From ddc12c130307da58cba10f183c2c6038e90344bb Mon Sep 17 00:00:00 2001
From: Baptiste Bauvin <baptiste.bauvin.1@ulaval.ca>
Date: Sat, 21 Oct 2017 13:49:05 -0400
Subject: [PATCH] Added graphs tovizualize errors on examples
---
.../ResultAnalysis.py | 22 ++++++++++++++++++-
1 file changed, 21 insertions(+), 1 deletion(-)
diff --git a/Code/MonoMultiViewClassifiers/ResultAnalysis.py b/Code/MonoMultiViewClassifiers/ResultAnalysis.py
index c185401f..ea7e04d8 100644
--- a/Code/MonoMultiViewClassifiers/ResultAnalysis.py
+++ b/Code/MonoMultiViewClassifiers/ResultAnalysis.py
@@ -90,7 +90,7 @@ def analyzeIterLabels(labelsAnalysisList, directory, classifiersNames, minSize=1
figKW = {"figsize": (figWidth, figHeight)}
fig, ax = plt.subplots(nrows=1, ncols=1, **figKW)
data = sum(labelsAnalysisList)
- cax = plt.imshow(data, interpolation='none', cmap="grey", aspect='auto')
+ cax = plt.imshow(-data, interpolation='none', cmap="Greys", aspect='auto')
plt.title('Errors depending on the classifier')
ticks = np.arange(nbIter/2-0.5, nbClassifiers * nbIter, nbIter)
plt.xticks(ticks, classifiersNames, rotation="vertical")
@@ -99,6 +99,16 @@ def analyzeIterLabels(labelsAnalysisList, directory, classifiersNames, minSize=1
fig.tight_layout()
fig.savefig(directory + time.strftime("%Y%m%d-%H%M%S") + "-error_analysis.png")
plt.close()
+ errorOnExamples = -1 * np.sum(data, axis=1) / nbIter + (nbClassifiers*len(labelsAnalysisList))
+ np.savetxt(directory + time.strftime("%Y%m%d-%H%M%S") + "-clf_errors.csv", data, delimiter=",")
+ np.savetxt(directory + time.strftime("%Y%m%d-%H%M%S") + "-example_errors.csv", errorOnExamples, delimiter=",")
+ fig, ax = plt.subplots()
+ x = np.arange(nbExamples)
+ plt.bar(x, errorOnExamples)
+ plt.ylim([0,nbClassifiers*len(labelsAnalysisList)])
+ plt.title("Number of classifiers that failed to classify each example")
+ fig.savefig(directory + time.strftime("%Y%m%d-%H%M%S") + "-example_errors.png")
+ plt.close()
def analyzeLabels(labelsArrays, realLabels, results, directory, minSize = 10):
@@ -130,6 +140,16 @@ def analyzeLabels(labelsArrays, realLabels, results, directory, minSize = 10):
fig.tight_layout()
fig.savefig(directory + time.strftime("%Y%m%d-%H%M%S") + "-error_analysis.png")
plt.close()
+ errorOnExamples = -1*np.sum(data, axis=1)/nbIter+nbClassifiers
+ np.savetxt(directory + time.strftime("%Y%m%d-%H%M%S") + "-clf_errors.csv", data, delimiter=",")
+ np.savetxt(directory + time.strftime("%Y%m%d-%H%M%S") + "-example_errors.csv", errorOnExamples, delimiter=",")
+ fig, ax = plt.subplots()
+ x = np.arange(nbExamples)
+ plt.bar(x, errorOnExamples)
+ plt.ylim([0,nbClassifiers])
+ plt.title("Number of classifiers that failed to classify each example")
+ fig.savefig(directory + time.strftime("%Y%m%d-%H%M%S") + "-example_errors.png")
+ plt.close()
return data
--
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