def process(s):
librarian = Librarian()
librarian.find_libraries('../..')
library = librarian.load_library('droneD_complete_templates')
library.use_cache_dir('_cached/drone_unc1')
ndp = library.parse_ndp(s)
combinations = {
"endurance": (np.linspace(1, 1.5, 10), "hour"),
"extra_payload": (100, "g"),
"num_missions": (1000, "[]"),
"velocity": (1.0, "m/s"),
'extra_power': (0.5, 'W'),
}
result_like = dict(total_cost="USD", total_mass='kg')
dataU = solve_combinations(ndp,
combinations,
result_like,
upper=1,
lower=None)
dataL = solve_combinations(ndp,
combinations,
result_like,
upper=None,
lower=1)
return dict(dataL=dataL, dataU=dataU)
def go_drone1_cost():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_min_cost')
combinations = get_combinations_drone()
result_like = dict(total_cost='USD')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_drone1_cost():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_min_cost')
combinations = get_combinations_drone()
result_like = dict(total_cost='USD')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_tco():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries6_min_tco')
combinations = get_combinations()
result_like = dict(tco="USD")
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_joint():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries4_min_joint')
combinations = get_combinations()
result_like = dict(cost="USD", maintenance="dimensionless", mass='g')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_cost_mass():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries5_min_cost_mass')
combinations = get_combinations()
result_like = dict(cost="USD", mass='g')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_maintenance():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries1_min_maintenance')
combinations = get_combinations()
result_like = dict(maintenance="dimensionless")
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_tco():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries6_min_tco')
combinations = get_combinations()
result_like = dict(tco="USD")
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_joint():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries4_min_joint')
combinations = get_combinations()
result_like = dict(cost="USD", maintenance="dimensionless", mass='g')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_cost_mass():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries5_min_cost_mass')
combinations = get_combinations()
result_like = dict(cost="USD", mass='g')
data = solve_combinations(ndp, combinations, result_like)
return data
def go_batteries_min_maintenance():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('batteries1_min_maintenance')
combinations = get_combinations()
result_like = dict(maintenance="dimensionless")
data = solve_combinations(ndp, combinations, result_like)
return data
def process(s):
librarian = Librarian()
librarian.find_libraries('../..')
library = librarian.load_library('droneD_complete_templates')
library.use_cache_dir('_cached/drone_unc1')
ndp = library.parse_ndp(s)
combinations = {
"endurance": (np.linspace(1, 1.5, 10), "hour"),
"extra_payload": (100, "g"),
"num_missions": ( 1000, "[]"),
"velocity": (1.0, "m/s"),
'extra_power': (0.5, 'W'),
}
result_like = dict(total_cost="USD", total_mass='kg')
dataU = solve_combinations(ndp, combinations, result_like, upper=1, lower=None)
dataL = solve_combinations(ndp, combinations, result_like, upper=None, lower=1)
return dict(dataL=dataL, dataU=dataU)
def go(model_name):
lib = get_library()
nt = 15 * 4
nr = 15 * 3
combinations = {
"min_throughput": (np.linspace(10, 1000, nt), "Hz"),
"resolution": (np.linspace(1.3, 10, nr), "pixels/deg"),
"inverse_of_max_latency": (0.0, '1/s')
}
result_like = dict(power="W", budget="USD")
ndp = lib.load_ndp(model_name)
data = solve_combinations(ndp, combinations, result_like)
return data
def go(lib):
combinations = {
"capacity": (np.linspace(50, 3000, 10), "Wh"),
"missions": ( 1000, "[]"),
}
result_like = dict(maintenance="dimensionless", cost="USD", mass='kg')
what_to_plot_res = result_like
what_to_plot_fun = dict(capacity="Wh", missions="[]")
ndp = lib.load_ndp('batteries')
data = solve_combinations(ndp, combinations, result_like)
r = Report()
plot_all_directions(r, queries=data['queries'], results=data['results'],
what_to_plot_res=what_to_plot_res,
what_to_plot_fun=what_to_plot_fun)
r.to_html('out/batteries-c1.html')
def go2(lib):
model_name = 'batteries_squash'
combinations = {
"capacity": (np.linspace(50, 3000, 10), "Wh"),
"missions": (1000, "[]"),
}
result_like = dict(cost="USD", mass='kg')
what_to_plot_res = result_like
what_to_plot_fun = dict(capacity="Wh", missions="[]")
ndp = lib.load_ndp(model_name)
data = solve_combinations(ndp, combinations, result_like)
r = Report()
plot_all_directions(r, queries=data['queries'], results=data['results'],
what_to_plot_res=what_to_plot_res,
what_to_plot_fun=what_to_plot_fun)
r.to_html('out/batteries_squash-c2.html')