Merge pull request #46 from phobson/minor-doc-typos

fix minor doc typos

Author: phobson

.travis.yml

@@ -24,9 +24,6 @@ matrix:
         - ARGS="--mpl --verbose --pep8"
 
 before_install:
-
-  # Here we just install Miniconda, which you shouldn't have to change.
-
   - wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
   - chmod +x miniconda.sh
   - ./miniconda.sh -b -p $HOME/miniconda
@@ -35,10 +32,6 @@ before_install:
   - conda install --yes nomkl
 
 install:
-
-  # We just set up a conda environment with the right Python version. This
-  # should not need changing.
-
   - conda create --yes -n test python=$TRAVIS_PYTHON_VERSION numpy matplotlib docopt requests pyyaml
   - source activate test
   - conda install --yes --channel=conda-forge pytest-mpl pytest-cov pytest-pep8 ${EXTRATESTERS}

conda.recipe/meta.yaml

@@ -1,13 +1,13 @@
 package:
   name: mpl-probscale
-  version: 0.2.2dev
+  version: 0.2.3
 
 source:
   path: ../
 
 build:
   script: python setup.py install
-  number: 1
+  number: 0
 
 requirements:
   build:

docs/conf.py

@@ -85,9 +85,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '0.2.2'
+version = '0.2.3'
 # The full version, including alpha/beta/rc tags.
-release = '0.2.2'
+release = '0.2.3'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

docs/tutorial/Makefile

@@ -140,7 +140,7 @@
     "Additionally, we'll compute the plotting positions two different but commone ways for each plot.\n",
     "\n",
     "First, in blue circles, we'll show the data with Weibull (α=0, β=0) plotting positions.\n",
-    "Weibull plotting positions are commonly use in my field, water resources engineering.\n",
+    "Weibull plotting positions are commonly use in fields such as hydrology and water resources engineering.\n",
     "\n",
     "In green squares, we'll use Cunnane (α=0.4, β=0.4) plotting positions.\n",
     "Cunnane plotting positions are good for normally distributed data and are the default values."
@@ -154,8 +154,8 @@
    },
    "outputs": [],
    "source": [
-    "w_opts = {'label': 'Weibull (α=0, β=0)',     'marker': 'o', 'markeredgecolor': 'b'}\n",
-    "c_opts = {'label': 'Cunnane (α=0.4, β=0.4)', 'marker': 's', 'markeredgecolor': 'g'}\n",
+    "w_opts = {'label': 'Weibull (a=0, b=0)',     'marker': 'o', 'markeredgecolor': 'b'}\n",
+    "c_opts = {'label': 'Cunnane (a=0.4, b=0.4)', 'marker': 's', 'markeredgecolor': 'g'}\n",
     "\n",
     "common_opts = {\n",
     "    'markerfacecolor': 'none',\n",
@@ -198,7 +198,7 @@
    },
    "outputs": [],
    "source": [
-    "h_opts = {'label': 'Hazen (α=0.5, β=0.5)', 'marker': '^', 'markeredgecolor': 'r'}\n",
+    "h_opts = {'label': 'Hazen (a=0.5, b=0.5)', 'marker': '^', 'markeredgecolor': 'r'}\n",
     "fig, (ax1, ax2) = pyplot.subplots(figsize=(10, 8), ncols=2, sharex=True, sharey=False)\n",
     "\n",
     "for dist, ax in zip([None, weibull], [ax1, ax2]):\n",
@@ -280,9 +280,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "probscale",
    "language": "python",
-   "name": "python3"
+   "name": "probscale"
   },
   "language_info": {
    "codemirror_mode": {

docs/tutorial/closer_look_at_plot_pos.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "## Overview\n",
     "\n",
-    "The `probscale.probplot` function lets you do a couple of things. They are:\n",
+    "The `probscale.probplot` function let's you do a couple of things. They are:\n",
     "\n",
     "  1. Creating percentile, quantile, or probability plots.\n",
     "  1. Placing your probability scale either axis.\n",
@@ -200,7 +200,7 @@
     "                         scatter_kws=dict(marker='.', linestyle='none', label='Bill Amount'))\n",
     "\n",
     "fig = probscale.probplot(tips['total_bill'], ax=ax2, plottype='qq', probax='y',\n",
-    "                         datascale='log', problabel='Normal Quantiles',datalabel='Total Bill (USD)',\n",
+    "                         datascale='log', problabel='Normal Quantiles', datalabel='Total Bill (USD)',\n",
     "                         scatter_kws=dict(marker='.', linestyle='none', label='Bill Amount'))\n",
     "ax.legend(loc='upper left')\n",
     "fig.tight_layout()\n",
@@ -708,9 +708,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "probscale",
    "language": "python",
-   "name": "python3"
+   "name": "probscale"
   },
   "language_info": {
    "codemirror_mode": {

docs/tutorial/closer_look_at_viz.ipynb

@@ -208,11 +208,11 @@
     "\n",
     "beta1 = stats.beta(a=3, b=2)\n",
     "ax2.set_xscale('prob', dist=beta1)\n",
-    "ax2.set_xlabel('Beta probability scale (α=3, β=2)')\n",
+    "ax2.set_xlabel('Beta probability scale (a=3, b=2)')\n",
     "\n",
     "beta2 = stats.beta(a=2, b=7)\n",
     "ax3.set_xscale('prob', dist=beta2)\n",
-    "ax3.set_xlabel('Beta probability scale (α=2, β=7)')\n",
+    "ax3.set_xlabel('Beta probability scale (a=2, b=7)')\n",
     "\n",
     "ax4.set_xticks(ax1.get_xticks()[12:-12])\n",
     "ax4.set_xlabel('Linear scale (for reference)')\n",
@@ -379,9 +379,9 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python [default]",
+   "display_name": "probscale",
    "language": "python",
-   "name": "python3"
+   "name": "probscale"
   },
   "language_info": {
    "codemirror_mode": {

docs/tutorial/getting_started.ipynb

@@ -0,0 +1,62 @@
+import os
+import glob
+
+import nbformat
+from nbconvert import RSTExporter, preprocessors
+
+
+def cache(nbfile):
+    basename, _ = os.path.splitext(nbfile)
+    bakfile = basename + '.bak'
+    with open(nbfile, 'r') as nb, open(bakfile, 'w') as bak:
+        bak.write(nb.read())
+    return bakfile
+
+
+def process(nbfile, processor):
+    meta = {'metadata': {'path': '.'}}
+    with open(nbfile, 'r') as nbf:
+        nbook = nbformat.read(nbf, as_version=4)
+
+    runner = processor(timeout=600, kernel_name='probscale')
+    runner.preprocess(nbook, meta)
+
+    with open(nbfile, 'w') as nbf:
+        nbformat.write(nbook, nbf)
+
+
+def convert(nbfile):
+    basename, _ = os.path.splitext(nbfile)
+    img_folder = basename + '_files'
+    os.makedirs(img_folder, exist_ok=True)
+    print("\tconverting " + nbfile)
+
+    with open(nbfile, 'r') as nb:
+        nbdata = nbformat.reads(nb.read(), as_version=4)
+
+    rst = RSTExporter()
+    body_raw, images = rst.from_notebook_node(nbdata)
+    body_final = body_raw.replace('.. image:: ', '.. image:: {}/'.format(img_folder))
+
+    with open(basename + '.rst', 'w') as rst_out:
+        rst_out.write(body_final)
+
+    for img_name, img_data in images['outputs'].items():
+        img_path = os.path.join(img_folder, img_name)
+        with open(img_path, 'wb') as img:
+            print('\twriting ' + img_path)
+            img.write(img_data)
+
+
+if __name__ == '__main__':
+    for nbfile in glob.glob('*.ipynb'):
+        bak = cache(nbfile)
+        success = False
+        try:
+            process(nbfile, preprocessors.ExecutePreprocessor)
+            convert(nbfile)
+            success = True
+        finally:
+            process(nbfile, preprocessors.ClearOutputPreprocessor)
+        if success:
+            os.remove(bak)