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i.gensigset manual: explain 'Unreliable clustering' warning; HTML cosmetics

git-svn-id: https://svn.osgeo.org/grass/grass/branches/releasebranch_7_0@60960 15284696-431f-4ddb-bdfa-cd5b030d7da7
Markus Neteler 11 years ago
parent
commit
9793ad03e5
1 changed files with 37 additions and 42 deletions
  1. 37 42
      imagery/i.gensigset/i.gensigset.html

+ 37 - 42
imagery/i.gensigset/i.gensigset.html

@@ -2,7 +2,6 @@
 
 
 <em>i.gensigset</em>
 <em>i.gensigset</em>
 is a non-interactive method for generating input into
 is a non-interactive method for generating input into
-
 <em><a href="i.smap.html">i.smap</a>.</em>
 <em><a href="i.smap.html">i.smap</a>.</em>
 
 
 It is used as the first pass in the a two-pass
 It is used as the first pass in the a two-pass
@@ -12,7 +11,6 @@ regions already classified.  <em>i.gensigset</em> will then
 extract spectral signatures from an image based on the
 extract spectral signatures from an image based on the
 classification of the pixels in the training map and make
 classification of the pixels in the training map and make
 these signatures available to
 these signatures available to
-
 <em><a href="i.smap.html">i.smap</a>.</em>
 <em><a href="i.smap.html">i.smap</a>.</em>
 
 
 
 
@@ -31,7 +29,6 @@ final classified map.
 
 
 <dd>ground truth training map
 <dd>ground truth training map
 
 
-
 <p>
 <p>
 This raster layer, supplied as input by the user, has some
 This raster layer, supplied as input by the user, has some
 of its pixels already classified, and the rest (probably
 of its pixels already classified, and the rest (probably
@@ -55,7 +52,6 @@ to define the areas
 representative
 representative
 of the classes in the image.
 of the classes in the image.
 
 
-
 <p>
 <p>
 At present, there is no fully-interactive tool specifically
 At present, there is no fully-interactive tool specifically
 designed for producing this layer.
 designed for producing this layer.
@@ -107,7 +103,6 @@ selected.
 <dd>maximum number of sub-signatures in any class
 <dd>maximum number of sub-signatures in any class
 
 
 <br>
 <br>
-
 default: 5
 default: 5
 
 
 <p>
 <p>
@@ -119,7 +114,6 @@ starts with a maximum number of subclasses and reduces this
 number to a minimal number of subclasses which are
 number to a minimal number of subclasses which are
 spectrally distinct.  The user has the option to set this
 spectrally distinct.  The user has the option to set this
 starting value with this option.
 starting value with this option.
-
 </dl>
 </dl>
 
 
 
 
@@ -188,59 +182,60 @@ and covariance of the subclasses are computed using the
 expectation maximization (EM) algorithm 
 expectation maximization (EM) algorithm 
 [<a href="#dempster77">2</a>,<a href="#redner84">3</a>].  
 [<a href="#dempster77">2</a>,<a href="#redner84">3</a>].  
 
 
+<h2>WARNINGS</h2>
 
 
-<h2>REFERENCES</h2>
+If warnings like this occur, reducing the remaining classes to 0:
 
 
-<ol>
+<div class="code"><pre>
+...
+WARNING: Removed a singular subsignature number 1 (4 remain)
+WARNING: Removed a singular subsignature number 1 (3 remain)
+WARNING: Removed a singular subsignature number 1 (2 remain)
+WARNING: Removed a singular subsignature number 1 (1 remain)
+WARNING: Unreliable clustering. Try a smaller initial number of clusters
+WARNING: Removed a singular subsignature number 1 (-1 remain)
+WARNING: Unreliable clustering. Try a smaller initial number of clusters
+Number of subclasses is 0
+</pre></div>
+
+then the user should check for:
+<ul>
+<li>the range of the input data should be between 0 and 100 or 255 but not
+  between 0.0 and 1.0 (<em>r.info</em> and <em>r.univar</em> show the range)</li>
+<li>the training areas need to contain a sufficient amount of pixels</li>
+</ul>
 
 
-<li><A NAME="rissanen83">J. Rissanen,</a>
-"A Universal Prior for Integers and Estimation by Minimum
-Description Length,"
-<em>Annals of Statistics,</em>
-vol. 11, no. 2, pp. 417-431, 1983.
 
 
+<h2>REFERENCES</h2>
 
 
+<ul>
+<li><A NAME="rissanen83">J. Rissanen,</a>
+"A Universal Prior for Integers and Estimation by Minimum Description Length,"
+<em>Annals of Statistics,</em> vol. 11, no. 2, pp. 417-431, 1983.
 <li><A NAME="dempster77">A. Dempster, N. Laird and D. Rubin,</a>
 <li><A NAME="dempster77">A. Dempster, N. Laird and D. Rubin,</a>
 "Maximum Likelihood from Incomplete Data via the EM Algorithm,"
 "Maximum Likelihood from Incomplete Data via the EM Algorithm,"
-<em>J. Roy. Statist. Soc. B,</em>
-vol. 39, no. 1, pp. 1-38, 1977.
-
+<em>J. Roy. Statist. Soc. B,</em> vol. 39, no. 1, pp. 1-38, 1977.
 <li><A NAME="redner84">E. Redner and H. Walker,</a>
 <li><A NAME="redner84">E. Redner and H. Walker,</a>
 "Mixture Densities, Maximum Likelihood and the EM Algorithm,"
 "Mixture Densities, Maximum Likelihood and the EM Algorithm,"
-<em>SIAM Review,</em>
-vol. 26, no. 2, April 1984.
-
-</ol>
+<em>SIAM Review,</em> vol. 26, no. 2, April 1984.
+</ul>
 
 
 <h2>SEE ALSO</h2>
 <h2>SEE ALSO</h2>
 
 
-<em><a href="i.group.html">i.group</a></em>
-for creating groups and subgroups
-
-
-<p>
-<em><a href="wxGUI.vdigit.html">wxGUI vector digitizer</a></em>
-and
-<em><a href="r.digit.html">r.digit</a></em>
-for interactively creating the training map.
-
-
-<p>
-<em><a href="i.smap.html">i.smap</a></em>
-for creating a final classification layer from the signatures
-generated by <em>i.gensigset.</em>
-
+<em>
+<a href="i.group.html">i.group</a>,
+<a href="i.smap.html">i.smap</a>,
+<a href="r.info.html">r.info</a>,
+<a href="r.univar.html">r.univar</a>,
+<a href="wxGUI.vdigit.html">wxGUI vector digitizer</a>
+</em>
 
 
 <h2>AUTHORS</h2>
 <h2>AUTHORS</h2>
 
 
 Charles Bouman, 
 Charles Bouman, 
-School of 
-Electrical Engineering, 
-Purdue University
+School of Electrical Engineering, Purdue University
 <br>
 <br>
-
 Michael Shapiro,
 Michael Shapiro,
-U.S.Army Construction Engineering 
-Research Laboratory
+U.S.Army Construction Engineering Research Laboratory
 
 
 <p><i>Last changed: $Date$</i>
 <p><i>Last changed: $Date$</i>