测试jupyter notebook导出md格式的兼容性

这部分是python的输出

for x in range(5) :

    print(x)

0

1

2

3

4

from sklearn import tree

feature = [[178,1],[155,0],[177,0],[165,0],[169,1],[160,0],[153,1]]

label = ['male','female','male','female','male','female','male']

clf = tree.DecisionTreeClassifier()

clf = clf.fit(feature, label)

a=clf.predict([[167,0]])

print(a)

b=clf.predict([[152,1]])

print(b)

['female']

['male']

c=clf.predict([[152,0]])

print(c)

['female']

d=clf.predict([[168,0]])

print(d)

['female']

e=clf.predict([[175,0]])

print(e)

['male']

这部分是测试数学公式的输出(LaTeX风格)

$ z = \frac{x}{y} $,

$E = mc^2$

$ \Vert A\Vert_1=\max_{1\le j\le}\sum_{i=1}^m|{a_{ij}}| $

$$ \Vert A\Vert_F=\sqrt{(\sum_{i=1}^m\sum_{j=1}n{| a_{ij}|}^2)} $$

这部分是matlab的输出

% % https://jingyan.baidu.com/article/e75aca85007345142edac6ca.html

close all; clear all; clc

n1=1; [x1,y1]=meshgrid(-2*pi:n1:2*pi);

z1=peaks(x1,y1);

n2=1/5*n1;

[x2,y2]=meshgrid(-2*pi:n2:2*pi);

%二维插值

% z2=interp2(x1,y1,z1,x2,y2,'Nearest');

%  z2=interp2(x1,y1,z1,x2,y2,'Linear');

z2=interp2(x1,y1,z1,y2,x2,'Spline');

mesh(x1,y1,z1-10);hold on;

mesh(x2,y2,z2+10);hold off;

axis([-6,6,-6,6,-15,15])

xlabel('x','fontsize',20);

ylabel('y','fontsize',20);

zlabel('z','fontsize',20);

1+2

ans =

     3

1+3

ans =

     4