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<h1>chronux
</h1>

<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="box"><strong>This library performs time-frequency analysis (mostly using the</strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="box"><strong>function chronux </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="fragment"><pre class="comment"> This library performs time-frequency analysis (mostly using the
 multi-taper spectral estimation method) of univariate and multivariate
 data, both for continuous processes such as LFP/EEG and for point
 processes such as spike times. Point process can either be stored as
 times or as a binned process of counts. The routines in this library
 are named differently for the three cases. For calculations
 that can be performed for each of the three data types, we use suffixes
 c, pb, or pt to refer to continuous, point process binned counts, or
 point process times. For example, the spectrum calculation is performed
 mtspectrumc for continuous processes, mtspectrumpb for a binned point
 process, and mtspectrumpt for a point process consisting of times. There
 are also routines for calculating hybrid quantities involving one continuous
 and one point process. These are suffixed in a similar manner. For
 example, coherencycpb calculates the coherency between a binned point process
 and a continuous process. 
 
 Certain variables are used repeatedly in this library.

 DATA
 data in most cases can be univariate or multivariate, and either point process, 
 or continuous.

      Continuous data: Continuous data is assumed to be a matrix with 
                       dimensions samples x channels/trials.

      Point Process: A single time series of spike times can be in the form of 
                     a column vector.
                     Multichannel/trial spike time data is not amenable to this 
                     storage format, since there are generally different 
                     number of spikes in each channel/trial. Instead, 
                     multichannel/trial spike data is stored in a structure 
                     array. A structure is a matlab data object with various 
                     fields. These fields contain the elements
                       e.g. The command data=struct('times',[]); creates an empty 
                            structure with field 'times'. Similarly, the command
                            data=struct('times',[1 2 3]); creates the structure with
                            the field 'times' containing integers 1, 2, and 3. 
        
                     We can also have a structure array (or an array of structures)
                     defined for example, by
                     data(1)=struct('times',rand(1,100)); and
                     data(2)=struct('times',rand(1,200));
                     This is a 2 dimensional structure array where the
                     first field is a 100 dimensional random vector, and
                     the second field is a 200 dimensional random vector.
                     This format allows storage of multichannel point
                     process times in a single variable data.
                     
                     The above holds for point processes stored as times.
                     If instead, the point processes are binned, then one
                     can use a matrix to represent them 
                     

      Summary: data - array of continuous data with dimensions time x channels
                      structural array of spike times with dimensions
                               equal to the number of channels
                      1d array of spike times as a column vector
                      array of binned spike counts with dimensions time x channels

 PARAMETERS:
 These are various parameters used in the spectral calculations. Since
 these parameters are used by most routines in Chronux, they are stored in
 a single structure params. The fields of params are

 tapers : precalculated tapers from dpss or in the one of the following
          forms: 
          (1) A numeric vector [TW K] where TW is the
              time-bandwidth product and K is the number of
              tapers to be used (less than or equal to
              2TW-1). 
          (2) A numeric vector [W T p] where W is the
              bandwidth, T is the duration of the data and p 
              is an integer such that 2TW-p tapers are used. In
              this form there is no default i.e. to specify
              the bandwidth, you have to specify T and p as
              well. Note that the units of W and T have to be
              consistent: if W is in Hz, T must be in seconds
              and vice versa. Note that these units must also
              be consistent with the units of params.Fs: W can
              be in Hz if and only if params.Fs is in Hz.
              The default is to use form 1 with TW=3 and K=5


 pad:   (padding factor for the FFT) - optional (can take values -1,0,1,2...). 
         -1 corresponds to no padding, 0 corresponds to padding
         to the next highest power of 2 etc.
              e.g. For N = 500, if PAD = -1, we do not pad; if PAD = 0, we pad the FFT
                   to 512 points, if pad=1, we pad to 1024 points etc.
                   Defaults to 0.

 Fs:sampling frequency.optional (default 1)


 fpass: frequencies in an fft calculation can range from 0 to Fs/2 where
        Fs is the sampling frequency. Sometimes it may be useful to
        compute fourier transforms (and resulting quantities like the
        spectrum over a smaller range of frequencies). This is specified
        by fpass, which can be in the form [fmin fmax] where fmin &gt;=0 and
        fmax&lt;=Fs/2. optional (default [0 Fs/2])

 err=[errtype p] calculates theoretical error bars (confidence levels)
                 when errtype=1 and jackknife error bars when errchk=2. In each case, the
                 error is calculated at a p value specified by p. -
                 optional (default 0)

 trialave: trialave controls whether or not to average over channels/trials for
           multichannel/trial analyses. trialave=0 (default) implies no trial
           averaging, trialave=1 implies that the quantity of interest is averaged
           over channels/trials. optional (default 0)
 
 Other parameters are discussed in individual routines as and when they
 are used.</pre></div>

