我有一个应用程序，我在其中进行了一个函数调用，该函数调用需要一些时间来计算，具体取决于用户输入。我尝试使用 AsyncTask 实现进度条显示，但是当我在 doinbackGround 中声明函数调用时，它给出了一个错误，因为它与 UI 线程交互。我为函数调用创建了一个单独的线程，并在 UI 线程中调用了 AsyncTask 类并同步了它们的时间，即将 Asynctask 的 doinbackground 中的 sleep 时间设置为一个较大的值，以便完成函数调用在那个时候。
但这不是一个好的解决方案，因为完成方法调用所花费的时间取决于用户输入，而我事先并不知道。我还希望我的进度条连续显示而不是离散显示。我正在提供 Asynctask 调用类和函数调用的代码。
异步任务调用类
package com.integrated.mpr;
public class Progess extends Activity {
static String[] display = new String[Model.n];
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.progress);
Thread threada=new Thread(){
public void run() {
display = new Logic().finaldata();
// this is the function call
}
};
threada.start();
new loadSomeStuff().execute(" ");
}
public class loadSomeStuff extends AsyncTask<String,Integer,String>{
ProgressDialog dialog;
protected void onPreExecute(){
dialog = new ProgressDialog(Progess.this);
dialog.setProgressStyle(ProgressDialog.STYLE_HORIZONTAL);
dialog.setMax(100);
dialog.setTitle("Generating the most sensitive positions");
dialog.show();
}
@Override
protected String doInBackground(String... arg0) {
for(int i=0;i<20;i++){
publishProgress(5);
try {
Thread.sleep(1200);// the timing set to a large value
} catch (InterruptedException e) {
e.printStackTrace();
}
}
dialog.dismiss();
return null;
}
protected void onProgressUpdate(Integer...progress){
dialog.incrementProgressBy(progress[0]);
}
protected void onPostExecute(String result){
Intent openList = new Intent("com.integrated.mpr.SENSITIVELIST");
startActivity(openList);
}
}
}
耗时较长的函数
package com.integrated.mpr;
public class Logic {
int n = Model.n;
int ns = Model.ns;
double final_matrix[][] = new double[n][5];
double swap =0;
double weightage_matrix[] = new double[n];
double sorted_weightage[] = new double[n];
String display[] = new String[n];
double[] peak_matrix = new double[n];
double[] sd_matrix = new double[n];
double[] rms_matrix = new double[n];
double[] cf_matrix = new double[n];
double[] mean_matrix = new double[n];
int[] sensitive_positions = new int[n];
double[] new_sensitive = new double[n];
int[] sortsensi = new int[n];
public String[] finaldata(){
for(int i=0;i<n;i++){
peak_matrix[i] = Model.timedata[i*5+0];
sd_matrix[i] = Model.timedata[i*5+1];
rms_matrix[i] = Model.timedata[i*5+2];
cf_matrix[i] = Model.timedata[i*5+3];
mean_matrix[i] = Model.timedata[i*5+4];
}
// Arrays sorted in asecnding order
java.util.Arrays.sort(peak_matrix);
java.util.Arrays.sort(sd_matrix);
java.util.Arrays.sort(rms_matrix);
java.util.Arrays.sort(mean_matrix);
java.util.Arrays.sort(cf_matrix);
Log.d("matrices", "sorted");
for(int i = 0;i<n;i++){
final_matrix[i][0]= peak_matrix[i];
final_matrix[i][1]= sd_matrix[i];
final_matrix[i][2]= rms_matrix[i];
final_matrix[i][3]= cf_matrix[i];
final_matrix[i][4]= mean_matrix[i];
}
Log.d("final ", "matrix");
double temp =0;
for(int i=0;i<n;i++){
for(int j=0;j<5;j++){
temp = final_matrix[i][j];
for(int k =0;k<n;k++){
if(temp==Model.timedata[k*5+j]){
weightage_matrix[k] = weightage_matrix[k]+(i+1)*n;
}
}
}
}
//copying the values into sorted matrix;
for(int i=0;i<n;i++){
sorted_weightage[i] = weightage_matrix[i];
}
//sorting weighatge matrix in descending order
for (int i = 0;i<n; i++ )
{
for ( int j = 0 ; j < n-i-1 ; j++ )
{
if ( sorted_weightage[j] <sorted_weightage[j+1] ) {
