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Co-authored-by: Markus Neteler <neteler@mundialis.de>
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<title>GRASS GIS manual: r.maxent.lambdas</title>
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<h2>NAME</h2>
<em><b>r.maxent.lambdas</b></em> - Computes raw and/or logistic prediction maps from MaxEnt lambdas files
<h2>KEYWORDS</h2>
raster, MaxEnt, species distribution modelling
<h2>SYNOPSIS</h2>
<b>r.maxent.lambdas</b><br>
<b>r.maxent.lambdas help</b><br>
<b>r.maxent.lambdas</b> [-<b>rl</b>] <b>lambdas_file</b>=<em>string</em> <b>output_prefix</b>=<em>string</em> [<b>alias_file</b>=<em>string</em>] [<b>integer_output</b>=<em>integer</em>] [<b>output_mapcalc</b>=<em>string</em>] [--<b>overwrite</b>] [--<b>verbose</b>] [--<b>quiet</b>]

<h3>Flags:</h3>
<dl>
<dt><b>-r</b></dt>
<dd>Produce only raw output (both are computed by default).</dd>

<dt><b>-l</b></dt>
<dd>Produce only logistic output (both are computed by default).</dd>

<dt><b>--overwrite</b></dt>
<dd>Allow output files to overwrite existing files</dd>
<dt><b>--verbose</b></dt>
<dd>Verbose module output</dd>
<dt><b>--quiet</b></dt>
<dd>Quiet module output</dd>
</dl>
<h2>DESCRIPTION</h2>

<h3>Parameters:</h3>
<dl>
<dt><b>lambdas_file</b>=<em>string</em></dt>
<dd>MaxEnt lambdas-file to compute distribution-model from</dd>
The script is intended to compute raw and/or logistic prediction maps
from a lambdas file produced with MaxEnt 3.3.3e.<br>

<dt><b>output_prefix</b>=<em>string</em></dt>
<dd>Prefix for output raster maps</dd>
It will parse the specified lambdas-file from MaxEnt 3.3.3e and
translate it into an r.mapcalc-expression which is then stored in a
temporary file and finally piped to r.mapcalc. If alias names had been
used in MaxEnt, these alias names can automatically be replaced
according to a CSV-like file provided by the user. This file should
contain alias names in the first column and map names in the second
column, seperated by comma, without header. It should look e.g. like
this:
<br>

<dt><b>alias_file</b>=<em>string</em></dt>
<dd>CSV-file to replace alias names from MaxEnt by GRASS map names</dd>
<div class="code"><pre>
alias_1,map_1
alias_2,map_2
...,...
</pre></div>

<dt><b>integer_output</b>=<em>integer</em></dt>
<dd>Produce logistic integer output with this number of digits preserved</dd>
<dd>Default: <em>0</em></dd>

<dt><b>output_mapcalc</b>=<em>string</em></dt>
<dd>Save r.mapcalc expression to file</dd>
</dl>
<h2>DESCRIPTION</h2>
The script is intended to compute raw and/or logistic prediction maps from a lambdas file produced with MaxEnt 3.3.3e.<br>
It will parse the specified lambdas-file from MaxEnt 3.3.3e and translate it into an r.mapcalc-expression
which is then stored in a temporary file and finally piped to r.mapcalc. If alias names had been used in MaxEnt, these
alias names can automatically be replaced according to a CSV-like file provided by the user.
This file should contain alias names in the first column and map names in the second column, seperated by comma,
without header. It should look e.g. like this:<br>
<br>
<em>
alias_1,map_1<br>
alias_2,map_2<br>
...,...<br>
</em>
<br>
If such a CSV-file with alias names used in MaxEnt is provided, the alias names from MaxEnt are replaced by map names.<br>
<br>
A raw output map is always computed from the MaxEnt model as a first step. If logistic output is requested, the raw output
map can be deleted by the script ( using the l-flag). The logistic map can be produced as an integer map. To do so the user
has to specify the number of decimal places, that should be preserved in integer output.<br>
Optionally the map calculator expressions can be saved in a text file as especially the one for the raw output is likely to exceed
the space in the map history.
<p>
If such a CSV-file with alias names used in MaxEnt is provided, the alias
names from MaxEnt are replaced by map names.
<p>
A raw output map is always computed from the MaxEnt model as a first
step. If logistic output is requested, the raw output map can be
deleted by the script ( using the l-flag). The logistic map can be
produced as an integer map. To do so the user has to specify the number
of decimal places, that should be preserved in integer output.
<p>
Optionally the map calculator expressions can be saved in a text file
as especially the one for the raw output is likely to exceed the space
in the map history.

<h2>NOTES</h2>
This script works only if the maps containing the input data to MaxEnt are accessible from the current region.<br>
Due to conversion from double to floating-point in exp()-function, a loss of precision from the 7th decimal place onwards may occur
in the logistic output.

This script works only if the maps containing the input data to MaxEnt are
accessible from the current region.
<p>
Due to conversion from double to floating-point in exp()-function, a loss of
precision from the 7th decimal place onwards may occur in the logistic output.

<h2>SEE ALSO</h2>

r.out.maxent_swd, r.in.xyz<br>

MaxEnt 3.3.3e <a href="http://biodiversityinformatics.amnh.org/open_source/maxent/">http://biodiversityinformatics.amnh.org/open_source/maxent/</a><br>
Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee, Colin J. Yates. 2011: A statistical explanation of MaxEnt
Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee, Colin J. Yates. 2011: A statistical explanation of MaxEnt
for ecologists. Diversity and Distributions, (17):43-57, 2011.<br>
Wilson, Peter D. 2009: Guidelines for computing MaxEnt model output values from a lambdas file. (Avaliable at <a href="http://groups.google.com/group/MaxEnt">
http://groups.google.com/group/MaxEnt</a>)

Wilson, Peter D. 2009: Guidelines for computing MaxEnt model output values from a lambdas file. (Available at <a href="https://groups.google.com/group/MaxEnt">
https://groups.google.com/group/MaxEnt</a>)

Steven J. Phillips, Robert P. Anderson, Robert E. Schapire. 2006: Maximum entropy modeling of species geographic distributions.
Ecological Modelling, (190):231-259, 2006.<br>
Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. 2004: A maximum entropy approach to species distribution modeling. In: Proceedings

Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. 2004: A maximum entropy approach to species distribution modeling. In: Proceedings
of the Twenty-First International Conference on Machine Learning, p. 655-662, 2004.

<h2>AUTHOR</h2>

Stefan Blumentrath, Norwegian Institute for Nature Research (NINA), <a href="http://www.nina.no">http://www.nina.no</a>

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