I am performing an analysis which involves simulation of over 1000 cases. I extracting lots of data for each case as well (about 70MB). Currently I am saving the results for each case as:
Vessel.TotalForce
Vessel.WindForce
Vessel.CurrentForce
Vessel.WaveForce
Vessel.ConnectionForce
...
Line1.EffectiveTension
Line1.X
Line1.Y
Line2.EfectiveTension
Line2.X
Line2.Y
...
save('CaseNo1.mat')
Now, I need to perform my analysis for CaseNo1.mat to CaseNo1000. Initially I planned to create a Database.mat file by loading all cases in it and then accessing any variable using h5read. This way Matlab doesn't need to load all the data at a time. However, I am concerned now that my database file will be too big.
Is there any way I can read the structured variables from individual case files for example CaseNo1.mat without loading the CaseNo1.mat file in memory.
Matlab examples shows loading just the variables directly from MAT file without loading the whole MAT file. But I am not sure how to read structures data the same way.
x=load('CaseNo1.mat','Line1.X')
says Line1.X not found. But it's there. The command is not correct to access the data. Also tried using h5read, but it says CaseNo1.mat is not an HDF5 file.
Can anyone help with this.
Apart from this, I would also appreciate if there is any suggestion about performing such data intensive analysis.
I was wrong! I'm leaving my old answer for context, though I've edited it to reference this one. I thought I had used matfile() in that way before, but I hadn't. I just did a thorough search and ran a few test cases. You've actually run into a limitation of the way Matlab handles and references structures stored in .mat files. There is, however, a solution. It does involve some refactoring of your original code, but it shouldn't be too egregious.
Vessel_TotalForce
Vessel_WindForce
Vessel_CurrentForce
Vessel_WaveForce
Vessel_ConnectionForce
...
Line1_EffectiveTension
Line1_X
Line1_Y
Line2_EfectiveTension
Line2_X
Line2_Y
...
save('CaseNo1.mat')
Then to access, just use matfile (or load) as you were before. Like so:
Vessel_WaveForce = load('CaseNo1.mat'', 'Vessel_WaveForce')
It's important to note that this restriction doesn't appear to be caused by anything you've chosen to do in your program, but rather is imposed by the way Matlab interacts with it's native storage files when they contain structures.
EDIT: This answer works, but doesn't actually solve the problem posed in OP's question. I thought I had used matfile to generate a handle that I could access, but I was wrong. See my other answer for details.
You could use matfile, like so:
myMatFileHandle = matfile('caseNo1.mat');
thisVessel = myMatFileHandle.vessel;
Also, from the little bit I can see, you seem to be on the right track for high-volume analysis. Just remember to use sparse when applicable, and generally avoid conditionals inside of loops if possible.
Good luck!
The objective of storing data in structured format is:
To be organized
Easy scripting post processor where looping through data under one data set it required.
To store structured dataset containing integer, floating and string variables in MAT file and to be able to read just the required variable using h5read command was sought. Matlab load command is not able to read variable beyond first level from stored data in a MAT file. The h5write couldn't write string variables. Hence needed a work around to solve this problem.
To do this I have used following method:
filename = 'myMatFile';
Vessel.TotalForce = %store some data
Vessel.WindForce = %store some data
Vessel.CurrentForce = %store some data
Vessel.WaveForce = %store some data
Vessel.ConnectionForce = %store some data
...
Lin1.LineType = 'Wire'
Line1.ArcLength_0.EffectiveTension = %store some data
Line1.ArcLength_50.EffectiveTension= %store some data
Line1.ArcLength_100.EffectiveTension= %store some data
Lin2.LineType = 'Chain'
Line2.ArcLength_0.EffectiveTension= %store some data
Line2.ArcLength_50.EffectiveTension= %store some data
Line2.ArcLength_100.EffectiveTension= %store some data
save([filename '_temp.mat']);
PointToMat=matfile([filename '.mat'],'Writable',true);
PointToMat.(char(filename)) = load([filename '_temp.mat']);
delete([filename '_temp.mat']);
Now to read from the MAT file created, we can use h5read as usual. To extract the EffectiveTension for Line1, ArcLength_0:
EffectiveTension = h5read([filename '.mat'],['/' filename '/Line1/ArcLength_0/EffectiveTension']);
For string variables, h5read returns decimal values corresponding to each character. To obtain the actual string I used:
name = char(h5read([filename '.mat'],['/' filename '/Line1/LineType']));
Tried this method on my data set which is about 200MB and I could process them pretty fast. Hope this would help someone someday.
Short answer:
Having saved the data into a MAT file with the '-v7.3' option, use something like h5read(filename, '/Line2/X') to read just one structure field. You can even read an array partially, for example:
s.a = 1:100;
save('test.mat', '-v7.3', 's');
clear
h5read('test.mat', '/s/a', [1 10], [1 5], [1 3])
returns each third element of the 1:100 array, starting with the 10th element and returning 5 values:
10 13 16 19 22
Long answer:
See answer by #Amitava for the more elaborate code and topic coverage.
Related
I'm working with .mat files which are saved at the end of a program. The command is save foo.mat so everything is saved. I'm hoping to determine if the program changes by inspecting the .mat files. I see that from run to run, most of the .mat file is the same, but the field labeled __function_workspace__ changes somewhat.
(I am inspecting the .mat files via scipy.io.loadmat -- just loading the files and printing them out as plain text and then comparing the text. I found that save -ascii in Matlab doesn't put string labels on things, so going through Python is roundabout, but I get labels and that's useful.)
I am trying to determine from where these changes originate. Can anyone explain what __function_workspace__ contains? Why would it not be the same from one run of a given program to the next?
The variables I am really interested in are the same, but I worry that I might be overlooking some changes that might come back to bite me. Thanks in advance for any light you can shed on this problem.
EDIT: As I mentioned in a comment, the value of __function_workspace__ is an array of integers. I looked at the elements of the array and it appears that these numbers are ASCII or non-ASCII character codes. I see runs of characters which look like names of variables or functions, so that makes sense. But there are also some characters (non-ASCII) which don't seem to be part of a name, and there are a lot of null (zero) characters too. So aside from seeing names of things in __function_workspace__, I'm not sure what that stuff is exactly.
SECOND EDIT: I found that after commenting out calls to plotting functions, the content of __function_workspace__ is the same from one run of the program to the next, so that's great. At this point the only difference from one run to the next is that there is a __header__ field which contains a timestamp for the time at which the .mat file was created, which changes from run to run.
THIRD EDIT: I found an article, http://nbviewer.jupyter.org/gist/mbauman/9121961 "Parsing MAT files with class objects in them", about reverse-engineering the __function_workspace__ field. Thanks to Matt Bauman for this very enlightening article and thanks to #mpaskov for the pointer. It appears that __function_workspace__ is an undocumented catch-all for various stuff, only one part of which is actually a "function workspace".
1) Diffing .mat files
You may want to take a look at DiffPlug. It can do diffs of MAT files and I believe there is a command line interface for it as well.
2) Contents of function_workspace
SciPy's __function_workspace__ refers to a special variable at the end of a MAT file that contains extra data needed for reference types (e.g. table, string, handle, etc.) and various other stuff that is not covered by the official documentation. The name is misleading as it really refers to the "Subsystem" (briefly mentioned in the official spec as an offset in the header).
For example, if you save a reference type, e.g., emptyString = "", the resulting .mat will contain the following two entries:
(1) The variable itself. It looks sort of like a UInt32 matrix, but is actually an Opaque MCOS Reference (MATLAB Class Object System) to a string object at some location in the subsystem.
[0] Compressed (81 bytes, position = 128)
[0] Matrix (144 bytes, position = 0)
[0] UInt32[2] = [17, 0] // Opaque
[1] Int8[11] = ['emptyString'] // Variable Name
[2] Int8[4] = ['MCOS'] // Object Type
[3] Int8[6] = ['string'] // Class Name
[4] Matrix (72 bytes, position = 72)
[0] UInt32[2] = [13, 0] // UInt32
[1] Int32[2] = [6, 1] // Dimensions
[2] Int8[0] = [''] // Variable Name (not needed)
[3] UInt32[6] = [-587202560, 2, 1, 1, 1, 1] // Data (Reference Target)
(2) A UInt8 matrix without name (SciPy renamed this to __function_workspace__) at the end of the file. Aside from the missing name it looks like a standard matrix, but the data is actually another MAT file (with a reduced header) that contains the real data.
[1] Compressed (251 bytes, position = 217)
[0] Matrix (968 bytes, position = 0)
[0] UInt32[2] = [9, 0] // UInt8
[1] Int32[2] = [1, 920] // Dimensions
[2] Int8[0] = [''] // Variable Name
[3] ... 920 bytes ... // Data (Nested MAT File)
The format of the data is unfortunately completely undocumented and somewhat of a mess. I could post the contents of the Subsystem, but it gets somewhat overwhelming even for such a simple case. It's essentially a MAT file that contains a struct that contains a special variable (MCOS FileWrapper__) that contains a cell array with various values, including one that magically encodes various Object Properties.
Matt Bauman has done some great reverse engineering efforts (Parsing MAT files with class objects in them) that I believe all supporting implementations are based on. The MFL Java library contains a full (read-only) implementation of this (see McosFileWrapper.java).
Some updates on Matt Bauman's post that we found are:
The MCOS reference can refer to an array of handle objects and may have more than 6 values. It contains sizing information followed by an array of indices (see McosReference.java).
The Object Id field looks like a unique id, but the order seems random and sometimes doesn't match. I don't know what this value is, but completely ignoring it seems to work well :)
I've seen Segment 5 populated in .fig files, but I haven't been able to narrow down what's in there yet.
Edit: Fyi, once the string object is correctly parsed and all properties are filled in, the actual string value is encoded in yet another undocumented format (see testDoubleQuoteString)
I have a list of .txt datafiles to import. Suppose they are called like that
file100data.txt file101data.txt ... file109data.txt I want to import them all using readtable.
I tried using the for to specify a vector a = [0:9] through which matlab could loop the readtable command but I cannot make it work.
for a = [0:9]
T_a_ = readtable('file10_a_data.txt')
end
I know I cannot just put _a_ where I want the vector to loop through, so my question is how can I actually do it?
Thank you in advance!
Here is a solution that should work even if you have missing files in your folder (e.g. you have file100data.txt to file107data.txt, but you are missing file file108data.txt and file109data.txt):
files=dir('file10*data.txt'); %list all data files in your folder
nof=size(files,1); %number of files
for i=1:nof %loop over the number of files
table_index=files(i).name(7) %recover table index from data filename
eval(sprintf('T%s = readtable(files(i).name)', table_index)); %read table
end
Now, please note that is it generally regarded as poor practice to dynamically name variables in Matlab (see this post for example). You may want to resort to structures or cells to store your data.
You need to convert the value of a into a string and combine strings together, like this:
Tables = struct();
for a = 0:9
% note: using dynamic structure field names to store the imported tables
fname = ['file10_' num2str(a) '_data'];
Tables.(fname) = readtable([fname '.txt']);
end
I am running a MATLAB program and storing the results in two matrices. For each run of the program, those matrices are written to the same .csv file.
How can I continue to store data to the same file for future runs of the program? Is there a function that checks for data already being present to avoid overwriting cells?
t = 0.0001*[0:70];
v = B_2*R_R.*exp(-alpha.*t).*sin(omega_d.*t);
tv = [t; v].';
csvwrite('thedata.csv',tv,3,0)
I couldn't resist rewriting your code a bit.
This should be equivalent to what you have, and print both vectors to thedata.csv.
t = 0.0001*[0:70];
v = B_2*R_R.*exp(-alpha.*t).*sin(omega_d.*t);
tv = [t; v].';
csvwrite('thedata.csv',tv,3,0)
Due to the way csv-files are stored, you can only append data at the end of the file, which happens to be the bottom row, not the last column. What you should do, is concatenate all data before writing to the csv-file. That way you avoid multiple calls to csvwrite or dlmwrite (they are time consuming).
If that's impossible, then I suggest reading the data from the csv-file, using csvread, append the new data to the data you retrieve, and write it all back again.
csvwrite('thedata.csv',tv)
mydata = csvread('thedata.csv');
mydata2 = [mydata, tv2];
csvwrite('thedata.csv',mydata2)
I have data stored in the .tdms format, gathering the data of many sensors, measured every second, every day. A new tdms file is created every day, and stored in a folder per month. Using the convertTDMS function, I have converted these tdms files to mat files.
As there are some errors in some of the measurements(e.g. negative values which can not physically occur), I have performed some corrections by loading one mat file at a time, do the calculations and then save the data into the original .mat file.
However, when I try to do what I described above in a loop (so: load .mat in folder, do calculations on one mat file (or channel therein), save mat file, repeat until all files in the folder have been done), I end up running into trouble with the limitations of the save function: so far I save all variables (or am unable to save) in the workspace when using the code below.
for k = 1:nFiles
w{k,1} = load(wMAT{k,1});
len = length(w{k,1}.(x).(y).(z));
pos = find(w{k,1}.(x).(y).(z)(1,len).(y)<0); %Wind speed must be >0 m/s
for n = 1:length(pos)
w{k,1}.(x).(y).(z)(1,len).(y)(pos(n)) = mean([w{k,1}.(x).(y).(z)(1,len).(y)(pos(n)+1),...
w{k,1}.(x).(y).(z)(1,len).(y)(pos(n)-1)],2);
end
save( name{k,1});
%save(wMAT{k,1},w{k,1}.(x),w{k,1}.ConvertVer,w{k,1}.ChanNames);
end
A bit of background information: the file names are stored in a cell array wMAT of length nFiles in the folder. Each cell in the cell array wMAT stores the fullfile path to the mat files.
