def main():
lines = fread(data_dir + "fifties.txt")
parsed = [line.strip() for line in lines.split("\n")]
S = add(parsed) # is str
print str(S)[0:10]
def main_alt():
lines = fread(data_dir + "fifties.txt")
# Simple solution taking advantage of python
parsed = [int(line.strip()) for line in lines.split("\n")]
S = sum(parsed) # is int
print str(S)[0:10]
def _token_from_authfile(self):
try:
filecontents = fread(self.authfile)
if filecontents == '':
filecontents = '{}'
return json.loads(filecontents)
except FileNotFoundError:
return {}
def main():
data=fread(data_dir+"grid.txt")
parsed = [map(int,line.split(' ')) for line in data.split('\n')]
# lengths=(list(set(map(len,parsed))))
# if len(lengths)==1: # one length
# horiz=lengths[0]
# vert = len(parsed)
dim,multiplicands=len(parsed),4
maxprod,maxfactors=0,[]
# horizontal products
for row in xrange(0,dim):
for col in xrange(0,dim-(multiplicands-1)):
cand,factors=1,[]
for i in xrange(col,col+multiplicands):
cand=cand*parsed[row][i]
factors=factors+[parsed[row][i]]
if cand>maxprod:
maxprod,maxfactors=cand,factors
# vertical products
for col in xrange(0,dim):
for row in xrange(0,dim-(multiplicands-1)):
cand,factors=1,[]
for i in xrange(row,row+multiplicands):
cand=cand*parsed[i][col]
factors=factors+[parsed[i][col]]
if cand>maxprod:
maxprod,maxfactors=cand,factors
# right descending products
for row in xrange(0,dim-(multiplicands-1)):
for col in xrange(0,dim-(multiplicands-1)):
cand,factors=1,[]
for i in xrange(0,multiplicands):
cand=cand*parsed[row+i][col+i]
factors=factors+[parsed[row+i][col+i]]
if cand>maxprod:
maxprod,maxfactors=cand,factors
# right ascending products
for row in xrange((multiplicands-1),dim):
for col in xrange(0,dim-(multiplicands-1)):
cand,factors=1,[]
for i in xrange(0,multiplicands):
cand=cand*parsed[row-i][col+i]
factors=factors+[parsed[row-i][col+i]]
if cand>maxprod:
maxprod,maxfactors=cand,factors
print maxprod#, maxfactors
def cons(fname):
fs = util.parseFasta(util.fread(fname))
M = map(lambda x: x.seq, fs)
columns = map(lambda c: map(str, c), cols(M))
ncols = len(columns)
freqs = {c: zeros(ncols) for c in "ACGT"}
for i in range(ncols):
for c in columns[i]:
freqs[c][i] += 1
return freqs
def main():
data=fread(data_dir+"largenumber.txt")
mNum=''.join(line.strip() for line in data)
i,length=0,5
mMax,mStr=0,''
for i in xrange(0,len(mNum)-length+1):
product=reduce(lambda x,y:int(x)*int(y),mNum[i:i+length],1)
if product>mMax:
mMax,mStr=product,mNum[i:i+length]
print mMax#,'(\''+mStr+'\')'
async def camera_request(state, payload):
tmp = temperature.get(state["cfg"]["philipshue"])
if "src" in payload and "dst" in payload:
imagefile, objects, ts, snapshots = state["monitor"].get_latest(
payload["snapshot"])
if imagefile == "":
await camera_request_send(state, payload["src"], payload["dst"],
"", 0, 0, 1, snapshots, tmp,
"No snapshot found: %s bytes")
return
ib = util.fread(imagefile, "rb")
encoded = base64.b64encode(ib).decode('ascii')
await camera_request_send(state, payload["src"], payload["dst"],
encoded, objects, ts, 0, snapshots, tmp,
"Snapshot sent: %s bytes")
def main():
data=fread("./data/ocr.txt")
print "".join(findall("[A-Za-z]", data))
def load(self):
try:
return json.loads(util.fread(self.dbfile, "r"))
except:
return {}
import math
from util import parseFasta, fread, fact
def pmch(S):
As = S.count("A")
Cs = S.count("C")
return fact(As) * fact(Cs)
fastas = parseFasta(fread("pmch.in"))
S = fastas[0].seq
print pmch(S)
from util import parseFasta, fread
def sseq(s, t):
"""
Return a collection of indices into s where symbols of
t appear as a subsequence.
"""
res = []
curr_t = 0
for i in range(len(s)):
if s[i] == t[curr_t]:
res.append(i + 1)
curr_t += 1
if curr_t == len(t):
break
return res
fastas = parseFasta(fread("sseq.in"))
s = fastas[0].seq
t = fastas[1].seq
print " ".join(map(str, sseq(s, t)))
from util import parseFasta, fread, kmp_prefix_fn
fastas = parseFasta(fread('kmp.in'))
s = fastas[0].seq
print " ".join(map(str, kmp_prefix_fn(s)))
def get_config():
filename = "config/skypeernet.cfg"
if (len(sys.argv) == 2):
filename = sys.argv[1]
c = util.fread(filename, "r")
return json.loads(c)
from util import transcribe, DNACodonTable, parseFasta, fread
import re
def splc(S, introns):
return transcribe(re.sub(r"|".join(introns), "", S), DNACodonTable)
fastas = parseFasta(fread("splc.in"))
S = fastas[0].seq
introns = map(lambda f: f.seq, fastas[1:])
print splc(S, introns)
from util import parseFasta, fread, transition_p, hamming_errors
def tran(s, t):
n = len(s)
errs = hamming_errors(s, t)
ntrans = sum([1 for i in range(len(errs)) if transition_p(errs[i])])
return float(ntrans) / (len(errs) - ntrans)
fastas = parseFasta(fread("tran.in"))
s = fastas[0].seq
t = fastas[1].seq
print tran(s, t)
from util import parseFasta, fread, reverse_comp
def reverse_pal(S):
return S == reverse_comp(S)
def revp(S):
n = len(S)
minlen = 4
maxlen = 12
res = []
for length in range(minlen, maxlen+1):
for start in range(n-length+1):
if reverse_pal(S[start:start+length]):
res.append([start+1, length])
return res
S = parseFasta(fread("revp.in"))[0].seq
for x in revp(S):
print " ".join(map(str, x))
def main():
data=fread("./data/equality.txt")
print "".join(findall("[^A-Z]+[A-Z]{3}([a-z])[A-Z]{3}[^A-Z]+", data))
import re
from util import outer_product, parseFasta, fread, occurrences, kmers
fastas = parseFasta(fread('kmer.in'))
S = fastas[0].seq
A = kmers(['A', 'C', 'T', 'G'], [0, 4])
for x in [occurrences(S, kmer) for kmer in A]:
print x
# print ' '.join(map(str, [occurrences(S, kmer) for kmer in A]))