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README.md

Jon Sedar Personal Project

PyMC3 Examples pymc3_examples

2019Q4

Experimental models to demonstrate pymc3 capabilities.

Where suitable, I will submit these Notebooks for inclusion in the pymc3 documentation

Note:

  • Each Notebook is designed to be standalone with a suggested MVP condaenv install, but you can also just install the env for this project.
  • This project is hosted publically on GitHub.
  • This README is MacOS oriented

1. Setup Development Environment

1.1 Libraries, Compilers, IDEs

1.1.1 Continuum Anaconda Python 3.6.* 64bit

Main site: https://www.continuum.io/downloads

1.1.2 C++ compiler

e.g. for Mac OSX using Homebrew

$> brew update && brew upgrade `brew outdated` 
$> brew install gcc

...optional cleanup of old versions afterwards

$> brew cleanup

1.2 Configs, Dotfiles

1.2.1 Global git config ~/.gitconfig

[user]
    name = $YOUR_USERNAME
    email = $YOUR_EMAIL
[filter "lfs"]
    clean = git-lfs clean -- %f
    smudge = git-lfs smudge -- %f
    process = git-lfs filter-process
    required = true

1.2.2 Theano config ~/.theanorc

[global]
    device=cpu

1.2.3 Optional: jupyter configs if not already setup

$> jupyter notebook --generate-config
$> jupyter qtconsole --generate-config
$> jupyter nbconvert --generate-config

1.3 Clone Code and Create Environment

1.3.1 Git clone the repo to your workspace.

$> git clone https://github.com/jonsedar/pymc3_examples.git
$> cd pymc3_examples/

1.3.2 Setup a virtual environment for Python libraries

IMPORTANT NOTE: We're not using the latest python here because we want stability for the pymc3 and theano installs.

Pay extra attention to the .theanorc config

$> conda env create --file condaenv_pymc3_examples.yml
$> activate pymc3_examples

Cheat sheet of conda commands available online here.

1.3.3 Test installation of scientific packages

A quick and cheap way to confirm your binaries are good and the installation works!

1.3.3.1 Test BLAS / MKL config

View the BLAS / MKL install

$> python -c "import numpy as np; np.__config__.show()"

Output example...

mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/include']
blas_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/include']
blas_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/include']
lapack_mkl_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/include']
lapack_opt_info:
    libraries = ['mkl_rt', 'pthread']
    library_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/lib']
    define_macros = [('SCIPY_MKL_H', None), ('HAVE_CBLAS', None)]
    include_dirs = ['/Users/jon/anaconda/envs/pymc3_examples/include']

1.3.3.2 Test numpy install

$> python -c "import numpy as np; np.test()"

Example output...

7285 passed, 80 skipped, 167 deselected, 12 xfailed, 3 xpassed, 2 warnings in 355.51 seconds

1.3.3.3 Test scipy install

$> python -c "import scipy as sp; sp.test()"
... many tests will run and output a results summary e.g. ...

Example output...

14522 passed, 1274 skipped, 1225 deselected, 79 xfailed, 10 xpassed, 25 warnings in 777.53 seconds 

1.3.3.4 OPTIONAL Test pymc3 install

Method 1:

$> python -m pytest -xv --cov=pymc3 --cov-report=html pymc3/

Method 2:

Takes ~90mins on my Macbook 2017 :/

$> python -c "import pymc3 as pm; pm.test()"

Example output...

1.3.3.5 OPTIONAL Test theano install

Takes forever, see installation docs

Quicker:

$> python -c "import theano; theano.test()"

Alternative (takes ~3 hours)

$> theano-nose -s
... many tests will run and output a results summary e.g. ...

1.4 General Python Dev - Useful stuff

1.4.1 List large objects currently consuming RAM

As per https://stackoverflow.com/questions/40993626/list-memory-usage-in-ipython-and-jupyter

import sys

# These are the usual ipython objects, including this one you are creating
ipython_vars = ['In', 'Out', 'exit', 'quit', 'get_ipython', 'ipython_vars']

# Get a sorted list of the objects and their sizes
sorted([(x, sys.getsizeof(globals().get(x))) for x in dir() if not x.startswith('_') and x not in sys.modules and x not in ipython_vars], key=lambda x: x[1], reverse=True)

1.4.2 Clean up conda packages

Remove unused packages and tarballs etc as explained https://conda.io/docs/commands/conda-clean.html

$> conda clean -v -a

NOTE @2019-01-19 there's an open bug in conda on Windows that the ~/AppData/Local/Continuum/Anaconda3/pkgs/.trash directory needs manual emptying afterwards

1.4.3 Specify number of CPUs for MKL to use

Ought to provide a speed-boost for MKL operations (many numpy, scipy operations under the hood). See docs

>>> import mkl
>>> mkl.set_num_threads(2)
>>> mkl.get_max_threads()
2

1.4.4 MVP Jupyter Widget

Interactive widgets are cool. Beware potential issue with lax requirements. Ensure conda_*.yaml contains correct pairs of :

- ipywidgets==6.0.0
- widgetsnbextension==2.*
from ipywidgets import widgets
from IPython.display import display
text = widgets.Text()
text.on_submit(lambda x: print('hello {}'.format(x.value)))
display(text)

1.4.5 Basic debugging / introspection

Straight breakpoint:

import pdb; pdb.set_trace()

Or print, often helpful if you can't set a breakpoint

for att in dir(myobject):
    print(att, getattr(myobject, att))

Data

See data/README_DATA.md


General Notes

AOB


Jonathan Sedar © 2019

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