adding first pie chart
This commit is contained in:
Sander Roosendaal
@@ -169,6 +169,80 @@ def tailwind(bearing,vwind,winddir):
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from rowers.dataprep import nicepaceformat,niceformat
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from rowers.dataprep import timedeltaconv
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from math import pi
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def interactive_hr_piechart(df,rower,title):
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df.sort_values(by='hr',inplace=True)
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qry = 'hr < {ut2}'.format(ut2=rower.ut2)
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frac_lut2 = len(df.query(qry))/len(df)
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qry = 'hr < {ut1}'.format(ut1=rower.ut1,ut2=rower.ut2)
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frac_ut2 = len(df.query(qry))/len(df)
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qry = 'hr < {at}'.format(ut1=rower.ut1,at=rower.at)
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frac_ut1 = len(df.query(qry))/len(df)
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qry = 'hr < {tr}'.format(at=rower.at,tr=rower.tr)
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frac_at = len(df.query(qry))/len(df)
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qry = 'hr < {an}'.format(tr=rower.tr,an=rower.an)
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frac_tr = len(df.query(qry))/len(df)
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frac_an = 1.
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source_starts = 2*pi*pd.Series([
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0,
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frac_lut2,
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frac_ut2,
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frac_ut1,
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frac_at,
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frac_tr,
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])
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source_ends = 2*pi*pd.Series([
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frac_lut2,
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frac_ut2,
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frac_ut1,
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frac_at,
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frac_tr,
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frac_an,
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])
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source_legends = [
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'<ut2',
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'ut2',
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'ut1',
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'at',
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'tr',
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'an',
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]
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colors = ['gray','yellow','lime','blue','purple','red']
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size=220
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TOOLS = 'save'
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z = figure(title="HR "+title, x_range=(-1,1), y_range=(-1,1), width=size, height=size,
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tools=TOOLS,
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)
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for start, end , legend, color in zip(source_starts, source_ends, source_legends, colors[0:len(source_starts)]):
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z.wedge(x=0, y=0, radius=1, start_angle=start, end_angle=end, color=color, legend=legend)
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z.toolbar_location = 'right'
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z.legend.visible = False
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z.axis.visible = False
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z.xgrid.grid_line_color = None
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z.ygrid.grid_line_color = None
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z.outline_line_color = None
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return components(z)
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def interactive_boxchart(datadf,fieldname,extratitle='',
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spmmin=0,spmmax=0,workmin=0,workmax=0):
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@@ -5,12 +5,76 @@
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{% block title %}Rowsandall {% endblock %}
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{% block main %}
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<h1>History</h1>
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<ul class="main-content">
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<li class="grid_4">
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<h1>Future Functionality</h1>
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<script async="true" src="https://cdn.pydata.org/bokeh/release/bokeh-1.0.4.min.js"></script>
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<li class="grid_1">
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<h2>All workouts</h2>
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<p>Watch this space</p>
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<p>
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<table class="listtable shortpadded">
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<tbody>
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<tr>
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<td>Total Distance</td><td>{{ totalsdict|lookup:"distance"}} meters</td>
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</tr>
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<tr>
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<td>Total Duration</td><td>{{ totalsdict|lookup:"duration"}} hours</td>
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</tr>
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<tr>
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<td>Number of workouts</td><td>{{ totalsdict|lookup:"nrworkouts"}}</td>
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</tr>
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<tr>
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<td>Average heart rate</td><td>{{ totalsdict|lookup:"hrmean"}} bpm</td>
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</tr>
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<tr>
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<td>Maximum heart rate</td><td>{{ totalsdict|lookup:"hrmax"}} bpm</td>
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</tr>
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<tr>
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<td>Average power</td><td>{{ totalsdict|lookup:"powermean"}} W</td>
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</tr>
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<tr>
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<td>Maximum power</td><td>{{ totalsdict|lookup:"powermax"}} W</td>
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</tr>
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</tbody>
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</table>
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</p>
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</li>
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<li>
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<div>{{ totalscript|safe }}{{ totaldiv|safe }}</div>
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</li>
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{% for ddict in typedicts %}
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<li class="grid_1">
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<h2>{{ ddict|lookup:"wtype"}}</h2>
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<p>
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<table class="listtable shortpadded">
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<tbody>
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<tr>
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<td>Total Distance</td><td>{{ ddict|lookup:"distance"}} meters</td>
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</tr>
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<tr>
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<td>Total Duration</td><td>{{ ddict|lookup:"duration"}} hours</td>
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</tr>
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<tr>
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<td>Number of workouts</td><td>{{ ddict|lookup:"nrworkouts"}}</td>
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</tr>
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<tr>
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<td>Average heart rate</td><td>{{ ddict|lookup:"hrmean"}} bpm</td>
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</tr>
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<tr>
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<td>Maximum heart rate</td><td>{{ ddict|lookup:"hrmax"}} bpm</td>
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</tr>
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<tr>
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<td>Average power</td><td>{{ ddict|lookup:"powermean"}} W</td>
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</tr>
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<tr>
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<td>Maximum power</td><td>{{ ddict|lookup:"powermax"}} W</td>
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</tr>
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</tbody>
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</table>
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</p>
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</li>
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{% endfor %}
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</ul>
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{% endblock %}
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@@ -4654,6 +4654,68 @@ class AlertDelete(DeleteView):
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@login_required()
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def history_view(request,userid=0):
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r = getrequestrower(request,userid=userid)
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usertimezone = pytz.timezone(r.defaulttimezone)
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activity_enddate = timezone.now()
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activity_enddate = activity_enddate.replace(hour=23,minute=59,second=59).astimezone(usertimezone)
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activity_startdate = activity_enddate-datetime.timedelta(days=15)
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activity_startdate = activity_startdate.replace(hour=0,minute=0,second=0)
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g_workouts = Workout.objects.filter(
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user=r,
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startdatetime__gte=activity_startdate,
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startdatetime__lte=activity_enddate,
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duplicate=False,
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privacy='visible'
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).order_by("-startdatetime")
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ids = [w.id for w in g_workouts]
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columns = ['hr','power']
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df = getsmallrowdata_db(columns,ids=ids)
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totalmeters,totalhours, totalminutes = get_totals(g_workouts)
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# meters, duration per workout type
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wtypes = list(set([w.workouttype for w in g_workouts]))
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listofdicts = []
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for wtype in wtypes:
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a_workouts = g_workouts.filter(workouttype=wtype)
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wmeters, whours, wminutes = get_totals(a_workouts)
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ddict = {}
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ddict['wtype'] = mytypes.workouttypes_ordered[wtype]
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ddict['distance'] = wmeters
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ddict['duration'] = "{whours}:{wminutes:02d}".format(
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whours=whours,
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wminutes=wminutes
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)
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ddf = getsmallrowdata_db(columns,ids=[w.id for w in a_workouts])
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ddict['hrmean'] = ddf['hr'].mean().astype(int)
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ddict['hrmax'] = ddf['hr'].max().astype(int)
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ddict['powermean'] = ddf['power'].mean().astype(int)
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ddict['powermax'] = ddf['power'].max().astype(int)
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ddict['nrworkouts'] = a_workouts.count()
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listofdicts.append(ddict)
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# interactive hr pie chart
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totalscript,totaldiv = interactive_hr_piechart(df,r,'All Workouts')
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# interactive power pie chart
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totalsdict = {}
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totalsdict['duration'] = "{totalhours}:{totalminutes}".format(
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totalhours=totalhours,
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totalminutes=totalminutes
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)
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totalsdict['distance'] = totalmeters
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totalsdict['powermean'] = df['power'].mean().astype(int)
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totalsdict['powermax'] = df['power'].max().astype(int)
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totalsdict['hrmean'] = df['hr'].mean().astype(int)
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totalsdict['hrmax'] = df['hr'].max().astype(int)
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totalsdict['nrworkouts'] = g_workouts.count()
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breadcrumbs = [
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{
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@@ -4670,5 +4732,9 @@ def history_view(request,userid=0):
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{
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'rower':r,
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'breadcrumbs':breadcrumbs,
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'active':'nav-analysis'
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'active':'nav-analysis',
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'totalsdict':totalsdict,
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'typedicts':listofdicts,
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'totalscript':totalscript,
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'totaldiv':totaldiv,
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})
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@@ -1918,7 +1918,7 @@ def workouts_view(request,message='',successmessage='',
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g_workouts = Workout.objects.filter(
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team=theteam,user=r,
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startdatetime__gte=activity_startdate,
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enddatetime__lte=activity_enddate,
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startdatetime__lte=activity_enddate,
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duplicate=False,
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privacy='visible').order_by("-startdatetime")
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