Metadata-Version: 1.2
Name: scipion-em-emready
Version: 3.1.1
Summary: EMReady: Improvement of cryo-EM maps by simultaneous local and non-local deep learning
Home-page: https://github.com/scipion-em/scipion-em-emready
Author: Jiahua He, Tao Li, Yunior C. Fonseca Reyna, Sheng-You Huang
Author-email: d201880053@hust.edu.cn, d202280084@hust.edu.cn, cfonseca@cnb.csic.es, huangsy@hust.edu.cn
License: UNKNOWN
Project-URL: Bug Reports, https://github.com/scipion-em/scipion-em-emready/issues
Project-URL: Source, https://github.com/scipion-em/scipion-em-emready/
Description: ==============
        EMReady plugin
        ==============
        
        `EMReady <http://huanglab.phys.hust.edu.cn/EMReady/>`_: Improvement of cryo-EM maps by simultaneous local and non-local deep learning.
        
        .. image:: https://img.shields.io/pypi/v/scipion-em-emready.svg
                :target: https://pypi.python.org/pypi/scipion-em-emready
                :alt: PyPI release
        
        .. image:: https://img.shields.io/pypi/l/scipion-em-emready.svg
                :target: https://pypi.python.org/pypi/scipion-em-emready
                :alt: License
        
        .. image:: https://img.shields.io/pypi/pyversions/scipion-em-emready.svg
                :target: https://pypi.python.org/pypi/scipion-em-emready
                :alt: Supported Python versions
        
        .. image:: https://img.shields.io/sonar/quality_gate/scipion-em_scipion-em-emready?server=https%3A%2F%2Fsonarcloud.io
                :target: https://sonarcloud.io/dashboard?id=scipion-em_scipion-em-emready
                :alt: SonarCloud quality gate
        
        .. image:: https://img.shields.io/pypi/dm/scipion-em-emready
                :target: https://pypi.python.org/pypi/scipion-em-emready
                :alt: Downloads
        
        Installation
        -------------
        
        You will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:
        
        a) Stable version
        
        .. code-block::
        
             scipion installp -p scipion-em-emready
        
        or through the **plugin manager** by launching Scipion and following **Configuration** >> **Plugins**
        
        b) Developer's version
        
           * download repository
        
            .. code-block::
        
                git clone -b devel https://github.com/scipion-em/scipion-em-emready.git
        
           * install
        
            .. code-block::
        
               scipion installp -p /path/to/scipion-em-emready --devel
        
        EMReady software will be installed automatically with the plugin but you can also use an existing installation by providing *EMREADY_ENV_ACTIVATION* and *EMREADY_HOME* (see below).
        
        **Important:** you need to have conda (miniconda3 or anaconda3) pre-installed to use this program.
        
        Configuration variables
        -----------------------
        *CONDA_ACTIVATION_CMD*: If undefined, it will rely on conda command being in the
        PATH (not recommended), which can lead to execution problems mixing scipion
        python with conda ones. One example of this could can be seen below but
        depending on your conda version and shell you will need something different:
        CONDA_ACTIVATION_CMD = eval "$(/extra/miniconda3/bin/conda shell.bash hook)"
        
        *EMREADY_ENV_ACTIVATION* (default = conda activate emready-2.0):
        Command to activate the EMReady environment.
        
        *EMREADY_HOME* (default = software/em/emready-2.0):
        Path with EMReady source code.
        
        Verifying
        ---------
        To check the installation, simply run the following Scipion test:
        
        ``scipion test emready.tests.test_protocol_sharpening.TestEMReadySharpening``
        
        Supported versions
        ------------------
        
        2.0
        
        Protocols
        ----------
        
        * sharpening
        
        References
        -----------
        
        1. He J, Li T, Huang S-Y. Improvement of cryo-EM maps by simultaneous local and non-local deep learning. Nature Communications, 2023; 14:3217.
        
Keywords: scipion electron-microscopy cryo-em structural-biology image-processing scipion-3.0 emready
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3
