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Simple methods to acutely measure multiple timing metrics among the sexual repertoire of male <i>Drosophila</i>.

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The authors' code

C++ · 457 lines · 16 KB · MIT

  1. #include "board.h"
  2. int s1=15,s2=15;
  3. int diffx = 0;
  4. int diffy = 0;
  5. int ss_threshold;
  6. int x[15],y[4];
  7. Mat image;
  8. board::board() {
  9. dstTri.emplace_back(Point2f(0,0));
  10. dstTri.emplace_back(Point2f(length,0));
  11. dstTri.emplace_back(Point2f(length,height));
  12. dstTri.emplace_back(Point2f(0,height));
  13. }
  14. void trackBar(int, void*)
  15. {
  16. diffx = s1 - 15;
  17. diffy = s2 - 15;
  18. x[0] = 0;
  19. y[0] = 36;
  20. for (int i=1;i<5;i++)
  21. x[i] = x[i-1]+66;
  22. x[5] = 333;
  23. for (int i=6;i<10;i++)
  24. x[i] = x[i-1]+66;
  25. x[10] = 666;
  26. for (int i=11;i<15;i++)
  27. x[i] = x[i-1]+66;
  28. for (int i=1;i<4;i++)
  29. y[i] = y[i-1]+66;
  30. for (int i=1;i<15;i++)
  31. x[i] +=diffx;
  32. for (int i=0;i<4;i++)
  33. y[i] +=diffy;
  34. Mat img2;
  35. img2 = image.clone();
  38. Mat img_gray,img_black;
  39. // Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
  40. vector<vector<cv::Point>> contours;
  41. vector<cv::Vec4i> hierarchy;
  43. img2 = image.clone();
  44. cvtColor(image,img_gray,CV_BGR2GRAY);
  45. medianBlur(img_gray,img_gray,3);
  46. threshold(img_gray,img_black,ss_threshold,255,CV_THRESH_BINARY);
  47. // dilate(img_black, img_black, kernel);
  48. findContours(img_black, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE);
  49. vector<RotatedRect> boundRect(contours.size());
  50. vector<double> contArea(contours.size());
  52. for (size_t i = 0; i < contours.size(); i++)
  53. {
  54. //approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
  55. boundRect[i] = minAreaRect(Mat(contours[i]));
  56. contArea[i] = contourArea(contours[i]);
  57. }
  58. for (size_t i = 0; i < contours.size(); i++)
  59. {
  60. int t_area = boundRect[i].size.area();
  61. if (t_area>=14 && contArea[i]>12 && contArea[i]<8000) {
  62. Scalar color = Scalar(0, 255, 255);
  63. drawContours(img2, contours, i, color, 1);
  64. }
  65. }
  67. for (int i=0;i<4;i++)
  68. line(img2,Point(0, y[i]),Point(155*6, y[i]),Scalar(0,0,255),1);
  69. for (int i=0;i<15;i++)
  70. line(img2,Point(x[i], 0),Point(x[i], 270),Scalar(0,0,255),1);
  71. // cout<<"threshold =" <<ss_threshold<<endl;
  72. imshow("output2", img2);
  73. // imshow("black", img_black);
  74. }
  75. void first(){
  76. diffx = s1 - 15;
  77. diffy = s2 - 15;
  78. x[0] = 0;
  79. y[0] = 36;
  80. for (int i=1;i<5;i++)
  81. x[i] = x[i-1]+66;
  82. x[5] = 333;
  83. for (int i=6;i<10;i++)
  84. x[i] = x[i-1]+66;
  85. x[10] = 666;
  86. for (int i=11;i<15;i++)
  87. x[i] = x[i-1]+66;
  88. for (int i=1;i<4;i++)
  89. y[i] = y[i-1]+66;
  90. for (int i=1;i<15;i++)
  91. x[i] +=diffx;
  92. for (int i=0;i<4;i++)
  93. y[i] +=diffy;
  95. Mat img_gray,img_black,img2;
  96. Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
  97. vector<vector<cv::Point>> contours;
  98. vector<cv::Vec4i> hierarchy;
  100. img2 = image.clone();
  101. cvtColor(image,img_gray,CV_BGR2GRAY);
  102. medianBlur(img_gray,img_gray,3);
  103. threshold(img_gray,img_black,ss_threshold,255,CV_THRESH_BINARY);
  104. // dilate(img_black, img_black, kernel);
  105. findContours(img_black, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE);
  106. vector<RotatedRect> boundRect(contours.size());
  107. vector<double> contArea(contours.size());
  109. for (size_t i = 0; i < contours.size(); i++)
  110. {
  111. //approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
  112. boundRect[i] = minAreaRect(Mat(contours[i]));
  113. contArea[i] = contourArea(contours[i]);
  114. }
  115. for (size_t i = 0; i < contours.size(); i++)
  116. {
  117. int t_area = boundRect[i].size.area();
  118. if (t_area>=14 && contArea[i]>12 && contArea[i]<8000) {
  119. Scalar color = Scalar(0, 255, 255);
  120. drawContours(img2, contours, i, color, 1);
  121. }
  122. }
  125. for (int i=0;i<4;i++)
  126. line(img2,Point(0, y[i]),Point(155*6, y[i]),Scalar(0,0,255),1);
  127. for (int i=0;i<15;i++)
  128. line(img2,Point(x[i], 0),Point(x[i], 270),Scalar(0,0,255),1);
  129. imshow("output2", img2);
  130. }
  131. void onMouse(int event, int x, int y, int flags, void *utsc)
  132. {
  133. callbackP cp = *(callbackP*)utsc; // 先转换类型，再取数据
  135. if (event == EVENT_LBUTTONUP) //响应鼠标左键事件
  136. {
  137. circle((*(callbackP*)utsc).src, Point(x, y), 2, Scalar(0, 0, 255), 2); //标记选中点
  138. // imshow("wait ", (*(callbackP*)utsc).src);
  139. (*(callbackP*)utsc).srcTri.emplace_back(Point2f(x, y));
  140. cout << "x:" << x << " " << "y:" << y << endl;
  141. (*(callbackP*)utsc).clickTimes++;
  143. if ((*(callbackP*)utsc).clickTimes == 4)
  144. {
  145. cout << "按任意键继续！" << endl;
  146. }
  147. }
  148. }
  150. void onMouse_threshold(int event, int x, int y, int flags, void *utsc)
  151. {
  152. callbackP cp = *(callbackP*)utsc; // 先转换类型，再取数据
  154. if (event == EVENT_LBUTTONUP) //响应鼠标左键事件
  155. {
  156. circle((*(callbackP*)utsc).src, Point(x, y), 1, Scalar(0, 0, 255), 2); //标记选中点
  157. // imshow("wait ", (*(callbackP*)utsc).src);
  158. (*(callbackP*)utsc).srcTri.emplace_back(Point2f(x, y));
  159. cout << "x:" << x << " " << "y:" << y << endl;
  160. (*(callbackP*)utsc).clickTimes++;
  162. if ((*(callbackP*)utsc).clickTimes == 3)
  163. {
  164. cout << "按任意键继续！" << endl;
  165. }
  166. }
  167. }
  169. void board::set_speed(int speed) {
  170. for (int i=0;i<37;i++)
  171. flies[i].speed = speed;
  172. }
  173. void board::get_point(Mat &img) {
  174. namedWindow("src",0);
  176. cvResizeWindow("src", 1080, 1080);
  177. bool process1 = true;
  178. utsc.src = img.clone();
  179. while(process1) {
  180. imshow("src", utsc.src);
  181. setMouseCallback("src", onMouse, (void *) &utsc); //类型转换
  182. if (utsc.clickTimes == 4) {
  183. //计算透视矩阵
  184. M = findHomography(utsc.srcTri, dstTri, RANSAC);
  185. //图像透视变换
  186. warpPerspective(utsc.src, dst, M,
  187. Size((length), (height)));
  188. imwrite("output.jpg", dst);
  189. break;
  190. } else {
  191. cout << "需要从左上角开始，顺时针依次点矩形的四个角！" << endl;
  192. cout << "现在点击了" << utsc.clickTimes << "次" << endl;
  193. }
  194. key = waitKey(1);
  195. if (key == 'q')
  196. break;
  197. }
  198. image = dst.clone();
  199. destroyWindow("src");
  200. }
  201. void board::adjust_lines() {
  202. cvNamedWindow("output2", 0);
  203. resizeWindow("output2", 1280, 1080);
  204. bool process2 = true;
  205. ss_threshold = set_threshold+28;
  206. first();
  207. while (process2){
  208. createTrackbar("diffx", "output2", &s1, 30, trackBar);
  209. createTrackbar("diffy", "output2", &s2, 30, trackBar);
  210. createTrackbar("threshold", "output2", &ss_threshold, 200, trackBar);
  211. key = waitKey(1);
  212. if (key == 'q')
  213. break;
  214. }
  215. destroyWindow("output2");
  216. }
  217. void board::reset_matcher() {
  218. Mat tempsrc = utsc.src.clone();
  219. Point center;
  220. for (int i=0;i<4;i++){
  221. center = utsc.srcTri[i];
  222. if (center.x>8 && center.y>8){
  223. matchimg.emplace_back(tempsrc(Rect(center.x-8,center.y-8,16,16)).clone());
  224. matchcenter.emplace_back(center);
  225. }
  226. }
  227. }
  228. void board::reset_threshold(){
  229. cvNamedWindow("threshold", 0);
  230. resizeWindow("threshold", 1280, 1080);
  231. Mat temp_src= image.clone();
  232. Mat temp_gray;
  233. imshow("threshold", temp_src);
  234. cvtColor(temp_src,temp_gray,CV_BGR2GRAY);
  235. bool process1 = true;
  236. int nums,maxnum;
  237. Point fly_center;
  238. utsc1.src = image.clone();
  239. while(process1) {
  240. imshow("threshold", utsc1.src);
  241. setMouseCallback("threshold", onMouse_threshold, (void *) &utsc1); //类型转换
  242. if (utsc1.clickTimes == 3) {
  243. break;
  244. } else {
  245. cout << "click flys" << endl;
  246. cout << "现在点击了" << utsc1.clickTimes << "次" << endl;
  247. }
  248. key = waitKey(1);
  249. if (key == 'q')
  250. break;
  251. }
  252. maxnum = 0;
  253. for (int i=0;i<3;i++){
  254. fly_center = utsc1.srcTri[i];
  255. nums = temp_gray.ptr<uchar>(fly_center.y)[fly_center.x];
  256. printf("num = %d \n",nums);
  257. if (nums>maxnum)
  258. maxnum = nums;
  259. }
  260. cout<<"min num ="<< maxnum<<endl;
  261. set_threshold = maxnum;
  262. destroyWindow("threshold");
  263. }
  264. float calc(Point2f rect[4]){
  265. float length,width;
  266. length = sqrt((rect[0].x-rect[1].x)*(rect[0].x-rect[1].x)+(rect[0].y-rect[1].y)*(rect[0].y-rect[1].y));
  267. width = sqrt((rect[2].x-rect[1].x)*(rect[2].x-rect[1].x)+(rect[2].y-rect[1].y)*(rect[2].y-rect[1].y));
  268. if (width/length < 1.0)
  269. return length/width*1.0;
  270. return width/length*1.0;
  271. }
  272. bool dis_judge(Point p1,Point p2){
  273. float dis;
  274. dis = sqrt((p1.x-p2.x)*(p1.x-p2.x)+(p1.y-p2.y)*(p1.y-p2.y));
  275. // if (dis>8.0)
  276. // cout<<"dis="<<dis<<endl;
  277. return dis <= 8.0;
  278. }
  279. void board::state(Mat &img, int time) {
  280. int wid,heigh;
  281. Mat img_gray,img_black;
  282. Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
  283. vector<vector<cv::Point>> contours;
  284. vector<cv::Vec4i> hierarchy;
  285. Point2f rect[4];
  286. Point leftup,rightdown,center;
  287. Mat srcimg,dstimg;
  288. for (int i=0;i<4;i++){
  289. center = matchcenter[i];
  290. if (center.x>20)
  291. leftup.x=center.x-20;
  292. else
  293. leftup.x = 0;
  294. if (center.y>20)
  295. leftup.y=center.y-20;
  296. else
  297. leftup.y = 0;
  298. if (center.x+20>img.cols)
  299. rightdown.x = img.cols;
  300. else
  301. rightdown.x = center.x+20;
  302. if (center.y+20>img.rows)
  303. rightdown.y = img.rows;
  304. else
  305. rightdown.y = center.y+20;
  306. wid = rightdown.x-leftup.x;
  307. heigh = rightdown.y - leftup.y;
  308. srcimg = img(Rect(leftup.x,leftup.y,wid,heigh)).clone();
  309. matchTemplate(srcimg, matchimg[i], dstimg, TM_SQDIFF);
  310. normalize(dstimg,dstimg,0, 1, NORM_MINMAX, -1, Mat());
  311. double minvalue,maxvalue;
  312. Point minLocat,maxLocat;
  313. Point matchLocate,location;
  314. minMaxLoc(dstimg, &minvalue, &maxvalue, &minLocat, &maxLocat, Mat());
  315. matchLocate = minLocat;
  316. location.x = matchLocate.x+leftup.x+(int)matchimg[i].cols/2;
  317. location.y = matchLocate.y+leftup.y+(int)matchimg[i].rows/2;
  318. if (dis_judge(location, matchcenter[i])){
  319. matchcenter[i]=location;
  320. // matchimg[i]=img(Rect(location.x-3,location.y-3,6,6)).clone();
  321. }
  322. rectangle(img,leftup,Point(leftup.x+wid,leftup.y+heigh),Scalar(0,255,0),2);
  323. circle(img,center,2,Scalar(255, 0,0),2);
  324. rectangle(img, Point(matchLocate.x+leftup.x,matchLocate.y+leftup.y),Point(matchLocate.x+matchimg[i].cols+leftup.x,matchLocate.y+matchimg[i].rows+leftup.y),Scalar(0,0,255),2);
  325. }
  326. imshow("test",img);
  327. imwrite ("img.jpg",img);
  328. waitKey(1);
  329. M = findHomography(matchcenter, dstTri, RANSAC);
  330. warpPerspective(img, dst, M,
  331. Size((length), (height)));
  332. for (int i=0;i<37;i++){
  333. P[i].clear();
  334. scale[i] = 0;
  335. }
  336. cvtColor(dst,img_gray,CV_BGR2GRAY);
  337. medianBlur(img_gray,img_gray,3);
  338. threshold(img_gray,img_black,ss_threshold,255,CV_THRESH_BINARY);
  339. // dilate(img_black, img_black, kernel);
  340. findContours(img_black, contours, hierarchy, cv::RETR_LIST, cv::CHAIN_APPROX_SIMPLE);
  341. // imshow ("test2", img_black);
  342. // imwrite ("black.jpg",img_black);
  343. waitKey(1);
  344. vector<RotatedRect> boundRect(contours.size());
  345. vector<double> contArea(contours.size());
  346. for (size_t i = 0; i < contours.size(); i++)
  347. {
  348. //approxPolyDP(Mat(contours[i]), contours_poly[i], 3, true);
  349. boundRect[i] = minAreaRect(Mat(contours[i]));
  350. contArea[i] = contourArea(contours[i]);
  351. }
  352. for (size_t i = 0; i < contours.size(); i++)
  353. {
  354. int t_area = boundRect[i].size.area();
  355. int t_x = boundRect[i].center.x;
  356. int t_y = boundRect[i].center.y;
  357. int add = 0;
  358. for (int j=0;j<3;j++)
  359. for (int k=0;k<4;k++){
  360. if ((t_x>x[k]&&t_x<x[k+1])&&(t_y>y[j]&&t_y<y[j+1])){
  361. int index_num = j*4+k+1;
  362. if (t_area>=14 && contArea[i]>12 && contArea[i]<8000)
  363. {
  364. Scalar color = Scalar(0, 255, 255);
  365. drawContours(dst, contours, i, color, 1);
  366. P[index_num].emplace_back(boundRect[i].center);
  367. boundRect[i].points(rect);
  368. float ca = calc(rect);
  369. scale[index_num] = ca;
  370. // cout<<"长宽比"<<ca<<endl;
  371. }
  372. }
  373. }
  374. add = 12;
  375. for (int j=0;j<3;j++)
  376. for (int k=5;k<9;k++){
  377. if ((t_x>x[k]&&t_x<x[k+1])&&(t_y>y[j]&&t_y<y[j+1])){
  378. int index_num = j*4+(k-5)+1+add;
  379. if (t_area>=14 && contArea[i]>12 && contArea[i]<8000)
  380. {
  381. Scalar color = Scalar(0, 255, 255);
  382. drawContours(dst, contours, i, color, 1);
  383. P[index_num].emplace_back(boundRect[i].center);
  384. boundRect[i].points(rect);
  385. float ca = calc(rect);
  386. scale[index_num] = ca;
  387. }
  388. }
  389. }
  390. add = 24;
  391. for (int j=0;j<3;j++)
  392. for (int k=10;k<14;k++){
  393. if ((t_x>x[k]&&t_x<x[k+1])&&(t_y>y[j]&&t_y<y[j+1])){
  394. int index_num = j*4+(k-10)+1+add;
  395. if (t_area>=14 && contArea[i]>12 && contArea[i]<8000)
  396. {
  397. Scalar color = Scalar(0, 255, 255);
  398. drawContours(dst, contours, i, color, 1);
  399. P[index_num].emplace_back(boundRect[i].center);
  400. boundRect[i].points(rect);
  401. float ca = calc(rect);
  402. scale[index_num] = ca;
  403. }
  404. }
  405. }
  406. }
  408. imshow ("test3", dst);
  409. imwrite ("dst.jpg",dst);
  410. waitKey(1);
  411. for (int i=0;i<37;i++){
  412. if (!P[i].empty() && P[i].size()<3){ //有2个果蝇才处理
  413. flies[i].Trajectory(P[i]);
  414. flies[i].update_state(P[i],time);
  415. flies[i].update_scale(scale[i]);
  416. string text =" ";
  417. string text1 = to_string(i);
  418. // if (flies[i].fly_state == 0)
  419. // text = "0";
  420. // if (flies[i].fly_state == 1)
  421. // if (flies[i].is_court || flies[i].buff_time1/fps>3)
  422. // text = "Court";
  423. // else
  424. // text = "MCourt";
  425. // if (flies[i].fly_state == 2)
  426. // text = "MMate";
  427. // if (flies[i].fly_state == 3)
  428. // text = "Mate";
  429. // putText(dst, text, flies[i].fly2.back(), cv::FONT_HERSHEY_COMPLEX, 1, cv::Scalar(0, 120, 255), 2);
  430. // if (i==32){
  431. // text=to_string(scale[i]);
  432. // putText(dst, text, flies[i].fly2.back(), cv::FONT_HERSHEY_COMPLEX, 1, cv::Scalar(0, 255, 0), 2);
  433. // }
  434. // if (flies[i].stop_judge(1))
  435. // putText(dst, "stop", flies[i].fly1.back(), cv::FONT_HERSHEY_COMPLEX, 1, cv::Scalar(0, 255, 255), 2);
  436. // else
  437. // putText(dst, "move", flies[i].fly1.back(), cv::FONT_HERSHEY_COMPLEX, 1, cv::Scalar(0, 255, 255), 2);
  438. }
  439. }
  440. }
  441. void board::csv_output(int pos) {
  442. cout<<"output to csv"<<endl;
  443. string file = "output_"+to_string(pos+1)+".csv";
  444. float CI;
  445. std::ofstream myfile;
  446. myfile.open (file);
  447. myfile << " ," << "courtship_duration(min),"<<"mate_duration(min),"<<"CI,"<<"court start time(min),"<<"mate start time(min),"<<"mate end time(min)"<<endl;
  448. for (int i = 0; i< 37; i++)
  449. {
  450. if (flies[i].mate_start == 0)
  451. CI = 0;
  452. else
  453. CI = (float)flies[i].courtship_time/(flies[i].mate_start-flies[i].court_start);
  454. myfile << i<< ","<< flies[i].courtship_time/flies[i].fps/60<< ","<<flies[i].mate_time/flies[i].fps/60 << "," << CI <<","<<flies[i].court_start/flies[i].fps/60<<","<<flies[i].mate_start/flies[i].fps/60<<","<<(flies[i].mate_start+flies[i].mate_time)/flies[i].fps/60<<endl;
  455. }
  456. myfile.close();
  457. }

board.cpp at commit c013d35, under MIT · at the source

Overview

Authors: Yutong Song1, Hongyu Miao1, Dongyu Sun1, Xiao Liu1, Fan Jiang2, Xuejiao Yang1, Woo Jae Kim1
ORCID iDs: Woo Jae Kim
  1. HIT Center for Life Sciences, School of Life Science and Technology, Harbin Institute of Technology Harbin China
  2. University of Science and Technology of China Hefei China
Institutions: Harbin Institute of Technology (China); University of Science and Technology of China (China)
Journal: eLife, volume 15, article RP109742
Dates: published online 6 November 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.7554/elife.109742 · PMID 42992539 · PMCID PMC13743079 · OpenAlex W7127572560
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: drosophila (organism), methods / tools (subfield)
Methods: Statistics, Evoked potentials
Keywords: mating behavior, automated behavior analysis, genetic circuit, neural circuit, D. melanogaster
MeSH: Drosophila*, Drosophila melanogaster*, Ethology*, Sexual Behavior, Animal*, Animals, Courtship, Image Processing, Computer-Assisted, Male, Software, Time Factors, Video Recording (* major topic)
Journal subjects: Neuroscience
Topic: Neurobiology and Insect Physiology Research (Cellular and Molecular Neuroscience, Neuroscience), according to OpenAlex
Funding: Harbin Institute of Technology (Startup funds)
Citations: not cited yet (Europe PMC); 61 references in the paper
Research resources: D. melanogaster: wild type: w1118 RRID:BDSC_145, y1 sc1 RRID:BDSC_176, UAS-TNT RRID:BDSC_28838, UAS-shits RRID:BDSC_44222, UAS-GFP.nls RRID:BDSC_4775, D. melanogaster: wild type: Oregon-R RRID:BDSC_5, D. melanogaster: wild type: Canton-S RRID:BDSC_64349, UAS-KCNJ RRID:BDSC_6596, UAS-TrpA1 RRID:BDSC_67132, tub-GAL80ts RRID:BDSC_7017, Df(1)Exel6234 RRID:BDSC_7708, GAL4OK107 RRID:BDSC_854, Yhs-hid RRID:BDSC_8846, rut2080 RRID:BDSC_9404, rut2080; UAS-rut RRID:BDSC_9405, orb2Δ RRID:BDSC_94346, orb2ΔQ RRID:BDSC_94347, UAS-NaChBac RRID:BDSC_9469

Abstract

Male Drosophila courtship behavior is a key model for studying temporal decision-making. While courtship index (CI) is widely used to quantify mating activity, other timing metrics like courtship latency, copulation latency (CL), and mating duration (MD) remain understudied. Traditional methods for quantifying these behaviors are often labor-intensive and prone to human error. In this study, we present a protocol combining a modular chamber system and automated software (DrosoMating) to quantify six key timing metrics during male courtship. Our image-based video analysis enables precise identification of courtship and copulation events, as well as quantification of their timing and duration under controlled conditions. Validation shows <0.05% error rates and 98–99% agreement with manual scoring for CL, CI, and MD. The protocol supports genetic and neural circuit manipulations, detecting subtle genetic, social, and environmental behavioral variations. By minimizing manual effort and standardizing data collection, this approach facilitates scalable, reproducible studies on adaptive trade-offs, learning, and neural mechanisms in mating behavior. This method streamlines timing analysis in male courtship, offering reproducible metrics for behavioral genetics.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repositories

