from osgeo import gdal import numpy as np path = './data/201912/anl_surf125.2019120100' dataset = gdal.Open(path) number_bands = dataset.RasterCount for i in range(1, number_bands): band = dataset.GetRasterBand(i) data_array = band.ReadAsArray() prin
思路,用read来全部读取,然后替换带*的元素来解决.代码如下 import numpy as np import re inf = open('SF.usr') title = inf.readline() l = inf.read() d = re.split('[^0-9.*]+',l.strip()) for i,x in enumerate(d): if x.find('*') != -1 : f = x.split('*') number = int(f[0]) value = f[
Over the years, I have collected, modified, adapted, adopted or created a number of software packages in FORTRAN. You might be able to use one of these libraries, or a routine or two from a library. The packages are at different levels of completion.
基于Python的Grib数据可视化 利用Python语言实现Grib数据可视化主要依靠三个库——pygrib.numpy和matplotlib.pygrib是欧洲中期天气预报中心(ECMWF)的GRIG API C库的Python接口,通过这个库可以将Grib数据读取出来:numpy是Python的一种开源的数值计算扩展,这种工具可用来存储和处理大型矩阵:matplotlib是python著名的绘图库,它提供了一整套和matlab相似的命令API,十分适合交互式地进行制图: