OK, now let's plot something actually fun and useful. This is where using psutil comes in. This is an excellent cross-platform system monitoring Python library. We'll use it for a couple of examples.
First up - CPU load and temperature. Here's the updated code:
# SPDX-FileCopyrightText: 2019 Carter Nelson for Adafruit Industries
#
# SPDX-License-Identifier: MIT
from collections import deque
import psutil
# Blinka CircuitPython
import board
import digitalio
import adafruit_rgb_display.ili9341 as ili9341
# Matplotlib
import matplotlib.pyplot as plt
# Python Imaging Library
from PIL import Image
#pylint: disable=bad-continuation
#==| User Config |========================================================
REFRESH_RATE = 1
HIST_SIZE = 61
PLOT_CONFIG = (
#--------------------
# PLOT 1 (upper plot)
#--------------------
{
'title' : 'LOAD',
'ylim' : (0, 100),
'line_config' : (
{'color' : '#0000FF', 'width' : 2},
{'color' : '#0060FF', 'width' : 2},
{'color' : '#00FF60', 'width' : 2},
{'color' : '#60FF00', 'width' : 2},
)
},
#--------------------
# PLOT 2 (lower plot)
#--------------------
{
'title' : 'TEMP',
'ylim' : (20, 50),
'line_config' : (
{'color' : '#FF0000', 'width' : 2},
{'color' : '#FF3000', 'width' : 2},
{'color' : '#FF8000', 'width' : 2},
{'color' : '#Ff0080', 'width' : 2},
)
}
)
CPU_COUNT = 4
def update_data():
''' Do whatever to update your data here. General form is:
y_data[plot][line].append(new_data_point)
'''
cpu_percs = psutil.cpu_percent(interval=REFRESH_RATE, percpu=True)
for cpu in range(CPU_COUNT):
y_data[0][cpu].append(cpu_percs[cpu])
cpu_temps = []
for shwtemp in psutil.sensors_temperatures()['coretemp']:
if 'Core' in shwtemp.label:
cpu_temps.append(shwtemp.current)
for cpu in range(CPU_COUNT):
y_data[1][cpu].append(cpu_temps[cpu])
#==| User Config |========================================================
#pylint: enable=bad-continuation
# Setup X data storage
x_time = [x * REFRESH_RATE for x in range(HIST_SIZE)]
x_time.reverse()
# Setup Y data storage
y_data = [ [deque([None] * HIST_SIZE, maxlen=HIST_SIZE) for _ in plot['line_config']]
for plot in PLOT_CONFIG
]
# Setup display
disp = ili9341.ILI9341(board.SPI(), baudrate = 24000000,
cs = digitalio.DigitalInOut(board.D4),
dc = digitalio.DigitalInOut(board.D5),
rst = digitalio.DigitalInOut(board.D6))
# Setup plot figure
plt.style.use('dark_background')
fig, ax = plt.subplots(2, 1, figsize=(disp.width / 100, disp.height / 100))
# Setup plot axis
ax[0].xaxis.set_ticklabels([])
for plot, a in enumerate(ax):
# add grid to all plots
a.grid(True, linestyle=':')
# limit and invert x time axis
a.set_xlim(min(x_time), max(x_time))
a.invert_xaxis()
# custom settings
if 'title' in PLOT_CONFIG[plot]:
a.set_title(PLOT_CONFIG[plot]['title'], position=(0.5, 0.8))
if 'ylim' in PLOT_CONFIG[plot]:
a.set_ylim(PLOT_CONFIG[plot]['ylim'])
# Setup plot lines
#pylint: disable=redefined-outer-name
plot_lines = []
for plot, config in enumerate(PLOT_CONFIG):
lines = []
for index, line_config in enumerate(config['line_config']):
# create line
line, = ax[plot].plot(x_time, y_data[plot][index])
# custom settings
if 'color' in line_config:
line.set_color(line_config['color'])
if 'width' in line_config:
line.set_linewidth(line_config['width'])
if 'style' in line_config:
line.set_linestyle(line_config['style'])
# add line to list
lines.append(line)
plot_lines.append(lines)
def update_plot():
# update lines with latest data
for plot, lines in enumerate(plot_lines):
for index, line in enumerate(lines):
line.set_ydata(y_data[plot][index])
# autoscale if not specified
if 'ylim' not in PLOT_CONFIG[plot].keys():
ax[plot].relim()
ax[plot].autoscale_view()
# draw the plots
canvas = plt.get_current_fig_manager().canvas
plt.tight_layout()
canvas.draw()
# transfer into PIL image and display
image = Image.frombytes('RGB', canvas.get_width_height(),
canvas.tostring_rgb())
disp.image(image)
print("looping")
while True:
update_data()
update_plot()
# update rate controlled by psutil.cpu_percent()
Save that as tft_sidekick_cpu.py and run it:
python3 tft_sidekick_cpu.py
Make sure you've set the BLINKA_FT232H environment variable.
and you should get something like this:
Note that pretty much all of the changes have been made in the user configuration section at the top. The plots are set up to track up to 4 cores. And then update_data() has been modified to use psutil to get the CPU load and temperature data and add it to the plot data.
And that's pretty much it. The one change that was done outside of this area was to remove the time.sleep() delay in the main loop. That's because we are using a blocking call to psutil.cpu_percent() , so we just let it set the pace.
