]
#[repr(C)]
struct InstanceData {
// Coords.
col: u16,
row: u16,
// Glyph offset.
left: i16,
top: i16,
// Glyph size.
width: i16,
height: i16,
// UV offset.
uv_left: f32,
uv_bot: f32,
// uv scale.
uv_width: f32,
uv_height: f32,
// Color.
r: u8,
g: u8,
b: u8,
// Cell flags like multicolor or fullwidth character.
cell_flags: RenderingGlyphFlags,
// Background color.
bg_r: u8,
bg_g: u8,
bg_b: u8,
bg_a: u8,
}
#[derive(Debug, Default)]
pub struct Batch {
tex: GLuint,
instances: Vec<InstanceData>,
}
impl TextRenderBatch for Batch {
#[inline]
fn tex(&self) -> GLuint {
self.tex
}
#[inline]
fn full(&self) -> bool {
self.capacity() == self.len()
}
#[inline]
fn is_empty(&self) -> bool {
self.len() == 0
}
fn add_item(&mut self, cell: &RenderableCell, glyph: &Glyph, _: &SizeInfo) {
if self.is_empty() {
self.tex = glyph.tex_id;
}
let mut cell_flags = RenderingGlyphFlags::empty();
cell_flags.set(RenderingGlyphFlags::COLORED, glyph.multicolor);
cell_flags.set(RenderingGlyphFlags::WIDE_CHAR, cell.flags.contains(Flags::WIDE_CHAR));
self.instances.push(InstanceData {
col: cell.point.column.0 as u16,
row: cell.point.line as u16,
top: glyph.top,
left: glyph.left,
width: glyph.width,
height: glyph.height,
uv_bot: glyph.uv_bot,
uv_left: glyph.uv_left,
uv_width: glyph.uv_width,
uv_height: glyph.uv_height,
r: cell.fg.r,
g: cell.fg.g,
b: cell.fg.b,
cell_flags,
bg_r: cell.bg.r,
bg_g: cell.bg.g,
bg_b: cell.bg.b,
bg_a: (cell.bg_alpha * 255.0) as u8,
});
}
}
impl Batch {
#[inline]
pub fn new() -> Self {
Self { tex: 0, instances: Vec::with_capacity(BATCH_MAX) }
}
#[inline]
pub fn len(&self) -> usize {
self.instances.len()
}
#[inline]
pub fn capacity(&self) -> usize {
BATCH_MAX
}
#[inline]
pub fn size(&self) -> usize {
self.len() * size_of::<InstanceData>()
}
pub fn clear(&mut self) {
self.tex = 0;
self.instances.clear();
}
}
/// Text drawing program.
///
/// Uniforms are prefixed with "u", and vertex attributes are prefixed with "a".
#[derive(Debug)]
pub struct TextShaderProgram {
/// Shader program.
program: ShaderProgram,
/// Projection scale and offset uniform.
u_projection: GLint,
/// Cell dimensions (pixels).
u_cell_dim: GLint,
/// Background pass flag.
///
/// Rendering is split into two passes; one for backgrounds, and one for text.
u_rendering_pass: GLint,
}
impl TextShaderProgram {
pub fn new(shader_version: ShaderVersion) -> Result<TextShaderProgram, Error> {
let program = ShaderProgram::new(shader_version, None, TEXT_SHADER_V, TEXT_SHADER_F)?;
Ok(Self {
u_projection: program.get_uniform_location(cstr!("projection"))?,
u_cell_dim: program.get_uniform_location(cstr!("cellDim"))?,
u_rendering_pass: program.get_uniform_location(cstr!("renderingPass"))?,
program,
})
}
fn set_term_uniforms(&self, props: &SizeInfo) {
unsafe {
gl::Uniform2f(self.u_cell_dim, props.cell_width(), props.cell_height());
}
}
fn set_rendering_pass(&self, rendering_pass: RenderingPass) {
let value = match rendering_pass {
RenderingPass::Background | RenderingPass::SubpixelPass1 => rendering_pass as i32,
_ => unreachable!("provided pass is not supported in GLSL3 renderer"),
};
unsafe {
gl::Uniform1i(self.u_rendering_pass, value);
}
}
}
impl TextShader for TextShaderProgram {
fn id(&self) -> GLuint {
self.program.id()
}
fn projection_uniform(&self) -> GLint {
self.u_projection
}
}
| RenderApi | identifier_name |
glsl3.rs | use std::mem::size_of;
use std::ptr;
use crossfont::RasterizedGlyph;
use log::info;
use alacritty_terminal::term::cell::Flags;
use crate::display::content::RenderableCell;
use crate::display::SizeInfo;
use crate::gl;
use crate::gl::types::*;
use crate::renderer::shader::{ShaderProgram, ShaderVersion};
use crate::renderer::{cstr, Error};
use super::atlas::{Atlas, ATLAS_SIZE};
use super::{
Glyph, LoadGlyph, LoaderApi, RenderingGlyphFlags, RenderingPass, TextRenderApi,
TextRenderBatch, TextRenderer, TextShader,
};
// Shader source.
pub static TEXT_SHADER_F: &str = include_str!("../../../res/glsl3/text.f.glsl");
static TEXT_SHADER_V: &str = include_str!("../../../res/glsl3/text.v.glsl");
/// Maximum items to be drawn in a batch.
const BATCH_MAX: usize = 0x1_0000;
#[derive(Debug)]
pub struct Glsl3Renderer {
program: TextShaderProgram,
vao: GLuint,
ebo: GLuint,
vbo_instance: GLuint,
atlas: Vec<Atlas>,
current_atlas: usize,
active_tex: GLuint,
batch: Batch,
}
impl Glsl3Renderer {
pub fn new() -> Result<Self, Error> {
info!("Using OpenGL 3.3 renderer");
let program = TextShaderProgram::new(ShaderVersion::Glsl3)?;
let mut vao: GLuint = 0;
let mut ebo: GLuint = 0;
let mut vbo_instance: GLuint = 0;
unsafe {
gl::Enable(gl::BLEND);
gl::BlendFunc(gl::SRC1_COLOR, gl::ONE_MINUS_SRC1_COLOR);
// Disable depth mask, as the renderer never uses depth tests.
gl::DepthMask(gl::FALSE);
gl::GenVertexArrays(1, &mut vao);
gl::GenBuffers(1, &mut ebo);
gl::GenBuffers(1, &mut vbo_instance);
gl::BindVertexArray(vao);
// ---------------------
// Set up element buffer
// ---------------------
let indices: [u32; 6] = [0, 1, 3, 1, 2, 3];
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, ebo);
gl::BufferData(
gl::ELEMENT_ARRAY_BUFFER,
(6 * size_of::<u32>()) as isize,
indices.as_ptr() as *const _,
gl::STATIC_DRAW,
);
// ----------------------------
// Setup vertex instance buffer
// ----------------------------
gl::BindBuffer(gl::ARRAY_BUFFER, vbo_instance);
gl::BufferData(
gl::ARRAY_BUFFER,
(BATCH_MAX * size_of::<InstanceData>()) as isize,
ptr::null(),
gl::STREAM_DRAW,
);
let mut index = 0;
let mut size = 0;
macro_rules! add_attr {
($count:expr, $gl_type:expr, $type:ty) => {
gl::VertexAttribPointer(
index,
$count,
$gl_type,
gl::FALSE,
size_of::<InstanceData>() as i32,
size as *const _,
);
gl::EnableVertexAttribArray(index);
gl::VertexAttribDivisor(index, 1);
#[allow(unused_assignments)]
{
size += $count * size_of::<$type>();
index += 1;
}
};
}
// Coords.
add_attr!(2, gl::UNSIGNED_SHORT, u16);
// Glyph offset and size.
add_attr!(4, gl::SHORT, i16);
// UV offset.
add_attr!(4, gl::FLOAT, f32);
// Color and cell flags.
//
// These are packed together because of an OpenGL driver issue on macOS, which caused a
// `vec3(u8)` text color and a `u8` cell flags to increase the rendering time by a
// huge margin.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Background color.
add_attr!(4, gl::UNSIGNED_BYTE, u8);
// Cleanup.
gl::BindVertexArray(0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
}
Ok(Self {
program,
vao,
ebo,
vbo_instance,
atlas: vec![Atlas::new(ATLAS_SIZE, false)],
current_atlas: 0,
active_tex: 0,
batch: Batch::new(),
})
}
}
impl<'a> TextRenderer<'a> for Glsl3Renderer {
type RenderApi = RenderApi<'a>;
type RenderBatch = Batch;
type Shader = TextShaderProgram;
fn with_api<'b: 'a, F, T>(&'b mut self, size_info: &'b SizeInfo, func: F) -> T
where
F: FnOnce(Self::RenderApi) -> T,
{
unsafe {
gl::UseProgram(self.program.id());
self.program.set_term_uniforms(size_info);
gl::BindVertexArray(self.vao);
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, self.ebo);
gl::BindBuffer(gl::ARRAY_BUFFER, self.vbo_instance);
gl::ActiveTexture(gl::TEXTURE0);
}
let res = func(RenderApi {
active_tex: &mut self.active_tex,
batch: &mut self.batch,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
program: &mut self.program,
});
unsafe {
gl::BindBuffer(gl::ELEMENT_ARRAY_BUFFER, 0);
gl::BindBuffer(gl::ARRAY_BUFFER, 0);
gl::BindVertexArray(0);
gl::UseProgram(0);
}
res
}
fn program(&self) -> &Self::Shader {
&self.program
}
fn loader_api(&mut self) -> LoaderApi<'_> {
LoaderApi {
active_tex: &mut self.active_tex,
atlas: &mut self.atlas,
current_atlas: &mut self.current_atlas,
}
}
}
impl Drop for Glsl3Renderer {
fn drop(&mut self) {
unsafe {
gl::DeleteBuffers(1, &self.vbo_instance);
gl::DeleteBuffers(1, &self.ebo);
gl::DeleteVertexArrays(1, &self.vao);
}
}
}
#[derive(Debug)]
pub struct RenderApi<'a> {
active_tex: &'a mut GLuint,
batch: &'a mut Batch,
atlas: &'a mut Vec<Atlas>,
current_atlas: &'a mut usize,
program: &'a mut TextShaderProgram,
}
impl<'a> TextRenderApi<Batch> for RenderApi<'a> {
fn batch(&mut self) -> &mut Batch {
self.batch
}
fn render_batch(&mut self) {
unsafe {
gl::BufferSubData(
gl::ARRAY_BUFFER,
0,
self.batch.size() as isize,
self.batch.instances.as_ptr() as *const _,
);
}
// Bind texture if necessary.
if *self.active_tex != self.batch.tex() {
unsafe {
gl::BindTexture(gl::TEXTURE_2D, self.batch.tex());
}
*self.active_tex = self.batch.tex();
}
unsafe {
self.program.set_rendering_pass(RenderingPass::Background);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
self.program.set_rendering_pass(RenderingPass::SubpixelPass1);
gl::DrawElementsInstanced(
gl::TRIANGLES,
6,
gl::UNSIGNED_INT,
ptr::null(),
self.batch.len() as GLsizei,
);
}
self.batch.clear();
}
}
impl<'a> LoadGlyph for RenderApi<'a> {
fn load_glyph(&mut self, rasterized: &RasterizedGlyph) -> Glyph {
Atlas::load_glyph(self.active_tex, self.atlas, self.current_atlas, rasterized)
}
fn clear(&mut self) {
Atlas::clear_atlas(self.atlas, self.current_atlas)
}
}
impl<'a> Drop for RenderApi<'a> {
fn drop(&mut self) {
if !self.batch.is_empty() {
self.render_batch();
}
}
}
#[derive(Debug)]
#[repr(C)]
struct InstanceData {
// Coords.
col: u16,
row: u16,
// Glyph offset.
left: i16,
top: i16,
// Glyph size.
width: i16,
height: i16,
// UV offset.
uv_left: f32,
uv_bot: f32,
// uv scale.
uv_width: f32,
uv_height: f32,
// Color.
r: u8,
g: u8,
b: u8,
// Cell flags like multicolor or fullwidth character.
cell_flags: RenderingGlyphFlags,
// Background color.
bg_r: u8,
bg_g: u8,
bg_b: u8,
bg_a: u8,
}
#[derive(Debug, Default)]
pub struct Batch {
tex: GLuint,
instances: Vec<InstanceData>,
}
impl TextRenderBatch for Batch {
#[inline]
fn tex(&self) -> GLuint {
self.tex
}
#[inline]
fn full(&self) -> bool {
self.capacity() == self.len()
}
#[inline]
fn is_empty(&self) -> bool {
self.len() == 0
}
fn add_item(&mut self, cell: &RenderableCell, glyph: &Glyph, _: &SizeInfo) {
if self.is_empty() {
self.tex = glyph.tex_id;
}
let mut cell_flags = RenderingGlyphFlags::empty();
cell_flags.set(RenderingGlyphFlags::COLORED, glyph.multicolor);
cell_flags.set(RenderingGlyphFlags::WIDE_CHAR, cell.flags.contains(Flags::WIDE_CHAR));
self.instances.push(InstanceData {
col: cell.point.column.0 as u16,
row: cell.point.line as u16,
top: glyph.top,
left: glyph.left,
width: glyph.width,
height: glyph.height,
uv_bot: glyph.uv_bot,
uv_left: glyph.uv_left,
uv_width: glyph.uv_width,
uv_height: glyph.uv_height,
r: cell.fg.r,
g: cell.fg.g,
b: cell.fg.b,
cell_flags,
bg_r: cell.bg.r,
bg_g: cell.bg.g,
bg_b: cell.bg.b,
bg_a: (cell.bg_alpha * 255.0) as u8,
});
}
}
impl Batch {
#[inline]
pub fn new() -> Self {
Self { tex: 0, instances: Vec::with_capacity(BATCH_MAX) }
}
#[inline]
pub fn len(&self) -> usize |
#[inline]
pub fn capacity(&self) -> usize {
BATCH_MAX
}
#[inline]
pub fn size(&self) -> usize {
self.len() * size_of::<InstanceData>()
}
pub fn clear(&mut self) {
self.tex = 0;
self.instances.clear();
}
}
/// Text drawing program.
///
/// Uniforms are prefixed with "u", and vertex attributes are prefixed with "a".
