def plotAreaVsStraddling(straddling_dictionary, sizes, savefilename=''):
X=np.zeros((len(sizes)))
Y=np.zeros((len(sizes)))
idx=0
for name, video in straddling_dictionary.iteritems():
dims=sizes[name]
X[idx]=dims[0]*dims[1]
measure= interpolateToFixedLength(video['origin'])
Y[idx]=measure.mean()
idx=idx+1
plt.scatter(X,Y)
plt.title('Effect of the size ')
plt.xlabel('Area, pixels')
plt.ylabel('Average straddling measure')
plt.xlim([0, 30000])
if savefilename=='':
plt.show()
else:
plt.savefig(savefilename)
def plotAreaVsStraddling(straddling_dictionary, sizes, savefilename=''):
X = np.zeros((len(sizes)))
Y = np.zeros((len(sizes)))
idx = 0
for name, video in straddling_dictionary.iteritems():
dims = sizes[name]
X[idx] = dims[0] * dims[1]
measure = interpolateToFixedLength(video['origin'])
Y[idx] = measure.mean()
idx = idx + 1
plt.scatter(X, Y)
plt.title('Effect of the size ')
plt.xlabel('Area, pixels')
plt.ylabel('Average straddling measure')
plt.xlim([0, 30000])
if savefilename == '':
plt.show()
else:
plt.savefig(savefilename)
def plotAverages(dictionary, title='No Title', savefilename=''):
#dictionary=dict()
experiment_names = list()
for value in dictionary.itervalues():
num_experiments = len(value)
for key in value.iterkeys():
experiment_names.append(key)
n = 100
X = np.zeros((num_experiments, n))
counts = np.zeros((num_experiments))
for video_dictionary in dictionary.itervalues():
for key, index in zip(video_dictionary.iterkeys(),
range(0, num_experiments)):
xs = interpolateToFixedLength(video_dictionary[key], n)
if xs is not None:
X[index, ] = X[index, ] + xs
counts[index] = counts[index] + 1
y = np.linspace(0, 1, n)
values = np.zeros((num_experiments))
for i in range(0, num_experiments):
z = X[i, ] / counts[i]
values[i] = simps(z, y)
fig = plt.figure()
sort_index = np.argsort(values)
values = values[sort_index]
labels = list()
for i in range(0, len(sort_index)):
labels.append(experiment_names[sort_index[i]])
values = values[::-1]
labels = list(reversed(labels))
width = 0.3
ind = np.arange(len(values))
plt.bar(ind, values, align="center")
plt.xticks(ind, labels)
plt.title(title)
#fig.autofmt_xdate()
if savefilename != '':
plt.savefig(savefilename)
else:
plt.show()
def plotAverages(dictionary,title='No Title',savefilename=''):
#dictionary=dict()
experiment_names=list()
for value in dictionary.itervalues():
num_experiments=len(value)
for key in value.iterkeys():
experiment_names.append(key)
n = 100
X=np.zeros((num_experiments,n))
counts=np.zeros((num_experiments))
for video_dictionary in dictionary.itervalues():
for key,index in zip(video_dictionary.iterkeys(),range(0,num_experiments)):
xs = interpolateToFixedLength(video_dictionary[key], n)
if xs is not None:
X[index,]= X[index,]+xs
counts[index]= counts[index]+1
y = np.linspace(0, 1, n)
values = np.zeros((num_experiments))
for i in range(0,num_experiments):
z=X[i,]/counts[i]
values[i]=simps(z,y)
fig = plt.figure()
sort_index = np.argsort(values)
values=values[sort_index]
labels=list()
for i in range(0,len(sort_index)):
labels.append(experiment_names[sort_index[i]])
values= values[::-1]
labels=list(reversed(labels))
width = 0.3
ind = np.arange(len(values))
plt.bar(ind, values,align="center")
plt.xticks(ind, labels)
plt.title(title)
#fig.autofmt_xdate()
if savefilename!='':
plt.savefig(savefilename)
else:
plt.show()