To help other M5Stack Fire players, here I attached the Pin Mapping of Fire.

So... if you use PSRAM, Port C(UART) will be unavailable. If you need UART anyway, you can map UART to GPIOs of Port B.

s = machine.UART(2, tx=26, rx=36)

GPIO 36 is INPUT ONLY, so rx has to be 36.

refer to: https://blog.csdn.net/zhufu86/article/details/93379087 (Chinese language)

@heybin
Thank you.

Yes I noticed Lobo MicroPython had been no updates for long time.

But I saw https://github.com/m5stack/M5Stack_MicroPython had been updated continuously.
I will go for it and give it a try.

Hi @heybin
I found this: https://github.com/m5stack/M5Stack_MicroPython
Is it a M5Stack version Lobo MicroPython which I could start with instead of the official Lobo MicroPython on https://github.com/loboris/MicroPython_ESP32_psRAM_LoBo ?

I also noticed this... don't know why.

@heybin
Thank you, heybin.
I will dig into it.

I have a M5Stack Fire with 4M PSRAM.
But when I tried to check the free mem, I got much less than that.

>>> import gc
>>> gc.mem_free()
7904
>>> gc.collect()
>>> gc.mem_free()
60464

I guess Micropython can not see those 4M PSRAM part.
What can I do so that I can use the 4M PSRAM in M5Stack Fire?

During the booting process, I saw the following. Does that mean the 4M PSRAM was not initiated?

W (129) MicroPython: SPIRAM: Disabled

I also tried the following and got:

>>> import micropython, machine
>>> micropython.mem_info()
stack: 752 out of 14336
GC: total: 86016, used: 29712, free: 56304
 No. of 1-blocks: 410, 2-blocks: 75, max blk sz: 654, max free sz: 2263
>>> machine.heap_info()
Heap outside of MicroPython heap:
---------------------------------
              Free: 95208
         Allocated: 187096
      Minimum free: 87724
      Total blocks: 200
Largest free block: 93252
  Allocated blocks: 196
       Free blocks: 4

It seems I only have 56k free RAM if I am correct.

But downloadable UIFlow Desktop IDE is still v1.2.3, so I'm not sure if the new UIFlow version is ready now.
I also see some bugs(look like...not sure) in the new UIFlow v1.3.2 so I've been back to v1.2.3 which seems to be more stable.

I can see new release UIFlow-v1.3.2 show up in M5Burner.
Any new update on this new version?

@heybin

but it is 11% more than 1g.
Is it normal? I suppose the tolerance is much lower than 10%.

I'm curious about the tolerance of the sh200q acceleration readings of StickC.
I put the StickC on the desk and make sure it will not be moved and be steady.
Then I tried the codes below but got the acceleration higher than "1g". Why is that?

>>> from hardware import sh200q
>>> import math
>>> imu = sh200q.Sh200q()
>>>
>>> for i in range(5):
...     print((imu.acceleration[0],imu.acceleration[1],imu.acceleration[2]))
...     wait(1)
...
...
...
(0.138, 0.058, 1.107)
(0.14, 0.055, 1.111)
(0.139, 0.058, 1.111)
(0.138, 0.055, 1.11)
(0.136, 0.06, 1.11)
>>> for i in range(5):
...     print(math.sqrt(imu.acceleration[0]**2+imu.acceleration[1]**2+imu.acceleration[2]**2))
...     wait(1)
...
...
...
1.11918095051694
1.12111150203715
1.12195989233127
1.12375308675883
1.11990892486845
>>>

I also tried with the configuration 16g range set. More or less the same.

>>> for i in range(5):
...     print((imu.acceleration[0],imu.acceleration[1],imu.acceleration[2]))
...     wait(1)
...
...
...
(0.137, 0.059, 1.12)
(0.137, 0.059, 1.11)
(0.142, 0.062, 1.11)
(0.139, 0.053, 1.108)
(0.128, 0.063, 1.107)
>>> 
>>> import math
>>> for i in range(5):
...     print(math.sqrt(imu.acceleration[0]**2+imu.acceleration[1]**2+imu.acceleration[2]**2))
...     wait(1)
...
...
...
1.13100221043108
1.12003080314784
1.1184927357833
1.11923321966425
1.117821094809
>>>
···