Merge branch 'feature/multiflexsize' into develop
This commit is contained in:
Sander Roosendaal
@@ -73,14 +73,15 @@ def errorbar(fig, x, y, source=ColumnDataSource(),
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xerr=False, yerr=False, color='red',
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point_kwargs={}, error_kwargs={}):
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fig.circle(x, y, source=source, name='data',color=color, **point_kwargs)
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fig.circle(x, y, source=source, name='data',color=color,
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**point_kwargs)
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xvalues = source.data[x]
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yvalues = source.data[y]
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xerrvalues = source.data['xerror']
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yerrvalues = source.data['yerror']
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try:
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a = xvalues[0]+1
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@@ -1182,6 +1183,8 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
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if groupby == 'workoutid':
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groupname = 'Workout'
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elif groupby == 'date':
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groupname = 'Date'
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else:
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groupname = axlabels[groupby]
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@@ -1234,12 +1237,29 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
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)
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,hover'
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TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize'
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if groupby != 'date':
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hover = HoverTool(names=['data'],
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tooltips = [
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(groupby,'@groupval{1.1}')
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])
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else:
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hover = HoverTool(names=['data'],
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tooltips = [
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(groupby,'@groupval')
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])
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hover.mode = 'mouse'
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TOOLS = [SaveTool(),PanTool(),BoxZoomTool(),WheelZoomTool(),
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ResetTool(),TapTool(),ResizeTool(),hover]
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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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# add watermark
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plot.extra_y_ranges = {"watermark": watermarkrange}
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plot.extra_x_ranges = {"watermark": watermarkrange}
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@@ -1264,7 +1284,7 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
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point_kwargs={
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'line_color':None,
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'legend':yparamname,
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'size':10,
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'size':"groupsize",
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})
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if xparam == 'workoutid':
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@@ -1290,20 +1310,6 @@ def interactive_multiflex(datadf,xparam,yparam,groupby,extratitle='',
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minutes = ["%M"]
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)
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hover = plot.select(dict(type=HoverTool))
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if groupby != 'date':
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hover.tooltips = OrderedDict([
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(groupby,'@groupval{1.1}'),
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])
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else:
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hover.tooltips = OrderedDict([
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(groupby,'@groupval'),
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])
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hover.mode = 'mouse'
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script,div = components(plot)
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282
rowers/views.py
282
rowers/views.py
@@ -3469,95 +3469,6 @@ def multiflex_view(request,userid=0,
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ids = [int(w.id) for w in workouts]
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request.session['ids'] = ids
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fieldlist,fielddict = dataprep.getstatsfields()
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fieldlist = [xparam,yparam,groupby,
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'workoutid','spm','driveenergy',
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'workoutstate']
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# prepare data frame
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datadf = dataprep.read_cols_df_sql(ids,fieldlist)
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datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
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datadf = dataprep.filter_df(datadf,'spm',spmmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'spm',spmmax,
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largerthan=False)
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datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
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largerthan=False)
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datadf.dropna(axis=0,how='any',inplace=True)
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datemapping = {
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w.id:w.date for w in workouts
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}
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datadf['date'] = datadf['workoutid']
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datadf['date'].replace(datemapping,inplace=True)
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today = datetime.date.today()
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datadf['days ago'] = map(lambda x : x.days, datadf.date - today)
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if groupby != 'date':
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bins = np.arange(datadf[groupby].min()-binsize,
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datadf[groupby].max()+binsize,
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binsize)
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groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
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else:
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bins = np.arange(datadf['days ago'].min()-binsize,
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datadf['days ago'].max()+binsize,
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binsize,
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)
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groups = datadf.groupby(pd.cut(datadf['days ago'], bins,
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labels=False))
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xvalues = groups.mean()[xparam]
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yvalues = groups.mean()[yparam]
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xerror = groups.std()[xparam]
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yerror = groups.std()[yparam]
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df = pd.DataFrame({
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xparam:xvalues,
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yparam:yvalues,
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'xerror':xerror,
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'yerror':yerror,
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})
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if groupby != 'date':
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try:
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df['groupval'] = groups.mean()[groupby],
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except ValueError:
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df['groupval'] = groups.mean()[groupby].fillna(value=0)
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else:
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try:
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df['groupval'] = [x.strftime("%Y-%m-%d") for x in groups.min()[groupby]]
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except AttributeError:
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df['groupval'] = groups.mean()['days ago'].fillna(value=0)
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if userid == 0:
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extratitle = ''
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else:
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u = User.objects.get(id=userid)
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extratitle = ' '+u.first_name+' '+u.last_name
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script,div = interactive_multiflex(df,xparam,yparam,
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groupby,
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extratitle=extratitle,
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ploterrorbars=ploterrorbars)
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return render(request,'multiflex.html',
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{'interactiveplot':script,
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'the_div':div,
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'chartform':chartform,
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'userid':userid,
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'teams':get_my_teams(request.user),
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})
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else:
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return HttpResponse("Form is not valid")
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elif request.method == 'POST' and 'ids' in request.session:
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@@ -3602,109 +3513,108 @@ def multiflex_view(request,userid=0,
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int(w.id): w.__unicode__() for w in workouts
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}
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fieldlist,fielddict = dataprep.getstatsfields()
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fieldlist = [xparam,yparam,groupby,
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'workoutid','spm','driveenergy',
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'workoutstate']
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# prepare data frame
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datadf = dataprep.read_cols_df_sql(ids,fieldlist)
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datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
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datadf = dataprep.filter_df(datadf,'spm',spmmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'spm',spmmax,
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largerthan=False)
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datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
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largerthan=False)
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datadf.dropna(axis=0,how='any',inplace=True)
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datemapping = {
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w.id:w.date for w in workouts
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}
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datadf['date'] = datadf['workoutid']
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datadf['date'].replace(datemapping,inplace=True)
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today = datetime.date.today()
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datadf['days ago'] = map(lambda x : x.days, datadf.date - today)
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if groupby != 'date':
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bins = np.arange(datadf[groupby].min()-binsize,
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datadf[groupby].max()+binsize,
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binsize)
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groups = datadf.groupby(pd.cut(datadf[groupby],bins,
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labels=False))
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else:
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bins = np.arange(datadf['days ago'].min()-binsize,
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datadf['days ago'].max()+binsize,
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binsize,
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)
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groups = datadf.groupby(pd.cut(datadf['days ago'], bins,
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labels=False))
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xvalues = groups.mean()[xparam]
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yvalues = groups.mean()[yparam]
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xerror = groups.std()[xparam]
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yerror = groups.std()[yparam]
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df = pd.DataFrame({
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xparam:xvalues,
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yparam:yvalues,
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'xerror':xerror,
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'yerror':yerror,
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})
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if groupby == 'pace':
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df['groupval'] = groups.mean()[groupby].fillna(value=0)/1000.
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elif groupby != 'date':
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try:
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df['groupval'] = groups.mean()[groupby],
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except ValueError:
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df['groupval'] = groups.mean()[groupby].fillna(value=0)
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else:
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try:
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df['groupval'] = [x.strftime("%Y-%m-%d") for x in groups.min()[groupby]]
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except AttributeError:
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df['groupval'] = groups.mean()['days ago'].fillna(value=0)
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if userid == 0:
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extratitle = ''
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else:
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u = User.objects.get(id=userid)
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extratitle = ' '+u.first_name+' '+u.last_name
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script,div = interactive_multiflex(df,xparam,yparam,
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groupby,
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extratitle=extratitle,
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ploterrorbars=ploterrorbars)
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return render(request,'multiflex.html',
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{'interactiveplot':script,
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'the_div':div,
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'chartform':chartform,
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'userid':userid,
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'teams':get_my_teams(request.user),
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})
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else:
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return HttpResponse("invalid form")
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else:
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url = reverse(user_multiflex_select)
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return HttpResponseRedirect(url)
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fieldlist,fielddict = dataprep.getstatsfields()
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fieldlist = [xparam,yparam,groupby,
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'workoutid','spm','driveenergy',
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'workoutstate']
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# prepare data frame
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datadf = dataprep.read_cols_df_sql(ids,fieldlist)
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datadf = dataprep.clean_df_stats(datadf,workstrokesonly=workstrokesonly)
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datadf = dataprep.filter_df(datadf,'spm',spmmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'spm',spmmax,
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largerthan=False)
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datadf = dataprep.filter_df(datadf,'driveenergy',workmin,
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largerthan=True)
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datadf = dataprep.filter_df(datadf,'driveneergy',workmax,
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largerthan=False)
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datadf.dropna(axis=0,how='any',inplace=True)
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datemapping = {
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w.id:w.date for w in workouts
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}
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datadf['date'] = datadf['workoutid']
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datadf['date'].replace(datemapping,inplace=True)
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today = datetime.date.today()
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datadf['days ago'] = map(lambda x : x.days, datadf.date - today)
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if groupby != 'date':
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bins = np.arange(datadf[groupby].min()-binsize,
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datadf[groupby].max()+binsize,
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binsize)
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groups = datadf.groupby(pd.cut(datadf[groupby],bins,labels=False))
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else:
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bins = np.arange(datadf['days ago'].min()-binsize,
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datadf['days ago'].max()+binsize,
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binsize,
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)
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groups = datadf.groupby(pd.cut(datadf['days ago'], bins,
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labels=False))
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xvalues = groups.mean()[xparam]
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yvalues = groups.mean()[yparam]
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xerror = groups.std()[xparam]
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yerror = groups.std()[yparam]
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groupsize = groups.count()[xparam]
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#groupsize = 15.*np.log10(1+99.*groupsize/float(max(groupsize)))
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groupsize = 30.*np.sqrt(groupsize/float(max(groupsize)))
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df = pd.DataFrame({
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xparam:xvalues,
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yparam:yvalues,
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'xerror':xerror,
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'yerror':yerror,
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'groupsize':groupsize,
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})
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if groupby != 'date':
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try:
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df['groupval'] = groups.mean()[groupby],
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except ValueError:
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df['groupval'] = groups.mean()[groupby].fillna(value=0)
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else:
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try:
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df['groupval'] = [x.strftime("%Y-%m-%d") for x in groups.min()[groupby]]
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except AttributeError:
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df['groupval'] = groups.mean()['days ago'].fillna(value=0)
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if userid == 0:
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extratitle = ''
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else:
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u = User.objects.get(id=userid)
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extratitle = ' '+u.first_name+' '+u.last_name
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script,div = interactive_multiflex(df,xparam,yparam,
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groupby,
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extratitle=extratitle,
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ploterrorbars=ploterrorbars)
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return render(request,'multiflex.html',
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{'interactiveplot':script,
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'the_div':div,
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'chartform':chartform,
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'userid':userid,
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'teams':get_my_teams(request.user),
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})
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# Box plots
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@user_passes_test(ispromember,login_url="/",redirect_field_name=None)
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def user_boxplot_select(request,
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Reference in New Issue
Block a user