#[derive(Debug)]
pub struct TextShaderProgram {
/// Shader program.
program: ShaderProgram,
/// Projection scale and offset uniform.
u_projection: GLint,
/// Cell dimensions (pixels).
u_cell_dim: GLint,
/// Background pass flag.
///
/// Rendering is split into two passes; one for backgrounds, and one for text.
u_rendering_pass: GLint,
}
impl TextShaderProgram {
pub fn new(shader_version: ShaderVersion) -> Result<TextShaderProgram, Error> {
let program = ShaderProgram::new(shader_version, None, TEXT_SHADER_V, TEXT_SHADER_F)?;
Ok(Self {
u_projection: program.get_uniform_location(cstr!("projection"))?,
u_cell_dim: program.get_uniform_location(cstr!("cellDim"))?,
u_rendering_pass: program.get_uniform_location(cstr!("renderingPass"))?,
program,
})
}
fn set_term_uniforms(&self, props: &SizeInfo) {
unsafe {
gl::Uniform2f(self.u_cell_dim, props.cell_width(), props.cell_height());
}
}
fn set_rendering_pass(&self, rendering_pass: RenderingPass) {
let value = match rendering_pass {
RenderingPass::Background | RenderingPass::SubpixelPass1 => rendering_pass as i32,
_ => unreachable!("provided pass is not supported in GLSL3 renderer"),
};
unsafe {
gl::Uniform1i(self.u_rendering_pass, value);
}
}
}
impl TextShader for TextShaderProgram {
fn id(&self) -> GLuint {
self.program.id()
}
fn projection_uniform(&self) -> GLint {
self.u_projection
}
}
| {
self.instances.len()
} | identifier_body |
service.rs | use crate::{
common::client::{ClientId, Credentials, Token},
coordinator,
};
use bytes::Bytes;
use derive_more::From;
use futures::{ready, stream::Stream};
use std::{
collections::HashMap,
error::Error,
future::Future,
pin::Pin,
task::{Context, Poll},
};
use tarpc::context::current as rpc_context;
use thiserror::Error;
use tokio::{
stream::StreamExt,
sync::{
mpsc::{unbounded_channel, UnboundedReceiver, UnboundedSender},
oneshot,
},
};
use tracing_futures::Instrument;
use std::env;
use std::fs::File;
use std::io::prelude::*;
use nix::sys::signal;
use nix::unistd::Pid;
use std::thread;
use std::time::Duration; | /// A future that orchestrates the entire aggregator service.
// TODO: maybe add a HashSet or HashMap of clients who already
// uploaded their weights to prevent a client from uploading weights
// multiple times. Or we could just remove that ID from the
// `allowed_ids` map.
// TODO: maybe add a HashSet for clients that are already
// downloading/uploading, to prevent DoS attacks.
pub struct Service<A>
where
A: Aggregator,
{
/// Clients that the coordinator selected for the current
/// round. They can use their unique token to download the global
/// weights and upload their own local results once they finished
/// training.
allowed_ids: HashMap<ClientId, Token>,
/// The latest global weights as computed by the aggregator.
// NOTE: We could store this directly in the task that handles the
// HTTP requests. I initially though that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, which handles the weights or performs
/// the aggregations.
aggregator: A,
/// A client for the coordinator RPC service.
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
aggregation_future: Option<AggregationFuture<A>>,
model_number: usize,
}
/// This trait defines the methods that an aggregator should
/// implement.
pub trait Aggregator {
type Error: Error + Send + 'static + Sync;
type AggregateFut: Future<Output = Result<Bytes, Self::Error>> + Unpin;
type AddWeightsFut: Future<Output = Result<(), Self::Error>> + Unpin + Send + 'static;
/// Check the validity of the given weights and if they are valid,
/// add them to the set of weights to aggregate.
fn add_weights(&mut self, weights: Bytes) -> Self::AddWeightsFut;
/// Run the aggregator and return the result.
fn aggregate(&mut self) -> Self::AggregateFut;
}
impl<A> Service<A>
where
A: Aggregator,
{
pub fn new(
aggregator: A,
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
) -> Self {
Self {
aggregator,
requests,
rpc_client,
allowed_ids: HashMap::new(),
global_weights: Bytes::new(),
aggregation_future: None,
model_number: 0,
}
}
/// Handle the incoming requests.
fn poll_requests(&mut self, cx: &mut Context) -> Poll<()> {
trace!("polling requests");
loop {
match ready!(Pin::new(&mut self.requests).poll_next(cx)) {
Some(request) => self.handle_request(request),
None => {
trace!("no more request to handle");
return Poll::Ready(());
}
}
}
}
fn handle_download_request(&mut self, request: DownloadRequest) {
debug!("handling download request");
let DownloadRequest {
credentials,
response_tx,
} = request;
if self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false)
{
let _ = response_tx.send(Ok(self.global_weights.clone()));
} else {
warn!("rejecting download request");
let _ = response_tx.send(Err(DownloadError::Unauthorized));
}
}
fn handle_upload_request(&mut self, request: UploadRequest) {
debug!("handling upload request");
let UploadRequest { credentials, data } = request;
let accept_upload = self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false);
if !accept_upload {
warn!("rejecting upload request");
return;
}
let mut rpc_client = self.rpc_client.clone();
let fut = self.aggregator.add_weights(data);
tokio::spawn(
async move {
let result = fut.await;
debug!("sending end training request to the coordinator");
rpc_client
.end_training(rpc_context(), *credentials.id(), result.is_ok())
.await
.map_err(|e| {
warn!(
"failed to send end training request to the coordinator: {}",
e
);
})
}
.instrument(trace_span!("end_training_rpc_request")),
);
}
fn handle_request(&mut self, request: Request<A>) {
match request {
Request::Download(req) => self.handle_download_request(req),
Request::Upload(req) => self.handle_upload_request(req),
Request::Select(req) => self.handle_select_request(req),
Request::Aggregate(req) => self.handle_aggregate_request(req),
}
}
fn handle_aggregate_request(&mut self, request: AggregateRequest<A>) {
info!("handling aggregate request");
let AggregateRequest { response_tx } = request;
self.allowed_ids = HashMap::new();
self.aggregation_future = Some(AggregationFuture {
future: self.aggregator.aggregate(),
response_tx,
});
}
fn handle_select_request(&mut self, request: SelectRequest<A>) {
info!("handling select request");
let SelectRequest {
credentials,
response_tx,
} = request;
let (id, token) = credentials.into_parts();
self.allowed_ids.insert(id, token);
if response_tx.send(Ok(())).is_err() {
warn!("failed to send reponse: channel closed");
}
}
#[allow(clippy::cognitive_complexity)]
fn poll_aggregation(&mut self, cx: &mut Context) {
// Check if we're waiting for an aggregation, ie whether
// there's a future to poll.
let future = if let Some(future) = self.aggregation_future.take() {
future
} else {
trace!("no aggregation future running: skipping polling");
return;
};
trace!("polling aggregation future");
let AggregationFuture {
mut future,
response_tx,
} = future;
let result = match Pin::new(&mut future).poll(cx) {
Poll::Ready(Ok(weights)) => {
info!("aggregation succeeded, settings global weights");
self.global_weights = weights;
if let Ok(path) = env::var("NEVERMINED_OUTPUTS_PATH") {
let file_name = format!("{}/model_{}.npy", path, self.model_number);
let mut file = File::create(&file_name).unwrap();
info!("Writing model {}", file_name);
file.write_all(&self.global_weights).unwrap();
self.model_number += 1;
}
Ok(())
}
Poll::Ready(Err(e)) => {
error!(error = %e, "aggregation failed");
Err(e)
}
Poll::Pending => {
debug!("aggregation future still running");
self.aggregation_future = Some(AggregationFuture {
future,
response_tx,
});
return;
}
};
if response_tx.send(result).is_err() {
error!("failed to send aggregation response to RPC task: receiver dropped");
}
if self.model_number == 10 {
thread::sleep(Duration::from_millis(10 * 1000));
signal::kill(Pid::this(), signal::Signal::SIGINT).unwrap();
}
}
}
struct AggregationFuture<A>
where
A: Aggregator,
{
future: A::AggregateFut,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
impl<A> Future for Service<A>
where
A: Aggregator + Unpin,
{
type Output = ();
fn poll(self: Pin<&mut Self>, cx: &mut Context) -> Poll<Self::Output> {
trace!("polling Service");
let pin = self.get_mut();
if let Poll::Ready(_) = pin.poll_requests(cx) {
return Poll::Ready(());
}
pin.poll_aggregation(cx);
Poll::Pending
}
}
pub struct ServiceRequests<A>(Pin<Box<dyn Stream<Item = Request<A>> + Send>>)
where
A: Aggregator;
impl<A> Stream for ServiceRequests<A>
where
A: Aggregator,
{
type Item = Request<A>;
fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context) -> Poll<Option<Self::Item>> {
trace!("polling ServiceRequests");
self.0.as_mut().poll_next(cx)
}
}
impl<A> ServiceRequests<A>
where
A: Aggregator + 'static,
{
fn new(
upload: UnboundedReceiver<UploadRequest>,
download: UnboundedReceiver<DownloadRequest>,
aggregate: UnboundedReceiver<AggregateRequest<A>>,
select: UnboundedReceiver<SelectRequest<A>>,
) -> Self {
let stream = download
.map(Request::from)
.merge(upload.map(Request::from))
.merge(aggregate.map(Request::from))
.merge(select.map(Request::from));
Self(Box::pin(stream))
}
}
#[derive(From)]
pub struct UploadRequest {
credentials: Credentials,
data: Bytes,
}
#[derive(From)]
pub struct DownloadRequest {
credentials: Credentials,
response_tx: oneshot::Sender<Result<Bytes, DownloadError>>,
}
#[derive(From)]
pub struct AggregateRequest<A>
where
A: Aggregator,
{
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub struct SelectRequest<A>
where
A: Aggregator,
{
credentials: Credentials,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub enum Request<A>
where
A: Aggregator,
{
Upload(UploadRequest),
Download(DownloadRequest),
Aggregate(AggregateRequest<A>),
Select(SelectRequest<A>),
}
pub struct ServiceHandle<A>
where
A: Aggregator,
{
upload: UnboundedSender<UploadRequest>,
download: UnboundedSender<DownloadRequest>,
aggregate: UnboundedSender<AggregateRequest<A>>,
select: UnboundedSender<SelectRequest<A>>,
}
// We implement Clone manually because it can only be derived if A:
// Clone, which we don't want.
impl<A> Clone for ServiceHandle<A>
where
A: Aggregator,
{
fn clone(&self) -> Self {
Self {
upload: self.upload.clone(),
download: self.download.clone(),
aggregate: self.aggregate.clone(),
select: self.select.clone(),
}
}
}
impl<A> ServiceHandle<A>
where
A: Aggregator + 'static,
{
pub fn new() -> (Self, ServiceRequests<A>) {
let (upload_tx, upload_rx) = unbounded_channel::<UploadRequest>();
let (download_tx, download_rx) = unbounded_channel::<DownloadRequest>();
let (aggregate_tx, aggregate_rx) = unbounded_channel::<AggregateRequest<A>>();
let (select_tx, select_rx) = unbounded_channel::<SelectRequest<A>>();
let handle = Self {
upload: upload_tx,
download: download_tx,
aggregate: aggregate_tx,
select: select_tx,
};
let service_requests =
ServiceRequests::new(upload_rx, download_rx, aggregate_rx, select_rx);
(handle, service_requests)
}
pub async fn download(
&self,
credentials: Credentials,
) -> Result<Bytes, ServiceError<DownloadError>> {
let (tx, rx) = oneshot::channel::<Result<Bytes, DownloadError>>();
let request = DownloadRequest::from((credentials, tx));
Self::send_request(request, &self.download)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn upload(
&self,
credentials: Credentials,
data: Bytes,
) -> Result<(), ServiceError<UploadError>> {
let request = UploadRequest::from((credentials, data));
Self::send_request(request, &self.upload)?;
Ok(())
}
pub async fn aggregate(&self) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(AggregateRequest::from(tx), &self.aggregate)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn select(&self, credentials: Credentials) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(SelectRequest::from((credentials, tx)), &self.select)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
fn send_request<P>(payload: P, tx: &UnboundedSender<P>) -> Result<(), ChannelError> {
trace!("send request to the service");
if tx.send(payload).is_err() {
warn!("failed to send request: channel closed");
Err(ChannelError::Request)
} else {
trace!("request sent");
Ok(())
}
}
async fn recv_response<R>(rx: oneshot::Receiver<R>) -> Result<R, ChannelError> {
rx.await.map_err(|_| {
warn!("could not receive response: channel closed");
ChannelError::Response
})
}
}
#[derive(Error, Debug)]
pub enum DownloadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum UploadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum ServiceError<E>
where
E: Error,
{
#[error("failed to send the request or receive the response")]
Handle(#[from] ChannelError),
#[error("request failed: {0}")]
Request(E),
}
#[derive(Error, Debug)]
pub enum ChannelError {
#[error("failed to send request to Service")]
Request,
#[error("failed to receive the response from Service")]
Response,
} | random_line_split | |
service.rs | use crate::{
common::client::{ClientId, Credentials, Token},
coordinator,
};
use bytes::Bytes;
use derive_more::From;
use futures::{ready, stream::Stream};
use std::{
collections::HashMap,
error::Error,
future::Future,
pin::Pin,
task::{Context, Poll},
};
use tarpc::context::current as rpc_context;
use thiserror::Error;
use tokio::{
stream::StreamExt,
sync::{
mpsc::{unbounded_channel, UnboundedReceiver, UnboundedSender},
oneshot,
},
};
use tracing_futures::Instrument;
use std::env;
use std::fs::File;
use std::io::prelude::*;
use nix::sys::signal;
use nix::unistd::Pid;
use std::thread;
use std::time::Duration;
/// A future that orchestrates the entire aggregator service.
// TODO: maybe add a HashSet or HashMap of clients who already
// uploaded their weights to prevent a client from uploading weights
// multiple times. Or we could just remove that ID from the
// `allowed_ids` map.
// TODO: maybe add a HashSet for clients that are already
// downloading/uploading, to prevent DoS attacks.
pub struct Service<A>
where
A: Aggregator,
{
/// Clients that the coordinator selected for the current
/// round. They can use their unique token to download the global
/// weights and upload their own local results once they finished
/// training.
allowed_ids: HashMap<ClientId, Token>,
/// The latest global weights as computed by the aggregator.
