Typos.

02_code.md

@@ -6,22 +6,22 @@ numbering:
 
 Python has inarguably become the leading programming language in the scientific community, continually gaining popularity for the past two decades. This is due to Python being friendly for beginners, owing to its less strict language structure (dynamic typing, automatic memory management, non-compiled language) and the plethora of tutorials and examples. It also benefits from being free (this text would be less accessible if it required a licence), with numerous high quality libraries covering a broad range of applications (numeric calculations, image analysis, machine learning, ...), including a number of packages dedicated to S/TEM. The diverse and broad scope of the python ecosystem allows for interoperability between different domains, and file formats as well as easily re-purposing existing implementations algorithms to new domains.
 
-There are a number of libraries dedicated to S/TEM:
-- *ab*TEM - All-Python S/TEM image simulation
-- pyPrismatic - Image simulation (Python wrapper to C++ package Prismatic)
-- pyMultislice - Image simulation 
+There are a number of codes dedicated to S/TEM:
+- *ab*TEM - all-Python S/TEM image simulation
+- pyPrismatic - image simulation (Python wrapper to C++ package Prismatic)
+- pyMultislice - image simulation 
 - py4DSTEM - 4D-STEM analysis
-- libreTEM - 4D-STEM analysis
-- pyxem - 4D-STEM
+- liberTEM - 4D-STEM analysis
+- pyxem - 4D-STEM analysis
 - Hyperspy - General S/TEM analysis 
 - ...
 
-The main libraries used here are:
+The main libraries used in the code examples of this text are:
 - NumPy (np) - fast numerical calculations
 - CuPy (cp) - drop-in replacement for NumPy to run on GPUs
 - Numba - just-in-time Python compiler for scientific and array-oriented computing
 - matplotlib - all things plotting 
-- ipywdigets - making interactive figures
+- ipywidgets - making interactive figures
 - ASE (Atomic Simulation Environment) - creating and visualizing atomic structures   
 - ...