def season(lats, days=[80, 52, 21, 355]):
" trade seasonal availibility with weight "
V = Aircraft(sp=False)
data = {}
for l in lats:
failed = False
mtows = []
for d in days:
if failed:
mtows = mtows + [np.nan] * (4 - len(mtows))
break
M = Mission(V, latitude=range(1, l + 1, 1), day=d)
M.cost = M[M.aircraft.Wtotal]
try:
sol = M.solve()
mtow = sol(M.aircraft.Wtotal).magnitude
mtows.append(mtow)
except RuntimeWarning:
mtows.append(np.nan)
failed = True
mtows = np.hstack(mtows)
data[l] = mtows
df = pd.DataFrame(data)
return df
def test():
" test for integrated testing "
v = Aircraft(Npod=0, sp=True)
model = Mission(v, latitude=[20])
model.cost = model[model.aircraft.Wtotal]
result = model.localsolve()
_ = get_highestsens(model, result)
vn = {
model.aircraft.Wpay: "$W_{\\mathrm{pay}}$",
model.aircraft.battery.etacharge: "$\\eta_{\\mathrm{charge}}$"
}
_ = get_highestsens(model, result, vn)
def build_solar(lat=15, day=140, sp=True):
" try different battery specific energies "
M = Mission(latitude=lat, day=day, sp=sp)
M.cost = M["W_{total}"]
M.substitutions.update({"W_{pay}": 0})
for vk in M.varkeys["P_{avn}"]:
M.substitutions.update({vk: 50})
for h in [150, 200, 260]:
M.substitutions.update({"h_{batt}": h})
try:
sol = M.localsolve("mosek", verbosity=2) if sp else M.solve("mosek")
print sol.table(["W_{total}", "b_Mission/Aircraft/Wing", "S",
"W_Mission/Aircraft/Wing",
"W_Mission/Aircraft/Battery",
"P_{oper}"])
except RuntimeWarning:
print "Not feasible"
return M
def pods(N=[1, 3, 5, 7, 9, 0], Nplot=5):
"trade number of pods"
SP = True
data = {}
for i in N:
print("\nN=%i" % i)
from solar import Mission, Aircraft
Vehicle = Aircraft(Npod=i, sp=SP)
M = Mission(Vehicle, latitude=[20])
M.cost = M[M.aircraft.Wtotal]
try:
sol = M.localsolve()
data[i] = sol("Wtotal").magnitude
except RuntimeWarning as e:
print("rw: %s" % e)
try:
V2 = Aircraft(Npod=i, sp=SP)
M2 = Mission(V2, latitude=[20])
M2.cost = M2[M2.aircraft.Wtotal]
feas = relaxed_constants(M2)
sol2 = feas.localsolve()
vks = post_process(sol2)
data[i] = np.NaN if vks else sol2("Wtotal").magnitude
M, sol = M2, sol2
except Exception as e:
print("e: %s" % e)
data[i] = np.NaN
except CalledProcessError as e:
print("cpe: %s" % e)
data[i] = np.NaN # mosek_cli can't process certain Ns
if Nplot == i:
plot_shear(M, sol)
df = pd.DataFrame(data, index=[0])
return df
ax.bar(ind - 0.25, pss, 0.5, color="#4D606E")
ax.bar(ind - 0.25, ngs, 0.5, color="#3FBAC2")
ax.set_xlim([0.0, ind[-1]+0.5])
ax.set_xticks(ind)
ax.set_xticklabels(labels, rotation=-45, ha="left")
ax.legend(["Positive", "Negative"])
ax.set_ylabel("sensitivities")
return fig, ax
if __name__ == "__main__":
sols = []
Ms = []
for l in [25, 29]:
for p in [85, 90]:
M = Mission(latitude=l)
M.cost = M["W_{total}"]
Ms.append(M)
for vk in M.varkeys["p_{wind}"]:
M.substitutions.update({vk: p/100.0})
sol = M.solve("mosek")
sols.append(sol)
varns = ["p_{wind}", "\\eta_Mission/Aircraft/SolarCells",
"\\eta_{charge}", "\\eta_{discharge}", "\\rho_{solar}",
"t_{night}", "(E/S)_{irr}", "h_{batt}", "W_{pay}",
"\\eta_{prop}"]
latns = ["$p_{\\mathrm{wind}}$", "$\\eta_{\\mathrm{solar}}$",
"$\\eta_{\\mathrm{charge}}$", "$\\eta_{\\mathrm{discharge}}$",
"$\\rho_{\\mathrm{solar}}$",
"$t_{\\mathrm{night}}$", "$(E/S)_{\\mathrm{irr}}$",
from solar import Aircraft, Mission from gpkitmodels.GP.aircraft.fuselage.elliptical_fuselage import Fuselage Aircraft.fuseModel = Fuselage m = Mission(latitude=[20]) sol = m.solve()
def plot_contours(path=None):
N = 100
stime = 0.0
numsolves = 0
plt.rcParams.update({'font.size': 19})
hmin = 250.0
hmax = 400.0
for av in [80, 85, 90]:
for lat in [25, 30, 35]:
zo = 10
if lat == 25:
bs = range(30, 80, 5)
elif lat == 30:
bs = range(35, 80, 5)
if av == 90:
del bs[0]
else:
bs = range(45, 80, 5)
if av == 90:
del bs[0]
fig, ax = plt.subplots()
M = Mission(latitude=lat)
M.substitutions.update({"W_{pay}": 10})
for vk in M.varkeys["\\eta_{prop}"]:
M.substitutions.update({vk: 0.75})
for vk in M.varkeys["p_{wind}"]:
M.substitutions.update({vk: av / 100.0})
del M.substitutions["\\eta_Mission/Aircraft/SolarCells"]
del M.substitutions["h_{batt}"]
M.cost = M["h_{batt}"]
lines = []
midx = []
for b in bs:
etamax = 0.4
etamin = 0.15
M.substitutions.update({"b_Mission/Aircraft/Wing": b})
M.substitutions.update(
{"\\eta_Mission/Aircraft/SolarCells": etamax})
sol = M.solve("mosek")
stime += sol["soltime"]
numsolves += 1
del M.substitutions["\\eta_Mission/Aircraft/SolarCells"]
if sol("h_{batt}").magnitude < hmin:
M.substitutions.update({"h_{batt}": hmin})
M.cost = M["\\eta_Mission/Aircraft/SolarCells"]
sol = M.solve("mosek")
stime += sol["soltime"]
numsolves += sol["soltime"]
etamax = sol("\\eta_Mission/Aircraft/SolarCells")
M.substitutions.update({"h_{batt}": hmax})
M.cost = M["\\eta_Mission/Aircraft/SolarCells"]
sol = M.solve("mosek")
stime += sol["soltime"]
numsolves += 1
etamin = sol("\\eta_Mission/Aircraft/SolarCells")
if etamin > etamax:
continue
del M.substitutions["h_{batt}"]
M.cost = M["h_{batt}"]
xmin_ = np.linspace(etamin, etamax, 100)
tol = 0.01
bst = autosweep_1d(M,
tol,
M["\\eta_Mission/Aircraft/SolarCells"],
[etamin, etamax],
solver="mosek")
bsts = find_sols([bst])
sols = np.hstack([bs.sols for bs in bsts])
stime += sum(np.unique([s["soltime"] for s in sols]))
numsolves += bst.nsols
if b % 10 == 0:
l = ax.plot(xmin_,
bst.sample_at(xmin_)["cost"],
"k",
label="%d [ft]" % b,
zorder=zo)
zo += 2
lines.append(l[0])
midx.append(np.median(xmin_))
else:
ax.plot(xmin_,
bst.sample_at(xmin_)["cost"],
"--",
c="0.5",
zorder=100)
# parato fontier
del M.substitutions["b_Mission/Aircraft/Wing"]
M.substitutions.update(
{"\\eta_Mission/Aircraft/SolarCells": etamax})
M.cost = M["h_{batt}"]
sol = M.solve("mosek")
etamax = 0.4
stime += sol["soltime"]
numsolves += 1
del M.substitutions["\\eta_Mission/Aircraft/SolarCells"]
if sol("h_{batt}").magnitude < hmin:
M.substitutions.update({"h_{batt}": hmin})
M.cost = M["\\eta_Mission/Aircraft/SolarCells"]
sol = M.solve("mosek")
stime += sol["soltime"]
numsolves += sol["soltime"]
etamax = sol("\\eta_Mission/Aircraft/SolarCells")
M.substitutions.update({"h_{batt}": hmax})
M.cost = M["\\eta_Mission/Aircraft/SolarCells"]
sol = M.solve("mosek")
stime += sol["soltime"]
numsolves += 1
etamin = sol("\\eta_Mission/Aircraft/SolarCells")
if etamin > etamax:
break
del M.substitutions["h_{batt}"]
M.cost = M["h_{batt}"]
xmin_ = np.linspace(etamin, etamax, 100)
tol = 0.01
bst = autosweep_1d(M,
tol,
M["\\eta_Mission/Aircraft/SolarCells"],
[etamin, etamax],
solver="mosek")
bsts = find_sols([bst])
sols = np.hstack([b.sols for b in bsts])
stime += sum(np.unique([s["soltime"] for s in sols]))
numsolves += bst.nsols
ax.set_xlabel("Solar Cell Efficiency")
ax.set_ylabel("Battery Specific Energy [Whr/kg]")
labelLines(lines[:-1],
align=True,
xvals=midx,
zorder=[11, 13, 15, 17])
ax.fill_between(np.hstack([0.15, xmin_]),
0,
np.hstack([hmax,
bst.sample_at(xmin_)["cost"]]),
edgecolor="r",
lw=2,
hatch="/",
facecolor="None",
zorder=100)
ax.text(0.17, 260, "Infeasible", fontsize=19)
ax.set_xlim([0.15, 0.4])
ax.set_ylim([250, 400])
if path:
fig.savefig(path + "bcontourl%da%d.pdf" % (lat, av),
bbox_inches="tight")
else:
fig.savefig("bcontourl%da%d.pdf" % (lat, av))
print "%d solves in %.4f seconds" % (numsolves, stime)
" contour plots "
import matplotlib.pyplot as plt
import numpy as np
from solar import Mission
from plotting import windalt_plot, labelLines
from gpkit.tools.autosweep import autosweep_1d
N = 100
plt.rcParams.update({'font.size':19})
fig, ax = plt.subplots()
bmax = []
lines = []
for lat in range(20, 31, 2):
hmax = 500
M = Mission(latitude=lat)
M.substitutions.update({"W_{pay}": 10})
for vk in M.varkeys["\\eta_{prop}"]:
M.substitutions.update({vk: 0.75})
for vk in M.varkeys["p_{wind}"]:
M.substitutions.update({vk: 90/100.0})
del M.substitutions["h_{batt}"]
M.cost = M["h_{batt}"]
sol = M.solve("mosek")
hmin = sol["cost"].magnitude + 1e-3
M.cost = M["b_Mission/Aircraft/Wing"]
xmin_ = np.linspace(hmin, hmax, 100)
tol = 0.01
bst = autosweep_1d(M, tol, M["h_{batt}"], [hmin, hmax], solver="mosek")
l = ax.plot(xmin_, bst.sample_at(xmin_)["cost"], "k", label="%d" % lat)
lines.append(l[0])
def plot_battsolarcon():
fig, ax = plt.subplots()
time = 0
numsolves = 0
etamax = []
lines = []
midx = []
passing = True
for lat in range(20, 44, 1):
if passing:
hmax = 500
M = Mission(latitude=lat)
M.substitutions.update({"W_{pay}": 10})
for vk in M.varkeys["\\eta_{prop}"]:
M.substitutions.update({vk: 0.75})
for vk in M.varkeys["p_{wind}"]:
M.substitutions.update({vk: 90 / 100.0})
del M.substitutions["h_{batt}"]
M.substitutions.update({"\\eta_Mission/Aircraft/SolarCells": 0.4})
M.cost = M["h_{batt}"]
sol = M.solve("mosek")
time += sol["soltime"]
numsolves += 1
hmin = sol["cost"].magnitude + 1e-3
if hmin >= hmax:
break
del M.substitutions["\\eta_Mission/Aircraft/SolarCells"]
M.cost = M["\\eta_Mission/Aircraft/SolarCells"]
xmin_ = np.linspace(hmin, hmax, 100)
tol = 0.01
notpassing = True
try:
bst = autosweep_1d(M,
tol,
M["h_{batt}"], [hmin, hmax],
solver="mosek")
bsts = find_sols([bst])
sols = np.hstack([b.sols for b in bsts])
time += sum(np.unique([s["soltime"] for s in sols]))
numsolves += bst.nsols
if lat % 4 == 0:
l = ax.plot(xmin_,
bst.sample_at(xmin_)["cost"],
"k",
label="%d$^{\\circ}$ Lat" % lat)
lines.append(l[0])
etamax.append(max(bst.sample_at(xmin_)["cost"].magnitude))
midx.append(np.median(xmin_))
elif lat % 2 == 0:
l = ax.plot(xmin_,
bst.sample_at(xmin_)["cost"],
"--",
c="0.5",
label="%d$^{\\circ}$ Lat" % lat)
except RuntimeWarning:
passing = False
# ax.fill_between(xmin_, bst.sample_at(xmin_)["cost"], max(etamax),
# edgecolor="r", lw=2, hatch="/", facecolor="None", zorder=100)
print "%d solves in %.4f seconds" % (numsolves, time)
labelLines(lines, align=False, xvals=midx, zorder=[10] * len(lines))
# ax.text(425, 0.36, "Infeasible")
ax.set_ylabel("Solar Cell Efficiency")
ax.set_xlabel("Battery Specific Energy [Whr/kg]")
ax.set_xlim([250, 500])
ax.set_ylim([0.1, max(etamax)])
ax.grid()
return fig, ax