lec4_code

# lec4_code - return minnum, maxnum, avg, sd #returns a tuple...

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def sumnums(*nums): sum=0 for num in nums: sum+=num return sum #can call functions from other functions def myavg(*nums): #pass the sequence *nums just as it is, otherwise it sends a tuple object to sumnums sum=float(sumnums(*nums)) #convert to float to avoid division problems return sum/len(nums) #Define this and have students write it. sigma=sqrt(1/N sum_i^N (x_i - xavg)^2) def stddev(nums): ''' sigma=stddev(sequence) returns the standard deviation of the sequence of numbers ''' from math import sqrt N=len(nums) avgnum=myavg(*nums) sum=0. for num in nums: sum+=(num-avgnum)**2 return sqrt(sum/N) def stats(nums): avg=myavg(*nums) maxnum=max(nums) minnum=min(nums) sd=stddev(nums) #Define this and have students write it.

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Unformatted text preview: return minnum, maxnum, avg, sd #returns a tuple with all the values #Then assign by lowest,highest,average,sd=stats(range(0,20)) #Test with a gaussian distributed random sequence: random.gauss(mean,sd) def randseq(mean,sd,number,type='g'): import random seq= if type=='g': for i in range(number): seq.append(random.gauss(mean,sd)) elif type=='u': for i in range(number): seq.append(random.uniform(mean,sd)) else: print &quot;The type of distribution is 'g' for gaussian (default) or 'u' for uniform&quot; return return seq randlst=randseq(50,3,1000) stddev(randlst) #should be about 3 #pylab has a histogram function from pylab import * hist(randlst)...
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## This note was uploaded on 10/05/2010 for the course PHYS phy503 taught by Professor Gladden during the Spring '09 term at Ole Miss.

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lec4_code - return minnum, maxnum, avg, sd #returns a tuple...

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