一、Amply
Amply允许您以Python数据结构加载和操作AMPL数据。
Amply只支持AMPL语法的特定子集：
1、设置声明
2、设置数据语句
3、参数声明
4、参数数据语句
二、声明和数据语句
通常，在AMPL中表达的问题包括两个部分，一个模型部分和一个数据部分。Amply只设计用于解析AMPL数据段中包含的参数和设置语句。然而，为了正确地解析这些语句，可能需要在模型部分中包含的信息。例如，它不可能从它的数据语句中推断出一个集合的维数。因此，Amply也支持设置和参数声明。这些不必放在单独的部分中，它们只需要在相应的数据语句之前发生。
支持的声明语法非常有限，并且不包含AMPL编程语言的大多数元素。其目的是将该库用作加载类似于amplam语法的数据的一种方式。
此外，Amply不对数据语句执行任何验证。
该文档的目的是指导Amply所支持的语法，而不是一般的AMPL参考手册。
三、快速入门指南
导入的类:
from pulp import Amply
一个简单的集合。
>>> data = Amply("set CITIES := Auckland Wellington Christchurch;")
>>> print data['CITIES']
<SetObject: ['Auckland', 'Wellington', 'Christchurch']>
>>> for c in data['CITIES']: print c
Auckland
Wellington
Christchurch
>>> print data['CITIES'][0]
Auckland
>>> print len(data['CITIES'])
3
数据可以是整数、实数、符号或引用字符串：
>>> data = Amply("""
... set BitsNPieces := 0 3.2 -6e4 Hello "Hello, World!";
... """)
>>> print data.BitsNPieces
<SetObject: [0.0, 3.2000000000000002, -60000.0, 'Hello', 'Hello, World!']>
集合可以包含多维数据，但是我们必须先声明它们。
>>> data = Amply("""
... set pairs dimen 2;
... set pairs := (1, 2) (2, 3) (3, 4);
... """)
>>> print data.pairs
<SetObject: [(1, 2), (2, 3), (3, 4)]>
集合他们自己可以是多维的：
>>> data = Amply("""
... set CITIES{COUNTRIES};
... set CITIES[Australia] := Adelaide Melbourne Sydney;
... set CITIES[Italy] := Florence Milan Rome;
... """)
>>> print data.CITIES['Australia']
['Adelaide', 'Melbourne', 'Sydney']
>>> print data.CITIES['Italy']
['Florence', 'Milan', 'Rome']
注意，在上面的例子中，集合COUNTRIES实际上并不需要存在。
>>> data = Amply("""
... set SUBURBS{COUNTRIES, CITIES};
... set SUBURBS[Australia, Melbourne] := Docklands 'South Wharf' Kensington;
... """)
>>> print data.SUBURBS['Australia', 'Melbourne']
['Docklands', 'South Wharf', 'Kensington']
可以使用切片指定多维数据
>>> data=Amply("""
... set TRIPLES dimen 3;
... set TRIPLES := (1, 1, *) 2 3 4 (*, 2, *) 6 7 8 9 (*, *, *) (1, 1, 1);
... """)
>>> print data.TRIPLES
<SetObject: [(1, 1, 2), (1, 1, 3), (1, 1, 4), (6, 2, 7), (8, 2, 9), (1, 1, 1)]>
集合数据也可以使用矩阵符号来指定。“+”表示这一对被包含在集合中，而“-”表示一对不在集合中。
>>> data=Amply("""
... set ROUTES dimen 2;
... set ROUTES : A B C D :=
... E + - - +
... F + + - -
... ;
... """)
>>> print data.ROUTES
<SetObject: [('E', 'A'), ('E', 'D'), ('F', 'A'), ('F', 'B')]>
矩阵也可以被调换：
>>> data=Amply("""
... set ROUTES dimen 2;
... set ROUTES (tr) : E F :=
... A + +
... B - +
... C - -
... D + -
... ;
... """)
>>> print data.ROUTES
<SetObject: [('E', 'A'), ('F', 'A'), ('F', 'B'), ('E', 'D')]>
矩阵只指定2d数据，但是它们可以与切片结合来定义更高维度的数据：
>>> data = Amply("""
... set QUADS dimen 2;
... set QUADS :=
... (1, 1, *, *) : 2 3 4 :=
... 2 + - +
... 3 - + +
... (1, 2, *, *) : 2 3 4 :=
... 2 - + -
... 3 + - -
... ;
... """)
>>> print data.QUADS
<SetObject: [(1, 1, 2, 2), (1, 1, 2, 4), (1, 1, 3, 3), (1, 1, 3, 4), (1, 2, 2, 3), (1, 2, 3, 2)]>
参数也支持:
>>> data = Amply("""
... param T := 30;
... param n := 5;
... """)
>>> print data.T
30
>>> print data.n
5
参数通常在集合上被索引。
>>> data = Amply("""
... param COSTS{PRODUCTS};
... param COSTS :=
... FISH 8.5
... CARROTS 2.4
... POTATOES 1.6
... ;
... """)
>>> print data.COSTS
<ParamObject: {'POTATOES': 1.6000000000000001, 'FISH': 8.5, 'CARROTS': 2.3999999999999999}>
>>> print data.COSTS['FISH']
8.5
参数可以包含默认值
>>> data = Amply("""
... param COSTS{P};
... param COSTS default 2 :=
... F 2
... E 1
... D .
