java - 在函数中使用 FileWriter；文件应该已经存在

Question

好的，所以在 distributionA 函数中，我想打开并写入已在 main 中成功写入的同一个文件，但它不会将 writer 识别为变量。我尝试使用追加，但有时它会覆盖我想保留的文本。我很茫然，如何才能有效地使这段代码满足我的需要？这是写入文件“outputScores.txt”。 澄清一下:我不想使用 System.out。我只是把它留在那里，因为我使用 FileWriter 时遇到错误。

import java.io.*;
import java.util.*;
public class readFile {

/* Distribution function: Steps are: 
 * -assign an array of doubles for each grade. 
 * -pass each array into getAverage, getMedian, and getStandardDeviation to get each individual statistic
 * -print out each line within the function.
 */
public static void distributionA(double[]score,int size) throws IOException{
    int countA=0,countAp=0,countAm= 0,countBp=0, countBm=0,countB=0,countCp =0, countCm=0,countC=0,countD=0,countDp=0,countDm=0,countF=0; 
    double averageA,averageAp,averageAm,averageB,averageBp,averageBm,averageC,averageCp,averageCm,averageDp,averageDm,averageD,averageF;
    double medianA,medianAp,medianAm,medianB,medianBp,medianBm,medianCp,medianCm,medianC,medianDp,medianDm,medianD,medianF;
    double deviationA,deviationAp,deviationAm,deviationBp,deviationBm,deviationB,deviationCp,deviationCm,deviationC,deviationDp,deviationDm,deviationD,deviationF;
    double []arrayA = new double[100];
    double []arrayAp = new double[100];
    double []arrayAm = new double[100];
    double []arrayB = new double[100];
    double []arrayBp = new double[100];
    double []arrayBm = new double[100];
    double []arrayC= new double[100];
    double []arrayCp= new double[100];
    double []arrayCm= new double[100];
    double []arrayD= new double[100];
    double []arrayDp= new double[100];
    double []arrayDm= new double[100];
    double []arrayF= new double[100];
    for(int i=0; i<size-1;i++){
        if(score[i] >=97){arrayAp[countAp] = score[i];countAp++;}
    else if(score[i] >= 93 && score[i] <97){arrayA[countA] = score[i];countA++;}
        else if(score[i] >=90 && score[i] <94){arrayAm[countAm] = score[i];countAm++;}
        else if(score[i] >=87 && score[i] <90){arrayBp[countBp] = score[i];countBp++;}
        else if(score[i] >= 83 && score[i] <87){arrayB[countB] = score[i];countB++;}
        else if(score[i] >= 80 && score[i] <83){arrayBm[countBm] = score[i];countBm++;}
        else if (score[i] >=73 && score[i] <77){arrayC[countC] = score[i];countC++;}
        else if (score[i] >=70 && score[i] <73){arrayCm[countCm] = score[i];countCm++;}
        else if (score[i] >=77 && score[i] <80){arrayCp[countCp] = score[i];countCp++;}
        else if(score[i] >=63 && score[i] < 67){arrayD[countD] = score[i];countD++;}
        else if(score[i] >=67 && score[i] < 70){arrayDp[countDp] = score[i];countDp++;}
        else if(score[i] >=60 && score[i] < 63){arrayDm[countDm] = score[i];countDm++;}
        else if (score[i] < 60){arrayF[countF] = score[i];countF++;}
    }
    averageA = getAverage(arrayA,countA);
    averageAp= getAverage(arrayAp,countAp);
    averageAm=getAverage(arrayAm,countAm);
    averageB= getAverage(arrayB,countB);
    averageBp=getAverage(arrayBp,countBp);
    averageBm=getAverage(arrayBm,countBm);
    averageC=getAverage(arrayC,countC);
    averageCp=getAverage(arrayCp,countCp);
    averageCm=getAverage(arrayCm,countCm);
    averageD=getAverage(arrayD,countD);
    averageDp=getAverage(arrayDp,countDp);
    averageDm=getAverage(arrayDm,countDm);
    averageF= getAverage(arrayF,countF);
    medianAp= getMedian(arrayAp,countAp);
    medianAm= getMedian(arrayAm,countAm);
    medianA= getMedian(arrayA,countA);
    medianB= getMedian(arrayB,countB);
    medianBp= getMedian(arrayBp,countBp);
    medianBm= getMedian(arrayBm,countBm);
    medianC=getMedian(arrayC,countC);
    medianCp=getMedian(arrayCp,countCp);
    medianCm=getMedian(arrayCm,countCm);
    medianD=getMedian(arrayD, countD);
    medianDp=getMedian(arrayDp, countDp);
    medianDm=getMedian(arrayDm, countDm);
    medianF=getMedian(arrayF,countF);
    deviationA=getStandardDeviation(arrayA,countA);
    deviationAp=getStandardDeviation(arrayAp,countAp);
    deviationAm=getStandardDeviation(arrayAm,countAm);
    deviationB=getStandardDeviation(arrayB,countB);
    deviationBp=getStandardDeviation(arrayBp,countBp);
    deviationBm=getStandardDeviation(arrayBm,countBm);
    deviationC=getStandardDeviation(arrayC,countC);
    deviationCp=getStandardDeviation(arrayCp,countCp);
    deviationCm=getStandardDeviation(arrayCm,countCm);
    deviationD=getStandardDeviation(arrayD,countD);
    deviationDp=getStandardDeviation(arrayDp,countDp);
    deviationDm=getStandardDeviation(arrayDm,countDm);
    deviationF=getStandardDeviation(arrayF,countF);
    System.out.println("A+: Occurances" + countAp + ", Average: " + averageAp + ", Median: " + medianAp + ", Standard Deviation: " +deviationAp);
    System.out.println("A: Occurances" + countA + ", Average: " + averageA + ", Median: " + medianA + ", Standard Deviation: " +deviationA);
    System.out.println("A-: Occurances" + countAm + ", Average: " + averageAm + ", Median: " + medianAm + ", Standard Deviation: " +deviationAm);
    System.out.println("B+: Occurances" + countBp + ", Average: " + averageBp + ", Median: " + medianBp + ", Standard Deviation: " +deviationBp);
    System.out.println("B: Occurances" + countB + ", Average: " + averageB + ", Median: " + medianB + ", Standard Deviation: " +deviationB);
    System.out.println("B-: Occurances" + countBm + ", Average: " + averageBm + ", Median: " + medianBm + ", Standard Deviation: " +deviationBm);
    System.out.println("C+: Occurances" + countCp + ", Average: " + averageCp + ", Median: " + medianCp + ", Standard Deviation: " +deviationCp);
    System.out.println("C: Occurances" + countC + ", Average: " + averageC + ", Median: " + medianC + ", Standard Deviation: " +deviationC);
    System.out.println("C-: Occurances" + countCm + ", Average: " + averageCm + ", Median: " + medianCm + ", Standard Deviation: " +deviationCm);
    System.out.println("D+: Occurances" + countDp + ", Average: " + averageDp + ", Median: " + medianDp + ", Standard Deviation: " +deviationDp);
    System.out.println("D: Occurances" + countD + ", Average: " + averageD + ", Median: " + medianD + ", Standard Deviation: " +deviationD);
    System.out.println("D-: Occurances" + countDm + ", Average: " + averageDm + ", Median: " + medianDm + ", Standard Deviation: " +deviationDm);
    System.out.println("F: Occurances" + countF + ", Average: " + averageF + ", Median: " + medianF + ", Standard Deviation: " +deviationF);
}
/* function getAverage steps:
 * -run through an array, adding the value at each location to the total. 
 * dividing that total by the size of the array.
 */
public static double getAverage(double [] score, int size){
double total = 0;
double average = 0;
for (int i = 0; i< size; i++){
total += score[i];
}
if (size!=0){
average = total/(size);
return average;}
/*to fix the case where we divide by zero, I did the following:*/
else{average = 0; return average;}/*There is only one case where the size        will be zero... when there is nothing in the array*/
}
/*function getMedian steps:
 * -sort the array in ascending order using a simple bubble sort.
 * -take the middle term; this is the median
 */
public static double getMedian(double [] score, int size){
double temp; boolean swapOccurred;
do {swapOccurred = false;
for (int i = 0; i<size;i++)
{if (score[i]< 0){score[i] = score[i] *-1;}
    if (score[i] >score[i+1])
    {
        temp = score[i];
        score[i] = score[i+1];
        score[i+1] = temp;
        swapOccurred = true;
    }

