repositories / TP_AA.git / blame
| Commit | Line | Data |
|---|---|---|
| ecf19406 JB |
1 | #!/usr/bin/env python3 |
| 2 | ||
| 3 | # -*- coding: utf-8 -*- | |
| 4 | import pylab as pl | |
| 5 | ||
| 6 | from sklearn.datasets import load_iris | |
| 7 | irisData = load_iris() | |
| 8 | ||
| 9 | X = irisData.data | |
| 10 | Y = irisData.target | |
| 11 | ||
| 5b0cb811 JB |
12 | colors = ["red", "green", "blue"] |
| 13 | ||
| ecf19406 JB |
14 | x = 0 |
| 15 | y = 1 | |
| 5b0cb811 JB |
16 | for i in range(3): |
| 17 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 18 | label=irisData.target_names[i]) | |
| 19 | pl.legend() | |
| 20 | pl.xlabel(irisData.feature_names[x]) | |
| 21 | pl.ylabel(irisData.feature_names[y]) | |
| 22 | pl.title(u"Données Iris - dimension des sépales uniquement") | |
| 23 | pl.show() | |
| ecf19406 | 24 | |
| 5b0cb811 JB |
25 | x = 2 |
| 26 | y = 3 | |
| 27 | for i in range(3): | |
| 28 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 29 | label=irisData.target_names[i]) | |
| 30 | pl.legend() | |
| 31 | pl.xlabel(irisData.feature_names[x]) | |
| 32 | pl.ylabel(irisData.feature_names[y]) | |
| 33 | pl.title(u"Données Iris - dimension des pétales uniquement") | |
| 34 | pl.show() | |
| 35 | ||
| 36 | x = 0 | |
| 37 | y = 3 | |
| 38 | for i in range(3): | |
| 39 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 40 | label=irisData.target_names[i]) | |
| 41 | pl.legend() | |
| 42 | pl.xlabel(irisData.feature_names[x]) | |
| 43 | pl.ylabel(irisData.feature_names[y]) | |
| 44 | pl.title(u"Données Iris - dimension des sépales et pétales") | |
| 45 | pl.show() | |
| 46 | ||
| 47 | x = 1 | |
| 48 | y = 2 | |
| 49 | for i in range(3): | |
| 50 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 51 | label=irisData.target_names[i]) | |
| 52 | pl.legend() | |
| 53 | pl.xlabel(irisData.feature_names[x]) | |
| 54 | pl.ylabel(irisData.feature_names[y]) | |
| 55 | pl.title(u"Données Iris - dimension des sépales et pétales") | |
| 56 | pl.show() | |
| ecf19406 | 57 | |
| 5b0cb811 JB |
58 | x = 0 |
| 59 | y = 2 | |
| ecf19406 JB |
60 | for i in range(3): |
| 61 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 62 | label=irisData.target_names[i]) | |
| 5b0cb811 JB |
63 | pl.legend() |
| 64 | pl.xlabel(irisData.feature_names[x]) | |
| 65 | pl.ylabel(irisData.feature_names[y]) | |
| 66 | pl.title(u"Données Iris - dimension des sépales et pétales") | |
| 67 | pl.show() | |
| ecf19406 | 68 | |
| 5b0cb811 JB |
69 | x = 1 |
| 70 | y = 3 | |
| 71 | for i in range(3): | |
| 72 | pl.scatter(X[Y == i][:, x], X[Y == i][:, y], color=colors[i], | |
| 73 | label=irisData.target_names[i]) | |
| ecf19406 JB |
74 | pl.legend() |
| 75 | pl.xlabel(irisData.feature_names[x]) | |
| 76 | pl.ylabel(irisData.feature_names[y]) | |
| 5b0cb811 | 77 | pl.title(u"Données Iris - dimension des sépales et pétales") |
| ecf19406 | 78 | pl.show() |