How do I create a secondary axis based on on a complex conversion?

Question

I am trying to create a secondary axis for my plot. I can get all of my lines to plot on the graph (y1 to y14) and all y values are in the same units. The conversion to a secondary unit is essentially "exp(y/7)." I struggled with this long enough to resort to chatgpt, which gave me the following after lengthy troubleshoointg:

def y_to_secondary(y):
    return  np.asarray(math.exp(np.asarray(y1)/(7)))

def secondary_to_y(secondary):
    return 7*math.log(np.asarray(secondary))

secay = ax1.secondary_yaxis('right', functions=(y_to_secondary, secondary_to_y))

I continue to get the error: TypeError: only size-1 arrays can be converted to Python scalars

I am defining my original arrays as followed:

y1=[]
T1=[]
for a in range(2,1000):
    y1.append(-7 + (2*a))

Any ideas how to fix the problem?

Answer 1

First, you don't need this np.asarray() method. You should have the following:

def y_to_secondary(y):
    return np.exp(y/7)

def secondary_to_y(secondary):
    return np.log(secondary) * 7

This should fix your TypeError.

Then I am not exactly sure what you do want to plot, but if you want a first function y1 = 2x-7 and a second y2 = exp(y/7), here is how you can do. You have to fix the x values not too high (<100), or you will encounter an overflow.

fig, ax1 = plt.subplots()

# First y-axis
X = np.arange(2,50,1)
y1 = 2*X-7
plt.plot(X, y1, label='$y1$')
ax1.plot(X, np.exp(X/7), label='$y2$')
ax1.legend()

# Second y-axis
_ = ax1.secondary_yaxis('right', functions=(y_to_secondary, secondary_to_y))

This is the result: The plot with 2 y-axis. Finally, you can play with the tick_params to better render the second y-axis.