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 )
