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In [5]:

    
d = loadtxt('./initial-value-distribution-cleanup.csv', delimiter=',')
plot(d)
m = d[:,0]
figure()
plot(m)









    Out[5]:





[<matplotlib.lines.Line2D at 0x7f15d7b92090>]



In [6]:

    
last = 0
r=[]
for v in m:
    if last != v:
        r.append(v)
        last=v

plot(r)









    Out[6]:





[<matplotlib.lines.Line2D at 0x7f15d7af5dd0>]



In [9]:

    
print ("Mean: " + str(mean(r)))
print ("Median: " + str(median(r)))
stddev=sqrt(sum((r-median(r))**2)/size(r))
print ("Standard deviation: " + str(stddev))
hist(r)
xlabel("Value in free air")
ylabel("Count")









    



Mean: 210.634615385
Median: 210.0
Standard deviation: 2.17355905702






    Out[9]:





<matplotlib.text.Text at 0x7f15d7f98e50>

Initial sensor value in free air: 210+-2



In [18]:

    
d = loadtxt('./initial-value-distribution2.csv', delimiter=',')
plot(d[:,0], label="Moisture")
plot(d[:,1], label="Temperature")

legend(loc=5)
title("Sensor initial value in free air experiment, 102 sensors")









    Out[18]:





<matplotlib.text.Text at 0x7f6d75be5f50>



In [25]:

    
r=d[:,0]
print ("Mean: " + str(mean(r)))
print ("Median: " + str(median(r)))
stddev=sqrt(sum((r-median(r))**2)/size(r))
print ("Standard deviation: " + str(stddev))
figure( figsize=(10, 8))
hist(r)
xlabel("Value in free air, batch:1")
ylabel("Count")









    



Mean: 211.450980392
Median: 211.0
Standard deviation: 1.99017193069






    Out[25]:





<matplotlib.text.Text at 0x7f6d755f58d0>

RS485 sensors Batch 1 - initial value: 211+-2