added basic docs generated with epydocs, and stripped downgh-pages

5 files changed, 2218 insertions, 0 deletions

diff --git a/b/lib/feast.py b/b/lib/feast.py
new file mode 100644
index 0000000..0d2fee6
--- /dev/null
+++ b/b/lib/feast.py
@@ -0,0 +1,412 @@
+import numpy as np
+from ctypes import * 
+
+
+'''
+  The FEAST module provides an interface between the C-library
+  for feature selection to Python. 
+
+  References: 
+  1) G. Brown, A. Pocock, M.-J. Zhao, and M. Lujan, "Conditional
+      likelihood maximization: A unifying framework for information
+      theoretic feature selection," Journal of Machine Learning 
+      Research, vol. 13, pp. 27-66, 2012.
+
+
+  __author__ = "Calvin Morrison"
+  __copyright__ = "Copyright 2013, EESI Laboratory"
+  __credits__ = ["Calvin Morrison", "Gregory Ditzler"]
+  __license__ = "GPL"
+  __version__ = "0.1.0"
+  __maintainer__ = "Calvin Morrison"
+  __email__ = "mutantturkey@gmail.com"
+  __status__ = "Release"
+'''
+
+# I listed the function definitions in alphabetical order. Lets
+# keep this up. 
+
+
+try:
+  libFSToolbox = CDLL("libFSToolbox.so"); 
+except:
+  print "Error: could not find libFSToolbox"
+  exit()
+
+
+def BetaGamma(data, labels, n_select, beta=1.0, gamma=1.0):
+  '''
+    BetaGamma(data, labels, n_select, beta=1.0, gamma=1.0)
+
+    This algotihm implements conditional mutual information 
+    feature select, such that beta and gamma control the 
+    weight attached to the redundant mutual and conditional
+    mutual information, respectively. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+      :beta - penalty attacted to I(X_j;X_k) 
+      :gamma - positive weight attached to the conditional
+        redundancy term I(X_k;X_j|Y)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+  c_beta = c_double(beta)
+  c_gamma = c_double(gamma)
+
+  libFSToolbox.BetaGamma.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.BetaGamma(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double)),
+                   c_beta,
+                   c_gamma
+                   )
+
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+def CMIM(data, labels, n_select):
+  '''
+    CMIM(data, labels, n_select)
+
+    This function implements the conditional mutual information
+    maximization feature selection algorithm. Note that this 
+    implementation does not allow for the weighting of the 
+    redundancy terms that BetaGamma will allow you to do. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.CMIM.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.CMIM(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+def CondMI(data, labels, n_select):
+  '''
+    CondMI(data, labels, n_select)
+
+    This function implements the conditional mutual information
+    maximization feature selection algorithm. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.CondMI.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.CondMI(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+
+
+
+def DISR(data, labels, n_select):
+  '''
+    DISR(data, labels, n_select)
+
+    This function implements the double input symmetrical relevance
+    feature selection algorithm. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.DISR.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.DISR(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+
+def ICAP(data, labels, n_select):
+  '''
+    ICAP(data, labels, n_select)
+
+    This function implements the interaction capping feature 
+    selection algorithm. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.ICAP.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.ICAP(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+
+
+def JMI(data, labels, n_select):
+  '''
+    JMI(data, labels, n_select)
+
+    This function implements the joint mutual information feature
+    selection algorithm. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.JMI.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.JMI(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+def mRMR(data, labels, n_select):
+  '''
+    mRMR(data, labels, n_select)
+
+    This funciton implements the max-relevance min-redundancy feature
+    selection algorithm. 
+
+    Input 
+      :data - data in a Numpy array such that len(data) = 
+        n_observations, and len(data.transpose()) = n_features
+        (REQUIRED)
+      :labels - labels represented in a numpy list with 
+        n_observations as the number of elements. That is 
+        len(labels) = len(data) = n_observations.
+        (REQUIRED)
+      :n_select - number of features to select. (REQUIRED)
+    Output 
+      :selected_features - returns a list containing the features
+        in the order they were selected. 
+  '''
+
+  # python values
+  n_observations, n_features = data.shape
+  output = np.zeros(n_select)
+
+  # cast as C types
+  c_n_observations = c_int(n_observations)
+  c_n_select = c_int(n_select)
+  c_n_features = c_int(n_features)
+
+  libFSToolbox.mRMR_D.restype = POINTER(c_double * n_select)
+  features = libFSToolbox.mRMR_D(c_n_select,
+                   c_n_observations,
+                   c_n_features, 
+                   data.ctypes.data_as(POINTER(c_double)),
+                   labels.ctypes.data_as(POINTER(c_double)),
+                   output.ctypes.data_as(POINTER(c_double))
+                   )
+
+  
+  # turn our output into a list
+  selected_features = []
+  for i in features.contents:
+    # recall that feast was implemented with Matlab in mind, so the 
+    # authors assumed the indexing started a one; however, in Python 
+    # the indexing starts at zero. 
+    selected_features.append(i - 1)
+
+  return selected_features
+
+
+
+
+
diff --git a/crarr.png b/crarr.png
new file mode 100644
index 0000000..26b43c5
--- /dev/null
+++ b/crarr.png
diff --git a/epydoc.css b/epydoc.css
new file mode 100644
index 0000000..86d4170
--- /dev/null
+++ b/epydoc.css
@@ -0,0 +1,322 @@
+
+
+/* Epydoc CSS Stylesheet
+ *
+ * This stylesheet can be used to customize the appearance of epydoc's
+ * HTML output.
+ *
+ */
+
+/* Default Colors & Styles
+ *   - Set the default foreground & background color with 'body'; and 
+ *     link colors with 'a:link' and 'a:visited'.
+ *   - Use bold for decision list terms.
+ *   - The heading styles defined here are used for headings *within*
+ *     docstring descriptions.  All headings used by epydoc itself use
+ *     either class='epydoc' or class='toc' (CSS styles for both
+ *     defined below).
+ */
+body                        { background: #ffffff; color: #000000; }
+p                           { margin-top: 0.5em; margin-bottom: 0.5em; }
+a:link                      { color: #0000ff; }
+a:visited                   { color: #204080; }
+dt                          { font-weight: bold; }
+h1                          { font-size: +140%; font-style: italic;
+                              font-weight: bold; }
+h2                          { font-size: +125%; font-style: italic;
+                              font-weight: bold; }
+h3                          { font-size: +110%; font-style: italic;
+                              font-weight: normal; }
+code                        { font-size: 100%; }
+/* N.B.: class, not pseudoclass */
+a.link                      { font-family: monospace; }
+ 
+/* Page Header & Footer
+ *   - The standard page header consists of a navigation bar (with
+ *     pointers to standard pages such as 'home' and 'trees'); a
+ *     breadcrumbs list, which can be used to navigate to containing
+ *     classes or modules; options links, to show/hide private
+ *     variables and to show/hide frames; and a page title (using
+ *     <h1>).  The page title may be followed by a link to the
+ *     corresponding source code (using 'span.codelink').
+ *   - The footer consists of a navigation bar, a timestamp, and a
+ *     pointer to epydoc's homepage.
+ */ 
+h1.epydoc                   { margin: 0; font-size: +140%; font-weight: bold; }
+h2.epydoc                   { font-size: +130%; font-weight: bold; }
+h3.epydoc                   { font-size: +115%; font-weight: bold;
+                              margin-top: 0.2em; }
+td h3.epydoc                { font-size: +115%; font-weight: bold;
+                              margin-bottom: 0; }
+table.navbar                { background: #a0c0ff; color: #000000;
+                              border: 2px groove #c0d0d0; }
+table.navbar table          { color: #000000; }
+th.navbar-select            { background: #70b0ff;
+                              color: #000000; } 
+table.navbar a              { text-decoration: none; }  
+table.navbar a:link         { color: #0000ff; }
+table.navbar a:visited      { color: #204080; }
+span.breadcrumbs            { font-size: 85%; font-weight: bold; }
+span.options                { font-size: 70%; }
+span.codelink               { font-size: 85%; }
+td.footer                   { font-size: 85%; }
+
+/* Table Headers
+ *   - Each summary table and details section begins with a 'header'
+ *     row.  This row contains a section title (marked by
+ *     'span.table-header') as well as a show/hide private link
+ *     (marked by 'span.options', defined above).
+ *   - Summary tables that contain user-defined groups mark those
+ *     groups using 'group header' rows.
+ */
+td.table-header             { background: #70b0ff; color: #000000;
+                              border: 1px solid #608090; }
+td.table-header table       { color: #000000; }
+td.table-header table a:link      { color: #0000ff; }
+td.table-header table a:visited   { color: #204080; }
+span.table-header           { font-size: 120%; font-weight: bold; }
+th.group-header             { background: #c0e0f8; color: #000000;
+                              text-align: left; font-style: italic; 
+                              font-size: 115%; 
+                              border: 1px solid #608090; }
+
+/* Summary Tables (functions, variables, etc)
+ *   - Each object is described by a single row of the table with
+ *     two cells.  The left cell gives the object's type, and is
+ *     marked with 'code.summary-type'.  The right cell gives the
+ *     object's name and a summary description.
+ *   - CSS styles for the table's header and group headers are
+ *     defined above, under 'Table Headers'
+ */
+table.summary               { border-collapse: collapse;
+                              background: #e8f0f8; color: #000000;
+                              border: 1px solid #608090;
+                              margin-bottom: 0.5em; }
+td.summary                  { border: 1px solid #608090; }
+code.summary-type           { font-size: 85%; }
+table.summary a:link        { color: #0000ff; }
+table.summary a:visited     { color: #204080; }
+
+
+/* Details Tables (functions, variables, etc)
+ *   - Each object is described in its own div.
+ *   - A single-row summary table w/ table-header is used as
+ *     a header for each details section (CSS style for table-header
+ *     is defined above, under 'Table Headers').
+ */
+table.details               { border-collapse: collapse;
+                              background: #e8f0f8; color: #000000;
+                              border: 1px solid #608090;
+                              margin: .2em 0 0 0; }
+table.details table         { color: #000000; }
+table.details a:link        { color: #0000ff; }
+table.details a:visited     { color: #204080; }
+
+/* Fields */
+dl.fields                   { margin-left: 2em; margin-top: 1em;
+                              margin-bottom: 1em; }
+dl.fields dd ul             { margin-left: 0em; padding-left: 0em; }
+dl.fields dd ul li ul       { margin-left: 2em; padding-left: 0em; }
+div.fields                  { margin-left: 2em; }
+div.fields p                { margin-bottom: 0.5em; }
+
+/* Index tables (identifier index, term index, etc)
+ *   - link-index is used for indices containing lists of links
+ *     (namely, the identifier index & term index).
+ *   - index-where is used in link indices for the text indicating
+ *     the container/source for each link.
+ *   - metadata-index is used for indices containing metadata
+ *     extracted from fields (namely, the bug index & todo index).
