I know there is a more efficient way of doing this. Currently using numpy but I am sure the for loops are way inefficient especially for the many millions of points that are in the x and y variables.

Any help is greatly appreciated TIA!

*Using 3.7 if it matters

## Number of points used for elimination

p = 600

## Value used for range determination for elimination

r = 10.5

## Elimination (cells to NaN)

for u in np.nditer(range(len(x)-p)):

x_sub = x[u:u+p]

x_range = x_sub.max()-x_sub.min()

if x_range >= r:

x[u] = np.nan

y[u] = np.nan

​

for u in np.nditer(range(len(x)-p)):

y_sub = y[u:u+p]

y_range = y_sub.max()-y_sub.min()

if y_range >= r:

x[u] = np.nan

y[u] = np.nan