I tried running the code:
library optmum, pgraph; optset; graphset;
and obviously it says I need to install the packages and all but I am not sure where exactly I am supposed to go to find these. I went to the Install application and package manager but neither seems to have the packages I am looking for. Ideally, I would like to have these packages in my library and run the command above. How do i proceed with this Gauss software?
pgraph comes standard with GAUSS, so you only need the optmum library. It is listed with the name of "op" and description of "Optmization 3.1".
If you don't own it, it will show up with a light red background to indicate that you don't own the package.
Related
Julia has a package for binary decision diagrams called CUDD_jll available from JuliaHub. The package is able to install and compile on the Apple M1 architecture. It does appear to install and compile on macOS v13 running Julia v1.82. But the user interface from an older package CUDD does not appear to be compatible with CUDD_jll.
What is needed is a test or examples revealing user commands for initializing cudd, defining logical variables, and the basic operations of AND, OR, NOT.
Does anyone have such information they will share?
_jll packages are generally not meant to be used directly, they're backend dependencies that will be automatically installed when you add a package that uses them.
In this case, CUDD.jl is the package you want to install and work with. That will automatically install CUDD_jll as a dependency and use it. Actually, the current CUDD.jl doesn't yet use CUDD_jll as a backend. It instead does its own download of the CUDD library, from a source that doesn't provide M1-compatible binaries. CUDD_jll is a recent effort to change that. It does provide binaries for the M1 architecture, but is yet to be merged in as a backend.
In the meantime, you can try ] add CUDD#update-to-yggdrasil to directly add the branch that uses CUDA_jll as the backend, and see if that works for you. (Once the PR gets merged, you can remove this branch-specific dependency and ] add CUDD like before.)
The Apple M1 system is not compatible with CUDD. My mistake, sorry.
I am trying to create my own customized linux image and I am trying to figure out how to install packages I need and found that there were multiple ways of installing packages.
I read through the yoctoproject manual and read through definitions of 'IMAGE_INSTALL' and 'FEATURE_PACKAGES' in which IMAGE_INSTALL 'specifies the packages to install into an image through image.bbclass' and FEATURE_PACKAGES 'Defines one or more packages to include in an image'. I have seen both used in the core-image.bbclass file and both use packagegroup-* so it's still unclear which is appropriate to use for what kinds of package installs.
Any human explanation of the difference between the two and what each is intended to be used for?
Answer from #Nayfe :
IMAGE_INSTALL is used if you want to install any and all packages.
FEATURE_PACKAGES is only used if you want to install packages if a FEATURE is enabled through the use of IMAGE_FEATURES.
Original Comment:
FEATURE_PACKAGES is intended to use in conjunction with IMAGE_FEATURES, as when an image feature xxx is enabled, corresponding packages defined in FEATURE_PACKAGES_xxx are added to image.
I'm a total newbie in Mac OS X, R and C++. Sound like a good mix, doesn't it?
I have the need to use RQuantLib, because I want to use some pricing functions part of the QuantLib package inside R, all on a Mac OS X-powered environment.
I've correctly installed QuantLib. I've already asked to the official QuantLib mailing list, and together we seem to have reached the conclusion that the problems I'm encountering are not related to my QuantLib installation, which seems ok and correctly configured.
So, I turned to R to try and solve the problem. Whenever I try to run ZeroCouponBond from within R, copying and pasting the first example provided with the official documentation, I get the following error:
"Error in DiscountCurve.default(discountCurve.param, list(flat = 0.05)) :
cannot find function errorOccured"
Now, I would rule any syntax.related problem out, since I'm copying the very same example present in the official help.
I don't know what I did wrong, but I know I need to find a solution at all costs. I've installed Rcpp, and the configuration seems really ok. Just one question I was not able to find an answert to: in my understanding, RQuantLib basically acts as a link between QuantLib and R. If that's correct, how can I tell RQuantLib where to look to find libQuantLib.a, that is, the compiled library resulting from the "make && sudo make install" commands performed while installing QuantLib itself?
Right, so, I've finally managed to get it to work.
First of all, I would like to say that things would have been much easier if a thorough, step-by-step installation procedure had been provided. I acknowledge I'm a total newbie, but I think other people approaching to R for the first time might encounter difficulties similar to those I had to overcome.
Anyway, this is what I did:
I've downloaded the .tar.gz source packages for both Rcpp and RQuantLib from cran.r-project.org
I've compiled them installing them from within the R environment. This is where I was making a mistake. Indeed, I was trying to compile them by invoking the configure installation script from the terminal; however, as Dirk said, the config script looks for QuantLib's quantlib-config script, and I didn't know the correct syntax to tell the configure script the correct path to QuantLib. Executing the procedure from R (by just installing the package) sorts out any problem, as all the dependencies are correctly located and loaded
So, that's pretty much it: just install the .tar.gz source package as you would do with the binary version, and everything should work ok.
Of course, I'm still curious to understand:
If it is possible to compile Rcpp and RQuantLib from the terminal; and
Why the binary version for Mac OS X will not work on my system, ie: why do I have to compile starting from the source code?
Thank you so much to anyone willing to answer my (probably naive and silly) questions. I'm eager to understand a bit more!
Thanks!
The RQuantLib package uses a tool called configure which determines the patch at package build-time. It looks for the script quantlib-config from which it learns about the location of libQuantLib.a.
First, install boost (brew install boost) and, secondly, Quantlib (currently at 1.7.1) by following instructions at http://quantlib.org/install/macosx.shtml:
cd QuantLib-1.x.y
./configure --enable-static --with-boost-include=/opt/local/include/ \
--with-boost-lib=/opt/local/lib/ --prefix=/opt/local/
make && sudo make install
It takes some time (~1 hour) for make.
Then in R or Rstudio, install packages Rcpp and RQuantlib. The later requires type="source" since only source package is available.
At this point, you should be able to use RQuantlib. The American Option value (SPY as of 4/1/2016, maturity 7/15/2016) can be calculated in R as
AmericanOption("put", strike=206, volatility=0.1525, underlying = 206.92, 0.021, 0.003, 73/252, engine="CrankNicolson")
For moderators: this question is about development of RPM based installer.
I'm developing packaging system for our software. We've designed our update management so that when we want to move to the new major version, we change RPM package to install all files into another directory (with another suffix) and change the package version. We keep the same name for the package (like: a-package-1.0.0 --> a-package-2.0.0). We want to install the new package keeping the old one to make user able to continue work with the old version while he moving to the new one.
So there is no file conflicts between our packages and RPM utility install them simultaneously without any issues (rpm -ivh ...). But Yum thinks that the new version is an update for the old one.
Is there a way to produce such RPM packages to make 'yum install a-package-1.0.0 a-package-2.0.0' installing them both? Maybe some flag in the package have to be set? I've found nothing.
Seems there is no way to install two RPM packages with the same name and without file conflicts usnig Yum.
So in my case I need to use some version suffix included into the package name.
I called RH and their preliminary answer is that there is no way to do this in YUM/RPM as this might cause confusion. After some discussion among their engineers, there does appear to be a way to do this, but they said it is cumbersome. I've asked them to send me their documentation (if any). I'm afraid you will need to call their customer service line and make the same request.
Here is the response from RH.
Thank you so much for your time on the phone today. You called asking if there was a way of installing different versions of tools like maven or java using yum to install them. After the engineers discussed it they have provided a document that shows you how to do this. I must say, if you do not have a log in to the customer portal, you will not be able to view the whole document.
How to switch Java Environment in Red Hat Enterprise Linux 5 and 6?
- https://access.redhat.com/solutions/21059
The engineers have also provided additional documents just for general use with Developer Toolset and Software Collections:
How to use Red Hat Software Collections (RHSCL) or Red Hat Developer Toolset (DTS)?
- https://access.redhat.com/solutions/472793
Developer Toolset and Red Hat Software Collections use in Red Hat Enterprise Linux 7
- https://access.redhat.com/solutions/915023
What's the difference between /etc/alternatives and the dynamic software collections framework?
- https://access.redhat.com/solutions/528643
If you do require further assistance, please provide me with a valid account number, login, or contract number, and I can get a case started and you will be able to be in direct contact with one of our Red Hat engineers.
edit: The real solution to this is now that OpenCV supports python 3. I'm leaving the details below for anyone who happens to be stuck with an old setup.
I'm trying to get OpenCV working with Python 3. A friend showed me ctypes-opencv that appears to work with Python 3. The problem is I totally can not figure out how to "install" or get any code working. I've followed all instructions I could find from a few people mentioning installs on google and none of those seemed to work or I couldn't even get through the basics that they mentioned.
I am just hacking around with the version of IDLE that came with Python 3. No IDE.
Start with OpenCV:
The only windows installer for OpenCV 2.1 is a visual studio installer. I assume that means that it installs files that make it easier to use in Visual Studio. However, does it also mean that I can't use that installer with Python 3? I tried the vs installer together with ctypes-opencv as below, and I got errors that the dlls were not in my path (but my path variable did include the OpenCV bin folder with dlls). Is this the wrong direction?
The apparent alternative is to build OpenCV myself. I tried following the directions here and all I get is "project files may be invalid" from the CMake gui application when pressing the "Configure" button. Same when following these hints from Stack Overflow. I'm suspicious that this is also the wrong direction since I am not currently using any of the tools that are listed in the CMake configure. Is this also the wrong direction?
Next ctypes-opencv:
I installed this and the installer recognizes Python3.1 and puts itself into the site-packages folder. If I try to run demos, it tells me the dlls are not in the path although they are, as mentioned above.
Summary:
I think I generally understand each piece here (code, compile, dll, imports, ...) but I do not know how all the pieces fit together and where I am going wrong. Can someone please tell me what steps or understanding I am missing here?
I get the feeling that I need to be reading a book or two to fill in the holes in my understanding of how all these pieces fit together. I wouldn't even know what area of books to get though so any suggestions there would be appreciated as well.
Python's ctypes is a wrapper around the opencv dll files, as long as you can point to the compiled libraries it doesn't matter what the source code is set up to be edited in. For windows I would simply run the installer, then try to load the dll with ctypes. If you can get that far, any other errors can be fixed by looking at the ctypes wrapper file and editing the load section to look like your test file.
Christoph Gohlke maintains Windows binaries for many Python packages, including the production version of OpenCV 3.0 with Python 3.x bindings, released 4 June 2015:
http://www.lfd.uci.edu/~gohlke/pythonlibs/#opencv
To install, just download the 64-bit or 32-bit .whl file appropriate for your system, then run pip install [filename]. Then the instruction import cv2 should work in your Python 3.x interpreter.
Yakiimo san, OpenCV 2.1 DLL can be loaded with ctypes. I have tested it.
p.s. I have set the C;\OpenCV2.1\bin in Env Path.