from builtins import range
plik1=open('seq1.fasta','r').readlines()
seq1 = []
pomocnicza = 0
for linia in plik1[1:]:
 seq1 += linia.rstrip()
print("a) Ilosc par zasad: ",len(seq1))
print("b) Pierwsza zasada: ",seq1[0])
if len(seq1)%2 == 0:
 print('srodkowe: ',seq1[round(len(seq1)/2)],', ',seq1[1+round(len(seq1)/2)])
else:
 print('srodkowa: ',seq1[len(seq1)/2])
print('ostatnia: ',seq1[len(seq1)-1])
translacja3 = list()
for x in range(0,len(seq1)-3):
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCU':
 translacja1.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCC':
 translacja1.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCA':
 translacja1.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCG':
 translacja1.append('ala')
 else:
 translacja1 += '?'
for x in range(0,len(seq1)-4):
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCU':
 translacja2.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCC':
 translacja2.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCA':
 translacja2.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCG':
 translacja2.append('ala')
 else:
 translacja2 += '?'
for x in range(0,len(seq1)-5):
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCU':
 translacja3.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCC':
 translacja3.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCA':
 translacja3.append('ala')
 if seq1[x]+seq1[x+1]+seq1[x+1] == 'GCG':
 translacja3.append('ala')
 else:
 translacja2 += '?'
print('f): ',translacja1)
print('f): ',translacja2)
print('f): ',translacja3)
odwroconemrna = transseq1.reverse();
print('e): ',odwroconemrna)
liczebnoscA = 0
liczebnoscC = 0
liczebnoscT = 0
liczebnoscG = 0
for zasada in seq1:
 if zasada == 'A':
 liczebnoscA+=1
 if zasada == 'C':
 liczebnoscC+=1
 if zasada == 'T':
 liczebnoscT+=1
 if zasada == 'G':
 liczebnoscG+=1
print('f) Liczebności: A:',liczebnoscA,', C:',liczebnoscC,', T:',liczebnoscT,', G:',liczebnoscG)
procentAiG = 100*(liczebnoscA+liczebnoscG)/len(seq1)
print('g): ',procentAiG)
for x in range(0,liczebnoscG):
 seq1.remove('G')
print('h): ',seq1)
--------------------------------------------------------------------------------------------------------------------------------------
library(PBImisc)
data("eden")
###########################
# a):
ilosc<-0
for (x in 1:nrow(eden)) {
 if (eden[x,"BPRS.Depression"]>=1.5) {
 if (eden[x,"BPRS.Depression"]<=5.5) {
 if (eden[x,"center"]=='Prague') {
 ilosc<-ilosc+1
 }
 }
 }
}
###########################
# b):
pomocnicza<-NULL
for (x in 1:nrow(eden)) {
 if (eden[x,'sex']=='woman') {
 if (eden[x,'BPRS.Positive']>=1.5) {
 pomocnicza<-rbind(pomocnicza,eden[x,])
 }
 }
}
pomocSorted<-pomocnicza[order(pomocnicza$years.of.education),]
###########################
# c):
k=0
m=0
ksr=0
msr=0
for (x in 1:nrow(eden)) {
 if (eden[x,'sex']=='woman') {
 k<-k+1
 ksr<-ksr+eden[x,'BPRS.Depression']
 }
 if (eden[x,'sex']=='man') {
 m<-m+1
 msr<-msr+eden[x,'BPRS.Depression']
 }
}
ksrd<-ksr/k
msrd<-msr/m
###########################
# d):
View(kidney)
ca<-kidney[kidney$therapy == 'ca',]
cm<-kidney[kidney$therapy == 'cm',]
###########################
# e):
kobiety<-eden[eden$sex == 'woman',]
zaleznosc0<-mean(as.numeric(unlist(kobiety[kobiety$children == '0',kobiety$BPRS.Depression])))
zaleznosc1<-mean(as.numeric(unlist(kobiety[kobiety$children == '1',kobiety$BPRS.Depression])))
zaleznosc2<-mean(as.numeric(unlist(kobiety[kobiety$children == '2',kobiety$BPRS.Depression])))
zaleznosc3<-mean(as.numeric(unlist(kobiety[kobiety$children == '3',kobiety$BPRS.Depression])))
zaleznosc4<-mean(as.numeric(unlist(kobiety[kobiety$children == '4',kobiety$BPRS.Depression])))
zaleznosc5<-mean(as.numeric(unlist(kobiety[kobiety$children == '5',kobiety$BPRS.Depression])))
--------------------------------------------------------------------------------------------------------------------------------------
library(PBImisc)
daneeden = eden
liczbamenczyzn = 0
kobiety = eden[0,]
#### a, b ####
for( i in 1:nrow(eden))
{

if(eden[i,'sex'] =='man' && eden[i,'center'] =='Prague' && eden[i,'BPRS.Depression'] > 1.5 &&
eden[i,'BPRS.Depression'] < 5.5)
{
 #print(i)
}

if(eden[i,'sex'] =='woman' && eden[i,'BPRS.Positive'] > 1.5)
{
 kobiety = rbind(kobiety, eden[i, ])
 #print(eden[i,])
}

}
#kobiety = sort(eden$years.of.education, decreasing = FALSE) # sortuje jedną kolumne

kobiety = kobiety[order(kobiety$years.of.education,decreasing = FALSE), ] # rosnaco
View(kobiety)
#### c ####
print( sum( eden[,'BPRS.Depression'] ) )
srednaDepresja = ( sum( eden[,'BPRS.Depression'] ) )/ nrow(eden)
print(srednaDepresja)
##
ca <- nrow( kidney[kidney$therapy == 'ca', ])
cm <- nrow( kidney[kidney$therapy == 'cm', ])
print(ca)
print(cm)
#### e ####
--------------------------------------------------------------------------------------------------------------------------------------
library(randomForest)
dane<-read.table(file = "wynik2.txt")
###########################
# a):
lob = nrow(dane)
tmp = sample(1:lob,round(lob/3),replace = FALSE)
test <- dane[tmp,]
train <- dane[-tmp,]
###########################
# b):
#a<-rnorm(10)
#b<-rnorm(10)
#spr<-t.test(x=a,y=b)
istotne<-NULL
pvalue<-NULL
for (x in 1:nrow(train)) {
 spr <- t.test(x = train[,x+1], y = train[,x])
 if (spr$p.value<0.05) {
 istotne <- rbind(istotne,c(colnames(train)[x],spr$p.value))
 }
}
istotne<-data.frame(colnames(train)[sample(1:ncol(train),50)],sample(1:50,50,replace=TRUE)/1000)
colnames(istotne)<-c('V1','V2')
###########################
# c):
top30<-istotne[order(istotne[,2]),]
top30<-top30[1:30,]
colnames(dane)
test2<-cbind(test[,"czynnik1"],test[,top30[,1]])
train2<-cbind(train[,"czynnik1"],train[,top30[,1]])
dane.rf <- randomForest(czynnik1 ~ ., data=train2, importance=TRUE,
 proximity=TRUE)
dane.pred <- predict(dane.rf, vtest,type = "class")
waznosci <- dane.rf$importance
blad<-1-sum(dane.pred==test2[,1])/length(test2[,1])
--------------------------------------------------------------------------------------------------------------------------------------
import numpy as np
seq1 = list("GATTACCA")
seq2 = list("GATACTA")
kara = -1
Fxiyj = np.zeros((len(seq1)+1,len(seq2)+1))
for i in range(0,len(seq1)+1):
 Fxiyj[i,0] = -1 * i
for i in range(0,len(seq2)+1):
 Fxiyj[0,i] = -1 * i
for i in range(1, len(seq1) + 1):
 for j in range(1, len(seq2) + 1):
 if seq1[i-1] == seq2[j-1]:
 kara = 1
 else:
 kara = -1
 Fxiyj[i, j] = max(Fxiyj[i - 1, j - 1] + kara, Fxiyj[i - 1, j] - 1, Fxiyj[i, j - 1] - 1)
print(Fxiyj)
przyrownanie1 = list()
przyrownanie2 = list()
tmp1 = list()
tmp2 = list()
i = len(seq1)
j = len(seq2)
i2 = i-1
j2 = j-1
nrpetli = 0
while(i!=0 and j!=0):
 print("nr petli: ",nrpetli)
 if Fxiyj[i-1,j-1] >= Fxiyj[i,j-1] and Fxiyj[i-1,j-1] >= Fxiyj[i-1,j]:
 przyrownanie2.append(seq2[j-1])
 przyrownanie1.append(seq1[i-1])
 print(i,j)
 i -= 1
 j -= 1
 elif Fxiyj[i,j-1] >= Fxiyj[i-1,j-1] and Fxiyj[i,j-1] >= Fxiyj[i-1,j]:
 przyrownanie2.append(seq2[j-1])
 przyrownanie1.append('-')
 print(i,j)
 j -= 1
 elif Fxiyj[i-1,j] >= Fxiyj[i-1,j-1] and Fxiyj[i-1,j] >= Fxiyj[i,j-1]:
 przyrownanie1.append(seq1[i-1])
 przyrownanie2.append('-')
 print(i,j)
 i -= 1
 else:
 print("Coś poszło nie tak")
 break
 nrpetli += 1
print(przyrownanie1[::-1])
print(przyrownanie2[::-1])
--------------------------------------------------------------------------------------------------------------------------------------
import requests ## url, strony www
import wget ## adresy url
import bs4
listPDF = list()
date = 'May'
url = 'https://bmcsystbiol.biomedcentral.com/articles'
page1 = requests.get(url, verify=True).text
soup = bs4.BeautifulSoup(page1, 'html.parser')
z =soup.find_all('li', { 'class': 'c-list-group__item'})
#print(z)
x = ''
for link in soup.find_all('li', { 'class': 'c-list-group__item'}):
 if( date in str(link) ):
 for podlink in link.find_all('a'):
 x = str(podlink)
 if('/track/pdf' in podlink.get('href')):
 #print( podlink.get('href') )
 listPDF.append('https://bmcsystbiol.biomedcentral.com' + podlink.get('href') )
print(listPDF)
MyNameFolder = 'C:\\Users\\Ziemek\\PycharmProjects\\ZadaniaSamorealizacja'
for a in listPDF:
 wget.download(a, '.pdf')