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Add cluster stats (#13)

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Co-authored-by: bastien ollier <bastien.ollier@etu.uca.fr>
Reviewed-on: https://codefirst.iut.uca.fr/git/clement.freville2/miner/pulls/13
Reviewed-by: Hugo PRADIER <hugo.pradier2@etu.uca.fr>
Reviewed-by: Clément FRÉVILLE <clement.freville2@etu.uca.fr>
Co-authored-by: Bastien OLLIER <bastien.ollier@noreply.codefirst.iut.uca.fr>
Co-committed-by: Bastien OLLIER <bastien.ollier@noreply.codefirst.iut.uca.fr>
This commit is contained in:
Bastien OLLIER
2024-06-25 08:37:38 +02:00
committed by Clément FRÉVILLE
parent 4d82767c68
commit 9da6e2d594
3 changed files with 74 additions and 14 deletions
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11
frontend/pages/clustering_dbscan.py
View File

@@ -1,10 +1,9 @@
import streamlit as st
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from clusters import DBSCAN_cluster
st.header("Clustering: dbscan")
if "data" in st.session_state:
data = st.session_state.data
@@ -17,8 +16,9 @@ if "data" in st.session_state:
if len(data_name) >= 2 and len(data_name) <=3:
x = data[data_name].to_numpy()
dbscan = DBSCAN(eps=eps, min_samples=min_samples)
y_dbscan = dbscan.fit_predict(x)
dbscan = DBSCAN_cluster(eps,min_samples,x)
y_dbscan = dbscan.run()
st.table(dbscan.get_stats())
fig = plt.figure()
if len(data_name) == 2:
@@ -28,8 +28,5 @@ if "data" in st.session_state:
ax = fig.add_subplot(projection='3d')
ax.scatter(x[:, 0], x[:, 1],x[:, 2], c=y_dbscan, s=50, cmap="viridis")
st.pyplot(fig)
else:
st.error("file not loaded")

14
frontend/pages/clustering_kmeans.py
View File

@@ -1,10 +1,9 @@
import streamlit as st
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
from clusters import KMeans_cluster
st.header("Clustering: kmeans")
if "data" in st.session_state:
data = st.session_state.data
@@ -23,21 +22,22 @@ if "data" in st.session_state:
if len(data_name) >= 2 and len(data_name) <=3:
x = data[data_name].to_numpy()
kmeans = KMeans(n_clusters=n_clusters, init="random", n_init=n_init, max_iter=max_iter, random_state=111)
y_kmeans = kmeans.fit_predict(x)
kmeans = KMeans_cluster(n_clusters, n_init, max_iter, x)
y_kmeans = kmeans.run()
st.table(kmeans.get_stats())
centers = kmeans.centers
fig = plt.figure()
if len(data_name) == 2:
ax = fig.add_subplot(projection='rectilinear')
plt.scatter(x[:, 0], x[:, 1], c=y_kmeans, s=50, cmap="viridis")
centers = kmeans.cluster_centers_
plt.scatter(centers[:, 0], centers[:, 1], c="black", s=200, marker="X")
else:
ax = fig.add_subplot(projection='3d')
ax.scatter(x[:, 0], x[:, 1],x[:, 2], c=y_kmeans, s=50, cmap="viridis")
centers = kmeans.cluster_centers_
ax.scatter(centers[:, 0], centers[:, 1],centers[:, 2], c="black", s=200, marker="X")
ax.scatter(centers[:, 0], centers[:, 1], centers[:, 2], c="black", s=200, marker="X")
st.pyplot(fig)
else: