from rowers.models import Workout, User, Rower, WorkoutForm,RowerForm,GraphImage from rowingdata import rower as rrower from rowingdata import main as rmain from rowingdata import cumcpdata,histodata from rowingdata import rowingdata as rrdata from django.utils import timezone from bokeh.plotting import figure, ColumnDataSource, Figure,curdoc from bokeh.models import CustomJS,Slider from bokeh.charts import Histogram,HeatMap from bokeh.resources import CDN,INLINE from bokeh.embed import components from bokeh.layouts import layout,widgetbox from bokeh.layouts import row as layoutrow from bokeh.layouts import column as layoutcolumn from bokeh.models import LinearAxis,LogAxis,Range1d,DatetimeTickFormatter,HoverTool from bokeh.io import output_file, show from bokeh.models import ( GMapPlot, GMapOptions, ColumnDataSource, Circle, DataRange1d, PanTool, WheelZoomTool, BoxSelectTool, SaveTool, ResizeTool, ResetTool, TapTool,CrosshairTool,BoxZoomTool, Span, Label ) #from bokeh.models.widgets import Slider, Select, TextInput from bokeh.core.properties import value from collections import OrderedDict from django.conf import settings import datetime import math import numpy as np import pandas as pd from pytz import timezone as tz,utc from django.utils.timezone import get_current_timezone from django.utils.timezone import activate activate(settings.TIME_ZONE) thetimezone = get_current_timezone() from scipy.stats import linregress from scipy import optimize from scipy.signal import savgol_filter import stravastuff from rowers.dataprep import rdata import rowers.dataprep as dataprep axlabels = { 'time': 'Time', 'distance': 'Distance (m)', 'cumdist': 'Distance (m)', 'hr': 'Heart Rate (bpm)', 'spm': 'Stroke Rate (spm)', 'pace': 'Pace (/500m)', 'power': 'Power (Watt)', 'averageforce': 'Average Drive Force (lbs)', 'drivelength': 'Drive Length (m)', 'peakforce': 'Peak Drive Force (lbs)', 'forceratio': 'Average/Peak Drive Force Ratio', 'driveenergy': 'Work per Stroke (J)', 'drivespeed': 'Drive Speed (m/s)', 'slip': 'Slip (degrees)', 'catch': 'Catch (degrees)', 'finish': 'Finish (degrees)', 'wash': 'Wash (degrees)', 'peakforceangle': 'Peak Force Angle (degrees)', 'None': '', } yaxminima = { 'hr':100, 'spm':15, 'pace': 1.0e3*210, 'power': 0, 'averageforce': 0, 'peakforce': 0, 'forceratio':0, 'drivelength':0.5, 'driveenergy': 0, 'drivespeed': 0, 'slip': 0, 'catch': -40, 'finish': 20, 'wash': 0, 'peakforceangle': -20, } yaxmaxima = { 'hr':200, 'spm':45, 'pace': 1.0e3*75, 'power': 600, 'averageforce':200, 'peakforce':400, 'forceratio':1, 'drivelength':2.0, 'driveenergy': 1000, 'drivespeed':4, 'slip': 15, 'catch': -75, 'finish': 55, 'wash': 30, 'peakforceangle': 20, } def tailwind(bearing,vwind,winddir): """ Calculates head-on head/tailwind in direction of rowing positive numbers are tail wind """ b = np.radians(bearing) w = np.radians(winddir) vtail = -vwind*np.cos(w-b) return vtail from rowers.dataprep import nicepaceformat,niceformat from rowers.dataprep import timedeltaconv def interactive_forcecurve(theworkouts,workstrokesonly=False): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' ids = [int(w.id) for w in theworkouts] boattype = theworkouts[0].boattype columns = ['catch','slip','wash','finish','averageforce', 'peakforceangle','peakforce','spm','distance', 'workoutstate'] rowdata = dataprep.getsmallrowdata_db(columns,ids=ids) workoutstateswork = [1,4,5,8,9,6,7] workoutstatesrest = [3] workoutstatetransition = [0,2,10,11,12,13] if workstrokesonly: try: rowdata = rowdata[~rowdata['workoutstate'].isin(workoutstatesrest)] except KeyError: pass catchav = rowdata['catch'].mean() finishav = rowdata['finish'].mean() washav = rowdata['wash'].mean() slipav = rowdata['slip'].mean() peakforceav = rowdata['peakforce'].mean() averageforceav = rowdata['averageforce'].mean() peakforceangleav = rowdata['peakforceangle'].mean() x = [catchav, catchav+slipav, peakforceangleav, finishav-washav, finishav] thresholdforce = 100 if 'x' in boattype else 200 thresholdforce /= 4.45 # N to lbs y = [0,thresholdforce, peakforceav, thresholdforce,0] source = ColumnDataSource( data = dict( x = x, y = y, )) source2 = ColumnDataSource( rowdata ) plot = Figure(tools=TOOLS, toolbar_sticky=False) avf = Span(location=averageforceav,dimension='width',line_color='blue', line_dash=[6,6],line_width=2) plot.line('x','y',source=source,color="red") plot.add_layout(avf) peakflabel = Label(x=455,y=530,x_units='screen',y_units='screen', text="Fpeak: {peakforceav:6.2f}".format(peakforceav=peakforceav), background_fill_alpha=.7, text_color='blue', ) avflabel = Label(x=465,y=500,x_units='screen',y_units='screen', text="Favg: {averageforceav:6.2f}".format(averageforceav=averageforceav), background_fill_alpha=.7, text_color='blue', ) catchlabel = Label(x=460,y=470,x_units='screen',y_units='screen', text="Catch: {catchav:6.2f}".format(catchav=catchav), background_fill_alpha=0.7, text_color='red', ) peakforceanglelabel = Label(x=420,y=440,x_units='screen',y_units='screen', text="Peak angle: {peakforceangleav:6.2f}".format(peakforceangleav=peakforceangleav), background_fill_alpha=0.7, text_color='red', ) finishlabel = Label(x=455,y=410,x_units='screen',y_units='screen', text="Finish: {finishav:6.2f}".format(finishav=finishav), background_fill_alpha=0.7, text_color='red', ) sliplabel = Label(x=470,y=380,x_units='screen',y_units='screen', text="Slip: {slipav:6.2f}".format(slipav=slipav), background_fill_alpha=0.7, text_color='red', ) washlabel = Label(x=460,y=350,x_units='screen',y_units='screen', text="Wash: {washav:6.2f}".format(washav=washav), background_fill_alpha=0.7, text_color='red', ) plot.add_layout(peakflabel) plot.add_layout(peakforceanglelabel) plot.add_layout(avflabel) plot.add_layout(catchlabel) plot.add_layout(sliplabel) plot.add_layout(washlabel) plot.add_layout(finishlabel) plot.xaxis.axis_label = "Angle" plot.yaxis.axis_label = "Force (lbs)" plot.title.text = theworkouts[0].name plot.title.text_font_size=value("1.0em") yrange1 = Range1d(start=0,end=200) plot.y_range = yrange1 xrange1 = Range1d(start=yaxmaxima['catch'],end=yaxmaxima['finish']) plot.x_range = xrange1 callback = CustomJS(args = dict( source=source, source2=source2, avf=avf, avflabel=avflabel, catchlabel=catchlabel, finishlabel=finishlabel, sliplabel=sliplabel, washlabel=washlabel, peakflabel=peakflabel, peakforceanglelabel=peakforceanglelabel, ), code=""" var data = source.data var data2 = source2.data var x = data['x'] var y = data['y'] var spm1 = data2['spm'] var distance1 = data2['distance'] var thresholdforce = y[1] var c = source2.data['catch'] var finish = data2['finish'] var slip = data2['slip'] var wash = data2['wash'] var peakforceangle = data2['peakforceangle'] var peakforce = data2['peakforce'] var averageforce = data2['averageforce'] var minspm = minspm.value var maxspm = maxspm.value var mindist = mindist.value var maxdist = maxdist.value var catchav = 0 var finishav = 0 var slipav = 0 var washav = 0 var peakforceangleav = 0 var averageforceav = 0 var peakforceav = 0 var count = 0 for (i=0; i=minspm && spm1[i]<=maxspm) { if (distance1[i]>=mindist && distance1[i]<=maxdist) { catchav += c[i] finishav += finish[i] slipav += slip[i] washav += wash[i] peakforceangleav += peakforceangle[i] averageforceav += averageforce[i] peakforceav += peakforce[i] count += 1 } } } catchav /= count finishav /= count slipav /= count washav /= count peakforceangleav /= count peakforceav /= count averageforceav /= count data['x'] = [catchav,catchav+slipav,peakforceangleav,finishav-washav,finishav] data['y'] = [0,thresholdforce,peakforceav,thresholdforce,0] avf.location = averageforceav avflabel.text = 'Favg: '+averageforceav.toFixed(2) catchlabel.text = 'Catch: '+catchav.toFixed(2) finishlabel.text = 'Finish: '+finishav.toFixed(2) sliplabel.text = 'Slip: '+slipav.toFixed(2) washlabel.text = 'Wash: '+washav.toFixed(2) peakflabel.text = 'Fpeak: '+peakforceav.toFixed(2) peakforceanglelabel.text = 'Peak angle: '+peakforceangleav.toFixed(2) source.trigger('change'); """) slider_spm_min = Slider(start=15.0, end=55,value=15.0, step=.1, title="Min SPM",callback=callback) callback.args["minspm"] = slider_spm_min slider_spm_max = Slider(start=15.0, end=55,value=55.0, step=.1, title="Max SPM",callback=callback) callback.args["maxspm"] = slider_spm_max distmax = 100+100*int(rowdata['distance'].max()/100.) slider_dist_min = Slider(start=0,end=distmax,value=0,step=1, title="Min Distance",callback=callback) callback.args["mindist"] = slider_dist_min slider_dist_max = Slider(start=0,end=distmax,value=distmax, step=1, title="Max Distance",callback=callback) callback.args["maxdist"] = slider_dist_max layout = layoutrow([layoutcolumn([slider_spm_min, slider_spm_max, slider_dist_min, slider_dist_max, ], ), plot]) script, div = components(layout) js_resources = INLINE.render_js() css_resources = INLINE.render_css() return [script,div,js_resources,css_resources] def interactive_histoall(theworkouts): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' ids = [int(w.id) for w in theworkouts] rowdata = dataprep.getsmallrowdata_db(['power'],ids=ids) histopwr = rowdata['power'].values if len(histopwr) == 0: return "","CSV file not found","","" # throw out nans histopwr = histopwr[~np.isinf(histopwr)] histopwr = histopwr[histopwr > 25] plot = Figure(tools=TOOLS,plot_width=900, toolbar_sticky=False, toolbar_location="above" ) hist,edges = np.histogram(histopwr,bins=150) histsum = np.cumsum(hist) histsum = 100.*histsum/max(histsum) hist_norm = 100.*hist/float(hist.sum()) source = ColumnDataSource( data = dict( left = edges[:-1], right = edges[1:], histsum = histsum, hist_norm = hist_norm, ) ) # plot.quad(top='hist_norm',bottom=0,left=edges[:-1],right=edges[1:]) plot.quad(top='hist_norm',bottom=0,left='left',right='right',source=source) plot.xaxis.axis_label = "Power (W)" plot.yaxis.axis_label = "% of strokes" plot.y_range = Range1d(0,1.05*max(hist_norm)) hover = plot.select(dict(type=HoverTool)) hover.tooltips = OrderedDict([ ('Power(W)','@left{int}'), ('% of strokes','@hist_norm'), ('Cumulative %','@histsum{int}'), ]) hover.mode = 'mouse' plot.extra_y_ranges = {"fraction": Range1d(start=0,end=105)} plot.line('right','histsum',source=source,color="red", y_range_name="fraction") plot.add_layout(LinearAxis(y_range_name="fraction", axis_label="Cumulative % of strokes"),'right') script, div = components(plot) return [script,div] def googlemap_chart(lat,lon,name=""): # plot tools TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize' map_options = GMapOptions(lat = lat.mean(),lng=lon.mean(), map_type="roadmap",zoom=11) plot = GMapPlot( x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, api_key = "AIzaSyAgu1w9QSthaGPMLp8y9JedPoMc9sfEgJ8", plot_width=400,plot_height=400, toolbar_sticky=False, ) source = ColumnDataSource( data = dict( lat=lat, lon=lon, ) ) circle = Circle(x="lon",y="lat",size=5,fill_color="blue", fill_alpha=0.2,line_color=None) plot.add_glyph(source,circle) plot.add_tools(PanTool(), WheelZoomTool(), SaveTool(), ResizeTool(), ResetTool(), TapTool(),CrosshairTool(), ) plot.title.text = name plot.title.text_font="1.0em" script, div = components(plot) return [script,div] def interactive_cpchart(thedistances,thesecs,theavpower, theworkouts,promember=0): message = 0 # plot tools if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair' x_axis_type = 'log' y_axis_type = 'linear' thesecs = pd.Series(thesecs) velo = thedistances/thesecs p = pd.Series(500./velo) p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) source = ColumnDataSource( data = dict( dist = thedistances, duration = thesecs, spm = 0*theavpower, tim = niceformat( thesecs.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) ), power = theavpower, fpace = nicepaceformat(p2), ) ) # fitting the data to Paul if len(thedistances)>=2: paulslope, paulintercept,r,p,stderr = linregress(np.log10(thedistances),p) else: paulslope = 5.0/np.log10(2.0) paulintercept = p[0]-paulslope*np.log10(thedistances[0]) fitx = pd.Series(np.arange(100)*2*max(np.log10(thedistances))/100.) fitp = paulslope*fitx+paulintercept fitvelo = 500./fitp fitpower = 2.8*(fitvelo**3) fitt = 10**fitx/fitvelo fitp2 = fitp.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) sourcepaul = ColumnDataSource( data = dict( dist = 10**fitx, duration = fitt, power = fitpower, spm = 0*fitpower, tim = niceformat( fitt.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) ), fpace = nicepaceformat(fitp2), ) ) # fitting the data to three parameter CP model fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3])) errfunc = lambda pars,x,y: fitfunc(pars,x)-y p0 = [500,350,10,8000] p1 = p0 if len(thesecs)>=4: p1, success = optimize.leastsq(errfunc, p0[:], args = (thesecs,theavpower)) else: factor = fitfunc(p0,thesecs.mean())/theavpower.mean() p1 = [p0[0]/factor,p0[1]/factor,p0[2],p0[3]] fitt = pd.Series(10**(4*np.arange(100)/100.)) fitpower = fitfunc(p1,fitt) message = "" if len(fitpower[fitpower<0]) > 0: message = "CP model fit didn't give correct results" fitvelo = (fitpower/2.8)**(1./3.) fitdist = fitt*fitvelo fitp = 500./fitvelo fitp2 = fitp.