|
|
@ -222,10 +222,10 @@ def get_ongoing_recession(n_runs, start_year, end_year, sea_level_rise,
|
|
|
|
slr[i, :] = np.ones([1, n_runs]) * slr_mode[i]
|
|
|
|
slr[i, :] = np.ones([1, n_runs]) * slr_mode[i]
|
|
|
|
|
|
|
|
|
|
|
|
# Sort each row, so SLR follows a smooth trajectory for each model run
|
|
|
|
# Sort each row, so SLR follows a smooth trajectory for each model run
|
|
|
|
slr.sort(axis=1)
|
|
|
|
slr = np.sort(slr, axis=1)
|
|
|
|
|
|
|
|
|
|
|
|
# Shuffle columns, so the order of model runs is randomised
|
|
|
|
# Shuffle columns, so the order of model runs is randomised
|
|
|
|
np.random.shuffle(slr.T)
|
|
|
|
slr = np.random.permutation(slr.T).T
|
|
|
|
|
|
|
|
|
|
|
|
# Shift sea level so it is zero in the start year
|
|
|
|
# Shift sea level so it is zero in the start year
|
|
|
|
slr -= slr[0, :].mean(axis=0)
|
|
|
|
slr -= slr[0, :].mean(axis=0)
|
|
|
|