def message(self, text, confirm=False): w = 400. h = w/((sqr(5)+1)/2) # goldener schnitt, yay! x = 1024/2-w/2 y = 780/((sqr(5)+1)/2)-h/((sqr(5)+1)/2) self.cnv.create_rectangle((x,y,x+w,y+h), fill='black', outline='red', width='5') self.text(text, (x+10,y+10), font='Liberation Serif', anchor=tk.NW) if confirm: self.mode = 'message' self.text('Hit any key to continue', (x+w-10,y+h-20), font='Liberation Serif', anchor=tk.NE) self.cnv.update_idletasks()
def main(): a = int(input("Please input a:")) b = int(input("Please input b:")) c = int(input("Please input c:")) q = quadratic(a, b, c) print(q) if q: print("无解") elif len(q) == 1: if a == 0: if q == -c / b: print('测试成功') else: print('测试失败') else: if q == -b / (2 * a): print("测试成功") else: print('测试失败') elif len(q) == 2: if q == ((-b + math.sqr(b * b - 4 * a * c)) / (2 * a), (-b - math.sqrt(b * b - 4 * a * c)) / (2 * a)): print('测试正确') else: print('测试失败') else: print('测试失败') return
def is_valid(self): file = len(self.data) if type(math.sqr(file)) != int: return False for n in self.data: if len(n) != file: return False for element in n: if type(element) != int: return False return True
def ComputeCorrLation(X, Y): xBar = np.mean(X) yBar = np.mean(Y) SSR = 0 varX = 0 varY = 0 for i in range(len(X)): diffXbar = X[i] - xBar diffYbar = Y[i] - yBar SSR += (diffXbar * diffYbar) varX += diffXbar**2 varY += diffYbar**2 SST = sqr(varX * varY) return SSR / SST
def similarity(self, pict): # distance of sizes #dim=sum(map(lambda (x,y):(x-y)**2, zip(self.size, pict.size))) #dim/=self.size[0]**2+self.size[1]**2 msr=[] dimensions=zip(self.size, pict.size) widths=sorted(dimensions[0]) heights=sorted(dimensions[1]) msr.append(sqr(1.*widths[0]/widths[1]*heights[0]/heights[1])) #hst=sum(map(lambda (x,y):(x-y)**2, zip(self.histogram, pict.histogram))) hstcor=measure.image_histograms(self, pict) msr.extend(hstcor) mood=measure.image_histmediandist(self, pict) msr.append(1-mood) #colorful=measure.image_histrelcor(self, pict) #msr.extend(colorful) return sum(msr)/len(msr)
def image_histmediandist(p,q): mediane=[image_histmediane(p), image_histmediane(q)] dists=map(lambda (x,y):sqr((x-y)**2), zip(mediane[0], mediane[1])) dist=sum(dists)/32. return dist
import math class Person: def __init__(self, name, age): self.name = name self.age = age def myfunc(self): print("Hello my name is " + self.name) p1 = Person("John", 36) p1.myfunc() num1 = 3 num2 = 6 sum = num1 +num2 print("tong 2 so la: ", sum) print(math.sqr(2))
print("Enter 1st number:") num1 = int(input()) print("Enter the operator: (+,-,*,/,**,%)") operator = input() print("Enter 2nd number:") num2 = int(input()) if operator == '+': plus = num1+num2 print('The ans is =',plus) elif operator == '-': minus = num1-num2 print('The ans is =',minus) elif operator == '*': multi = num1*num2 print('The ans is =',multi) elif operator == '/': devide = num1/num2 print('The ans is =',devide) elif operator == '**': power = num1**num2 print('The ans is =',power) elif operator == '%': modulas = num1%num2 print('The ans is =', modulas) elsif operator == 'sqr': square = math.sqr(num1) print('The ans is =', square) else: print("Error! Please check your input")
def r(self): return math.sqr(self.x**2, self.y**2)
def dist_between_colors(list1, list2): dist = math.sqrt(math.sqr(list1[0]-list2[0]) + math.sqr(list1[1]-list2[1]) // + math.sqr(list1[2]-list2[2])) return dist
