docs: update examples

f-aguzzi · Jun 4, 2024 · c919596 · c919596
1 parent 57a3497
commit c919596
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Showing 5 changed files with 17 additions and 15 deletions.
diff --git a/examples/knn_notebook.ipynb b/examples/knn_notebook.ipynb
@@ -50,12 +50,12 @@
     "# Perform preliminary data fusion\n",
     "lldf_settings = LLDFSettings(output=GraphMode.NONE)\n",
     "qepas_table = Table(\n",
-    "    file_path=\"tests/qepas.xlsx\",\n",
+    "    file_path=\"qepas.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"snv\"\n",
     ")\n",
     "rt_table = Table(\n",
-    "    file_path=\"tests/rt.xlsx\",\n",
+    "    file_path=\"rt.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"none\"\n",
     ")\n",
@@ -3366,7 +3366,7 @@
     ")\n",
     "\n",
     "# Initialize and run the PCA class\n",
-    "knn = KNN(fused_data=lldf.fused_data, settings=knn_settings)\n",
+    "knn = KNN(settings=knn_settings, data=lldf.fused_data)\n",
     "knn.knn()"
    ]
   },

diff --git a/examples/pca_lda_notebook.ipynb b/examples/pca_lda_notebook.ipynb
@@ -50,12 +50,12 @@
     "# Perform preliminary data fusion\n",
     "lldf_settings = LLDFSettings(output=GraphMode.NONE)\n",
     "qepas_table = Table(\n",
-    "    file_path=\"tests/qepas.xlsx\",\n",
+    "    file_path=\"qepas.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"snv\"\n",
     ")\n",
     "rt_table = Table(\n",
-    "    file_path=\"tests/rt.xlsx\",\n",
+    "    file_path=\"rt.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"none\"\n",
     ")\n",
@@ -107,7 +107,7 @@
     ")\n",
     "\n",
     "# Initialize and run the PCA class\n",
-    "pca = PCA(lldf.fused_data, pca_settings)\n",
+    "pca = PCA(pca_settings, lldf.fused_data)\n",
     "pca.pca()\n",
     "\n",
     "# Print the number of components and the statistics\n",
@@ -140,7 +140,7 @@
     ")\n",
     "\n",
     "# Initialize and run the LDA class\n",
-    "lda = LDA(lldf.fused_data, settings)\n",
+    "lda = LDA(settings, lldf.fused_data)\n",
     "lda.lda()"
    ]
   },

diff --git a/examples/pca_lr_notebook.ipynb b/examples/pca_lr_notebook.ipynb
@@ -50,12 +50,12 @@
     "# Perform preliminary data fusion\n",
     "lldf_settings = LLDFSettings(output=GraphMode.NONE)\n",
     "qepas_table = Table(\n",
-    "    file_path=\"tests/qepas.xlsx\",\n",
+    "    file_path=\"qepas.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"snv\"\n",
     ")\n",
     "rt_table = Table(\n",
-    "    file_path=\"tests/rt.xlsx\",\n",
+    "    file_path=\"rt.xlsx\",\n",
     "    sheet_name=\"Sheet1\",\n",
     "    preprocessing=\"none\"\n",
     ")\n",
@@ -25531,12 +25531,15 @@
     ")\n",
     "\n",
     "# Initialize and run the PCA class\n",
-    "pca = PCA(lldf.fused_data, pca_settings)\n",
+    "pca = PCA(pca_settings, lldf.fused_data)\n",
     "pca.pca()\n",
     "\n",
     "# Print the number of components and the statistics\n",
     "print(f\"\\nNumber of components: {pca.components}\\n\")\n",
-    "pca.pca_stats()"
+    "pca.pca_stats()\n",
+    "\n",
+    "# Get the data out of PCA\n",
+    "pca_data = pca.export_data()"
    ]
   },
   {
@@ -50065,8 +50068,7 @@
     "# Initialize and run the LDA class\n",
     "lr = LR(\n",
     "    settings=settings,\n",
-    "    array_scores=pca.array_scores,  # use the data from PCA\n",
-    "    y=lldf.fused_data.y\n",
+    "    data=pca_data   # use the data from PCA\n",
     ")\n",
     "lr.lr()"
    ]

diff --git a/examples/plsda_notebook.ipynb b/examples/plsda_notebook.ipynb
@@ -18114,7 +18114,7 @@
     ")\n",
     "\n",
     "# Initialize and run the PLSDA class\n",
-    "plsda = PLSDA(fused_data=lldf.fused_data, settings=plsda_settings)\n",
+    "plsda = PLSDA(settings=plsda_settings, data=lldf.fused_data)\n",
     "plsda.plsda()"
    ]
   },

diff --git a/examples/svm_notebook.ipynb b/examples/svm_notebook.ipynb
@@ -2090,7 +2090,7 @@
     ")\n",
     "\n",
     "# Initialize and run the SVM class\n",
-    "svm = SVM(fused_data=lldf.fused_data, settings=svm_settings)\n",
+    "svm = SVM(settings=svm_settings, data=lldf.fused_data)\n",
     "svm.svm()"
    ]
   },