修复具有多个数据集的Matplotlib直方图的范围？

huangapple
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英文:

Fix range of matplotlib histogram with multiple datasets?

问题

抱歉，我只翻译代码部分，以下是代码的翻译：

我有多个数据集，我想将它们合并成直方图。不幸的是，我的数据显示不同的范围。

使用简单的`range=(0,1)`参数会触发奇怪的行为。

这是它应该看起来的样子：

[![在此输入图像描述](https://i.stack.imgur.com/xjk4t.png)](https://i.stack.imgur.com/xjk4t.png)

当数据范围为0-1时，它目前看起来确实是这样的。

但有时它的范围不同，我得到了：[![在此输入图像描述](https://i.stack.imgur.com/rUOSN.png)](https://i.stack.imgur.com/rUOSN.png)

在这里，我想强制范围为0-1。

但当我使用以下代码时：

`axs.hist(plot_data, range=(0,1),color=colors,label=plot_label, histtype='bar')`

我得到了[![在此输入图像描述](https://i.stack.imgur.com/FwutW.png)](https://i.stack.imgur.com/FwutW.png)

我无法解释为什么会发生这种情况。

这是代码：
```python
fig, axs = plt.subplots(1,1,tight_layout=True)
fig.set_size_inches(7, 4)
# 为每个直方图定义颜色
colors = ['g', 'b', 'r', 'purple']
# 为所有错误条件制作组合直方图
# 绘制直方图
axs.hist(plot_data,color=colors,label=plot_label, histtype='bar')
# 在当前轴的右侧放置图例
axs.legend(loc='center left',bbox_to_anchor=(1, 0.5))
# 设置坐标轴标签
axs.set_xlabel(f"相似性：{wildcards.metric}")
axs.set_ylabel("频率")
# 让x轴从左到右递增
axs.invert_xaxis()
# 确保正确的布局
fig.tight_layout()
# 保存直方图
fig.savefig(Path(output.hist))

一些示例数据如下：

[array(['1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0','1.0',
       '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
       '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
       '1.0', '1.0', '1.0'], dtype='<U46'),
 array(['1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
       '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
       '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0', '1.0',
       '1.0', '1.0', '1.0'], dtype='<U46'),
 array(['0.25', '0.3', '0.3', '0.3', '0.3', '0.3', '0.0', '0.0', '0.3',
       '0.0', '0.3', '0.3', '0.0', '0.0', '0.3', '0.5', '0.4', '0.0',
       '0.5', '0.5', '0.5', '0.0', '0.4', '0.0', '0.0', '0.6', '0.3',
       '0.1', '0.0', '0.0'], dtype='<U46'),
 array(['0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0','0.0','0.0',
       '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
       '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0', '0.0',
       '0.0', '0.0', '0.0'], dtype='<U46')]

我已尝试了所有可能的range和bin组合。


<details>
<summary>英文:</summary>
I have multiple datasets of that I&#39;d like to combine into a histogram. Unfortunately, my data shows different ranges. 
Using the simple `range=(0,1)` argument triggers weird behaviour.
This is what it should look like:
[![enter image description here](https://i.stack.imgur.com/xjk4t.png)](https://i.stack.imgur.com/xjk4t.png)
and it currently does when the data has the range 0-1. 
But sometimes it has not and I get: [![enter image description here](https://i.stack.imgur.com/rUOSN.png)](https://i.stack.imgur.com/rUOSN.png)
Here I would like to force the 0-1 range. 
But when I do with 
`axs.hist(plot_data, range=(0,1),color=colors,label=plot_label, histtype=&#39;bar&#39;)`
I get [![enter image description here](https://i.stack.imgur.com/FwutW.png)](https://i.stack.imgur.com/FwutW.png)
I cannot explain why that happens. 
This is the code:
```python
fig, axs = plt.subplots(1,1,tight_layout=True)
fig.set_size_inches(7, 4)
# Define colors for each histogram
colors = [&#39;g&#39;, &#39;b&#39;, &#39;r&#39;, &#39;purple&#39;]
# make combined histogram for all error conditions
# plot the histogram
axs.hist(plot_data,color=colors,label=plot_label, histtype=&#39;bar&#39;)
# Put a legend to the right of the current axis
axs.legend(loc=&#39;center left&#39;,bbox_to_anchor=(1, 0.5))
# set the axis labels
axs.set_xlabel(f&quot;Similarity: {wildcards.metric}&quot;)
axs.set_ylabel(&quot;Frequency&quot;)
# have the x-axis go increasing from left to right
axs.invert_xaxis()
# ensure proper layout
fig.tight_layout()
# save the histogram
fig.savefig(Path(output.hist))

and some example data is:

[array([
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,&#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;], dtype=&#39;&lt;U46&#39;),
array([&#39;
1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;,
&#39;1.0&#39;, &#39;1.0&#39;, &#39;1.0&#39;], dtype=&#39;&lt;U46&#39;),
array([
&#39;0.25&#39;, &#39;0.3&#39;, &#39;0.3&#39;, &#39;0.3&#39;, &#39;0.3&#39;, &#39;0.3&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.3&#39;,
&#39;0.0&#39;, &#39;0.3&#39;, &#39;0.3&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.3&#39;, &#39;0.5&#39;, &#39;0.4&#39;, &#39;0.0&#39;,
&#39;0.5&#39;, &#39;0.5&#39;, &#39;0.5&#39;, &#39;0.0&#39;, &#39;0.4&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.6&#39;, &#39;0.3&#39;,
&#39;0.1&#39;, &#39;0.0&#39;, &#39;0.0&#39;], dtype=&#39;&lt;U46&#39;),
array([
&#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;,&#39;0.0&#39;,&#39;0.0&#39;,
&#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;,
&#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;,
&#39;0.0&#39;, &#39;0.0&#39;, &#39;0.0&#39;], dtype=&#39;&lt;U46&#39;)]

I have tried every possible range and bin combination.

答案1

得分: 1

你的数组中充满了字符串值，但你正在传递一个期望浮点数/整数值的范围参数。我不确定为什么你的值是字符串，但使用浮点值（而不是使用 dtype = '<U46'）会使图表的范围参数按预期行为：

plot_data = [np.array([
       1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
       1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
       1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
       1.0, 1.0, 1.0]),
 np.array([
     1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
     1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
     1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
     1.0, 1.0, 1.0]),
 np.array([
     0.25, 0.3, 0.3, 0.3, 0.3, 0.3, 0.0, 0.0, 0.3,
     0.0, 0.3, 0.3, 0.0, 0.0, 0.3, 0.5, 0.4, 0.0,
     0.5, 0.5, 0.5, 0.0, 0.4, 0.0, 0.0, 0.6, 0.3,
     0.1, 0.0, 0.0]),
 np.array([
     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
     0.0, 0.0, 0.0])]

fig, axs = plt.subplots(1, 1, tight_layout=True)
fig.set_size_inches(7, 4)
# 为每个直方图定义颜色
colors = ['g', 'b', 'r', 'purple']
plot_label = ['IDEAL', 'TYPICAL', 'LARGE', 'EXTREME']
# 创建所有错误条件的组合直方图
# 绘制直方图
axs.hist(plot_data, range=(0, 1), color=colors, label=plot_label, histtype='bar')
#axs.hist(plot_data, histtype='bar', color=colors, label=plot_label)
# 在当前轴的右侧放置图例
axs.legend(loc='center left', bbox_to_anchor=(1, 0.5))
# 设置坐标轴标签
axs.set_xlabel(f"相似度:")
axs.set_ylabel("频率")
# 使x轴从左到右递增
axs.invert_xaxis()
# 确保正确的布局
fig.tight_layout()
plt.xlim(0, 1)
plt.show()

修复具有多个数据集的Matplotlib直方图的范围？

英文:

Your arrays are full of string values but you're passing a range parameter that is expecting float/int values. I'm not sure why your values are strings, but using float values (and not using dtype = &#39;&lt;U46&#39;) leads to the graph behaving as expected with the range parameter:

plot_data = [np.array([
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0]),
np.array([
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0]),
np.array([
0.25, 0.3, 0.3, 0.3, 0.3, 0.3, 0.0, 0.0, 0.3,
0.0, 0.3, 0.3, 0.0, 0.0, 0.3, 0.5, 0.4, 0.0,
0.5, 0.5, 0.5, 0.0, 0.4, 0.0, 0.0, 0.6, 0.3,
0.1, 0.0, 0.0]),
np.array([
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,0.0,0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0])]
fig, axs = plt.subplots(1,1,tight_layout=True)
fig.set_size_inches(7, 4)
# Define colors for each histogram
colors = [&#39;g&#39;, &#39;b&#39;, &#39;r&#39;, &#39;purple&#39;]
plot_label = [&#39;IDEAL&#39;, &#39;TYPICAL&#39;, &#39;LARGE&#39;, &#39;EXTREME&#39;]
# make combined histogram for all error conditions
# plot the histogram
axs.hist(plot_data, range=(0,1),color=colors,label=plot_label, histtype=&#39;bar&#39;)
#axs.hist(plot_data,histtype=&#39;bar&#39;, color=colors, label=plot_label)
# Put a legend to the right of the current axis
axs.legend(loc=&#39;center left&#39;,bbox_to_anchor=(1, 0.5))
# set the axis labels
axs.set_xlabel(f&quot;Similarity:&quot;)
axs.set_ylabel(&quot;Frequency&quot;)
# have the x-axis go increasing from left to right
axs.invert_xaxis()
# ensure proper layout
fig.tight_layout()
plt.xlim(0, 1)
plt.show()

修复具有多个数据集的Matplotlib直方图的范围？

huangapple
  • 本文由 发表于 2023年8月5日 01:19:34
  • 转载请务必保留本文链接：https://go.coder-hub.com/76838005.html
  • histogram
  • matplotlib
  • python
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