import mcp3008 m = mcp3008.read_pct(0) print("Maisture level: {:>5}".format(m))
PREVIOUS_LINE="\x1b[1F" RED_BACK="\x1b[41;37m" GREEN_BACK="\x1b[42;30m" YELLOW_BACK="\x1b[43;30m" RESET="\x1b[0m" readings = [] delta = datetime.timedelta(minutes=10) next_time = datetime.datetime.now()+delta next_water = datetime.datetime.now() #the main sensor reading and plotting loop while True: dt = datetime.datetime.now() while dt < next_time: n = mcp3008.read_pct(5) if n>15 and n<85: if len(readings) >= 1000: del readings[0]; readings.append(n) dt = datetime.datetime.now(); else: # Take the average from the readings list to smooth the graph a little m = round(((sum(readings)/float(len(readings)))),1) readings = [] # write the data to plotly stream.write({'x': datetime.datetime.now(), 'y': m}) if m < 25: background = RED_BACK elif m < 65: background = YELLOW_BACK
PREVIOUS_LINE="\x1b[1F" RED_BACK="\x1b[41;37m" GREEN_BACK="\x1b[42;30m" YELLOW_BACK="\x1b[43;30m" RESET="\x1b[0m" readings = [] delta = datetime.timedelta(minutes=10) next_time = datetime.datetime.now()+delta next_water = datetime.datetime.now() #the main sensor reading and plotting loop while True: dt = datetime.datetime.now() while dt < next_time: n = 100-mcp3008.read_pct(5) if n>15 and n<85: if len(readings) >= 1000: del readings[0]; readings.append(n) dt = datetime.datetime.now(); else: # Take the average from the readings list to smooth the graph a little m = round(1.5*((sum(readings)/float(len(readings)))),1) readings = [] # write the data to plotly stream.write({'x': datetime.datetime.now(), 'y': m}) if m < 25: background = RED_BACK elif m < 65: background = YELLOW_BACK