Only plot selected rows

daqviewer/tables.py

@@ -4,6 +4,7 @@ from dash.dependencies import Input, Output
 import dash_table
 import dash_core_components as dcc
 import dash_html_components as html
+import plotly.graph_objs as go
 import pandas as pd
 import numpy as np
 
@@ -80,56 +81,24 @@ def update_graphs(row_ids, selected_row_ids, active_cell):
     # the component.
     selected_id_set = set(selected_row_ids or [])
 
-    if row_ids is None:
-        dff = df
-        # pandas Series works enough like a list for this to be OK
-        row_ids = df['id']
+    if selected_id_set:
+        dff = df.loc[selected_id_set]
     else:
-        dff = df.loc[row_ids]
-
-    active_row_id = active_cell['row_id'] if active_cell else None
-
-    colors = [
-        '#FF69B4' if i == active_row_id else
-        '#7FDBFF' if i in selected_id_set else '#0074D9' for i in row_ids
-    ]
-
-    return [
-        dcc.Graph(
-            id=column + '--row-ids',
-            figure={
-                'data': [{
-                    'x': dff['id'],
-                    'y': dff[column],
-                    'type': 'bar',
-                    'marker': {
-                        'color': colors
-                    },
-                }],
-                'layout': {
-                    'xaxis': {
-                        'automargin': True
-                    },
-                    'yaxis': {
-                        'automargin': True,
-                        'title': {
-                            'text': column
-                        }
-                    },
-                    'height': 250,
-                    'margin': {
-                        't': 10,
-                        'l': 10,
-                        'r': 10
-                    },
-                },
-            },
-        )
-        # check if column exists - user may have deleted it
-        # If `column.deletable=False`, then you don't
-        # need to do this check.
-        for column in ['H_sig', 'H_1%', 'H_max'] if column in dff
-    ]
+        dff = df
+
+    spec = []
+    for i, row in dff.iterrows():
+        x = np.arange(10)
+        y = x * row['H_sig']
+
+        trace = go.Scatter(x=x, y=y, name=i)
+        spec.append(trace)
+
+        energy = dict(data=spec)
+
+        graph = dcc.Graph(id='time-series', figure=energy)
+
+    return graph
 
 
 if __name__ == '__main__':