I have a file containing the following data.
File1:
Server counter 1:00 2:00 3:00 4:00
site1 serverdowntime 15 0 3 500
site1 serverdowntimesuc 15 0 3 500
...
site12 serverdowntime 2 7 8 5
site12 serverdowntimesuc 2 7 8 5
...
site50 serverdowntime 2 12 8 45
site50 serverdowntimesuc 2 0 0 45
...
site57 serverdowntime 2 12 8 45
site57 serverdowntimesuc 2 0 0 0
Each 2 lines are for the same site. First colum is equipment, second is problem and the third could contain as many columns for the amount of hours pulled. Im looking for a way to look under the time data and find each two lines that contain only single zeros.
Output after parsing data:
site57 serverdowntime 2 12 8 45
site57 serverdowntimesuc 2 0 0 0
site1 serverdowntime 15 0 3 500
site1 serverdowntimesuc 15 0 3 500
site50 serverdowntime 2 12 8 45
site50 serverdowntimesuc 2 0 0 45
$ awk 'NR==1{next} !(NR%2){line1=$0;next} {$0=line1"\n"$0} /\<0\>/' file
site1 serverdowntime 15 0 3 500
site1 serverdowntimesuc 15 0 3 500
site50 serverdowntime 2 12 8 45
site50 serverdowntimesuc 2 0 0 45
site57 serverdowntime 2 12 8 45
site57 serverdowntimesuc 2 0 0 0
This might work for you (GNU sed):
sed -r '$!N;/^(\S+)\s.*\n\1/!D;/(^|\n)(\S+\s+){2}[^\n]*\s0(\s+|\n|$)/p;d' file
This gets a pair of lines with the first field as key and then searches for a 0 pattern in the 3rd onwards fields.
perl -ne '($k)=/^(\w+)/; if (/\b0\b/){ print $v{$k}, $_ }else{ $v{$k}=$_ }' file
Related
I have the two following tables of data, one named data1, the other named data2. The left-hand column is a categorical variable and the right hand column is frequency I would like to rewrite these tables but where there are missing categories in the left-hand column I would like it to put in the correct missing category and then put a '0' in the right-hand frequency column.
data1 = [
1 170
2 120
3 100
4 40
5 30
6 20
7 10
9 8
10 2
11 1
14 1
];
data2 = [
1 240
2 200
3 180
4 60
5 50
6 40
7 30
8 20
9 8
10 2
12 1
19 1
];
To be clearer I will explain with an example. In data1, 8 12 and 13 are missing in the left-hand column. I would like matlab to recreate this table but with 0 values for 8, 12 and 13 so it looks as follows. I would also like it to have additional empty categories after '14' because data2 is longer and has more categories. I have also included what data2 should look like with filled in values.
data1 = [
1 170
2 120
3 100
4 40
5 30
6 20
7 10
8 0
9 8
10 2
11 1
12 0
13 0
14 1
15 0
16 0
17 0
18 0
19 0
];
data2 = [
1 240
2 200
3 180
4 60
5 50
6 40
7 30
8 20
9 8
10 2
11 0
12 1
13 0
14 0
15 0
16 0
17 0
18 0
19 1
];
I have a handful of datasets which generally all start with 1,2,3,4,5...etc but then they all have slightly different categories on the left-hand column, because where values are missing it just omits the category rather than putting 0. How do i write a code so that it automatically fills in any blanks with a 0. It would be good if the code could identify what the 'highest' number of categories is amongst all the datasets and then fill in blanks based on this.
my aim is to put together a grouped bar chart with data series that are all the same length.
UPDATED OUTPUT WITH 3 DATASETS
this is what your AllJoins code outputs in my matlab:
A table1 table2 table3
__ ______ ______ ______
1 170 240 2400
2 120 200 2000
3 100 180 0
4 40 60 0
5 30 50 0
6 20 40 0
7 10 30 0
8 0 20 0
9 8 8 0
10 2 2 0
11 1 0 0
12 0 1 0
14 1 0 0
19 0 1 0
20 0 0 1800
I would like the code to fill in the missing consecutive numbers in column A so that it looks as follows:
A table1 table2 table3
__ ______ ______ ______
1 170 240 2400
2 120 200 2000
3 100 180 0
4 40 60 0
5 30 50 0
6 20 40 0
7 10 30 0
8 0 20 0
9 8 8 0
10 2 2 0
11 1 0 0
12 0 1 0
13 0 0 0
14 1 0 0
15 0 0 0
16 0 0 0
17 0 0 0
18 0 0 0
19 0 1 0
20 0 0 1800
You can convert the datasets to a table and then use outerjoin. Then you can replace the NaNs with whatever you want using fillmissing.
table1 = array2table(data1);
table1.Properties.VariableNames = {'A', 'B'};
table2 = array2table(data2);
table2.Properties.VariableNames = {'A', 'B'};
newTable = outerjoin(table1, table2, 'LeftKeys', {'A'}, 'RightKeys', {'A'}, 'MergeKeys', true)
which produces:
A B_table1 B_table2
__ ________ ________
1 170 240
2 120 200
3 100 180
4 40 60
5 30 50
6 20 40
7 10 30
8 NaN 20
9 8 8
10 2 2
11 1 NaN
12 NaN 1
14 1 NaN
19 NaN 1
And then get your zeros with newTable2 = fillmissing(newTable, 'constant', 0), which prints:
A B_table1 B_table2
__ ________ ________
1 170 240
2 120 200
3 100 180
4 40 60
5 30 50
6 20 40
7 10 30
8 0 20
9 8 8
10 2 2
11 1 0
12 0 1
14 1 0
19 0 1
UPDATE
To combine multiple tables, you can either nest the outerjoin or write a function to loop over it (see similar Matlab forum question). Here's an example.
Given data1 and data2 in OP, plus a new data3:
data3 = [
1 2400
2 2000
20 1800
];
Contents of myscript.m:
table1 = MakeTable(data1);
table2 = MakeTable(data2);
table3 = MakeTable(data3);
AllJoins = MultiOuterJoin(table1, table2, table3);
% Functions
function Table = MakeTable(Array)
Table = array2table(Array);
Table.Properties.VariableNames = {'A', 'B'}; % set your column names, e.g. {'freq', 'count'}
end
function Joined = MultiOuterJoin(varargin)
Joined = varargin{1};
Joined.Properties.VariableNames{end} = inputname(1); % set #2 column name to be based on table name
for k = 2:nargin
Joined = outerjoin(Joined, varargin{k}, 'LeftKeys', {'A'}, 'RightKeys', {'A'}, 'MergeKeys', true);
name = inputname(k);
Joined.Properties.VariableNames{end} = name; % set merged column name to be based on table name
end
end
Which returns AllJoins:
A table1 table2 table3
__ ______ ______ ______
1 170 240 2400
2 120 200 2000
3 100 180 NaN
4 40 60 NaN
5 30 50 NaN
6 20 40 NaN
7 10 30 NaN
8 0 20 NaN
9 8 8 NaN
10 2 2 NaN
11 1 0 NaN
12 0 1 NaN
13 0 0 NaN
14 1 0 NaN
15 0 0 NaN
16 0 0 NaN
17 0 0 NaN
18 0 0 NaN
19 0 1 NaN
20 NaN NaN 1800
Feel free to change the maximum length of the array, this is a generic answer. The maximum length is max(data1(:,1)), but you can compute this in any way, e.g. the maximum value of multiple arrays.
% make new data
new_data1=zeros(max(data1(:,1),2));
new_data(:,1)=1:max(data1(:,1));
% Fill data. You can do this in a loop if its easier for you to understand.
% in essence, it says: in all the data1(:,1) indices of new_data's second column, put data1(:,2)
new_data(data1(:,1),2)=data1(:,2);
I'm trying to get this for loop to work on Matlab so I can plot these three histograms. I'm guessing it won't output because it says that my variables such as a_M_S1 keep changing size on every loop iteration, so the process is essentially inefficient. Any help? Below is the code.
I'm basically trying to generate 500 samples of 100 readings so I can then plot a histogram using estimated parameter values.
clear
clc
% Importing Data
%a = 0.9575
for m=1:500
seed=m;
rng(seed);
syms x
F=((1/atanh(0.9575))*((0.9575^(2*x-1))/(2*x-1)));
for n=1:100
data_1(n)=ceil(vpasolve(F==rand(1)));
end
Data_1(m,:)=data_1;
end
clear
clc
Data_1=[49 1 3 17 13 3 5 51 7 1
9 3 67 1 3 1 1 1 1 99
5 13 21 17 41 1 1 9 23 1
1 5 1 1 41 1 13 1 5 27
5 37 99 1 1 33 1 1 9 1
1 3 47 11 7 1 1 41 21 27
5 1 1 11 45 7 3 5 1 17
13 5 3 3 1 99 1 59 1 13
3 5 1 35 1 1 1 1 5 19
5 1 1 1 79 3 1 1 1 1
31 3 1 1 1 21 69 39 1 29
3 3 1 1 5 1 3 1 1 15
1 1 9 1 7 1 1 1 1 11
27 9 1 3 39 5 1 5 7 1
1 1 7 5 1 1 3 1 3 23
5 1 21 1 1 7 1 17 1 3
11 11 5 1 9 1 1 1 1 37
33 1 9 7 1 1 31 27 1 1
5 5 1 17 3 31 1 45 37 1
1 1 19 47 9 7 5 1 9 1
11 1 61 5 29 1 95 1 1 1
13 19 1 1 13 1 23 7 73 1
1 1 11 1 5 1 3 1 7 1
15 1 9 53 3 7 3 21 7 3
1 7 1 1 23 7 5 1 3 1
1 7 1 3 1 1 1 7 3 5
1 1 1 43 7 3 1 1 21 5
1 39 1 5 13 3 1 5 1 3
1 11 1 1 29 17 25 1 9 1
17 9 13 11 1 5 29 3 3 1
65 5 63 1 1 3 5 1 7 1
21 3 7 1 1 1 27 11 15 3
1 1 1 1 21 1 5 3 1 11
5 1 3 7 1 5 43 5 7 75
29 7 83 1 3 5 15 1 1 3
1 1 9 1 13 1 17 23 1 5
99 1 1 1 5 7 9 3 7 1
1 11 1 11 21 1 5 9 5 1
33 49 3 9 15 1 1 5 1 1
1 17 1 1 1 1 13 1 1 9
5 13 1 1 5 3 1 1 67 1
5 1 1 1 7 27 1 21 47 1
1 1 1 21 3 17 1 5 5 1
1 1 17 29 99 1 9 1 5 15
17 5 1 13 1 1 1 1 1 21
1 21 1 1 1 11 9 35 31 15
99 15 1 1 9 3 1 21 1 1
1 1 9 33 1 1 31 9 29 47
41 99 1 7 17 5 9 3 3 13
1 29 9 5 11 1 1 7 37 15];
Data_2=[1 1 3 3 5 7 1 3 1 1
1 1 1 1 1 1 1 1 1 13
5 1 5 1 1 1 1 3 1 1
1 1 3 1 1 1 1 3 1 1
1 1 13 5 1 3 1 1 5 1
3 3 1 7 3 5 3 1 3 1
1 1 1 1 1 3 3 5 1 1
1 1 1 9 1 1 1 1 5 1
1 1 1 1 1 11 7 1 5 1
17 1 1 7 3 7 3 5 5 1];
for o=1:500
syms a
%Method of Moments (MM)
mean_S1 = mean(transpose(Data_1(o,:)));
a_MM_S1(o) = vpa(vpasolve((a)/((atanh(a))*(1-a.^2)) == mean_S1,a),4);
mean_S2 = mean(transpose(Data_2(o,:)));
a_MM_S2(o) = vpa(vpasolve((a)/((atanh(a))*(1-a.^2)) == mean_S2,a),4);
%Using Lower Quantile (OS)
lower_S1 = floor(quantile(Data_1(o,:),0.25));
a_LQ_S1(o) = vpa(vpasolve((a)/(atanh(a)) == 0.25,a),4);
lower_S2 = floor(quantile(Data_2(o,:),0.25));
a_LQ_S2(o) = vpa(vpasolve((a)/(atanh(a)) == 0.25,a),4);
%Using Median (OSM)
median_S1 = floor(quantile(Data_1(o,:),0.5));
a_M_S1(o) = vpa(vpasolve((a)/(atanh(a)) == 0.5,a),4);
median_S2 = floor(quantile(Data_2(o,:),0.5));
a_M_S2(o) = vpa(vpasolve((a)/(atanh(a)) == 0.5,a),4);
end
a_MM_S1=transpose(a_MM_S1);
a_LQ_S1=transpose(a_LQ_S1);
a_M_S1=transpose(a_M_S1);
a_MM_S2=transpose(a_MM_S2);
a_LQ_S2=transpose(a_LQ_S2);
a_M_S2=transpose(a_M_S2);
figure(1)
histogram([double(a_MM_S1),double(a_MM_S2)],20),title('Method of Moments')
figure(2)
histogram([double(a_LQ_S1),double(a_LQ_S2)],20),title('Using Lower Quartile as Estimator')
figure(3)
histogram([double(a_M_S1),double(a_M_S2)],20),title('Using Median as Estimator')
I am making an exclude vector, so that the rows containing any value present in the second column of the matrix user from the exclude list are removed. How do I do that efficiently, without using a for loop to iterate through user for each item in exclude one by one?
My code below does not work:
count=0;
% Just showing how I am constructing `exclude`, to show that it can be long.
% So, manually removing each item from `exclude` is not an option.
% And using a for loop to iterate through each element in `exclude` can be inefficient.
for b=1:size(user_cat,1)
if user_cat(b,4)==0
count=count+1;
exclude(count,1) = user_cat(b,1);
end
end
% This is the important line of focus. You can ignore the previous parts.
user = user(user(:,2)~=exclude(:),:);
The last line gives the following error:
Error using ~=
Matrix dimensions must agree.
So, I am having to use this instead:
for b=1:size(exclude,1)
user = user(user(:,2)~=exclude(b,1),:);
end
Example:
user=[1433100000.00000 26 620260 7 1433100000000.00 0 0 2 1 100880 290 23
1433100000.00000 26 620260 7 1433100000000.00 0 0 2 1 100880 290 23
1433100000.00000 25 620160 7 1433100000000.00 0 0 2 1 100880 7274 22
1433100000.00000 21 619910 7 1433100000000.00 24.1190000000000 120.670000000000 2 0 100880 53871 21
1433100000.00000 19 620040 7 1433100000000.00 24.1190000000000 120.670000000000 2 0 100880 22466 21
1433100000.00000 28 619030 7 1433100000000.00 24.6200000000000 120.810000000000 2 0 100880 179960 16
1433100000.00000 28 619630 7 1433100000000.00 24.6200000000000 120.810000000000 2 0 100880 88510 16
1433100000.00000 28 619790 7 1433100000000.00 24.6200000000000 120.810000000000 2 0 100880 12696 16
1433100000.00000 7 36582000 7 1433100000000.00 0 0 2 0 100880 33677 14
1433000000.00000 24 620010 7 1433000000000.00 0 0 2 1 100880 3465 14
1433000000.00000 4 36581000 7 1433000000000.00 0 0 2 0 100880 27809 12
1433000000.00000 20 619960 7 1433000000000.00 0 0 2 1 100880 860 11
1433000000.00000 30 619760 7 1433000000000.00 25.0060000000000 121.510000000000 2 0 100880 34706 10
1433000000.00000 33 619910 7 1433000000000.00 0 0 2 0 100880 15060 9
