Replaced : with _in names

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:

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))

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

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")
 

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: