import pylab as plt plt.plot(x, y) plt.show() 2. 在一张图纸里绘制多个图形 (1)注意这里不需要matlab的hold on操作。 plt.plot(x, y) plt.plot(x, y * 2) plt.show() (2)更丰富绘图:顺序是——颜色、点的形状、线型 plt.plot(x, y, 'y*-') #画图,颜色yellow,点为*,线型为- 常见的...
import matplotlib.pyplot as plt import numpy as np x = np.linspace(-1, 1, 50) y1 = x * x + 1 y2 = 2 * x plt.figure(num=1) plt.plot(x, y1) plt.figure(num=2, figsize=(8, 5)) plt.plot(x, y2) plt.plot(x, y1, color='red', linewidth='1.0', linestyle='--') plt...
How To Make tSNE plot in R - Data Viz with Python and R (http://datavizpyr.com) How to make UMAP plot in R - Data Viz with Python and R (http://datavizpyr.com) How To Make PCA Plot with R - Data Viz with Python and R (http://datavizpyr.com) 理解⼀种疾病的某种现象仅...
Z=Z.rename(columns={0:"dim1",1:"dim2"})Z['state']=df['state'].astype('str').astype('category')sns.scatterplot(x="dim1",y="dim2",hue="state",data=Z,edgecolors='none',alpha=0.2,palette='husl')sns.despine()plt.tight_layout()plt.xlabel('Dimension 1')plt.ylabel('Dimension ...
cmap = plt.get_cmap('viridis')colors = [cmap(i) for i in np.linspace(0, 1, len(np.unique(y)))] class_distr = []# Plot the different class distributionsfor i, l in enumerate(np.unique(y)):_x1 = x1[y == l]_x2 = x2[y == ...
sns.scatterplot(data=data_pca, hue='class', x='1st_component', y='2nd_component') plt.show()第5步-t-SNE降维与可视化 （1）导入所需的库 from sklearn.manifold import TSNE （2）t-SNE降维 tsne = TSNE(n_components=2)tsne.fit(X_std)（3）可视化t-SNE降维分类结果 X_tsne = pd.DataFrame...
tSNE Plot 参考 How To Make tSNE plot in R - Data Viz with Python and R (datavizpyr.com) How to make UMAP plot in R - Data Viz with Python and R (datavizpyr.com) How To Make PCA Plot with R - Data Viz with Python and R (datavizpyr.com) 往期内容 CNS图表复现|生信分析|R绘图...
TSNE的可视化特征结果 一、可视化特征或embeddings 1.1 二维的值 对bert输出层的可视化(这是个二维的,batch, hidden_state) codeantenna 1.2 三维的值 对bert的last_state进行可视化(这个是三维的,batch,seq_length, hidden_state) deftsne_plot_similar_words_png(title, embedding_clusters, a, filename=""): ...
plt.plot((0, 55), (0.005, 0.005), 'r--') plt.text(36, 0.003, r'$q_{ij}$') plt.text(55, 0.007, r'$p_{ij}$') plt.title("probability of distance") plt.xlabel("distance") plt.ylabel("probability") plt.legend() plt.savefig("sne_norm_t_dist_cost.png") ...
视频中提到的参考链接是 https://datavizpyr.com/how-to-make-tsne-plot-in-r/ 这个链接还有许多其他python和R语言的内容 大家可以自己找来看看欢迎大家关注我的公众号 小明的数据分析笔记本 公众号分享的内容包括1、R语言和python做数据分析和数据可视化的简单小例子;2、园艺植物相关的转录组、基因组学文献阅读...