}
}while(swapOccurred);
return score[(size)/2];
}
/*function getStandardDeviation steps: 
 * -get the average from the array using the getAverage function.
 * -run through the array, and subtract the average from each term.
 * -square that number, and add it to the sum total.
 * -finally, divide that variable by (n-1).
 */
public static double getStandardDeviation(double []score, int size){
double average = getAverage(score,size);
double sum;double sumtotal=0;double hold;double step;double deviation;
for (int i = 0; i<size;i++){
    sum = score[i]-average;
    hold = sum*sum;
    sumtotal += hold;
}
step = sumtotal/(size-1);
/*special case handling. We can't divide by zero, so in the case that there is only one element, we just return the deviation as zero.*/
if (size!=1){
deviation = Math.sqrt(step);
return deviation;}
else{deviation = 0;return deviation;}
}
public static void main(String[] args)/*main implementation; open the scanner, and read each element of the file.*/
throws IOException{
PrintWriter writer = new PrintWriter("outputScores.txt");
int size = 0;
double [] scores = new double[100];
Scanner input = new Scanner(new File("scores.dat"));
while(input.hasNext()){

    if (input.hasNextDouble()){
        double store = input.nextDouble();/*To make sure that the numbers are only within our accepted range*/
        if(store > 0 && store <= 100){
        scores[size]=store;
    size++;/*Increase the current size of the array*/
    }
    }
    else{
        input.next();

    }

}
double deviation = getStandardDeviation(scores,size);
double average = getAverage(scores, size);  
double median = getMedian(scores,size);

writer.println("1. Enrolled student number: " + (size));
writer.println("2. Statistics for all students");
writer.println(" - Average: " + average);
writer.println(" - Median: " + median);
writer.println(" - Standard Deviation: " + deviation);
distributionA(scores,size);
writer.close();
}

}

Answer 1

您需要将 writer 传递给 distributionA()，以便它可以使用它:

distributionA(writer, scores, size);

您必须更改方法签名:

public static void distributionA(PrintWriter writer, double[]score, int size)

Then, inside distributionA, you can write to it:

writer.println("...");