程序员最近都爱上了这个网站  程序员们快来瞅瞅吧！  it98k网:it98k.com

Given latitude and longitude arrays, I'm tryin to genereate a land_mask, an array of the same size that tells whether a coordinate is land or not.

lon=np.random.uniform(0,150,size=[1000,1000])
lat=np.random.uniform(-90,90,size=[1000,1000])

from global_land_mask import globe
land_mask=globe.is_land(lat,lon)

This is a very efficient method to create land mask if all values are defined. But if some values in lat or lon are masked or are nan values, it throws an error.

I've tried to use for loops to avoid that error but it's taking almost 15-20 minutes to run. I've to run it on an array with 3000×3000 elements, some of which are masked.

What would be a better way for generating land mask for arrays with masked/nan values?

解决方案

所以它似乎globe.is_land(y,x)不需要屏蔽数组。一个公平的解决方案是使用域外的坐标（如果可能）。所以：

lon[lon==327.67] = 170
lat[lat==327.67] = -90

from global_land_mask import globe
land_mask=globe.is_land(lat,lon)

masked = np.where((lat==-90)|(lon==170), False, land_mask)

或者，您可以在传入值之前屏蔽这些值：

lat_mask = np.where(lat==326.67, np.nan, lat)
lon_mask = np.where(lon==326.67, np.nan, lon)

master_mask = np.where((lat_mask==np.nan)|(lon_mask==np.nan), False, True)

lat[master_mask]==True 
lon[master_mask]==True 

from global_land_mask import globe
land_mask=globe.is_land(lat,lon)

第二种解决方案将更改（展平）您的纬度/经度数组，但不需要您找到域外的区域