I'm trying to get the first Digit of a Long but the Long i'm getting in from the user will be between 13 - 16 digits long how can I get that first Digit without knowing the exact length
Just format it into a character buffer and get the first one. Only if that becomes a performance bottleneck, come back for a more complex solution.
In Java:
// assuming the number is non-negative,
// otherwise need to deal with sign
String firstDigit = String.valueOf(myLong).substring(0,1);
You mentioned this is Java. In Java (and many C based languages), division of integers returns an integer and throws the remainder away. This means that while you have a multiple digit number (in other words, greater than 9), you can divide by 10 to remove the last digit. What you end up with is a single digit number that was the first digit of the original number:
if ( myLong < 0 ) {
myLong *= -1;
}
while ( myLong > 9 ) {
myLong /= 10;
}
The number of digits a number has is just (int)log_10(n). Therefore a power of 10 with the same number of digits as n is (int)pow(10, (int)log_10(n)).
The last digit therefore is just n / (int)pow(10, (int)log_10(n)).
In Java this translates to:
long n = 8797123456789L;
long numDigs = (long)Math.log10(n);
long lastDigit = n / (long)Math.pow(10, numDigs);
System.out.println(lastDigit);
>> 8
Related
How do I call out a particular digit from a number. For example: bringing out 6 from 768, then using 6 to multiply 3. I've tried using the code below, but it does not work.
digits = []
digits = str(input("no:"))
print (int(digits[1] * 5))
If my input is 234 since the value in[1] is 3, how can I multiply the 3 by 5?
input() returns a string (wether or not you explicitly convert it to str() again), so digits[1] is still a single character string.
You need to convert that single digit to an integer with int(), not the result of the multiplication:
print (int(digits[1]) * 5)
All I did was move a ) parenthesis there.
Your mistake was to multiply the single-character string; multiplying a string by n produces that string repeated n times.
digits[1] = '3' so digits[1] * 5 = '33333'. You want int(digits[1]) * 5.
We are given a string which consists of digits 0-9. We have to count number of sub-strings divisible by a number k. One way is to generate all the sub-strings and check if it is divisible by k but this will take O(n^2) time. I want to solve this problem in O(n*k) time.
1 <= n <= 100000 and 2 <= k <= 1000.
I saw a similar question here. But k was fixed as 4 in that question. So, I used the property of divisibility by 4 to solve the problem.
Here is my solution to that problem:
int main()
{
string s;
vector<int> v[5];
int i;
int x;
long long int cnt = 0;
cin>>s;
x = 0;
for(i = 0; i < s.size(); i++) {
if((s[i]-'0') % 4 == 0) {
cnt++;
}
}
for(i = 1; i < s.size(); i++) {
int f = s[i-1]-'0';
int s1 = s[i] - '0';
if((10*f+s1)%4 == 0) {
cnt = cnt + (long long)(i);
}
}
cout<<cnt;
}
But I wanted a general algorithm for any value of k.
This is a really interesting problem. Rather than jumping into the final overall algorithm, I thought I'd start with a reasonable algorithm that doesn't quite cut it, then make a series of modifications to it to end up with the final, O(nk)-time algorithm.
This approach combines together a number of different techniques. The major technique is the idea of computing a rolling remainder over the digits. For example, let's suppose we want to find all prefixes of the string that are multiples of k. We could do this by listing off all the prefixes and checking whether each one is a multiple of k, but that would take time at least Θ(n2) since there are Θ(n2) different prefixes. However, we can do this in time Θ(n) by being a bit more clever. Suppose we know that we've read the first h characters of the string and we know the remainder of the number formed that way. We can use this to say something about the remainder of the first h+1 characters of the string as well, since by appending that digit we're taking the existing number, multiplying it by ten, and then adding in the next digit. This means that if we had a remainder of r, then our new remainder is (10r + d) mod k, where d is the digit that we uncovered.
Here's quick pseudocode to count up the number of prefixes of a string that are multiples of k. It runs in time Θ(n):
remainder = 0
numMultiples = 0
for i = 1 to n: // n is the length of the string
remainder = (10 * remainder + str[i]) % k
if remainder == 0
numMultiples++
return numMultiples
We're going to use this initial approach as a building block for the overall algorithm.
