“数组”的版本间差异

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无编辑摘要
无编辑摘要
 
(未显示同一用户的2个中间版本)
第6行: 第6行:
A=reform(data[1,*])
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
* rotate
第40行: 第42行:
:数组的位数,
:数组的位数,
print,size(array)
print,size(array)
:size 还可以用来确定[[变量的类型]] Ctype=size(A,/type),
:size 还可以用来确定变量的类型 Ctype=size(A,/type),


* 数组随机打乱(shuffle)
* 数组随机打乱(shuffle)
第50行: 第52行:
*数组求和
*数组求和
a=total(indgen(10),/cum);输出为数组的累计分布
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

2017年1月9日 (一) 04:37的最新版本

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