Update notebooks and readme with cosmetic changes

README.md

@@ -4,11 +4,21 @@
 
 Oblique Tree classifier based on SVM nodes
 
-## Example
+## Examples
 
-### Jupyter
+### Jupyter notebooks
 
-[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Doctorado-ML/STree/master?urlpath=lab/tree/test.ipynb)
+##### Slow launch but better integration
+
+* [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Doctorado-ML/STree/master?urlpath=lab/tree/test.ipynb) Test notebook
+
+##### Fast launch but have to run first commented out cell for setup
+
+* [![Test](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/test.ipynb) Test notebook
+
+* [![Test2](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/test2.ipynb) Another Test notebook
+
+* [![Test Graphics](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Doctorado-ML/STree/blob/master/test_graphs.ipynb) Test Graphics notebook
 
 ### Command line
 

test.ipynb

@@ -1,5 +1,20 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#\n",
+    "# Google Colab setup\n",
+    "#\n",
+    "#import os\n",
+    "#os.chdir(\"/content\")\n",
+    "#!git clone https://github.com/Doctorado-ML/STree.git\n",
+    "#os.chdir(\"/content/STree\")"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,

test2.ipynb

@@ -9,10 +9,10 @@
     "#\n",
     "# Google Colab setup\n",
     "#\n",
-    "#!git clone https://github.com/Doctorado-ML/STree.git\n",
-    "# Set working dir to Stree\n",
     "#import os\n",
-    "#os.chdir(\"STree\")"
+    "#os.chdir(\"/content\")\n",
+    "#!git clone https://github.com/Doctorado-ML/STree.git\n",
+    "#os.chdir(\"/content/STree\")"
    ]
   },
   {

trees/Snode_graph.py

@@ -31,12 +31,12 @@ class Snode_graph(Snode):
         return False
 
     def plot_hyperplane(self):
-        # get the splitting hyperplane
-        def hyperplane(x, y): return (-self._interceptor - self._vector[0][0] * x
-                                      - self._vector[0][1] * y) / self._vector[0][2]
         fig = plt.figure(figsize=self._plot_size)
         ax = fig.add_subplot(1, 1, 1, projection='3d')
         if not self._is_pure():
+             # get the splitting hyperplane
+            def hyperplane(x, y): return (-self._interceptor - self._vector[0][0] * x
+                                      - self._vector[0][1] * y) / self._vector[0][2]
             # Can't plot hyperplane of leaves with one label because it hasn't classiffier
             tmpx = np.linspace(self._X[:, 0].min(), self._X[:, 0].max())
             tmpy = np.linspace(self._X[:, 1].min(), self._X[:, 1].max())