# -*- coding: utf-8 -*-

"""

Created on Fri Aug 16 21:22:07 2013

@author: Vasya

"""

import numpy as np

import os

import getLikes

import pandas as pd

import genSimLDAlib as gslib

modelDir = r'Z:\ermunds\results\2012 20topics'

modelName = '2012 20topics'

topicsPs = np.genfromtxt(os.path.join(modelDir,'topics_marginal.csv'))

words = getLikes.words_from_file(r"Z:\ermunds\adjectives.txt")

brands =getLikes.words_from_file(r"Z:\ermunds\brands.txt")

(divs,_,_) = getLikes.get_divs (words,brands,indir=modelDir, modelName=modelName ,topics_marginal_probs=topicsPs)

(sims,b,w) = getLikes.get_likes(words,brands,indir=modelDir, modelName=modelName )

dirs = gslib.LDAdirs(modelName,modelDir)

(dict1,_,lda)=gslib.loadStuff(dirs)

brands_df = getLikes.pruneWordsList(brands,lda)

words_df = getLikes.pruneWordsList(words,lda)

probs = getLikes.ptopic_given_word(lda,topicsPs)

probs_df = pd.DataFrame(probs, columns=lda.id2word.values())

alls = pd.concat([ brands_df["IDs"] ,words_df["IDs"]])

x = probs_df[alls]

x.columns = alls.index

writer = pd.ExcelWriter(os.path.join(modelDir,modelName+'_new.xlsx'))

sims.to_excel(writer, sheet_name='cosine distance')

divs.to_excel(writer, sheet_name='KL divs')

b.to_excel(writer, sheet_name='brands')

w.to_excel(writer, sheet_name='words')

x.to_excel(writer, sheet_name='p_topic_given_word')

writer.save()

words = "Different Distinctive Unique Dynamic Innovative Leader Reliable Arrogant Authentic Carefree Charming Daring Energetic Friendly Fun Glamorous Healthy Helpful Independent Intelligent Kind Obliging Original Prestigious Progressive Restrained Rugged Sensuous Simple Social Straightforward Stylish Traditional Trendy Trustworthy Unapproachable"

words=words.split()

def total_purge(words):

return stats