Merge pull request #121 from lucasimi/develop

Develop

Author: lucasimi

app/streamlit_app.py

@@ -7,7 +7,6 @@
 import pandas as pd
 import numpy as np
 import plotly.express as px
-import plotly.graph_objects as go
 
 import networkx as nx 
 from networkx.readwrite.json_graph import adjacency_data
@@ -90,8 +89,6 @@
 
 VD_SEED = 42
 
-VD_DIM = 3
-
 # S_* are reusable session stored objects
 
 S_RESULTS = 'stored_results'
@@ -108,40 +105,16 @@ def __init__(self):
         self.df_all_sample = pd.DataFrame()
         self.X = self.df_X.to_numpy()
         self.df_summary = pd.DataFrame()
-        self.mapper_graph = nx.Graph()
+        self.mapper_graph = None
         self.mapper_plot = None
-        self.mapper_fig = self._init_fig()
+        self.mapper_dim = None
+        self.mapper_fig = None
         self.mapper_fig_outdated = True
         self.auto_rendering = self._auto_rendering()
 
-    def _init_fig(self):
-        fig = go.Figure(
-            data=[go.Scatter3d(
-                x=[],
-                y=[],
-                z=[],
-                mode='markers')])
-        fig.update_layout(
-            uirevision='constant',
-            scene=dict(
-                xaxis=dict(
-                    showgrid=True,
-                    zeroline=True,
-                    showline=True,
-                    ticks='outside'),
-                yaxis=dict(
-                    showgrid=True,
-                    zeroline=True,
-                    showline=True,
-                    ticks='outside'),
-                zaxis=dict(
-                    showgrid=True,
-                    zeroline=True,
-                    showline=True,
-                    ticks='outside')))
-        return fig
-    
     def _auto_rendering(self):
+        if self.mapper_graph is None:
+            return False
         nodes_num = self.mapper_graph.number_of_nodes()
         return nodes_num <= MAX_NODES
 
@@ -154,27 +127,57 @@ def set_df(self, X, y):
         self.df_all_sample = pd.concat([self.df_y_sample, self.df_X_sample], axis=1)
         self.X = self.df_X.to_numpy()
         self.df_summary = _get_data_summary(self.df_X, self.df_y)
-        self.mapper_graph = nx.Graph()
+        self.mapper_graph = None
         self.mapper_plot = None
-        self.mapper_fig = self._init_fig()
+        self.mapper_dim = None
+        self.mapper_fig = None
         self.mapper_fig_outdated = True
         self.auto_rendering = self._auto_rendering()
 
     def set_mapper(self, mapper_graph):
         self.mapper_graph = mapper_graph
-        self.mapper_plot = MapperLayoutInteractive(
-            self.mapper_graph,
-            dim=VD_DIM,
-            height=500,
-            width=500,
-            colors=self.X,
-            seed=VD_SEED)
-        self.mapper_fig = self._init_fig()
+        self.mapper_plot = None
+        self.mapper_dim = None
+        self.mapper_fig = None
         self.mapper_fig_outdated = True
         self.auto_rendering = self._auto_rendering()
 
-    def set_mapper_fig(self, mapper_fig):
-        self.mapper_fig = mapper_fig
+    def set_mapper_fig(self, dim, seed, color_feat, agg, cmap, title):
+        colors = self.X
+        df_all = st.session_state[S_RESULTS].df_all
+        if color_feat in df_all.columns:
+            df_col = df_all[color_feat]
+            colors = df_col.to_numpy()
+        if (self.mapper_plot is None) or (dim != self.mapper_dim):
+            self.mapper_plot = MapperLayoutInteractive(
+                self.mapper_graph,
+                dim=dim,
+                seed=seed,
+                colors=colors,
+                agg=agg,
+                cmap=cmap,
+                title=title,
+                height=500,
+                width=500)
+            self.mapper_dim = dim
+        else:
+            self.mapper_plot.update(
+                seed=seed,
+                colors=colors,
+                agg=agg,
+                cmap=cmap,
+                title=title)
+        self.mapper_fig = self.mapper_plot.plot()
+        self.mapper_fig.update_layout(
+            uirevision='constant',
+            margin=dict(b=0, l=0, r=0, t=0))
+        self.mapper_fig.update_xaxes(
+            #constrain='domain',
+            showline=False)
+        self.mapper_fig.update_yaxes(
+            showline=False,
+            scaleanchor='x',
+            scaleratio = 1)
         self.mapper_fig_outdated = False
 
 
@@ -295,27 +298,8 @@ def _update_mapper(X, lens, cover, clustering):
         st.toast('Automatic Rendering Disabled: Graph Too Large', icon='⚠️')
 
 
-def _update_fig(seed, color_feat, agg, cmap, title):
-    mapper_plot = st.session_state[S_RESULTS].mapper_plot
-    if mapper_plot is None:
-        return
-    X = st.session_state[S_RESULTS].X
-    colors = X
-    df_all = st.session_state[S_RESULTS].df_all
-    if color_feat in df_all.columns:
-        df_col = df_all[color_feat]
-        colors = df_col.to_numpy()
-    mapper_plot.update(
-        colors=colors,
-        seed=seed,
-        agg=agg,
-        title=title,
-        cmap=cmap)
-    mapper_fig = mapper_plot.plot()
-    mapper_fig.update_layout(
-        uirevision='constant',
-        margin=dict(b=0, l=0, r=0, t=0))
-    st.session_state[S_RESULTS].set_mapper_fig(mapper_fig)
+def _update_fig(dim, seed, color_feat, agg, cmap, title):
+    st.session_state[S_RESULTS].set_mapper_fig(dim, seed, color_feat, agg, cmap, title)
     st.toast('Successfully Rendered Graph', icon='🖌️')
 
 
@@ -374,11 +358,12 @@ def _clustering_tuning(clustering_type):
     if clustering_type == V_CLUSTERING_TRIVIAL:
         clustering = TrivialClustering()
     elif clustering_type == V_CLUSTERING_AGGLOMERATIVE:
-        clust_n = st.number_input(
+        clust_num = st.number_input(
             '🧮 Clusters',
             value=2,
             min_value=1)
-        clustering = AgglomerativeClustering(n_clusters=clust_n)
+        n_clusters = int(clust_num)
+        clustering = AgglomerativeClustering(n_clusters=n_clusters)
     return clustering
 
 
@@ -457,6 +442,15 @@ def _mapper_aggregation():
     return agg, agg_name
 
 
+def _mapper_dim():
+    toggle_3d = st.toggle(
+        '3D Rendering',
+        value=True,
+        on_change=_update_mapper_fig_outdated)
+    dim = 3 if toggle_3d else 2
+    return dim
+
+
 def _mapper_seed():
     seed = st.number_input(
         '🎲 Seed',
@@ -500,29 +494,35 @@ def _mapper_caption():
 
 def _mapper_histogram():
     mapper_graph = st.session_state[S_RESULTS].mapper_graph
-    ccs = nx.connected_components(mapper_graph)
-    size = nx.get_node_attributes(mapper_graph, ATTR_SIZE)
-    node_cc, node_size = {}, {}
-    node_cc_max, node_size_max = 1, 1
-    for cc in ccs:
-        cc_len = len(cc)
-        for u in cc:
-            u_size = size[u]
-            node_cc[u] = cc_len
-            node_size[u] = u_size
-            if u_size > node_size_max:
-                node_size_max = u_size
-        if cc_len > node_cc_max:
-            node_cc_max = cc_len
-    arr_size = np.array([node_size[u]/node_size_max for u in mapper_graph.nodes()])
-    arr_cc = np.array([node_cc[u]/node_cc_max for u in mapper_graph.nodes()])
+    node_size_feat = 'node size (rel.)'
+    cc_size_feat = 'conn. comp. size (rel.)'
     df = pd.DataFrame(dict(
-        series=np.concatenate((
-            ['node size (rel.)'] * len(arr_size),
-            ['conn. comp. size (rel.)'] * len(arr_cc))),
-        data=np.concatenate((
-            arr_size,
-            arr_cc))))
+        series=[node_size_feat, cc_size_feat],
+        data=[0.0, 0.0]))
+    if mapper_graph:
+        ccs = nx.connected_components(mapper_graph)
+        size = nx.get_node_attributes(mapper_graph, ATTR_SIZE)
+        node_cc, node_size = {}, {}
+        node_cc_max, node_size_max = 1, 1
+        for cc in ccs:
+            cc_len = len(cc)
+            for u in cc:
+                u_size = size[u]
+                node_cc[u] = cc_len
+                node_size[u] = u_size
+                if u_size > node_size_max:
+                    node_size_max = u_size
+            if cc_len > node_cc_max:
+                node_cc_max = cc_len
+        arr_size = np.array([node_size[u]/node_size_max for u in mapper_graph.nodes()])
+        arr_cc = np.array([node_cc[u]/node_cc_max for u in mapper_graph.nodes()])
+        df = pd.DataFrame(dict(
+            series=np.concatenate((
+                [node_size_feat] * len(arr_size),
+                [cc_size_feat] * len(arr_cc))),
+            data=np.concatenate((
+                arr_size,
+                arr_cc))))
     fig = px.histogram(
         df,
         nbins=20,
@@ -559,11 +559,10 @@ def _mapper_download():
     mapper_graph = st.session_state[S_RESULTS].mapper_graph
     mapper_adj = {} if mapper_graph is None else adjacency_data(mapper_graph)
     mapper_json = json.dumps(mapper_adj, default=int)
-    nodes_num = mapper_graph.number_of_nodes()
     return st.download_button(
         '📥 Download Mapper',
         data=get_gzip_bytes(mapper_json),
-        disabled=nodes_num < 1,
+        disabled=mapper_graph is None,
         use_container_width=True,
         file_name=f'mapper_graph_{int(time.time())}.json.gzip')
 
@@ -622,7 +621,6 @@ def mapper_run_section(lens_type, cover_type, clustering_type):
 
 
 def mapper_color_section():
-    X = st.session_state[S_RESULTS].X
     df_all = st.session_state[S_RESULTS].df_all
     col_feat = st.selectbox(
         '🎨 Color',
@@ -632,6 +630,7 @@ def mapper_color_section():
 
 
 def mapper_draw_section(color_feat):
+    dim = _mapper_dim()
     seed = _mapper_seed()
     cmap = _mapper_cmap()
     agg, agg_name = _mapper_aggregation()
@@ -644,9 +643,9 @@ def mapper_draw_section(color_feat):
     auto_rendering = st.session_state[S_RESULTS].auto_rendering
     title = f'{agg_name} of {color_feat}'
     if auto_rendering and mapper_fig_outdated:
-        _update_fig(seed, color_feat, agg, cmap, title)
+        _update_fig(dim, seed, color_feat, agg, cmap, title)
     elif update_button:
-        _update_fig(seed, color_feat, agg, cmap, title)
+        _update_fig(dim, seed, color_feat, agg, cmap, title)
 
 
 def data_summary_section():
@@ -669,11 +668,12 @@ def mapper_output_section():
 
 def mapper_rendering_section():
     mapper_fig = st.session_state[S_RESULTS].mapper_fig
-    with st.container(border=False):
-        st.plotly_chart(
-            mapper_fig,
-            height=350,
-            use_container_width=True)
+    if mapper_fig is not None:
+        with st.container(border=False):
+            st.plotly_chart(
+                mapper_fig,
+                height=350,
+                use_container_width=True)
 
 
 def main():