I have a set of IDs associated with costs which is just a double value. IDs are integers and unique. Two IDs may have same costs. I stored them as:-
a=containers.Map('KeyType','uint32','ValueType','double');
a(1)=7.3
a(2)=8.4
a(3)=7.3
Now i want to find the minimum cost.
b=[];
c=values(a);
b=[b,c{:}];
cost_min=min(b);
Now i want to find all IDs associated i.e. 1 and 3 with the minimum cost i.e. 7.3. I can collect all the keys into an array and then do a for loop over this array. Is there a better way to do this entire thing in Matlab so that for loops are not required?
sparse matrix can work as a hashmap, just do this:
a= sparse(1:3,1,[7.3 8.4 7.3])
find(a == min(nonzeros(a))
There are methods which can be used on maps for this kind of operations
http://se.mathworks.com/help/matlab/ref/containers.map-class.html
The approach finding minimum values and minimum keys can be done something like this,
a=containers.Map('KeyType','uint32','ValueType','double');
a(1)=7.3;
a(3)=8.4;
a(4)=7.3;
minval = inf;
minkeys = -1;
for k = keys(a)
val = a.values(k);
val = val{1};
if (val < minval(1))
minkeys = k;
minval = val;
elseif (val == minval(1))
minkeys = [minkeys,k];
end
end
disp(minval);
disp(minkeys);
This is not efficient though and value search is clumsy for maps. This is not what they are intended for. Maps is supposed to do efficient key lookup. In case you are going to do a lot of lookups and this is what takes time, then use a map. If you need to do a lot of value searches, I would recommend that you use a matrix (or two arrays) for this instead.
idx = [1;3;4];
val = [7.3,8.3,7.3];
minval = min(val);
minidx = idx(val==minval);
disp(minval);
disp(minidx);
There is also another post with an example where it is shown how a sparse matrix can be used as a hashmap. Let the index become the key. This will take about 3 times the memory as all non-zero elements an ordinary array, but a map uses more memory than an array as well.
Related
I am trying to choose a random index for quicksort, but for some reason, the array is not sorting. In fact, the algorithm returns a different array (ex. input [2,1,4] and [1,1,4] is outputted) sometimes. Any help would be much appreciated. This algorithm works if, instead of choosing a random index, I always choose the first element of the array as the pivot.
def quicksort(array):
if len(array) < 2:
return array
else:
random_pivot_index = randint(0, len(array) - 1)
pivot = array[random_pivot_index]
less = [i for i in array[1:] if i =< pivot]
greater = [i for i in array[1:] if i > pivot]
return quicksort(less) + [pivot] + quicksort(greater)
less = [i for i in array[1:] if i =< pivot]
You're including elements equal to the pivot value in less here.
But here, you also include the pivot value explicitly in the result:
return quicksort(less) + [pivot] + quicksort(greater)
Instead try it with just:
return quicksort(less) + quicksort(greater)
Incidentally, though this does divide-and-conquer in the same way as QuickSort does, it's not really an implementation of that algorithm: Actual QuickSort sorts the elements in place - your version will suffer from the run-time overhead associated with allocating and concatenating the utility arrays.
I currently have the deck of cards coded, but it is unshuffled. This is for programming the card game of War if it helps. I need to shuffle the deck, but whenever I do, it will only shuffle together the card numbers and the suits, not the full card. For example, I have A identified as an ace and the suits come after each number. A normal card would be "AH" (an ace of hearts) or "6D" (a six of diamonds). Instead, it will output "5A" as one of the cards, as in a 5 of aces. I don't know how to fix this, but the code that I currently have is this:
card_nums = ('A23456789TJQK')';
card_suits = ('HDSC')';
unshuffled_deck = [repmat(card_nums,4,1),repmat(card_suits,13,1)];
disp(unshuffled_deck)
shuffled_deck = unshuffled_deck(randperm(numel(unshuffled_deck)));
disp(shuffled_deck)
I would appreciate any help with this, and thank you very much for your time!
You're creating a random permutation of all of the elements from both columns of unshuffled_deck combined. Instead you need to create a random permutation of the rows of unshuffled_deck:
shuffled_deck = unshuffled_deck(randperm(size(unshuffled_deck,1)),:);
The call to size gives you the number of rows in the deck array, then we get a random permutation of the row indices, and copy the row (value, suit) as a single entity.
Here's a version using a structure array in response to #Carl Witthoft's comment. I was afraid it would add too much complexity to the solution, but it really isn't bad:
card_nums = ('A23456789TJQK')';
card_suits = ('HDSC')';
deck_nums = repmat(card_nums,4,1);
deck_suits = repmat(card_suits,13,1);
cell_nums = cellstr(deck_nums).'; %// Change strings to cell arrays...
cell_suits = cellstr(deck_suits).'; %// so we can use them in struct
%// Construct a struct array with fields 'value' and 'suit'
unshuffled_deck = struct('value',cell_nums,'suit',cell_suits);
disp('unshuffled deck:');
disp([unshuffled_deck.value;unshuffled_deck.suit]);
%// Shuffle the deck using the number of elements in the structure array
shuffled_deck = unshuffled_deck(randperm(numel(unshuffled_deck)));
disp('shuffled deck:');
disp([shuffled_deck.value; shuffled_deck.suit]);
Here's a test run:
unshuffled deck:
A23456789TJQKA23456789TJQKA23456789TJQKA23456789TJQK
HDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSCHDSC
shuffled deck:
4976TT93KTJQJATK953A75QA82Q6226K5J784J4A3372486K859Q
CHSSSHCDSCSSHDDCDSHHCDHSDDCDHCCHHCHHHDDCSCDSSCHDSCSD
To access an individual card, you can do:
>> shuffled_deck(2)
ans =
scalar structure containing the fields:
value = 9
suit = H
Or you can access the individual fields:
>> shuffled_deck(2).value
ans = 9
>> shuffled_deck(2).suit
ans = H
Unfortunately, I don't know of any way to simply index the struct array and get, for instance, 9H as you would in a regular array using disp(shuffled_deck(2,:)). In this case, the only option I know of is to explicitly concatenate each field:
disp([shuffled_deck(2).value,shuffled_deck(2).suit]);
As simple as in title. I have nx1 sized vector p. I'm interested in the maximum value of r = p/foo - floor(p/foo), with foo being a scalar, so I just call:
max_value = max(p/foo-floor(p/foo))
How can I get which value of p gave out max_value?
I thought about calling:
[max_value, max_index] = max(p/foo-floor(p/foo))
but soon I realised that max_index is pretty useless. I'm sorry asking this, real beginner here.
Having dropped the issue to pieces, I realized there's no unique corrispondence between values p and values in my related vector p/foo-floor(p/foo), so there's a logical issue rather than a language one.
However, given my input data, I know that the solution is unique. How can I fix this?
I ended up doing:
result = p(p/foo-floor(p/foo) == max(p/foo-floor(p/foo)))
Looks terrible, so if you know any other way...
Once you have the index, use it:
result = p(max_index)
You can create a new vector with your lets say "transformed" values:
p2 = (p/foo-floor(p/foo))
and then just use find to find the max values on p2:
max_index = find(p2 == max(p2))
that will return the index or indices of p2 with the max value of that operation, and finally just lookup the original value in p
p(max_index)
in 1 line, this is:
p(find((p/foo-floor(p/foo) == max((p/foo-floor(p/foo))))))
which is basically the same thing you did in the end :)
In MatLab, I have several data vectors that are in text. For example:
speciesname = [species1 species2 species3];
genomelength = [8 10 5];
gonometype = [RNA DNA RNA];
I realise that to make a plot, arrays must be numerical. Is there a quick and easy way to assign unique entries in an array a number, for example so that RNA = 1 and DNA = 2? Note that some arrays might not be binary (i.e. have more than two options).
Thanks!
So there is a quick way to do it, but im not sure that your plots will be very intelligible if you use numbers instead of words.
You can make a unique array like this:
u = unique(gonometype);
and make a corresponding number array is just 1:length(u)
then when you go through your data the number of the current word will be:
find(u == current_name);
For your particular case you will need to utilize cells:
gonometype = {'RNA', 'DNA', 'RNA'};
u = unique(gonometype)
u =
'DNA' 'RNA'
current = 'RNA';
find(strcmp(u, current))
ans =
2
We've got an array of values, and we would like to create another array whose values are not in the first one.
Example:
load('internet.mat')
The first column contains the values in MBs, we have thought in something like:
MB_no = setdiff(v, internet(:,1))
where v is a 0 vector whose length equals to the number of rows in internet.mat. But it just doesn't work.
So, how do we do this?
You need to specify the range of possible values to define what values are not in internet . Say the range is v = 1:10 then setdiff(v,internet(:,1)) will give you the values in 1:10 that are not in the first column of internet.
It seems as if you don't want the first column.
You can simply do:
MB_no=internet(:,2:end);
assuming internet(:,1) has only positive integers and you wish to find which are the integers in [1,...,max( internet(:,1) )] that do not appear in that range you can simply do
app = [];
app( internet(:,1) ) = 1;
MB_no = find( app == 0 );
This is somewhat like bucket sort.