b@1554: #!/usr/bin/python
b@1554: 
b@1554: import sys
b@1554: import os
b@1554: import csv
b@1554: import matplotlib.pyplot as plt
b@1554: import numpy as np
b@1554: import scipy as sp
b@1554: import scipy.stats
b@1554: 
b@1554: # CONFIGURATION
b@1554: 
b@1554: # Which type(s) of plot do you want? 
b@1554: enable_boxplot    = False     # show box plot
b@1554: enable_confidence = True      # show confidence interval
b@1554: confidence        = 0.90      # confidence value (for confidence interval plot)
b@1554: enable_individual = True      # show all individual ratings
b@1554: show_individual   = []        # show specific individuals
b@1554: show_legend       = False     # show names of individuals
b@1554: #TODO: Merge, implement this functionality
b@1554: #TODO: Control by CLI arguments (plot types, save and/or show, ...) 
b@1554: 
b@1554: # Enter folder where rating CSV files are (generated with score_parser.py or same format).
b@1554: rating_folder = '../saves/ratings/' # folder with rating csv files
b@1554: 
b@1554: # Font settings
b@1554: font = {'weight' : 'bold',
b@1554:         'size'   : 10}
b@1554: plt.rc('font', **font)
b@1554: 
b@1554: 
b@1554: # CODE
b@1554: 
b@1554: # get every csv file in folder
b@1554: for file in os.listdir(rating_folder): # You have to put this in folder where rating csv files are.
b@1554:     if file.endswith(".csv"):
b@1554:         page_name = file[:-4] # file name (without extension) is page ID
b@1554: 
b@1554:         # get header
b@1554:         with open(rating_folder+file, 'rb') as readfile: # read this csv file
b@1554:             filereader = csv.reader(readfile, delimiter=',')
b@1554:             headerrow = filereader.next() # use headerrow as X-axis
b@1554:             headerrow = headerrow[1:]
b@1554: 
b@1554:         # read ratings into matrix
b@1554: #         ratings = np.loadtxt(open(rating_folder+file,"rb"),
b@1554: #                             delimiter=",",
b@1554: #                             skiprows=1,
b@1554: #                             usecols=range(1,len(headerrow)+1)
b@1554: #                             )
b@1554:             ratings = np.genfromtxt(readfile,
b@1554:                                    delimiter=",",
b@1554:                                    #skip_header = 1,
b@1554:                                    converters = {3: lambda s: float(s or 'Nan')},
b@1554:                                    usecols=range(1,len(headerrow)+1)
b@1554:                                    )
b@1554:         
b@1554:         # assert at least 2 subjects (move on to next file if violated)
b@1554:         if ratings.shape[1]<2:
b@1554:             print "WARNING: Just one subject for " + page_name + ". Moving on to next file."
b@1554:             break
b@1554: 
b@1554:         # BOXPLOT
b@1554:         if enable_boxplot:
b@1554:             plt.boxplot(ratings)
b@1554:             
b@1554:         # CONFIDENCE INTERVAL
b@1554:         if enable_confidence:
b@1554:             iterator = 0
b@1554:             for column in ratings.T: # iterate over transposed matrix
b@1554:                 # remove all 'Nan's from column
b@1554:                 column = column[~np.isnan(column)]
b@1554:             
b@1554:                 # get number of non-Nan ratings (= #subjects)
b@1554:                 n = column.size
b@1554:         
b@1554:                 # get mean
b@1554:                 mean_rating = np.mean(column)
b@1554:         
b@1554:                 # get errors
b@1554:                 err = scipy.stats.sem(column)* sp.stats.t._ppf((1+confidence)/2., n-1)
b@1554:         
b@1554:                 # draw plot
b@1554:                 plt.errorbar(iterator+1, 
b@1554:                             mean_rating, 
b@1554:                             yerr=err,
b@1554:                             marker="x",
b@1554:                             color ="k",
b@1554:                             markersize=12,
b@1554:                             linestyle='None')
b@1554:                             
b@1554:                 iterator += 1 # increase counter
b@1554:     
b@1554:     
b@1554:         # INDIVIDUAL PLOT
b@1554:         if enable_individual or show_individual:
b@1554:             # marker list and color map to cycle through
b@1554:             markerlist = ["x", ".", "o", "*", "+", "v", ">", "<", "8", "s", "p"]
b@1554:             colormap = ['b', 'r', 'g', 'c', 'm', 'y', 'k'] 
b@1554:             increment = 0
b@1554:             linehandles = []
b@1554:             legendnames = []
b@1554:             with open(rating_folder+file, 'rb') as readfile: # read this csv file
b@1554:                 filereader = csv.reader(readfile, delimiter=',')
b@1554:                 headerrow = filereader.next() # use headerrow as X-axis
b@1554:                 headerrow = headerrow[1:]
b@1554:                 for row in filereader:
b@1554:                     subject_id = row[0][:-4] # read from beginning of line
b@1554:                     # assume plotting all individuals if no individual(s) specified
b@1554:                     if not show_individual or subject_id in show_individual:
b@1554:                         plothandle, = plt.plot(range(1,len(row)), # x-values
b@1554:                                  ratings[increment,:],#row[1:], # y-values: csv values except subject name
b@1554:                                  color=colormap[increment%len(colormap)],
b@1554:                                  marker=markerlist[increment%len(markerlist)],
b@1554:                                  markersize=10,
b@1554:                                  linestyle='None',
b@1554:                                  label=subject_id
b@1554:                                 )
b@1554:                         linehandles.append(plothandle)
b@1554:                         legendnames.append(subject_id)
b@1554:                         if show_legend:
b@1554:                             plt.legend(linehandles, legendnames,
b@1554:                                        loc='upper right',
b@1554:                                        bbox_to_anchor=(1.1, 1),
b@1554:                                        borderaxespad=0.,
b@1554:                                        numpoints=1 # remove extra marker
b@1554:                                        )
b@1554:                     increment += 1 # increase counter
b@1554: 
b@1554:         # TITLE, AXIS LABELS AND LIMITS
b@1554:         plt.title(page_name)
b@1554:         plt.xlabel('Fragment')
b@1554:         plt.xlim(0, len(headerrow)+1) # only show relevant region, leave space left & right)
b@1554:         plt.xticks(range(1, len(headerrow)+1), headerrow) # show fragment names
b@1554:         plt.ylabel('Rating')
b@1554:         plt.ylim(0,1)
b@1554:         
b@1554:         
b@1554: 
b@1554:         # SHOW PLOT
b@1554:         #plt.show()
b@1554:         #exit()
b@1554:     
b@1554:         # SAVE PLOT
b@1554:         # automatically 
b@1554:         plot_type = ("-box" if enable_boxplot else "") + \
b@1554:                     ("-conf" if enable_confidence else "") + \
b@1554:                     ("-ind" if enable_individual else "")
b@1554:         plt.savefig(rating_folder+page_name+plot_type+".png")
b@1554:         plt.close()