Getting Started
This page helps you get to a first successful MKMCXX 3 run quickly, even if you are new to microkinetic modeling.
You do not need to understand the whole software before you begin. The goal is simply to get one example running in a calm, reliable way and then point you to the best next step.
Prerequisites
- a downloaded MKMCXX 3 package
- a terminal
- a plain text editor such as VS Code, Notepad++,
nano, orvim
Learning Outcomes
- run one bundled example successfully
- find the output written by MKMCXX
- know what “success” looks like after a first run
- know where to go next in the manual
Tip
If you are completely new to this area, that is perfectly fine. Start by running one bundled example first. You can learn the input structure and the scientific details step by step afterwards.
Step 1: Unpack MKMCXX
Download the latest package from the downloads page, then unpack it somewhere convenient.
Inside the extracted folder, you should see:
- a
binfolder containing the executable - an
examplesfolder containing ready-to-run simulations
The executable is called:
mkmcxx.exeon Windowsmkmcxxon Unix, Linux, and macOS
Note
MKMCXX 3 does not need a separate installation step. In most cases, you can unpack the download and run it directly.
Step 2: Run One Example
The easiest and safest way to begin is to run one of the bundled examples before editing your own files.
Pick any example directory you like. At this stage, the goal is not to choose the “best” model, but simply to complete one successful run.
On Windows
- Open the folder where you unpacked MKMCXX 3.
- Open the
examplesfolder. - Open one of the example directories.
- Right-click in that folder and choose Open in Terminal.
- Run:
..\..\bin\mkmcxx.exe -i input.mkx
On Unix, Linux, or macOS
- Open a terminal.
- Move to the unpacked MKMCXX 3 folder.
- Enter the
examplesfolder. - Enter one of the example directories.
- Run:
../../bin/mkmcxx -i input.mkx
If the executable is not yet marked as runnable, use:
chmod +x ../../bin/mkmcxx
Note
MKMCXX 3 input files use the .mkx extension. This is one of the clearest
differences from older MKMCXX 2 workflows.
Step 3: Check That It Worked
After you run the command, MKMCXX reads input.mkx, performs the simulation,
and creates a results folder in your current working directory.
In a typical example folder, you will end up with something like:
example-folder/
├── input.mkx
└── results/
If you see a results folder, you have already completed the main goal of this
page. Your first MKMCXX 3 run has worked, and the output has been written to
disk.
Step 4: Open the Results
MKMCXX 3 always writes its main consolidated output to:
results/results.h5
Depending on your output settings, you may also see .tsv and .xlsx files.
You can inspect the results in several ways:
- open
.tsvfiles in a text editor or spreadsheet tool - open
.xlsxfiles in Excel or another spreadsheet application - open
results.h5in HDFView - read
results.h5from Python using h5py
Tip
Do not worry if HDF5 is unfamiliar at first. You can start with the text or spreadsheet outputs and move to HDF5 later when you want more structured analysis.
Optional: Save Log Files
By default, warnings and errors are shown in the terminal. If you would like them written to files instead, run:
SUNLOGGER_ERROR_FILENAME=error.log SUNLOGGER_WARNING_FILENAME=warnings.log ../../bin/mkmcxx -i input.mkx
On Windows, use the corresponding environment-variable syntax in the terminal you work in.
What To Do Next
Once you have completed one successful run, these are the most useful next steps:
- Basic simulation for a guided walkthrough of a full MKMCXX 3 model
- Comparing simulation modes for a minimal example that
contrasts
transient_solveandsteady_state_solve - Manual overview if you want to browse the main documentation
Common Questions
Do I need to install anything first?
Usually no. In normal use, you only need to unpack the download and run the executable.
Where should I make my first edits?
Start from one of the bundled examples, make a copy, and edit its input.mkx
file. That is usually much easier than starting from a blank file.
I am still learning the science behind the model. Is that a problem?
Not at all. Many users first learn the software workflow and the scientific background in parallel. Running small examples is a very good way to build confidence.
I already know MKMCXX 2. What feels different in MKMCXX 3?
The most visible changes are the .mkx input format, the revised syntax, and
the newer output workflow centered around HDF5 and spreadsheet export.