diff --git a/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py b/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py
index 859c1bb72c21ceb8972862449a2072b3b373fbcc..63588616f00f5841c310c4e58eb5b09214e14151 100644
--- a/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py
+++ b/multiview_platform/MonoMultiViewClassifiers/ExecClassif.py
@@ -594,7 +594,7 @@ def execClassif(arguments):
# m, s = divmod(totalDur, 60)
# h, m = divmod(m, 60)
# d, h = divmod(h, 24)
- # # print "%d:%02d:%02d" % (h, m, s)
+ # # print "%d_%02d_%02d" % (h, m, s)
# logging.info("Info:\t Total duration : " + str(d) + " days, " + str(h) + " hours, " + str(m) + " mins, " + str(
# int(s)) + "secs.")
#
@@ -618,7 +618,7 @@ def execClassif(arguments):
# m, s = divmod(totalDur, 60)
# h, m = divmod(m, 60)
# d, h = divmod(h, 24)
- # # print "%d:%02d:%02d" % (h, m, s)
+ # # print "%d_%02d_%02d" % (h, m, s)
# logging.info("Info:\t Total duration : "+str(d)+ " days, "+str(h)+" hours, "+str(m)+" mins, "+str(int(s))+"secs.")
#
# if statsIter > 1:
diff --git a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py b/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
index cd9e4dc44990641865b5e3113e6fb9b6836f1005..a67b45a2be4b4b51745d2bec353bd77c51bdd3f9 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Monoview/ExecClassifMonoView.py
@@ -126,7 +126,7 @@ def initConstants(args, X, classificationIndices, labelsNames, name, directory):
learningRate = float(len(classificationIndices[0])) / (len(classificationIndices[0]) + len(classificationIndices[1]))
labelsString = "-".join(labelsNames)
CL_type_string = CL_type
- timestr = time.strftime("%Y_%m_%d-%H:%M:%S")
+ timestr = time.strftime("%Y_%m_%d-%H_%M_%S")
outputFileName = directory + CL_type_string + "/" + feat + "/" + timestr + "-Results-" + CL_type_string + "-" + labelsString + \
'-learnRate_{0:.2f}'.format(learningRate) + '-' + name + "-" + feat + "-"
if not os.path.exists(os.path.dirname(outputFileName)):
@@ -268,7 +268,7 @@ if __name__ == '__main__':
X, Y = Dataset.getMonoviewShared(path, name, viewName)
# Init log
- logFileName = time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + name + "-"+ viewName +"-" + classifierName +'-LOG'
+ logFileName = time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + name + "-"+ viewName +"-" + classifierName +'-LOG'
if not os.path.exists(os.path.dirname(directory + logFileName)):
try:
os.makedirs(os.path.dirname(directory + logFileName))
diff --git a/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py b/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
index bf929a2fce7fbf6458047066b4e5f7fd11cc1bf5..1f2a5d10e6ac9d176bc9e8fec1e3823fd0bd0abe 100644
--- a/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
+++ b/multiview_platform/MonoMultiViewClassifiers/Multiview/ExecMultiview.py
@@ -42,7 +42,7 @@ def saveResults(LABELS_DICTIONARY, stringAnalysis, views, classifierModule, clas
logging.info(stringAnalysis)
viewsString = "-".join(views)
labelsString = "-".join(labelsSet)
- timestr = time.strftime("%Y_%m_%d-%H:%M:%S")
+ timestr = time.strftime("%Y_%m_%d-%H_%M_%S")
CL_type_string = classifierModule.genName(classificationKWARGS)
outputFileName = directory + "/" + CL_type_string + "/" + timestr + "-Results-" + CL_type_string + "-" + viewsString + '-' + labelsString + \
'-learnRate_{0:.2f}'.format(learningRate) + '-' + name
diff --git a/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py b/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py
index 40dbd2801b22acb6130c2f248fcdec2ed3e42993..f948c9fd571ae3e8633cd66741977122cba5f025 100644
--- a/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py
+++ b/multiview_platform/MonoMultiViewClassifiers/ResultAnalysis.py
@@ -126,7 +126,7 @@ def publishMetricsGraphs(metricsScores, directory, databaseName, labelsNames):
testScores = metricScores["testScores"]
names = metricScores["classifiersNames"]
nbResults = len(testScores)
- fileName = directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-" + metricName + ".png"
+ fileName = directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-" + metricName + ".png"
plotMetricOneIter(trainScores, testScores, names, nbResults, metricName, fileName)
logging.debug("Done:\t Biclass score graph generation for " + metricName)
@@ -167,7 +167,7 @@ def publishExampleErrors(exampleErrors, directory, databaseName, labelsNames, mi
borderaxespad=0,
ncol=3)
fig.tight_layout()
- fig.savefig(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-error_analysis.png", bbox_inches="tight")
+ fig.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-error_analysis.png", bbox_inches="tight")
plt.close()
logging.debug("Done:\t Biclass Label analysis figure generation")
@@ -180,7 +180,7 @@ def publishExampleErrors(exampleErrors, directory, databaseName, labelsNames, mi
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") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-example_errors.png")
+ fig.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName +"-"+"_vs_".join(labelsNames)+ "-example_errors.png")
plt.close()
logging.debug("Done:\t Biclass Error by example figure generation")
@@ -290,7 +290,7 @@ def publishMulticlassScores(multiclassResults, metrics, statsIter, direcories, d
ax.set_xticks(np.arange(nbResults) + barWidth)
