From 602579c4f3886544f13306b3dd0a19adbaeae88d Mon Sep 17 00:00:00 2001
From: Andre Anjos <andre.dos.anjos@gmail.com>
Date: Tue, 18 Feb 2014 13:20:49 +0100
Subject: [PATCH] Inline plotting code
---
doc/guide.rst | 60 ++++++++++++++++++++++++++++++++++++--------
doc/plot/perf_det.py | 20 ---------------
doc/plot/perf_epc.py | 18 -------------
doc/plot/perf_roc.py | 18 -------------
4 files changed, 49 insertions(+), 67 deletions(-)
delete mode 100644 doc/plot/perf_det.py
delete mode 100644 doc/plot/perf_epc.py
delete mode 100644 doc/plot/perf_roc.py
diff --git a/doc/guide.rst b/doc/guide.rst
index 0a1d16c..0bbb982 100644
--- a/doc/guide.rst
+++ b/doc/guide.rst
@@ -185,8 +185,20 @@ town. To plot an ROC curve, in possession of your **negatives** and
You should see an image like the following one:
-.. plot:: plot/perf_roc.py
- :include-source: False
+.. plot::
+
+ import numpy
+ import xbob.measure
+ from matplotlib import pyplot
+
+ positives = numpy.random.normal(1,1,100)
+ negatives = numpy.random.normal(-1,1,100)
+ npoints = 100
+ xbob.measure.plot.roc(negatives, positives, npoints, color=(0,0,0), linestyle='-', label='test')
+ pyplot.grid(True)
+ pyplot.xlabel('FAR (%)')
+ pyplot.ylabel('FRR (%)')
+ pyplot.title('ROC')
As can be observed, plotting methods live in the namespace
:py:mod:`xbob.measure.plot`. They work like `Matplotlib`_'s `plot()`_ method
@@ -221,8 +233,22 @@ A DET curve can be drawn using similar commands such as the ones for the ROC cur
This will produce an image like the following one:
-.. plot:: plot/perf_det.py
- :include-source: False
+.. plot::
+
+ import numpy
+ import xbob.measure
+ from matplotlib import pyplot
+
+ positives = numpy.random.normal(1,1,100)
+ negatives = numpy.random.normal(-1,1,100)
+
+ npoints = 100
+ xbob.measure.plot.det(negatives, positives, npoints, color=(0,0,0), linestyle='-', label='test')
+ xbob.measure.plot.det_axis([0.1, 80, 0.1, 80])
+ pyplot.grid(True)
+ pyplot.xlabel('FAR (%)')
+ pyplot.ylabel('FRR (%)')
+ pyplot.title('DET')
.. note::
@@ -257,8 +283,20 @@ the test (or evaluation) set ones. Because of this the API is slightly modified:
This will produce an image like the following one:
-.. plot:: plot/perf_epc.py
- :include-source: False
+.. plot::
+
+ import numpy
+ import xbob.measure
+ from matplotlib import pyplot
+
+ dev_pos = numpy.random.normal(1,1,100)
+ dev_neg = numpy.random.normal(-1,1,100)
+ test_pos = numpy.random.normal(0.9,1,100)
+ test_neg = numpy.random.normal(-1.1,1,100)
+ npoints = 100
+ xbob.measure.plot.epc(dev_neg, dev_pos, test_neg, test_pos, npoints, color=(0,0,0), linestyle='-')
+ pyplot.grid(True)
+ pyplot.title('EPC')
Fine-tunning
============
@@ -285,7 +323,7 @@ Error Rate) on a set, after setting up |project|, just do:
.. code-block:: sh
- $ bob_eval_threshold.py --scores=development-scores-4col.txt
+ $ xbob_eval_threshold.py --scores=development-scores-4col.txt
Threshold: -0.004787956164
FAR : 6.731% (35/520)
FRR : 6.667% (26/390)
@@ -296,22 +334,22 @@ the given set, calculated using such a threshold. The relative counts of FAs
and FRs are also displayed between parenthesis.
To evaluate the performance of a new score file with a given threshold, use the
-application ``bob_apply_threshold.py``:
+application ``xbob_apply_threshold.py``:
.. code-block:: sh
- $ bob_apply_threshold.py --scores=test-scores-4col.txt --threshold=-0.0047879
+ $ xbob_apply_threshold.py --scores=test-scores-4col.txt --threshold=-0.0047879
FAR : 2.115% (11/520)
FRR : 7.179% (28/390)
HTER: 4.647%
In this case, only the error figures are presented. You can conduct the
evaluation and plotting of development and test set data using our combined
-``bob_compute_perf.py`` script. You pass both sets and it does the rest:
+``xbob_compute_perf.py`` script. You pass both sets and it does the rest:
.. code-block:: sh
- $ bob_compute_perf.py --devel=development-scores-4col.txt --test=test-scores-4col.txt
+ $ xbob_compute_perf.py --devel=development-scores-4col.txt --test=test-scores-4col.txt
[Min. criterium: EER] Threshold on Development set: -4.787956e-03
| Development | Test
-------+-----------------+------------------
diff --git a/doc/plot/perf_det.py b/doc/plot/perf_det.py
deleted file mode 100644
index bbbde45..0000000
--- a/doc/plot/perf_det.py
+++ /dev/null
@@ -1,20 +0,0 @@
-#!/usr/bin/env python
-# vim: set fileencoding=utf-8 :
-
-"""Tutorial for plotting a DET curve
-"""
-
-import numpy
-import xbob.measure
-from matplotlib import pyplot
-
-positives = numpy.random.normal(1,1,100)
-negatives = numpy.random.normal(-1,1,100)
-
-npoints = 100
-xbob.measure.plot.det(negatives, positives, npoints, color=(0,0,0), linestyle='-', label='test')
-xbob.measure.plot.det_axis([0.1, 80, 0.1, 80])
-pyplot.grid(True)
-pyplot.xlabel('FAR (%)')
-pyplot.ylabel('FRR (%)')
-pyplot.title('DET')
diff --git a/doc/plot/perf_epc.py b/doc/plot/perf_epc.py
deleted file mode 100644
index ed2bbc3..0000000
--- a/doc/plot/perf_epc.py
+++ /dev/null
@@ -1,18 +0,0 @@
-#!/usr/bin/env python
-# vim: set fileencoding=utf-8 :
-
-"""Tutorial for plotting an EPC curve
-"""
-
-import numpy
-import xbob.measure
-from matplotlib import pyplot
-
-dev_pos = numpy.random.normal(1,1,100)
-dev_neg = numpy.random.normal(-1,1,100)
-test_pos = numpy.random.normal(0.9,1,100)
-test_neg = numpy.random.normal(-1.1,1,100)
-npoints = 100
-xbob.measure.plot.epc(dev_neg, dev_pos, test_neg, test_pos, npoints, color=(0,0,0), linestyle='-')
-pyplot.grid(True)
-pyplot.title('EPC')
diff --git a/doc/plot/perf_roc.py b/doc/plot/perf_roc.py
deleted file mode 100644
index 371092e..0000000
--- a/doc/plot/perf_roc.py
+++ /dev/null
@@ -1,18 +0,0 @@
-#!/usr/bin/env python
-# vim: set fileencoding=utf-8 :
-
-"""Tutorial for plotting a ROC curve
-"""
-
-import numpy
-import xbob.measure
-from matplotlib import pyplot
-
-positives = numpy.random.normal(1,1,100)
-negatives = numpy.random.normal(-1,1,100)
-npoints = 100
-xbob.measure.plot.roc(negatives, positives, npoints, color=(0,0,0), linestyle='-', label='test')
-pyplot.grid(True)
-pyplot.xlabel('FAR (%)')
-pyplot.ylabel('FRR (%)')
-pyplot.title('ROC')
--
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