category
This commit is contained in:
@@ -0,0 +1,118 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/417
|
||||
"""
|
||||
|
||||
|
||||
# 第一部分：Python基本操作（循环，判断，函数，文件写入）
|
||||
print('\n第一部分：Python基本操作（循环，判断，函数，文件写入）\n') # \n代表换行
|
||||
|
||||
for i in range(5): # 循环（这里只举例for循环，还有其他循环）
|
||||
print('我是循环产生的数：', i) # Python中没有end，因此每个语句的缩进很重要
|
||||
if i == 2: # 判断
|
||||
print('判断：我是第三个数 2')
|
||||
else:
|
||||
pass # pass代表不执行任何语句，用于占位，可以之后再补充，不然空着会报错
|
||||
print() # 输出空一行
|
||||
|
||||
def fun0(arg): # 定义函数
|
||||
print('我是函数中的内容，参数值为：', arg)
|
||||
return arg*2 # 返回值
|
||||
|
||||
print('函数返回值：', fun0(5)) # 调用函数
|
||||
print()
|
||||
|
||||
def main(): # “主函数”，其实也是一个普通的函数，也可以起其他名字
|
||||
print('我是主函数中的内容。')
|
||||
print()
|
||||
|
||||
if __name__ == '__main__': # 如果直接运行本文件，那么执行以下内容。如果是import本文件，那么不执行。
|
||||
main()
|
||||
|
||||
# 关于类class，这里不举例了。科学计算中主要还是面向过程，面向对象用的比较少。
|
||||
|
||||
# 文件写入
|
||||
# 第一种方式
|
||||
with open('test1.txt', 'w') as f1: # 其中'w'为重新写入，改为'a'是补充内容
|
||||
f1.write(str(100)+'\n这是第一种方式写入文件') # str()为转换成字符串
|
||||
# 第二种方式
|
||||
f2 = open('test2.txt', 'w') # 打开文件
|
||||
f2.write(str(200)+'\n这是第二种方式写入文件') # 写入文件
|
||||
f2.close() # 关闭文件
|
||||
print('已写入文件！')
|
||||
print()
|
||||
|
||||
|
||||
|
||||
|
||||
# 第二部分：Numpy库中常用的语句
|
||||
print('\n\n\n第二部分：Numpy库中常用的语句\n')
|
||||
import numpy as np
|
||||
|
||||
print('零矩阵：\n', np.zeros((2, 3))) # 注意np.zeros()里需要填元组，因此显示的是两个括号
|
||||
print('单位矩阵：\n', np.identity(3)) # 3行3列的单位矩阵,或者可以用np.eye()
|
||||
print('把一维数组按对角矩阵排列：\n', np.diag([1, 3, 5]))
|
||||
print()
|
||||
|
||||
print('指定步长的等差数列：\n', np.arange(1, 5, .5)) # 区间是左闭右开[1, 5)，步长为0.5
|
||||
print('指定个数的等差数列：\n', np.linspace(-2, 2, 5)) # 区间是左闭右闭[-2, 2], 数量是5
|
||||
print()
|
||||
|
||||
print('随机数：\n', np.random.uniform(-2, 2)) # 随机浮点数
|
||||
print('随机整数：\n', np.random.randint(-10, 10)) # 区间是左闭右开[-10, 10)
|
||||
print()
|
||||
|
||||
# 随机数除了使用numpy库，也使用random生成
|
||||
import random
|
||||
print('使用random库的随机数：\n', random.uniform(-2,2)) # 随机浮点数
|
||||
print('使用random库的随机整数：\n', random.randint(-10, 10)) # 区间是左闭右闭[-10, 10]
|
||||
print()
|
||||
|
||||
print('数组从小到大排列：\n', np.sort([1, 7, 0, 3]))
|
||||
print('数组从小到大排列对应的索引：\n', np.argsort([1, 7, 0, 3])) # 注意Python中下标是从0开始的
|
||||
print()
|
||||
|
||||
matrix0 = np.array([[1, 2+9j, 3], [2, 5, 7]]) # numpy数组
|
||||
print('矩阵0：\n', matrix0)
|
||||
print('矩阵的维度：\n', matrix0.shape) # 查看矩阵的维度
|
||||
print('矩阵的行数：\n', matrix0.shape[0]) # 查看矩阵的行数
|
||||
print('矩阵的列数：\n', matrix0.shape[1]) # 查看矩阵的列数
|
||||
print('矩阵转置：\n', matrix0.transpose()) # 矩阵转置
|
||||
print('矩阵转置共轭：\n', matrix0.transpose().conj()) # 矩阵转置共轭
|
||||
print()
|
||||
|
||||
matrix1 = np.array([[3, 5], [2, 7]])
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix1) # 求本征值，本征向量
|
||||
print('矩阵1：\n', matrix1)
|
||||
print('本征值：\n', eigenvalue)
|
||||
print('本征向量：\n', eigenvector) # 列向量为本征向量
|
||||
print('逆矩阵：\n', np.linalg.inv(matrix1)) # 求逆
|
||||
print('计算行列式：\n', np.linalg.det(matrix1)) # 行列式
|
||||
print()
|
||||
|
||||
matrix2 = np.array([[1, 2], [3, 4]])
|
||||
print('矩阵2：\n', matrix2)
|
||||
print('矩阵1和矩阵2相乘：\n', np.matmul(matrix1, matrix2)) # 矩阵乘积，或者可以用np.dot()
|
||||
print()
|
||||
|
||||
a = np.array([1, 2])
|
||||
print('numpy数组a=', a)
|
||||
b = np.array([3, 4])
|
||||
print('numpy数组b=', b)
|
||||
c = np.append(a, b, axis=0) # 增加元素
|
||||
print('numpy数组增加元素：\n', c)
|
||||
d = np.append([a], [b], axis=0) # 增加行（列数要相同），或者用np.row_stack(([a], [b]))
|
||||
print('numpy数组增加行：\n', d)
|
||||
e = np.append([a], [b], axis=1) # 增加列（行数要相同），或者用np.column_stack(([a], [b]))
|
||||
print('numpy数组增加列：\n', e)
|
||||
print('重新观察：a=', a)
|
||||
print('重新观察：b=', b)
|
||||
print()
|
||||
|
||||
|
||||
# 如果不是numpy数组，原python数组可以直接用以下方法增加元素
|
||||
c = [100, 200]
|
||||
print('python数组c=', c)
|
||||
c.append(300)
|
||||
print('增加元素后，c=', c)
|
||||
print()
|
||||
@@ -0,0 +1,77 @@
|
||||
import tensorflow as tf
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
||||
def add_layer(inputs, in_size, out_size, activation_function=None): # 定义一层的所有神经元
|
||||
Weights = tf.Variable(tf.random_normal([in_size, out_size])) # 定义Weights为tf变量，并给予初值
|
||||
biases = tf.Variable(tf.zeros([1, out_size]) + 0.1) # 定义biases为tf变量，并给予初值
|
||||
Wx_plus_b = tf.matmul(inputs, Weights) + biases # 得分
|
||||
if activation_function is None: # 没有激活函数
|
||||
outputs = Wx_plus_b
|
||||
else:
|
||||
outputs = activation_function(Wx_plus_b) # 使用激活函数
|
||||
return outputs # 返回该层每个神经元的输出值（维度为out_size）
|
||||
|
||||
|
||||
# 产生训练的数据
|
||||
x_data = np.linspace(-1, 1, 300, dtype=np.float32)[:, np.newaxis] # 产生数据，作为神经网络的输入数据。注：[:, np.newaxis]是用来增加一个轴，变成一个矩阵。
|
||||
noise = np.random.normal(0, 0.05, x_data.shape).astype(np.float32) # 产生噪声
|
||||
y_data = np.square(x_data) - 0.5 + noise # x_data加上噪声，作为神经网络的输出数据。
|
||||
print(x_data.shape) # 查看数据维度
|
||||
print(noise.shape) # 查看数据维度
|
||||
print(y_data.shape) # 查看数据维度
|
||||
print() # 打印输出空一行
|
||||
|
||||
|
||||
# 神经网络模型的建立
|
||||
xs = tf.placeholder(tf.float32, [None, 1]) # 定义占位符，为神经网络训练的输入数据。这里的None代表无论输入有多少数据都可以
|
||||
ys = tf.placeholder(tf.float32, [None, 1]) # 定义占位符，为神经网络训练的输出数据。
|
||||
l1 = add_layer(xs, 1, 10, activation_function=tf.nn.relu) # 增加一个隐藏层
|
||||
prediction = add_layer(l1, 10, 1, activation_function=None) # 输出层
|
||||
loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys - prediction), reduction_indices=[1])) # 损失函数
|
||||
train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss) # 梯度下降
|
||||
init = tf.global_variables_initializer() # 变量初始化
|
||||
|
||||
# 画出原始的输入输出数据点图
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(1, 1, 1)
|
||||
ax.scatter(x_data, y_data)
|
||||
plt.ion() # 开启交互模式
|
||||
plt.show() # 显示图像
|
||||
|
||||
# 训练神经网络模型
|
||||
sess = tf.Session() # 启动一个会话
|
||||
sess.run(init) # 初始化变量
|
||||
for i in range(1000): # 训练1000次
|
||||
sess.run(train_step, feed_dict={xs: x_data, ys: y_data}) # 喂数据，梯度下降循环1000次。
|
||||
if i % 50 == 0: # 每训练50次画一下图
|
||||
try: # to visualize the result and improvement
|
||||
ax.lines.remove(lines[0])
|
||||
except Exception:
|
||||
pass
|
||||
prediction_value = sess.run(prediction, feed_dict={xs: x_data}) # 神经网络预测的值
|
||||
print('loss=', sess.run(loss, feed_dict={xs: x_data, ys: y_data})) # 打印输出，查看损失函数下降情况
|
||||
print('prediction=', sess.run(prediction, feed_dict={xs: [x_data[0, :]]})) # # 打印输出神经网络预测的值
|
||||
print() # 打印空一行
|
||||
lines = ax.plot(x_data, prediction_value, 'r-', lw=5) # 画出预测的值，用线连起来
|
||||
plt.pause(.1) # 暂停0.1，防止画图过快看不清。
|
||||
plt.ioff() # 关闭交互模式，再画一次图。作用是不让图自动关掉。
|
||||
lines = ax.plot(x_data, prediction_value, 'r-', lw=5)
|
||||
plt.show()
|
||||
|
||||
|
||||
# 保存训练好的神经网络模型tf.train.Saver()
|
||||
saver = tf.train.Saver()
|
||||
save_path = saver.save(sess, "my_net/save_net.ckpt") # 保存模型
|
||||
print("Save to path: ", save_path)
|
||||
print()
|
||||
sess.close() # 关闭会话
|
||||
|
||||
|
||||
# 调用神经网络模型，来预测新的值
|
||||
with tf.Session() as sess2:
|
||||
saver.restore(sess2, "my_net/save_net.ckpt") # 提取模型中的所有变量
|
||||
print(y_data[0, :]) # 输出的原始值
|
||||
print(sess2.run(prediction, feed_dict={xs: [x_data[0, :]]})) # 预测值
|
||||
|
||||
@@ -0,0 +1,39 @@
|
||||
import tensorflow as tf # 导入tensorflow
|
||||
|
||||
greeting = tf.constant('Hello Google Tensorflow!') # 定义一个常量
|
||||
|
||||
# 第一种方式
|
||||
sess = tf.Session() # 启动一个会话
|
||||
result = sess.run(greeting) # 使用会话执行greeting计算模块
|
||||
print(result) # 打印显示
|
||||
sess.close() # 关闭会话
|
||||
|
||||
# 第二种方式
|
||||
with tf.Session() as sess: # 启动一个会话
|
||||
print(sess.run(greeting)) # 打印显示
|
||||
|
||||
|
||||
# 例子1：
|
||||
matrix1 = tf.constant([[1., 3.]]) # 定义常数矩阵1 tf.constant()
|
||||
matrix2 = tf.constant([[2.], [2.]]) # 定义常数矩阵2 tf.constant()
|
||||
product = tf.matmul(matrix1, matrix2) # 矩阵乘积 tf.matmul()
|
||||
linear = tf.add(product, tf.constant(2.)) # 矩阵乘积后再加上一个常数 tf.add()
|
||||
with tf.Session() as sess: # 启动一个会话 tf.Session()
|
||||
print(sess.run(matrix1)) # 执行语句并打印显示 tf.Session().run
|
||||
print(sess.run(linear)) # 执行语句并打印显示 tf.Session().run
|
||||
print(linear) # 直接打印是不能看到计算结果的，因为还未执行，只是一个张量。这里打印显示的结果是：Tensor("Add:0", shape=(1, 1), dtype=float32)
|
||||
|
||||
|
||||
# 例子2：变量tf.Variable()
|
||||
state = tf.Variable(3, name='counter') # 变量tf.Variable
|
||||
init = tf.global_variables_initializer() # 如果定义了变量,后面一定要有这个语句，用来初始化变量。
|
||||
with tf.Session() as sess:
|
||||
sess.run(init) # 变量一定要初始化变量
|
||||
print(sess.run(state)) # 执行语句并打印显示
|
||||
|
||||
# 例子3：占位符tf.placeholder()，用来临时占坑，需要用feed_dict来传入数值。
|
||||
x1 = tf.placeholder(tf.float32)
|
||||
x2 = tf.placeholder(tf.float32)
|
||||
y = x1 + x2
|
||||
with tf.Session() as sess:
|
||||
print(sess.run(y, feed_dict={x1: 7, x2: 2}))
|
||||
@@ -0,0 +1,359 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/703
|
||||
"""
|
||||
|
||||
import pygame
|
||||
import random
|
||||
import math
|
||||
import numpy as np
|
||||
|
||||
# 参数
|
||||
screen_width = 1500 # 屏幕宽度
|
||||
screen_height = 900 # 屏幕高度
|
||||
map_width = screen_width*4 # 地图的大小
|
||||
map_height = screen_height*4 # 地图的大小
|
||||
number_enemy = map_width*map_height/500000 # 敌人的数量
|
||||
number_dots = map_width * map_height / 50 # 点点的数量
|
||||
max_show_size = 100 # 球显示的最大半径（屏幕有限，球再增大时，改变的地图比例尺寸）
|
||||
|
||||
my_value = 1000 # 我的初始值
|
||||
enemy_value_low = 500 # 敌人的初始值（最低）
|
||||
enemy_value_high = 1500 # 敌人的初始值（最高）
|
||||
dot_value = 30 # 点点的值（地上的豆豆/食物值）
|
||||
my_speed = 10 # 我的球运动的速度
|
||||
speed_up = 20 # 按下鼠标时加速
|
||||
speed_enemy = 10 # 敌人球正常运动速度
|
||||
speed_enemy_anomaly = 20 # 敌人突然加速时的速度（速度异常时的速度）
|
||||
anomaly_pro = 0.5 # 敌人加速的概率
|
||||
change_pro = 0.05 # 敌人移动路径变化的概率，也就是1/change_pro左右会变化一次
|
||||
eat_percent = 0.9 # 吃掉敌人的球，按多少比例并入自己的体积，1对应的是100%
|
||||
loss = 0.001 # 按比例减小体重（此外越重的减少越多，10万体积损失值为loss的一倍）
|
||||
enemy_bigger_pro = 0.0005 # 敌人的值增加了我的球的值的enemy_bigger_rate倍的几率
|
||||
enemy_bigger_rate = 0.1 # 增加我的球的体积的enemy_bigger_rate倍
|
||||
|
||||
|
||||
class Color(object): # 定义颜色的类
|
||||
@classmethod # 加了这个可以不需要把实例化，能直接调用类的方法
|
||||
def random_color(cls): # cls, 即class，表示可以通过类名直接调用
|
||||
red = random.randint(0, 255)
|
||||
green = random.randint(0, 255)
|
||||
blue = random.randint(0, 255)
|
||||
return red, green, blue
|
||||
|
||||
|
||||
class Ball(object): # 定义球
|
||||
def __init__(self, x, y, sx, sy, color, value): # 初始化
|
||||
self.x = x # 球的地图位置参数
|
||||
self.y = y
|
||||
self.sx = sx # 速度参数
|
||||
self.sy = sy
|
||||
self.color = color # 颜色
|
||||
self.value = value # 球的值，也就是球的大小（不是显示的大小）
|
||||
self.is_alive = True # 球默认是存活状态
|
||||
|
||||
|
||||
class My_Ball(Ball): # 定义我的球，继承了Ball类的方法
|
||||
def __init__(self, x, y, sx, sy, color, value):
|
||||
# 注意：如果重写了__init__() 时，实例化子类，就不会调用父类已经定义的__init__()
|
||||
# 如果子类不重写__init__()方法，实例化子类后，会自动调用父类的__init__()的方法
|
||||
# 如果子类重写__init__()方法又需要调用父类的方法，则要使用super关键词。
|
||||
super().__init__(x, y, sx, sy, color, value) # 调用父类Ball的初始化方法__init__()
|
||||
self.radius = int(self.value**0.5) # 我的球的半径（不考虑系数pi）
|
||||
if self.radius >= max_show_size: # 如果半径比规定的最大半径还大，则显示最大半径
|
||||
self.show_radius = max_show_size # 我的球显示的半径
|
||||
else:
|
||||
self.show_radius = self.radius # 如果半径没有超过规定最大的半径，则显示原来实际大小的半径
|
||||
self.position_x = int(screen_width/2) # 把我的球固定在屏幕中间position_x，是屏幕显示的位置
|
||||
self.position_y = int(screen_height/2) # 把我的球固定在屏幕中间position_y，是屏幕显示的位置
|
||||
|
||||
def draw(self, window): # 把我的球画出来
|
||||
self.radius = int(self.value ** 0.5) # 这里重复上面的，因为除了初始化之后，还要更新
|
||||
if self.radius >= max_show_size:
|
||||
self.show_radius = max_show_size
|
||||
else:
|
||||
self.show_radius = self.radius
|
||||
self.position_x = int(screen_width / 2)
|
||||
self.position_y = int(screen_height / 2)
|
||||
pygame.draw.circle(window, self.color, (self.position_x , self.position_y), self.show_radius)
|
||||
|
||||
def eat_ball(self, other): # 吃别的球（包括小点点和敌人）
|
||||
if self != other and self.is_alive and other.is_alive: # 如果other不是自身，自身和对方也都是存活状态，则执行下面动作
|
||||
distance = ((self.position_x - other.position_x) ** 2 + (self.position_y - other.position_y) ** 2) ** 0.5 # 两个球之间的距离
|
||||
if distance < self.show_radius and (self.show_radius > other.show_radius or (self.show_radius == other.show_radius and self.value > other.value)): # 如果自身半径比别人大，而且两者距离小于自身半径，那么可以吃掉。
|
||||
other.is_alive = False # 吃球（敌方已死）
|
||||
self.value += other.value*eat_percent # 自己的值增大（体量增大）
|
||||
self.radius = int(self.value ** 0.5) # 计算出半径
|
||||
if self.radius >= max_show_size: # 我的球的显示半径
|
||||
self.show_radius = max_show_size
|
||||
else:
|
||||
self.show_radius = self.radius
|
||||
|
||||
def move(self): # 移动规则
|
||||
self.x += self.sx # 地图位置加上速度
|
||||
self.y += self.sy
|
||||
# 横向出界
|
||||
if self.x < 0: # 离开了地图左边
|
||||
self.x = 0
|
||||
if self.x > map_width: # 离开了地图右边
|
||||
self.x = map_width
|
||||
# 纵向出界
|
||||
if self.y <= 0: # 离开了地图下边
|
||||
self.y = 0
|
||||
if self.y >= map_height: # 离开了地图上边
|
||||
self.y = map_height
|
||||
|
||||
|
||||
class Enemy_Ball(Ball): # 定义敌人的球，继承了Ball类的方法
|
||||
def __init__(self, x, y, sx, sy, color, value, host_ball): # 初始化带上host_ball，也就是我的球
|
||||
super().__init__(x, y, sx, sy, color, value)
|
||||
self.host_ball = host_ball
|
||||
self.radius = int(self.value**0.5)
|
||||
if self.host_ball.radius >= max_show_size: # 如果我的球比规定的最大尺寸还大，则敌人的球显示的比例要减小
|
||||
self.show_radius = max(10, int(self.radius/(self.host_ball.radius/max_show_size))) # 敌人的球也不能太小，最小半径为10
|
||||
self.position_x = int((self.x - self.host_ball.x) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_width / 2) # 计算出敌人的球和我的球的相对位置，并且按比例减小
|
||||
self.position_y = int((self.y - self.host_ball.y) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_height / 2) # 计算出敌人的球和我的球的相对位置，并且按比例减小
|
||||
else:
|
||||
self.show_radius = self.radius # 正常显示
|
||||
self.position_x = (self.x - self.host_ball.x) + int(screen_width / 2) # 敌人和我的球的相对位置
|
||||
self.position_y = (self.y - self.host_ball.y) + int(screen_height / 2) # 敌人和我的球的相对位置
|
||||
|
||||
# 画出球
|
||||
def draw(self, window):
|
||||
self.radius = int(self.value ** 0.5)
|
||||
if self.host_ball.radius >= max_show_size: # 这边把初始化的内容再写一遍，因为敌人的球初始化之后还要根据我的球而动态改变
|
||||
self.show_radius = max(10, int(self.radius/(self.host_ball.radius/max_show_size)))
|
||||
self.position_x = int((self.x - self.host_ball.x) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_width / 2)
|
||||
self.position_y = int((self.y - self.host_ball.y) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_height / 2)
|
||||
else:
|
||||
self.show_radius = self.radius
|
||||
self.position_x = (self.x - self.host_ball.x) + int(screen_width / 2)
|
||||
self.position_y = (self.y - self.host_ball.y) + int(screen_height / 2)
|
||||
pygame.draw.circle(window, self.color, (self.position_x, self.position_y), self.show_radius)
|
||||
|
||||
def eat_ball(self, other):
|
||||
if self != other and self.is_alive and other.is_alive:
|
||||
distance = ((self.position_x - other.position_x) ** 2 + (self.position_y - other.position_y) ** 2) ** 0.5
|
||||
if distance < self.show_radius and (self.show_radius > other.show_radius or (self.show_radius == other.show_radius and self.value > other.value)):
|
||||
other.is_alive = False # 吃球
|
||||
self.value += other.value*eat_percent
|
||||
self.radius = int(self.value ** 0.5)
|
||||
|
||||
def move(self): # 移动规则
|
||||
self.x += self.sx # 地图位置加上速度
|
||||
self.y += self.sy
|
||||
# 横向出界
|
||||
if self.x < 0: # 离开了地图左边
|
||||
self.sx = -self.sx
|
||||
self.x = 0
|
||||
if self.x > map_width: # 离开了地图右边
|
||||
self.sx = -self.sx
|
||||
self.x = map_width
|
||||
# 纵向出界
|
||||
if self.y <= 0: # 离开了地图下边
|
||||
self.sy = -self.sy
|
||||
self.y = 0
|
||||
if self.y >= map_height: # 离开了地图上边
|
||||
self.sy = -self.sy
|
||||
self.y = map_height
|
||||
|
||||
|
||||
class Dot_Ball(Ball): # 定义地上的小点点，供自己的球和敌人的球吃，继承了Ball类的方法
|
||||
def __init__(self, x, y, sx, sy, color, value, host_ball):
|
||||
super().__init__(x, y, sx, sy, color, value)
|
||||
self.host_ball = host_ball
|
||||
self.radius = 8 # 初始小点点大小
|
||||
if self.host_ball.radius >= max_show_size:
|
||||
self.show_radius = max(3, int(self.radius/(self.host_ball.radius/max_show_size))) # 小点点显示也不能太小，最小显示半径为3
|
||||
self.position_x = int((self.x - self.host_ball.x) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_width / 2)
|
||||
self.position_y = int((self.y - self.host_ball.y) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_height / 2)
|
||||
else:
|
||||
self.show_radius = self.radius
|
||||
self.position_x = (self.x - self.host_ball.x) + int(screen_width / 2)
|
||||
self.position_y = (self.y - self.host_ball.y) + int(screen_height / 2)
|
||||
|
||||
# 画出球
|
||||
def draw(self, window):
|
||||
if self.host_ball.radius >= max_show_size: # 这边把初始化的内容再写一遍，因为小点点初始化之后还要根据我的球而动态改变
|
||||
self.show_radius = max(3, int(self.radius/(self.host_ball.radius/max_show_size)))
|
||||
self.position_x = int((self.x - self.host_ball.x) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_width / 2)
|
||||
self.position_y = int((self.y - self.host_ball.y) / (self.host_ball.radius / max_show_size)) + int(
|
||||
screen_height / 2)
|
||||
else:
|
||||
self.show_radius = self.radius
|
||||
self.position_x = (self.x - self.host_ball.x) + int(screen_width / 2)
|
||||
self.position_y = (self.y - self.host_ball.y) + int(screen_height / 2)
|
||||
pygame.draw.circle(window, self.color, (self.position_x, self.position_y) , self.show_radius)
|
||||
|
||||
|
||||
def creat_my_ball(): # 产生我的球
|
||||
x = random.randint(0, map_width) # 我的球在地图中的位置，随机生成
|
||||
y = random.randint(0, map_height)
|
||||
value = my_value # 我的球的初始值
|
||||
color = 255, 255, 255 # 我的球的颜色
|
||||
sx = 0 # 速度默认为0
|
||||
sy = 0
|
||||
host_ball = My_Ball(x, y, sx, sy, color, value) # 调用My_Ball类
|
||||
return host_ball # 返回我的球
|
||||
|
||||
|
||||
def auto_creat_ball(balls, host_ball): # 自动产生敌人的球
|
||||
if len(balls) <= number_enemy: # 控制敌人的数量，如果个数够了，就不再生成
|
||||
x = random.randint(0, map_width) # 敌人球在地图中的位置，随机生成
|
||||
y = random.randint(0, map_height)
|
||||
value = random.randint(enemy_value_low, enemy_value_high) # 敌人的球初始值
|
||||
sx = random.randint(-speed_enemy, speed_enemy) # 敌人的球移动速度
|
||||
i2 = random.randint(0, 1) # y的移动方向
|
||||
if i2 == 0:
|
||||
sy = int((speed_enemy**2 - sx**2) ** 0.5)
|
||||
else:
|
||||
sy = -int((speed_enemy ** 2 - sx ** 2) ** 0.5)
|
||||
color = Color.random_color() # 敌人的颜色随机生成
|
||||
enemy = Enemy_Ball(x, y, sx, sy, color, value, host_ball)
|
||||
balls.append(enemy)
|
||||
|
||||
|
||||
def auto_creat_dots(dots, host_ball): # 自动生成点点
|
||||
if len(dots) <= number_dots: # 控制点点的数量
|
||||
x = random.randint(0, map_width) # 随机生成点点的位置
|
||||
y = random.randint(0, map_height)
|
||||
value = dot_value # 点点的值
|
||||
sx = 0 # 点点速度为0
|
||||
sy = 0
|
||||
color = Color.random_color() # 颜色
|
||||
dot = Dot_Ball(x, y, sx, sy, color, value, host_ball)
|
||||
dots.append(dot)
|
||||
|
||||
|
||||
def control_my_ball(host_ball): # 控制我的球
|
||||
host_ball.move()
|
||||
host_ball.value = host_ball.value*(1-loss*host_ball.value/100000)
|
||||
for event in pygame.event.get(): # 监控事件（鼠标移动）
|
||||
# print(event)
|
||||
if event.type == pygame.MOUSEBUTTONDOWN:
|
||||
pos = event.pos
|
||||
speed = speed_up
|
||||
elif event.type == pygame.MOUSEMOTION:
|
||||
pos = event.pos
|
||||
if event.buttons[0] == 1:
|
||||
speed = speed_up
|
||||
if event.buttons[0] == 0:
|
||||
speed = my_speed
|
||||
elif event.type == pygame.MOUSEBUTTONUP:
|
||||
pos = event.pos
|
||||
speed = my_speed
|
||||
else:
|
||||
pos = [screen_width/2, screen_height/2]
|
||||
speed = my_speed
|
||||
if abs(pos[0] - screen_width/2) < 30 and abs(pos[1] - screen_height/2) < 30:
|
||||
host_ball.sx = 0
|
||||
host_ball.sy = 0
|
||||
elif pos[0] > screen_width/2 and pos[1] >= screen_height/2:
|
||||
angle = abs(math.atan((pos[1] - screen_height/2) / (pos[0] - screen_width/2)))
|
||||
host_ball.sx = int(speed * math.cos(angle))
|
||||
host_ball.sy = int(speed * math.sin(angle))
|
||||
elif pos[0] > screen_width/2 and pos[1] < screen_height/2:
|
||||
angle = abs(math.atan((pos[1] - screen_height/2) / (pos[0] - screen_width/2)))
|
||||
host_ball.sx = int(speed * math.cos(angle))
|
||||
host_ball.sy = -int(speed * math.sin(angle))
|
||||
elif pos[0] < screen_width/2 and pos[1] >= screen_height/2:
|
||||
angle = abs(math.atan((pos[1] - screen_height/2) / (pos[0] - screen_width/2)))
|
||||
host_ball.sx = -int(speed * math.cos(angle))
|
||||
host_ball.sy = int(speed * math.sin(angle))
|
||||
elif pos[0] < screen_width/2 and pos[1] < screen_height/2:
|
||||
angle = abs(math.atan((pos[1] - screen_height/2) / (pos[0] - screen_width/2)))
|
||||
host_ball.sx = -int(speed * math.cos(angle))
|
||||
host_ball.sy = -int(speed * math.sin(angle))
|
||||
elif pos[0] == screen_width/2:
|
||||
host_ball.sx = 0
|
||||
if pos[1] >= 0:
|
||||
host_ball.sy = speed
|
||||
else:
|
||||
host.ball.sy = -speed
|
||||
|
||||
|
||||
def enemy_move(balls, host_ball): # 敌人移动
|
||||
for enemy in balls:
|
||||
enemy.move() # 移动
|
||||
enemy.value = enemy.value*(1-loss*enemy.value/100000)
|
||||
if random.randint(1, int(1/enemy_bigger_pro)) == 1:
|
||||
enemy.value += host_ball.value*enemy_bigger_rate
|
||||
if random.randint(1, int(1/anomaly_pro)) == 1:
|
||||
speed_enemy0 = speed_enemy_anomaly # 敌人异常速度
|
||||
else:
|
||||
speed_enemy0 = speed_enemy # 敌人正常速度
|
||||
i = random.randint(1, int(1/change_pro)) # 一定的概率改变轨迹
|
||||
if i == 1:
|
||||
enemy.sx = random.randint(-speed_enemy0, speed_enemy0)
|
||||
i2 = random.randint(0, 1)
|
||||
if i2 == 0:
|
||||
enemy.sy = int((speed_enemy0 ** 2 - enemy.sx ** 2) ** 0.5)
|
||||
else:
|
||||
enemy.sy = -int((speed_enemy0 ** 2 - enemy.sx ** 2) ** 0.5)
|
||||
|
||||
|
||||
def eat_each_other(host_ball, balls, dots): # 吃球
|
||||
for enemy in balls:
|
||||
for enemy2 in balls:
|
||||
enemy.eat_ball(enemy2) # 敌人互吃
|
||||
for food in dots:
|
||||
enemy.eat_ball(food) # 敌人吃点点
|
||||
for enemy in balls:
|
||||
host_ball.eat_ball(enemy) # 我吃敌人
|
||||
enemy.eat_ball(host_ball) # 敌人吃我
|
||||
for food in dots:
|
||||
host_ball.eat_ball(food) # 我吃点点
|
||||
|
||||
|
||||
def paint(host_ball, balls, dots, screen):
|
||||
screen.fill((0, 0, 0)) # 刷漆
|
||||
if host_ball.is_alive:
|
||||
host_ball.draw(screen)
|
||||
for enemy in balls: # 遍历容器
|
||||
if enemy.is_alive:
|
||||
enemy.draw(screen)
|
||||
else:
|
||||
balls.remove(enemy)
|
||||
for food in dots: # 遍历容器
|
||||
if food.is_alive:
|
||||
food.draw(screen)
|
||||
else:
|
||||
dots.remove(food)
|
||||
|
||||
|
||||
def main():
|
||||
pygame.init() # 初始化
|
||||
screen = pygame.display.set_mode((screen_width, screen_height)) # 设置屏幕
|
||||
pygame.display.set_caption("球球大作战") # 设置屏幕标题
|
||||
balls = [] # 定义一容器 存放所有的敌方球
|
||||
dots = [] # 定义一容器 存放所有的点点
|
||||
is_running = True # 默认运行状态
|
||||
host_ball = creat_my_ball() # 产生我的球
|
||||
i00 = 0 # 一个参数
|
||||
while is_running:
|
||||
for event in pygame.event.get():
|
||||
if event.type == pygame.QUIT:
|
||||
is_running = False
|
||||
auto_creat_dots(dots, host_ball) # 自动生成点点
|
||||
auto_creat_ball(balls, host_ball) # 自动生成敌人
|
||||
paint(host_ball, balls, dots, screen) # 把所有的都画出来 调用draw方法
|
||||
pygame.display.flip() # 渲染
|
||||
pygame.time.delay(30) # 设置动画的时间延迟
|
||||
|
||||
control_my_ball(host_ball) # 移动我的球
|
||||
enemy_move(balls, host_ball) # 敌人的球随机运动
|
||||
eat_each_other(host_ball, balls, dots) # 吃球 调用eat_ball方法
|
||||
i00 += 1
|
||||
if np.mod(i00, 50) == 0:
|
||||
print(host_ball.value)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,106 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/706
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import time
|
||||
import matplotlib.pyplot as plt
|
||||
import tushare as ts
|
||||
|
||||
|
||||
def main():
|
||||
start_clock = time.perf_counter()
|
||||
pro = ts.pro_api('到官网上注册，寻找Token填在这里!')
|
||||
print('\n我的策略：见好就收，遇低抄底。\n'
|
||||
' 【卖出】买入后涨了5%就卖出\n'
|
||||
' 【买入】卖出后跌了5%就买入\n'
|
||||
'注：第一天必须买进，最后一天前必须卖出(为了与不操作的做对比)\n')
|
||||
number = 1
|
||||
for i in range(number):
|
||||
data = pro.stock_basic(exchange='', list_status='L', fields='ts_code,symbol,name,area,industry,list_date') # 所有股票列表
|
||||
# print(data.columns) # 查看该数据的表头
|
||||
# print(data) # 3688多行的股票数据
|
||||
i = 1 # 查看第二行数据“万科A”股
|
||||
ts_code = data.values[i, 0] # 股票代码
|
||||
stock = data.values[i, 2] # 股票名称
|
||||
industry = data.values[i, 4] # 属于哪个行业
|
||||
start_date = '20110101' # 开始时间
|
||||
end_date = '20191027' # 结束时间
|
||||
df = pro.daily(ts_code=ts_code, start_date=start_date, end_date=end_date) # 查看该股票的日线数据
|
||||
# print(df.columns) # 查看该数据的表头
|
||||
# print(df) # 查看该股票的日线数据
|
||||
close = np.array(list(reversed(df.values[:, 5]))) # 提取出收盘价，并按时间顺序排列，从过去到现在
|
||||
pct_chg = np.array(list(reversed(df.values[:, 8]))) # 提取出涨跌幅，并按时间顺序排列，从过去到现在
|
||||
# print(df.columns[5], '=', close, '\n') # 查看收盘价
|
||||
# print(df.columns[8], '=', pct_chg, '\n') # 查看涨跌幅
|
||||
profit, profit_no_operation, times, invest_money, buy_time_all, sell_time_all = back_test(close.shape[0], close, pct_chg)
|
||||
# 调用回测函数，返回了“利润，未操作的利润， 按该策略操作了几次， 总投资金额， 按该策略买的时间， 按该策略卖的时间”的值
|
||||
print('\n------股票：', stock, ts_code, industry, '[买入市值=%7.2f' % invest_money, ']------')
|
||||
print('回测时间段：', start_date, '-', end_date)
|
||||
print('操作后利润= %6.2f' % profit, ' 买入（卖出）次数=', times, ' ')
|
||||
print('不操作利润= %6.2f' % profit_no_operation, '（第一天买入，最后一天卖出，中间未操作）')
|
||||
end_clock = time.perf_counter()
|
||||
print('CPU执行时间=', end_clock - start_clock, 's')
|
||||
plt.figure(1)
|
||||
plt.title('Stock Code: '+ts_code+' (red point: buy, green point: sell)')
|
||||
plt.grid()
|
||||
plt.plot(range(close.shape[0]), close, '-')
|
||||
for i in buy_time_all:
|
||||
plt.plot(i, close[int(i)], 'or', markersize=13) # 红色是买进的点
|
||||
for i in sell_time_all:
|
||||
plt.plot(i, close[int(i)], 'dg', markersize=13) # 绿色是卖出的点
|
||||
plt.show()
|
||||
|
||||
|
||||
def back_test(days, close, pct_chg, money_in=10000): # 定义该策略的回测效果（按旧数据检查该策略是否有效）
|
||||
money_in_amount = int(money_in/close[0]) # 投资金额换算成股票股数
|
||||
invest_money = close[0]*money_in_amount # 实际买了股票的金额
|
||||
profit_no_operation = (close[close.shape[0]-1]-close[0])*money_in_amount # 不操作的利润
|
||||
position = -1 # 买入还是卖出的状态，默认卖出
|
||||
total_profit = 0
|
||||
times = 0
|
||||
current_buy_pct = -999
|
||||
current_sell_pct = 999
|
||||
buy_time_all = np.array([])
|
||||
sell_time_all = np.array([])
|
||||
for i in range(days): # 总天数
|
||||
if i == 0: # 第一天，满仓买买买！为了和不操作的对比，第一天就要买入。
|
||||
buy_time = i # 买入时间
|
||||
buy_time_all = np.append(buy_time_all, [buy_time], axis=0) # 买入时间存档
|
||||
position = 1 # 标记为买入状态
|
||||
print('------------------第', buy_time, '天买进-------------')
|
||||
else:
|
||||
profit = 0
|
||||
if position == 1: # 买入状态
|
||||
current_buy_pct = (close[i]-close[buy_time])/close[buy_time]*100 # 买入后的涨跌情况
|
||||
# print('当前买进后的涨跌情况：第', i, '天=', current_buy_pct)
|
||||
if position == 0: # 卖出状态
|
||||
current_sell_pct = (close[i]-close[sell_time])/close[sell_time]*100 # 卖出后的涨跌情况
|
||||
|
||||
if current_sell_pct < -5 and position == 0: # 卖出状态，且卖出后跌了有3%，这时候买入
|
||||
buy_time = i # 买入时间
|
||||
buy_time_all = np.append(buy_time_all, [buy_time], axis=0) # 买入时间存档
|
||||
print('------------------第', buy_time, '天买进-------------')
|
||||
position = 1 # 标记为买入状态
|
||||
continue
|
||||
|
||||
if current_buy_pct > 5 and position == 1: # 买入状态，且买入后涨了有3%，这时候卖出
|
||||
sell_time = i # 卖出时间
|
||||
sell_time_all = np.append(sell_time_all, [sell_time], axis=0) # 卖出时间存档
|
||||
print('----------第', sell_time, '天卖出，持有天数：', sell_time-buy_time, '--------------\n')
|
||||
position = 0 # 标记为卖出状态
|
||||
profit = close[sell_time]-close[buy_time] # 赚取利润
|
||||
times = times + 1 # 买入（卖出）次数加1
|
||||
total_profit = total_profit + profit*money_in_amount # 计算总利润
|
||||
if position == 1: # 最后一天如果是买入状态，则卖出
|
||||
profit = close[i]-close[buy_time] # 赚取利润
|
||||
total_profit = total_profit + profit # 计算总利润
|
||||
times = times + 1 # 买入（卖出）次数加1
|
||||
print('--------------第', i, '天（最后一天）卖出，持有天数：', sell_time-buy_time, '--------------\n')
|
||||
sell_time_all = np.append(sell_time_all, [i], axis=0) # 卖出时间存档
|
||||
return total_profit, profit_no_operation, times, invest_money, buy_time_all, sell_time_all
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,11 @@
|
||||
import imageio
|
||||
import numpy as np
|
||||
import os
|
||||
# os.chdir('E:/data') # 设置文件读取和保存位置
|
||||
|
||||
images = []
|
||||
for i in range(1000):
|
||||
image = str(i)+'.jpg'
|
||||
im = imageio.imread(image)
|
||||
images.append(im)
|
||||
imageio.mimsave("a.gif", images, 'GIF', duration=0.1) # durantion是延迟时间
|
||||
@@ -0,0 +1,35 @@
|
||||
from multiprocessing import Process
|
||||
import os
|
||||
import time
|
||||
import numpy as np
|
||||
import guan
|
||||
|
||||
def main(parameter_array, task_index):
|
||||
print ('Process id = %s' % (os.getpid()))
|
||||
result_array = []
|
||||
for parameter in parameter_array:
|
||||
result = parameter*2
|
||||
result_array.append(result)
|
||||
time.sleep(np.random.uniform(1,10))
|
||||
guan.write_one_dimensional_data(parameter_array, result_array, filename='task_index='+str(task_index))
|
||||
|
||||
if __name__ == '__main__':
|
||||
cpus = 4
|
||||
parameter_array_all = np.arange(0, 17, 1)
|
||||
start_time = time.perf_counter()
|
||||
process_array = []
|
||||
for task_index in range(cpus):
|
||||
parameter_array = guan.preprocess_for_parallel_calculations(parameter_array_all, cpus, task_index)
|
||||
process_array.append(Process(target=main, args=(parameter_array, task_index)))
|
||||
for process in process_array: # 运行子进程
|
||||
process.start()
|
||||
for process in process_array: # 等待子进程完成
|
||||
process.join()
|
||||
end_time = time.perf_counter()
|
||||
print('运行时间=', (end_time-start_time), '\n')
|
||||
f = open('result.txt', 'w')
|
||||
for task_index in range(cpus):
|
||||
with open('task_index='+str(task_index)+'.txt', 'r') as f0:
|
||||
text = f0.read()
|
||||
f.write(text)
|
||||
f.close()
|
||||
@@ -0,0 +1,42 @@
|
||||
from multiprocessing import Process
|
||||
import os
|
||||
import time
|
||||
|
||||
def run_proc(name): # 要执行的代码
|
||||
start_time = time.perf_counter()
|
||||
time.sleep(2)
|
||||
end_time = time.perf_counter()
|
||||
print ('Process id running on %s = %s' % (name, os.getpid()), '; running time = %s' % (end_time-start_time))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
|
||||
# 串行
|
||||
print('串行程序')
|
||||
print('Process id = %s.' % os.getpid())
|
||||
start_time = time.perf_counter()
|
||||
run_proc('job1')
|
||||
run_proc('job2')
|
||||
run_proc('job3')
|
||||
run_proc('job4')
|
||||
end_time = time.perf_counter()
|
||||
print('CPU执行时间(s)=', (end_time-start_time), '\n')
|
||||
|
||||
# 并行
|
||||
print('并行程序')
|
||||
print('Process id = %s.' % os.getpid())
|
||||
start_time = time.perf_counter()
|
||||
p1 = Process(target=run_proc, args=('job1',))
|
||||
p2 = Process(target=run_proc, args=('job2',))
|
||||
p3 = Process(target=run_proc, args=('job3',))
|
||||
p4 = Process(target=run_proc, args=('job4',))
|
||||
p1.start()
|
||||
p2.start()
|
||||
p3.start()
|
||||
p4.start()
|
||||
p1.join() # join()方法可以等待子进程结束后再继续往下运行
|
||||
p2.join()
|
||||
p3.join()
|
||||
p4.join()
|
||||
end_time = time.perf_counter()
|
||||
print('运行时间(s)=', (end_time-start_time))
|
||||
@@ -0,0 +1,16 @@
|
||||
from multiprocessing import Process, Value
|
||||
|
||||
def run_proc(name, a, num): # 要执行的代码
|
||||
num.value = a
|
||||
|
||||
if __name__ == '__main__':
|
||||
num1 = Value('d', 0.0) # 共享内存
|
||||
num2 = Value('d', 0.0) # 共享内存
|
||||
p1 = Process(target=run_proc, args=('job1', 100, num1))
|
||||
p2 = Process(target=run_proc, args=('job2', 200, num2))
|
||||
p1.start()
|
||||
p2.start()
|
||||
p1.join()
|
||||
p2.join()
|
||||
print(num1.value)
|
||||
print(num2.value)
|
||||
@@ -0,0 +1,30 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def main():
|
||||
k1 = np.arange(-pi, pi, 0.05)
|
||||
k2 = np.arange(-pi, pi, 0.05)
|
||||
value = np.ones((k2.shape[0], k1.shape[0]))
|
||||
plot_matrix(k1, k2, value)
|
||||
|
||||
|
||||
def plot_matrix(k1, k2, matrix):
|
||||
import matplotlib.pyplot as plt
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator, FormatStrFormatter
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
k1, k2 = np.meshgrid(k1, k2)
|
||||
ax.plot_surface(k1, k2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False)
|
||||
plt.xlabel('k1')
|
||||
plt.ylabel('k2')
|
||||
ax.set_zlabel('Z')
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,31 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def main():
|
||||
k1 = np.arange(-pi, pi, 0.05)
|
||||
k2 = np.arange(-pi, pi, 0.05)
|
||||
value = np.ones((k2.shape[0], k1.shape[0]))
|
||||
write_matrix(k1, k2, value)
|
||||
|
||||
|
||||
def write_matrix(k1, k2, matrix):
|
||||
with open('a.txt', 'w') as f:
|
||||
# np.set_printoptions(suppress=True) # 取消输出科学记数法
|
||||
f.write('0 ')
|
||||
for k10 in k1:
|
||||
f.write(str(k10)+' ')
|
||||
f.write('\n')
|
||||
i0 = 0
|
||||
for k20 in k2:
|
||||
f.write(str(k20))
|
||||
for j0 in range(k1.shape[0]):
|
||||
f.write(' '+str(matrix[i0, j0])+' ')
|
||||
f.write('\n')
|
||||
i0 += 1
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,35 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def hamiltonian(k):
|
||||
pass
|
||||
|
||||
|
||||
def main():
|
||||
k = np.arange(-pi, pi, 0.05)
|
||||
plot_bands_one_dimension(k, hamiltonian)
|
||||
|
||||
|
||||
def plot_bands_one_dimension(k, hamiltonian):
|
||||
import matplotlib.pyplot as plt
|
||||
dim = hamiltonian(0).shape[0]
|
||||
dim_k = k.shape[0]
|
||||
eigenvalue_k = np.zeros((dim_k, dim))
|
||||
i0 = 0
|
||||
for k0 in k:
|
||||
matrix0 = hamiltonian(k0)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue_k[i0, :] = np.sort(np.real(eigenvalue[:]))
|
||||
i0 += 1
|
||||
for dim0 in range(dim):
|
||||
plt.plot(k, eigenvalue_k[:, dim0], '-k')
|
||||
plt.xlabel('k')
|
||||
plt.ylabel('E')
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,47 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def hamiltonian(k1, k2):
|
||||
pass
|
||||
|
||||
|
||||
def main():
|
||||
k1 = np.arange(-pi, pi, 0.05)
|
||||
k2 = np.arange(-pi, pi, 0.05)
|
||||
plot_bands_two_dimension(k1, k2, hamiltonian)
|
||||
|
||||
|
||||
def plot_bands_two_dimension(k1, k2, hamiltonian):
|
||||
import matplotlib.pyplot as plt
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator, FormatStrFormatter
|
||||
dim = hamiltonian(0, 0).shape[0]
|
||||
dim1 = k1.shape[0]
|
||||
dim2 = k2.shape[0]
|
||||
eigenvalue_k = np.zeros((dim2, dim1, dim))
|
||||
i0 = 0
|
||||
for k20 in k2:
|
||||
j0 = 0
|
||||
for k10 in k1:
|
||||
matrix0 = hamiltonian(k10, k20)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue_k[i0, j0, :] = np.sort(np.real(eigenvalue[:]))
|
||||
j0 += 1
|
||||
i0 += 1
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
k1, k2 = np.meshgrid(k1, k2)
|
||||
for dim0 in range(dim):
|
||||
ax.plot_surface(k1, k2, eigenvalue_k[:, :, dim0], cmap=cm.coolwarm, linewidth=0, antialiased=False)
|
||||
plt.xlabel('k1')
|
||||
plt.ylabel('k2')
|
||||
ax.set_zlabel('E')
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,31 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def hamiltonian(k):
|
||||
pass
|
||||
|
||||
|
||||
def main():
|
||||
k = np.arange(-pi, pi, 0.05)
|
||||
write_bands_one_dimension(k, hamiltonian)
|
||||
|
||||
|
||||
def write_bands_one_dimension(k, hamiltonian):
|
||||
dim = hamiltonian(0).shape[0]
|
||||
f = open('a.txt','w')
|
||||
for k0 in k:
|
||||
f.write(str(k0)+' ')
|
||||
matrix0 = hamiltonian(k0)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue = np.sort(np.real(eigenvalue))
|
||||
for dim0 in range(dim):
|
||||
f.write(str(eigenvalue[dim0])+' ')
|
||||
f.write('\n')
|
||||
f.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,42 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def hamiltonian(k1, k2):
|
||||
pass
|
||||
|
||||
|
||||
def main():
|
||||
k1 = np.arange(-pi, pi, 0.05)
|
||||
k2 = np.arange(-pi, pi, 0.05)
|
||||
write_bands_two_dimension(k1, k2, hamiltonian)
|
||||
|
||||
|
||||
def write_bands_two_dimension(k1, k2, hamiltonian):
|
||||
f1 = open('a1.txt', 'w')
|
||||
f2 = open('a2.txt', 'w')
|
||||
f1.write('0 ')
|
||||
f2.write('0 ')
|
||||
for k10 in k1:
|
||||
f1.write(str(k10)+' ')
|
||||
f2.write(str(k10)+' ')
|
||||
f1.write('\n')
|
||||
f2.write('\n')
|
||||
for k20 in k2:
|
||||
f1.write(str(k20)+' ')
|
||||
f2.write(str(k20)+' ')
|
||||
for k10 in k1:
|
||||
matrix0 = hamiltonian(k10, k20)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue = np.sort(np.real(eigenvalue))
|
||||
f1.write(str(eigenvalue[0])+' ')
|
||||
f2.write(str(eigenvalue[1])+' ')
|
||||
f1.write('\n')
|
||||
f2.write('\n')
|
||||
f1.close()
|
||||
f2.close()
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,7 @@
|
||||
import numpy as np # 导入numpy库，用来存储和处理大型矩阵，比python自带的嵌套列表更高效。numpy库还包含了许多数学函数库。python+numpy等同于matlab。
|
||||
|
||||
def main(): # 主函数的内容放在这里。
|
||||
pass
|
||||
|
||||
if __name__ == '__main__': # 如果是当前文件直接运行，执行main()函数中的内容；如果是import当前文件，则不执行。同时将main()语句放在最后运行，可以避免书写的函数出现未定义的情况。
|
||||
main()
|
||||
@@ -0,0 +1,4 @@
|
||||
1 1.2 2.4
|
||||
2 5.5 3.2
|
||||
3 6.7 7.1
|
||||
4 3.6 4.9
|
||||
@@ -0,0 +1,4 @@
|
||||
0 1 2 3 4
|
||||
1 1.3 2.7 6.7 8.3
|
||||
2 4.3 2.9 5.4 7.4
|
||||
3 9.1 8.2 2.6 3.1
|
||||
@@ -0,0 +1,47 @@
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def main():
|
||||
x, y = read_one_dimension('1D_data.txt')
|
||||
for dim0 in range(y.shape[1]):
|
||||
plt.plot(x, y[:, dim0], '-k')
|
||||
plt.show()
|
||||
|
||||
|
||||
def read_one_dimension(file_name):
|
||||
f = open(file_name, 'r')
|
||||
text = f.read()
|
||||
f.close()
|
||||
row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行
|
||||
# print('文本格式：')
|
||||
# print(text)
|
||||
# print('row_list:')
|
||||
# print(row_list)
|
||||
# print('column:')
|
||||
dim_column = np.array(row_list[0].split()).shape[0] # 列数
|
||||
x = np.array([])
|
||||
y = np.array([])
|
||||
for row in row_list:
|
||||
column = np.array(row.split()) # 每一行根据“空格”继续分割
|
||||
# print(column)
|
||||
if column.shape[0] != 0: # 解决最后一行空白的问题
|
||||
x = np.append(x, [float(column[0])], axis=0) # 第一列为x数据
|
||||
y_row = np.zeros(dim_column-1)
|
||||
for dim0 in range(dim_column-1):
|
||||
y_row[dim0] = float(column[dim0+1])
|
||||
if np.array(y).shape[0] == 0:
|
||||
y = [y_row]
|
||||
else:
|
||||
y = np.append(y, [y_row], axis=0)
|
||||
# print('x:')
|
||||
# print(x)
|
||||
# print('y:')
|
||||
# print(y)
|
||||
return x, y
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,69 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
def main():
|
||||
x1, x2, matrix = read_two_dimension('2D_data.txt')
|
||||
plot_matrix(x1, x2, matrix)
|
||||
|
||||
|
||||
def read_two_dimension(file_name):
|
||||
f = open(file_name, 'r')
|
||||
text = f.read()
|
||||
f.close()
|
||||
row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行
|
||||
# print('文本格式：')
|
||||
# print(text)
|
||||
# print('row_list:')
|
||||
# print(row_list)
|
||||
# print('column:')
|
||||
dim_column = np.array(row_list[0].split()).shape[0] # 列数
|
||||
x1 = np.array([])
|
||||
x2 = np.array([])
|
||||
matrix = np.array([])
|
||||
for i0 in range(row_list.shape[0]):
|
||||
column = np.array(row_list[i0].split()) # 每一行根据“空格”继续分割
|
||||
# print(column)
|
||||
if i0 == 0:
|
||||
x1_str = column[1::] # x1坐标（去除第一个在角落的值）
|
||||
x1 = np.zeros(x1_str.shape[0])
|
||||
for i00 in range(x1_str.shape[0]):
|
||||
x1[i00] = float(x1_str[i00]) # 字符串转浮点
|
||||
elif column.shape[0] != 0: # 解决最后一行空白的问题
|
||||
x2 = np.append(x2, [float(column[0])], axis=0) # 第一列为x数据
|
||||
matrix_row = np.zeros(dim_column-1)
|
||||
for dim0 in range(dim_column-1):
|
||||
matrix_row[dim0] = float(column[dim0+1])
|
||||
if np.array(matrix).shape[0] == 0:
|
||||
matrix = [matrix_row]
|
||||
else:
|
||||
matrix = np.append(matrix, [matrix_row], axis=0)
|
||||
# print('x1:')
|
||||
# print(x1)
|
||||
# print('x2:')
|
||||
# print(x2)
|
||||
# print('matrix:')
|
||||
# print(matrix)
|
||||
return x1, x2, matrix
|
||||
|
||||
|
||||
|
||||
def plot_matrix(x1, x2, matrix):
|
||||
import matplotlib.pyplot as plt
|
||||
from mpl_toolkits.mplot3d import Axes3D
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator, FormatStrFormatter
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
x1, x2 = np.meshgrid(x1, x2)
|
||||
ax.plot_surface(x1, x2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False)
|
||||
plt.xlabel('x1')
|
||||
plt.ylabel('x2')
|
||||
ax.set_zlabel('z')
|
||||
plt.show()
|
||||
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,18 @@
|
||||
import numpy as np
|
||||
from math import *
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置路径
|
||||
|
||||
|
||||
f = open('a.txt', 'w')
|
||||
f.write('0 ')
|
||||
for k1 in np.arange(-pi, pi, 0.05):
|
||||
f.write(str(k1)+' ')
|
||||
f.write('\n')
|
||||
for k2 in np.arange(-pi, pi, 0.05):
|
||||
f.write(str(k2)+' ')
|
||||
for k1 in np.arange(-pi, pi, 0.05):
|
||||
data = 1000 # 运算数据
|
||||
f.write(str(data)+' ')
|
||||
f.write('\n')
|
||||
f.close()
|
||||
@@ -0,0 +1,47 @@
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
|
||||
# 最简单的情况
|
||||
html = urlopen("https://mofanpy.com/static/scraping/basic-structure.html").read().decode('utf-8')
|
||||
print('\n显示网页的代码信息1：\n\n ----------------开始----------------\n', html, '\n\n----------------结束----------------') # 显示网页的代码信息
|
||||
|
||||
soup = BeautifulSoup(html, features='lxml') # 把网页放进BeautifulSoup
|
||||
print('\n获取标签_标题h1_中的内容soup.h1：\n', soup.h1)
|
||||
print('\n获取标签_段落p_中的内容soup.p：\n', soup.p)
|
||||
print('\n获取标签_链接a_中的内容soup.a：\n', soup.a)
|
||||
|
||||
all_href = soup.find_all('a')
|
||||
print('\n获取所有"a标签"的内容soup.find_all(‘a’)：\n', all_href)
|
||||
|
||||
print('\n获取某个字典的值_1：')
|
||||
for a in all_href:
|
||||
print(a)
|
||||
print(a['href'])
|
||||
|
||||
all_href = [a['href'] for a in all_href]
|
||||
print('\n获取某个字典的值_2：\n', all_href, '\n')
|
||||
|
||||
|
||||
|
||||
|
||||
# 加入CSS内容
|
||||
html = urlopen("https://mofanpy.com/static/scraping/list.html").read().decode('utf-8')
|
||||
print('\n显示网页的代码信息2：\n\n ----------------开始----------------\n', html, '\n\n----------------结束----------------') # 显示网页的代码信息
|
||||
|
||||
soup = BeautifulSoup(html, features='lxml') # 把网页放进BeautifulSoup
|
||||
|
||||
print('\n利用class筛选出所需要的信息：')
|
||||
month = soup.find_all('li', {"class": "month"})
|
||||
print(month, '\n')
|
||||
|
||||
print('只显示文本：')
|
||||
for m in month:
|
||||
print(m.get_text())
|
||||
|
||||
print('\n 多次筛选：')
|
||||
january = soup.find('ul', {"class": 'jan'})
|
||||
print(january, '\n')
|
||||
d_january = january.find_all('li') # use january as a parent
|
||||
print(d_january, '\n')
|
||||
for d in d_january:
|
||||
print(d.get_text())
|
||||
@@ -0,0 +1,78 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/6869
|
||||
"""
|
||||
|
||||
import PyPDF2
|
||||
import os
|
||||
import re
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import requests
|
||||
|
||||
|
||||
|
||||
def main():
|
||||
os.chdir('D:/') # PDF文件存放的位置
|
||||
filename = input('输入PDF文件名：')
|
||||
pdfFile = open(filename+'.pdf','rb') # 打开PDF文件
|
||||
links = all_links_in_pdf(pdfFile) # 获取PDF文件中的链接
|
||||
pdfFile.close() # 关闭PDF文件
|
||||
os.chdir('D:/Reference') # 设置参考文献保存的位置
|
||||
download(links) # 下载文献
|
||||
|
||||
|
||||
|
||||
def all_links_in_pdf(pdfFile):
|
||||
pdfReader = PyPDF2.PdfFileReader(pdfFile)
|
||||
pages = pdfReader.getNumPages()
|
||||
i0 = 0
|
||||
links = []
|
||||
print()
|
||||
for page in range(pages):
|
||||
pageSliced = pdfReader.getPage(page)
|
||||
pageObject = pageSliced.getObject()
|
||||
if '/Annots' in pageObject.keys():
|
||||
ann = pageObject['/Annots']
|
||||
old = ''
|
||||
for a in ann:
|
||||
u = a.getObject()
|
||||
if '/A' in u.keys():
|
||||
if re.search(re.compile('^https://doi.org'), u['/A']['/URI']): # 排除其他形式的链接
|
||||
if u['/A']['/URI'] != old: # 排除重复链接
|
||||
print(i0 , u['/A']['/URI'])
|
||||
links.append(u['/A']['/URI']) # 链接存在link数组中
|
||||
i0 += 1
|
||||
old = u['/A']['/URI']
|
||||
return links
|
||||
|
||||
|
||||
|
||||
def download(links):
|
||||
for i0 in [0, 1, 3]: # 指定参考文献下载，如需全部下载用for i0 in range(links.shape[0]):
|
||||
address = links[i0]
|
||||
r = requests.post('https://sci-hub.st/', data={'request': address})
|
||||
print('\n响应结果是：', r)
|
||||
print('访问的地址是：', r.url)
|
||||
soup = BeautifulSoup(r.text, features='lxml')
|
||||
pdf_URL = soup.embed['src']
|
||||
# pdf_URL = soup.iframe['src'] # This is a code line of history version which fails to get pdf URL.
|
||||
if re.search(re.compile('^https:'), pdf_URL):
|
||||
pass
|
||||
else:
|
||||
pdf_URL = 'https:'+pdf_URL
|
||||
print('PDF的地址是：', pdf_URL)
|
||||
name = re.search(re.compile('fdp.*?/'),pdf_URL[::-1]).group()[::-1][1::]
|
||||
print('PDF文件名是：', name)
|
||||
print('保存的位置在：', os.getcwd())
|
||||
print('\n正在下载第',i0,'篇')
|
||||
r = requests.get(pdf_URL, stream=True)
|
||||
with open(name, 'wb') as f:
|
||||
for chunk in r.iter_content(chunk_size=32):
|
||||
f.write(chunk)
|
||||
print('第',i0,'篇下载完成！')
|
||||
print('\n全部下载完成！')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,30 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/6869
|
||||
"""
|
||||
|
||||
import PyPDF2
|
||||
import os
|
||||
import re
|
||||
|
||||
os.chdir('D:/') # PDF文件存放的位置
|
||||
filename = input('输入PDF文件名：')
|
||||
pdfFile = open(filename+'.pdf','rb')
|
||||
pdfReader = PyPDF2.PdfFileReader(pdfFile)
|
||||
pages = pdfReader.getNumPages()
|
||||
i0 = 0
|
||||
for page in range(pages):
|
||||
pageSliced = pdfReader.getPage(page)
|
||||
pageObject = pageSliced.getObject()
|
||||
if '/Annots' in pageObject.keys():
|
||||
ann = pageObject['/Annots']
|
||||
old = ''
|
||||
for a in ann:
|
||||
u = a.getObject()
|
||||
if '/A' in u.keys():
|
||||
if re.search(re.compile('^https://doi.org'), u['/A']['/URI']): # 排除其他形式的链接
|
||||
if u['/A']['/URI'] != old: # 排除重复链接
|
||||
print(i0 , u['/A']['/URI'])
|
||||
i0 += 1
|
||||
old = u['/A']['/URI']
|
||||
pdfFile.close()
|
||||
@@ -0,0 +1,47 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
"""
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
import re
|
||||
import requests
|
||||
import urllib.request
|
||||
import os
|
||||
import ssl
|
||||
ssl._create_default_https_context = ssl._create_unverified_context
|
||||
html = urllib.request.urlopen("https://www.guanjihuan.com/archives/4418").read().decode('utf-8')
|
||||
soup = BeautifulSoup(html, features='lxml')
|
||||
all_a_tag = soup.find_all('a', href=True)
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href']
|
||||
if re.search('https://www.ldoceonline.com/dictionary/', href):
|
||||
print(href[39:])
|
||||
exist_1 = os.path.exists('words_mp3_breProns/'+href[39:]+'.mp3')
|
||||
exist_2 = os.path.exists('words_mp3_ameProns/'+href[39:]+'.mp3')
|
||||
if exist_1 and exist_2:
|
||||
continue
|
||||
header = {'User-Agent':'Mozilla/5.0 (X11; Fedora; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'} # 头部信息
|
||||
request = urllib.request.Request(href,headers=header)
|
||||
reponse = urllib.request.urlopen(request).read()
|
||||
soup2 = BeautifulSoup(reponse, features='lxml')
|
||||
span = soup2.find_all('span', {"class":"speaker brefile fas fa-volume-up hideOnAmp"})
|
||||
for span0 in span:
|
||||
href2 = span0['data-src-mp3']
|
||||
if re.search('https://www.ldoceonline.com/media/english/breProns/', href2):
|
||||
print(href2)
|
||||
r = requests.get(href2, headers=header, stream=True)
|
||||
with open('words_mp3_breProns/'+href[39:]+'.mp3', 'wb') as f:
|
||||
for chunk in r.iter_content(chunk_size=32):
|
||||
f.write(chunk)
|
||||
break
|
||||
span = soup2.find_all('span', {"class":"speaker amefile fas fa-volume-up hideOnAmp"})
|
||||
for span0 in span:
|
||||
href2 = span0['data-src-mp3']
|
||||
if re.search('https://www.ldoceonline.com/media/english/ameProns/', href2):
|
||||
print(href2)
|
||||
r = requests.get(href2, headers=header, stream=True)
|
||||
with open('words_mp3_ameProns/'+href[39:]+'.mp3', 'wb') as f:
|
||||
for chunk in r.iter_content(chunk_size=32):
|
||||
f.write(chunk)
|
||||
break
|
||||
print()
|
||||
@@ -0,0 +1,9 @@
|
||||
# Words in webpage: https://www.guanjihuan.com/archives/4418
|
||||
# installation:
|
||||
# (1) pip install pygame
|
||||
# (2) pip install --upgrade guan
|
||||
|
||||
import guan
|
||||
guan.play_academic_words()
|
||||
# guan.play_academic_words(reverse=1)
|
||||
# guan.play_academic_words(reverse=0, random_on=0, bre_or_ame='ame', show_translation=1, show_link=1, translation_time=2, rest_time=1)
|
||||
@@ -0,0 +1,32 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置文件保存的位置
|
||||
|
||||
|
||||
def main():
|
||||
x = [4, 3, 5, 7]
|
||||
y = [6, 1, 3, 2]
|
||||
value = [3, 1, 10, 2]
|
||||
Plot_2D_Scatter(x, y, value, title='Plot 2D Scatter')
|
||||
|
||||
|
||||
def Plot_2D_Scatter(x, y, value, xlabel='x', ylabel='y', title='title', filename='a'):
|
||||
import matplotlib.pyplot as plt
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111)
|
||||
plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2)
|
||||
for i in range(np.array(x).shape[0]):
|
||||
ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=[(1,0,0)])
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.tick_params(labelsize=15) # 设置刻度值字体大小
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体
|
||||
# plt.savefig(filename+'.jpg', dpi=300)
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,38 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置文件保存的位置
|
||||
|
||||
|
||||
def main():
|
||||
x = [1, 3, 5, 7]
|
||||
y = [2, 4, 6, 8]
|
||||
z = [2, 8, 6, 1]
|
||||
value = [3, 1, 10, 2]
|
||||
Plot_3D_Scatter(x, y, z, value, title='Plot 3D Scatter')
|
||||
|
||||
|
||||
def Plot_3D_Scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='title', filename='a'):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.ticker import LinearLocator
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
plt.subplots_adjust(bottom=0.1, right=0.8)
|
||||
for i in range(np.array(x).shape[0]):
|
||||
ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=[(1,0,0)])
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
# ax.set_zlim(0, 20)
|
||||
# ax.zaxis.set_major_locator(LinearLocator(6)) # 设置z轴主刻度的个数
|
||||
# ax.zaxis.set_major_formatter('{x:.0f}') # 设置z轴主刻度的格式
|
||||
ax.tick_params(labelsize=15) # 设置刻度值字体大小
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体
|
||||
# plt.savefig(filename+'.jpg', dpi=300)
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,43 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置文件保存的位置
|
||||
|
||||
|
||||
def main():
|
||||
x = np.arange(-5, 5, 0.25)
|
||||
y = np.arange(-5, 5, 0.25)
|
||||
X, Y = np.meshgrid(x, y)
|
||||
R = np.sqrt(X**2 + Y**2)
|
||||
Z = np.sin(R)
|
||||
Plot_3D_Surface(x,y,Z)
|
||||
|
||||
|
||||
def Plot_3D_Surface(x,y,matrix,filename='a.jpg', titlename='Plot 3D Surface'):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
plt.subplots_adjust(bottom=0.1, right=0.65) # 调整位置
|
||||
x, y = np.meshgrid(x, y)
|
||||
surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) # Plot the surface.
|
||||
ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
ax.set_zlabel('z', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
# ax.set_zlim(-1, 1) # 设置z轴的范围
|
||||
ax.zaxis.set_major_locator(LinearLocator(5)) # 设置z轴主刻度的个数
|
||||
ax.zaxis.set_major_formatter('{x:.2f}') # 设置z轴主刻度的格式
|
||||
ax.tick_params(labelsize=15) # 设置刻度值字体大小
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体
|
||||
cax = plt.axes([0.75, 0.15, 0.05, 0.75]) # color bar的位置 [左，下，宽度， 高度]
|
||||
cbar = fig.colorbar(surf, cax=cax) # color bar
|
||||
cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小
|
||||
[l.set_family('Times New Roman') for l in cbar.ax.yaxis.get_ticklabels()] # 设置color bar刻度的字体
|
||||
# plt.savefig(filename, dpi=800) # 保存图片文件
|
||||
plt.show()
|
||||
plt.close('all') # 关闭所有plt，防止循环画图时占用内存
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,41 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置文件保存的位置
|
||||
|
||||
|
||||
def main():
|
||||
x = np.arange(-5, 5, 0.25)
|
||||
y = np.arange(-5, 5, 0.25)
|
||||
X, Y = np.meshgrid(x, y)
|
||||
R = np.sqrt(X**2 + Y**2)
|
||||
Z = np.sin(R)
|
||||
Plot_Contour(x,y,Z)
|
||||
|
||||
|
||||
def Plot_Contour(x,y,matrix,filename='a.jpg', titlename='Plot Contour'):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator
|
||||
fig, ax = plt.subplots()
|
||||
plt.subplots_adjust(bottom=0.15, right=0.7) # 调整位置
|
||||
x, y = np.meshgrid(x, y)
|
||||
contour = ax.contourf(x,y,matrix,cmap='jet')
|
||||
ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
# plt.xlabel('x')
|
||||
# plt.ylabel('y')
|
||||
ax.tick_params(labelsize=15) # 设置刻度值字体大小
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体
|
||||
cax = plt.axes([0.75, 0.15, 0.08, 0.73]) # color bar的位置 [左，下，宽度， 高度]
|
||||
cbar = fig.colorbar(contour, cax=cax) # color bar
|
||||
cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小
|
||||
[l.set_family('Times New Roman') for l in cbar.ax.yaxis.get_ticklabels()] # 设置color bar刻度的字体
|
||||
# plt.savefig(filename, dpi=800) # 保存图片文件
|
||||
plt.show()
|
||||
plt.close('all') # 关闭所有plt，防止循环画图时占用内存
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,30 @@
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data') # 设置文件保存的位置
|
||||
|
||||
|
||||
def main():
|
||||
x = np.arange(0.0, 2.0, 0.01)
|
||||
y = 1 + np.sin(2 * np.pi * x)
|
||||
Plot_Line(x,y)
|
||||
|
||||
|
||||
def Plot_Line(x,y,filename='a.jpg', titlename='Plot Line'):
|
||||
import matplotlib.pyplot as plt
|
||||
fig, ax = plt.subplots()
|
||||
plt.subplots_adjust(bottom=0.20, left=0.16)
|
||||
ax.plot(x, y, '-o')
|
||||
ax.grid()
|
||||
ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签
|
||||
ax.tick_params(labelsize=20) # 设置刻度值字体大小
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体
|
||||
# plt.savefig(filename, dpi=800) # 保存图片文件
|
||||
plt.show()
|
||||
plt.close('all') # 关闭所有plt，防止循环画图时占用内存
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,322 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/8734
|
||||
|
||||
函数调用目录：
|
||||
1. x, y = read_one_dimensional_data(filename='a')
|
||||
2. x, y, matrix = read_two_dimensional_data(filename='a')
|
||||
3. write_one_dimensional_data(x, y, filename='a')
|
||||
4. write_two_dimensional_data(x, y, matrix, filename='a')
|
||||
5. plot(x, y, xlabel='x', ylabel='y', title='', filename='a')
|
||||
6. plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a')
|
||||
7. plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a')
|
||||
8. plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a')
|
||||
9. plot_3d_surface(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a')
|
||||
10. creat_animation(image_names, duration_time=0.5, filename='a')
|
||||
11. eigenvalue_array = calculate_eigenvalue_with_one_paramete(x, matrix)
|
||||
12. eigenvalue_array = calculate_eigenvalue_with_two_parameters(x, y, matrix)
|
||||
|
||||
函数对应的功能：
|
||||
1. 读取filename.txt文件中的一维数据y(x)
|
||||
2. 读取filename.txt文件中的二维数据matrix(x,y)
|
||||
3. 把一维数据y(x)写入filename.txt文件
|
||||
4. 把二维数据matrix(x,y)写入filename.txt文件
|
||||
5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
7. 画contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
10. 制作动画
|
||||
11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index]
|
||||
12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index]
|
||||
"""
|
||||
|
||||
|
||||
import numpy as np
|
||||
# import os
|
||||
# os.chdir('D:/data')
|
||||
|
||||
|
||||
def main():
|
||||
pass # 读取数据 + 数据处理 + 保存新数据
|
||||
|
||||
|
||||
# 1. 读取filename.txt文件中的一维数据y(x)
|
||||
def read_one_dimensional_data(filename='a'):
|
||||
f = open(filename+'.txt', 'r')
|
||||
text = f.read()
|
||||
f.close()
|
||||
row_list = np.array(text.split('\n'))
|
||||
dim_column = np.array(row_list[0].split()).shape[0]
|
||||
x = np.array([])
|
||||
y = np.array([])
|
||||
for row in row_list:
|
||||
column = np.array(row.split())
|
||||
if column.shape[0] != 0:
|
||||
x = np.append(x, [float(column[0])], axis=0)
|
||||
y_row = np.zeros(dim_column-1)
|
||||
for dim0 in range(dim_column-1):
|
||||
y_row[dim0] = float(column[dim0+1])
|
||||
if np.array(y).shape[0] == 0:
|
||||
y = [y_row]
|
||||
else:
|
||||
y = np.append(y, [y_row], axis=0)
|
||||
return x, y
|
||||
|
||||
|
||||
# 2. 读取filename.txt文件中的二维数据matrix(x,y)
|
||||
def read_two_dimensional_data(filename='a'):
|
||||
f = open(filename+'.txt', 'r')
|
||||
text = f.read()
|
||||
f.close()
|
||||
row_list = np.array(text.split('\n'))
|
||||
dim_column = np.array(row_list[0].split()).shape[0]
|
||||
x = np.array([])
|
||||
y = np.array([])
|
||||
matrix = np.array([])
|
||||
for i0 in range(row_list.shape[0]):
|
||||
column = np.array(row_list[i0].split())
|
||||
if i0 == 0:
|
||||
x_str = column[1::]
|
||||
x = np.zeros(x_str.shape[0])
|
||||
for i00 in range(x_str.shape[0]):
|
||||
x[i00] = float(x_str[i00])
|
||||
elif column.shape[0] != 0:
|
||||
y = np.append(y, [float(column[0])], axis=0)
|
||||
matrix_row = np.zeros(dim_column-1)
|
||||
for dim0 in range(dim_column-1):
|
||||
matrix_row[dim0] = float(column[dim0+1])
|
||||
if np.array(matrix).shape[0] == 0:
|
||||
matrix = [matrix_row]
|
||||
else:
|
||||
matrix = np.append(matrix, [matrix_row], axis=0)
|
||||
return x, y, matrix
|
||||
|
||||
|
||||
# 3. 把一维数据y(x)写入filename.txt文件
|
||||
def write_one_dimensional_data(x, y, filename='a'):
|
||||
with open(filename+'.txt', 'w') as f:
|
||||
i0 = 0
|
||||
for x0 in x:
|
||||
f.write(str(x0)+' ')
|
||||
if len(y.shape) == 1:
|
||||
f.write(str(y[i0])+'\n')
|
||||
elif len(y.shape) == 2:
|
||||
for j0 in range(y.shape[1]):
|
||||
f.write(str(y[i0, j0])+' ')
|
||||
f.write('\n')
|
||||
i0 += 1
|
||||
|
||||
|
||||
# 4. 把二维数据matrix(x,y)写入filename.txt文件
|
||||
def write_two_dimensional_data(x, y, matrix, filename='a'):
|
||||
with open(filename+'.txt', 'w') as f:
|
||||
f.write('0 ')
|
||||
for x0 in x:
|
||||
f.write(str(x0)+' ')
|
||||
f.write('\n')
|
||||
i0 = 0
|
||||
for y0 in y:
|
||||
f.write(str(y0))
|
||||
j0 = 0
|
||||
for x0 in x:
|
||||
f.write(' '+str(matrix[i0, j0])+' ')
|
||||
j0 += 1
|
||||
f.write('\n')
|
||||
i0 += 1
|
||||
|
||||
|
||||
# 5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改。
|
||||
def plot(x, y, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0):
|
||||
import matplotlib.pyplot as plt
|
||||
fig, ax = plt.subplots()
|
||||
plt.subplots_adjust(bottom=0.20, left=0.18)
|
||||
ax.plot(x, y, '-o')
|
||||
ax.grid()
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.tick_params(labelsize=20)
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels]
|
||||
if save == 1:
|
||||
plt.savefig(filename+'.jpg', dpi=300)
|
||||
if show == 1:
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
|
||||
# 6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改。
|
||||
def plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
plt.subplots_adjust(bottom=0.1, right=0.65)
|
||||
x, y = np.meshgrid(x, y)
|
||||
if len(matrix.shape) == 2:
|
||||
surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False)
|
||||
elif len(matrix.shape) == 3:
|
||||
for i0 in range(matrix.shape[2]):
|
||||
surf = ax.plot_surface(x, y, matrix[:,:,i0], cmap=cm.coolwarm, linewidth=0, antialiased=False)