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) sourcecomplex = ColumnDataSource( data = dict( dist = fitdist, duration = fitt, tim = niceformat( fitt.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) ), spm = 0*fitpower, power = fitpower, fpace = nicepaceformat(fitp2), ) ) # making the plot plot = Figure(tools=TOOLS,x_axis_type=x_axis_type, plot_width=900, toolbar_location="above", toolbar_sticky=False) plot.circle('duration','power',source=source,fill_color='red',size=15, legend='Power') plot.xaxis.axis_label = "Duration (seconds)" plot.yaxis.axis_label = "Power (W)" therows = [] for workout in theworkouts: f1 = workout.csvfilename rowdata = rdata(f1) if rowdata != 0: therows.append(rowdata) cpdata = cumcpdata(therows) velo = cpdata['Distance']/cpdata['Delta'] p = 500./velo p2 = p.fillna(method='ffill').apply(lambda x: timedeltaconv(x)) source2 = ColumnDataSource( data = dict( duration = cpdata['Delta'], power = cpdata['CP'], tim = niceformat( cpdata['Delta'].fillna(method='ffill').apply(lambda x: timedeltaconv(x)) ), dist = cpdata['Distance'], pace = nicepaceformat(p2), ) ) plot.circle('duration','power',source=source2, fill_color='blue',size=3, legend = 'Power from segments') hover = plot.select(dict(type=HoverTool)) hover.tooltips = OrderedDict([ ('Duration ','@tim'), ('Power (W)','@power{int}'), ('Distance (m)','@dist{int}'), ('Pace (/500m)','@fpace'), ]) hover.mode = 'mouse' plot.y_range = Range1d(0,1.5*max(theavpower)) plot.x_range = Range1d(1,2*max(thesecs)) plot.legend.orientation = "vertical" plot.line('duration','power',source=sourcepaul,legend="Paul's Law") plot.line('duration','power',source=sourcecomplex,legend="CP Model", color='green') script, div = components(plot) return [script,div,paulslope,paulintercept,p1,message] def interactive_windchart(id=0,promember=0): # check if valid ID exists (workout exists) row = Workout.objects.get(id=id) # g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime") f1 = row.csvfilename # create interactive plot plot = Figure(plot_width=400,plot_height=300) # get user # u = User.objects.get(id=row.user.id) r = row.user u = r.user rr = rrower(hrmax=r.max,hrut2=r.ut2, hrut1=r.ut1,hrat=r.at, hrtr=r.tr,hran=r.an,ftp=r.ftp) rowdata = rdata(f1,rower=rr) if rowdata == 0: return 0 dist = rowdata.df.ix[:,'cum_dist'] try: vwind = rowdata.df.ix[:,'vwind'] winddirection = rowdata.df.ix[:,'winddirection'] bearing = rowdata.df.ix[:,'bearing'] except KeyError: rowdata.add_wind(0,0) rowdata.add_bearing() vwind = rowdata.df.ix[:,'vwind'] winddirection = rowdata.df.ix[:,'winddirection'] bearing = rowdata.df.ix[:,'winddirection'] rowdata.write_csv(f1,gzip=True) dataprep.update_strokedata(id,rowdata.df) winddirection = winddirection % 360 winddirection = (winddirection + 360) % 360 tw = tailwind(bearing,vwind,1.0*winddirection) source = ColumnDataSource( data = dict( dist=dist, vwind=vwind, tw=tw, winddirection=winddirection, ) ) # plot tools if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,crosshair' # making the plot plot = Figure(tools=TOOLS,plot_width=400,height=500, # toolbar_location="below", toolbar_sticky=False, ) plot.line('dist','vwind',source=source,legend="Wind Speed (m/s)") plot.line('dist','tw',source=source,legend="Tail (+)/Head (-) Wind (m/s)",color='black') plot.title.text = row.name # plot.title.text_font_size=value("1.0em") plot.title.text_font="1.0em" plot.xaxis.axis_label = "Distance (m)" plot.yaxis.axis_label = "Wind Speed (m/s)" plot.y_range = Range1d(-7,7) plot.extra_y_ranges = {"winddirection": Range1d(start=0,end=360)} plot.line('dist','winddirection',source=source, legend='Wind Direction',color="red", y_range_name="winddirection") plot.add_layout(LinearAxis(y_range_name="winddirection",axis_label="Wind Direction (degree)"),'right') script, div = components(plot) return [script,div] def interactive_streamchart(id=0,promember=0): # check if valid ID exists (workout exists) row = Workout.objects.get(id=id) # g = GraphImage.objects.filter(workout=row).order_by("-creationdatetime") f1 = row.csvfilename # create interactive plot plot = Figure(plot_width=400, ) # get user # u = User.objects.get(id=row.user.id) r = row.user u = r.user rr = rrower(hrmax=r.max,hrut2=r.ut2, hrut1=r.ut1,hrat=r.at, hrtr=r.tr,hran=r.an,ftp=r.ftp) rowdata = rdata(f1,rower=rr) if rowdata == 0: return "","CSV Data File Not Found" dist = rowdata.df.ix[:,'cum_dist'] try: vstream = rowdata.df.ix[:,'vstream'] except KeyError: rowdata.add_stream(0) vstream = rowdata.df.ix[:,'vstream'] rowdata.write_csv(f1,gzip=True) dataprep.update_strokedata(id,rowdata.df) # plot tools if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,crosshair' # making the plot plot = Figure(tools=TOOLS,plot_width=400,height=500, # toolbar_location="below", toolbar_sticky=False, ) plot.line(dist,vstream,legend="River Stream Velocity (m/s)") plot.title.text = row.name plot.title.text_font_size=value("1.0em") plot.xaxis.axis_label = "Distance (m)" plot.yaxis.axis_label = "River Current (m/s)" plot.y_range = Range1d(-2,2) script, div = components(plot) return [script,div] def interactive_chart(id=0,promember=0): # Add hover to this comma-separated string and see what changes if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair' columns = ['time','pace','hr','fpace','ftime'] datadf = dataprep.getsmallrowdata_db(columns,ids=[id]) row = Workout.objects.get(id=id) if datadf.empty: return "","CSV Data File Not Found" else: datadf.sort_values(by='time',ascending=True,inplace=True) #datadf,row = dataprep.getrowdata_db(id=id) #if datadf.empty: #return "","CSV Data File Not Found" source = ColumnDataSource( datadf ) plot = Figure(x_axis_type="datetime",y_axis_type="datetime", plot_width=400, plot_height=400, toolbar_sticky=False, tools=TOOLS) plot.line('time','pace',source=source,legend="Pace") plot.title.text = row.name plot.title.text_font_size=value("1.0em") plot.xaxis.axis_label = "Time" plot.yaxis.axis_label = "Pace (/500m)" plot.xaxis[0].formatter = DatetimeTickFormatter( hours = ["%H"], minutes = ["%M"], seconds = ["%S"], days = ["0"], months = [""], years = [""] ) plot.yaxis[0].formatter = DatetimeTickFormatter( seconds = ["%S"], minutes = ["%M"] ) ymax = 90. ymin = 150. if row.workouttype == 'water': ymax = 90. ymin = 210. plot.y_range = Range1d(1.e3*ymin,1.e3*ymax) hover = plot.select(dict(type=HoverTool)) hover.tooltips = OrderedDict([ ('Time','@ftime'), ('Pace','@fpace'), ('HR','@hr{int}'), ('SPM','@spm{1.1}'), ]) hover.mode = 'mouse' plot.extra_y_ranges = {"hrax": Range1d(start=100,end=200)} plot.line('time','hr',source=source,color="red", y_range_name="hrax", legend="Heart Rate") plot.add_layout(LinearAxis(y_range_name="hrax",axis_label="HR"),'right') plot.legend.location = "bottom_right" script, div = components(plot) return [script,div] def interactive_cum_flex_chart2(theworkouts,promember=0, xparam='spm', yparam1='power', yparam2='spm'): # datadf = dataprep.smalldataprep(theworkouts,xparam,yparam1,yparam2) ids = [int(w.id) for w in theworkouts] datadf = dataprep.getsmallrowdata_db([xparam,yparam1,yparam2],ids=ids) yparamname1 = axlabels[yparam1] yparamname2 = axlabels[yparam2] datadf = datadf[datadf[yparam1] > 0] datadf = datadf[datadf[xparam] > 0] if yparam2 != 'None': datadf = datadf[datadf[yparam2] > 0] # check if dataframe not empty if datadf.empty: return ['','

No non-zero data in selection

','',''] datadf['x1'] = datadf.ix[:,xparam] datadf['y1'] = datadf.ix[:,yparam1] if yparam2 != 'None': datadf['y2'] = datadf.ix[:,yparam2] else: datadf['y2'] = datadf['y1'] if xparam=='distance': xaxmax = datadf['x1'].max() xaxmin = datadf['x1'].min() else: xaxmax = yaxmaxima[xparam] xaxmin = yaxminima[xparam] # average values x1mean = datadf['x1'].mean() y1mean = datadf['y1'].mean() y2mean = datadf['y2'].mean() xvals = pd.Series(xaxmin+np.arange(100)*(xaxmax-xaxmin)/100.) x_axis_type = 'linear' y_axis_type = 'linear' datadf['xname'] = xparam datadf['yname1'] = yparam1 if yparam2 != 'None': datadf['yname2'] = yparam2 else: datadf['yname2'] = yparam1 source = ColumnDataSource( datadf ) source2 = ColumnDataSource( datadf.copy() ) # Add hover to this comma-separated string and see what changes if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,crosshair' plot = Figure(x_axis_type=x_axis_type,y_axis_type=y_axis_type, tools=TOOLS, toolbar_location="above", toolbar_sticky=False) x1means = Span(location=x1mean,dimension='height',line_color='green', line_dash=[6,6], line_width=2) y1means = Span(location=y1mean,dimension='width',line_color='blue', line_dash=[6,6],line_width=2) y2means = y1means xlabel = Label(x=370,y=130,x_units='screen',y_units='screen', text=xparam+": {x1mean:6.2f}".format(x1mean=x1mean), background_fill_alpha=.7, text_color='green', ) plot.add_layout(x1means) plot.add_layout(xlabel) plot.add_layout(y1means) y1label = Label(x=370,y=100,x_units='screen',y_units='screen', text=yparam1+": {y1mean:6.2f}".format(y1mean=y1mean), background_fill_alpha=.7, text_color='blue', ) plot.add_layout(y1label) y2label = y1label plot.circle('x1','y1',source=source2,fill_alpha=0.3,line_color=None, legend=yparamname1, ) plot.xaxis.axis_label = axlabels[xparam] plot.yaxis.axis_label = axlabels[yparam1] yrange1 = Range1d(start=yaxminima[yparam1],end=yaxmaxima[yparam1]) plot.y_range = yrange1 xrange1 = Range1d(start=yaxminima[xparam],end=yaxmaxima[xparam]) plot.x_range = xrange1 if yparam2 != 'None': yrange2 = Range1d(start=yaxminima[yparam2],end=yaxmaxima[yparam2]) plot.extra_y_ranges = {"yax2": yrange2} plot.circle('x1','y2',color="red",y_range_name="yax2", legend=yparamname2, source=source2,fill_alpha=0.3,line_color=None) plot.add_layout(LinearAxis(y_range_name="yax2", axis_label=axlabels[yparam2]),'right') y2means = Span(location=y2mean,dimension='width',line_color='red', line_dash=[6,6],line_width=2,y_range_name="yax2") plot.add_layout(y2means) y2label = Label(x=370,y=70,x_units='screen',y_units='screen', text=yparam2+": {y2mean:6.2f}".format(y2mean=y2mean), background_fill_alpha=.7, text_color='red', ) if yparam2 != 'pace' and yparam2 != 'time': plot.add_layout(y2label) callback = CustomJS(args = dict(source=source,source2=source2, x1means=x1means, y1means=y1means, y1label=y1label, y2label=y2label, xlabel=xlabel, y2means=y2means), code=""" var data = source.data var data2 = source2.data var x1 = data['x1'] var y1 = data['y1'] var y2 = data['y2'] var spm1 = data['spm'] var distance1 = data['distance'] var xname = data['xname'][0] var yname1 = data['yname1'][0] var yname2 = data['yname2'][0] var minspm = minspm.value var maxspm = maxspm.value var mindist = mindist.value var maxdist = maxdist.value var xm = 0 var ym1 = 0 var ym2 = 0 data2['x1'] = [] data2['y1'] = [] data2['y2'] = [] data2['spm'] = [] data2['distance'] = [] data2['x1mean'] = [] data2['y1mean'] = [] data2['y2mean'] = [] data2['xvals'] = [] data2['y1vals'] = [] data2['y2vals'] = [] for (i=0; i=minspm && spm1[i]<=maxspm) { if (distance1[i]>=mindist && distance1[i]<=maxdist) { data2['x1'].push(x1[i]) data2['y1'].push(y1[i]) data2['y2'].push(y2[i]) data2['spm'].push(spm1[i]) data2['distance'].push(distance1[i]) xm += x1[i] ym1 += y1[i] ym2 += y2[i] } } } xm /= data2['x1'].length ym1 /= data2['x1'].length ym2 /= data2['x1'].length data2['x1mean'] = [xm,xm] data2['y1mean'] = [ym1,ym1] data2['y2mean'] = [ym2,ym2] x1means.location = xm y1means.location = ym1 y2means.location = ym2 y1label.text = yname1+': '+ym1.toFixed(2) y2label.text = yname2+': '+ym2.toFixed(2) xlabel.text = xname+': '+xm.toFixed(2) source2.trigger('change'); """) slider_spm_min = Slider(start=15.0, end=55,value=15.0, step=.1, title="Min SPM",callback=callback) callback.args["minspm"] = slider_spm_min slider_spm_max = Slider(start=15.0, end=55,value=55.0, step=.1, title="Max SPM",callback=callback) callback.args["maxspm"] = slider_spm_max distmax = 100+100*int(datadf['distance'].max()/100.) slider_dist_min = Slider(start=0,end=distmax,value=0,step=1, title="Min Distance",callback=callback) callback.args["mindist"] = slider_dist_min slider_dist_max = Slider(start=0,end=distmax,value=distmax, step=1, title="Max Distance",callback=callback) callback.args["maxdist"] = slider_dist_max layout = layoutrow([layoutcolumn([slider_spm_min, slider_spm_max, slider_dist_min, slider_dist_max, ], ), plot]) script, div = components(layout) js_resources = INLINE.render_js() css_resources = INLINE.render_css() return [script,div,js_resources,css_resources] def interactive_flex_chart2(id=0,promember=0, xparam='time', yparam1='pace', yparam2='hr', plottype='line', workstrokesonly=False): #rowdata,row = dataprep.getrowdata_db(id=id) columns = [xparam,yparam1,yparam2, 'ftime','distance','fpace', 'power','hr','spm', 'time','pace','workoutstate'] rowdata = dataprep.getsmallrowdata_db(columns,ids=[id]) row = Workout.objects.get(id=id) if rowdata.empty: return "","CSV Data File Not Found" else: rowdata.sort_values(by='time',ascending=True,inplace=True) workoutstateswork = [1,4,5,8,9,6,7] workoutstatesrest = [3] workoutstatetransition = [0,2,10,11,12,13] if workstrokesonly: try: rowdata = rowdata[~rowdata['workoutstate'].isin(workoutstatesrest)] except KeyError: pass rowdata['x1'] = rowdata.ix[:,xparam] rowdata['y1'] = rowdata.ix[:,yparam1] tseconds = rowdata.ix[:,'time'] if yparam2 != 'None': rowdata['y2'] = rowdata.ix[:,yparam2] else: rowdata['y2'] = rowdata['y1'] if xparam=='time': xaxmax = tseconds.max() xaxmin = tseconds.min() elif xparam=='distance' or xparam=='cumdist': xaxmax = rowdata['x1'].max() xaxmin = rowdata['x1'].min() else: xaxmax = yaxmaxima[xparam] xaxmin = yaxminima[xparam] # average values if xparam != 'time': x1mean = rowdata['x1'].mean() else: x1mean = 0 y1mean = rowdata['y1'].mean() y2mean = rowdata['y2'].mean() if xparam != 'time': xvals = xaxmin+np.arange(100)*(xaxmax-xaxmin)/100. else: xvals = np.arange(100) # constant power plot if yparam1 == 'driveenergy': if xparam == 'spm': yconstantpower = rowdata['y1'].mean()*rowdata['x1'].mean()/xvals x_axis_type = 'linear' y_axis_type = 'linear' if xparam == 'time': x_axis_type = 'datetime' if yparam1 == 'pace': y_axis_type = 'datetime' y1mean = rowdata.ix[:,'pace'].mean() rowdata['xname'] = xparam rowdata['yname1'] = yparam1 if yparam2 != 'None': rowdata['yname2'] = yparam2 else: rowdata['yname2'] = yparam1 # prepare data source = ColumnDataSource( rowdata ) # second source for filtering source2 = ColumnDataSource( rowdata.copy() ) # Add hover to this comma-separated string and see what changes if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair' sizing_mode = 'fixed' # 'scale_width' also looks nice with this example plot = Figure(x_axis_type=x_axis_type,y_axis_type=y_axis_type, tools=TOOLS, toolbar_sticky=False ) x1means = Span(location=x1mean,dimension='height',line_color='green', line_dash=[6,6], line_width=2) y1means = Span(location=y1mean,dimension='width',line_color='blue', line_dash=[6,6],line_width=2) y2means = y1means xlabel = Label(x=370,y=130,x_units='screen',y_units='screen', text=xparam+": {x1mean:6.2f}".format(x1mean=x1mean), background_fill_alpha=.7, text_color='green', ) if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'): plot.add_layout(x1means) plot.add_layout(xlabel) plot.add_layout(y1means) y1label = Label(x=370,y=100,x_units='screen',y_units='screen', text=yparam1+": {y1mean:6.2f}".format(y1mean=y1mean), background_fill_alpha=.7, text_color='blue', ) if yparam1 != 'time' and yparam1 != 'pace': plot.add_layout(y1label) y2label = y1label # average values if yparam1 == 'driveenergy': if xparam == 'spm': plot.line(xvals,yconstantpower,color="green",legend="Constant Power") if plottype=='line': plot.line('x1','y1',source=source2,legend=axlabels[yparam1]) elif plottype=='scatter': plot.scatter('x1','y1',source=source2,legend=axlabels[yparam1],fill_alpha=0.4, line_color=None) plot.title.text = row.name plot.title.text_font_size=value("1.0em") plot.xaxis.axis_label = axlabels[xparam] plot.yaxis.axis_label = axlabels[yparam1] yrange1 = Range1d(start=yaxminima[yparam1],end=yaxmaxima[yparam1]) plot.y_range = yrange1 if (xparam != 'time') and (xparam != 'distance') and (xparam != 'cumdist'): xrange1 = Range1d(start=yaxminima[xparam],end=yaxmaxima[xparam]) plot.x_range = xrange1 if xparam == 'time': xrange1 = Range1d(start=xaxmin,end=xaxmax) plot.x_range = xrange1 plot.xaxis[0].formatter = DatetimeTickFormatter( hours = ["%H"], minutes = ["%M"], seconds = ["%S"], days = ["0"], months = [""], years = [""] ) if yparam1 == 'pace': plot.yaxis[0].formatter = DatetimeTickFormatter( seconds = ["%S"], minutes = ["%M"] ) if yparam2 != 'None': yrange2 = Range1d(start=yaxminima[yparam2],end=yaxmaxima[yparam2]) plot.extra_y_ranges = {"yax2": yrange2} if plottype=='line': plot.line('x1','y2',color="red",y_range_name="yax2", legend=axlabels[yparam2], source=source2) elif plottype=='scatter': plot.scatter('x1','y2',source=source2,legend=axlabels[yparam2] ,fill_alpha=0.4, line_color=None,color="red",y_range_name="yax2") plot.add_layout(LinearAxis(y_range_name="yax2", axis_label=axlabels[yparam2]),'right') y2means = Span(location=y2mean,dimension='width',line_color='red', line_dash=[6,6],line_width=2,y_range_name="yax2") plot.add_layout(y2means) y2label = Label(x=370,y=70,x_units='screen',y_units='screen', text=yparam2+": {y2mean:6.2f}".format(y2mean=y2mean), background_fill_alpha=.7, text_color='red', ) if yparam2 != 'pace' and yparam2 != 'time': plot.add_layout(y2label) hover = plot.select(dict(type=HoverTool)) hover.tooltips = OrderedDict([ ('Time','@ftime'), ('Distance','@distance{int}'), ('Pace','@fpace'), ('HR','@hr{int}'), ('SPM','@spm{1.1}'), ('Power','@power{int}'), ]) hover.mode = 'mouse' callback = CustomJS(args = dict(source=source,source2=source2, x1means=x1means, y1means=y1means, y1label=y1label, y2label=y2label, xlabel=xlabel, y2means=y2means), code=""" var data = source.data var data2 = source2.data var x1 = data['x1'] var y1 = data['y1'] var y2 = data['y2'] var spm1 = data['spm'] var time1 = data['time'] var pace1 = data['pace'] var hr1 = data['hr'] var fpace1 = data['fpace'] var distance1 = data['distance'] var power1 = data['power'] var xname = data['xname'][0] var yname1 = data['yname1'][0] var yname2 = data['yname2'][0] var minspm = minspm.value var maxspm = maxspm.value var mindist = mindist.value var maxdist = maxdist.value var xm = 0 var ym1 = 0 var ym2 = 0 data2['x1'] = [] data2['y1'] = [] data2['y2'] = [] data2['spm'] = [] data2['time'] = [] data2['pace'] = [] data2['hr'] = [] data2['fpace'] = [] data2['distance'] = [] data2['power'] = [] data2['x1mean'] = [] data2['y1mean'] = [] data2['y2mean'] = [] data2['xvals'] = [] data2['y1vals'] = [] data2['y2vals'] = [] for (i=0; i=minspm && spm1[i]<=maxspm) { if (distance1[i]>=mindist && distance1[i]<=maxdist) { data2['x1'].push(x1[i]) data2['y1'].push(y1[i]) data2['y2'].push(y2[i]) data2['spm'].push(spm1[i]) data2['time'].push(time1[i]) data2['fpace'].push(fpace1[i]) data2['pace'].push(pace1[i]) data2['hr'].push(hr1[i]) data2['distance'].push(distance1[i]) data2['power'].push(power1[i]) xm += x1[i] ym1 += y1[i] ym2 += y2[i] } } } xm /= data2['x1'].length ym1 /= data2['x1'].length ym2 /= data2['x1'].length data2['x1mean'] = [xm,xm] data2['y1mean'] = [ym1,ym1] data2['y2mean'] = [ym2,ym2] x1means.location = xm y1means.location = ym1 y2means.location = ym2 y1label.text = yname1+': '+ym1.toFixed(2) y2label.text = yname2+': '+ym2.toFixed(2) xlabel.text = xname+': '+xm.toFixed(2) source2.trigger('change'); """) slider_spm_min = Slider(start=15.0, end=55,value=15.0, step=.1, title="Min SPM",callback=callback) callback.args["minspm"] = slider_spm_min slider_spm_max = Slider(start=15.0, end=55,value=55.0, step=.1, title="Max SPM",callback=callback) callback.args["maxspm"] = slider_spm_max distmax = 100+100*int(rowdata['distance'].max()/100.) slider_dist_min = Slider(start=0,end=distmax,value=0,step=1, title="Min Distance",callback=callback) callback.args["mindist"] = slider_dist_min slider_dist_max = Slider(start=0,end=distmax,value=distmax, step=1, title="Max Distance",callback=callback) callback.args["maxdist"] = slider_dist_max layout = layoutrow([layoutcolumn([slider_spm_min, slider_spm_max, slider_dist_min, slider_dist_max, ], ), plot]) script, div = components(layout) js_resources = INLINE.render_js() css_resources = INLINE.render_css() return [script,div,js_resources,css_resources] def interactive_bar_chart(id=0,promember=0): # check if valid ID exists (workout exists) rowdata,row = dataprep.getrowdata_db(id=id) if rowdata.empty: return "","CSV Data File Not Found" # Add hover to this comma-separated string and see what changes if (promember==1): TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,resize,crosshair' else: TOOLS = 'pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair' source = ColumnDataSource( rowdata ) plot = Figure(x_axis_type="datetime",y_axis_type="datetime", toolbar_sticky=False, plot_width=920, tools=TOOLS) plot.title.text = row.name plot.title.text_font_size=value("1.0em") plot.xaxis.axis_label = "Time" plot.yaxis.axis_label = "Pace (/500m)" plot.xaxis[0].formatter = DatetimeTickFormatter( hours ="", minutes = ["%M"], seconds = ["%S"], days = ["0"], months = [""], years = [""] ) plot.yaxis[0].formatter = DatetimeTickFormatter( hours = "", seconds = ["%S"], minutes = ["%M"], ) ymax = 1.0e3*90 ymin = 1.0e3*180 if row.workouttype == 'water': ymax = 1.0e3*90 ymin = 1.0e3*210 plot.y_range = Range1d(ymin,ymax) hover = plot.select(dict(type=HoverTool)) hover.tooltips = OrderedDict([ ('Time','@ftime'), ('Pace','@fpace'), ('HR','@hr{int}'), ('SPM','@spm{1.1}'), ]) hover.mode = 'mouse' plot.extra_y_ranges = {"hr": Range1d(start=100,end=200)} plot.quad(left='time',top='hr_ut2',bottom='hr_bottom', right='x_right',source=source,color="gray", y_range_name="hr", legend="