+ */
+table.link-index            { border-collapse: collapse;
+                              background: #e8f0f8; color: #000000;
+                              border: 1px solid #608090; }
+td.link-index               { border-width: 0px; }
+table.link-index a:link     { color: #0000ff; }
+table.link-index a:visited  { color: #204080; }
+span.index-where            { font-size: 70%; }
+table.metadata-index        { border-collapse: collapse;
+                              background: #e8f0f8; color: #000000;
+                              border: 1px solid #608090; 
+                              margin: .2em 0 0 0; }
+td.metadata-index           { border-width: 1px; border-style: solid; }
+table.metadata-index a:link { color: #0000ff; }
+table.metadata-index a:visited  { color: #204080; }
+
+/* Function signatures
+ *   - sig* is used for the signature in the details section.
+ *   - .summary-sig* is used for the signature in the summary 
+ *     table, and when listing property accessor functions.
+ * */
+.sig-name                   { color: #006080; }
+.sig-arg                    { color: #008060; }
+.sig-default                { color: #602000; }
+.summary-sig                { font-family: monospace; }
+.summary-sig-name           { color: #006080; font-weight: bold; }
+table.summary a.summary-sig-name:link
+                            { color: #006080; font-weight: bold; }
+table.summary a.summary-sig-name:visited
+                            { color: #006080; font-weight: bold; }
+.summary-sig-arg            { color: #006040; }
+.summary-sig-default        { color: #501800; }
+
+/* Subclass list
+ */
+ul.subclass-list { display: inline; }
+ul.subclass-list li { display: inline; }
+
+/* To render variables, classes etc. like functions */
+table.summary .summary-name { color: #006080; font-weight: bold;
+                              font-family: monospace; }
+table.summary
+     a.summary-name:link    { color: #006080; font-weight: bold;
+                              font-family: monospace; }
+table.summary
+    a.summary-name:visited  { color: #006080; font-weight: bold;
+                              font-family: monospace; }
+
+/* Variable values
+ *   - In the 'variable details' sections, each varaible's value is
+ *     listed in a 'pre.variable' box.  The width of this box is
+ *     restricted to 80 chars; if the value's repr is longer than
+ *     this it will be wrapped, using a backslash marked with
+ *     class 'variable-linewrap'.  If the value's repr is longer
+ *     than 3 lines, the rest will be ellided; and an ellipsis
+ *     marker ('...' marked with 'variable-ellipsis') will be used.
+ *   - If the value is a string, its quote marks will be marked
+ *     with 'variable-quote'.
+ *   - If the variable is a regexp, it is syntax-highlighted using
+ *     the re* CSS classes.
+ */
+pre.variable                { padding: .5em; margin: 0;
+                              background: #dce4ec; color: #000000;
+                              border: 1px solid #708890; }
+.variable-linewrap          { color: #604000; font-weight: bold; }
+.variable-ellipsis          { color: #604000; font-weight: bold; }
+.variable-quote             { color: #604000; font-weight: bold; }
+.variable-group             { color: #008000; font-weight: bold; }
+.variable-op                { color: #604000; font-weight: bold; }
+.variable-string            { color: #006030; }
+.variable-unknown           { color: #a00000; font-weight: bold; }
+.re                         { color: #000000; }
+.re-char                    { color: #006030; }
+.re-op                      { color: #600000; }
+.re-group                   { color: #003060; }
+.re-ref                     { color: #404040; }
+
+/* Base tree
+ *   - Used by class pages to display the base class hierarchy.
+ */
+pre.base-tree               { font-size: 80%; margin: 0; }
+
+/* Frames-based table of contents headers
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+ */
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+                              margin: 0.5em 0 0 -0.3em; }
+
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+ *   - doctest examples are displayed in a 'pre.py-doctest' block.
+ *     If the example is in a details table entry, then it will use
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+ *   - Source code listings are displayed in a 'pre.py-src' block.
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+ *     The expand/collapse block toggle button is displayed with
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+ *     modify the font size of the text.)
+ *   - If a source code page is opened with an anchor, then the
+ *     corresponding code block will be highlighted.  The code
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+ *     etc.)
+ */
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+ *     clickable).
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+img.graph-with-title        { border: 1px solid #000000; }
+span.graph-title            { font-weight: bold; }
+span.graph-caption          { }
+
+/* General-purpose classes
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+ *     is not indented, but whose subsequent lines are.
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+ *     from lists).  The 'nomargin' class is used to remove both the
+ *     top and bottom margin (but not the left or right margin --
+ *     for lists, that would cause the bullets to disappear.)
+ */
+p.indent-wrapped-lines      { padding: 0 0 0 7em; text-indent: -7em; 
+                              margin: 0; }
+.nomargin-top               { margin-top: 0; }
+.nomargin                   { margin-top: 0; margin-bottom: 0; }
+
+/* HTML Log */
+div.log-block               { padding: 0; margin: .5em 0 .5em 0;
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diff --git a/feast-module.html b/feast-module.html
new file mode 100644
index 0000000..557d352
--- /dev/null
+++ b/feast-module.html
@@ -0,0 +1,864 @@
+<?xml version="1.0" encoding="ascii"?>
+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
+          "DTD/xhtml1-transitional.dtd">
+<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
+<head>
+  <title>feast</title>
+  <link rel="stylesheet" href="epydoc.css" type="text/css" />
+  <script type="text/javascript" src="epydoc.js"></script>
+</head>
+
+<body bgcolor="white" text="black" link="blue" vlink="#204080"
+      alink="#204080">
+<!-- ==================== NAVIGATION BAR ==================== -->
+<table class="navbar" border="0" width="100%" cellpadding="0"
+       bgcolor="#a0c0ff" cellspacing="0">
+  <tr valign="middle">
+  <!-- Home link -->
+      <th bgcolor="#70b0f0" class="navbar-select"
+          >&nbsp;&nbsp;&nbsp;Home&nbsp;&nbsp;&nbsp;</th>
+
+  <!-- Tree link -->
+      <th>&nbsp;&nbsp;&nbsp;<a
+        href="module-tree.html">Trees</a>&nbsp;&nbsp;&nbsp;</th>
+
+  <!-- Index link -->
+      <th>&nbsp;&nbsp;&nbsp;<a
+        href="identifier-index.html">Indices</a>&nbsp;&nbsp;&nbsp;</th>
+
+  <!-- Help link -->
+      <th>&nbsp;&nbsp;&nbsp;<a
+        href="help.html">Help</a>&nbsp;&nbsp;&nbsp;</th>
+
+  <!-- Project homepage -->
+      <th class="navbar" align="right" width="100%">
+        <table border="0" cellpadding="0" cellspacing="0">
+          <tr><th class="navbar" align="center"
+            >PyFeast</th>
+          </tr></table></th>
+  </tr>
+</table>
+<table width="100%" cellpadding="0" cellspacing="0">
+  <tr valign="top">
+    <td width="100%">
+      <span class="breadcrumbs">
+        Module&nbsp;feast
+      </span>
+    </td>
+    <td>
+      <table cellpadding="0" cellspacing="0">
+        <!-- hide/show private -->
+      </table>
+    </td>
+  </tr>
+</table>
+<!-- ==================== MODULE DESCRIPTION ==================== -->
+<h1 class="epydoc">Module feast</h1><p class="nomargin-top"><span class="codelink"><a href="feast-pysrc.html">source&nbsp;code</a></span></p>
+<pre class="literalblock">
+
+The FEAST module provides an interface between the C-library
+for feature selection to Python. 
+
+References: 
+1) G. Brown, A. Pocock, M.-J. Zhao, and M. Lujan, &quot;Conditional
+    likelihood maximization: A unifying framework for information
+    theoretic feature selection,&quot; Journal of Machine Learning 
+    Research, vol. 13, pp. 27-66, 2012.
+
+</pre>
+
+<hr />
+<div class="fields">      <p><strong>Version:</strong>
+        0.2.0
+      </p>
+      <p><strong>Author:</strong>
+        Calvin Morrison
+      </p>
+      <p><strong>Copyright:</strong>
+        Copyright 2013, EESI Laboratory
+      </p>
+      <p><strong>License:</strong>
+        GPL
+      </p>
+</div><!-- ==================== FUNCTIONS ==================== -->
+<a name="section-Functions"></a>
+<table class="summary" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr bgcolor="#70b0f0" class="table-header">
+  <td align="left" colspan="2" class="table-header">
+    <span class="table-header">Functions</span></td>
+</tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#BetaGamma" class="summary-sig-name">BetaGamma</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>,
+        <span class="summary-sig-arg">beta</span>=<span class="summary-sig-default">1.0</span>,
+        <span class="summary-sig-arg">gamma</span>=<span class="summary-sig-default">1.0</span>)</span><br />
+      This algorithm implements conditional mutual information feature 
+      select, such that beta and gamma control the weight attached to the 
+      redundant mutual and conditional mutual information, respectively.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#BetaGamma">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#CIFE" class="summary-sig-name">CIFE</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the Condred feature selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#CIFE">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#CMIM" class="summary-sig-name">CMIM</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the conditional mutual information 
+      maximization feature selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#CMIM">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#CondMI" class="summary-sig-name">CondMI</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the conditional mutual information 
+      maximization feature selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#CondMI">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#Condred" class="summary-sig-name">Condred</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the Condred feature selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#Condred">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#DISR" class="summary-sig-name">DISR</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the double input symmetrical relevance 
+      feature selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#DISR">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#ICAP" class="summary-sig-name">ICAP</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the interaction capping feature selection 
+      algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#ICAP">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#JMI" class="summary-sig-name">JMI</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the joint mutual information feature 
+      selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#JMI">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#MIFS" class="summary-sig-name">MIFS</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the MIFS algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#MIFS">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#MIM" class="summary-sig-name">MIM</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This function implements the MIM algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#MIM">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">list</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#mRMR" class="summary-sig-name">mRMR</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>,
+        <span class="summary-sig-arg">n_select</span>)</span><br />
+      This funciton implements the max-relevance min-redundancy feature 
+      selection algorithm.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#mRMR">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">tuple</span>
+    </td><td class="summary">
+      <table width="100%" cellpadding="0" cellspacing="0" border="0">
+        <tr>
+          <td><span class="summary-sig"><a href="feast-module.html#check_data" class="summary-sig-name">check_data</a>(<span class="summary-sig-arg">data</span>,
+        <span class="summary-sig-arg">labels</span>)</span><br />
+      Check dimensions of the data and the labels.</td>
+          <td align="right" valign="top">
+            <span class="codelink"><a href="feast-pysrc.html#check_data">source&nbsp;code</a></span>
+            
+          </td>
+        </tr>
+      </table>
+      
+    </td>
+  </tr>
+</table>
+<!-- ==================== VARIABLES ==================== -->
+<a name="section-Variables"></a>
+<table class="summary" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr bgcolor="#70b0f0" class="table-header">
+  <td align="left" colspan="2" class="table-header">
+    <span class="table-header">Variables</span></td>
+</tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a name="__credits__"></a><span class="summary-name">__credits__</span> = <code title="['Calvin Morrison', 'Gregory Ditzler']"><code class="variable-group">[</code><code class="variable-quote">'</code><code class="variable-string">Calvin Morrison</code><code class="variable-quote">'</code><code class="variable-op">, </code><code class="variable-quote">'</code><code class="variable-string">Gregory Ditzler</code><code class="variable-quote">'</code><code class="variable-group">]</code></code>
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a name="__maintainer__"></a><span class="summary-name">__maintainer__</span> = <code title="'Calvin Morrison'"><code class="variable-quote">'</code><code class="variable-string">Calvin Morrison</code><code class="variable-quote">'</code></code>
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a name="__email__"></a><span class="summary-name">__email__</span> = <code title="'mutantturkey@gmail.com'"><code class="variable-quote">'</code><code class="variable-string">mutantturkey@gmail.com</code><code class="variable-quote">'</code></code>
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a name="__status__"></a><span class="summary-name">__status__</span> = <code title="'Release'"><code class="variable-quote">'</code><code class="variable-string">Release</code><code class="variable-quote">'</code></code>
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a href="feast-module.html#libFSToolbox" class="summary-name">libFSToolbox</a> = <code title="&lt;CDLL 'libFSToolbox.so', handle 2be1240 at 2b4bc10&gt;">&lt;CDLL 'libFSToolbox.so', handle 2be1240 at 2b4b<code class="variable-ellipsis">...</code></code>
+    </td>
+  </tr>
+<tr>
+    <td width="15%" align="right" valign="top" class="summary">
+      <span class="summary-type">&nbsp;</span>
+    </td><td class="summary">
+        <a name="__package__"></a><span class="summary-name">__package__</span> = <code title="None">None</code>
+    </td>
+  </tr>
+</table>
+<!-- ==================== FUNCTION DETAILS ==================== -->
+<a name="section-FunctionDetails"></a>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr bgcolor="#70b0f0" class="table-header">
+  <td align="left" colspan="2" class="table-header">
+    <span class="table-header">Function Details</span></td>
+</tr>
+</table>
+<a name="BetaGamma"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">BetaGamma</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>,
+        <span class="sig-arg">beta</span>=<span class="sig-default">1.0</span>,
+        <span class="sig-arg">gamma</span>=<span class="sig-default">1.0</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#BetaGamma">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This algorithm implements conditional mutual information feature 
+  select, such that beta and gamma control the weight attached to the 
+  redundant mutual and conditional mutual information, respectively.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features (REQUIRED)</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations. (REQUIRED)</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+        <li><strong class="pname"><code>beta</code></strong> (float between 0 and 1.0) - penalty attacted to I(X_j;X_k)</li>
+        <li><strong class="pname"><code>gamma</code></strong> (float between 0 and 1.0) - positive weight attached to the conditional redundancy term 
+          I(X_k;X_j|Y)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="CIFE"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">CIFE</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#CIFE">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the Condred feature selection algorithm. beta
+  = 1; gamma = 1;</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - A Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select.</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+  </dl>
+</td></tr></table>
+</div>
+<a name="CMIM"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">CMIM</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#CMIM">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the conditional mutual information 
+  maximization feature selection algorithm. Note that this implementation 
+  does not allow for the weighting of the redundancy terms that BetaGamma 
+  will allow you to do.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - A Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy array with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select.</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>features in the order that they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="CondMI"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">CondMI</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#CondMI">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the conditional mutual information 
+  maximization feature selection algorithm.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - represented in a numpy list with n_observations as the number of 
+          elements. That is len(labels) = len(data) = n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select.</li>
+    </ul></dd>
+    <dt>Returns:</dt>
+        <dd>features in the order they were selected. @rtype list</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="Condred"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">Condred</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#Condred">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the Condred feature selection algorithm. beta
+  = 0; gamma = 1;</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select.</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="DISR"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">DISR</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#DISR">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the double input symmetrical relevance 
+  feature selection algorithm.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="ICAP"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">ICAP</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#ICAP">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the interaction capping feature selection 
+  algorithm.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="JMI"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">JMI</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#JMI">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the joint mutual information feature 
+  selection algorithm.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="MIFS"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">MIFS</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#MIFS">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the MIFS algorithm. beta = 1; gamma = 0;</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="MIM"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">MIM</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#MIM">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This function implements the MIM algorithm. beta = 0; gamma = 0;</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="mRMR"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">mRMR</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>,
+        <span class="sig-arg">n_select</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#mRMR">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>This funciton implements the max-relevance min-redundancy feature 
+  selection algorithm.</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> (ndarray) - data in a Numpy array such that len(data) = n_observations, and 
+          len(data.transpose()) = n_features</li>
+        <li><strong class="pname"><code>labels</code></strong> (ndarray) - labels represented in a numpy list with n_observations as the 
+          number of elements. That is len(labels) = len(data) = 
+          n_observations.</li>
+        <li><strong class="pname"><code>n_select</code></strong> (integer) - number of features to select. (REQUIRED)</li>
+    </ul></dd>
+    <dt>Returns: list</dt>
+        <dd>the features in the order they were selected.</dd>
+  </dl>
+</td></tr></table>
+</div>
+<a name="check_data"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <table width="100%" cellpadding="0" cellspacing="0" border="0">
+  <tr valign="top"><td>
+  <h3 class="epydoc"><span class="sig"><span class="sig-name">check_data</span>(<span class="sig-arg">data</span>,
+        <span class="sig-arg">labels</span>)</span>
+  </h3>
+  </td><td align="right" valign="top"
+    ><span class="codelink"><a href="feast-pysrc.html#check_data">source&nbsp;code</a></span>&nbsp;
+    </td>
+  </tr></table>
+  
+  <p>Check dimensions of the data and the labels.  Raise and exception if 
+  there is a problem.</p>
+  <p>Data and Labels are automatically cast as doubles before calling the 
+  feature selection functions</p>
+  <dl class="fields">
+    <dt>Parameters:</dt>
+    <dd><ul class="nomargin-top">
+        <li><strong class="pname"><code>data</code></strong> - the data</li>
+        <li><strong class="pname"><code>labels</code></strong> - the labels</li>
+    </ul></dd>
+    <dt>Returns: tuple</dt>
+  </dl>
+</td></tr></table>
+</div>
+<br />
+<!-- ==================== VARIABLES DETAILS ==================== -->
+<a name="section-VariablesDetails"></a>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr bgcolor="#70b0f0" class="table-header">
+  <td align="left" colspan="2" class="table-header">
+    <span class="table-header">Variables Details</span></td>
+</tr>
+</table>
+<a name="libFSToolbox"></a>
+<div>
+<table class="details" border="1" cellpadding="3"
+       cellspacing="0" width="100%" bgcolor="white">
+<tr><td>
+  <h3 class="epydoc">libFSToolbox</h3>
+  
+  <dl class="fields">
+  </dl>
+  <dl class="fields">
+    <dt>Value:</dt>
+      <dd><table><tr><td><pre class="variable">
+&lt;CDLL 'libFSToolbox.so', handle 2be1240 at 2b4bc10&gt;
+</pre></td></tr></table>
+</dd>
+  </dl>
+</td></tr></table>
+</div>
+<br />
+<!-- ==================== NAVIGATION BAR ==================== -->
+<table class="navbar" border="0" width="100%" cellpadding="0"
+       bgcolor="#a0c0ff" cellspacing="0">
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+  <!-- Home link -->
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+          >&nbsp;&nbsp;&nbsp;Home&nbsp;&nbsp;&nbsp;</th>
+
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+
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+</html>
diff --git a/feast-pysrc.html b/feast-pysrc.html
new file mode 100644
index 0000000..d5f5dc1
--- /dev/null
+++ b/feast-pysrc.html
@@ -0,0 +1,620 @@
+<?xml version="1.0" encoding="ascii"?>
+<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
+          "DTD/xhtml1-transitional.dtd">
+<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
+<head>
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+  <link rel="stylesheet" href="epydoc.css" type="text/css" />
+  <script type="text/javascript" src="epydoc.js"></script>
+</head>
+
+<body bgcolor="white" text="black" link="blue" vlink="#204080"
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+<!-- ==================== NAVIGATION BAR ==================== -->
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+        Module&nbsp;feast
+      </span>
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+</table>
+<h1 class="epydoc">Source Code for <a href="feast-module.html">Module feast</a></h1>
+<pre class="py-src">
+<a name="L1"></a><tt class="py-lineno">  1</tt>  <tt class="py-line"><tt class="py-docstring">'''</tt> </tt>
+<a name="L2"></a><tt class="py-lineno">  2</tt>  <tt class="py-line"><tt class="py-docstring">  The FEAST module provides an interface between the C-library</tt> </tt>
+<a name="L3"></a><tt class="py-lineno">  3</tt>  <tt class="py-line"><tt class="py-docstring">  for feature selection to Python. </tt> </tt>
+<a name="L4"></a><tt class="py-lineno">  4</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L5"></a><tt class="py-lineno">  5</tt>  <tt class="py-line"><tt class="py-docstring">  References: </tt> </tt>
+<a name="L6"></a><tt class="py-lineno">  6</tt>  <tt class="py-line"><tt class="py-docstring">  1) G. Brown, A. Pocock, M.-J. Zhao, and M. Lujan, "Conditional</tt> </tt>
+<a name="L7"></a><tt class="py-lineno">  7</tt>  <tt class="py-line"><tt class="py-docstring">      likelihood maximization: A unifying framework for information</tt> </tt>
+<a name="L8"></a><tt class="py-lineno">  8</tt>  <tt class="py-line"><tt class="py-docstring">      theoretic feature selection," Journal of Machine Learning </tt> </tt>
+<a name="L9"></a><tt class="py-lineno">  9</tt>  <tt class="py-line"><tt class="py-docstring">      Research, vol. 13, pp. 27-66, 2012.</tt> </tt>
+<a name="L10"></a><tt class="py-lineno"> 10</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L11"></a><tt class="py-lineno"> 11</tt>  <tt class="py-line"><tt class="py-docstring">'''</tt> </tt>