1433000000.00000 26 619740 6 1433000000000.00 0 0 2 0 100880 52514 8
1433000000.00000 18 619900 6 1433000000000.00 0 0 2 0 100880 21696 8
1433000000.00000 16 619850 6 1433000000000.00 24.9910000000000 121.470000000000 2 0 100880 10505 1
1433000000.00000 16 619880 6 1433000000000.00 24.9910000000000 121.470000000000 2 0 100880 1153 1
1433000000.00000 28 619120 6 1433000000000.00 0 0 2 0 100880 103980 24
1433000000.00000 21 619870 6 1433000000000.00 0 0 2 0 100880 1442 24];
exclude=[ 3
4
7
10
17
18
19
28
30
33 ];
Desired output:
1433100000.00000 26 620260 7 1433100000000.00 0 0 2 1 100880 290 23
1433100000.00000 26 620260 7 1433100000000.00 0 0 2 1 100880 290 23
1433100000.00000 25 620160 7 1433100000000.00 0 0 2 1 100880 7274 22
1433100000.00000 21 619910 7 1433100000000.00 24.1190000000000 120.670000000000 2 0 100880 53871 21
1433000000.00000 24 620010 7 1433000000000.00 0 0 2 1 100880 3465 14
1433000000.00000 20 619960 7 1433000000000.00 0 0 2 1 100880 860 11
1433000000.00000 26 619740 6 1433000000000.00 0 0 2 0 100880 52514 8
1433000000.00000 16 619850 6 1433000000000.00 24.9910000000000 121.470000000000 2 0 100880 10505 1
1433000000.00000 16 619880 6 1433000000000.00 24.9910000000000 121.470000000000 2 0 100880 1153 1
1433000000.00000 21 619870 6 1433000000000.00 0 0 2 0 100880 1442 24
Use ismember to find the indices of the second column of user where elements of exclude exist to get the indices of the rows to be removed. Negate these row indices to get the row indices to be kept and use matrix indexing to keep these rows.
user = user(~ismember(user(:,2),exclude),:);
New to [R]studio and respectfully requesting help.
Goal: I'd like to take data collected at 1 second intervals, collapse it to 30 sec intervals, and, subsequently, have the "mean" of each variable associated with it.
Here is what my data looks like:
line datetime AA BB CC
1 2016-06-27 14:13:16 6 0 0.0
2 2016-06-27 14:13:17 10 0 48.6
3 2016-06-27 14:13:18 7 0 52.0
4 2016-06-27 14:13:19 13 0 54.4
5 2016-06-27 14:13:20 16 0 60.8
6 2016-06-27 14:13:21 6 0 65.5
7 2016-06-27 14:13:22 6 0 47.5
8 2016-06-27 14:13:23 6 1 46.8
9 2016-06-27 14:13:24 4 1 55.5
10 2016-06-27 14:13:25 4 1 51.1
11 2016-06-27 14:13:26 4 1 53.4
What I'd like to see is this:
line datetime AA BB CC
1 2016-06-27 14:13:16 18 1 50.5
2 2016-06-27 14:13:46 19 1 52.8
(here, variables AA, BB, and CC were averaged).
There have been questions similar to this, but none that were similar enough to give me a foundation to work on with my little coding and programming knowledge. I've been pacing back and forth between probable base r solutions and probable package solutions to no avail; mainly because the language/syntax implementation is still a bit foreign to me.
I think you want to try this: (base solution)
etw
datetime AA BB CC
1 2016-06-27 14:13:16 6 0 0.0
2 2016-06-27 14:13:17 10 0 48.6
3 2016-06-27 14:13:18 7 0 52.0
4 2016-06-27 14:13:19 13 0 54.4
5 2016-06-27 14:13:20 16 0 60.8
6 2016-06-27 14:13:21 6 0 65.5
7 2016-06-27 14:13:22 6 0 47.5
8 2016-06-27 14:13:23 6 1 46.8
9 2016-06-27 14:13:24 4 1 55.5
10 2016-06-27 14:13:25 4 1 51.1
11 2016-06-27 14:13:26 4 1 53.4
aggregate(x = etw, by = list(cut(etw$datetime,breaks = "10 sec")), FUN=mean )
Group.1 datetime AA BB CC
1 2016-06-27 14:13:16 2016-06-27 14:13:20 7.8 0.3 48.22
2 2016-06-27 14:13:26 2016-06-27 14:13:26 4.0 1.0 53.40
you can change the 10 sec part to 30 sec. however - take care: breaks = "10 sec" will cut the range into 10 sec slices starting with the minimum time. which in your case result in a single slice.
you can also manually define the range using
breaks = seq.POSIXt(from = as.POSIXct("2016-06-27 14:13:00"),to = as.POSIXct("2016-06-27 14:14:00"),by="10 sec"))
aggregate(x = etw,FUN=mean, by = list(cut(etw$datetime,breaks = seq.POSIXt(from = as.POSIXct("2016-06-27 14:13:00"),to = as.POSIXct("2016-06-27 14:14:00"),by="10 sec"))) )
Group.1 datetime AA BB CC
1 2016-06-27 14:13:10 2016-06-27 14:13:17 9.000000 0.0000000 38.75000
2 2016-06-27 14:13:20 2016-06-27 14:13:23 6.571429 0.5714286 54.37143
this is not exactly what you wanted to get but imho - your sample data does not correspond to the desired output :)
I have 4 variables a,b,c,d. a can vary 1,2 i.e. a=1,2, b=1,2,3, c=1,2,3,4, d=1,2,3,4,5 so by varying each element I want to make output value i.e.
a b c d output
1 1 1 1 1
1 1 1 2 2
1 1 1 3 3
1 1 1 4 4
1 1 1 5 5
now varying c with 1 value and d with all values i.e.
a b c d output
1 1 2 1 6
1 1 2 2 7
1 1 2 3 8
1 1 2 4 9
1 1 2 5 10
now change c to 3 and doing above so getting output as 11,12,13,14,15. when c reaches max varying limit then change b i.e.
a b c d output
1 2 1 1 16
1 2 1 2 17
1 2 1 3 18
1 2 1 4 19
1 2 1 5 20
then
a b c d output
1 2 2 1 21
1 2 2 2 22
1 2 2 3 23
1 2 2 4 24
1 2 2 5 25
so like this I want to proceed and want output for all conditions of a,b,c,d. so how to do it or any equation to do this in matlab. in above a,b,c,d vary 2,3,4,5 i.e in increasing order but in general case they can vary without increasing order e.g. a,b,c,d can vary 7,4,9,13.
A possible algorithm could be to buil the combinations column by column considering the number of times eache value has to be repeted starting form the array d
Defined:
len_a the length of the arraya
len_b the length of the arrayb
len_c the length of the arrayc
len_d the length of the arrayd
you need to replicate the d array len_a * len_b * len_c times.
The array c needs to be replicated len_c * len_d times to cover the "right side" combination, the this set of data have to be replicated len_a * len_b times to account for the "left side" to come.
Similar approach applies for the definiton of the array a and b.
To have the set of combinations in a "random" sequence, is sufficient to
use the randperm function.
