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 dist(player, missile):
return math.sqrt(math.sqr(player.x - missile.x), math.sqr(player.y - missile.y))
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