So right now we have an algorithm that can find the number of prefixes of our string that are multiples of k. How might we convert this into an algorithm that finds the number of substrings that are multiples of k? Let's start with an approach that doesn't quite work. What if we count all the prefixes of the original string that are multiples of k, then drop off the first character of the string and count the prefixes of what's left, then drop off the second character and count the prefixes of what's left, etc? This will eventually find every substring, since each substring of the original string is a prefix of some suffix of the string.
Here's some rough pseudocode:
numMultiples = 0
for i = 1 to n:
remainder = 0
for j = i to n:
remainder = (10 * remainder + str[j]) % k
if remainder == 0
numMultiples++
return numMultiples
For example, running this approach on the string 14917 looking for multiples of 7 will turn up these strings:
String 14917: Finds 14, 1491, 14917
String 4917: Finds 49,
String 917: Finds 91, 917
String 17: Finds nothing
String 7: Finds 7
The good news about this approach is that it will find all the substrings that work. The bad news is that it runs in time Θ(n2).
But let's take a look at the strings we're seeing in this example. Look, for example, at the substrings found by searching for prefixes of the entire string. We found three of them: 14, 1491, and 14917. Now, look at the "differences" between those strings:
The difference between 14 and 14917 is 917.
The difference between 14 and 1491 is 91
The difference between 1491 and 14917 is 7.
Notice that the difference of each of these strings is itself a substring of 14917 that's a multiple of 7, and indeed if you look at the other strings that we've matched later on in the run of the algorithm we'll find these other strings as well.
This isn't a coincidence. If you have two numbers with a common prefix that are multiples of the same number k, then the "difference" between them will also be a multiple of k. (It's a good exercise to check the math on this.)
So this suggests another route we can take. Suppose that we find all prefixes of the original string that are multiples of k. If we can find all of them, we can then figure out how many pairwise differences there are among those prefixes and potentially avoid rescanning things multiple times. This won't find everything, necessarily, but it will find all substrings that can be formed by computing the difference of two prefixes. Repeating this over all suffixes - and being careful not to double-count things - could really speed things up.
First, let's imagine that we find r different prefixes of the string that are multiples of k. How many total substrings did we just find if we include differences? Well, we've found k strings, plus one extra string for each (unordered) pair of elements, which works out to k + k(k-1)/2 = k(k+1)/2 total substrings discovered. We still need to make sure we don't double-count things, though.
To see whether we're double-counting something, we can use the following technique. As we compute the rolling remainders along the string, we'll store the remainders we find after each entry. If in the course of computing a rolling remainder we rediscover a remainder we've already computed at some point, we know that the work we're doing is redundant; some previous scan over the string will have already computed this remainder and anything we've discovered from this point forward will have already been found.
Putting these ideas together gives us this pseudocode:
numMultiples = 0
seenRemainders = array of n sets, all initially empty
for i = 1 to n:
remainder = 0
prefixesFound = 0
for j = i to n:
remainder = (10 * remainder + str[j]) % k
if seenRemainders[j] contains remainder:
break
add remainder to seenRemainders[j]
if remainder == 0
prefixesFound++
numMultiples += prefixesFound * (prefixesFound + 1) / 2
return numMultiples
So how efficient is this? At first glance, this looks like it runs in time O(n2) because of the outer loops, but that's not a tight bound. Notice that each element can only be passed over in the inner loop at most k times, since after that there aren't any remainders that are still free. Therefore, since each element is visited at most O(k) times and there are n total elements, the runtime is O(nk), which meets your runtime requirements.
I have been given a binary string of length n and i need to find the minimum numbers of operations to perform such that string does not contain more than k consecutive equal characters.
Only kind of operation I am allowed to perform is to flip any ith character of the string. flipping a character means changing a '1' to '0' or a '0' to '1'.
for example:
if n = 4 , k = 1 and string = 1001
then Answer:
string = 1010 and minimum operations = 2
I need to also find the new string.
can anyone tell me an efficient algorithm for solving problem considering n <=10^5
There's one way:
if k>1:
if k+1 matching characters are found:
if a[k+1]==a[k+2]:
flip a[k+1]
else if a[k+1]!=a[k+2]:
flip a[k]
for k=1 you can do it!
