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文档更新 (#2)
* 更新其中的1.17版本官方文档
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‎README.md‎

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@@ -58,7 +58,7 @@ The AS library generates some log data when performing many calculation function
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</dependency>
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</dependencies>
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```
61-
#### 可选依赖项
61+
#### Optional Dependencies
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When interfacing with various platforms such as databases and Sparks, the AS library needs to use third-party dependency packages, which are optional. If you do not need to use these functions, you may not need to import dependencies. If you need to, you can refer to the following configuration.
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```xml
@@ -243,25 +243,25 @@ AS library runs.
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### KnowledgeDocument
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246-
The knowledge base file archive is used for the storage task of ASMB series knowledge documents. You can access it
246+
The knowledge base file archive is used for the storage task of AS-MB series knowledge documents. You can access it
247247
directly through the documents on the home page. There is no need to enter here directly. It is messy internally.
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### src_code
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251-
The source code storage directory of ASMB, where you can view the relevant source code of ASMB. Of course, here is the
251+
The source code storage directory of AS-MB, where you can view the relevant source code of AS-MB. Of course, here is the
252252
latest source code, which you can use to compile, so that you can obtain the latest version.
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254254
Note: The latest version is often unstable, so we recommend you to use the version that has been released for a long
255255
time!
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### README-Chinese.md
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259-
The Chinese version of the ASMB homepage document. You can switch languages on the homepage default page to access this
259+
The Chinese version of the AS-MB homepage document. You can switch languages on the homepage default page to access this
260260
file.
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262262
### README.md
263263

264-
The default version of the ASMB homepage document. You can directly access this file on the homepage!
264+
The default version of the AS-MB homepage document. You can directly access this file on the homepage!
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266266
- 切换到 [中文文档](https://github.com/BeardedManZhao/algorithmStar/blob/main/README-Chinese.md)
267267

‎src_code/README-Chinese.md‎

Lines changed: 15 additions & 15 deletions
Original file line numberDiff line numberDiff line change
@@ -22,7 +22,7 @@ import zhao.algorithmMagic.operands.matrix.block.IntegerMatrixSpace;
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2323
public class MAIN1 {
2424
public static void main(String[] args) {
25-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_1.jpg";
25+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_1.jpg";
2626
IntegerMatrix integerMatrix;
2727
{
2828
// 设置权重
@@ -39,7 +39,7 @@ public class MAIN1 {
3939
// 输出图片1的卷积图像文件
4040
ImageRenderingIntegrator image = new ImageRenderingIntegrator(
4141
"image",
42-
new ImageRenderingMarLauncher<>(integerMatrix, "C:\\Users\\Liming\\Desktop\\fsdownload\\res12.jpg", 1)
42+
new ImageRenderingMarLauncher<>(integerMatrix, "C:\\Users\\Liming\\Desktop\\fsDownload\\res12.jpg", 1)
4343
);
4444
if (image.run()) {
4545
System.out.println("ok!!!");
@@ -57,7 +57,7 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
5757

5858
public class MAIN1 {
5959
public static void main(String[] args) throws InterruptedException {
60-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_1.jpg";
60+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_1.jpg";
6161
ColorMatrix parse = ColorMatrix.parse(s1);
6262
parse.show("image");
6363
Thread.sleep(1024);
@@ -114,15 +114,15 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
114114

