I will jump straight into a minimal example as I find this difficult to put into words. I have the following example:
Data.Startdate=[datetime(2000,1,1,0,0,0) datetime(2000,1,2,0,0,0) datetime(2000,1,3,0,0,0) datetime(2000,1,4,0,0,0)];
Data.Enddate=[datetime(2000,1,1,24,0,0) datetime(2000,1,2,24,0,0) datetime(2000,1,3,24,0,0) datetime(2000,1,4,24,0,0)];
Data.Value=[0.5 0.1 0.2 0.4];
Event_start=[datetime(2000,1,1,12,20,0) datetime(2000,1,1,16,0,0) datetime(2000,1,4,8,0,0)];
Event_end=[datetime(2000,1,1,14,20,0) datetime(2000,1,1,23,0,0) datetime(2000,1,4,16,0,0)];
What I want to do is add a flag to the Data structure (say a 1) if any time between Data.Startdate and Data.Enddate falls between Event_start and Event_end. In the example above Data.Flag would have have the values 1 0 0 1 because from the Event_start and Event_end vectors you can see there are events on January 1st and January 4th. The idea is that I will use this flag to process the data further.
I am sure this is straightforward but would appreciate any help you can give.
I would convert the dates to numbers using datenum, which then allows fairly convenient comparisons using bsxfun:
isStartBeforeEvent = bsxfun(#gt,datenum(Event_start)',datenum(Data.Startdate));
isEndAfterEvent = bsxfun(#lt,datenum(Event_end)',datenum(Data.Enddate));
flag = any(isStartBeforeEvent & isEndAfterEvent, 1)
Related
For two arrays (of different length) with datetime values, I want to flag those entries where the date (year, month, day) in both is the same while ignoring the time values. The issue is that the datetime type internally always also contains a time (even the constructor datetime(Y,M,D) will internally set the time to 00:00:00). Therefore a direct comparison of datetimes (dt1 == dt2) will give true only if the times are also the same.
E.g.:
arDt1 = datetime(2021,5,1:10,0,0,0); % 1. to 10. May, always at time 00:00:00
arDt2 = datetime(2021,5,1:2:10,12,0,0); % 1.,3.,5.,7.,9. May always at time 12:00:00
The desired logical array of flags for arDt1 would thus be
[ 1 0 1 0 1 0 1 0 1 0] % days in arDt1 which are also in arDt2, *never mind the time*
The real data extend across multiple months and years, so using the day-of-month number alone is not sufficient (even if it would be for the example above).
I can think of various work-arounds (converting datetime to string and parsing; using ymd() and then compare year, month, day "piecewise"; or forcing all times, at least temporarily, to be the same, e.g. 00:00:00), but it all gets a bit clumsy, esp. when arrays of different lengths are involved, which means ismember() has to be used instead of a direct one-to-one array comparison.
The problem of of processing only the date part of datetime values, regardless of the time part, should be a rather general one, but I can't find any examples or references. Can someone advise a more elegant/efficient way?
You can use the DATESHIFT function to move all of the dates to the start of the day and then do the comparison.
ismember(dateshift(arDt1,'start','day'),dateshift(arDt2,'start','day'))
ans =
1×10 logical array
1 0 1 0 1 0 1 0 1 0
Alternative solution would be to use the properties of datetime directly. Meaning comparing the year, month and day properties. I prefere this approch since it allows me for example also to filter for a given month (neglecting the day).
arDt1 = datetime(2021,5,1:10,0,0,0); % 1. to 10. May, always at time 00:00:00
arDt2 = datetime(2021,5,1:2:10,12,0,0); % 1.,3.,5.,7.,9. May always at time 12:00:00
arDtYMD1 = [arDt1.Year', arDt1.Month', arDt1.Day']; % 10x3 double
arDtYMD2 = [arDt2.Year', arDt2.Month', arDt2.Day']; % 5x3 double
all(ismember(arDtYMD1, arDtYMD2),2) % 10x1 logical array
I am recording voltage changes over a small circuit- this records mouse feeding. When the mouse is eating, the circuit voltage changes, I convert that into ones and zeroes, all is well.
BUT- I want to calculate the number and duration of 'bursts' of feeding- that is, instances of circuit closing that occur within 250 ms (75 samples) of one another. If the gap between closings is larger than 250ms I want to count it as a new 'burst'
I guess I am looking for help in asking matlab to compare the sample number of each 1 in the digital file with the sample number of the next 1 down- if the difference is more than 75, call the first 1 the end of one bout and the second one the start of another bout, classifying the difference as a gap, but if it is NOT, keep the sample number of the first 1 and compare it against the next and next and next until there is a 75-sample difference
I can compare each 1 to the next 1 down:
n=1; m=2;
for i = 1:length(bouts4)-1
if bouts4(i+1) - bouts4(i) >= 75 %250 msec gap at a sample rate of 300
boutend4(n) = bouts4(i);
boutstart4(m)= bouts4(i+1);
m = m+1;
n = n+1;
end
I don't really want to iterate through i for both variables though...
any ideas??
-DB
You can try the following code
time_diff = diff(bouts4);
new_feeding = time_diff > 75;
boutend4 = bouts4(new_feeding);
boutstart4 = [0; bouts4(find(new_feeding) + 1)];
That's actually not too bad. We can actually make this completely vectorized. First, let's start with two signals:
A version of your voltages untouched
A version of your voltages that is shifted in time by 1 step (i.e. it starts at time index = 2).
Now the basic algorithm is really:
Go through each element and see if the difference is above a threshold (in your case 75).
Enumerate the locations of each one in separate arrays
Now onto the code!
%// Make those signals
bout4a = bouts4(1:end-1);
bout4b = bouts4(2:end);
%// Ensure column vectors - you'll see why soon
bout4a = bout4a(:);
bout4b = bout4b(:);
% // Step #1
loc = find(bouts4b - bouts4a >= 75);
% // Step #2
boutend4 = [bouts4(loc); 0];
boutstart4 = [0; bouts4(loc + 1)];
Aside:
Thanks to tail.b.lo, you can also use diff. It basically performs that difference operation with the copying of those vectors like I did before. diff basically works the same way. However, I decided not to use it so you can see how exactly your code that you wrote translates over in a vectorized way. Only way to learn, right?
Back to it!
Let's step through this slowly. The first two lines of code make those signals I was talking about. An original one (up to length(bouts) - 1) and another one that is the same length but shifted over by one time index. Next, we use find to find those time slots where the time index was >= 75. After, we use these locations to access the bouts array. The ending array accesses the original array while the starting array accesses the same locations but moved over by one time index.
The reason why we need to make these two signals column vector is the way I am appending information to the starting vector. I am not sure whether your data comes in rows or columns, so to make this completely independent of orientation, I'm going to make sure that your data is in columns. This is because if I try to append a 0, if I do it to a row vector I have to use a space to denote that I'm going to the next column. If I do it for a column vector, I have to use a semi-colon to go to the next row. To completely avoid checking to see whether it's a row or column vector, I'm going to make sure that it's a column vector no matter what.
By looking at your code m=2. This means that when you start writing into this array, the first location is 0. As such, I've artificially placed a 0 at the beginning of this array and followed that up with the rest of the values.
Hope this helps!
I've been stuck on a MATLAB coding problem where I needed to create market weights for many stocks from a large data file with multiple days and portfolios.
I received help from an expert the other day using 'nested loops' it worked, but I don't understand what he has done in the final line. I was wondering if anyone could shed some light and provide an explanation of the last coding line.
xp = x (where x = market value)
dates=unique(x(:,1)); (finds the unique dates in the data set Dates are column 1)
for i=1:size(dates,1) (creates an empty matrix to fill the data in)
for j=5:size(xp,2)
xp(xp(:,1)==dates(i),j)=xp(xp(:,1)==dates(i),j)./sum(xp(xp(:,1)==dates(i),j)); (help???)
end
end
Any comment are much appreciated!
To understand the code, you have to understand the colon operator, logical indexing and the difference between / and ./. If any of these is unclear, please look it up in the documentation.
The following code does the same, but is easier to read because I separated each step into a single line:
dates=unique(x(:,1));
%iterates over all dates. size(dates,1) returns the number of dates
for i=1:size(dates,1)
%iterates over the fifth to last column, which contains the data that will be normalised.
for j=5:size(xp,2)
%mdate is a logical vector, which is used to select the rows with the currently processed date.
mdate=(xp(:,1)==dates(i))
%s is the sums up all values in column j same date
s=sum(xp(mdate,j))
%divide all values in column j with the same date by s, which normalises to 1
xp(mdate,j)=xp(mdate,j)./s;
end
end
With this code, I suggest to use the debugger and step through the code.
