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- # main imports
- import os
- import logging
- import numpy as np
- # module imports
- from .Checkpoint import Checkpoint
- class BasicCheckpoint(Checkpoint):
- def __init__(self, _algo, _every, _filepath):
- self.algo = _algo
- self.every = _every
- self.filepath = _filepath
- def run(self):
- # get current best solution
- solution = self.algo.bestSolution
- currentEvaluation = self.algo.getGlobalEvaluation()
- # backup if necessary
- if currentEvaluation % self.every == 0:
- logging.info("Checkpoint is done into " + self.filepath)
- solutionData = ""
- solutionSize = len(solution.data)
- for index, val in enumerate(solution.data):
- solutionData += str(val)
- if index < solutionSize - 1:
- solutionData += ' '
- line = str(currentEvaluation) + ';' + solutionData + ';' + str(
- solution.fitness()) + ';\n'
- # check if file exists
- if not os.path.exists(self.filepath):
- with open(self.filepath, 'w') as f:
- f.write(line)
- else:
- with open(self.filepath, 'a') as f:
- f.write(line)
- def load(self):
- if os.path.exists(self.filepath):
- logging.info('Load best solution from last checkpoint')
- with open(self.filepath) as f:
- # get last line and read data
- lastline = f.readlines()[-1]
- data = lastline.split(';')
- # get evaluation information
- globalEvaluation = int(data[0])
- if self.algo.parent is not None:
- self.algo.parent.numberOfEvaluations = globalEvaluation
- else:
- self.algo.numberOfEvaluations = globalEvaluation
- # get best solution data information
- solutionData = list(map(int, data[1].split(' ')))
- self.algo.bestSolution.data = np.array(solutionData)
- self.algo.bestSolution.score = float(data[2])
- else:
- print('No backup found... Start running')
- logging.info(
- "Can't load backup... Backup filepath not valid in Checkpoint")
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