b@1402: #!/usr/bin/python
b@1402: 
b@1402: import sys
b@1402: import os
b@1402: import csv
b@1402: import matplotlib.pyplot as plt
b@1402: import numpy as np
b@1402: import scipy as sp
b@1402: import scipy.stats
b@1402: 
b@1402: # COMMAND LINE ARGUMENTS
b@1402: 
b@1402: #TODO: Merge, implement this functionality
b@1402: #TODO: Control by CLI arguments (plot types, save and/or show, ...) 
b@1402: 
b@1402: assert len(sys.argv)<4, "score_plot takes at most 2 command line arguments\n"+\
b@1402:                         "Use: python score_plot.py [ratings_folder_location]."+\
b@1402:                         "Type 'python score_plot.py -h' for more options"
b@1402: 
b@1402: # initialise plot types (false by default) and options
b@1402: enable_boxplot    = False     # show box plot
b@1402: enable_confidence = False     # show confidence interval
b@1402: confidence        = 0.90      # confidence value (for confidence interval plot)
b@1402: enable_individual = False     # show all individual ratings
b@1402: show_individual   = []        # show specific individuals (empty: show all individuals found)
b@1402: show_legend       = False     # show names of individuals
b@1402: 
b@1402: # DEFAULT: Looks in 'saves/ratings/' folder from 'scripts/' folder
b@1402: rating_folder = "../saves/ratings/" 
b@1402: 
b@1402: # XML results files location
b@1402: if len(sys.argv) == 1: # no extra arguments
b@1402:     enable_boxplot    = True # show box plot
b@1402:     print "Use: python score_plot.py [rating folder] [plot_type] [-l/-legend]"
b@1402:     print "Type 'python score_plot.py -h' for help."
b@1402:     print "Using default path: " + rating_folder + " with boxplot."
b@1402: else:
b@1402:     for arg in sys.argv: # go over all arguments
b@1402:         if arg == '-h':
b@1402:             # show help
b@1402:             #TODO: replace with contents of helpfile score_plot.info (or similar)
b@1402:             print "Use: python score_plot.py [rating_folder] [plot_type] [-l] [confidence]"
b@1402:             print "   rating_folder:"
b@1402:             print "            folder where output of 'score_parser' can be found, and"
b@1402:             print "            where plots will be stored."
b@1402:             print "            By default, '../saves/ratings/' is used."
b@1402:             print ""
b@1402:             print "PLOT TYPES"
b@1402:             print " Can be used in combination."
b@1402:             print "    box | boxplot | -b"
b@1402:             print "            Enables the boxplot" 
b@1402:             print "    conf | confidence | -c"
b@1402:             print "            Enables the confidence interval plot" 
b@1402:             print "    ind | individual | -i"
b@1402:             print "            Enables plot of individual ratings" 
b@1402:             print ""
b@1402:             print "PLOT OPTIONS"
b@1402:             print "    leg | legend | -l"
b@1402:             print "            For individual plot: show legend with individual file names"
b@1402:             print "    numeric value between 0 and 1, e.g. 0.95"
b@1402:             print "            For confidence interval plot: confidence value"
b@1402:             assert False, ""# stop immediately after showing help #TODO cleaner way
b@1402:             
b@1402:         # PLOT TYPES
b@1402:         elif arg == 'box' or arg == 'boxplot' or arg == '-b':
b@1402:             enable_boxplot    = True     # show box plot
b@1402:         elif arg == 'conf' or arg == 'confidence' or arg == '-c':
b@1402:             enable_confidence = True     # show confidence interval
b@1402:             #TODO add confidence value input
b@1402:         elif arg == 'ind' or arg == 'individual' or arg == '-i':
b@1402:             enable_individual = True     # show all individual ratings
b@1402:             
b@1402:         # PLOT OPTIONS
b@1402:         elif arg == 'leg' or arg == 'legend' or arg == '-l':
b@1402:             if not enable_individual: 
b@1402:                 print "WARNING: The 'legend' option is only relevant to plots of "+\
b@1402:                       "individual ratings"
b@1402:             show_legend = True     # show all individual ratings
b@1402:         elif arg.isdigit():
b@1402:             if not enable_confidence: 
b@1402:                 print "WARNING: The numeric confidence value is only relevant when "+\
b@1402:                       "confidence plot is enabled"
b@1402:             if float(arg)>0 and float(arg)<1:
b@1402:                 confidence = float(arg)
b@1402:             else: 
b@1402:                 print "WARNING: The confidence value needs to be between 0 and 1"
b@1402:         
b@1402:         # FOLDER NAME
b@1402:         else: 
b@1402:              # assume it's the folder name
b@1402:              rating_folder = arg
b@1402: 
b@1402: # at least one plot type should be selected: box plot by default
b@1402: if not enable_boxplot and not enable_confidence and not enable_individual:
b@1402:     enable_boxplot = True
b@1402: 
b@1402: # check if folder_name exists
b@1402: if not os.path.exists(rating_folder):
b@1402:     #the file is not there
b@1402:     print "Folder '"+rating_folder+"' does not exist."
b@1402:     sys.exit() # terminate script execution
b@1402: elif not os.access(os.path.dirname(rating_folder), os.W_OK):
b@1402:     #the file does exist but write rating_folder are not given
b@1402:     print "No write privileges in folder '"+rating_folder+"'."
b@1402: 
b@1402: 
b@1402: # CONFIGURATION
b@1402: 
b@1402: # Font settings
b@1402: font = {'weight' : 'bold',
b@1402:         'size'   : 10}
b@1402: plt.rc('font', **font)
b@1402: 
b@1402: 
b@1402: # CODE
b@1402: 
b@1402: # get every csv file in folder
b@1402: for file in os.listdir(rating_folder): # You have to put this in folder where rating csv files are.
b@1402:     if file.endswith(".csv"):
b@1402:         page_name = file[:-4] # file name (without extension) is page ID
b@1402: 
b@1402:         # get header
b@1402:         with open(rating_folder+file, 'rb') as readfile: # read this csv file
b@1402:             filereader = csv.reader(readfile, delimiter=',')
b@1402:             headerrow = filereader.next() # use headerrow as X-axis
b@1402:             headerrow = headerrow[1:]
b@1402: 
b@1402:         # read ratings into matrix
b@1402: #         ratings = np.loadtxt(open(rating_folder+file,"rb"),
b@1402: #                             delimiter=",",
b@1402: #                             skiprows=1,
b@1402: #                             usecols=range(1,len(headerrow)+1)
b@1402: #                             )
b@1402:             ratings = np.genfromtxt(readfile,
b@1402:                                    delimiter=",",
b@1402:                                    #skip_header = 1,
b@1402:                                    converters = {3: lambda s: float(s or 'Nan')},
b@1402:                                    usecols=range(1,len(headerrow)+1)
b@1402:                                    )
b@1402:         
b@1402:         # assert at least 2 subjects (move on to next file if violated)
b@1402:         if ratings.shape[0]<2:
b@1402:             print "WARNING: Just one subject for " + page_name + ". Moving on to next file."
b@1402:             break
b@1402: 
b@1402:         # BOXPLOT
b@1402:         if enable_boxplot:
b@1402:             plt.boxplot(ratings)
b@1402:             
b@1402:         # CONFIDENCE INTERVAL
b@1402:         if enable_confidence:
b@1402:             iterator = 0
b@1402:             for column in ratings.T: # iterate over transposed matrix
b@1402:                 # remove all 'Nan's from column
b@1402:                 column = column[~np.isnan(column)]
b@1402:             
b@1402:                 # get number of non-Nan ratings (= #subjects)
b@1402:                 n = column.size
b@1402:         
b@1402:                 # get mean
b@1402:                 mean_rating = np.mean(column)
b@1402:         
b@1402:                 # get errors
b@1402:                 err = scipy.stats.sem(column)* sp.stats.t._ppf((1+confidence)/2., n-1)
b@1402:         
b@1402:                 # draw plot
b@1402:                 plt.errorbar(iterator+1, 
b@1402:                             mean_rating, 
b@1402:                             yerr=err,
b@1402:                             marker="x",
b@1402:                             color ="k",
b@1402:                             markersize=12,
b@1402:                             linestyle='None')
b@1402:                             
b@1402:                 iterator += 1 # increase counter
b@1402:     
b@1402:     
b@1402:         # INDIVIDUAL PLOT
b@1402:         if enable_individual or show_individual:
b@1402:             # marker list and color map to cycle through
b@1402:             markerlist = ["x", ".", "o", "*", "+", "v", ">", "<", "8", "s", "p"]
b@1402:             colormap = ['b', 'r', 'g', 'c', 'm', 'y', 'k'] 
b@1402:             increment = 0
b@1402:             linehandles = []
b@1402:             legendnames = []
b@1402:             with open(rating_folder+file, 'rb') as readfile: # read this csv file
b@1402:                 filereader = csv.reader(readfile, delimiter=',')
b@1402:                 headerrow = filereader.next() # use headerrow as X-axis
b@1402:                 headerrow = headerrow[1:]
b@1402:                 for row in filereader:
b@1402:                     subject_id = row[0][:-4] # read from beginning of line
b@1402:                     # assume plotting all individuals if no individual(s) specified
b@1402:                     if not show_individual or subject_id in show_individual:
b@1402:                         plothandle, = plt.plot(range(1,len(row)), # x-values
b@1402:                                  ratings[increment,:],#row[1:], # y-values: csv values except subject name
b@1402:                                  color=colormap[increment%len(colormap)],
b@1402:                                  marker=markerlist[increment%len(markerlist)],
b@1402:                                  markersize=10,
b@1402:                                  linestyle='None',
b@1402:                                  label=subject_id
b@1402:                                 )
b@1402:                         linehandles.append(plothandle)
b@1402:                         legendnames.append(subject_id)
b@1402:                         if show_legend:
b@1402:                             plt.legend(linehandles, legendnames,
b@1402:                                        loc='upper right',
b@1402:                                        bbox_to_anchor=(1.1, 1),
b@1402:                                        borderaxespad=0.,
b@1402:                                        numpoints=1 # remove extra marker
b@1402:                                        )
b@1402:                     increment += 1 # increase counter
b@1402: 
b@1402:         # TITLE, AXIS LABELS AND LIMITS
b@1402:         plt.title(page_name)
b@1402:         plt.xlabel('Fragment')
b@1402:         plt.xlim(0, len(headerrow)+1) # only show relevant region, leave space left & right)
b@1402:         plt.xticks(range(1, len(headerrow)+1), headerrow, rotation=90) # show fragment names
b@1402:         plt.ylabel('Rating')
b@1402:         plt.ylim(0,1)
b@1402:         
b@1402:         
b@1402: 
b@1402:         # SHOW PLOT
b@1402:         #plt.show()
b@1402:         #exit()
b@1402:     
b@1402:         # SAVE PLOT
b@1402:         # automatically 
b@1402:         plot_type = ("-box" if enable_boxplot else "") + \
b@1402:                     ("-conf" if enable_confidence else "") + \
b@1402:                     ("-ind" if enable_individual else "")
b@1402:         plt.savefig(rating_folder+page_name+plot_type+".pdf", bbox_inches='tight')
b@1402:         plt.close()