my_discretization = sampler.compute_QoI_and_create_discretization(input_samples,
savefile = '3to2_discretization.txt.gz')
'''
Suggested changes for user:
Try different reference parameters.
'''
# Define the reference parameter
param_ref = np.array([0.5, 0.5, 0.5])
#param_ref = np.array([0.75, 0.75, 0.5])
#param_ref = np.array([0.75, 0.75, 0.75])
#param_ref = np.array([0.5, 0.5, 0.75])
# Compute the reference QoI
Q_ref = my_model(param_ref)
# Create some plots of input and output discretizations
plotD.scatter_2D_multi(input_samples, ref_sample= param_ref, showdim = 'all',
filename = 'linearMap_ParameterSamples',
file_extension = '.eps')
plotD.show_data_domain_2D(my_discretization, Q_ref = Q_ref, file_extension='.eps')
'''
Suggested changes for user:
Try different ways of discretizing the probability measure on D defined as a uniform
probability measure on a rectangle (since D is 2-dimensional) centered at Q_ref whose
size is determined by scaling the circumscribing box of D.
'''
randomDataDiscretization = False
# Create the discretization object using the input samples
my_discretization = sampler.compute_QoI_and_create_discretization(
input_samples, savefile='NonlinearExample.txt.gz')
'''
Suggested changes for user:
Try different reference parameters.
'''
# Define the reference parameter
param_ref = np.array([5.5, 4.5])
#param_ref = np.array([4.5, 3.0])
#param_ref = np.array([3.5, 1.5])
# Compute the reference QoI
Q_ref = my_model(param_ref)
# Create some plots of input and output discretizations
plotD.scatter_2D(input_samples,
ref_sample=param_ref,
filename='nonlinearMapParameterSamples',
file_extension='.eps')
if Q_ref.size == 2:
plotD.show_data_domain_2D(my_discretization,
Q_ref=Q_ref,
file_extension=".eps")
'''
Suggested changes for user:
Try different ways of discretizing the probability measure on D defined
as a uniform probability measure on a rectangle or interval depending