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管理

管理

为确保你提交的代码身份被 Gitee 正确识别,请执行以下命令完成配置

git config --global user.name userName git config --global user.email userEmail

初次使用 SSH 协议进行代码克隆、推送等操作时,需按下述提示完成 SSH 配置

1 生成 RSA 密钥

2 获取 RSA 公钥内容,并配置到 SSH公钥 中

在 Gitee 上使用 SVN,请访问 使用指南

使用 HTTPS 协议时,命令行会出现如下账号密码验证步骤。基于安全考虑,Gitee 建议 配置并使用私人令牌 替代登录密码进行克隆、推送等操作

Username for 'https://gitee.com': userName

Password for 'https://userName@gitee.com': # 私人令牌

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benchmarks

README.rst

asv.conf.json

PyWavelets benchmarks

Benchmarking PyWavelets with Airspeed Velocity.

Usage

Airspeed Velocity manages building and Python virtualenvs (or conda environments) by itself, unless told otherwise. To run the benchmarks, you do not need to install a development version of PyWavelets to your current Python environment.

First navigate to the benchmarks subfolder of the repository.

cd benchmarks

To run all benchmarks against the current build of PyWavelets:

asv run --python=same --quick

The following notation (tag followed by ^!) can be used to run only on a specific tag or commit. (In this case, a python version for the virtualenv must be provided)

asv run --python=3.5 --quick v0.4.0^!

To record the results use:

asv publish

And to see the results via a web browser, run:

asv preview

More on how to use asv can be found in Writing benchmarks

See

try:

from pywt import cwt

except ImportError:

raise NotImplementedError("cwt not available")

• Try to keep the runtime of the benchmark reasonable.
• Use ASV's time_ methods for benchmarking times rather than cooking up time measurements via time.clock, even if it requires some juggling when writing the benchmark.
• Preparing arrays etc. should generally be put in the setup method rather than the time_ methods, to avoid counting preparation time together with the time of the benchmarked operation.