17035))#产生17001到17035的一个整数型随机数...:print(random.uniform(60.0,100.0))#产生60.0...
fromsklearn.clusterimportMiniBatchKMeans, KMeans fromsklearn.metrics.pairwiseimportpairwise_distances_argmin fromsklearn.datasetsimportmake_blobs # Generate sample data np.random.seed(0) batch_size =45 centers = [[1,1], [-1,-1], [1,-1]...
return ERR return OK def get_file_list_cur(types=0): filelist = [] fileNames = glob.glob(FLASH_HOME_PATH + r"/*.*") try: for fileName in fileNames: name = os.path.basename(fileName) filelist.append(name) except Exception as reason: logging.error("Failed to get file list! reas...
from wordcloud import WordCloudimport matplotlib.pyplot as plt# 添加词语text=("Python Python Python Matplotlib Chart Wordcloud Boxplot")# 创建词云对象wordcloud = WordCloud(width=480, height=480, margin=0).generate(text)# 显示词云图plt.imshow(wordcloud, interpolation='bilinear')plt.axis("off")plt....
The main difference between the two is thatGeneratorrelies on an additional BitGenerator to manage state and generate the random bits, which are then transformed into random values from useful distributions. The default BitGenerator used byGeneratorisPCG64. ...
至于判断是否是完全平方数,最简单的方法是:平方根的值小数为0即可。 结合起来: n=0while(n+1)**2-n*n<=168: n+=1foriinrange((n+1)**2):ifi**0.5==int(i**0.5)and(i+168)**0.5==int((i+168)**0.5):print(i-100) 实例004:这天第几天 ...
图0 不同样本数目下的四种模型的测试精度( 数据集大小从 100 到 5800,间隔 100 ) 1.开发环境 python: 3.6.3 import PIL, cv2, pandas, numpy, os, csv, random 需要调用的 sklearn 库: 1fromsklearn.linear_modelimportLogisticRegression#线性模型中的 Logistic 回归模型2fromsklearn.linear_modelimportSGDCl...
"Maine man wins $1M from $25 lottery ticket", "Make huge profits without work, earn up to $100,000 a day"] print("%-20s %s" % ("Query", "Best Match")) print("-" * 50) for query in ("feel good story", "climate change", "health", "war", "wildlife", "asia...
5.编写函数,输出1~100中偶数之和 def i(): h=0 for a in range(1, 101): if a % 2 == 0: h+=a print('1~100的偶数之和是:', h) i() 1. 2. 3. 4. 5. 6. 7. 6.要求编写代码,实现计算器的四则运算功能。 # 计算器可以进行基础运算(加、减、乘、除)被除数不为0 ...
="",xlabel='Date',ylabel='Value',dpi=100):plt.figure(figsize=(16,5),dpi=dpi)plt.plot(x,y,color='tab:red')plt.gca().set(title=title,xlabel=xlabel,ylabel=ylabel)plt.show()plot_df(df,x=df.index,y=df.value,title='Monthly anti-diabetic drug sales in Australia from 1992 to 2008....