Reduced data stream to cum_flex
This commit is contained in:
Sander Roosendaal
@@ -7,7 +7,7 @@ from rowingdata import rowingdata as rrdata
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from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc
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from bokeh.models import CustomJS,Slider
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from bokeh.charts import Histogram
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from bokeh.charts import Histogram,HeatMap
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from bokeh.resources import CDN,INLINE
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from bokeh.embed import components
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from bokeh.layouts import layout,widgetbox
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@@ -563,6 +563,305 @@ def interactive_chart(id=0,promember=0):
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return [script,div]
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def interactive_cum_flex_chart2(theworkouts,promember=0,
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xparam='spm',
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yparam1='power',
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yparam2='spm'):
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datadf = dataprep.smalldataprep(theworkouts,xparam,yparam1,yparam2)
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axlabels = {
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'time': 'Time',
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'distance': 'Distance (m)',
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'hr': 'Heart Rate (bpm)',
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'spm': 'Stroke Rate (spm)',
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'pace': 'Pace (/500m)',
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'power': 'Power (Watt)',
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'averageforce': 'Average Drive Force (lbs)',
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'drivelength': 'Drive Length (m)',
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'peakforce': 'Peak Drive Force (lbs)',
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'forceratio': 'Average/Peak Drive Force Ratio',
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'driveenergy': 'Work per Stroke (J)',
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'drivespeed': 'Drive Speed (m/s)',
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'None': '',
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}
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yparamname1 = axlabels[yparam1]
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yparamname2 = axlabels[yparam2]
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yaxminima = {
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'hr':100,
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'spm':15,
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'pace': 1.0e3*210,
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'power': 0,
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'averageforce': 0,
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'peakforce': 0,
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'forceratio':0,
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'drivelength':0.5,
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'driveenergy': 0,
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'drivespeed': 0,
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}
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yaxmaxima = {
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'hr':200,
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'spm':45,
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'pace':1.0e3*90,
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'power': 600,
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'averageforce':200,
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'peakforce':400,
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'forceratio':1,
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'drivelength':2.0,
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'driveenergy': 1000,
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'drivespeed':4,
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}
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datadf = datadf[datadf[yparam1] > 0]
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datadf = datadf[datadf[xparam] > 0]
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if yparam2 != 'None':
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datadf = datadf[datadf[yparam2] > 0]
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# check if dataframe not empty
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if datadf.empty:
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return ['','<p>No non-zero data in selection</p>','','']
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datadf['x1'] = datadf.ix[:,xparam]
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datadf['y1'] = datadf.ix[:,yparam1]
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if yparam2 != 'None':
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datadf['y2'] = datadf.ix[:,yparam2]
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else:
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datadf['y2'] = datadf['y1']
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if xparam=='distance':
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xaxmax = datadf['x1'].max()
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xaxmin = datadf['x1'].min()
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else:
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xaxmax = yaxmaxima[xparam]
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xaxmin = yaxminima[xparam]
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# average values
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x1mean = datadf['x1'].mean()
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y1mean = datadf['y1'].mean()
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y2mean = datadf['y2'].mean()
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xvals = pd.Series(xaxmin+np.arange(100)*(xaxmax-xaxmin)/100.)
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x_axis_type = 'linear'
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y_axis_type = 'linear'
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datadf['xname'] = xparam
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datadf['yname1'] = yparam1
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if yparam2 != 'None':
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datadf['yname2'] = yparam2
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else:
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datadf['yname2'] = yparam1
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source = ColumnDataSource(
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datadf
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)
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source2 = ColumnDataSource(
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datadf.copy()
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)
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# Add hover to this comma-separated string and see what changes
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if (promember==1):
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,crosshair'
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else:
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TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
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plot = Figure(x_axis_type=x_axis_type,y_axis_type=y_axis_type,
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tools=TOOLS,
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toolbar_location="above",
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toolbar_sticky=False)
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x1means = Span(location=x1mean,dimension='height',line_color='green',
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line_dash=[6,6], line_width=2)
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y1means = Span(location=y1mean,dimension='width',line_color='blue',
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line_dash=[6,6],line_width=2)
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y2means = y1means
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xlabel = Label(x=370,y=130,x_units='screen',y_units='screen',
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text=xparam+": {x1mean:6.2f}".format(x1mean=x1mean),
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background_fill_alpha=.7,
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text_color='green',
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)
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plot.add_layout(x1means)
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plot.add_layout(xlabel)
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plot.add_layout(y1means)
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y1label = Label(x=370,y=100,x_units='screen',y_units='screen',
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text=yparam1+": {y1mean:6.2f}".format(y1mean=y1mean),
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background_fill_alpha=.7,
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text_color='blue',
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)
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plot.add_layout(y1label)
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y2label = y1label
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plot.circle('x1','y1',source=source2,fill_alpha=0.3,line_color=None,
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legend=yparamname1,
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)
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plot.xaxis.axis_label = axlabels[xparam]
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plot.yaxis.axis_label = axlabels[yparam1]
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yrange1 = Range1d(start=yaxminima[yparam1],end=yaxmaxima[yparam1])
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plot.y_range = yrange1
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xrange1 = Range1d(start=yaxminima[xparam],end=yaxmaxima[xparam])
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plot.x_range = xrange1
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if yparam2 != 'None':
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yrange2 = Range1d(start=yaxminima[yparam2],end=yaxmaxima[yparam2])
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plot.extra_y_ranges = {"yax2": yrange2}
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plot.circle('x1','y2',color="red",y_range_name="yax2",
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legend=yparamname2,
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source=source2,fill_alpha=0.3,line_color=None)
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plot.add_layout(LinearAxis(y_range_name="yax2",
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axis_label=axlabels[yparam2]),'right')
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y2means = Span(location=y2mean,dimension='width',line_color='red',
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line_dash=[6,6],line_width=2,y_range_name="yax2")
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plot.add_layout(y2means)
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y2label = Label(x=370,y=70,x_units='screen',y_units='screen',
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text=yparam2+": {y2mean:6.2f}".format(y2mean=y2mean),
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background_fill_alpha=.7,
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text_color='red',
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)
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if yparam2 != 'pace' and yparam2 != 'time':
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plot.add_layout(y2label)
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callback = CustomJS(args = dict(source=source,source2=source2,
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x1means=x1means,
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y1means=y1means,
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y1label=y1label,
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y2label=y2label,
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xlabel=xlabel,
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y2means=y2means), code="""
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var data = source.data
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var data2 = source2.data
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var x1 = data['x1']
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var y1 = data['y1']
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var y2 = data['y2']
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var spm1 = data['spm']
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var distance1 = data['distance']
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var xname = data['xname'][0]
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var yname1 = data['yname1'][0]
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var yname2 = data['yname2'][0]
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var minspm = minspm.value
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var maxspm = maxspm.value
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var mindist = mindist.value
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var maxdist = maxdist.value
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var xm = 0
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var ym1 = 0
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var ym2 = 0
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data2['x1'] = []
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data2['y1'] = []
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data2['y2'] = []
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data2['spm'] = []
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data2['distance'] = []
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data2['x1mean'] = []
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data2['y1mean'] = []
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data2['y2mean'] = []
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data2['xvals'] = []
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data2['y1vals'] = []
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data2['y2vals'] = []
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for (i=0; i<x1.length; i++) {
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if (spm1[i]>=minspm && spm1[i]<=maxspm) {
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if (distance1[i]>=mindist && distance1[i]<=maxdist) {
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data2['x1'].push(x1[i])
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data2['y1'].push(y1[i])
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data2['y2'].push(y2[i])
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data2['spm'].push(spm1[i])
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data2['distance'].push(distance1[i])
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xm += x1[i]
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ym1 += y1[i]
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ym2 += y2[i]
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}
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}
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}
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xm /= data2['x1'].length
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ym1 /= data2['x1'].length
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ym2 /= data2['x1'].length
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data2['x1mean'] = [xm,xm]
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data2['y1mean'] = [ym1,ym1]
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data2['y2mean'] = [ym2,ym2]
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x1means.location = xm
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y1means.location = ym1
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y2means.location = ym2
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y1label.text = yname1+': '+ym1.toFixed(2)
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y2label.text = yname2+': '+ym2.toFixed(2)
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xlabel.text = xname+': '+xm.toFixed(2)
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source2.trigger('change');
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""")
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slider_spm_min = Slider(start=15.0, end=55,value=15.0, step=.1,
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title="Min SPM",callback=callback)
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callback.args["minspm"] = slider_spm_min
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slider_spm_max = Slider(start=15.0, end=55,value=55.0, step=.1,
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title="Max SPM",callback=callback)
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callback.args["maxspm"] = slider_spm_max
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distmax = 100+100*int(datadf['distance'].max()/100.)
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slider_dist_min = Slider(start=0,end=distmax,value=0,step=1,
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title="Min Distance",callback=callback)
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callback.args["mindist"] = slider_dist_min
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slider_dist_max = Slider(start=0,end=distmax,value=distmax,
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step=1,
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title="Max Distance",callback=callback)
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callback.args["maxdist"] = slider_dist_max
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layout = layoutrow([layoutcolumn([slider_spm_min,
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slider_spm_max,
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slider_dist_min,
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slider_dist_max,
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],
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),
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plot])
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script, div = components(layout)
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js_resources = INLINE.render_js()
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css_resources = INLINE.render_css()
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return [script,div,js_resources,css_resources]
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def interactive_cum_flex_chart(theworkouts,promember=0,
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xparam='spm',
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yparam1='power',
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@@ -578,8 +877,7 @@ def interactive_cum_flex_chart(theworkouts,promember=0,
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therows.append(rowdata.df)
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datadf = pd.concat(therows)
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axlabels = {
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'time': 'Time',
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'distance': 'Distance (m)',
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