From 7c9f6a55a5b96ceaf4049aa5cb63fbc6bb8be55e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Nils=20H=C3=B6lscher?= Date: Thu, 2 Jun 2022 10:29:04 +0200 Subject: [PATCH] Better Task Sets and printing. --- README.md | 2 +- SchedTest.py | 33 +- schedTests/TimeDemandAnalysis.py | 1 - task_sets/100tasks.txt | 3402 ++++++++++++++---------------- task_sets/10tasks.txt | 342 ++- task_sets/TaskSetGenerator.py | 101 + task_sets/old/100tasks.txt | 1819 ++++++++++++++++ task_sets/old/10tasks.txt | 199 ++ 8 files changed, 3904 insertions(+), 1995 deletions(-) create mode 100644 task_sets/TaskSetGenerator.py create mode 100644 task_sets/old/100tasks.txt create mode 100644 task_sets/old/10tasks.txt diff --git a/README.md b/README.md index 682f110..939e398 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,7 @@ The tasksets are represented by a 2D array, where row i is a Task i and the colu ## Runing the Tests -Make sure you have at least python3, argparse and numpy installed. +Make sure you have at least python3, argparse, numpy and tabulate installed. Argpoarse and Numpy can be installed via pip. Use the SchedTest.py Script diff --git a/SchedTest.py b/SchedTest.py index 121f527..1b5c2ff 100644 --- a/SchedTest.py +++ b/SchedTest.py @@ -1,9 +1,12 @@ import argparse import numpy as np +from tabulate import tabulate + import schedTests.LiuAndLaylandBound as LLB import schedTests.TimeDemandAnalysis as TDA import schedTests.HyperbolicBound as HB import include.TasksHelper as TH +import task_sets.TaskSetGenerator as gen # This function Parses the Input Arguments @@ -35,9 +38,10 @@ def main(): # Parse Arguments args = parse_args() print(args.i) - + np.set_printoptions(threshold=np.inf) # Read Tasksets from txt files tasksets = get_tasksets(args.i, args.n) + #tasksets = gen.gen_np_taskset(100) print("Successfully parsed Task Sets") shape = tasksets.shape print("Nr. of Task Sets: " + str(shape[0])) @@ -46,15 +50,18 @@ def main(): # Starting the analysis print("Starting Liu and Layland bound analysis!") stubLLB = [] - for _ in range(shape[0]): + stubU = [] + for k in range(shape[0]): stubLLB.append(False) + stubU.append(TH.getTotalUtilization(tasksets[k], shape[1])) LLBresults = np.array(stubLLB) + U = np.array(stubU) for i in range(shape[0]): if LLB.test(tasksets[i]): LLBresults[i] = True - print("Task Set: " + str(i) + - " fulfills necessary the Liu and Layland Bound!") - print() + # print("Task Set: " + str(i) + + # " fulfills necessary the Liu and Layland Bound!") + #print() print("Starting Hyperbolic bound analysis!") stubHB = [] @@ -64,9 +71,9 @@ def main(): for i in range(shape[0]): if HB.test(tasksets[i]): HBresults[i] = True - print("Task Set: " + str(i) + - " fulfills the sufficient Hyperbolic Bound!") - print() + # print("Task Set: " + str(i) + + # " fulfills the sufficient Hyperbolic Bound!") + #print() print("Starting Time Demand Analysis!") stubTDA = [] @@ -76,7 +83,15 @@ def main(): for i in range(shape[0]): if TDA.test(tasksets[i]) > 0: TDAresults[i] = True - print("Task Set: " + str(i) + " is feasible by TDA analysis!") + #print("Task Set: " + str(i) + " is feasible by TDA analysis!") + + #print results + headers = ["#", "U", "LLB", "HB", "TDA"] + # Generate the table in fancy format. + results = np.array((np.arange(shape[0]), U, LLBresults, HBresults, TDAresults)).T + table = tabulate(results, headers, tablefmt="fancy_grid") + print(table) + if __name__ == "__main__": diff --git a/schedTests/TimeDemandAnalysis.py b/schedTests/TimeDemandAnalysis.py index 3f90b59..6ff254b 100644 --- a/schedTests/TimeDemandAnalysis.py +++ b/schedTests/TimeDemandAnalysis.py @@ -13,7 +13,6 @@ import include.TasksHelper as TH # C_i is accessed as: tasks[i][2] # The number of tasks can be accessed as: tasks.shape[0] - #The Time Demand Analysis Test def test(tasks): #Sorting Taskset by Period/Deadline diff --git a/task_sets/100tasks.txt b/task_sets/100tasks.txt index ced971d..c1929c8 100644 --- a/task_sets/100tasks.txt +++ b/task_sets/100tasks.txt @@ -1,1819 +1,1617 @@ -5.37799781772,5.37799781772,0.00617893909592 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generate_periods_loguniform( + num_tasks, num_tasksets, min_period, max_period, rounded) + # Create utilizations. + tasksets_utilizations = generate_utilizations_uniform( + num_tasks, num_tasksets, utilization) + # Create tasksets by matching both of the above. + tasksets = [] + tasksetsnp = [] + for i in range(num_tasksets): + taskset = [] + for j in range(num_tasks): + task = { + 'execution': (tasksets_periods[i][j] + * tasksets_utilizations[i][j]), + 'period': tasksets_periods[i][j], + 'deadline': tasksets_periods[i][j] + } + taskset.append(task) + tasksets.append(taskset) + tasksetsnp.append(np.array((tasksets_periods[0],tasksets_periods[0], np.array(tasksets_periods[0])*np.array(tasksets_utilizations[0]))).T) + return np.array(tasksetsnp) + +def generate_utilizations_uniform(num_tasks, num_tasksets, utilization): + """Generate utilizations with UUNIFAST. + Variables: + num_tasks: number of tasks per set + num_tasksets: number of sets + utilization: desired utilization in (0,1] + """ + def uunifast(num_tasks, utilization): + """UUNIFAST utilization pulling.""" + utilizations = [] + cumulative_utilization = utilization + for i in range(1, num_tasks): + # Randomly set next utilization. + cumulative_utilization_next = ( + cumulative_utilization + * random.random() ** (1.0/(num_tasks-i))) + utilizations.append( + cumulative_utilization - cumulative_utilization_next) + # Compute remaining utilization. + cumulative_utilization = cumulative_utilization_next + utilizations.append(cumulative_utilization_next) + # Return list of utilizations. + return utilizations + # Return one list of utilizations for each task set. + return [uunifast(num_tasks, utilization) for i in range(num_tasksets)] + + +# help functions + +def generate_periods_loguniform(num_tasks, num_tasksets, min_period, + max_period, rounded=False): + """Generate log-uniformly distributed periods to create tasks. + Variables: + num_tasks: number of tasks per set + num_tasksets: number of sets + min_period: minimal period + max_period: maximal period + rounded: flag to round periods to integers + """ + # Create random periods. + periods = np.exp(np.random.uniform( + low=np.log(min_period), + high=np.log(max_period), + size=(num_tasksets, num_tasks))) + # Make list out of them + if rounded: # round periods to nearest integer + return np.rint(periods).tolist() + else: + return periods.tolist() + + +def gen_np_taskset(NrTasks): + tasksets = [] + for i in range(55,101,3): + tasksets.append(gen_tasksets(NrTasks,1,1,100,i/100)[0]) + return np.array(tasksets) + diff --git a/task_sets/old/100tasks.txt b/task_sets/old/100tasks.txt new file mode 100644 index 0000000..ced971d --- /dev/null +++ b/task_sets/old/100tasks.txt @@ -0,0 +1,1819 @@ +5.37799781772,5.37799781772,0.00617893909592 +66.713260637,66.713260637,0.126599069162 +8.60569818104,8.60569818104,0.0512612786092 +31.8732059856,31.8732059856,0.295861380775 +7.58340298712,7.58340298712,0.0349438818557 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