Sep 22, 2019 NanoGUI. NanoGUI is a minimalistic cross-platform widget library for OpenGL 3.x or higher. It supports automatic layout generation, stateful C11 lambdas callbacks, a variety of useful widget types and Retina-capable rendering on Apple devices thanks to NanoVG by Mikko Mononen. Python bindings of all functionality are provided using pybind11. Note: this repository is currently in.
Install OpenGL. Sudo apt-get update sudo apt-get install libsm-dev libxrender-dev build-essential libgl1-mesa-dev mesa-utils mesa-common-dev libglu1-mesa libglu1-mesa-dev sudo apt-get autoremove; Install Xming X Server for Windows. Don't forget the fonts and Mesa (OpenGL) modules!
GLEW provides efficient run-time mechanisms for determining which OpenGL extensions are supported on the target platform. OpenGL core and extension functionality is exposed in a single header file. Download gcc compiler for mac os x. GLEW has been tested on a variety of operating systems, including Windows, Linux, Mac OS X, FreeBSD, Irix, and Solaris.
Plugins extend the core functionality of IntelliJ IDEA. They:
provide integration with version control systems, application servers, and other tools
add coding assistance support for various languages and frameworks
boost your productivity with shortcut hints, live previews, File Watchers, and so on
help you learn a new programming language with coding exercises and verification
Open plugin settings
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
Use the Marketplace tab to browse and install plugins from the JetBrains Plugin Repository or from a custom plugin repository.
Use the Installed tab to browse installed plugins, enable, disable, update, or remove them. Disabling unnecessary plugins can increase performance.
Most plugins can be used with any JetBrains product. Some are limited only to commercial products. There are also plugins that require a separate license.
If a plugin depends on some other plugin, IntelliJ IDEA will notify you about the dependencies. If your project depends on certain plugins, add them to the list of required plugins.
If existing plugins do not provide some functionality that you need, you can create your own plugin for IntelliJ IDEA. For more information, see Develop your own plugins.
By default, IntelliJ IDEA includes a number of bundled plugins. You can disable bundled plugins, but they cannot be removed. You can install additional plugins from the plugin repository or from a local archive file (ZIP or JAR).
Mac Os X Versions
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
Find the plugin in the Marketplace and click Install.
To install a specific version, go to the plugin page in the JetBrains Plugin Repository, download and install it as described in Install plugin from disk. For example, you can do it if the most recent version of the plugin is broken.
After you download the plugin archive (ZIP or JAR), do the following:
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
On the Plugins page, click and then click Install Plugin from Disk.
Select the plugin archive file and click OK.
Click OK to apply the changes and restart the IDE if prompted.
You can also drag the downloaded plugin archive file and drop it into the IntelliJ IDEA Welcome screen.
You cannot remove bundled plugins.
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
Open the Installed tab and find the plugin that you want to remove.
Click next to the Disable/Enable button and select Uninstall from the drop-down menu.
If you need to remove a plugin without launching IntelliJ IDEA, you can delete it manually from the plugin directory.
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
Open the Installed tab, find and select the plugin that you want to disable.
Click Disable. The button will change to Enable.
Alternatively, you can use the checkboxes in the list of plugins or the Disable All buttons for plugin categories.
You can disable or enable all manually installed plugins at once (non-bundled) in the menu under .
Custom plugin repositories
By default, IntelliJ IDEA is configured to use plugins from the JetBrains Plugin Repository. This is where all the community plugins are hosted, and you are free to host your plugins there. However, if you develop plugins for internal use only, you can set up a custom plugin repository for them.
For information about setting up a custom plugin repository, see the IntelliJ Platform SDK documentation.
Once you set up your plugin repository, add it to IntelliJ IDEA:
In the Settings/Preferences dialog Ctrl+Alt+S, select Plugins.
On the Plugins page, click and then click Manage Plugin Repositories.
In the Custom Plugin Repositories dialog, click and specify your repository URL. It must point to the location of the updatePlugins.xml file. The file can be on the same server as your custom plugins, or on a dedicated one.
Click OK in the Custom Plugin Repositories dialog to save the list of plugin repositories.
Click OK in the Settings/Preferences dialog to apply the changes.