// NOTE: We could store this directly in the task that handles the
// HTTP requests. I initially though that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, which handles the weights or performs
/// the aggregations.
aggregator: A,
/// A client for the coordinator RPC service.
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
aggregation_future: Option<AggregationFuture<A>>,
model_number: usize,
}
/// This trait defines the methods that an aggregator should
/// implement.
pub trait Aggregator {
type Error: Error + Send + 'static + Sync;
type AggregateFut: Future<Output = Result<Bytes, Self::Error>> + Unpin;
type AddWeightsFut: Future<Output = Result<(), Self::Error>> + Unpin + Send + 'static;
/// Check the validity of the given weights and if they are valid,
/// add them to the set of weights to aggregate.
fn add_weights(&mut self, weights: Bytes) -> Self::AddWeightsFut;
/// Run the aggregator and return the result.
fn aggregate(&mut self) -> Self::AggregateFut;
}
impl<A> Service<A>
where
A: Aggregator,
{
pub fn new(
aggregator: A,
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
) -> Self {
Self {
aggregator,
requests,
rpc_client,
allowed_ids: HashMap::new(),
global_weights: Bytes::new(),
aggregation_future: None,
model_number: 0,
}
}
/// Handle the incoming requests.
fn poll_requests(&mut self, cx: &mut Context) -> Poll<()> {
trace!("polling requests");
loop {
match ready!(Pin::new(&mut self.requests).poll_next(cx)) {
Some(request) => self.handle_request(request),
None => {
trace!("no more request to handle");
return Poll::Ready(());
}
}
}
}
fn handle_download_request(&mut self, request: DownloadRequest) {
debug!("handling download request");
let DownloadRequest {
credentials,
response_tx,
} = request;
if self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false)
{
let _ = response_tx.send(Ok(self.global_weights.clone()));
} else {
warn!("rejecting download request");
let _ = response_tx.send(Err(DownloadError::Unauthorized));
}
}
fn handle_upload_request(&mut self, request: UploadRequest) {
debug!("handling upload request");
let UploadRequest { credentials, data } = request;
let accept_upload = self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false);
if !accept_upload {
warn!("rejecting upload request");
return;
}
let mut rpc_client = self.rpc_client.clone();
let fut = self.aggregator.add_weights(data);
tokio::spawn(
async move {
let result = fut.await;
debug!("sending end training request to the coordinator");
rpc_client
.end_training(rpc_context(), *credentials.id(), result.is_ok())
.await
.map_err(|e| {
warn!(
"failed to send end training request to the coordinator: {}",
e
);
})
}
.instrument(trace_span!("end_training_rpc_request")),
);
}
fn handle_request(&mut self, request: Request<A>) {
match request {
Request::Download(req) => self.handle_download_request(req),
Request::Upload(req) => self.handle_upload_request(req),
Request::Select(req) => self.handle_select_request(req),
Request::Aggregate(req) => self.handle_aggregate_request(req),
}
}
fn handle_aggregate_request(&mut self, request: AggregateRequest<A>) {
info!("handling aggregate request");
let AggregateRequest { response_tx } = request;
self.allowed_ids = HashMap::new();
self.aggregation_future = Some(AggregationFuture {
future: self.aggregator.aggregate(),
response_tx,
});
}
fn handle_select_request(&mut self, request: SelectRequest<A>) {
info!("handling select request");
let SelectRequest {
credentials,
response_tx,
} = request;
let (id, token) = credentials.into_parts();
self.allowed_ids.insert(id, token);
if response_tx.send(Ok(())).is_err() {
warn!("failed to send reponse: channel closed");
}
}
#[allow(clippy::cognitive_complexity)]
fn poll_aggregation(&mut self, cx: &mut Context) {
// Check if we're waiting for an aggregation, ie whether
// there's a future to poll.
let future = if let Some(future) = self.aggregation_future.take() {
future
} else {
trace!("no aggregation future running: skipping polling");
return;
};
trace!("polling aggregation future");
let AggregationFuture {
mut future,
response_tx,
} = future;
let result = match Pin::new(&mut future).poll(cx) {
Poll::Ready(Ok(weights)) => {
info!("aggregation succeeded, settings global weights");
self.global_weights = weights;
if let Ok(path) = env::var("NEVERMINED_OUTPUTS_PATH") {
let file_name = format!("{}/model_{}.npy", path, self.model_number);
let mut file = File::create(&file_name).unwrap();
info!("Writing model {}", file_name);
file.write_all(&self.global_weights).unwrap();
self.model_number += 1;
}
Ok(())
}
Poll::Ready(Err(e)) => {
error!(error = %e, "aggregation failed");
Err(e)
}
Poll::Pending => {
debug!("aggregation future still running");
self.aggregation_future = Some(AggregationFuture {
future,
response_tx,
});
return;
}
};
if response_tx.send(result).is_err() {
error!("failed to send aggregation response to RPC task: receiver dropped");
}
if self.model_number == 10 {
thread::sleep(Duration::from_millis(10 * 1000));
signal::kill(Pid::this(), signal::Signal::SIGINT).unwrap();
}
}
}
struct AggregationFuture<A>
where
A: Aggregator,
{
future: A::AggregateFut,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
impl<A> Future for Service<A>
where
A: Aggregator + Unpin,
{
type Output = ();
fn poll(self: Pin<&mut Self>, cx: &mut Context) -> Poll<Self::Output> {
trace!("polling Service");
let pin = self.get_mut();
if let Poll::Ready(_) = pin.poll_requests(cx) {
return Poll::Ready(());
}
pin.poll_aggregation(cx);
Poll::Pending
}
}
pub struct ServiceRequests<A>(Pin<Box<dyn Stream<Item = Request<A>> + Send>>)
where
A: Aggregator;
impl<A> Stream for ServiceRequests<A>
where
A: Aggregator,
{
type Item = Request<A>;
fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context) -> Poll<Option<Self::Item>> {
trace!("polling ServiceRequests");
self.0.as_mut().poll_next(cx)
}
}
impl<A> ServiceRequests<A>
where
A: Aggregator + 'static,
{
fn new(
upload: UnboundedReceiver<UploadRequest>,
download: UnboundedReceiver<DownloadRequest>,
aggregate: UnboundedReceiver<AggregateRequest<A>>,
select: UnboundedReceiver<SelectRequest<A>>,
) -> Self {
let stream = download
.map(Request::from)
.merge(upload.map(Request::from))
.merge(aggregate.map(Request::from))
.merge(select.map(Request::from));
Self(Box::pin(stream))
}
}
#[derive(From)]
pub struct UploadRequest {
credentials: Credentials,
data: Bytes,
}
#[derive(From)]
pub struct DownloadRequest {
credentials: Credentials,
response_tx: oneshot::Sender<Result<Bytes, DownloadError>>,
}
#[derive(From)]
pub struct AggregateRequest<A>
where
A: Aggregator,
{
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub struct SelectRequest<A>
where
A: Aggregator,
{
credentials: Credentials,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub enum Request<A>
where
A: Aggregator,
{
Upload(UploadRequest),
Download(DownloadRequest),
Aggregate(AggregateRequest<A>),
Select(SelectRequest<A>),
}
pub struct ServiceHandle<A>
where
A: Aggregator,
{
upload: UnboundedSender<UploadRequest>,
download: UnboundedSender<DownloadRequest>,
aggregate: UnboundedSender<AggregateRequest<A>>,
select: UnboundedSender<SelectRequest<A>>,
}
// We implement Clone manually because it can only be derived if A:
// Clone, which we don't want.
impl<A> Clone for ServiceHandle<A>
where
A: Aggregator,
{
fn clone(&self) -> Self |
}
impl<A> ServiceHandle<A>
where
A: Aggregator + 'static,
{
pub fn new() -> (Self, ServiceRequests<A>) {
let (upload_tx, upload_rx) = unbounded_channel::<UploadRequest>();
let (download_tx, download_rx) = unbounded_channel::<DownloadRequest>();
let (aggregate_tx, aggregate_rx) = unbounded_channel::<AggregateRequest<A>>();
let (select_tx, select_rx) = unbounded_channel::<SelectRequest<A>>();
let handle = Self {
upload: upload_tx,
download: download_tx,
aggregate: aggregate_tx,
select: select_tx,
};
let service_requests =
ServiceRequests::new(upload_rx, download_rx, aggregate_rx, select_rx);
(handle, service_requests)
}
pub async fn download(
&self,
credentials: Credentials,
) -> Result<Bytes, ServiceError<DownloadError>> {
let (tx, rx) = oneshot::channel::<Result<Bytes, DownloadError>>();
let request = DownloadRequest::from((credentials, tx));
Self::send_request(request, &self.download)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn upload(
&self,
credentials: Credentials,
data: Bytes,
) -> Result<(), ServiceError<UploadError>> {
let request = UploadRequest::from((credentials, data));
Self::send_request(request, &self.upload)?;
Ok(())
}
pub async fn aggregate(&self) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(AggregateRequest::from(tx), &self.aggregate)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn select(&self, credentials: Credentials) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(SelectRequest::from((credentials, tx)), &self.select)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
fn send_request<P>(payload: P, tx: &UnboundedSender<P>) -> Result<(), ChannelError> {
trace!("send request to the service");
if tx.send(payload).is_err() {
warn!("failed to send request: channel closed");
Err(ChannelError::Request)
} else {
trace!("request sent");
Ok(())
}
}
async fn recv_response<R>(rx: oneshot::Receiver<R>) -> Result<R, ChannelError> {
rx.await.map_err(|_| {
warn!("could not receive response: channel closed");
ChannelError::Response
})
}
}
#[derive(Error, Debug)]
pub enum DownloadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum UploadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum ServiceError<E>
where
E: Error,
{
#[error("failed to send the request or receive the response")]
Handle(#[from] ChannelError),
#[error("request failed: {0}")]
Request(E),
}
#[derive(Error, Debug)]
pub enum ChannelError {
#[error("failed to send request to Service")]
Request,
#[error("failed to receive the response from Service")]
Response,
}
| {
Self {
upload: self.upload.clone(),
download: self.download.clone(),
aggregate: self.aggregate.clone(),
select: self.select.clone(),
}
} | identifier_body |
service.rs | use crate::{
common::client::{ClientId, Credentials, Token},
coordinator,
};
use bytes::Bytes;
use derive_more::From;
use futures::{ready, stream::Stream};
use std::{
collections::HashMap,
error::Error,
future::Future,
pin::Pin,
task::{Context, Poll},
};
use tarpc::context::current as rpc_context;
use thiserror::Error;
use tokio::{
stream::StreamExt,
sync::{
mpsc::{unbounded_channel, UnboundedReceiver, UnboundedSender},
oneshot,
},
};
use tracing_futures::Instrument;
use std::env;
use std::fs::File;
use std::io::prelude::*;
use nix::sys::signal;
use nix::unistd::Pid;
use std::thread;
use std::time::Duration;
/// A future that orchestrates the entire aggregator service.
// TODO: maybe add a HashSet or HashMap of clients who already
// uploaded their weights to prevent a client from uploading weights
// multiple times. Or we could just remove that ID from the
// `allowed_ids` map.
// TODO: maybe add a HashSet for clients that are already
// downloading/uploading, to prevent DoS attacks.
pub struct Service<A>
where
A: Aggregator,
{
/// Clients that the coordinator selected for the current
/// round. They can use their unique token to download the global
/// weights and upload their own local results once they finished
/// training.
allowed_ids: HashMap<ClientId, Token>,
/// The latest global weights as computed by the aggregator.
// NOTE: We could store this directly in the task that handles the
// HTTP requests. I initially though that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, which handles the weights or performs
/// the aggregations.
aggregator: A,
/// A client for the coordinator RPC service.
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
aggregation_future: Option<AggregationFuture<A>>,
model_number: usize,
}
/// This trait defines the methods that an aggregator should
/// implement.
pub trait Aggregator {
type Error: Error + Send + 'static + Sync;
type AggregateFut: Future<Output = Result<Bytes, Self::Error>> + Unpin;
type AddWeightsFut: Future<Output = Result<(), Self::Error>> + Unpin + Send + 'static;
/// Check the validity of the given weights and if they are valid,
/// add them to the set of weights to aggregate.
fn add_weights(&mut self, weights: Bytes) -> Self::AddWeightsFut;
/// Run the aggregator and return the result.
fn aggregate(&mut self) -> Self::AggregateFut;
}
impl<A> Service<A>
where
A: Aggregator,
{
pub fn new(
aggregator: A,
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
) -> Self {
Self {
aggregator,
requests,
rpc_client,
allowed_ids: HashMap::new(),
global_weights: Bytes::new(),
aggregation_future: None,
model_number: 0,
}
}
/// Handle the incoming requests.
fn poll_requests(&mut self, cx: &mut Context) -> Poll<()> {
trace!("polling requests");
loop {
match ready!(Pin::new(&mut self.requests).poll_next(cx)) {
Some(request) => self.handle_request(request),
None => {
trace!("no more request to handle");
return Poll::Ready(());
}
}
}
}
fn handle_download_request(&mut self, request: DownloadRequest) {
debug!("handling download request");
let DownloadRequest {
credentials,
response_tx,
} = request;
if self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false)
{
let _ = response_tx.send(Ok(self.global_weights.clone()));
} else {
warn!("rejecting download request");
let _ = response_tx.send(Err(DownloadError::Unauthorized));
}
}
fn handle_upload_request(&mut self, request: UploadRequest) {
debug!("handling upload request");
let UploadRequest { credentials, data } = request;
let accept_upload = self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false);
if !accept_upload {
warn!("rejecting upload request");
return;
}
let mut rpc_client = self.rpc_client.clone();
let fut = self.aggregator.add_weights(data);
tokio::spawn(
async move {
let result = fut.await;
debug!("sending end training request to the coordinator");
rpc_client
.end_training(rpc_context(), *credentials.id(), result.is_ok())
.await
.map_err(|e| {
warn!(
"failed to send end training request to the coordinator: {}",
e
);
})
}
.instrument(trace_span!("end_training_rpc_request")),
);
}
fn handle_request(&mut self, request: Request<A>) {
match request {
Request::Download(req) => self.handle_download_request(req),
Request::Upload(req) => self.handle_upload_request(req),
Request::Select(req) => self.handle_select_request(req),
Request::Aggregate(req) => self.handle_aggregate_request(req),
}
}
fn handle_aggregate_request(&mut self, request: AggregateRequest<A>) {
info!("handling aggregate request");
let AggregateRequest { response_tx } = request;
self.allowed_ids = HashMap::new();
self.aggregation_future = Some(AggregationFuture {
future: self.aggregator.aggregate(),
response_tx,
});
}
fn | (&mut self, request: SelectRequest<A>) {
info!("handling select request");
let SelectRequest {
credentials,
response_tx,
} = request;
let (id, token) = credentials.into_parts();
self.allowed_ids.insert(id, token);
if response_tx.send(Ok(())).is_err() {
warn!("failed to send reponse: channel closed");
}
}
#[allow(clippy::cognitive_complexity)]
fn poll_aggregation(&mut self, cx: &mut Context) {
// Check if we're waiting for an aggregation, ie whether
// there's a future to poll.
