v1 instroke_compare

rowers/interactiveplots.py

@@ -2756,12 +2756,14 @@ def forcecurve_multi_interactive_chart(selected): # pragma: no cover
     return (script, div)
 
 def instroke_multi_interactive_chart(selected, *args, **kwargs): # pragma: no cover
-    df_plot = pd.DataFrame()
+    df2 = []
     ids = [analysis.id for analysis in selected]
     metrics = list(set([analysis.metric for analysis in selected]))
     maximum_values = {}
+    workouts = []
     for metric in metrics:
         maximum_values[metric] = 0
+    cntr = 1
     for analysis in selected:
         #start_second, end_second, spm_min, spm_max, name
         activeminutesmin = int(analysis.start_second/60.)
@@ -2781,79 +2783,48 @@ def instroke_multi_interactive_chart(selected, *args, **kwargs): # pragma: no co
             if mean_vals.max() > maximum_values[analysis.metric]:
                 maximum_values[analysis.metric] = mean_vals.max()
         xvals = np.arange(len(mean_vals))
-        xname = 'x_'+str(analysis.id)
-        yname = 'y_'+str(analysis.id)
-        df_plot[xname] = pd.Series(xvals)
-        df_plot[yname] = pd.Series(mean_vals)
 
-    if len(metrics) > 1:
-        for analysis in selected:
-            yname = 'y_'+str(analysis.id)
-            df_plot[yname] = df_plot[yname] / maximum_values[analysis.metric]
+        data2 = pd.DataFrame({
+            'x': pd.Series(xvals),
+            'y': pd.Series(mean_vals),
+            
+        })
+        data2['id'] = cntr
+        df2.append(data2)
 
-    source = ColumnDataSource(
-        df_plot
-    )
-
-    TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,crosshair'
-    plot = figure(width=920,tools=TOOLS,
-                  toolbar_location='above',
-                  toolbar_sticky=False)
-
-    #plot.sizing_mode = 'stretch_both'
-
-    # add watermark
-    watermarkurl = "/static/img/logo7.png"
-
-    watermarkrange = Range1d(start=0, end=1)
-    watermarkalpha = 0.6
-    watermarkx = 0.99
-    watermarky = 0.01
-    watermarkw = 184
-    watermarkh = 35
-    watermarkanchor = 'bottom_right'
-    plot.extra_y_ranges = {"watermark": watermarkrange}
-    plot.extra_x_ranges = {"watermark": watermarkrange}
-
-    if len(metrics)>1:
-        plot.yaxis.axis_label = 'Scaled'
-    else:
-        plot.yaxis.axis_label = metrics[0]
-
-    plot.image_url([watermarkurl], watermarkx, watermarky,
-                   watermarkw, watermarkh,
-                   global_alpha=watermarkalpha,
-                   w_units='screen',
-                   h_units='screen',
-                   anchor=watermarkanchor,
-                   dilate=True,
-                   x_range_name="watermark",
-                   y_range_name="watermark",
-                   )
-
-    colors = itertools.cycle(palette)
-
-    try:
-        items = itertools.izip(ids, colors)
-    except AttributeError:
-        items = zip(ids, colors)
-
-    for id, color in items:
-        xname = 'x_'+str(id)
-        yname = 'y_'+str(id)
-        analysis = InStrokeAnalysis.objects.get(id=id)
         legendlabel = '{name} - {metric} - {workout}'.format(
             name = analysis.name,
             metric = analysis.metric,
             date = analysis.date,
             workout = str(analysis.workout)
         )
-        plot.line(xname,yname,source=source,legend_label=legendlabel,
-              line_width=2, color=color)
+        workouts.append({'id': cntr, 'label': legendlabel})
+        cntr = cntr + 1
 
-    script, div = components(plot)
+    
+    ytitle = metrics[0]
+    if len(metrics) > 1:
+        cntr = 1
+        for analysis in selected:
+            df2[cntr-1]['y'] = df2[cntr-1]['y'] / maximum_values[analysis.metric]
+            ytitle = 'Scaled'
+            cntr = cntr+1
 
-    return (script, div)
+    df2 = pd.concat(df2, axis=0)
+
+    data_dict = df2.to_dict("records")
+
+    chart_data = {
+        'title': '',
+        'data': data_dict,
+        'ytitle': ytitle,
+        'workouts': workouts,
+    }
+
+    script, div = get_chart("/instroke_compare", chart_data)
+
+    return script, div
+            
 
 def instroke_interactive_chart(df,metric, workout, spm_min, spm_max,
                                activeminutesmin, activeminutesmax,