Matplotlib axis with two scales shared origin
axis, matplotlib, scale
Solution
use the align_yaxis() function:
import numpy as np
import matplotlib.pyplot as plt
def align_yaxis(ax1, v1, ax2, v2):
"""adjust ax2 ylimit so that v2 in ax2 is aligned to v1 in ax1"""
_, y1 = ax1.transData.transform((0, v1))
_, y2 = ax2.transData.transform((0, v2))
inv = ax2.transData.inverted()
_, dy = inv.transform((0, 0)) - inv.transform((0, y1-y2))
miny, maxy = ax2.get_ylim()
ax2.set_ylim(miny+dy, maxy+dy)
fig = plt.figure()
ax1 = fig.add_subplot(111)
ax2 = ax1.twinx()
ax1.bar(range(6), (2, -2, 1, 0, 0, 0))
ax2.plot(range(6), (0, 2, 8, -2, 0, 0))
align_yaxis(ax1, 0, ax2, 0)
plt.show()
Problem
I need two overlay two datasets with different Y-axis scales in Matplotlib. The data contains both positive and negative values. I want the two axes to share one origin, but Matplotlib does not align the two scales by default. ``` import numpy as np import matplotlib.pyplot as plt fig = plt.figure() ax1 = fig.add_subplot(111) ax2 = ax1.twinx() ax1.bar(range(6), (2, -2, 1, 0, 0, 0)) ax2.plot(range(6), (0, 2, 8, -2, 0, 0)) plt.show() ``` I suppose it is possible to perform some computation with `.get_ylim()` and `.set_ylim()` two align the two scales. Is there an easier solution?