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