The data of the files is loaded and saved into the cell array w, also of length nFiles.
Each cell in "w" has all the data stored from the tdms to mat conversion, in the format described in the convertTDMS description.
This means: to get at the actual data, I need to go from the
cell in the cell array w{k,1} (my addition)
to the struct array "ConvertedData" (Structure of all of the data objects - part of convertTDMS)
to the struct array below called "Data" (convertTDMS)
to the struct array below called "MeasuredData" (convertTDMS) -> at this level, I can access the channels which store the data.
to finally access/manipulate the values stored, I have to select a channel, e.g. (1,len), and then go via the struct array to the actual values (="Data"). (convertTDMS)
In Matlab format, this looks like "w{1, 1}.ConvertedData.Data.MeasuredData(1, len).Data(1:end)" or "w{1, 1}.ConvertedData.Data.MeasuredData(1, len).Data".
To make typing easier, I took
x = 'ConvertedData';
y = 'Data';
z = 'MeasuredData';
allowing me to write instead:
w{k,1}.(x).(y).(z)(1,len).(y)
using the dot notation.
My goal/question: I want to load the values stored in a .mat file from the original .tdms files in a loop to a cell array (or if I can do better than a cell array: please tell me), do the necessary calculations, and then save each 'corrected' .mat file using the original name.
So far, I have gotten a multitude of errors from trying a variety of solutions, going from "getfieldnames", trying to pass the name of the (dynamically changing) variable(s), etc.
Similar questions which have helped me get in the right direction include Saving matlab files with a name having a variable input, Dynamically Assign Variables in Matlab and http://www.mathworks.com/matlabcentral/answers/4042-load-files-containing-part-of-a-string-in-the-file-name-and-the-load-that-file , yet the result is that I am still no closer than doing manual labour in this case.
Any help would be appreciated.
If I understand your ultimate goal correctly, I think you're pretty much there. I think you're trying to process your .mat files and that the loading of all of the files into a cell array is not a requirement, but just part of your solution? Assuming this is the case, you could just load the data from one file, process it, save it and then repeat. This way you only ever have one file loaded at a time and shouldn't hit any limits.
Edit
You could certainly make a function out of your code and then call that in a loop, passing in the file name to modify. Personally I'd probably do that as I think it's neater solution. If you don't want to do that though, you could just replace w{k,1} with w then each time you load a file w would be overwritten. If you wanted to explicitly clear variables you can use the clear command with a space separated list of variables e.g. clear w len pos, but I don't think that this is necessary.
I want to create a structure with a variable name in a matlab script. The idea is to extract a part of an input string filled by the user and to create a structure with this name. For example:
CompleteCaseName = input('s');
USER WRITES '2013-06-12_test001_blabla';
CompleteCaseName = '2013-06-12_test001_blabla'
casename(12:18) = struct('x','y','z');
In this example, casename(12:18) gives me the result test001.
I would like to do this to allow me to compare easily two cases by importing the results of each case successively. So I could write, for instance :
plot(test001.x,test001.y,test002.x,test002.y);
The problem is that the line casename(12:18) = struct('x','y','z'); is invalid for Matlab because it makes me change a string to a struct. All the examples I find with struct are based on a definition like
S = struct('x','y','z');
And I can't find a way to make a dynamical name for S based on a string.
I hope someone understood what I write :) I checked on the FAQ and with Google but I wasn't able to find the same problem.
Use a structure with a dynamic field name.
For example,
mydata.(casename(12:18)) = struct;
will give you a struct mydata with a field test001.
You can then later add your x, y, z fields to this.
You can use the fields later either by mydata.test001.x, or by mydata.(casename(12:18)).x.
If at all possible, try to stay away from using eval, as another answer suggests. It makes things very difficult to debug, and the example given there, which directly evals user input:
eval('%s = struct(''x'',''y'',''z'');',casename(12:18));
is even a security risk - what happens if the user types in a string where the selected characters are system(''rm -r /''); a? Something bad, that's what.
As I already commented, the best case scenario is when all your x and y vectors have same length. In this case you can store all data from the different files into 2 matrices and call plot(x,y) to plot each column as a series.
Alternatively, you can use a cell array such that:
c = cell(2,nufiles);
for ii = 1:numfiles
c{1,ii} = import x data from file ii
c{2,ii} = import y data from file ii
end
plot(c{:})
A structure, on the other hand
s.('test001').x = ...
s.('test001').y = ...
Use eval:
eval(sprintf('%s = struct(''x'',''y'',''z'');',casename(12:18)));
Edit: apologies, forgot the sprintf.