I am looking for a way to list the differences between two .mat files, something that can be usefull for many people.
Though I searched everywhere I could think of, I have not found anything that meets my requirements:
Pick 2 mat files
Find the differences
Save them properly
The closest I have come is visdiff. As long as I stay within matlab, it will allow me to browse the differences, but when I save the result it only shows me the top level.
Here is a simplified example of what my files typically look like:
a = 6;
b.c.d = 7;
b.c.e = 'x';
save f1
f = a;
clear a
b.c.e = 'y';
save f2
visdiff('f1.mat','f2.mat')
If I click here on b, I can find the difference. However if I run this and use 'file>save', I am not able to click on b. Thus I still don't know what has been changed.
Note: I don't have Simulink
Hence my question is:
How can I show all differences between 2 mat files to someone without Matlab
Here are the answers that I personally consider to be most suitable for different situations:
Answer for users with Simulink
General answer
Answer displaying all value differences
Find all differences between mat files without MATLAB?
You can find the differences between HDF5 based .mat files with the HDF5 Tools.
Example
Let me shorten your MATLAB example and assume you create two mat files with
clear ; a = 6 ; b.c = 'hello' ; save -v7.3 f1
clear ; a = 7 ; b.e = 'world' ; save -v7.3 f2
Outside MATLAB use
h5ls -v -r f1.mat
to get a listing about the kind of data included f1.mat:
Opened "f1.mat" with sec2 driver.
/ Group
Location: 1:96
Links: 1
/a Dataset {1/1, 1/1}
Attribute: MATLAB_class scalar
Type: 6-byte null-terminated ASCII string
Data: "double"
Location: 1:2576
Links: 1
Storage: 8 logical bytes, 8 allocated bytes, 100.00% utilization
Type: native double
/b Group
Attribute: MATLAB_class scalar
Type: 6-byte null-terminated ASCII string
Data: "struct"
Location: 1:800
Links: 1
/b/c Dataset {5/5, 1/1}
Attribute: H5PATH scalar
Type: 2-byte null-terminated ASCII string
Data: "/b"
Attribute: MATLAB_class scalar
Type: 4-byte null-terminated ASCII string
Data: "char"
Attribute: MATLAB_int_decode scalar
Type: native int
Data: 2
Location: 1:1832
Links: 1
Storage: 10 logical bytes, 10 allocated bytes, 100.00% utilization
Type: native unsigned short
Use of
h5ls -d -r f1.mat
returns the values of the stored data:
/ Group
/a Dataset {1, 1}
Data:
(0,0) 6
/b Group
/b/c Dataset {5, 1}
Data:
(0,0) 104, 101, 108, 108, 111
The data 104, 101, 108, 108, 111 represents the word hello, which can be seen with
h5ls -d -r f1.mat | tail -1 | awk '{FS=",";printf("%c%c%c%c%c \n",$2,$3,$4,$5,$6)}'
You can get the same listing for f2.mat and compare the two outputs with the tool of your choice.
Comparison also works directly with HDF5 Tools. To compare the two numbers a from both files use
h5diff -r f1.mat f2.mat /a
which will show you the values and their difference
dataset: </a> and </a>
size: [1x1] [1x1]
position a a difference
------------------------------------------------------------
[ 0 0 ] 6 7 1
1 differences found
attribute: <MATLAB_class of </a>> and <MATLAB_class of </a>>
0 differences found
Remarks
There are a few more commands and options in the HDF5 Tools, which may help to get your real problem solved.
Binary distributions are available for Linux and Windows from The HDF Group. For OS X you can get them installed via MacPorts. If needed there is also a GUI: HDFView.
If you have simulink you can use Simulink.saveVars to generate an m-file that upon execution creates the same variables in work space:
a = 6;
b.c.d = 7;
b.c.e = 'x';
Simulink.saveVars('f1');
f = a;
clear a
b.c.e = 'y';
Simulink.saveVars('f2');
visdiff('f1.m','f2.m')
as illustrated in this sctreenshot
Note that by default it limits the number of elements in arrays to 1000 and you can increase it to 10000. Arrays larger than that limit will be saved in a separate mat-file.
UPDATE: From R2014a a new function similar to Simulink.saveVars has been added to MATLAB. see matlab.io.saveVariablesToScript
This is only part of the answer, but maybe it helps.
You could use gencode, a Matlab function that generates Matlab code from a variable such that running the code reproduces the variable. You do this for all of the variables in each mat-file (takes some programming, but should be doable) and put the results in different .m-files.
Then you use a standard text comparison tool (maybe even visdiff) to compare the .m-files.
There are several good tools to compare XML-Files, this I would proceed this way:
Download struct2xml.m
Load both matfiles
Export each with struct2xml
compare, using XMLSpy or similar
Simple general answer, without displaying value differences
Due to the insight I gained from the answers of #BHF, #Daniel R and #Dennis Jaheruddin, I have managed to find a simple scalable solution:
[fs1, fs2, er] = comp_struct(load('f1.mat'),load('f2.mat'))
Note that it works for .mat containing an arbritrary number of variables.
This uses the Compare Structures - File Exchange submission.
Answer for small files, displaying all value differences
Based on the suggestion by #A. Donda I have tried to use gencode to create a variable for everything.
Though it works for my toy example, it is quite slow and tells me that I exceed the allowed amount of variables for my real .mat files.
Anyway, for those who are looking for something that works with small files, I will post this option:
wList=who;
for iLoop = 1:numel(wList)
eval(['generated_' wList{iLoop} '= gencode(' wList{iLoop} ');'])
for jLoop = 1:numel(eval(['generated_' wList{iLoop}]))
eval(['generated_' wList{iLoop} '_' num2str(jLoop) '= generated_' wList{iLoop} '(' num2str(jLoop) ');' ])
end
end
Though it may work, I don't feel like this is the best way to go.
General answer, without displaying value differences
Due to the insight I gained from the answers of #BHF and #Daniel R I have managed to find a reasonably scalable solution.
Step 1: Save all variables from each files as a single struct
This uses the Save workspace to struct - File Exchange submission.
Here are the steps to take assuming you want to compare f1.mat and f2.mat:
clear
load f1
myStruct1 = ws2struct;
save myStruct1 myStruct1
clear
load f2
myStruct2 = ws2struct;
save myStruct2 myStruct2
clear
load myStruct1
load myStruct2
Step 2: Compare the structs
This uses the Compare Structures - File Exchange submission
Given that you want to compare myStruct1 and myStruct2 you can simply call:
[fs1, fs2, er] = comp_struct(myStruct1,myStruct2)
I was positively surprised at how readable the list of differences in er is, here is the output for the example that was used in the question:
er =
's2 is missing field a'
's1(1).b(1).c(1).e and s2(1).b(1).c(1).e do not match'
Note that it will not show values, from a technical point of view it is probably not too hard to change the m file if value difference displays are desirable. However, especially if there are some big matrices I suppose this could result in problematic output.
Related
I am reading in a binary EDF file and I have to split it into multiple smaller EDF files at specific points and then adjust some of the values inside. Overall it works quite well but when I read in the file it combines 2 character arrays with each other. Obviously everything afterwords gets corrupted as well. I am at a dead end and have no idea what I'm doing wrong.
The part of the code (writing) that has to contain the problem:
byt=fread(fid,8,'*char');
fwrite(tfid,byt,'*char');
fwrite(tfid,fread(fid,44));
%new number of records
s = records;
fwrite(tfid,s,'*char');
fseek(fid,8,0);
%test
fwrite(tfid,fread(fid,8,'*char'),'*char');
When I use the reader it combines the records (fwrite(tfid,s,'*char'))
with the value of the next variable. All variables before this are displayed correctly. The relevant code of the reader:
hdr.bytes = str2double(fread(fid,8,'*char')');
reserved = fread(fid,44);%#ok
hdr.records = str2double(fread(fid,8,'*char')');
if hdr.records == -1
beep
disp('There appears to be a problem with this file; it returns an out-of-spec value of -1 for ''numberOfRecords.''')
disp('Attempting to read the file with ''edfReadUntilDone'' instead....');
[hdr, record] = edfreadUntilDone(fname, varargin);
return
end
hdr.duration = str2double(fread(fid,8,'*char')');
The likely problem is that your character array s does not have 8 characters in it, but you expect there to be 8 when you read it from the file. Whatever the number of characters in the array is, that's how many values fwrite will write out to the file. Anything less than 8 characters and you'll end up reading part of the next piece of data when you read from the file.
One fix would be to pad s with blanks before writing it:
s = [blanks(8-numel(records)) records];
In addition, the syntax '*char' is only valid when using fread: the * indicates that the output class should be 'char' as well. It's unnecessary when using fwrite.
I am trying to read all the images in the folder in MATLAB using this code
flst=dir(str_Expfold);
But it shows me output like this. which is not the sequence as i want.
Can anyone please tell me how can i read all of them in sequence?
for giving downmark, please explain the reason for that too.
By alphabetical order depth10 comes before depth2. If at all possible, when creating string + num type filenames, use a fixed width numerical part (e.g. depth01, depth02) - this tends to avoid sorting problems.
If you are stuck with the filenames you have, and know the filename pattern, though, you can not bother using dir at all and create your filename list in the correct order in the first place:
for n = 1:50
fname = sprintf('depth%d.png',n);
% code to read and process images goes here
end
From the Matlab forums, the dir command output sorting is not specified, but it seems to be purely alphabetical order (with purely I mean that it does not take into account sorter filenames first). Therefore, you would have to manually sort the names. The following code is taken from this link (you probably want to change the file extension):
list = dir(fullfile(cd, '*.mat'));
name = {list.name};
str = sprintf('%s#', name{:});
num = sscanf(str, 'r_%d.mat#');
[dummy, index] = sort(num);
name = name(index);
I want to import the large data set (multiple column) by using the following code. I want to get all in a single column instead only one row (multi column). So i did transpose operation but it still doesn't work appropriately.
clc
clear all
close all
dataX_Real = fopen('dataX_Real_in.txt');dataX_Real=dataX_Real';
I will really appreciate your support and suggestions. Thank You
The sample files can be found using the following link.
When using fopen, all you are doing is opening up the file. You aren't reading in the data. What is returned from fopen is actually a file pointer that gives you access to the contents of the file. It doesn't actually read in the contents itself. You would need to use things like fread or fscanf to read in the content from the text data.
However, I would recommend you use dlmread instead, as this doesn't require a fopen call to open your file. This will open up the file, read the contents and store it into a variable in one function call:
dataX_Real = dlmread('dataX_Real_in.txt');
By doing the above and using your text file, I get 44825 elements. Here are the first 10 entries of your data:
>> format long;
>> dataX_Real(1:10)
ans =
Columns 1 through 4
-0.307224970000000 0.135961950000000 -1.072544100000000 0.114566020000000
Columns 5 through 8
0.499754310000000 -0.340369000000000 0.470609910000000 1.107567700000000
Columns 9 through 10
-0.295783020000000 -0.089266816000000
Seems to match up with what we see in your text file! However, you said you wanted it as a single column. This by default reads the values in on a row basis, so here you can certainly transpose:
dataX_Real = dataX_Real.';
Displaying the first 10 elements, we get:
>> dataX_Real = dataX_Real.';
>> dataX_Real(1:10)
ans =
-0.307224970000000
0.135961950000000
-1.072544100000000
0.114566020000000
0.499754310000000
-0.340369000000000
0.470609910000000
1.107567700000000
-0.295783020000000
-0.089266816000000
I am looking for the hash algorithm that symstore uses to create the directory name. I found this link Microsoft Symbol Server / Local Cache Hash Algorithm that describes the data elements that are used to generate the hash, but it does not go into any detail on how the hash value is calculated. I am interested to see how symstore generates the hash directory and if anyone has any sample code that they can show, that would be great!
symstore.exe calculates hash directory names as follows:
For PDB files, the GUID + Age, are used. Here is a python example:
pdb = pdbparse.parse("some.pdb")
pdb.STREAM_PDB.load()
guid = pdb.STREAM_PDB.GUID
guid_str = "%.8X%.4X%.4X%s" % (guid.Data1, guid.Data2, guid.Data3,
guid.Data4.encode("hex").upper())
symstore_hash = "%s%s" % (guid_str, pdb.STREAM_PDB.Age)
For PE (exe/dll) files, the TimeDateStamp (from IMAGE_FILE_HEADER) and SizeOfImage (from IMAGE_OPTIONAL_HEADER) are used. Here is a python example:
pe = pefile.PE("some.exe")
symstore_hash = "%X%X" % (pe.FILE_HEADER.TimeDateStamp,
pe.OPTIONAL_HEADER.SizeOfImage)
Here is an example python script that prints symstore hash values for PDB and PE files:
https://gist.github.com/lennartblanco/9a70961a5aa66fe49df6
Not sure if you have already reviewed this but it is the U.S. Patent describing the symbol store process. Its pretty dense as you can imagine but it does describe in quite a bit of detail how the symbol store directories are expanded and deleted (specifically in sections 6, 7, 8). Hope this helps or points you in the right direction.
EDIT: Link should work now, sorry for the trouble
I have a text file that looks like this:
Name, Test 1, Test 2, Test 3, Test 4, Test 5
Bob, 86, 83, 86, 80, 23
Alice, 38, 90, 100, 53, 32
Jill, 49, 53, 63, 43, 23.
I am writing a program that given this text file, it will generate a Pearson's correlation coefficient table that looks like this where the entry (x,y) is the correlation between person x and person y:
Name,Bob,Alice,Jill
Bob, 1, 0.567088412588577, 0.899798494392584
Alice, 0.567088412588577, 1, 0.812425393004088
Jill, 0.899798494392584, 0.812425393004088, 1
My program works, except that the data set I am feeding it has 82 columns and, more importantly, 54000 rows. When I run my program right now, it is incredibly slow and I get an out of memory error. Is there a way I can first of all, remove any possibility of an out of memory error and maybe make the program run a little more efficiently? The code is here: code.
Thanks for your help,
Jack
Edit: In case anyone else is trying to do large scale computation, convert your data into hdf5 format. This is what I ended up doing to solve this issue.
You're going to have to do at least 54000^2*82 calculations and comparisons. Of course it's going to take a lot of time. Are you holding everything in memory? That's going to be pretty large too. It will be slower, but it might use less memory if you can keep the users in a database and calculate one user against all the others, then go on to the next and do it against all the others instead of one massive array or hash.
Have a look at Tie::File to deal with the high memory usage of having your input and output files stored in memory.
Have you searched CPAN? My own search yielded another method gsl_stats_correlation for computing Pearsons correlation. This one is in Math::GSL::Statisics. This module binds to the GNU Scientific Library.
gsl_stats_correlation($data1, $stride1, $data2, $stride2, $n) - This function efficiently computes the Pearson correlation coefficient between the array reference $data1 and $data2 which must both be of the same length $n. r = cov(x, y) / (\Hat\sigma_x \Hat\sigma_y) = {1/(n-1) \sum (x_i - \Hat x) (y_i - \Hat y) \over \sqrt{1/(n-1) \sum (x_i - \Hat x)^2} \sqrt{1/(n-1) \sum (y_i - \Hat y)^2} }
You may want to look at PDL:
PDL ("Perl Data Language") gives
standard Perl the ability to compactly
store and speedily manipulate the
large N-dimensional data arrays which
are the bread and butter of scientific
computing
.
Essentially Paul Tomblin has given you the answer: It's a lot of calculation so it will take a long time. It's a lot of data, so it will take a lot of memory.
However, there may be one gotcha: If you use perl 5.10.0, your list assignments at the start of each method may be victims of a subtle performance bug in that version of perl (cf. perlmonks thread).
A couple of minor points:
The printout may actually slow down the program somewhat depending one where it goes.
There is no need to reopen the output file for each line! Just do something like this:
open FILE, ">", "file.txt" or die $!;
print FILE "Name, ", join(", ", 0..$#{$correlations[0]}+1), "\n";
my $rowno = 1;
foreach my $row (#correlations) {
print FILE "$rowno, " . join(", ", #$row) . "\n";
$rowno++;
}
close FILE;
Finally, while I do use Perl whenever I can, with a program and data set such as you describe, it might be the simplest route to simply use C++ with its iostreams (which make parsing easy enough) for this task.
Note that all of this is just minor optimization. There's no algorithmic gain.
I don't know enough about what you are trying to do to give good advice about implementation, but you might look at Statistics::LSNoHistory, it claims to have a method pearson_r that returns Pearson's r correlation coefficient.
Further to the comment above about PDL, here is the code how to calculate the correlation table even for very big datasets quite efficiently:
use PDL::Stats; # this useful module can be downloaded from CPAN
my $data = random(82, 5400); # your data should replace this
my $table = $data->corr_table(); # that's all, really
You might need to set $PDL::BIGPDL = 1; in the header of your script and make sure you run this on a machine with A LOT of memory. The computation itself is reasonably fast, a 82 x 5400 table took only a few seconds on my laptop.