swap = sorted_weightage[j];
sorted_weightage[j] = sorted_weightage[j+1];
sorted_weightage[j+1] = swap;
}
}
}
Log.d("sorted weightage", "matrix");
for(int i =0;i<n;i++){
temp = sorted_weightage[i];
for(int j =0;j<n;j++){
if(temp==weightage_matrix[j]){
sensitive_positions[i]=j+1;
}
}
}
RealMatrix pcorrdata = new PearsonsCorrelation().computeCorrelationMatrix(Model.input_matrix);
// the above statement takes time depending on the user input
for(int i =0;i<n;i++){
for(int j =0;j<n;j++){
if(pcorrdata.getEntry(i, j)<0){
pcorrdata.setEntry(i, j, pcorrdata.getEntry(i, j)*-1);
}
}
}
for(int i =0;i<n;i++){
for(int j =0;j<n;j++){
Log.d(" "+i+" "+j, ""+pcorrdata.getEntry(i, j));
}
}
for(int i =0;i<n;i++){
Log.d("sensitive osition before correlation", ""+sensitive_positions[i]);
}
int[] perm_sensitive = sensitive_positions;
for(int i =0;i<ns;i++){
int temp1 = perm_sensitive[i]-1;
if(i+1<n){
for(int j=i+1;j<ns;j++){
int temp2 = perm_sensitive[j]-1;
if(pcorrdata.getEntry(temp1, temp2)>0.5){
sensitive_positions =append((temp2)+1,sensitive_positions);
}
}
perm_sensitive = sensitive_positions;
Log.d("perm", ""+perm_sensitive[0]);
Log.d("perm", ""+perm_sensitive[1]);
}
}
for(int i =0;i<n;i++){
Log.d("values",""+perm_sensitive[i]);
}
for(int i =0;i<n;i++){
display[i] = Model.posnames[perm_sensitive[i]-1];
}
return display;
}
private int[] append(int j, int[] sensitive_positions) {
int[] sort_sensitive = new int[n];
int z = 0;
for(int i =0;i<n;i++){
if(sensitive_positions[i]!=j){
sort_sensitive[z]=sensitive_positions[i];
z = z+1;
}
}
sort_sensitive[n-1] = j;
return sort_sensitive;
}
}
使用Asynctask的progressupdate更新UI
package com.integrated.mpr;
public class Logic extends Activity{
int n = Choose.n;
double final_matrix[][] = new double[n][5];
double swap =0;
double weightage_matrix[] = {0,0,0,0,0,0,0,0,0,0,0};
double sorted_weightage[] = {0,0,0,0,0,0,0,0,0,0};
static String display[] = new String[Choose.n];
static double[][] input_matrix;
double[] peak_matrix;
double[] sd_matrix;
double[] rms_matrix ;
double[] cf_matrix ;
double[] mean_matrix ;
int[] sensitive_positions ;
double[] new_sensitive ;
int[] sortsensi ;
RealMatrix pcorrdata ;
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.progress);
String x = "abc";
new loadSomeStuff().execute(x);
}
public class loadSomeStuff extends AsyncTask<String,Integer,String>{
ProgressDialog dialog;
protected void onPreExecute(){
dialog = new ProgressDialog(Logic.this);
dialog.setProgressStyle(ProgressDialog.STYLE_HORIZONTAL);
dialog.setMax(100);
dialog.setMessage("Computing Most Sensitive Positions");
dialog.show();
}
@Override
protected String doInBackground(String... params) {
publishProgress(25);
publishProgress(50);
publishProgress(75);
publishProgress(100);
}
private int[] append(int j, int[] sensitive_positions) {
int[] sort_sensitive = new int[n];
int z = 0;
for(int i =0;i<n;i++){
if(sensitive_positions[i]!=j){
sort_sensitive[z]=sensitive_positions[i];
z = z+1;
}
}
sort_sensitive[n-1] = j;
return sort_sensitive;
}
protected void onProgressUpdate(Integer...progress){
if(progress[0]==25){
Log.d("loop 1 ", "start");
Log.d("now in ", "35 loop");
input_matrix = new double[22050][n];
peak_matrix = new double[n];
sd_matrix = new double[n];
rms_matrix = new double[n];
cf_matrix = new double[n];
mean_matrix = new double[n];
sensitive_positions = new int[n];
new_sensitive = new double[n];
sortsensi = new int[n];
for(int i=0;i<n;i++){
peak_matrix[i] = Choose.timedata[i*5+0];
sd_matrix[i] = Choose.timedata[i*5+1];
rms_matrix[i] = Choose.timedata[i*5+2];
cf_matrix[i] = Choose.timedata[i*5+3];
mean_matrix[i] = Choose.timedata[i*5+4];
}
for(int i = 0;i<n;i++){
final_matrix[i][0]= peak_matrix[i];
final_matrix[i][1]= sd_matrix[i];
final_matrix[i][2]= rms_matrix[i];
final_matrix[i][3]= cf_matrix[i];
final_matrix[i][4]= mean_matrix[i];
}
//final sorted matrix obtained
for(int i =0;i<n;i++){
for(int j=0;j<5;j++){
if(final_matrix[i][j]== new Page1().timedata1[j]){
weightage_matrix[0] = weightage_matrix[0]+(i+1)*24;
}
else if (final_matrix[i][j]== new Page2().timedata2[j]){
weightage_matrix[1] = weightage_matrix[1]+(i+1)*24;
}
else if (final_matrix[i][j]== new Page3().timedata3[j]){
weightage_matrix[2] = weightage_matrix[2]+(i+1)*24;
}
else if (final_matrix[i][j]== new Page4().timedata4[j]){
weightage_matrix[3] = weightage_matrix[3]+(i+1)*24;
}
else{
weightage_matrix[4] = weightage_matrix[4]+(i+1)*24;
}
}
}
Log.d("loop 1 ", "stop");
Log.d("now ", "incrementing");
dialog.incrementProgressBy(15);
}
else if (progress[0]==50){
Log.d("loop 2 ", "start");
//copying the values into sorted matrix;
for(int i=0;i<n;i++){
sorted_weightage[i] = weightage_matrix[i];
}
//sorting weighatge matrix in descending order
for (int i = 0;i<n; i++ ){
for ( int j = 0 ; j < n-i-1 ; j++ ){
if ( sorted_weightage[j] <sorted_weightage[j+1] ) {
swap = sorted_weightage[j];
sorted_weightage[j] = sorted_weightage[j+1];
sorted_weightage[j+1] = swap;
}
}
}
for(int i =0;i<n;i++){
double temp = sorted_weightage[i];
for(int j =0;j<n;j++){
if(temp==weightage_matrix[j]){
sensitive_positions[i]=j+1;
}
}
}
Log.d("loop 2 ", "stop");
dialog.incrementProgressBy(20);
//now for correaltion
}
else if (progress[0] == 75){
// genearting the input matrix for correaltion
Log.d("loop 3 ", "start");
for(int i=0;i<n;i++){
for(int j=0;j<22050;j++){
input_matrix[j][i] = new Choose().rawdata[i*22050+j];
}
}
// now generating correlation matrix of N x n by using pearson correaltion
pcorrdata = new PearsonsCorrelation().computeCorrelationMatrix(input_matrix);
dialog.incrementProgressBy(35);
}
else{
Log.d("checkng correlation mtrix", "yup");
for(int i =0;i<n;i++){
for(int j =0;j<n;j++){
if(pcorrdata.getEntry(i, j)<0){
pcorrdata.setEntry(i, j, pcorrdata.getEntry(i, j)*-1);
}
}
}
Log.d("now in", "75 l00p");
for(int i =0;i<n;i++){
Log.d("sensitive osition before correlation", ""+sensitive_positions[i]);
}
Log.d("loop 3 ", "stop");
Log.d("loop 4 ", "start");
int[] perm_sensitive = sensitive_positions;
if((pcorrdata.getEntry(perm_sensitive[0]-1, perm_sensitive[1]-1))>0.5){
sensitive_positions = append(perm_sensitive[1],sensitive_positions);
}
perm_sensitive = sensitive_positions;
if((pcorrdata.getEntry(perm_sensitive[2]-1, perm_sensitive[3]-1))>0.5){
sensitive_positions = append(perm_sensitive[3],sensitive_positions);
}
for(int i =0;i<n;i++){
Log.d("values",""+perm_sensitive[i]);
}
for(int i =0;i<n;i++){
display[i] = new Choose().posnames[perm_sensitive[i]-1];
}
Log.d("loop 4 ", "stop");
dialog.incrementProgressBy(20);
Log.d("now in ","100 loop");
Intent openList = new Intent("com.integrated.mpr.SENSITIVELIST");
startActivity(openList);
}
}
protected void onPostExecute(String result){
dialog.dismiss();
Intent openList = new Intent("com.integrated.mpr.SENSITIVELIST");
startActivity(openList);
}
}
}
LogCat 错误
06-09 16:32:05.670: E/AndroidRuntime(8009): FATAL EXCEPTION: AsyncTask #4
06-09 16:32:05.670: E/AndroidRuntime(8009): java.lang.RuntimeException: An error occured while executing doInBackground()
06-09 16:32:05.670: E/AndroidRuntime(8009): at android.os.AsyncTask$3.done(AsyncTask.java:200)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.FutureTask$Sync.innerSetException(FutureTask.java:273)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.FutureTask.setException(FutureTask.java:124)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:307)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.FutureTask.run(FutureTask.java:137)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1068)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:561)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.lang.Thread.run(Thread.java:1096)
06-09 16:32:05.670: E/AndroidRuntime(8009): Caused by: java.lang.RuntimeException: Can't create handler inside thread that has not called Looper.prepare()
06-09 16:32:05.670: E/AndroidRuntime(8009): at android.os.Handler.<init>(Handler.java:121)
06-09 16:32:05.670: E/AndroidRuntime(8009): at android.app.Activity.<init>(Activity.java:679)
06-09 16:32:05.670: E/AndroidRuntime(8009): at com.integrated.mpr.Logic.<init>(Logic.java:13)
06-09 16:32:05.670: E/AndroidRuntime(8009): at com.integrated.mpr.Progess$loadSomeStuff.doInBackground(Progess.java:53)
06-09 16:32:05.670: E/AndroidRuntime(8009): at com.integrated.mpr.Progess$loadSomeStuff.doInBackground(Progess.java:1)
06-09 16:32:05.670: E/AndroidRuntime(8009): at android.os.AsyncTask$2.call(AsyncTask.java:185)
06-09 16:32:05.670: E/AndroidRuntime(8009): at java.util.concurrent.FutureTask$Sync.innerRun(FutureTask.java:305)
06-09 16:32:05.670: E/AndroidRuntime(8009): ... 4 more
请建议我如何实现这一目标的方法？？？
最佳答案
使用 AsyncTask。它可以在 onProgressUpdate 和 onPostExecute 中与 UI 线程交互。 您必须将计算保留在 doInBackground() 中，并且仅在 onProgressUpdate() 中更新 UI。 将您的 Logic 类分解为更多方法，并像这样进行操作。
public class LogicAsync extends AsyncTask<Void, Integer, Void> {
@Override
protected Void doInBackground(Void... p) {
Logic logic = new Logic();
logic.loadArrays();
publishProgress(10); //10% done
try {
Thread.sleep(1000);
} catch {
}
logic.sortArraysAndMatrix();
publishProgress(20); //20% done
logic.copyAndSortWeightages();
publishProgress(30);
logic.finalData();
publishProgress(100);
}
@Override
protected void onProgressUpdate(Integer... progress) {
updateUIWithPercent(progress[0]);
}
}
这是一个修改后的逻辑类，其中包含一些分解的方法。
package com.integrated.mpr;
import org.apache.commons.math.linear.RealMatrix;
import org.apache.commons.math.stat.correlation.Covariance;
import org.apache.commons.math.stat.correlation.PearsonsCorrelation;
import org.apache.commons.math.util.FastMath;
import android.util.Log;
public class Logic {
int n = Model.n;
int ns = Model.ns;
double final_matrix[][] = new double[n][5];
double swap =0;
double weightage_matrix[] = new double[n];
double sorted_weightage[] = new double[n];
String display[] = new String[n];
double[] peak_matrix = new double[n];
