Java FileWriter.append方法代碼示例

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the configuration file name for required to run python from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will be saved
* @param columns : Number of columns in the data
*/
private void create_config_file_pred(String filename , String datset, String model, String predictionfile, int columns){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
		writer.append("task=predict\n");
	    writer.append("columns=" + columns+ "\n");				
	    writer.append("model=" +model+ "\n");	
	    writer.append("data=" +datset+ "\n");				
	    writer.append("prediction=" +predictionfile+ "\n");	
	    if (this.verbose){
	    	writer.append("verbose=1" +  "\n");
	    }else {
	    	writer.append("verbose=0" +  "\n");			    	
	    }				    
	   
    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
private static void logDebugInfo(File debugLogFile, String msg, @Nullable Throwable t) {
    Log.d(LOG_TAG, msg);

    try {
        FileWriter debugLogFileWriter = new FileWriter(debugLogFile, true);
        msg = Utils.getFormattedDateTime(System.currentTimeMillis(), true) + " -> " + msg;
        debugLogFileWriter.append("\n").append(msg).append("\n");
        if (t != null) {
            debugLogFileWriter.append(Utils.getStackTrace(t));
        }
        debugLogFileWriter.flush();
        debugLogFileWriter.close();
    }
    catch (IOException ignored) {
    }
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
private void createGOPFile(String fileName) throws IOException {
    File gpsTrackDetailGOPFile = FileUtils.createGpsTrackDetailFile(GOP_FORMAT, fileName);
    gpsTrackDetailGOPFileWriter = new FileWriter(gpsTrackDetailGOPFile);

    //create the header
    gpsTrackDetailGOPFileWriter.append("LatitudeE6,LongitudeE6,PointType\n");

    ContentValues cvData = new ContentValues();
    cvData.put(DBAdapter.COL_NAME_GPSTRACKDETAIL__GPSTRACK_ID, gpsTrackId);
    cvData.put(DBAdapter.COL_NAME_GPSTRACKDETAIL__FILEFORMAT, GOP_FORMAT);
    cvData.put(DBAdapter.COL_NAME_GPSTRACKDETAIL__FILE, gpsTrackDetailGOPFile.getAbsolutePath());
    mDbAdapter.createRecord(DBAdapter.TABLE_NAME_GPSTRACKDETAIL, cvData);

    gpsTrackDetailGOPFileWriter.flush();

    if (isEnableDebugLog) {
        logDebugInfo(debugLogFile, "createGOPFile: File created. gpsTrackDetailGOPFile = " + fileName, null);
    }
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the configuration file name for required to run python from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will be saved
* @param columns : Number of columns in the data
*/
private void create_config_file_pred(String filename , String datset, String model, String predictionfile, int columns){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
		writer.append("task=predict\n");
	    writer.append("columns=" + columns+ "\n");				
	    writer.append("usedense=" + this.use_dense+ "\n");	
	    writer.append("model=" +model+ "\n");	
	    writer.append("data=" +datset+ "\n");				
	    writer.append("prediction=" +predictionfile+ "\n");				    
	   
    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
public void runMT() {
    ClientManager manager = new ClientManager(parameterPool, this);

    manager.createClients();
    manager.startWarmup();
    manager.startRun();
    logger.info(printResults(true));
    try {
        FileWriter resultWriter = new FileWriter(xmlResultFile);
        resultWriter.append(printXMLResults(true));
        resultWriter.flush();
        resultWriter.close();
    } catch (IOException e) {
        e.printStackTrace();
    }
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the configuration file name for required to run python from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will be saved
* @param columns : Number of columns in the data
*/
 
 private void create_config_file_pred(String filename , String datset, String model, String predictionfile, int columns){

	try{  // Catch errors in I/O if necessary.
		  // Open a file to write to.
			String saveFile = filename;
			
			FileWriter writer = new FileWriter(saveFile);
		writer.append("task=predict\n");
	    writer.append("columns=" + columns+ "\n");				
	    writer.append("usedense=" + this.use_dense+ "\n");	
	    writer.append("use_scale=" + this.use_scale+ "\n");				    
	    writer.append("model=" +model+ "\n");	
	    writer.append("data=" +datset+ "\n");				
	    writer.append("prediction=" +predictionfile+ "\n");	
	    if (this.verbose){
	    	writer.append("verbose=1" +  "\n");
	    }else {
	    	writer.append("verbose=0" +  "\n");			    	
	    }						    
			writer.close();

