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MIT-CS6-00课程笔记Lec16-18

Lec16.

Class:

  • template for data type
  • cluster data & method
  • modularity/abstraction
  • data hiding:only acess the parts though a method
  • class used to make instances

Encapsulation:(封装)

  • data hide
  • inheritance:继承
  • shadow/override methods
  • hierarchy of classes

    Lec17.&Lec18.

  • Informal problem description to a formal problem statement:把一个非正式的问题转化到一个更加通用的模型上来

  • Inventing computational models:创造计算模型
  • dealing with & exploiting randomness:探索随机性
  • making sense of data:让数据变得有意义,如何理解数据
  • evaluating quality of answers:如何来判断和分析程序给出的答案是不是我们所想要的答案

随机走动:

  • simolate(模拟) random walk(无规则运动)
  • 数据抽象
    • Location
    • compass Pt
    • Field
    • Drunk
  • pseudo random(伪随机)

课程使用的代码:

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import mathimport randomimport pylab

class Location(object):
def __init__(self, x, y):
self.x = float(x)
self.y = float(y)

def move(self, xc, yc):
return Location(self.x + float(xc), self.y+float(yc))

def getCoords(self):
return self.x, self.y

def getDist(self, other):
ox, oy = other.getCoords()
xDist = self.x - ox
yDist = self.y - oy
return math.sqrt(xDist**2 + yDist ** 2)


class CompassPt(object):
possibles = ('N', 'S', 'E', 'W')
def __init__(self, pt):
if pt in self.possibles:
self.pt = pt
else:
raise ValueError('in CompassPt.__init__')

def move(self, dist):
if self.pt == 'N':
return (0, dist)
elif self.pt == 'S':
return (0, -dist)
elif self.pt == 'E':
return (dist, 0)
elif self.pt == 'W':
return (-dist, 0)
else:
raise ValueError('in compassPt.move')


class Field(object):
def __init__(self, drunk, loc):
self.drunk = drunk
self.loc = loc

def move(self, cp, dist):
oldLoc = self.loc
xc, yc = cp.move(dist)
self.loc = oldLoc.move(xc, yc)

def getLoc(self):
return self.loc

def getDrunk(self):
return self.drunk


class Drunk(object):
def __init__(self, name):
self.name = name

def move(self, field, time=1):
if field.getDrunk() != self:
raise ValueError('Drunk.move called with drunk not in field')
for i in range(time):
pt = CompassPt(random.choice(CompassPt.possibles))
field.move(pt, 1)

def performTrial(time, f):
start = f.getLoc()
distances = [0.0]
for t in range(1, time+1):
f.getDrunk().move(f)
newLoc = f.getLoc()
distance = newLoc.getDist(start)
distances.append(distance)
return distances

# assert False
drunk = Drunk('a man')
for i in range(3):
f = Field(drunk, Location(0, 0))
distances = performTrial(500, f)
pylab.plot(distances)
pylab.title('random walk')
pylab.xlabel('time')
pylab.ylabel('distance from origin')

pylab.show()

assert False

perform trial 的解释:

  1. inner loop that simolates 1 trial
  2. ‘enclose’ inner loop in a loop that conducts appropriate of trials
  3. calculate and present statics

随机运动的应用:

  • Browning motion:布朗运动
  • stock market:预测股票
  • kinetics
  • evolution