def go_plane1():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_plane1')
n = 10
def interpolate_endurance(i):
assert 0 <= i< n
x = np.linspace(5, 120, n)[i]
return (x, "minutes")
def interpolate_missions(i):
assert 0 <= i< n
x = np.linspace(1, 1000, n)[i]
return (x, "[]")
queries = []
for i in range(n):
q = {}
q['endurance'] = interpolate_endurance(i)
q['num_missions'] = interpolate_missions(i)
queries.append(q)
result_like = dict(total_mass="kg", total_cost="USD")
data = solve_queries(ndp, queries, result_like, lower=None, upper=None)
return data
def go_plane2():
# combinations = {
# "endurance": (np.linspace(5, 120, 10), "minutes"),
# "extra_payload": (np.linspace(1, 1000, 10), "g"),
# }
#
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_plane2')
n = 10
def interpolate_endurance(i):
assert 0 <= i< n
x = np.linspace(5, 60, n)[i]
return (x, "minutes")
def interpolate_extra_payload(i):
assert 0 <= i< n
x = np.linspace(1, 500, n)[i]
return (x, "g")
queries = []
for i in range(n):
q = {}
q['endurance'] = interpolate_endurance(i)
q['extra_payload'] = interpolate_extra_payload(i)
queries.append(q)
result_like = dict(total_mass="kg", total_cost="USD")
data = solve_queries(ndp, queries, result_like, lower=None, upper=None)
return data
def go_plane2():
# combinations = {
# "endurance": (np.linspace(5, 120, 10), "minutes"),
# "extra_payload": (np.linspace(1, 1000, 10), "g"),
# }
#
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_plane2')
n = 10
def interpolate_endurance(i):
assert 0 <= i < n
x = np.linspace(5, 60, n)[i]
return (x, "minutes")
def interpolate_extra_payload(i):
assert 0 <= i < n
x = np.linspace(1, 500, n)[i]
return (x, "g")
queries = []
for i in range(n):
q = {}
q['endurance'] = interpolate_endurance(i)
q['extra_payload'] = interpolate_extra_payload(i)
queries.append(q)
result_like = dict(total_mass="kg", total_cost="USD")
data = solve_queries(ndp, queries, result_like, lower=None, upper=None)
return data
def go_plane1():
librarian = get_test_librarian()
lib = librarian.load_library('mcdp_theory')
ndp = lib.load_ndp('drone1_plane1')
n = 10
def interpolate_endurance(i):
assert 0 <= i < n
x = np.linspace(5, 120, n)[i]
return (x, "minutes")
def interpolate_missions(i):
assert 0 <= i < n
x = np.linspace(1, 1000, n)[i]
return (x, "[]")
queries = []
for i in range(n):
q = {}
q['endurance'] = interpolate_endurance(i)
q['num_missions'] = interpolate_missions(i)
queries.append(q)
result_like = dict(total_mass="kg", total_cost="USD")
data = solve_queries(ndp, queries, result_like, lower=None, upper=None)
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_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 render(libname, docname, generate_pdf):
librarian = get_test_librarian()
library = librarian.load_library('manual')
d = tempfile.mkdtemp()
library.use_cache_dir(d)
l = library.load_library(libname)
basename = docname + '.' + MCDPLibrary.ext_doc_md
f = l._get_file_data(basename)
data = f['data']
realpath = f['realpath']
html_contents = render_complete(library=l,
s=data, raise_errors=True, realpath=realpath,
generate_pdf=generate_pdf)
doc = get_minimal_document(html_contents, add_markdown_css=True)
return ((libname, docname), doc)