<!-- crossreference -->
<h2><a name="_cross"></a>CROSS-REFERENCE INFORMATION <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
This function calls:
<ul style="list-style-image:url(../../matlabicon.gif)">
</ul>
This function is called by:
<ul style="list-style-image:url(../../matlabicon.gif)">
<li><a href="../../chronux_2_10/test/testAvg3.html" class="code" title="">testAvg3</a>	This is a calling routine to test & check out the power spectrum &</li><li><a href="../../chronux_2_10/test/testAvg4.html" class="code" title="">testAvg4</a>	This is a calling routine to test & check out the power spectrum &</li></ul>
<!-- crossreference -->


<h2><a name="_source"></a>SOURCE CODE <a href="#_top"><img alt="^" border="0" src="../../up.png"></a></h2>
<div class="fragment"><pre>0001 <a name="_sub0" href="#_subfunctions" class="code">function chronux</a>
0002 <span class="comment">% This library performs time-frequency analysis (mostly using the</span>
0003 <span class="comment">% multi-taper spectral estimation method) of univariate and multivariate</span>
0004 <span class="comment">% data, both for continuous processes such as LFP/EEG and for point</span>
0005 <span class="comment">% processes such as spike times. Point process can either be stored as</span>
0006 <span class="comment">% times or as a binned process of counts. The routines in this library</span>
0007 <span class="comment">% are named differently for the three cases. For calculations</span>
0008 <span class="comment">% that can be performed for each of the three data types, we use suffixes</span>
0009 <span class="comment">% c, pb, or pt to refer to continuous, point process binned counts, or</span>
0010 <span class="comment">% point process times. For example, the spectrum calculation is performed</span>
0011 <span class="comment">% mtspectrumc for continuous processes, mtspectrumpb for a binned point</span>
0012 <span class="comment">% process, and mtspectrumpt for a point process consisting of times. There</span>
0013 <span class="comment">% are also routines for calculating hybrid quantities involving one continuous</span>
0014 <span class="comment">% and one point process. These are suffixed in a similar manner. For</span>
0015 <span class="comment">% example, coherencycpb calculates the coherency between a binned point process</span>
0016 <span class="comment">% and a continuous process.</span>
0017 <span class="comment">%</span>
0018 <span class="comment">% Certain variables are used repeatedly in this library.</span>
0019 <span class="comment">%</span>
0020 <span class="comment">% DATA</span>
0021 <span class="comment">% data in most cases can be univariate or multivariate, and either point process,</span>
0022 <span class="comment">% or continuous.</span>
0023 <span class="comment">%</span>
0024 <span class="comment">%      Continuous data: Continuous data is assumed to be a matrix with</span>
0025 <span class="comment">%                       dimensions samples x channels/trials.</span>
0026 <span class="comment">%</span>
0027 <span class="comment">%      Point Process: A single time series of spike times can be in the form of</span>
0028 <span class="comment">%                     a column vector.</span>
0029 <span class="comment">%                     Multichannel/trial spike time data is not amenable to this</span>
0030 <span class="comment">%                     storage format, since there are generally different</span>
0031 <span class="comment">%                     number of spikes in each channel/trial. Instead,</span>
0032 <span class="comment">%                     multichannel/trial spike data is stored in a structure</span>
0033 <span class="comment">%                     array. A structure is a matlab data object with various</span>
0034 <span class="comment">%                     fields. These fields contain the elements</span>
0035 <span class="comment">%                       e.g. The command data=struct('times',[]); creates an empty</span>
0036 <span class="comment">%                            structure with field 'times'. Similarly, the command</span>
0037 <span class="comment">%                            data=struct('times',[1 2 3]); creates the structure with</span>
0038 <span class="comment">%                            the field 'times' containing integers 1, 2, and 3.</span>
0039 <span class="comment">%</span>
0040 <span class="comment">%                     We can also have a structure array (or an array of structures)</span>
0041 <span class="comment">%                     defined for example, by</span>
0042 <span class="comment">%                     data(1)=struct('times',rand(1,100)); and</span>
0043 <span class="comment">%                     data(2)=struct('times',rand(1,200));</span>
0044 <span class="comment">%                     This is a 2 dimensional structure array where the</span>
0045 <span class="comment">%                     first field is a 100 dimensional random vector, and</span>
0046 <span class="comment">%                     the second field is a 200 dimensional random vector.</span>
0047 <span class="comment">%                     This format allows storage of multichannel point</span>
0048 <span class="comment">%                     process times in a single variable data.</span>
0049 <span class="comment">%</span>
0050 <span class="comment">%                     The above holds for point processes stored as times.</span>
0051 <span class="comment">%                     If instead, the point processes are binned, then one</span>
0052 <span class="comment">%                     can use a matrix to represent them</span>
0053 <span class="comment">%</span>
0054 <span class="comment">%</span>
0055 <span class="comment">%      Summary: data - array of continuous data with dimensions time x channels</span>
0056 <span class="comment">%                      structural array of spike times with dimensions</span>
0057 <span class="comment">%                               equal to the number of channels</span>
0058 <span class="comment">%                      1d array of spike times as a column vector</span>
0059 <span class="comment">%                      array of binned spike counts with dimensions time x channels</span>
0060 <span class="comment">%</span>
0061 <span class="comment">% PARAMETERS:</span>
0062 <span class="comment">% These are various parameters used in the spectral calculations. Since</span>
0063 <span class="comment">% these parameters are used by most routines in Chronux, they are stored in</span>
0064 <span class="comment">% a single structure params. The fields of params are</span>
0065 <span class="comment">%</span>
0066 <span class="comment">% tapers : precalculated tapers from dpss or in the one of the following</span>
0067 <span class="comment">%          forms:</span>
0068 <span class="comment">%          (1) A numeric vector [TW K] where TW is the</span>
0069 <span class="comment">%              time-bandwidth product and K is the number of</span>
0070 <span class="comment">%              tapers to be used (less than or equal to</span>
0071 <span class="comment">%              2TW-1).</span>
0072 <span class="comment">%          (2) A numeric vector [W T p] where W is the</span>
0073 <span class="comment">%              bandwidth, T is the duration of the data and p</span>
0074 <span class="comment">%              is an integer such that 2TW-p tapers are used. In</span>
0075 <span class="comment">%              this form there is no default i.e. to specify</span>
0076 <span class="comment">%              the bandwidth, you have to specify T and p as</span>
0077 <span class="comment">%              well. Note that the units of W and T have to be</span>
0078 <span class="comment">%              consistent: if W is in Hz, T must be in seconds</span>
0079 <span class="comment">%              and vice versa. Note that these units must also</span>
0080 <span class="comment">%              be consistent with the units of params.Fs: W can</span>
0081 <span class="comment">%              be in Hz if and only if params.Fs is in Hz.</span>
0082 <span class="comment">%              The default is to use form 1 with TW=3 and K=5</span>
0083 <span class="comment">%</span>
0084 <span class="comment">%</span>
0085 <span class="comment">% pad:   (padding factor for the FFT) - optional (can take values -1,0,1,2...).</span>
0086 <span class="comment">%         -1 corresponds to no padding, 0 corresponds to padding</span>
0087 <span class="comment">%         to the next highest power of 2 etc.</span>
0088 <span class="comment">%              e.g. For N = 500, if PAD = -1, we do not pad; if PAD = 0, we pad the FFT</span>
0089 <span class="comment">%                   to 512 points, if pad=1, we pad to 1024 points etc.</span>
0090 <span class="comment">%                   Defaults to 0.</span>
0091 <span class="comment">%</span>
0092 <span class="comment">% Fs:sampling frequency.optional (default 1)</span>
0093 <span class="comment">%</span>
0094 <span class="comment">%</span>
0095 <span class="comment">% fpass: frequencies in an fft calculation can range from 0 to Fs/2 where</span>
0096 <span class="comment">%        Fs is the sampling frequency. Sometimes it may be useful to</span>
0097 <span class="comment">%        compute fourier transforms (and resulting quantities like the</span>
0098 <span class="comment">%        spectrum over a smaller range of frequencies). This is specified</span>
0099 <span class="comment">%        by fpass, which can be in the form [fmin fmax] where fmin &gt;=0 and</span>
0100 <span class="comment">%        fmax&lt;=Fs/2. optional (default [0 Fs/2])</span>
0101 <span class="comment">%</span>
0102 <span class="comment">% err=[errtype p] calculates theoretical error bars (confidence levels)</span>
0103 <span class="comment">%                 when errtype=1 and jackknife error bars when errchk=2. In each case, the</span>
0104 <span class="comment">%                 error is calculated at a p value specified by p. -</span>
0105 <span class="comment">%                 optional (default 0)</span>
0106 <span class="comment">%</span>
0107 <span class="comment">% trialave: trialave controls whether or not to average over channels/trials for</span>
0108 <span class="comment">%           multichannel/trial analyses. trialave=0 (default) implies no trial</span>
0109 <span class="comment">%           averaging, trialave=1 implies that the quantity of interest is averaged</span>
0110 <span class="comment">%           over channels/trials. optional (default 0)</span>
0111 <span class="comment">%</span>
0112 <span class="comment">% Other parameters are discussed in individual routines as and when they</span>
0113 <span class="comment">% are used.</span></pre></div>
<hr><address>Generated on Fri 12-Aug-2011 11:36:15 by <strong><a href="http://www.artefact.tk/software/matlab/m2html/" target="_parent">m2html</a></strong> &copy; 2005</address>
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