% Define the input arrays
a=1:2;
len_a=length(a);
b=1:3;
len_b=length(b);
c=1:4;
len_c=length(c);
d=1:5;
len_d=length(d);
% Generate the fourth column of the table
%
d1=repmat(d',len_a*len_b*len_c,1)
%
% Generate the third column of the table
c1=repmat(reshape(bsxfun(#plus,zeros(len_d,1),[1:len_c]),len_c*len_d,1),len_a*len_b,1)
%
% Generate the second column of the table
b1=repmat(reshape(bsxfun(#plus,zeros(len_c*len_d,1),[1:len_b]),len_b*len_c*len_d,1),len_a,1)
%
% Generate the first column of the table
a1=reshape(bsxfun(#plus,zeros(len_b*len_c*len_d,1),[1:len_a]),len_a*len_b*len_c*len_d,1)
%
% Merge the colums and add the counter in the fifth column
combination_set_1=[a1 b1 c1 d1 (1:len_a*len_b*len_c*len_d)']
% Randomize the rows
combination_set_2=combination_set_1(randperm(len_a*len_b*len_c*len_d),:)
Output:
1 1 1 1 1
1 1 1 2 2
1 1 1 3 3
1 1 1 4 4
1 1 1 5 5
1 1 2 1 6
1 1 2 2 7
1 1 2 3 8
1 1 2 4 9
1 1 2 5 10
1 1 3 1 11
1 1 3 2 12
1 1 3 3 13
1 1 3 4 14
1 1 3 5 15
1 1 4 1 16
1 1 4 2 17
1 1 4 3 18
1 1 4 4 19
1 1 4 5 20
1 2 1 1 21
1 2 1 2 22
1 2 1 3 23
1 2 1 4 24
1 2 1 5 25
1 2 2 1 26
1 2 2 2 27
1 2 2 3 28
1 2 2 4 29
1 2 2 5 30
1 2 3 1 31
1 2 3 2 32
1 2 3 3 33
1 2 3 4 34
1 2 3 5 35
1 2 4 1 36
1 2 4 2 37
1 2 4 3 38
1 2 4 4 39
1 2 4 5 40
1 3 1 1 41
1 3 1 2 42
1 3 1 3 43
1 3 1 4 44
1 3 1 5 45
1 3 2 1 46
1 3 2 2 47
1 3 2 3 48
1 3 2 4 49
1 3 2 5 50
1 3 3 1 51
1 3 3 2 52
1 3 3 3 53
1 3 3 4 54
1 3 3 5 55
1 3 4 1 56
1 3 4 2 57
1 3 4 3 58
1 3 4 4 59
1 3 4 5 60
2 1 1 1 61
2 1 1 2 62
2 1 1 3 63
2 1 1 4 64
2 1 1 5 65
2 1 2 1 66
2 1 2 2 67
2 1 2 3 68
2 1 2 4 69
2 1 2 5 70
2 1 3 1 71
2 1 3 2 72
2 1 3 3 73
2 1 3 4 74
2 1 3 5 75
2 1 4 1 76
2 1 4 2 77
2 1 4 3 78
2 1 4 4 79
2 1 4 5 80
2 2 1 1 81
2 2 1 2 82
2 2 1 3 83
2 2 1 4 84
2 2 1 5 85
2 2 2 1 86
2 2 2 2 87
2 2 2 3 88
2 2 2 4 89
2 2 2 5 90
2 2 3 1 91
2 2 3 2 92
2 2 3 3 93
2 2 3 4 94
2 2 3 5 95
2 2 4 1 96
2 2 4 2 97
2 2 4 3 98
2 2 4 4 99
2 2 4 5 100
2 3 1 1 101
2 3 1 2 102
2 3 1 3 103
2 3 1 4 104
2 3 1 5 105
2 3 2 1 106
2 3 2 2 107
2 3 2 3 108
2 3 2 4 109
2 3 2 5 110
2 3 3 1 111
2 3 3 2 112
2 3 3 3 113
2 3 3 4 114
2 3 3 5 115
2 3 4 1 116
2 3 4 2 117
2 3 4 3 118
2 3 4 4 119
2 3 4 5 120
Hope this helps.
Qapla'