+<a name="L12"></a><tt class="py-lineno"> 12</tt>  <tt class="py-line"><tt class="py-name">__author__</tt> <tt class="py-op">=</tt> <tt class="py-string">"Calvin Morrison"</tt> </tt>
+<a name="L13"></a><tt class="py-lineno"> 13</tt>  <tt class="py-line"><tt class="py-name">__copyright__</tt> <tt class="py-op">=</tt> <tt class="py-string">"Copyright 2013, EESI Laboratory"</tt> </tt>
+<a name="L14"></a><tt class="py-lineno"> 14</tt>  <tt class="py-line"><tt id="link-0" class="py-name" targets="Variable feast.__credits__=feast-module.html#__credits__"><a title="feast.__credits__" class="py-name" href="#" onclick="return doclink('link-0', '__credits__', 'link-0');">__credits__</a></tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-string">"Calvin Morrison"</tt><tt class="py-op">,</tt> <tt class="py-string">"Gregory Ditzler"</tt><tt class="py-op">]</tt> </tt>
+<a name="L15"></a><tt class="py-lineno"> 15</tt>  <tt class="py-line"><tt class="py-name">__license__</tt> <tt class="py-op">=</tt> <tt class="py-string">"GPL"</tt> </tt>
+<a name="L16"></a><tt class="py-lineno"> 16</tt>  <tt class="py-line"><tt class="py-name">__version__</tt> <tt class="py-op">=</tt> <tt class="py-string">"0.2.0"</tt> </tt>
+<a name="L17"></a><tt class="py-lineno"> 17</tt>  <tt class="py-line"><tt id="link-1" class="py-name" targets="Variable feast.__maintainer__=feast-module.html#__maintainer__"><a title="feast.__maintainer__" class="py-name" href="#" onclick="return doclink('link-1', '__maintainer__', 'link-1');">__maintainer__</a></tt> <tt class="py-op">=</tt> <tt class="py-string">"Calvin Morrison"</tt> </tt>
+<a name="L18"></a><tt class="py-lineno"> 18</tt>  <tt class="py-line"><tt id="link-2" class="py-name" targets="Variable feast.__email__=feast-module.html#__email__"><a title="feast.__email__" class="py-name" href="#" onclick="return doclink('link-2', '__email__', 'link-2');">__email__</a></tt> <tt class="py-op">=</tt> <tt class="py-string">"mutantturkey@gmail.com"</tt> </tt>
+<a name="L19"></a><tt class="py-lineno"> 19</tt>  <tt class="py-line"><tt id="link-3" class="py-name" targets="Variable feast.__status__=feast-module.html#__status__"><a title="feast.__status__" class="py-name" href="#" onclick="return doclink('link-3', '__status__', 'link-3');">__status__</a></tt> <tt class="py-op">=</tt> <tt class="py-string">"Release"</tt> </tt>
+<a name="L20"></a><tt class="py-lineno"> 20</tt>  <tt class="py-line"> </tt>
+<a name="L21"></a><tt class="py-lineno"> 21</tt>  <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">numpy</tt> <tt class="py-keyword">as</tt> <tt class="py-name">np</tt> </tt>
+<a name="L22"></a><tt class="py-lineno"> 22</tt>  <tt class="py-line"><tt class="py-keyword">import</tt> <tt class="py-name">ctypes</tt> <tt class="py-keyword">as</tt> <tt class="py-name">c</tt> </tt>
+<a name="L23"></a><tt class="py-lineno"> 23</tt>  <tt class="py-line"> </tt>
+<a name="L24"></a><tt class="py-lineno"> 24</tt>  <tt class="py-line"><tt class="py-keyword">try</tt><tt class="py-op">:</tt> </tt>
+<a name="L25"></a><tt class="py-lineno"> 25</tt>  <tt class="py-line">  <tt id="link-4" class="py-name" targets="Variable feast.libFSToolbox=feast-module.html#libFSToolbox"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-4', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">CDLL</tt><tt class="py-op">(</tt><tt class="py-string">"libFSToolbox.so"</tt><tt class="py-op">)</tt><tt class="py-op">;</tt>  </tt>
+<a name="L26"></a><tt class="py-lineno"> 26</tt>  <tt class="py-line"><tt class="py-keyword">except</tt><tt class="py-op">:</tt> </tt>
+<a name="L27"></a><tt class="py-lineno"> 27</tt>  <tt class="py-line">  <tt class="py-keyword">raise</tt> <tt class="py-name">Exception</tt><tt class="py-op">(</tt><tt class="py-string">"Error: could not load libFSToolbox.so"</tt><tt class="py-op">)</tt> </tt>
+<a name="L28"></a><tt class="py-lineno"> 28</tt>  <tt class="py-line"> </tt>
+<a name="L29"></a><tt class="py-lineno"> 29</tt>  <tt class="py-line"> </tt>
+<a name="BetaGamma"></a><div id="BetaGamma-def"><a name="L30"></a><tt class="py-lineno"> 30</tt> <a class="py-toggle" href="#" id="BetaGamma-toggle" onclick="return toggle('BetaGamma');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#BetaGamma">BetaGamma</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">,</tt> <tt class="py-param">beta</tt><tt class="py-op">=</tt><tt class="py-number">1.0</tt><tt class="py-op">,</tt> <tt class="py-param">gamma</tt><tt class="py-op">=</tt><tt class="py-number">1.0</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="BetaGamma-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="BetaGamma-expanded"><a name="L31"></a><tt class="py-lineno"> 31</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L32"></a><tt class="py-lineno"> 32</tt>  <tt class="py-line"><tt class="py-docstring">    This algorithm implements conditional mutual information </tt> </tt>
+<a name="L33"></a><tt class="py-lineno"> 33</tt>  <tt class="py-line"><tt class="py-docstring">    feature select, such that beta and gamma control the </tt> </tt>
+<a name="L34"></a><tt class="py-lineno"> 34</tt>  <tt class="py-line"><tt class="py-docstring">    weight attached to the redundant mutual and conditional</tt> </tt>
+<a name="L35"></a><tt class="py-lineno"> 35</tt>  <tt class="py-line"><tt class="py-docstring">    mutual information, respectively. </tt> </tt>
+<a name="L36"></a><tt class="py-lineno"> 36</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L37"></a><tt class="py-lineno"> 37</tt>  <tt class="py-line"><tt class="py-docstring">      @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L38"></a><tt class="py-lineno"> 38</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L39"></a><tt class="py-lineno"> 39</tt>  <tt class="py-line"><tt class="py-docstring">        (REQUIRED)</tt> </tt>
+<a name="L40"></a><tt class="py-lineno"> 40</tt>  <tt class="py-line"><tt class="py-docstring">      @type data: ndarray</tt> </tt>
+<a name="L41"></a><tt class="py-lineno"> 41</tt>  <tt class="py-line"><tt class="py-docstring">      @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L42"></a><tt class="py-lineno"> 42</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L43"></a><tt class="py-lineno"> 43</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L44"></a><tt class="py-lineno"> 44</tt>  <tt class="py-line"><tt class="py-docstring">        (REQUIRED)</tt> </tt>
+<a name="L45"></a><tt class="py-lineno"> 45</tt>  <tt class="py-line"><tt class="py-docstring">      @type labels: ndarray</tt> </tt>
+<a name="L46"></a><tt class="py-lineno"> 46</tt>  <tt class="py-line"><tt class="py-docstring">      @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L47"></a><tt class="py-lineno"> 47</tt>  <tt class="py-line"><tt class="py-docstring">      @type n_select: integer</tt> </tt>
+<a name="L48"></a><tt class="py-lineno"> 48</tt>  <tt class="py-line"><tt class="py-docstring">      @param beta: penalty attacted to I(X_j;X_k) </tt> </tt>
+<a name="L49"></a><tt class="py-lineno"> 49</tt>  <tt class="py-line"><tt class="py-docstring">      @type beta: float between 0 and 1.0 </tt> </tt>
+<a name="L50"></a><tt class="py-lineno"> 50</tt>  <tt class="py-line"><tt class="py-docstring">      @param gamma: positive weight attached to the conditional</tt> </tt>
+<a name="L51"></a><tt class="py-lineno"> 51</tt>  <tt class="py-line"><tt class="py-docstring">        redundancy term I(X_k;X_j|Y)</tt> </tt>
+<a name="L52"></a><tt class="py-lineno"> 52</tt>  <tt class="py-line"><tt class="py-docstring">      @type gamma: float between 0 and 1.0 </tt> </tt>
+<a name="L53"></a><tt class="py-lineno"> 53</tt>  <tt class="py-line"><tt class="py-docstring">      @return: features in the order they were selected. </tt> </tt>
+<a name="L54"></a><tt class="py-lineno"> 54</tt>  <tt class="py-line"><tt class="py-docstring">      @rtype: list</tt> </tt>
+<a name="L55"></a><tt class="py-lineno"> 55</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L56"></a><tt class="py-lineno"> 56</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-5" class="py-name" targets="Function feast.check_data()=feast-module.html#check_data"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-5', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L57"></a><tt class="py-lineno"> 57</tt>  <tt class="py-line"> </tt>
+<a name="L58"></a><tt class="py-lineno"> 58</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L59"></a><tt class="py-lineno"> 59</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L60"></a><tt class="py-lineno"> 60</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L61"></a><tt class="py-lineno"> 61</tt>  <tt class="py-line"> </tt>
+<a name="L62"></a><tt class="py-lineno"> 62</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L63"></a><tt class="py-lineno"> 63</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L64"></a><tt class="py-lineno"> 64</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L65"></a><tt class="py-lineno"> 65</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L66"></a><tt class="py-lineno"> 66</tt>  <tt class="py-line">  <tt class="py-name">c_beta</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">(</tt><tt class="py-name">beta</tt><tt class="py-op">)</tt> </tt>
+<a name="L67"></a><tt class="py-lineno"> 67</tt>  <tt class="py-line">  <tt class="py-name">c_gamma</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">(</tt><tt class="py-name">gamma</tt><tt class="py-op">)</tt> </tt>
+<a name="L68"></a><tt class="py-lineno"> 68</tt>  <tt class="py-line"> </tt>
+<a name="L69"></a><tt class="py-lineno"> 69</tt>  <tt class="py-line">  <tt id="link-6" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-6', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-7" class="py-name" targets="Function feast.BetaGamma()=feast-module.html#BetaGamma"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-7', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L70"></a><tt class="py-lineno"> 70</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-8" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-8', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-9" class="py-name"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-9', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L71"></a><tt class="py-lineno"> 71</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L72"></a><tt class="py-lineno"> 72</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L73"></a><tt class="py-lineno"> 73</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L74"></a><tt class="py-lineno"> 74</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L75"></a><tt class="py-lineno"> 75</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L76"></a><tt class="py-lineno"> 76</tt>  <tt class="py-line">                   <tt class="py-name">c_beta</tt><tt class="py-op">,</tt> </tt>
+<a name="L77"></a><tt class="py-lineno"> 77</tt>  <tt class="py-line">                   <tt class="py-name">c_gamma</tt> </tt>
+<a name="L78"></a><tt class="py-lineno"> 78</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L79"></a><tt class="py-lineno"> 79</tt>  <tt class="py-line"> </tt>
+<a name="L80"></a><tt class="py-lineno"> 80</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L81"></a><tt class="py-lineno"> 81</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L82"></a><tt class="py-lineno"> 82</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L83"></a><tt class="py-lineno"> 83</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L84"></a><tt class="py-lineno"> 84</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L85"></a><tt class="py-lineno"> 85</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L86"></a><tt class="py-lineno"> 86</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L87"></a><tt class="py-lineno"> 87</tt>  <tt class="py-line"> </tt>
+<a name="L88"></a><tt class="py-lineno"> 88</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L89"></a><tt class="py-lineno"> 89</tt>  <tt class="py-line"> </tt>
+<a name="L90"></a><tt class="py-lineno"> 90</tt>  <tt class="py-line"> </tt>
+<a name="L91"></a><tt class="py-lineno"> 91</tt>  <tt class="py-line"> </tt>
+<a name="CIFE"></a><div id="CIFE-def"><a name="L92"></a><tt class="py-lineno"> 92</tt> <a class="py-toggle" href="#" id="CIFE-toggle" onclick="return toggle('CIFE');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#CIFE">CIFE</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="CIFE-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="CIFE-expanded"><a name="L93"></a><tt class="py-lineno"> 93</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L94"></a><tt class="py-lineno"> 94</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the Condred feature selection algorithm.</tt> </tt>
+<a name="L95"></a><tt class="py-lineno"> 95</tt>  <tt class="py-line"><tt class="py-docstring">    beta = 1; gamma = 1;</tt> </tt>
+<a name="L96"></a><tt class="py-lineno"> 96</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L97"></a><tt class="py-lineno"> 97</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: A Numpy array such that len(data) = </tt> </tt>
+<a name="L98"></a><tt class="py-lineno"> 98</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L99"></a><tt class="py-lineno"> 99</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L100"></a><tt class="py-lineno">100</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L101"></a><tt class="py-lineno">101</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L102"></a><tt class="py-lineno">102</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L103"></a><tt class="py-lineno">103</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L104"></a><tt class="py-lineno">104</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select:  number of features to select.</tt> </tt>
+<a name="L105"></a><tt class="py-lineno">105</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L106"></a><tt class="py-lineno">106</tt>  <tt class="py-line"><tt class="py-docstring">    @return selected_features: features in the order they were selected. </tt> </tt>
+<a name="L107"></a><tt class="py-lineno">107</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L108"></a><tt class="py-lineno">108</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L109"></a><tt class="py-lineno">109</tt>  <tt class="py-line"> </tt>
+<a name="L110"></a><tt class="py-lineno">110</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt id="link-10" class="py-name"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-10', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">,</tt> <tt class="py-name">n_select</tt><tt class="py-op">,</tt> <tt class="py-name">beta</tt><tt class="py-op">=</tt><tt class="py-number">1.0</tt><tt class="py-op">,</tt> <tt class="py-name">gamma</tt><tt class="py-op">=</tt><tt class="py-number">1.0</tt><tt class="py-op">)</tt> </tt>
+</div><a name="L111"></a><tt class="py-lineno">111</tt>  <tt class="py-line"> </tt>
+<a name="L112"></a><tt class="py-lineno">112</tt>  <tt class="py-line"> </tt>
+<a name="L113"></a><tt class="py-lineno">113</tt>  <tt class="py-line"> </tt>
+<a name="L114"></a><tt class="py-lineno">114</tt>  <tt class="py-line"> </tt>
+<a name="CMIM"></a><div id="CMIM-def"><a name="L115"></a><tt class="py-lineno">115</tt> <a class="py-toggle" href="#" id="CMIM-toggle" onclick="return toggle('CMIM');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#CMIM">CMIM</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="CMIM-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="CMIM-expanded"><a name="L116"></a><tt class="py-lineno">116</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L117"></a><tt class="py-lineno">117</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the conditional mutual information</tt> </tt>
+<a name="L118"></a><tt class="py-lineno">118</tt>  <tt class="py-line"><tt class="py-docstring">    maximization feature selection algorithm. Note that this </tt> </tt>
+<a name="L119"></a><tt class="py-lineno">119</tt>  <tt class="py-line"><tt class="py-docstring">    implementation does not allow for the weighting of the </tt> </tt>
+<a name="L120"></a><tt class="py-lineno">120</tt>  <tt class="py-line"><tt class="py-docstring">    redundancy terms that BetaGamma will allow you to do.</tt> </tt>
+<a name="L121"></a><tt class="py-lineno">121</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L122"></a><tt class="py-lineno">122</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: A Numpy array such that len(data) = </tt> </tt>
+<a name="L123"></a><tt class="py-lineno">123</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L124"></a><tt class="py-lineno">124</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L125"></a><tt class="py-lineno">125</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy array with </tt> </tt>
+<a name="L126"></a><tt class="py-lineno">126</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L127"></a><tt class="py-lineno">127</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L128"></a><tt class="py-lineno">128</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L129"></a><tt class="py-lineno">129</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select.</tt> </tt>
+<a name="L130"></a><tt class="py-lineno">130</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L131"></a><tt class="py-lineno">131</tt>  <tt class="py-line"><tt class="py-docstring">    @return: features in the order that they were selected. </tt> </tt>
+<a name="L132"></a><tt class="py-lineno">132</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L133"></a><tt class="py-lineno">133</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L134"></a><tt class="py-lineno">134</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-11" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-11', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L135"></a><tt class="py-lineno">135</tt>  <tt class="py-line"> </tt>
+<a name="L136"></a><tt class="py-lineno">136</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L137"></a><tt class="py-lineno">137</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L138"></a><tt class="py-lineno">138</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L139"></a><tt class="py-lineno">139</tt>  <tt class="py-line"> </tt>
+<a name="L140"></a><tt class="py-lineno">140</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L141"></a><tt class="py-lineno">141</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L142"></a><tt class="py-lineno">142</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L143"></a><tt class="py-lineno">143</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L144"></a><tt class="py-lineno">144</tt>  <tt class="py-line"> </tt>
+<a name="L145"></a><tt class="py-lineno">145</tt>  <tt class="py-line">  <tt id="link-12" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-12', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-13" class="py-name" targets="Function feast.CMIM()=feast-module.html#CMIM"><a title="feast.CMIM" class="py-name" href="#" onclick="return doclink('link-13', 'CMIM', 'link-13');">CMIM</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L146"></a><tt class="py-lineno">146</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-14" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-14', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-15" class="py-name"><a title="feast.CMIM" class="py-name" href="#" onclick="return doclink('link-15', 'CMIM', 'link-13');">CMIM</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L147"></a><tt class="py-lineno">147</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L148"></a><tt class="py-lineno">148</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L149"></a><tt class="py-lineno">149</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L150"></a><tt class="py-lineno">150</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L151"></a><tt class="py-lineno">151</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L152"></a><tt class="py-lineno">152</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L153"></a><tt class="py-lineno">153</tt>  <tt class="py-line"> </tt>
+<a name="L154"></a><tt class="py-lineno">154</tt>  <tt class="py-line">   </tt>
+<a name="L155"></a><tt class="py-lineno">155</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L156"></a><tt class="py-lineno">156</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L157"></a><tt class="py-lineno">157</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L158"></a><tt class="py-lineno">158</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L159"></a><tt class="py-lineno">159</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L160"></a><tt class="py-lineno">160</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L161"></a><tt class="py-lineno">161</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L162"></a><tt class="py-lineno">162</tt>  <tt class="py-line"> </tt>
+<a name="L163"></a><tt class="py-lineno">163</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L164"></a><tt class="py-lineno">164</tt>  <tt class="py-line"> </tt>
+<a name="L165"></a><tt class="py-lineno">165</tt>  <tt class="py-line"> </tt>
+<a name="L166"></a><tt class="py-lineno">166</tt>  <tt class="py-line"> </tt>
+<a name="CondMI"></a><div id="CondMI-def"><a name="L167"></a><tt class="py-lineno">167</tt> <a class="py-toggle" href="#" id="CondMI-toggle" onclick="return toggle('CondMI');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#CondMI">CondMI</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="CondMI-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="CondMI-expanded"><a name="L168"></a><tt class="py-lineno">168</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L169"></a><tt class="py-lineno">169</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the conditional mutual information</tt> </tt>
+<a name="L170"></a><tt class="py-lineno">170</tt>  <tt class="py-line"><tt class="py-docstring">    maximization feature selection algorithm. </tt> </tt>
+<a name="L171"></a><tt class="py-lineno">171</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L172"></a><tt class="py-lineno">172</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = n_observations,</tt> </tt>
+<a name="L173"></a><tt class="py-lineno">173</tt>  <tt class="py-line"><tt class="py-docstring">       and len(data.transpose()) = n_features</tt> </tt>
+<a name="L174"></a><tt class="py-lineno">174</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L175"></a><tt class="py-lineno">175</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: represented in a numpy list with </tt> </tt>
+<a name="L176"></a><tt class="py-lineno">176</tt>  <tt class="py-line"><tt class="py-docstring">      n_observations as the number of elements. That is </tt> </tt>
+<a name="L177"></a><tt class="py-lineno">177</tt>  <tt class="py-line"><tt class="py-docstring">      len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L178"></a><tt class="py-lineno">178</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L179"></a><tt class="py-lineno">179</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select.</tt> </tt>
+<a name="L180"></a><tt class="py-lineno">180</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L181"></a><tt class="py-lineno">181</tt>  <tt class="py-line"><tt class="py-docstring">    @return: features in the order they were selected. </tt> </tt>
+<a name="L182"></a><tt class="py-lineno">182</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype list</tt> </tt>
+<a name="L183"></a><tt class="py-lineno">183</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L184"></a><tt class="py-lineno">184</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-16" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-16', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L185"></a><tt class="py-lineno">185</tt>  <tt class="py-line"> </tt>
+<a name="L186"></a><tt class="py-lineno">186</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L187"></a><tt class="py-lineno">187</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L188"></a><tt class="py-lineno">188</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L189"></a><tt class="py-lineno">189</tt>  <tt class="py-line"> </tt>
+<a name="L190"></a><tt class="py-lineno">190</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L191"></a><tt class="py-lineno">191</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L192"></a><tt class="py-lineno">192</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L193"></a><tt class="py-lineno">193</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L194"></a><tt class="py-lineno">194</tt>  <tt class="py-line"> </tt>
+<a name="L195"></a><tt class="py-lineno">195</tt>  <tt class="py-line">  <tt id="link-17" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-17', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-18" class="py-name" targets="Function feast.CondMI()=feast-module.html#CondMI"><a title="feast.CondMI" class="py-name" href="#" onclick="return doclink('link-18', 'CondMI', 'link-18');">CondMI</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L196"></a><tt class="py-lineno">196</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-19" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-19', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-20" class="py-name"><a title="feast.CondMI" class="py-name" href="#" onclick="return doclink('link-20', 'CondMI', 'link-18');">CondMI</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L197"></a><tt class="py-lineno">197</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L198"></a><tt class="py-lineno">198</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L199"></a><tt class="py-lineno">199</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L200"></a><tt class="py-lineno">200</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L201"></a><tt class="py-lineno">201</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L202"></a><tt class="py-lineno">202</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L203"></a><tt class="py-lineno">203</tt>  <tt class="py-line"> </tt>
+<a name="L204"></a><tt class="py-lineno">204</tt>  <tt class="py-line">   </tt>
+<a name="L205"></a><tt class="py-lineno">205</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L206"></a><tt class="py-lineno">206</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L207"></a><tt class="py-lineno">207</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L208"></a><tt class="py-lineno">208</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L209"></a><tt class="py-lineno">209</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L210"></a><tt class="py-lineno">210</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L211"></a><tt class="py-lineno">211</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L212"></a><tt class="py-lineno">212</tt>  <tt class="py-line"> </tt>
+<a name="L213"></a><tt class="py-lineno">213</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L214"></a><tt class="py-lineno">214</tt>  <tt class="py-line"> </tt>
+<a name="L215"></a><tt class="py-lineno">215</tt>  <tt class="py-line"> </tt>
+<a name="Condred"></a><div id="Condred-def"><a name="L216"></a><tt class="py-lineno">216</tt> <a class="py-toggle" href="#" id="Condred-toggle" onclick="return toggle('Condred');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#Condred">Condred</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="Condred-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="Condred-expanded"><a name="L217"></a><tt class="py-lineno">217</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L218"></a><tt class="py-lineno">218</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the Condred feature selection algorithm.</tt> </tt>
+<a name="L219"></a><tt class="py-lineno">219</tt>  <tt class="py-line"><tt class="py-docstring">    beta = 0; gamma = 1;</tt> </tt>
+<a name="L220"></a><tt class="py-lineno">220</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L221"></a><tt class="py-lineno">221</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L222"></a><tt class="py-lineno">222</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L223"></a><tt class="py-lineno">223</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L224"></a><tt class="py-lineno">224</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L225"></a><tt class="py-lineno">225</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L226"></a><tt class="py-lineno">226</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L227"></a><tt class="py-lineno">227</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L228"></a><tt class="py-lineno">228</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select.</tt> </tt>
+<a name="L229"></a><tt class="py-lineno">229</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L230"></a><tt class="py-lineno">230</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L231"></a><tt class="py-lineno">231</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L232"></a><tt class="py-lineno">232</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L233"></a><tt class="py-lineno">233</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-21" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-21', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L234"></a><tt class="py-lineno">234</tt>  <tt class="py-line"> </tt>
+<a name="L235"></a><tt class="py-lineno">235</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt id="link-22" class="py-name"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-22', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">,</tt> <tt class="py-name">n_select</tt><tt class="py-op">,</tt> <tt class="py-name">beta</tt><tt class="py-op">=</tt><tt class="py-number">0.0</tt><tt class="py-op">,</tt> <tt class="py-name">gamma</tt><tt class="py-op">=</tt><tt class="py-number">1.0</tt><tt class="py-op">)</tt> </tt>
+</div><a name="L236"></a><tt class="py-lineno">236</tt>  <tt class="py-line"> </tt>
+<a name="L237"></a><tt class="py-lineno">237</tt>  <tt class="py-line"> </tt>
+<a name="L238"></a><tt class="py-lineno">238</tt>  <tt class="py-line"> </tt>
+<a name="DISR"></a><div id="DISR-def"><a name="L239"></a><tt class="py-lineno">239</tt> <a class="py-toggle" href="#" id="DISR-toggle" onclick="return toggle('DISR');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#DISR">DISR</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="DISR-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="DISR-expanded"><a name="L240"></a><tt class="py-lineno">240</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L241"></a><tt class="py-lineno">241</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the double input symmetrical relevance</tt> </tt>
+<a name="L242"></a><tt class="py-lineno">242</tt>  <tt class="py-line"><tt class="py-docstring">    feature selection algorithm. </tt> </tt>
+<a name="L243"></a><tt class="py-lineno">243</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L244"></a><tt class="py-lineno">244</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L245"></a><tt class="py-lineno">245</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L246"></a><tt class="py-lineno">246</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L247"></a><tt class="py-lineno">247</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L248"></a><tt class="py-lineno">248</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L249"></a><tt class="py-lineno">249</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L250"></a><tt class="py-lineno">250</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L251"></a><tt class="py-lineno">251</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L252"></a><tt class="py-lineno">252</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L253"></a><tt class="py-lineno">253</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L254"></a><tt class="py-lineno">254</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L255"></a><tt class="py-lineno">255</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L256"></a><tt class="py-lineno">256</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-23" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-23', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L257"></a><tt class="py-lineno">257</tt>  <tt class="py-line"> </tt>
+<a name="L258"></a><tt class="py-lineno">258</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L259"></a><tt class="py-lineno">259</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L260"></a><tt class="py-lineno">260</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L261"></a><tt class="py-lineno">261</tt>  <tt class="py-line"> </tt>
+<a name="L262"></a><tt class="py-lineno">262</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L263"></a><tt class="py-lineno">263</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L264"></a><tt class="py-lineno">264</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L265"></a><tt class="py-lineno">265</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L266"></a><tt class="py-lineno">266</tt>  <tt class="py-line"> </tt>
+<a name="L267"></a><tt class="py-lineno">267</tt>  <tt class="py-line">  <tt id="link-24" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-24', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-25" class="py-name" targets="Function feast.DISR()=feast-module.html#DISR"><a title="feast.DISR" class="py-name" href="#" onclick="return doclink('link-25', 'DISR', 'link-25');">DISR</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L268"></a><tt class="py-lineno">268</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-26" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-26', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-27" class="py-name"><a title="feast.DISR" class="py-name" href="#" onclick="return doclink('link-27', 'DISR', 'link-25');">DISR</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L269"></a><tt class="py-lineno">269</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L270"></a><tt class="py-lineno">270</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L271"></a><tt class="py-lineno">271</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L272"></a><tt class="py-lineno">272</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L273"></a><tt class="py-lineno">273</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L274"></a><tt class="py-lineno">274</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L275"></a><tt class="py-lineno">275</tt>  <tt class="py-line"> </tt>
+<a name="L276"></a><tt class="py-lineno">276</tt>  <tt class="py-line">   </tt>
+<a name="L277"></a><tt class="py-lineno">277</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L278"></a><tt class="py-lineno">278</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L279"></a><tt class="py-lineno">279</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L280"></a><tt class="py-lineno">280</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L281"></a><tt class="py-lineno">281</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L282"></a><tt class="py-lineno">282</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L283"></a><tt class="py-lineno">283</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L284"></a><tt class="py-lineno">284</tt>  <tt class="py-line"> </tt>
+<a name="L285"></a><tt class="py-lineno">285</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L286"></a><tt class="py-lineno">286</tt>  <tt class="py-line"> </tt>
+<a name="L287"></a><tt class="py-lineno">287</tt>  <tt class="py-line"> </tt>
+<a name="L288"></a><tt class="py-lineno">288</tt>  <tt class="py-line"> </tt>
+<a name="L289"></a><tt class="py-lineno">289</tt>  <tt class="py-line"> </tt>
+<a name="ICAP"></a><div id="ICAP-def"><a name="L290"></a><tt class="py-lineno">290</tt> <a class="py-toggle" href="#" id="ICAP-toggle" onclick="return toggle('ICAP');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#ICAP">ICAP</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="ICAP-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="ICAP-expanded"><a name="L291"></a><tt class="py-lineno">291</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L292"></a><tt class="py-lineno">292</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the interaction capping feature </tt> </tt>
+<a name="L293"></a><tt class="py-lineno">293</tt>  <tt class="py-line"><tt class="py-docstring">    selection algorithm. </tt> </tt>
+<a name="L294"></a><tt class="py-lineno">294</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L295"></a><tt class="py-lineno">295</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L296"></a><tt class="py-lineno">296</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L297"></a><tt class="py-lineno">297</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L298"></a><tt class="py-lineno">298</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L299"></a><tt class="py-lineno">299</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L300"></a><tt class="py-lineno">300</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L301"></a><tt class="py-lineno">301</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L302"></a><tt class="py-lineno">302</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L303"></a><tt class="py-lineno">303</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L304"></a><tt class="py-lineno">304</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L305"></a><tt class="py-lineno">305</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L306"></a><tt class="py-lineno">306</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L307"></a><tt class="py-lineno">307</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-28" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-28', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L308"></a><tt class="py-lineno">308</tt>  <tt class="py-line"> </tt>
+<a name="L309"></a><tt class="py-lineno">309</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L310"></a><tt class="py-lineno">310</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L311"></a><tt class="py-lineno">311</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L312"></a><tt class="py-lineno">312</tt>  <tt class="py-line"> </tt>
+<a name="L313"></a><tt class="py-lineno">313</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L314"></a><tt class="py-lineno">314</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L315"></a><tt class="py-lineno">315</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L316"></a><tt class="py-lineno">316</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L317"></a><tt class="py-lineno">317</tt>  <tt class="py-line"> </tt>
+<a name="L318"></a><tt class="py-lineno">318</tt>  <tt class="py-line">  <tt id="link-29" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-29', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-30" class="py-name" targets="Function feast.ICAP()=feast-module.html#ICAP"><a title="feast.ICAP" class="py-name" href="#" onclick="return doclink('link-30', 'ICAP', 'link-30');">ICAP</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L319"></a><tt class="py-lineno">319</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-31" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-31', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-32" class="py-name"><a title="feast.ICAP" class="py-name" href="#" onclick="return doclink('link-32', 'ICAP', 'link-30');">ICAP</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L320"></a><tt class="py-lineno">320</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L321"></a><tt class="py-lineno">321</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L322"></a><tt class="py-lineno">322</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L323"></a><tt class="py-lineno">323</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L324"></a><tt class="py-lineno">324</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L325"></a><tt class="py-lineno">325</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L326"></a><tt class="py-lineno">326</tt>  <tt class="py-line"> </tt>
