klipper-dgus/docs/Debugging.md

This document describes some of the Klipper debugging tools.

Translating gcode files to micro-controller commands
====================================================

The Klippy host code can run in a batch mode to produce the low-level
micro-controller commands associated with a gcode file. Inspecting
these low-level commands is useful when trying to understand the
actions of the low-level hardware. It can also be useful to compare
the difference in micro-controller commands after a code change.

To run Klippy in this batch mode, there is a one time step necessary
to generate the micro-controller "data dictionary". This is done by
compiling the micro-controller code to obtain the **out/klipper.dict**
file:

```
make menuconfig
make
```

Once the above is done it is possible to run Klipper in batch mode
(see [installation](Installation.md) for the steps necessary to build
the python virtual environment and a printer.cfg file):

```
~/klippy-env/bin/python ./klippy/klippy.py ~/printer.cfg -i test.gcode -o test.serial -v -d out/klipper.dict
```

The above will produce a file **test.serial** with the binary serial
output. This output can be translated to readable text with:

```
~/klippy-env/bin/python ./klippy/parsedump.py out/klipper.dict test.serial > test.txt
```

The resulting file **test.txt** contains a human readable list of
micro-controller commands.

The batch mode disables certain response / request commands in order
to function. As a result, there will be some differences between
actual commands and the above output. The generated data is useful for
testing and inspection; it is not useful for sending to a real
micro-controller.

Testing with simulavr
=====================

The [simulavr](http://www.nongnu.org/simulavr/) tool enables one to
simulate an Atmel ATmega micro-controller. This section describes how
one can run test gcode files through simulavr. It is recommended to
run this on a desktop class machine (not a Raspberry Pi) as it does
require significant cpu to run efficiently.

To use simulavr, download the simulavr package and compile with python
support:

```
git clone git://git.savannah.nongnu.org/simulavr.git
cd simulavr
./bootstrap
./configure --enable-python
make
```

Note that the build system may need to have some packages (such as
swig) installed in order to build the python module. Make sure the
file **src/python/_pysimulavr.so** is present after the above
compilation.

To compile Klipper for use in simulavr, run:

```
cd /patch/to/klipper
make menuconfig
```

and compile the micro-controller software for an AVR atmega644p, set
the MCU frequency to 20Mhz, and select SIMULAVR software emulation
support. Then one can compile Klipper (run `make`) and then start the
simulation with:

```
PYTHONPATH=/path/to/simulavr/src/python/ ./scripts/avrsim.py -m atmega644 -s 20000000 -b 250000 out/klipper.elf
```

Then, with simulavr running in another window, one can run the
following to read gcode from a file (eg, "test.gcode"), process it
with Klippy, and send it to Klipper running in simulavr (see
[installation](Installation.md) for the steps necessary to build the
python virtual environment):

```
~/klippy-env/bin/python ./klippy/klippy.py config/avrsim.cfg -i test.gcode -v
```

Using simulavr with gtkwave
---------------------------

One useful feature of simulavr is its ability to create signal wave
generation files with the exact timing of events. To do this, follow
the directions above, but run avrsim.py with a command-line like the
following:

```
PYTHONPATH=/path/to/simulavr/src/python/ ./scripts/avrsim.py -m atmega644 -s 20000000 -b 250000 out/klipper.elf -t PORTA.PORT,PORTC.PORT
```

The above would create a file **avrsim.vcd** with information on each
change to the GPIOs on PORTA and PORTB. This could then be viewed
using gtkwave with:

```
gtkwave avrsim.vcd
```

Manually sending commands to the micro-controller
=================================================

Normally, the host klippy.py process would be used to translate gcode
commands to Klipper micro-controller commands. However, it's also
possible to manually send these MCU commands (functions marked with
the DECL_COMMAND() macro in the Klipper source code). To do so, run:

```
~/klippy-env/bin/python ./klippy/console.py /tmp/pseudoserial 250000
```

See the "HELP" command within the tool for more information on its
functionality.

Generating load graphs
======================

The Klippy log file (/tmp/klippy.log) stores statistics on bandwidth,
micro-controller load, and host buffer load. It can be useful to graph
these statistics after a print.

To generate a graph, a one time step is necessary to install the
"matplotlib" package:

```
sudo apt-get update
sudo apt-get install python-matplotlib
```

Then graphs can be produced with:

```
~/klipper/scripts/graphstats.py /tmp/klippy.log -o loadgraph.png
```

One can then view the resulting **loadgraph.png** file.

Different graphs can be produced. For more information run:
`~/klipper/scripts/graphstats.py --help`

Extracting information from the klippy.log file
===============================================

The Klippy log file (/tmp/klippy.log) also contains debugging
information. There is a logextract.py script that may be useful when
analyzing a micro-controller shutdown or similar problem. It is
typically run with something like:

```
mkdir work_directory
cd work_directory
cp /tmp/klippy.log .
~/klipper/scripts/logextract.py ./klippy.log
```

The script will extract the printer config file and will extract MCU
shutdown information. The information dumps from an MCU shutdown (if
present) will be reordered by timestamp to assist in diagnosing cause
and effect scenarios.

Running the regression tests
============================

The main Klipper GitHub repository uses TravisCI to run a series of
regression tests. It can be useful to run some of these tests locally.

The source code "whitespace check" can be run with:
```
./scripts/check_whitespace.sh
```

The Klippy regression test suite requires "data dictionaries" from
many platforms. The easiest way to obtain them is to
[download them from github](https://github.com/KevinOConnor/klipper/issues/1438).
Once the data dictionaries are downloaded, use the following to run
the regression suite:
```
tar xfz klipper-dict-20??????.tar.gz
~/klippy-env/bin/python ~/klipper/scripts/test_klippy.py -d dict/ ~/klipper/test/klippy/*.test
```