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hcls-kimlab/drosomating

License: MIT
State: the link answers, verified on 9 November 2026
Evidence: files inventoried
Commit: c013d35e93fab73edd4dda032475fa51b8ca6d2b, 20 August 2024
Languages: C++ (6), C/C++ (2), C (2)
Size: 101 files, 10 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 9 November 2026: the link answers
  • 9 November 2026: the link answers
12 files
At the source: github.com/hcls-kimlab/DrosoMating/tree/win-ff

liuxiao916/Fruit_Flies

License: MIT
State: the link answers, verified on 9 November 2026
Evidence: files inventoried
Commit: b3beb2f7a6b2af95f677d1edadfdd249a0c5941a, 12 May 2025
Languages: C++ (6), C/C++ (2), C (2)
Size: 101 files, 10 scripts
Software Heritage: not archived
Found in: “Data availability”
Holds: README, license file
Not found: CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 9 November 2026: the link answers
  • 9 November 2026: the link answers
12 files
At the source: github.com/liuxiao916/Fruit_Flies

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Tracing map

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Data

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The code for the analyses presented in this paper is openly accessible at https://github.com/hcls-kimlab/DrosoMating/tree/win-ff, (copy archived at hcls-kimlab, 2026) and https://github.com/liuxiao916/Fruit_Flies (copy archived at Liu, 2026).

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Version 1, 9 November 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 7 authors, 5 keywords, 11 MeSH terms, 1 funder, 59 references, 18 RRIDs.

Cite

This paper

Song, Y., Miao, H., Sun, D., Liu, X., Jiang, F., Yang, X., & Kim, W. J. (2026). Simple methods to acutely measure multiple timing metrics among the sexual repertoire of male &lt;i&gt;Drosophila&lt;/i&gt;. eLife, 15, RP109742. https://doi.org/10.7554/elife.109742

BibTeX

@article{song2026simple,
author = {Song, Yutong and Miao, Hongyu and Sun, Dongyu and Liu, Xiao and Jiang, Fan and Yang, Xuejiao and Kim, Woo Jae},
title = {{Simple methods to acutely measure multiple timing metrics among the sexual repertoire of male \&lt;i\&gt;Drosophila\&lt;/i\&gt;}},
journal = {eLife},
year = {2026},
month = nov,
volume = {15},
pages = {RP109742},
publisher = {eLife Sciences Publications, Ltd},
issn = {2050-084X},
doi = {10.7554/elife.109742},
url = {https://doi.org/10.7554/elife.109742},
pmid = {42992539},
pmcid = {PMC13743079}
}

RIS

TY - JOUR
AU - Song, Yutong
AU - Miao, Hongyu
AU - Sun, Dongyu
AU - Liu, Xiao
AU - Jiang, Fan
AU - Yang, Xuejiao
AU - Kim, Woo Jae
TI - Simple methods to acutely measure multiple timing metrics among the sexual repertoire of male &lt;i&gt;Drosophila&lt;/i&gt;
T2 - eLife
J2 - eLife
PY - 2026
DA - 2026/11/06
VL - 15
SP - RP109742
SN - 2050-084X
PB - eLife Sciences Publications, Ltd
DO - 10.7554/elife.109742
UR - https://doi.org/10.7554/elife.109742
LA - en
ER -

CSL-JSON

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"id": "10.7554/elife.109742",
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"container-title": "eLife",
"author": [
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"family": "Song",
"given": "Yutong"
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{
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"given": "Hongyu"
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{
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{
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}
],
"container-title-short": "eLife",
"volume": "15",
"page": "RP109742",
"DOI": "10.7554/elife.109742",
"PMID": "42992539",
"PMCID": "PMC13743079",
"ISSN": "2050-084X",
"publisher": "eLife Sciences Publications, Ltd",
"URL": "https://doi.org/10.7554/elife.109742",
"language": "en",
"issued": {
"date-parts": [
[
2026,
11,
6
]
]
}
}

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