To browse the custom plugin repository, type repository: followed by the URL of the repository in the Marketplace tab of the Plugins page. For example:
Alternatively, you can replace the default JetBrains Plugin Repository with your custom repository URL. This can be helpful if you want only your custom repository plugins to be available from IntelliJ IDEA. To do this, edit the platform properties or VM options file as described below. For more information, see Advanced configuration.
From the main menu, select Help | Edit Custom Properties.
Add the idea.plugins.host property to the platform properties file. For example:
To add multiple URLs, separate them with semicolons ;.
Make sure that there is no plugins.jetbrains.com URL.
Restart IntelliJ IDEA.
If you replace the default plugin repository with a custom one, the search field on the Marketplace tab of the Plugins dialog will browse only the plugins in your custom repository.
Required plugins
A project may require plugins that provide support for certain technologies or frameworks. You can add such plugins to the list of required plugins for the current project, so that IntelliJ IDEA will verify that the plugins are installed and enabled. It will notify you if you forget about some plugin, or someone on your team is not aware about the dependency as they work on the project.
Add a required plugin for your current project
Make sure that the required plugin is installed.
In the Settings/Preferences dialog Ctrl+Alt+S, select Build, Execution, Deployment | Required Plugins.
On the Required Plugins page, click and select the plugin. Optionally, specify the minimum and maximum version of the plugin.
To specify the required version of IntelliJ IDEA itself, add IDE Core to the list of required plugins.
After the required plugin is added, when you open the project in IntelliJ IDEA, it will notify you if the plugin is disabled, not installed, or requires an update.
Click the link in the notification message to quickly enable, install, or update the required plugin.
Develop your own plugins
You can use any edition of IntelliJ IDEA to develop plugins. It provides an open API, a dedicated SDK, module, and run/debug configurations to help you.
The recommended workflow is to use Gradle. The old workflow using the internal IntelliJ IDEA build system is also supported. For more information, see the IntelliJ Platform SDK Developer Guide.
All Systems
Official releases are in reverse chronological order. The Continuous Build is rebuilt any time a developer makes a change they think users should have access too. It is normally reasonably stable, and will contain the latest pre-publication features. Alternatively, the highest numbered version will contain a stable and tested release. Windows10 users please see the instructions below before downloading.
Download EMAN2
Mac OS X
Note: the neural network code in EMAN2 works best on GPUs, which are available only on the Linux installations. It can still run on Mac, but will be quite slow.
If you have previously installed EMAN2:
Please remove or rename any existing installed EMAN2 folder you might have.
LD_LIBRARY_PATH, DYLD_LIBRARY_PATH and PYTHONPATH are NO LONGER USED, and should be removed if you have them set.
If you have any of these shell variables set for use with other software, it may be necessary to remove those settings as well. If the tests below fail after installation, this is the first thing to check.
Download eman2.X.MacOS.sh.
Run:
You will be prompted for a location to install EMAN2. Note that you cannot rename this folder after installation! You must reinstall if you wish to move the installation.
You will be asked if you want to add export PATH=.. to your .profile file.
If you use a different shell, such as tcsh or zsh, you may need to edit the appropriate file yourself.
You should not normally need to run the OpenMPI reinstallation scripts. The copy of OpenMPI/Pydusa now distributed with the binaries should work on Macs in most cases.
Don't forget to restart your shell if you changed the .profile or other scripts.
If you don't understand what the .profile instructions are talking about, this may help: https://stackoverflow.com/questions/7501678/set-environment-variables-on-mac-os-x-lion
Run these programs to see if the install worked:
If you have problems with any of these programs, the first thing to check is whether you have PYTHONPATH, LD_LIBRARY_PATH or DYLD_LIBRARY_PATH set in your shell. While used in previous versions of EMAN, these variables are no longer necessary. If they are set to make some other software package work, but they interfere with the programs above, you will have to unset them, and set them only when you need the other software.
Linux Workstations (not clusters)
Mac Os X 10.7 Download Free
If you have previously installed EMAN2:
Please remove or rename any existing installed EMAN2 folder you might have.
LD_LIBRARY_PATH, DYLD_LIBRARY_PATH and PYTHONPATH are NO LONGER USED, and should be removed if you have them set.
If you have any of these shell variables set for use with other software, it may be necessary to remove those settings as well. If the tests below fail after installation, this is the first thing to check.
Run:
You will be prompted for a location to install EMAN2. Note that you cannot rename this folder after installation! You must reinstall if you wish to move the installation.
You will be asked if you want to add export PATH=.. to your .profile file.
If you use a different shell, such as tcsh or zsh, you may need to edit the appropriate file yourself.
You should not normally need to run the OpenMPI reinstallation scripts. The copy of OpenMPI/Pydusa now distributed with the binaries should work on Linux workstations in most cases.
Don't forget to restart your shell if you changed the .profile or other scripts.
The new neural network based routines are much faster running on a GPU. If you have an NVidia graphics card, see Using the GPU section below.
Run these programs to see if the install worked:
If you have problems with any of these programs, the first thing to check is whether you have PYTHONPATH or LD_LIBRARY_PATH set in your shell. While used in previous versions of EMAN, these variables are no longer used, and in some cases may interfere with Anaconda. If they have been set to make some other software package work, but they interfere with the programs above, you will have to unset them, and set them only when you need the other software.
Specifically, if only the last command fails and you are using a Nvidia graphic card, it is likely caused by a graphic card driver incompatibility. Updating the Nvidia driver usually fix the problem. On recent Ubuntu systems, running apt-get install nvidia-current works. On other systems, you may need to follow the installation guide from Nvidia.
Linux Clusters
Follow the Linux workstation instructions above.
When using EMAN2/SPARX/SPHIRE on a cluster, the version of OpenMPI provided with the EMAN2.3 binaries may not be aware of the batch queuing system used to launch jobs on the cluster, and may only be able to run on one node at a time unless you follow the OpenMPI reinstallation instructions below. Follow only ONE of the sets of instructions below.
You will need conda-build for the instructions to work. Binaries include it, but for source installations, it needs to be installed.
If you have a file named .condarc in your home directory, temporarily rename or move it for the following instructions to work properly.
Reinstall pytz. Binary installation script installs it to a wrong location.
Use system OpenMPI
Most Linux clusters will have at least one OpenMPI installation on the cluster. In some cases there may be more than one, and you may have to select a 'module' to get the correct one. It is also critical that OpenMPI be compiled with the --disable-dlopen option. If you don't understand this statement, please consult with your cluster sysadmin.
Remove the OpenMPI we provided:
Make sure that the correct OpenMPI for your cluster is in your path. You should be able to run 'mpicc' and get a message like 'gcc: no input files'.
Rebuild Pydusa using the system installed OpenMPI.
Warning: If you see an error after this process like:
this means the fftw download failed. You will need to re-run this step, but first, delete the failed download : rm EMAN2/conda-bld/src_cache/fftw-3.3.6.tar.gz
Finally, install the compiled Pydusa:
Rebuild your own OpenMPI
This option insures that --disable-dlopen is used when compiling OpenMPI, but may lack some system-specific optimizations provided by your sysadmin.
It doesn’t matter whether you use macOS or Windows 10, it’s just a matter of time until your device will refuse to start, which could happen for many reasons, including (and not limited to) file corruption, hardware failure, and buggy update. Make-bootable-usb-mac-os-x-windows. If the unexpected happens with an Apple computer, you can use a macOS bootable USB with the installation media to repair it.This is one of the main reasons why you should always consider making a macOS bootable USB when your device is working properly. However, if it happens that none of your devices (MacBook, MacBook Air, MacBook Pro, iMac, Mac Pro or Mac Mini) aren’t working when you need them the most, then you can use a PC to rescue your Apple device. (If this works for you and want to support the developer, you can purchase the full version.).Connect the USB flash drive you want to use to fix your Mac. Quick note: This is a paid software, but it gives you a 15-day trial, which is more than enough time.
Remove the OpenMPI we provided:
Rebuild OpenMPI.
Rebuild Pydusa using the rebuilt OpenMPI:
Warning: If you see an error after this process like:
this means the fftw download failed. You will need to re-run this step, but first, delete the failed download : rm EMAN2/conda-bld/src_cache/fftw-3.3.6.tar.gz
Finally, install the compiled Pydusa:
Windows
We are finally able to provide 64 bit Windows binaries for EMAN2, however, please see the Windows 10- Linux/Bash shell option below for what may be a better alternative. Notes:
SPARX/SPHIRE are not supported.
EMAN2 functionality may not be complete using this first approach. You may get more complete functionality, but with some additional effort using the Linux/Bash shell approach below.
Even for EMAN2, Windows support remains somewhat marginal, and is provided primarily for utility functions and basic GUI tools, like micrograph evaluation and particle picking. Complete refinements may not work well under Windows. You are welcome to ask questions in the mailing list, but there may be limited help we can provide because we simply don't have Windows machines around for testing.
Native Win7/10 64 bit
Download eman2.X.win64.exe.
Launch the installer, and answer any security questions you are prompted for.
Start a command prompt by clicking Start menu and typing cmd.exe in the dialog at the bottom.
On the command prompt, type
Close the command prompt and open a new one.
In most cases you will want to install: Python Launcher.
Run these programs to see if the install worked:
Windows 10 - Linux/Bash shell
Windows 10 includes an embedded Ubuntu Linux environment. It is possible to run the EMAN2 Linux binaries within this Win10 environment, but you will need to install some additional dependencies to do so. Also, you will effectively be running at a Linux command prompt, so you will have to become a bit familiar with Linux to do this, but it does avoid installing an additional operating system on your machine.
Install 'Bash on Windows 10', https://www.howtogeek.com/249966/how-to-install-and-use-the-linux-bash-shell-on-windows-10/.
When prompted to set a user name, enter root. This should give you an account without a password.
Install OpenGL and X Server, set environment variables
Install OpenGL.
Install Xming X Server for Windows.
Don't forget the fonts and Mesa (OpenGL) modules! If it seems to work, but the letters are black boxes, or you have other visual artifacts, the problem is probably with OpenGL support.
Set environment variables.
Download and install eman2.X.linux64.centos7.sh.
Start X Server before running eman2 programs.
Run these programs to see if the install worked:
Using the GPU
Currently, the GPU is only used for neural network operations in tomogram annotation and in particle picking. It provides a ~10 fold or more speed up in neural network training. The new GPU developments are currently based on TensorFlow. From about 2006-2012 EMAN2 had its own internal CUDA code, which could be compiled into the C++ library. This has been deprecated, and likely no longer works, though the code is still present. We are working on a new GPU support strategy moving forward.
Note that due to the NumPy version in the 2.2 release, we are still using the 'old' GPU backend for compatibility (i.e. NOT the libgpuarray backend), so be sure to use device=gpu in your .theanorc. Hopefully this will change in the 2.21 update (unfortunately it did not..but it is upgraded in the daily build newer than 2.21).
On a freshly installed Ubuntu 16.10, an easy way to install the GPU support is to run the following command after successful binary installation.
If you are using a new GPU (like GTX1080 or better), you may need the newest version of CUDA to support the hardware. The following command should work.
If this does not work, you may consider downloading the latest CUDA from Nvidia through the following link and follow their instruction to install. https://developer.nvidia.com/cuda-downloads
After the CUDA installation (run 'nvcc --version' to check if it works), create a text file called .theanorc in your $HOME directory with the following content:
Then try running any neural network related program or simply run e2.py then import theano. If you see print out message like Using gpu device ******* (CNMeM is disabled, cuDNN ****), it means the GPU is now being used. For other system (or if the guide above does not work), you may follow the instruction from Theano and Nvidia. Keep in mind that CUDA installation can be a painful process on some computers especially when some of the hardware are old. CUDA also has internal incompatibility issue with newer version of gcc, so it might also break other software you have installed. So be careful and good luck..
CUDA 9.0 support
(requires EMAN2.21 or newer)
In Theano, we now support CUDA9.0 and the gpuarray backend. To upgrade to CUDA9.0, you will need:
Latest version of EMAN2 from GitHub (2017-10-25 or later).
Edit ~/.theanorc file to:
Upgrade Theano to latest GitHub version:
Upgrade pygpu
The latest Theano tries to use CuDNN by default. CuDNN speeds up neural network training, although the improvement is not very significant for the size of networks we are using. So you need to either install the latest CuDNN from Nvidia (https://developer.nvidia.com/cudnn), or disable it by adding this to ~/.theanorc
If you get a very long string of errors a few seconds after trying to train a network, and see references to 'narrowing' in the errors, this probably means your C++ compiler is newer than Theano expects. You can try adding the following to your .theanorc file: