[custom] fix lesson contents

Author: zkamvar

episodes/02-numpy.md

@@ -218,7 +218,7 @@ It takes a bit of getting used to,
 but one way to remember the rule is that
 the index is how many steps we have to take from the start to get the item we want.
 
-![](fig/python-zero-index.svg){alt="\\"data\\" is a 3 by 3 numpy array containing row 0: \['A', 'B', 'C'\], row 1: \['D', 'E', 'F'\], androw 2: \['G', 'H', 'I'\]. Starting in the upper left hand corner, data\[0, 0\] = 'A', data\[0, 1\] = 'B',data\[0, 2\] = 'C', data\[1, 0\] = 'D', data\[1, 1\] = 'E', data\[1, 2\] = 'F', data\[2, 0\] = 'G',data\[2, 1\] = 'H', and data\[2, 2\] = 'I',in the bottom right hand corner."}
+![](fig/python-zero-index.svg){alt="'data' is a 3 by 3 numpy array containing row 0: \['A', 'B', 'C'\], row 1: \['D', 'E', 'F'\], androw 2: \['G', 'H', 'I'\]. Starting in the upper left hand corner, data\[0, 0\] = 'A', data\[0, 1\] = 'B',data\[0, 2\] = 'C', data\[1, 0\] = 'D', data\[1, 1\] = 'E', data\[1, 2\] = 'F', data\[2, 0\] = 'G',data\[2, 1\] = 'H', and data\[2, 2\] = 'I',in the bottom right hand corner."}
 
 :::::::::::::::::::::::::::::::::::::::::  callout
 

episodes/11-debugging.md

@@ -90,7 +90,7 @@ scientists tend to do the following:
   Data analysts frequently use simple visualizations to check both
   the science they're doing
   and the correctness of their code
-  (just as we did in the [opening lesson](01-numpy) of this tutorial).
+  (just as we did in the [opening lesson](02-numpy.html) of this tutorial).
   This should only be used for debugging as a last resort,
   though,
   since it's very hard to compare two visualizations automatically.

episodes/12-cmdline.md

@@ -704,7 +704,7 @@ main()
 
 ## Finding Particular Files
 
-Using the `glob` module introduced [earlier](04-files),
+Using the `glob` module introduced [earlier](06-files.html),
 write a simple version of `ls` that shows files in the current directory
 with a particular suffix.
 A call to this script should look like this:

code/Makefile renamed to episodes/files/code/Makefile

@@ -31,7 +31,7 @@ To see how effective the treatment is we would like to:
 1. Calculate the average inflammation per day across all patients.
 2. Plot the result to discuss and share with colleagues.
 
-![](fig/lesson-overview.svg "Lesson Overview"){alt='3-step flowchart shows inflammation data records for patients moving to the Analysis stepwhere a heat map of provided data is generated moving to the Conclusion step that asks thequestion, How does the medication affect patients?'}
+![](episodes/fig/lesson-overview.svg "Lesson Overview"){alt='3-step flowchart shows inflammation data records for patients moving to the Analysis stepwhere a heat map of provided data is generated moving to the Conclusion step that asks thequestion, How does the medication affect patients?'}
 
 ### Data Format
 

code/argv_list.py renamed to episodes/files/code/argv_list.py

@@ -20,7 +20,7 @@ arthritis treatment.
 
 We make reference in the lesson that this data is suspicious and has been
 synthetically generated in Python by the imaginary "Dr. Maverick"! The script used to generate
-the inflammation data is included as [`code/gen_inflammation.py`](code/gen_inflammation.py).
+the inflammation data is included as [`code/gen_inflammation.py`](../episodes/files/code/gen_inflammation.py).
 
 ## Overall
 
@@ -99,7 +99,7 @@ which are covered in the lesson on the shell.
 
 - NumPy methods.
 
-  We used to use NumPy array methods in the first [NumPy topic](01-numpy).
+  We used to use NumPy array methods in the first [NumPy topic](02-numpy.html).
   We switched these methods to the equivalent functions because a majority
   of instructors supported the change; see
   [PR #244](https://github.com/swcarpentry/python-novice-inflammation/pull/244)