Added documentation + licences for Cython implementation

README.md

@@ -43,6 +43,19 @@ pip3 install pypiemma
 
 Dependencies: Python 3.6 or higher; `pip3 install Pygments Markdown matplotlib pandas pypiscout`
 
+<details closed>
+<summary>Optional: Cython</summary>
+For bigger projects escpecially the number of objects will grow. We provide an optional Cython implementation which can speed-up your analysis (you will gain typically about **30 % speed-up**).
+
+For now we do not provide the binaries with Emma, hence you have to compile (make sure a suitable compiler is installed) it yourself (don't worry it is quick and easy):
+
+Install the `Cython` package (`pip install Cython`) and (in the Emma top level folder) execute (MSVC is recommended on Windows):
+
+```
+python setup.py build_ext --inplace --compiler=msvc
+```
+</details>
+
 
 ## General Workflow
 The following figure shows a possible workflow using Emma:
@@ -155,20 +168,21 @@ emma-dev (. at) googlegroups.com
 | SCout (v1.8+)        | [pypiscout](https://pypi.org/project/pypiscout/)    | MIT                                  | [https://github.com/holzkohlengrill/SCout](https://github.com/holzkohlengrill/SCout)                                                                                                         |
 
 
-**Dependencies needed to generate documentation:**
+**Optional dependencies:**
 
 Utility scripts in `./doc/` need additional dependencies. As a normal user you can ignore this.
 
 | Library (version)        | pip package name                                    | Licence                              | URL                                                                                                                                                |
 |--------------------------|-----------------------------------------------------|--------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------|
 | gprof2dot (v2017.9.19+)  | [gprof2dot](https://pypi.org/project/gprof2dot/)    | LGPL-3.0                             | [https://github.com/jrfonseca/gprof2dot](https://github.com/jrfonseca/gprof2dot)                                                                   |
 | pylint (v2.3.1+)         | [pylint](https://pypi.org/project/pylint/)          | GPL-2.0                              | [https://github.com/PyCQA/pylint](https://github.com/PyCQA/pylint)                                                                                 |
+| Cython (v0.29.13+)       | [Cython](https://pypi.org/project/Cython/)          | Apache-2.0                           | [https://cython.org/](https://cython.org/)                                                                                                         |
 
 Please refer to the [gprof2dot project site](https://github.com/jrfonseca/gprof2dot) and install **its dependencies (this has to be done even if you install Emma via pip)**.
 
 Note that those modules are invoked via subprocess calls within the ./genDoc/ scripts.
 
-**Dependencies used for documentation on GitHub pages (separate, independent branch `gh-pages`):**
+**Dependencies used to generate documentation for GitHub pages (separate, independent branch `gh-pages`):**
 
 Utility scripts used to build GitHub pages documentation. As a normal user you can ignore this.
 

doc/readme-emma.md

@@ -11,16 +11,28 @@ This tool creates a summary/overview about static memory usage in form of a comm
     * pypiscout 2.0 or higher: (`pip3 install pypiscout`)
 * Tested on Windows and Linux systems
 
+<details closed>
+<summary>Optional: Cython</summary>
+For bigger projects escpecially the number of objects will grow. We provide an optional Cython implementation which can speed-up your analysis (you will gain typically about **30 % speed-up**).
+
+For now we do not provide the binaries with Emma, hence you have to compile (make sure a suitable compiler is installed) it yourself (don't worry it is quick and easy):
+
+Install the `Cython` package (`pip install Cython`) and (in the Emma top level folder) execute (MSVC is recommended on Windows):
+
+```
+python setup.py build_ext --inplace --compiler=msvc
+```
+</details>
+
 
 ## Process
 Using the Mapfile Analyser is a two step process. The first step is to extract the required information from the mapfiles and save it to .csv files.
 This is done with the `Emma.py a` script. The second step is to visualise the data. This document explains the first part only, the visualisation is documented in the Emma visualiser readme document.
 
 ## Limitations
-The Emma is only suitable for analyzing projects where the devices have a single linear physical address space:
+The devices must have a single linear physical address space:
 
-* Devices that use for example the Intel 8051 architecture have separate code and data address spaces that both
-    start at address 0x0000. Devices based on architectures like this can not be analyzed with Emma.
+* Devices that use for example a Intel 8051 architecture have separate code and data address spaces that both start at address `0x0000`. Devices based on architectures like this can not entirely analysed with Emma.
 * Devices that use for example the ARMv6M architecture have a single linear address space.
     Devices based on architectures like this can be analyzed with Emma.