如何在matplotlib中将数字十进制数据(例如0到1之间)的刻度标记更改为“0”,“。1”,“。2”而不是“0.0”,“0.1”,“0.2” ?例如,
hist(rand(100))
xticks([0, .2, .4, .6, .8])
将标签格式化为“0.0”,“0.2”等。我知道这摆脱了“0.0”中的前导“0”和“1.0”上的尾随“0”:
from matplotlib.ticker import FormatStrFormatter
majorFormatter = FormatStrFormatter('%g')
myaxis.xaxis.set_major_formatter(majorFormatter)
这是一个好的开始,但我也想摆脱“0.2”和“0.4”等的“0”前缀。如何做到这一点?
答案 0 :(得分:9)
虽然我不确定这是最好的方法,但您可以使用matplotlib.ticker.FuncFormatter
来执行此操作。例如,定义以下函数。
def my_formatter(x, pos):
"""Format 1 as 1, 0 as 0, and all values whose absolute values is between
0 and 1 without the leading "0." (e.g., 0.7 is formatted as .7 and -0.4 is
formatted as -.4)."""
val_str = '{:g}'.format(x)
if np.abs(x) > 0 and np.abs(x) < 1:
return val_str.replace("0", "", 1)
else:
return val_str
现在,您可以使用majorFormatter = FuncFormatter(my_formatter)
替换问题中的majorFormatter
。
让我们看一个完整的例子。
from matplotlib import pyplot as plt
from matplotlib.ticker import FuncFormatter
import numpy as np
def my_formatter(x, pos):
"""Format 1 as 1, 0 as 0, and all values whose absolute values is between
0 and 1 without the leading "0." (e.g., 0.7 is formatted as .7 and -0.4 is
formatted as -.4)."""
val_str = '{:g}'.format(x)
if np.abs(x) > 0 and np.abs(x) < 1:
return val_str.replace("0", "", 1)
else:
return val_str
# Generate some data.
np.random.seed(1) # So you can reproduce these results.
vals = np.random.rand((1000))
# Set up the formatter.
major_formatter = FuncFormatter(my_formatter)
plt.hist(vals, bins=100)
ax = plt.subplot(111)
ax.xaxis.set_major_formatter(major_formatter)
plt.show()
运行此代码会生成以下直方图。
请注意,刻度标签符合问题中要求的条件。
答案 1 :(得分:-3)
将所有值加倍10。