根据地理数据框检查Numpy 3d数组

Question

我正在使用numpy数组，在该数组中，对于不同的坐标（插值），我具有一定的地下水位。我想使数组中与我要检查的地理数据帧中不存在的点无效。我有一个有效的代码，但是循环的数量很大。如果有人可以提出更好的方法？我当前的代码如下：

        x = np.array(SpatialTable['x'])
        y = np.array(SpatialTable['y'])
        z = np.array(SpatialTable['Difference']) 
        #identify the extreme points of the aquifer system for which data is available
        lon_min = min(x)
        lat_min = min(y)
        lon_max = max(x)
        lat_max = max(y)
        #create grid points of defined spacing for interpolation, spacing in x and y=150
        numcols, numrows = int((lon_max-lon_min)/150), int((lat_max-lat_min)/150)
        xi = np.linspace(lon_min, lon_max, numcols)
        yi = np.linspace(lat_min, lat_max, numrows)
        xx, yy = np.meshgrid(xi, yi)  
        #interpolate the data available for all defined grid points
        zi = griddata((x,y),z,(xx,yy),method='cubic')  
        for i in range(numcols):
            for j in range(numrows):
                if (np.isnan(zi[j][i])==False):
                    if (Point(xi[i],yi[j]).within(shape['geometry'][0]) or \Point(xi[i],yi[j]).within(shape['geometry'][1]) or Point(xi[i],yi[j]).within(shape['geometry'][2]) or \`enter code here`Point(xi[i],yi[j]).within(shape['geometry'][3])):
                        pass
                    else:
                        zi[j][i]=np.nan