Here flipping means from 1 to 0 and vice-versa
For k=1 there are only two possible output strings - the one beginning with 0 and the one beginning with 1. You can check which of them is closer to the input string.
For larger k, you can just look at every sequence of k+1 identical characters, and fix it internally - without changing the characters at either end. For a sequence of k' > k you would need floor(k'/(k+1)) flips. It should not be hard to show that this is optimal.
Running time is linear and extra space is constant.
There are 2 cases:
1)For k>1
We have 2 possibilities.
a)one that is starting with 0:
eg:0101010101
b)one that is starrting with 1
eg:10101010.....
We should now calculate the distance(the number of different elements between the 2 strings)for each possiblity.Then the ans will be the one that has minimum changes.
2)for k>1
res2=0;res1=1;
c1=A[i];//it represents the last elemnet
i=1;
while(A[i]!='\0'){
if(A[i]==c1){
res1++;//the no of consecutive elements
if(res1>k){
if(A[i]==A[i+1])
flip(i);//it flips the ith element
else
flip(i-1);
res2++;//it counts the no of changes
res1=1;
}
}
else
res1=1;
c1=A[i];
i++;
}
Many languages have functions for converting string to integer and vice versa. So what happens there? What algorithm is being executed during conversion?
I don't ask in specific language because I think it should be similar in all of them.
To convert a string to an integer, take each character in turn and if it's in the range '0' through '9', convert it to its decimal equivalent. Usually that's simply subtracting the character value of '0'. Now multiply any previous results by 10 and add the new value. Repeat until there are no digits left. If there was a leading '-' minus sign, invert the result.
To convert an integer to a string, start by inverting the number if it is negative. Divide the integer by 10 and save the remainder. Convert the remainder to a character by adding the character value of '0'. Push this to the beginning of the string; now repeat with the value that you obtained from the division. Repeat until the divided value is zero. Put out a leading '-' minus sign if the number started out negative.
Here are concrete implementations in Python, which in my opinion is the language closest to pseudo-code.
def string_to_int(s):
i = 0
sign = 1
if s[0] == '-':
sign = -1
s = s[1:]
for c in s:
if not ('0' <= c <= '9'):
raise ValueError
i = 10 * i + ord(c) - ord('0')
return sign * i
def int_to_string(i):
s = ''
sign = ''
if i < 0:
sign = '-'
i = -i
while True:
remainder = i % 10
i = i / 10
s = chr(ord('0') + remainder) + s
if i == 0:
break
return sign + s
I wouldn't call it an algorithm per se, but depending on the language it will involve the conversion of characters into their integral equivalent. Many languages will either stop on the first character that cannot be represented as an integer (e.g. the letter a), will blindly convert all characters into their ASCII value (e.g. the letter a becomes 97), or will ignore characters that cannot be represented as integers and only convert the ones that can - or return 0 / empty. You have to get more specific on the framework/language to provide more information.
String to integer:
Many (most) languages represent strings, on some level or another, as an array (or list) of characters, which are also short integers. Map the ones corresponding to number characters to their number value. For example, '0' in ascii is represented by 48. So you map 48 to 0, 49 to 1, and so on to 9.
Starting from the left, you multiply your current total by 10, add the next character's value, and move on. (You can make a larger or smaller map, change the number you multiply by at each step, and convert strings of any base you like.)
Integer to string is a longer process involving base conversion to 10. I suppose that since most integers have limited bits (32 or 64, usually), you know that it will come to a certain number of characters at most in a string (20?). So you can set up your own adder and iterate through each place for each bit after calculating its value (2^place).
how can i do this integer value is converted to integerlist with three pairs from the and of the integer
input : 24889375
output : [375,889,24]
The same way you do it with one digit, except that you divide and mod by 1000 instead of 10.
You don't list the language, so this will be pseudo code. Use the mod operator (% in The following)
First number = X % 1000;
Second Number = (X/1000)%1000;
Third Number = (X/1000000)%1000;
Note that these operations are all integer operations. The above only works if the / divide operator is an integer divide. If not, truncate it before calculating the modulo.