Python Scripts and Things

Firmware Patcher

The python based firmware patcher implements most of the functionality from the bash based script. It also adds:

• Patches boot logos.
• Patches in serial monitor code.

Note it's currently partially a 'port' of the bash script, so it just has calls in the main file which more closely mirror the bash script.

ASMonitor in Serial

This is a simple method of doing read/writes to system memory. For example:

from asmonitor_serial import ASSerialMonitor 

AS = ASSerialMonitor()
AS.open("COM57")

#Should be nothing at this address so safe...
AS.write_mem32(0x20001F00, 0x11223344)

base = 0x20000000
for i in range(0, 1000, 4):
    print("%08X: %08X"%(0x20000000+i, (AS.read_mem32(0x20000000+i))))

#Read a float
for i in range(0, 1000):
    print(AS.read_float(0x200157cc))

AS.close()

If you want to update in a terminal, you can pip install colorama for cross-platform support that works even on Windows. Just do something like this to plot a floating-point variable from some memory location:

import sys
import time
from colorama import init
from asmonitor_serial import ASSerialMonitor 

init()

AS = ASSerialMonitor()
AS.open("COM57")

while True:
    val = AS.read_float(0x200157cc)
    val = str(val)
    print('\033[2J')
    print(val)
    time.sleep(0.01)

ASMonitor (High-Level)

This high-level library provides a slightly more generic way to perform reads from memory, using either the serial monitor patch or a J-Link (openocd etc should also work but needs to be added).

Note that the J-Link has VERY HIGH throughput - you can easily dump the entire variable table for example. If using the serial monitor you should ensure you are only reading actual variables needed!

Plotting Example

If using J-Link, you can plot full variable tables. Here's a simple example:

import matplotlib.pylab as plt
import numpy as np
from asmonitor import ASMonitor, ASMonitor_JLink

print("Connecting to low-level...")
asjl = ASMonitor_JLink()
asjl.connect()

asm = ASMonitor(asjl)

samples = 2000

floatarrays = np.zeros( (samples, 255))

print("Starting to sample now - ensure airflow on and unit is working")
#Dump 255 variables from table (how many are there?)
for i in range(0, samples):
    floatarrays[i,:] = asm.return_therapy_float(num_fps=255)
    
plt.plot(floatarrays)
plt.show()

Which generates a graph of everything at once:

You can use standard Python plotting libraries, and/or Jupyter as well. This allows you to do real-time plotting etc.

See examples for similar thing using serial monitor (but with less variables plotted due to more limited speeds).