ax.set_xticklabels(names, rotation="vertical")
plt.tight_layout()
- f.savefig(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + databaseName + "-" + metric[0] + ".png")
+ f.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName + "-" + metric[0] + ".png")
plt.close()
logging.debug("Done:\t Multiclass score graph generation for " + metric[0])
@@ -326,20 +326,20 @@ def publishMulticlassExmapleErrors(multiclassResults, directories, databaseName,
green_patch = mpatches.Patch(color='green', label='Classifier succeded')
plt.legend(handles=[red_patch, green_patch], bbox_to_anchor=(0,1.02,1,0.2), loc="lower left",mode="expand", borderaxespad=0, ncol=2)
fig.tight_layout()
- fig.savefig(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + databaseName +"-error_analysis.png", bbox_inches="tight")
+ fig.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName +"-error_analysis.png", bbox_inches="tight")
plt.close()
logging.debug("Done:\t Label analysis figure generation")
logging.debug("Start:\t Error by example figure generation")
errorOnExamples = -1*np.sum(data, axis=1)/nbIter+nbClassifiers
- np.savetxt(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-clf_errors_doubled.csv", data, delimiter=",")
- np.savetxt(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-example_errors.csv", temp_data, delimiter=",")
+ np.savetxt(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-clf_errors_doubled.csv", data, delimiter=",")
+ np.savetxt(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-example_errors.csv", temp_data, 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") + "-" + databaseName +"-example_errors.png")
+ fig.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + databaseName +"-example_errors.png")
plt.close()
logging.debug("Done:\t Error by example figure generation")
@@ -451,7 +451,7 @@ def publishIterBiclassMetricsScores(iterResults, directory, labelsDictionary, cl
ax.set_xticks(np.arange(nbResults) + barWidth)
ax.set_xticklabels(names, rotation="vertical")
f.tight_layout()
- f.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + dataBaseName + "-Mean_on_"
+ f.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + dataBaseName + "-Mean_on_"
+ str(statsIter) + "_iter-" + metricName + ".png")
plt.close()
@@ -491,7 +491,7 @@ def publishIterBiclassExampleErrors(iterResults, directory, labelsDictionary, cl
cbar = fig.colorbar(cax, ticks=[-100*statsIter/2, 0, statsIter])
cbar.ax.set_yticklabels(['Unseen', 'Always Wrong', 'Always Right'])
fig.tight_layout()
- fig.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-error_analysis.png")
+ fig.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-error_analysis.png")
plt.close()
logging.debug("Done:\t Global label analysis figure generation")
@@ -504,7 +504,7 @@ def publishIterBiclassExampleErrors(iterResults, directory, labelsDictionary, cl
plt.bar(x, errorOnExamples)
plt.ylim([0,nbClassifiers*statsIter])
plt.title("Number of classifiers that failed to classify each example")
- fig.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-example_errors.png")
+ fig.savefig(currentDirectory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-example_errors.png")
plt.close()
logging.debug("Done:\t Global error by example figure generation")
@@ -542,7 +542,7 @@ def publishIterMulticlassMetricsScores(iterMulticlassResults, classifiersNames,
ax.set_xticks(np.arange(nbResults) + barWidth)
ax.set_xticklabels(names, rotation="vertical")
f.tight_layout()
- f.savefig(directory + time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + dataBaseName + "-Mean_on_"
+ f.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + dataBaseName + "-Mean_on_"
+ str(statsIter) + "_iter-" + metricName + ".png")
plt.close()
@@ -570,14 +570,14 @@ def publishIterMulticlassExampleErrors(iterMulticlassResults, directory, classif
logging.debug("Start:\t Global error by example figure generation")
errorOnExamples = -1 * np.sum(data, axis=1) + (nbClassifiers*statsIter)
- 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=",")
+ 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*statsIter])
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")
+ fig.savefig(directory + time.strftime("%Y_%m_%d-%H_%M_%S") + "-example_errors.png")
plt.close()
logging.debug("Done:\t Global error by example figure generation")
diff --git a/multiview_platform/MonoMultiViewClassifiers/utils/execution.py b/multiview_platform/MonoMultiViewClassifiers/utils/execution.py
index 3498b807683890d8f354ffe3ff426461a9c72a52..097914255da877277a6daae647e9f51947d72b5f 100644
--- a/multiview_platform/MonoMultiViewClassifiers/utils/execution.py
+++ b/multiview_platform/MonoMultiViewClassifiers/utils/execution.py
@@ -239,7 +239,7 @@ def initRandomState(randomStateArg, directory):
def initLogFile(args):
"""Used to init the directory where the preds will be stored and the log file"""
resultDirectory = "../Results/" + args.name + "/started_" + time.strftime("%Y_%m_%d-%H_%M") + "/"
- logFileName = time.strftime("%Y_%m_%d-%H:%M:%S") + "-" + ''.join(args.CL_type) + "-" + "_".join(
+ logFileName = time.strftime("%Y_%m_%d-%H_%M_%S") + "-" + ''.join(args.CL_type) + "-" + "_".join(
args.views) + "-" + args.name + "-LOG"
if not os.path.exists(os.path.dirname(resultDirectory + logFileName)):
try: