successully implemented TDA
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@ -21,43 +21,31 @@ def test(tasks):
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# This makes implementing TDA a lot easier
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shape = tasks.shape
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sortedtasks = tasks[tasks[:, 0].argsort()]
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isSchedulable = True
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global set_num
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set_num += 1
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print(f"\n======= TASK SET #{set_num} =======\n")
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# For each tasks in the ordered set
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for i in range(len(sortedtasks)):
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print(f'Task #{i} {tasks[i]}:')
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# calculate the time points for the demand function
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t_old = 10**-3
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i = 0
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# calculate the time points for the demand function
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# t = j * P_k for k = 1, 2,...i and j = 1, 2,...,math.ceil(P_i / P_k)
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# list_of_t = [
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# j * TH.P_i(sortedtasks, k)
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# for k in range(i-1)
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# for j in range(1, int(math.ceil(TH.D_i(sortedtasks, i) / TH.P_i(sortedtasks, k))))
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# ]
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# list_of_t = [TH.P_i(sortedtasks, k-1) for k in range(i+1)]
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list_of_t = []
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for k in range(i):
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list_of_t.append(TH.P_i(sortedtasks, k-1))
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while True:
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t_new = workload_func(sortedtasks, i, t_old)
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# if the workload of task i exceeds the deadline
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if t_new > TH.D_i(sortedtasks, i):
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return False # task not schedulable
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print(f'\t list of t: {list_of_t}')
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# at any time t between 0 and and TH.P_i
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for j in range(len(list_of_t)):
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# for t in range(int(TH.C_i(sortedtasks, i)), int(TH.P_i(sortedtasks, i)+1), int(step)):
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# if the demand for CPU time of task i exceeds the available time t
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if time_demand_func(sortedtasks, i, list_of_t[j]) > list_of_t[j]:
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isSchedulable = False # then the task i will not meet its deadline, hence taskset not schedulable
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print(f'\t time-demand for t := {list_of_t[j]} ---> {time_demand_func(sortedtasks, i, list_of_t[j])} is schedulable: {isSchedulable}')
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return isSchedulable
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if t_new == t_old:
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i += 1
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t_old = 10**-3
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# chech array out of bounds
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if i == len(sortedtasks):
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return True
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t_old = t_new
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def time_demand_func(tasks, i, t):
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def workload_func(tasks, i, t):
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sum = 0
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for k in range(i-1):
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for k in range(i):
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sum += math.ceil(t / TH.P_i(tasks, k)) * TH.C_i(tasks, k)
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return TH.C_i(tasks, i) + sum
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