POI+XChart图形报告
一、基础示例,写入Excel
生成一个图形,并将其写入 Excel 中。
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.xlsx";
double[] xData = new double[]{0.0, 1.0, 2.0};
double[] yData = new double[]{2.0, 1.0, 0.0};
// Create Chart
XYChart chart = QuickChart.getChart("Sample Chart", "X", "Y", "y(x)", xData, yData);
// 将图表转换为byte数组
byte[] bytes = BitmapEncoder.getBitmapBytes(chart, BitmapEncoder.BitmapFormat.PNG);
try (XSSFWorkbook workbook = new XSSFWorkbook();
ByteArrayInputStream inputStream = new ByteArrayInputStream(bytes);
FileOutputStream outputStream = new FileOutputStream(filePath)) {
// 创建Excel
XSSFSheet sheet = workbook.createSheet("图表");
// 写入Excel的指定位置
XSSFDrawing shapes = sheet.createDrawingPatriarch();
XSSFClientAnchor anchor = new XSSFClientAnchor(0, 0, 0, 0, 0, 0, 6, 10);
shapes.createPicture(anchor, sheet.getWorkbook().addPicture(inputStream, HSSFWorkbook.PICTURE_TYPE_PNG));
// 将Excel写到文件中
workbook.write(outputStream);
}
}
生成的基础图片
上面我们演示了如何
将 XChart生成的图片导入 Excel
,下面的部分,都会将生成的图形导出为图片,如果需要导入Excel的话,只需要将chart套入第一章即可。
二、将生成的图形导出成为图片
获取随机数的方法也是通用的,这里先给出,具体的数据应该根据业务而定:
/**
* 获取随机数
* @param numPoints 随机的数量
* @return 随机数组
*/
private double[] getRandomWalk(int numPoints) {
double[] y = new double[numPoints];
y[0] = 0;
for (int i = 1; i < y.length; i++) {
y[i] = y[i - 1] + Math.random() - .5;
}
return y;
}
折线图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
XYChart chart = new XYChartBuilder().xAxisTitle("X").yAxisTitle("Y").width(600).height(400).build();
chart.getStyler().setYAxisMin(-10.0);
chart.getStyler().setYAxisMax(10.0);
XYSeries series = chart.addSeries("新绿", null, getRandomWalk(200));
series.setMarker(SeriesMarkers.NONE);
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
效果如下:
输入图片说明面积图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
// Create Chart
XYChart chart = new XYChartBuilder().width(800).height(600).title(getClass().getSimpleName()).xAxisTitle("X").yAxisTitle("Y").build();
// Customize Chart
chart.getStyler().setLegendPosition(Styler.LegendPosition.InsideNE);
chart.getStyler().setAxisTitlesVisible(false);
chart.getStyler().setDefaultSeriesRenderStyle(XYSeries.XYSeriesRenderStyle.Area);
// Series
chart.addSeries("a", new double[] { 0, 3, 5, 7, 9 }, new double[] { -3, 5, 9, 6, 5 });
chart.addSeries("b", new double[] { 0, 2, 4, 6, 9 }, new double[] { -1, 6, 4, 0, 4 });
chart.addSeries("c", new double[] { 0, 1, 3, 8, 9 }, new double[] { -2, -1, 1, 0, 1 });
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
面积图
饼状图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
PieChart chart = new PieChartBuilder().width(800).height(600).title(getClass().getSimpleName()).build();
// Customize Chart
Color[] sliceColors = new Color[] { new Color(224, 68, 14), new Color(230, 105, 62), new Color(236, 143, 110), new Color(243, 180, 159), new Color(246, 199, 182) };
chart.getStyler().setSeriesColors(sliceColors);
// Series
chart.addSeries("Gold", 24);
chart.addSeries("Silver", 21);
chart.addSeries("Platinum", 39);
chart.addSeries("Copper", 17);
chart.addSeries("Zinc", 40);
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
饼状图
散点图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
// Create Chart
XYChart chart = new XYChartBuilder().width(800).height(600).build();
// Customize Chart
chart.getStyler().setDefaultSeriesRenderStyle(XYSeries.XYSeriesRenderStyle.Scatter);
chart.getStyler().setChartTitleVisible(false);
chart.getStyler().setLegendPosition(Styler.LegendPosition.InsideSW);
chart.getStyler().setMarkerSize(16);
// Series
List<Double> xData = new LinkedList<Double>();
List<Double> yData = new LinkedList<Double>();
Random random = new Random();
int size = 1000;
for (int i = 0; i < size; i++) {
xData.add(random.nextGaussian() / 1000);
yData.add(-1000000 + random.nextGaussian());
}
chart.addSeries("Gaussian Blob", xData, yData);
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
散点图
柱状图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
// Create Chart
CategoryChart chart = new CategoryChartBuilder().width(800).height(600).title("Score Histogram").xAxisTitle("Score").yAxisTitle("Number").build();
// Customize Chart
chart.getStyler().setLegendPosition(Styler.LegendPosition.InsideNW);
chart.getStyler().setHasAnnotations(true);
// Series
chart.addSeries("test 1", Arrays.asList(0, 1, 2, 3, 4), Arrays.asList(4, 5, 9, 6, 5));
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
柱状图
堆叠图
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
// Create Chart
CategoryChart chart = new CategoryChartBuilder().width(800).height(600).title("Score Histogram").xAxisTitle("Mean").yAxisTitle("Count").build();
// Customize Chart
chart.getStyler().setLegendPosition(Styler.LegendPosition.InsideNW);
chart.getStyler().setAvailableSpaceFill(.96);
chart.getStyler().setOverlapped(true);
// Series
Histogram histogram1 = new Histogram(getGaussianData(10000), 20, -20, 20);
Histogram histogram2 = new Histogram(getGaussianData(5000), 20, -20, 20);
chart.addSeries("histogram 1", histogram1.getxAxisData(), histogram1.getyAxisData());
chart.addSeries("histogram 2", histogram2.getxAxisData(), histogram2.getyAxisData());
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
private List<Double> getGaussianData(int count) {
List<Double> data = new ArrayList<Double>(count);
Random r = new Random();
for (int i = 0; i < count; i++) {
data.add(r.nextGaussian() * 10);
}
return data;
}
堆叠图
百分比堆叠柱状图
这个其实是堆叠图的变种。
@Test
public void generate() throws IOException {
String filePath = "C:\\Users\\user\\Desktop\\first.png";
CategoryChart chart = new CategoryChartBuilder().width(800).height(600).build();
chart.getStyler().setChartBackgroundColor(Color.WHITE);
chart.getStyler().setLegendBorderColor(Color.WHITE);
chart.getStyler().setLegendPosition(Styler.LegendPosition.InsideNW);
chart.getStyler().setAvailableSpaceFill(0.7);
chart.getStyler().setStacked(true);
List<String> xData = Arrays.asList("学院A", "学院B", "学院C","学院D","学院E");
chart.addSeries("得分A", xData, getGaussianData(5));
chart.addSeries("得分B", xData, getGaussianData(5));
chart.addSeries("得分C", xData, getGaussianData(5));
chart.addSeries("得分D", xData, getGaussianData(5));
BitmapEncoder.saveBitmap(chart, filePath, BitmapEncoder.BitmapFormat.PNG);
}
private List<Double> getGaussianData(int count) {
List<Double> data = new ArrayList<Double>(count);
for (int i = 0; i < count; i++) {
data.add(RandomUtils.nextDouble(0,1) * 10);
}
return data;
}
百分比堆叠柱状图
参考:
(1) XChart Demo
(2) 自己
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