def get_prediction_velocity(fileNumber):
"""
Used to get the Tracers as a numpy array corresponding to a vtu file from the Fluids dataset
:param fileNumber: int or string
Used to identify which vtu file to return
Values are between 0 and 988
:return: numpy array
Tracers are returned as numpy array
"""
networkName = 'vDA' # Change this to prediction folder name
folderPath = defaultFilePath + '/' + networkName
filePath = folderPath + '/' + networkName + '_' + str(fileNumber) + '.vtu'
sys.path.append('fluidity-master')
ug = vtktools.vtu(filePath)
ug.GetFieldNames()
p = ug.GetVectorField('Latent-GAN')
p = np.array(p)
# Normalise p
p = normalise(p, x_min, x_max)
# Convert p into 3 x N array
#p = np.array([p[:]])
p = p.transpose()
return p
def get_velocity_field(fileNumber):
"""
Used to get the Velocity Field as a numpy array corresponding to a vtu file
from the Fluids dataset. Note this normalises the returned array.
:param fileNumber: int or string
Used to identify which vtu file to return
Values are between 0 and 988
:return: numpy array
Velocity Fields are returned as numpy array
"""
folderPath = defaultFilePath + '/small3DLSBU'
filePath = folderPath + '/LSBU_' + str(fileNumber) + '.vtu'
sys.path.append('fluidity-master')
ug = vtktools.vtu(filePath)
ug.GetFieldNames()
p = ug.GetVectorField('Velocity')
p = np.array(p)
# Normalise p
p = normalise(p, x_min, x_max)
# Convert p into 1 x N array
p = np.array(p)
p = p.transpose()
#p = np.array([p[:]])
return p
def get_prediction_tracer(fileNumber):
"""
Used to get the Tracers as a numpy array corresponding to a vtu file from the Fluids dataset .
Note this normalises the returned array.
:param fileNumber: int or string
Used to identify which vtu file to return
Values are between 0 and 988
:return: numpy array
Tracers are returned as numpy array
"""
networkName = 'tDA2' # Change this to prediction folder name
folderPath = defaultFilePath + '/' + networkName
filePath = folderPath + '/' + networkName + '_' + str(fileNumber) + '.vtu'
sys.path.append('fluidity-master')
ug = vtktools.vtu(filePath)
ug.GetFieldNames()
p = ug.GetScalarField('Latent-GAN')
p = np.array(p)
# Normalise p
p = normalise(p, x_min, x_max)
# Convert p into 1 x N array
p = np.array([p[:]])
return p
###### LEGACY ######
# def get_tracer_from_latent(fileNumber):
# """
# Used to get the Tracers as a numpy array corresponding to a .csv file from
# the Latent dataset
# :param fileNumber: int or string
# Used to identify which vtu file to return
# Values are between 0 and 988
# :return: numpy array
# Tracers are returned as numpy array
# """
# folderPath = defaultFilePath + '/LatentSpace'
# filePath = folderPath + '/LS_' + str(fileNumber) + '.csv'
# p = np.loadtxt(filePath, delimiter=",")
# return p
def get_velocity_field_structured(fileNumber):
"""
Used to get the Velocity Field as a numpy array corresponding to a vtu file from the Fluids dataset.
Note this normalises the returned array.
:param fileNumber: int or string
Used to identify which vtu file to return
Values are between 0 and 988
:return: numpy array
Tracers are returned as numpy array
"""
folderPath = defaultFilePath + '/small3DLSBU'
filePath = folderPath + '/LSBU_' + str(fileNumber) + '.vtu'
sys.path.append('fluidity-master')
mesh = pv.read(filePath)
p = mesh.point_arrays['Velocity']
# Normalise p
p = normalise(p, x_min, x_max)
# Convert p into 3 x N array
p = np.array(p)
p = p.transpose()
#p = np.array([p[:]])
return p