很多刚玩github对于contribution settings 颜色存有疑问,比如什么时候是深绿色,什么时候是浅绿色。
workflow 填入你的GitHub用户名 选择configure 4.填写代码 你应该会看到这个页面 去掉原来的所有内容,填入以下内容 # GitHub Action for generating a contribution /assets/github-contribution-grid-snake.gif svg_out_path: . /assets/github-contribution-grid-snake.svg - name: Push to GitHub uses: EndBug/add-and-commit @v7.2.1 with: branch: main message: 'Generate Contribution Snake' 5.运行 [](https://raw.githubusercontent.com/你的GitHub用户名/你的GitHub用户名/main/assets/github-contribution-grid-snake.svg
具体不再一个一个参数细讲,我们直接看实例: plot_contribution(nmf_res$contribution,nmf_res$signature,mode= "relative") ? plot_contribution(nmf_res$contribution,nmf_res$signature,mode= "absolute") ? plot_contribution(nmf_res$contribution,nmf_res$signature,mode= "absolute",index = c(1,2)) ? plot_contribution(nmf_res$contribution,nmf_res$signature,mode= "absolute",coord_flip = TRUE) ? ## Contribution heatmap without sampleclustering plot_contribution_heatmap(nmf_res$contribution,
=perioddata['战斗ID'].drop_duplicates().count() s_t=(contribution/number_of_battles) print (contribution ,number_of_battles,s_t) return (contribution,number_of_battles,s_t) 调用函数,计算出需要的数据 contribution_1, _1(本月战功),contribution_2(上月战功),contribution_3(上年同期战功) 第2行的数据项填充为'number_of_battles_1(本月战斗次数),number_of_battles _1,contribution_2,contribution_3],[number_of_battles_1,number_of_battles_2,number_of_battles_3],[a_n_ (Same_data) #分别计算上年同期的战功,战斗次数,每场战功 report=pd.DataFrame([[contribution_1,contribution_2,contribution
配置代码 # GitHub Action for generating a contribution graph with a snake eating your contributions. /assets/github-contribution-grid-snake.gif svg_out_path: . /assets/github-contribution-grid-snake.svg - name: Push to GitHub uses: EndBug/add-and-commit 3、引入 svg 动画 上面的 Github Actions 执行完毕后,会在当前的仓库中添加一个assets文件夹,文件夹中有 github-contribution-grid-snake.gif 和github-contribution-grid-snake.svg两个文件。
-- Snake Code Contribution Map 贪吃蛇代码贡献图 --> <picture> <source media="(prefers-color-scheme: dark )" srcset="https://cdn.jsdelivr.net/gh/Damon-Liu-code/Damon-Liu-code/profile-snake-contrib/github-<em>contribution</em>-grid-snake-dark.svg : ${{ github.repository_owner }} outputs: | dist/profile-snake-contrib/github-<em>contribution</em>-grid-snake.svg dist/profile-snake-contrib/github-<em>contribution</em>-grid-snake-dark.svg? palette=github-dark - name: push github-<em>contribution</em>-grid-snake.svg to the output
# 这个时候的pca图非常的原始,丑爆了 pca <- PCA(data) print(pca) # 主要输出这15个结果 # 每个变量对每个主成分的贡献程度保存在pca$var$contrib contribution <- as.data.frame(pca$var$contrib) colnames(contribution) <- c('PC1', 'PC2', 'PC3', 'PC4', 'PC5') contribution <- cbind(gene = rownames(contribution), contribution) head(contribution) # write.table(contribution, /results/Figure 1B PCA contribution.txt', # row.names = F, col.names = T, quote = F, sep
Contribution Points 4.3. VS Code API 1. VSCode 插件能干啥? Contribution Points: static declarations that you make in the package.json Extension Manifest to extend Contribution Points Contribution Points are a set of JSON declarations that you make in the contributes Your extension registers Contribution Points to extend various functionalities within Visual Studio Code
= TRUE) 可视化NMF结果 colnames(nmf_res$signatures) <- c("Signature A", "Signature B") rownames(nmf_res$contribution (nmf_res$contribution, nmf_res$signature, mode = "relative" ) plot_contribution_heatmap(nmf_res$contribution (fit_res$contribution, coord_flip = FALSE, mode = "absolute" ) Bootstrapped (contri_boots) plot_bootstrapped_contribution(contri_boots, mode = " (nmf_res_region$contribution, cluster_samples = TRUE,
db.Column(db.String(255), nullable=False) energy_value = db.Column(db.Integer, default=0) contribution_value ) user = User.query.get(user_id) user.energy_value += energy_value_reward user.contribution_value += contribution_value_reward user.shared_value += shared_value_reward # 创建订单记录 python复制代码# 静态释放(简化示例,实际应定期运行) def static_release(): total_contribution = User.query.sum(User.contribution_value ) for user in User.query.all(): user_share = (user.contribution_value / total_contribution
