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Latest 100 public snipts » dgg32's snipts The latest snipts from dgg32.

showing 1-20 of 42 snipts
  • ∞ watchdog 
    #!/usr/bin/env python

import time
import sys
import os
import shutil
from sets import Set

dir = sys.argv[1]
dirList = os.listdir(dir)
fileList = set()


while len(fileList) <= 105:
    time.sleep(60)
    for d in dirList:
        if "Flavobacteria" in d or "Gammaproteobacteria" in d or "Alphaproteobacteria" in d:
            fileList.add(d)

"""
for d in dirList:
    if "Flavobacteria" in d or "Gammaproteobacteria" in d or "Alphaproteobacteria" in d:
        fileList.append(d)
"""     
for f in fileList:
    fullpath = dir + f
    shutil.copy2(fullpath,"/Users/user/Dropbox/mimas_function")

    copy | embed

    0 comments - tagged in  posted by dgg32 on Sep 02, 2010 at 8:41 a.m. EDT
  • ∞ leverage, core 2 duo combining linear and poisson 
    #!/usr/bin/env python
import sys
import re

from collections import defaultdict
import math

#usage: cat file1 file2 file3... | python poisson.py no_of_project r_cutoff filter_value p_cutoff norm_factor (eliminate records with too many zero. For 3 "0" out of 7, filter_value = floor(3/7) = floor(0.42) = 0.4. That means only records with no more than 2 "0" are gonna included in the result)
#written to answer the question: why are there more genes, gene copy or simply more genomes? This program is to check whether the second one is true
#be careful with r: http://en.wikipedia.org/wiki/Anscombe%27s_quartet

def stand_unit(values):
    average = sum(values) / float(len(values))
    quar = 0
    for i in range(len(values)):
        quar += (values[i] - average)**2
    SD = math.sqrt(quar /float(len(values)))
    #print values,SD, quar, average
    
    if SD == 0:
        return []
    else:
        stand_u = []
        for i in range(len(values)):
            stand_u.append((values[i]-average)/float(SD))
        
        return stand_u

def r(x_su, y_su):
    if len(x_su) != len(y_su):
        return -2
    else:
        product = 0
        for i in range(len(x_su)):
            product += x_su[i] * y_su[i]
        #print "product",product
        return product/len(x_su)

def poisson_probability(actual, mean):
    # naive:   math.exp(-mean) * mean**actual / factorial(actual)

    # iterative, to keep the components from getting too large or small:
    p = math.exp(-mean)
    for i in xrange(actual):
        p *= mean
        p /= i+1
    return p

N = list()

Column = -1
Table = defaultdict(list)
rx_contig = re.compile(r'Base\s+(\d+)')
rx_item = re.compile(r'^(.+?)\t\t(\d+)\t\t.+')
rx_total = re.compile(r'total.+')


no_of_project = int(sys.argv[1])
r_cutoff = float(sys.argv[2])
filter_value = float(sys.argv[3])

p_cutoff = float(sys.argv[4])
norm_factor = float(sys.argv[5])

for line in sys.stdin:
    contig = rx_contig.match(line)
    total = rx_total.match(line)    
    item = rx_item.match(line)
    
    if contig:
        Column = Column + 1
        N.append(int(contig.group(1)))
        #print int(contig.group(1))
        
    elif total:
        pass
    elif line == "":
        pass
    elif item:
        #print line
        
        name = item.group(1)
        amount = int(item.group(2))
        
        if name in Table.keys():

                Table[name][Column] = amount
                
        else:
            for i in range(no_of_project):
                if i == Column:
                    Table[name].append(amount)
                else:
                    Table[name].append(0)



Y_stand_unit = stand_unit(N)

print N
for enzyme in Table.keys():
    
    if Table[enzyme].count(0) / float(len(Table[enzyme])) < filter_value: 
        X_stand_unit = stand_unit(Table[enzyme])
        #print "X_stand_unit",X_stand_unit
        if len(X_stand_unit) != 0:
            r_value = r(X_stand_unit, Y_stand_unit)
            #print r_value
            if r_value == -2:
                print "something is wrong. len(x) != len(y)"
            else:
                if abs(r_value) >= r_cutoff:
                    print "linear\t",enzyme,"r:",r_value,Table[enzyme]
                else:
                   
                    
                    
                    total = sum(Table[enzyme])
                    base = sum(N)
                    
                    norm = 0
                    if norm_factor == 0:
                        norm = N[i] 
                    else:
                        norm = norm_factor
                    
                    #norm_occur has no calculatoric meaning for the analysis, i.e. its values are not used in further calculation. It only approximately shows how fit the sample for poisson is.
                    #Based on the approximation: (1/4 + 2/5)/2 about = (1+2)/(4+5)
                    norm_occur = []
                    for j in range(len(N)):
    
                        norm_occur.append(Table[enzyme][j]/(N[j]/float(norm)))
    
                    for i in range(len(Table[enzyme])):
                        rest_total = total - Table[enzyme][i]
                        rest_base = base - N[i]

        
            
        
                        expected = rest_total / (rest_base/float(norm))
        
                        p = poisson_probability(int(math.ceil(Table[enzyme][i]/(N[i]/float(norm)))), expected)
                        
                        if p < p_cutoff:
                        #if int(math.ceil(Table[enzyme][i])) > expected and enzyme == "DAO":
                      #  print "sample",i+1,":",N,Table[enzyme], enzyme,"\t\thigh\t\tcutoff",cutoff,"\t\tp", p, "\t\texpected",expected,"\t\tabundance",Table[enzyme][i],"\t\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm))))
                            if int(math.ceil(Table[enzyme][i])) > expected:
                                print "poisson\tsample",i+1,":",enzyme,"\t\thigh\tp", p, "\texpected",expected,"\tabundance",Table[enzyme][i],"\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm)))),"\t",norm_occur
            
                            else:
                                print "poisson\tsample",i+1,":",enzyme,"\t\tlow\tp", p, "\texpected",expected,"\tabundance",Table[enzyme][i],"\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm)))),"\t",norm_occur

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    0 comments - tagged in  posted by dgg32 on Aug 28, 2010 at 4:12 p.m. EDT
  • ∞ r plot linear line 
    y <- c(1034869, 7258090, 11788562, 32434044, 21325944, 10605149, 1716304);x <- c(3, 10, 9, 37, 26, 23, 3)

plot(x,y, xlab="x axis", ylab="y axis", main="my plot", pch=15, col="blue")
myline.fit <- lm(y ~ x)
abline(myline.fit)

    copy | embed

    0 comments - tagged in  posted by dgg32 on Aug 28, 2010 at 11:02 a.m. EDT
  • ∞ linear_analysis 
    #!/usr/bin/env python
import sys
import re

from collections import defaultdict
import math

#usage: cat file1 file2 file3... | python poisson.py no_of_project r_cutoff filter_value (eliminate records with too many zero. For 3 "0" out of 7, filter_value = floor(3/7) = floor(0.42) = 0.4. That means only records with no more than 2 "0" are gonna included in the result)
#written to answer the question: why are there more genes, gene copy or simply more genomes? This program is to check whether the second one is true
#be careful with r: http://en.wikipedia.org/wiki/Anscombe%27s_quartet

def stand_unit(values):
    average = sum(values) / float(len(values))
    quar = 0
    for i in range(len(values)):
        quar += (values[i] - average)**2
    SD = math.sqrt(quar /float(len(values)))
    #print values,SD, quar, average
    
    if SD == 0:
        return []
    else:
        stand_u = []
        for i in range(len(values)):
            stand_u.append((values[i]-average)/float(SD))
        
        return stand_u

def r(x_su, y_su):
    if len(x_su) != len(y_su):
        return -2
    else:
        product = 0
        for i in range(len(x_su)):
            product += x_su[i] * y_su[i]
        #print "product",product
        return product/len(x_su)


N = list()

Column = -1
Table = defaultdict(list)
rx_contig = re.compile(r'Base\s+(\d+)')
rx_item = re.compile(r'^(.+?)\t\t(\d+)\t\t.+')
rx_total = re.compile(r'total.+')


no_of_project = int(sys.argv[1])
cutoff = float(sys.argv[2])
filter_value = float(sys.argv[3])

for line in sys.stdin:
    contig = rx_contig.match(line)
    total = rx_total.match(line)    
    item = rx_item.match(line)
    
    if contig:
        Column = Column + 1
        N.append(int(contig.group(1)))
        #print int(contig.group(1))
        
    elif total:
        pass
    elif line == "":
        pass
    elif item:
        #print line
        
        name = item.group(1)
        amount = int(item.group(2))
        
        if name in Table.keys():

                Table[name][Column] = amount
                
        else:
            for i in range(no_of_project):
                if i == Column:
                    Table[name].append(amount)
                else:
                    Table[name].append(0)



Y_stand_unit = stand_unit(N)

print N
for enzyme in Table.keys():
    
    if Table[enzyme].count(0) / float(len(Table[enzyme])) < filter_value: 
        X_stand_unit = stand_unit(Table[enzyme])
        #print "X_stand_unit",X_stand_unit
        if len(X_stand_unit) != 0:
            r_value = r(X_stand_unit, Y_stand_unit)
            if r_value == -2:
                print "something is wrong. len(x) != len(y)"
            else:
                if abs(r_value) >= cutoff:
                    print enzyme,"r:",r_value,Table[enzyme], Table[enzyme].count(0)

    copy | embed

    0 comments - tagged in  posted by dgg32 on Aug 28, 2010 at 10:54 a.m. EDT
  • ∞ poisson for paola output 
    #!/usr/bin/env python

import sys
import re

from collections import defaultdict
import math

def poisson_probability(actual, mean):
    # naive:   math.exp(-mean) * mean**actual / factorial(actual)

    # iterative, to keep the components from getting too large or small:
    p = math.exp(-mean)
    for i in xrange(actual):
        p *= mean
        p /= i+1
    return p

#usage: cat file1 file2 file3... | python poisson.py no_of_project p_cutoff norm_factor (0 for individual bin size)
#attention Rashomon effect!
#result largely affected by norm_factor. In my opionion, choosing a norm_factor = average genome size of the target makes most of the sense. In
# that case, the normalization can be understood as computing the amount of gene copies. For Flavo, 3M is reasonal for me.
#written to answer the question: why are there more genes, gene copy or simply more genomes? This program is to check whether the first one is true

N = list()
Column = -1
Table = defaultdict(list)
rx_contig = re.compile(r'Base\s+(\d+)')
rx_item = re.compile(r'^(.+?)\t\t(\d+)\t\t.+')
rx_total = re.compile(r'total.+')


no_of_project = int(sys.argv[1])
cutoff = float(sys.argv[2])
norm_factor = float(sys.argv[3])

for line in sys.stdin:
    contig = rx_contig.match(line)
    total = rx_total.match(line)    
    item = rx_item.match(line)
    
    if contig:
        Column = Column + 1
        N.append(int(contig.group(1)))
        #print int(contig.group(1))
        
    elif total:
        pass
    elif line == "":
        pass
    elif item:
        #print line
        
        name = item.group(1)
        amount = int(item.group(2))
        
        if name in Table.keys():

                Table[name][Column] = amount
                
        else:
            for i in range(no_of_project):
                if i == Column:
                    Table[name].append(amount)
                else:
                    Table[name].append(0)

for enzyme in Table.keys():
    total = sum(Table[enzyme])
    base = sum(N)
    
    for i in range(len(Table[enzyme])):
        rest_total = total - Table[enzyme][i]
        rest_base = base - N[i]
        norm = 0
        if norm_factor == 0:
            norm = N[i] 
        else:
            norm = norm_factor
        
        
            
        
        expected = rest_total / (rest_base/float(norm))
        
        p = poisson_probability(int(math.ceil(Table[enzyme][i]/(N[i]/float(norm)))), expected)
        
        if p < cutoff:
            #if int(math.ceil(Table[enzyme][i])) > expected and enzyme == "DAO":
              #  print "sample",i+1,":",N,Table[enzyme], enzyme,"\t\thigh\t\tcutoff",cutoff,"\t\tp", p, "\t\texpected",expected,"\t\tabundance",Table[enzyme][i],"\t\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm))))
            if int(math.ceil(Table[enzyme][i])) > expected:
                print "sample",i+1,":",enzyme,"\t\thigh\t\tcutoff",cutoff,"\t\tp", p, "\t\texpected",expected,"\t\tabundance",Table[enzyme][i],"\t\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm))))
            
            else:
                print "sample",i+1,":",enzyme,"\t\tlow\t\tcutoff",cutoff,"\t\tp", p, "\t\texpected",expected,"\t\tabundance",Table[enzyme][i],"\t\tactual",int(math.ceil(Table[enzyme][i]/(N[i]/float(norm))))

    copy | embed

    0 comments - tagged in  posted by dgg32 on Aug 23, 2010 at 8:47 p.m. EDT
  • ∞ batch rename, ls | python rename.py 
    #!/usr/bin/env python

import shutil
import sys
import re

rx_ori = re.compile(r'\d+_(fs_img2.+)')
for line in sys.stdin:
    ori = rx_ori.match(line.rstrip())
    
    if ori:
        #print ori.group(1)
        
        shutil.copy2(line.rstrip(), ori.group(1))

