def test_argpercentile():
# Create random Data
test_arr = np.random.randint(0, 10000, 50000).reshape(5, 100, 100).astype(np.float32)
np.random.shuffle(test_arr)
# place random NaNs
rand_nan = np.random.randint(0, 50000, 500).astype(np.float32)
for r in rand_nan:
test_arr[test_arr == r] = np.NaN
np_result = np.nanpercentile(test_arr, q=25, axis=0, interpolation='nearest')
argpercentile_result = axisindex(test_arr, argpercentile(test_arr, q=25, axis=0), axis=0)
assert np.isclose(np_result, argpercentile_result).all()
def index_dataset(var):
return axisindex(data.data_vars[var.name].values, var.values)
def index_dataset(var, axis):
return axisindex(var, index, axis=axis)