#!/usr/bin/env python
# coding: utf-8

# # pyhasse.core

# ### Objectives
# 
# pyhasse.core is the basic module for calculations within  
# partially ordered sets.
# Beside others: It imports the dataset, which is to be analyzed.

# In[1]:


import os
import pathlib
from pyhasse.core.csv_io import CSVReader
from pyhasse.core.matrix import Matrix


# In[2]:


#TESTFILENAME = '/csvdata/zeta-test.csv'
#TESTFILENAME = '/csvdata/acm-houses.csv'
#TESTFILENAME = '/csvdata/chain-demo.csv'
#TESTFILENAME = '/csvdata/chain-pollution.csv'
#TESTFILENAME = '/csvdata/copeland_demo.csv'
#TESTFILENAME = '/csvdata/fuzzy-demo.csv'
#TESTFILENAME = '/csvdata/main19chemicals.csv'
#TESTFILENAME = '/csvdata/pesticides-demo.txt'
#TESTFILENAME = '/csvdata/spyout-demo.csv'
#TESTFILENAME = '/csvdata/zeta-test.csv'
TESTFILENAME = '/csvdata/check-K.csv'

HERE = pathlib.Path('__file__').parent
csv = CSVReader(fn=str(HERE) + TESTFILENAME, ndec=3)
# calc a reduced system


# ### Check if all data are correct imported

# ### Objects

# In[3]:


print(csv.obj)


# ### Attributes

# In[4]:


print(csv.prop)


# ### All data

# In[5]:


for row in csv.data:
    print(row)


# ## Basic calculations

# ### Equivalence classes

# In[6]:


# prepare dataset
matrix = Matrix(csv.data, csv.obj, csv.prop, reduced=True)


# #### The next step delivers the equivalence classes in terms of the object's pointers and their labels, additionally the characteristic of the structure induced by equivalences: K

# K = sum Ni*(Ni-1)
# 
# K = 0: There is no nontrivial equivalence class
# 
# K > 0: Check the list below to detect the nontirivial equivalence classes

# In[7]:


k = 0
for i in csv.eqm:
    k += (len(i))*(len(i)-1)
print(f"K = {k} <-- sum Ni*(Ni-1)")


# In[8]:


#eqm = csv.generate_eqcl(csv.obj,csv.eqm)
eqm, rred =  matrix.generate_equivalenceclasses(csv.data, csv.rows, csv.cols, prec=None)
print(f'{"Pointer":>8} {"object label represents":^30} {"equivalence class":^20}')
print(f'{59 * "-"}')
for idx, value in enumerate(matrix.obj):
      print(f'{csv.obj.index(value):>8} {value:^30} {str(eqm[idx]):^20}')     


# In[9]:


from pyhasse.core.order import Order
precision = 4
order = Order(csv.data,
              csv.rows,
              csv.cols)
zeta =order.calc_relatmatrix(csv.data, csv.rows, csv.cols)
zeta = order.calc_relatmatrix(
    datamatrix=matrix.data,
    rows=matrix.rows,
    cols=matrix.cols,
    prec=precision)
covd_act, cov_act = order.calc_cov(zeta, matrix.rows)


# In[10]:


print(csv.eqm)


# ### Zeta-Matrix

# In[11]:


for row in zeta:
    print(row)


# In[ ]: