Merge pull request #97 from lucasimi/develop

Develop

Author: lucasimi

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "tda-mapper"
-version = "0.5.1"
+version = "0.5.2"
 description = "A simple and efficient Python implementation of Mapper algorithm for Topological Data Analysis"
 readme = "README.md"
 authors = [{ name = "Luca Simi", email = "lucasimi90@gmail.com" }]

src/tdamapper/plot.py

@@ -42,6 +42,13 @@ def _node_pos(graph, dim, seed, iterations):
         iterations=iterations)
 
 
+def _node_col(graph, colors, agg, default=0.5):
+    if colors is not None:
+        return aggregate_graph(colors, graph, agg)
+    else:
+        return [default for _ in graph.nodes()]
+
+
 def _node_pos_array(graph, dim, node_pos):
     return tuple([node_pos[n][i] for n in graph.nodes()] for i in range(dim))
 
@@ -116,12 +123,8 @@ def __init__(self, graph, dim,
         self.__width = width
         self.__height = height
         self.__cmap = cmap
-        node_col = aggregate_graph(self.__colors, self.__graph, self.__agg)
+        node_col = _node_col(self.__graph, self.__colors, self.__agg)
         self.__fig = self._figure(node_col)
-        #self._update_traces_col()
-        #self._update_layout()
-        #self._update_traces_cmap()
-        #self._update_traces_title()
 
     def _nodes_trace(self, node_pos_arr, node_col):
         attr_size = nx.get_node_attributes(self.__graph, ATTR_SIZE)
@@ -192,7 +195,6 @@ def _layout(self):
         line_col = 'rgba(230, 230, 230, 1.0)'
         axis = dict(
             showline=True,
-            #linecolor='rgba(230, 230, 230, 1.0)',
             linewidth=1,
             mirror=True,
             visible=True,
@@ -263,17 +265,13 @@ def _colorbar(self):
         elif self.__dim == 2:
             return go.scatter.marker.ColorBar(cbar)
 
-    def _text(self, colors=None):
+    def _text(self, colors):
         attr_size = nx.get_node_attributes(self.__graph, ATTR_SIZE)
-        if colors is None:
-            def _lbl(n):
-                size = _fmt(attr_size[n], 5)
-                return f'node: {n}<br>size: {size}'
-        else:
-            def _lbl(n):
-                col = _fmt(colors[n], 3)
-                size = _fmt(attr_size[n], 5)
-                return f'color: {col}<br>node: {n}<br>size: {size}'
+
+        def _lbl(n):
+            col = _fmt(colors[n], 3)
+            size = _fmt(attr_size[n], 5)
+            return f'color: {col}<br>node: {n}<br>size: {size}'
         return [_lbl(n) for n in self.__graph.nodes()]
 
     def _update_traces_pos(self):
@@ -311,10 +309,10 @@ def _update_traces_pos(self):
 
     def _update_traces_col(self):
         if (self.__colors is not None) and (self.__agg is not None):
-            colors_agg = aggregate_graph(self.__colors, self.__graph, self.__agg)
-            colors_list = list(colors_agg.values())
-            self._update_node_trace_col(colors_agg, colors_list)
-            self._update_edge_trace_col(colors_agg, colors_list)
+            nodes_col = _node_col(self.__graph, self.__colors, self.__agg)
+            colors_list = list(nodes_col.values())
+            self._update_node_trace_col(nodes_col, colors_list)
+            self._update_edge_trace_col(nodes_col, colors_list)
 
     def _update_edge_trace_col(self, colors_agg, colors_list):
         colors_avg = []
@@ -538,7 +536,7 @@ def _plot_nodes(self, ax, nodes_pos):
         nodes_arr = _node_pos_array(self.__graph, self.__dim, nodes_pos)
         attr_size = nx.get_node_attributes(self.__graph, ATTR_SIZE)
         max_size = max(attr_size.values()) if attr_size else 1.0
-        colors_agg = aggregate_graph(self.__colors, self.__graph, self.__agg)
+        colors_agg = _node_col(self.__graph, self.__colors, self.__agg)
         marker_color = [colors_agg[n] for n in self.__graph.nodes()]
         marker_size = [200.0 * math.sqrt(attr_size[n] / max_size) for n in self.__graph.nodes()]
         verts = ax.scatter(

tests/test_plot.py

@@ -21,17 +21,34 @@ def testTwoConnectedClusters(self):
         mp = MapperAlgorithm(cover=BallCover(1.1, metric=dist),
             clustering=TrivialClustering())
         g = mp.fit_transform(data, data)
-        mp_plot1 = MapperLayoutInteractive(g, colors=data, dim=2)
+        mp_plot1 = MapperLayoutInteractive(g, dim=2,
+            colors=data,
+            seed=123,
+            iterations=10,
+            agg=np.nanmax,
+            width=200,
+            height=200,
+            title='example',
+            cmap='jet')
         mp_plot1.plot()
-        mp_plot2 = MapperLayoutInteractive(g, colors=data, dim=3)
-        mp_plot2.plot()
-        mp_plot2.update(
+        mp_plot2 = MapperLayoutInteractive(g, dim=3,
             colors=data,
             seed=123,
             iterations=10,
             agg=np.nanmax,
             width=200,
             height=200,
+            title='example',
+            cmap='jet')
+        mp_plot2.plot()
+        mp_plot2.update(
+            colors=data,
+            seed=124,
+            iterations=15,
+            agg=np.nanmin,
+            width=300,
+            height=300,
+            title='example-updated',
             cmap='viridis')
         mp_plot2.plot()
         mp_plot3 = MapperLayoutStatic(g, colors=data, dim=2)