adding back todos

src/eliater/network_validation.py

@@ -13,8 +13,8 @@
 If the percentage of failed tests is higher than the user expects, additional experiments
 is required to change the model.
 
-T. How does the user set their expectation? This kind of text gives no help to someone reading this for the
-T. first time that wants to understand how to use this or why to use it
+.. todo:: How does the user set their expectation? This kind of text gives no help to someone reading this for the
+.. todo:: first time that wants to understand how to use this or why to use it
 
 
 T Cell Signalling Example
@@ -23,7 +23,7 @@
 in [Sachs2005]_. It models the molecular mechanisms and regulatory processes involved
 in T cell activation, proliferation, and function.
 
-T. what about explanation of data?
+.. todo:: what about explanation of data?
 
 .. figure:: img/signaling.png
    :width: 200px
@@ -64,7 +64,7 @@
 The results show that out of 35 cases, 1 failed. The failed test is
 the conditional independence between P38 and PIP2, given PKC, with a p-value of 0.00425.
 
-T. link all mentions of biological entities to HGNC or UniProt pages
+.. todo:: link all mentions of biological entities to HGNC or UniProt pages
 
 Finding False Negatives
 -----------------------
@@ -76,11 +76,11 @@
 
 There are three main reasons that the result of the test may be false negative or false positive:
 
-1. T. 1 sentence summary of scenario 1
-2. T. 1 sentence summary of scenario 2
-3. T. 1 sentence summary of scenario 3
+1. .. todo:: 1 sentence summary of scenario 1
+2. .. todo:: 1 sentence summary of scenario 2
+3. .. todo:: 1 sentence summary of scenario 3
 
-T. give meaningful names for all point headers
+.. todo:: give meaningful names for all point headers
 
 False Negatives Scenario 1
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -92,7 +92,7 @@
 
 Note that this module employs traditional tests where the null hypothesis is conditional independence.
 
-T. demonstrate an example
+.. todo:: demonstrate an example
 
 False Negatives Scenario 2
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -102,7 +102,7 @@
 utilizing the Pearson test yields a test statistic that adheres to the Normal distribution. If these
 assumptions are not satisfied by the data, the outcomes may lead to both false positives and false negatives.
 
-T. demonstrate an example
+.. todo:: demonstrate an example
 
 False Negatives Scenario 3
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -112,9 +112,9 @@
 as dependent. Hence, chances of false negatives increases, i.e., a pair of variables that are
 conditionally independent, be concluded as conditional dependent by the test.
 
-T. this can be one sentence (super wordy), but also needs a second sentence answering the question: "why?"
+.. todo:: this can be one sentence (super wordy), but also needs a second sentence answering the question: "why?"
 
-T. don't use first person in a demo. Just use active verbs about the demo itself
+.. todo:: don't use first person in a demo. Just use active verbs about the demo itself
 
 We demonstrate this third phenomena below using the following example graph, observational data
 (simulated specifically for this graph using