deprecating all visualization functions

gneiss/plot/_decompose.py

@@ -9,6 +9,7 @@
 import matplotlib.pyplot as plt
 import pandas as pd
 from gneiss.util import NUMERATOR, DENOMINATOR
+import warning
 
 
 def balance_boxplot(balance_name, data, num_color='#FFFFFF',
@@ -49,6 +50,7 @@ def balance_boxplot(balance_name, data, num_color='#FFFFFF',
     --------
     seaborn.boxplot
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     import seaborn as sns
     if ax is None:
         f, ax = plt.subplots()
@@ -118,6 +120,7 @@ def balance_barplots(tree, balance_name, header, feature_metadata,
     ax_denom : matplotlib axes object
         Barplot of the features in the denominator of the balance.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     import seaborn as sns
     if axes[0] is None or axes[1] is None:
         f, (ax_num, ax_denom) = plt.subplots(2)
@@ -238,6 +241,7 @@ def proportion_plot(table, metadata, category, left_group, right_group,
     Since this method will return the raw matplotlib object, labels, titles,
     ticks, etc can directly modified using this object.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     import seaborn as sns
     if axes[0] is None or axes[1] is None:
         f, (ax_num, ax_denom) = plt.subplots(1, 2)

gneiss/plot/_heatmap.py

@@ -279,6 +279,7 @@ def _plot_heatmap(ax_heatmap, table, mdvar, grid_col,
     colorbar_ax : matplotlib axes object
         The colorbar axis.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     # TODO add explicit test for this, since matplotlib orientation
     # is from top to down (i.e. is backwards)
     table, mdvar = _sort_table(table, mdvar)

gneiss/plot/_radial.py

@@ -56,8 +56,7 @@ def radialplot(tree, node_color='node_color', node_size='node_size',
     --------
     bifurcate
     """
-    # TODO: Add in example doc string
-
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     # This entire function was motivated by
     # http://chuckpr.github.io/blog/trees2.html
     t = UnrootedDendrogram.from_tree(tree.copy())

gneiss/plot/_regression_plot.py

@@ -14,15 +14,18 @@
 from gneiss.regression._ols import OLSModel
 from gneiss.regression._mixedlm import LMEModel
 
-from bokeh.embed import file_html
-from bokeh.resources import CDN
-from bokeh.plotting import figure, ColumnDataSource
-from bokeh.layouts import row, column
-from bokeh.models import (HoverTool, BoxZoomTool, WheelZoomTool,
-                          ResetTool, SaveTool, PanTool,
-                          FuncTickFormatter, FixedTicker)
-from bokeh.palettes import RdYlBu11 as palette
 from statsmodels.sandbox.stats.multicomp import multipletests
+try:
+    from bokeh.embed import file_html
+    from bokeh.resources import CDN
+    from bokeh.plotting import figure, ColumnDataSource
+    from bokeh.layouts import row, column
+    from bokeh.models import (HoverTool, BoxZoomTool, WheelZoomTool,
+                              ResetTool, SaveTool, PanTool,
+                              FuncTickFormatter, FixedTicker)
+    from bokeh.palettes import RdYlBu11 as palette
+except:
+    warnings.warn("Bokeh isn't installed - the interactive visualizations won't work.")
 
 
 def _projected_prediction(model, plot_width=400, plot_height=400):
@@ -41,6 +44,7 @@ def _projected_prediction(model, plot_width=400, plot_height=400):
     -------
     bokeh plot
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     hover = HoverTool(tooltips=[("#SampleID", "@index")])
     pred = model.predict()
     pcvar = model.percent_explained()
@@ -82,6 +86,7 @@ def _projected_residuals(model, plot_width=400, plot_height=400):
     -------
     bokeh plot
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     hover = HoverTool(tooltips=[("#SampleID", "@index")])
     pcvar = model.percent_explained()
     resid = model.residuals()
@@ -121,6 +126,8 @@ def _heatmap_summary(pvals, coefs, plot_width=1200, plot_height=400):
     bokeh.charts.Heatmap
         Heatmap summarizing the regression statistics.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
+
     c = coefs.reset_index()
     c = c.rename(columns={'index': 'balance'})
 
@@ -228,6 +235,7 @@ def _decorate_tree(t, series):
 
 def _deposit_results(model, output_dir):
     """ Store all of the core regression results into a folder. """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     coefficients = model.coefficients()
     coefficients.T.to_csv(os.path.join(output_dir, 'coefficients.csv'),
                           header=True, index=True)
@@ -270,6 +278,7 @@ def ols_summary(output_dir: str, model: OLSModel,
         Tree object that defines the partitions of the features. Each of the
         leaves correspond to the balances in the model.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     # Cross validation
     w, h = 500, 300  # plot width and height
 
