Python-使用点列表从没有for循环的网格NetCDF中提取数据 [英] Python - Use list of points to extract data from gridded NetCDF without for loops
问题描述
以下示例使用东风的"Unidata"样本netCDF数据集，该数据集可以是从此处下载(2.8 MB)
The following example uses the "Unidata" sample netCDF dataset of eastward wind which can be downloaded from here (2.8 MB)
我有两个整数列表，分别与netCDF文件中网格数组的x和y索引相对应.我想提取数据并将其保存到一维数组或每个点组合的列表(例如，点:[(x[0],y[0]), (x[1],y[1]), (x[2],y[2]), ... , (x[n],y[n])]).
I have two lists of integers that correspond to the x and y index of a gridded array in a netCDF file. I want to extract the data and save it to a 1 dimensional array or list for each of the point combinations (e.g. points: [(x[0],y[0]), (x[1],y[1]), (x[2],y[2]), ... , (x[n],y[n])]).
使用此方法，我可以很容易地做到这一点...
I can do this quite easily using this method...
from netCDF4 import Dataset
# grid point lists
lat = [20, 45, 56, 67, 88, 98, 115]
lon = [32, 38, 48, 58, 87, 92, 143]
# open netCDF file
nc_file = "./sresa1b_ncar_ccsm3-example.nc"
fh = Dataset(nc_file, mode='r')
# extract variable
point_list = zip(lat,lon)
ua_list = []
for i, j in point_list:
ua_list.append(fh.variables['ua'][0,16,i,j])
print(ua_list)
哪个返回:
[59.29171, 17.413916, -4.4006901, -11.15424, -5.2684789, 2.1235929, -6.134573]
但是append()在大型数据集上比较笨拙，并且我试图加快代码的速度，因此我也不想使用for循环，而是希望在一行中返回结果.我尝试使用此行来这样做:
However append() is clunky on big datasets and I'm trying to speed up my code so I also do not want to use a for loop and would rather return the results in a single line. I've tried doing so using this line:
# extract variable
ua_array = fh.variables['ua'][0,16,lat,lon]
print(ua_array)
这将返回每个可能的点组合，而不仅仅是我所追求的:
Which returns every single possible combination of points instead of just the ones I am after:
[[ 59.2917099 60.3418541 61.81352234 62.66215515 60.6419754 60.00745392 52.48550797]
[ 18.80122566 17.41391563 14.83201313 12.67425823 13.99616718 14.4371767 14.12419605]
[ -5.56457043 -5.20643377 -4.40069008 -3.25902319 -2.36573601 -2.25667071 -1.0884304 ]
[-11.66207981 -11.46785831 -11.35252953 -11.15423965 -11.35271263 -11.55139542 -11.68573093]
[ -1.15064895 -1.52471519 -2.12152767 -2.67548943 -5.26847887 -5.79328251 -6.16713762]
[ -1.95770085 -0.56232995 0.82722098 1.39629912 2.65125418 2.12359285 -6.47501516]
[ -9.76508904 -10.13490105 -10.76805496 -11.31607246 -11.93865585 -11.56440639 -6.13457298]]
如何对netCDF文件进行切片，以便在一行中获得与上述代码相同的结果?提前致谢.
How can I slice the netCDF file so I can get the same result as the above code in a single line? Thanks in advance.
推荐答案
首先使用0和16进行普通索引编制，然后使用lat和lon进行高级索引编制:
Do normal indexing with 0and 16 first, followed by advanced indexing with lat and lon:
ua_array = fh.variables['ua'][0,16][lat,lon]
print(ua_array)
输出:
[ 59.2917099 17.41391563 -4.40069008 -11.15423965 -5.26847887
2.12359285 -6.13457298]
BTW，ua_array是一个NumPy数组.因此，调用它的ua_list有点误导.
BTW, ua_array is a NumPy array. Therefore, calling its ua_list is bit misleading.
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