Performance comparison for https://stackoverflow.com/a/66102212/3944322

so66101913.py

import numpy as np
import perfplot
import matplotlib.pyplot as plt

plt.figure(figsize=(10,6))

xy = [51,52]
maxint = 10

def setup(n):
    np.random.seed(0)
    a = np.random.randint(0,maxint,n)
    a[:2] = xy
    return a

def unique_without_index(vec):
    first_occurrence = []
    for x in np.unique(vec):
        if x not in xy:
            first_occurrence.append(np.argmax(x==vec))
    return first_occurrence

def unique_with_index(vec):
    u, i =  np.unique(vec, return_index=True)
    return i[np.isin(u, xy, invert=True)]


def isin_sorted(a, i, invert=False):
    ind = np.searchsorted(a, i)
    ind = ind[a[ind.clip(max=a.size)] == i]
    if invert:
        mask = np.ones(a.size, dtype=bool)
        mask[ind] = False
    else:
        mask = np.zeros(a.size, dtype=bool)
        mask[ind] = True
    return mask

def unique_with_index_sorted(vec):
    u, i =  np.unique(vec, return_index=True)
    return i[isin_sorted(u, xy, invert=True)]

perfplot.show(
    setup=setup,
    kernels=[
        lambda a: unique_without_index(a),
        lambda a: unique_with_index(a),
        lambda a: unique_with_index_sorted(a),
    ],
    labels=["unique_without_index", "unique_with_index", "unique_with_index_sorted"],
    n_range=[2 ** k for k in range(5,25)],
    xlabel="len(vec) xy = [51,52] ",
)

ax = plt.gca()
ax.spines['bottom'].set_visible(True)
ax.set_ylabel(ax.get_title())
ax.set_title(f'numbers 0 .. {maxint}')

vec = np.array([2, 2, 2, 51, 51, 52, 52, 14, 14, 14, 51, 51, 52, 52])
xy = [51,52]

%timeit unique_with_index(vec)
#27.5 µs ± 185 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)

%timeit unique_with_index_sorted(vec)
#38.9 µs ± 109 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)

%timeit unique_without_index(vec)
#16.2 µs ± 43.5 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)