进阶用法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183 动态写文档 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184 18 Functionality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 871 70 动态链接器 909 71 线性代数 913 71.1 特殊矩阵 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 科学计算对性能一直有着最高的需求，但目前各领域的专家却大量使用较慢的动态语言来开展他们 的日常工作。偏爱动态语言有很多很好的理由，因此我们不会舍弃动态的特性。幸运的是，现代编 程语言设计与编译器技术可以大大消除性能折衷（trade-off），并提供有足够生产力的单一环境进行 原型设计，而且能高效地部署性能密集型应用程序。Julia 语言在这其中扮演了这样一个角色：它是 一门灵活的动态语言，适合用于科学计算和数值计算，并且性能可与传统的静态类型语言媲美。

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 27.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 28.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 27.1 Propagation of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situa�ons. 29.1 Propaga�on of Missing Values The behavior following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract defini�on actually corresponds to a rela�vely natural behavior which is Nothing} arguments or fields. To represent missing data in the sta�s�cal sense (NA in R or NULL in SQL), use the missing object. See the Missing Values sec�on for more details. The empty tuple (()) is

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the

missing object, which is the singleton instance of the type Missing. missing is equivalent to NULL in SQL and NA in R, and behaves like them in most situations. 20.1 Propagation of Missing Values missing following the well-established rules of three-valued logic which are also implemented by NULL in SQL and NA in R. This abstract definition actually corresponds to a relatively natural behavior which is Nothing} arguments or fields. To represent missing data in the statistical sense (NA in R or NULL in SQL), use the missing object. See the Missing Values section for more details. In some languages, the