Replace atomic_properties_magpie.py

atomicfeaturespackage/atomicproperties/atomic_properties_magpie.py

 #!/usr/bin/env python
 # coding: utf-8
 
-# In[1]:
+'''
+Module : atomic_properties_magpie
 
+This module with help of  atomic_properties_magpie class from metainfo module instantiates objects with atomic element symbol as identifier to access atomic features available 
+'''
 
 from atomicfeaturespackage.metainfo.metainfo import atomic_properties_magpie,metadata
 import pandas as pd
@@ -10,28 +13,20 @@ import numpy as np
 from mendeleev import element
 import os
 
-# In[2]:
-
 
+# This method_list object could be called after importing this module so one can easily see all the quantities accessible.
 method_list = [method for method in dir(atomic_properties_magpie) if (method.startswith('m_') or method.startswith('_') or method.startswith('__') or method.startswith('val') or method.startswith('section_') or method.startswith('get'))  is False]
 
 
-# In[3]:
-
 
 ls = list(range(0,112))
 df = pd.DataFrame(index = ls,columns = method_list)
 
 
-# In[ ]:
 
 path = os.path.abspath(os.path.join(os.path.dirname(__file__),".."))
 
 
-
-# In[4]:
-
-
 def ionizationen():
     ie = pd.read_table(os.path.join(path, "data","matminer", "IonizationEnergies.table"),header=None,sep = '\t')
     ie['combined']= ie.values.tolist()
@@ -54,15 +49,11 @@ def oxistates():
 def atomicsymbol():
     count = 0
     for i in df['atomic_number']:
-    #for item in df.iloc[count,5]:
         df.iloc[count,5] = element(i).symbol
         count+=1
+        
+#Read the magpie data files and clean and arrange systematically in a pandas dataframe.
     
-
-
-# In[5]:
-
-
 df['atomic_ICSD_vol'] = pd.read_table(os.path.join(path, "data","matminer", "ICSDVolume.table"),header=None)
 df['atomic_cpmass'] = pd.read_table(os.path.join(path, "data","matminer", "HeatCapacityMass.table"),header=None)
 df['atomic_cpmolar'] = pd.read_table(os.path.join(path, "data","matminer", "HeatCapacityMolar.table"),header=None)
@@ -129,22 +120,10 @@ df['thermal_cond_log'] = pd.read_table(os.path.join(path, "data","matminer", "Lo
 df['atomic_ie'] = ionizationen()
 
 
-# In[6]:
-
-
 df.replace(to_replace = ['Missing','Missing["NotAvailable"]','Missing["Unknown"]','None','NA'], value = np.nan,inplace=True )
 
 
-# In[ ]:
-
-
-
-
-
-# ### Section instantiation and its objects attributes are filled. This will create 118 objects unique ( atomic element symbol) which can be used to access its properties
-
-# In[7]:
-
+#Section instantiation and its objects attributes are filled. This will create 118 objects unique ( atomic element symbol) which can be used to access its properties
 
 objs = []
 for i in df['atomic_element_symbol']:
@@ -152,16 +131,6 @@ for i in df['atomic_element_symbol']:
     prop = matminer.m_create(metadata)
     objs.append(matminer)
 
-
-# In[ ]:
-
-
-
-
-
-# In[8]:
-
-
 count = 0
 for obj in objs:
         obj.section_magpie_metadata.source = 'Magpie'
@@ -238,16 +207,11 @@ for count, symbol in enumerate(atomic_element_symbol):
     globals()[symbol] = objs[count]
 
 
-# In[9]:
-
-
-df.columns
-
-
-# In[10]:
-
-
 def definition(abc):
+    '''
+    This function can be used to access quantity definitions for each element features accessible
+    '''
+    
     if abc == 'atomic_ICSD_vol':
         return atomic_properties_magpie.atomic_ICSD_vol.__doc__
     if abc == 'atomic_cpmass':
@@ -386,21 +350,7 @@ def definition(abc):
         return metadata.atomic_basis_set.__doc__
 
 
-# In[11]:
-
-
 def symbol(abc):
-    return globals()[abc]
-
-
-# In[ ]:
-
-
-
-
-
-# In[ ]:
-
-
 
+    return globals()[abc]