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.zaxis.set_major_locator(LinearLocator(5))
|
||||
ax.zaxis.set_major_formatter('{x:.2f}')
|
||||
ax.tick_params(labelsize=15)
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels]
|
||||
cax = plt.axes([0.80, 0.15, 0.05, 0.75])
|
||||
cbar = fig.colorbar(surf, cax=cax)
|
||||
cbar.ax.tick_params(labelsize=15)
|
||||
for l in cbar.ax.yaxis.get_ticklabels():
|
||||
l.set_family('Times New Roman')
|
||||
if save == 1:
|
||||
plt.savefig(filename+'.jpg', dpi=300)
|
||||
if show == 1:
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
|
||||
# 7. 画plot_contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改。
|
||||
def plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib import cm
|
||||
from matplotlib.ticker import LinearLocator
|
||||
fig, ax = plt.subplots()
|
||||
plt.subplots_adjust(bottom=0.2, right=0.75, left = 0.16)
|
||||
x, y = np.meshgrid(x, y)
|
||||
contour = ax.contourf(x,y,matrix,cmap='jet')
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.tick_params(labelsize=15)
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels]
|
||||
cax = plt.axes([0.78, 0.17, 0.08, 0.71])
|
||||
cbar = fig.colorbar(contour, cax=cax)
|
||||
cbar.ax.tick_params(labelsize=15)
|
||||
for l in cbar.ax.yaxis.get_ticklabels():
|
||||
l.set_family('Times New Roman')
|
||||
if save == 1:
|
||||
plt.savefig(filename+'.jpg', dpi=300)
|
||||
if show == 1:
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
# 8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
def plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.axes._axes import _log as matplotlib_axes_logger
|
||||
matplotlib_axes_logger.setLevel('ERROR')
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111)
|
||||
plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2)
|
||||
for i in range(np.array(x).shape[0]):
|
||||
ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=(1,0,0))
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.tick_params(labelsize=15)
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels]
|
||||
if save == 1:
|
||||
plt.savefig(filename+'.jpg', dpi=300)
|
||||
if show == 1:
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
# 9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！
|
||||
def plot_3d_scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0):
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.ticker import LinearLocator
|
||||
from matplotlib.axes._axes import _log as matplotlib_axes_logger
|
||||
matplotlib_axes_logger.setLevel('ERROR')
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
plt.subplots_adjust(bottom=0.1, right=0.8)
|
||||
for i in range(np.array(x).shape[0]):
|
||||
ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=(1,0,0))
|
||||
ax.set_title(title, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman')
|
||||
ax.tick_params(labelsize=15)
|
||||
labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
|
||||
[label.set_fontname('Times New Roman') for label in labels]
|
||||
if save == 1:
|
||||
plt.savefig(filename+'.jpg', dpi=300)
|
||||
if show == 1:
|
||||
plt.show()
|
||||
plt.close('all')
|
||||
|
||||
|
||||
# 10. 制作动画
|
||||
def creat_animation(image_names, duration_time=0.5, filename='a'):
|
||||
import imageio
|
||||
images = []
|
||||
for name in image_names:
|
||||
image = name+'.jpg'
|
||||
im = imageio.imread(image)
|
||||
images.append(im)
|
||||
imageio.mimsave(filename+'.gif', images, 'GIF', duration=duration_time) # durantion是延迟时间
|
||||
|
||||
|
||||
# 11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index]
|
||||
def calculate_eigenvalue_with_one_parameter(x, matrix):
|
||||
dim_x = np.array(x).shape[0]
|
||||
i0 = 0
|
||||
if np.array(matrix(0)).shape==():
|
||||
eigenvalue_array = np.zeros((dim_x, 1))
|
||||
for x0 in x:
|
||||
matrix0 = matrix(x0)
|
||||
eigenvalue_array[i0, 0] = np.real(matrix0)
|
||||
i0 += 1
|
||||
else:
|
||||
dim = np.array(matrix(0)).shape[0]
|
||||
eigenvalue_array = np.zeros((dim_x, dim))
|
||||
for x0 in x:
|
||||
matrix0 = matrix(x0)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue_array[i0, :] = np.sort(np.real(eigenvalue[:]))
|
||||
i0 += 1
|
||||
return eigenvalue_array
|
||||
|
||||
|
||||
# 12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index]
|
||||
def calculate_eigenvalue_with_two_parameters(x, y, matrix):
|
||||
dim_x = np.array(x).shape[0]
|
||||
dim_y = np.array(y).shape[0]
|
||||
if np.array(matrix(0,0)).shape==():
|
||||
eigenvalue_array = np.zeros((dim_y, dim_x, 1))
|
||||
i0 = 0
|
||||
for y0 in y:
|
||||
j0 = 0
|
||||
for x0 in x:
|
||||
matrix0 = matrix(x0, y0)
|
||||
eigenvalue_array[i0, j0, 0] = np.real(matrix0)
|
||||
j0 += 1
|
||||
i0 += 1
|
||||
else:
|
||||
dim = np.array(matrix(0, 0)).shape[0]
|
||||
eigenvalue_array = np.zeros((dim_y, dim_x, dim))
|
||||
i0 = 0
|
||||
for y0 in y:
|
||||
j0 = 0
|
||||
for x0 in x:
|
||||
matrix0 = matrix(x0, y0)
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix0)
|
||||
eigenvalue_array[i0, j0, :] = np.sort(np.real(eigenvalue[:]))
|
||||
j0 += 1
|
||||
i0 += 1
|
||||
return eigenvalue_array
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,21 @@
|
||||
import os
|
||||
import time
|
||||
|
||||
start = time.time()
|
||||
|
||||
print('程序1开始的时间：', time.ctime())
|
||||
start1 = time.time()
|
||||
os.chdir('D:') # 代码位置
|
||||
os.system('python a.py') # 运行a.py
|
||||
end1 = time.time()
|
||||
print('程序1运行时间(min)=', (end1-start1)/60,'\n')
|
||||
|
||||
print('程序2开始的时间：', time.ctime())
|
||||
start2 = time.time()
|
||||
os.chdir('E:') # 代码位置
|
||||
os.system('python b.py') # 运行b.py
|
||||
end2 = time.time()
|
||||
print('程序2运行时间(min)=', (end2-start2)/60, '\n')
|
||||
|
||||
end = time.time()
|
||||
print('总运行时间(min)=', (end-start)/60)
|
||||
@@ -0,0 +1,137 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/9129
|
||||
"""
|
||||
|
||||
import os
|
||||
import re
|
||||
import time
|
||||
import logging
|
||||
logging.Logger.propagate = False
|
||||
logging.getLogger().setLevel(logging.ERROR) # 只显示error级别的通知
|
||||
|
||||
|
||||
def main():
|
||||
# 参数
|
||||
key_word_array = ['photonic', 'Berry phase']
|
||||
original_path = 'D:\\文献'
|
||||
|
||||
# 查找所有的PDF文件路径
|
||||
pdf_file_all = find_files_pdf(original_path)
|
||||
print('\n该文件夹下总共有', len(pdf_file_all), '个PDF文件。\n')
|
||||
|
||||
f = open('error.txt','w',encoding='utf-8')
|
||||
f.close()
|
||||
for key_word in key_word_array:
|
||||
f = open(str(key_word)+'.txt','w',encoding='utf-8')
|
||||
f.write('该文件夹下总共有'+str(len(pdf_file_all))+'个PDF文件。\n')
|
||||
f.close()
|
||||
|
||||
# 查找包含关键词的PDF文件
|
||||
i0 = 1
|
||||
begin = time.time()
|
||||
for pdf_file in pdf_file_all:
|
||||
print('查找第', i0, '个文件，', end='')
|
||||
begin0 = time.time()
|
||||
try:
|
||||
content = get_text_from_pdf(pdf_file)
|
||||
for key_word in key_word_array:
|
||||
if re.search(re.compile(key_word),content):
|
||||
print('发现文件！关键词', key_word, '对应的文件位置在：\n\n', pdf_file, '\n')
|
||||
with open(str(key_word)+'.txt','a',encoding='utf-8') as f:
|
||||
f.write('\n查找第'+str(i0)+'个文件时发现文件！位置在：\n'+pdf_file+'\n')
|
||||
except:
|
||||
print('出现异常！位置在：\n\n', pdf_file, '\n')
|
||||
with open('error.txt','a',encoding='utf-8') as f:
|
||||
f.write('\n解析第'+str(i0)+'个文件时出现异常！位置在：\n'+pdf_file+'\n')
|
||||
end0 = time.time()
|
||||
print('用时', end0-begin0, '秒')
|
||||
i0 += 1
|
||||
print('\n全部搜索结束！')
|
||||
end = time.time()
|
||||
print('\n总共用时：', (end-begin)/60, '分')
|
||||
|
||||
|
||||
def find_files_pdf(path): # 查找所有PDF文件
|
||||
file_all = find_files(path)
|
||||
pdf_file_all = []
|
||||
for file0 in file_all:
|
||||
if re.search(re.compile('^fdp.'),file0[::-1]): # 如果文件是以.pdf结尾
|
||||
pdf_file_all.append(file0)
|
||||
return pdf_file_all
|
||||
|
||||
|
||||
def find_files(path): # 查找所有文件
|
||||
file_all = []
|
||||
path_next_loop = [path]
|
||||
for i in range(10000): # i为文件在文件夹中的深度
|
||||
file_all_in_one_loop, path_next_loop = find_files_loop_module(path_next_loop)
|
||||
for file_in_one_loop in file_all_in_one_loop:
|
||||
file_all.append(file_in_one_loop)
|
||||
if path_next_loop == []:
|
||||
break
|
||||
return file_all
|
||||
|
||||
|
||||
def find_files_loop_module(path_all): # 查找文件的一个循环模块
|
||||
file_all_in_one_loop = []
|
||||
path_next_loop = []
|
||||
for path in path_all:
|
||||
filenames = os.listdir(path)
|
||||
for filename in filenames:
|
||||
filename = os.path.join(path,filename)
|
||||
if os.path.isfile(filename): # 如果是文件
|
||||
file_all_in_one_loop.append(filename)
|
||||
else: # 如果是文件夹
|
||||
path_next_loop.append(filename)
|
||||
return file_all_in_one_loop, path_next_loop
|
||||
|
||||
|
||||
def get_text_from_pdf(file_path): # 从PDF中获取文本
|
||||
from pdfminer.pdfparser import PDFParser, PDFDocument
|
||||
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
|
||||
from pdfminer.converter import PDFPageAggregator
|
||||
from pdfminer.layout import LAParams, LTTextBox
|
||||
from pdfminer.pdfinterp import PDFTextExtractionNotAllowed
|
||||
|
||||
# 用文件对象来创建一个pdf文档分析器
|
||||
praser = PDFParser(open(file_path, 'rb'))
|
||||
# 创建一个PDF文档
|
||||
doc = PDFDocument()
|
||||
# 连接分析器 与文档对象
|
||||
praser.set_document(doc)
|
||||
doc.set_parser(praser)
|
||||
|
||||
# 提供初始化密码
|
||||
# 如果没有密码 就创建一个空的字符串
|
||||
doc.initialize()
|
||||
|
||||
# 检测文档是否提供txt转换，不提供就忽略
|
||||
if not doc.is_extractable:
|
||||
raise PDFTextExtractionNotAllowed
|
||||
else:
|
||||
# 创建PDf 资源管理器 来管理共享资源
|
||||
rsrcmgr = PDFResourceManager()
|
||||
# 创建一个PDF设备对象
|
||||
laparams = LAParams()
|
||||
device = PDFPageAggregator(rsrcmgr, laparams=laparams)
|
||||
# 创建一个PDF解释器对象
|
||||
interpreter = PDFPageInterpreter(rsrcmgr, device)
|
||||
|
||||
# 循环遍历列表，每次处理一个page的内容
|
||||
content = ''
|
||||
for page in doc.get_pages():
|
||||
interpreter.process_page(page)
|
||||
# 接受该页面的LTPage对象
|
||||
layout = device.get_result()
|
||||
# 这里layout是一个LTPage对象，里面存放着这个 page 解析出的各种对象
|
||||
# 包括 LTTextBox, LTFigure, LTImage, LTTextBoxHorizontal 等
|
||||
for x in layout:
|
||||
if isinstance(x, LTTextBox):
|
||||
# print(x.get_text().strip())
|
||||
content = content + x.get_text().strip()
|
||||
return content
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,63 @@
|
||||
import os
|
||||
os.chdir('D:/') # PDF文件存放的位置
|
||||
import logging
|
||||
logging.Logger.propagate = False
|
||||
logging.getLogger().setLevel(logging.ERROR) # 只显示error级别的通知
|
||||
|
||||
|
||||
def main():
|
||||
content = get_text_from_pdf('a')
|
||||
with open('a.txt', 'w', encoding='utf-8') as f:
|
||||
f.write(content)
|
||||
|
||||
|
||||
def get_text_from_pdf(filename):
|
||||
from pdfminer.pdfparser import PDFParser, PDFDocument
|
||||
from pdfminer.pdfinterp import PDFResourceManager, PDFPageInterpreter
|
||||
from pdfminer.converter import PDFPageAggregator
|
||||
from pdfminer.layout import LAParams, LTTextBox
|
||||
from pdfminer.pdfinterp import PDFTextExtractionNotAllowed
|
||||
|
||||
path = filename+".pdf"
|
||||
|
||||
# 用文件对象来创建一个pdf文档分析器
|
||||
praser = PDFParser(open(path, 'rb'))
|
||||
# 创建一个PDF文档
|
||||
doc = PDFDocument()
|
||||
# 连接分析器 与文档对象
|
||||
praser.set_document(doc)
|
||||
doc.set_parser(praser)
|
||||
|
||||
# 提供初始化密码
|
||||
# 如果没有密码 就创建一个空的字符串
|
||||
doc.initialize()
|
||||
|
||||
# 检测文档是否提供txt转换，不提供就忽略
|
||||
if not doc.is_extractable:
|
||||
raise PDFTextExtractionNotAllowed
|
||||
else:
|
||||
# 创建PDf 资源管理器 来管理共享资源
|
||||
rsrcmgr = PDFResourceManager()
|
||||
# 创建一个PDF设备对象
|
||||
laparams = LAParams()
|
||||
device = PDFPageAggregator(rsrcmgr, laparams=laparams)
|
||||
# 创建一个PDF解释器对象
|
||||
interpreter = PDFPageInterpreter(rsrcmgr, device)
|
||||
|
||||
# 循环遍历列表，每次处理一个page的内容
|
||||
content = ''
|
||||
for page in doc.get_pages():
|
||||
interpreter.process_page(page)
|
||||
# 接受该页面的LTPage对象
|
||||
layout = device.get_result()
|
||||
# 这里layout是一个LTPage对象，里面存放着这个 page 解析出的各种对象
|
||||
# 包括 LTTextBox, LTFigure, LTImage, LTTextBoxHorizontal 等
|
||||
for x in layout:
|
||||
if isinstance(x, LTTextBox):
|
||||
# print(x.get_text().strip())
|
||||
content = content + x.get_text().strip()
|
||||
return content
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,33 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
"""
|
||||
|
||||
from urllib import response
|
||||
from bs4 import BeautifulSoup
|
||||
import re
|
||||
import requests
|
||||
import urllib.request
|
||||
import os
|
||||
import ssl
|
||||
from urllib.request import urlopen
|
||||
|
||||
ssl._create_default_https_context = ssl._create_unverified_context
|
||||
html = urllib.request.urlopen("https://www.guanjihuan.com/archives/10897").read().decode('utf-8')
|
||||
soup = BeautifulSoup(html, features='lxml')
|
||||
all_a_tag = soup.find_all('a', href=True)
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href']
|
||||
if re.search('https://www.merriam-webster.com/dictionary/', href):
|
||||
print(href[43:])
|
||||
exist = os.path.exists('prons/'+href[43:]+'.mp3')
|
||||
if exist:
|
||||
continue
|
||||
header = {'User-Agent':'Mozilla/5.0 (X11; Fedora; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'} # 头部信息
|
||||
html = urlopen(href).read().decode('utf-8')
|
||||
mp3_file = re.findall('https://media.merriam-webster.com/audio/prons/en/us/mp3/.*.mp3",', html, re.S)[0][:-2]
|
||||
print(mp3_file[:-2])
|
||||
print()
|
||||
r = requests.get(mp3_file, headers=header, stream=True)
|
||||
with open('prons/'+href[43:]+'.mp3', 'wb') as f:
|
||||
for chunk in r.iter_content(chunk_size=32):
|
||||
f.write(chunk)
|
||||
@@ -0,0 +1,8 @@
|
||||
# Words in webpage: https://www.guanjihuan.com/archives/10897
|
||||
# installation:
|
||||
# (1) pip install pygame
|
||||
# (2) pip install --upgrade guan
|
||||
|
||||
import guan
|
||||
guan.play_element_words()
|
||||
# guan.play_element_words(random_on=0, show_translation=1, show_link=1, translation_time=2, rest_time=1)
|
||||
@@ -0,0 +1,29 @@
|
||||
import numpy as np
|
||||
|
||||
# 设置
|
||||
cpus = 7 # 使用的CPU个数（等于提交任务的个数）
|
||||
parameter_array_all = np.arange(0, 10, 0.1) # 需要计算的参数
|
||||
|
||||
|
||||
# 通过.sh脚本文件修改的任务指标。job_index从0开始，最大值为cpus-1
|
||||
job_index = -1
|
||||
|
||||
|
||||
# 预处理
|
||||
len_of_parameter_all = len(parameter_array_all) # 需要计算参数的个数
|
||||
if len_of_parameter_all%cpus == 0:
|
||||
len_parameter = int(len_of_parameter_all/cpus) # 一个CPU/任务需要计算参数的个数
|
||||
parameter_array = parameter_array_all[job_index*len_parameter:(job_index+1)*len_parameter]
|
||||
else:
|
||||
len_parameter = int(len_of_parameter_all/(cpus-1)) # 一个CPU/任务需要计算参数的个数
|
||||
if job_index != cpus-1:
|
||||
parameter_array = parameter_array_all[job_index*len_parameter:(job_index+1)*len_parameter]
|
||||
else:
|
||||
parameter_array = parameter_array_all[job_index*len_parameter:len_of_parameter_all]
|
||||
|
||||
|
||||
# 任务
|
||||
with open('a'+str(job_index)+'.txt', 'w') as f:
|
||||
for parameter in parameter_array:
|
||||
result = parameter**2
|
||||
f.write(str(parameter)+' '+str(result)+'\n')
|
||||
@@ -0,0 +1,5 @@
|
||||
#!/bin/sh
|
||||
#PBS -N task
|
||||
#PBS -l nodes=1:ppn=1
|
||||
export OMP_NUM_THREADS=1
|
||||
python a.py
|
||||
@@ -0,0 +1,6 @@
|
||||
f = open('combine.txt', 'w')
|
||||
for job_index in range(7):
|
||||
with open('a'+str(job_index)+'.txt', 'r') as f0:
|
||||
text = f0.read()
|
||||
f.write(text)
|
||||
f.close()
|
||||
@@ -0,0 +1,14 @@
|
||||
#!/bin/sh
|
||||
|
||||
for ((job_index=0; job_index<7; job_index++))
|
||||
do
|
||||
|
||||
cp a.py a${job_index}.py
|
||||
sed -i "s/job_index = -1/job_index = ${job_index}/" a${job_index}.py
|
||||
|
||||
|
||||
cp a.sh a${job_index}.sh
|
||||
sed -i "s/python a.py/python a${job_index}.py/" a${job_index}.sh
|
||||
qsub a${job_index}.sh
|
||||
|
||||
done
|
||||
@@ -0,0 +1,88 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/13623
|
||||
"""
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
from collections import Counter
|
||||
import datetime
|
||||
import random
|
||||
import time
|
||||
|
||||
|
||||
# time.sleep(random.uniform(0,1800)) # 爬虫简单伪装，在固定时间后0到30分钟后开始运行。调试的时候把该语句注释。
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
|
||||
# 获取链接
|
||||
try:
|
||||
with open('prb_link_list.txt', 'r', encoding='UTF-8') as f: # 如果文件存在
|
||||
link_list = f.read().split('\n') # 历史已经访问过的链接（数组类型）
|
||||
except:
|
||||
with open('prb_link_list.txt', 'w', encoding='UTF-8') as f: # 如果文件不存在
|
||||
link_list = []
|
||||
f = open('prb_link_list.txt', 'a', encoding='UTF-8') # 打开文件（补充）
|
||||
f.write('\nLink list obtained on '+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+':\n')
|
||||
match_href = [] # 在本次运行中满足条件的链接
|
||||
for loop in range(3):
|
||||
if loop == 0:
|
||||
start_link = "https://journals.aps.org/prb/recent?page=1" # 看第一页
|
||||
elif loop == 1:
|
||||
start_link = "https://journals.aps.org/prb/recent?page=2" # 看第二页
|
||||
elif loop == 2:
|
||||
start_link = "https://journals.aps.org/prb/recent?page=3" # 看第三页（三页基本上覆盖了当天的所有更新）
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_a_tag = soup.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/abstract/', href): # 文章的链接
|
||||
if re.search('https://journals.aps.org', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://journals.aps.org'+ href
|
||||
if href not in match_href and href not in link_list and re.search('\?', href)==None: # 链接不重复
|
||||
match_href.append(href)
|
||||
f.write(href+'\n')
|
||||
f.close()
|
||||
|
||||
|
||||
|
||||
# 获取摘要
|
||||
try:
|
||||
f = open('prb_all.txt', 'a', encoding='UTF-8') # 全部记录
|
||||
except:
|
||||
f = open('prb_all.txt', 'w', encoding='UTF-8') # 如果文件不存在
|
||||
try:
|
||||
f_month = open('prb_'+str(year)+'.'+str(month).rjust(2,'0')+'.txt', 'a', encoding='UTF-8') # 一个月的记录
|
||||
except:
|
||||
f_month = open('prb_'+str(year)+'.'+str(month).rjust(2,'0')+'.txt', 'w', encoding='UTF-8') # 如果文件不存在
|
||||
f.write('\n\n['+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+'][total number='+str(len(match_href))+']\n\n\n')
|
||||
f_month.write('\n\n['+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+'][total number='+str(len(match_href))+']\n\n\n')
|
||||
print('total number=', len(match_href)) # 调试的时候显示这个
|
||||
i00 = 0
|
||||
for href in match_href:
|
||||
i00 += 1
|
||||
print('reading number', i00, '...') # 调试的时候显示这个
|
||||
# time.sleep(random.uniform(10,110)) # 爬虫简单伪装，休息一分钟左右。如果链接个数有60个，那么程序运行时间延长60分钟。调试的时候把该语句注释。
|
||||
try:
|
||||
html = urlopen(href).read().decode('utf-8') # 打开文章链接
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
title = soup.title # 文章标题
|
||||
f.write(str(title.get_text())+'\n\n')
|
||||
f_month.write(str(title.get_text())+'\n\n')
|
||||
f.write(str(href)+'\n\n') # 文章链接
|
||||
f_month.write(str(href)+'\n\n')
|
||||
abstract = re.findall('"yes"><p>.*</p><div', html, re.S)[0][9:-8] # 文章摘要
|
||||
word_list = abstract.split(' ') # 划分单词
|
||||
for word in word_list:
|
||||
if re.search('<', word)==None and re.search('>', word)==None: # 有些内容满足过滤条件，因此信息可能会丢失。
|
||||
f.write(word+' ')
|
||||
f_month.write(word+' ')
|
||||
f.write('\n\n\n')
|
||||
f_month.write('\n\n\n')
|
||||
except:
|
||||
pass
|
||||
f.close()
|
||||
@@ -0,0 +1,88 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/13623
|
||||
"""
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
from collections import Counter
|
||||
import datetime
|
||||
import random
|
||||
import time
|
||||
|
||||
|
||||
# time.sleep(random.uniform(0,1800)) # 爬虫简单伪装，在固定时间后0到30分钟后开始运行。调试的时候把该语句注释。
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
|
||||
# 获取链接
|
||||
try:
|
||||
with open('prl_link_list.txt', 'r', encoding='UTF-8') as f: # 如果文件存在
|
||||
link_list = f.read().split('\n') # 历史已经访问过的链接（数组类型）
|
||||
except:
|
||||
with open('prl_link_list.txt', 'w', encoding='UTF-8') as f: # 如果文件不存在
|
||||
link_list = []
|
||||
f = open('prl_link_list.txt', 'a', encoding='UTF-8') # 打开文件（补充）
|
||||
f.write('\nLink list obtained on '+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+':\n')
|
||||
match_href = [] # 在本次运行中满足条件的链接
|
||||
for loop in range(3):
|
||||
if loop == 0:
|
||||
start_link = "https://journals.aps.org/prl/recent?page=1" # 看第一页
|
||||
elif loop == 1:
|
||||
start_link = "https://journals.aps.org/prl/recent?page=2" # 看第二页
|
||||
elif loop == 2:
|
||||
start_link = "https://journals.aps.org/prl/recent?page=3" # 看第三页（三页基本上覆盖了当天的所有更新）
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_a_tag = soup.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/abstract/', href): # 文章的链接
|
||||
if re.search('https://journals.aps.org', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://journals.aps.org'+ href
|
||||
if href not in match_href and href not in link_list and re.search('\?', href)==None: # 链接不重复
|
||||
match_href.append(href)
|
||||
f.write(href+'\n')
|
||||
f.close()
|
||||
|
||||
|
||||
|
||||
# 获取摘要
|
||||
try:
|
||||
f = open('prl_all.txt', 'a', encoding='UTF-8') # 全部记录
|
||||
except:
|
||||
f = open('prl_all.txt', 'w', encoding='UTF-8') # 如果文件不存在
|
||||
try:
|
||||
f_month = open('prl_'+str(year)+'.'+str(month).rjust(2,'0')+'.txt', 'a', encoding='UTF-8') # 一个月的记录
|
||||
except:
|
||||
f_month = open('prl_'+str(year)+'.'+str(month).rjust(2,'0')+'.txt', 'w', encoding='UTF-8') # 如果文件不存在
|
||||
f.write('\n\n['+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+'][total number='+str(len(match_href))+']\n\n\n')
|
||||
f_month.write('\n\n['+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+'][total number='+str(len(match_href))+']\n\n\n')
|
||||
print('total number=', len(match_href)) # 调试的时候显示这个
|
||||
i00 = 0
|
||||
for href in match_href:
|
||||
i00 += 1
|
||||
print('reading number', i00, '...') # 调试的时候显示这个
|
||||
# time.sleep(random.uniform(10,110)) # 爬虫简单伪装，休息一分钟左右。如果链接个数有60个，那么程序运行时间延长60分钟。调试的时候把该语句注释。
|
||||
try:
|
||||
html = urlopen(href).read().decode('utf-8') # 打开文章链接
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
title = soup.title # 文章标题
|
||||
f.write(str(title.get_text())+'\n\n')
|
||||
f_month.write(str(title.get_text())+'\n\n')
|
||||
f.write(str(href)+'\n\n') # 文章链接
|
||||
f_month.write(str(href)+'\n\n')
|
||||
abstract = re.findall('"yes"><p>.*</p><div', html, re.S)[0][9:-8] # 文章摘要
|
||||
word_list = abstract.split(' ') # 划分单词
|
||||
for word in word_list:
|
||||
if re.search('<', word)==None and re.search('>', word)==None: # 有些内容满足过滤条件，因此信息可能会丢失。
|
||||
f.write(word+' ')
|
||||
f_month.write(word+' ')
|
||||
f.write('\n\n\n')
|
||||
f_month.write('\n\n\n')
|
||||
except:
|
||||
pass
|
||||
f.close()
|
||||
@@ -0,0 +1,41 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/13623
|
||||
"""
|
||||
|
||||
import re
|
||||
from collections import Counter
|
||||
|
||||
|
||||
def main():
|
||||
file_name = 'prb_all.txt'
|
||||
with open(file_name, 'r', encoding='UTF-8') as f: # 打开文件
|
||||
paper_list = f.read().split('\n\n\n') # 通过三个回车划分不同文章
|
||||
word_list = []
|
||||
ignore = ignore_words() # 过滤常见单词
|
||||
for paper in paper_list:
|
||||
word_list_in_one_paper = []
|
||||
if len(paper)>20: # 通过字符串长度过滤日期
|
||||
content_list = paper.split('\n\n') # 通过两个回车划分内容
|
||||
for content in content_list:
|
||||
if re.search('https://', content)==None: # 过滤文章链接
|
||||
words = content.split(' ') # 通过空格划分单词
|
||||
for word in words:
|
||||
if word not in word_list_in_one_paper: # 一篇文章的某个单词只统计一次
|
||||
if word not in ignore and len(word)>1: # 过滤词汇
|
||||
word_list.append(word)
|
||||
word_list_in_one_paper.append(word)
|
||||
num = 300
|
||||
most_common_words = Counter(word_list).most_common(num) # 统计出现最多的num个词汇
|
||||
print('\n出现频率最高的前', num, '个词汇：')
|
||||
for word in most_common_words:
|
||||
print(word)
|
||||
|
||||
|
||||
def ignore_words(): # 可自行增删
|
||||
ignore = ['Phys.', 'the', 'to', 'of', 'in', 'under', 'and', 'by', 'The', 'at', 'with', 'up', 'be', 'above', 'below', 'are', 'is', 'for', 'that', 'as', 'we', '<a', 'abstract', 'abstract"','<span', 'which', 'We', 'such', 'has', 'two', 'these', 'it', 'all', 'results', 'result', 'each', 'have', 'between', 'on', 'an', 'can', 'also', 'from', 'Our', 'our', 'using', 'where', 'These', 'out', 'both', 'due', 'less', 'along', 'but', 'In', 'show', 'into', 'study', 'find', 'provide', 'change','not', 'open', 'this', 'show', 'into', 'study', 'find', 'provide', 'change', 'present', 'Using', 'large', 'This', 'However', 'appear', 'studied', 'obtain', 'been', 'Both', 'they', 'effects', 'effect', 'compute', 'more', 'does', 'shown', 'Based', 'reveal', 'highly', 'number', 'However,', 'was', 'near', 'full', 'based', 'several', 'suggest', 'agreement', 'predicted', 'values', 'work', 'emphasize', 'without', 'or', 'work,', 'studies', 'future', 'identify', 'present.', 'predict', 'presence', 'their', 'were', 'From', 'its', 'By', 'how', 'ground', 'observed', 'recent', 'For', 'other', 'Here', 'test', 'further', 'Its', 'similar', 'however,', 'range', 'within', 'value', 'possible', 'may', 'than', 'low', 'us', 'obtained', 'around', 'consider', 'about', 'very', 'will', 'when', 'played', 'consist', 'consists', 'Here,', 'observe', 'gives', 'It', 'over', 'cannot', 'As', 'whose', 'new', 'some', 'only', 'from', 'yields', 'shows', 'data', 'direct', 'related', 'different', 'evidence', 'role', 'function', 'origin', 'specific', 'set', 'confirm', 'give', 'Moreover', 'develop', 'including', 'could', 'used', 'means', 'allows', 'make', 'e.g.,', 'provides', 'system', 'systems', 'field', 'fields', 'model', 'model,', 'state', 'states', 'states.', 'state.', 'band', 'bands', 'method', 'methods', 'nature', 'rate', 'zero', 'single', 'theory', 'first', 'one', 'complex', 'approach', 'schemes', 'terms', 'even', 'case', 'analysis', 'weight', 'volume', 'evolution', 'well', 'external', 'measured', 'introducing', 'dependence', 'properties', 'demonstrate', 'remains', 'through', 'measurements', 'samples', 'findings', 'respect', 'investigate', 'behavior', 'importance', 'considered', 'experimental', 'increase', 'propose', 'follows', 'increase', 'emerged', 'interesting', 'behaviors', 'influenced', 'paramount', 'indicate', 'Rev.', 'concepts', 'induced', 'zone', 'regions', 'exact', 'contribution', 'behavior', 'formation', 'measurements.', 'utilizing', 'constant', 'regime', 'features', 'strength', 'compare', 'determined', 'combination', 'compare', 'determined', 'At', 'inside', 'ambient', 'then', 'important', 'report', 'Moreover,', 'Despite', 'found', 'because', 'process', 'and,', 'significantly', 'realized', 'much', 'natural', 'since', 'grows', 'any', 'compared', 'while', 'forms.', 'appears', 'indicating', 'coefficient', 'suggested', 'time', 'exhibits', 'calculations.', 'developed', 'array', 'discuss', 'field', 'becomes', 'allowing', 'indicates', 'via', 'introduce', 'considering', 'times.', 'constructed', 'explain', 'form', 'owing', 'parameters.', 'parameter', 'operation', 'probe', 'experiments', 'interest', 'strategies', 'seen', 'emerge', 'generic', 'geometry', 'numbers', 'observation', 'avenue', 'theretically', 'three', 'excellent', 'amount', 'notable', 'example', 'being', 'promising', 'latter', 'little', 'imposed', 'put', 'resource', 'together', 'produce', 'successfully','there', 'enhanced', 'this', 'great', 'dirven', 'increasing','should', 'otherwise', 'Further', 'field,', 'known', 'changes', 'still', 'beyond', 'various', 'center', 'previously', 'way', 'peculiar', 'detailed', 'understanding', 'good', 'years', 'where', 'Me', 'origins', 'years.', 'attributed', 'known,', 'them', 'reported', 'no', 'systems', 'agree', 'examined', 'rise', 'calculate', 'those', 'particular', 'relation', 'defined', 'either', 'again', 'current', 'exhibit', 'calculated', 'here', 'made', 'Further', 'consisting', 'constitutes', 'originated', 'if', 'exceed', 'access']
|
||||
return ignore
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,88 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/14684
|
||||
"""
|
||||
|
||||
import sympy
|
||||
|
||||
|
||||
# 定义符号
|
||||
print()
|
||||
print('定义符号：')
|
||||
x, y, z = sympy.symbols('x y z') # 使用sympy.symbols
|
||||
print(x)
|
||||
print(y+1)
|
||||
print(z**2)
|
||||
print()
|
||||
|
||||
|
||||
# 替换（Substitution）
|
||||
print('变量替换：')
|
||||
expression_1 = x**2+1
|
||||
value_1 = expression_1.subs(x, 3) # 使用.subs()方法
|
||||
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'
|
||||
print(expression_string)
|
||||
expression_2 = sympy.sympify(expression_string) # 使用sympy.sympify()
|
||||
print(expression_2)
|
||||
value_2 = expression_2.subs(x, 2)
|
||||
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()
|
||||
print(expression_3)
|
||||
print()
|
||||
|
||||
|
||||
# 符号矩阵
|
||||
print('符号矩阵：')
|
||||
a, b = sympy.symbols('a b')
|
||||
matrix = sympy.Matrix([[1, a], [0, b]]) # 使用sympy.Matrix()
|
||||
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) # 使用sympy.pprint()输出
|
||||
print('\n', sympy.pretty(eigenvalue)) # 使用sympy.pretty()美化后输出
|
||||
print()
|
||||
|
||||
eigenvector = matrix.eigenvects() # 使用.eigenvects()方法
|
||||
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, '\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
|
||||
print('和numpy对比：')
|
||||
import numpy as np
|
||||
matrix = np.array([[1, -4], [0, 2]])
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix)
|
||||
print('特征值\n', eigenvalue)
|
||||
print('特征向量\n', eigenvector)
|
||||
print()
|
||||
@@ -0,0 +1,32 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/17789
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
|
||||
def hamiltonian(width=2, length=2):
|
||||
h00 = np.zeros((width*length, width*length))
|
||||
for i0 in range(length):
|
||||
for j0 in range(width-1):
|
||||
h00[i0*width+j0, i0*width+j0+1] = 1
|
||||
h00[i0*width+j0+1, i0*width+j0] = 1
|
||||
for i0 in range(length-1):
|
||||
for j0 in range(width):
|
||||
h00[i0*width+j0, (i0+1)*width+j0] = 1
|
||||
h00[(i0+1)*width+j0, i0*width+j0] = 1
|
||||
return h00
|
||||
|
||||
print('矩阵：\n', hamiltonian(), '\n')
|
||||
|
||||
eigenvalue, eigenvector = np.linalg.eig(hamiltonian())
|
||||
print('eig求解特征值：', eigenvalue)
|
||||
print('eig求解特征向量：\n',eigenvector)
|
||||
print('判断特征向量是否正交：\n', np.dot(eigenvector.transpose(), eigenvector))
|
||||
|
||||
print()
|
||||
|
||||
eigenvalue, eigenvector = np.linalg.eigh(hamiltonian())
|
||||
print('eigh求解特征值：', eigenvalue)
|
||||
print('eigh求解特征向量：\n',eigenvector)
|
||||
print('判断特征向量是否正交：\n', np.dot(eigenvector.transpose(), eigenvector))
|
||||
37
language_learning/python/2021.11.17_zhihu/nature_physics.py
Normal file
37
language_learning/python/2021.11.17_zhihu/nature_physics.py
Normal file
@@ -0,0 +1,37 @@
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
import datetime
|
||||
|
||||
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
|
||||
f = open('nature_physics.html', 'w', encoding='UTF-8')
|
||||
f.write('<meta charset="utf-8"><style type="text/css">a{text-decoration: none;color: #0a5794;}a:hover {text-decoration: underline;color: red; }</style>')
|
||||
f.write('<p>'+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+' 已更新</p>')
|
||||
|
||||
match_href = []
|
||||
start_link = "https://www.nature.com/nphys/research-articles"
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_article = soup.find_all('article', {"class":"u-full-height c-card c-card--flush"})
|
||||
for article in all_article:
|
||||
all_a_tag = article.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/articles/', href): # 文章的链接
|
||||
if re.search('https://www.nature.com', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://www.nature.com'+ href
|
||||
if href not in match_href and re.search('\?', href)==None: # 链接不重复
|
||||
match_href.append(href)
|
||||
f.write('<li><a target=\"_blank\" href=\"')
|
||||
f.write(href) # 文章链接
|
||||
f.write('\">')
|
||||
f.write(a_tag.get_text())
|
||||
f.write('</a> ')
|
||||
time = article.find('time', {"class": "c-meta__item c-meta__item--block-at-lg"}).get_text()
|
||||
f.write(time+'</li>')
|
||||
f.close()
|
||||
@@ -0,0 +1,36 @@
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
import datetime
|
||||
|
||||
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
f = open('physics_magazine.html', 'w', encoding='UTF-8')
|
||||
f.write('<meta charset="utf-8"><style type="text/css">a{text-decoration: none;color: #0a5794;}a:hover {text-decoration: underline;color: red; }</style>')
|
||||
f.write('<p>'+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+' 已更新</p>')
|
||||
|
||||
match_href = []
|
||||
start_link = "https://physics.aps.org/"
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_articles = soup.find_all('div', {"class":"feed-item-details"})
|
||||
for article in all_articles:
|
||||
all_a_tag = article.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/articles/', href): # 文章的链接
|
||||
if re.search('https://physics.aps.org', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://physics.aps.org'+ href
|
||||
if href not in match_href:
|
||||
match_href.append(href)
|
||||
f.write('<li><a target=\"_blank\" href=\"')
|
||||
f.write(href) # 文章链接
|
||||
f.write('\">')
|
||||
f.write(a_tag.get_text())
|
||||
f.write('</a> ')
|
||||
time = article.find('time', {"class": "feed-item-date"}).get_text()
|
||||
f.write(time+'</li>')
|
||||
f.close()
|
||||
42
language_learning/python/2021.11.17_zhihu/prb.py
Normal file
42
language_learning/python/2021.11.17_zhihu/prb.py
Normal file
@@ -0,0 +1,42 @@
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
import datetime
|
||||
|
||||
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
|
||||
f = open('prb.html', 'w', encoding='UTF-8')
|
||||
f.write('<meta charset="utf-8"><style type="text/css">a{text-decoration: none;color: #0a5794;}a:hover {text-decoration: underline;color: red; }</style>')
|
||||
f.write('<p>'+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+' 已更新</p>')
|
||||
|
||||
match_href = []
|
||||
for loop in range(1):
|
||||
if loop == 0:
|
||||
start_link = "https://journals.aps.org/prb/recent" # 看第一页
|
||||
# elif loop == 1:
|
||||
# start_link = "https://journals.aps.org/prb/recent?page=2" # 看第二页
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_article = soup.find_all('div', {"class":"article panel article-result"})
|
||||
for article in all_article:
|
||||
all_a_tag = article.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/abstract/', href): # 文章的链接
|
||||
if re.search('https://journals.aps.org', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://journals.aps.org'+ href
|
||||
if href not in match_href and re.search('\?', href)==None: # 链接不重复
|
||||
match_href.append(href)
|
||||
f.write('<li><a target=\"_blank\" href=\"')
|
||||
f.write(href) # 文章链接
|
||||
f.write('\">')
|
||||
f.write(a_tag.get_text())
|
||||
f.write('</a> ')
|
||||
info = article.find('h6', {"class": "pub-info"}).get_text()
|
||||
f.write(re.findall('– Published .*', info, re.S)[0][12:]+'</li>')
|
||||
f.close()
|
||||
|
||||
42
language_learning/python/2021.11.17_zhihu/prl.py
Normal file
42
language_learning/python/2021.11.17_zhihu/prl.py
Normal file
@@ -0,0 +1,42 @@
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
import datetime
|
||||
|
||||
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
|
||||
f = open('prl.html', 'w', encoding='UTF-8')
|
||||
f.write('<meta charset="utf-8"><style type="text/css">a{text-decoration: none;color: #0a5794;}a:hover {text-decoration: underline;color: red; }</style>')
|
||||
f.write('<p>'+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+' 已更新</p>')
|
||||
|
||||
match_href = []
|
||||
for loop in range(1):
|
||||
if loop == 0:
|
||||
start_link = "https://journals.aps.org/prl/recent" # 看第一页
|
||||
# elif loop == 1:
|
||||
# start_link = "https://journals.aps.org/prl/recent?page=2" # 看第二页
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_article = soup.find_all('div', {"class":"article panel article-result"})
|
||||
for article in all_article:
|
||||
all_a_tag = article.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('/abstract/', href): # 文章的链接
|
||||
if re.search('https://journals.aps.org', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https://journals.aps.org'+ href
|
||||
if href not in match_href and re.search('\?', href)==None: # 链接不重复
|
||||
match_href.append(href)
|
||||
f.write('<li><a target=\"_blank\" href=\"')
|
||||
f.write(href) # 文章链接
|
||||
f.write('\">')
|
||||
f.write(a_tag.get_text())
|
||||
f.write('</a> ')
|
||||
info = article.find('h6', {"class": "pub-info"}).get_text()
|
||||
f.write(re.findall('– Published.*', info, re.S)[0][12:]+'</li>')
|
||||
f.close()
|
||||
|
||||
61
language_learning/python/2021.11.17_zhihu/zhihu.py
Normal file
61
language_learning/python/2021.11.17_zhihu/zhihu.py
Normal file
@@ -0,0 +1,61 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/17937
|
||||
"""
|
||||
|
||||
from bs4 import BeautifulSoup
|
||||
from urllib.request import urlopen
|
||||
import re
|
||||
import datetime
|
||||
|
||||
year = datetime.datetime.now().year
|
||||
month = datetime.datetime.now().month
|
||||
day = datetime.datetime.now().day
|
||||
|
||||
# 获取链接
|
||||
match_href = []
|
||||
# 由于没有模拟登录知乎，因此只能爬取到最新的两篇文章
|
||||
authors = ["https://www.zhihu.com/people/guanjihuan/posts", # Guan
|
||||
]
|
||||
for i0 in range(len(authors)):
|
||||
start_link = authors[i0]
|
||||
html = urlopen(start_link).read().decode('utf-8') # 打开网页
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
all_a_tag = soup.find_all('a', href=True) # 获取超链接标签
|
||||
for a_tag in all_a_tag:
|
||||
href = a_tag['href'] # 超链接字符串
|
||||
if re.search('//zhuanlan.zhihu.com/p/', href) and not re.search('edit', href): # 文章的链接
|
||||
if re.search('https:', href)==None: # 如果链接不是完整的，那么补充完整
|
||||
href = 'https:'+ href
|
||||
if href not in match_href:
|
||||
match_href.append(href)
|
||||
# 对链接进行排序
|
||||
numbers = []
|
||||
match_href_new = []
|
||||
for href in match_href:
|
||||
numbers.append(int(href[29:]))
|
||||
numbers.sort(reverse = True)
|
||||
for n in numbers:
|
||||
match_href_new.append('https://zhuanlan.zhihu.com/p/'+str(n))
|
||||
|
||||
# 获取内容并写入文件
|
||||
f = open('zhihu.html', 'w', encoding='UTF-8')
|
||||
f.write('<meta charset="utf-8"><style type="text/css">a{text-decoration: none;color: #0a5794;}a:hover {text-decoration: underline;color: red; }</style>')
|
||||
f.write('<p>'+str(year)+'.'+str(month).rjust(2,'0')+'.'+str(day).rjust(2,'0')+' 已更新</p>')
|
||||
for href in match_href_new:
|
||||
try:
|
||||
html = urlopen(href).read().decode('utf-8') # 打开文章链接
|
||||
soup = BeautifulSoup(html, features='lxml') # 放入soup中
|
||||
title = soup.title # 文章标题
|
||||
f.write('<li><a target=\"_blank\" href=\"')
|
||||
f.write(str(href)) # 文章链接
|
||||
f.write('\">')
|
||||
f.write(str(title.get_text()[:-5]))
|
||||
f.write('</a> ')
|
||||
author = soup.find("span", {"class": "UserLink AuthorInfo-name"})
|
||||
f.write(str(author.get_text()+' '))
|
||||
post_time = soup.find("div", {"class" : "ContentItem-time"})
|
||||
f.write(str(post_time.get_text()[4:-6])+'</li>')
|
||||
except:
|
||||
pass
|
||||
f.close()
|
||||
@@ -0,0 +1,4 @@
|
||||
import guan
|
||||
guan.change_directory_by_replacement(current_key_word='code', new_key_word='data')
|
||||
with open('data.txt', 'w') as f: # 保存数据
|
||||
f.write('Hello world')
|
||||
@@ -0,0 +1,4 @@
|
||||
import guan
|
||||
guan.change_directory_by_replacement(current_key_word='working/code', new_key_word='local/data')
|
||||
with open('data.txt', 'w') as f: # 保存数据
|
||||
f.write('Hello world')
|
||||
@@ -0,0 +1,9 @@
|
||||
import os
|
||||
code_path = os.getcwd() # 当前代码文件的路径
|
||||
data_path = code_path.replace('\\', '/') # \改为/，防止路径报错
|
||||
data_path = data_path.replace('code', 'data') # 把路径中code改为data
|
||||
if os.path.exists(data_path) == False: # 如果文件夹不存在，新建文件夹
|
||||
os.makedirs(data_path)
|
||||
os.chdir(data_path) # 转到数据的存放路径
|
||||
with open('data.txt', 'w') as f: # 保存数据
|
||||
f.write('Hello world')
|
||||
42
language_learning/python/2022.03.06_numba_time/numba_time.py
Normal file
42
language_learning/python/2022.03.06_numba_time/numba_time.py
Normal file
@@ -0,0 +1,42 @@
|
||||
import numpy as np
|
||||
from numba import jit
|
||||
import time
|
||||
|
||||
def for_sum(numpy_array):
|
||||
sum = 0
|
||||
for number in numpy_array:
|
||||
sum += number
|
||||
return sum
|
||||
|
||||
@jit
|
||||
def numba_for_sum(numpy_array):
|
||||
sum = 0
|
||||
for number in numpy_array:
|
||||
sum += number
|
||||
return sum
|
||||
|
||||
numpy_array = np.arange(0,1e8,1)
|
||||
|
||||
start = time.time()
|
||||
result = sum(numpy_array)
|
||||
end = time.time()
|
||||
print('\nresult:', result)
|
||||
print('python中sum()函数求和时间：\n', end - start)
|
||||
|
||||
start = time.time()
|
||||
result = np.sum(numpy_array)
|
||||
end = time.time()
|
||||
print('\nresult:', result)
|
||||
print('numpy.sum()函数求和时间：\n', end - start)
|
||||
|
||||
start = time.time()
|
||||
result = for_sum(numpy_array)
|
||||
end = time.time()
|
||||
print('\nresult:', result)
|
||||
print('for循环求和numpy数组的时间：\n', end - start)
|
||||
|
||||
start = time.time()
|
||||
result = numba_for_sum(numpy_array)
|
||||
end = time.time()
|
||||
print('\nresult:', result)
|
||||
print('numba加速for循环求和numpy数组的时间：\n', end - start, '\n')
|
||||
@@ -0,0 +1,2 @@
|
||||
import cmath
|
||||
print(cmath.exp(1j*cmath.pi))
|
||||
@@ -0,0 +1,26 @@
|
||||
import copy
|
||||
import numpy as np
|
||||
|
||||
array_1 = [1, 2, 3]
|
||||
array_2 = array_1
|
||||
array_1[0] = 100
|
||||
print('array_1=', array_1)
|
||||
print('array_2=', array_2, '\n')
|
||||
|
||||
array_1 = np.array([1, 2, 3])
|
||||
array_2 = array_1
|
||||
array_1[0] = 100
|
||||
print('array_1=', array_1)
|
||||
print('array_2=', array_2, '\n')
|
||||
|
||||
array_1 = [1, 2, 3]
|
||||
array_2 = copy.deepcopy(array_1)
|
||||
array_1[0] = 100
|
||||
print('array_1=', array_1)
|
||||
print('array_2=', array_2, '\n')
|
||||
|
||||
array_1 = np.array([1, 2, 3])
|
||||
array_2 = copy.deepcopy(array_1)
|
||||
array_1[0] = 100
|
||||
print('array_1=', array_1)
|
||||
print('array_2=', array_2)
|
||||
@@ -0,0 +1,7 @@
|
||||
import functools
|
||||
|
||||
def func(x, y, z):
|
||||
return x-y+z
|
||||
|
||||
partial_func = functools.partial(func, x=5, z=0)
|
||||
print(partial_func(y=2))
|
||||
@@ -0,0 +1,13 @@
|
||||
import math
|
||||
print(math.pi)
|
||||
print(math.e)
|
||||
print(math.exp(1))
|
||||
print(math.cos(math.pi))
|
||||
print(math.sqrt(2), '\n')
|
||||
|
||||
import numpy as np
|
||||
print(np.pi)
|
||||
print(np.e)
|
||||
print(np.exp(1))
|
||||
print(np.cos(np.pi))
|
||||
print(np.sqrt(2))
|
||||
@@ -0,0 +1,8 @@
|
||||
import matplotlib.pyplot as plt
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111)
|
||||
ax.plot(range(10), range(10))
|
||||
ax.set_title('Example', fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_xlabel('x', fontsize=20, fontfamily='Times New Roman')
|
||||
ax.set_ylabel('y', fontsize=20, fontfamily='Times New Roman')
|
||||
plt.show()
|
||||
@@ -0,0 +1,23 @@
|
||||
from multiprocessing import Process
|
||||
import time
|
||||
|
||||
def f(name):
|
||||
time.sleep(5)
|
||||
print('Hello', name)
|
||||
|
||||
if __name__ == '__main__':
|
||||
start_time = time.time()
|
||||
p1 = Process(target=f, args=('Bob',))
|
||||
p2 = Process(target=f, args=('Alice',))
|
||||
p1.start()
|
||||
p2.start()
|
||||
p1.join()
|
||||
p2.join()
|
||||
end_time = time.time()
|
||||
print(end_time - start_time, '\n')
|
||||
|
||||
start_time = time.time()
|
||||
f('Bob')
|
||||
f('Alice')
|
||||
end_time = time.time()
|
||||
print(end_time - start_time)
|
||||
@@ -0,0 +1,21 @@
|
||||
import numpy as np
|
||||
np.zeros((2, 3)) # 零矩阵
|
||||
np.identity(3) # 单位矩阵
|
||||
np.diag([1, 3, 5]) # 对角矩阵
|
||||
matrix1 = np.array([[3, 5+1j], [2, 7]]) # numpy矩阵
|
||||
matrix1.shape # 矩阵的维度
|
||||
matrix1.transpose() # 矩阵转置
|
||||
matrix1.conj() # 矩阵所有元素共轭
|
||||
np.conj(matrix1) # 矩阵所有元素共轭（同上）
|
||||
np.arange(1, 5, 1) # 数列（左闭右开）
|
||||
np.linspace(-2, 2, 5) # 数列（左闭右闭）
|
||||
np.random.uniform(-2, 2) # 随机数
|
||||
np.random.randint(0, 2) # 随机整数（左闭右开）
|
||||
np.sort([1, 7, 0, 3]) # 排列
|
||||
np.argsort([1, 7, 0, 3]) # 排列索引
|
||||
np.linalg.det(matrix1) # 行列式
|
||||
matrix2 = np.linalg.inv(matrix1) # 求逆
|
||||
np.matmul(matrix1, matrix2) # 矩阵乘积
|
||||
np.dot(matrix1, matrix2) # 矩阵乘积（同上）
|
||||
eigenvalue, eigenvector = np.linalg.eig(matrix1) # 求本征值，本征向量
|
||||
matrix3 = np.append(matrix1, matrix2, axis=0) # 增加数组元素或者矩阵的行
|
||||
@@ -0,0 +1,6 @@
|
||||
import os
|
||||
os.getcwd() # 获取路径
|
||||
if os.path.exists('new_dir') == False: # 判断路径是否存在
|
||||
os.makedirs('new_dir') # 新建文件夹
|
||||
os.chdir('new_dir') # 切换到该文件夹
|
||||
print(os.walk('/')) # 游走目录
|
||||
@@ -0,0 +1,5 @@
|
||||
import time
|
||||
start_time = time.time()
|
||||
time.sleep(5)
|
||||
end_time = time.time()
|
||||
print(end_time-start_time)
|
||||
@@ -0,0 +1,31 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/23000
|
||||
"""
|
||||
|
||||
|
||||
string_array = ['关', '。', '3', '.']
