Jak的博客

import numpy as npimport numpy as npdata = np.array([[1,9,3,4,5], [1,3,3,6,7], [2,2,4,5,7], [3,1,5,6,7], [4,6,6,7,8]])# 按照第一列排序idex=np.lexsort([data[:,1]])sorted_data = data[idex, :]print(sorte...

import os import matplotlib.pyplot as plt import numpy as np import tensorflow as tffrom scipy.stats import wilcoxonfrom scipy.stats import kruskalfrom scipy.stats import mannwhitneyufrom s...

import os import matplotlib.pyplot as plt import numpy as np import tensorflow as tffrom scipy.stats import wilcoxonfrom scipy.stats import kruskalfrom scipy.stats import mannwhitneyufrom s...

from __future__ import divisionimport mathimport randomimport pprintimport scipy.miscimport numpy as npfrom time import gmtime,strftimefrom six.moves import xrangeimport matplotlib.pyplot as...

import argparsedesc = "测试Python的argparse模块"parser = argparse.ArgumentParser(description=desc)parser.add_argument('--test', type=str, default='测试代码' ,help='test')parser.add_argument('--epoch', ty...

import numpy as npdef transform_one_hot(labels): n_labels = np.max(labels) + 1 one_hot = np.eye(n_labels)[labels] return one_hotlabels = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])one_hot = tra...

(x,y)为要转的点，（pointx,pointy)为中心点，如果顺时针角度为anglesrx = (x-pointx)*cos(angle) + (y-pointy)*sin(angle)+pointxsry = (y-pointy)*cos(angle) - (x-pointx)*sin(angle)+pointy(x,y)为要转的点，（pointx,pointy)为中心点，如果逆时...

import tensorflow as tfimport scipy.io as sioimport numpy as npfrom PIL import Imageimport os import copyimport mathimport matplotlib.pyplot as pltnp.set_printoptions(threshold=np.inf) #输出全部矩...

import tensorflow as tfimport scipy.io as sioimport numpy as npfrom PIL import Imageimport os import copyimport mathimport matplotlib.pyplot as pltnp.set_printoptions(threshold=np.inf) #输出全部矩...

#提取目录下所有图片,更改尺寸后保存到另一目录from PIL import Imageimport os.pathimport globdef convertjpg(file,outdir,width=1000,height=1000): img=Image.open(file) try: new_img=img.resize((width,height...

import numpy as npimport matplotlib.pyplot as pltfrom PIL import Imagefrom glob import globimport osimport path# 将路径和文件连接起来# C:\Users\Administrator\Desktop\第6周内容\原始直线\*.pngfiles = os.path.joi...

import numpy as npimport matplotlib.pyplot as pltnet = 913num = [1,2,3,4,5,6,7,8,9,10]# net_913动脉树net_913_ArtNorm = [1.3501,1.3311,1.3186,1.3331,1.3387,1.3273,1.3271,1.3421,1.3299,1.2932]net_91...

import numpy as np import matplotlib.pyplot as pltimport os # 读取文件夹def file_name(file_dir): L=[] for root, dirs, files in os.walk(file_dir): for file in files: if os.path.spli...

import mathimport copyimport numpy as npimport matplotlib.pyplot as plt# 距离计算公式def get_len(x1,x2,y1,y2): diff_x = (x1-x2)**2 diff_y = (y1-y2)**2 length = np.sqrt(diff_x+diff_y) r...

前几天系统崩掉，重置系统，很多安装过的软件也需要重新安装。之前python安装路径在C:\Users\XXX\AppData\Local\Programs\Python\Python37\python.exe，现在我把安装路径改为C:\python\python.exe，eclipse安装包位置不变，仍在D盘。安装并配置好python后，新建python项目报错：The interpreter...

import numpy as np arr = [1,2,3,4,5,6]#求均值arr_mean = np.mean(arr)#求方差arr_var = np.var(arr)#求标准差arr_std = np.std(arr,ddof=1)print("平均值为：%f" % arr_mean)print("方差为：%f" % arr_var)print("标准差为:%f...

统计性检验本文分为四个部分：正态性检验 相关性检验 参数统计假设检验 非参数统计假设检验 1.正态性检验本部分列出了可用于检查数据是否具有高斯分布的统计检验。w检验（Shapiro-wilk test)检验数据样本是否具有高斯分布。from scipy.stats import shapirodata = [21,12,12,23,19,13,20,17,14,...

import numpy as npimport operatorimport osimport copyfrom matplotlib.font_manager import FontPropertiesfrom scipy.interpolate import lagrangeimport randomimport matplotlib.pyplot as plt# 把opt...

 绘制直线，三角形，正方形import matplotlib.pyplot as pltdef plotLine(): x = [1,2,3,4,5] y = [3,3,3,3,3] plt.figure(figsize=(100,100),dpi=1) plt.plot(x,y,linewidth=150) plt.axis('off') ...

https://www.cnblogs.com/beginner-boy/p/7239696.htmlimport xlwtbook = xlwt.Workbook(encoding='utf-8',style_compression=0)sheet = book.add_sheet('mysheet',cell_overwrite_ok=True)for i in range(4):...

角度测试import numpy as npimport matplotlib.pyplot as pltx = [0,3,0,0]y = [0,0,4,0]a = 3b = 4c = 5cos_angle = (a**2 +b**2-c**2)/(2*b*c)angle = np.arccos(cos_angle)angle1 = angle*180/np.piprin...

对于彩色转灰度，有一个很著名的心理学公式：Gray = R*0.299 + G*0.587 + B*0.114from PIL import Imageimport matplotlib.image as mpimgimport numpy as npimport matplotlib.pyplot as pltimg = mpimg.imread('C:\\Users\\Administ...

欧氏距离 欧式距离（L2范数）是最易于理解的一种距离计算方法，源自欧式空间中两点间的距离公式（如下图所示）。 #导入math包import math#定义点的函数class Point: def __init__(self,x=0,y=0): self.x=x self.y=y def getx(self): re...

import numpy as npimport operatorimport osimport copyfrom matplotlib.font_manager import FontPropertiesfrom scipy.interpolate import lagrangeimport randomimport matplotlib.pyplot as pltimport...

 import numpy as np import matplotlib.pyplot as plt from pylab import mplmpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体plt.rcParams['axes.unicode_minus']=False #解决负数坐标显示问题 #x的个数决定了样本...

数据旋转公式x1=cos(angle)*x-sin(angle)*y;y1=cos(angle)*y+sin(angle)*x;从数学上来说，此公式可以用来计算某个点绕另外一点旋转一定角度后的坐标，例如：A（x，y）绕B（a，b)旋转β度后的位置为C（c，d），则x，y，a，b，β，c，d有如下关系式：import matplotlib.pyplot as plti...

import numpy as npimport operatorimport osimport copyfrom matplotlib.font_manager import FontPropertiesfrom scipy.interpolate import lagrangeimport randomimport matplotlib.pyplot as pltimport...

import numpy as npimport operatorimport osimport copyfrom matplotlib.font_manager import FontPropertiesfrom scipy.interpolate import lagrangeimport randomimport matplotlib.pyplot as pltimport...

import mathimport numpy as npimport matplotlib.pyplot as pltxy1 = [1,2,2,2]xy2 = [2,2,2,0,1,2]xy3 = [2,3,4,5,2,3,4,5]def get_len(x1,x2,y1,y2): diff_x = (x1-x2)**2 diff_y = (y1-y2)**2...

import numpy as npimport cv2from matplotlib import pyplot as plt img = cv2.imread('b.jpg')mask = np.zeros(img.shape[:2], np.uint8) bgdModel = np.zeros((1, 65), np.float64)fgdModel = np.zero...

import os import os.pathrootdir = 'C:\\Users\\Administrator\\Desktop\\Exp5\\'files = os.listdir(rootdir) #文件夹内文件名列表seq = 1for name in files:# print(name) newname = str(seq) +'-'+name ...