+<a name="L327"></a><tt class="py-lineno">327</tt>  <tt class="py-line">   </tt>
+<a name="L328"></a><tt class="py-lineno">328</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L329"></a><tt class="py-lineno">329</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L330"></a><tt class="py-lineno">330</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L331"></a><tt class="py-lineno">331</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L332"></a><tt class="py-lineno">332</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L333"></a><tt class="py-lineno">333</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L334"></a><tt class="py-lineno">334</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L335"></a><tt class="py-lineno">335</tt>  <tt class="py-line"> </tt>
+<a name="L336"></a><tt class="py-lineno">336</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L337"></a><tt class="py-lineno">337</tt>  <tt class="py-line"> </tt>
+<a name="L338"></a><tt class="py-lineno">338</tt>  <tt class="py-line"> </tt>
+<a name="L339"></a><tt class="py-lineno">339</tt>  <tt class="py-line"> </tt>
+<a name="L340"></a><tt class="py-lineno">340</tt>  <tt class="py-line"> </tt>
+<a name="L341"></a><tt class="py-lineno">341</tt>  <tt class="py-line"> </tt>
+<a name="JMI"></a><div id="JMI-def"><a name="L342"></a><tt class="py-lineno">342</tt> <a class="py-toggle" href="#" id="JMI-toggle" onclick="return toggle('JMI');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#JMI">JMI</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="JMI-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="JMI-expanded"><a name="L343"></a><tt class="py-lineno">343</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L344"></a><tt class="py-lineno">344</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the joint mutual information feature</tt> </tt>
+<a name="L345"></a><tt class="py-lineno">345</tt>  <tt class="py-line"><tt class="py-docstring">    selection algorithm. </tt> </tt>
+<a name="L346"></a><tt class="py-lineno">346</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L347"></a><tt class="py-lineno">347</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L348"></a><tt class="py-lineno">348</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L349"></a><tt class="py-lineno">349</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L350"></a><tt class="py-lineno">350</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L351"></a><tt class="py-lineno">351</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L352"></a><tt class="py-lineno">352</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L353"></a><tt class="py-lineno">353</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L354"></a><tt class="py-lineno">354</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L355"></a><tt class="py-lineno">355</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L356"></a><tt class="py-lineno">356</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L357"></a><tt class="py-lineno">357</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L358"></a><tt class="py-lineno">358</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L359"></a><tt class="py-lineno">359</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-33" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-33', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L360"></a><tt class="py-lineno">360</tt>  <tt class="py-line"> </tt>
+<a name="L361"></a><tt class="py-lineno">361</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L362"></a><tt class="py-lineno">362</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L363"></a><tt class="py-lineno">363</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L364"></a><tt class="py-lineno">364</tt>  <tt class="py-line"> </tt>
+<a name="L365"></a><tt class="py-lineno">365</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L366"></a><tt class="py-lineno">366</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L367"></a><tt class="py-lineno">367</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L368"></a><tt class="py-lineno">368</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L369"></a><tt class="py-lineno">369</tt>  <tt class="py-line"> </tt>
+<a name="L370"></a><tt class="py-lineno">370</tt>  <tt class="py-line">  <tt id="link-34" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-34', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-35" class="py-name" targets="Function feast.JMI()=feast-module.html#JMI"><a title="feast.JMI" class="py-name" href="#" onclick="return doclink('link-35', 'JMI', 'link-35');">JMI</a></tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L371"></a><tt class="py-lineno">371</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-36" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-36', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt id="link-37" class="py-name"><a title="feast.JMI" class="py-name" href="#" onclick="return doclink('link-37', 'JMI', 'link-35');">JMI</a></tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L372"></a><tt class="py-lineno">372</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L373"></a><tt class="py-lineno">373</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L374"></a><tt class="py-lineno">374</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L375"></a><tt class="py-lineno">375</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L376"></a><tt class="py-lineno">376</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L377"></a><tt class="py-lineno">377</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L378"></a><tt class="py-lineno">378</tt>  <tt class="py-line"> </tt>
+<a name="L379"></a><tt class="py-lineno">379</tt>  <tt class="py-line">   </tt>
+<a name="L380"></a><tt class="py-lineno">380</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L381"></a><tt class="py-lineno">381</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L382"></a><tt class="py-lineno">382</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L383"></a><tt class="py-lineno">383</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L384"></a><tt class="py-lineno">384</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L385"></a><tt class="py-lineno">385</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L386"></a><tt class="py-lineno">386</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L387"></a><tt class="py-lineno">387</tt>  <tt class="py-line"> </tt>
+<a name="L388"></a><tt class="py-lineno">388</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L389"></a><tt class="py-lineno">389</tt>  <tt class="py-line"> </tt>
+<a name="L390"></a><tt class="py-lineno">390</tt>  <tt class="py-line"> </tt>
+<a name="L391"></a><tt class="py-lineno">391</tt>  <tt class="py-line"> </tt>
+<a name="MIFS"></a><div id="MIFS-def"><a name="L392"></a><tt class="py-lineno">392</tt> <a class="py-toggle" href="#" id="MIFS-toggle" onclick="return toggle('MIFS');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#MIFS">MIFS</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="MIFS-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="MIFS-expanded"><a name="L393"></a><tt class="py-lineno">393</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L394"></a><tt class="py-lineno">394</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the MIFS algorithm.</tt> </tt>
+<a name="L395"></a><tt class="py-lineno">395</tt>  <tt class="py-line"><tt class="py-docstring">    beta = 1; gamma = 0;</tt> </tt>
+<a name="L396"></a><tt class="py-lineno">396</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L397"></a><tt class="py-lineno">397</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L398"></a><tt class="py-lineno">398</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L399"></a><tt class="py-lineno">399</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L400"></a><tt class="py-lineno">400</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L401"></a><tt class="py-lineno">401</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L402"></a><tt class="py-lineno">402</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L403"></a><tt class="py-lineno">403</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L404"></a><tt class="py-lineno">404</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L405"></a><tt class="py-lineno">405</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L406"></a><tt class="py-lineno">406</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L407"></a><tt class="py-lineno">407</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L408"></a><tt class="py-lineno">408</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L409"></a><tt class="py-lineno">409</tt>  <tt class="py-line"> </tt>
+<a name="L410"></a><tt class="py-lineno">410</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt id="link-38" class="py-name"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-38', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">,</tt> <tt class="py-name">n_select</tt><tt class="py-op">,</tt> <tt class="py-name">beta</tt><tt class="py-op">=</tt><tt class="py-number">0.0</tt><tt class="py-op">,</tt> <tt class="py-name">gamma</tt><tt class="py-op">=</tt><tt class="py-number">0.0</tt><tt class="py-op">)</tt> </tt>
+</div><a name="L411"></a><tt class="py-lineno">411</tt>  <tt class="py-line"> </tt>
+<a name="L412"></a><tt class="py-lineno">412</tt>  <tt class="py-line"> </tt>
+<a name="MIM"></a><div id="MIM-def"><a name="L413"></a><tt class="py-lineno">413</tt> <a class="py-toggle" href="#" id="MIM-toggle" onclick="return toggle('MIM');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#MIM">MIM</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="MIM-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="MIM-expanded"><a name="L414"></a><tt class="py-lineno">414</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L415"></a><tt class="py-lineno">415</tt>  <tt class="py-line"><tt class="py-docstring">    This function implements the MIM algorithm.</tt> </tt>
+<a name="L416"></a><tt class="py-lineno">416</tt>  <tt class="py-line"><tt class="py-docstring">    beta = 0; gamma = 0;</tt> </tt>
+<a name="L417"></a><tt class="py-lineno">417</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L418"></a><tt class="py-lineno">418</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L419"></a><tt class="py-lineno">419</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L420"></a><tt class="py-lineno">420</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L421"></a><tt class="py-lineno">421</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L422"></a><tt class="py-lineno">422</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L423"></a><tt class="py-lineno">423</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L424"></a><tt class="py-lineno">424</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L425"></a><tt class="py-lineno">425</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L426"></a><tt class="py-lineno">426</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L427"></a><tt class="py-lineno">427</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L428"></a><tt class="py-lineno">428</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L429"></a><tt class="py-lineno">429</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L430"></a><tt class="py-lineno">430</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-39" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-39', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L431"></a><tt class="py-lineno">431</tt>  <tt class="py-line"> </tt>
+<a name="L432"></a><tt class="py-lineno">432</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt id="link-40" class="py-name"><a title="feast.BetaGamma" class="py-name" href="#" onclick="return doclink('link-40', 'BetaGamma', 'link-7');">BetaGamma</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">,</tt> <tt class="py-name">n_select</tt><tt class="py-op">,</tt> <tt class="py-name">beta</tt><tt class="py-op">=</tt><tt class="py-number">0.0</tt><tt class="py-op">,</tt> <tt class="py-name">gamma</tt><tt class="py-op">=</tt><tt class="py-number">0.0</tt><tt class="py-op">)</tt> </tt>
+</div><a name="L433"></a><tt class="py-lineno">433</tt>  <tt class="py-line"> </tt>
+<a name="L434"></a><tt class="py-lineno">434</tt>  <tt class="py-line"> </tt>
+<a name="L435"></a><tt class="py-lineno">435</tt>  <tt class="py-line"> </tt>
+<a name="mRMR"></a><div id="mRMR-def"><a name="L436"></a><tt class="py-lineno">436</tt> <a class="py-toggle" href="#" id="mRMR-toggle" onclick="return toggle('mRMR');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#mRMR">mRMR</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">,</tt> <tt class="py-param">n_select</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="mRMR-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="mRMR-expanded"><a name="L437"></a><tt class="py-lineno">437</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L438"></a><tt class="py-lineno">438</tt>  <tt class="py-line"><tt class="py-docstring">    This funciton implements the max-relevance min-redundancy feature</tt> </tt>
+<a name="L439"></a><tt class="py-lineno">439</tt>  <tt class="py-line"><tt class="py-docstring">    selection algorithm. </tt> </tt>
+<a name="L440"></a><tt class="py-lineno">440</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L441"></a><tt class="py-lineno">441</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: data in a Numpy array such that len(data) = </tt> </tt>
+<a name="L442"></a><tt class="py-lineno">442</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations, and len(data.transpose()) = n_features</tt> </tt>
+<a name="L443"></a><tt class="py-lineno">443</tt>  <tt class="py-line"><tt class="py-docstring">    @type data: ndarray</tt> </tt>
+<a name="L444"></a><tt class="py-lineno">444</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: labels represented in a numpy list with </tt> </tt>
+<a name="L445"></a><tt class="py-lineno">445</tt>  <tt class="py-line"><tt class="py-docstring">        n_observations as the number of elements. That is </tt> </tt>
+<a name="L446"></a><tt class="py-lineno">446</tt>  <tt class="py-line"><tt class="py-docstring">        len(labels) = len(data) = n_observations.</tt> </tt>
+<a name="L447"></a><tt class="py-lineno">447</tt>  <tt class="py-line"><tt class="py-docstring">    @type labels: ndarray</tt> </tt>
+<a name="L448"></a><tt class="py-lineno">448</tt>  <tt class="py-line"><tt class="py-docstring">    @param n_select: number of features to select. (REQUIRED)</tt> </tt>
+<a name="L449"></a><tt class="py-lineno">449</tt>  <tt class="py-line"><tt class="py-docstring">    @type n_select: integer</tt> </tt>
+<a name="L450"></a><tt class="py-lineno">450</tt>  <tt class="py-line"><tt class="py-docstring">    @return: the features in the order they were selected. </tt> </tt>
+<a name="L451"></a><tt class="py-lineno">451</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: list</tt> </tt>
+<a name="L452"></a><tt class="py-lineno">452</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L453"></a><tt class="py-lineno">453</tt>  <tt class="py-line">  <tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt> <tt class="py-op">=</tt> <tt id="link-41" class="py-name"><a title="feast.check_data" class="py-name" href="#" onclick="return doclink('link-41', 'check_data', 'link-5');">check_data</a></tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">labels</tt><tt class="py-op">)</tt> </tt>
+<a name="L454"></a><tt class="py-lineno">454</tt>  <tt class="py-line"> </tt>
+<a name="L455"></a><tt class="py-lineno">455</tt>  <tt class="py-line">  <tt class="py-comment"># python values</tt> </tt>
+<a name="L456"></a><tt class="py-lineno">456</tt>  <tt class="py-line">  <tt class="py-name">n_observations</tt><tt class="py-op">,</tt> <tt class="py-name">n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">shape</tt> </tt>
+<a name="L457"></a><tt class="py-lineno">457</tt>  <tt class="py-line">  <tt class="py-name">output</tt> <tt class="py-op">=</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">zeros</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L458"></a><tt class="py-lineno">458</tt>  <tt class="py-line"> </tt>
+<a name="L459"></a><tt class="py-lineno">459</tt>  <tt class="py-line">  <tt class="py-comment"># cast as C types</tt> </tt>
+<a name="L460"></a><tt class="py-lineno">460</tt>  <tt class="py-line">  <tt class="py-name">c_n_observations</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_observations</tt><tt class="py-op">)</tt> </tt>
+<a name="L461"></a><tt class="py-lineno">461</tt>  <tt class="py-line">  <tt class="py-name">c_n_select</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L462"></a><tt class="py-lineno">462</tt>  <tt class="py-line">  <tt class="py-name">c_n_features</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_int</tt><tt class="py-op">(</tt><tt class="py-name">n_features</tt><tt class="py-op">)</tt> </tt>
+<a name="L463"></a><tt class="py-lineno">463</tt>  <tt class="py-line"> </tt>
+<a name="L464"></a><tt class="py-lineno">464</tt>  <tt class="py-line">  <tt id="link-42" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-42', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt class="py-name">mRMR_D</tt><tt class="py-op">.</tt><tt class="py-name">restype</tt> <tt class="py-op">=</tt> <tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt> <tt class="py-op">*</tt> <tt class="py-name">n_select</tt><tt class="py-op">)</tt> </tt>
+<a name="L465"></a><tt class="py-lineno">465</tt>  <tt class="py-line">  <tt class="py-name">features</tt> <tt class="py-op">=</tt> <tt id="link-43" class="py-name"><a title="feast.libFSToolbox" class="py-name" href="#" onclick="return doclink('link-43', 'libFSToolbox', 'link-4');">libFSToolbox</a></tt><tt class="py-op">.</tt><tt class="py-name">mRMR_D</tt><tt class="py-op">(</tt><tt class="py-name">c_n_select</tt><tt class="py-op">,</tt> </tt>
+<a name="L466"></a><tt class="py-lineno">466</tt>  <tt class="py-line">                   <tt class="py-name">c_n_observations</tt><tt class="py-op">,</tt> </tt>
+<a name="L467"></a><tt class="py-lineno">467</tt>  <tt class="py-line">                   <tt class="py-name">c_n_features</tt><tt class="py-op">,</tt>  </tt>
+<a name="L468"></a><tt class="py-lineno">468</tt>  <tt class="py-line">                   <tt class="py-name">data</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L469"></a><tt class="py-lineno">469</tt>  <tt class="py-line">                   <tt class="py-name">labels</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt><tt class="py-op">,</tt> </tt>
+<a name="L470"></a><tt class="py-lineno">470</tt>  <tt class="py-line">                   <tt class="py-name">output</tt><tt class="py-op">.</tt><tt class="py-name">ctypes</tt><tt class="py-op">.</tt><tt class="py-name">data_as</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">POINTER</tt><tt class="py-op">(</tt><tt class="py-name">c</tt><tt class="py-op">.</tt><tt class="py-name">c_double</tt><tt class="py-op">)</tt><tt class="py-op">)</tt> </tt>
+<a name="L471"></a><tt class="py-lineno">471</tt>  <tt class="py-line">                   <tt class="py-op">)</tt> </tt>
+<a name="L472"></a><tt class="py-lineno">472</tt>  <tt class="py-line"> </tt>
+<a name="L473"></a><tt class="py-lineno">473</tt>  <tt class="py-line">   </tt>
+<a name="L474"></a><tt class="py-lineno">474</tt>  <tt class="py-line">  <tt class="py-comment"># turn our output into a list</tt> </tt>
+<a name="L475"></a><tt class="py-lineno">475</tt>  <tt class="py-line">  <tt class="py-name">selected_features</tt> <tt class="py-op">=</tt> <tt class="py-op">[</tt><tt class="py-op">]</tt> </tt>
+<a name="L476"></a><tt class="py-lineno">476</tt>  <tt class="py-line">  <tt class="py-keyword">for</tt> <tt class="py-name">i</tt> <tt class="py-keyword">in</tt> <tt class="py-name">features</tt><tt class="py-op">.</tt><tt class="py-name">contents</tt><tt class="py-op">:</tt> </tt>
+<a name="L477"></a><tt class="py-lineno">477</tt>  <tt class="py-line">    <tt class="py-comment"># recall that feast was implemented with Matlab in mind, so the </tt> </tt>
+<a name="L478"></a><tt class="py-lineno">478</tt>  <tt class="py-line">    <tt class="py-comment"># authors assumed the indexing started a one; however, in Python </tt> </tt>
+<a name="L479"></a><tt class="py-lineno">479</tt>  <tt class="py-line">    <tt class="py-comment"># the indexing starts at zero. </tt> </tt>
+<a name="L480"></a><tt class="py-lineno">480</tt>  <tt class="py-line">    <tt class="py-name">selected_features</tt><tt class="py-op">.</tt><tt class="py-name">append</tt><tt class="py-op">(</tt><tt class="py-name">i</tt> <tt class="py-op">-</tt> <tt class="py-number">1</tt><tt class="py-op">)</tt> </tt>
+<a name="L481"></a><tt class="py-lineno">481</tt>  <tt class="py-line"> </tt>
+<a name="L482"></a><tt class="py-lineno">482</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-name">selected_features</tt> </tt>
+</div><a name="L483"></a><tt class="py-lineno">483</tt>  <tt class="py-line"> </tt>
+<a name="check_data"></a><div id="check_data-def"><a name="L484"></a><tt class="py-lineno">484</tt> <a class="py-toggle" href="#" id="check_data-toggle" onclick="return toggle('check_data');">-</a><tt class="py-line"><tt class="py-keyword">def</tt> <a class="py-def-name" href="feast-module.html#check_data">check_data</a><tt class="py-op">(</tt><tt class="py-param">data</tt><tt class="py-op">,</tt> <tt class="py-param">labels</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+</div><div id="check_data-collapsed" style="display:none;" pad="+++" indent="++++"></div><div id="check_data-expanded"><a name="L485"></a><tt class="py-lineno">485</tt>  <tt class="py-line">  <tt class="py-docstring">'''</tt> </tt>
+<a name="L486"></a><tt class="py-lineno">486</tt>  <tt class="py-line"><tt class="py-docstring">    Check dimensions of the data and the labels.  Raise and exception</tt> </tt>
+<a name="L487"></a><tt class="py-lineno">487</tt>  <tt class="py-line"><tt class="py-docstring">    if there is a problem.</tt> </tt>
+<a name="L488"></a><tt class="py-lineno">488</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L489"></a><tt class="py-lineno">489</tt>  <tt class="py-line"><tt class="py-docstring">    Data and Labels are automatically cast as doubles before calling the </tt> </tt>
+<a name="L490"></a><tt class="py-lineno">490</tt>  <tt class="py-line"><tt class="py-docstring">    feature selection functions</tt> </tt>
+<a name="L491"></a><tt class="py-lineno">491</tt>  <tt class="py-line"><tt class="py-docstring"></tt> </tt>
+<a name="L492"></a><tt class="py-lineno">492</tt>  <tt class="py-line"><tt class="py-docstring">    @param data: the data </tt> </tt>
+<a name="L493"></a><tt class="py-lineno">493</tt>  <tt class="py-line"><tt class="py-docstring">    @param labels: the labels</tt> </tt>
+<a name="L494"></a><tt class="py-lineno">494</tt>  <tt class="py-line"><tt class="py-docstring">    @return (data, labels): ndarray of floats</tt> </tt>
+<a name="L495"></a><tt class="py-lineno">495</tt>  <tt class="py-line"><tt class="py-docstring">    @rtype: tuple</tt> </tt>
+<a name="L496"></a><tt class="py-lineno">496</tt>  <tt class="py-line"><tt class="py-docstring">  '''</tt> </tt>
+<a name="L497"></a><tt class="py-lineno">497</tt>  <tt class="py-line"> </tt>
+<a name="L498"></a><tt class="py-lineno">498</tt>  <tt class="py-line">  <tt class="py-keyword">if</tt> <tt class="py-name">isinstance</tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">ndarray</tt><tt class="py-op">)</tt> <tt class="py-keyword">is</tt> <tt class="py-name">False</tt><tt class="py-op">:</tt> </tt>
+<a name="L499"></a><tt class="py-lineno">499</tt>  <tt class="py-line">    <tt class="py-keyword">raise</tt> <tt class="py-name">Exception</tt><tt class="py-op">(</tt><tt class="py-string">"data must be an numpy ndarray."</tt><tt class="py-op">)</tt> </tt>
+<a name="L500"></a><tt class="py-lineno">500</tt>  <tt class="py-line">  <tt class="py-keyword">if</tt> <tt class="py-name">isinstance</tt><tt class="py-op">(</tt><tt class="py-name">labels</tt><tt class="py-op">,</tt> <tt class="py-name">np</tt><tt class="py-op">.</tt><tt class="py-name">ndarray</tt><tt class="py-op">)</tt> <tt class="py-keyword">is</tt> <tt class="py-name">False</tt><tt class="py-op">:</tt> </tt>
+<a name="L501"></a><tt class="py-lineno">501</tt>  <tt class="py-line">    <tt class="py-keyword">raise</tt> <tt class="py-name">Exception</tt><tt class="py-op">(</tt><tt class="py-string">"labels must be an numpy ndarray."</tt><tt class="py-op">)</tt> </tt>
+<a name="L502"></a><tt class="py-lineno">502</tt>  <tt class="py-line"> </tt>
+<a name="L503"></a><tt class="py-lineno">503</tt>  <tt class="py-line">  <tt class="py-keyword">if</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">data</tt><tt class="py-op">)</tt> <tt class="py-op">!=</tt> <tt class="py-name">len</tt><tt class="py-op">(</tt><tt class="py-name">labels</tt><tt class="py-op">)</tt><tt class="py-op">:</tt> </tt>
+<a name="L504"></a><tt class="py-lineno">504</tt>  <tt class="py-line">    <tt class="py-keyword">raise</tt> <tt class="py-name">Exception</tt><tt class="py-op">(</tt><tt class="py-string">"data and labels must be the same length"</tt><tt class="py-op">)</tt> </tt>
+<a name="L505"></a><tt class="py-lineno">505</tt>  <tt class="py-line">   </tt>
+<a name="L506"></a><tt class="py-lineno">506</tt>  <tt class="py-line">  <tt class="py-keyword">return</tt> <tt class="py-number">1.0</tt><tt class="py-op">*</tt><tt class="py-name">data</tt><tt class="py-op">,</tt> <tt class="py-number">1.0</tt><tt class="py-op">*</tt><tt class="py-name">labels</tt> </tt>
+</div><a name="L507"></a><tt class="py-lineno">507</tt>  <tt class="py-line"> </tt><script type="text/javascript">
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