From 93b74c642f3975ddf313b6f702b5a4f9782c9bc2 Mon Sep 17 00:00:00 2001
From: guanjihuan <34735497+guanjihuan@users.noreply.github.com>
Date: Fri, 25 Jun 2021 11:35:19 +0800
Subject: [PATCH] Update sympy_example.py

---
 .../2021.06.24_sympy_example/sympy_example.py | 35 ++++++++++---------
 1 file changed, 19 insertions(+), 16 deletions(-)

diff --git a/language_learning/2021.06.24_sympy_example/sympy_example.py b/language_learning/2021.06.24_sympy_example/sympy_example.py
index e6c0e1a..988f45e 100644
--- a/language_learning/2021.06.24_sympy_example/sympy_example.py
+++ b/language_learning/2021.06.24_sympy_example/sympy_example.py
@@ -16,8 +16,6 @@ print(z**2)
 print()
 
 
-
-
 # 替换（Substitution）
 print('变量替换：')
 expression_1 = x**2+1
@@ -26,8 +24,6 @@ print(value_1)
 print()
 
 
-
-
 # 字符串转成符号表达式
 print('字符串转成符号表达式：')
 expression_string = 'x**3+1'
@@ -39,8 +35,6 @@ print(value_2)
 print()
 
 
-
-
 # 简化表达式
 print('简化表达式：')
 expression_3 = sympy.simplify(sympy.sin(x)**2 + sympy.cos(x)**2)  # 使用sympy.simplify()
@@ -48,8 +42,6 @@ print(expression_3)
 print()
 
 
-
-
 # 符号矩阵
 print('符号矩阵：')
 a, b = sympy.symbols('a b')
@@ -58,21 +50,32 @@ print(matrix)
 print()
 
 
-
-
+sympy.init_printing(use_unicode=True)
 # 符号矩阵的特征值和特征向量
 print('符号矩阵的特征值和特征向量：')
 eigenvalue = matrix.eigenvals()  # 使用.eigenvals()方法
+print('特征值\n', eigenvalue, '\n')
+sympy.pprint(eigenvalue)
+print('\n', sympy.pretty(eigenvalue))
+print()
+
 eigenvector = matrix.eigenvects() # 使用.eigenvects()方法
-print('特征值\n', eigenvalue)
-print('特征向量\n', eigenvector)
+print('特征向量\n', eigenvector, '\n')
+sympy.pprint(eigenvector)
+print('\n', sympy.pretty(eigenvector))
 print()
 
 P, D = matrix.diagonalize()  # 使用.diagonalize()方法
-print('特征值\n', D)
-print('特征向量\n', P)
-print('特征值\n', D.subs(a, -4).subs(b, 2))
-print('特征向量\n', P.subs(a, -4).subs(b, 2))
+print('特征值\n', D, '\n')
+print(sympy.pretty(D), '\n')
+print('特征向量\n', P, '\n')
+print(sympy.pretty(P), '\n')
+print()
+
+print('特征值\n', D.subs(a, -4).subs(b, 2), '\n')
+print(sympy.pretty(D.subs(a, -4).subs(b, 2)), '\n')
+print('特征向量\n', P.subs(a, -4).subs(b, 2), '\n')
+print(sympy.pretty(P.subs(a, -4).subs(b, 2)), '\n')
 print()
 
 # 和numpy对比