I'm a newbie to Matlab and just stumped how to do a simple task that can be easily performed in excel. I'm simply trying to get the percent change between cells in a matrix. I would like to create a for loop for this task. The data is setup in the following format:
DAY1 DAY2 DAY3...DAY 100
SUBJECT RESULTS
I could only perform getting the percent change between two data points. How would I conduct it if across multiple days and multiple subjects? And please provide explanation
Thanks a bunch
FOR EXAMPLE, FOR DAY 1 SUBJECT1(RESULT=1), SUBJECT2(RESULT=4), SUBJECT3(RESULT=5), DAY 2 SUBJECT1(RESULT=2), SUBJECT2(RESULT=8), SUBJECT3(RESULT=10), DAY 3 SUBJECT1(RESULT=1), SUBJECT2(RESULT=4), SUBJECT3(RESULT=5).
I WANT THE PERCENT CHANGE SO OUTPUT WILL BE DAY 2 SUBJECT1(RESULT=100%), SUBJECT2(RESULT=100%), SUBJECT3(RESULT=100%). DAY3 SUBJECT1(RESULT=50%), SUBJECT2(RESULT=50%), SUBJECT3(RESULT=50%)
updated:
Hi thanks for responding guys. sorry for the confusion. zebediah49 is pretty close to what I'm looking for. My data is for example a 10 x 10 double. I merely wanted to get the percentage change from column to column. For example, if I want the percentage change from rows 1 through 10 on all columns (from columns 2:10). I would like the code to function for any matrix dimension (e.g., 1000 x 1000 double) zebediah49 could you explain the code you posted? thanks
updated2:
zebediah49,
(data(1:end,100)- data(1:end,99))./data(1:end,99)
output=[data(:,2:end)-data(:,1:end-1)]./data(:,1:end-1)*100;
Observing the code above, How would I go about modifying it so that column 100 is used as the index against all of the other columns(1-99)? If I change the code to the following:
(data(1:end,100)- data(1:end,:))./data(1:end,:)
matlab is unable because of exceeding matrix dimensions. How would I go about implementing that?
UPDATE 3
zebediah49,
Worked perfectly!!! Originally I created a new variable for the index and repmat the index to match the matrices which was not a good idea. It took forever to replicate when dealing with large numbers.
Thanks for you contribution once again.
Thanks Chris for your contribution too!!! I was looking more on how to address and manipulate arrays within a matrix.
It's matlab; you don't actually want a loop.
output=input(2:end,:)./input(1:end-1,:)*100;
will probably do roughly what you want. Since you didn't give anything about your matlab structure, you may have to change index order, etc. in order to make it work.
If it's not obvious, that line defines output as a matrix consisting of the input matrix, divided by the input matrix shifted right by one element. The ./ operator is important, because it means that you will divide each element by its corresponding one, as opposed to doing matrix division.
EDIT: further explanation was requested:
I assumed you wanted % change of the form 1->1->2->3->1 to be 100%, 200%, 150%, 33%.
The other form can be obtained by subtracting 100%.
input(2:end,:) will grab a sub-matrix, where the first row is cut off. (I put the time along the first dimension... if you want it the other way it would be input(:,2:end).
Matlab is 1-indexed, and lets you use the special value end to refer to the las element.
Thus, end-1 is the second-last.
The point here is that element (i) of this matrix is element (i+1) of the original.
input(1:end-1,:), like the above, will also grab a sub-matrix, except that that it's missing the last column.
I then divide element (i) by element (i+1). Because of how I picked out the sub-matrices, they now line up.
As a semi-graphical demonstration, using my above numbers:
input: [1 1 2 3 1]
input(2,end): [1 2 3 1]
input(1,end-1): [1 1 2 3]
When I do the division, it's first/first, second/second, etc.
input(2:end,:)./input(1:end-1,:):
[1 2 3 1 ]
./ [1 1 2 3 ]
---------------------
== [1.0 2.0 1.5 0.3]
The extra index set to (:) means that it will do that procedure across all of the other dimension.
EDIT2: Revised question: How do I exclude a row, and keep it as an index.
You say you tried something to the effect of (data(1:end,100)- data(1:end,:))./data(1:end,:). Matlab will not like this, because the element-by-element operators need them to be the same size. If you wanted it to only work on the 100th column, setting the second index to be 100 instead of : would do that.
I would, instead, suggest setting the first to be the index, and the rest to be data.
Thus, the data is processed by cutting off the first:
output=[data(2:end,2:end)-data(2:end,1:end-1)]./data(2:end,1:end-1)*100;
OR, (if you neglect the start, matlab assumes 1; neglect the end and it assumes end, making (:) shorthand for (1:end).
output=[data(2:,2:end)-data(2:,1:end-1)]./data(2:,1:end-1)*100;
However, you will probably still want the indices back, in which case you will need to append that subarray back:
output=[data(1,1:end-1) data(2:,2:end)-data(2:,1:end-1)]./data(2:,1:end-1)*100];
This is probably not how you should be doing it though-- keep data in one matrix, and time or whatever else in a separate array. That makes it much easier to do stuff like this to data, without having to worry about excluding time. It's especially nice when graphing.
Oh, and one more thing:
(data(:,2:end)-data(:,1:end-1))./data(:,1:end-1)*100;
is identically equivalent to
data(:,2:end)./data(:,1:end-1)*100-100;
Assuming zebediah49 guessed right in the comment above and you want
1 4 5
2 8 10
1 4 5
to turn into
1 1 1
-.5 -.5 -.5
then try this:
data = [1,4,5; 2,8,10; 1,4,5];
changes_absolute = diff(data);
changes_absolute./data(1:end-1,:)
ans =
1.0000 1.0000 1.0000
-0.5000 -0.5000 -0.5000
You don't need the intermediate variable, you can directly write diff(data)./data(1:end,:). I just thought the above might be easier to read. Getting from that result to percentage numbers is left as an exercise to the reader. :-)
Oh, and if you really want 50%, not -50%, just use abs around the final line.
I have a data file which contains time data. The list is quite long, 100,000+ points. There is data every 0.1 seconds, and the time stamps are so:
'2010-10-10 12:34:56'
'2010-10-10 12:34:56.1'
'2010-10-10 12:34:56.2'
'2010-10-10 12:34:53.3'
etc.
Not every 0.1 second interval is necessarily present. I need to check whether a 0.1 second interval is missing, then insert this missing time into the date vector. Comparing strings seems unnecessarily complicated. I tried comparing seconds since midnight:
date_nums=datevec(time_stamps);
secs_since_midnight=date_nums(:,4)*3600+date_nums(:,5)*60+date_nums(:,6);
comparison_secs=linspace(0,86400,864000);
res=(ismember(comparison_secs,secs_since_midnight)~=1);
However this approach doesn't work due to rounding errors. Both the seconds since midnight and the linspace of the seconds to compare it to never quite equal up (due to the tenth of a second resolution?). The intent is to later do an fft on the data associated with the time stamps, so I want as much uniform data as possible (the data associated with the missing intervals will be interpolated). I've considered blocking it into smaller chunks of time and just checking the small chunks one at a time, but I don't know if that's the best way to go about it. Thanks!
Multiply your numbers-of-seconds by 10 and round to the nearest integer before comparing against your range.
There may be more efficient ways to do this than ismember. (I don't know offhand how clever the implementation of ismember is, but if it's The Simplest Thing That Could Possibly Work then you'll be taking O(N^2) time that way.) For instance, you could use the timestamps that are actually present (as integer numbers of 0.1-second intervals) as indices into an array.
Since you're concerned with missing data records and not other timing issues such as a drifting time channel, you could check for missing records by converting the time values to seconds, doing a DIFF and finding those first differences that are greater than some tolerance. This would tell you the indices where the missing records should go. It's then up to you to do something about this. Remember, if you're going to use this list of indices to fill the gaps, process the list in descending index order since inserting the records will cause the index list to be unsynchronized with the data.
>> time_stamps = now:.1/86400:now+1; % Generate test data.
>> time_stamps(randi(length(time_stamps), 10, 1)) = []; % Remove 10 random records.
>> t = datenum(time_stamps); % Convert to date numbers.
>> t = 86400 * t; % Convert to seconds.
>> index = find(diff(t) > 1.999 * 0.1)' + 1 % Find missing records.
index =
30855
147905
338883
566331
566557
586423
642062
654682
733641
806963