diff --git a/Applications/standalone/deb/control b/Applications/standalone/deb/control index 4d1b9804..b0e88a15 100644 --- a/Applications/standalone/deb/control +++ b/Applications/standalone/deb/control @@ -3,6 +3,7 @@ Version: @IFIT_VERSION@ Architecture: arch Installed-Size: 48100 Depends: bash +Recommends: mcrinstaller Section: Science Priority: optional Homepage: http://ifit.mccode.org diff --git a/Docs/Loaders.html b/Docs/Loaders.html index 9ef54528..361537df 100644 --- a/Docs/Loaders.html +++ b/Docs/Loaders.html @@ -168,10 +168,11 @@

Supported data formats (defaul The Loaders sub-library comes with a large number of predefined import filters. These are tested one after the other, based on an initial filter selection using the file name extension and optionally pattern -(wods) recognition in file headers.
+(words) recognition in file headers.
A compact list of all supported formats is shown with 
>> a = iLoad('formats');
+Some of these formats can be written back, providing a vast conversion capability (see the Save page).
The filters have been divided into two categories: those that directly use formats natively known by Matlab, and those that are more specific to neutron and X-ray communities (or other research areas).
@@ -197,7 +198,7 @@

Legacy data formats (text, Net Description
iData/saveas
-Write
+Write
diff --git a/Docs/Math.html b/Docs/Math.html index e91e4629..e1819b45 100644 --- a/Docs/Math.html +++ b/Docs/Math.html @@ -811,7 +811,19 @@

Binary operators

interpolation (linear is default, see below)
- + + corrcoef
+ + cov(s1,s2)/σ(s1)σ(s2) in [-1:1]
+ +
+ +
+ + Pearson correlation coefficient
+ + +
@@ -917,6 +929,8 @@

Convolution/correlation

Similarly, the xcorr operator computes the cross correlation of two signals. The auto-correlation is simply xcorr(a).
+
+Last, the corrcoef method returns the Pearson product-moment correlation coefficient, which measures the similarity between two data sets. It returns a measure of the similarity between data sets (1=equal, 0=non correlated, -1=anti-correlated).

Warning: The accuracy of the conv and xcorr operators depends on the axis sampling. A coarse axis sampling (that is diff --git a/Docs/Methods.html b/Docs/Methods.html index 82f5038d..fd5a8134 100644 --- a/Docs/Methods.html +++ b/Docs/Methods.html @@ -736,7 +736,7 @@

fits: finds best model parameters to fit the Signal. New fit functions/models can be created with the iFunc/Model Builder tool. -
  • corrcoef: compute the correlation between an object and something else.
    +
  • corrcoef: compute the correlation (Pearson) between an object and something else.
    • @@ -1002,4 +1002,5 @@

    text based lossless be compressed afterwards with e.g. ZIP.

    The last column indicates if the generated format for export can be -re-used afterwards and re-imported with iFit.
    +re-used afterwards and re-imported with iFit (see the Loaders and Load page).

     @@ -277,7 +277,7 @@

    binary lossless workspace binary file is compact and fast to read/write. It carries the whole object -information. Such files require Matlab (or Octave) to be installed prior to +information. Such files require Matlab (or iFit standalone or Octave) to be installed prior to importation. This file contains serialized data, to be re-imported into an iData object.

    diff --git a/Objects/@iData/corrcoef.m b/Objects/@iData/corrcoef.m index 56dc19dd..565a58ec 100644 --- a/Objects/@iData/corrcoef.m +++ b/Objects/@iData/corrcoef.m @@ -10,7 +10,7 @@ % ex: b=corrcoef(a); c=corrcoef(a, gauss); % % Version: $Revision$ -% See also iData, iData/mean, iData/fits +% See also corrcoef, iData, iData/mean, iData/fits % either 'a' or 'b' is an iData if nargin > 1 && isa(b, 'iData') @@ -41,6 +41,11 @@ b = feval(b, NaN, a); end +% find intersection +if isa(a, 'iData') && isa(b, 'iData') + [a,b] = intersect(a,b); % perform operation on intersection +end +% get the Signal of the two objects if isa(b, 'iData') b = getaxis(b, 0); end @@ -48,7 +53,7 @@ a = getaxis(a, 0); end -if ~isnumeric(a) || ~isnumeric(b) +if ~isnumeric(a) || ~isnumeric(b) || numel(a) ~= numel(b) c = []; return end
    Yes