__author__ = 'panos' from ini import * import os import analysis, plotting import datasetDivision as dsDv imageNames = os.listdir(IMAGE_FOLDER) print imageNames datasets = [] paintingsDsDict = dsDv.divide_datasets() imageNamesDict = dict([(imageNames[4], paintingsDsDict.get(1)), (imageNames[5], paintingsDsDict.get(2)), (imageNames[10], paintingsDsDict.get(3)), (imageNames[7], paintingsDsDict.get(4)), (imageNames[6], paintingsDsDict.get(5)), (imageNames[8], paintingsDsDict.get(6)), (imageNames[1], paintingsDsDict.get(7)), (imageNames[11], paintingsDsDict.get(8)), (imageNames[2], paintingsDsDict.get(9)), (imageNames[3], paintingsDsDict.get(10)), (imageNames[0], paintingsDsDict.get(11)), (imageNames[9], paintingsDsDict.get(12))]) parameters = { 'gridWidth': 21, # the grid size: set to None for dynamic calcluation 'gridHeight': None, # the grid size: set to None for square shaped boxes 'errorRadius': 5, # error smoothing sigma (pixels) 'groupingRadius': 50, # filtering radius (pixels) 'fixationLengthFilter': 100 # minimum fixation length }
__author__ = 'panos' import numpy as np import matplotlib.pyplot as plt import datasetDivision as div from ini import * paintingsDictionary = div.divide_datasets() def gender_plot(): N = 2 menNum = (len(MALE_PARTICIPANTS)) womenNum = (len(FEMALE_PARTICIPANTS)) index=np.arange(N) width = 0.35 fig,ax = plt.subplots() men_rectangle = ax.bar(0, menNum, width, color='r',align='center') women_rectangle = ax.bar(width,womenNum,width,color='y',align='center') ax.set_ylabel('Viewers') ax.set_title('Viewers by gender') plt.xticks(index+0.5, ('Male','Female')) plt.show() def agegroups_plot(): print "age groups"
__author__ = 'panos' from ini import * import os import analysis, plotting import datasetDivision as dsDv imageNames = os.listdir(IMAGE_FOLDER) print imageNames datasets=[] paintingsDsDict = dsDv.divide_datasets() imageNamesDict = dict([(imageNames[4],paintingsDsDict.get(1)),(imageNames[5],paintingsDsDict.get(2)), (imageNames[10],paintingsDsDict.get(3)),(imageNames[7],paintingsDsDict.get(4)), (imageNames[6],paintingsDsDict.get(5)),(imageNames[8],paintingsDsDict.get(6)), (imageNames[1],paintingsDsDict.get(7)),(imageNames[11],paintingsDsDict.get(8)), (imageNames[2],paintingsDsDict.get(9)),(imageNames[3],paintingsDsDict.get(10)), (imageNames[0],paintingsDsDict.get(11)),(imageNames[9],paintingsDsDict.get(12))]) parameters = { 'gridWidth': 21, # the grid size: set to None for dynamic calcluation 'gridHeight': None, # the grid size: set to None for square shaped boxes 'errorRadius': 5, # error smoothing sigma (pixels) 'groupingRadius': 50, # filtering radius (pixels) 'fixationLengthFilter': 100 # minimum fixation length } def visualizeFamiliarityResults(imageName,parameters): analysisOb = analysis.Analysis(parameters) analysisOb.outputPath= DATASET_FOLDER #add datasets to array for later comparison datasets=[] for i in range(0,3):
__author__ = 'panos' import os import analysis, plotting from ini import * import datasetDivision recordings = os.listdir(GAZE_DATA) imageNames = os.listdir(IMAGE_FOLDER) gridsize=0 paintingsDict = datasetDivision.divide_datasets() parameters = { 'gridWidth': 21, # the grid size: set to None for dynamic calcluation 'gridHeight': None, # the grid size: set to None for square shaped boxes 'errorRadius': 5, # error smoothing sigma (pixels) 'groupingRadius': 50, # filtering radius (pixels) 'fixationLengthFilter': 100 # minimum fixation length } def createImageDataset(imageName,eyeTrackingRecordings,datasetLabel): analysisObject = analysis.Analysis(parameters) analysisObject.outputPath = DATASET_FOLDER imageDataset = analysisObject.buildDataSetForStimulus(datasetLabel,eyeTrackingRecordings,imageName,GAZE_DATA) newParameters = { 'gridWidth': 21, # the grid size: set to None for dynamic calcluation 'gridHeight': None, # the grid size: set to None for square shaped boxes
__author__ = 'panos' import numpy as np import matplotlib.pyplot as plt import datasetDivision as div from ini import * paintingsDictionary = div.divide_datasets() def gender_plot(): N = 2 menNum = (len(MALE_PARTICIPANTS)) womenNum = (len(FEMALE_PARTICIPANTS)) index = np.arange(N) width = 0.35 fig, ax = plt.subplots() men_rectangle = ax.bar(0, menNum, width, color='r', align='center') women_rectangle = ax.bar(width, womenNum, width, color='y', align='center') ax.set_ylabel('Viewers') ax.set_title('Viewers by gender') plt.xticks(index + 0.5, ('Male', 'Female')) plt.show() def agegroups_plot(): print "age groups"