    	} catch (Exception e) {
    		throw new IllegalStateException(" failed to write the config file at: " + filename);
    	}   
 }
 

import java.io.FileWriter; //導入方法依賴的package包/類
public void addToReport(MSSQLTestData td, Object result) {
  try {
    FileWriter fr = new FileWriter(getOutputFileName(), true);
    String offset = td.getData(KEY_STRINGS.OFFSET);
    String dt = td.getDatatype();
    String res = "_";
    if (result == null) {
      res = "Success";
    } else {
      try {
        res = "FAILED "
            + removeNewLines(((AssertionError) result)
                .getMessage());

      } catch (Exception ae) {
        if (result instanceof Exception) {
          res = "FAILED "
              + removeNewLines(((Exception) result)
                  .getMessage());
        } else {
          res = "FAILED " + result.toString();
        }
      }
    }

    fr.append(offset + "\t" + "\t" + res + "\t" + dt + "\t"
        + removeNewLines(td.toString()) + "\n");
    fr.close();
  } catch (Exception e) {
    LOG.error(StringUtils.stringifyException(e));
  }

}
 

import java.io.FileWriter; //導入方法依賴的package包/類
protected void assertContents(CharSequence sb) throws IOException {
    File out = new File(getWorkDir(), fname + ".parsed");
    FileWriter wr = new FileWriter(out);
    wr.append(sb);
    wr.close();
    
    assertFile(out, getGoldenFile(fname + ".pass"), new File(getWorkDir(), fname + ".diff"));
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the conifiguration file name for required to run xgboost from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will eb saved
*/
private void create_config_file_pred(String filename , String datset, String model, String predictionfile){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
	    writer.append("objective=" + this.Objective+ "\n");
	    writer.append("is_sparse=true" + "\n");				  
	    writer.append("num_threads=" + this.threads + "\n");
	    if (this.verbose){
	    	writer.append("verbosity=1" +  "\n");
	    }else {
	    	writer.append("verbosity=0" +  "\n");			    	
	    }
	    
	    //file details
	    writer.append(datset+ "\n");
	    writer.append( model+ "\n");
	    writer.append( "output_result=" + predictionfile + "\n");
    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the conifiguration file name for required to run xgboost from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will eb saved
*/
private void create_config_file_pred(String filename , String datset, String model, String predictionfile){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
	    writer.append("objective=" + this.Objective+ "\n");
	    writer.append("nthread=" + this.threads + "\n");
	    writer.append("max_leaves=" + this.max_leaves + "\n");
	    writer.append("save_period=0" + "\n");
	    if (this.verbose){
	    	writer.append("silent=0" +  "\n");
	    }else {
	    	writer.append("silent=1" +  "\n");			    	
	    }
	    
	    //file details
	    writer.append(datset+ "\n");
	    writer.append( model+ "\n");
	    writer.append( "name_pred=" + predictionfile + "\n");
    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
private void writeIterationReport(FileWriter writer, IterationReport report) {
    try {
        writer.append("Iteration " + report.getIteration() + ":" + LINE_SEPARATOR);
        writer.append(INDENT + "Start Time: " + report.getStart().format(DateTimeFormatter.ISO_DATE_TIME) + LINE_SEPARATOR);
        writer.append(INDENT + "End Time: " + report.getEnd().format(DateTimeFormatter.ISO_DATE_TIME) + LINE_SEPARATOR);
        writer.append(INDENT + "Duration: " + report.getDuration().toMillis() + "ms" + LINE_SEPARATOR + LINE_SEPARATOR);
    }catch (IOException e){
        throw new WrappedIOException(e);
    }
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
public void writeToFile(int startCount, int endCount, String fileName) throws IOException {
  if (logger.isDebugEnabled()) {
    logger.debug("MTableDataCommandResult.writeToFile startCount = " + startCount + " endCount = "
        + endCount + " fileName = " + fileName);
  }
  boolean isFTable = this.isFTable;

  FileWriter writer = new FileWriter(fileName, true);
  for (int i = startCount; i <= endCount; i++) {
    if (i >= this.resultValues.size()) {
      break;
    }
    Row row = resultValues.get(i);
    if (i == 0) {
      StringBuilder stringBuilder = new StringBuilder();
      stringBuilder.append("#"); // This is for header (comment in csv).
      if (!isFTable) {
        stringBuilder.append("RowID");
      }
      List<Cell> cells = row.getCells();
      for (int j = 0; j < cells.size(); j++) {
        if (isFTable) {
          if (j > 0) {
            stringBuilder.append(",");
          }
        } else {
          stringBuilder.append(",");
        }
        stringBuilder.append(Bytes.toString(cells.get(j).getColumnName()));
        stringBuilder.append(":");
        stringBuilder.append(cells.get(j).getColumnType().toString());
      }
      writer.append(stringBuilder.toString());
      writer.append('\n');
      writer.flush();
    }
    toMResultCSV(row, writer, isFTable);
  }
  writer.close();
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the configuration file name for required to run python from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param predictionfile : where the predictions will be saved
* @param columns : Number of columns in the data
*/
private void create_config_file_pred(String filename , String datset, String model, String predictionfile, int columns){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
		writer.append("task=predict\n");
	    writer.append("columns=" + columns+ "\n");				
	    writer.append("usedense=" + this.use_dense+ "\n");	
	    writer.append("model=" +model+ "\n");	
	    writer.append("data=" +datset+ "\n");				
	    writer.append("prediction=" +predictionfile+ "\n");	
	    if (this.verbose){
	    	writer.append("verbose=1" +  "\n");
	    }else {
	    	writer.append("verbose=0" +  "\n");			    	
	    }				    
	   
    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
public  synchronized void addToReport(MSSQLTestData td, Object result) {
  System.out.println("called");
  try {
    FileWriter fr = new FileWriter(getResportFileName(), true);
    String offset = td.getData(KEY_STRINGS.OFFSET);
    String res = "_";
    if (result == null) {
    res = "Success";
  } else {
    try {
    res = "FAILED "
    + removeNewLines(((AssertionError) result)
    .getMessage());
    } catch (Exception ae) {
      if (result instanceof Exception
        && ((Exception) result) != null) {
        res = "FAILED "
        + removeNewLines(((Exception) result)
        .getMessage());
      } else {
        res = "FAILED " + result.toString();
      }
    }
  }

  fr.append(offset + "\t" + res + "\n");
  fr.close();
  } catch (Exception e) {
    LOG.error(StringUtils.stringifyException(e));
  }
}
 

import java.io.FileWriter; //導入方法依賴的package包/類
/**
* 
* @param filename : the conifiguration file name for required to run xgboost from the command line
* @param datset : the dataset to be used
* @param model : model dump name
* @param columns : Number of columns in the data
*/
 private void create_config_file(String filename , String datset, String model, int columns){

try{  // Catch errors in I/O if necessary.
	  // Open a file to write to.
	
		String saveFile = filename;
		
		FileWriter writer = new FileWriter(saveFile);
		writer.append("task=train\n");
	    writer.append("columns=" + columns+ "\n");					
	    writer.append("usedense=" + this.use_dense+ "\n");	
	    writer.append("model=" +model+ "\n");	
	    writer.append("data=" +datset+ "\n");				    
	    writer.append("criterion=" + this.criterion  + "\n");
	    writer.append("max_depth=" +this.max_depth + "\n");
	    writer.append("max_features=" + this.max_features + "\n");
	    writer.append("max_leaf_nodes=" + this.max_leaf_nodes+ "\n");
	    writer.append("min_impurity_split=" + this.min_impurity_split + "\n");
	    writer.append("min_samples_leaf=" + this.min_samples_leaf + "\n");
	    writer.append("min_samples_split=" + this.min_samples_split  + "\n");
	    writer.append("min_weight_fraction_leaf=" + this.min_weight_fraction_leaf + "\n");
	    writer.append("max_depth=" +  this.max_depth + "\n");
	    writer.append("random_state=" +  this.seed + "\n");	    
		writer.close();

   	} catch (Exception e) {
   		throw new IllegalStateException(" failed to write the config file at: " + filename);
   	}   
 }