I am plotting a function in matplotlib using subplots (I have to use subplots because of other reasons) and like to set the y-scale to logarithmic while having the y-ticks in the color red.
I used this code:
import matplotlib.pyplot as plt
x_data = np.arange(500.0, 900.0, 1.0)
def func(x):
return a*(x/500.0)**(-b)
fig, ax = plt.subplots()
ax.plot(x_data, 10*func(x_data))
ax.set_yscale('log')
ax.tick_params('y', colors='r')
plt.show()
The tickcolor is black although I specificly set it to red. However, when I choose a linear scale, the tickcolor is red:
import matplotlib.pyplot as plt
x_data = np.arange(500.0, 900.0, 1.0)
def func(x):
return a*(x/500.0)**(-b)
fig, ax = plt.subplots()
ax.plot(x_data, 10*func(x_data))
ax.set_yscale('linear')
ax.tick_params('y', colors='r')
plt.show()
Also, when a manually select the y-axis range, the first tick is red:
import matplotlib.pyplot as plt
x_data = np.arange(500.0, 900.0, 1.0)
def func(x):
return a*(x/500.0)**(-b)
fig, ax = plt.subplots()
ax.plot(x_data, 10*func(x_data))
ax.set_yscale('linear')
ax.tick_params('y', colors='r')
plt.show()
It has something to do with the logarithmic scale but I don't know how to solve it. Can someone help me with this?
The ticks you see in the first graph are minor ticks, and ax.tick_params applies to major ticks by default.
You can specify which ticks ax.tick_params applies to using the which= argument:
ax.tick_params('y', which="both", colors='r')