win+1: 快速建立便签 ctrl+N: 新建便笺 ctrl+d： 删除当前便笺 win+3: Todo list ctrl+win+d: 快速建立新的桌面 win+tab: 切换桌面的工具栏 ctrl+win+ <- or ->： 快速切换桌面到左或者右 shift+win + <- or ->: 快速切换副屏或主屏

另外，这周终于获得了电竞之星卡背，开心一下下哈哈哈哈

折腾了有一个小时，我服了 第一步：在Word 开始界面 Ctrl + Shift + Alt + S 设置标题 第二部: 在页眉切换域代码 {STYLEREF "标题 1" \n * MERGEFORMAT}{STYLEREF "标题 1" * MERGEFORMAT} 然后点击 更新域

:laughing:

We attribute these discrepancies to the limited number of stations in the area. the computational cost of the UKI is primarily dictated by the size of the model ensembles associated with the sigma points multiplied by the number of iterations. With 19 model parameters, UKI conducts 39 model evaluations in each iteration, and we run 10 iterations to obtain the final result, thus processing 380 model evaluations in each prior setting. Through extensive testing, it demonstrates that UKI requires minimal prior information about S-wave velocity for joint inversion of RF and SWD, although some prior means regarding layer thickness are necessary. Conversely, the trans-dimensional methods excel in this aspect, they do not require specific layer counts but allows for a general range. Where \mu_n represent mean and covairan of Gaussian distribution pn in the nth iteration, \mu_n+1,C_n+1 denote the updates in the n+1th iteration.

This article requires a password to view.

发微博好像不太合适，来写博客更好一些。 2023再见😁 2023年吃不上肉本家了... 吱猪的2024年第一顿，浙大走起！

放个电视看一看

最近几天总算把服务器折腾好了，来庆祝一下伊立扎德奶站的重新开张🎇🎇🎇 附上最近的学生年会报告😁😁😁

plot 线型 linestyle '-'/':'/'--'/'-.'/' ' 共用坐标轴 axd["B"].set_ylim(axd["A"].get_ylim()) 自己设颜色 cmap = plt.cm.RdYlBu # define the colormap ## extract all colors from the .jet map cmaplist = [cmap(i) for i in range(cmap.N)] cn = cmap.N nhv = len(HVV) for i in range(nhv): abc=ax.plot(thv_series,HVV[i],c=cmaplist[cn//nhv*i]) 整体调整字体 parameters = {'axes.labelsize': 10, 'axes.titlesize': 35} plt.rcParams.update(parameters) 图片保存 bbox_inches=’tight’ 对坐标轴的细更改 from matplotlib.ticker import FormatStrFormatter 1. starte, ende = axd["E"].get_ylim() axd["E"].yaxis.set_ticks(np.linspace(starte, ende,6) axd["E"].yaxis.set_major_formatter(FormatStrFormatter('%.e')) 2. axd["F"].set_xlim(0,22) starte, ende = axd["F"].get_xlim() axd["F"].xaxis.set_ticks(np.arange(starte, ende,2)) axd["F"].xaxis.set_major_formatter(FormatStrFormatter('%d')) 调整坐标轴之间的间距 fig.tight_layout(w_pad=3) plt 初始化 parameters = {'axes.labelsize': 35, 标号刻度 'axes.titlesize': 35, 'xtick.labelsize': 20, x轴刻度size 'ytick.labelsize': 20, y轴刻度size 'font.sans-serif': "Arial", 'legend.fontsize': 16, 'legend.handlelength': 1.1, 'legend.shadow':0, 'legend.edgecolor':'k', 'legend.framealpha':0.90} 手动更改坐标轴 ！！！ 重要 ll, bb, ww, hh = axd["H"].get_position().bounds axd["H"].set_position([ll- 2 * ww, bb, ww, hh]) 颠倒图例顺序 handles, labels = axd["E"].get_legend_handles_labels() axd["E"].legend(handles[::-1],labels[::-1],fontsize=15,loc=4) 去除最后一个图例 han, lab = ax.get_legend_handles_labels() ax.legend(han[:-1], lab[:-1], loc=3 删除一个图 axd["I"].remove() 设置刻度为平均间隔 ## 设置刻度间隔 x_major_locator=MultipleLocator(30) ## 设置刻度 # axd["A"].xaxis.set_major_locator(x_major_locator) 设置确定的刻度(如台站距离) axd["A"].set_xticks(Dist,minor=False); axd["A"].set_xticklabels(stts,fontsize=10,rotation=270); 设置刻度字体大小 axd["C"].tick_params(labelsize=ftt) #刻度字体大小20 设置 log 刻度 axd["F"].set_yscale('log') 刻度是整数 from matplotlib.ticker import MaxNLocator plt.gca().xaxis.set_major_locator(MaxNLocator(integer=True)) plt.gca().yaxis.set_major_locator(MaxNLocator(integer=True))