Suppose I had the following code:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(520)
y = np.random.rand(520)
plt.plot(x, y)
which produces the following graph:
How can I define a custom axis so my X-axis looks like this:
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1 Answer
You can use:
plt.xscale('log')to change the scale to a log scaleset_major_formatter(ScalarFormatter())to set the formatting back to normal (replacing theLogFormatter)set_minor_locator(NullLocator())to remove the minor ticks (that were also set by the log scale)set_major_locator(FixedLocator([...]orplt.xticks([...])to set the desired ticks on the x-axis
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter, NullLocator, FixedLocator
import numpy as np
x = np.arange(520)
y = np.random.uniform(-1, 1, 520).cumsum()
plt.plot(x, y)
plt.xscale('log')
# plt.xticks([...])
plt.gca().xaxis.set_major_locator(FixedLocator([2**i for i in range(0, 7)] + [130, 260, 510]))
plt.gca().xaxis.set_major_formatter(ScalarFormatter())
plt.gca().xaxis.set_minor_locator(NullLocator())
plt.show()
