如何解决我们如何创建输入栅格的掩码版本,其中落入其中一个字段的像素设置为 ` & 其他设置为 0?
我认为一切都写得正确,但似乎我遗漏了一些东西。当我试图断言它时,我仍然得到错误的答案。看代码
def masked_raster(input_file,raster_file):
# Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`
with fiona.open(input_file,"r") as shapefile:
geoms = [feature["geometry"] for feature in shapefile]
with Rasterio.open(raster_file) as src:
out_img,out_transform = mask(src,geoms,invert = True,crop=False,all_touched= True)
out_Meta = src.Meta.copy()
out_Meta.update({"driver": "GTiff","height": out_img.shape[1],"width": out_img.shape[2],"transform": out_transform})
return out_img
def reproject_raster(raster_file,dst_crs):
# Reproject the input raster to the provided CRS
with Rasterio.open('masked2.tif',"w",**out_Meta) as dst:
dst.write(out_image)
dst = src
return dst
要测试我使用的代码:
assert masked_raster('crops.geojson','crops.tif')[0].sum() == 1144636.0,"Sorry wrong answer"
assert str(reproject_raster('crops.tif','epsg:4326').crs) == 'epsg:4326',"Sorry wrong answer"
解决方法
这里有一个详细的解决方案,我用内联注释来回答
"""
Solution
"""
import fiona
import rasterio
import rasterio.mask
import pycrs
def masked_raster(input_file,raster_file):
# Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`
#open the geojson file with fiona
with fiona.open("crops.geojson","r") as geojson:
#creating features
features = [feature["geometry"] for feature in geojson]
#open raster file with rasterio
with rasterio.open("crops.tif") as src:
#clip the raster with polygon
out_img,out_transform = rasterio.mask.mask(src,features,crop=True)
#copy meta data of the src
out_meta = src.meta.copy()
return out_img
def reproject_raster(raster_file,dst_crs):
# Reproject the input raster to the provided CRS
#import rioxarray module and crs
import rioxarray
from rasterio.crs import CRS
#open raster file ("crops.tif") using rioxaarray
raster_file = rioxarray.open_rasterio(raster_file,masked=True).squeeze()
#create the crs object
crs_wgs84 = CRS.from_string(dst_crs)
raster_4326 = raster_file.rio.set_crs(crs_wgs84)
#convert DataArray to RasterArray to be able to use .crs on the output
dst = raster_4326.rio
return dst
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