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    0 comments - tagged in  posted by dgg32 on Aug 23, 2010 at 7:49 p.m. EDT
  • ∞ euler_problem_297 
    #!/usr/bin/env python
found = 0
F = list()
F.append(1)
F.append(2)
i = 0
#print F

Z = list()
Z.append(1)
Z.append(2)
    
    
while found == 0:

    newValue = F[i] + F[i+1]
    
    
    if newValue >= 10**17:
        F.append(newValue)
        found = 1
    else:
        F.append(newValue)
        newSum = Z[i] + Z[i+1] + F[i] - 1
        Z.append(newSum)
        i += 1
        

def sumZ(n):
    
    if n in F:
        return Z[F.index(n)]
    else:
        lastF = 0
        i = 1
        found = 0
        while found == 0:
            print i,n,len(F),F[len(F)-1]
            if F[i] > n:
                lastF = F[i-1]
                
                #print lastF
                found = 1
            i += 1
                        
        return sumZ(lastF) + sumZ(n-lastF) + n - lastF
        
Value = 10**17-1
print sumZ(Value)

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    0 comments - tagged in  posted by dgg32 on Aug 17, 2010 at 7:34 a.m. EDT
  • ∞ euler_project_267 
    FindMinimum[(9*Log[10] - 1000*Log[1 - f])/Log[(1 + 2 f)/(1 - f)], {f, 
  0.0001, 1}]
N[1 - CDF[BinomialDistribution[1000, 1/2], 431], 12]

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    0 comments - tagged in  posted by dgg32 on Aug 16, 2010 at 7:07 p.m. EDT
  • ∞ euler_project_29 
    #!/usr/bin/env python
from sets import Set

collect = Set()
for a in range(2,101):
    for b in range(2,101):
        collect.add(a**b)
        
print len(collect)

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    0 comments - tagged in  posted by dgg32 on Aug 15, 2010 at 5:20 p.m. EDT
  • ∞ euler_project_286 
    #!/usr/bin/env python

def what_pro(q):
    MasterHash = {0:1}
    for throw in range(1,51):
        newHash = {}
    
        for key in MasterHash.keys():
        
        #score!
            score = key + 1
            probability = MasterHash[key] * (1-throw/float(q))
            if score in newHash:
                newHash[score] += probability
            else:
                newHash[score] = probability
                
            score = key
            probability = MasterHash[key] * (throw/float(q))
            if score in newHash:
                newHash[score] += probability
            else:
                newHash[score] = probability
    
        MasterHash = newHash
    
    return MasterHash[20]


l = 52
u = 53
step = 0
m = 0
while step <= 100:
    m = (l+u)/(float(2))
    
    pro = what_pro(m)
    
    if 0.02 > pro:
        u= m
    elif 0.02 < pro:
        l = m
    step += 1
    print m, pro,l,u
print m

#print what_pro(52.5)

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    0 comments - tagged in  posted by dgg32 on Aug 14, 2010 at 5:08 p.m. EDT
  • ∞ euler_project_280 
    #!/usr/bin/env python



    

# direction: 0 : up, 1 : down, 2 : left, 3 : right

#print Begin.position
#0: position
#1: upper
#2: lower
#3: loaded
MasterHash = {((2,2),(0,0,0,0,0),(1,1,1,1,1),0):1}

sum = 0
for steps in range (1,3000):
    newHash = {}
    
    
    for key in MasterHash.keys():
        possibleDirs = [1,1,1,1]
       
        if key[0][0] == 0:
            possibleDirs[0] = 0
        if key[0][0] == 4:
            possibleDirs[1] = 0
        if key[0][1] == 0:
            possibleDirs[2] = 0
        if key[0][1] == 4:
            possibleDirs[3] = 0
            
        
        
        if possibleDirs[0] == 1:
            
            newkey = list(key)
            
            probability = MasterHash[key] / float(possibleDirs.count(1))
            newpro = (newkey[0][0] - 1, newkey[0][1])
            newkey[0] = newpro
            if newkey[3] == 1 and newkey[0][0] == 0 and newkey[1][newkey[0][1]] == 0:
                newkey[3] = 0
                l = list(newkey[1])
                l[newkey[0][1]] = 1
                newkey[1] = tuple(l)
                
            if newkey[1] == (1,1,1,1,1):
                sum += probability * steps
            elif tuple(newkey) in newHash:
                
                newHash[tuple(newkey)] += probability
            else:
                
                newHash[tuple(newkey)] = probability
           
# direction: 0 : up, 1 : down, 2 : left, 3 : right

#print Begin.position
#0: position
#1: upper
#2: lower
#3: probability
#4: loaded

        if possibleDirs[1] == 1:
            
            newkey = list(key)
            
            probability = MasterHash[key] / float(possibleDirs.count(1))
            newpro = (newkey[0][0] + 1, newkey[0][1])
            newkey[0] = newpro
            if newkey[3] == 0 and newkey[0][0] == 4 and newkey[2][newkey[0][1]] == 1:
                newkey[3] = 1
                l = list(newkey[2])
                l[newkey[0][1]] = 0
                newkey[2] = tuple(l)
                

            if tuple(newkey) in newHash:
                
                newHash[tuple(newkey)] += probability
            else:
                
                newHash[tuple(newkey)] = probability
                

# direction: 0 : up, 1 : down, 2 : left, 3 : right

#print Begin.position
#0: position
#1: upper
#2: lower
#3: probability
#4: loaded
            
        if possibleDirs[2] == 1:
            
            newkey = list(key)
            
            probability = MasterHash[key] / float(possibleDirs.count(1))
            newpro = (newkey[0][0], newkey[0][1] - 1)
            newkey[0] = newpro
            if newkey[3] == 0 and newkey[0][0] == 4 and newkey[2][newkey[0][1]] == 1:
                newkey[3] = 1
                l = list(newkey[2])
                l[newkey[0][1]] = 0
                newkey[2] = tuple(l)
            elif newkey[3] == 1 and newkey[0][0] == 0 and newkey[1][newkey[0][1]] == 0:
                newkey[3] = 0
                l = list(newkey[1])
                l[newkey[0][1]] = 1
                newkey[1] = tuple(l)
                
            if newkey[1] == (1,1,1,1,1):
                sum += probability * steps
            elif tuple(newkey) in newHash:
                
                newHash[tuple(newkey)] += probability
            else:
                
                newHash[tuple(newkey)] = probability
            
            
            
        if possibleDirs[3] == 1:
            
            newkey = list(key)
            
            probability = MasterHash[key] / float(possibleDirs.count(1))
            newpro = (newkey[0][0], newkey[0][1] + 1)
            newkey[0] = newpro
            if newkey[3] == 0 and newkey[0][0] == 4 and newkey[2][newkey[0][1]] == 1:
                newkey[3] = 1
                l = list(newkey[2])
                l[newkey[0][1]] = 0
                newkey[2] = tuple(l)
            elif newkey[3] == 1 and newkey[0][0] == 0 and newkey[1][newkey[0][1]] == 0:
                newkey[3] = 0
                l = list(newkey[1])
                l[newkey[0][1]] = 1
                newkey[1] = tuple(l)
                
            if newkey[1] == (1,1,1,1,1):
                sum += probability * steps
            elif tuple(newkey) in newHash:
                
                newHash[tuple(newkey)] += probability
            else:
                
                newHash[tuple(newkey)] = probability

    
    MasterHash = newHash
    #print steps, len(MasterHash)
    #print len(MasterHash)
"""
    for newkey in newHash.keys():
        print newkey[0],newkey[1],newkey[2],newkey[3], newHash[newkey]
"""
print sum

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    0 comments - tagged in  posted by dgg32 on Aug 14, 2010 at 8:41 a.m. EDT
  • ∞ euler_project_19 
    #!/usr/bin/env python

def cYearCode (n):
    result_d4 = n / 4
    result_m7 = n % 7
    return (result_d4 + result_m7) % 7

def cDayCode (n):
    return (n % 7)

monthcode = [0,3,3,6,1,4,6,2,5,0,3,5]
day = ["sun", "mon", "tue", "wed","thu","fri","sat"]

year = 2000
month = 3
date = 1

code = (cYearCode (year - 1900) +monthcode[month] + cDayCode(1)) % 7
        
if (year - 1900) % 4 == 0 and month <= 1:
    code -= 1
print day[code]


"""
sum = 0
for year in range(1901,2001):
    for month in range(12):
        code = (cYearCode (year - 1900) +monthcode[month] + cDayCode(1)) % 7
        
        if (year - 1900) % 4 == 0 and month <= 1:
            code -= 1
        if code == 0:
            sum += 1
            
print sum
"""

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    0 comments - tagged in  posted by dgg32 on Aug 11, 2010 at 3:26 p.m. EDT
  • ∞ euler_project_18_67 
    #!/usr/bin/env python

import sys

numbers = []

for line in sys.stdin:
    numbers.append([int(x) for x in line.rstrip().split(" ")])
    
MasterHash = {(0, 0):numbers[0][0]}

for line in range(len(numbers)):
    if line != 0:
        prev = numbers[line-1]
        now = numbers[line]
        newHash = {}
        for i in range(len(now)):
            if i == 0:
                tempsum = now[i] + MasterHash[(line-1,i)]
                newHash[(line,i)] = tempsum
            elif i == len(now) - 1:
                tempsum = now[i] + MasterHash[(line-1,i-1)]
                newHash[(line,i)] = tempsum
            else:
                tempsum1 = now[i] + MasterHash[(line-1,i)]
                tempsum2 = now[i] + MasterHash[(line-1,i-1)]
                newHash[(line,i)] = max(tempsum1,tempsum2)
        MasterHash = newHash
            
            
print max([MasterHash[key] for key in MasterHash.keys()])

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    0 comments - tagged in  posted by dgg32 on Aug 11, 2010 at 2:54 p.m. EDT
  • ∞ euler_project_298 
    #!/usr/bin/env python

def RobinResponse(call, Mem):
    newMem = Mem
    if call not in newMem:
        if len(newMem) == 5:
            newMem.pop(0)
        
        newMem.append(call)
    
    return newMem


def LarryResponse(call, Mem):
    newMem = Mem
    if call not in newMem:
        if len(newMem) == 5:
            newMem.pop(0)
        
    else:
        newMem.remove(call)    
    
    newMem.append(call)
        
    return newMem
    
    
def NormalizeLarry (LarryMem, RobinMem):
    outlaw = 5
    newLarryMem = []
    
    for i in range(len(LarryMem)):
        found = 0
        
        for j in range(len(RobinMem)):
            if LarryMem[i] == RobinMem[j]:
                found = 1
                newLarryMem.append(j)
                
        if found == 0:
            newLarryMem.append(outlaw)
            outlaw += 1
    
    return newLarryMem


MasterHash = {((),0):1}

for round in range(50):
    
    
    newHash = {}
    for key in MasterHash.keys():
        for call in range(10):
            RobinPoint = 0
            LarryPoint = 0
            LarryMem = list(key[0])
            RobinMem = range(len(LarryMem))
            
            
            if call in RobinMem:
                RobinPoint = 1
            if call in LarryMem:
                LarryPoint = 1
                
            LarryMem= LarryResponse(call, LarryMem)
            
            RobinMem = RobinResponse(call, RobinMem)
            
            LarryMem = NormalizeLarry(LarryMem, RobinMem)
            
            newDiff = key[1] + LarryPoint - RobinPoint
            if (tuple(LarryMem), newDiff) in newHash:
                newHash[(tuple(LarryMem), newDiff)] += MasterHash[key]
            else:
                newHash[(tuple(LarryMem), newDiff)] = MasterHash[key]
    MasterHash = newHash
    print "round",round,"MasterHash.size",len(MasterHash)
    
    
sum = 0
    
for key in MasterHash.keys():
    
    sum += MasterHash[key]*abs(key[1])
print sum/float(10**50)

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    0 comments - tagged in  posted by dgg32 on Aug 10, 2010 at 5:24 p.m. EDT
  • ∞ correct txt format subtitle 
    #!/usr/bin/env python




import sys
import re


"""
{8078}{8161} 5:25 325 24,85

{45272}{45351} 30:12 1812 24,98

{54078}{54153} 36:04 2164 24,98
"""

offset = sys.argv[1]

rx_time = re.compile(r'{(\d+)}{(\d+)} (.+)')

for line in sys.stdin:
    time = rx_time.match(line)
    
    if time:
        output =  "{"+ str(int(time.group(1)) + int(offset) ) + "}{" + str(int(time.group(2)) + int(offset) ) + "} " + time.group(3).rstrip()
        

        print output

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    0 comments - tagged in  posted by dgg32 on Aug 02, 2010 at 5:11 p.m. EDT
  • ∞ euler_project_290 
    #include <iostream>
#include <QMap>

qulonglong digitsum(qulonglong n)
{
    qulonglong sum = 0;
    while (n > 0)
    {
        sum += n % 10;
        n /= 10;
    }
    return sum;
}

