From be26fcdf49183cf2b3d9c07ffb4f6e6a4f5722dd Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Tue, 18 Feb 2020 11:47:54 +0100
Subject: [PATCH] Fix the scale of the ROC plot in the LDA tutorial
---
doc/plot/iris_lda_roc.py | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/doc/plot/iris_lda_roc.py b/doc/plot/iris_lda_roc.py
index bd352e8..0c0a8aa 100644
--- a/doc/plot/iris_lda_roc.py
+++ b/doc/plot/iris_lda_roc.py
@@ -9,7 +9,7 @@ import bob.db.iris
import bob.learn.linear
import bob.measure
import numpy
-from matplotlib import pyplot
+import matplotlib.pyplot as plt
# Training is a 3-step thing
data = bob.db.iris.data()
@@ -26,8 +26,9 @@ negatives = numpy.vstack([output["setosa"], output["versicolor"]])[:, 0]
positives = output["virginica"][:, 0]
# Plot ROC curve
-bob.measure.plot.roc(negatives, positives)
-pyplot.xlabel("False Virginica Acceptance (%)")
-pyplot.ylabel("False Virginica Rejection (%)")
-pyplot.title("ROC Curve for Virginica Classification")
-pyplot.grid()
+fpr, fnr = bob.measure.roc(negatives, positives, n_points=2000)
+plt.plot(100 * fpr, 100 * fnr)
+plt.xlabel("False Virginica Acceptance (%)")
+plt.ylabel("False Virginica Rejection (%)")
+plt.title("ROC Curve for Virginica Classification")
+plt.grid()
--
GitLab