查看“数组”的源代码

==数组==
* REFORM 数组变形
:将数组变为制定的维数
  A=indgen(20), B=reform(A,2,10) 
:reform在默认（无输入参数）的情况下将数组变为一维
  A＝reform(data[1,*])

* 中位值
a=median(A,/even);偶数位的数据，取中间两个数的平均值

* rotate
:可以把数组旋转后组成矩阵，类似于列操作。
 a=indgen(10)
 b=indgen(10)
 c=[rotate(a,1),rotate(b,10]
:转置
 IDL>print,transpose([a,b])

* reverse 
:数组反向
:例：数组降序排列,结合sort（默认升序）
 PRINT, 'Elements of A in descending order: ', A[REVERSE(SORT(A))]

*扩维
:fan程序(http://astro.berkeley.edu/~johnjohn/idl.html#FAN )
 IDL>print,fan(indgen(3),2)
 IDL>print,fan(indgen(3),2,/trans)
可以用rebin实现
 IDL>print,rebin(indgen(3),3,2)

* 多维数组的位置
:用array_indices

  array = RANDOMU(seed, 10, 10)  
  mx = MAX(array, location) 
  ind=array_indices(array,location)
  print, ind, array[ind[0],ind[1]], format = '(%"Value at [%d, %d] is %f")'  

  IDL prints:
  Value at [3, 6] is 0.973381 

:数组的位数,
 print,size(array) 
:size 还可以用来确定变量的类型 Ctype=size(A,/type),

* 数组随机打乱（shuffle)
 Arr_S=arr[sort(randomu(seed,N_elements(arr))]

*数组去重
 Arr=Arr[uniq(Arr,sort(arr))

*数组求和
 a=total(indgen(10),/cum)；输出为数组的累计分布

==数组和矩阵运算==
*For A # B, where A and B are vectors, IDL performs A # TRANSPOSE(B). In this case, C = A # B is a matrix with Cij = Ai Bj. Mathematically, this is equivalent to the outer product, usually denoted by A Å B.
*For A ## B, where A and B are vectors, IDL performs TRANSPOSE(A) ## B. In this case, C = A ## B is a matrix with Cij = Bi Aj.
*To compute the dot product, usually denoted by A • B, use TRANSPOSE(A) # B.
*A # B = B ## A
*A # B = (BT # AT)T ;T表示转置运算