@@ -340,6 +349,7 @@ def lme_summary(output_dir: str, model: LMEModel, tree: TreeNode) -> None:
         Tree object that defines the partitions of the features. Each of the
         leaves correspond to the balances in the model.
     """
+    warnings.warn("This visualization are deprecated.", DeprecationWarning)
     # log likelihood
     loglike = pd.Series({r.model.endog_names: r.model.loglike(r.params)
                          for r in model.results})

gneiss/plot/tests/test_decompose.py

@@ -31,6 +31,7 @@ def setUp(self):
             index=["a", "b", "c", "d"]
         )
 
+    @unittest.skip('Visualizations are deprecated')
     def test_basic_boxplot(self):
         a = balance_boxplot('y', y='group', data=self.df)
         res = np.vstack([i._xy for i in a.get_lines()])
@@ -56,6 +57,7 @@ def test_basic_boxplot(self):
                         [1.8, 1.4]])
         npt.assert_allclose(res, exp)
 
+    @unittest.skip('Visualizations are deprecated')
     def test_basic_hue_boxplot(self):
         a = balance_boxplot('y', y='group', hue='hue', data=self.df)
         res = np.vstack([i._xy for i in a.get_lines()])
@@ -101,6 +103,7 @@ def test_basic_hue_boxplot(self):
                         [1.8, 1.396]])
         npt.assert_allclose(res, exp)
 
+    @unittest.skip('Visualizations are deprecated')
     def test_basic_barplot(self):
         ax_denom, ax_num = balance_barplots(self.tree, 'y', header='food',
                                             feature_metadata=self.feature_df)
@@ -128,6 +131,7 @@ def setUp(self):
             'dry': [1, 2, 3, 4, 5, 6]
         }, index=['S1', 'S2', 'S3', 'S4', 'S5', 'S6'])
 
+    @unittest.skip('Visualizations are deprecated')
     def test_proportion_plot(self):
         np.random.seed(0)
         num_features = ['A', 'B']
@@ -151,6 +155,7 @@ def test_proportion_plot(self):
         exp = ['p__bar', 'p__bar', 'p__tar', 'p__far']
         self.assertListEqual(res, exp)
 
+    @unittest.skip('Visualizations are deprecated')
     def test_proportion_plot_order(self):
         self.maxDiff = None
         np.random.seed(0)
@@ -176,6 +181,7 @@ def test_proportion_plot_order(self):
         exp = ['p__bar', 'p__bar', 'p__far', 'p__tar']
         self.assertListEqual(res, exp)
 
+    @unittest.skip('Visualizations are deprecated')
     def test_proportion_plot_order_figure(self):
         self.maxDiff = None
         np.random.seed(0)

gneiss/plot/tests/test_heatmap.py

@@ -52,7 +52,7 @@ def test_sort_table(self):
         pdt.assert_index_equal(pd.Index(['s1', 's3', 's5', 's2', 's4']),
                                res_table.columns)
 
-    @unittest.skip()
+    @unittest.skip('Visualizations are deprecated')
     def test_basic(self):
         fig = heatmap(self.table, self.t, self.md,
                       figsize=(5, self.table.shape[0]))
@@ -116,7 +116,7 @@ def test_basic_line_width(self):
         widths = [L.get_lw() for L in lines]
         np.allclose(widths, [1.0] * len(widths))
 
-    @unittest.skip()
+    @unittest.skip('Visualizations are deprecated')
     def test_highlights(self):
 
         table = pd.DataFrame(block_diagonal(ncols=5, nrows=5, nblocks=2),

gneiss/plot/tests/test_radial.py

@@ -21,6 +21,7 @@ def setUp(self):
             columns=['x', 'y', 'child0', 'child1', 'is_tip'],
             index=['0', '1', '2', 'y3', 'y4'])
 
+    @unittest.skip('Visualizations are deprecated')
     def test_basic_plot(self):
         self.maxDiff = None
         exp_edges = {'dest_node': ['0', '1', '2', 'y3'],

gneiss/plot/tests/test_regression_plot.py

@@ -57,6 +57,7 @@ def setUp(self):
     def tearDown(self):
         shutil.rmtree(self.results)
 
+    @unittest.skip('Visualizations are deprecated')
     def test_visualization(self):
         res = ols(formula="x1 + x2 + x3 + x4",
                   table=self.y, metadata=self.x)
@@ -130,7 +131,7 @@ def setUp(self):
     def tearDown(self):
         shutil.rmtree(self.results)
 
-    @unittest.skip()
+    @unittest.skip('Visualizations are deprecated')
     def test_visualization(self):
         model = mixedlm("x1 + x2", self.table, self.metadata,
                         groups="groups")