double[] sd_matrix = new double[n];
double[] rms_matrix = new double[n];
double[] cf_matrix = new double[n];
double[] mean_matrix = new double[n];
int[] sensitive_positions = new int[n];
double[] new_sensitive = new double[n];
int[] sortsensi = new int[n];
public void loadArrays() {
for(int i=0;i<n;i++){
peak_matrix[i] = Model.timedata[i*5+0];
sd_matrix[i] = Model.timedata[i*5+1];
rms_matrix[i] = Model.timedata[i*5+2];
cf_matrix[i] = Model.timedata[i*5+3];
mean_matrix[i] = Model.timedata[i*5+4];
}
}
public void sortArraysAndMatrix() {
// Arrays sorted in asecnding order
java.util.Arrays.sort(peak_matrix);
java.util.Arrays.sort(sd_matrix);
java.util.Arrays.sort(rms_matrix);
java.util.Arrays.sort(mean_matrix);
java.util.Arrays.sort(cf_matrix);
Log.d("matrices", "sorted");
for(int i = 0;i<n;i++){
final_matrix[i][0]= peak_matrix[i];
final_matrix[i][1]= sd_matrix[i];
final_matrix[i][2]= rms_matrix[i];
final_matrix[i][3]= cf_matrix[i];
final_matrix[i][4]= mean_matrix[i];
}
}
public void copyAndSortWeightages() {
Log.d("final ", "matrix");
double temp =0;
for(int i=0;i<n;i++){
for(int j=0;j<5;j++){
temp = final_matrix[i][j];
for(int k =0;k<n;k++){
if(temp==Model.timedata[k*5+j]){
weightage_matrix[k] = weightage_matrix[k]+(i+1)*n;
}
}
}
}
//copying the values into sorted matrix;
for(int i=0;i<n;i++){
sorted_weightage[i] = weightage_matrix[i];
}
//sorting weighatge matrix in descending order
for (int i = 0;i<n; i++ )
{
for ( int j = 0 ; j < n-i-1 ; j++ )
{
if ( sorted_weightage[j] <sorted_weightage[j+1] ) {
swap = sorted_weightage[j];
sorted_weightage[j] = sorted_weightage[j+1];
sorted_weightage[j+1] = swap;
}
}
}
Log.d("sorted weightage", "matrix");
}
public String[] finaldata(){
for(int i =0;i<n;i++){
temp = sorted_weightage[i];
for(int j =0;j<n;j++){
if(temp==weightage_matrix[j]){
sensitive_positions[i]=j+1;
}
}
}
RealMatrix pcorrdata = new PearsonsCorrelation().computeCorrelationMatrix(Model.input_matrix);
// the above statement takes time depending on the user input
for(int i =0;i<n;i++){
for(int j =0;j<n;j++){
if(pcorrdata.getEntry(i, j)<0){
pcorrdata.setEntry(i, j, pcorrdata.getEntry(i, j)*-1);
}
}
}
for(int i =0;i<n;i++){
for(int j =0;j<n;j++){
Log.d(" "+i+" "+j, ""+pcorrdata.getEntry(i, j));
}
}
for(int i =0;i<n;i++){
Log.d("sensitive osition before correlation", ""+sensitive_positions[i]);
}
int[] perm_sensitive = sensitive_positions;
for(int i =0;i<ns;i++){
int temp1 = perm_sensitive[i]-1;
if(i+1<n){
for(int j=i+1;j<ns;j++){
int temp2 = perm_sensitive[j]-1;
if(pcorrdata.getEntry(temp1, temp2)>0.5){
sensitive_positions =append((temp2)+1,sensitive_positions);
}
}
perm_sensitive = sensitive_positions;
Log.d("perm", ""+perm_sensitive[0]);
Log.d("perm", ""+perm_sensitive[1]);
}
}
for(int i =0;i<n;i++){
Log.d("values",""+perm_sensitive[i]);
}
for(int i =0;i<n;i++){
display[i] = Model.posnames[perm_sensitive[i]-1];
}
return display;
}
private int[] append(int j, int[] sensitive_positions) {
// TODO Auto-generated method stub
int[] sort_sensitive = new int[n];
int z = 0;
for(int i =0;i<n;i++){
if(sensitive_positions[i]!=j){
sort_sensitive[z]=sensitive_positions[i];
z = z+1;
}
}
sort_sensitive[n-1] = j;
return sort_sensitive;
}
}
关于android - 使用 Asynctask 显示进度条，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/10959866/