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<H1><A NAME="SECTION001320000000000000000">&#160;</A> 
<A NAME="function-specification">&#160;</A>
<BR>
Function Specification
</H1>

<P>
The  functions to be fitted to data are
linear combinations of a set of, so called, ``basic'' functions. Basic
functions are either defined in the system or defined by the user as
external FORTRAN routines. The actual combination of basic functions
is defined via an interactive editor, (MIDAS command <TT>EDIT/FIT</TT>) 

<P>
Basic functions are specified by the name, the independent variable(s) and
parameter(s), with optional guesses for the parameters, following the syntax:<BLOCKQUOTE>
<TT>name(var1[,</TT><IMG
 WIDTH="31" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
 SRC="img288.gif"
 ALT="$\ldots$"><TT>];par1[,</TT><IMG
 WIDTH="30" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
 SRC="img289.gif"
 ALT="$\ldots$"><TT>]) [par1=value] </TT><IMG
 WIDTH="31" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
 SRC="img290.gif"
 ALT="$\ldots$"></BLOCKQUOTE>The function name <TT>name</TT> defines the basic function used, it can be a
system function, as defined in the 
table&nbsp;<A HREF="node133.html#basic-fit-functions">8.1</A>, or a external function with
name <TT>USER00</TT>, ..., <TT>USER09</TT>. In this case, the corresponding 
file(s)
<TT>USER00.FOR</TT>, ..., <TT>USER09.FOR</TT> will exist in the working area
and will contain the definition of the routines following the syntax
described in  the next section. 

<P>
The number of independent variables of the function is determined by the string
<TT>var1[,</TT><IMG
 WIDTH="30" HEIGHT="21" ALIGN="BOTTOM" BORDER="0"
 SRC="img291.gif"
 ALT="$\ldots$"><TT>]</TT>. The actual names of the independent variables are
considered as dummy names but their number has to coincide with the
actual number of parameters of the function.
All the functions defined in a given fit <B>must</B>
have the same number of independent variables. 

<P>
Parameters are defined by unique names after the semicolon in the
function specification. Parameters are interpreted according to the position
and to the number of independent variables in the function. 

<P>
A parameter is generally given a first guess on the same line, 
as <TT>pari=value</TT>,
it can also be fixed to a given value or kept proportional to
another parameter.
The parameter is defined as fixed with the symbol @ immediately
following the value
as <TT>pari=value@</TT>. Linear constrains between parameters are defined as <TT>pari=parj*value</TT> or <TT>pari=parj/value</TT>. 

<P>
According to these rules, a one dimensional gaussian function is specified
with the <TT>EDIT/FIT</TT> command as<BLOCKQUOTE>
<TT>1 GAUSS(X;A,B,C) A=10. B=3200.@ C=1.</TT></BLOCKQUOTE>where <TT>X</TT> is the dummy name of the only independent variable, the first
parameter, defining the maximum of the function, is called <TT>A</TT>, initialized
to&nbsp;10, the second parameter, defining the position of the gaussian, is called
<TT>B</TT>, and its fixed value is&nbsp;3200 in world coordinates, and the FWHM is the
parameter <TT>C</TT>, with initial value&nbsp;1. 

<P>
A linear combination of a gaussian and a Cauchy distribution, centered at the
same position is specified as<BLOCKQUOTE>
<TT>1 GAUSS(X;A1,B1,C1) A1=10. B1=3200. C1=1. <BR>
2 CAUCHY(X;A2,B2,C2) A2=A1/10. B2=B1 C2=4.</TT></BLOCKQUOTE>in this case, the maximum of the Cauchy distribution is determined by the 
corresponding parameter of the Gaussian.

<P>
We include in table&nbsp;<A HREF="node133.html#basic-fit-functions">8.1</A> a summary of the system
basic functions; the actual mathematical expressions, with the meaning of the
function parameters are given in section&nbsp;<A HREF="node139.html#basic-functions">8.8</A>.

<P>
<BR>
<DIV ALIGN="CENTER"><A NAME="11366">&#160;</A>
<TABLE>
<CAPTION><STRONG>Table 8.1:</STRONG>
Basic Fit Functions</CAPTION>
<TR><TD>
  <DIV ALIGN="CENTER">
<TABLE CELLPADDING=3 BORDER="1" ALIGN="CENTER">
<TR><TD ALIGN="LEFT"><TT>POLY(X;A,B,...)     </TT></TD>
<TD ALIGN="LEFT">polynomial (1D, 2D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>LOG(X;A,B,C)        </TT></TD>
<TD ALIGN="LEFT">natural logarithm</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>EXP(X;A,B,C)        </TT></TD>
<TD ALIGN="LEFT">exponential</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>SIN(X;A,B,C)        </TT></TD>
<TD ALIGN="LEFT">sinus</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>TAN(X;A,B,C)        </TT></TD>
<TD ALIGN="LEFT">tangent</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>SINC(X;A,B,C)       </TT></TD>
<TD ALIGN="LEFT">sinc</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>SINCS(X;A,B,C)      </TT></TD>
<TD ALIGN="LEFT">sinc square</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>GAUSS(X;A,B,C)      </TT></TD>
<TD ALIGN="LEFT">(FWHM) Gaussian distribution (1D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>GAUSS(X,Y;A,B,C,D,E,F)    </TT></TD>
<TD ALIGN="LEFT">(FWHM) Gaussian distribution (2D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>GAUSSA(X;A,B,C)      </TT></TD>
<TD ALIGN="LEFT">(Standard) Gaussian distribution (1D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>CAUCHY(X;A,B,C)     </TT></TD>
<TD ALIGN="LEFT">Cauchy distribution (1D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>CAUCHY(X,Y;A,B,C,D,E,F)   </TT></TD>
<TD ALIGN="LEFT">Cauchy distribution (2D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>LORENTZ(X,Y;A,B,C,D,E,F)  </TT></TD>
<TD ALIGN="LEFT">Modified Cauchy (Lorentz) distribution</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>LAPLACE(X;A,B,C)    </TT></TD>
<TD ALIGN="LEFT">Laplace distribution</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>TRIANG(X;A,B,C)    </TT></TD>
<TD ALIGN="LEFT">Triangular distribution</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>POISSON(X;A,B,C)    </TT></TD>
<TD ALIGN="LEFT">Poisson distribution</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>IGAUSS(X;A,B,C)      </TT></TD>
<TD ALIGN="LEFT">Integrated (FWHM) Gaussian distribution (1D)</TD>
</TR>
<TR><TD ALIGN="LEFT"><TT>IGAUSSA(X;A,B,C)     </TT></TD>
<TD ALIGN="LEFT">Integrated (Standard) Gaussian distribution (1D)</TD>
</TR>
</TABLE></DIV>  
  <A NAME="basic-fit-functions">&#160;</A></TD></TR>
</TABLE>
</DIV>
<BR>

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<ADDRESS>
<I>Petra Nass</I>
<BR><I>1999-06-09</I>
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