README visualizations example code error in Colab environment

[gzorpidis]

I am running, in a Colab environment, the code that is suggested in the README.md for visualizations. However there is an error that keeps popping up when initializing ZADU(). I have tried both !pip install zadu and !pip install git+https://github.com/hj-n/zadu.git but neither work and the error seems to be coming from knn_with_ranking(). Python version is: 3.10.12.

Error:

TypeError                                 Traceback (most recent call last)
[<ipython-input-6-6c5f17626372>](https://localhost:8080/#) in <cell line: 18>()
     16     "params": {"k": 50}
     17 }]
---> 18 zadu_obj = zadu.ZADU(spec, hd, return_local=True)
     19 
     20 ld = TSNE().fit_transform(hd)

1 frames
[/usr/local/lib/python3.10/dist-packages/zadu/measures/utils/knn.py](https://localhost:8080/#) in knn_with_ranking(points, k, distance_matrix)
     21     distance_matrix = pairwise_distance_matrix(points, "euclidean")
     22 
---> 23   knn_indices = np.empty((points.shape[0], k), dtype=np.int32)
     24   ranking = np.empty((points.shape[0], points.shape[0]), dtype=np.int32)
     25 

TypeError: an integer is required

Code:

from zaduvis import zaduvis
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from sklearn.datasets import fetch_openml


hd = fetch_openml('mnist_784', version=1, cache=True).data.to_numpy()[::7]

spec = [{
    "id": "tnc",
    "params": {"k": 25}
},{
    "id": "snc",
    "params": {"k": 50}
}]
zadu_obj = zadu.ZADU(spec, hd, return_local=True)

ld = TSNE().fit_transform(hd)
scores, local_list = zadu_obj.measure(ld)

tnc_local = local_list[0]
snc_local = local_list[1]

local_trustworthiness = tnc_local["local_trustworthiness"]
local_continuity = tnc_local["local_continuity"]
local_steadiness = snc_local["local_steadiness"]
local_cohesiveness = snc_local["local_cohesiveness"]

fig, ax = plt.subplots(1, 4, figsize=(50, 12.5))
zaduvis.checkviz(ld, local_trustworthiness, local_continuity, ax=ax[0])
zaduvis.reliability_map(ld, local_trustworthiness, local_continuity, k=10, ax=ax[1])
zaduvis.checkviz(ld, local_steadiness, local_cohesiveness, ax=ax[2])
zaduvis.reliability_map(ld, local_steadiness, local_cohesiveness, k=10, ax=ax[3])