115115
public class MAIN1 {
116116
public static void main(String[] args) {
117-
String s1 = "C:\\Users\\zhao\\Desktop\\fsdownload\\微信图片_2.jpg";
117+
String s1 = "C:\\Users\\zhao\\Desktop\\fsDownload\\微信图片_2.jpg";
118118
// 获取到图像矩阵对象
119119
ColorMatrix parse = ColorMatrix.parse(s1);
120120
// 将图像在原图像的基础上进行颜色反转操作
121121
parse.colorReversal(false);
122122
// 查看颜色反转之后的图像
123123
parse.show("image1");
124124
// 输出反转之后的图像
125-
parse.save("C:\\Users\\zhao\\Desktop\\fsdownload\\res123.jpg");
125+
parse.save("C:\\Users\\zhao\\Desktop\\fsDownload\\res123.jpg");
126126
}
127127
}
128128
```
@@ -136,11 +136,11 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
136136

137137
public class MAIN1 {
138138
public static void main(String[] args) {
139-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_2.jpg";
139+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_2.jpg";
140140
// 获取到图像矩阵对象
141141
ColorMatrix parse = ColorMatrix.parse(s1);
142142
// 输出图像RGB文本数据
143-
parse.save("C:\\Users\\Liming\\Desktop\\fsdownload\\res1234.csv", ',');
143+
parse.save("C:\\Users\\Liming\\Desktop\\fsDownload\\res1234.csv", ',');
144144
}
145145
}
146146
```
@@ -179,7 +179,7 @@ public class MAIN1 {
179179
.count() // 将每一组进行统计
180180
.sort("count()") // 按照统计结果进行正序排序
181181
.limit(3); // 获取最多前3行数据
182-
System.out.println(select.into_outfile("C:\\Users\\zhao\\Desktop\\fsdownload\\res1.csv"));
182+
System.out.println(select.into_outfile("C:\\Users\\zhao\\Desktop\\fsDownload\\res1.csv"));
183183
// 打印存储 FDF 中的数据行数
184184
System.out.println("数据行数 = " + execute.count());
185185
// 打印出其中的信息
@@ -459,7 +459,7 @@ public class MAIN1 {
459459
parse1.show("image");
460460
// 输出图像的 ASCII 数值，输出规则为 G 通道颜色数值 大于 40 的 输出符号 'A' 其它输出符号 ' '
461461
parse1.save(
462-
new File("C:\\Users\\zhao\\Desktop\\fsdownload\\res.txt"),
462+
new File("C:\\Users\\zhao\\Desktop\\fsDownload\\res.txt"),
463463
ColorMatrix._G_, 40, 'A', ' '
464464
);
465465
}
@@ -607,7 +607,7 @@ public class MAIN1 {
607607
);
608608
// 输出表的HTML 然后查看表中的数据
609609
System.out.println(
610-
insert.into_outHtml("C:\\Users\\Liming\\Desktop\\fsdownload\\res11234.html", "myTable")
610+
insert.into_outHtml("C:\\Users\\Liming\\Desktop\\fsDownload\\res11234.html", "myTable")
611611
);
612612
}
613613
}
@@ -625,8 +625,8 @@ import java.sql.SQLException;
625625
public class MAIN1 {
626626
public static void main(String[] args) {
627627
// 将一些图像文件转换成为一个图像矩阵对象
628-
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test.bmp");
629-
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test1.bmp");
628+
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test.bmp");
629+
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test1.bmp");
630630
// 将 colorMatrix2 + colorMatrix1 的结果图像展示出来
631631
(colorMatrix1.add(colorMatrix2)).show("image");
632632
}
@@ -645,8 +645,8 @@ import java.sql.SQLException;
645645
public class MAIN1 {
646646
public static void main(String[] args) {
647647
// 将一些图像文件转换成为一个图像矩阵对象
648-
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test.bmp");
649-
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test1.bmp");
648+
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test.bmp");
649+
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test1.bmp");
650650
// 使用 agg 函数以及内置的计算方案进行两个矩阵的合并
651651
// 下面函数中的第二个形参代表的就是矩阵中元素的聚合逻辑，这里使用的是求和，并对越界颜色数值进行规整的逻辑实现
652652
colorMatrix1.agg(colorMatrix2, ColorMatrix.COLOR_SUM_REGULATE).show("image");
@@ -667,7 +667,7 @@ import java.sql.SQLException;
667667
public class MAIN1 {
668668
public static void main(String[] args) {
669669
// 将一些图像文件转换成为一个图像矩阵对象
670-
ColorMatrix colorMatrix1 = ColorMatrix.parseGrayscale("C:\\Users\\Liming\\Desktop\\fsdownload\\test2.bmp");
670+
ColorMatrix colorMatrix1 = ColorMatrix.parseGrayscale("C:\\Users\\Liming\\Desktop\\fsDownload\\test2.bmp");
671671
// 对图像进行二值化
672672
colorMatrix1.globalBinary(ColorMatrix._G_, 100, 0xffffff, 0);
673673
colorMatrix1.show("腐蚀之前的 image");

‎src_code/README.md‎

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Original file line numberDiff line numberDiff line change
@@ -23,7 +23,7 @@ import zhao.algorithmMagic.operands.matrix.block.IntegerMatrixSpace;
2323

2424
public class MAIN1 {
2525
public static void main(String[] args) {
26-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_1.jpg";
26+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_1.jpg";
2727
IntegerMatrix integerMatrix;
2828
{
2929
// 设置权重
@@ -40,7 +40,7 @@ public class MAIN1 {
4040
// 输出图片1的卷积图像文件
4141
ImageRenderingIntegrator image = new ImageRenderingIntegrator(
4242
"image",
43-
new ImageRenderingMarLauncher<>(integerMatrix, "C:\\Users\\Liming\\Desktop\\fsdownload\\res12.jpg", 1)
43+
new ImageRenderingMarLauncher<>(integerMatrix, "C:\\Users\\Liming\\Desktop\\fsDownload\\res12.jpg", 1)
4444
);
4545
if (image.run()) {
4646
System.out.println("ok!!!");
@@ -58,7 +58,7 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
5858

5959
public class MAIN1 {
6060
public static void main(String[] args) throws InterruptedException {
61-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_1.jpg";
61+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_1.jpg";
6262
ColorMatrix parse = ColorMatrix.parse(s1);
6363
parse.show("image");
6464
Thread.sleep(1024);
@@ -117,15 +117,15 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
117117

