157 lines
106 KiB
Python
157 lines
106 KiB
Python
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import PySimpleGUI as sg
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import math
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import psutil
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"""
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Demo Program - Display CPI Usage as a VU Meter
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Artwork and algorithm for handling of needle positioning generously provided by GitHub user neovich.
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A long-time PySimpleGUI user and brilliant programmer posted a screenshot of an incredibly
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complex audio recording mixing application with features like custom sliders and VU meters made
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entirely of Graph elements. I asked him to draw us some special artwork for this demo. An ENORMOUS
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thank you to him for the encouragement, support, and hard work!
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This demo uses the psutil library to get the CPI utilization. It is then shown on a nicely rendered
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VU meter.
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Copyright 2023 PySimpleGUI
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"""
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# --- VU Meter Parameters ----------------------------------------------
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x_needle_base = 169
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y_needle_base = 10
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needle_length = 280
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needle_multiply = 2
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needle_width = 2
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needle_color = '#434443'
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needle_cutoff = 100
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angle_min = 60
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angle_max = 122
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CANVAS_KEY = 'CANVAS_vu_meter'
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# --- Colours ----------------------------------------------------------
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tick1_color = '#222222'
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tick2_color = tick1_color
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background = '#626059'
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module_background = '#F2E2CA'
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win0_background_color = background
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tab_inner_colour = 'black'
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background_main = background
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sg.set_options(background_color=background, element_background_color=background)
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# ---------------------- Definitions -----------------------------------
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def VU_METER_update(CONT_CANVAS_vu_meter, a):
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if a < angle_min :
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a = angle_min
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if a > angle_max:
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a = angle_max
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CONT_CANVAS_vu_meter.erase()
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OBJ_VU_meter = CONT_CANVAS_vu_meter.draw_image(data=vu_meter_2,location= (0,234))
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x_angle = math.cos(math.radians(180-a))
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y_angle = math.sin(math.radians(180-a))
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x_cur = x_needle_base+(x_angle * needle_length)
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y_cur = y_needle_base+int((y_angle * needle_length)*0.7)
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x_cur_low = int(x_needle_base+(x_angle * (needle_length/needle_multiply)))
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y_cur_low = int(y_needle_base+int((y_angle * (needle_length/needle_multiply))*0.7))
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OBJ_VU_meter_needle = CONT_CANVAS_vu_meter.draw_line( (x_cur_low,y_cur_low),(int(x_cur),int(y_cur)) ,color=needle_color,width=needle_width)
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def main():
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# ------------------------- Init the VU_Meter --------------------------
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VU_METER_cont = [[sg.Graph ( canvas_size = ( 339,234 ),
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graph_bottom_left=(0,0),
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graph_top_right=(339,234),
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background_color=module_background,
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drag_submits=True,
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enable_events=True,
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float_values=True,
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key=CANVAS_KEY )]]
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# ------------------------- Tab Set Ups --------------------------------
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layout = [[sg.Column(VU_METER_cont ,background_color=module_background )]]
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location = sg.user_settings_get_entry('-location-', (None, None))
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# ------------------------ Finalize Windows ----------------------------
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window = sg.Window('CPU Usage as a VU Meter', layout,
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no_titlebar=True,
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auto_size_buttons=False,
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keep_on_top=True,
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grab_anywhere=True,
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force_toplevel=False,
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finalize=True,
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location=location,
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right_click_menu=sg.MENU_RIGHT_CLICK_EDITME_VER_EXIT,
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enable_close_attempted_event=True)
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# ------------------------ Init the VU_Meter ---------------------------
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CONT_CANVAS_vu_meter = window[CANVAS_KEY]
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angle = angle_min
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x_angle = math.cos(math.radians(180-angle))
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y_angle = math.sin(math.radians(180-angle))
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x_cur = x_needle_base+(x_angle * needle_length)
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y_cur = y_needle_base+int((y_angle * needle_length)*0.7)
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x_cur_low = int(x_needle_base+(x_angle * (needle_length/needle_multiply)))
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y_cur_low = int(y_needle_base+int((y_angle * (needle_length/needle_multiply))*0.7))
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OBJ_VU_meter_needle = CONT_CANVAS_vu_meter.draw_line( (x_cur_low,y_cur_low),(int(x_cur),int(y_cur)) ,color=needle_color,width=needle_width)
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window.refresh()
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########################################################################
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## MAIN LOOP ##
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########################################################################
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temp_angle = 0
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angle_impulse = 2
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angle_range = angle_max-angle_min
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while True:
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event, values = window.read(timeout=30)
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if event in (sg.WIN_CLOSE_ATTEMPTED_EVENT, 'Exit'):
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sg.user_settings_set_entry('-location-', window.current_location()) # The line of code to save the position before exiting
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break
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if event == 'Edit Me':
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sg.execute_editor(__file__)
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elif event == 'Version':
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sg.popup_scrolled(__file__, sg.get_versions(), location=window.current_location(), keep_on_top=True, non_blocking=True)
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cpu_percent = psutil.cpu_percent(interval=1)
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target_angle = angle_range * cpu_percent/100 + angle_min
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if temp_angle == 0:
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temp_angle = target_angle
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delta = abs(temp_angle - target_angle)
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if temp_angle > target_angle:
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temp_angle -= min(angle_impulse, delta)
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else:
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temp_angle += min(angle_impulse, delta)
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VU_METER_update(CONT_CANVAS_vu_meter, temp_angle)
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CONT_CANVAS_vu_meter.draw_text(f'{int(cpu_percent)}% CPU USED', (170, 40), color=module_background, font='_ 18')
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if __name__ == '__main__':
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# --------- Images -----------------------------------------------------
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needle = b'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'
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vu_meter_2 = b'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dot3 = b'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'
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main()
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