int main()
{
char str[100];
while(scanf("%s",str))
{
int len=strlen(str);
int ar[100];
for( int i=0; i<len; i++ ) ar[i]=i;
VS v;
string st;
sort(ar,ar+len);
do
{
for( int i=0; i<len; i++ ) st+=str[ar[i]];
v.PB(st);
st.clear();
}
while(next_permutation(ar,ar+len));
for( int i=0; i<v.size()/len; i++ )
{
for( int j=i; j<v.size(); j+=7 )
cout<<v[j]<<endl;
}
v.clear();
printf("\n");
}
return 0;
}
int main() {
int m, n;
int i, j, k;
int max_subfile, max_file;
string s, x;
//freopen("f:\\in.txt", "r", stdin);
while (cin >> s) {
flist.clear();
for (i=3; s[i]; ++i) {
if (s[i] == '\\') flist.push_back(s.substr(0, i));
}
n = flist.size();
for (i=0; i!=n; ++i) {
if (fc.find(flist[i]) == fc.end()) {
for (j=0; j!=i; ++j) {
if (subfile.find(flist[j]) == subfile.end()) subfile.insert(make_pair(flist[j], 1));
else ++subfile[flist[j]];
}
fc.insert(flist[i]);
}
if (file.find(flist[i]) == file.end()) file.insert(make_pair(flist[i], 1));
else ++file[flist[i]];
}
}
max_subfile = 0, max_file = 0;
for (MSII it=subfile.begin(); it!=subfile.end(); ++it) max_subfile = max(max_subfile, it->second);
for (MSII it=file.begin(); it!=file.end(); ++it) max_file = max(max_file, it->second);
printf("%d %d\n", max_subfile, max_file);
return 0;
}
int main(){
int i, n; char buff[MAXL]; VS code;
while(scanf("%d", &n) == 1){
code.clear();
for(i = 0; i < n; i++){
scanf(" %s", buff);
code.push_back(buff);
}
printf("[%s]\n", UDFind(code).c_str());
}
return 0;
}
void generateTestData(const int scenario, const int subset) {
size_t subset_total = dataSamples.size() / subsetsNum;
int train_start_index = subset * (int)subset_total;
int test_start_index = train_start_index + subset_total * 0.66;
int end_index = train_start_index + (int)subset_total;
if (end_index > dataSamples.size()) {
end_index = (int)dataSamples.size();
}
//
// prepare train data
//
DTrain.clear();
double mean = 0;
int countIq = 0;
for (int i = train_start_index; i < test_start_index; i++) {
VS rows = dataSamples[i];
for (int r = 0; r < rows.size(); r++) {
string line = rows[r];
VS values = splt(line);
double iq = atof(values[iqCol].c_str());
if (scenario > 0) {
DTrain.push_back(line);
} else if (iq > 0) {
// add only line with IQ set for 1 scenario
DTrain.push_back(line);
}
if (iq > 0) {
mean += iq;
countIq++;
}
}
}
// filterDataSet(DTrain, scenario, true);
//
// prepare test data
//
DTest.clear();
groundTruth.clear();
for (int i = test_start_index; i < end_index; i++) {
VS rows = dataSamples[i];
for (int r = 0; r < rows.size(); r++) {
string line = rows[r];
VS values = splt(line);
double iq = atof(values[iqCol].c_str());
if (iq > 0) {
groundTruth.push_back(iq);
// add only line with IQ set for 1 scenario
DTest.push_back(line);
} else if (scenario > 0) {
DTest.push_back(line);
}
}
}
// filterDataSet(DTest, scenario, false);
//
// calculate sse0
//
mean /= countIq;
sse0 = 0;
for (const double &iq : groundTruth) {
double e = mean - iq;
sse0 += e * e;
}
}