qulonglong carry(qulonglong product)
{

    return product / 10;
}

qulonglong diff (qulonglong original, qulonglong m_137_plus_carry)
{
    qulonglong d_original = digitsum(original);
    qulonglong d_m_137_plus_carry = digitsum(m_137_plus_carry);
    return d_original - d_m_137_plus_carry;
}

qulonglong ge_wei_cha(qulonglong n, qulonglong m_137_plus_carry)
{
    qulonglong ge_of_m_137_plus_carry = m_137_plus_carry % 10;
    return n - ge_of_m_137_plus_carry;
}

int main()
{
    //diff, carry, amount
    QMap <qulonglong, QMap <qulonglong, qulonglong> > diff_carry_amount;
    QMap <qulonglong, qulonglong> map;
    map.insert(0,1);
    diff_carry_amount.insert(0,map);
    QMap <qulonglong, QMap <qulonglong, qulonglong> >::iterator diff_carry_amount_it;
    QMap <qulonglong, qulonglong>::iterator carry_amount_it;
    qulonglong sum = 0;

    for (int position = 1; position <=18; position++)
    {

        //std::cout << "position " << position << std::endl;
        QMap <qulonglong, QMap <qulonglong, qulonglong> > temp;
        for (int digit = 0; digit <= 9; ++digit)
        {
            //qulonglong smallsum = 0;
            for (diff_carry_amount_it = diff_carry_amount.begin(); diff_carry_amount_it != diff_carry_amount.end(); ++diff_carry_amount_it)
            {
                for (carry_amount_it = diff_carry_amount_it.value().begin(); carry_amount_it != diff_carry_amount_it.value().end(); ++carry_amount_it)
                {
                    //std::cout << "carry_amount_it.key " << carry_amount_it.key()  << " carry_amount_it.value " << carry_amount_it.value() << std::endl;

                    if (diff(digit,137*digit+carry_amount_it.key()) == -diff_carry_amount_it.key() && digit != 0)
                    {
                        //smallsum += carry_amount_it.value();
                        sum += carry_amount_it.value();
                    }



                    int c = carry(137*digit + carry_amount_it.key());
                    int d =  ge_wei_cha(digit, 137*digit + carry_amount_it.key())+ diff_carry_amount_it.key();
                   // std::cout <<digit*137+ carry_amount_it.key() << " " << digit << " " << c << " " << d << std::endl;
                    QMap <qulonglong, QMap <qulonglong, qulonglong> >::iterator found = temp.find(d);
                    if (found == temp.end())
                    {
                        QMap <qulonglong, qulonglong> smap;
                        smap.insert(c,carry_amount_it.value());
                        temp.insert(d,smap);
                    }
                    else
                    {
                        QMap <qulonglong, qulonglong>::iterator found2 = found.value().find(c);
                        if (found2 == found.value().end())
                        {
                            found.value().insert(c,carry_amount_it.value());
                        }
                        else
                        {
                            found2.value() += carry_amount_it.value();
                        }
                    }
                }
            }
            //std::cout << "position " << position << " digit: " << digit << " smallsum " << smallsum << std::endl;
        }
        diff_carry_amount = temp;
    }
/**
    QMap <int, int> result= diff_carry_amount.value(0);

    sum = result.size();
*/

    std::cout << "Total: " << sum + 1<< std::endl;
    return 0;
}

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    0 comments - tagged in  posted by dgg32 on Aug 02, 2010 at 6:12 a.m. EDT
  • ∞ binary search 
    #!/usr/bin/env python

import sys

phonebook = [2,3,5,8,11,17]
#phonebook = [2,5,8]
wanted = int(sys.argv[1])
spacesize = len(phonebook)
found = 0
start = 0

while found == 0:
    if len(phonebook) == 1:
        if phonebook[0] != wanted:
            print "wanted not found in phonebook"
            
        else:
            print "wanted found","where:",start
        
        found = 1
    else:
        midindex = int(len(phonebook) / 2)
        print "minindex",midindex

        if wanted > phonebook[midindex]:
            phonebook = phonebook[midindex:]
            start += midindex
        elif wanted < phonebook[midindex]:
            phonebook = phonebook[:midindex]
             
        else:
            found = 1
            print "wanted found","where:",start+midindex

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    0 comments - tagged in  posted by dgg32 on Jul 20, 2010 at 6:09 a.m. EDT
  • ∞ significa 
    #!/usr/bin/env python

import sys
import re

from collections import defaultdict
import math


#usage: cat file1 file2 | python significa.py >> output.txt
# p > e: x < y
# p < e: x > y

def factorial(n):
    f = 1
    for i in range(1,n+1):
        f = f * i
    return f


def proba(x, N1, y, N2, epsi, name):
    #print "x:",x,"y:",y
    p = 0

    for i in range(0, y + 1):
            
        expo = i*math.log10(N2/float(N1)) + math.log10(factorial(x+i)) - (math.log10(factorial(x)) + math.log10(factorial(i)) + (x + i+ 1)* math.log10(1+N2/float(N1)))
            #print expo
        p = p + 10**expo

    if p < epsi or p > (1 - epsi):
        print name,": x and y are significantly different. p = ",p
    else:
        #pass
        print name,": not a big deal, p = ",p

N = list()
Column = -1
Table = defaultdict(list)
rx_contig = re.compile(r'Base\s+(\d+)')
rx_item = re.compile(r'^(.+?)\t\t(\d+)\t\t.+')
rx_total = re.compile(r'total.+')

epsi = 0.05
epsi = float(sys.argv[1])

for line in sys.stdin:
    contig = rx_contig.match(line)
    total = rx_total.match(line)    
    item = rx_item.match(line)
    
    if contig:
        Column = Column + 1
        N.append(int(contig.group(1)))
    elif total:
        pass
    elif line == "":
        pass
    elif item:
        #print line
        
        name = item.group(1)
        amount = int(item.group(2))
        
        if name in Table.keys():

                Table[name][Column] = amount
                
        else:
            if Column == 0:
                Table[name].append(amount)
                Table[name].append(0)
            else:
                Table[name].append(0)
                Table[name].append(amount)
                

#print Table
for key in Table.keys():
    x = Table[key][0]
    y = Table[key][1]
    
    proba(x, N[0], y, N[1], epsi, key)

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    0 comments - tagged in  posted by dgg32 on May 26, 2010 at 11:41 a.m. EDT
  • ∞ winflat 
    #!/usr/bin/env python

import sys
import math

def proba(x, N1, y, N2):
    p = float (0)
    for i in range(0, y + 1):
        p = p + math.factorial(x+i) * (N2/float(N1))**i/float(math.factorial(x)*math.factorial(i)*(1+N2/float(N1))**(x+i+1))
    print "P( y <= ",y," | x = ",x," ) =",p
    print "P( y >= ",y," | x = ",x," ) =",1-p

def sign(x, N1, N2, sig):
    previous = float(0)
    p = float(0)
    i = 0
    while p <= sig and i <= N2:
        previous = p
        p = p + math.factorial(x+i) * (N2/float(N1))**i/float(math.factorial(x)*math.factorial(i)*(1+N2/float(N1))**(x+i+1))
        
        i = i + 1
    
    if p < sig:
        print "error, no value is found"
    else:
        print "sig value",sig,"is between x=",i-2," (p=",previous,") and x=",i-1," (p=",p,")."

x= 0
y =0
N1 = 0
N2 = 0
sig = 0
if sys.argv[1] == "-sig":
    x = int(sys.argv[2])
    N1 = int(sys.argv[3])
    N2 = int(sys.argv[4])
    sig = float(sys.argv[5])
elif sys.argv [1] == "-proba":
    x = int(sys.argv[2])
    N1 = int(sys.argv[3])
    y = int(sys.argv[4])
    N2 = int(sys.argv[5])


if x > N1:
    print "x is bigger than N1"
elif y > N2:
    print "y is bigger than N2"
elif sig > 1:
    print "sig is bigger than 1"
elif sig == 0:
    proba(x,N1,y,N2)
elif sig != 0:
    sign(x, N1, N2, sig)

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    0 comments - tagged in  posted by dgg32 on May 26, 2010 at 4:54 a.m. EDT
  • ∞ export and import tabular data for sector chart 
    Export ["/Users/dgg32/Downloads/test2.dat", {{a, 1, 1}, {b, 2, 3}, {c,
    3, 4}}]

data = Import["/Users/dgg32/Downloads/test2.dat", "Table"];
names = data[[All, 1]]
numbers = data[[All, {2, 3}]]
SectorChart [numbers, SectorOrigin -> {Automatic, 1}, 
 ChartLabels -> Placed[names, "RadialCallout"]]

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    0 comments - tagged in  posted by dgg32 on May 08, 2010 at 5:47 p.m. EDT
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