Script for generating a Lipo table and TWR vs. flight time scatter graph

mini-ecalc.py

from __future__ import division
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter

# http://godsnotwheregodsnot.blogspot.ru/2013/11/kmeans-color-quantization-seeding.html
Colormap = ["#FFFF00", "#1CE6FF", "#FF34FF", "#FF4A46", "#008941", "#006FA6", "#A30059",
        "#FFDBE5", "#7A4900", "#0000A6", "#63FFAC", "#B79762", "#004D43", "#8FB0FF", "#997D87",
        "#5A0007", "#809693", "#FEFFE6", "#1B4400", "#4FC601", "#3B5DFF", "#4A3B53", "#FF2F80",
        "#61615A", "#BA0900", "#6B7900", "#00C2A0", "#FFAA92", "#FF90C9", "#B903AA", "#D16100",
        "#DDEFFF", "#000035", "#7B4F4B", "#A1C299", "#300018", "#0AA6D8", "#013349", "#00846F",
        "#372101", "#FFB500", "#C2FFED", "#A079BF", "#CC0744", "#C0B9B2", "#C2FF99", "#001E09",
        "#00489C", "#6F0062", "#0CBD66", "#EEC3FF", "#456D75", "#B77B68", "#7A87A1", "#788D66",
        "#885578", "#FAD09F", "#FF8A9A", "#D157A0", "#BEC459", "#456648", "#0086ED", "#886F4C"]

PrintBBCode = True
#FigureToFile = False 
FigureToFile = "F:\Dropbox\Quadcopter\QR400\Rechner\plot.png"

NumberOfRotors = 4
CopterWeight = 830

FigureTitle = "QR400"
FigureSubtitle = "Flyduino X2212-1000kv, 9x4.5SF (%dg w/o battery)" % CopterWeight

MotorPropThrust = np.array([0, 		337, 	533, 	698, 	849, 	1087])
MotorPropAmps 	= np.array([0.4,	2.8,	6,		8.5,	11.7,	17.5])

Lipos = [
	dict(Name 		= "Hacker 4S 5000 20C",
		 AmpHours 	= 5,
		 CRating 	= 20,
		 Mass		= 503),
	dict(Name 		= "Multistar 4S 5200 10C",
		 AmpHours 	= 5.2,
		 CRating 	= 10,
		 Mass		= 433),
	dict(Name 		= "Multistar Race 4S 1400 40C",
		 AmpHours 	= 1.4,
		 CRating 	= 40,
		 Mass		= 153),
	dict(Name 		= "Multistar 4S 16000 10C",
		 AmpHours 	= 16,
		 CRating 	= 10,
		 Mass		= 1290),
#	dict(Name 		= "Mylipo 4S 15000 15C",
#		 AmpHours 	= 15,
#		 CRating 	= 15,
#		 Mass		= 1310),
	dict(Name 		= "Multistar 4S 8000 10C",
		 AmpHours 	= 8,
		 CRating 	= 10,
		 Mass		= 643),
	dict(Name 		= "Multistar 4S 10000 10C",
		 AmpHours 	= 10,
		 CRating 	= 10,
		 Mass		= 804),
	dict(Name 		= "Tattu 4S 1800 45C",
		 AmpHours 	= 1.8,
		 CRating 	= 45,
		 Mass		= 200),
#	dict(Name 		= "Nanotech 4S 1800 65C",
#		 AmpHours 	= 1.8,
#		 CRating 	= 65,
#		 Mass		= 203),
	dict(Name 		= "SLS APL Magnum 4S 1800 45C",
		 AmpHours 	= 1.8,
		 CRating 	= 45,
		 Mass		= 225),
	dict(Name 		= "SLS XTRON 4S 4000 20C",
		 AmpHours 	= 4,
		 CRating 	= 20,
		 Mass		= 427),
	dict(Name 		= "SLS XTRON 4S 3000 30C",
		 AmpHours 	= 3,
		 CRating 	= 30,
		 Mass		= 339),
	dict(Name 		= "SLS XTRON 4S 3200 20C",
		 AmpHours 	= 3.2,
		 CRating 	= 20,
		 Mass		= 345),
	dict(Name 		= "SLS XTRON 4S 2600 30C",
		 AmpHours 	= 2.6,
		 CRating 	= 30,
		 Mass		= 284),
	dict(Name 		= "Tattu 4S 6750 25C",
		 AmpHours 	= 7,
		 CRating 	= 25,
		 Mass		= 605),
#	dict(Name 		= "SLS XTRON 4S 3600 30C",
#		 AmpHours 	= 3.6,
#		 CRating 	= 30,
#		 Mass		= 417)
]

Lipos = sorted(Lipos, key=lambda k: k["AmpHours"])

# Step 1: interpolate motor thrust-amps function
Coefficients = np.polyfit(MotorPropThrust, MotorPropAmps, 2)
InvCoefficients = np.polyfit(MotorPropAmps, MotorPropThrust, 2)

