小编cht*_*mon的帖子

为了熟悉全局优化方法，特别是shgo优化器，scipy.optimize v1.3.0我尝试在具有给定平均值的约束下最小化向量的方差var(x)：x = [x1,...,xN]0 <= xi <= 1x

import numpy as np
from scipy.optimize import shgo

# Constraint
avg = 0.5  # Given average value of x
cons = {'type': 'eq', 'fun': lambda x: np.mean(x)-avg}

# Minimize the variance of x under the given constraint
res = shgo(lambda x: np.var(x), bounds=6*[(0, 1)], constraints=cons)

该shgo方法在这个问题上失败了：

>>> res
     fun: 0.0
 message: 'Failed to find a feasible minimiser point. Lowest sampling point …

import random

myfile = open('numbers.txt', 'w')
file_size = random.randint(4,7)

for count in range(file_size):
    numbers = random.randint(5,19)
    myfile.write(str(numbers) + '\n')

myfile.close()

这是我到目前为止所拥有的，但我需要数字是所有赔率和“file_size”告诉代码的正确赔率。每个整数必须是随机的，介于 5 和 19 之间。

我正在使用Anaconda 2.7,我的fill_between()尝试也变得毫无结果.我不确定我是否错过了一个包或者我的绘图语法是否抛出python ...

这是我的代码:

from scipy import stats
import matplotlib.pyplot as plt
from numpy import linspace

alpha_A = 11
beta_A = 41
alpha_B = 3
beta_B = 3

x = linspace(0,1,num = 1000)
postA = stats.beta(alpha_A, beta_A).pdf(x)
postB = stats.beta(alpha_B, beta_B).pdf(x)


plt.figure(2, figsize = (6,4))
plt.plot(postA, color = 'r', label = "A: Beta(" + str(alpha_A) + ',' + str(beta_A) + ')')
plt.plot(postB, color = 'b',label = "B: Beta(" + str(alpha_B) + ',' + str(beta_B) + ')')
plt.legend(loc = …

class Player:
    # __slots__ = ['name','age','gsnum']
    def __init__(self,name,age,gsnum):
        self.name = name
        self.age = age
        self.gsnum = gsnum

我定义了这个类,有三个属性

当__slots__用于节省内存时:

我得到36个一个实例(sys.getsizeof())如果没有使用__slots__,我仍然得到36作为内存大小,

这有什么问题？32位Python 2.7

我无法理解以下代码段-

if cv2.waitKey(0) & 0xFF == ord('q'):
break

在此代码中-

    1 import numpy as np
    2 import cv2
    3 
    4 cap = cv2.VideoCapture(0)
    5 
    6 while(True):
    7     # Capture frame-by-frame
    8     ret, frame = cap.read()
    9 
   10     # Our operations on the frame come here
   11     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
   12 
   13     # Display the resulting frame
   14     cv2.imshow('frame',gray)
   15     if cv2.waitKey(1) & 0xFF == ord('q'):
   16         break
   17 
   18 # When everything done, release the capture
   19 cap.release()
   20 cv2.destroyAllWindows() …