Add hello world example and check to tests

.travis.yml

@@ -43,6 +43,7 @@ jobs:
       - sudo apt-get -qq install pandoc
       - pip install -U -q -e .[develop,tensorflow,mxnet,torch]
     script:
+    - python -m doctest README.md
     - cd docs && make html && cd -
     - touch docs/_build/html/.nojekyll
     deploy:

README.md

@@ -11,17 +11,19 @@
 The HistFactory p.d.f. template [[CERN-OPEN-2012-016](https://cds.cern.ch/record/1456844)] is per-se independent of its implementation in ROOT and sometimes, it's useful to be able to run statistical analysis outside
 of ROOT, RooFit, RooStats framework.
 
-This repo is a pure-python implementation of that statistical model for multi-bin histogram-based analysis and its interval estimation is based on the asymptotic formulas of "Asymptotic formulae for likelihood-based tests of new physics" [[arxiv:1007.1727](https://arxiv.org/abs/1007.1727)]. The aim is also to support modern computational graph libraries such as PyTorch and Tensorflow in order to make use of features such as autodifferentiation and GPU acceleration.
+This repo is a pure-python implementation of that statistical model for multi-bin histogram-based analysis and its interval estimation is based on the asymptotic formulas of "Asymptotic formulae for likelihood-based tests of new physics" [[arxiv:1007.1727](https://arxiv.org/abs/1007.1727)]. The aim is also to support modern computational graph libraries such as PyTorch and TensorFlow in order to make use of features such as autodifferentiation and GPU acceleration.
 
 ## Hello World
 
 ```python
 >>> import pyhf
 >>> import pyhf.simplemodels
->>> p = pyhf.simplemodels.hepdata_like(signal_data=[12.,11.], bkg_data=[50.,52.], bkg_uncerts=[3.,7.])
->>> *_, CLs_obs,CLs_exp = pyhf.runOnePoint(1.0, [51, 48] + p.config.auxdata, p)
->>> print('obs: {} exp: {}'.format(CLs_obs, CLs_exp[2]))
-obs: [0.05290116] exp: [0.06445521]
+>>> import pyhf.utils
+>>> pdf = pyhf.simplemodels.hepdata_like(signal_data=[12.,11.], bkg_data=[50.,52.], bkg_uncerts=[3.,7.])
+>>> *_, CLs_obs,CLs_exp = pyhf.utils.runOnePoint(1.0, [51, 48] + pdf.config.auxdata, pdf)
+>>> print('Observed: {} Expected: {}'.format(CLs_obs, CLs_exp[2]))
+Observed: [0.05290116] Expected: [0.06445521]
+
 ```
 
 ## What does it support

docs/examples.rst

@@ -11,6 +11,7 @@ Notebooks:
 .. toctree::
    :maxdepth: 2
 
+   examples/notebooks/hello-world.ipynb
    examples/notebooks/binderexample/StatisticalAnalysis.ipynb
    examples/notebooks/Recast.ipynb
    examples/notebooks/ShapeFactor.ipynb

docs/examples/notebooks/hello-world.ipynb

@@ -0,0 +1,73 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Hello World, `pyhf` style"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pyhf\n",
+    "import pyhf.simplemodels\n",
+    "import pyhf.utils"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Observed: [0.05290116] Expected: [0.06445521]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/mcf/Code/GitHub/pyhf/pyhf/tensor/numpy_backend.py:82: RuntimeWarning: divide by zero encountered in log\n",
+      "  return np.log(tensor_in)\n",
+      "/home/mcf/Code/GitHub/pyhf/pyhf/tensor/numpy_backend.py:126: RuntimeWarning: divide by zero encountered in log\n",
+      "  return np.exp(n*np.log(lam)-lam-gammaln(n+1.))\n"
+     ]
+    }
+   ],
+   "source": [
+    "pdf = pyhf.simplemodels.hepdata_like(signal_data=[12.,11.], bkg_data=[50.,52.], bkg_uncerts=[3.,7.])\n",
+    "# *_, CLs_obs,CLs_exp = pyhf.utils.runOnePoint(1.0, [51, 48] + pdf.config.auxdata, pdf) # Python3\n",
+    "_, _, _, _, CLs_obs,CLs_exp = pyhf.utils.runOnePoint(1.0, [51, 48] + pdf.config.auxdata, pdf)\n",
+    "print('Observed: {} Expected: {}'.format(CLs_obs, CLs_exp[2]))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

tests/test_notebooks.py

@@ -9,6 +9,9 @@ def test_notebooks(tmpdir):
         'kernel_name': 'python{}'.format(sys.version_info.major)
     }
 
+    pm.execute_notebook(
+        'docs/examples/notebooks/hello-world.ipynb', **common_kwargs)
+
     pm.execute_notebook(
         'docs/examples/notebooks/ShapeFactor.ipynb', **common_kwargs)
     pm.execute_notebook('docs/examples/notebooks/multichannel-coupled-histo.ipynb',