Module Owntools.PFtoDEM_Multi
@author: Alexandre Sac–Morane alexandre.sac-morane@uclouvain.be
This file contains the different functions used to translate phase field data in DEM data in the simulation.
Expand source code
# -*- coding: utf-8 -*-
"""
@author: Alexandre Sac--Morane
alexandre.sac-morane@uclouvain.be
This file contains the different functions used to translate phase field data in DEM data in the simulation.
"""
#-------------------------------------------------------------------------------
#Librairy
#-------------------------------------------------------------------------------
import numpy as np
#-------------------------------------------------------------------------------
def solute_PFtoDEM_Multi(FileToRead,dict_algorithm,dict_sample):
'''
Read file from MOOSE simulation to reconstruct the phase field of the solute.
Input :
the name of the file to read (a string)
an algorithm dictionnary (a dictionnary)
a sample dictionnary (a dictionnary)
Output :
Nothing but the sample dictionnary gets an updated attribute (a n_y x n_x numpy array)
'''
#---------------------------------------------------------------------------
#Global parameters
#---------------------------------------------------------------------------
dict_sample['solute_M'] = np.array(np.zeros((len(dict_sample['y_L']),len(dict_sample['x_L']))))
id_L = None
c_selector_len = len(' <DataArray type="Float64" Name="c')
end_len = len(' </DataArray>')
XYZ_selector_len = len(' <DataArray type="Float64" Name="Points"')
data_jump_len = len(' ')
for i_proc in range(dict_algorithm['np_proc']):
L_Work = [[], #X
[], #Y
[]] #c
#---------------------------------------------------------------------------
#Reading file
#---------------------------------------------------------------------------
f = open(f'{FileToRead}_{i_proc}.vtu','r')
data = f.read()
f.close()
lines = data.splitlines()
#iterations on line
for line in lines:
if line[0:c_selector_len] == ' <DataArray type="Float64" Name="c':
id_L = 2
elif line[0:XYZ_selector_len] == ' <DataArray type="Float64" Name="Points"':
id_L = 0
elif (line[0:end_len] == ' </DataArray>' or line[0:len(' <InformationKey')] == ' <InformationKey') and id_L != None:
id_L = None
elif line[0:data_jump_len] == ' ' and id_L == 2: #Read c
line = line[data_jump_len:]
c_start = 0
for c_i in range(0,len(line)):
if line[c_i]==' ':
c_end = c_i
L_Work[id_L].append(float(line[c_start:c_end]))
c_start = c_i+1
L_Work[id_L].append(float(line[c_start:]))
elif line[0:data_jump_len] == ' ' and id_L == 0: #Read [X, Y, Z]
line = line[data_jump_len:]
XYZ_temp = []
c_start = 0
for c_i in range(0,len(line)):
if line[c_i]==' ':
c_end = c_i
XYZ_temp.append(float(line[c_start:c_end]))
if len(XYZ_temp)==3:
L_Work[0].append(XYZ_temp[0])
L_Work[1].append(XYZ_temp[1])
XYZ_temp = []
c_start = c_i+1
XYZ_temp.append(float(line[c_start:]))
L_Work[0].append(XYZ_temp[0])
L_Work[1].append(XYZ_temp[1])
#Adaptating data and update of solute_M
for i in range(len(L_Work[0])):
#Interpolation method
L_dy = []
for y_i in dict_sample['y_L'] :
L_dy.append(abs(y_i - L_Work[1][i]))
L_dx = []
for x_i in dict_sample['x_L'] :
L_dx.append(abs(x_i - L_Work[0][i]))
dict_sample['solute_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i]
#---------------------------------------------------------------------------
def Ed_PFtoDEM_Multi(FileToRead,dict_algorithm,dict_sample):
'''
Read file from MOOSE simulation to follow the external energy used in the phase field formulation.
Input :
the name of the file to read (a string)
an algorithm dictionnary (a dictionnary)
a sample dictionnary (a dictionnary)
Output :
Nothing but the sample dictionnary gets updated attributes (three n_y x n_x numpy array)
'''
#---------------------------------------------------------------------------
#Global parameters
#---------------------------------------------------------------------------
id_L = None
Emec_selector_len = len(' <DataArray type="Float64" Name="Ed_mec')
Eche_selector_len = len(' <DataArray type="Float64" Name="Ed_pre')
end_len = len(' </DataArray>')
XYZ_selector_len = len(' <DataArray type="Float64" Name="Points"')
data_jump_len = len(' ')
for i_proc in range(dict_algorithm['np_proc']):
L_Work = [[], #X
[], #Y
[], #Emec
[]] #Eche
#---------------------------------------------------------------------------
#Reading file
#---------------------------------------------------------------------------
f = open(f'{FileToRead}_{i_proc}.vtu','r')
data = f.read()
f.close()
lines = data.splitlines()
#iterations on line
for line in lines:
if line[0:Emec_selector_len] == ' <DataArray type="Float64" Name="Ed_mec':
id_L = 2
elif line[0:Eche_selector_len] == ' <DataArray type="Float64" Name="Ed_pre':
id_L = 3
elif line[0:XYZ_selector_len] == ' <DataArray type="Float64" Name="Points"':
id_L = 0
elif (line[0:end_len] == ' </DataArray>' or line[0:len(' <InformationKey')] == ' <InformationKey') and id_L != None:
id_L = None
elif line[0:data_jump_len] == ' ' and (id_L == 2 or id_L == 3): #Read Ed_mec or Ed_pre
line = line[data_jump_len:]
c_start = 0
for c_i in range(0,len(line)):
if line[c_i]==' ':
c_end = c_i
L_Work[id_L].append(float(line[c_start:c_end]))
c_start = c_i+1
L_Work[id_L].append(float(line[c_start:]))
elif line[0:data_jump_len] == ' ' and id_L == 0: #Read [X, Y, Z]
line = line[data_jump_len:]
XYZ_temp = []
c_start = 0
for c_i in range(0,len(line)):
if line[c_i]==' ':
c_end = c_i
XYZ_temp.append(float(line[c_start:c_end]))
if len(XYZ_temp)==3:
L_Work[0].append(XYZ_temp[0])
L_Work[1].append(XYZ_temp[1])
XYZ_temp = []
c_start = c_i+1
XYZ_temp.append(float(line[c_start:]))
L_Work[0].append(XYZ_temp[0])
L_Work[1].append(XYZ_temp[1])
#Adaptating data and update of Ed_M, Emec_M and Eche_M
for i in range(len(L_Work[0])):
#Interpolation method
L_dy = []
for y_i in dict_sample['y_L'] :
L_dy.append(abs(y_i - L_Work[1][i]))
L_dx = []
for x_i in dict_sample['x_L'] :
L_dx.append(abs(x_i - L_Work[0][i]))
dict_sample['Emec_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i]
dict_sample['Eche_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[3][i]
dict_sample['Ed_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i] - L_Work[3][i]Functions
def Ed_PFtoDEM_Multi(FileToRead, dict_algorithm, dict_sample)-
Read file from MOOSE simulation to follow the external energy used in the phase field formulation.
Input : the name of the file to read (a string) an algorithm dictionnary (a dictionnary) a sample dictionnary (a dictionnary) Output : Nothing but the sample dictionnary gets updated attributes (three n_y x n_x numpy array)Expand source code
def Ed_PFtoDEM_Multi(FileToRead,dict_algorithm,dict_sample): ''' Read file from MOOSE simulation to follow the external energy used in the phase field formulation. Input : the name of the file to read (a string) an algorithm dictionnary (a dictionnary) a sample dictionnary (a dictionnary) Output : Nothing but the sample dictionnary gets updated attributes (three n_y x n_x numpy array) ''' #--------------------------------------------------------------------------- #Global parameters #--------------------------------------------------------------------------- id_L = None Emec_selector_len = len(' <DataArray type="Float64" Name="Ed_mec') Eche_selector_len = len(' <DataArray type="Float64" Name="Ed_pre') end_len = len(' </DataArray>') XYZ_selector_len = len(' <DataArray type="Float64" Name="Points"') data_jump_len = len(' ') for i_proc in range(dict_algorithm['np_proc']): L_Work = [[], #X [], #Y [], #Emec []] #Eche #--------------------------------------------------------------------------- #Reading file #--------------------------------------------------------------------------- f = open(f'{FileToRead}_{i_proc}.vtu','r') data = f.read() f.close() lines = data.splitlines() #iterations on line for line in lines: if line[0:Emec_selector_len] == ' <DataArray type="Float64" Name="Ed_mec': id_L = 2 elif line[0:Eche_selector_len] == ' <DataArray type="Float64" Name="Ed_pre': id_L = 3 elif line[0:XYZ_selector_len] == ' <DataArray type="Float64" Name="Points"': id_L = 0 elif (line[0:end_len] == ' </DataArray>' or line[0:len(' <InformationKey')] == ' <InformationKey') and id_L != None: id_L = None elif line[0:data_jump_len] == ' ' and (id_L == 2 or id_L == 3): #Read Ed_mec or Ed_pre line = line[data_jump_len:] c_start = 0 for c_i in range(0,len(line)): if line[c_i]==' ': c_end = c_i L_Work[id_L].append(float(line[c_start:c_end])) c_start = c_i+1 L_Work[id_L].append(float(line[c_start:])) elif line[0:data_jump_len] == ' ' and id_L == 0: #Read [X, Y, Z] line = line[data_jump_len:] XYZ_temp = [] c_start = 0 for c_i in range(0,len(line)): if line[c_i]==' ': c_end = c_i XYZ_temp.append(float(line[c_start:c_end])) if len(XYZ_temp)==3: L_Work[0].append(XYZ_temp[0]) L_Work[1].append(XYZ_temp[1]) XYZ_temp = [] c_start = c_i+1 XYZ_temp.append(float(line[c_start:])) L_Work[0].append(XYZ_temp[0]) L_Work[1].append(XYZ_temp[1]) #Adaptating data and update of Ed_M, Emec_M and Eche_M for i in range(len(L_Work[0])): #Interpolation method L_dy = [] for y_i in dict_sample['y_L'] : L_dy.append(abs(y_i - L_Work[1][i])) L_dx = [] for x_i in dict_sample['x_L'] : L_dx.append(abs(x_i - L_Work[0][i])) dict_sample['Emec_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i] dict_sample['Eche_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[3][i] dict_sample['Ed_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i] - L_Work[3][i] def solute_PFtoDEM_Multi(FileToRead, dict_algorithm, dict_sample)-
Read file from MOOSE simulation to reconstruct the phase field of the solute.
Input : the name of the file to read (a string) an algorithm dictionnary (a dictionnary) a sample dictionnary (a dictionnary) Output : Nothing but the sample dictionnary gets an updated attribute (a n_y x n_x numpy array)Expand source code
def solute_PFtoDEM_Multi(FileToRead,dict_algorithm,dict_sample): ''' Read file from MOOSE simulation to reconstruct the phase field of the solute. Input : the name of the file to read (a string) an algorithm dictionnary (a dictionnary) a sample dictionnary (a dictionnary) Output : Nothing but the sample dictionnary gets an updated attribute (a n_y x n_x numpy array) ''' #--------------------------------------------------------------------------- #Global parameters #--------------------------------------------------------------------------- dict_sample['solute_M'] = np.array(np.zeros((len(dict_sample['y_L']),len(dict_sample['x_L'])))) id_L = None c_selector_len = len(' <DataArray type="Float64" Name="c') end_len = len(' </DataArray>') XYZ_selector_len = len(' <DataArray type="Float64" Name="Points"') data_jump_len = len(' ') for i_proc in range(dict_algorithm['np_proc']): L_Work = [[], #X [], #Y []] #c #--------------------------------------------------------------------------- #Reading file #--------------------------------------------------------------------------- f = open(f'{FileToRead}_{i_proc}.vtu','r') data = f.read() f.close() lines = data.splitlines() #iterations on line for line in lines: if line[0:c_selector_len] == ' <DataArray type="Float64" Name="c': id_L = 2 elif line[0:XYZ_selector_len] == ' <DataArray type="Float64" Name="Points"': id_L = 0 elif (line[0:end_len] == ' </DataArray>' or line[0:len(' <InformationKey')] == ' <InformationKey') and id_L != None: id_L = None elif line[0:data_jump_len] == ' ' and id_L == 2: #Read c line = line[data_jump_len:] c_start = 0 for c_i in range(0,len(line)): if line[c_i]==' ': c_end = c_i L_Work[id_L].append(float(line[c_start:c_end])) c_start = c_i+1 L_Work[id_L].append(float(line[c_start:])) elif line[0:data_jump_len] == ' ' and id_L == 0: #Read [X, Y, Z] line = line[data_jump_len:] XYZ_temp = [] c_start = 0 for c_i in range(0,len(line)): if line[c_i]==' ': c_end = c_i XYZ_temp.append(float(line[c_start:c_end])) if len(XYZ_temp)==3: L_Work[0].append(XYZ_temp[0]) L_Work[1].append(XYZ_temp[1]) XYZ_temp = [] c_start = c_i+1 XYZ_temp.append(float(line[c_start:])) L_Work[0].append(XYZ_temp[0]) L_Work[1].append(XYZ_temp[1]) #Adaptating data and update of solute_M for i in range(len(L_Work[0])): #Interpolation method L_dy = [] for y_i in dict_sample['y_L'] : L_dy.append(abs(y_i - L_Work[1][i])) L_dx = [] for x_i in dict_sample['x_L'] : L_dx.append(abs(x_i - L_Work[0][i])) dict_sample['solute_M'][-1-list(L_dy).index(min(L_dy))][list(L_dx).index(min(L_dx))] = L_Work[2][i]