def compute_square_root(number): # compute the square root using the math library result = math.sqr(number) return result
#!/usr/bin/python # -*- coding: UTF-8 -*- # 5.1.1 使用逗号输出 import math as foobar from math import sqrt as sqr print 'Age:', 42 # 如果在结尾处加上逗号,那么接下来的语句会与前一条语句在同一行打印 print 'Hello', print 'world!' print foobar.sqrt(4) print sqr(4) # 序列解包或可选代解包 x, y, z = 1, 2, 3 print x, y, z x, y = y, x print x, y, z values = 1, 2, 3 print values x, y, z = values print x, y, z scoundrel = {'name': 'Robin', 'girlfriend': 'Marion'} key, value = scoundrel.popitem() print scoundrel print key, value
def dist(player, missile): return math.sqrt(math.sqr(player.x - missile.x), math.sqr(player.y - missile.y))
def compose(self,x,y): deltax=x-self.axis1.beta deltay=y-self.axis2.beta angle=math.atan2(y, x) module=math.sqr(deltax*deltax+deltay*deltay) return module,angle
def image_histmediandist(p,q): mediane=[p.histogram.mediane, q.histogram.mediane] dists=map(lambda (x,y):(x-y)**2, zip(mediane[0], mediane[1])) dist=sqr(sum(dists))/32. return dist
def r( self ): return math.sqr( self.x**2, self.y**2 )
def compose(self, x, y): deltax = x - self.axis1.beta deltay = y - self.axis2.beta angle = math.atan2(y, x) module = math.sqr(deltax * deltax + deltay * deltay) return module, angle
def distance_from(self, p): d = math.sqr(math.pow(p.x - self.x, 2) + math.pow(p.y - self.y, 2)) return d
import random import math import numpy as np sig = 3.0 mu = 0 dufile = open("gauss.dat", "w") for i in range(-100, 100, 1): p = (1 / math.sqr(math.pi) * sig**2) * math.exp(-((x - mu)**2) / 2 * (sig**2))
def EuklidAbstand(self, other): """ Liefert den euklidischen Abstand zwischen vector1 und vector2, Beispiel: abstand = vector1.EuklidAbstand(vector2) \ z.B. Vec1(3,9), Vec2(9,5) = 7,21 = sqrt(52) = sqrt(36 + 16) = sqrt ((3-9)**2 + (9-5)**2)""" return math.sqr(sum((a-b)**2 for a, b in zip(self, other)))
def BuildCircle(fn): # returns err & circle - list of 3 float c = [] l1 = [] xx = [] yy = [] try: with open(fn, 'r') as f: for word in [ s for s1 in f for s2 in s1.split('\n') for s3 in s2.split('\t') for s4 in s3.split(',') for s in s4.split(' ') if s != '' ]: try: x = (float(word)) l1.append(x) except ValueError: return 2, 0, 0, 0 e, dmax, i1, j1 = FindMax(fn) for k in range(int(len(l1))): if k % 2 == 0: xx.append(l1[k]) if k % 2 == 1: yy.append(l1[k]) if len(xx) == 0: c = None if len(xx) == 1: #окружность в точке c = [0, xx[0], yy[0]] if len(xx) == 2: #окружность по двум точкам r = math.sqrt( math.sqr(xx[0] - xx[1]) + math.sqr(yy[0] - yy[1])) c = [r / 2, (xx[0] + xx[1]) / 2, (yy[0] + yy[1]) / 2] elif len(xx) > 2: #по длиннейшему диаметру, или строим описанную c = [dmax / 2, (xx[i1] + xx[j1]) / 2, (yy[i1] + yy[j1]) / 2] #проверим flag = 0 for i in range(len(xx)): if IsInCircle(xx[i], yy[i], c[1], c[2], c[0]): flag = flag + 1 if flag != len(xx): #если не прошло по длиннейшему диаметру, то sx, sy, mx = 0, 0, 0 #найдем координаты центра тяжести множества точек for i in range(len(xx)): sx = sx + xx[i] sy = sy + yy[i] sx = sx / n sy = sy / n mx = (math.sqr(sx - xx[0]) + math.sqr(sy - yy[0])) #найдем наиболее удаленную точку от центра for i in range(len(xx)): if (math.sqr(sx - xx[i]) + math.sqr(sy - yy[i])) > mx: mx = (math.sqr(sx - xx[i]) + math.sqr(sy - yy[i])) mx = math.sqrt(mx) c = [mx, sx, sy] if c == None: return 2, 0 else: return 0, c except FileNotFoundError: return 1, 0