So I have data, in the form of 2 numpy arrays, that look like the above when plotted. For some reason, when I add the 2 numpy arrays together, element-wise as such:
c = a + b
and then plot c, I get this:
All I'm doing is plot.plot(c)
But that doesn't make sense right? I shouldn't get the same exact plot as plot b (except shifted up) when adding those 2 together right? I'm really confused about this.
You shouldn't. However, plot can be deceiving. a is almost constant: max changes is about 2e-3 compare to 0.7 in b.
a is practically a constant, the variations in a are much smaller than the variations in b so when you sum them together you only wind up seeing the variations in b on a plot. This will be more apparent if you plot c = 1000*a + b
a is so small that it may as well just be a=5.95 when it gets added to b, which has large variations. So multiplying a by 1000 will increase the size of its variations enough to be noticeable, for demonstration purposesI agree with all the other answers above. I think it will be much clearer to the original poster if they try drawing all three plots on the same graph, rather than showing each of them on a separate graph.
plt.plot(a)
plt.plot(b)
plt.plot(a + b)
plt.show()
