Loading README.rst +14 −19 Changes for README.rst: 14 added lines, 19 removed lines. Original line number Diff line number Diff line Loading @@ -19,25 +19,20 @@ AutoCNet :target: http://autocnet.readthedocs.org/en/latest/ :alt: Documentation Status R&D for automated control network generation. Automated sparse control network generation to support photogrammetric control of planetary image data. * Documentation: https://autocnet.readthedocs.org. Developer TODOs --------------- * Ensure installation requirements are met * Watch for the OpenCV dependency * Read comparing workflows (https://www.atlassian.com/git/tutorials/comparing-workflows) Credits --------- Tools used in rendering this package: * Cookiecutter_ * `cookiecutter-pypackage`_ .. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _`cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage Installation Instructions ------------------------- We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process. 1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompted to add conda to your BASH profile. 1. (Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this: * ``conda create -n <your_environment_name> python=3 && source activate <your_environment_name>`` 1. Bring up a command line and add three channels to your conda config (``~/condarc``): * ``conda config --add channels conda-forge`` * ``conda condig --add channels jlaura`` * ``conda config --add channels menpo`` 1. Finally, install autocnet: ``conda install -c jlaura autocnet-dev`` docs/installation.rst +9 −9 Changes for docs/installation.rst: 9 added lines, 9 removed lines. Original line number Diff line number Diff line Loading @@ -7,13 +7,15 @@ installation via the standard setup.py script. Via Conda --------- 1. Download and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompeted to add conda to your BASH profile. 2. Bring up a command line and add the ``conda-forge`` channel to your channel list: ``conda config --add channels conda-forge``. This adds an entry to your ``~/.condarc`` file. 3. Install plio: ``conda install -c jlaura autocnet`` 4. To update plio: ``conda update -c jlaura autocnet`` 1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompted to add conda to your BASH profile. 1. (Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this: * ``conda create -n <your_environment_name> python=3 && source activate <your_environment_name>`` 1. Bring up a command line and add three channels to your conda config (``~/condarc``): * ``conda config --add channels conda-forge`` * ``conda condig --add channels jlaura`` * ``conda config --add channels menpo`` 1. Finally, install autocnet: ``conda install -c jlaura autocnet-dev`` Via setup.py ------------ Loading Loading @@ -41,5 +43,3 @@ support automated testing, documentation builds, etc. 2. Install coveralls: ``pip install coveralls`` 3. Install the nbsphinx plugin: ``pip install nbshpinx`` 4. Install Jupyter for notebook support: ``conda install jupyter`` Loading
README.rst +14 −19 Changes for README.rst: 14 added lines, 19 removed lines. Original line number Diff line number Diff line Loading @@ -19,25 +19,20 @@ AutoCNet :target: http://autocnet.readthedocs.org/en/latest/ :alt: Documentation Status R&D for automated control network generation. Automated sparse control network generation to support photogrammetric control of planetary image data. * Documentation: https://autocnet.readthedocs.org. Developer TODOs --------------- * Ensure installation requirements are met * Watch for the OpenCV dependency * Read comparing workflows (https://www.atlassian.com/git/tutorials/comparing-workflows) Credits --------- Tools used in rendering this package: * Cookiecutter_ * `cookiecutter-pypackage`_ .. _Cookiecutter: https://github.com/audreyr/cookiecutter .. _`cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage Installation Instructions ------------------------- We suggest using Anaconda Python to install Autocnet within a virtual environment. These steps will walk you through the process. 1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompted to add conda to your BASH profile. 1. (Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this: * ``conda create -n <your_environment_name> python=3 && source activate <your_environment_name>`` 1. Bring up a command line and add three channels to your conda config (``~/condarc``): * ``conda config --add channels conda-forge`` * ``conda condig --add channels jlaura`` * ``conda config --add channels menpo`` 1. Finally, install autocnet: ``conda install -c jlaura autocnet-dev``
docs/installation.rst +9 −9 Changes for docs/installation.rst: 9 added lines, 9 removed lines. Original line number Diff line number Diff line Loading @@ -7,13 +7,15 @@ installation via the standard setup.py script. Via Conda --------- 1. Download and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompeted to add conda to your BASH profile. 2. Bring up a command line and add the ``conda-forge`` channel to your channel list: ``conda config --add channels conda-forge``. This adds an entry to your ``~/.condarc`` file. 3. Install plio: ``conda install -c jlaura autocnet`` 4. To update plio: ``conda update -c jlaura autocnet`` 1. [Download](https://www.continuum.io/downloads) and install the Python 3.x Miniconda installer. Respond ``Yes`` when prompted to add conda to your BASH profile. 1. (Optional) We like to sequester applications in their own environments to avoid any dependency conflicts. To do this: * ``conda create -n <your_environment_name> python=3 && source activate <your_environment_name>`` 1. Bring up a command line and add three channels to your conda config (``~/condarc``): * ``conda config --add channels conda-forge`` * ``conda condig --add channels jlaura`` * ``conda config --add channels menpo`` 1. Finally, install autocnet: ``conda install -c jlaura autocnet-dev`` Via setup.py ------------ Loading Loading @@ -41,5 +43,3 @@ support automated testing, documentation builds, etc. 2. Install coveralls: ``pip install coveralls`` 3. Install the nbsphinx plugin: ``pip install nbshpinx`` 4. Install Jupyter for notebook support: ``conda install jupyter``
