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Merge pull request #275 from plotly/distplot
Distplot
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‎optional-requirements.txt

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@@ -19,3 +19,6 @@ ipython[all]
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## pandas deps for some matplotlib functionality ##
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pandas
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## scipy deps for some FigureFactory functions ##
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scipy

‎plotly/tests/test_core/test_tools/test_figure_factory.py

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@@ -686,3 +686,22 @@ def test_datetime_candlestick(self):
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self.assertEqual(candle, exp_candle)
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# class TestDistplot(TestCase):
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# def test_scipy_import_error(self):
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# # make sure Import Error is raised when _scipy_imported = False
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# hist_data = [[1.1, 1.1, 2.5, 3.0, 3.5,
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# 3.5, 4.1, 4.4, 4.5, 4.5,
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# 5.0, 5.0, 5.2, 5.5, 5.5,
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# 5.5, 5.5, 5.5, 6.1, 7.0]]
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# group_labels = ['distplot example']
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# self.assertRaisesRegexp(ImportError,
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# "FigureFactory.create_distplot requires scipy",
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# tls.FigureFactory.create_distplot,
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# hist_data, group_labels)
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‎plotly/tests/test_optional/test_opt_tracefactory.py

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import numpy as np
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class TestDistplot(TestCase):
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def test_wrong_curve_type(self):
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# check: PlotlyError (and specific message) is raised if curve_type is
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# not 'kde' or 'normal'
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kwargs = {'hist_data': [[1, 2, 3]], 'group_labels': ['group'],
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'curve_type': 'curve'}
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self.assertRaisesRegexp(PlotlyError, "curve_type must be defined as "
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"'kde' or 'normal'",
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tls.FigureFactory.create_distplot, **kwargs)
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def test_wrong_histdata_format(self):
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# check: PlotlyError if hist_data is not a list of lists or list of
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# np.ndarrays (if hist_data is entered as just a list the function
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# will fail)
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kwargs = {'hist_data': [1, 2, 3], 'group_labels': ['group']}
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self.assertRaises(PlotlyError, tls.FigureFactory.create_distplot,
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**kwargs)
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def test_unequal_data_label_length(self):
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kwargs = {'hist_data': [[1, 2]], 'group_labels': ['group', 'group2']}
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self.assertRaises(PlotlyError, tls.FigureFactory.create_distplot,
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**kwargs)
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kwargs = {'hist_data': [[1, 2], [1, 2, 3]], 'group_labels': ['group']}
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self.assertRaises(PlotlyError, tls.FigureFactory.create_distplot,
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**kwargs)
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def test_simple_distplot(self):
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# we should be able to create a single distplot with a simple dataset
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# and default kwargs
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dp = tls.FigureFactory.create_distplot(hist_data=[[1, 2, 2, 3]],
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group_labels=['distplot'])
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expected_dp_layout = {'barmode': 'overlay',
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'hovermode': 'closest',
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'legend': {'traceorder': 'reversed'},
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'xaxis1': {'anchor': 'y2', 'domain': [0.0, 1.0], 'zeroline': False},
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'yaxis1': {'anchor': 'free', 'domain': [0.35, 1], 'position': 0.0},
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'yaxis2': {'anchor': 'x1',
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'domain': [0, 0.25],
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'dtick': 1,
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'showticklabels': False}}
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self.assertEqual(dp['layout'], expected_dp_layout)
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expected_dp_data_hist = {'autobinx': False,
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'histnorm': 'probability',
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'legendgroup': 'distplot',
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'marker': {'color': 'rgb(31, 119, 180)'},
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'name': 'distplot',
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'opacity': 0.7,
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'type': 'histogram',
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'x': [1, 2, 2, 3],
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'xaxis': 'x1',
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'xbins': {'end': 3.0, 'size': 1.0, 'start': 1.0},
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'yaxis': 'y1'}
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self.assertEqual(dp['data'][0], expected_dp_data_hist)
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expected_dp_data_rug = {'legendgroup': 'distplot',
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'marker': {'color': 'rgb(31, 119, 180)',
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'symbol': 'line-ns-open'},
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'mode': 'markers',
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'name': 'distplot',
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'showlegend': False,
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'text': None,
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'type': 'scatter',
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'x': [1, 2, 2, 3],
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'xaxis': 'x1',
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'y': ['distplot', 'distplot',
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'distplot', 'distplot'],
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'yaxis': 'y2'}
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self.assertEqual(dp['data'][2], expected_dp_data_rug)
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def test_distplot_more_args(self):
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# we should be able to create a distplot with 2 datasets no
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# rugplot, defined bin_size, and added title
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hist1_x = [0.8, 1.2, 0.2, 0.6, 1.6,
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-0.9, -0.07, 1.95, 0.9, -0.2,
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-0.5, 0.3, 0.4, -0.37, 0.6]
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hist2_x = [0.8, 1.5, 1.5, 0.6, 0.59,
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1.0, 0.8, 1.7, 0.5, 0.8,
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-0.3, 1.2, 0.56, 0.3, 2.2]
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hist_data = [hist1_x] + [hist2_x]
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group_labels = ['2012', '2013']
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dp = tls.FigureFactory.create_distplot(hist_data, group_labels,
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show_rug=False, bin_size=.2)
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dp['layout'].update(title='Dist Plot')
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expected_dp_layout = {'barmode': 'overlay',
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'hovermode': 'closest',
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'legend': {'traceorder': 'reversed'},
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'title': 'Dist Plot',
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'xaxis1': {'anchor': 'y2', 'domain': [0.0, 1.0],
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'zeroline': False},
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'yaxis1': {'anchor': 'free', 'domain': [0.0, 1],
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'position': 0.0}}
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self.assertEqual(dp['layout'], expected_dp_layout)
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expected_dp_data_hist_1 = {'autobinx': False,
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'histnorm': 'probability',
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'legendgroup': '2012',
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'marker': {'color': 'rgb(31, 119, 180)'},
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'name': '2012',
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'opacity': 0.7,
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'type': 'histogram',
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'x': [0.8, 1.2, 0.2, 0.6, 1.6, -0.9, -0.07,
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1.95, 0.9, -0.2, -0.5, 0.3, 0.4,
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-0.37, 0.6],
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'xaxis': 'x1',
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'xbins': {'end': 1.95, 'size': 0.2,
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'start': -0.9},
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'yaxis': 'y1'}
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self.assertEqual(dp['data'][0], expected_dp_data_hist_1)
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expected_dp_data_hist_2 = {'autobinx': False,
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'histnorm': 'probability',
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'legendgroup': '2013',
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'marker': {'color': 'rgb(255, 127, 14)'},
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'name': '2013',
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'opacity': 0.7,
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'type': 'histogram',
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'x': [0.8, 1.5, 1.5, 0.6, 0.59, 1.0, 0.8,
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1.7, 0.5, 0.8, -0.3, 1.2, 0.56, 0.3,
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2.2],
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'xaxis': 'x1',
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'xbins': {'end': 2.2, 'size': 0.2,
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'start': -0.3},
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'yaxis': 'y1'}
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self.assertEqual(dp['data'][1], expected_dp_data_hist_2)
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class TestStreamline(TestCase):
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def test_wrong_arrow_scale(self):

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