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Klaus Böhnlein
dune-microstructure-backup
Commits
5203d9dd
Commit
5203d9dd
authored
3 years ago
by
Klaus Böhnlein
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Add option to plot angle over mu_gamma
parent
28dae3c8
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src/Plotq3-Angle.py
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5203d9dd
import
numpy
as
np
import
matplotlib.pyplot
as
plt
import
sympy
as
sym
import
math
import
os
import
subprocess
import
fileinput
import
re
import
matlab.engine
import
sys
from
ClassifyMin
import
*
# from CellScript import *
from
mpl_toolkits.mplot3d
import
Axes3D
import
matplotlib.cm
as
cm
from
vtk.util
import
numpy_support
from
pyevtk.hl
import
gridToVTK
import
time
# from subprocess import Popen, PIPE
#import sys
# unabhängig von alpha...
def
GetMuGamma
(
beta
,
theta
,
gamma
,
mu1
,
rho1
,
InputFilePath
=
os
.
path
.
dirname
(
os
.
getcwd
())
+
"
/inputs/computeMuGamma.parset
"
):
# ------------------------------------ get mu_gamma ------------------------------
# ---Scenario 1.1: extreme regimes
if
gamma
==
'
0
'
:
print
(
'
extreme regime: gamma = 0
'
)
mu_gamma
=
(
1.0
/
6.0
)
*
arithmeticMean
(
mu1
,
beta
,
theta
)
# = q2
print
(
"
mu_gamma:
"
,
mu_gamma
)
elif
gamma
==
'
infinity
'
:
print
(
'
extreme regime: gamma = infinity
'
)
mu_gamma
=
(
1.0
/
6.0
)
*
harmonicMean
(
mu1
,
beta
,
theta
)
# = q1
print
(
"
mu_gamma:
"
,
mu_gamma
)
else
:
# --- Scenario 1.2: compute mu_gamma with 'Compute_MuGamma' (much faster than running full Cell-Problem)
# print("Run computeMuGamma for Gamma = ", gamma)
with
open
(
InputFilePath
,
'
r
'
)
as
file
:
filedata
=
file
.
read
()
filedata
=
re
.
sub
(
'
(?m)^gamma=.*
'
,
'
gamma=
'
+
str
(
gamma
),
filedata
)
# filedata = re.sub('(?m)^alpha=.*','alpha='+str(alpha),filedata)
filedata
=
re
.
sub
(
'
(?m)^beta=.*
'
,
'
beta=
'
+
str
(
beta
),
filedata
)
filedata
=
re
.
sub
(
'
(?m)^theta=.*
'
,
'
theta=
'
+
str
(
theta
),
filedata
)
filedata
=
re
.
sub
(
'
(?m)^mu1=.*
'
,
'
mu1=
'
+
str
(
mu1
),
filedata
)
filedata
=
re
.
sub
(
'
(?m)^rho1=.*
'
,
'
rho1=
'
+
str
(
rho1
),
filedata
)
f
=
open
(
InputFilePath
,
'
w
'
)
f
.
write
(
filedata
)
f
.
close
()
# --- Run Cell-Problem
# Check Time
# t = time.time()
# subprocess.run(['./build-cmake/src/Cell-Problem', './inputs/cellsolver.parset'],
# capture_output=True, text=True)
# --- Run Cell-Problem_muGama -> faster
# subprocess.run(['./build-cmake/src/Cell-Problem_muGamma', './inputs/cellsolver.parset'],
# capture_output=True, text=True)
# --- Run Compute_muGamma (2D Problem much much faster)
subprocess
.
run
([
'
./build-cmake/src/Compute_MuGamma
'
,
'
./inputs/computeMuGamma.parset
'
],
capture_output
=
True
,
text
=
True
)
# print('elapsed time:', time.time() - t)
#Extract mu_gamma from Output-File TODO: GENERALIZED THIS FOR QUANTITIES OF INTEREST
with
open
(
OutputFilePath
,
'
r
'
)
as
file
:
output
=
file
.
read
()
tmp
=
re
.
search
(
r
'
(?m)^mu_gamma=.*
'
,
output
).
group
()
# Not necessary for Intention of Program t output Minimizer etc.....
s
=
re
.
findall
(
r
"
[-+]?\d*\.\d+|\d+
"
,
tmp
)
mu_gamma
=
float
(
s
[
0
])
# print("mu_gamma:", mu_gammaValue)
# --------------------------------------------------------------------------------------
return
mu_gamma
InputFile
=
"
/inputs/computeMuGamma.parset
"
OutputFile
=
"
/outputs/outputMuGamma.txt
"
# path = os.getcwd()
# InputFilePath = os.getcwd()+InputFile
# OutputFilePath = os.getcwd()+OutputFile
# --------- Run from src folder:
path_parent
=
os
.
path
.
dirname
(
os
.
getcwd
())
os
.
chdir
(
path_parent
)
path
=
os
.
getcwd
()
print
(
path
)
InputFilePath
=
os
.
getcwd
()
+
InputFile
OutputFilePath
=
os
.
getcwd
()
+
OutputFile
print
(
"
InputFilepath:
"
,
InputFilePath
)
print
(
"
OutputFilepath:
"
,
OutputFilePath
)
print
(
"
Path:
"
,
path
)
#1. Define Inputs Gamma-Array..
#2. for(i=0; i<length(array)) ..compute Q_hom, B_eff from Cell-Problem
#3
# matrix = np.loadtxt(path + 'Qmatrix.txt', usecols=range(3))
# print(matrix)
# Use Shell Commands:
# subprocess.run('ls', shell=True)
#---------------------------------------------------------------
# -------------------------- Input Parameters --------------------
mu1
=
10.0
rho1
=
1.0
alpha
=
10
#1.05263158
beta
=
40.0
#5.0
# theta = 1.0/4.0
theta
=
1.0
/
8.0
# 0.5
# InterestingParameterSet :
# mu1 = 10.0
# rho1 = 1.0
# alpha = 10
# beta = 40.0
# theta = 1.0/8.0
#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
# gamma = '0'
# gamma = 'infinity'
# gamma = 0.5
print
(
'
---- Input parameters: -----
'
)
print
(
'
mu1:
'
,
mu1
)
print
(
'
rho1:
'
,
rho1
)
print
(
'
alpha:
'
,
alpha
)
print
(
'
beta:
'
,
beta
)
print
(
'
theta:
'
,
theta
)
# print('gamma:', gamma)
print
(
'
----------------------------
'
)
# ----------------------------------------------------------------
Gamma_Values
=
np
.
linspace
(
0.01
,
5
,
num
=
15
)
# TODO variable Input Parameters...alpha,beta...
print
(
'
(Input) Gamma_Values:
'
,
Gamma_Values
)
# mu_gamma = []
#
# # --- Options
# RUN = True
# # RUN = False
# # make_Plot = False
make_Plot
=
True
# vll besser : Plot_muGamma
#
# if RUN:
# for gamma in Gamma_Values:
# print("Run Cell-Problem for Gamma = ", gamma)
# # print('gamma='+str(gamma))
# with open(InputFilePath, 'r') as file:
# filedata = file.read()
# filedata = re.sub('(?m)^gamma=.*','gamma='+str(gamma),filedata)
# f = open(InputFilePath,'w')
# f.write(filedata)
# f.close()
# # --- Run Cell-Problem
# t = time.time()
# # subprocess.run(['./build-cmake/src/Cell-Problem', './inputs/cellsolver.parset'],
# # capture_output=True, text=True)
# # --- Run Cell-Problem_muGama -> faster
# # subprocess.run(['./build-cmake/src/Cell-Problem_muGamma', './inputs/cellsolver.parset'],
# # capture_output=True, text=True)
# # --- Run Compute_muGamma (2D Problem much much faster)
# subprocess.run(['./build-cmake/src/Compute_MuGamma', './inputs/computeMuGamma.parset'],
# capture_output=True, text=True)
# print('elapsed time:', time.time() - t)
#
# #Extract mu_gamma from Output-File TODO: GENERALIZED THIS FOR QUANTITIES OF INTEREST
# with open(OutputFilePath, 'r') as file:
# output = file.read()
# tmp = re.search(r'(?m)^mu_gamma=.*',output).group() # Not necessary for Intention of Program t output Minimizer etc.....
# s = re.findall(r"[-+]?\d*\.\d+|\d+", tmp)
# mu_gammaValue = float(s[0])
# print("mu_gamma:", mu_gammaValue)
# mu_gamma.append(mu_gammaValue)
# # ------------end of for-loop -----------------
# print("(Output) Values of mu_gamma: ", mu_gamma)
# # ----------------end of if-statement -------------
#
# # mu_gamma=[2.06099, 1.90567, 1.905]
# # mu_gamma=[2.08306, 1.905, 1.90482, 1.90479, 1.90478, 1.90477]
#
# ##Gamma_Values = np.linspace(0.01, 20, num=12) :
# #mu_gamma= [2.08306, 1.91108, 1.90648, 1.90554, 1.90521, 1.90505, 1.90496, 1.90491, 1.90487, 1.90485, 1.90483, 1.90482]
#
# ##Gamma_Values = np.linspace(0.01, 2.5, num=12)
# # mu_gamma=[2.08306, 2.01137, 1.96113, 1.93772, 1.92592, 1.91937, 1.91541, 1.91286, 1.91112, 1.90988, 1.90897, 1.90828]
#
# # Gamma_Values = np.linspace(0.01, 2.5, num=6)
# # mu_gamma=[2.08306, 1.95497, 1.92287, 1.91375, 1.9101, 1.90828]
GetMuGammaVec
=
np
.
vectorize
(
GetMuGamma
)
muGammas
=
GetMuGammaVec
(
beta
,
theta
,
Gamma_Values
,
mu1
,
rho1
)
classifyMin_anaVec
=
np
.
vectorize
(
classifyMin_ana
)
G
,
angles
,
Types
,
curvature
=
classifyMin_anaVec
(
alpha
,
beta
,
theta
,
muGammas
,
mu1
,
rho1
)
# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
print
(
'
angles:
'
,
angles
)
# Make Plot
if
make_Plot
:
plt
.
figure
()
plt
.
title
(
r
'
angle$-\mu_\gamma(\gamma)$-Plot
'
)
plt
.
plot
(
muGammas
,
angles
)
plt
.
scatter
(
muGammas
,
angles
)
# plt.axis([0, 6, 0, 20])
# plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
# plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
plt
.
axvline
(
x
=
1.90476
,
color
=
'
b
'
,
linestyle
=
'
:
'
,
label
=
'
$q_1$
'
)
plt
.
axvline
(
x
=
2.08333
,
color
=
'
r
'
,
linestyle
=
'
dashed
'
,
label
=
'
$q_2$
'
)
plt
.
xlabel
(
"
$\mu_\gamma$
"
)
plt
.
ylabel
(
"
angle
"
)
plt
.
legend
()
plt
.
show
()
#
# # ------------- RUN Matlab symbolic minimization program
# eng = matlab.engine.start_matlab()
# # s = eng.genpath(path + '/Matlab-Programs')
# s = eng.genpath(path)
# eng.addpath(s, nargout=0)
# # print('current Matlab folder:', eng.pwd(nargout=1))
# eng.cd('Matlab-Programs', nargout=0) #switch to Matlab-Programs folder
# # print('current Matlab folder:', eng.pwd(nargout=1))
# Inp = False
# print('Run symbolic Minimization...')
# G, angle, type, kappa = eng.symMinimization(Inp,Inp,Inp,Inp, nargout=4) #Name of program:symMinimization
# # G, angle, type, kappa = eng.symMinimization(Inp,Inp,Inp,Inp,path + "/outputs", nargout=4) #Optional: add Path
# G = np.asarray(G) #cast Matlab Outout to numpy array
#
# # --- print Output ---
# print('Minimizer G:')
# print(G)
# print('angle:', angle)
# print('type:', type )
# print('curvature:', kappa)
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