new first page of documentation

dokato · Aug 13, 2015 · 8cfe7b3 · 8cfe7b3
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diff --git a/doc/html/_sources/index.txt b/doc/html/_sources/index.txt
@@ -11,9 +11,12 @@ You can find it and download from `GitHub
 <https://github.com/dokato/connectivipy>`_.
 
 *Connectivity estimation is one of the most important problem in EEG/MEG 
-studies. Many estimators work correctly in different applications and
-this is python tool which allows to have them in one place. ConnectiviPy 
-is light and  extendable module open for many data formats.*
+studies. Many estimators work correctly in different applications, so it's
+convenient to have them all in one tool. ConnectiviPy 
+is light and  extendable python module open for many data formats. In
+opposite to other packages it allows you to work with all types of data,
+not only biomedical. Calculations base on numpy and scipy what provides
+good efficiency.*
 
 
 Contents:

diff --git a/doc/html/_static/connpy2.jpg b/doc/html/_static/connpy2.jpg
diff --git a/doc/html/_static/connpy_org.png b/doc/html/_static/connpy_org.png
diff --git a/doc/html/conn.html b/doc/html/conn.html
@@ -67,7 +67,7 @@
 <em>calculate</em> method and <em>values_range</em> attribute.</p>
 <dl class="method">
 <dt id="conn.Coherency.calculate">
-<code class="descname">calculate</code><span class="sig-paren">(</span><em>data</em>, <em>cnfft=None</em>, <em>cno=None</em>, <em>window=&lt;function hanning at 0x0000000003A335F8&gt;</em>, <em>im=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/conn.html#Coherency.calculate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#conn.Coherency.calculate" title="Permalink to this definition">¶</a></dt>
+<code class="descname">calculate</code><span class="sig-paren">(</span><em>data</em>, <em>cnfft=None</em>, <em>cno=None</em>, <em>window=&lt;function hanning at 0x00000000039C05F8&gt;</em>, <em>im=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/conn.html#Coherency.calculate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#conn.Coherency.calculate" title="Permalink to this definition">¶</a></dt>
 <dd><p>Coherency calculation using FFT mehtod.
 Args:</p>
 <blockquote>
@@ -217,7 +217,7 @@
 <em>calculate</em> method.</p>
 <dl class="method">
 <dt id="conn.PSI.calculate">
-<code class="descname">calculate</code><span class="sig-paren">(</span><em>data</em>, <em>band_width=4</em>, <em>psinfft=None</em>, <em>psino=0</em>, <em>window=&lt;function hanning at 0x0000000003A335F8&gt;</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/conn.html#PSI.calculate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#conn.PSI.calculate" title="Permalink to this definition">¶</a></dt>
+<code class="descname">calculate</code><span class="sig-paren">(</span><em>data</em>, <em>band_width=4</em>, <em>psinfft=None</em>, <em>psino=0</em>, <em>window=&lt;function hanning at 0x00000000039C05F8&gt;</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/conn.html#PSI.calculate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#conn.PSI.calculate" title="Permalink to this definition">¶</a></dt>
 <dd><p>Phase Slope Index calculation using FFT mehtod.
 Args:</p>
 <blockquote>

diff --git a/doc/html/index.html b/doc/html/index.html
@@ -59,9 +59,12 @@ <h1>ConnectiviPy documentation<a class="headerlink" href="#connectivipy-document
 <p>Python connectivity module. It is a part of GSOC 2015 project.</p>
 <p>You can find it and download from <a class="reference external" href="https://github.com/dokato/connectivipy">GitHub</a>.</p>
 <p><em>Connectivity estimation is one of the most important problem in EEG/MEG
-studies. Many estimators work correctly in different applications and
-this is python tool which allows to have them in one place. ConnectiviPy
-is light and  extendable module open for many data formats.</em></p>
+studies. Many estimators work correctly in different applications, so it&#8217;s
+convenient to have them all in one tool. ConnectiviPy
+is light and  extendable python module open for many data formats. In
+opposite to other packages it allows you to work with all types of data,
+not only biomedical. Calculations base on numpy and scipy what provides
+good efficiency.</em></p>
 <div class="section" id="contents">
 <h2>Contents:<a class="headerlink" href="#contents" title="Permalink to this headline">¶</a></h2>
 <div class="toctree-wrapper compound">

diff --git a/doc/html/objects.inv b/doc/html/objects.inv
diff --git a/doc/html/searchindex.js b/doc/html/searchindex.js
diff --git a/doc/index.rst b/doc/index.rst
@@ -11,9 +11,12 @@ You can find it and download from `GitHub
 <https://github.com/dokato/connectivipy>`_.
 
 *Connectivity estimation is one of the most important problem in EEG/MEG 
-studies. Many estimators work correctly in different applications and
-this is python tool which allows to have them in one place. ConnectiviPy 
-is light and  extendable module open for many data formats.*
+studies. Many estimators work correctly in different applications, so it's
+convenient to have them all in one tool. ConnectiviPy 
+is light and  extendable python module open for many data formats. In
+opposite to other packages it allows you to work with all types of data,
+not only biomedical. Calculations base on numpy and scipy what provides
+good efficiency.*
 
 
 Contents: