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4 changes: 4 additions & 0 deletions .buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: 74086f8b321d0b81b229867e48c39ddb
tags: d77d1c0d9ca2f4c8421862c7c5a0d620
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[oneAPI]
name=Intel(R) oneAPI repository
baseurl=https://yum.repos.intel.com/oneapi
enabled=1
gpgcheck=1
repo_gpgcheck=1
gpgkey=https://yum.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
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diff --git a/Makefile b/Makefile
index 5676245..11aac94 100644
--- a/Makefile
+++ b/Makefile
@@ -1,9 +1,10 @@
+FC=gfortran
optimize=-O
-FFLAGS=$(optimize) -ffpe-trap=overflow,invalid,denormal
+FFLAGS=$(optimize) -ffpe-trap=overflow,invalid,denormal -ffixed-line-length-none
CFLAGS=$(optimize)
#if SAC library has been installed, uncomment the next two lines
-#CFLAGS=$(optimize) -DSAC_LIB
-#SACLIB=-L$(SACHOME)/lib -lsac -lsacio
+CFLAGS=$(optimize) -DSAC_LIB
+SACLIB=-L$(SACHOME)/lib -lsac -lsacio
#

SUBS = fft.o Complex.o sacio.o
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192 changes: 192 additions & 0 deletions _sources/anaconda/index.md
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# Anaconda/Miniconda

- 本节贡献者: {{田冬冬}}(作者)、{{姚家园}}(审稿)
- 最近更新时间:2023-09-23

---

[Anaconda](https://www.anaconda.com/download/) 是一个跨平台的、用于科学计算的 Python 发行版,
其提供了 Python、包管理器 `conda` 并内置了几百个科学计算相关的软件包。
[Miniconda](https://docs.conda.io/en/latest/miniconda.html) 可以看做是
Anaconda 的精简版,其只提供了 Python、包管理器 `conda` 以及相关的必须依赖包。

与 Anaconda 相比,Miniconda 安装包更小,安装速度更快,且安装后占用的硬盘空间更小。
Anaconda 内置的数百个软件包也都可以很容易通过 `conda` 安装。因而,
**建议所有 Python 用户使用 Miniconda,而非 Linux 或 macOS 系统自带的 Python。**

## 安装

1. 下载 Miniconda

根据自己使用的系统,从 [Miniconda 官方下载页面](https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links)
[清华大学 Miniconda 镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/) 下载对应的安装包。

- Linux 64 位系统:
[官方链接](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh) |
[清华镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh)
- Windows 64 位系统:
[官方链接](https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe) |
[清华镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-Windows-x86_64.exe)
- macOS (Intel 芯片):
[官方链接](https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh) |
[清华镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-MacOSX-x86_64.sh)
- macOS (M1 芯片):
[官方链接](https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh)
[清华镜像](https://mirrors.tuna.tsinghua.edu.cn/anaconda/miniconda/Miniconda3-latest-MacOSX-arm64.sh)

2. 安装 Miniconda

::::{tab-set}

:::{tab-item} Windows
直接双击安装包即可安装。
:::

:::{tab-item} Linux
```
$ bash Miniconda3-latest-Linux-x86_64.sh
```
:::

:::{tab-item} macOS
```
# Intel 芯片
$ bash Miniconda3-latest-MacOSX-x86_64.sh
# M1 芯片
$ bash Miniconda3-latest-MacOSX-arm64.sh
```
:::

::::

Miniconda 默认会安装到 {file}`${HOME}/miniconda3` 下,在安装过程中可以
设置为其他路径。

安装通常只需要十几秒,在安装的最后会出现:

```
Do you wish the installer to initialize Miniconda3 by running conda init? [yes|no]
[yes] >>>
```

建议输入 `yes`,此时安装包会向当前 SHELL 的配置文件(如 {file}`~/.bashrc`
或 {file}`~/.zshrc`)中写入 `conda` 初始化语句。

3. 测试安装

打开一个新的终端,在终端中输入 `python`,输出中看到 **Anaconda, Inc.**
字样即代表安装完成:

```
$ python
Python 3.8.5 (default, Sep 4 2020, 02:22:02)
[Clang 10.0.0 ] :: Anaconda, Inc. on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
```

# 配置 `conda`

Anaconda/Miniconda 中提供的 `conda` 命令可以用于安装 Python 包、管理虚拟环境,
此外,也可以使用 Python 自带的工具 `pip` 来安装 Python 包,其详细用法见
[pip 官方文档](https://pip.pypa.io/en/stable/)。我们建议尽可能使用 `conda` 来安装 Python 包,
仅在 conda 没有提供需要的程序包时才使用 `pip` 来安装。

在使用 `conda` 前需要对 `conda` 做简单的配置。

[conda-forge](https://conda-forge.org/) 是一个由社区维护的大量 Python 包的通道。
为 conda 增加 conda-forge 通道,可以安装更多的软件包:
```
$ conda config --add channels conda-forge
```

设置通道优先级为 strict。当一个包同时位于 conda-forge 和 main 通道时,总是使用 conda-forge 提供的包,
以避免混用 conda-forge 和 main 通道导致环境依赖关系解析变慢:
```
$ conda config --set channel_priority true
```