118118
public class MAIN1 {
119119
public static void main(String[] args) {
120-
String s1 = "C:\\Users\\zhao\\Desktop\\fsdownload\\微信图片_2.jpg";
120+
String s1 = "C:\\Users\\zhao\\Desktop\\fsDownload\\微信图片_2.jpg";
121121
// 获取到图像矩阵对象
122122
ColorMatrix parse = ColorMatrix.parse(s1);
123123
// 将图像在原图像的基础上进行颜色反转操作
124124
parse.colorReversal(false);
125125
// 查看颜色反转之后的图像
126126
parse.show("image1");
127127
// 输出反转之后的图像
128-
parse.save("C:\\Users\\zhao\\Desktop\\fsdownload\\res123.jpg");
128+
parse.save("C:\\Users\\zhao\\Desktop\\fsDownload\\res123.jpg");
129129
}
130130
}
131131
```
@@ -140,11 +140,11 @@ import zhao.algorithmMagic.operands.matrix.ColorMatrix;
140140

141141
public class MAIN1 {
142142
public static void main(String[] args) {
143-
String s1 = "C:\\Users\\Liming\\Desktop\\fsdownload\\微信图片_2.jpg";
143+
String s1 = "C:\\Users\\Liming\\Desktop\\fsDownload\\微信图片_2.jpg";
144144
// 获取到图像矩阵对象
145145
ColorMatrix parse = ColorMatrix.parse(s1);
146146
// 输出图像RGB文本数据
147-
parse.save("C:\\Users\\Liming\\Desktop\\fsdownload\\res1234.csv", ',');
147+
parse.save("C:\\Users\\Liming\\Desktop\\fsDownload\\res1234.csv", ',');
148148
}
149149
}
150150
```
@@ -184,7 +184,7 @@ public class MAIN1 {
184184
.count() // 将每一组进行统计
185185
.sort("count()") // 按照统计结果进行正序排序
186186
.limit(3); // 获取最多前3行数据
187-
System.out.println(select.into_outfile("C:\\Users\\zhao\\Desktop\\fsdownload\\res1.csv"));
187+
System.out.println(select.into_outfile("C:\\Users\\zhao\\Desktop\\fsDownload\\res1.csv"));
188188
// 打印存储 FDF 中的数据行数
189189
System.out.println("数据行数 = " + execute.count());
190190
// 打印出其中的信息
@@ -459,7 +459,7 @@ public class MAIN1 {
459459
parse1.show("image");
460460
// 输出图像的 ASCII 数值，输出规则为 G 通道颜色数值 大于 40 的 输出符号 'A' 其它输出符号 ' '
461461
parse1.save(
462-
new File("C:\\Users\\zhao\\Desktop\\fsdownload\\res.txt"),
462+
new File("C:\\Users\\zhao\\Desktop\\fsDownload\\res.txt"),
463463
ColorMatrix._G_, 40, 'A', ' '
464464
);
465465
}
@@ -608,7 +608,7 @@ public class MAIN1 {
608608
);
609609
// 输出表的HTML 然后查看表中的数据
610610
System.out.println(
611-
insert.into_outHtml("C:\\Users\\Liming\\Desktop\\fsdownload\\res11234.html", "myTable")
611+
insert.into_outHtml("C:\\Users\\Liming\\Desktop\\fsDownload\\res11234.html", "myTable")
612612
);
613613
}
614614
}
@@ -627,8 +627,8 @@ import java.sql.SQLException;
627627
public class MAIN1 {
628628
public static void main(String[] args) {
629629
// 将一些图像文件转换成为一个图像矩阵对象
630-
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test.bmp");
631-
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test1.bmp");
630+
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test.bmp");
631+
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test1.bmp");
632632
// 将 colorMatrix2 + colorMatrix1 的结果图像展示出来
633633
(colorMatrix1.add(colorMatrix2)).show("image");
634634
}
@@ -647,8 +647,8 @@ import java.sql.SQLException;
647647
public class MAIN1 {
648648
public static void main(String[] args) {
649649
// 将一些图像文件转换成为一个图像矩阵对象
650-
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test.bmp");
651-
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsdownload\\test1.bmp");
650+
ColorMatrix colorMatrix1 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test.bmp");
651+
ColorMatrix colorMatrix2 = ColorMatrix.parse("C:\\Users\\Liming\\Desktop\\fsDownload\\test1.bmp");
652652
// 使用 agg 函数以及内置的计算方案进行两个矩阵的合并
653653
// 下面函数中的第二个形参代表的就是矩阵中元素的聚合逻辑，这里使用的是求和，并对越界颜色数值进行规整的逻辑实现
654654
colorMatrix1.agg(colorMatrix2, ColorMatrix.COLOR_SUM_REGULATE).show("image");
@@ -669,7 +669,7 @@ import java.sql.SQLException;
669669
public class MAIN1 {
670670
public static void main(String[] args) {
671671
// 将一些图像文件转换成为一个图像矩阵对象
672-
ColorMatrix colorMatrix1 = ColorMatrix.parseGrayscale("C:\\Users\\Liming\\Desktop\\fsdownload\\test2.bmp");
672+
ColorMatrix colorMatrix1 = ColorMatrix.parseGrayscale("C:\\Users\\Liming\\Desktop\\fsDownload\\test2.bmp");
673673
// 对图像进行二值化
674674
colorMatrix1.globalBinary(ColorMatrix._G_, 100, 0xffffff, 0);
675675
colorMatrix1.show("腐蚀之前的 image");

‎src_code/src/main/java/zhao/algorithmMagic/operands/matrix/ColorMatrix.java‎

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Original file line numberDiff line numberDiff line change
@@ -1279,7 +1279,6 @@ public void save(String path, char sep) {
12791279
* <p>
12801280
* Directory path to save.
12811281
* @param sep 保存时使用的分隔符。
1282-
*
12831282
*/
12841283
@Override
12851284
public void save(File path, char sep) {

‎src_code/src/main/java/zhao/algorithmMagic/operands/matrix/ColumnDoubleMatrix.java‎

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Original file line numberDiff line numberDiff line change
@@ -636,7 +636,6 @@ public void save(String path) {
636636
* <p>
637637
* Directory path to save.
638638
* @param sep 保存时使用的分隔符。
639-
*
640639
*/
641640
@Override
642641
public void save(String path, char sep) {
@@ -652,7 +651,6 @@ public void save(String path, char sep) {
652651
* <p>
653652
* Directory path to save.
654653
* @param sep 保存时使用的分隔符。
655-
*
656654
*/
657655
@Override
658656
public void save(File path, char sep) {

‎src_code/src/main/java/zhao/algorithmMagic/operands/matrix/ColumnIntegerMatrix.java‎

Lines changed: 0 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -632,7 +632,6 @@ public void save(String path) {
632632
* <p>
633633
* Directory path to save.
634634
* @param sep 保存时使用的分隔符。
635-
*
636635
*/
637636
@Override
638637
public void save(String path, char sep) {
@@ -648,7 +647,6 @@ public void save(String path, char sep) {
648647
* <p>
649648
* Directory path to save.
650649
* @param sep 保存时使用的分隔符。
651-
*
652650
*/
653651
@Override
654652
public void save(File path, char sep) {

‎src_code/src/main/java/zhao/algorithmMagic/operands/matrix/block/IntegerMatrixSpace.java‎

Lines changed: 6 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -183,10 +183,10 @@ public IntegerMatrixSpace transpose() {
183183
/**
184184
* 对矩阵空间进行卷积计算，在卷积计算的时候会产生出一个更小的特征矩阵。
185185
*
186-
* @param width 矩阵进行卷积运算的时的子图像宽度，最好选择能够被矩阵的列数整除的数值。
187-
* @param height 矩阵进行卷积运算时的子图像高度，最好选中能够被矩阵的行数整除的数值。
186+
* @param width 矩阵进行卷积运算的时的子图像宽度，最好选择能够被矩阵的列数整除的数值。
187+
* @param height 矩阵进行卷积运算时的子图像高度，最好选中能够被矩阵的行数整除的数值。
188188
* @param weightMat 在进行卷积计算时需要的卷积核矩阵对象，该对象的宽高应与卷积函数的形参一致。
189-
*
189+
* <p>
190190
* The convolution kernel matrix object required for convolution computation, whose width and height should be consistent with the formal parameters of the convolution function.
191191
* @return 矩阵空间卷积结果特征图，保持三通道的格式返回。
192192
*/
@@ -252,12 +252,11 @@ public IntegerMatrixSpace folding(int width, int height, IntegerMatrixSpace weig
252252
/**
253253
* 对矩阵空间进行卷积计算，在卷积计算的时候会产生出一个更小的特征矩阵。
254254
*
255-
* @param width 矩阵进行卷积运算的时的子图像宽度，最好选择能够被矩阵的列数整除的数值。
256-
* @param height 矩阵进行卷积运算时的子图像高度，最好选中能够被矩阵的行数整除的数值。
255+
* @param width 矩阵进行卷积运算的时的子图像宽度，最好选择能够被矩阵的列数整除的数值。
256+
* @param height 矩阵进行卷积运算时的子图像高度，最好选中能够被矩阵的行数整除的数值。
257257
* @param weightMat 在进行卷积计算时需要的卷积核矩阵对象，该对象的宽高应与卷积函数的形参一致。
258-
*
258+
* <p>
259259
* The convolution kernel matrix object required for convolution computation, whose width and height should be consistent with the formal parameters of the convolution function.
260-
*
261260
* @return 矩阵空间卷积结果特征图，以三原色通道之和的方式返回一个矩阵。
262261
*/
263262
public final IntegerMatrix foldingAndSum(int width, int height, IntegerMatrixSpace weightMat) {

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