let future = if let Some(future) = self.aggregation_future.take() {
future
} else {
trace!("no aggregation future running: skipping polling");
return;
};
trace!("polling aggregation future");
let AggregationFuture {
mut future,
response_tx,
} = future;
let result = match Pin::new(&mut future).poll(cx) {
Poll::Ready(Ok(weights)) => {
info!("aggregation succeeded, settings global weights");
self.global_weights = weights;
if let Ok(path) = env::var("NEVERMINED_OUTPUTS_PATH") {
let file_name = format!("{}/model_{}.npy", path, self.model_number);
let mut file = File::create(&file_name).unwrap();
info!("Writing model {}", file_name);
file.write_all(&self.global_weights).unwrap();
self.model_number += 1;
}
Ok(())
}
Poll::Ready(Err(e)) => {
error!(error = %e, "aggregation failed");
Err(e)
}
Poll::Pending => {
debug!("aggregation future still running");
self.aggregation_future = Some(AggregationFuture {
future,
response_tx,
});
return;
}
};
if response_tx.send(result).is_err() {
error!("failed to send aggregation response to RPC task: receiver dropped");
}
if self.model_number == 10 {
thread::sleep(Duration::from_millis(10 * 1000));
signal::kill(Pid::this(), signal::Signal::SIGINT).unwrap();
}
}
}
struct AggregationFuture<A>
where
A: Aggregator,
{
future: A::AggregateFut,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
impl<A> Future for Service<A>
where
A: Aggregator + Unpin,
{
type Output = ();
fn poll(self: Pin<&mut Self>, cx: &mut Context) -> Poll<Self::Output> {
trace!("polling Service");
let pin = self.get_mut();
if let Poll::Ready(_) = pin.poll_requests(cx) {
return Poll::Ready(());
}
pin.poll_aggregation(cx);
Poll::Pending
}
}
pub struct ServiceRequests<A>(Pin<Box<dyn Stream<Item = Request<A>> + Send>>)
where
A: Aggregator;
impl<A> Stream for ServiceRequests<A>
where
A: Aggregator,
{
type Item = Request<A>;
fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context) -> Poll<Option<Self::Item>> {
trace!("polling ServiceRequests");
self.0.as_mut().poll_next(cx)
}
}
impl<A> ServiceRequests<A>
where
A: Aggregator + 'static,
{
fn new(
upload: UnboundedReceiver<UploadRequest>,
download: UnboundedReceiver<DownloadRequest>,
aggregate: UnboundedReceiver<AggregateRequest<A>>,
select: UnboundedReceiver<SelectRequest<A>>,
) -> Self {
let stream = download
.map(Request::from)
.merge(upload.map(Request::from))
.merge(aggregate.map(Request::from))
.merge(select.map(Request::from));
Self(Box::pin(stream))
}
}
#[derive(From)]
pub struct UploadRequest {
credentials: Credentials,
data: Bytes,
}
#[derive(From)]
pub struct DownloadRequest {
credentials: Credentials,
response_tx: oneshot::Sender<Result<Bytes, DownloadError>>,
}
#[derive(From)]
pub struct AggregateRequest<A>
where
A: Aggregator,
{
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub struct SelectRequest<A>
where
A: Aggregator,
{
credentials: Credentials,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub enum Request<A>
where
A: Aggregator,
{
Upload(UploadRequest),
Download(DownloadRequest),
Aggregate(AggregateRequest<A>),
Select(SelectRequest<A>),
}
pub struct ServiceHandle<A>
where
A: Aggregator,
{
upload: UnboundedSender<UploadRequest>,
download: UnboundedSender<DownloadRequest>,
aggregate: UnboundedSender<AggregateRequest<A>>,
select: UnboundedSender<SelectRequest<A>>,
}
// We implement Clone manually because it can only be derived if A:
// Clone, which we don't want.
impl<A> Clone for ServiceHandle<A>
where
A: Aggregator,
{
fn clone(&self) -> Self {
Self {
upload: self.upload.clone(),
download: self.download.clone(),
aggregate: self.aggregate.clone(),
select: self.select.clone(),
}
}
}
impl<A> ServiceHandle<A>
where
A: Aggregator + 'static,
{
pub fn new() -> (Self, ServiceRequests<A>) {
let (upload_tx, upload_rx) = unbounded_channel::<UploadRequest>();
let (download_tx, download_rx) = unbounded_channel::<DownloadRequest>();
let (aggregate_tx, aggregate_rx) = unbounded_channel::<AggregateRequest<A>>();
let (select_tx, select_rx) = unbounded_channel::<SelectRequest<A>>();
let handle = Self {
upload: upload_tx,
download: download_tx,
aggregate: aggregate_tx,
select: select_tx,
};
let service_requests =
ServiceRequests::new(upload_rx, download_rx, aggregate_rx, select_rx);
(handle, service_requests)
}
pub async fn download(
&self,
credentials: Credentials,
) -> Result<Bytes, ServiceError<DownloadError>> {
let (tx, rx) = oneshot::channel::<Result<Bytes, DownloadError>>();
let request = DownloadRequest::from((credentials, tx));
Self::send_request(request, &self.download)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn upload(
&self,
credentials: Credentials,
data: Bytes,
) -> Result<(), ServiceError<UploadError>> {
let request = UploadRequest::from((credentials, data));
Self::send_request(request, &self.upload)?;
Ok(())
}
pub async fn aggregate(&self) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(AggregateRequest::from(tx), &self.aggregate)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn select(&self, credentials: Credentials) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(SelectRequest::from((credentials, tx)), &self.select)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
fn send_request<P>(payload: P, tx: &UnboundedSender<P>) -> Result<(), ChannelError> {
trace!("send request to the service");
if tx.send(payload).is_err() {
warn!("failed to send request: channel closed");
Err(ChannelError::Request)
} else {
trace!("request sent");
Ok(())
}
}
async fn recv_response<R>(rx: oneshot::Receiver<R>) -> Result<R, ChannelError> {
rx.await.map_err(|_| {
warn!("could not receive response: channel closed");
ChannelError::Response
})
}
}
#[derive(Error, Debug)]
pub enum DownloadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum UploadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum ServiceError<E>
where
E: Error,
{
#[error("failed to send the request or receive the response")]
Handle(#[from] ChannelError),
#[error("request failed: {0}")]
Request(E),
}
#[derive(Error, Debug)]
pub enum ChannelError {
#[error("failed to send request to Service")]
Request,
#[error("failed to receive the response from Service")]
Response,
}
| handle_select_request | identifier_name |
service.rs | use crate::{
common::client::{ClientId, Credentials, Token},
coordinator,
};
use bytes::Bytes;
use derive_more::From;
use futures::{ready, stream::Stream};
use std::{
collections::HashMap,
error::Error,
future::Future,
pin::Pin,
task::{Context, Poll},
};
use tarpc::context::current as rpc_context;
use thiserror::Error;
use tokio::{
stream::StreamExt,
sync::{
mpsc::{unbounded_channel, UnboundedReceiver, UnboundedSender},
oneshot,
},
};
use tracing_futures::Instrument;
use std::env;
use std::fs::File;
use std::io::prelude::*;
use nix::sys::signal;
use nix::unistd::Pid;
use std::thread;
use std::time::Duration;
/// A future that orchestrates the entire aggregator service.
// TODO: maybe add a HashSet or HashMap of clients who already
// uploaded their weights to prevent a client from uploading weights
// multiple times. Or we could just remove that ID from the
// `allowed_ids` map.
// TODO: maybe add a HashSet for clients that are already
// downloading/uploading, to prevent DoS attacks.
pub struct Service<A>
where
A: Aggregator,
{
/// Clients that the coordinator selected for the current
/// round. They can use their unique token to download the global
/// weights and upload their own local results once they finished
/// training.
allowed_ids: HashMap<ClientId, Token>,
/// The latest global weights as computed by the aggregator.
// NOTE: We could store this directly in the task that handles the
// HTTP requests. I initially though that having it here would
// make it easier to bypass the HTTP layer, which is convenient
// for testing because we can simulate client with just
// AggregatorHandles. But maybe that's just another layer of
// complexity that is not worth it.
global_weights: Bytes,
/// The aggregator itself, which handles the weights or performs
/// the aggregations.
aggregator: A,
/// A client for the coordinator RPC service.
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
aggregation_future: Option<AggregationFuture<A>>,
model_number: usize,
}
/// This trait defines the methods that an aggregator should
/// implement.
pub trait Aggregator {
type Error: Error + Send + 'static + Sync;
type AggregateFut: Future<Output = Result<Bytes, Self::Error>> + Unpin;
type AddWeightsFut: Future<Output = Result<(), Self::Error>> + Unpin + Send + 'static;
/// Check the validity of the given weights and if they are valid,
/// add them to the set of weights to aggregate.
fn add_weights(&mut self, weights: Bytes) -> Self::AddWeightsFut;
/// Run the aggregator and return the result.
fn aggregate(&mut self) -> Self::AggregateFut;
}
impl<A> Service<A>
where
A: Aggregator,
{
pub fn new(
aggregator: A,
rpc_client: coordinator::rpc::Client,
requests: ServiceRequests<A>,
) -> Self {
Self {
aggregator,
requests,
rpc_client,
allowed_ids: HashMap::new(),
global_weights: Bytes::new(),
aggregation_future: None,
model_number: 0,
}
}
/// Handle the incoming requests.
fn poll_requests(&mut self, cx: &mut Context) -> Poll<()> {
trace!("polling requests");
loop {
match ready!(Pin::new(&mut self.requests).poll_next(cx)) {
Some(request) => self.handle_request(request),
None => {
trace!("no more request to handle");
return Poll::Ready(());
}
}
}
}
fn handle_download_request(&mut self, request: DownloadRequest) {
debug!("handling download request");
let DownloadRequest {
credentials,
response_tx,
} = request;
if self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false)
{
let _ = response_tx.send(Ok(self.global_weights.clone()));
} else {
warn!("rejecting download request");
let _ = response_tx.send(Err(DownloadError::Unauthorized));
}
}
fn handle_upload_request(&mut self, request: UploadRequest) {
debug!("handling upload request");
let UploadRequest { credentials, data } = request;
let accept_upload = self
.allowed_ids
.get(credentials.id())
.map(|expected_token| credentials.token() == expected_token)
.unwrap_or(false);
if !accept_upload {
warn!("rejecting upload request");
return;
}
let mut rpc_client = self.rpc_client.clone();
let fut = self.aggregator.add_weights(data);
tokio::spawn(
async move {
let result = fut.await;
debug!("sending end training request to the coordinator");
rpc_client
.end_training(rpc_context(), *credentials.id(), result.is_ok())
.await
.map_err(|e| {
warn!(
"failed to send end training request to the coordinator: {}",
e
);
})
}
.instrument(trace_span!("end_training_rpc_request")),
);
}
fn handle_request(&mut self, request: Request<A>) {
match request {
Request::Download(req) => self.handle_download_request(req),
Request::Upload(req) => self.handle_upload_request(req),
Request::Select(req) => self.handle_select_request(req),
Request::Aggregate(req) => self.handle_aggregate_request(req),
}
}
fn handle_aggregate_request(&mut self, request: AggregateRequest<A>) {
info!("handling aggregate request");
let AggregateRequest { response_tx } = request;
self.allowed_ids = HashMap::new();
self.aggregation_future = Some(AggregationFuture {
future: self.aggregator.aggregate(),
response_tx,
});
}
fn handle_select_request(&mut self, request: SelectRequest<A>) {
info!("handling select request");
let SelectRequest {
credentials,
response_tx,
} = request;
let (id, token) = credentials.into_parts();
self.allowed_ids.insert(id, token);
if response_tx.send(Ok(())).is_err() {
warn!("failed to send reponse: channel closed");
}
}
#[allow(clippy::cognitive_complexity)]
fn poll_aggregation(&mut self, cx: &mut Context) {
// Check if we're waiting for an aggregation, ie whether
// there's a future to poll.
let future = if let Some(future) = self.aggregation_future.take() {
future
} else {
trace!("no aggregation future running: skipping polling");
return;
};
trace!("polling aggregation future");
let AggregationFuture {
mut future,
response_tx,
} = future;
let result = match Pin::new(&mut future).poll(cx) {
Poll::Ready(Ok(weights)) => {
info!("aggregation succeeded, settings global weights");
self.global_weights = weights;
if let Ok(path) = env::var("NEVERMINED_OUTPUTS_PATH") {
let file_name = format!("{}/model_{}.npy", path, self.model_number);
let mut file = File::create(&file_name).unwrap();
info!("Writing model {}", file_name);
file.write_all(&self.global_weights).unwrap();
self.model_number += 1;
}
Ok(())
}
Poll::Ready(Err(e)) => {
error!(error = %e, "aggregation failed");
Err(e)
}
Poll::Pending => {
debug!("aggregation future still running");
self.aggregation_future = Some(AggregationFuture {
future,
response_tx,
});
return;
}
};
if response_tx.send(result).is_err() {
error!("failed to send aggregation response to RPC task: receiver dropped");
}
if self.model_number == 10 {
thread::sleep(Duration::from_millis(10 * 1000));
signal::kill(Pid::this(), signal::Signal::SIGINT).unwrap();
}
}
}
struct AggregationFuture<A>
where
A: Aggregator,
{
future: A::AggregateFut,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
impl<A> Future for Service<A>
where
A: Aggregator + Unpin,
{
type Output = ();
fn poll(self: Pin<&mut Self>, cx: &mut Context) -> Poll<Self::Output> {
trace!("polling Service");
let pin = self.get_mut();
if let Poll::Ready(_) = pin.poll_requests(cx) |
pin.poll_aggregation(cx);
Poll::Pending
}
}
pub struct ServiceRequests<A>(Pin<Box<dyn Stream<Item = Request<A>> + Send>>)
where
A: Aggregator;
impl<A> Stream for ServiceRequests<A>
where
A: Aggregator,
{
type Item = Request<A>;
fn poll_next(mut self: Pin<&mut Self>, cx: &mut Context) -> Poll<Option<Self::Item>> {
trace!("polling ServiceRequests");
self.0.as_mut().poll_next(cx)
}
}
impl<A> ServiceRequests<A>
where
A: Aggregator + 'static,
{
fn new(
upload: UnboundedReceiver<UploadRequest>,
download: UnboundedReceiver<DownloadRequest>,
aggregate: UnboundedReceiver<AggregateRequest<A>>,
select: UnboundedReceiver<SelectRequest<A>>,
) -> Self {
let stream = download
.map(Request::from)
.merge(upload.map(Request::from))
.merge(aggregate.map(Request::from))
.merge(select.map(Request::from));
Self(Box::pin(stream))
}
}
#[derive(From)]
pub struct UploadRequest {
credentials: Credentials,
data: Bytes,
}
#[derive(From)]
pub struct DownloadRequest {
credentials: Credentials,
response_tx: oneshot::Sender<Result<Bytes, DownloadError>>,
}
#[derive(From)]
pub struct AggregateRequest<A>
where
A: Aggregator,
{
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub struct SelectRequest<A>
where
A: Aggregator,
{
credentials: Credentials,
response_tx: oneshot::Sender<Result<(), A::Error>>,
}
#[derive(From)]
pub enum Request<A>
where
A: Aggregator,
{
Upload(UploadRequest),
Download(DownloadRequest),
Aggregate(AggregateRequest<A>),
Select(SelectRequest<A>),
}
pub struct ServiceHandle<A>
where
A: Aggregator,
{
upload: UnboundedSender<UploadRequest>,
download: UnboundedSender<DownloadRequest>,
aggregate: UnboundedSender<AggregateRequest<A>>,
select: UnboundedSender<SelectRequest<A>>,
}
// We implement Clone manually because it can only be derived if A:
// Clone, which we don't want.
impl<A> Clone for ServiceHandle<A>
where
A: Aggregator,
{
fn clone(&self) -> Self {
Self {
upload: self.upload.clone(),
download: self.download.clone(),
aggregate: self.aggregate.clone(),
select: self.select.clone(),
}
}
}
impl<A> ServiceHandle<A>
where
A: Aggregator + 'static,
{
pub fn new() -> (Self, ServiceRequests<A>) {
let (upload_tx, upload_rx) = unbounded_channel::<UploadRequest>();
let (download_tx, download_rx) = unbounded_channel::<DownloadRequest>();
let (aggregate_tx, aggregate_rx) = unbounded_channel::<AggregateRequest<A>>();
let (select_tx, select_rx) = unbounded_channel::<SelectRequest<A>>();
let handle = Self {
upload: upload_tx,
download: download_tx,
aggregate: aggregate_tx,
select: select_tx,
};
let service_requests =
ServiceRequests::new(upload_rx, download_rx, aggregate_rx, select_rx);
(handle, service_requests)
}
pub async fn download(
&self,
credentials: Credentials,
) -> Result<Bytes, ServiceError<DownloadError>> {
let (tx, rx) = oneshot::channel::<Result<Bytes, DownloadError>>();
let request = DownloadRequest::from((credentials, tx));
Self::send_request(request, &self.download)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn upload(
&self,
credentials: Credentials,
data: Bytes,
) -> Result<(), ServiceError<UploadError>> {
let request = UploadRequest::from((credentials, data));
Self::send_request(request, &self.upload)?;
Ok(())
}
pub async fn aggregate(&self) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(AggregateRequest::from(tx), &self.aggregate)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
pub async fn select(&self, credentials: Credentials) -> Result<(), ServiceError<A::Error>> {
let (tx, rx) = oneshot::channel::<Result<(), A::Error>>();
Self::send_request(SelectRequest::from((credentials, tx)), &self.select)?;
Self::recv_response(rx)
.await?
.map_err(ServiceError::Request)
}
fn send_request<P>(payload: P, tx: &UnboundedSender<P>) -> Result<(), ChannelError> {
trace!("send request to the service");
if tx.send(payload).is_err() {
warn!("failed to send request: channel closed");
Err(ChannelError::Request)
} else {
trace!("request sent");
Ok(())
}
}
async fn recv_response<R>(rx: oneshot::Receiver<R>) -> Result<R, ChannelError> {
rx.await.map_err(|_| {
warn!("could not receive response: channel closed");
ChannelError::Response
})
}
}
#[derive(Error, Debug)]
pub enum DownloadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum UploadError {
#[error("the user does not have the proper permissions")]
Unauthorized,
}
#[derive(Error, Debug)]
pub enum ServiceError<E>
where
E: Error,
{
#[error("failed to send the request or receive the response")]
Handle(#[from] ChannelError),
#[error("request failed: {0}")]
Request(E),
}
#[derive(Error, Debug)]
pub enum ChannelError {
#[error("failed to send request to Service")]
Request,
#[error("failed to receive the response from Service")]
Response,
}
| {
return Poll::Ready(());
} | conditional_block |
utils.py | from mpi4py import MPI
import matplotlib
from tmm import coh_tmm
import pandas as pd
import os
from numpy import pi
from scipy.interpolate import interp1d
from joblib import Parallel, delayed
import numpy as np
import glob
import matplotlib.pyplot as plt
import pickle as pkl
import seaborn as sns
from scipy.optimize import minimize
import json
from tqdm import tqdm
DATABASE = './data'
INSULATORS = ['HfO2', 'SiO2', 'SiC', 'Al2O3', 'MgF2', 'TiO2', 'Fe2O3', 'MgF2', 'Si3N4', 'TiN', 'ZnO', 'ZnS', 'ZnSe']
METALS = ['Ag', 'Al', 'Cr', 'Ge', 'Si', 'Ni']
num_workers = 8
def cal_reward(R, T, A, target):
'''
Calculate reward based on given spectrums.
We calculate the reward using averaged (1-mse).
Args:
R, T, A: numpy array. Reflection, transmission, and
absorption spectrums, respectively.
target: dict. {'R':np.array, 'T':np.array, 'A':np.array}
Returns:
reward: float. Reward for the spectrum.
'''
reward = 0
for k, v in target.items():
if k == 'R':
res = R
elif k == 'T':
res = T
else:
res = A
reward += 1 - np.abs(res.squeeze() - v).mean()
reward /= len(target)
return reward
class Memory:
def __init__(self):
self.actions = []
self.states = []
self.logprobs = []
self.rewards = []
self.is_terminals = []
def clear_memory(self):
del self.actions[:]
del self.states[:]
del self.logprobs[:]
del self.rewards[:]
del self.is_terminals[:]
def batch_spectrum(env, names_list, thickness_list):
def spectrum(args):
'''
Inputs:
1. names: list of lists, each list correspond to the structures
2. thickness: list of lists
'''
names, thickness = args
R, T, A = env.spectrum(names, thickness, 0, False)
return R, T, A
res = Parallel(n_jobs=num_workers)(delayed(spectrum)(args)
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categories, thicknesses):
'''
Merges consecutive layers with the same material types.
'''
thicknesses = thicknesses[1:-1]
c_output = [categories[0]]
t_output = [thicknesses[0]]
for i, (c, d) in enumerate(zip(categories[1:], thicknesses[1:])):
if c == c_output[-1]:
t_output[-1] += d
continue
else:
c_output.append(c)
t_output.append(d)
t_output.insert(0, np.inf)
t_output.insert(len(t_output), np.inf)
return c_output, t_output
def get_structure(categories, values, materials, ds, continuous=False,
max_value=400):
'''
Given categories and values, return the strucure in the form
(name (str), thickness (nm))
'''
def threshold(value):
'''
'''
names = [materials[item] for item in categories]
if not continuous:
thickness = [np.inf] + [ds[item] for item in values] + [np.inf]
else:
thickness = []
for category, value in zip(categories, values):
name = materials[category]
if name == 'Ag':
thickness.append(
min(max(15, int(value * max_value//2)), max_value))
elif name in METALS:
thickness.append(
min(max(5, int(value * max_value//2)), max_value))
elif name in INSULATORS:
thickness.append(
min(max(1, int(value * max_value//2)), max_value))
else:
raise ValueError('Material not known')
# thickness = [np.inf] + [min(max(5, int(item * 2e2)), 200) for i,
# item in enumerate(values)] + [np.inf]
thickness = [np.inf] + thickness + [np.inf]
return names, thickness
class DesignTracker():
def __init__(self, epochs, **kwargs):
"""
This class tracks the best designs discovered.
"""
if epochs == -1:
self.layer_ls = []
self.thick_ls = []
self.max_ret_ls = []
self.layer_ls = [0] * epochs
self.thick_ls = [0] * epochs
self.max_ret_ls = [0] * epochs
self.kwargs = kwargs
self.current_e = 0
def store(self, layers, thicknesses, ret, e, append_mode=False):
if append_mode:
self.layer_ls.append(layers)
self.thick_ls.append(thicknesses)
self.max_ret_ls.append(ret)
else:
if ret >= self.max_ret_ls[e]:
self.layer_ls[e] = layers
self.thick_ls[e] = thicknesses
self.max_ret_ls[e] = ret
def save_state(self):
# save buffer from all processes
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
filename = os.path.join(self.kwargs['output_dir'], 'design_tracker_{}.pkl'.format(rank))
pkl.dump(self, open(filename, 'wb'))
def print_progress(self):
progress = list(zip(self.layer_ls, self.thick_ls, self.max_ret_ls))
read_progress = []
for i in range(len(progress)):
if progress[i] == (0,0,0):
break
read_progress.append(['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]) + ', Merit {:.3f}'.format(progress[i][2])])
return read_progress
def print_progress(progress):
|
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_mats = mats + [substrate] if substrate not in ['Glass', 'Air'] else mats
self.wavelength = wavelength
self.nk_dict = self.load_materials()
self.substrate = substrate
self.substrate_thick = substrate_thick
def load_materials(self):
'''
Load material nk and return corresponding interpolators.
Return:
nk_dict: dict, key -- material name, value: n, k in the
self.wavelength range
'''
nk_dict = {}
for mat in self.all_mats:
nk = pd.read_csv(os.path.join(DATABASE, mat + '.csv'))
nk.dropna(inplace=True)
wl = nk['wl'].to_numpy()
index = (nk['n'] + nk['k'] * 1.j).to_numpy()
mat_nk_data = np.hstack((wl[:, np.newaxis], index[:, np.newaxis]))
mat_nk_fn = interp1d(
mat_nk_data[:, 0].real, mat_nk_data[:, 1], kind='quadratic')
nk_dict[mat] = mat_nk_fn(self.wavelength)
return nk_dict
def spectrum(self, materials, thickness, theta=0, plot=False, title=False):
'''
Input:
materials: list
thickness: list
theta: degree, the incidence angle
Return:
s: array, spectrum
'''
degree = pi/180
if self.substrate != 'Air':
thickness.insert(-1, self.substrate_thick) # substrate thickness
R, T, A = [], [], []
for i, lambda_vac in enumerate(self.wavelength * 1e3):
# we assume the last layer is glass
if self.substrate == 'Glass':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1.45, 1]
elif self.substrate == 'Air':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1]
else:
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict[self.substrate][i], 1]
# n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict['Cr'][i]]
# mport pdb; pdb.set_trace()
res = coh_tmm('s', n_list, thickness, theta * degree, lambda_vac)
R.append(res['R'])
T.append(res['T'])
R, T = np.array(R), np.array(T)
A = 1 - R - T
if plot:
self.plot_spectrum(R, T, A)
if title:
thick = thickness[1:-1]
title = ' | '.join(['{}nm {}'.format(d, m)
for d, m in zip(thick, materials)])
if self.substrate is not 'Air':
title = 'Air | ' + title + ' | {}nm {} '.format(self.substrate_thick, self.substrate) + '| Air'
else:
title = 'Air | ' + title + ' | Air'
plt.title(title, **{'size': '10'})
return R, T, A
def plot_spectrum(self, R, T, A):
plt.plot(self.wavelength * 1000, R, self.wavelength *
1000, T, self.wavelength * 1000, A, linewidth=3)
plt.ylabel('R/T/A')
plt.xlabel('Wavelength (nm)')
plt.legend(['R: Average = {:.2f}%'.
format(np.mean(R)*100),
'T: Average = {:.2f}%'.
format(np.mean(T)*100),
'A: Average = {:.2f}%'.
format(np.mean(A)*100)])
plt.grid('on', linestyle='--')
plt.ylim([0, 1])
# Plotting utils
def visualize_progress(file, x, ax=None, color='b', alpha=1):
df = pd.read_csv(file, sep="\t")
width = 0.5
# x = 'Time'
if ax is None:
fig, ax = plt.subplots(2,1)
sns.lineplot(x=x, y='MaxEpRet', data=df, ax=ax[0], color=color, alpha=alpha)
# ax[0].legend(['Max {}'.format(np.max(df['MaxEpRet']))])
sns.lineplot(x=x, y='AverageEpRet', data=df,
ax=ax[1], color=color, alpha=alpha)
plt.fill_between(df[x],
df['AverageEpRet']-width/2*df['StdEpRet'],
df['AverageEpRet']+width/2*df['StdEpRet'],
alpha=0.3, color=color)
return df
def combine_tracker(folder):
'''
Merge all buffers
'''
trackers = []
if 'design_tracker_merged.pkl' in os.listdir(folder):
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
combined_tracker = pkl.load(open(tracker_file, 'rb'))
return combined_tracker
for file in os.listdir(folder):
if file.startswith('design_tracker_'):
tracker_file = os.path.join(folder, file)
trackers.append(pkl.load(open(tracker_file, 'rb')))
combined_tracker = DesignTracker(len(trackers[0].layer_ls))
max_idx = np.argmax(np.array([tracker.max_ret_ls for tracker in trackers]), axis=0)
for e in range(len(trackers[0].layer_ls)):
combined_tracker.layer_ls[e] = trackers[max_idx[e]].layer_ls[e]
combined_tracker.thick_ls[e] = trackers[max_idx[e]].thick_ls[e]
combined_tracker.max_ret_ls[e] = trackers[max_idx[e]].max_ret_ls[e]
if combined_tracker.layer_ls[-1] != 0:
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
pkl.dump(combined_tracker, open(os.path.join(folder, tracker_file), 'wb'))
return combined_tracker
def summarize_res(exp_ls, seed_ls, color, alpha, x='Epoch'):
root = '../spinningup/data/'
progress_ls = []
max_ret_ls = []
params = {'size':14}
matplotlib.rc('font', **params)
fig, ax = plt.subplots(2,1, figsize=(10,8))
for a, c, exp, seed in zip(alpha, color, exp_ls, seed_ls):
folder = os.path.join(root, exp, exp+'_s{}'.format(seed))
progress_file = os.path.join(folder, 'progress.txt')
df = visualize_progress(progress_file, x=x, ax=ax, color=c, alpha=a)
tracker = combine_tracker(folder)
progress = tracker.print_progress()
print('{}, Best discovered so far {}'.format(exp, progress[np.argmax(tracker.max_ret_ls)]))
progress_ls.append(progress)
max_ret_ls.append('Max merit {:.3f}'.format(np.max(df['MaxEpRet'])))
ax[0].legend(max_ret_ls)
ax[1].legend(exp_ls)
plt.show()
return progress_ls
def load_exp_res(folder):
subfolders = [item for item in glob.glob(folder+'/*')]
def read_hyper(file_name, rep=10):
with open(os.path.join(file_name, 'config.json')) as f:
hypers = json.load(f)
hypers_dict = {}
for k, v in hypers.items():
if k.startswith('logger'):
continue
elif isinstance(v, dict):
for kk, vv in v.items():
if isinstance(vv, list):
hypers_dict[str(k)+'_'+str(kk)] = [vv[0]]*rep
else:
hypers_dict[str(k)+'_'+str(kk)] = [vv]*rep
else:
hypers_dict[k] = [v] * rep
hyper_df = pd.DataFrame(hypers_dict)
return hyper_df
first=True # first pandas file to load
for subfolder in tqdm(subfolders):
runs = glob.glob(subfolder+'/*')
num_epochs = len(pd.read_csv(os.path.join(runs[0], 'progress.txt'),sep='\t'))
for run in runs:
tracker = combine_tracker(run)
progress = tracker.print_progress()
best_design = progress[np.argmax(tracker.max_ret_ls)]
if first:
df = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df))
df = pd.concat([df, hyper_df, best_designs_df], axis=1)
first = False
else:
df_ = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df_))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df_))
df_ = pd.concat([df_, hyper_df, best_designs_df], axis=1)
df = pd.concat([df, df_], axis=0)
return df
def finetune(simulator, m0, x0, target, display=False, bounds=None):
'''
Finetune the structure using quasi-Newton's method.
Args:
m0: materials list given by the upstream RL
x0: thicknesses given by the upstream RL
display: if true, then plot the spectrum before and after the finetuning.
Returns:
x_opt: finetuned thickness list
'''
def objective_func(x):
R, T, A = simulator.spectrum(m0, [np.inf]+list(x)+[np.inf])
return 1-cal_reward(R, T, A, target)
if bounds is None:
bounds = [(15, 200)] * len(x0)
res = minimize(objective_func, x0, bounds=bounds, options={'disp':True})
x_opt = [int(item) for item in res.x]
if display:
plt.figure()
simulator.spectrum(m0, [np.inf]+x0+[np.inf], title=True, plot=True)
plt.figure()
simulator.spectrum(m0, [np.inf]+x_opt+[np.inf], title=True, plot=True)
return x_opt, res
| for i in range(len(progress)):
print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]]
return progress | identifier_body |
utils.py | from mpi4py import MPI
import matplotlib
from tmm import coh_tmm
import pandas as pd
import os
from numpy import pi
from scipy.interpolate import interp1d
from joblib import Parallel, delayed
import numpy as np
import glob
import matplotlib.pyplot as plt
import pickle as pkl
import seaborn as sns
from scipy.optimize import minimize
import json
from tqdm import tqdm
DATABASE = './data'
INSULATORS = ['HfO2', 'SiO2', 'SiC', 'Al2O3', 'MgF2', 'TiO2', 'Fe2O3', 'MgF2', 'Si3N4', 'TiN', 'ZnO', 'ZnS', 'ZnSe']
METALS = ['Ag', 'Al', 'Cr', 'Ge', 'Si', 'Ni']
num_workers = 8
def cal_reward(R, T, A, target):
'''
Calculate reward based on given spectrums.
We calculate the reward using averaged (1-mse).
Args:
R, T, A: numpy array. Reflection, transmission, and
absorption spectrums, respectively.
target: dict. {'R':np.array, 'T':np.array, 'A':np.array}
Returns:
reward: float. Reward for the spectrum.
'''
reward = 0
for k, v in target.items():
if k == 'R':
res = R
elif k == 'T':
res = T
else:
res = A
reward += 1 - np.abs(res.squeeze() - v).mean()
reward /= len(target)
return reward
class Memory:
def __init__(self):
self.actions = []
self.states = []
self.logprobs = []
self.rewards = []
self.is_terminals = []
def clear_memory(self):
del self.actions[:]
del self.states[:]
del self.logprobs[:]
del self.rewards[:]
del self.is_terminals[:]
def batch_spectrum(env, names_list, thickness_list):
def spectrum(args):
'''
Inputs:
1. names: list of lists, each list correspond to the structures
2. thickness: list of lists
'''
names, thickness = args
R, T, A = env.spectrum(names, thickness, 0, False)
return R, T, A |
res = Parallel(n_jobs=num_workers)(delayed(spectrum)(args)
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categories, thicknesses):
'''
Merges consecutive layers with the same material types.
'''
thicknesses = thicknesses[1:-1]
c_output = [categories[0]]
t_output = [thicknesses[0]]
for i, (c, d) in enumerate(zip(categories[1:], thicknesses[1:])):
if c == c_output[-1]:
t_output[-1] += d
continue
else:
c_output.append(c)
t_output.append(d)
t_output.insert(0, np.inf)
t_output.insert(len(t_output), np.inf)
return c_output, t_output
def get_structure(categories, values, materials, ds, continuous=False,
max_value=400):
'''
Given categories and values, return the strucure in the form
(name (str), thickness (nm))
'''
def threshold(value):
'''
'''
names = [materials[item] for item in categories]
if not continuous:
thickness = [np.inf] + [ds[item] for item in values] + [np.inf]
else:
thickness = []
for category, value in zip(categories, values):
name = materials[category]
if name == 'Ag':
thickness.append(
min(max(15, int(value * max_value//2)), max_value))
elif name in METALS:
thickness.append(
min(max(5, int(value * max_value//2)), max_value))
elif name in INSULATORS:
thickness.append(
min(max(1, int(value * max_value//2)), max_value))
else:
raise ValueError('Material not known')
# thickness = [np.inf] + [min(max(5, int(item * 2e2)), 200) for i,
# item in enumerate(values)] + [np.inf]
thickness = [np.inf] + thickness + [np.inf]
return names, thickness
class DesignTracker():
def __init__(self, epochs, **kwargs):
"""
This class tracks the best designs discovered.
"""
if epochs == -1:
self.layer_ls = []
self.thick_ls = []
self.max_ret_ls = []
self.layer_ls = [0] * epochs
self.thick_ls = [0] * epochs
self.max_ret_ls = [0] * epochs
self.kwargs = kwargs
self.current_e = 0
def store(self, layers, thicknesses, ret, e, append_mode=False):
if append_mode:
self.layer_ls.append(layers)
self.thick_ls.append(thicknesses)
self.max_ret_ls.append(ret)
else:
if ret >= self.max_ret_ls[e]:
self.layer_ls[e] = layers
self.thick_ls[e] = thicknesses
self.max_ret_ls[e] = ret
def save_state(self):
# save buffer from all processes
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
filename = os.path.join(self.kwargs['output_dir'], 'design_tracker_{}.pkl'.format(rank))
pkl.dump(self, open(filename, 'wb'))
def print_progress(self):
progress = list(zip(self.layer_ls, self.thick_ls, self.max_ret_ls))
read_progress = []
for i in range(len(progress)):
if progress[i] == (0,0,0):
break
read_progress.append(['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]) + ', Merit {:.3f}'.format(progress[i][2])])
return read_progress
def print_progress(progress):
for i in range(len(progress)):
print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]]
return progress
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_mats = mats + [substrate] if substrate not in ['Glass', 'Air'] else mats
self.wavelength = wavelength
self.nk_dict = self.load_materials()
self.substrate = substrate
self.substrate_thick = substrate_thick
def load_materials(self):
'''
Load material nk and return corresponding interpolators.
Return:
nk_dict: dict, key -- material name, value: n, k in the
self.wavelength range
'''
nk_dict = {}
for mat in self.all_mats:
nk = pd.read_csv(os.path.join(DATABASE, mat + '.csv'))
nk.dropna(inplace=True)
wl = nk['wl'].to_numpy()
index = (nk['n'] + nk['k'] * 1.j).to_numpy()
mat_nk_data = np.hstack((wl[:, np.newaxis], index[:, np.newaxis]))
mat_nk_fn = interp1d(
mat_nk_data[:, 0].real, mat_nk_data[:, 1], kind='quadratic')
nk_dict[mat] = mat_nk_fn(self.wavelength)
return nk_dict
def spectrum(self, materials, thickness, theta=0, plot=False, title=False):
'''
Input:
materials: list
thickness: list
theta: degree, the incidence angle
Return:
s: array, spectrum
'''
degree = pi/180
if self.substrate != 'Air':
thickness.insert(-1, self.substrate_thick) # substrate thickness
R, T, A = [], [], []
for i, lambda_vac in enumerate(self.wavelength * 1e3):
# we assume the last layer is glass
if self.substrate == 'Glass':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1.45, 1]
elif self.substrate == 'Air':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1]
else:
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict[self.substrate][i], 1]
# n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict['Cr'][i]]
# mport pdb; pdb.set_trace()
res = coh_tmm('s', n_list, thickness, theta * degree, lambda_vac)
R.append(res['R'])
T.append(res['T'])
R, T = np.array(R), np.array(T)
A = 1 - R - T
if plot:
self.plot_spectrum(R, T, A)
if title:
thick = thickness[1:-1]
title = ' | '.join(['{}nm {}'.format(d, m)
for d, m in zip(thick, materials)])
if self.substrate is not 'Air':
title = 'Air | ' + title + ' | {}nm {} '.format(self.substrate_thick, self.substrate) + '| Air'
else:
title = 'Air | ' + title + ' | Air'
plt.title(title, **{'size': '10'})
return R, T, A
def plot_spectrum(self, R, T, A):
plt.plot(self.wavelength * 1000, R, self.wavelength *
1000, T, self.wavelength * 1000, A, linewidth=3)
plt.ylabel('R/T/A')
plt.xlabel('Wavelength (nm)')
plt.legend(['R: Average = {:.2f}%'.
format(np.mean(R)*100),
'T: Average = {:.2f}%'.
format(np.mean(T)*100),
'A: Average = {:.2f}%'.
format(np.mean(A)*100)])
plt.grid('on', linestyle='--')
plt.ylim([0, 1])
# Plotting utils
def visualize_progress(file, x, ax=None, color='b', alpha=1):
df = pd.read_csv(file, sep="\t")
width = 0.5
# x = 'Time'
if ax is None:
fig, ax = plt.subplots(2,1)
sns.lineplot(x=x, y='MaxEpRet', data=df, ax=ax[0], color=color, alpha=alpha)
# ax[0].legend(['Max {}'.format(np.max(df['MaxEpRet']))])
sns.lineplot(x=x, y='AverageEpRet', data=df,
ax=ax[1], color=color, alpha=alpha)
plt.fill_between(df[x],
df['AverageEpRet']-width/2*df['StdEpRet'],
df['AverageEpRet']+width/2*df['StdEpRet'],
alpha=0.3, color=color)
return df
def combine_tracker(folder):
'''
Merge all buffers
'''
trackers = []
if 'design_tracker_merged.pkl' in os.listdir(folder):
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
combined_tracker = pkl.load(open(tracker_file, 'rb'))
return combined_tracker
for file in os.listdir(folder):
if file.startswith('design_tracker_'):
tracker_file = os.path.join(folder, file)
trackers.append(pkl.load(open(tracker_file, 'rb')))
combined_tracker = DesignTracker(len(trackers[0].layer_ls))
max_idx = np.argmax(np.array([tracker.max_ret_ls for tracker in trackers]), axis=0)
for e in range(len(trackers[0].layer_ls)):
combined_tracker.layer_ls[e] = trackers[max_idx[e]].layer_ls[e]
combined_tracker.thick_ls[e] = trackers[max_idx[e]].thick_ls[e]
combined_tracker.max_ret_ls[e] = trackers[max_idx[e]].max_ret_ls[e]
if combined_tracker.layer_ls[-1] != 0:
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
pkl.dump(combined_tracker, open(os.path.join(folder, tracker_file), 'wb'))
return combined_tracker
def summarize_res(exp_ls, seed_ls, color, alpha, x='Epoch'):
root = '../spinningup/data/'
progress_ls = []
max_ret_ls = []
params = {'size':14}
matplotlib.rc('font', **params)
fig, ax = plt.subplots(2,1, figsize=(10,8))
for a, c, exp, seed in zip(alpha, color, exp_ls, seed_ls):
folder = os.path.join(root, exp, exp+'_s{}'.format(seed))
progress_file = os.path.join(folder, 'progress.txt')
df = visualize_progress(progress_file, x=x, ax=ax, color=c, alpha=a)
tracker = combine_tracker(folder)
progress = tracker.print_progress()
print('{}, Best discovered so far {}'.format(exp, progress[np.argmax(tracker.max_ret_ls)]))
progress_ls.append(progress)
max_ret_ls.append('Max merit {:.3f}'.format(np.max(df['MaxEpRet'])))
ax[0].legend(max_ret_ls)
ax[1].legend(exp_ls)
plt.show()
return progress_ls
def load_exp_res(folder):
subfolders = [item for item in glob.glob(folder+'/*')]
def read_hyper(file_name, rep=10):
with open(os.path.join(file_name, 'config.json')) as f:
hypers = json.load(f)
hypers_dict = {}
for k, v in hypers.items():
if k.startswith('logger'):
continue
elif isinstance(v, dict):
for kk, vv in v.items():
if isinstance(vv, list):
hypers_dict[str(k)+'_'+str(kk)] = [vv[0]]*rep
else:
hypers_dict[str(k)+'_'+str(kk)] = [vv]*rep
else:
hypers_dict[k] = [v] * rep
hyper_df = pd.DataFrame(hypers_dict)
return hyper_df
first=True # first pandas file to load
for subfolder in tqdm(subfolders):
runs = glob.glob(subfolder+'/*')
num_epochs = len(pd.read_csv(os.path.join(runs[0], 'progress.txt'),sep='\t'))
for run in runs:
tracker = combine_tracker(run)
progress = tracker.print_progress()
best_design = progress[np.argmax(tracker.max_ret_ls)]
if first:
df = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df))
df = pd.concat([df, hyper_df, best_designs_df], axis=1)
first = False
else:
df_ = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df_))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df_))
df_ = pd.concat([df_, hyper_df, best_designs_df], axis=1)
df = pd.concat([df, df_], axis=0)
return df
def finetune(simulator, m0, x0, target, display=False, bounds=None):
'''
Finetune the structure using quasi-Newton's method.
Args:
m0: materials list given by the upstream RL
x0: thicknesses given by the upstream RL
display: if true, then plot the spectrum before and after the finetuning.
Returns:
x_opt: finetuned thickness list
'''
def objective_func(x):
R, T, A = simulator.spectrum(m0, [np.inf]+list(x)+[np.inf])
return 1-cal_reward(R, T, A, target)
if bounds is None:
bounds = [(15, 200)] * len(x0)
res = minimize(objective_func, x0, bounds=bounds, options={'disp':True})
x_opt = [int(item) for item in res.x]
if display:
plt.figure()
simulator.spectrum(m0, [np.inf]+x0+[np.inf], title=True, plot=True)
plt.figure()
simulator.spectrum(m0, [np.inf]+x_opt+[np.inf], title=True, plot=True)
return x_opt, res | random_line_split | |
utils.py | from mpi4py import MPI
import matplotlib
from tmm import coh_tmm
import pandas as pd
import os
from numpy import pi
from scipy.interpolate import interp1d
from joblib import Parallel, delayed
import numpy as np
import glob
import matplotlib.pyplot as plt
import pickle as pkl
import seaborn as sns
from scipy.optimize import minimize
import json
from tqdm import tqdm
DATABASE = './data'
INSULATORS = ['HfO2', 'SiO2', 'SiC', 'Al2O3', 'MgF2', 'TiO2', 'Fe2O3', 'MgF2', 'Si3N4', 'TiN', 'ZnO', 'ZnS', 'ZnSe']
METALS = ['Ag', 'Al', 'Cr', 'Ge', 'Si', 'Ni']
num_workers = 8
def cal_reward(R, T, A, target):
'''
Calculate reward based on given spectrums.
We calculate the reward using averaged (1-mse).
Args:
R, T, A: numpy array. Reflection, transmission, and
absorption spectrums, respectively.
target: dict. {'R':np.array, 'T':np.array, 'A':np.array}
Returns:
reward: float. Reward for the spectrum.
'''
reward = 0
for k, v in target.items():
if k == 'R':
res = R
elif k == 'T':
res = T
else:
res = A
reward += 1 - np.abs(res.squeeze() - v).mean()
reward /= len(target)
return reward
class Memory:
def __init__(self):
self.actions = []
self.states = []
self.logprobs = []
self.rewards = []
self.is_terminals = []
def clear_memory(self):
del self.actions[:]
del self.states[:]
del self.logprobs[:]
del self.rewards[:]
del self.is_terminals[:]
def batch_spectrum(env, names_list, thickness_list):
def spectrum(args):
'''
Inputs:
1. names: list of lists, each list correspond to the structures
2. thickness: list of lists
'''
names, thickness = args
R, T, A = env.spectrum(names, thickness, 0, False)
return R, T, A
res = Parallel(n_jobs=num_workers)(delayed(spectrum)(args)
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def merge_layers(categories, thicknesses):
'''
Merges consecutive layers with the same material types.
'''
thicknesses = thicknesses[1:-1]
c_output = [categories[0]]
t_output = [thicknesses[0]]
for i, (c, d) in enumerate(zip(categories[1:], thicknesses[1:])):
if c == c_output[-1]:
t_output[-1] += d
continue
else:
c_output.append(c)
t_output.append(d)
t_output.insert(0, np.inf)
t_output.insert(len(t_output), np.inf)
return c_output, t_output
def get_structure(categories, values, materials, ds, continuous=False,
max_value=400):
'''
Given categories and values, return the strucure in the form
(name (str), thickness (nm))
'''
def threshold(value):
'''
'''
names = [materials[item] for item in categories]
if not continuous:
thickness = [np.inf] + [ds[item] for item in values] + [np.inf]
else:
thickness = []
for category, value in zip(categories, values):
name = materials[category]
if name == 'Ag':
thickness.append(
min(max(15, int(value * max_value//2)), max_value))
elif name in METALS:
thickness.append(
min(max(5, int(value * max_value//2)), max_value))
elif name in INSULATORS:
thickness.append(
min(max(1, int(value * max_value//2)), max_value))
else:
raise ValueError('Material not known')
# thickness = [np.inf] + [min(max(5, int(item * 2e2)), 200) for i,
# item in enumerate(values)] + [np.inf]
thickness = [np.inf] + thickness + [np.inf]
return names, thickness
class DesignTracker():
def __init__(self, epochs, **kwargs):
"""
This class tracks the best designs discovered.
"""
if epochs == -1:
self.layer_ls = []
self.thick_ls = []
self.max_ret_ls = []
self.layer_ls = [0] * epochs
self.thick_ls = [0] * epochs
self.max_ret_ls = [0] * epochs
self.kwargs = kwargs
self.current_e = 0
def store(self, layers, thicknesses, ret, e, append_mode=False):
if append_mode:
self.layer_ls.append(layers)
self.thick_ls.append(thicknesses)
self.max_ret_ls.append(ret)
else:
if ret >= self.max_ret_ls[e]:
self.layer_ls[e] = layers
self.thick_ls[e] = thicknesses
self.max_ret_ls[e] = ret
def save_state(self):
# save buffer from all processes
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
filename = os.path.join(self.kwargs['output_dir'], 'design_tracker_{}.pkl'.format(rank))
pkl.dump(self, open(filename, 'wb'))
def print_progress(self):
progress = list(zip(self.layer_ls, self.thick_ls, self.max_ret_ls))
read_progress = []
for i in range(len(progress)):
if progress[i] == (0,0,0):
break
read_progress.append(['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]) + ', Merit {:.3f}'.format(progress[i][2])])
return read_progress
def print_progress(progress):
for i in range(len(progress)):
|
return progress
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_mats = mats + [substrate] if substrate not in ['Glass', 'Air'] else mats
self.wavelength = wavelength
self.nk_dict = self.load_materials()
self.substrate = substrate
self.substrate_thick = substrate_thick
def load_materials(self):
'''
Load material nk and return corresponding interpolators.
Return:
nk_dict: dict, key -- material name, value: n, k in the
self.wavelength range
'''
nk_dict = {}
for mat in self.all_mats:
nk = pd.read_csv(os.path.join(DATABASE, mat + '.csv'))
nk.dropna(inplace=True)
wl = nk['wl'].to_numpy()
index = (nk['n'] + nk['k'] * 1.j).to_numpy()
mat_nk_data = np.hstack((wl[:, np.newaxis], index[:, np.newaxis]))
mat_nk_fn = interp1d(
mat_nk_data[:, 0].real, mat_nk_data[:, 1], kind='quadratic')
nk_dict[mat] = mat_nk_fn(self.wavelength)
return nk_dict
def spectrum(self, materials, thickness, theta=0, plot=False, title=False):
'''
Input:
materials: list
thickness: list
theta: degree, the incidence angle
Return:
s: array, spectrum
'''
degree = pi/180
if self.substrate != 'Air':
thickness.insert(-1, self.substrate_thick) # substrate thickness
R, T, A = [], [], []
for i, lambda_vac in enumerate(self.wavelength * 1e3):
# we assume the last layer is glass
if self.substrate == 'Glass':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1.45, 1]
elif self.substrate == 'Air':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1]
else:
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict[self.substrate][i], 1]
# n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict['Cr'][i]]
# mport pdb; pdb.set_trace()
res = coh_tmm('s', n_list, thickness, theta * degree, lambda_vac)
R.append(res['R'])
T.append(res['T'])
R, T = np.array(R), np.array(T)
A = 1 - R - T
if plot:
self.plot_spectrum(R, T, A)
if title:
thick = thickness[1:-1]
title = ' | '.join(['{}nm {}'.format(d, m)
for d, m in zip(thick, materials)])
if self.substrate is not 'Air':
title = 'Air | ' + title + ' | {}nm {} '.format(self.substrate_thick, self.substrate) + '| Air'
else:
title = 'Air | ' + title + ' | Air'
plt.title(title, **{'size': '10'})
return R, T, A
def plot_spectrum(self, R, T, A):
plt.plot(self.wavelength * 1000, R, self.wavelength *
1000, T, self.wavelength * 1000, A, linewidth=3)
plt.ylabel('R/T/A')
plt.xlabel('Wavelength (nm)')
plt.legend(['R: Average = {:.2f}%'.
format(np.mean(R)*100),
'T: Average = {:.2f}%'.
format(np.mean(T)*100),
'A: Average = {:.2f}%'.
format(np.mean(A)*100)])
plt.grid('on', linestyle='--')
plt.ylim([0, 1])
# Plotting utils
def visualize_progress(file, x, ax=None, color='b', alpha=1):
df = pd.read_csv(file, sep="\t")
width = 0.5
# x = 'Time'
if ax is None:
fig, ax = plt.subplots(2,1)
sns.lineplot(x=x, y='MaxEpRet', data=df, ax=ax[0], color=color, alpha=alpha)
# ax[0].legend(['Max {}'.format(np.max(df['MaxEpRet']))])
sns.lineplot(x=x, y='AverageEpRet', data=df,
ax=ax[1], color=color, alpha=alpha)
plt.fill_between(df[x],
df['AverageEpRet']-width/2*df['StdEpRet'],
df['AverageEpRet']+width/2*df['StdEpRet'],
alpha=0.3, color=color)
return df
def combine_tracker(folder):
'''
Merge all buffers
'''
trackers = []
if 'design_tracker_merged.pkl' in os.listdir(folder):
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
combined_tracker = pkl.load(open(tracker_file, 'rb'))
return combined_tracker
for file in os.listdir(folder):
if file.startswith('design_tracker_'):
tracker_file = os.path.join(folder, file)
trackers.append(pkl.load(open(tracker_file, 'rb')))
combined_tracker = DesignTracker(len(trackers[0].layer_ls))
max_idx = np.argmax(np.array([tracker.max_ret_ls for tracker in trackers]), axis=0)
for e in range(len(trackers[0].layer_ls)):
combined_tracker.layer_ls[e] = trackers[max_idx[e]].layer_ls[e]
combined_tracker.thick_ls[e] = trackers[max_idx[e]].thick_ls[e]
combined_tracker.max_ret_ls[e] = trackers[max_idx[e]].max_ret_ls[e]
if combined_tracker.layer_ls[-1] != 0:
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
pkl.dump(combined_tracker, open(os.path.join(folder, tracker_file), 'wb'))
return combined_tracker
def summarize_res(exp_ls, seed_ls, color, alpha, x='Epoch'):
root = '../spinningup/data/'
progress_ls = []
max_ret_ls = []
params = {'size':14}
matplotlib.rc('font', **params)
fig, ax = plt.subplots(2,1, figsize=(10,8))
for a, c, exp, seed in zip(alpha, color, exp_ls, seed_ls):
folder = os.path.join(root, exp, exp+'_s{}'.format(seed))
progress_file = os.path.join(folder, 'progress.txt')
df = visualize_progress(progress_file, x=x, ax=ax, color=c, alpha=a)
tracker = combine_tracker(folder)
progress = tracker.print_progress()
print('{}, Best discovered so far {}'.format(exp, progress[np.argmax(tracker.max_ret_ls)]))
progress_ls.append(progress)
max_ret_ls.append('Max merit {:.3f}'.format(np.max(df['MaxEpRet'])))
ax[0].legend(max_ret_ls)
ax[1].legend(exp_ls)
plt.show()
return progress_ls
def load_exp_res(folder):
subfolders = [item for item in glob.glob(folder+'/*')]
def read_hyper(file_name, rep=10):
with open(os.path.join(file_name, 'config.json')) as f:
hypers = json.load(f)
hypers_dict = {}
for k, v in hypers.items():
if k.startswith('logger'):
continue
elif isinstance(v, dict):
for kk, vv in v.items():
if isinstance(vv, list):
hypers_dict[str(k)+'_'+str(kk)] = [vv[0]]*rep
else:
hypers_dict[str(k)+'_'+str(kk)] = [vv]*rep
else:
hypers_dict[k] = [v] * rep
hyper_df = pd.DataFrame(hypers_dict)
return hyper_df
first=True # first pandas file to load
for subfolder in tqdm(subfolders):
runs = glob.glob(subfolder+'/*')
num_epochs = len(pd.read_csv(os.path.join(runs[0], 'progress.txt'),sep='\t'))
for run in runs:
tracker = combine_tracker(run)
progress = tracker.print_progress()
best_design = progress[np.argmax(tracker.max_ret_ls)]
if first:
df = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df))
df = pd.concat([df, hyper_df, best_designs_df], axis=1)
first = False
else:
df_ = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df_))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df_))
df_ = pd.concat([df_, hyper_df, best_designs_df], axis=1)
df = pd.concat([df, df_], axis=0)
return df
def finetune(simulator, m0, x0, target, display=False, bounds=None):
'''
Finetune the structure using quasi-Newton's method.
Args:
m0: materials list given by the upstream RL
x0: thicknesses given by the upstream RL
display: if true, then plot the spectrum before and after the finetuning.
