matplotlib / matplotlib/ipympl
Plot is duplicated with repeated calls to plt.show()
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描述
Describe the issue
When I use the "%matplotlib ipympl" backend and display a plot with plt.show(), it works fine, but that plot is displayed again for every future call to plt.show(). The expected behavior is for show() to not repeat the plot output. This occurs with a fresh Anaconda (2024.10-1) installation of Python (3.12.7). This does not happen with default backend.
Versions
3.12.7 | packaged by Anaconda, Inc. | (main, Oct 4 2024, 08:22:19) [Clang 14.0.6 ]
ipympl version: 0.9.6
Selected Jupyter core packages...
IPython : 8.30.0
ipykernel : 6.29.5
ipywidgets : 8.1.5
jupyter_client : 8.6.0
jupyter_core : 5.7.2
jupyter_server : 2.14.1
jupyterlab : 4.2.5
nbclient : 0.8.0
nbconvert : 7.16.4
nbformat : 5.10.4
notebook : 7.2.2
qtconsole : 5.6.0
traitlets : 5.14.3
usage: jupyter [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir]
[--paths] [--json] [--debug]
[subcommand]
Jupyter: Interactive Computing
positional arguments:
subcommand the subcommand to launch
options:
-h, --help show this help message and exit
--version show the versions of core jupyter packages and exit
--config-dir show Jupyter config dir
--data-dir show Jupyter data dir
--runtime-dir show Jupyter runtime dir
--paths show all Jupyter paths. Add --json for machine-readable
format.
--json output paths as machine-readable json
--debug output debug information about paths
Available subcommands: console dejavu events execute kernel kernelspec lab
labextension labhub migrate nbconvert notebook qtconsole run server
troubleshoot trust
Jupyter command `jupyter-nbextension` not found.
I believe that last error is expected for notebook>7, but I'm not certain.
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调研方向
该 issue 未指定源文件或测试。首先,在报告中的 Jupyter 和 Python 版本上使用 %matplotlib ipympl 后端复现重复调用 plt.show() 的行为,然后将其与默认后端进行比较。完成标准是:重复调用 show() 不再复制现有的绘图输出。
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- jupyter, jupyter-notebook, python
- 领域
- data-visualization, frontend
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 需要澄清
- 新手友好度
- 32/100