INSTALL:

In order to use this package, you have to have at least those packages on your computer:

	1.	Compiler and linker
	 		e.g. gcc, ld

	2.	Ipopt. 
			Download it from https://projects.coin-or.org/Ipopt
		
		Numpy
			https://numpy.scipy.org/	
	
	3.	Python.h
			Usually you can use apt-get install python-dev (Debian family) or 
			download the source code from python.org
			

The install is very simple, just use

	make pyipopt

or 
	make install [might need superuser privilege as it will copy file to python dir]

[IMPORTANT]
	Before you type 
		make install,
	please exam that all the env variables in the makefile are correctly set. 
	
	Then, just issue
		make install

USE:
	If everything is OK by now, you can just issue
	
		python example.py
		
	Ipopt will solve a toy application for you. This python file is self-documented. You can also check the document in the python interactive shell. This module is extensively documented. 
	
	Ipopt can also solve problems w/o hessian estimation. example.py demonstrates the idea. If you provide the pyipopt.create function with the eval_h callback function as well as the apply_new callback function, ipopt will delegate the Hessian matrix calculation to you. Otherwise Ipopt will use it's own approximate hessian calculation.


---------------------skip this section if you don't use AMPL--------------------

Use it with AMPL

For people that use AMPL, the amplipopt is a very easy client that connect ampl and ipopt. Although it's also available in the ipopt package, here you can manipulate the model much easier in Python instead of in C/C++;

To use that, you have to download nlpy from sf.net and fix a bug in it. 

[BUG FIX IN NLPY]

Edit $NLPYHOME$/Src/_amplpy.c around line 454
change the code of 
                     pirow[ j ] = (long)i;
                     picol[ j ] = (long)(cg->varno);

to 

	  pirow[ cg->goff ] = (long)i;
	  picol[ cg->goff ] = (long)(cg->varno);

It's a bug in NLpy. AMPL return the sparse matrix in col-wise manner
	[@See Hook your solver with AMPL, page 12, the jacval description]

The sparse matrix is stored as the triple (row, col, values). Nlpy return the row, col tuple in the row-wise manner but AMPL set the values in a col-wise manner according to goff. The way to fix that is to output the row-col tuple also in the col-wise manner. 

Another way to fix this is to set AMPL's goff value to make it row-wise. 

trimloss.nl and test.nl are all test samples. You can just
	python amplipopt.py trimloss.nl 
to test if everything is OK

If everything goes OK, please close this poorly written document and enjoy pyipopt.
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----------------------Wait, I have an error......................--------------

Some people reported that they don't have -lg2c or can't find libipopt.so.0. Note that this is not the problem of pyipopt itself. Please install libg2c and copy libipopt.so.0 to the dir where ld can identify. 

Also, some people reported that when they use 

	import pyipopt

they got 

	import pyipopt
	ImportError: /usr/lib/libipopt.so.0: undefined symbol: _gfortran_XXX
		
If you get this error, it is VERY LIKELY that your ipopt library compiling is not correct. (Yes, I know you can use ipopt). Try to go to your 

"$IPOPT_DIR/Ipopt/examples/hs071_c/" directory and do a "make"


Please make sure that you can successfully compile and run this example. Pyipopt,as you might know, uses the same mechanism this example uses to call ipopt via C interface. Thus, if you can't go through this step, please don't proceed to send me a bug report, because I have no way to help you solve the problem with IPOPT itself :). My personal suggestion for this is the ipopt mailing list. 

Once you have everything ready and get the ipopt example correct, you can get start to compile pyipopt. 

I do apologize for the lacking of configure/make system. This is under construction. 

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For bug report and other suggestions, please contact me at 

youxu AT wustl.edu (Change AT to @)

You can simply call me Eric.