Returns:
x_opt: finetuned thickness list
'''
def objective_func(x):
R, T, A = simulator.spectrum(m0, [np.inf]+list(x)+[np.inf])
return 1-cal_reward(R, T, A, target)
if bounds is None:
bounds = [(15, 200)] * len(x0)
res = minimize(objective_func, x0, bounds=bounds, options={'disp':True})
x_opt = [int(item) for item in res.x]
if display:
plt.figure()
simulator.spectrum(m0, [np.inf]+x0+[np.inf], title=True, plot=True)
plt.figure()
simulator.spectrum(m0, [np.inf]+x_opt+[np.inf], title=True, plot=True)
return x_opt, res
| print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]] | conditional_block |
utils.py | from mpi4py import MPI
import matplotlib
from tmm import coh_tmm
import pandas as pd
import os
from numpy import pi
from scipy.interpolate import interp1d
from joblib import Parallel, delayed
import numpy as np
import glob
import matplotlib.pyplot as plt
import pickle as pkl
import seaborn as sns
from scipy.optimize import minimize
import json
from tqdm import tqdm
DATABASE = './data'
INSULATORS = ['HfO2', 'SiO2', 'SiC', 'Al2O3', 'MgF2', 'TiO2', 'Fe2O3', 'MgF2', 'Si3N4', 'TiN', 'ZnO', 'ZnS', 'ZnSe']
METALS = ['Ag', 'Al', 'Cr', 'Ge', 'Si', 'Ni']
num_workers = 8
def cal_reward(R, T, A, target):
'''
Calculate reward based on given spectrums.
We calculate the reward using averaged (1-mse).
Args:
R, T, A: numpy array. Reflection, transmission, and
absorption spectrums, respectively.
target: dict. {'R':np.array, 'T':np.array, 'A':np.array}
Returns:
reward: float. Reward for the spectrum.
'''
reward = 0
for k, v in target.items():
if k == 'R':
res = R
elif k == 'T':
res = T
else:
res = A
reward += 1 - np.abs(res.squeeze() - v).mean()
reward /= len(target)
return reward
class Memory:
def __init__(self):
self.actions = []
self.states = []
self.logprobs = []
self.rewards = []
self.is_terminals = []
def clear_memory(self):
del self.actions[:]
del self.states[:]
del self.logprobs[:]
del self.rewards[:]
del self.is_terminals[:]
def batch_spectrum(env, names_list, thickness_list):
def spectrum(args):
'''
Inputs:
1. names: list of lists, each list correspond to the structures
2. thickness: list of lists
'''
names, thickness = args
R, T, A = env.spectrum(names, thickness, 0, False)
return R, T, A
res = Parallel(n_jobs=num_workers)(delayed(spectrum)(args)
for args in
zip(names_list, thickness_list))
res = np.array(res)
Rs, Ts, As = res[:, 0, :], res[:, 1, :], res[:, 2, :]
return Rs, Ts, As
def | (categories, thicknesses):
'''
Merges consecutive layers with the same material types.
'''
thicknesses = thicknesses[1:-1]
c_output = [categories[0]]
t_output = [thicknesses[0]]
for i, (c, d) in enumerate(zip(categories[1:], thicknesses[1:])):
if c == c_output[-1]:
t_output[-1] += d
continue
else:
c_output.append(c)
t_output.append(d)
t_output.insert(0, np.inf)
t_output.insert(len(t_output), np.inf)
return c_output, t_output
def get_structure(categories, values, materials, ds, continuous=False,
max_value=400):
'''
Given categories and values, return the strucure in the form
(name (str), thickness (nm))
'''
def threshold(value):
'''
'''
names = [materials[item] for item in categories]
if not continuous:
thickness = [np.inf] + [ds[item] for item in values] + [np.inf]
else:
thickness = []
for category, value in zip(categories, values):
name = materials[category]
if name == 'Ag':
thickness.append(
min(max(15, int(value * max_value//2)), max_value))
elif name in METALS:
thickness.append(
min(max(5, int(value * max_value//2)), max_value))
elif name in INSULATORS:
thickness.append(
min(max(1, int(value * max_value//2)), max_value))
else:
raise ValueError('Material not known')
# thickness = [np.inf] + [min(max(5, int(item * 2e2)), 200) for i,
# item in enumerate(values)] + [np.inf]
thickness = [np.inf] + thickness + [np.inf]
return names, thickness
class DesignTracker():
def __init__(self, epochs, **kwargs):
"""
This class tracks the best designs discovered.
"""
if epochs == -1:
self.layer_ls = []
self.thick_ls = []
self.max_ret_ls = []
self.layer_ls = [0] * epochs
self.thick_ls = [0] * epochs
self.max_ret_ls = [0] * epochs
self.kwargs = kwargs
self.current_e = 0
def store(self, layers, thicknesses, ret, e, append_mode=False):
if append_mode:
self.layer_ls.append(layers)
self.thick_ls.append(thicknesses)
self.max_ret_ls.append(ret)
else:
if ret >= self.max_ret_ls[e]:
self.layer_ls[e] = layers
self.thick_ls[e] = thicknesses
self.max_ret_ls[e] = ret
def save_state(self):
# save buffer from all processes
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
filename = os.path.join(self.kwargs['output_dir'], 'design_tracker_{}.pkl'.format(rank))
pkl.dump(self, open(filename, 'wb'))
def print_progress(self):
progress = list(zip(self.layer_ls, self.thick_ls, self.max_ret_ls))
read_progress = []
for i in range(len(progress)):
if progress[i] == (0,0,0):
break
read_progress.append(['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]) + ', Merit {:.3f}'.format(progress[i][2])])
return read_progress
def print_progress(progress):
for i in range(len(progress)):
print(progress[i], 0)
progress[i] = ['|'.join([l + ' ' + str(d) + ' nm' for l, d in zip(progress[i][0], progress[i][1])]), progress[i][2]]
return progress
class TMM_sim():
def __init__(self, mats=['Ge'], wavelength=np.arange(0.38, 0.805, 0.01), substrate='Cr', substrate_thick=500):
'''
This class returns the spectrum given the designed structures.
'''
self.mats = mats
# include substrate
self.all_mats = mats + [substrate] if substrate not in ['Glass', 'Air'] else mats
self.wavelength = wavelength
self.nk_dict = self.load_materials()
self.substrate = substrate
self.substrate_thick = substrate_thick
def load_materials(self):
'''
Load material nk and return corresponding interpolators.
Return:
nk_dict: dict, key -- material name, value: n, k in the
self.wavelength range
'''
nk_dict = {}
for mat in self.all_mats:
nk = pd.read_csv(os.path.join(DATABASE, mat + '.csv'))
nk.dropna(inplace=True)
wl = nk['wl'].to_numpy()
index = (nk['n'] + nk['k'] * 1.j).to_numpy()
mat_nk_data = np.hstack((wl[:, np.newaxis], index[:, np.newaxis]))
mat_nk_fn = interp1d(
mat_nk_data[:, 0].real, mat_nk_data[:, 1], kind='quadratic')
nk_dict[mat] = mat_nk_fn(self.wavelength)
return nk_dict
def spectrum(self, materials, thickness, theta=0, plot=False, title=False):
'''
Input:
materials: list
thickness: list
theta: degree, the incidence angle
Return:
s: array, spectrum
'''
degree = pi/180
if self.substrate != 'Air':
thickness.insert(-1, self.substrate_thick) # substrate thickness
R, T, A = [], [], []
for i, lambda_vac in enumerate(self.wavelength * 1e3):
# we assume the last layer is glass
if self.substrate == 'Glass':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1.45, 1]
elif self.substrate == 'Air':
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [1]
else:
n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict[self.substrate][i], 1]
# n_list = [1] + [self.nk_dict[mat][i] for mat in materials] + [self.nk_dict['Cr'][i]]
# mport pdb; pdb.set_trace()
res = coh_tmm('s', n_list, thickness, theta * degree, lambda_vac)
R.append(res['R'])
T.append(res['T'])
R, T = np.array(R), np.array(T)
A = 1 - R - T
if plot:
self.plot_spectrum(R, T, A)
if title:
thick = thickness[1:-1]
title = ' | '.join(['{}nm {}'.format(d, m)
for d, m in zip(thick, materials)])
if self.substrate is not 'Air':
title = 'Air | ' + title + ' | {}nm {} '.format(self.substrate_thick, self.substrate) + '| Air'
else:
title = 'Air | ' + title + ' | Air'
plt.title(title, **{'size': '10'})
return R, T, A
def plot_spectrum(self, R, T, A):
plt.plot(self.wavelength * 1000, R, self.wavelength *
1000, T, self.wavelength * 1000, A, linewidth=3)
plt.ylabel('R/T/A')
plt.xlabel('Wavelength (nm)')
plt.legend(['R: Average = {:.2f}%'.
format(np.mean(R)*100),
'T: Average = {:.2f}%'.
format(np.mean(T)*100),
'A: Average = {:.2f}%'.
format(np.mean(A)*100)])
plt.grid('on', linestyle='--')
plt.ylim([0, 1])
# Plotting utils
def visualize_progress(file, x, ax=None, color='b', alpha=1):
df = pd.read_csv(file, sep="\t")
width = 0.5
# x = 'Time'
if ax is None:
fig, ax = plt.subplots(2,1)
sns.lineplot(x=x, y='MaxEpRet', data=df, ax=ax[0], color=color, alpha=alpha)
# ax[0].legend(['Max {}'.format(np.max(df['MaxEpRet']))])
sns.lineplot(x=x, y='AverageEpRet', data=df,
ax=ax[1], color=color, alpha=alpha)
plt.fill_between(df[x],
df['AverageEpRet']-width/2*df['StdEpRet'],
df['AverageEpRet']+width/2*df['StdEpRet'],
alpha=0.3, color=color)
return df
def combine_tracker(folder):
'''
Merge all buffers
'''
trackers = []
if 'design_tracker_merged.pkl' in os.listdir(folder):
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
combined_tracker = pkl.load(open(tracker_file, 'rb'))
return combined_tracker
for file in os.listdir(folder):
if file.startswith('design_tracker_'):
tracker_file = os.path.join(folder, file)
trackers.append(pkl.load(open(tracker_file, 'rb')))
combined_tracker = DesignTracker(len(trackers[0].layer_ls))
max_idx = np.argmax(np.array([tracker.max_ret_ls for tracker in trackers]), axis=0)
for e in range(len(trackers[0].layer_ls)):
combined_tracker.layer_ls[e] = trackers[max_idx[e]].layer_ls[e]
combined_tracker.thick_ls[e] = trackers[max_idx[e]].thick_ls[e]
combined_tracker.max_ret_ls[e] = trackers[max_idx[e]].max_ret_ls[e]
if combined_tracker.layer_ls[-1] != 0:
tracker_file = os.path.join(folder, 'design_tracker_merged.pkl')
pkl.dump(combined_tracker, open(os.path.join(folder, tracker_file), 'wb'))
return combined_tracker
def summarize_res(exp_ls, seed_ls, color, alpha, x='Epoch'):
root = '../spinningup/data/'
progress_ls = []
max_ret_ls = []
params = {'size':14}
matplotlib.rc('font', **params)
fig, ax = plt.subplots(2,1, figsize=(10,8))
for a, c, exp, seed in zip(alpha, color, exp_ls, seed_ls):
folder = os.path.join(root, exp, exp+'_s{}'.format(seed))
progress_file = os.path.join(folder, 'progress.txt')
df = visualize_progress(progress_file, x=x, ax=ax, color=c, alpha=a)
tracker = combine_tracker(folder)
progress = tracker.print_progress()
print('{}, Best discovered so far {}'.format(exp, progress[np.argmax(tracker.max_ret_ls)]))
progress_ls.append(progress)
max_ret_ls.append('Max merit {:.3f}'.format(np.max(df['MaxEpRet'])))
ax[0].legend(max_ret_ls)
ax[1].legend(exp_ls)
plt.show()
return progress_ls
def load_exp_res(folder):
subfolders = [item for item in glob.glob(folder+'/*')]
def read_hyper(file_name, rep=10):
with open(os.path.join(file_name, 'config.json')) as f:
hypers = json.load(f)
hypers_dict = {}
for k, v in hypers.items():
if k.startswith('logger'):
continue
elif isinstance(v, dict):
for kk, vv in v.items():
if isinstance(vv, list):
hypers_dict[str(k)+'_'+str(kk)] = [vv[0]]*rep
else:
hypers_dict[str(k)+'_'+str(kk)] = [vv]*rep
else:
hypers_dict[k] = [v] * rep
hyper_df = pd.DataFrame(hypers_dict)
return hyper_df
first=True # first pandas file to load
for subfolder in tqdm(subfolders):
runs = glob.glob(subfolder+'/*')
num_epochs = len(pd.read_csv(os.path.join(runs[0], 'progress.txt'),sep='\t'))
for run in runs:
tracker = combine_tracker(run)
progress = tracker.print_progress()
best_design = progress[np.argmax(tracker.max_ret_ls)]
if first:
df = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df))
df = pd.concat([df, hyper_df, best_designs_df], axis=1)
first = False
else:
df_ = pd.read_csv(os.path.join(run, 'progress.txt'),sep='\t')
hyper_df = read_hyper(run, rep=len(df_))
best_designs_df = pd.DataFrame([{'best_design':best_design}]*len(df_))
df_ = pd.concat([df_, hyper_df, best_designs_df], axis=1)
df = pd.concat([df, df_], axis=0)
return df
def finetune(simulator, m0, x0, target, display=False, bounds=None):
'''
Finetune the structure using quasi-Newton's method.
Args:
m0: materials list given by the upstream RL
x0: thicknesses given by the upstream RL
display: if true, then plot the spectrum before and after the finetuning.
Returns:
x_opt: finetuned thickness list
'''
def objective_func(x):
R, T, A = simulator.spectrum(m0, [np.inf]+list(x)+[np.inf])
return 1-cal_reward(R, T, A, target)
if bounds is None:
bounds = [(15, 200)] * len(x0)
res = minimize(objective_func, x0, bounds=bounds, options={'disp':True})
x_opt = [int(item) for item in res.x]
if display:
plt.figure()
simulator.spectrum(m0, [np.inf]+x0+[np.inf], title=True, plot=True)
plt.figure()
simulator.spectrum(m0, [np.inf]+x_opt+[np.inf], title=True, plot=True)
return x_opt, res
| merge_layers | identifier_name |
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