... ;
... """)
>>> print data.COSTS['D']
2.0
>>> data = Amply("""
... param COSTS{P} default 42;
... param COSTS :=
... F 2
... E 1
... ;
... """)
>>> print data.COSTS['DOES NOT EXIST']
42.0
集合的复合索引：
>>> data = Amply("""
... param COSTS{CITIES, PRODUCTS};
... param COSTS :=
... Auckland FISH 5
... Auckland CHIPS 3
... Wellington FISH 4
... Wellington CHIPS 1
... ;
... """)
>>> print data.COSTS
<ParamObject: {'Wellington': {'FISH': 4.0, 'CHIPS': 1.0}, 'Auckland': {'FISH': 5.0, 'CHIPS': 3.0}}>
>>> print data.COSTS['Wellington']['CHIPS'] # nested dict
1.0
>>> print data.COSTS['Wellington', 'CHIPS'] # tuple as key
1.0
>>> data = Amply("""
... param COSTS{CITIES, PRODUCTS};
... param COSTS :=
... [Auckland, * ]
... FISH 5
... CHIPS 3
... [Wellington, * ]
... FISH 4
... CHIPS 1
... ;
... """)
>>> print data.COSTS
<ParamObject: {'Wellington': {'FISH': 4.0, 'CHIPS': 1.0}, 'Auckland': {'FISH': 5.0, 'CHIPS': 3.0}}>
>>> data = Amply("""
... param COSTS{CITIES, PRODUCTS};
... param COSTS: FISH CHIPS :=
... Auckland 5 3
... Wellington 4 1
... ;
... """)
>>> print data.COSTS
<ParamObject: {'Wellington': {'FISH': 4.0, 'CHIPS': 1.0}, 'Auckland': {'FISH': 5.0, 'CHIPS': 3.0}}>
>>> data = Amply("""
... param COSTS{CITIES, PRODUCTS};
... param COSTS (tr): Auckland Wellington :=
... FISH 5 4
... CHIPS 3 1
... ;
... """)
>>> print data.COSTS
<ParamObject: {'Wellington': {'FISH': 4.0, 'CHIPS': 1.0}, 'Auckland': {'FISH': 5.0, 'CHIPS': 3.0}}>
高维：
>>> data = Amply("""
... param COSTS{CITIES, PRODUCTS, SIZE};
... param COSTS :=
... [Auckland, *, *] : SMALL LARGE :=
... FISH 5 9
... CHIPS 3 5
... [Wellington, *, *] : SMALL LARGE :=
... FISH 4 7
... CHIPS 1 2
... ;
... """)
>>> print data.COSTS
<ParamObject: {'Wellington': {'FISH': {'SMALL': 4.0, 'LARGE': 7.0}, 'CHIPS': {'SMALL': 1.0, 'LARGE': 2.0}}, 'Auckland': {'FISH': {'SMALL': 5.0, 'LARGE': 9.0}, '
三、API
class Amply(string="")：
load_string(string): Parse string data.
load_file(file): Parse contents of file or file-like object (has a read() method).
static from_file(file): Alternate constructor. Create Amply object from contents of file or file-like object.
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