include "primitives.alh" include "modelling.alh" include "object_operations.alh" include "conformance_scd.alh" include "io.alh" include "metamodels.alh" include "mini_modify.alh" Boolean function main(model : Element): String cmd Boolean running Element schedule_init Element schedule_run Element schedule Float current_time String time time = set_pop(allInstances(model, "FullRuntime/Time")) current_time = read_attribute(model, time, "current_time") schedule_init = create_schedule(model) schedule_run = read_root() Element nodes Element inputs String node nodes = allInstances(model, "FullRuntime/Block") inputs = dict_create() while (set_len(nodes) > 0): node = set_pop(nodes) dict_add(inputs, node, allAssociationOrigins(model, node, "FullRuntime/Link")) while (bool_not(has_input())): if (read_attribute(model, time, "start_time") == read_attribute(model, time, "current_time")): schedule = schedule_init else: if (element_eq(schedule_run, read_root())): schedule_run = create_schedule(model) schedule = schedule_run current_time = step_simulation(model, schedule, current_time, inputs) instantiate_attribute(model, time, "current_time", current_time) output("CLOSE") return True! Element function create_schedule(model : Element): // Create nice graph first Element nodes Element successors Element predecessors String element_name Element incoming_links Element all_blocks nodes = allInstances(model, "FullRuntime/Block") successors = dict_create() predecessors = dict_create() while (set_len(nodes) > 0): element_name = set_pop(nodes) if (bool_not(dict_in(successors, element_name))): dict_add(successors, element_name, create_node()) if (bool_not(dict_in(predecessors, element_name))): dict_add(predecessors, element_name, create_node()) if (is_nominal_instance(model, element_name, "FullRuntime/ICBlock")): if (bool_not(is_physical_float(read_attribute(model, element_name, "last_in")))): incoming_links = allIncomingAssociationInstances(model, element_name, "FullRuntime/InitialCondition") else: incoming_links = create_node() if (is_nominal_instance(model, element_name, "FullRuntime/DerivatorBlock")): Element new_incoming_links new_incoming_links = allIncomingAssociationInstances(model, element_name, "FullRuntime/Link") while (read_nr_out(new_incoming_links) > 0): list_append(incoming_links, set_pop(new_incoming_links)) else: incoming_links = allIncomingAssociationInstances(model, element_name, "FullRuntime/Link") while (set_len(incoming_links) > 0): String source source = readAssociationSource(model, set_pop(incoming_links)) if (bool_not(dict_in(successors, source))): dict_add(successors, source, create_node()) set_add(successors[source], element_name) set_add(predecessors[element_name], source) Element values values = create_node() dict_add(values, "model", model) dict_add(values, "S", create_node()) dict_add(values, "index", 0) dict_add(values, "indices", create_node()) dict_add(values, "lowlink", create_node()) dict_add(values, "onStack", create_node()) dict_add(values, "successors", successors) dict_add(values, "predecessors", predecessors) dict_add(values, "SCC", create_node()) nodes = get_topolist(values) while (list_len(nodes) > 0): strongconnect(list_pop_final(nodes), values) return values["SCC"]! Element function get_topolist(values : Element): Element result Element predecessors Element remaining String current_element Element cur_predecessors result = list_create() predecessors = dict_copy(values["predecessors"]) while (dict_len(predecessors) > 0): remaining = dict_keys(predecessors) while (set_len(remaining) > 0): current_element = set_pop(remaining) cur_predecessors = predecessors[current_element] if (set_len(set_overlap(list_to_set(result), cur_predecessors)) == set_len(cur_predecessors)): // All predecessors of this node have already been visited dict_delete(predecessors, current_element) remaining = dict_keys(predecessors) list_append(result, current_element) return result! Integer function min(a : Integer, b : Integer): if (a < b): return a! else: return b! Void function strongconnect(v : String, values : Element): if (dict_in(values["indices"], v)): return! dict_overwrite(values["indices"], v, values["index"]) dict_overwrite(values["lowlink"], v, values["index"]) dict_overwrite(values, "index", cast_integer(values["index"]) + 1) list_append(values["S"], v) dict_overwrite(values["onStack"], v, True) Element successors String w successors = values["successors"][v] while (set_len(successors) > 0): w = set_pop(successors) if (bool_not(dict_in(values["indices"], w))): strongconnect(w, values) dict_overwrite(values["lowlink"], v, min(values["lowlink"][v], values["lowlink"][w])) elif (dict_in(values["onStack"], w)): if (values["onStack"][w]): dict_overwrite(values["lowlink"], v, min(values["lowlink"][v], values["indices"][w])) if (value_eq(values["lowlink"][v], values["indices"][v])): Element scc scc = create_node() // It will always differ now w = list_pop_final(values["S"]) list_append(scc, w) dict_overwrite(values["onStack"], w, False) while (w != v): w = list_pop_final(values["S"]) list_append(scc, w) dict_overwrite(values["onStack"], w, False) list_insert(values["SCC"], scc, 0) return! Boolean function solve_scc(model : Element, scc : Element): Element m Integer i Integer j String block String blocktype Element incoming String selected Float constant Element t // Construct the matrix first, with as many rows as there are variables // Number of columns is 1 higher i = 0 m = create_node() while (i < read_nr_out(scc)): j = 0 t = create_node() while (j < (read_nr_out(scc) + 1)): list_append(t, 0.0) j = j + 1 list_append(m, t) i = i + 1 // Matrix initialized to 0.0 i = 0 while (i < read_nr_out(scc)): // First element of scc block = scc[i] blocktype = read_type(model, block) // First write 1 in the current block dict_overwrite(m[i], i, 1.0) // Now check all blocks that are incoming if (blocktype == "FullRuntime/AdditionBlock"): constant = 0.0 elif (blocktype == "FullRuntime/MultiplyBlock"): constant = 1.0 incoming = allIncomingAssociationInstances(model, block, "Link") Integer index_to_write_constant index_to_write_constant = -1 while (read_nr_out(incoming) > 0): selected = readAssociationSource(model, set_pop(incoming)) if (set_in(scc, selected)): // Part of the loop, so in the index of selected in scc // Five options: if (blocktype == "FullRuntime/AdditionBlock"): // 1) AdditionBlock // Add the negative of this signal, which is as of yet unknown // x = y + z --> x - y - z = 0 dict_overwrite(m[i], list_index_of(scc, selected), -1.0) elif (blocktype == "FullRuntime/MultiplyBlock"): // 2) MultiplyBlock if (index_to_write_constant != -1): return False! index_to_write_constant = list_index_of(scc, selected) elif (blocktype == "FullRuntime/NegatorBlock"): // 3) NegatorBlock // Add the positive of the signal, which is as of yet unknown dict_overwrite(m[i], list_index_of(scc, selected), 1.0) elif (blocktype == "FullRuntime/DelayBlock"): // 5) DelayBlock // Just copies a single value dict_overwrite(m[i], list_index_of(scc, selected), -1.0) else: // Block that cannot be handled return False! else: // A constant, which we can assume is already computed and thus usable if (blocktype == "FullRuntime/AdditionBlock"): constant = constant + cast_float(read_attribute(model, selected, "signal")) dict_overwrite(m[i], read_nr_out(scc), constant) elif (blocktype == "FullRuntime/MultiplyBlock"): constant = constant * cast_float(read_attribute(model, selected, "signal")) // Not written to constant part, as multiplies a variable // Any other block is impossible: // * Constant would never be part of a SCC // * Delay would never get an incoming constant // * Negation and Inverse only get 1 input, which is a variable in a loop // * Integrator and Derivator never get an incoming constant if (index_to_write_constant != -1): dict_overwrite(m[i], index_to_write_constant, -constant) i = i + 1 // Constructed a complete matrix, so we can start! log(matrix2string(m)) // Solve matrix now eliminateGaussJordan(m) // Now go over m and set signals for each element // Assume that everything worked out... i = 0 while (i < read_nr_out(m)): block = scc[i] instantiate_attribute(model, block, "signal", m[i][read_nr_out(scc)]) log((("Solved " + block) + " to ") + cast_string(m[i][read_nr_out(scc)])) i = i + 1 return True! Integer function list_index_of(lst : Element, elem : Element): Integer i i = 0 while (i < read_nr_out(lst)): if (value_eq(list_read(lst, i), elem)): return i! else: i = i + 1 return -1! Float function step_simulation(model : Element, schedule : Element, time : Float, inputs : Element): Float signal Element incoming String selected String block String elem String blocktype Element memory_blocks Integer i Float delta_t Element scc delta_t = 0.1 memory_blocks = set_create() i = 0 while (i < list_len(schedule)): scc = list_read(schedule, i) i = i + 1 if (list_len(scc) > 1): if (bool_not(solve_scc(model, scc))): output("ALGEBRAIC_LOOP") return time! else: block = list_read(scc, 0) // Execute "block" blocktype = read_type(model, block) incoming = set_copy(inputs[block]) if (blocktype == "FullRuntime/ConstantBlock"): signal = read_attribute(model, block, "value") elif (blocktype == "FullRuntime/AdditionBlock"): signal = 0.0 while (set_len(incoming) > 0): selected = set_pop(incoming) signal = signal + cast_float(read_attribute(model, selected, "signal")) elif (blocktype == "FullRuntime/MultiplyBlock"): signal = 1.0 while (set_len(incoming) > 0): selected = set_pop(incoming) signal = signal * cast_float(read_attribute(model, selected, "signal")) elif (blocktype == "FullRuntime/NegatorBlock"): signal = 0.0 while (set_len(incoming) > 0): selected = set_pop(incoming) signal = float_neg(cast_float(read_attribute(model, selected, "signal"))) elif (blocktype == "FullRuntime/InverseBlock"): signal = 0.0 while (set_len(incoming) > 0): selected = set_pop(incoming) signal = float_division(1.0, cast_float(read_attribute(model, selected, "signal"))) elif (blocktype == "FullRuntime/DelayBlock"): signal = 0.0 if (bool_not(is_physical_float(read_attribute(model, block, "last_in")))): // No memory yet, so use initial condition incoming = allAssociationOrigins(model, block, "FullRuntime/InitialCondition") while (set_len(incoming) > 0): selected = set_pop(incoming) signal = cast_float(read_attribute(model, selected, "signal")) else: signal = read_attribute(model, block, "last_in") set_add(memory_blocks, block) elif (blocktype == "FullRuntime/IntegratorBlock"): if (bool_not(is_physical_float(read_attribute(model, block, "last_in")))): // No history yet, so use initial values incoming = allAssociationOrigins(model, block, "FullRuntime/InitialCondition") while (set_len(incoming) > 0): selected = set_pop(incoming) signal = cast_float(read_attribute(model, selected, "signal")) else: signal = cast_float(read_attribute(model, block, "last_out")) + (delta_t * cast_float(read_attribute(model, block, "last_in"))) instantiate_attribute(model, block, "last_out", signal) set_add(memory_blocks, block) elif (blocktype == "FullRuntime/DerivatorBlock"): if (bool_not(is_physical_float(read_attribute(model, block, "last_in")))): // No history yet, so use initial values incoming = allAssociationOrigins(model, block, "FullRuntime/InitialCondition") while (set_len(incoming) > 0): selected = set_pop(incoming) signal = cast_float(read_attribute(model, selected, "signal")) else: while (set_len(incoming) > 0): selected = set_pop(incoming) signal = (cast_float(read_attribute(model, selected, "signal")) - cast_float(read_attribute(model, block, "last_in"))) / delta_t set_add(memory_blocks, block) elif (blocktype == "FullRuntime/ProbeBlock"): while (set_len(incoming) > 0): signal = cast_float(read_attribute(model, set_pop(incoming), "signal")) output(cast_string(time) + " " + cast_string(read_attribute(model, block, "name")) + " " + cast_string(signal)) instantiate_attribute(model, block, "signal", signal) while (set_len(memory_blocks) > 0): block = set_pop(memory_blocks) // Update memory incoming = set_copy(inputs[block]) while (set_len(incoming) > 0): selected = set_pop(incoming) instantiate_attribute(model, block, "last_in", cast_float(read_attribute(model, selected, "signal"))) // Increase simulation time return time + delta_t! Void function eliminateGaussJordan(m : Element): Integer i Integer j Integer f Integer g Boolean searching Element t Float divisor i = 0 j = 0 while (i < read_nr_out(m)): // Make sure pivot m[i][j] != 0, swapping if necessary while (cast_float(m[i][j]) == 0.0): // Is zero, so find row which is not zero f = i + 1 searching = True while (searching): if (f >= read_nr_out(m)): // No longer any rows left, so just increase column counter searching = False j = j + 1 else: if (cast_float(m[f][j]) == 0.0): // Also zero, so continue f = f + 1 else: // Found non-zero, so swap row t = cast_float(m[f]) dict_overwrite(m, f, cast_float(m[i])) dict_overwrite(m, i, t) searching = False // If we have increased j, we will just start the loop again (possibly), as m[i][j] might be zero again // Pivot in m[i][j] guaranteed to not be 0 // Now divide complete row by value of m[i][j] to make it equal 1 f = j divisor = cast_float(m[i][j]) while (f < read_nr_out(m[i])): dict_overwrite(m[i], f, float_division(cast_float(m[i][f]), divisor)) f = f + 1 // Eliminate all rows in the j-th column, except the i-th row f = 0 while (f < read_nr_out(m)): if (bool_not(f == i)): g = j divisor = cast_float(m[f][j]) while (g < read_nr_out(m[f])): dict_overwrite(m[f], g, cast_float(m[f][g]) - (divisor * cast_float(m[i][g]))) g = g + 1 f = f + 1 // Increase row and column i = i + 1 j = j + 1 return ! String function matrix2string(m : Element): Integer i Integer j String result result = "" i = 0 while (i < read_nr_out(m)): j = 0 while (j < read_nr_out(m[i])): result = result + cast_string(m[i][j]) + ", " j = j + 1 i = i + 1 result = result + "\n" return result!