comparison scripts/score_plot.py @ 1316:279930a008ca

All interfaces support comment boxes. Comment box identification matches presented tag (for instance, AB will be Comment on fragment A, rather than 1). Tighter buffer loading protocol, audioObjects register with the buffer rather than checking for buffer existence (which can be buggy depending on the buffer state). Buffers now have a state to ensure exact location in loading chain (downloading, decoding, LUFS, ready).

+#!/usr/bin/python
+
+import sys
+import os
+import csv
+import matplotlib.pyplot as plt
+import numpy as np
+import scipy as sp
+import scipy.stats
+
+# COMMAND LINE ARGUMENTS
+
+#TODO: Merge, implement this functionality
+#TODO: Control by CLI arguments (plot types, save and/or show, ...) 
+
+assert len(sys.argv)<4, "score_plot takes at most 2 command line arguments\n"+\
+                        "Use: python score_plot.py [ratings_folder_location]."+\
+                        "Type 'python score_plot.py -h' for more options"
+
+# initialise plot types (false by default) and options
+enable_boxplot    = False     # show box plot
+enable_confidence = False     # show confidence interval
+confidence        = 0.90      # confidence value (for confidence interval plot)
+enable_individual = False     # show all individual ratings
+show_individual   = []        # show specific individuals (empty: show all individuals found)
+show_legend       = False     # show names of individuals
+
+# DEFAULT: Looks in 'saves/ratings/' folder from 'scripts/' folder
+rating_folder = "../saves/ratings/" 
+
+# XML results files location
+if len(sys.argv) == 1: # no extra arguments
+    enable_boxplot    = True # show box plot
+    print "Use: python score_plot.py [rating folder] [plot_type] [-l/-legend]"
+    print "Type 'python score_plot.py -h' for help."
+    print "Using default path: " + rating_folder + " with boxplot."
+else:
+    for arg in sys.argv: # go over all arguments
+        if arg == '-h':
+            # show help
+            #TODO: replace with contents of helpfile score_plot.info (or similar)
+            print "Use: python score_plot.py [rating_folder] [plot_type] [-l] [confidence]"
+            print "   rating_folder:"
+            print "            folder where output of 'score_parser' can be found, and"
+            print "            where plots will be stored."
+            print "            By default, '../saves/ratings/' is used."
+            print ""
+            print "PLOT TYPES"
+            print " Can be used in combination."
+            print "    box | boxplot | -b"
+            print "            Enables the boxplot" 
+            print "    conf | confidence | -c"
+            print "            Enables the confidence interval plot" 
+            print "    ind | individual | -i"
+            print "            Enables plot of individual ratings" 
+            print ""
+            print "PLOT OPTIONS"
+            print "    leg | legend | -l"
+            print "            For individual plot: show legend with individual file names"
+            print "    numeric value between 0 and 1, e.g. 0.95"
+            print "            For confidence interval plot: confidence value"
+            assert False, ""# stop immediately after showing help #TODO cleaner way
+            
+        # PLOT TYPES
+        elif arg == 'box' or arg == 'boxplot' or arg == '-b':
+            enable_boxplot    = True     # show box plot
+        elif arg == 'conf' or arg == 'confidence' or arg == '-c':
+            enable_confidence = True     # show confidence interval
+            #TODO add confidence value input
+        elif arg == 'ind' or arg == 'individual' or arg == '-i':
+            enable_individual = True     # show all individual ratings
+            
+        # PLOT OPTIONS
+        elif arg == 'leg' or arg == 'legend' or arg == '-l':
+            if not enable_individual: 
+                print "WARNING: The 'legend' option is only relevant to plots of "+\
+                      "individual ratings"
+            show_legend = True     # show all individual ratings
+        elif arg.isdigit():
+            if not enable_confidence: 
+                print "WARNING: The numeric confidence value is only relevant when "+\
+                      "confidence plot is enabled"
+            if float(arg)>0 and float(arg)<1:
+                confidence = float(arg)
+            else: 
+                print "WARNING: The confidence value needs to be between 0 and 1"
+        
+        # FOLDER NAME
+        else: 
+             # assume it's the folder name
+             rating_folder = arg
+
+# at least one plot type should be selected: box plot by default
+if not enable_boxplot and not enable_confidence and not enable_individual:
+    enable_boxplot = True
+
+# check if folder_name exists
+if not os.path.exists(rating_folder):
+    #the file is not there
+    print "Folder '"+rating_folder+"' does not exist."
+    sys.exit() # terminate script execution
+elif not os.access(os.path.dirname(rating_folder), os.W_OK):
+    #the file does exist but write rating_folder are not given
+    print "No write privileges in folder '"+rating_folder+"'."
+
+
+# CONFIGURATION
+
+# Font settings
+font = {'weight' : 'bold',
+        'size'   : 10}
+plt.rc('font', **font)
+
+
+# CODE
+
+# get every csv file in folder
+for file in os.listdir(rating_folder):
+    if file.endswith(".csv"):
+        page_name = file[:-4] # file name (without extension) is page ID
+
+        # get header
+        with open(rating_folder+file, 'rb') as readfile: # read this csv file
+            filereader = csv.reader(readfile, delimiter=',')
+            headerrow = filereader.next() # use headerrow as X-axis
+            headerrow = headerrow[1:]
+
+        # read ratings into matrix
+#         ratings = np.loadtxt(open(rating_folder+file,"rb"),
+#                             delimiter=",",
+#                             skiprows=1,
+#                             usecols=range(1,len(headerrow)+1)
+#                             )
+            ratings = np.genfromtxt(readfile,
+                                   delimiter=",",
+                                   #skip_header = 1,
+                                   converters = {3: lambda s: float(s or 'Nan')},
+                                   usecols=range(1,len(headerrow)+1)
+                                   )
+        
+        # assert at least 2 subjects (move on to next file if violated)
+        if ratings.shape[0]<2:
+            print "WARNING: Just one subject for " + page_name + ". Moving on to next file."
+            break
+
+        # BOXPLOT
+        if enable_boxplot:
+            plt.boxplot(ratings)
+            
+        # CONFIDENCE INTERVAL
+        if enable_confidence:
+            iterator = 0
+            for column in ratings.T: # iterate over transposed matrix
+                # remove all 'Nan's from column
+                column = column[~np.isnan(column)]
+            
+                # get number of non-Nan ratings (= #subjects)
+                n = column.size
+        
+                # get mean
+                mean_rating = np.mean(column)
+        
+                # get errors
+                err = scipy.stats.sem(column)* sp.stats.t._ppf((1+confidence)/2., n-1)
+        
+                # draw plot
+                plt.errorbar(iterator+1, 
+                            mean_rating, 
+                            yerr=err,
+                            marker="x",
+                            color ="k",
+                            markersize=12,
+                            linestyle='None')
+                            
+                iterator += 1 # increase counter
+    
+    
+        # INDIVIDUAL PLOT
+        if enable_individual or show_individual:
+            # marker list and color map to cycle through
+            markerlist = ["x", ".", "o", "*", "+", "v", ">", "<", "8", "s", "p"]
+            colormap = ['b', 'r', 'g', 'c', 'm', 'y', 'k'] 
+            increment = 0
+            linehandles = []
+            legendnames = []
+            with open(rating_folder+file, 'rb') as readfile: # read this csv file
+                filereader = csv.reader(readfile, delimiter=',')
+                headerrow = filereader.next() # use headerrow as X-axis
+                headerrow = headerrow[1:]
+                for row in filereader:
+                    subject_id = row[0][:-4] # read from beginning of line
+                    # assume plotting all individuals if no individual(s) specified
+                    if not show_individual or subject_id in show_individual:
+                        plothandle, = plt.plot(range(1,len(row)), # x-values
+                                 ratings[increment,:],#row[1:], # y-values: csv values except subject name
+                                 color=colormap[increment%len(colormap)],
+                                 marker=markerlist[increment%len(markerlist)],
+                                 markersize=10,
+                                 linestyle='None',
+                                 label=subject_id
+                                )
+                        linehandles.append(plothandle)
+                        legendnames.append(subject_id)
+                        if show_legend:
+                            plt.legend(linehandles, legendnames,
+                                       loc='upper right',
+                                       bbox_to_anchor=(1.1, 1),
+                                       borderaxespad=0.,
+                                       numpoints=1 # remove extra marker
+                                       )
+                    increment += 1 # increase counter
+
+        # TITLE, AXIS LABELS AND LIMITS
+        plt.title(page_name)
+        plt.xlabel('Fragment')
+        plt.xlim(0, len(headerrow)+1) # only show relevant region, leave space left & right)
+        plt.xticks(range(1, len(headerrow)+1), headerrow, rotation=90) # show fragment names
+        plt.ylabel('Rating')
+        plt.ylim(0,1)
+        
+        
+
+        # SHOW PLOT
+        #plt.show()
+        #exit()
+    
+        # SAVE PLOT
+        # automatically 
+        plot_type = ("-box" if enable_boxplot else "") + \
+                    ("-conf" if enable_confidence else "") + \
+                    ("-ind" if enable_individual else "")
+        plt.savefig(rating_folder+page_name+plot_type+".pdf", bbox_inches='tight')
+        plt.close()