例如,运行以下命令以创建一个名为 "my-contribution" 的分支: git checkout -b my-contribution 或者直接拉起原有分支: git clone -b 分支名称 使用以下命令: git push origin my-contribution 这会将你的修改推送到名为 "my-contribution" 的分支上。
主要包括如下几部分: Site Type 8 mer > 7 mer-m8 > 7 mer-1a; 3' pairing contribution:除了与 miRNA seed 区域配对,与 miRNA12 -16nt 的配对也有可能对 miRNA target 的功能产生影响; local AU contribution:AU rich 的区域更有可能有功能; position contribution Type:配对类型(8mer、7 mer-m8、7 mer-1a) UTR start:UTR 起始位置 UTR end:UTR 终止位置(起始和终止的长度大概是 6nt) 3' pairing contribution : 3' 端配对的贡献值 local AU contribution : AU rich 区域的贡献值 position contribution : 结合位点的贡献值 context score :
github_user_name>) contributions graph, output a svg animation at <svg_out_path> - name: Generate github-contribution-grid-snake.svg github_user_name: ${{ github.repository_owner }} outputs: | dist/github-contribution-grid-snake.svg dist/github-contribution-grid-snake-dark.svg? [HuiDBK's github activity graph](https://raw.githubusercontent.com/HuiDBK/HuiDBK/output/github-contribution-grid-snake.svg )换成自己Github用户名就行https://raw.githubusercontent.com/HuiDBK/HuiDBK/output/github-contribution-grid-snake.svg
+ h]; h++); lcp[rank[i] - 1] = h; } } int stack[MAX_N][2]; // 0放lcp,1放个数 long long contribution ans = 0; for (int i = 0; i < n; i++) { if (lcp[i] < K) { top = contribution is_s1 && sa[i] > l1)) { ++size; contribution += lcp[i] - 0 && lcp[i] <= stack[top - 1][0]) {// 单调减栈,栈顶最小 --top; contribution is_s1 && sa[i + 1] < l1)) // 与s2组合 { ans += contribution; }
= sum(score)) contributions %>% top_n(25, abs(contribution)) %>% mutate(word = reorder(word, contribution )) %>% ggplot(aes(word, contribution, fill = contribution > 0)) + ggtitle('Words with the greatest not_words %>% mutate(contribution = n * score) %>% arrange(desc(abs(contribution))) %>% head(20 = n * score, word2 = reorder(paste(word2, word1, sep = "__"), contribution)) %>% group_by (word1) %>% top_n(12, abs(contribution)) %>% ggplot(aes(word2, contribution, fill = n * score > 0
其中最主要的设置是 Activation Events(插件的激活时机) 和 contribution points (插件的能力)。接下来我们主要看看这两个配置具体是什么意思。 points 需要在 package.json 中声明的另一个重要字段就是 contribution points。 contribution points描述了当前插件支持哪些能力,以及对应能力的配置。 由于 vscode 禁止直接操作dom,往 UI 中插入功能的正确方式是声明贡献点。 目前 vscode 支持的贡献点 举个例子 接下来我们来看几个插件的 contribution points 声明 超越鼓励师 支持通过 commands 触发杨超越的提醒,同时可以配置提醒出现的时机, points 的更多说明可以参考: https://code.visualstudio.com/api/references/contribution-points 编程语言支持 那么,要怎么给 vscode
github_user_name>) contributions graph, output a svg animation at <svg_out_path> - name: generate github-contribution-grid-snake.svg github_user_name: ${{ github.repository_owner }} outputs: | dist/github-contribution-grid-snake.svg dist/github-contribution-grid-snake-dark.svg? raw.githubusercontent.com/<github_user>/<repository>/<target_branch>/<file> , or as github page - name: push github-contribution-grid-snake.svg [](https://raw.githubusercontent.com/javadog-net/javadog-net/output/github-contribution-grid-snake.svg
If you like the project, please ask star, fork and Contribution! :D Thanks!! Contribution Opens for everybody to contribute to the repository, including typo or different perspectives I welcome your contribution under the identical contribution guide of kamranahmedse/developer-roadmap
"Contribution" shall mean any work of authorship, including the original version of the Work and any "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution (s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was (s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was (s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was
methods.append(method_got) 计算每个函数对该次出错的贡献 贡献 考虑一个函数与直接导致错误的函数(输入的堆栈中的原始栈帧)的距离(语法树中的距离)、其原始栈帧到栈顶的距离以及其置信度 Contribution = Confidence ∗ 1frameNumber+1 ∗ (NUMBER_OF_ITERATION−relevanceDist)\mathit{Contribution}\ =\ \mathit {Confidence\ *\ \frac{1}{frameNumber+1}\ *\ \left( NUMBER\_OF\_ITERATION - relevanceDist \right)}Contribution 同时超参数d使得PropensistyForChange始终小于1,保证每次置信度更新时都会更趋近于1(代码留存的时间越长,认为其置信度越高) 计算获取一个函数的主要贡献者 commiters = [] contribution_rate = 1 for commit in related_commits: weight = commit.commiter.weight weight += contribution_rate