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

# # Some system statistics (Nestle1904GBI)

# ## Table of content <a class="anchor" id="TOC"></a>
# * <a href="#bullet1">1 - Introduction</a>
# * <a href="#bullet2">2 - Load Text-Fabric app and data</a>
# * <a href="#bullet3">3 - Performing the queries</a>
#     * <a href="#bullet3x1">3.1 - Print the Text-Fabric version</a>
#     * <a href="#bullet3x2">3.2 - Dump selection of header </a>    
#     * <a href="#bullet3x3">3.3 - Memory footprint</a>    
#     * <a href="#bullet3x4">3.4 - List loaded features</a> 
#     * <a href="#bullet3x5">3.5 - Statistics on node types</a>
#     * <a href="#bullet3x6">3.6 - Node number ranges</a>
# * <a href="#bullet4">4 - Required libraries</a>

# # 1 - Introduction <a class="anchor" id="bullet1"></a>
# ##### [Back to TOC](#TOC)
# 
# This Jupyter Notebook showcases several examples of statistical analysis performed on a Text-Fabric corpus.

# # 2 - Load Text-Fabric app and data <a class="anchor" id="bullet2"></a>
# ##### [Back to TOC](#TOC)

# In[1]:


get_ipython().run_line_magic('load_ext', 'autoreload')
get_ipython().run_line_magic('autoreload', '2')


# In[2]:


# Loading the Text-Fabric code
# Note: it is assumed Text-Fabric is installed in your environment
from tf.fabric import Fabric
from tf.app import use


# In[3]:


# load the N1904 app and data
N1904 = use ("tonyjurg/Nestle1904GBI", version="0.4", hoist=globals())


# In[4]:


# The following will push the Text-Fabric stylesheet to this notebook (to facilitate proper display with notebook viewer)
N1904.dh(N1904.getCss())


# # 3 - Performing the queries <a class="anchor" id="bullet3"></a>
# ##### [Back to TOC](#TOC)

# ## 3.1 - Print the Text-Fabric version <a class="anchor" id="bullet3x1"></a>
# ##### [Back to TOC](#TOC)
# 
# Although this is somewhat trivial, this example does serve a purpose. We will print te version by means of calling the Text-Fabric parameter [VERSION](https://annotation.github.io/text-fabric/tf/parameters.html#tf.parameters.VERSION) which is fixed for the whole programm. To access any of these parameters in our notebook, it first needs to be imported from `tf.parameters`.

# In[5]:


from tf.parameters import VERSION
print ('TextFabric version: {}'.format(VERSION))


# Note that any other parameters can be dumped in similar manner.

# In[6]:


N1904.showContext(...)


# ## 3.2 - Dump selection of header<a class="anchor" id="bullet3x2"></a>
# ##### [Back to TOC](#TOC)
# 
# In this example the header of the loaded Text-Fabric dataset is dumped. This is done by means of an API call to [`A.header()`](https://annotation.github.io/text-fabric/tf/advanced/links.html#tf.advanced.links.header). 
# 
# Please note that in the example below `A` is replaced by `N1904`. This is result of the method of incantation:
# > N1904 = use (... *etc* ... )
# 
# The [`use`](https://annotation.github.io/text-fabric/tf/app.html#tf.app.use) function returns an oject whose attributes and methods constitute the advanced API. In the 
# 
# 
# 

# In[7]:


N1904.header(allMeta=False)


# ## 3.3 - Memory footprint <a class="anchor" id="bullet3x3"></a>
# ##### [Back to TOC](#TOC)
# 
# The following API call [`footprint`](https://annotation.github.io/text-fabric/tf/core/api.html#tf.core.api.Api.footprint) provides a nicely formatted overview of memory footprint for each of the features in the Text_fabric corpus.

# In[8]:


TF.footprint()


# ## 3.4 - List loaded features <a class="anchor" id="bullet3x4"></a>
# ##### [Back to TOC](#TOC)
# 
# The API call [`A.isLoaded()`](https://annotation.github.io/text-fabric/tf/core/api.html#tf.core.api.Api.isLoaded) will show information about loaded features.

# In[9]:


N1904.isLoaded()


# ## 3.5 - Statistics on node types<a class="anchor" id="bullet3x5"></a>
# ##### [Back to TOC](#TOC)
# 
# This example will show various statistics on node types. The call to [`C.levels.data`](https://annotation.github.io/text-fabric/tf/core/prepare.html#tf.core.prepare.levels) results in list of ordered tuples which will be nicely displayed using the tabulate function.

# In[10]:


# Library to format table
from tabulate import tabulate
headers = ["Node", "Avarage # of slots","first","last"]
ResultList= C.levels.data
print(tabulate(ResultList, headers=headers, tablefmt='fancy_grid'))


# ## 3.6 - Node number ranges <a class="anchor" id="bullet3x6"></a>
# ##### [Back to TOC](#TOC)

# In[11]:


for NodeType in F.otype.all:
    print (NodeType, F.otype.sInterval(NodeType))


# Note that the ranges shown as output of this command are (except, possibly with repect to order) the same as found in file `otype.tf`:
# >
# ```@node
# @TextFabric version=11.4.10
# ...
# @valueType=str
# @writtenBy=Text-Fabric
# @dateWritten=2023-06-19T16:21:20Z
# 
# 1-137779	word
# 137780-137806	book
# 137807-138066	chapter
# 138067-154190	clause
# 154191-226864	phrase
# 226865-232584	sentence
# 232585-240527	verse
# ```

# # 4 - Required libraries <a class="anchor" id="bullet4"></a>
# ##### [Back to TOC](#TOC)
# 
# The scripts in this notebook require (beside `text-fabric`) the following Python libraries to be installed in the environment:
# 
#     tabulate
# 
# You can install any missing library from within Jupyter Notebook using either`pip` or `pip3`.

# In[ ]: