def dashboard_performance_plots(myDataDF, runPeriodDF, myID):
print 'Now make plots for ', myDataDF
xKey='timeStamp'
myPdf = PdfPages('images/plots_for_ID' + str(myID) + '.pdf')
chartOptionsDict = {'InsideTemp': {'color': 'mediumturquoise', 'style': '-', 'desc': 'Inside Temp', 'linewidth':2},
'OutsideTemp': {'color': 'mediumvioletred', 'style': '-', 'desc': 'Outside Temp', 'linewidth':2},
'SetPoint': {'color': 'blue', 'style': '-', 'desc': 'Setpoint', 'linewidth':2}
}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Temperature', 'grid': True, 'doDates': True, 'figsize': (15,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 10.0,
'y_limit': [45,135]}
print 'datetime values are: ', myDataDF[xKey]
drawLegOutputs, drawLegLabels = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
plt.legend(drawLegOutputs, drawLegLabels, prop={'size':28})
#plt.show()
myPdf.savefig()
plt.close()
# ### now do runPeriodDF
print 'Will draw duration from runPeriodDF: ', runPeriodDF
chartOptionsDict = {'duration': {'type': 'bar', 'maxBarWidth': 30. / (60.*24.), 'color': 'gold', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Run Duration [minutes]', 'grid': True, 'doDates': True, 'figsize': (15,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 2.0}
drawOutput = drawing.overlayChartsFromPandasDF(plt, runPeriodDF, 'beginRunTime', chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
#print 'Now draw performance plot'
chartOptionsDict = {'performance': {'type': 'bar', 'maxBarWidth': 30. / (60.*24.), 'color': 'lightseagreen', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Performance', 'grid': True, 'doDates': True,'figsize': (15,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 2.0}
drawing.overlayChartsFromPandasDF(plt, runPeriodDF, 'beginRunTime', chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
myPdf.close()
def dashboard_performance_plots(myDataDF, myID):
#print 'Now make plots for ', myDataDF
xKey='timeStamp'
myPdf = PdfPages('images/plots_for_ID' + str(myID) + '_AggregatedResults.pdf')
# draw avgTemperatures
chartOptionsDict = collections.OrderedDict([
('maxInsideTemp', {'color': 'mediumturquoise', 'style': '--', 'desc': 'DayMaxInsideTemp', 'linewidth':6}),
('avgInsideTemp', {'color': 'mediumturquoise', 'style': '-', 'desc': 'DayAvgInsideTemp', 'linewidth':6}),
('minInsideTemp', {'color': 'mediumturquoise', 'style': '--', 'desc': 'DayMinInsideTemp', 'linewidth':6}),
('maxOutsideTemp', {'color': 'mediumvioletred', 'style': '--', 'desc': 'DayMaxOutsideTemp', 'linewidth':6}),
('avgOutsideTemp', {'color': 'mediumvioletred', 'style': '-', 'desc': 'DayAvgOutsideTemp', 'linewidth':6}),
('minOutsideTemp', {'color': 'mediumvioletred', 'style': '--', 'desc': 'DayMinOutsideTemp', 'linewidth':6}),
('avgSetPoint', {'color': 'blue', 'style': '-', 'desc': 'Setpoint', 'linewidth':6})
])
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Temperature', 'grid': True, 'doDates': True, 'figsize': (20,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 35, 'yLabelSize': 35, 'xMarginXtra': 10.0,
'y_limit': [20,150]}
# print 'datetime values are: ', myDataDF[xKey]
drawLegOutputs, drawLegLabels = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict,plotOptionsDict)
plt.legend(drawLegOutputs, drawLegLabels, prop={'size':28})
#plt.show()
myPdf.savefig()
plt.close()
#### Run the Suggested filter functions: remove days with no runtime, such as avgDuration < 0.000001
myDataDF = filterData(myDataDF)
# draw now avgRunningMode
#print 'Will draw average running time'
chartOptionsDict = {'avgRunningMode': {'type': 'bar', 'color': 'gold', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Fraction Run Time', 'grid': True, 'doDates': True, 'figsize': (20,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 35, 'yLabelSize': 35, 'xMarginXtra': 2.0}
drawOutput = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
# draw avgPerformance plot
chartOptionsDict = {'avgPerformance': {'type': 'bar', 'color': 'lightseagreen', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'avgPerformance', 'grid': True, 'doDates': True,'figsize': (20,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 2.0}
drawOutput = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
#draw avgDuration plot
chartOptionsDict = {'avgDuration': {'type': 'bar', 'color': 'pink', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'avgDuration [minute]', 'grid': True, 'doDates': True,'figsize': (20,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 2.0}
drawOutput = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
#draw numCycles plot
chartOptionsDict = {'numCycles': {'type': 'bar', 'color': 'blue', 'style': '-'}}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Number Of Cycles', 'grid': True, 'doDates': True,'figsize': (20,10),
'xAxisFontSize': 25, 'yAxisFontSize': 25, 'xLabelSize': 28, 'yLabelSize': 28, 'xMarginXtra': 2.0}
drawOutput = drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
myPdf.savefig()
plt.close()
myPdf.close()
def draw_plots(myDataDF, peakInfoObjects, myID):
#print 'Now make plots for ', myDataDF
#### First make inclusive plot:
xKey='timeStamp'
#myPdf = PdfPages('images/plots_for_ID_'+ str(myID) + 'PowerSummary_LightBulb.pdf')
#myPdf = PdfPages('images/plots_for_ID_'+ str(myID) + 'PowerSummary_Microwave.pdf')
#myPdf = PdfPages('images/plots_for_ID_'+ str(myID) + 'PowerSummary_HairDryer.pdf')
myPdf = PdfPages('images/plots_for_ID_'+ str(myID) + 'PowerSummary_LaundaryDryer.pdf')
chartOptionsDict = {'powerUsage': {'color': 'blue', 'style': '-'}
}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Power usage [Watts]',
'grid': True, 'figsize': (50,10), 'doDates': True,
'xAxisFontSize': 24, 'yAxisFontSize': 24,
'xLabelSize': 28, 'yLabelSize': 28,
'xMarginXtra': 2.0}
# for item in ([ax.title, ax.xaxis.label, ax.yaxis.label] +
# ax.get_xticklabels() + ax.get_yticklabels()):
# item.set_fontsize(20)
#plt.figure(figsize=(50,10))
# print 'datetime values are: ', myDataDF[xKey]
drawing.overlayChartsFromPandasDF(plt, myDataDF, xKey, chartOptionsDict, plotOptionsDict)
#plt.show()
myPdf.savefig()
plt.close()
#### Now make peak plots:
print 'Now draw peaks: ', peakInfoObjects
for peak in peakInfoObjects:
# 'peakInfoObject['startWindowPower']
# 'peakInfoObject['endWindowPower']
peakDataDF = myDataDF[peak['startTestIndex']-2:peak['endTestIndex']+ 3]
chartOptionsDict = {
'powerUsage': {'color': 'blue', 'style': '-'}
}
plotOptionsDict = {'xlabel': 'Time', 'ylabel': 'Power usage [Watts]', 'grid': True, 'doDates': True}
xKey = 'timeStamp'
print 'draw for this peak:'
#drawBackgroundAndPeak()
ax = drawing.getPlotFrame(plotOptionsDict)
startSidebandOut = drawing.drawDatetimeOnePtBarPlot(ax, startTime=peak['startTime']-datetime.timedelta(minutes=6),
endTime=peak['startTime'],
value=peak['startWindowPower'], color='mediumvioletred')
endSidebandOut = drawing.drawDatetimeOnePtBarPlot(ax, startTime=peak['endTime'],
endTime=peak['endTime']+datetime.timedelta(minutes=6),
value=peak['endWindowPower'], color='mediumvioletred')
peakOut = drawing.drawDatetimeOnePtBarPlot(ax, startTime=peak['startTime'], endTime=peak['endTime'],
value=peak['peakPower'], color='powderblue')
bkgOut = drawing.drawDatetimeOnePtBarPlot(ax, startTime=peak['startTime'], endTime=peak['endTime'],
value=peak['bkgPower'], color='pink')
timeSeriesOut = drawing.overlayChartsFromPandasDF(plt, peakDataDF, xKey, chartOptionsDict, plotOptionsDict, createNewFig=False, ax=ax)
startTestTime = peak['startTestTime']
endTestTime = peak['endTestTime']
startEndTestTimeValues = [drawing.convertDatetime64ToDatetime(ele) for ele in [startTestTime, endTestTime]]
startEndTestTimeDates = matplotlib.dates.date2num(startEndTestTimeValues)
canvasStartTestTime = startEndTestTimeDates[0]
canvasEndTestTime = startEndTestTimeDates[1]
ymin, ymax = ax.get_ylim()
startTestOut = ax.plot([canvasStartTestTime,canvasStartTestTime],[ymin, ymax],color='black',linestyle='--', linewidth=2)
endTestTout = ax.plot([canvasEndTestTime,canvasEndTestTime],[ymin, ymax],color='black',linestyle='--', linewidth=2)
ax.legend((startSidebandOut[0], bkgOut[0], peakOut[0], timeSeriesOut[0], startTestOut[0]),
('Sideband', 'Background', 'Device power', 'Power usage', 'Test begin/end'))
myPdf.savefig()
plt.close()
myPdf.close()