TempPlot.py

import gobject
import matplotlib
matplotlib.use('GTKAgg')

import matplotlib.pyplot as plt

current_pos = 0
temps = []
pad = 5.0

f = plt.figure(figsize=(5.45,4.5), dpi=72)

def update(vars):
	# Unpack variables that need to be persistent between
	# executions of this method.
	temps = vars[0]
	current_pos = vars[1]
	pad = vars[2]
	
	# Open the data file and get any new data points since
	# the last time we read from this file
	data = open("out.txt", "r")
	data.seek(current_pos)
	new_temps = map(lambda x:
		float(x) * (1 + 4.0/5.0) + 32.0,
		data.read().split("\n")[:-1])
	current_pos = data.tell()
	data.close()
	
	# If we got new data then append it to the list of
	# temperatures and trim to 750 points
	if len(new_temps) > 0:
		temps.extend(new_temps)
		temps = temps[-750:]
	
	f.clear()
	f.suptitle("Live Temperature")
	a = f.add_subplot(111)
	a.grid(True)
	l, = a.plot(temps)
	plt.xlabel("Time (Seconds)")
	plt.ylabel(r'Temperature $^{\circ}$F')
	
	# Get the minimum and maximum temperatures these are
	# used for annotations and scaling the plot of data
	min_t = min(temps)
	max_t = max(temps)
	
	# Add annotations for minimum and maximum temperatures
	a.annotate(r'Min: %0.2f$^{\circ}$F' % (min_t),
		xy=(temps.index(min_t), min_t), 
		xycoords='data', xytext=(20, -20),
		textcoords='offset points',
		bbox=dict(boxstyle="round", fc="0.8"),
		arrowprops=dict(arrowstyle="->",
		shrinkA=0, shrinkB=1,
		connectionstyle="angle,angleA=0,angleB=90,rad=10"))

	a.annotate(r'Max: %0.2f$^{\circ}$F' % (max_t),
		xy=(temps.index(max_t), max_t),
		xycoords='data', xytext=(20, 20),
		textcoords='offset points',
		bbox=dict(boxstyle="round", fc="0.8"),
		arrowprops=dict(arrowstyle="->",
		shrinkA=0, shrinkB=1,
		connectionstyle="angle,angleA=0,angleB=90,rad=10"))
	
	# Set the axis limits to make the data more readable
	a.axis([0,len(temps), min_t - pad,max_t + pad])
	
	f.canvas.draw_idle()
	
	# Repack variables that need to be persistent between
	# executions of this method
	vars = {0: temps, 1: current_pos, 2: pad}
	
	return True

vars = {0: temps, 1: current_pos, 2: pad}

# Execute update method every 500ms
gobject.timeout_add(500, update, vars)

# Display the plot
plt.show()