iData/corrcoef: use intersect prior to corrcoef

Docs: Few notes on corrcoef and Load/Save

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

Docs/Loaders.html

@@ -168,10 +168,11 @@ <h3><a class="mozTocH3" name="mozTocId485865"></a>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. <br>
+(words) recognition in file headers. <br>
 A compact list of all supported formats is shown with <br>
 <pre style="margin-left: 40px;">&gt;&gt; a = <span style="color: rgb(51, 102, 255);">iLoad</span>(<span style="color: rgb(204, 51, 204);">'formats'</span>);</pre>
 
+Some of these formats can be written back, providing a vast conversion capability (see the <a href="Save.html">Save</a> page).<br>
 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).<br>
@@ -197,7 +198,7 @@ <h4><a class="mozTocH4" name="mozTocId876478"></a>Legacy data formats (text, Net
       <td style="vertical-align: top; background-color: rgb(255, 204, 204); font-weight: bold; font-style: italic;">Description<br>
       </td>
       <td style="vertical-align: top; font-weight: bold;">iData/saveas<br>
-Write<br>
+<a href="Save.html">Write</a><br>
       </td>
     </tr>
     <tr>

Docs/Math.html

@@ -811,7 +811,19 @@ <h3><a class="mozTocH3" name="mozTocId660745"></a>Binary operators</h3>
       <td style="vertical-align: top;">interpolation (linear is
 default, see <a href="#mozTocId991507">below)</a><br>
       </td>
-    </tr>
+    </tr><tr>
+  <td style="vertical-align: top;"><span style="font-weight: bold;">corrcoef</span><br>
+  </td>
+  <td style="vertical-align: top;">cov(s1,s2)/&#963;(s1)&#963;(s2) in [-1:1]<br>
+  </td>
+  <td style="vertical-align: top;"><br>
+  </td>
+  <td style="vertical-align: top;"><br>
+  </td>
+  <td style="vertical-align: top;"><a href="http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient">Pearson correlation coefficient</a> <br>
+  </td>
+</tr>
+
   </tbody>
 </table>
 <br>
@@ -917,6 +929,8 @@ <h4><a class="mozTocH4" name="mozTocId121035"></a>Convolution/correlation</h4>
 Similarly, the <span style="font-weight: bold;">xcorr</span> operator
 computes the <a href="http://en.wikipedia.org/wiki/Cross-correlation">cross correlation</a> of two signals. The auto-correlation is simply
 <span style="font-style: italic;">xcorr(a)</span>.<br>
+<br>
+Last, the <span style="font-weight: bold;">corrcoef</span> method returns the <a href="http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient">Pearson product-moment correlation coefficient</a>, 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).<br>
 <br><span style="color: rgb(255, 0, 0);">
 Warning: </span>The accuracy of the <span style="font-style: italic;">conv</span> and <span style="font-style: italic;">xcorr</span>
 operators depends on the axis sampling. A coarse axis sampling (that is

Docs/Methods.html

@@ -736,7 +736,7 @@ <h3><a class="mozTocH3" name="mozTocId179983"></a><span style="font-weight: bold
 <li><a href="matlab:doc iData/fits"><span style="font-weight: bold;">fits: </span></a>finds best model
 parameters to fit the <span style="font-style: italic;">Signal. </span>New
 fit functions/models can be created with the <a href="Models.html#mozTocId210092">iFunc/Model Builder</a> tool.</li>
-<li><a href="matlab:doc iData/corrcoef"><b>corrcoef: </b></a>compute the correlation between an object and something else.<span style="font-style: italic;"> <br>
+<li><a href="matlab:doc iData/corrcoef"><b>corrcoef: </b></a>compute the correlation (Pearson) between an object and something else.<span style="font-style: italic;"> <br>
     </span></li>
 
 </ul>
@@ -1002,4 +1002,5 @@ <h3><a class="mozTocH3" name="mozTocId341680"></a><span style="font-weight: bold
 
 
 
+
 </body></html>

Docs/Save.html

@@ -155,7 +155,7 @@ <h4><a class="mozTocH4" name="mozTocId593918"></a>text based lossless
 be compressed afterwards with e.g. ZIP.<br>
 <br>
 The last column indicates if the generated format for export can be
-re-used afterwards and re-imported with iFit.<br>
+re-used afterwards and re-imported with iFit (see the <a href="Loaders.html">Loaders</a> and <a href="Load.html">Load</a> page).<br>
 <span style="font-weight: bold;"><br>
 </span>
 <table style="text-align: left; width: 100%;" border="1" cellpadding="2" cellspacing="2">
@@ -277,7 +277,7 @@ <h4><a class="mozTocH4" name="mozTocId238422"></a>binary lossless
 workspace
 binary
 file is compact and fast to read/write. It carries the whole object
-information. Such files require Matlab (or <a href="http://www.octave.org">Octave</a>) to be installed prior to
+information. Such files require Matlab (or <a href="iFit.html">iFit standalone</a> or <a href="http://www.octave.org">Octave</a>) to be installed prior to
 importation. <span style="font-style: italic;">This file contains serialized data, to be re-imported into an iData object.</span><span style="font-weight: bold;"> </span></td>
       <td style="vertical-align: top;">Yes<br>
 </td>

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')
@@ -41,14 +41,19 @@
   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
 if isa(a, 'iData')
   a = getaxis(a, 0);
 end
 
-if ~isnumeric(a) || ~isnumeric(b)
+if ~isnumeric(a) || ~isnumeric(b) || numel(a) ~= numel(b)
   c = [];
   return
 end