# How to use the gudhi.PersistenceLandscapes function in gudhi

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GUDHI / gudhi-devel / src / cython / example / persistence_representations_landscapes_example.py View on Github
``````along with this program.  If not, see .
"""

__author__ = "Pawel Dlotko"

print("#####################################################################")
print("Persistence representations landscapes example")

persistence1 = [(1,2),(6,8),(0,4),(3,8)]
persistence2 = [(2,9),(1,6),(3,5),(6,10)]

#create two persistence landscapes based on persistence1 and persistence2:
l1 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence1, dimension=3)
l2 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence2)

#This is how to compute integral of landscapes:
print "Integral of the first landscape : ", l1.compute_integral_of_landscape()
print "Integral of the second landscape : ", l2.compute_integral_of_landscape()

#here are the maxima of the functions:
print "Maximum of l1 : ", l1.compute_maximum()
print "Maximum of l2 : ", l2.compute_maximum()

#here are the norms of landscapes:
print "L^1 Norm of l1 : ", l1.compute_norm_of_landscape(1.)
print "L^1 Norm of l2 : ", l2.compute_norm_of_landscape(1.)

#here is the average of landscapes:
average = gudhi.PersistenceLandscapes()``````
GUDHI / gudhi-devel / src / cython / example / persistence_representations_landscapes_example.py View on Github
``````l2 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence2)

#This is how to compute integral of landscapes:
print "Integral of the first landscape : ", l1.compute_integral_of_landscape()
print "Integral of the second landscape : ", l2.compute_integral_of_landscape()

#here are the maxima of the functions:
print "Maximum of l1 : ", l1.compute_maximum()
print "Maximum of l2 : ", l2.compute_maximum()

#here are the norms of landscapes:
print "L^1 Norm of l1 : ", l1.compute_norm_of_landscape(1.)
print "L^1 Norm of l2 : ", l2.compute_norm_of_landscape(1.)

#here is the average of landscapes:
average = gudhi.PersistenceLandscapes()
average.compute_average(to_average=[l1, l2])

#here is the distance of landscapes:
print "Distance : ", l1.distance(average,1)

#here is the scalar product of landscapes:
print "Scalar product : ", l1.compute_scalar_product(l2)``````
GUDHI / gudhi-devel / src / cython / example / persistence_representations_landscapes_example.py View on Github
``````"""

__author__ = "Pawel Dlotko"

print("#####################################################################")
print("Persistence representations landscapes example")

persistence1 = [(1,2),(6,8),(0,4),(3,8)]
persistence2 = [(2,9),(1,6),(3,5),(6,10)]

#create two persistence landscapes based on persistence1 and persistence2:
l1 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence1, dimension=3)
l2 = gudhi.PersistenceLandscapes(vector_of_intervals=persistence2)

#This is how to compute integral of landscapes:
print "Integral of the first landscape : ", l1.compute_integral_of_landscape()
print "Integral of the second landscape : ", l2.compute_integral_of_landscape()

#here are the maxima of the functions:
print "Maximum of l1 : ", l1.compute_maximum()
print "Maximum of l2 : ", l2.compute_maximum()

#here are the norms of landscapes:
print "L^1 Norm of l1 : ", l1.compute_norm_of_landscape(1.)
print "L^1 Norm of l2 : ", l2.compute_norm_of_landscape(1.)

#here is the average of landscapes:
average = gudhi.PersistenceLandscapes()
average.compute_average(to_average=[l1, l2])``````

## gudhi

The Gudhi library is an open source library for Computational Topology and Topological Data Analysis (TDA).

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