From 48f00006d7129df7718305d59fdbd30aa41a0708 Mon Sep 17 00:00:00 2001 From: Daniel Emaasit Date: Mon, 26 Nov 2018 09:13:13 -0500 Subject: [PATCH 1/2] dependent packages were pinned too specifically --- pmlearn/__init__.py | 2 +- requirements-dev.txt | 6 +++--- requirements.txt | 18 +++++++++--------- 3 files changed, 13 insertions(+), 13 deletions(-) diff --git a/pmlearn/__init__.py b/pmlearn/__init__.py index 3e3d1ac..41a115e 100644 --- a/pmlearn/__init__.py +++ b/pmlearn/__init__.py @@ -10,7 +10,7 @@ See http://pymc-learn.org for complete documentation. """ -__version__ = '0.0.1.rc0' +__version__ = '0.0.1.rc2' __all__ = ['gaussian_process', 'linear_model', diff --git a/requirements-dev.txt b/requirements-dev.txt index 1fc7ced..4db3e1a 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -1,4 +1,4 @@ -CommonMark==0.5.4 +CommonMark>=0.5.4 flake8>=3.5.0 # gpflowopt>=1.1 jupyter-sphinx>=0.1.3 @@ -11,6 +11,6 @@ pytest-cov>=2.5.1 pytest>=3.0.7 recommonmark>=0.4.0 sphinx>=1.5.5 -sphinx-autobuild==0.7.1 -sphinx-rtd-theme==0.4.2 +sphinx-autobuild>=0.7.1 +sphinx-rtd-theme>=0.4.2 pymc_learn_sphinx_theme>=0.1.5 diff --git a/requirements.txt b/requirements.txt index 8efdd10..8b22fe9 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,13 +1,13 @@ future>=0.16.0 -joblib==0.11 -matplotlib==2.1.1 -numpy==1.13.1 -numpydoc==0.7.0 -pandas==0.21.1 -pymc3==3.4.1 -scikit-learn==0.19.1 -scipy==1.0.0 -seaborn==0.8.1 +joblib>=0.11 +matplotlib>=2.1.1 +numpy>=1.13.1 +numpydoc>=0.7.0 +pandas>=0.21.1 +pymc3>=3.4.1 +scikit-learn>=0.19.1 +scipy>=1.0.0 +seaborn>=0.8.1 six>=1.10.0 theano>=1.0.0 tqdm>=4.8.4 From 3b309bc8f7f5ab200e72d000fc2d2286bb4d8a5c Mon Sep 17 00:00:00 2001 From: Daniel Emaasit Date: Mon, 26 Nov 2018 10:48:54 -0500 Subject: [PATCH 2/2] install in conda env --- README.rst | 21 +++++++++++++++++++-- docs/install.rst | 10 ++++++++-- docs/modules/neural_networks.rst | 11 ++++++----- setup.cfg | 5 ++++- 4 files changed, 37 insertions(+), 10 deletions(-) diff --git a/README.rst b/README.rst index 6965abf..2a9e343 100644 --- a/README.rst +++ b/README.rst @@ -6,7 +6,7 @@ pymc-learn: Practical Probabilistic Machine Learning in Python :alt: Pymc-Learn logo :align: center -|Travis| |Coverage| |Docs| |License| |Pypi| |Binder| +|status| |Travis| |Coverage| |Docs| |License| |Pypi| |Binder| **Contents:** @@ -80,6 +80,13 @@ parameters and predictions. Quick Install ----------------- +``pymc-learn`` requires a working Python interpreter (2.7 or 3.5+). +It is recommend installing Python and key numerical libraries using the `Anaconda Distribution `_, +which has one-click installers available on all major platforms. + +Assuming a standard Python environment is installed on your machine +(including pip), ``pymc-learn`` itself can be installed in one line using pip: + You can install ``pymc-learn`` from PyPi using pip as follows: .. code-block:: bash @@ -97,6 +104,14 @@ Or from source as follows: .. CAUTION:: ``pymc-learn`` is under heavy development. + It is recommended installing ``pymc-learn`` in a Conda environment because it + provides `Math Kernel Library `_ (MKL) + routines to accelerate math functions. If you are having trouble, try using + a distribution of Python that includes these packages like + `Anaconda `_. + + + Dependencies ................ @@ -282,7 +297,7 @@ Models project: https://github.com/parsing-science/pymc3_models. changelog.rst cite.rst -.. |Binder| image:: https://mybinder.org/badge.svg +.. |Binder| image:: https://img.shields.io/badge/try-online-579ACA.svg?logo=data:image/png;base64,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 :target: https://mybinder.org/v2/gh/pymc-learn/pymc-learn/master?filepath=%2Fdocs%2Fnotebooks?urlpath=lab .. |Travis| image:: https://travis-ci.com/pymc-learn/pymc-learn.svg?branch=master @@ -307,3 +322,5 @@ Models project: https://github.com/parsing-science/pymc3_models. .. |Pypi| image:: https://badge.fury.io/py/pymc-learn.svg :target: https://badge.fury.io/py/pymc-learn + +.. |status| image:: https://img.shields.io/badge/Status-Beta-blue.svg \ No newline at end of file diff --git a/docs/install.rst b/docs/install.rst index 68a3fa5..9050891 100644 --- a/docs/install.rst +++ b/docs/install.rst @@ -1,8 +1,8 @@ Install pymc-learn =================== -``pymc-learn`` requires a working Python interpreter (2.7 or 3.3+). -It is recommend installing Python and key numerical libraries using the `Anaconda Distribution `_, +``pymc-learn`` requires a working Python interpreter (2.7 or 3.5+). +It is recommend installing Python and key numerical libraries using the `Anaconda Distribution `_, which has one-click installers available on all major platforms. Assuming a standard Python environment is installed on your machine @@ -25,6 +25,12 @@ Or from source as follows: .. CAUTION:: ``pymc-learn`` is under heavy development. + It is recommended installing ``pymc-learn`` in a Conda environment because it + provides `Math Kernel Library `_ (MKL) + routines to accelerate math functions. If you are having trouble, try using + a distribution of Python that includes these packages like + `Anaconda `_. + This also installs required dependencies including Theano. For alternative Theano installations (e.g., gpu), please see the diff --git a/docs/modules/neural_networks.rst b/docs/modules/neural_networks.rst index 965ecf8..67082ae 100644 --- a/docs/modules/neural_networks.rst +++ b/docs/modules/neural_networks.rst @@ -7,12 +7,13 @@ Neural network models (supervised) .. currentmodule:: pmlearn.neural_network -.. warning:: +.. NOTE:: - This implementation is not intended for large-scale applications. In particular, - scikit-learn offers no GPU support. For much faster, GPU-based implementations, - as well as frameworks offering much more flexibility to build deep learning - architectures, see :ref:`related_projects`. + Unlike scikit-learn, this implementation of neural networks in pymc-learn is + intended for large-scale applications. Pymc-learn relies on Theano for GPU + support. + + scikit-learn offers no GPU support. .. _multilayer_perceptron: diff --git a/setup.cfg b/setup.cfg index 38b775c..c291257 100644 --- a/setup.cfg +++ b/setup.cfg @@ -13,4 +13,7 @@ python_files = test_*.py [pydocstyle] add-ignore = D100,D104 -convention = numpy \ No newline at end of file +convention = numpy + +[bdist_wheel] +universal=1 \ No newline at end of file