# Step 2: calculate and print tabular data for all lipos
TotalMotorPropMaxAmps = MotorPropAmps.max() * NumberOfRotors

ColumnLabels = (
		"Lipo name", 
		"Weight",
		"AUW", 
		"Hover amps", 
		"Hover time", 
		"TWR"
	)	
if PrintBBCode:
	print '[table="align: left"]'
	print '[tr][td] [/td]'
	for label in ColumnLabels:
		print '[td][b]%s[/b][/td]' % label
	print '[/tr]'
else:
	print "%26s: %5d g" % ("Copter weight without lipo", CopterWeight)
	print "%26s: %5d" % ("Number of motors", NumberOfRotors)
	print
	print "%-26s %6s %13s %12s %12s %10s" % ColumnLabels
	print "-----------------------------------------------------------------------------"
	
LipoTWRs = np.array([])
LipoTimes = np.array([])
	
i = -1
	
for Lipo in Lipos:
	i = i + 1

	# hover thrust, amps, flight time
	TotalMass = CopterWeight + Lipo["Mass"]
	HoverThrustPerMotor = TotalMass / NumberOfRotors
	HoverAmpsPerMotor = Coefficients[0] * HoverThrustPerMotor * HoverThrustPerMotor + Coefficients[1] * HoverThrustPerMotor + Coefficients[2]
	TotalHoverAmps = HoverAmpsPerMotor * NumberOfRotors
	FlightTimeMinutes = Lipo["AmpHours"] / TotalHoverAmps * 60
	
	# thrust to weight
	NominalThrustToWeight = MotorPropThrust.max() * NumberOfRotors / TotalMass
	
	# thrust limit by C-rating
	MaxAmps = Lipo["AmpHours"] * Lipo["CRating"]
	if MaxAmps < TotalMotorPropMaxAmps:
		MaxAmpsPerMotor = MaxAmps / NumberOfRotors
		MotorPropMaxThrust = InvCoefficients[0] * MaxAmpsPerMotor * MaxAmpsPerMotor + InvCoefficients[1] * MaxAmpsPerMotor + InvCoefficients[2]
		RealThrustToWeight = MotorPropMaxThrust * NumberOfRotors / TotalMass
	else:
		RealThrustToWeight = NominalThrustToWeight
		
	# print line
	if PrintBBCode:
		print '[tr]'
		print '[td][COLOR="%s"][b]*[/b][/COLOR][/td]' % Colormap[i]
		print '[td]%s[/td]' % Lipo["Name"]
		print '[td]%d g[/td]' % Lipo["Mass"]
		print '[td]%d g[/td]' % TotalMass
		print '[td]%.1f A[/td]' % TotalHoverAmps
		print '[td]%.2f min[/td]' % FlightTimeMinutes
		print '[td]%.1f : 1%s[/td]' % (RealThrustToWeight, "*" if RealThrustToWeight < NominalThrustToWeight else "")
		print '[/tr]'
	else:
		print "%-26s %d g %11d g %10.1f A %8.2f min %6.1f : 1%s" % (
			Lipo["Name"],
			Lipo["Mass"],
			TotalMass,
			TotalHoverAmps,
			FlightTimeMinutes,
			RealThrustToWeight,
			"*" if RealThrustToWeight < NominalThrustToWeight else ""
		)
	
	if RealThrustToWeight < NominalThrustToWeight:
		Lipo["Name"] = Lipo["Name"] + " *"
	
	# save data for plots
	LipoTWRs = np.append(LipoTWRs, RealThrustToWeight)
	LipoTimes = np.append(LipoTimes, FlightTimeMinutes)
	Lipo["TWR"] = RealThrustToWeight
	Lipo["Time"] = FlightTimeMinutes
	
if PrintBBCode:
	print '[/table]'
else:
	print "-----------------------------------------------------------------------------"
	print "(*) Maximum thrust and TWR limited by lipo C-rating"

# Step 3: Plot scatter graph of TWR vs. flight time
fig, ax = plt.subplots(figsize=(7,6))

plt.scatter(LipoTimes, LipoTWRs, c=Colormap, s=50)

for Lipo in Lipos:
	plt.annotate(
		Lipo["Name"],
		xy = (Lipo["Time"], Lipo["TWR"]),
		xytext = (5, 0),
		fontsize = 9,
		textcoords = 'offset points', ha = 'left', va = 'center')
	
plt.grid()
fig.suptitle(FigureTitle, fontsize=14, fontweight='bold')
ax.set_title(FigureSubtitle)
plt.ylabel('Thrust-to-weight ratio')
plt.xlabel('Hover time (100% capacity)')
plt.ylim((2, 4.5))
plt.xlim((10, 45))
ax.yaxis.set_major_formatter(FormatStrFormatter('%3.1f : 1'))
ax.xaxis.set_major_formatter(FormatStrFormatter('%d min'))

if FigureToFile:
	plt.savefig(FigureToFile)
else:
	plt.show()