显示通道 URL,以更清楚地知道每个包是从哪个通道安装的:
```
$ conda config --set show_channel_urls true
```

配置使用国内清华源以加快软件包下载速度:
```
$ conda config --add default_channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
$ conda config --set 'custom_channels.conda-forge' https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
```

设置 `conda` 使用更快的 libmamab solver:
```
$ conda config --set solver libmamba
```

## 使用 conda

以下仅介绍一些 `conda` 的常用命令,其详细用法见
[conda 官方文档](https://docs.conda.io/projects/conda/en/latest/index.html)

创建虚拟环境:
```
# 虚拟环境名为 seismo-learn,初始 Python 版本与 base 环境相同
$ conda create --name seismo-learn
```

激活虚拟环境:
```
# 激活名为 seismo-learn 的虚拟环境
$ conda activate seismo-learn
```

取消激活当前虚拟环境:
```
$ conda deactivate
```

:::{note}
安装 Anaconda/Miniconda 后,打开终端默认会激活 base 环境。不经常使用
Python 的读者可以通过如下命令取消此默认设置:

```
$ conda config --set auto_activate_base False
```

取消后,可以临时激活 base 环境:
```
$ conda activate base
```

重新激活此默认设置:
```
$ conda config --set auto_activate_base True
```
:::

搜索模块:
```
$ conda search numpy
```

安装模块:
```
$ conda install numpy
```

更新模块:
```
$ conda update numpy
```

使用 pip 安装模块:
```
$ pip install numpy
```

## 参考文档

- <https://docs.anaconda.com/anaconda/install/>
- <https://conda.io/projects/conda/en/latest/user-guide/install/index.html>
- <https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html>
- <https://mirrors.tuna.tsinghua.edu.cn/help/anaconda/>
- <https://mirrors.tuna.tsinghua.edu.cn/help/pypi/>
20 changes: 20 additions & 0 deletions _sources/cps/index.md
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# CPS

- 软件名称: Computer Programs in Seismology
- 作者: [Robert B. Herrmann](https://www.eas.slu.edu/People/RBHerrmann/)
- 主页: <http://www.eas.slu.edu/eqc/eqccps.html>
- 官方文档: <http://www.eas.slu.edu/eqc/eqc_cps/CPS/CPS330.html>
- 最新版本: v3.30 (2022-11-08)
- 适用平台: {{Linux}} {{macOS}} {{Windows}}
- 编程语言: Fortran、C
- 许可协议: 未知

---

:::{note}
CPS 在十几年前就发布了 3.30 版本,之后不断修复程序错误和更新代码,但并未更新版本号。
因而 CPS v3.30 实际上有多个不同的小版本。

本教程仅在 Linux 和 macOS 系统下使用 v3.30 (2022-11-08)
测试通过,其余版本或系统可能有所差异。
:::
105 changes: 105 additions & 0 deletions _sources/cps/install.md
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# 安装

- 本节贡献者: {{田冬冬}}(作者)、 {{姚家园}}(审稿)
- 最近更新日期: 2021-01-26

---

{{ install_notes }}

1. 下载:

CPS 源码需要先填写申请表格才可以下载。
<http://www.eas.slu.edu/eqc/eqc_cps/CPS/cpslisc.html> 填写表格并提交。

% CPS 的源码也可以直接 http://www.eas.slu.edu/eqc/eqc_cps/ 的 download 目录下载

2. 解压:

```
$ tar -xvf NP330.Nov-08-2022.tgz
```

将解压得到的 {file}`PROGRAMS.330` 文件夹移至 {file}`~/src/` 目录下,并重命名为 {file}`CPS`

```
$ mkdir -p ~/src/
$ mv PROGRAMS.330 ~/src/CPS
```

3. 安装依赖

::::{tab-set}

:::{tab-item} Fedora
```
$ sudo dnf install libX11-devel
```
:::

:::{tab-item} Ubuntu/Debian
```
$ sudo apt install libx11-dev
```
:::

:::{tab-item} macOS
```
# macOS 安装 XQuartz 后需要重启方可生效
$ brew install --cask xquartz
```
::::

4. 配置:

若使用的是 Linux 系统,首先需要确认当前系统是 32 还是 64 位。
终端键入 `uname -a`,若输出中包含 `x86_64` 则是 64 位,若输出包含类似
`i686` 则是 32 位。

进入源码目录:

```
$ cd ~/src/CPS
```
::::{tab-set}

:::{tab-item} 64 位 Linux 系统
```
$ ./Setup LINUX6440
```
:::

:::{tab-item} 32 位 Linux 系统
```
$ ./Setup LINUX40
```
:::

:::{tab-item} macOS 系统
```
$ ./Setup OSX40
```
:::
::::

:::{note}
终端键入 `./Setup` 可查询全部选项。
:::

5. 编译:

```
$ ./C
```

接下来会编译一段时间,最终在 bin 目录下应该生成一百多个可执行文件。

6. 修改环境变量,将 CPS 的 bin 路径添加到环境变量 **PATH** 中:
```
$ echo 'export PATH=${HOME}/src/CPS/bin:${PATH}' >> ~/.bashrc
$ source ~/.bashrc
```

7. 检查安装是否成功

终端键入一些 CPS 的命令,比如 `sdisp96 -h`,若出现该命令的使用选项则表示安装成功。
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