|
||||
|
||||
for string in string_array:
|
||||
# 编码
|
||||
gb2312 = string.encode(encoding="gb2312")
|
||||
gbk = string.encode(encoding="gbk")
|
||||
gb18030 = string.encode(encoding="gb18030")
|
||||
uft8 = string.encode(encoding="utf-8")
|
||||
|
||||
# 查看
|
||||
print('字符串 =', string, ' | 数据类型 =', type(string), ' | 长度 =', len(string))
|
||||
print('gb2312编码 =', gb2312, ' | 数据类型 =', type(gb2312), ' | 长度 =', len(gb2312))
|
||||
print('gbk编码 =', gbk, ' | 数据类型 =', type(gbk), ' | 长度 =', len(gbk))
|
||||
print('gb18030编码 =', gb18030, ' | 数据类型 =', type(gb18030), ' | 长度 =', len(gb18030))
|
||||
print('utf8编码 =', uft8, ' | 数据类型 =', type(uft8), ' | 长度 =', len(uft8))
|
||||
print()
|
||||
|
||||
|
||||
# 乱码例子
|
||||
string = '关关'
|
||||
uft8 = string.encode(encoding="utf-8")
|
||||
new_string_1 = uft8.decode(encoding="utf-8")
|
||||
new_string_2 = uft8.decode(encoding="gbk")
|
||||
print("使用utf-8解码utf-8编码的数据 =", new_string_1)
|
||||
print("使用gbk解码utf-8编码的数据 =", new_string_2)
|
||||
@@ -0,0 +1,41 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/25453
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
# 选取某个目录
|
||||
directory = 'E:/'
|
||||
|
||||
def main():
|
||||
for root, dirs, files in os.walk(directory):
|
||||
for i0 in range(len(files)):
|
||||
if 'pdf' in files[i0] or 'djvu' in files[i0]: # 满足某个条件的文件
|
||||
|
||||
# 显示旧文件名
|
||||
name = files[i0]
|
||||
print(name) # 显示旧文件名
|
||||
|
||||
# 显示新文件名
|
||||
new_name = modify_name(name)
|
||||
print(new_name)
|
||||
print()
|
||||
|
||||
# # 修改文件名。注意：需要检查前面的代码，尤其是modify_name的规则看是否都满足，再运行下面的代码，否则文件名的修改会出现遗漏或混乱。
|
||||
# if new_name != None:
|
||||
# os.rename(root+'/'+name, root+'/'+new_name)
|
||||
|
||||
|
||||
def modify_name(name): # 按某种规则修改文件名
|
||||
array = name.split(' - ') # 通过' - '把这类型的文件名切开
|
||||
if len(array) != 3:
|
||||
print('Miss:', name)
|
||||
new_name = None # 如果不满足规则，则不修改
|
||||
else:
|
||||
new_name= array[1]+' - '+array[0]+' - '+array[2] # 做个对调
|
||||
return new_name
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,35 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/25685
|
||||
"""
|
||||
|
||||
# 注意：这个程序请小心使用，防止误操作把系统文件或个人文件破坏。在选取好directory目录后，请经过再三确认无误后再运行，尤其是directory的层级不能太高。
|
||||
|
||||
|
||||
def main():
|
||||
# 选取某个目录
|
||||
directory = 'E:/test/all_files'
|
||||
move_all_files_to_root_directory(directory)
|
||||
|
||||
# import guan
|
||||
# guan.move_all_files_to_root_directory(directory)
|
||||
|
||||
|
||||
def move_all_files_to_root_directory(directory):
|
||||
import os
|
||||
import shutil
|
||||
for root, dirs, files in os.walk(directory):
|
||||
for i0 in range(len(files)):
|
||||
# print(root) # 文件对应目录
|
||||
# print(files[i0], '\n') # 文件
|
||||
shutil.move(root+'/'+files[i0], directory+'/'+files[i0]) # 移动所有文件至根目录
|
||||
for i0 in range(100): # 多次尝试删除层数比较多的空文件夹，例如100层
|
||||
for root, dirs, files in os.walk(directory):
|
||||
try:
|
||||
os.rmdir(root) # 删除空文件夹
|
||||
except:
|
||||
pass
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,116 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/25699
|
||||
"""
|
||||
|
||||
|
||||
def main():
|
||||
directory = 'E:/literature'
|
||||
write_file_list_in_markdown(directory)
|
||||
|
||||
|
||||
def write_file_list_in_markdown(directory='./', filename='a', reverse_positive_or_negative=1, starting_from_h1=None, banned_file_format=[], hide_file_format=None, divided_line=None, show_second_number=None, show_third_number=None):
|
||||
import os
|
||||
f = open(filename+'.md', 'w', encoding="utf-8")
|
||||
filenames1 = os.listdir(directory)
|
||||
u0 = 0
|
||||
for filename1 in filenames1[::reverse_positive_or_negative]:
|
||||
filename1_with_path = os.path.join(directory,filename1)
|
||||
if os.path.isfile(filename1_with_path): # 文件
|
||||
if os.path.splitext(filename1)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename1)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename1)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
u0 += 1
|
||||
if divided_line != None and u0 != 1:
|
||||
f.write('--------\n\n')
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
f.write('# '+str(filename1)+'\n\n')
|
||||
|
||||
filenames2 = os.listdir(filename1_with_path)
|
||||
i0 = 0
|
||||
for filename2 in filenames2[::reverse_positive_or_negative]:
|
||||
filename2_with_path = os.path.join(directory, filename1, filename2)
|
||||
if os.path.isfile(filename2_with_path): # 文件
|
||||
if os.path.splitext(filename2)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename2)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename2)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
i0 += 1
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
if show_second_number != None:
|
||||
f.write('## '+str(i0)+'. '+str(filename2)+'\n\n')
|
||||
else:
|
||||
f.write('## '+str(filename2)+'\n\n')
|
||||
|
||||
j0 = 0
|
||||
filenames3 = os.listdir(filename2_with_path)
|
||||
for filename3 in filenames3[::reverse_positive_or_negative]:
|
||||
filename3_with_path = os.path.join(directory, filename1, filename2, filename3)
|
||||
if os.path.isfile(filename3_with_path): # 文件
|
||||
if os.path.splitext(filename3)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename3)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename3)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
j0 += 1
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
if show_third_number != None:
|
||||
f.write('### ('+str(j0)+') '+str(filename3)+'\n\n')
|
||||
else:
|
||||
f.write('### '+str(filename3)+'\n\n')
|
||||
|
||||
filenames4 = os.listdir(filename3_with_path)
|
||||
for filename4 in filenames4[::reverse_positive_or_negative]:
|
||||
filename4_with_path = os.path.join(directory, filename1, filename2, filename3, filename4)
|
||||
if os.path.isfile(filename4_with_path): # 文件
|
||||
if os.path.splitext(filename4)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename4)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename4)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
f.write('#### '+str(filename4)+'\n\n')
|
||||
|
||||
filenames5 = os.listdir(filename4_with_path)
|
||||
for filename5 in filenames5[::reverse_positive_or_negative]:
|
||||
filename5_with_path = os.path.join(directory, filename1, filename2, filename3, filename4, filename5)
|
||||
if os.path.isfile(filename5_with_path): # 文件
|
||||
if os.path.splitext(filename5)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename5)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename5)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
f.write('##### '+str(filename5)+'\n\n')
|
||||
|
||||
filenames6 = os.listdir(filename5_with_path)
|
||||
for filename6 in filenames6[::reverse_positive_or_negative]:
|
||||
filename6_with_path = os.path.join(directory, filename1, filename2, filename3, filename4, filename5, filename6)
|
||||
if os.path.isfile(filename6_with_path): # 文件
|
||||
if os.path.splitext(filename6)[1] not in banned_file_format:
|
||||
if hide_file_format == None:
|
||||
f.write('+ '+str(filename6)+'\n\n')
|
||||
else:
|
||||
f.write('+ '+str(os.path.splitext(filename6)[0])+'\n\n')
|
||||
else: # 文件夹
|
||||
if starting_from_h1 == None:
|
||||
f.write('#')
|
||||
f.write('###### '+str(filename6)+'\n\n')
|
||||
f.close()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,55 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/25943
|
||||
"""
|
||||
|
||||
|
||||
def main():
|
||||
directory = 'E:/test'
|
||||
creat_necessary_file(directory)
|
||||
# delete_file_with_specific_name(directory)
|
||||
|
||||
# import guan
|
||||
# guan.creat_necessary_file(directory)
|
||||
# guan.delete_file_with_specific_name(directory)
|
||||
|
||||
|
||||
def creat_necessary_file(directory, filename='readme', file_format='.md', content='', overwrite=None, ignored_directory_with_words=[]):
|
||||
import os
|
||||
directory_with_file = []
|
||||
ignored_directory = []
|
||||
for root, dirs, files in os.walk(directory):
|
||||
for i0 in range(len(files)):
|
||||
if root not in directory_with_file:
|
||||
directory_with_file.append(root)
|
||||
if files[i0] == filename+file_format:
|
||||
if root not in ignored_directory:
|
||||
ignored_directory.append(root)
|
||||
if overwrite == None:
|
||||
for root in ignored_directory:
|
||||
directory_with_file.remove(root)
|
||||
ignored_directory_more =[]
|
||||
for root in directory_with_file:
|
||||
for word in ignored_directory_with_words:
|
||||
if word in root:
|
||||
if root not in ignored_directory_more:
|
||||
ignored_directory_more.append(root)
|
||||
for root in ignored_directory_more:
|
||||
directory_with_file.remove(root)
|
||||
for root in directory_with_file:
|
||||
os.chdir(root)
|
||||
f = open(filename+file_format, 'w', encoding="utf-8")
|
||||
f.write(content)
|
||||
f.close()
|
||||
|
||||
|
||||
def delete_file_with_specific_name(directory, filename='readme', file_format='.md'):
|
||||
import os
|
||||
for root, dirs, files in os.walk(directory):
|
||||
for i0 in range(len(files)):
|
||||
if files[i0] == filename+file_format:
|
||||
os.remove(root+'/'+files[i0])
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,45 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/26113
|
||||
"""
|
||||
|
||||
# 仅支持文件名判断是否重复，不支持对文件内容的判断。
|
||||
# 如需对文件名和内容都判断，需要计算文件的哈希值。这里暂时不考虑。
|
||||
|
||||
|
||||
def main():
|
||||
directory = 'E:/test'
|
||||
repeated_file = find_repeated_file_with_same_filename(directory)
|
||||
print(repeated_file)
|
||||
|
||||
# import guan
|
||||
# repeated_file = guan.find_repeated_file_with_same_filename(directory='./', ignored_directory_with_words=[], ignored_file_with_words=[], num=1000)
|
||||
# print(repeated_file)
|
||||
|
||||
|
||||
def find_repeated_file_with_same_filename(directory='./', ignored_directory_with_words=[], ignored_file_with_words=[], num=1000):
|
||||
import os
|
||||
from collections import Counter
|
||||
file_list = []
|
||||
for root, dirs, files in os.walk(directory):
|
||||
for i0 in range(len(files)):
|
||||
file_list.append(files[i0])
|
||||
for word in ignored_directory_with_words:
|
||||
if word in root:
|
||||
file_list.remove(files[i0])
|
||||
for word in ignored_file_with_words:
|
||||
if word in files[i0]:
|
||||
try:
|
||||
file_list.remove(files[i0])
|
||||
except:
|
||||
pass
|
||||
count_file = Counter(file_list).most_common(num)
|
||||
repeated_file = []
|
||||
for item in count_file:
|
||||
if item[1]>1:
|
||||
repeated_file.append(item)
|
||||
return repeated_file
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,41 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/26536
|
||||
"""
|
||||
|
||||
|
||||
def main():
|
||||
# 如果子文件夹中所有文件的数量小于5，输出路径。
|
||||
count_file_in_sub_directory(directory='./', smaller_than_num=5)
|
||||
|
||||
# import guan
|
||||
# guan.count_file_in_sub_directory(directory='./', smaller_than_num=5)
|
||||
|
||||
|
||||
def count_file_in_sub_directory(directory='./', smaller_than_num=None):
|
||||
import os
|
||||
from collections import Counter
|
||||
dirs_list = []
|
||||
for root, dirs, files in os.walk(directory):
|
||||
if dirs != []:
|
||||
for i0 in range(len(dirs)):
|
||||
dirs_list.append(root+'/'+dirs[i0])
|
||||
for sub_dir in dirs_list:
|
||||
file_list = []
|
||||
for root, dirs, files in os.walk(sub_dir):
|
||||
for i0 in range(len(files)):
|
||||
file_list.append(files[i0])
|
||||
count_file = len(file_list)
|
||||
if smaller_than_num == None:
|
||||
print(sub_dir)
|
||||
print(count_file)
|
||||
print()
|
||||
else:
|
||||
if count_file<smaller_than_num:
|
||||
print(sub_dir)
|
||||
print(count_file)
|
||||
print()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
@@ -0,0 +1,48 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/29155
|
||||
"""
|
||||
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
def get_data(x_array, y_array):
|
||||
z_matrix = np.zeros((y_array.shape[0], x_array.shape[0]))
|
||||
j0 = -1
|
||||
for x in x_array:
|
||||
j0 += 1
|
||||
i0 = -1
|
||||
for y in y_array:
|
||||
i0 += 1
|
||||
z_matrix[i0, j0] = x**2+y**2
|
||||
return z_matrix
|
||||
|
||||
x_array = np.linspace(-1, 1, 1000)
|
||||
y_array = x_array
|
||||
z_matrix = get_data(x_array, y_array) # 举例的数据
|
||||
|
||||
fix_value = 0.5 # 画这个值附近的等高线
|
||||
precision = 0.01 # 选取该值附近的范围
|
||||
|
||||
# 方法一
|
||||
x_array_new = []
|
||||
y_array_new = []
|
||||
for i0 in range(y_array.shape[0]):
|
||||
for j0 in range(x_array.shape[0]):
|
||||
if abs(z_matrix[i0, j0]-fix_value)<precision:
|
||||
x_array_new.append(x_array[j0])
|
||||
y_array_new.append(y_array[i0])
|
||||
fig, ax = plt.subplots()
|
||||
plt.plot(x_array_new, y_array_new, 'o')
|
||||
ax.set_xlim(min(x_array), max(x_array))
|
||||
ax.set_ylim(min(y_array), max(y_array))
|
||||
plt.show()
|
||||
|
||||
# 方法二
|
||||
for i0 in range(y_array.shape[0]):
|
||||
for j0 in range(x_array.shape[0]):
|
||||
if abs(z_matrix[i0, j0]-fix_value)>precision:
|
||||
z_matrix[i0, j0] = None
|
||||
fig, ax = plt.subplots()
|
||||
ax.contourf(x_array,y_array,z_matrix)
|
||||
plt.show()
|
||||
@@ -0,0 +1,8 @@
|
||||
import numpy as np
|
||||
|
||||
def run(parameter_array):
|
||||
for parameter in parameter_array:
|
||||
print('hello world'+' '+str(parameter))
|
||||
|
||||
parameter_array_labeled_for_replacement = []
|
||||
run(parameter_array_labeled_for_replacement)
|
||||
@@ -0,0 +1,7 @@
|
||||
#!/bin/sh
|
||||
#PBS -N task
|
||||
#PBS -l nodes=1:ppn=1
|
||||
#PBS -q bigmem
|
||||
cd $PBS_O_WORKDIR
|
||||
export OMP_NUM_THREADS=1
|
||||
python a.py
|
||||
@@ -0,0 +1,56 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/29200
|
||||
"""
|
||||
|
||||
import os
|
||||
|
||||
parameter_str_array = ['np.arange(1, 11, 1)', 'np.arange(11, 21, 1)']
|
||||
|
||||
index = 0
|
||||
for parameter_str in parameter_str_array:
|
||||
index += 1
|
||||
|
||||
# 以下处理代码文件
|
||||
old_file = 'a.py'
|
||||
new_file = 'a'+str(index)+'.py'
|
||||
|
||||
# 说明：linux系统下复制用cp，windows系统下复制用copy
|
||||
os.system('cp '+old_file+' '+new_file) # 复制python代码文件
|
||||
with open(new_file, 'r') as f: # 读取
|
||||
content = f.read()
|
||||
|
||||
old_str = 'parameter_array_labeled_for_replacement = []'
|
||||
new_str = 'parameter_array_labeled_for_replacement = ' + parameter_str
|
||||
content = content.replace(old_str, new_str)
|
||||
|
||||
# 如果程序需要将数据写入文件，除了需要替代参数，还需要替代文件名，方法和以上相同
|
||||
|
||||
with open('a'+str(index)+'.py', 'w') as f: # 写入
|
||||
f.write(content)
|
||||
|
||||
|
||||
|
||||
# 以下处理任务上传文件
|
||||
old_file = 'a.sh'
|
||||
new_file = 'a'+str(index)+'.sh'
|
||||
|
||||
os.system('cp '+old_file+' '+new_file) # 复制任务调度系统的sh上传文件
|
||||
with open(new_file, 'r') as f: # 读取
|
||||
content = f.read()
|
||||
|
||||
old_str = 'python a.py'
|
||||
new_str = 'python a'+str(index)+'.py'
|
||||
content = content.replace(old_str, new_str)
|
||||
|
||||
old_str = 'task'
|
||||
new_str = 'task_'+str(index)
|
||||
content = content.replace(old_str, new_str)
|
||||
|
||||
with open('a'+str(index)+'.sh', 'w') as f: # 写入
|
||||
f.write(content)
|
||||
|
||||
|
||||
|
||||
# 提交任务
|
||||
os.system('qsub '+new_file)
|
||||
@@ -0,0 +1,32 @@
|
||||
"""
|
||||
This code is supported by the website: https://www.guanjihuan.com
|
||||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/34649
|
||||
"""
|
||||
|
||||
import PyPDF2
|
||||
|
||||
# 创建一个空的PDF对象
|
||||
output_pdf = PyPDF2.PdfWriter()
|
||||
|
||||
# 打开第一个PDF文件
|
||||
with open('a.pdf', 'rb') as file1:
|
||||
pdf1 = PyPDF2.PdfReader(file1)
|
||||
|
||||
# 将第一个PDF文件的所有页面添加到输出PDF对象中
|
||||
for page in range(len(pdf1.pages)):
|
||||
output_pdf.add_page(pdf1.pages[page])
|
||||
|
||||
# 打开第二个PDF文件
|
||||
with open('b.pdf', 'rb') as file2:
|
||||
pdf2 = PyPDF2.PdfReader(file2)
|
||||
|
||||
# 将第二个PDF文件的所有页面添加到输出PDF对象中
|
||||
for page in range(len(pdf2.pages)):
|
||||
output_pdf.add_page(pdf2.pages[page])
|
||||
|
||||
# 保存合并后的PDF文件
|
||||
with open('combined_file.pdf', 'wb') as combined_file:
|
||||
output_pdf.write(combined_file)
|
||||
|
||||
# import guan
|
||||
# guan.combine_two_pdf_files(input_file_1='a.pdf', input_file_2='b.pdf', output_file='combined_file.pdf')
|
||||
Reference in New Issue
Block a user