def calculate_total_performance(algo) : winder_metrics = datfile.load_metrics( dataset="winder", stripsize="300", algorithm=algo ) uwiii_metrics = datfile.load_metrics( dataset="uwiii", stripsize="300", algorithm=algo ) print winder_metrics.shape print uwiii_metrics.shape all_300 = np.concatenate((winder_metrics, uwiii_metrics)) print "all {0} len={1}".format( algo, len(all_300) ) print "all {0} mean={1}".format( algo, np.mean(all_300) ) print "all {0} stddev={1}".format( algo, np.std(all_300) ) nz = np.nonzero(all_300) print len(all_300[nz]) print "all {0} numzeros={1}".format( algo, len(all_300)-len(all_300[nz]))
def count_uwiii_zeros() : metrics = datfile.load_metrics( dataset="uwiii", stripsize="300", algorithm="rast") num_nonzero = np.count_nonzero(metrics) num_elements = len(metrics) print num_elements, num_nonzero print "num_nonzero=",num_nonzero print "num_elements=",num_elements print "num_zero=",num_elements-num_nonzero
def count_uwiii_zeros(): metrics = datfile.load_metrics(dataset="uwiii", stripsize="300", algorithm="rast") num_nonzero = np.count_nonzero(metrics) num_elements = len(metrics) print num_elements, num_nonzero print "num_nonzero=", num_nonzero print "num_elements=", num_elements print "num_zero=", num_elements - num_nonzero
def calculate_total_performance(algo): winder_metrics = datfile.load_metrics(dataset="winder", stripsize="300", algorithm=algo) uwiii_metrics = datfile.load_metrics(dataset="uwiii", stripsize="300", algorithm=algo) print winder_metrics.shape print uwiii_metrics.shape all_300 = np.concatenate((winder_metrics, uwiii_metrics)) print "all {0} len={1}".format(algo, len(all_300)) print "all {0} mean={1}".format(algo, np.mean(all_300)) print "all {0} stddev={1}".format(algo, np.std(all_300)) nz = np.nonzero(all_300) print len(all_300[nz]) print "all {0} numzeros={1}".format(algo, len(all_300) - len(all_300[nz]))
def count_zeros(dataset,algorithm,stripsize) : metrics = datfile.load_metrics(dataset=dataset,algorithm=algorithm,stripsize=stripsize ) # zeros = np.where(metrics==0) num_nonzero = np.count_nonzero(metrics) num_elements = len(metrics) # print name, num_elements, num_nonzero # print "num_nonzero=",num_nonzero # print "num_elements=",len(metrics) return (num_nonzero, num_elements, float(num_nonzero)/float(num_elements) )
def count_zeros(dataset, algorithm, stripsize): metrics = datfile.load_metrics(dataset=dataset, algorithm=algorithm, stripsize=stripsize) # zeros = np.where(metrics==0) num_nonzero = np.count_nonzero(metrics) num_elements = len(metrics) # print name, num_elements, num_nonzero # print "num_nonzero=",num_nonzero # print "num_elements=",len(metrics) return (num_nonzero, num_elements, float(num_nonzero) / float(num_elements))
def draw_four_up_histogram(dataset) : # draw a 2x2 plot of # fullpage+rast 300+rast # fullpage+vor 300_vor outfilename = "{0}_2x2.png".format(dataset) figure_label_iter = iter(("(a)","(b)","(c)","(d)")) subplot_counter = 1 for algo in algorithm_list : for stripsize in ("fullpage","300") : fig = Figure() fig.suptitle(dataset) metrics = datfile.load_metrics( dataset=dataset, stripsize=stripsize, algorithm=algo) ax = fig.add_subplot(111) ax.hist(metrics[np.nonzero(np.nan_to_num(metrics))],bins=25) # ax.hist(metrics[np.nonzero(np.nan_to_num(metrics))],bins=25,normed=True) # ax.set_title("{0} {1} {2}".format(figure_label_iter.next(),algo,stripsize)) ax.set_xlabel( "Metric" ) ax.set_xlim(0,1.0) subplot_counter += 1 fig.tight_layout(pad=2.0) outfilename = "{0}_{1}_{2}_histo.png".format(dataset,stripsize,algo) canvas = FigureCanvasAgg(fig) canvas.print_figure(outfilename) print "wrote", outfilename stretch_width( outfilename )