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_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)