WIP: Added a sphinx-gallery

docs/source/conf.py

@@ -43,8 +43,26 @@
     'sphinx.ext.viewcode',
     'sphinx.ext.napoleon',
     'jupyter_sphinx.embed_widgets',
+    'sphinx_gallery.gen_gallery',
 ]
 
+sphinx_gallery_conf = {
+     # path to your examples scripts
+     'examples_dirs': '../../examples',
+     # path where to save gallery generated examples
+     'gallery_dirs': 'auto_examples',
+    #  'image_scrapers': ('matplotlib'),#, 'ipyvolume'),
+     'executor': 'notebook',
+    #  'show_memory': True,
+    'nbconvert': {
+        'snapshot': {
+            'port': 10101,
+            'page_opener_class': 'headless'
+        }
+    }
+}
+
+
 autosummary_generate = True
 
 # Add any paths that contain templates here, relative to this directory.
@@ -128,6 +146,14 @@
 # a list of builtin themes.
 #html_theme = 'alabaster'
 
+html_theme = 'default'
+try:
+	import sphinx_rtd_theme
+	html_theme = "sphinx_rtd_theme"
+	html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
+except:
+	print("rtd theme not found")
+
 # Theme options are theme-specific and customize the look and feel of a theme
 # further.  For a list of options available for each theme, see the
 # documentation.

docs/source/index.rst

@@ -7,3 +7,4 @@ bqplot: Plotting for Jupyter
    introduction
    usage
    api_documentation
+   auto_examples/index

examples/plot_lines_basic.py

@@ -0,0 +1,38 @@
+"""
+Line chart
+==========
+
+A simple line chart
+"""
+import numpy as np
+from bqplot import pyplot as plt
+
+np.random.seed(0)
+n = 200
+x = np.linspace(0.0, 10.0, n)
+y = np.cumsum(np.random.randn(n))
+
+
+fig = plt.figure(title='Line Chart')
+plt.plot(x, y)
+plt.show()
+
+################################################
+# Using the object model
+# ----------------------
+# A similar result can be obtained using the object model.
+
+import bqplot
+scales = {'x': bqplot.LinearScale(), 'y': bqplot.LinearScale()}
+
+scatter = bqplot.Lines(x=x, y=y, default_size=100, scales=scales)
+
+axis_x = bqplot.Axis(scale=scales['x'], grid_lines='solid', label='X')
+axis_y = bqplot.Axis(scale=scales['y'], orientation='vertical', tick_format='0.2f',
+            grid_lines='solid', label='Y')
+
+fig = bqplot.Figure(marks=[scatter], axes=[axis_x, axis_y], title='Line Chart')
+fig.interaction = bqplot.PanZoom(scales={'x': [scales['x']], 'y': [scales['y']]})
+fig
+
+

examples/plot_ohlc_basic.py

@@ -0,0 +1,36 @@
+"""
+Open-high-low-close chart
+=========================
+
+A simple OHLC chart
+"""
+import numpy as np
+from bqplot import pyplot as plt
+import datetime as dt
+
+
+dates = np.arange(dt.datetime(2014, 1, 2), dt.datetime(2014, 1, 30), dt.timedelta(days=1))
+
+prices = np.array([[ 187.21  ,  187.4   ,  185.2   ,  185.53  ],
+       [ 185.83  ,  187.35  ,  185.3   ,  186.64  ],
+       [ 187.15  ,  187.355 ,  185.3   ,  186.    ],
+       [ 186.39  ,  190.35  ,  186.38  ,  189.71  ],
+       [ 189.33  ,  189.4175,  187.26  ,  187.97  ],
+       [ 189.02  ,  189.5   ,  186.55  ,  187.38  ],
+       [ 188.31  ,  188.57  ,  186.28  ,  187.26  ],
+       [ 186.26  ,  186.95  ,  183.86  ,  184.16  ],
+       [ 185.06  ,  186.428 ,  183.8818,  185.92  ],
+       [ 185.82  ,  188.65  ,  185.49  ,  187.74  ],
+       [ 187.53  ,  188.99  ,  186.8   ,  188.76  ],
+       [ 188.04  ,  190.81  ,  187.86  ,  190.09  ],
+       [ 190.23  ,  190.39  ,  186.79  ,  188.43  ],
+       [ 181.28  ,  183.5   ,  179.67  ,  182.25  ],
+       [ 181.43  ,  183.72  ,  180.71  ,  182.73  ],
+       [ 181.25  ,  182.8141,  179.64  ,  179.64  ],
+       [ 179.605 ,  179.65  ,  177.66  ,  177.9   ],
+       [ 178.05  ,  178.45  ,  176.16  ,  176.85  ],
+       [ 175.98  ,  178.53  ,  175.89  ,  176.4   ],
+       [ 177.17  ,  177.86  ,  176.36  ,  177.36  ]])
+plt.figure(title='Open-high-low-close chart')
+plt.ohlc(dates, prices)
+plt.show()

examples/plot_pie_basic.py

@@ -0,0 +1,16 @@
+"""
+Pie chart
+=========
+
+A simple pie chart
+"""
+import numpy as np
+from bqplot import pyplot as plt
+
+np.random.seed(0)
+n = 5
+y = np.cumsum(np.random.randn(n))
+
+fig = plt.figure(title='Pie Chart')
+plt.pie(y)
+plt.show()

examples/plot_scatter_basic.py

@@ -0,0 +1,39 @@
+"""
+Scatter
+=======
+
+A simple scatter plot
+
+Using the pylab API
+-------------------
+"""
+import bqplot.pyplot as plt
+import numpy as np
+# create some random data
+N = 1000
+x, y = np.random.normal(0, 1, (2, N))
+
+fig = plt.figure(title='Scatter plot')
+s = plt.scatter(x, y, default_size=100)
+plt.show()
+
+
+################################################
+# Using the object model
+# ----------------------
+# A similar result can be obtained using the object model.
+
+
+import bqplot
+scales = {'x': bqplot.LinearScale(), 'y': bqplot.LinearScale()}
+
+scatter = bqplot.Scatter(x=x, y=y, default_size=100, scales=scales)
+
+axis_x = bqplot.Axis(scale=scales['x'], grid_lines='solid', label='X')
+axis_y = bqplot.Axis(scale=scales['y'], orientation='vertical', tick_format='0.2f',
+            grid_lines='solid', label='Y')
+
+fig = bqplot.Figure(marks=[scatter], axes=[axis_x, axis_y], title='Scatter plot')
+fig.interaction = bqplot.PanZoom(scales={'x': [scales['x']], 'y': [scales['y']]})
+fig
+