mpml2.py

import Perspective as pr
import Learn as lr
import Analyse as alz
import DrawGraph as dr

class mpml:
    def __init__(self,base_classifier,dataFrame,target,max_perspectives=0,sig=False,perspectiveList=[]):
        self.max_perspectives = max_perspectives
        self.sig = sig #Significant change value
        self.base_classifier = base_classifier #The algo that will create the base classifiers
        self.dataFrame = dataFrame
        self.target = target
        self.perspectiveList = perspectiveList
        self.clf_name = self.base_classifier.__class__.__name__

    #Calcualte the significant change value
    def calc_sig(self):
        pr.sigValCsv(self.dataFrame,self.target)

    #Generate relationship scores between features 
    def gen_relation_scores(self):
        pr.generateRelations(self.dataFrame,self.target)

    #Generate perspectives 
    def gen_perspectives(self):
        self.perspectiveList = pr.generatePerspectives(self.dataFrame,self.target)

    #Generate custom perspectives
    def gen_custom_perspectives(self, custom_perspective_list):
        self.perspectiveList = pr.generatePerspectives(self.dataFrame,self.target,custom_perspective_list)

    #Train a modle on each perspective created
    def train_perspectives(self):
        lr.MPML(self.dataFrame,self.base_classifier,self.perspectiveList,self.target,1,"Name")
    
    #Prints out th list of all features in the dataset
    def list_features(self):
        print(pr.viewFeatures(self.dataFrame,self.target))

    #Prints out a list of all perspectives generated by this instance
    def view_perspectives(self):
        print(self.perspectiveList)

    #Generates an analysis report for a single instance
    def analyse_inst(self,inst):
        alz.analysePerspective(self.dataFrame,self.target,inst,self.base_classifier,self.base_classifier.__class__.__name__,"Data",False)

    #Generates an analysis report for a list instances
    def analyse_inst_list(self,instList):
        for inst in instList:
            alz.analysePerspective(self.dataFrame,self.target,inst,self.base_classifier,self.clf_name,"Data",False,self.perspectiveList)
        dr.quad_plot(instList,self.clf_name)

    

    

    #List of Methods
    #analye a particular instance
    # analyse_inst()
    # #if they want to control truon test and returen score on spcific inourt
    # fit()
    # score()
    # #get the modles created from each perspective
    # get_models()
    # #get_acuracy on each perspective
    # get_models_score()
    # #functon to set custom persspectives
    # set_perspectives()
    # train_custom_perspeectives()