def align(options, path, included):
'''
Display side by side.
'''
actual = get_src_file(path)
if is_simple_inclusion(options, included, actual):
return
included = included.rstrip('\n').split('\n')
actual = actual.rstrip('\n').split('\n')
matches = [Match(0, 0, 0)] + \
SequenceMatcher(a=included, b=actual).get_matching_blocks()
result = []
diffs_found = False
fmt = '{{0}}|{{1:{}}}|{{2}}'.format(max([len(x) for x in included]))
for i in range(len(matches) - 1):
diffs_found |= align_one(result, options, fmt, included, actual,
matches[i], matches[i + 1])
if options['names_only']:
if diffs_found:
print(path)
elif diffs_found or options['verbose']:
print('\n-- {}'.format(path))
for r in result:
print(r)
def __init__(self,src_file_index,bounds):
self.model = XGBRFRegressor()
self.model_name = "XGBRFRegressor"
self.src = util.get_src_file(src_file_index=src_file_index)
self.lower_bounds = bounds["lower_bounds"]
self.upper_bounds = bounds["upper_bounds"]
self.with_rain = False
self.optimization_methods = optimization_methods
self.num_iterations = 200
self.results = {}
self.result_save_path = 'optimization_result/with_rain_'+str(self.with_rain)+'/'+self.src.split('.')[0].split('/')[-1]+'/'
self.optimization()
self.save_optimization_result()
def __init__(self,
src_file_index,
model_index,
is_ensemble=False,
with_rain=False,
method='bayesian_optimization'):
self.set_bounds(lower_bounds=[36, 2], upper_bounds=[60, 30])
self.model, self.model_name = util.get_model(is_ensemble=is_ensemble,
model_index=model_index)
self.src = util.get_src_file(src_file_index=src_file_index)
self.method = method
self.num_iterations = 200
self.with_rain = with_rain
self.results = None
def __init__(self, src_file_index, model_index, bounds):
self.src = util.get_src_file(src_file_index=src_file_index)
self.model, self.model_name = util.get_model(is_ensemble=True,
model_index=model_index)
self.lower_bounds = bounds["lower_bounds"]
self.upper_bounds = bounds["upper_bounds"]
self.with_rain = False
self.optimization_methods = ["random_search", 'bayesian_optimization']
self.num_iterations = 200
self.results = {}
self.result_save_path = 'optimization_result/with_rain_' + str(
self.with_rain) + '/' + self.src.split('.')[0].split('/')[-1] + '/'
self.optimization()
self.save_optimization_result()