Created
August 20, 2014 23:36
-
-
Save adilo/79a95b2757c8eb76b4f0 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| ''' | |
| Created on 16 sept. 2013 | |
| @author: Adil OURIDA. | |
| @contact: adilourida@gmail.com | |
| =========== | |
| Algorithm : | |
| =========== | |
| Let's take this example : | |
| 50 | |
| 0 5 10 | |
| 1 3 5 | |
| 3 7 12 | |
| 6 11 20 | |
| 14 17 8 | |
| 19 24 14 | |
| 21 22 2 | |
| I think that one of the solutions is to delimit the whole list into | |
| independent lists so to calculate the optimum energy unit for each one. | |
| And the global energy unit is the sum. | |
| ______10______ ____20____ | |
| | | | | | |
| 0 1 3 5 6 7 11 | |
| |_5__|_______12_____| | |
| => optimum is 80 : 10 + 50 + 20 | |
| ___8__ | |
| | | | |
| 14 17 | |
| => 14 - 11 is the distance between the two sequential lists. | |
| => optimum is 8 | |
| _________14_______ | |
| | | | |
| 19 21 22 24 | |
| |__2__| | |
| => 19 - 17 is the distance between the two sequential lists. | |
| => optimum is 14 | |
| => The global is : 80 + 3*50 + 8 + 2*50 + 14 = 352 | |
| ''' | |
| class Model: | |
| ''' | |
| class docs | |
| ''' | |
| def __repr__(self): | |
| return repr((self.x, self.y, self.eu)) | |
| # Energy Unit | |
| eu_normal = 0; | |
| def delimitList(models): | |
| """ | |
| """ | |
| retModels = list(); | |
| retModels.append(models[0]) | |
| comp = models[0].y | |
| i = 0 | |
| for model in models: | |
| if i != 0: | |
| if model.x < comp: | |
| # add | |
| retModels.append(model) | |
| if model.y > comp : | |
| comp = model.y | |
| else: | |
| # stopList | |
| break | |
| i = i + 1 | |
| return retModels | |
| def getOptimumValue(models, diffList): | |
| optimumValue_ = 0 | |
| tuples_ = [] | |
| i = 0 | |
| for model in models: | |
| tuples = [(model.x,model.y)] | |
| opt = 0 | |
| opt = opt + (model.x - diffList) * eu_normal | |
| opt = opt + model.eu | |
| comp = model.y | |
| for model2 in models: | |
| if model2.x >= comp: | |
| # add | |
| opt = opt + (model2.x - model.y) * eu_normal | |
| opt = opt + model2.eu | |
| comp = model2.y | |
| tuples.append((model2.x,model2.y)) | |
| sortedY = sorted(models, key=lambda model: model.y) | |
| opt = opt + (sortedY[-1].y - comp) * eu_normal | |
| if i != 0: | |
| if opt < optimumValue_: | |
| optimumValue_ = opt | |
| tuples_ = tuples | |
| else: | |
| optimumValue_ = opt | |
| tuples_ = tuples | |
| i = i + 1 | |
| return optimumValue_,tuples_ | |
| f = open('in', 'r') | |
| i = 0; | |
| models = list() | |
| for line in f: | |
| if i == 0 : | |
| eu_normal = int(line) | |
| else: | |
| split = line.split(" ") | |
| model = Model(); | |
| model.x = int(split[0]) | |
| model.y = int(split[1]) | |
| model.eu = int(split[2]) | |
| models.append(model) | |
| i = i + 1 | |
| # print(eu_normal) | |
| models = sorted(models, key=lambda model: model.x) | |
| # print(models) | |
| f.close() | |
| hasNext = True | |
| diffList = 0 | |
| optimumValue = 0 | |
| tuples = [] | |
| while hasNext: | |
| if not models: | |
| hasNext = False | |
| else: | |
| result = delimitList(models); | |
| value = getOptimumValue(result, diffList) | |
| optimumValue = optimumValue + value[0] | |
| for t in value[1]: | |
| tuples.append(t) | |
| diffList = result[-1].y | |
| for model in result: | |
| models.remove(model) | |
| print(optimumValue) | |
| print(tuples) | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment