change config language to simple (or complex) code
Signed-off-by: Csaba Kiraly <csaba.kiraly@gmail.com>
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"""Example configuration file
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This file illustrates how to define options and simulation parameter ranges.
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It also defines the traversal order of the simulation space. As the file
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extension suggests, configuration is pure python code, allowing complex
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setups. Use at your own risk.
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To use this example, run
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python3 study.py config_example
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Otherwise copy it and modify as needed. The default traversal order defined
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in the nested loop of nextShape() is good for most cases, but customizable
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if needed.
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"""
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import logging
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from DAS.shape import Shape
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dumpXML = 1
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visualization = 1
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logLevel = logging.INFO
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# Number of simulation runs with the same parameters for statistical relevance
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runs = range(10)
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# Number of validators
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numberValidators = range(256, 513, 128)
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# Percentage of block not released by producer
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failureRates = range(10, 91, 40)
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# Block size in one dimension in segments. Block is blockSizes * blockSizes segments.
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blockSizes = range(32,65,16)
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# Per-topic mesh neighborhood size
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netDegrees = range(6, 9, 2)
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# number of rows and columns a validator is interested in
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chis = range(4, 9, 2)
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deterministic = False
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def nextShape():
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for run in runs:
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for fr in failureRates:
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for chi in chis:
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for blockSize in blockSizes:
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for nv in numberValidators:
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for netDegree in netDegrees:
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# Network Degree has to be an even number
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if netDegree % 2 == 0:
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shape = Shape(blockSize, nv, fr, chi, netDegree, run)
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yield shape
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32
study.py
32
study.py
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#! /bin/python3
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import time, sys, random, copy
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import importlib
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from DAS import *
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@ -9,7 +10,7 @@ def study():
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print("You need to pass a configuration file in parameter")
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exit(1)
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config = Configuration(sys.argv[1])
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config = importlib.import_module(sys.argv[1])
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shape = Shape(0, 0, 0, 0, 0, 0)
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sim = Simulator(shape, config)
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sim.initLogger()
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@ -22,26 +23,17 @@ def study():
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sim.logger.info("Starting simulations:", extra=sim.format)
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start = time.time()
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for run in range(config.numberRuns):
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for nv in range(config.nvStart, config.nvStop+1, config.nvStep):
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for blockSize in range(config.blockSizeStart, config.blockSizeStop+1, config.blockSizeStep):
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for fr in range(config.failureRateStart, config.failureRateStop+1, config.failureRateStep):
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for netDegree in range(config.netDegreeStart, config.netDegreeStop+1, config.netDegreeStep):
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for chi in range(config.chiStart, config.chiStop+1, config.chiStep):
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for shape in config.nextShape():
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if not config.deterministic:
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random.seed(datetime.now())
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if not config.deterministic:
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random.seed(datetime.now())
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# Network Degree has to be an even number
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if netDegree % 2 == 0:
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shape = Shape(blockSize, nv, fr, chi, netDegree, run)
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sim.resetShape(shape)
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sim.initValidators()
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sim.initNetwork()
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result = sim.run()
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sim.logger.info("Shape: %s ... Block Available: %d in %d steps" % (str(sim.shape.__dict__), result.blockAvailable, len(result.missingVector)), extra=sim.format)
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results.append(copy.deepcopy(result))
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simCnt += 1
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sim.resetShape(shape)
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sim.initValidators()
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sim.initNetwork()
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result = sim.run()
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sim.logger.info("Shape: %s ... Block Available: %d in %d steps" % (str(sim.shape.__dict__), result.blockAvailable, len(result.missingVector)), extra=sim.format)
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results.append(copy.deepcopy(result))
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simCnt += 1
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end = time.time()
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sim.logger.info("A total of %d simulations ran in %d seconds" % (simCnt, end-start), extra=sim.format)
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