From d6eb78a905090a230db084f31cf4e6ce64066aac Mon Sep 17 00:00:00 2001
From: DIANE <abderrahim.diane@cefe.cnrs.fr>
Date: Mon, 29 Apr 2024 13:57:26 +0200
Subject: [PATCH] AFFINITY PROPAGATION
---
src/Class_Mod/Ap.py | 16 ++++++++++++++++
src/Class_Mod/__init__.py | 3 ++-
src/Modules.py | 2 +-
src/Packages.py | 3 +--
src/pages/1-samples_selection.py | 5 +++++
5 files changed, 25 insertions(+), 4 deletions(-)
create mode 100644 src/Class_Mod/Ap.py
diff --git a/src/Class_Mod/Ap.py b/src/Class_Mod/Ap.py
new file mode 100644
index 0000000..2084d25
--- /dev/null
+++ b/src/Class_Mod/Ap.py
@@ -0,0 +1,16 @@
+from Packages import *
+
+class AP:
+ def __init__(self, X):
+ ## input matrix
+ self.__x = np.array(X)
+
+ # Fit PCA model
+ self.M = AffinityPropagation(damping=0.5, max_iter=200, convergence_iter=15, copy=True, preference=None,
+ affinity='euclidean', verbose=False, random_state=None)
+ self.M.fit(self.__x)
+ self.yp = self.M.predict(self.__x)+1
+ @property
+ def fit_optimal_(self):
+ clu = [f'cluster#{i}' for i in self.yp]
+ return self.__x, clu, self.M.cluster_centers_
\ No newline at end of file
diff --git a/src/Class_Mod/__init__.py b/src/Class_Mod/__init__.py
index 7c978ea..540a093 100644
--- a/src/Class_Mod/__init__.py
+++ b/src/Class_Mod/__init__.py
@@ -13,4 +13,5 @@ from .DxReader import DxRead, read_dx
from .HDBSCAN_Clustering import Hdbscan
from .SK_PLSR_ import PlsR
from .PLSR_Preprocess import PlsProcess
-from .NMF_ import Nmf
\ No newline at end of file
+from .NMF_ import Nmf
+from .Ap import AP
\ No newline at end of file
diff --git a/src/Modules.py b/src/Modules.py
index 436e30d..6ac6f12 100644
--- a/src/Modules.py
+++ b/src/Modules.py
@@ -1,5 +1,5 @@
from Packages import *
-from Class_Mod import PlsR, LinearPCA, Umap, find_col_index, PinardPlsr, Nmf
+from Class_Mod import PlsR, LinearPCA, Umap, find_col_index, PinardPlsr, Nmf, AP
from Class_Mod import LWPLSR, list_files, metrics, TpeIpls, reg_plot, resid_plot, Sk_Kmeans, DxRead, Hdbscan, read_dx, PlsProcess
from Class_Mod.DATA_HANDLING import *
from Class_Mod.Miscellaneous import prediction, download_results, plot_spectra, local_css
diff --git a/src/Packages.py b/src/Packages.py
index fd98471..1313851 100644
--- a/src/Packages.py
+++ b/src/Packages.py
@@ -19,7 +19,7 @@ from umap.umap_ import UMAP
from sklearn.decomposition import PCA, NMF
# Clustering
-from sklearn.cluster import KMeans, HDBSCAN
+from sklearn.cluster import KMeans, HDBSCAN,AffinityPropagation
from scipy.spatial.distance import euclidean, cdist
from scipy.sparse.csgraph import minimum_spanning_tree
from scipy.sparse import csgraph
@@ -36,7 +36,6 @@ from sklearn.pipeline import Pipeline, FeatureUnion
from sklearn.compose import TransformedTargetRegressor
from sklearn.metrics import mean_absolute_error, mean_squared_error, mean_absolute_percentage_error, r2_score
from sklearn.cross_decomposition import PLSRegression
-
## Images and plots
from PIL import Image
import plotly.express as px
diff --git a/src/pages/1-samples_selection.py b/src/pages/1-samples_selection.py
index 77a8863..de03b98 100644
--- a/src/pages/1-samples_selection.py
+++ b/src/pages/1-samples_selection.py
@@ -157,6 +157,11 @@ if not t.empty:
non_clustered = np.where(labels == -1)
labels[non_clustered] = 1000
labels = labels.tolist()
+
+ elif clus_method == cluster_methods[3]:
+ cl_model = AP(X=tcr)
+ data, labels, clu_centers = cl_model.fit_optimal_
+
###### 3- Samples selection using the reduced data preentation ######
selec_strategy = ['center','random']
--
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