diff --git a/dune/microstructure/prestrain_material_geometry.hh b/dune/microstructure/prestrain_material_geometry.hh
index 27fed7b4a6b416319e542855d5cbc87a92d4f9b5..4522baef8c95f754ee706c0b19e16ba951665611 100644
--- a/dune/microstructure/prestrain_material_geometry.hh
+++ b/dune/microstructure/prestrain_material_geometry.hh
@@ -81,13 +81,14 @@ public:
return muTerm;
}
else if (imp == "parametrized_Laminate"){
- double mu1 = parameters.get<double>("mu1",10.0);
+ double mu1 = parameters.get<double>("mu1",1.0);
double beta = parameters.get<double>("beta",2.0);
double mu2 = beta*mu1;
auto muTerm = [mu1, mu2, theta] (const Domain& z) {
// std::cout << "Analytical-MU is used" << std::endl;
- if (abs(z[0]) > (theta/2.0))
+// if (abs(z[0]) >= (theta/2.0))
+ if (abs(z[0]) > (theta/2.0))
return mu1;
else
return mu2;
diff --git a/inputs/cellsolver.parset b/inputs/cellsolver.parset
index 535be32ea8a6fbf12b9f04f0f15c90831d870081..594a8bbb2bc7bb0d2b1eed08268407d57a5b3696 100644
--- a/inputs/cellsolver.parset
+++ b/inputs/cellsolver.parset
@@ -68,7 +68,7 @@ gamma=1.0
beta = 2.0 # ratio between material parameters mu1 & mu2 .... beta = 1.0 corresponds to homogeneous case
mu1=1.0
-lambda1=5.0
+lambda1=0.0
diff --git a/inputs/computeMuGamma.parset b/inputs/computeMuGamma.parset
index 924f8e8d28b25bbae4ba9f147293746515970e38..561be018606473876fdbedf8396afb1d2c12de95 100644
--- a/inputs/computeMuGamma.parset
+++ b/inputs/computeMuGamma.parset
@@ -28,8 +28,15 @@
nElements = 32 32
+#nElements = 64 64
+#nElements = 64 64
+#nElements = 94 94
+#nElements = 40 40
+#nElements = 52 52
+#nElements = 104 104
-gamma=1000000
+
+gamma=3.0
#############################################
# Material parameters
@@ -37,7 +44,7 @@ gamma=1000000
write_materialFunctions = true # VTK mu-functions , lambda-functions
-beta=2.0
+beta=10.0
mu1=1.0
@@ -66,7 +73,7 @@ write_prestrainFunctions = false # VTK norm of B ,
rho1=1.0
alpha=2.0
-theta=0.125
+theta=0.25
#theta = 0.3 # volume fraction #default = 1.0/4.0
#theta = 0.25 # volume fraction
diff --git a/src/2DPhaseDiagram_PlotScriptV2.py b/src/2DPhaseDiagram_PlotScriptV2.py
index 378cb51052a26ad84d8dec343c562b867cf6667b..70f27ad2734ae460e2f27263e056261d975e0d88 100644
--- a/src/2DPhaseDiagram_PlotScriptV2.py
+++ b/src/2DPhaseDiagram_PlotScriptV2.py
@@ -12,23 +12,55 @@ paraview.simple._DisableFirstRenderCameraReset()
case = 1
case = 2
+case = 3
#
drawLine = False
-curvature = 1
+curvature = 0
+gamma = 'infinity'
+gamma = '0'
+gamma = 0.05
+# gamma = 0.25
+gamma = 0.5
+gamma = 0.75
+gamma = 1.0
+gamma = 1.25
+gamma = 1.5
+# gamma = 1.5
+smallerRegion = True
+
# create a new 'XML Structured Grid Reader'
-if case == 1:
- phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0_4000P.vts'])
- # phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.vts'])
+# if case == 1:
+if gamma == '0':
+ # phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0_4000P.vts'])
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.vts'])
-if case == 2:
+# if case == 2:
+elif gamma == 'infinity':
phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_infinity_4000P.vts'])
- # phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_infinity.vts'])
- # phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.5.vts'])
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_infinity.vts'])
+
+else :
+# if case == 3:
+ smallerRegion = True
+ if gamma == 0.05:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.05.vts'])
+ if gamma == 0.25:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.25.vts'])
+ if gamma == 0.5:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.5.vts'])
+ if gamma == 0.75:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_0.75.vts'])
+ if gamma == 1.0:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_1.0.vts'])
+ if gamma == 1.25:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_1.25.vts'])
+ if gamma == 1.5:
+ phaseDiagram2DGamma_infinity55_4000spvts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/PhaseDiagram2DGamma_1.5.vts'])
@@ -400,8 +432,35 @@ transform1.Transform.Translate = [0.0, 0.0, 0.0]
transform1.Transform.Rotate = [0.0, 0.0, 0.0]
transform1.Transform.Scale = [1.0, 1.0, 1.0]
-# Properties modified on transform1.Transform
-transform1.Transform.Scale = [0.1, 1.0, 1.0]
+
+
+
+# if case == 3 :
+# # Properties modified on transform1.Transform
+# transform1.Transform.Scale = [0.0666667, 1.0, 1.0]
+# else :
+# # Properties modified on transform1.Transform
+# transform1.Transform.Scale = [0.1, 1.0, 1.0]
+
+
+
+# if gamma == '0' or gamma == 'infinity':
+# # Properties modified on transform1.Transform
+# transform1.Transform.Scale = [0.1, 1.0, 1.0]
+# else :
+# # Properties modified on transform1.Transform
+# transform1.Transform.Scale = [0.0666667, 1.0, 1.0]
+
+
+if smallerRegion:
+ # Properties modified on transform1.Transform
+ transform1.Transform.Scale = [0.0666667, 1.0, 1.0]
+
+else :
+ # Properties modified on transform1.Transform
+ transform1.Transform.Scale = [0.1, 1.0, 1.0]
+
+
# show data in view
transform1Display = Show(transform1, renderView1)
@@ -1153,8 +1212,8 @@ renderView1.CameraParallelScale = 0.7506135276429463
#
-if case == 1:
-
+# if case == 1:
+if gamma == '0':
# get color transfer function/color map for 'angles'
anglesLUT = GetColorTransferFunction('angles')
anglesLUT.AutomaticRescaleRangeMode = "Grow and update on 'Apply'"
@@ -1238,7 +1297,6 @@ if case == 1:
-
if curvature == 1 :
# find source
@@ -1428,6 +1486,75 @@ if curvature == 1 :
# rescale color and/or opacity maps used to exactly fit the current data range
transform1Display.RescaleTransferFunctionToDataRange(False, True)
+
+
+
+# if case == 3:
+# if gamma != '0' and gamma != 'infinity':
+if smallerRegion:
+ paraview.simple._DisableFirstRenderCameraReset()
+
+ # get active view
+ renderView1 = GetActiveViewOrCreate('RenderView')
+ # uncomment following to set a specific view size
+ # renderView1.ViewSize = [1184, 905]
+
+ #### saving camera placements for all active views
+
+ renderView1.AxesGrid.DataScale = [0.0666667, 1.0, 1.0]
+
+
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.ZAxisLabels = [ 0.4, 0.5, 0.6]
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.ShowEdges = 0
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.XAxisPrecision = 1
+ renderView1.AxesGrid.XAxisLabels = [0.0]
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.ZAxisPrecision = 1
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.XAxisUseCustomLabels = 1
+ renderView1.AxesGrid.XAxisLabels = [-2.0, -1.0, 0.0, 1.0]
+ # current camera placement for renderView1
+ renderView1.InteractionMode = '2D'
+ renderView1.CameraPosition = [0.0, -14.510745305395833, 0.5]
+ renderView1.CameraFocalPoint = [0.0, 5.0, 0.5]
+ renderView1.CameraViewUp = [0.0, 0.0, 1.0]
+ renderView1.CameraParallelScale = 0.7506135276429463
+
+
+ if gamma == '0' or gamma == 'infinity':
+ # Properties modified on transform1Display
+ transform1Display.GaussianRadius = 0.00075
+
+ else :
+ # transform1Display.GaussianRadius= 0.00001
+ transform1Display.GaussianRadius= 0.00075
+ # reset view to fit data
+ renderView1.ResetCamera()
+
+
+ # # current camera placement for renderView1
+ # renderView1.InteractionMode = '2D'
+ # renderView1.CameraPosition = [-0.03333335, 9.453589701883667, 0.5]
+ # renderView1.CameraFocalPoint = [-0.03333335, 10.0, 0.5]
+ # renderView1.CameraViewUp = [0.0, 0.0, 1.0]
+ # renderView1.CameraParallelScale = 0.14142139159265296
+
+
+
+
+
+
+
+
+
#### uncomment the following to render all views
# RenderAllViews()
# alternatively, if you want to write images, you can use SaveScreenshot(...).
@@ -1437,7 +1564,11 @@ if curvature == 1 :
# SaveScreenshot('/home/klaus/Desktop/PhaseDiagramPlot.png', renderView1, ImageResolution=[2514, 1868])
# SaveScreenshot('/home/klaus/Desktop/PhaseDiagramPlot.png', renderView1, ImageResolution=[1063, 657])
+outputName = '/home/klaus/Desktop/2DPhaseDiagram_' + str(gamma) + ".png"
+
+
+# SaveScreenshot('/home/klaus/Desktop/2DPhaseDiagram.png', renderView1, ImageResolution=[2126, 1314])
-SaveScreenshot('/home/klaus/Desktop/2DPhaseDiagram.png', renderView1, ImageResolution=[2126, 1314])
+SaveScreenshot(outputName , renderView1, ImageResolution=[2126, 1314])
# export view
# ExportView('/home/klaus/Desktop/PhaseDiagramPlot.pdf', view=renderView1)
diff --git a/src/2DPhaseDiagram_Ratios_PlotScript.py b/src/2DPhaseDiagram_Ratios_PlotScript.py
new file mode 100644
index 0000000000000000000000000000000000000000..be77851528d03608f4060855ed6dcb28616a93bd
--- /dev/null
+++ b/src/2DPhaseDiagram_Ratios_PlotScript.py
@@ -0,0 +1,579 @@
+## trace generated using paraview version 5.7.0
+#
+# To ensure correct image size when batch processing, please search
+# for and uncomment the line `# renderView*.ViewSize = [*,*]`
+
+#### import the simple module from the paraview
+from paraview.simple import *
+#### disable automatic camera reset on 'Show'
+paraview.simple._DisableFirstRenderCameraReset()
+
+
+
+case = 1
+case = 2
+case = 3
+#
+drawLine = False
+
+prestrain = 1
+
+gamma = 'infinity'
+
+
+
+
+
+
+
+# trace generated using paraview version 5.7.0
+#
+# To ensure correct image size when batch processing, please search
+# for and uncomment the line `# renderView*.ViewSize = [*,*]`
+
+#### import the simple module from the paraview
+from paraview.simple import *
+#### disable automatic camera reset on 'Show'
+paraview.simple._DisableFirstRenderCameraReset()
+
+# create a new 'XML Structured Grid Reader'
+elasticRatiovts = XMLStructuredGridReader(FileName=['/home/klaus/Desktop/DUNE/dune-microstructure/outputs/ElasticRatio.vts'])
+elasticRatiovts.PointArrayStatus = ['elasticRatio', 'prestrainRatio', 'Type', 'angles', 'curvature']
+
+# get active view
+renderView1 = GetActiveViewOrCreate('RenderView')
+# uncomment following to set a specific view size
+# renderView1.ViewSize = [1067, 518]
+
+# show data in view
+elasticRatiovtsDisplay = Show(elasticRatiovts, renderView1)
+
+# get color transfer function/color map for 'elasticRatio'
+elasticRatioLUT = GetColorTransferFunction('elasticRatio')
+elasticRatioLUT.RGBPoints = [0.3303091106505249, 0.001462, 0.000466, 0.013866, 0.33293563447422064, 0.002258, 0.001295, 0.018331, 0.33556148860800733, 0.003279, 0.002305, 0.023708, 0.33818801243170304, 0.004512, 0.00349, 0.029965, 0.34081386656548973, 0.00595, 0.004843, 0.03713, 0.3434403903891855, 0.007588, 0.006356, 0.044973, 0.346066244522972, 0.009426, 0.008022, 0.052844, 0.3486927683466678, 0.011465, 0.009828, 0.06075, 0.3513192921703637, 0.013708, 0.011771, 0.068667, 0.3539451463041502, 0.016156, 0.01384, 0.076603, 0.35657167012784596, 0.018815, 0.016026, 0.084584, 0.35919752426163265, 0.021692, 0.01832, 0.09261, 0.3618240480853284, 0.024792, 0.020715, 0.100676, 0.36444990221911505, 0.028123, 0.023201, 0.108787, 0.3670764260428108, 0.031696, 0.025765, 0.116965, 0.3697029498665066, 0.03552, 0.028397, 0.125209, 0.3723288040002933, 0.039608, 0.03109, 0.133515, 0.37495532782398905, 0.04383, 0.03383, 0.141886, 0.3775811819577757, 0.048062, 0.036607, 0.150327, 0.38020770578147145, 0.05232, 0.039407, 0.158841, 0.38283355991525797, 0.056615, 0.04216, 0.167446, 0.38546008373895374, 0.060949, 0.044794, 0.176129, 0.3880866075626497, 0.06533, 0.047318, 0.184892, 0.39071246169643614, 0.069764, 0.049726, 0.193735, 0.3933389855201319, 0.074257, 0.052017, 0.20266, 0.3959648396539186, 0.078815, 0.054184, 0.211667, 0.39859136347761437, 0.083446, 0.056225, 0.220755, 0.40121721761140106, 0.088155, 0.058133, 0.229922, 0.4038437414350968, 0.092949, 0.059904, 0.239164, 0.40646959556888346, 0.097833, 0.061531, 0.248477, 0.4090961193925792, 0.102815, 0.06301, 0.257854, 0.411722643216275, 0.107899, 0.064335, 0.267289, 0.41434849735006163, 0.113094, 0.065492, 0.276784, 0.4169750211737574, 0.118405, 0.066479, 0.286321, 0.4196008753075439, 0.123833, 0.067295, 0.295879, 0.4222273991312397, 0.12938, 0.067935, 0.305443, 0.4248532532650264, 0.135053, 0.068391, 0.315, 0.42747977708872215, 0.140858, 0.068654, 0.324538, 0.43010630091241786, 0.146785, 0.068738, 0.334011, 0.43273215504620455, 0.152839, 0.068637, 0.343404, 0.4353586788699003, 0.159018, 0.068354, 0.352688, 0.437984533003687, 0.165308, 0.067911, 0.361816, 0.4406110568273828, 0.171713, 0.067305, 0.370771, 0.4432369109611694, 0.178212, 0.066576, 0.379497, 0.4458634347848652, 0.184801, 0.065732, 0.387973, 0.44848995860856095, 0.19146, 0.064818, 0.396152, 0.45111581274234747, 0.198177, 0.063862, 0.404009, 0.45374233656604335, 0.204935, 0.062907, 0.411514, 0.4563681906998299, 0.211718, 0.061992, 0.418647, 0.4589947145235257, 0.218512, 0.061158, 0.425392, 0.4616205686573123, 0.225302, 0.060445, 0.431742, 0.4642470924810081, 0.232077, 0.059889, 0.437695, 0.46687361630470386, 0.238826, 0.059517, 0.443256, 0.4694994704384905, 0.245543, 0.059352, 0.448436, 0.47212599426218627, 0.25222, 0.059415, 0.453248, 0.47475184839597295, 0.258857, 0.059706, 0.45771, 0.4773783722196687, 0.265447, 0.060237, 0.46184, 0.4800042263534554, 0.271994, 0.060994, 0.46566, 0.4826307501771512, 0.278493, 0.061978, 0.46919, 0.4852572740008469, 0.284951, 0.063168, 0.472451, 0.4878831281346336, 0.291366, 0.064553, 0.475462, 0.4905096519583293, 0.29774, 0.066117, 0.478243, 0.49313550609211587, 0.304081, 0.067835, 0.480812, 0.49576202991581164, 0.310382, 0.069702, 0.483186, 0.4983878840495983, 0.316654, 0.07169, 0.48538, 0.5010144078732941, 0.322899, 0.073782, 0.487408, 0.5036409316969899, 0.329114, 0.075972, 0.489287, 0.5062667858307764, 0.335308, 0.078236, 0.491024, 0.5088933096544722, 0.341482, 0.080564, 0.492631, 0.5115191637882589, 0.347636, 0.082946, 0.494121, 0.5141456876119547, 0.353773, 0.085373, 0.495501, 0.5167715417457412, 0.359898, 0.087831, 0.496778, 0.5193980655694371, 0.366012, 0.090314, 0.49796, 0.5220245893931329, 0.372116, 0.092816, 0.499053, 0.5246504435269194, 0.378211, 0.095332, 0.500067, 0.5272769673506152, 0.384299, 0.097855, 0.501002, 0.5299028214844018, 0.390384, 0.100379, 0.501864, 0.5325293453080976, 0.396467, 0.102902, 0.502658, 0.5351551994418843, 0.402548, 0.10542, 0.503386, 0.53778172326558, 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0.899552, 0.314616, 0.391037, 0.7505067138381176, 0.904281, 0.31961, 0.388137, 0.7531332376618134, 0.908884, 0.324755, 0.385308, 0.7557590917956001, 0.913354, 0.330052, 0.382563, 0.7583856156192957, 0.917689, 0.3355, 0.379915, 0.7610114697530823, 0.921884, 0.341098, 0.377376, 0.7636379935767782, 0.925937, 0.346844, 0.374959, 0.7662638477105649, 0.929845, 0.352734, 0.372677, 0.7688903715342605, 0.933606, 0.358764, 0.370541, 0.7715168953579563, 0.937221, 0.364929, 0.368567, 0.774142749491743, 0.940687, 0.371224, 0.366762, 0.7767692733154387, 0.944006, 0.377643, 0.365136, 0.7793951274492253, 0.94718, 0.384178, 0.363701, 0.7820216512729212, 0.95021, 0.39082, 0.362468, 0.7846475054067077, 0.953099, 0.397563, 0.361438, 0.7872740292304035, 0.955849, 0.4044, 0.360619, 0.7899005530540992, 0.958464, 0.411324, 0.360014, 0.7925264071878859, 0.960949, 0.418323, 0.35963, 0.7951529310115817, 0.96331, 0.42539, 0.359469, 0.7977787851453684, 0.965549, 0.432519, 0.359529, 0.8004053089690639, 0.967671, 0.439703, 0.35981, 0.8030311631028506, 0.96968, 0.446936, 0.360311, 0.8056576869265466, 0.971582, 0.45421, 0.36103, 0.8082835410603333, 0.973381, 0.46152, 0.361965, 0.8109100648840288, 0.975082, 0.468861, 0.363111, 0.8135365887077248, 0.97669, 0.476226, 0.364466, 0.8161624428415113, 0.97821, 0.483612, 0.366025, 0.8187889666652071, 0.979645, 0.491014, 0.367783, 0.8214148207989938, 0.981, 0.498428, 0.369734, 0.8240413446226895, 0.982279, 0.505851, 0.371874, 0.826667198756476, 0.983485, 0.51328, 0.374198, 0.829293722580172, 0.984622, 0.520713, 0.376698, 0.8319202464038677, 0.985693, 0.528148, 0.379371, 0.8345461005376542, 0.9867, 0.535582, 0.38221, 0.8371726243613502, 0.987646, 0.543015, 0.38521, 0.8397984784951367, 0.988533, 0.550446, 0.388365, 0.8424250023188324, 0.989363, 0.557873, 0.391671, 0.8450508564526191, 0.990138, 0.565296, 0.395122, 0.8476773802763149, 0.990871, 0.572706, 0.398714, 0.8503039041000107, 0.991558, 0.580107, 0.402441, 0.8529297582337974, 0.992196, 0.587502, 0.406299, 0.8555562820574931, 0.992785, 0.594891, 0.410283, 0.8581821361912796, 0.993326, 0.602275, 0.41439, 0.8608086600149754, 0.993834, 0.609644, 0.418613, 0.863434514148762, 0.994309, 0.616999, 0.42295, 0.8660610379724578, 0.994738, 0.62435, 0.427397, 0.8686875617961536, 0.995122, 0.631696, 0.431951, 0.8713134159299403, 0.99548, 0.639027, 0.436607, 0.8739399397536358, 0.99581, 0.646344, 0.441361, 0.8765657938874225, 0.996096, 0.653659, 0.446213, 0.8791923177111185, 0.996341, 0.660969, 0.45116, 0.881818171844905, 0.99658, 0.668256, 0.456192, 0.8844446956686007, 0.996775, 0.675541, 0.461314, 0.8870712194922967, 0.996925, 0.682828, 0.466526, 0.8896970736260832, 0.997077, 0.690088, 0.471811, 0.892323597449779, 0.997186, 0.697349, 0.477182, 0.8949494515835656, 0.997254, 0.704611, 0.482635, 0.8975759754072614, 0.997325, 0.711848, 0.488154, 0.9002018295410479, 0.997351, 0.719089, 0.493755, 0.9028283533647439, 0.997351, 0.726324, 0.499428, 0.9054548771884396, 0.997341, 0.733545, 0.505167, 0.9080807313222261, 0.997285, 0.740772, 0.510983, 0.9107072551459221, 0.997228, 0.747981, 0.516859, 0.9133331092797088, 0.997138, 0.75519, 0.522806, 0.9159596331034043, 0.997019, 0.762398, 0.528821, 0.918585487237191, 0.996898, 0.769591, 0.534892, 0.9212120110608868, 0.996727, 0.776795, 0.541039, 0.9238385348845826, 0.996571, 0.783977, 0.547233, 0.9264643890183692, 0.996369, 0.791167, 0.553499, 0.929090912842065, 0.996162, 0.798348, 0.55982, 0.9317167669758517, 0.995932, 0.805527, 0.566202, 0.9343432907995475, 0.99568, 0.812706, 0.572645, 0.9369691449333339, 0.995424, 0.819875, 0.57914, 0.9395956687570297, 0.995131, 0.827052, 0.585701, 0.9422215228908164, 0.994851, 0.834213, 0.592307, 0.9448480467145122, 0.994524, 0.841387, 0.598983, 0.9474745705382079, 0.994222, 0.84854, 0.605696, 0.9501004246719944, 0.993866, 0.855711, 0.612482, 0.9527269484956904, 0.993545, 0.862859, 0.619299, 0.9553528026294769, 0.99317, 0.870024, 0.626189, 0.9579793264531726, 0.992831, 0.877168, 0.633109, 0.9606051805869593, 0.99244, 0.88433, 0.640099, 0.9632317044106551, 0.992089, 0.89147, 0.647116, 0.9658582282343509, 0.991688, 0.898627, 0.654202, 0.9684840823681375, 0.991332, 0.905763, 0.661309, 0.9711106061918333, 0.99093, 0.912915, 0.668481, 0.9737364603256198, 0.99057, 0.920049, 0.675675, 0.9763629841493158, 0.990175, 0.927196, 0.682926, 0.9789888382831025, 0.989815, 0.934329, 0.690198, 0.981615362106798, 0.989434, 0.94147, 0.697519, 0.984241885930494, 0.989077, 0.948604, 0.704863, 0.9868677400642807, 0.988717, 0.955742, 0.712242, 0.9894942638879762, 0.988367, 0.962878, 0.719649, 0.9921201180217629, 0.988033, 0.970012, 0.727077, 0.9947466418454587, 0.987691, 0.977154, 0.734536, 0.9973724959792454, 0.987387, 0.984288, 0.742002, 0.9999990198029411, 0.987053, 0.991438, 0.749504]
+elasticRatioLUT.ColorSpace = 'RGB'
+elasticRatioLUT.NanColor = [0.0, 1.0, 0.0]
+elasticRatioLUT.ScalarRangeInitialized = 1.0
+
+# get opacity transfer function/opacity map for 'elasticRatio'
+elasticRatioPWF = GetOpacityTransferFunction('elasticRatio')
+elasticRatioPWF.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+elasticRatioPWF.ScalarRangeInitialized = 1
+
+# trace defaults for the display properties.
+elasticRatiovtsDisplay.Representation = 'Surface'
+elasticRatiovtsDisplay.ColorArrayName = ['POINTS', 'elasticRatio']
+elasticRatiovtsDisplay.LookupTable = elasticRatioLUT
+elasticRatiovtsDisplay.OSPRayScaleArray = 'elasticRatio'
+elasticRatiovtsDisplay.OSPRayScaleFunction = 'PiecewiseFunction'
+elasticRatiovtsDisplay.SelectOrientationVectors = 'None'
+elasticRatiovtsDisplay.ScaleFactor = 0.9
+elasticRatiovtsDisplay.SelectScaleArray = 'elasticRatio'
+elasticRatiovtsDisplay.GlyphType = 'Arrow'
+elasticRatiovtsDisplay.GlyphTableIndexArray = 'elasticRatio'
+elasticRatiovtsDisplay.GaussianRadius = 0.045
+elasticRatiovtsDisplay.SetScaleArray = ['POINTS', 'elasticRatio']
+elasticRatiovtsDisplay.ScaleTransferFunction = 'PiecewiseFunction'
+elasticRatiovtsDisplay.OpacityArray = ['POINTS', 'elasticRatio']
+elasticRatiovtsDisplay.OpacityTransferFunction = 'PiecewiseFunction'
+elasticRatiovtsDisplay.DataAxesGrid = 'GridAxesRepresentation'
+elasticRatiovtsDisplay.PolarAxes = 'PolarAxesRepresentation'
+elasticRatiovtsDisplay.ScalarOpacityFunction = elasticRatioPWF
+elasticRatiovtsDisplay.ScalarOpacityUnitDistance = 0.24673084980136809
+
+# init the 'PiecewiseFunction' selected for 'OSPRayScaleFunction'
+elasticRatiovtsDisplay.OSPRayScaleFunction.Points = [1.0, 0.8602941036224365, 0.5, 0.0, 1.213836476688135, 0.625, 0.5, 0.0, 1.3616352081298828, 0.6691176295280457, 0.5, 0.0, 1.6666333299996667, 0.8676470518112183, 0.5, 0.0, 1.7358490228652954, 0.6911764740943909, 0.5, 0.0, 2.0, 0.8014705777168274, 0.5, 0.0]
+
+# init the 'PiecewiseFunction' selected for 'ScaleTransferFunction'
+elasticRatiovtsDisplay.ScaleTransferFunction.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+
+# init the 'PiecewiseFunction' selected for 'OpacityTransferFunction'
+elasticRatiovtsDisplay.OpacityTransferFunction.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+
+# reset view to fit data
+renderView1.ResetCamera()
+
+#changing interaction mode based on data extents
+renderView1.InteractionMode = '2D'
+renderView1.CameraPosition = [9999.5, 5.51, 0.5]
+renderView1.CameraFocalPoint = [-0.5, 5.51, 0.5]
+renderView1.CameraViewUp = [0.0, 0.0, 1.0]
+
+# show color bar/color legend
+elasticRatiovtsDisplay.SetScalarBarVisibility(renderView1, True)
+
+# update the view to ensure updated data information
+renderView1.Update()
+
+# create a new 'Transform'
+transform1 = Transform(Input=elasticRatiovts)
+transform1.Transform = 'Transform'
+
+# Properties modified on transform1.Transform
+transform1.Transform.Scale = [1.0, 0.1, 1.0]
+
+# show data in view
+transform1Display = Show(transform1, renderView1)
+
+# trace defaults for the display properties.
+transform1Display.Representation = 'Surface'
+transform1Display.ColorArrayName = ['POINTS', 'elasticRatio']
+transform1Display.LookupTable = elasticRatioLUT
+transform1Display.OSPRayScaleArray = 'elasticRatio'
+transform1Display.OSPRayScaleFunction = 'PiecewiseFunction'
+transform1Display.SelectOrientationVectors = 'None'
+transform1Display.ScaleFactor = 0.098
+transform1Display.SelectScaleArray = 'elasticRatio'
+transform1Display.GlyphType = 'Arrow'
+transform1Display.GlyphTableIndexArray = 'elasticRatio'
+transform1Display.GaussianRadius = 0.0049
+transform1Display.SetScaleArray = ['POINTS', 'elasticRatio']
+transform1Display.ScaleTransferFunction = 'PiecewiseFunction'
+transform1Display.OpacityArray = ['POINTS', 'elasticRatio']
+transform1Display.OpacityTransferFunction = 'PiecewiseFunction'
+transform1Display.DataAxesGrid = 'GridAxesRepresentation'
+transform1Display.PolarAxes = 'PolarAxesRepresentation'
+transform1Display.ScalarOpacityFunction = elasticRatioPWF
+transform1Display.ScalarOpacityUnitDistance = 0.03626244811262771
+
+# init the 'PiecewiseFunction' selected for 'OSPRayScaleFunction'
+transform1Display.OSPRayScaleFunction.Points = [1.0, 0.8602941036224365, 0.5, 0.0, 1.213836476688135, 0.625, 0.5, 0.0, 1.3616352081298828, 0.6691176295280457, 0.5, 0.0, 1.6666333299996667, 0.8676470518112183, 0.5, 0.0, 1.7358490228652954, 0.6911764740943909, 0.5, 0.0, 2.0, 0.8014705777168274, 0.5, 0.0]
+
+# init the 'PiecewiseFunction' selected for 'ScaleTransferFunction'
+transform1Display.ScaleTransferFunction.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+
+# init the 'PiecewiseFunction' selected for 'OpacityTransferFunction'
+transform1Display.OpacityTransferFunction.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+
+# hide data in view
+Hide(elasticRatiovts, renderView1)
+
+# show color bar/color legend
+transform1Display.SetScalarBarVisibility(renderView1, True)
+
+# update the view to ensure updated data information
+renderView1.Update()
+
+# reset view to fit data
+renderView1.ResetCamera()
+
+# reset view to fit data
+renderView1.ResetCamera()
+
+# toggle 3D widget visibility (only when running from the GUI)
+Hide3DWidgets(proxy=transform1.Transform)
+
+# Apply a preset using its name. Note this may not work as expected when presets have duplicate names.
+elasticRatioLUT.ApplyPreset('Warm to Cool (Extended)', True)
+
+# change representation type
+transform1Display.SetRepresentationType('Point Gaussian')
+
+# Properties modified on transform1Display
+transform1Display.ShaderPreset = 'Plain circle'
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.Visibility = 1
+
+
+
+
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.XTitle = ''
+renderView1.AxesGrid.ZTitle = ' $\\theta$ '
+renderView1.AxesGrid.YTitle = ' $\\theta_\\mu$ '
+renderView1.AxesGrid.ZTitleFontSize = 20
+renderView1.AxesGrid.YTitleFontSize = 20
+
+
+
+renderView1.AxesGrid.FacesToRender = 0
+renderView1.AxesGrid.CullFrontface = 0
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.FacesToRender = 32
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.FacesToRender = 16
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.FacesToRender = 4
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.FacesToRender = 1
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ShowEdges = 0
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ShowTicks = 0
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ShowGrid = 1
+renderView1.AxesGrid.GridColor = [0.1803921568627451, 0.20392156862745098, 0.21176470588235294]
+# Properties modified on renderView1.AxesGrid
+# renderView1.AxesGrid.ShowGrid = 0
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.AxesToLabel = 7
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.DataScale = [1.0, 0.1, 1.0]
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.YAxisUseCustomLabels = 1
+renderView1.AxesGrid.YAxisLabels = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ZAxisUseCustomLabels = 1
+renderView1.AxesGrid.ZAxisLabels = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ZAxisLabels = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
+
+# Properties modified on renderView1.AxesGrid
+renderView1.AxesGrid.ZAxisLabels = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
+
+
+
+#### saving camera placements for all active views
+
+# current camera placement for renderView1
+renderView1.InteractionMode = '2D'
+renderView1.CameraPosition = [2.0704518571099406, 0.551, 0.5]
+renderView1.CameraFocalPoint = [-0.5, 0.551, 0.5]
+renderView1.CameraViewUp = [0.0, 0.0, 1.0]
+renderView1.CameraParallelScale = 0.6652818951391959
+
+
+
+
+
+renderView1.AxesGrid.YTitleFontSize = 65 #24
+renderView1.AxesGrid.ZTitleFontSize = 65
+renderView1.AxesGrid.YLabelFontSize = 45 #default:12
+renderView1.AxesGrid.ZLabelFontSize = 45
+#### uncomment the following to render all views
+# RenderAllViews()
+# alternatively, if you want to write images, you can use SaveScreenshot(...).
+
+
+# --------------------------------------------------------------------------------------------------------------------------------------------
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# --------------------------------------------------------------------------------------------------------------------------------------------
+
+if prestrain:
+ # set scalar coloring
+ ColorBy(transform1Display, ('POINTS', 'prestrainRatio'))
+ # get color transfer function/color map for 'prestrainRatio'
+ prestrainRatioLUT = GetColorTransferFunction('prestrainRatio')
+ prestrainRatioLUT.AutomaticRescaleRangeMode = "Grow and update on 'Apply'"
+ prestrainRatioLUT.InterpretValuesAsCategories = 0
+ prestrainRatioLUT.AnnotationsInitialized = 0
+ prestrainRatioLUT.ShowCategoricalColorsinDataRangeOnly = 0
+ prestrainRatioLUT.RescaleOnVisibilityChange = 0
+ prestrainRatioLUT.EnableOpacityMapping = 0
+ prestrainRatioLUT.RGBPoints = [1.0000497462439073, 0.001462, 0.000466, 0.013866, 1.0017355871052882, 0.002258, 0.001295, 0.018331, 1.0034209981245321, 0.003279, 0.002305, 0.023708, 1.005106838985913, 0.004512, 0.00349, 0.029965, 1.006792250005157, 0.00595, 0.004843, 0.03713, 1.008478090866538, 0.007588, 0.006356, 0.044973, 1.0101635018857817, 0.009426, 0.008022, 0.052844, 1.0118493427471627, 0.011465, 0.009828, 0.06075, 1.0135351836085438, 0.013708, 0.011771, 0.068667, 1.0152205946277877, 0.016156, 0.01384, 0.076603, 1.0169064354891686, 0.018815, 0.016026, 0.084584, 1.0185918465084125, 0.021692, 0.01832, 0.09261, 1.0202776873697934, 0.024792, 0.020715, 0.100676, 1.0219630983890373, 0.028123, 0.023201, 0.108787, 1.0236489392504182, 0.031696, 0.025765, 0.116965, 1.0253347801117991, 0.03552, 0.028397, 0.125209, 1.027020191131043, 0.039608, 0.03109, 0.133515, 1.028706031992424, 0.04383, 0.03383, 0.141886, 1.030391443011668, 0.048062, 0.036607, 0.150327, 1.032077283873049, 0.05232, 0.039407, 0.158841, 1.0337626948922927, 0.056615, 0.04216, 0.167446, 1.0354485357536738, 0.060949, 0.044794, 0.176129, 1.0371343766150547, 0.06533, 0.047318, 0.184892, 1.0388197876342986, 0.069764, 0.049726, 0.193735, 1.0405056284956795, 0.074257, 0.052017, 0.20266, 1.0421910395149234, 0.078815, 0.054184, 0.211667, 1.0438768803763043, 0.083446, 0.056225, 0.220755, 1.0455622913955482, 0.088155, 0.058133, 0.229922, 1.0472481322569291, 0.092949, 0.059904, 0.239164, 1.0489335432761733, 0.097833, 0.061531, 0.248477, 1.0506193841375542, 0.102815, 0.06301, 0.257854, 1.052305224998935, 0.107899, 0.064335, 0.267289, 1.053990636018179, 0.113094, 0.065492, 0.276784, 1.05567647687956, 0.118405, 0.066479, 0.286321, 1.0573618878988038, 0.123833, 0.067295, 0.295879, 1.0590477287601847, 0.12938, 0.067935, 0.305443, 1.0607331397794286, 0.135053, 0.068391, 0.315, 1.0624189806408095, 0.140858, 0.068654, 0.324538, 1.0641048215021904, 0.146785, 0.068738, 0.334011, 1.0657902325214343, 0.152839, 0.068637, 0.343404, 1.0674760733828152, 0.159018, 0.068354, 0.352688, 1.0691614844020592, 0.165308, 0.067911, 0.361816, 1.0708473252634403, 0.171713, 0.067305, 0.370771, 1.0725327362826842, 0.178212, 0.066576, 0.379497, 1.074218577144065, 0.184801, 0.065732, 0.387973, 1.075904418005446, 0.19146, 0.064818, 0.396152, 1.07758982902469, 0.198177, 0.063862, 0.404009, 1.0792756698860708, 0.204935, 0.062907, 0.411514, 1.0809610809053147, 0.211718, 0.061992, 0.418647, 1.0826469217666956, 0.218512, 0.061158, 0.425392, 1.0843323327859395, 0.225302, 0.060445, 0.431742, 1.0860181736473205, 0.232077, 0.059889, 0.437695, 1.0877040145087014, 0.238826, 0.059517, 0.443256, 1.0893894255279453, 0.245543, 0.059352, 0.448436, 1.0910752663893262, 0.25222, 0.059415, 0.453248, 1.0927606774085703, 0.258857, 0.059706, 0.45771, 1.0944465182699512, 0.265447, 0.060237, 0.46184, 1.0961319292891951, 0.271994, 0.060994, 0.46566, 1.097817770150576, 0.278493, 0.061978, 0.46919, 1.099503611011957, 0.284951, 0.063168, 0.472451, 1.1011890220312008, 0.291366, 0.064553, 0.475462, 1.1028748628925817, 0.29774, 0.066117, 0.478243, 1.1045602739118257, 0.304081, 0.067835, 0.480812, 1.1062461147732066, 0.310382, 0.069702, 0.483186, 1.1079315257924505, 0.316654, 0.07169, 0.48538, 1.1096173666538314, 0.322899, 0.073782, 0.487408, 1.1113032075152123, 0.329114, 0.075972, 0.489287, 1.1129886185344562, 0.335308, 0.078236, 0.491024, 1.1146744593958373, 0.341482, 0.080564, 0.492631, 1.1163598704150812, 0.347636, 0.082946, 0.494121, 1.1180457112764621, 0.353773, 0.085373, 0.495501, 1.119731122295706, 0.359898, 0.087831, 0.496778, 1.121416963157087, 0.366012, 0.090314, 0.49796, 1.1231028040184678, 0.372116, 0.092816, 0.499053, 1.1247882150377118, 0.378211, 0.095332, 0.500067, 1.1264740558990927, 0.384299, 0.097855, 0.501002, 1.1281594669183366, 0.390384, 0.100379, 0.501864, 1.1298453077797175, 0.396467, 0.102902, 0.502658, 1.1315307187989614, 0.402548, 0.10542, 0.503386, 1.1332165596603425, 0.408629, 0.10793, 0.504052, 1.1349019706795864, 0.414709, 0.110431, 0.504662, 1.1365878115409673, 0.420791, 0.11292, 0.505215, 1.1382736524023482, 0.426877, 0.115395, 0.505714, 1.1399590634215921, 0.432967, 0.117855, 0.50616, 1.141644904282973, 0.439062, 0.120298, 0.506555, 1.143330315302217, 0.445163, 0.122724, 0.506901, 1.1450161561635979, 0.451271, 0.125132, 0.507198, 1.1467015671828418, 0.457386, 0.127522, 0.507448, 1.148387408044223, 0.463508, 0.129893, 0.507652, 1.1500732489056036, 0.46964, 0.132245, 0.507809, 1.1517586599248475, 0.47578, 0.134577, 0.507921, 1.1534445007862284, 0.481929, 0.136891, 0.507989, 1.1551299118054725, 0.488088, 0.139186, 0.508011, 1.1568157526668534, 0.494258, 0.141462, 0.507988, 1.1585011636860973, 0.500438, 0.143719, 0.50792, 1.1601870045474783, 0.506629, 0.145958, 0.507806, 1.1618728454088592, 0.512831, 0.148179, 0.507648, 1.163558256428103, 0.519045, 0.150383, 0.507443, 1.165244097289484, 0.52527, 0.152569, 0.507192, 1.1669295083087279, 0.531507, 0.154739, 0.506895, 1.1686153491701088, 0.537755, 0.156894, 0.506551, 1.1703007601893527, 0.544015, 0.159033, 0.506159, 1.1719866010507336, 0.550287, 0.161158, 0.505719, 1.1736724419121147, 0.556571, 0.163269, 0.50523, 1.1753578529313584, 0.562866, 0.165368, 0.504692, 1.1770436937927395, 0.569172, 0.167454, 0.504105, 1.1787291048119835, 0.57549, 0.16953, 0.503466, 1.1804149456733644, 0.581819, 0.171596, 0.502777, 1.1821003566926083, 0.588158, 0.173652, 0.502035, 1.1837861975539892, 0.594508, 0.175701, 0.501241, 1.18547203841537, 0.600868, 0.177743, 0.500394, 1.187157449434614, 0.607238, 0.179779, 0.499492, 1.188843290295995, 0.613617, 0.181811, 0.498536, 1.1905287013152388, 0.620005, 0.18384, 0.497524, 1.1922145421766197, 0.626401, 0.185867, 0.496456, 1.1938999531958636, 0.632805, 0.187893, 0.495332, 1.1955857940572445, 0.639216, 0.189921, 0.49415, 1.1972716349186254, 0.645633, 0.191952, 0.49291, 1.1989570459378696, 0.652056, 0.193986, 0.491611, 1.2006428867992505, 0.658483, 0.196027, 0.490253, 1.2023282978184944, 0.664915, 0.198075, 0.488836, 1.2040141386798753, 0.671349, 0.200133, 0.487358, 1.2056995496991192, 0.677786, 0.202203, 0.485819, 1.2073853905605, 0.684224, 0.204286, 0.484219, 1.209071231421881, 0.690661, 0.206384, 0.482558, 1.210756642441125, 0.697098, 0.208501, 0.480835, 1.2124424833025058, 0.703532, 0.210638, 0.479049, 1.2141278943217497, 0.709962, 0.212797, 0.477201, 1.2158137351831309, 0.716387, 0.214982, 0.47529, 1.2174991462023748, 0.722805, 0.217194, 0.473316, 1.2191849870637557, 0.729216, 0.219437, 0.471279, 1.2208703980829996, 0.735616, 0.221713, 0.46918, 1.2225562389443805, 0.742004, 0.224025, 0.467018, 1.2242420798057614, 0.748378, 0.226377, 0.464794, 1.2259274908250053, 0.754737, 0.228772, 0.462509, 1.2276133316863862, 0.761077, 0.231214, 0.460162, 1.22929874270563, 0.767398, 0.233705, 0.457755, 1.230984583567011, 0.773695, 0.236249, 0.455289, 1.2326699945862551, 0.779968, 0.238851, 0.452765, 1.2343558354476358, 0.786212, 0.241514, 0.450184, 1.236041676309017, 0.792427, 0.244242, 0.447543, 1.2377270873282609, 0.798608, 0.24704, 0.444848, 1.2394129281896418, 0.804752, 0.249911, 0.442102, 1.2410983392088857, 0.810855, 0.252861, 0.439305, 1.2427841800702666, 0.816914, 0.255895, 0.436461, 1.2444695910895105, 0.822926, 0.259016, 0.433573, 1.2461554319508914, 0.828886, 0.262229, 0.430644, 1.2478412728122723, 0.834791, 0.26554, 0.427671, 1.2495266838315162, 0.840636, 0.268953, 0.424666, 1.2512125246928971, 0.846416, 0.272473, 0.421631, 1.252897935712141, 0.852126, 0.276106, 0.418573, 1.2545837765735222, 0.857763, 0.279857, 0.415496, 1.2562691875927658, 0.86332, 0.283729, 0.412403, 1.257955028454147, 0.868793, 0.287728, 0.409303, 1.2596408693155277, 0.874176, 0.291859, 0.406205, 1.2613262803347718, 0.879464, 0.296125, 0.403118, 1.2630121211961527, 0.884651, 0.30053, 0.400047, 1.2646975322153966, 0.889731, 0.305079, 0.397002, 1.2663833730767775, 0.8947, 0.309773, 0.393995, 1.2680687840960214, 0.899552, 0.314616, 0.391037, 1.2697546249574023, 0.904281, 0.31961, 0.388137, 1.2714404658187832, 0.908884, 0.324755, 0.385308, 1.2731258768380274, 0.913354, 0.330052, 0.382563, 1.274811717699408, 0.917689, 0.3355, 0.379915, 1.276497128718652, 0.921884, 0.341098, 0.377376, 1.278182969580033, 0.925937, 0.346844, 0.374959, 1.279868380599277, 0.929845, 0.352734, 0.372677, 1.2815542214606577, 0.933606, 0.358764, 0.370541, 1.2832400623220388, 0.937221, 0.364929, 0.368567, 1.2849254733412827, 0.940687, 0.371224, 0.366762, 1.2866113142026636, 0.944006, 0.377643, 0.365136, 1.2882967252219075, 0.94718, 0.384178, 0.363701, 1.2899825660832884, 0.95021, 0.39082, 0.362468, 1.2916679771025323, 0.953099, 0.397563, 0.361438, 1.2933538179639132, 0.955849, 0.4044, 0.360619, 1.2950396588252944, 0.958464, 0.411324, 0.360014, 1.296725069844538, 0.960949, 0.418323, 0.35963, 1.2984109107059192, 0.96331, 0.42539, 0.359469, 1.300096321725163, 0.965549, 0.432519, 0.359529, 1.301782162586544, 0.967671, 0.439703, 0.35981, 1.3034675736057877, 0.96968, 0.446936, 0.360311, 1.3051534144671688, 0.971582, 0.45421, 0.36103, 1.3068388254864127, 0.973381, 0.46152, 0.361965, 1.3085246663477936, 0.975082, 0.468861, 0.363111, 1.3102105072091748, 0.97669, 0.476226, 0.364466, 1.3118959182284184, 0.97821, 0.483612, 0.366025, 1.3135817590897994, 0.979645, 0.491014, 0.367783, 1.3152671701090433, 0.981, 0.498428, 0.369734, 1.3169530109704244, 0.982279, 0.505851, 0.371874, 1.318638421989668, 0.983485, 0.51328, 0.374198, 1.3203242628510492, 0.984622, 0.520713, 0.376698, 1.32201010371243, 0.985693, 0.528148, 0.379371, 1.323695514731674, 0.9867, 0.535582, 0.38221, 1.325381355593055, 0.987646, 0.543015, 0.38521, 1.3270667666122988, 0.988533, 0.550446, 0.388365, 1.3287526074736797, 0.989363, 0.557873, 0.391671, 1.3304380184929236, 0.990138, 0.565296, 0.395122, 1.3321238593543048, 0.990871, 0.572706, 0.398714, 1.3338097002156855, 0.991558, 0.580107, 0.402441, 1.3354951112349294, 0.992196, 0.587502, 0.406299, 1.3371809520963103, 0.992785, 0.594891, 0.410283, 1.3388663631155544, 0.993326, 0.602275, 0.41439, 1.3405522039769353, 0.993834, 0.609644, 0.418613, 1.3422376149961792, 0.994309, 0.616999, 0.42295, 1.3439234558575601, 0.994738, 0.62435, 0.427397, 1.345609296718941, 0.995122, 0.631696, 0.431951, 1.347294707738185, 0.99548, 0.639027, 0.436607, 1.3489805485995658, 0.99581, 0.646344, 0.441361, 1.3506659596188098, 0.996096, 0.653659, 0.446213, 1.3523518004801907, 0.996341, 0.660969, 0.45116, 1.3540372114994346, 0.99658, 0.668256, 0.456192, 1.3557230523608155, 0.996775, 0.675541, 0.461314, 1.3574088932221966, 0.996925, 0.682828, 0.466526, 1.3590943042414403, 0.997077, 0.690088, 0.471811, 1.3607801451028214, 0.997186, 0.697349, 0.477182, 1.3624655561220653, 0.997254, 0.704611, 0.482635, 1.3641513969834462, 0.997325, 0.711848, 0.488154, 1.36583680800269, 0.997351, 0.719089, 0.493755, 1.367522648864071, 0.997351, 0.726324, 0.499428, 1.369208489725452, 0.997341, 0.733545, 0.505167, 1.3708939007446959, 0.997285, 0.740772, 0.510983, 1.372579741606077, 0.997228, 0.747981, 0.516859, 1.3742651526253207, 0.997138, 0.75519, 0.522806, 1.3759509934867016, 0.997019, 0.762398, 0.528821, 1.3776364045059455, 0.996898, 0.769591, 0.534892, 1.3793222453673266, 0.996727, 0.776795, 0.541039, 1.3810080862287073, 0.996571, 0.783977, 0.547233, 1.3826934972479514, 0.996369, 0.791167, 0.553499, 1.3843793381093323, 0.996162, 0.798348, 0.55982, 1.3860647491285762, 0.995932, 0.805527, 0.566202, 1.3877505899899572, 0.99568, 0.812706, 0.572645, 1.389436001009201, 0.995424, 0.819875, 0.57914, 1.391121841870582, 0.995131, 0.827052, 0.585701, 1.3928072528898259, 0.994851, 0.834213, 0.592307, 1.394493093751207, 0.994524, 0.841387, 0.598983, 1.3961789346125877, 0.994222, 0.84854, 0.605696, 1.3978643456318316, 0.993866, 0.855711, 0.612482, 1.3995501864932127, 0.993545, 0.862859, 0.619299, 1.4012355975124566, 0.99317, 0.870024, 0.626189, 1.4029214383738373, 0.992831, 0.877168, 0.633109, 1.4046068493930814, 0.99244, 0.88433, 0.640099, 1.4062926902544624, 0.992089, 0.89147, 0.647116, 1.4079785311158433, 0.991688, 0.898627, 0.654202, 1.4096639421350872, 0.991332, 0.905763, 0.661309, 1.411349782996468, 0.99093, 0.912915, 0.668481, 1.413035194015712, 0.99057, 0.920049, 0.675675, 1.4147210348770929, 0.990175, 0.927196, 0.682926, 1.416406445896337, 0.989815, 0.934329, 0.690198, 1.4180922867577177, 0.989434, 0.94147, 0.697519, 1.4197781276190988, 0.989077, 0.948604, 0.704863, 1.4214635386383427, 0.988717, 0.955742, 0.712242, 1.4231493794997236, 0.988367, 0.962878, 0.719649, 1.4248347905189676, 0.988033, 0.970012, 0.727077, 1.4265206313803485, 0.987691, 0.977154, 0.734536, 1.4282060423995924, 0.987387, 0.984288, 0.742002, 1.4298918832609733, 0.987053, 0.991438, 0.749504]
+ prestrainRatioLUT.UseLogScale = 0
+ prestrainRatioLUT.ColorSpace = 'RGB'
+ prestrainRatioLUT.UseBelowRangeColor = 0
+ prestrainRatioLUT.BelowRangeColor = [0.0, 0.0, 0.0]
+ prestrainRatioLUT.UseAboveRangeColor = 0
+ prestrainRatioLUT.AboveRangeColor = [0.5, 0.5, 0.5]
+ prestrainRatioLUT.NanColor = [0.0, 1.0, 0.0]
+ prestrainRatioLUT.NanOpacity = 1.0
+ prestrainRatioLUT.Discretize = 1
+ prestrainRatioLUT.NumberOfTableValues = 256
+ prestrainRatioLUT.ScalarRangeInitialized = 1.0
+ prestrainRatioLUT.HSVWrap = 0
+ prestrainRatioLUT.VectorComponent = 0
+ prestrainRatioLUT.VectorMode = 'Magnitude'
+ prestrainRatioLUT.AllowDuplicateScalars = 1
+ prestrainRatioLUT.Annotations = []
+ prestrainRatioLUT.ActiveAnnotatedValues = []
+ prestrainRatioLUT.IndexedColors = []
+ prestrainRatioLUT.IndexedOpacities = []
+
+ # Apply a preset using its name. Note this may not work as expected when presets have duplicate names.
+ prestrainRatioLUT.ApplyPreset('Warm to Cool (Extended)', True)
+
+ # get opacity transfer function/opacity map for 'prestrainRatio'
+ prestrainRatioPWF = GetOpacityTransferFunction('prestrainRatio')
+ prestrainRatioPWF.Points = [1.0000497462439073, 0.8602941036224365, 0.5, 0.0, 1.0919656743557353, 0.625, 0.5, 0.0, 1.1554957969270676, 0.6691176295280457, 0.5, 0.0, 1.2865968414177669, 0.8676470518112183, 0.5, 0.0, 1.3163486627542458, 0.6911764740943909, 0.5, 0.0, 1.4298918832609733, 0.8014705777168274, 0.5, 0.0]
+ prestrainRatioPWF.AllowDuplicateScalars = 1
+ prestrainRatioPWF.UseLogScale = 0
+ prestrainRatioPWF.ScalarRangeInitialized = 1
+
+ # Apply a preset using its name. Note this may not work as expected when presets have duplicate names.
+ prestrainRatioLUT.ApplyPreset('Warm to Cool (Extended)', True)
+
+ # invert the transfer function
+ prestrainRatioLUT.InvertTransferFunction()
+
+
+
+ # get active source.
+ transform1 = GetActiveSource()
+
+ # get active view
+ renderView1 = GetActiveViewOrCreate('RenderView')
+ # uncomment following to set a specific view size
+ # renderView1.ViewSize = [1067, 547]
+
+ # get display properties
+ transform1Display = GetDisplayProperties(transform1, view=renderView1)
+
+ # show color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, True)
+
+ # hide color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, False)
+
+ # show color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, True)
+
+ # hide color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, False)
+
+ # set scalar coloring using an separate color/opacity maps
+ ColorBy(transform1Display, ('POINTS', 'prestrainRatio'), True)
+
+ # get color transfer function/color map for 'prestrainRatio'
+ prestrainRatioLUT = GetColorTransferFunction('prestrainRatio')
+ prestrainRatioLUT.RGBPoints = [1.0000497462439073, 0.12549, 0.0, 0.380392, 1.010795799669334, 0.113725, 0.0235294, 0.45098, 1.0215418530947606, 0.105882, 0.0509804, 0.509804, 1.032287906520187, 0.0392157, 0.0392157, 0.560784, 1.043033959945614, 0.0313725, 0.0980392, 0.6, 1.0537800133710404, 0.0431373, 0.164706, 0.639216, 1.0645260667964673, 0.054902, 0.243137, 0.678431, 1.0752721202218938, 0.054902, 0.317647, 0.709804, 1.0860181736473205, 0.0509804, 0.396078, 0.741176, 1.0967642270727471, 0.0392157, 0.466667, 0.768627, 1.1075102804981738, 0.0313725, 0.537255, 0.788235, 1.1234423793067114, 0.0313725, 0.615686, 0.811765, 1.1369149214072372, 0.0235294, 0.709804, 0.831373, 1.1497461390393338, 0.0509804, 0.8, 0.85098, 1.1591553834186372, 0.0705882, 0.854902, 0.870588, 1.1694204434927418, 0.262745, 0.901961, 0.862745, 1.177332977550952, 0.423529, 0.941176, 0.87451, 1.187383976240822, 0.572549, 0.964706, 0.835294, 1.1948688173727002, 0.658824, 0.980392, 0.843137, 1.2014982726519143, 0.764706, 0.980392, 0.866667, 1.2079136665468941, 0.827451, 0.980392, 0.886275, 1.2145409726154233, 0.913725, 0.988235, 0.937255, 1.2149708147524403, 1.0, 1.0, 1.0, 1.2154006568894573, 0.988235, 0.980392, 0.870588, 1.2220279629579864, 0.992157, 0.964706, 0.713725, 1.2278020323845367, 0.988235, 0.956863, 0.643137, 1.2389224783113053, 0.980392, 0.917647, 0.509804, 1.2498288628538392, 0.968627, 0.87451, 0.407843, 1.2598798615437092, 0.94902, 0.823529, 0.321569, 1.2687010818795734, 0.929412, 0.776471, 0.278431, 1.2794471353050003, 0.909804, 0.717647, 0.235294, 1.2901931887304268, 0.890196, 0.658824, 0.196078, 1.3009392421558534, 0.878431, 0.619608, 0.168627, 1.31168529558128, 0.870588, 0.54902, 0.156863, 1.3224313490067068, 0.85098, 0.47451, 0.145098, 1.3331774024321335, 0.831373, 0.411765, 0.133333, 1.3439234558575601, 0.811765, 0.345098, 0.113725, 1.3546695092829868, 0.788235, 0.266667, 0.0941176, 1.3654155627084135, 0.741176, 0.184314, 0.0745098, 1.3761616161338401, 0.690196, 0.12549, 0.0627451, 1.3869076695592666, 0.619608, 0.0627451, 0.0431373, 1.3976537229846933, 0.54902, 0.027451, 0.0705882, 1.40839977641012, 0.470588, 0.0156863, 0.0901961, 1.4191458298355466, 0.4, 0.00392157, 0.101961, 1.4298918832609733, 0.34902, 0.0, 0.129412]
+ prestrainRatioLUT.ColorSpace = 'Lab'
+ prestrainRatioLUT.NanColor = [0.250004, 0.0, 0.0]
+ prestrainRatioLUT.ScalarRangeInitialized = 1.0
+
+ # Hide the scalar bar for this color map if no visible data is colored by it.
+ HideScalarBarIfNotNeeded(prestrainRatioLUT, renderView1)
+
+ # rescale color and/or opacity maps used to include current data range
+ transform1Display.RescaleTransferFunctionToDataRange(True, False)
+
+ # show color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, True)
+
+ # get separate color transfer function/color map for 'prestrainRatio'
+ separate_transform1Display_prestrainRatioLUT = GetColorTransferFunction('prestrainRatio', transform1Display, separate=True)
+ separate_transform1Display_prestrainRatioLUT.RGBPoints = [1.0000497462439073, 0.001462, 0.000466, 0.013866, 1.0017355871052882, 0.002258, 0.001295, 0.018331, 1.0034209981245321, 0.003279, 0.002305, 0.023708, 1.005106838985913, 0.004512, 0.00349, 0.029965, 1.006792250005157, 0.00595, 0.004843, 0.03713, 1.008478090866538, 0.007588, 0.006356, 0.044973, 1.0101635018857817, 0.009426, 0.008022, 0.052844, 1.0118493427471627, 0.011465, 0.009828, 0.06075, 1.0135351836085438, 0.013708, 0.011771, 0.068667, 1.0152205946277877, 0.016156, 0.01384, 0.076603, 1.0169064354891686, 0.018815, 0.016026, 0.084584, 1.0185918465084125, 0.021692, 0.01832, 0.09261, 1.0202776873697934, 0.024792, 0.020715, 0.100676, 1.0219630983890373, 0.028123, 0.023201, 0.108787, 1.0236489392504182, 0.031696, 0.025765, 0.116965, 1.0253347801117991, 0.03552, 0.028397, 0.125209, 1.027020191131043, 0.039608, 0.03109, 0.133515, 1.028706031992424, 0.04383, 0.03383, 0.141886, 1.030391443011668, 0.048062, 0.036607, 0.150327, 1.032077283873049, 0.05232, 0.039407, 0.158841, 1.0337626948922927, 0.056615, 0.04216, 0.167446, 1.0354485357536738, 0.060949, 0.044794, 0.176129, 1.0371343766150547, 0.06533, 0.047318, 0.184892, 1.0388197876342986, 0.069764, 0.049726, 0.193735, 1.0405056284956795, 0.074257, 0.052017, 0.20266, 1.0421910395149234, 0.078815, 0.054184, 0.211667, 1.0438768803763043, 0.083446, 0.056225, 0.220755, 1.0455622913955482, 0.088155, 0.058133, 0.229922, 1.0472481322569291, 0.092949, 0.059904, 0.239164, 1.0489335432761733, 0.097833, 0.061531, 0.248477, 1.0506193841375542, 0.102815, 0.06301, 0.257854, 1.052305224998935, 0.107899, 0.064335, 0.267289, 1.053990636018179, 0.113094, 0.065492, 0.276784, 1.05567647687956, 0.118405, 0.066479, 0.286321, 1.0573618878988038, 0.123833, 0.067295, 0.295879, 1.0590477287601847, 0.12938, 0.067935, 0.305443, 1.0607331397794286, 0.135053, 0.068391, 0.315, 1.0624189806408095, 0.140858, 0.068654, 0.324538, 1.0641048215021904, 0.146785, 0.068738, 0.334011, 1.0657902325214343, 0.152839, 0.068637, 0.343404, 1.0674760733828152, 0.159018, 0.068354, 0.352688, 1.0691614844020592, 0.165308, 0.067911, 0.361816, 1.0708473252634403, 0.171713, 0.067305, 0.370771, 1.0725327362826842, 0.178212, 0.066576, 0.379497, 1.074218577144065, 0.184801, 0.065732, 0.387973, 1.075904418005446, 0.19146, 0.064818, 0.396152, 1.07758982902469, 0.198177, 0.063862, 0.404009, 1.0792756698860708, 0.204935, 0.062907, 0.411514, 1.0809610809053147, 0.211718, 0.061992, 0.418647, 1.0826469217666956, 0.218512, 0.061158, 0.425392, 1.0843323327859395, 0.225302, 0.060445, 0.431742, 1.0860181736473205, 0.232077, 0.059889, 0.437695, 1.0877040145087014, 0.238826, 0.059517, 0.443256, 1.0893894255279453, 0.245543, 0.059352, 0.448436, 1.0910752663893262, 0.25222, 0.059415, 0.453248, 1.0927606774085703, 0.258857, 0.059706, 0.45771, 1.0944465182699512, 0.265447, 0.060237, 0.46184, 1.0961319292891951, 0.271994, 0.060994, 0.46566, 1.097817770150576, 0.278493, 0.061978, 0.46919, 1.099503611011957, 0.284951, 0.063168, 0.472451, 1.1011890220312008, 0.291366, 0.064553, 0.475462, 1.1028748628925817, 0.29774, 0.066117, 0.478243, 1.1045602739118257, 0.304081, 0.067835, 0.480812, 1.1062461147732066, 0.310382, 0.069702, 0.483186, 1.1079315257924505, 0.316654, 0.07169, 0.48538, 1.1096173666538314, 0.322899, 0.073782, 0.487408, 1.1113032075152123, 0.329114, 0.075972, 0.489287, 1.1129886185344562, 0.335308, 0.078236, 0.491024, 1.1146744593958373, 0.341482, 0.080564, 0.492631, 1.1163598704150812, 0.347636, 0.082946, 0.494121, 1.1180457112764621, 0.353773, 0.085373, 0.495501, 1.119731122295706, 0.359898, 0.087831, 0.496778, 1.121416963157087, 0.366012, 0.090314, 0.49796, 1.1231028040184678, 0.372116, 0.092816, 0.499053, 1.1247882150377118, 0.378211, 0.095332, 0.500067, 1.1264740558990927, 0.384299, 0.097855, 0.501002, 1.1281594669183366, 0.390384, 0.100379, 0.501864, 1.1298453077797175, 0.396467, 0.102902, 0.502658, 1.1315307187989614, 0.402548, 0.10542, 0.503386, 1.1332165596603425, 0.408629, 0.10793, 0.504052, 1.1349019706795864, 0.414709, 0.110431, 0.504662, 1.1365878115409673, 0.420791, 0.11292, 0.505215, 1.1382736524023482, 0.426877, 0.115395, 0.505714, 1.1399590634215921, 0.432967, 0.117855, 0.50616, 1.141644904282973, 0.439062, 0.120298, 0.506555, 1.143330315302217, 0.445163, 0.122724, 0.506901, 1.1450161561635979, 0.451271, 0.125132, 0.507198, 1.1467015671828418, 0.457386, 0.127522, 0.507448, 1.148387408044223, 0.463508, 0.129893, 0.507652, 1.1500732489056036, 0.46964, 0.132245, 0.507809, 1.1517586599248475, 0.47578, 0.134577, 0.507921, 1.1534445007862284, 0.481929, 0.136891, 0.507989, 1.1551299118054725, 0.488088, 0.139186, 0.508011, 1.1568157526668534, 0.494258, 0.141462, 0.507988, 1.1585011636860973, 0.500438, 0.143719, 0.50792, 1.1601870045474783, 0.506629, 0.145958, 0.507806, 1.1618728454088592, 0.512831, 0.148179, 0.507648, 1.163558256428103, 0.519045, 0.150383, 0.507443, 1.165244097289484, 0.52527, 0.152569, 0.507192, 1.1669295083087279, 0.531507, 0.154739, 0.506895, 1.1686153491701088, 0.537755, 0.156894, 0.506551, 1.1703007601893527, 0.544015, 0.159033, 0.506159, 1.1719866010507336, 0.550287, 0.161158, 0.505719, 1.1736724419121147, 0.556571, 0.163269, 0.50523, 1.1753578529313584, 0.562866, 0.165368, 0.504692, 1.1770436937927395, 0.569172, 0.167454, 0.504105, 1.1787291048119835, 0.57549, 0.16953, 0.503466, 1.1804149456733644, 0.581819, 0.171596, 0.502777, 1.1821003566926083, 0.588158, 0.173652, 0.502035, 1.1837861975539892, 0.594508, 0.175701, 0.501241, 1.18547203841537, 0.600868, 0.177743, 0.500394, 1.187157449434614, 0.607238, 0.179779, 0.499492, 1.188843290295995, 0.613617, 0.181811, 0.498536, 1.1905287013152388, 0.620005, 0.18384, 0.497524, 1.1922145421766197, 0.626401, 0.185867, 0.496456, 1.1938999531958636, 0.632805, 0.187893, 0.495332, 1.1955857940572445, 0.639216, 0.189921, 0.49415, 1.1972716349186254, 0.645633, 0.191952, 0.49291, 1.1989570459378696, 0.652056, 0.193986, 0.491611, 1.2006428867992505, 0.658483, 0.196027, 0.490253, 1.2023282978184944, 0.664915, 0.198075, 0.488836, 1.2040141386798753, 0.671349, 0.200133, 0.487358, 1.2056995496991192, 0.677786, 0.202203, 0.485819, 1.2073853905605, 0.684224, 0.204286, 0.484219, 1.209071231421881, 0.690661, 0.206384, 0.482558, 1.210756642441125, 0.697098, 0.208501, 0.480835, 1.2124424833025058, 0.703532, 0.210638, 0.479049, 1.2141278943217497, 0.709962, 0.212797, 0.477201, 1.2158137351831309, 0.716387, 0.214982, 0.47529, 1.2174991462023748, 0.722805, 0.217194, 0.473316, 1.2191849870637557, 0.729216, 0.219437, 0.471279, 1.2208703980829996, 0.735616, 0.221713, 0.46918, 1.2225562389443805, 0.742004, 0.224025, 0.467018, 1.2242420798057614, 0.748378, 0.226377, 0.464794, 1.2259274908250053, 0.754737, 0.228772, 0.462509, 1.2276133316863862, 0.761077, 0.231214, 0.460162, 1.22929874270563, 0.767398, 0.233705, 0.457755, 1.230984583567011, 0.773695, 0.236249, 0.455289, 1.2326699945862551, 0.779968, 0.238851, 0.452765, 1.2343558354476358, 0.786212, 0.241514, 0.450184, 1.236041676309017, 0.792427, 0.244242, 0.447543, 1.2377270873282609, 0.798608, 0.24704, 0.444848, 1.2394129281896418, 0.804752, 0.249911, 0.442102, 1.2410983392088857, 0.810855, 0.252861, 0.439305, 1.2427841800702666, 0.816914, 0.255895, 0.436461, 1.2444695910895105, 0.822926, 0.259016, 0.433573, 1.2461554319508914, 0.828886, 0.262229, 0.430644, 1.2478412728122723, 0.834791, 0.26554, 0.427671, 1.2495266838315162, 0.840636, 0.268953, 0.424666, 1.2512125246928971, 0.846416, 0.272473, 0.421631, 1.252897935712141, 0.852126, 0.276106, 0.418573, 1.2545837765735222, 0.857763, 0.279857, 0.415496, 1.2562691875927658, 0.86332, 0.283729, 0.412403, 1.257955028454147, 0.868793, 0.287728, 0.409303, 1.2596408693155277, 0.874176, 0.291859, 0.406205, 1.2613262803347718, 0.879464, 0.296125, 0.403118, 1.2630121211961527, 0.884651, 0.30053, 0.400047, 1.2646975322153966, 0.889731, 0.305079, 0.397002, 1.2663833730767775, 0.8947, 0.309773, 0.393995, 1.2680687840960214, 0.899552, 0.314616, 0.391037, 1.2697546249574023, 0.904281, 0.31961, 0.388137, 1.2714404658187832, 0.908884, 0.324755, 0.385308, 1.2731258768380274, 0.913354, 0.330052, 0.382563, 1.274811717699408, 0.917689, 0.3355, 0.379915, 1.276497128718652, 0.921884, 0.341098, 0.377376, 1.278182969580033, 0.925937, 0.346844, 0.374959, 1.279868380599277, 0.929845, 0.352734, 0.372677, 1.2815542214606577, 0.933606, 0.358764, 0.370541, 1.2832400623220388, 0.937221, 0.364929, 0.368567, 1.2849254733412827, 0.940687, 0.371224, 0.366762, 1.2866113142026636, 0.944006, 0.377643, 0.365136, 1.2882967252219075, 0.94718, 0.384178, 0.363701, 1.2899825660832884, 0.95021, 0.39082, 0.362468, 1.2916679771025323, 0.953099, 0.397563, 0.361438, 1.2933538179639132, 0.955849, 0.4044, 0.360619, 1.2950396588252944, 0.958464, 0.411324, 0.360014, 1.296725069844538, 0.960949, 0.418323, 0.35963, 1.2984109107059192, 0.96331, 0.42539, 0.359469, 1.300096321725163, 0.965549, 0.432519, 0.359529, 1.301782162586544, 0.967671, 0.439703, 0.35981, 1.3034675736057877, 0.96968, 0.446936, 0.360311, 1.3051534144671688, 0.971582, 0.45421, 0.36103, 1.3068388254864127, 0.973381, 0.46152, 0.361965, 1.3085246663477936, 0.975082, 0.468861, 0.363111, 1.3102105072091748, 0.97669, 0.476226, 0.364466, 1.3118959182284184, 0.97821, 0.483612, 0.366025, 1.3135817590897994, 0.979645, 0.491014, 0.367783, 1.3152671701090433, 0.981, 0.498428, 0.369734, 1.3169530109704244, 0.982279, 0.505851, 0.371874, 1.318638421989668, 0.983485, 0.51328, 0.374198, 1.3203242628510492, 0.984622, 0.520713, 0.376698, 1.32201010371243, 0.985693, 0.528148, 0.379371, 1.323695514731674, 0.9867, 0.535582, 0.38221, 1.325381355593055, 0.987646, 0.543015, 0.38521, 1.3270667666122988, 0.988533, 0.550446, 0.388365, 1.3287526074736797, 0.989363, 0.557873, 0.391671, 1.3304380184929236, 0.990138, 0.565296, 0.395122, 1.3321238593543048, 0.990871, 0.572706, 0.398714, 1.3338097002156855, 0.991558, 0.580107, 0.402441, 1.3354951112349294, 0.992196, 0.587502, 0.406299, 1.3371809520963103, 0.992785, 0.594891, 0.410283, 1.3388663631155544, 0.993326, 0.602275, 0.41439, 1.3405522039769353, 0.993834, 0.609644, 0.418613, 1.3422376149961792, 0.994309, 0.616999, 0.42295, 1.3439234558575601, 0.994738, 0.62435, 0.427397, 1.345609296718941, 0.995122, 0.631696, 0.431951, 1.347294707738185, 0.99548, 0.639027, 0.436607, 1.3489805485995658, 0.99581, 0.646344, 0.441361, 1.3506659596188098, 0.996096, 0.653659, 0.446213, 1.3523518004801907, 0.996341, 0.660969, 0.45116, 1.3540372114994346, 0.99658, 0.668256, 0.456192, 1.3557230523608155, 0.996775, 0.675541, 0.461314, 1.3574088932221966, 0.996925, 0.682828, 0.466526, 1.3590943042414403, 0.997077, 0.690088, 0.471811, 1.3607801451028214, 0.997186, 0.697349, 0.477182, 1.3624655561220653, 0.997254, 0.704611, 0.482635, 1.3641513969834462, 0.997325, 0.711848, 0.488154, 1.36583680800269, 0.997351, 0.719089, 0.493755, 1.367522648864071, 0.997351, 0.726324, 0.499428, 1.369208489725452, 0.997341, 0.733545, 0.505167, 1.3708939007446959, 0.997285, 0.740772, 0.510983, 1.372579741606077, 0.997228, 0.747981, 0.516859, 1.3742651526253207, 0.997138, 0.75519, 0.522806, 1.3759509934867016, 0.997019, 0.762398, 0.528821, 1.3776364045059455, 0.996898, 0.769591, 0.534892, 1.3793222453673266, 0.996727, 0.776795, 0.541039, 1.3810080862287073, 0.996571, 0.783977, 0.547233, 1.3826934972479514, 0.996369, 0.791167, 0.553499, 1.3843793381093323, 0.996162, 0.798348, 0.55982, 1.3860647491285762, 0.995932, 0.805527, 0.566202, 1.3877505899899572, 0.99568, 0.812706, 0.572645, 1.389436001009201, 0.995424, 0.819875, 0.57914, 1.391121841870582, 0.995131, 0.827052, 0.585701, 1.3928072528898259, 0.994851, 0.834213, 0.592307, 1.394493093751207, 0.994524, 0.841387, 0.598983, 1.3961789346125877, 0.994222, 0.84854, 0.605696, 1.3978643456318316, 0.993866, 0.855711, 0.612482, 1.3995501864932127, 0.993545, 0.862859, 0.619299, 1.4012355975124566, 0.99317, 0.870024, 0.626189, 1.4029214383738373, 0.992831, 0.877168, 0.633109, 1.4046068493930814, 0.99244, 0.88433, 0.640099, 1.4062926902544624, 0.992089, 0.89147, 0.647116, 1.4079785311158433, 0.991688, 0.898627, 0.654202, 1.4096639421350872, 0.991332, 0.905763, 0.661309, 1.411349782996468, 0.99093, 0.912915, 0.668481, 1.413035194015712, 0.99057, 0.920049, 0.675675, 1.4147210348770929, 0.990175, 0.927196, 0.682926, 1.416406445896337, 0.989815, 0.934329, 0.690198, 1.4180922867577177, 0.989434, 0.94147, 0.697519, 1.4197781276190988, 0.989077, 0.948604, 0.704863, 1.4214635386383427, 0.988717, 0.955742, 0.712242, 1.4231493794997236, 0.988367, 0.962878, 0.719649, 1.4248347905189676, 0.988033, 0.970012, 0.727077, 1.4265206313803485, 0.987691, 0.977154, 0.734536, 1.4282060423995924, 0.987387, 0.984288, 0.742002, 1.4298918832609733, 0.987053, 0.991438, 0.749504]
+ separate_transform1Display_prestrainRatioLUT.ColorSpace = 'RGB'
+ separate_transform1Display_prestrainRatioLUT.NanColor = [0.0, 1.0, 0.0]
+ separate_transform1Display_prestrainRatioLUT.ScalarRangeInitialized = 1.0
+
+ # get separate opacity transfer function/opacity map for 'prestrainRatio'
+ separate_transform1Display_prestrainRatioPWF = GetOpacityTransferFunction('prestrainRatio', transform1Display, separate=True)
+ separate_transform1Display_prestrainRatioPWF.Points = [1.0000497462439073, 0.8602941036224365, 0.5, 0.0, 1.0919656743557353, 0.625, 0.5, 0.0, 1.1554957969270676, 0.6691176295280457, 0.5, 0.0, 1.2865968414177669, 0.8676470518112183, 0.5, 0.0, 1.3163486627542458, 0.6911764740943909, 0.5, 0.0, 1.4298918832609733, 0.8014705777168274, 0.5, 0.0]
+ separate_transform1Display_prestrainRatioPWF.ScalarRangeInitialized = 1
+
+ # set scalar coloring
+ ColorBy(transform1Display, ('POINTS', 'prestrainRatio'))
+
+ # Hide the scalar bar for this color map if no visible data is colored by it.
+ HideScalarBarIfNotNeeded(separate_transform1Display_prestrainRatioLUT, renderView1)
+
+ # rescale color and/or opacity maps used to include current data range
+ transform1Display.RescaleTransferFunctionToDataRange(True, False)
+
+ # show color bar/color legend
+ transform1Display.SetScalarBarVisibility(renderView1, True)
+
+ # get opacity transfer function/opacity map for 'prestrainRatio'
+ prestrainRatioPWF = GetOpacityTransferFunction('prestrainRatio')
+ prestrainRatioPWF.Points = [1.0000497462439073, 0.8602941036224365, 0.5, 0.0, 1.0919656743557353, 0.625, 0.5, 0.0, 1.1554957969270676, 0.6691176295280457, 0.5, 0.0, 1.2865968414177669, 0.8676470518112183, 0.5, 0.0, 1.3163486627542458, 0.6911764740943909, 0.5, 0.0, 1.4298918832609733, 0.8014705777168274, 0.5, 0.0]
+ prestrainRatioPWF.ScalarRangeInitialized = 1
+
+ # get color legend/bar for prestrainRatioLUT in view renderView1
+ prestrainRatioLUTColorBar = GetScalarBar(prestrainRatioLUT, renderView1)
+ prestrainRatioLUTColorBar.WindowLocation = 'UpperRightCorner'
+ prestrainRatioLUTColorBar.Position = [0.8912839737582006, 0.6471663619744058]
+ prestrainRatioLUTColorBar.Title = 'prestrainRatio'
+ prestrainRatioLUTColorBar.ComponentTitle = ''
+
+ # find source
+ xMLStructuredGridReader1 = FindSource('XMLStructuredGridReader1')
+
+ # set active source
+ SetActiveSource(xMLStructuredGridReader1)
+
+ # get color transfer function/color map for 'elasticRatio'
+ elasticRatioLUT = GetColorTransferFunction('elasticRatio')
+ elasticRatioLUT.RGBPoints = [0.3303091106505249, 0.34902, 0.0, 0.129412, 0.34705135837933526, 0.4, 0.00392157, 0.101961, 0.3637936061081457, 0.470588, 0.0156863, 0.0901961, 0.3805358538369561, 0.54902, 0.027451, 0.0705882, 0.3972781015657665, 0.619608, 0.0627451, 0.0431373, 0.4140203492945769, 0.690196, 0.12549, 0.0627451, 0.4307625970233873, 0.741176, 0.184314, 0.0745098, 0.4475048447521977, 0.788235, 0.266667, 0.0941176, 0.46424709248100815, 0.811765, 0.345098, 0.113725, 0.48098934020981854, 0.831373, 0.411765, 0.133333, 0.4977315879386289, 0.85098, 0.47451, 0.145098, 0.5144738356674393, 0.870588, 0.54902, 0.156863, 0.5312160833962497, 0.878431, 0.619608, 0.168627, 0.5479583311250602, 0.890196, 0.658824, 0.196078, 0.5647005788538706, 0.909804, 0.717647, 0.235294, 0.581442826582681, 0.929412, 0.776471, 0.278431, 0.5951862028983068, 0.94902, 0.823529, 0.321569, 0.6108455620440179, 0.968627, 0.87451, 0.407843, 0.6278376041089421, 0.980392, 0.917647, 0.509804, 0.6451631517486243, 0.988235, 0.956863, 0.643137, 0.6541590962982686, 0.992157, 0.964706, 0.713725, 0.6644843753175806, 0.988235, 0.980392, 0.870588, 0.6651540652267329, 1.0, 1.0, 1.0, 0.6658237551358854, 0.913725, 0.988235, 0.937255, 0.6761490341551974, 0.827451, 0.980392, 0.886275, 0.6861441560492971, 0.764706, 0.980392, 0.866667, 0.6964727835181548, 0.658824, 0.980392, 0.843137, 0.708134093906226, 0.572549, 0.964706, 0.835294, 0.7237934530519369, 0.423529, 0.941176, 0.87451, 0.7361211048996146, 0.262745, 0.901961, 0.862745, 0.7521139696200834, 0.0705882, 0.854902, 0.870588, 0.7667734817314298, 0.0509804, 0.8, 0.85098, 0.7867643952095386, 0.0235294, 0.709804, 0.831373, 0.8077544860321026, 0.0313725, 0.615686, 0.811765, 0.832576542514837, 0.0313725, 0.537255, 0.788235, 0.8493187902436474, 0.0392157, 0.466667, 0.768627, 0.8660610379724578, 0.0509804, 0.396078, 0.741176, 0.8828032857012682, 0.054902, 0.317647, 0.709804, 0.8995455334300786, 0.054902, 0.243137, 0.678431, 0.916287781158889, 0.0431373, 0.164706, 0.639216, 0.9330300288876996, 0.0313725, 0.0980392, 0.6, 0.94977227661651, 0.0392157, 0.0392157, 0.560784, 0.9665145243453201, 0.105882, 0.0509804, 0.509804, 0.9832567720741308, 0.113725, 0.0235294, 0.45098, 0.9999990198029411, 0.12549, 0.0, 0.380392]
+ elasticRatioLUT.ColorSpace = 'Lab'
+ elasticRatioLUT.NanColor = [0.250004, 0.0, 0.0]
+ elasticRatioLUT.ScalarRangeInitialized = 1.0
+
+ # get opacity transfer function/opacity map for 'elasticRatio'
+ elasticRatioPWF = GetOpacityTransferFunction('elasticRatio')
+ elasticRatioPWF.Points = [0.3303091106505249, 0.8602941036224365, 0.5, 0.0, 0.47351324129727485, 0.625, 0.5, 0.0, 0.5724925603293413, 0.6691176295280457, 0.5, 0.0, 0.7767467248559744, 0.8676470518112183, 0.5, 0.0, 0.8230997759230788, 0.6911764740943909, 0.5, 0.0, 0.9999990198029411, 0.8014705777168274, 0.5, 0.0]
+ elasticRatioPWF.ScalarRangeInitialized = 1
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.Visibility = 0
+
+ # Properties modified on renderView1.AxesGrid
+ renderView1.AxesGrid.Visibility = 1
+
+ # get display properties
+ xMLStructuredGridReader1Display = GetDisplayProperties(xMLStructuredGridReader1, view=renderView1)
+
+ # hide color bar/color legend
+ xMLStructuredGridReader1Display.SetScalarBarVisibility(renderView1, False)
+
+ # set active source
+ SetActiveSource(transform1)
+
+ # Properties modified on prestrainRatioLUTColorBar
+ prestrainRatioLUTColorBar.WindowLocation = 'LowerRightCorner'
+
+ # Properties modified on prestrainRatioLUTColorBar
+ prestrainRatioLUTColorBar.HorizontalTitle = 1
+
+else:
+
+ # get color transfer function/color map for 'elasticRatio'
+ elasticRatioLUT = GetColorTransferFunction('elasticRatio')
+ elasticRatioLUT.AutomaticRescaleRangeMode = "Grow and update on 'Apply'"
+ elasticRatioLUT.InterpretValuesAsCategories = 0
+ elasticRatioLUT.AnnotationsInitialized = 0
+ elasticRatioLUT.ShowCategoricalColorsinDataRangeOnly = 0
+ elasticRatioLUT.RescaleOnVisibilityChange = 0
+ elasticRatioLUT.EnableOpacityMapping = 0
+ elasticRatioLUT.RGBPoints = [0.3303091106505249, 0.34902, 0.0, 0.129412, 0.34705135837933526, 0.4, 0.00392157, 0.101961, 0.3637936061081457, 0.470588, 0.0156863, 0.0901961, 0.3805358538369561, 0.54902, 0.027451, 0.0705882, 0.3972781015657665, 0.619608, 0.0627451, 0.0431373, 0.4140203492945769, 0.690196, 0.12549, 0.0627451, 0.4307625970233873, 0.741176, 0.184314, 0.0745098, 0.4475048447521977, 0.788235, 0.266667, 0.0941176, 0.46424709248100815, 0.811765, 0.345098, 0.113725, 0.48098934020981854, 0.831373, 0.411765, 0.133333, 0.4977315879386289, 0.85098, 0.47451, 0.145098, 0.5144738356674393, 0.870588, 0.54902, 0.156863, 0.5312160833962497, 0.878431, 0.619608, 0.168627, 0.5479583311250602, 0.890196, 0.658824, 0.196078, 0.5647005788538706, 0.909804, 0.717647, 0.235294, 0.581442826582681, 0.929412, 0.776471, 0.278431, 0.5951862028983068, 0.94902, 0.823529, 0.321569, 0.6108455620440179, 0.968627, 0.87451, 0.407843, 0.6278376041089421, 0.980392, 0.917647, 0.509804, 0.6451631517486243, 0.988235, 0.956863, 0.643137, 0.6541590962982686, 0.992157, 0.964706, 0.713725, 0.6644843753175806, 0.988235, 0.980392, 0.870588, 0.6651540652267329, 1.0, 1.0, 1.0, 0.6658237551358854, 0.913725, 0.988235, 0.937255, 0.6761490341551974, 0.827451, 0.980392, 0.886275, 0.6861441560492971, 0.764706, 0.980392, 0.866667, 0.6964727835181548, 0.658824, 0.980392, 0.843137, 0.708134093906226, 0.572549, 0.964706, 0.835294, 0.7237934530519369, 0.423529, 0.941176, 0.87451, 0.7361211048996146, 0.262745, 0.901961, 0.862745, 0.7521139696200834, 0.0705882, 0.854902, 0.870588, 0.7667734817314298, 0.0509804, 0.8, 0.85098, 0.7867643952095386, 0.0235294, 0.709804, 0.831373, 0.8077544860321026, 0.0313725, 0.615686, 0.811765, 0.832576542514837, 0.0313725, 0.537255, 0.788235, 0.8493187902436474, 0.0392157, 0.466667, 0.768627, 0.8660610379724578, 0.0509804, 0.396078, 0.741176, 0.8828032857012682, 0.054902, 0.317647, 0.709804, 0.8995455334300786, 0.054902, 0.243137, 0.678431, 0.916287781158889, 0.0431373, 0.164706, 0.639216, 0.9330300288876996, 0.0313725, 0.0980392, 0.6, 0.94977227661651, 0.0392157, 0.0392157, 0.560784, 0.9665145243453201, 0.105882, 0.0509804, 0.509804, 0.9832567720741308, 0.113725, 0.0235294, 0.45098, 0.9999990198029411, 0.12549, 0.0, 0.380392]
+ elasticRatioLUT.UseLogScale = 0
+ elasticRatioLUT.ColorSpace = 'Lab'
+ elasticRatioLUT.UseBelowRangeColor = 0
+ elasticRatioLUT.BelowRangeColor = [0.0, 0.0, 0.0]
+ elasticRatioLUT.UseAboveRangeColor = 0
+ elasticRatioLUT.AboveRangeColor = [0.5, 0.5, 0.5]
+ elasticRatioLUT.NanColor = [0.250004, 0.0, 0.0]
+ elasticRatioLUT.NanOpacity = 1.0
+ elasticRatioLUT.Discretize = 1
+ elasticRatioLUT.NumberOfTableValues = 256
+ elasticRatioLUT.ScalarRangeInitialized = 1.0
+ elasticRatioLUT.HSVWrap = 0
+ elasticRatioLUT.VectorComponent = 0
+ elasticRatioLUT.VectorMode = 'Magnitude'
+ elasticRatioLUT.AllowDuplicateScalars = 1
+ elasticRatioLUT.Annotations = []
+ elasticRatioLUT.ActiveAnnotatedValues = []
+ elasticRatioLUT.IndexedColors = []
+ elasticRatioLUT.IndexedOpacities = []
+
+ # get active view
+ renderView1 = GetActiveViewOrCreate('RenderView')
+ # uncomment following to set a specific view size
+ # renderView1.ViewSize = [1067, 547]
+
+ # get color legend/bar for elasticRatioLUT in view renderView1
+ elasticRatioLUTColorBar = GetScalarBar(elasticRatioLUT, renderView1)
+ elasticRatioLUTColorBar.AutoOrient = 1
+ elasticRatioLUTColorBar.Orientation = 'Vertical'
+ elasticRatioLUTColorBar.WindowLocation = 'LowerRightCorner'
+ elasticRatioLUTColorBar.Position = [0.89, 0.02]
+ elasticRatioLUTColorBar.Title = 'elasticRatio'
+ elasticRatioLUTColorBar.ComponentTitle = ''
+ elasticRatioLUTColorBar.TitleJustification = 'Centered'
+ elasticRatioLUTColorBar.HorizontalTitle = 0
+ elasticRatioLUTColorBar.TitleColor = [1.0, 1.0, 1.0]
+ elasticRatioLUTColorBar.TitleOpacity = 1.0
+ elasticRatioLUTColorBar.TitleFontFamily = 'Arial'
+ elasticRatioLUTColorBar.TitleFontFile = ''
+ elasticRatioLUTColorBar.TitleBold = 0
+ elasticRatioLUTColorBar.TitleItalic = 0
+ elasticRatioLUTColorBar.TitleShadow = 0
+ elasticRatioLUTColorBar.TitleFontSize = 16
+ elasticRatioLUTColorBar.LabelColor = [1.0, 1.0, 1.0]
+ elasticRatioLUTColorBar.LabelOpacity = 1.0
+ elasticRatioLUTColorBar.LabelFontFamily = 'Arial'
+ elasticRatioLUTColorBar.LabelFontFile = ''
+ elasticRatioLUTColorBar.LabelBold = 0
+ elasticRatioLUTColorBar.LabelItalic = 0
+ elasticRatioLUTColorBar.LabelShadow = 0
+ elasticRatioLUTColorBar.LabelFontSize = 16
+ elasticRatioLUTColorBar.AutomaticLabelFormat = 1
+ elasticRatioLUTColorBar.LabelFormat = '%-#6.3g'
+ elasticRatioLUTColorBar.DrawTickMarks = 1
+ elasticRatioLUTColorBar.DrawTickLabels = 1
+ elasticRatioLUTColorBar.UseCustomLabels = 0
+ elasticRatioLUTColorBar.CustomLabels = []
+ elasticRatioLUTColorBar.AddRangeLabels = 1
+ elasticRatioLUTColorBar.RangeLabelFormat = '%-#6.1e'
+ elasticRatioLUTColorBar.DrawAnnotations = 1
+ elasticRatioLUTColorBar.AddRangeAnnotations = 0
+ elasticRatioLUTColorBar.AutomaticAnnotations = 0
+ elasticRatioLUTColorBar.DrawNanAnnotation = 0
+ elasticRatioLUTColorBar.NanAnnotation = 'NaN'
+ elasticRatioLUTColorBar.TextPosition = 'Ticks right/top, annotations left/bottom'
+ elasticRatioLUTColorBar.ReverseLegend = 0
+ elasticRatioLUTColorBar.ScalarBarThickness = 16
+ elasticRatioLUTColorBar.ScalarBarLength = 0.33
+
+ # Properties modified on elasticRatioLUTColorBar
+ elasticRatioLUTColorBar.HorizontalTitle = 1
+
+
+
+
+renderView1.OrientationAxesVisibility = 0
+
+#### uncomment the following to render all views
+# RenderAllViews()
+# alternatively, if you want to write images, you can use SaveScreenshot(...).
+# ----------------- EXPORT -----------------
+# save screenshot
+# SaveScreenshot('/home/klaus/Desktop/PhaseDiagramPlot.png', renderView1, ImageResolution=[1257, 934])
+# SaveScreenshot('/home/klaus/Desktop/PhaseDiagramPlot.png', renderView1, ImageResolution=[2514, 1868])
+# SaveScreenshot('/home/klaus/Desktop/PhaseDiagramPlot.png', renderView1, ImageResolution=[1063, 657])
+#
+if prestrain:
+ outputName = '/home/klaus/Desktop/PrestrainRatio' + ".png"
+
+else:
+ outputName = '/home/klaus/Desktop/ElasticRatio' + ".png"
+# SaveScreenshot('/home/klaus/Desktop/2DPhaseDiagram.png', renderView1, ImageResolution=[2126, 1314])
+
+SaveScreenshot(outputName , renderView1, ImageResolution=[2126, 1314])
+# export view
+# ExportView('/home/klaus/Desktop/PhaseDiagramPlot.pdf', view=renderView1)
diff --git a/src/ParaViewSettings.txt b/src/ParaViewSettings.txt
new file mode 100644
index 0000000000000000000000000000000000000000..88039a836e99c07910ca09e482e7c62fe8e5ba9a
--- /dev/null
+++ b/src/ParaViewSettings.txt
@@ -0,0 +1,8 @@
+
+Colormap: Cool-to-Warm
+
+Representation: Point-Gaussian
+Opacity: 0.01
+PointSize: 2
+Gaussian-radius: 0.0075
+Shader-Preset: Plain-Circle
diff --git a/src/PhaseDiagram.py b/src/PhaseDiagram.py
index c7f32e5cd6fe680ca4abe540d76a26b115f699f2..f82a4cb64d992f9564d046e79204aa6dbda55014 100644
--- a/src/PhaseDiagram.py
+++ b/src/PhaseDiagram.py
@@ -115,7 +115,7 @@ mu1 = 1.0
rho1 = 1.0
alpha = 2.0
beta = 2.0
-beta = 5.0
+# beta = 5.0
theta = 1.0/4.0
#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
gamma = '0'
@@ -159,9 +159,9 @@ print('----------------------------')
print('type of gamma:', type(gamma))
# # #
-# Gamma_Values = ['0', 'infinity']
-Gamma_Values = ['infinity']
-Gamma_Values = ['0']
+Gamma_Values = ['0', 'infinity']
+# Gamma_Values = ['infinity']
+# Gamma_Values = ['0']
print('(Input) Gamma_Values:', Gamma_Values)
for gamma in Gamma_Values:
@@ -233,7 +233,7 @@ for gamma in Gamma_Values:
# SamplePoints_3D = 400 # Number of sample points in each direction
# SamplePoints_2D = 7500 # Number of sample points in each direction
SamplePoints_2D = 4000 # 4000 # Number of sample points in each direction
- SamplePoints_2D = 200 # 4000 # Number of sample points in each direction
+ SamplePoints_2D = 400 # 4000 # Number of sample points in each direction
if make_3D_PhaseDiagram:
alphas_ = np.linspace(-20, 20, SamplePoints_3D)
@@ -307,12 +307,16 @@ for gamma in Gamma_Values:
# thetas_ = np.linspace(0.05,0.2,SamplePoints_2D)
# betas_ = np.linspace(0.01,40.01,1)
#fix to one value:
- # betas_ = 2.0;
+ betas_ = 2.0;
# betas_ = 10.0;
- betas_ = 5.0;
-
+ # betas_ = 5.0;
+ # betas_ = 0.5;
+ #intermediate Values
+ alphas_ = np.linspace(-2, 1, SamplePoints_2D)
+ thetas_ = np.linspace(0.4,0.6,SamplePoints_2D)
+ betas_ = 10.0;
# TEST
# alphas_ = np.linspace(-8, 8, SamplePoints_2D)
diff --git a/src/PhaseDiagram_backup.py b/src/PhaseDiagram_backup.py
new file mode 100644
index 0000000000000000000000000000000000000000..ae7f66cb9c85ee1c1c07a3137812f7286da77692
--- /dev/null
+++ b/src/PhaseDiagram_backup.py
@@ -0,0 +1,389 @@
+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 HelperFunctions 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
+# print(sys.executable)
+
+# --------------------------------------------------------------------
+# START :
+# INPUT (Parameters): alpha, beta, theta, gamma, mu1, rho1
+#
+# -Option 1 : (Case lambda = 0 => q12 = 0)
+# compute q1,q2,b1,b2 from Formula
+# Option 1.1 :
+# set mu_gamma = 'q1' or 'q2' (extreme regimes: gamma \in {0,\infty})
+# Option 1.2 :
+# compute mu_gamma with 'Compute_MuGamma' (2D problem much faster then Cell-Problem)
+# -Option 2 :
+# compute Q_hom & B_eff by running 'Cell-Problem'
+#
+# -> CLASSIFY ...
+#
+# OUTPUT: Minimizer G, angle , type, curvature
+# -----------------------------------------------------------------------
+#
+#
+# def GetMuGamma(beta,theta,gamma,mu1,rho1, InputFilePath = os.path.dirname(os.getcwd()) +"/inputs/computeMuGamma.parset",
+# OutputFilePath = os.path.dirname(os.getcwd()) + "/outputs/outputMuGamma.txt" ):
+# # ------------------------------------ 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
+#
+
+
+
+# ----------- SETUP PATHS
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+InputFile = "/inputs/computeMuGamma.parset"
+OutputFile = "/outputs/outputMuGamma.txt"
+# --------- 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)
+
+
+# -------------------------- Input Parameters --------------------
+# mu1 = 10.0 # TODO : here must be the same values as in the Parset for computeMuGamma
+mu1 = 1.0
+rho1 = 1.0
+alpha = 2.0
+beta = 2.0
+beta = 10.0
+theta = 1.0/4.0
+#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
+gamma = '0'
+gamma = 'infinity'
+# gamma = 0.5
+# gamma = 0.25
+# gamma = 1.0
+
+# gamma = 5.0
+
+#added
+# lambda1 = 10.0
+lambda1 = 0.0
+
+
+
+
+
+print('---- Input parameters: -----')
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+
+print('lambda1: ', lambda1)
+print('----------------------------')
+# ----------------------------------------------------------------
+
+#
+# gamma_min = 0.5
+# gamma_max = 1.0
+#
+# # gamma_min = 1
+# # gamma_max = 1
+# Gamma_Values = np.linspace(gamma_min, gamma_max, num=3)
+# # #
+# # # Gamma_Values = np.linspace(gamma_min, gamma_max, num=13) # TODO variable Input Parameters...alpha,beta...
+# print('(Input) Gamma_Values:', Gamma_Values)
+# # #
+# for gamma in Gamma_Values:
+
+
+ # muGamma = GetMuGamma(beta,theta,gamma,mu1,rho1,InputFilePath)
+ # # muGamma = GetMuGamma(beta,theta,gamma,mu1,rho1)
+ # print('Test MuGamma:', muGamma)
+
+ # ------- Options --------
+ # print_Cases = True
+ # print_Output = True
+
+ #TODO
+# generalCase = True #Read Output from Cell-Problem instead of using Lemma1.4 (special case)
+generalCase = False
+
+# make_3D_plot = True
+make_3D_PhaseDiagram = True
+make_2D_plot = False
+make_2D_PhaseDiagram = False
+make_3D_plot = False
+# make_3D_PhaseDiagram = False
+# make_2D_plot = True
+# make_2D_PhaseDiagram = True
+#
+
+# --- Define effective quantities: q1, q2 , q3 = mu_gamma, q12 ---
+# q1 = harmonicMean(mu1, beta, theta)
+# q2 = arithmeticMean(mu1, beta, theta)
+# --- Set q12
+# q12 = 0.0 # (analytical example) # TEST / TODO read from Cell-Output
+
+
+
+
+
+# b1 = prestrain_b1(rho1, beta, alpha, theta)
+# b2 = prestrain_b2(rho1, beta, alpha, theta)
+#
+# print('---- Input parameters: -----')
+# print('mu1: ', mu1)
+# print('rho1: ', rho1)
+# print('alpha: ', alpha)
+# print('beta: ', beta)
+# print('theta: ', theta)
+# print("q1: ", q1)
+# print("q2: ", q2)
+# print("mu_gamma: ", mu_gamma)
+# print("q12: ", q12)
+# print("b1: ", b1)
+# print("b2: ", b2)
+# print('----------------------------')
+# print("machine epsilon", sys.float_info.epsilon)
+
+# G, angle, type, kappa = classifyMin(q1, q2, mu_gamma, q12, b1, b2, print_Cases, print_Output)
+# Test = f(1,2 ,q1,q2,mu_gamma,q12,b1,b2)
+# print("Test", Test)
+
+# ---------------------- MAKE PLOT / Write to VTK------------------------------------------------------------------------------
+
+# SamplePoints_3D = 10 # Number of sample points in each direction
+# SamplePoints_2D = 10 # Number of sample points in each direction
+SamplePoints_3D = 300 # Number of sample points in each direction
+# SamplePoints_3D = 150 # Number of sample points in each direction
+# SamplePoints_3D = 100 # Number of sample points in each direction
+# SamplePoints_3D = 200 # Number of sample points in each direction
+# SamplePoints_3D = 400 # Number of sample points in each direction
+# SamplePoints_2D = 7500 # Number of sample points in each direction
+SamplePoints_2D = 4000 # 4000 # Number of sample points in each direction
+
+
+if make_3D_PhaseDiagram:
+ alphas_ = np.linspace(-20, 20, SamplePoints_3D)
+ # alphas_ = np.linspace(-10, 10, SamplePoints_3D)
+
+ # betas_ = np.linspace(0.01,40.01,SamplePoints_3D) # Full Range
+ # betas_ = np.linspace(0.01,20.01,SamplePoints_3D) # FULL Range
+
+
+
+ # betas_ = np.linspace(0.01,1.0,SamplePoints_3D) # weird part
+ betas_ = np.linspace(1.01,40.01,SamplePoints_3D) #TEST !!!!! For Beta <1 weird tings happen...
+ thetas_ = np.linspace(0.01,0.99,SamplePoints_3D)
+
+
+ # TEST
+ # alphas_ = np.linspace(-2, 2, SamplePoints_3D)
+ # betas_ = np.linspace(1.01,10.01,SamplePoints_3D)
+ # print('betas:', betas_)
+
+ # TEST :
+ # alphas_ = np.linspace(-40, 40, SamplePoints_3D)
+ # betas_ = np.linspace(0.01,80.01,SamplePoints_3D) # Full Range
+
+ # print('type of alphas', type(alphas_))
+ # print('Test:', type(np.array([mu_gamma])) )
+ alphas, betas, thetas = np.meshgrid(alphas_, betas_, thetas_, indexing='ij')
+ classifyMin_anaVec = np.vectorize(classifyMin_ana)
+
+ # Get MuGamma values ...
+ GetMuGammaVec = np.vectorize(GetMuGamma)
+ muGammas = GetMuGammaVec(betas, thetas, gamma, mu1, rho1)
+ # Classify Minimizers....
+ G, angles, Types, curvature = classifyMin_anaVec(alphas, betas, thetas, muGammas, mu1, rho1) # Sets q12 to zero!!!
+
+ # G, angles, Types, curvature = classifyMin_anaVec(alphas, betas, thetas, muGammas, mu1, rho1, True, True)
+ # print('size of G:', G.shape)
+ # print('G:', G)
+
+ # Option to print angles
+ # print('angles:', angles)
+
+
+ # Out = classifyMin_anaVec(alphas,betas,thetas)
+ # T = Out[2]
+ # --- Write to VTK
+
+ GammaString = str(gamma)
+ VTKOutputName = "outputs/PhaseDiagram3D" + "Gamma" + GammaString
+ gridToVTK(VTKOutputName , alphas, betas, thetas, pointData = {'Type': Types, 'angles': angles, 'curvature': curvature} )
+ print('Written to VTK-File:', VTKOutputName )
+
+if make_2D_PhaseDiagram:
+ # alphas_ = np.linspace(-20, 20, SamplePoints_2D)
+ # alphas_ = np.linspace(0, 1, SamplePoints_2D)
+ thetas_ = np.linspace(0.01,0.99,SamplePoints_2D)
+ alphas_ = np.linspace(-5, 5, SamplePoints_2D)
+ # alphas_ = np.linspace(-5, 15, SamplePoints_2D)
+ # thetas_ = np.linspace(0.05,0.25,SamplePoints_2D)
+
+
+ # good range:
+ # alphas_ = np.linspace(9, 10, SamplePoints_2D)
+ # thetas_ = np.linspace(0.075,0.14,SamplePoints_2D)
+
+ # range used:
+ # alphas_ = np.linspace(8, 10, SamplePoints_2D)
+ # thetas_ = np.linspace(0.05,0.16,SamplePoints_2D)
+
+ # alphas_ = np.linspace(8, 12, SamplePoints_2D)
+ # thetas_ = np.linspace(0.05,0.2,SamplePoints_2D)
+ # betas_ = np.linspace(0.01,40.01,1)
+ #fix to one value:
+ # betas_ = 2.0;
+ betas_ = 10.0;
+
+ # TEST
+ # alphas_ = np.linspace(-8, 8, SamplePoints_2D)
+ # thetas_ = np.linspace(0.01,0.99,SamplePoints_2D)
+ # betas_ = 1.0; #TEST Problem: disvison by zero if alpha = 9, theta = 0.1 !
+ # betas_ = 0.9;
+ # betas_ = 0.5; #TEST!!!
+ alphas, betas, thetas = np.meshgrid(alphas_, betas_, thetas_, indexing='ij')
+
+
+ if generalCase:
+ classifyMin_matVec = np.vectorize(classifyMin_mat)
+ GetCellOutputVec = np.vectorize(GetCellOutput, otypes=[np.ndarray, np.ndarray])
+ Q, B = GetCellOutputVec(alphas,betas,thetas,gamma,mu1,rho1,lambda1, InputFilePath ,OutputFilePath )
+
+
+ # print('type of Q:', type(Q))
+ # print('Q:', Q)
+ G, angles, Types, curvature = classifyMin_matVec(Q,B)
+
+ else:
+ classifyMin_anaVec = np.vectorize(classifyMin_ana)
+ GetMuGammaVec = np.vectorize(GetMuGamma)
+ muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+ G, angles, Types, curvature = classifyMin_anaVec(alphas,betas,thetas, muGammas, mu1, rho1) # Sets q12 to zero!!!
+ # print('size of G:', G.shape)
+ # print('G:', G)
+ # print('Types:', Types)
+ # Out = classifyMin_anaVec(alphas,betas,thetas)
+ # T = Out[2]
+ # --- Write to VTK
+ # VTKOutputName = + path + "./PhaseDiagram2DNEW"
+
+
+ GammaString = str(gamma)
+ VTKOutputName = "outputs/PhaseDiagram2D" + "Gamma_" + GammaString
+ gridToVTK(VTKOutputName , alphas, betas, thetas, pointData = {'Type': Types, 'angles': angles, 'curvature': curvature} )
+ print('Written to VTK-File:', VTKOutputName )
+
+
+# --- Make 3D Scatter plot
+if(make_3D_plot or make_2D_plot):
+ fig = plt.figure()
+ ax = fig.add_subplot(111, projection='3d')
+ colors = cm.plasma(Types)
+ # if make_2D_plot: pnt3d=ax.scatter(alphas,thetas,c=Types.flat)
+ # if make_3D_plot: pnt3d=ax.scatter(alphas,betas,thetas,c=Types.flat)
+ if make_2D_plot: pnt3d=ax.scatter(alphas,thetas,c=angles.flat)
+ if make_3D_plot: pnt3d=ax.scatter(alphas,betas,thetas,c=angles.flat)
+ # cbar=plt.colorbar(pnt3d)
+ # cbar.set_label("Values (units)")
+ plt.axvline(x = 8, color = 'b', linestyle = ':', label='$q_1$')
+ plt.axhline(y = 0.083333333, color = 'b', linestyle = ':', label='$q_1$')
+
+ ax.set_xlabel('alpha')
+ ax.set_ylabel('beta')
+ if make_3D_plot: ax.set_zlabel('theta')
+ plt.show()
+ # plt.savefig('common_labels.png', dpi=300)
+ # print('T:', T)
+ # print('Type 1 occured here:', np.where(T == 1))
+ # print('Type 2 occured here:', np.where(T == 2))
+
+
+ # print(alphas_)
+ # print(betas_)
+
+
+
+
+
+# ALTERNATIVE
+# colors = ("red", "green", "blue")
+# groups = ("Type 1", "Type2", "Type3")
+#
+# # Create plot
+# fig = plt.figure()
+# ax = fig.add_subplot(1, 1, 1)
+#
+# for data, color, group in zip(Types, colors, groups):
+# # x, y = data
+# ax.scatter(alphas, thetas, alpha=0.8, c=color, edgecolors='none', label=group)
+#
+# plt.title('Matplot scatter plot')
+# plt.legend(loc=2)
+# plt.show()
diff --git a/src/PhaseDiagram_intermediateGamma.py b/src/PhaseDiagram_intermediateGamma.py
index a142890ba5d4f0ad44e661acc5725e7eb7348d5e..277f8c34a84bae641e260b0ac84bb59b0c3bd684 100644
--- a/src/PhaseDiagram_intermediateGamma.py
+++ b/src/PhaseDiagram_intermediateGamma.py
@@ -110,7 +110,8 @@ print("Path: ", path)
# -------------------------- Input Parameters --------------------
-mu1 = 10.0 # TODO : here must be the same values as in the Parset for computeMuGamma
+# mu1 = 10.0 # TODO : here must be the same values as in the Parset for computeMuGamma
+mu1 = 1.0
rho1 = 1.0
alpha = 2.0
beta = 2.0
@@ -137,7 +138,7 @@ print('---- Input parameters: -----')
print('mu1: ', mu1)
print('rho1: ', rho1)
print('alpha: ', alpha)
-print('beta: ', beta)
+# print('beta: ', beta)
print('theta: ', theta)
print('gamma:', gamma)
@@ -155,7 +156,9 @@ print('----------------------------')
# # #
# # # Gamma_Values = np.linspace(gamma_min, gamma_max, num=13) # TODO variable Input Parameters...alpha,beta...
-Gamma_Values = [0.05, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5]
+# Gamma_Values = [0.05, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5]
+Gamma_Values = [0.5, 0.75, 1.5, 3.0]
+# Gamma_Values = [3.0]
# Gamma_Values = ['infinity']
print('(Input) Gamma_Values:', Gamma_Values)
# #
@@ -222,7 +225,7 @@ for gamma in Gamma_Values:
# SamplePoints_2D = 10 # Number of sample points in each direction
SamplePoints_3D = 300 # Number of sample points in each direction
SamplePoints_2D = 200 # Number of sample points in each direction
-
+ SamplePoints_2D = 50
if make_3D_PhaseDiagram:
@@ -272,8 +275,8 @@ for gamma in Gamma_Values:
# thetas_ = np.linspace(0.05,0.2,SamplePoints_2D)
# betas_ = np.linspace(0.01,40.01,1)
#fix to one value:
- # betas_ = 2.0;
- betas_ = 10.0;
+ betas_ = 2.0;
+ # betas_ = 10.0;
alphas, betas, thetas = np.meshgrid(alphas_, betas_, thetas_, indexing='ij')
diff --git a/src/Plot-1-ParameterFamily.py b/src/Plot-1-ParameterFamily.py
index b2a5a9b9664478d243daab89c88841b659ad7733..173f2c6f47dad29aaa0a29c877068b344c3b54c1 100644
--- a/src/Plot-1-ParameterFamily.py
+++ b/src/Plot-1-ParameterFamily.py
@@ -200,11 +200,11 @@ ax.set_xticks([-np.pi/2, -np.pi/4 ,0, np.pi/4, np.pi/2 ])
-ax.legend(loc='upper right')
+# ax.legend(loc='upper right')
fig.set_size_inches(width, height)
-fig.savefig('Plot-1-ParameterFamily.pdf')
+fig.savefig('Plot-1-ParameterFamily2.pdf')
plt.show()
diff --git a/src/Plot-Angle-Alpha_intermediateGamma.py b/src/Plot-Angle-Alpha_intermediateGamma.py
new file mode 100644
index 0000000000000000000000000000000000000000..c070ed4c1678b30a95547ae37cade0a85cfd2c42
--- /dev/null
+++ b/src/Plot-Angle-Alpha_intermediateGamma.py
@@ -0,0 +1,864 @@
+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
+from HelperFunctions import *
+from ClassifyMin import *
+
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+# import tikzplotlib
+# # from pylab import *
+# from tikzplotlib import save as tikz_save
+
+
+# Needed ?
+mpl.use('pdf')
+
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### makePlot.py #########################
+# Generalized Plot-Script giving the option to define
+# quantity of interest and the parameter it depends on
+# to create a plot
+#
+# Input: Define y & x for "x-y plot" as Strings
+# - Run the 'Cell-Problem' for the different Parameter-Points
+# (alternatively run 'Compute_MuGamma' if quantity of interest
+# is q3=muGamma for a significant Speedup)
+
+###########################################################
+
+
+
+# figsize argument takes inputs in inches
+# and we have the width of our document in pts.
+# To set the figure size we construct a function
+# to convert from pts to inches and to determine
+# an aesthetic figure height using the golden ratio:
+# def set_size(width, fraction=1):
+# """Set figure dimensions to avoid scaling in LaTeX.
+#
+# Parameters
+# ----------
+# width: float
+# Document textwidth or columnwidth in pts
+# fraction: float, optional
+# Fraction of the width which you wish the figure to occupy
+#
+# Returns
+# -------
+# fig_dim: tuple
+# Dimensions of figure in inches
+# """
+# # Width of figure (in pts)
+# fig_width_pt = width * fraction
+#
+# # Convert from pt to inches
+# inches_per_pt = 1 / 72.27
+#
+# # Golden ratio to set aesthetic figure height
+# # https://disq.us/p/2940ij3
+# golden_ratio = (5**.5 - 1) / 2
+#
+# # Figure width in inches
+# fig_width_in = fig_width_pt * inches_per_pt
+# # Figure height in inches
+# fig_height_in = fig_width_in * golden_ratio
+#
+# fig_dim = (fig_width_in, fig_height_in)
+#
+# return fig_dim
+#
+
+
+
+def format_func(value, tick_number):
+ # # find number of multiples of pi/2
+ # N = int(np.round(2 * value / np.pi))
+ # if N == 0:
+ # return "0"
+ # elif N == 1:
+ # return r"$\pi/2$"
+ # elif N == 2:
+ # return r"$\pi$"
+ # elif N % 2 > 0:
+ # return r"${0}\pi/2$".format(N)
+ # else:
+ # return r"${0}\pi$".format(N // 2)
+ # find number of multiples of pi/2
+ N = int(np.round(4 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/4$"
+ elif N == 2:
+ return r"$\pi/2$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+
+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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+mu1 = 1.0 #10.0
+# lambda1 = 10.0
+rho1 = 1.0
+# alpha = 5.0
+# beta = 10.0
+# alpha = 2.0
+# beta = 2.0
+# theta = 1.0/8.0 #1.0/4.0
+
+lambda1 = 0.0
+# gamma = 1.0/4.0
+
+# TEST:
+# alpha=3.0;
+
+
+
+
+# # INTERESTING!:
+# alpha = 3
+beta = 2.0
+# theta= 1/8
+
+
+
+
+#TEST
+# beta=2
+
+
+
+gamma = 'infinity' #Elliptic Setting
+gamma = '0' #Hyperbolic Setting
+# gamma = 0.01
+# # gamma= 3.0
+gamma = 0.5
+gamma = 0.75
+# # gamma = 100.0
+# gamma = 3.0
+
+Gamma_Values = [0.5, 0.75, 1.5, 3.0]
+Gamma_Values = [ 1.5, 3.0]
+# Gamma_Values = [3.0]
+# Gamma_Values = ['infinity']
+print('(Input) Gamma_Values:', Gamma_Values)
+# #
+for gamma in Gamma_Values:
+
+ print('mu1: ', mu1)
+ print('rho1: ', rho1)
+ # print('alpha: ', alpha)
+ print('beta: ', beta)
+ # print('theta: ', theta)
+ print('gamma:', gamma)
+ print('----------------------------')
+
+
+
+ # --- define Interval of x-va1ues:
+ xmin = -2.0
+ # xmax = 0.41
+ xmax = 3.0
+
+
+ xmin = -1.5
+ xmax = 2.0
+
+ xmin = -1.0
+ xmax = -0.5
+
+
+ Jumps = False
+
+
+ numPoints = 2000
+ numPoints = 300
+ X_Values = np.linspace(xmin, xmax, num=numPoints)
+ print(X_Values)
+
+
+ Y_Values = []
+
+
+
+
+
+ Angle_Theta01 = []
+ Angle_Theta025 = []
+ Angle_Theta05 = []
+
+ Angle_Theta075 = []
+ Angle_Theta09 = []
+
+
+
+
+
+
+ for alpha in X_Values:
+ print('Situation of Lemma1.4')
+ q12 = 0.0
+ # q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+ # q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+ # b1 = prestrain_b1(rho1, beta, alpha,theta)
+ # b2 = prestrain_b2(rho1, beta, alpha,theta)
+ # b3 = 0.0
+ # q3_Theta01 = GetMuGamma(beta,0.1,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+ # q3_Theta025 = GetMuGamma(beta,0.25,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+ q3_Theta05 = GetMuGamma(beta,0.5,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+ # q3_Theta075 = GetMuGamma(beta,0.75,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+ # q3_Theta09 = GetMuGamma(beta,0.9,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+
+
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,0.1, q3_Theta01, mu1, rho1)
+ # Angle_Theta01.append(angle)
+ #
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,0.25, q3_Theta025, mu1, rho1)
+ # Angle_Theta025.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(alpha,beta,0.5, q3_Theta05, mu1, rho1)
+ Angle_Theta05.append(angle)
+
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,0.75, q3_Theta075, mu1, rho1)
+ # Angle_Theta075.append(angle)
+ #
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,0.9, q3_Theta09, mu1, rho1)
+ # Angle_Theta09.append(angle)
+
+
+
+
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.5,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg05 .append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.25,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg025.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(3.0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha3.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-1.0,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg075.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha0.append(angle)
+ # # G, angle, Type, curvature = classifyMin_ana(-0.125,beta,theta, q3, mu1, rho1)
+ # # Angle_alphaNeg0125.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.7,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0125.append(angle)
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.625,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0625.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.875,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0875.append(angle)
+
+ #
+ #
+ # print("(Output) Values of angle: ", Y_Values)
+ #
+ #
+ # idx = find_nearestIdx(Y_Values, 0)
+ # print(' Idx of value closest to 0', idx)
+ # ValueClose = Y_Values[idx]
+ # print('GammaValue(Idx) with mu_gamma closest to q_3^*', ValueClose)
+ #
+ #
+ #
+ # # Find Indices where the difference between the next one is larger than epsilon...
+ # jump_idx = []
+ # jump_xValues = []
+ # jump_yValues = []
+ # tmp = X_Values[0]
+ # for idx, x in enumerate(X_Values):
+ # print(idx, x)
+ # if idx > 0:
+ # if abs(Y_Values[idx]-Y_Values[idx-1]) > 1:
+ # print('jump candidate')
+ # jump_idx.append(idx)
+ # jump_xValues.append(x)
+ # jump_yValues.append(Y_Values[idx])
+ #
+ #
+ #
+ #
+ #
+ #
+ #
+ # print("Jump Indices", jump_idx)
+ # print("Jump X-values:", jump_xValues)
+ # print("Jump Y-values:", jump_yValues)
+ #
+ # y_plotValues = [Y_Values[0]]
+ # x_plotValues = [X_Values[0]]
+ # # y_plotValues.extend(jump_yValues)
+ # for i in jump_idx:
+ # y_plotValues.extend([Y_Values[i-1], Y_Values[i]])
+ # x_plotValues.extend([X_Values[i-1], X_Values[i]])
+ #
+ #
+ # y_plotValues.append(Y_Values[-1])
+ # # x_plotValues = [X_Values[0]]
+ # # x_plotValues.extend(jump_xValues)
+ # x_plotValues.append(X_Values[-1])
+ #
+ #
+ # print("y_plotValues:", y_plotValues)
+ # print("x_plotValues:", x_plotValues)
+
+
+ # Y_Values[np.diff(y) >= 0.5] = np.nan
+
+
+ #get values bigger than jump position
+ # gamma = infty
+ # x_rest = X_Values[X_Values>x_plotValues[1]]
+ # Y_Values = np.array(Y_Values) #convert the np array
+ # y_rest = Y_Values[X_Values>x_plotValues[1]]
+ #
+ #
+ # # gamma = 0
+ # x_rest = X_Values[X_Values>x_plotValues[3]]
+ # Y_Values = np.array(Y_Values) #convert the np array
+ # y_rest = Y_Values[X_Values>x_plotValues[3]]
+
+ # gamma between
+ # Y_Values = np.array(Y_Values) #convert the np array
+ # X_Values = np.array(X_Values) #convert the np array
+ #
+ # x_one = X_Values[X_Values>x_plotValues[3]]
+ # # ax.scatter(X_Values, Y_Values)
+ # y_rest = Y_Values[X_Values>x_plotValues[3]]
+ # ax.plot(X_Values[X_Values>0.135], Y_Values[X_Values<0.135])
+ #
+ #
+ #
+
+
+ # y_rest = Y_Values[np.nonzero(X_Values>x_plotValues[1]]
+ # print('X_Values:', X_Values)
+ # print('Y_Values:', Y_Values)
+ # print('x_rest:', x_rest)
+ # print('y_rest:', y_rest)
+ # print('np.nonzero(X_Values>x_plotValues[1]', np.nonzero(X_Values>x_plotValues[1]) )
+
+
+
+
+ # --- Convert to numpy array
+ Y_Values = np.array(Y_Values)
+ X_Values = np.array(X_Values)
+
+ Angle_Theta01 = np.array(Angle_Theta01)
+ Angle_Theta025 = np.array(Angle_Theta025)
+
+ Angle_Theta05 = np.array(Angle_Theta05)
+
+ Angle_Theta075 = np.array(Angle_Theta075)
+ Angle_Theta09 = np.array(Angle_Theta09)
+ # ---------------- Create Plot -------------------
+
+ #--- change plot style: SEABORN
+ # plt.style.use("seaborn-paper")
+
+
+ #--- Adjust gobal matplotlib variables
+ # mpl.rcParams['pdf.fonttype'] = 42
+ # mpl.rcParams['ps.fonttype'] = 42
+ mpl.rcParams['text.usetex'] = True
+ mpl.rcParams["font.family"] = "serif"
+ mpl.rcParams["font.size"] = "9"
+
+
+ # plt.rc('font', family='serif', serif='Times')
+ # plt.rc('font', family='serif')
+ # # plt.rc('text', usetex=True) #also works...
+ # plt.rc('xtick', labelsize=8)
+ # plt.rc('ytick', labelsize=8)
+ # plt.rc('axes', labelsize=8)
+
+
+
+
+
+ #---- Scale Figure apropriately to fit tex-File Width
+ # width = 452.9679
+
+ # width as measured in inkscape
+ width = 6.28 *0.5
+ width = 6.28 *0.333
+ # width = 6.28
+ height = width / 1.618
+
+ #setup canvas first
+ fig = plt.figure() #main
+ # fig, ax = plt.subplots()
+ # fig, (ax, ax2) = plt.subplots(ncols=2)
+ # fig,axes = plt.subplots(nrows=1,ncols=2,figsize=(width,height)) # more than one plot
+
+
+ # fig.subplots_adjust(left=.15, bottom=.16, right=.99, top=.97) #TEST
+
+
+ # TEST
+ # mpl.rcParams['figure.figsize'] = (width+0.1,height+0.1)
+ # fig = plt.figure(figsize=(width+0.1,height+0.1))
+
+
+ # mpl.rcParams['figure.figsize'] = (width,height)
+ # fig = plt.figure(figsize=(10,6)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+ # fig = plt.figure(figsize=(width,height)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+ # fig = plt.figure(figsize=set_size(width))
+ # fig = plt.subplots(1, 1, figsize=set_size(width))
+
+ # --- To create a figure half the width of your document:#
+ # fig = plt.figure(figsize=set_size(width, fraction=0.5))
+
+
+
+ #--- You must select the correct size of the plot in advance
+ # fig.set_size_inches(3.54,3.54)
+
+ # ax = plt.axes((0.15,0.18,0.8,0.8))
+ # ax = plt.axes((0.15,0.18,0.6,0.6))
+ # ax = plt.axes((0.15,0.2,0.75,0.75))
+ # ax = plt.axes((0.18,0.2,0.75,0.75))
+ ax = plt.axes((0.28,0.3,0.65,0.65))
+ # ax = plt.axes((0.1,0.1,0.5,0.8))
+ # ax = plt.axes((0.1,0.1,1,1))
+ # ax = plt.axes()
+
+ # ax.spines['right'].set_visible(False)
+ # ax.spines['left'].set_visible(False)
+ # ax.spines['bottom'].set_visible(False)
+ # ax.spines['top'].set_visible(False)
+ # ax.tick_params(axis='x',which='major',direction='out',length=10,width=5,color='red',pad=15,labelsize=15,labelcolor='green',
+ # labelrotation=15)
+ # ax.tick_params(axis='x',which='major', direction='out',pad=5,labelsize=10)
+ # ax.tick_params(axis='y',which='major', length=5, width=1, direction='out',pad=5,labelsize=10)
+ ax.tick_params(axis='x',which='major', direction='out',pad=3)
+ ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+ # ax.xaxis.set_major_locator(MultipleLocator(0.05))
+ # ax.xaxis.set_minor_locator(MultipleLocator(0.025))
+ # ax.xaxis.set_major_locator(MultipleLocator(0.1))
+ # ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+ ax.xaxis.set_major_locator(MultipleLocator(0.25))
+ ax.xaxis.set_minor_locator(MultipleLocator(0.125))
+ # ax.xaxis.set_major_locator(MultipleLocator(0.5))
+ # ax.xaxis.set_minor_locator(MultipleLocator(0.25))
+ #---- print data-types
+ print(ax.xaxis.get_major_locator())
+ print(ax.xaxis.get_minor_locator())
+ print(ax.xaxis.get_major_formatter())
+ print(ax.xaxis.get_minor_formatter())
+
+ #---- Hide Ticks or Labels
+ # ax.yaxis.set_major_locator(plt.NullLocator())
+ # ax.xaxis.set_major_formatter(plt.NullFormatter())
+
+ #---- Reducing or Increasing the Number of Ticks
+ # ax.xaxis.set_major_locator(plt.MaxNLocator(3))
+ # ax.yaxis.set_major_locator(plt.MaxNLocator(3))
+
+
+ #----- Fancy Tick Formats
+ ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
+ ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+ ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+
+
+
+
+
+
+ # --- manually change ticks&labels:
+ # ax.set_xticks([0.2,1])
+ # ax.set_xticklabels(['pos1','pos2'])
+
+ # ax.set_yticks([0, np.pi/8, np.pi/4 ])
+ # labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+ # ax.set_yticklabels(labels)
+
+ a=ax.yaxis.get_major_locator()
+ b=ax.yaxis.get_major_formatter()
+ c = ax.get_xticks()
+ d = ax.get_xticklabels()
+ print('xticks:',c)
+ print('xticklabels:',d)
+
+ ax.grid(True,which='major',axis='both',alpha=0.3)
+
+
+
+
+
+
+ # plt.figure()
+
+ # f,ax=plt.subplots(1)
+
+ # plt.title(r''+ yName + '-Plot')
+ # plt.plot(X_Values, Y_Values,linewidth=2, '.k')
+ # plt.plot(X_Values, Y_Values,'.k',markersize=1)
+ # plt.plot(X_Values, Y_Values,'.',markersize=0.8)
+
+ # plt.plot(X_Values, Y_Values)
+
+ # ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+
+
+
+ # Gamma = '0'
+ # ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
+ #
+ # ax.plot([x_plotValues[1],x_plotValues[3]], [y_plotValues[2],y_plotValues[3]] , 'b')
+ #
+ # ax.plot(x_rest, y_rest, 'b')
+
+
+ # Gamma between
+
+ # x jump values (gamma 0): [0.13606060606060608, 0.21090909090909093]
+
+ # ax.plot([[0,jump_xValues[0]], [0, 0]] , 'b')
+ # ax.plot([jump_xValues[0],xmin], [y_plotValues[2],y_plotValues[2]] , 'b')
+
+ # ax.plot([[0,0.13606060606060608], [0, 0]] , 'b')
+ # ax.plot([[0.13606060606060608,xmin], [(math.pi/2),(math.pi/2)]], 'b')
+
+ # jump_xValues[0]
+
+
+
+ # --- leave out jumps:
+ # ax.scatter(X_Values, Y_Values)
+
+ ax.set_xlabel(r"prestrain ratio $\theta_\rho$")
+ ax.set_ylabel(r"angle $\alpha$")
+
+
+ if Jumps:
+
+ # --- leave out jumps:
+ if gamma == 'infinity':
+ ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]] , 'royalblue')
+ ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+
+
+
+ # ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]])
+ # ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]])
+
+
+
+
+ # ax.plot(X_Values[X_Values>0.136], Y_Values[X_Values>0.136])
+ # ax.plot(X_Values[X_Values<0.135], Y_Values[X_Values<0.135])
+ # ax.scatter(X_Values, Y_Values)
+ # ax.plot(X_Values, Y_Values)
+
+ # plt.plot(x_plotValues, y_plotValues,'.')
+ # plt.scatter(X_Values, Y_Values, alpha=0.3)
+ # plt.scatter(X_Values, Y_Values)
+ # plt.plot(X_Values, Y_Values,'.')
+ # plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+ # plt.axis([0, 6, 0, 20])
+
+ # ax.set_xlabel(r"volume fraction $\theta$", size=11)
+ # ax.set_ylabel(r"angle $\angle$", size=11)
+ # ax.set_xlabel(r"volume fraction $\theta$")
+ # # ax.set_ylabel(r"angle $\angle$")
+ # ax.set_ylabel(r"angle $\alpha$")
+ # plt.ylabel('$\kappa$')
+
+ # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+ # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+ # Plot every other line.. not the jumps...
+
+ if gamma == '0':
+ tmp = 1
+ for idx, x in enumerate(x_plotValues):
+ if idx > 0 and tmp == 1:
+ # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
+ ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]], 'royalblue', zorder=2)
+ tmp = 0
+ else:
+ tmp = 1
+
+ # plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
+ # plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
+ # plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
+ # plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
+
+
+ for x in jump_xValues:
+ plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1, zorder=1)
+ # plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', label=r'$\theta_*$')
+
+ # plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+ # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+ # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+ # plt.legend()
+
+
+ # -- SETUP LEGEND
+ # ax.legend(prop={'size': 11})
+ # ax.legend()
+
+ # ------------------ SAVE FIGURE
+ # tikzplotlib.save("TesTout.tex")
+ # plt.close()
+ # mpl.rcParams.update(mpl.rcParamsDefault)
+
+ # plt.savefig("graph.pdf",
+ # #This is simple recomendation for publication plots
+ # dpi=1000,
+ # # Plot will be occupy a maximum of available space
+ # bbox_inches='tight',
+ # )
+ # plt.savefig("graph.pdf")
+
+
+
+ # ---- ADD additional scatter:
+ # ax.scatter(X_Values,Y_Values,s=1,c='black',zorder=4)
+
+ # Find transition point
+ lastIdx = len(Y_Values)-1
+
+ for idx, y in enumerate(Y_Values):
+ if idx != lastIdx:
+ if abs(y-0) < 0.01 and abs(Y_Values[idx+1] - 0) > 0.05:
+ transition_point1 = X_Values[idx+1]
+ print('transition point1:', transition_point1 )
+ if abs(y-0.5*np.pi) < 0.01 and abs(Y_Values[idx+1] -0.5*np.pi)>0.01:
+ transition_point2 = X_Values[idx]
+ print('transition point2:', transition_point2 )
+ if abs(y-0) > 0.01 and abs(Y_Values[idx+1] - 0) < 0.01:
+ transition_point3 = X_Values[idx+1]
+ print('transition point3:', transition_point3 )
+
+ # Add transition Points:
+ if gamma == '0':
+ ax.scatter([transition_point1, transition_point2],[np.pi/2,np.pi/2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2+0.012 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+ else:
+ ax.scatter([transition_point1, transition_point2, transition_point3 ],[np.pi/2,np.pi/2,0 ],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2 +0.011 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point3 +0.009 , 0+0.08, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ else:
+ # ax.scatter(X_Values,Y_Values,s=1, marker='o', cmap=None, norm=None, facecolor = 'blue',
+ # edgecolor = 'none', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alpha0,s=1, marker='o', edgecolor = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=0.75, linewidths=None, zorder=4)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1, label=r"$\theta_\rho = -1.0$")
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg05,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg025,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0125,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ #
+ # line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = 3.0$"]
+ # ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ # labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ # ax.set_yticklabels(labels)
+ #
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7],
+ # labels= [ r"$\theta_\rho = 0$", r"$\theta_\rho = -0.125$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.75$", r"$\theta_\rho = -1.0$", r"$\theta_\rho = 3.0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0875,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg075,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg0625,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg05,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg025,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alphaNeg0125,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l8 = ax.scatter(X_Values,Angle_alpha0,s=2, marker='s', edgecolor = 'black', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+
+ # l1 = ax.plot(X_Values,Angle_alphaNeg05, color='blue', linewidth=1.5, zorder=3, label=r"$\theta_\rho=-0.5$")
+ # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ # l3 = ax.plot(X_Values,Angle_alphaNeg06,color='orangered', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.6$")
+ # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ # l5 = ax.plot(X_Values,Angle_alphaNeg07,color='orange', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.7$")
+ # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ # l7 = ax.plot(X_Values,Angle_alphaNeg08, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.8$")
+ # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ # l9 = ax.plot(X_Values,Angle_alphaNeg09, color='teal',linestyle = '--', linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.9$")
+ # l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.95$")
+ # l11 = ax.plot(X_Values,Angle_alphaNeg1, color='red', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-1.0$")
+
+
+ # l1 = ax.plot(X_Values,Angle_Theta01, color='blue', linewidth=1.5, zorder=3, label=r"$\theta=0.1$")
+ # # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ # l3 = ax.plot(X_Values,Angle_Theta025,color='orangered', linewidth=1.5 ,zorder=3, label=r"$\theta = 0.25$")
+ # # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ # l5 = ax.plot(X_Values,Angle_Theta05,color='orange', linewidth=1.5 ,zorder=3, label=r"$\theta = 0.5$")
+ # # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ # l7 = ax.plot(X_Values,Angle_Theta075, linewidth=1.5 , zorder=3, label=r"$\theta = 0.75$")
+ # # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ # l9 = ax.plot(X_Values,Angle_Theta09, color='teal', linewidth=1.5 , zorder=3, label=r"$\theta =0.9$")
+ # # l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.95$")
+
+
+ # l1 = ax.scatter(X_Values,Angle_Theta01, color='blue', s=2, zorder=3, label=r"$\theta=0.1$")
+ # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ # l3 = ax.scatter(X_Values,Angle_Theta025,color='orangered', s=2 ,zorder=3, label=r"$\theta = 0.25$")
+ # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ l5 = ax.scatter(X_Values,Angle_Theta05, color='royalblue', s=0.15 ,zorder=3, label=r"$\theta = 0.5$")
+ # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ # l7 = ax.scatter(X_Values,Angle_Theta075, s=2, zorder=3, label=r"$\theta = 0.75$")
+ # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ # l9 = ax.scatter(X_Values,Angle_Theta09, color='teal',s=2, zorder=3, alpha=1.0, label=r"$\theta =0.9$")
+
+ # ax.legend(handles=[l1[0],l2[0],l3[0],l4[0], l5[0], l6[0], l7[0], l8[0], l9[0], l10[0], l11[0]],
+ # # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ # ax.legend(handles=[l1[0],l3[0], l5[0], l7[0], l9[0]] ,
+ # # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ # ax.legend(handles=[l1,l3, l5, l7, l9] ,
+ # # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ # ax.legend(handles=[l5] ,
+ # # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ # ax.plot(X_Values, Y_Values, marker='o', markerfacecolor='orange', markeredgecolor='black', markeredgewidth=1, linewidth=1, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+
+ # line_labels = [r"$\theta_\rho = -1.0$",r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = - \frac{3}{4}$", r"$\theta_\rho = - \frac{5}{8}$",r"$\theta_\rho = - 0.5 $" ,r"$\theta_\rho = - 0.25", r"$\theta_\rho = - \frac{1}{8}" , r"$\theta_\rho = 0$"]
+ ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ ax.set_yticklabels(labels)
+
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7, l8],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ #
+ # ax.legend(handles=[l1,l3, l5, l7, l8],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ #
+
+
+
+
+
+ # fig.legend([l1, l2, l3, l4], # The line objects
+ # labels=line_labels, # The labels for each line
+ # # loc="upper center", # Position of legend
+ # loc='upperleft', bbox_to_anchor=(1,1),
+ # borderaxespad=0.15 # Small spacing around legend box
+ # # title="Legend Title" # Title for the legend
+ # )
+
+ pdf_outputName = 'Plot-Angle-Alpha_Gamma'+ str(gamma)+ '_transition'+'.pdf'
+
+ fig.set_size_inches(width, height)
+ # fig.savefig('Plot-Angle-Theta.pdf')
+ fig.savefig(pdf_outputName)
+
+
+
+
+ # tikz_save('someplot.tex', figureheight='5cm', figurewidth='9cm')
+
+ # tikz_save('fig.tikz',
+ # figureheight = '\\figureheight',
+ # figurewidth = '\\figurewidth')
+
+ # ----------------------------------------
+
+
+# plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot-Angle-GammaV2.py b/src/Plot-Angle-GammaV2.py
index 7982203914e20664c325ff1a58ba07ab397a69bf..8167db04d6ee43f455d655158d878ddf408c4c43 100644
--- a/src/Plot-Angle-GammaV2.py
+++ b/src/Plot-Angle-GammaV2.py
@@ -139,6 +139,9 @@ theta= 1/8
+alpha = -1.0
+beta = 2.0
+theta= 0.25
@@ -156,7 +159,7 @@ print('----------------------------')
gamma_min = 0.01
gamma_max = 1.0
-Gamma_Values = np.linspace(gamma_min, gamma_max, num=100) # TODO variable Input Parameters...alpha,beta...
+Gamma_Values = np.linspace(gamma_min, gamma_max, num=10) # TODO variable Input Parameters...alpha,beta...
print('(Input) Gamma_Values:', Gamma_Values)
# mu_gamma = []
diff --git a/src/Plot-Angle-GammaV2_SubPlots.py b/src/Plot-Angle-GammaV2_SubPlots.py
new file mode 100644
index 0000000000000000000000000000000000000000..35ba8cf1540ff290cd244ab2065bbf89093ecd4e
--- /dev/null
+++ b/src/Plot-Angle-GammaV2_SubPlots.py
@@ -0,0 +1,451 @@
+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 HelperFunctions 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
+import matplotlib.ticker as ticker
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+
+def format_func(value, tick_number):
+ # # find number of multiples of pi/2
+ # N = int(np.round(2 * value / np.pi))
+ # if N == 0:
+ # return "0"
+ # elif N == 1:
+ # return r"$\pi/2$"
+ # elif N == 2:
+ # return r"$\pi$"
+ # elif N % 2 > 0:
+ # return r"${0}\pi/2$".format(N)
+ # else:
+ # return r"${0}\pi$".format(N // 2)
+ # find number of multiples of pi/2
+ N = int(np.round(4 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/4$"
+ elif N == 2:
+ return r"$\pi/2$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+InputFile = "/inputs/computeMuGamma.parset"
+OutputFile = "/outputs/outputMuGamma.txt"
+# --------- 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)
+
+print('---- Input parameters: -----')
+alpha = 10
+mu1 = 1.0
+rho1 = 1.0
+beta = 2.0 #5.0
+theta = 1.0/8.0
+#
+
+alpha = -0.5
+beta = 40.0
+theta= 1/8.0
+
+
+
+# # INTERESTING! from pi/2:
+alpha = -0.5
+beta = 40.0
+theta= 1/8.0
+#
+# # # INTERESTING! from pi/2:
+# alpha = -0.2
+# beta = 25.0
+# theta= 1/2
+
+# INTERESTING!:
+# alpha = -0.5
+# beta = 5.0
+# theta= 1/30
+
+
+
+# INTERESTING!:
+# alpha = -0.25
+# beta = 10.0
+# theta= 3/4
+
+
+# # INTERESTING!:
+alpha = -0.25
+beta = 10.0
+theta= 1/8
+
+#
+# INTERESTING!:
+# alpha = -0.25
+# beta = 5.0
+# theta= 1/8
+#
+
+
+# # INTERESTING!:
+alpha = -0.5
+beta = 10.0
+theta= 1/8
+
+
+
+alpha_1 = -1.0
+alpha_2 = -0.75
+alpha_3 = -0.70
+
+angles_1 = []
+angles_2 = []
+angles_3 = []
+
+beta = 2.0
+theta= 0.25
+
+
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha_1: ', alpha_1)
+print('alpha_2: ', alpha_2)
+print('alpha_3: ', alpha_3)
+print('beta: ', beta)
+print('theta: ', theta)
+# print('gamma:', gamma)
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+gamma_min = 0.01
+gamma_max = 1.5
+Gamma_Values = np.linspace(gamma_min, gamma_max, num=100) # TODO variable Input Parameters...alpha,beta...
+print('(Input) Gamma_Values:', Gamma_Values)
+# mu_gamma = []
+
+# Gamma_Values = '0'
+
+
+
+# Get values for mu_Gamma
+GetMuGammaVec = np.vectorize(GetMuGamma)
+muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1, InputFilePath ,OutputFilePath )
+print('muGammas:', muGammas)
+
+q12 = 0.0
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+print('q1: ', q1)
+print('q2: ', q2)
+b1 = prestrain_b1(rho1, beta, alpha,theta)
+b2 = prestrain_b2(rho1, beta, alpha,theta)
+q3_star = math.sqrt(q1*q2)
+print('q3_star:', q3_star)
+
+# TODO these have to be compatible with input parameters!!!
+# compute certain ParameterValues that this makes sense
+# b1 = q3_star
+# b2 = q1
+print('b1: ', b1)
+print('b2: ', b2)
+
+# return classifyMin(q1, q2, q3, q12, b1, b2, print_Cases, print_Output)
+
+
+
+# classifyMin_anaVec = np.vectorize(classifyMin_ana)
+# G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
+classifyMin_anaVec = np.vectorize(classifyMin_ana)
+G, angles_1, Types, curvature = classifyMin_anaVec(alpha_1, beta, theta, muGammas, mu1, rho1)
+G, angles_2, Types, curvature = classifyMin_anaVec(alpha_2, beta, theta, muGammas, mu1, rho1)
+G, angles_3, Types, curvature = classifyMin_anaVec(alpha_3, beta, theta, muGammas, mu1, rho1)
+
+# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
+
+print('angles_1:', angles_1)
+print('angles_2:', angles_2)
+print('angles_3:', angles_3)
+
+
+idx = find_nearestIdx(muGammas, q3_star)
+print('GammaValue Idx closest to q_3^*', idx)
+gammaClose = Gamma_Values[idx]
+print('GammaValue(Idx) with mu_gamma closest to q_3^*', gammaClose)
+
+
+
+determinantVec = np.vectorize(determinant)
+
+detValues = determinantVec(q1,q2,muGammas,q12)
+print('detValues:', detValues)
+
+
+detZeroidx = find_nearestIdx(detValues, 0)
+print('idx where det nearest to zero', idx)
+gammaClose = Gamma_Values[detZeroidx]
+print('gammaClose:', gammaClose)
+
+
+# --- Convert to numpy array
+Gamma_Values = np.array(Gamma_Values)
+
+
+angles_1 = np.array(angles_1)
+angles_2 = np.array(angles_2)
+angles_3 = np.array(angles_3)
+
+# ---------------- Create Plot -------------------
+# plt.figure()
+
+
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+width = 6.28
+height = width / 1.618
+height = width / 2.5
+fig = plt.figure()
+
+fig,ax = plt.subplots(nrows=1,ncols=3,figsize=(width,height)) # more than one plot
+# fig,ax = plt.subplots(nrows=1,ncols=3,figsize=(width,height),sharey=True) # Share Y-axis
+
+
+fig = plt.figure()
+gs = fig.add_gridspec(1,3, hspace=0.2, wspace=0.1)
+ax = gs.subplots(sharey=True)
+
+# ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+ax[0].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+ax[0].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+ax[0].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax[1].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+ax[1].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+ax[1].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+ax[2].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+ax[2].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+ax[2].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+ax[0].grid(True,which='major',axis='both',alpha=0.3)
+ax[1].grid(True,which='major',axis='both',alpha=0.3)
+ax[2].grid(True,which='major',axis='both',alpha=0.3)
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+
+
+# # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
+# # plt.title(r'angle$-\gamma$-Plot')
+# plt.plot(Gamma_Values, angles)
+# plt.scatter(Gamma_Values, angles)
+# plt.plot(muGammas, angles)
+# plt.scatter(muGammas, angles)
+# # plt.axis([0, 6, 0, 20])
+# # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+# # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+# plt.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
+# plt.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
+# # plt.axvline(x = q3_star, color = 'r', linestyle = 'dashed', label='$\gamma^*$')
+
+ax[0].plot(Gamma_Values, angles_1, 'royalblue', zorder=3, )
+ax[1].plot(Gamma_Values, angles_2, 'royalblue', zorder=3, )
+ax[2].plot(Gamma_Values, angles_3, 'royalblue', zorder=3, )
+
+ax[0].set_xlabel(r"$\gamma$")
+ax[0].set_ylabel(r"angle $\alpha$")
+ax[0].xaxis.set_minor_locator(MultipleLocator(0.25))
+ax[0].xaxis.set_major_locator(MultipleLocator(0.5))
+
+ax[1].set_xlabel(r"$\gamma$")
+# ax[1].set_ylabel(r"angle $\alpha$")
+ax[1].xaxis.set_minor_locator(MultipleLocator(0.25))
+ax[1].xaxis.set_major_locator(MultipleLocator(0.5))
+
+ax[2].set_xlabel(r"$\gamma$")
+# ax[2].set_ylabel(r"angle $\alpha$")
+ax[2].xaxis.set_minor_locator(MultipleLocator(0.25))
+ax[2].xaxis.set_major_locator(MultipleLocator(0.5))
+# Labels to use in the legend for each line
+line_labels = [r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 5.0$", r"$\theta_\mu = 10.0$"]
+
+
+# ax.plot(Gamma_Values, angles, 'royalblue', zorder=3, )
+# ax.set_xlabel(r"$\gamma$")
+# ax.set_ylabel(r"angle $\alpha$")
+
+# plt.xlabel("$q_3$")
+# plt.xlabel("$\gamma$")
+# plt.ylabel("angle")
+# ax.grid(True)
+
+
+# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+
+# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
+# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+# ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.25))
+
+
+# ax.yaxis.set_major_formatter(ticker.FuncFormatter(
+# lambda val,pos: '{:.0g}$\pi$'.format(2*val/np.pi) if val !=0 else '0'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.5*np.pi))
+
+# ---------------------------- show pi values ------------------------------------
+# ax.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
+# ax.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
+# ax.legend()
+# # ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# # ax.set_yticks([0, np.pi/4 ,np.pi/2])
+# # labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+# ax.set_yticklabels(labels)
+# ---------------------------------------------------------------
+
+
+# ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
+
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# ax.set_yticks([0, np.pi/4 ,np.pi/2])
+# labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
+
+
+# OLD :
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+
+labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+ax[0].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, ])
+ax[1].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2 ])
+ax[2].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2 ])
+
+ax[0].set_yticklabels(labels)
+ax[1].set_yticklabels(labels)
+ax[2].set_yticklabels(labels)
+
+for i in range(3):
+ ax[i].set_ylim([0-0.1, np.pi/2+0.1])
+
+# Plot Gamma Value that is closest to q3_star
+l1 = ax[0].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$')
+l2 = ax[1].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$')
+l3 = ax[2].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$')
+# color elliptic/hyperbolic region
+# ax.axvspan(gamma_min, gammaClose, color='red', alpha=0.2)
+# ax.axvspan(gammaClose, gamma_max, color='green', alpha=0.2)
+
+
+# ax[0].legend(loc='upper right')
+# ax[2].legend(l3,
+# labels=['$\gamma^*$'],
+# loc='upper left',
+# bbox_to_anchor=(1,1))
+
+# ax[2].legend(
+# loc='upper left',
+# bbox_to_anchor=(1,1))
+
+# fig.legend([l1], # The line objects
+# # label='$\gamma^*$', # The labels for each line
+# loc="center right", # Position of legend
+# borderaxespad=0.15 # Small spacing around legend box
+# # title="Legend Title" # Title for the legend
+# )
+
+
+line_labels = [r"$\gamma^*$"]
+
+fig.legend([l1], [r"$\gamma^*$"],
+ # bbox_to_anchor=[0.5, 0.92],
+ bbox_to_anchor=[0.5, 0.94],
+ loc='center', ncol=3)
+
+
+
+# plt.subplots_adjust(wspace=0.4, hspace=0.0)
+# plt.tight_layout()
+
+# Adjust the scaling factor to fit your legend text completely outside the plot
+# (smaller value results in more space being made for the legend)
+# plt.subplots_adjust(right=0.9)
+plt.subplots_adjust(bottom=0.2)
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Angle-Gamma.pdf')
+
+plt.show()
+
+
+
+
+# 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()
+#
diff --git a/src/Plot-Curvature-GammaV2_SubPlots.py b/src/Plot-Curvature-GammaV2_SubPlots.py
new file mode 100644
index 0000000000000000000000000000000000000000..36a677ddfa1221f480d2628228d93d9a4827654c
--- /dev/null
+++ b/src/Plot-Curvature-GammaV2_SubPlots.py
@@ -0,0 +1,471 @@
+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 HelperFunctions 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
+import matplotlib.ticker as ticker
+
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+# from matplotlib import rc
+# rc('text', usetex=True) # Use LaTeX font
+#
+# import seaborn as sns
+# sns.set(color_codes=True)
+
+
+def format_func(value, tick_number):
+ # # find number of multiples of pi/2
+ # N = int(np.round(2 * value / np.pi))
+ # if N == 0:
+ # return "0"
+ # elif N == 1:
+ # return r"$\pi/2$"
+ # elif N == 2:
+ # return r"$\pi$"
+ # elif N % 2 > 0:
+ # return r"${0}\pi/2$".format(N)
+ # else:
+ # return r"${0}\pi$".format(N // 2)
+ # find number of multiples of pi/2
+ N = int(np.round(4 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/4$"
+ elif N == 2:
+ return r"$\pi/2$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+InputFile = "/inputs/computeMuGamma.parset"
+OutputFile = "/outputs/outputMuGamma.txt"
+# --------- 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)
+
+print('---- Input parameters: -----')
+alpha = 10
+mu1 = 1.0
+rho1 = 1.0
+beta = 2.0 #5.0
+theta = 1.0/8.0
+#
+
+alpha = -0.5
+beta = 40.0
+theta= 1/8.0
+
+
+
+# # INTERESTING! from pi/2:
+alpha = -0.5
+beta = 40.0
+theta= 1/8.0
+#
+# # # INTERESTING! from pi/2:
+# alpha = -0.2
+# beta = 25.0
+# theta= 1/2
+
+# INTERESTING!:
+# alpha = -0.5
+# beta = 5.0
+# theta= 1/30
+
+
+
+# INTERESTING!:
+# alpha = -0.25
+# beta = 10.0
+# theta= 3/4
+
+
+# # INTERESTING!:
+alpha = -0.25
+beta = 10.0
+theta= 1/8
+
+#
+# INTERESTING!:
+# alpha = -0.25
+# beta = 5.0
+# theta= 1/8
+#
+
+
+# # INTERESTING!:
+alpha = -0.5
+beta = 10.0
+theta= 1/8
+
+
+
+alpha_1 = -1.0
+alpha_2 = -0.75
+alpha_3 = -0.70
+
+angles_1 = []
+angles_2 = []
+angles_3 = []
+
+beta = 2.0
+theta= 0.25
+
+#Test
+beta = 10.0
+# alpha_1 = -1.0
+# alpha_2 = -0.75
+# alpha_3 = -0.5
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha_1: ', alpha_1)
+print('alpha_2: ', alpha_2)
+print('alpha_3: ', alpha_3)
+print('beta: ', beta)
+print('theta: ', theta)
+# print('gamma:', gamma)
+print('----------------------------')
+
+# ----------------------------------------------------------------
+
+
+gamma_min = 0.01
+gamma_max = 3
+Gamma_Values = np.linspace(gamma_min, gamma_max, num=100) # TODO variable Input Parameters...alpha,beta...
+print('(Input) Gamma_Values:', Gamma_Values)
+# mu_gamma = []
+
+# Gamma_Values = '0'
+
+
+
+# Get values for mu_Gamma
+GetMuGammaVec = np.vectorize(GetMuGamma)
+muGammas = GetMuGammaVec(beta,theta,Gamma_Values,mu1,rho1, InputFilePath ,OutputFilePath )
+print('muGammas:', muGammas)
+
+q12 = 0.0
+q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+print('q1: ', q1)
+print('q2: ', q2)
+b1 = prestrain_b1(rho1, beta, alpha,theta)
+b2 = prestrain_b2(rho1, beta, alpha,theta)
+q3_star = math.sqrt(q1*q2)
+print('q3_star:', q3_star)
+
+# TODO these have to be compatible with input parameters!!!
+# compute certain ParameterValues that this makes sense
+# b1 = q3_star
+# b2 = q1
+print('b1: ', b1)
+print('b2: ', b2)
+
+# return classifyMin(q1, q2, q3, q12, b1, b2, print_Cases, print_Output)
+
+
+
+# classifyMin_anaVec = np.vectorize(classifyMin_ana)
+# G, angles, Types, curvature = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
+classifyMin_anaVec = np.vectorize(classifyMin_ana)
+G, angles_1, Types, curvature_1 = classifyMin_anaVec(alpha_1, beta, theta, muGammas, mu1, rho1)
+G, angles_2, Types, curvature_2 = classifyMin_anaVec(alpha_2, beta, theta, muGammas, mu1, rho1)
+G, angles_3, Types, curvature_3 = classifyMin_anaVec(alpha_3, beta, theta, muGammas, mu1, rho1)
+
+# _,angles,_,_ = classifyMin_anaVec(alpha, beta, theta, muGammas, mu1, rho1)
+
+print('angles_1:', angles_1)
+print('angles_2:', angles_2)
+print('angles_3:', angles_3)
+
+print('curvature_1:', curvature_1)
+print('curvature_2:', curvature_2)
+print('curvature_3:', curvature_3)
+
+
+idx = find_nearestIdx(muGammas, q3_star)
+print('GammaValue Idx closest to q_3^*', idx)
+gammaClose = Gamma_Values[idx]
+print('GammaValue(Idx) with mu_gamma closest to q_3^*', gammaClose)
+
+
+
+determinantVec = np.vectorize(determinant)
+
+detValues = determinantVec(q1,q2,muGammas,q12)
+print('detValues:', detValues)
+
+
+detZeroidx = find_nearestIdx(detValues, 0)
+print('idx where det nearest to zero', idx)
+gammaClose = Gamma_Values[detZeroidx]
+print('gammaClose:', gammaClose)
+
+
+# --- Convert to numpy array
+Gamma_Values = np.array(Gamma_Values)
+
+
+angles_1 = np.array(angles_1)
+angles_2 = np.array(angles_2)
+angles_3 = np.array(angles_3)
+
+curvature_1 = np.array(curvature_1)
+curvature_2 = np.array(curvature_2)
+curvature_3 = np.array(curvature_3)
+
+# ---------------- Create Plot -------------------
+# plt.figure()
+
+
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+width = 6.28
+height = width / 1.618
+height = width / 2.5
+fig = plt.figure()
+
+fig,ax = plt.subplots(nrows=1,ncols=3,figsize=(width,height)) # more than one plot
+
+
+
+# pos1 = ax.get_position() # get the original position
+# pos2 = [pos1.x0 + 0.3, pos1.y0 + 0.3, pos1.width / 2.0, pos1.height / 2.0]
+# ax.set_position(pos2)
+
+
+
+
+# ax = plt.axes((0.15,0.21 ,0.75,0.75))
+# ax = plt.axes((0.15,0.21 ,0.8,0.75))
+# ax.tick_params(axis='x',which='major', direction='out',pad=5)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+
+
+
+# ax[0].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax[0].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax[0].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax[1].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax[1].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax[1].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+# ax[2].yaxis.set_major_locator(plt.MultipleLocator(np.pi / 8))
+# ax[2].yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 16))
+# ax[2].yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+ax[0].grid(True,which='major',axis='both',alpha=0.3)
+ax[1].grid(True,which='major',axis='both',alpha=0.3)
+ax[2].grid(True,which='major',axis='both',alpha=0.3)
+# ax.grid(True,which='major',axis='both',alpha=0.3)
+
+
+# # plt.title(r'angle$-\mu_\gamma(\gamma)$-Plot')
+# # plt.title(r'angle$-\gamma$-Plot')
+# plt.plot(Gamma_Values, angles)
+# plt.scatter(Gamma_Values, angles)
+# 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 = q1, color = 'b', linestyle = ':', label='$q_1$')
+# plt.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
+# # plt.axvline(x = q3_star, color = 'r', linestyle = 'dashed', label='$\gamma^*$')
+
+# ax[0].plot(Gamma_Values, curvature_1, 'royalblue', zorder=3, )
+# ax[1].plot(Gamma_Values, curvature_2, 'royalblue', zorder=3, )
+# ax[2].plot(Gamma_Values, curvature_3, 'royalblue', zorder=3, )
+
+ax[0].plot(Gamma_Values, curvature_1, 'forestgreen', zorder=3, )
+ax[1].plot(Gamma_Values, curvature_2, 'forestgreen', zorder=3, )
+ax[2].plot(Gamma_Values, curvature_3, 'forestgreen', zorder=3, )
+
+ax[0].set_xlabel(r"$\gamma$")
+ax[0].set_ylabel(r"curvature $\kappa$")
+ax[0].xaxis.set_minor_locator(MultipleLocator(0.5))
+ax[0].xaxis.set_major_locator(MultipleLocator(1))
+
+ax[1].set_xlabel(r"$\gamma$")
+# ax[1].set_ylabel(r"angle $\alpha$")
+ax[1].xaxis.set_minor_locator(MultipleLocator(0.5))
+ax[1].xaxis.set_major_locator(MultipleLocator(1))
+
+ax[2].set_xlabel(r"$\gamma$")
+# ax[2].set_ylabel(r"angle $\alpha$")
+ax[2].xaxis.set_minor_locator(MultipleLocator(0.5))
+ax[2].xaxis.set_major_locator(MultipleLocator(1))
+# Labels to use in the legend for each line
+line_labels = [r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 5.0$", r"$\theta_\mu = 10.0$"]
+
+
+# ax.plot(Gamma_Values, angles, 'royalblue', zorder=3, )
+# ax.set_xlabel(r"$\gamma$")
+# ax.set_ylabel(r"angle $\alpha$")
+
+# plt.xlabel("$q_3$")
+# plt.xlabel("$\gamma$")
+# plt.ylabel("angle")
+# ax.grid(True)
+
+
+# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+
+# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
+# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+# ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.25))
+
+
+# ax.yaxis.set_major_formatter(ticker.FuncFormatter(
+# lambda val,pos: '{:.0g}$\pi$'.format(2*val/np.pi) if val !=0 else '0'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.5*np.pi))
+
+# ---------------------------- show pi values ------------------------------------
+# ax.axvline(x = q1, color = 'b', linestyle = ':', label='$q_1$')
+# ax.axvline(x = q2, color = 'r', linestyle = 'dashed', label='$q_2$')
+# ax.legend()
+# # ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# # ax.set_yticks([0, np.pi/4 ,np.pi/2])
+# # labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+# ax.set_yticklabels(labels)
+# ---------------------------------------------------------------
+
+
+# ax.set(xlim=(1.750, 1.880), ylim=(0, math.pi/2.0))
+
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# ax.set(xlim=(1.760, 1.880), ylim=(-0.1, np.pi/4.0))
+# ax.set_yticks([0, np.pi/4 ,np.pi/2])
+# labels = ['$0$', r'$\pi/4$', r'$\pi/2$']
+
+
+# OLD :
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$']
+# ax[0].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, ])
+# ax[1].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2 ])
+# ax[2].set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2 ])
+#
+# ax[0].set_yticklabels(labels)
+# ax[1].set_yticklabels(labels)
+# ax[2].set_yticklabels(labels)
+
+# for i in range(3):
+# ax[i].set_ylim([0-0.1, np.pi/2+0.1])
+
+# Plot Gamma Value that is closest to q3_star
+l1 = ax[0].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$', zorder=4)
+l2 = ax[1].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$', zorder=4)
+l3 = ax[2].axvline(x = gammaClose, color = 'midnightblue', linestyle = 'dashed', linewidth=1, label='$\gamma^*$' ,zorder=4)
+# color elliptic/hyperbolic region
+# ax.axvspan(gamma_min, gammaClose, color='red', alpha=0.2)
+# ax.axvspan(gammaClose, gamma_max, color='green', alpha=0.2)
+
+
+# ax[0].legend(loc='upper right')
+# ax[2].legend(l3,
+# labels=['$\gamma^*$'],
+# loc='upper left',
+# bbox_to_anchor=(1,1))
+
+# ax[1].legend(
+# loc='upper center',
+# # bbox_to_anchor=(1,1))
+# bbox_to_anchor=(1.0,1.0))
+#
+
+line_labels = [r"$\gamma^*$"]
+
+# fig.legend([l1], # The line objects
+# label=line_labels, # The labels for each line
+# loc="center right", # Position of legend
+# borderaxespad=0.15 # Small spacing around legend box
+# # title="Legend Title" # Title for the legend
+# )
+fig.legend([l1], [r"$\gamma^*$"],
+ # bbox_to_anchor=[0.5, 0.92],
+ bbox_to_anchor=[0.5, 0.94],
+ loc='center', ncol=3)
+
+plt.subplots_adjust(wspace=0.4, hspace=0.0)
+# plt.tight_layout()
+
+# Adjust the scaling factor to fit your legend text completely outside the plot
+# (smaller value results in more space being made for the legend)
+# plt.subplots_adjust(right=0.9)
+plt.subplots_adjust(bottom=0.2)
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Curvature-Gamma.pdf')
+
+plt.show()
+
+
+
+
+# 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()
+#
diff --git a/src/Plot_Angle_Alpha.py b/src/Plot_Angle_Alpha.py
index 8a5ecf4819d75ae2bb7e3bc6125b7c94a592f898..4869f56475fb89e734d95202ec4ff81a83435f2e 100644
--- a/src/Plot_Angle_Alpha.py
+++ b/src/Plot_Angle_Alpha.py
@@ -173,17 +173,23 @@ alpha=3.0;
# # INTERESTING!:
-alpha = 3
+# alpha = 3
beta = 10.0
theta= 1/8
+# theta = 0.5
+theta=0.1
+
+#TEST
+beta = 2.0
+theta = 0.5
gamma = 'infinity' #Elliptic Setting
-gamma = '0' #Hyperbolic Settings
+# gamma = '0' #Hyperbolic Settings
# gamma = 0.5
@@ -206,12 +212,11 @@ xmax = 0.99
xmin = -2.0
xmax = 1.0
-xmin = -5.0
-xmax = 5.0
+# xmin = -5.0
+# xmax = 5.0
+
-# theta = 0.5
-theta=0.1
Jumps = True
@@ -410,7 +415,7 @@ mpl.rcParams["font.size"] = "9"
# width as measured in inkscape
width = 6.28 *0.5
-width = 6.28
+# width = 6.28
height = width / 1.618
#setup canvas first
@@ -443,7 +448,8 @@ fig = plt.figure() #main
# fig.set_size_inches(3.54,3.54)
# ax = plt.axes((0.15,0.18,0.8,0.8))
-ax = plt.axes((0.15,0.18,0.6,0.6))
+ax = plt.axes((0.15,0.2,0.75,0.75))
+# ax = plt.axes((0.15,0.18,0.6,0.6))
# ax = plt.axes((0.1,0.1,0.5,0.8))
# ax = plt.axes((0.1,0.1,1,1))
# ax = plt.axes()
@@ -465,8 +471,8 @@ ax.xaxis.set_minor_locator(MultipleLocator(0.05))
ax.xaxis.set_major_locator(MultipleLocator(0.5))
ax.xaxis.set_minor_locator(MultipleLocator(0.25))
-ax.xaxis.set_major_locator(MultipleLocator(1.0))
-ax.xaxis.set_minor_locator(MultipleLocator(0.5))
+# ax.xaxis.set_major_locator(MultipleLocator(1.0))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.5))
#---- print data-types
print(ax.xaxis.get_major_locator())
@@ -556,7 +562,7 @@ ax.grid(True,which='major',axis='both',alpha=0.3)
# --- leave out jumps:
# ax.scatter(X_Values, Y_Values)
-ax.set_xlabel(r"volume fraction $\theta$")
+ax.set_xlabel(r"prestrain ratio $\theta_\rho$")
ax.set_ylabel(r"angle $\alpha$")
@@ -671,22 +677,37 @@ if Jumps:
ax.scatter([transition_point1, transition_point2],[np.pi/2,np.pi/2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- ax.text(transition_point1-0.11 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # ax.text(transition_point1-0.11 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+ #
+ # ax.text(transition_point2+0.06 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+
+ ax.text(transition_point1-0.17 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
)
- ax.text(transition_point2+0.06 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ ax.text(transition_point2+0.1 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
)
else:
ax.scatter([transition_point1, transition_point2, transition_point3 ],[np.pi/2,np.pi/2,0 ],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- ax.text(transition_point1-0.11 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # ax.text(transition_point1-0.11 , np.pi/2-0.02, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+ #
+ # ax.text(transition_point2 + 0.06 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+ #
+ # ax.text(transition_point3 +0.04 , 0+0.04, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+
+ ax.text(transition_point1-0.17 , np.pi/2-0.02, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
)
- ax.text(transition_point2 + 0.06 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ ax.text(transition_point2 + 0.1 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
)
- ax.text(transition_point3 +0.04 , 0+0.04, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ ax.text(transition_point3 +0.08 , 0+0.08, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
)
else:
diff --git a/src/Plot_Angle_Lemma1.4V3_Transition.py b/src/Plot_Angle_Lemma1.4V3_Transition.py
index bdbcef34688e0e6f1fe0a4cd07e9385488925b04..701f8687fc14f80c38628991c433ab19c7f3cc8a 100644
--- a/src/Plot_Angle_Lemma1.4V3_Transition.py
+++ b/src/Plot_Angle_Lemma1.4V3_Transition.py
@@ -180,6 +180,9 @@ theta= 1/8
+#TEST
+beta=2
+
gamma = 'infinity' #Elliptic Setting
diff --git a/src/Plot_Angle_Lemma1.4V3_Transition_Beta2.py b/src/Plot_Angle_Lemma1.4V3_Transition_Beta2.py
new file mode 100644
index 0000000000000000000000000000000000000000..b3ae9bd03e44c3409d89fc9867bcea496413161e
--- /dev/null
+++ b/src/Plot_Angle_Lemma1.4V3_Transition_Beta2.py
@@ -0,0 +1,859 @@
+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
+from HelperFunctions import *
+from ClassifyMin import *
+
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+# import tikzplotlib
+# # from pylab import *
+# from tikzplotlib import save as tikz_save
+
+
+# Needed ?
+mpl.use('pdf')
+
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### makePlot.py #########################
+# Generalized Plot-Script giving the option to define
+# quantity of interest and the parameter it depends on
+# to create a plot
+#
+# Input: Define y & x for "x-y plot" as Strings
+# - Run the 'Cell-Problem' for the different Parameter-Points
+# (alternatively run 'Compute_MuGamma' if quantity of interest
+# is q3=muGamma for a significant Speedup)
+
+###########################################################
+
+
+
+# figsize argument takes inputs in inches
+# and we have the width of our document in pts.
+# To set the figure size we construct a function
+# to convert from pts to inches and to determine
+# an aesthetic figure height using the golden ratio:
+# def set_size(width, fraction=1):
+# """Set figure dimensions to avoid scaling in LaTeX.
+#
+# Parameters
+# ----------
+# width: float
+# Document textwidth or columnwidth in pts
+# fraction: float, optional
+# Fraction of the width which you wish the figure to occupy
+#
+# Returns
+# -------
+# fig_dim: tuple
+# Dimensions of figure in inches
+# """
+# # Width of figure (in pts)
+# fig_width_pt = width * fraction
+#
+# # Convert from pt to inches
+# inches_per_pt = 1 / 72.27
+#
+# # Golden ratio to set aesthetic figure height
+# # https://disq.us/p/2940ij3
+# golden_ratio = (5**.5 - 1) / 2
+#
+# # Figure width in inches
+# fig_width_in = fig_width_pt * inches_per_pt
+# # Figure height in inches
+# fig_height_in = fig_width_in * golden_ratio
+#
+# fig_dim = (fig_width_in, fig_height_in)
+#
+# return fig_dim
+#
+
+
+
+def format_func(value, tick_number):
+ # # find number of multiples of pi/2
+ # N = int(np.round(2 * value / np.pi))
+ # if N == 0:
+ # return "0"
+ # elif N == 1:
+ # return r"$\pi/2$"
+ # elif N == 2:
+ # return r"$\pi$"
+ # elif N % 2 > 0:
+ # return r"${0}\pi/2$".format(N)
+ # else:
+ # return r"${0}\pi$".format(N // 2)
+ # find number of multiples of pi/2
+ N = int(np.round(4 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/4$"
+ elif N == 2:
+ return r"$\pi/2$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+
+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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+mu1 = 1.0 #10.0
+# lambda1 = 10.0
+rho1 = 1.0
+alpha = 5.0
+beta = 10.0
+# alpha = 2.0
+# beta = 2.0
+theta = 1.0/8.0 #1.0/4.0
+
+lambda1 = 0.0
+# gamma = 1.0/4.0
+
+# TEST:
+alpha=3.0;
+
+
+
+
+# # INTERESTING!:
+# alpha = 3
+beta = 2.0
+# theta= 1/8
+
+
+
+
+#TEST
+# beta=2
+
+
+
+gamma = 'infinity' #Elliptic Setting
+# gamma = '0' #Hyperbolic Setting
+# gamma = 0.5
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+
+# --- define Interval of x-va1ues:
+xmin = 0.01
+xmax = 0.41
+xmax = 0.99
+
+
+Jumps = False
+
+
+numPoints = 2000
+numPoints = 100
+X_Values = np.linspace(xmin, xmax, num=numPoints)
+print(X_Values)
+
+
+Y_Values = []
+
+
+
+
+Angle_alpha0 = []
+
+Angle_alphaNeg05 = []
+Angle_alphaNeg055 = []
+Angle_alphaNeg06 = []
+Angle_alphaNeg065 = []
+Angle_alphaNeg07 = []
+Angle_alphaNeg075 = []
+Angle_alphaNeg08 = []
+Angle_alphaNeg085 = []
+Angle_alphaNeg09 = []
+Angle_alphaNeg095 = []
+Angle_alphaNeg1 = []
+
+
+Angle_alphaNeg0125 = []
+Angle_alphaNeg025 = []
+
+Angle_alphaNeg05 = []
+Angle_alphaNeg075 = []
+
+Angle_alpha3 = []
+
+Angle_alphaNeg0625 = []
+Angle_alphaNeg0875 = []
+
+
+
+for theta in X_Values:
+ print('Situation of Lemma1.4')
+ q12 = 0.0
+ q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+ q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+ b1 = prestrain_b1(rho1, beta, alpha,theta)
+ b2 = prestrain_b2(rho1, beta, alpha,theta)
+ b3 = 0.0
+ q3 = GetMuGamma(beta,theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,theta, q3, mu1, rho1)
+ # Y_Values.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.5,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg05.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.55,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg055.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.6,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg06.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.65,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg065.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.7,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg07.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.75,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg075.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.8,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg08.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.85,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg085.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.9,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg09.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.95,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg095.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-1.0,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg1.append(angle)
+
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.5,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg05 .append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.25,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg025.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(3.0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha3.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-1.0,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg075.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha0.append(angle)
+ # # G, angle, Type, curvature = classifyMin_ana(-0.125,beta,theta, q3, mu1, rho1)
+ # # Angle_alphaNeg0125.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.7,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0125.append(angle)
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.625,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0625.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.875,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0875.append(angle)
+
+#
+#
+# print("(Output) Values of angle: ", Y_Values)
+#
+#
+# idx = find_nearestIdx(Y_Values, 0)
+# print(' Idx of value closest to 0', idx)
+# ValueClose = Y_Values[idx]
+# print('GammaValue(Idx) with mu_gamma closest to q_3^*', ValueClose)
+#
+#
+#
+# # Find Indices where the difference between the next one is larger than epsilon...
+# jump_idx = []
+# jump_xValues = []
+# jump_yValues = []
+# tmp = X_Values[0]
+# for idx, x in enumerate(X_Values):
+# print(idx, x)
+# if idx > 0:
+# if abs(Y_Values[idx]-Y_Values[idx-1]) > 1:
+# print('jump candidate')
+# jump_idx.append(idx)
+# jump_xValues.append(x)
+# jump_yValues.append(Y_Values[idx])
+#
+#
+#
+#
+#
+#
+#
+# print("Jump Indices", jump_idx)
+# print("Jump X-values:", jump_xValues)
+# print("Jump Y-values:", jump_yValues)
+#
+# y_plotValues = [Y_Values[0]]
+# x_plotValues = [X_Values[0]]
+# # y_plotValues.extend(jump_yValues)
+# for i in jump_idx:
+# y_plotValues.extend([Y_Values[i-1], Y_Values[i]])
+# x_plotValues.extend([X_Values[i-1], X_Values[i]])
+#
+#
+# y_plotValues.append(Y_Values[-1])
+# # x_plotValues = [X_Values[0]]
+# # x_plotValues.extend(jump_xValues)
+# x_plotValues.append(X_Values[-1])
+#
+#
+# print("y_plotValues:", y_plotValues)
+# print("x_plotValues:", x_plotValues)
+
+
+# Y_Values[np.diff(y) >= 0.5] = np.nan
+
+
+#get values bigger than jump position
+# gamma = infty
+# x_rest = X_Values[X_Values>x_plotValues[1]]
+# Y_Values = np.array(Y_Values) #convert the np array
+# y_rest = Y_Values[X_Values>x_plotValues[1]]
+#
+#
+# # gamma = 0
+# x_rest = X_Values[X_Values>x_plotValues[3]]
+# Y_Values = np.array(Y_Values) #convert the np array
+# y_rest = Y_Values[X_Values>x_plotValues[3]]
+
+# gamma between
+# Y_Values = np.array(Y_Values) #convert the np array
+# X_Values = np.array(X_Values) #convert the np array
+#
+# x_one = X_Values[X_Values>x_plotValues[3]]
+# # ax.scatter(X_Values, Y_Values)
+# y_rest = Y_Values[X_Values>x_plotValues[3]]
+# ax.plot(X_Values[X_Values>0.135], Y_Values[X_Values<0.135])
+#
+#
+#
+
+
+# y_rest = Y_Values[np.nonzero(X_Values>x_plotValues[1]]
+# print('X_Values:', X_Values)
+# print('Y_Values:', Y_Values)
+# print('x_rest:', x_rest)
+# print('y_rest:', y_rest)
+# print('np.nonzero(X_Values>x_plotValues[1]', np.nonzero(X_Values>x_plotValues[1]) )
+
+
+
+
+# --- Convert to numpy array
+Y_Values = np.array(Y_Values)
+X_Values = np.array(X_Values)
+
+Angle_alphaNeg05 = np.array(Angle_alphaNeg05)
+Angle_alphaNeg055 = np.array(Angle_alphaNeg055)
+Angle_alphaNeg06 = np.array(Angle_alphaNeg06)
+Angle_alphaNeg065 = np.array(Angle_alphaNeg065)
+Angle_alphaNeg07 = np.array(Angle_alphaNeg07)
+Angle_alphaNeg075 = np.array(Angle_alphaNeg075)
+Angle_alphaNeg08 = np.array(Angle_alphaNeg08)
+Angle_alphaNeg085 = np.array(Angle_alphaNeg085)
+Angle_alphaNeg09 = np.array(Angle_alphaNeg09)
+Angle_alphaNeg095 = np.array(Angle_alphaNeg095)
+
+
+Angle_alphaNeg1 = np.array(Angle_alphaNeg1)
+
+Angle_alphaNeg025 = np.array(Angle_alphaNeg025)
+Angle_alphaNeg075 = np.array(Angle_alphaNeg075)
+Angle_alpha3 = np.array(Angle_alpha3)
+Angle_alphaNeg0 = np.array(Angle_alpha0)
+Angle_alphaNeg0125 = np.array(Angle_alphaNeg0125)
+
+Angle_alphaNeg0625 = np.array(Angle_alphaNeg0625)
+Angle_alphaNeg0875 = np.array(Angle_alphaNeg0875)
+# ---------------- Create Plot -------------------
+
+#--- change plot style: SEABORN
+# plt.style.use("seaborn-paper")
+
+
+#--- Adjust gobal matplotlib variables
+# mpl.rcParams['pdf.fonttype'] = 42
+# mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+
+# plt.rc('font', family='serif', serif='Times')
+# plt.rc('font', family='serif')
+# # plt.rc('text', usetex=True) #also works...
+# plt.rc('xtick', labelsize=8)
+# plt.rc('ytick', labelsize=8)
+# plt.rc('axes', labelsize=8)
+
+
+
+
+
+#---- Scale Figure apropriately to fit tex-File Width
+# width = 452.9679
+
+# width as measured in inkscape
+width = 6.28 *0.5
+width = 6.28
+height = width / 1.618
+
+#setup canvas first
+fig = plt.figure() #main
+# fig, ax = plt.subplots()
+# fig, (ax, ax2) = plt.subplots(ncols=2)
+# fig,axes = plt.subplots(nrows=1,ncols=2,figsize=(width,height)) # more than one plot
+
+
+# fig.subplots_adjust(left=.15, bottom=.16, right=.99, top=.97) #TEST
+
+
+# TEST
+# mpl.rcParams['figure.figsize'] = (width+0.1,height+0.1)
+# fig = plt.figure(figsize=(width+0.1,height+0.1))
+
+
+# mpl.rcParams['figure.figsize'] = (width,height)
+# fig = plt.figure(figsize=(10,6)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=(width,height)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=set_size(width))
+# fig = plt.subplots(1, 1, figsize=set_size(width))
+
+# --- To create a figure half the width of your document:#
+# fig = plt.figure(figsize=set_size(width, fraction=0.5))
+
+
+
+#--- You must select the correct size of the plot in advance
+# fig.set_size_inches(3.54,3.54)
+
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+ax = plt.axes((0.15,0.18,0.6,0.6))
+# ax = plt.axes((0.1,0.1,0.5,0.8))
+# ax = plt.axes((0.1,0.1,1,1))
+# ax = plt.axes()
+
+# ax.spines['right'].set_visible(False)
+# ax.spines['left'].set_visible(False)
+# ax.spines['bottom'].set_visible(False)
+# ax.spines['top'].set_visible(False)
+# ax.tick_params(axis='x',which='major',direction='out',length=10,width=5,color='red',pad=15,labelsize=15,labelcolor='green',
+# labelrotation=15)
+# ax.tick_params(axis='x',which='major', direction='out',pad=5,labelsize=10)
+# ax.tick_params(axis='y',which='major', length=5, width=1, direction='out',pad=5,labelsize=10)
+ax.tick_params(axis='x',which='major', direction='out',pad=3)
+ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.05))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.025))
+ax.xaxis.set_major_locator(MultipleLocator(0.1))
+ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+
+#---- print data-types
+print(ax.xaxis.get_major_locator())
+print(ax.xaxis.get_minor_locator())
+print(ax.xaxis.get_major_formatter())
+print(ax.xaxis.get_minor_formatter())
+
+#---- Hide Ticks or Labels
+# ax.yaxis.set_major_locator(plt.NullLocator())
+# ax.xaxis.set_major_formatter(plt.NullFormatter())
+
+#---- Reducing or Increasing the Number of Ticks
+# ax.xaxis.set_major_locator(plt.MaxNLocator(3))
+# ax.yaxis.set_major_locator(plt.MaxNLocator(3))
+
+
+#----- Fancy Tick Formats
+ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
+ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+
+
+
+
+
+
+# --- manually change ticks&labels:
+# ax.set_xticks([0.2,1])
+# ax.set_xticklabels(['pos1','pos2'])
+
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+# ax.set_yticklabels(labels)
+
+a=ax.yaxis.get_major_locator()
+b=ax.yaxis.get_major_formatter()
+c = ax.get_xticks()
+d = ax.get_xticklabels()
+print('xticks:',c)
+print('xticklabels:',d)
+
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+
+
+
+
+
+# plt.figure()
+
+# f,ax=plt.subplots(1)
+
+# plt.title(r''+ yName + '-Plot')
+# plt.plot(X_Values, Y_Values,linewidth=2, '.k')
+# plt.plot(X_Values, Y_Values,'.k',markersize=1)
+# plt.plot(X_Values, Y_Values,'.',markersize=0.8)
+
+# plt.plot(X_Values, Y_Values)
+
+# ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+
+
+
+# Gamma = '0'
+# ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
+#
+# ax.plot([x_plotValues[1],x_plotValues[3]], [y_plotValues[2],y_plotValues[3]] , 'b')
+#
+# ax.plot(x_rest, y_rest, 'b')
+
+
+# Gamma between
+
+# x jump values (gamma 0): [0.13606060606060608, 0.21090909090909093]
+
+# ax.plot([[0,jump_xValues[0]], [0, 0]] , 'b')
+# ax.plot([jump_xValues[0],xmin], [y_plotValues[2],y_plotValues[2]] , 'b')
+
+# ax.plot([[0,0.13606060606060608], [0, 0]] , 'b')
+# ax.plot([[0.13606060606060608,xmin], [(math.pi/2),(math.pi/2)]], 'b')
+
+# jump_xValues[0]
+
+
+
+# --- leave out jumps:
+# ax.scatter(X_Values, Y_Values)
+
+ax.set_xlabel(r"volume fraction $\theta$")
+ax.set_ylabel(r"angle $\alpha$")
+
+
+if Jumps:
+
+ # --- leave out jumps:
+ if gamma == 'infinity':
+ ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]] , 'royalblue')
+ ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+
+
+
+ # ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]])
+ # ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]])
+
+
+
+
+ # ax.plot(X_Values[X_Values>0.136], Y_Values[X_Values>0.136])
+ # ax.plot(X_Values[X_Values<0.135], Y_Values[X_Values<0.135])
+ # ax.scatter(X_Values, Y_Values)
+ # ax.plot(X_Values, Y_Values)
+
+ # plt.plot(x_plotValues, y_plotValues,'.')
+ # plt.scatter(X_Values, Y_Values, alpha=0.3)
+ # plt.scatter(X_Values, Y_Values)
+ # plt.plot(X_Values, Y_Values,'.')
+ # plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+ # plt.axis([0, 6, 0, 20])
+
+ # ax.set_xlabel(r"volume fraction $\theta$", size=11)
+ # ax.set_ylabel(r"angle $\angle$", size=11)
+ # ax.set_xlabel(r"volume fraction $\theta$")
+ # # ax.set_ylabel(r"angle $\angle$")
+ # ax.set_ylabel(r"angle $\alpha$")
+ # plt.ylabel('$\kappa$')
+
+ # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+ # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+ # Plot every other line.. not the jumps...
+
+ if gamma == '0':
+ tmp = 1
+ for idx, x in enumerate(x_plotValues):
+ if idx > 0 and tmp == 1:
+ # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
+ ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]], 'royalblue', zorder=2)
+ tmp = 0
+ else:
+ tmp = 1
+
+ # plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
+ # plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
+ # plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
+ # plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
+
+
+ for x in jump_xValues:
+ plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1, zorder=1)
+ # plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', label=r'$\theta_*$')
+
+ # plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+ # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+ # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+ # plt.legend()
+
+
+ # -- SETUP LEGEND
+ # ax.legend(prop={'size': 11})
+ # ax.legend()
+
+ # ------------------ SAVE FIGURE
+ # tikzplotlib.save("TesTout.tex")
+ # plt.close()
+ # mpl.rcParams.update(mpl.rcParamsDefault)
+
+ # plt.savefig("graph.pdf",
+ # #This is simple recomendation for publication plots
+ # dpi=1000,
+ # # Plot will be occupy a maximum of available space
+ # bbox_inches='tight',
+ # )
+ # plt.savefig("graph.pdf")
+
+
+
+ # ---- ADD additional scatter:
+ # ax.scatter(X_Values,Y_Values,s=1,c='black',zorder=4)
+
+ # Find transition point
+ lastIdx = len(Y_Values)-1
+
+ for idx, y in enumerate(Y_Values):
+ if idx != lastIdx:
+ if abs(y-0) < 0.01 and abs(Y_Values[idx+1] - 0) > 0.05:
+ transition_point1 = X_Values[idx+1]
+ print('transition point1:', transition_point1 )
+ if abs(y-0.5*np.pi) < 0.01 and abs(Y_Values[idx+1] -0.5*np.pi)>0.01:
+ transition_point2 = X_Values[idx]
+ print('transition point2:', transition_point2 )
+ if abs(y-0) > 0.01 and abs(Y_Values[idx+1] - 0) < 0.01:
+ transition_point3 = X_Values[idx+1]
+ print('transition point3:', transition_point3 )
+
+ # Add transition Points:
+ if gamma == '0':
+ ax.scatter([transition_point1, transition_point2],[np.pi/2,np.pi/2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2+0.012 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+ else:
+ ax.scatter([transition_point1, transition_point2, transition_point3 ],[np.pi/2,np.pi/2,0 ],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2 +0.011 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point3 +0.009 , 0+0.08, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+else:
+ # ax.scatter(X_Values,Y_Values,s=1, marker='o', cmap=None, norm=None, facecolor = 'blue',
+ # edgecolor = 'none', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alpha0,s=1, marker='o', edgecolor = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=0.75, linewidths=None, zorder=4)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1, label=r"$\theta_\rho = -1.0$")
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg05,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg025,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0125,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ #
+ # line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = 3.0$"]
+ # ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ # labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ # ax.set_yticklabels(labels)
+ #
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7],
+ # labels= [ r"$\theta_\rho = 0$", r"$\theta_\rho = -0.125$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.75$", r"$\theta_\rho = -1.0$", r"$\theta_\rho = 3.0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0875,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg075,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg0625,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg05,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg025,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alphaNeg0125,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l8 = ax.scatter(X_Values,Angle_alpha0,s=2, marker='s', edgecolor = 'black', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+
+ l1 = ax.plot(X_Values,Angle_alphaNeg05, color='blue', linewidth=1.5, zorder=3, label=r"$\theta_\rho=0.5$")
+ l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=0.55$")
+ l3 = ax.plot(X_Values,Angle_alphaNeg06,color='orangered', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=0.6$")
+ l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=0.65$")
+ l5 = ax.plot(X_Values,Angle_alphaNeg07,color='orange', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=0.7$")
+ l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=0.75$")
+ l7 = ax.plot(X_Values,Angle_alphaNeg08, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=0.8$")
+ l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=0.85$")
+ l9 = ax.plot(X_Values,Angle_alphaNeg09, color='teal',linestyle = '--', linewidth=1.5 , zorder=3, label=r"$\theta_\rho=0.9$")
+ l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=0.95$")
+ l11 = ax.plot(X_Values,Angle_alphaNeg1, color='red', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=1.0$")
+
+ # l6 = ax.plot(X_Values,Angle_alphaNeg025,color='lightskyblue', linewidth=1.5,linestyle = '--', zorder=3)
+ # l7 = ax.plot(X_Values,Angle_alphaNeg0125,color='dodgerblue', linewidth=1.5,linestyle = ':', zorder=5)
+ # l8 = ax.plot(X_Values,Angle_alpha0, color='blue', linewidth=1.5 ,zorder=1)
+
+
+ # l1 = ax.plot(X_Values,Angle_alphaNeg1, color='red', linewidth=1.5, zorder=3, label = 'test')
+ # l2 = ax.plot(X_Values,Angle_alphaNeg0875,color='orangered', linewidth=1.5 ,linestyle = '--' ,zorder=3)
+ # l3 = ax.plot(X_Values,Angle_alphaNeg075,color='orange', linewidth=1.5,linestyle = '--' ,zorder=3)
+ # l4 = ax.plot(X_Values,Angle_alphaNeg0625, linewidth=1.5,linestyle = '--' , zorder=3)
+ # l5 = ax.plot(X_Values,Angle_alphaNeg05, color='teal',linestyle = '--', linewidth=1.5 , zorder=3)
+ # l6 = ax.plot(X_Values,Angle_alphaNeg025,color='lightskyblue', linewidth=1.5,linestyle = '--', zorder=3)
+ # l7 = ax.plot(X_Values,Angle_alphaNeg0125,color='dodgerblue', linewidth=1.5,linestyle = ':', zorder=5)
+ # l8 = ax.plot(X_Values,Angle_alpha0, color='blue', linewidth=1.5 ,zorder=1)
+
+ ax.legend(handles=[l1[0],l2[0],l3[0],l4[0], l5[0], l6[0], l7[0], l8[0], l9[0], l10[0], l11[0]],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ loc='upper left',
+ bbox_to_anchor=(1,1))
+ #
+ # ax.legend(handles=[l1[0],l2[0],l3[0],l4[0], l5[0], l6[0], l7[0], l8[0]],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ #
+
+
+
+# ax.plot(X_Values, Y_Values, marker='o', markerfacecolor='orange', markeredgecolor='black', markeredgewidth=1, linewidth=1, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+
+ # line_labels = [r"$\theta_\rho = -1.0$",r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = - \frac{3}{4}$", r"$\theta_\rho = - \frac{5}{8}$",r"$\theta_\rho = - 0.5 $" ,r"$\theta_\rho = - 0.25", r"$\theta_\rho = - \frac{1}{8}" , r"$\theta_\rho = 0$"]
+ ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ ax.set_yticklabels(labels)
+
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7, l8],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+
+
+
+
+
+
+ # fig.legend([l1, l2, l3, l4], # The line objects
+ # labels=line_labels, # The labels for each line
+ # # loc="upper center", # Position of legend
+ # loc='upperleft', bbox_to_anchor=(1,1),
+ # borderaxespad=0.15 # Small spacing around legend box
+ # # title="Legend Title" # Title for the legend
+ # )
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Angle-Theta.pdf')
+
+
+
+
+# tikz_save('someplot.tex', figureheight='5cm', figurewidth='9cm')
+
+# tikz_save('fig.tikz',
+# figureheight = '\\figureheight',
+# figurewidth = '\\figurewidth')
+
+# ----------------------------------------
+
+
+plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot_Angle_Theta_intermediateGamma.py b/src/Plot_Angle_Theta_intermediateGamma.py
new file mode 100644
index 0000000000000000000000000000000000000000..465bb9eb26103eab7e4239d5f100a4f917aaddee
--- /dev/null
+++ b/src/Plot_Angle_Theta_intermediateGamma.py
@@ -0,0 +1,924 @@
+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
+from HelperFunctions import *
+from ClassifyMin import *
+
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+# import tikzplotlib
+# # from pylab import *
+# from tikzplotlib import save as tikz_save
+
+
+# Needed ?
+mpl.use('pdf')
+
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### makePlot.py #########################
+# Generalized Plot-Script giving the option to define
+# quantity of interest and the parameter it depends on
+# to create a plot
+#
+# Input: Define y & x for "x-y plot" as Strings
+# - Run the 'Cell-Problem' for the different Parameter-Points
+# (alternatively run 'Compute_MuGamma' if quantity of interest
+# is q3=muGamma for a significant Speedup)
+
+###########################################################
+
+
+
+# figsize argument takes inputs in inches
+# and we have the width of our document in pts.
+# To set the figure size we construct a function
+# to convert from pts to inches and to determine
+# an aesthetic figure height using the golden ratio:
+# def set_size(width, fraction=1):
+# """Set figure dimensions to avoid scaling in LaTeX.
+#
+# Parameters
+# ----------
+# width: float
+# Document textwidth or columnwidth in pts
+# fraction: float, optional
+# Fraction of the width which you wish the figure to occupy
+#
+# Returns
+# -------
+# fig_dim: tuple
+# Dimensions of figure in inches
+# """
+# # Width of figure (in pts)
+# fig_width_pt = width * fraction
+#
+# # Convert from pt to inches
+# inches_per_pt = 1 / 72.27
+#
+# # Golden ratio to set aesthetic figure height
+# # https://disq.us/p/2940ij3
+# golden_ratio = (5**.5 - 1) / 2
+#
+# # Figure width in inches
+# fig_width_in = fig_width_pt * inches_per_pt
+# # Figure height in inches
+# fig_height_in = fig_width_in * golden_ratio
+#
+# fig_dim = (fig_width_in, fig_height_in)
+#
+# return fig_dim
+#
+
+
+
+def format_func(value, tick_number):
+ # # find number of multiples of pi/2
+ # N = int(np.round(2 * value / np.pi))
+ # if N == 0:
+ # return "0"
+ # elif N == 1:
+ # return r"$\pi/2$"
+ # elif N == 2:
+ # return r"$\pi$"
+ # elif N % 2 > 0:
+ # return r"${0}\pi/2$".format(N)
+ # else:
+ # return r"${0}\pi$".format(N // 2)
+ # find number of multiples of pi/2
+ N = int(np.round(4 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/4$"
+ elif N == 2:
+ return r"$\pi/2$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+
+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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+mu1 = 1.0 #10.0
+# lambda1 = 10.0
+rho1 = 1.0
+# alpha = 5.0
+# beta = 10.0
+# alpha = 2.0
+# beta = 2.0
+# theta = 1.0/8.0 #1.0/4.0
+
+lambda1 = 0.0
+# gamma = 1.0/4.0
+
+# TEST:
+# alpha=3.0;
+
+
+
+
+# # INTERESTING!:
+# alpha = 3
+beta = 2.0
+# theta= 1/8
+
+
+
+
+#TEST
+# beta=2
+
+
+
+gamma = 'infinity' #Elliptic Setting
+gamma = '0' #Hyperbolic Setting
+gamma = 0.00001
+gamma = 100
+gamma = 10000
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+# print('alpha: ', alpha)
+print('beta: ', beta)
+# print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+
+# --- define Interval of x-va1ues:
+xmin = 0.01
+# xmax = 0.41
+# xmax = 0.99
+xmin = 0.06
+xmax = 0.94
+
+
+Jumps = False
+
+
+numPoints = 2000
+numPoints = 11
+X_Values = np.linspace(xmin, xmax, num=numPoints)
+print(X_Values)
+
+
+
+###Test with theta values that satisfy condition: theta = k*(1/(2^level)) for k=1,2...
+# integers = np.linspace(1,30, num=30)
+integers = np.linspace(10,60, num=13)
+print('integers:',integers)
+
+Theta_Values = []
+
+for i in integers:
+ # Theta_Values.append(i*(1/32))
+ Theta_Values.append(i*(1/64))
+
+print('Theta_Values',Theta_Values)
+
+
+
+
+
+
+
+
+
+
+Y_Values = []
+
+
+
+
+Angle_alpha0 = []
+
+Angle_alphaNeg05 = []
+Angle_alphaNeg055 = []
+Angle_alphaNeg06 = []
+Angle_alphaNeg065 = []
+Angle_alphaNeg07 = []
+Angle_alphaNeg075 = []
+Angle_alphaNeg08 = []
+Angle_alphaNeg085 = []
+Angle_alphaNeg09 = []
+Angle_alphaNeg095 = []
+Angle_alphaNeg1 = []
+
+Angle_alphaNeg3 = []
+
+
+Angle_alphaNeg0125 = []
+Angle_alphaNeg025 = []
+
+Angle_alphaNeg05 = []
+Angle_alphaNeg075 = []
+
+Angle_alpha3 = []
+
+Angle_alphaNeg0625 = []
+Angle_alphaNeg0875 = []
+
+
+
+# for theta in X_Values:
+for theta in Theta_Values:
+ print('Situation of Lemma1.4')
+ q12 = 0.0
+ q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+ q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+ # b1 = prestrain_b1(rho1, beta, alpha,theta)
+ # b2 = prestrain_b2(rho1, beta, alpha,theta)
+ # b3 = 0.0
+ q3 = GetMuGamma(beta,theta,gamma,mu1,rho1,InputFilePath ,OutputFilePath)
+ print('-----------------')
+ print('theta:', theta)
+ print('q1=',q1)
+ print('q2=',q2)
+ print('q3=',q3)
+ print('-----------------')
+ # G, angle, Type, curvature = classifyMin_ana(alpha,beta,theta, q3, mu1, rho1)
+ # Y_Values.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.5,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg05.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.55,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg055.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.6,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg06.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.65,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg065.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.7,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg07.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.75,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg075.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.8,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg08.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.85,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg085.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.9,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg09.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-0.95,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg095.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-1.0,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg1.append(angle)
+
+ G, angle, Type, curvature = classifyMin_ana(-3.0,beta,theta, q3, mu1, rho1)
+ Angle_alphaNeg3.append(angle)
+
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.5,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg05 .append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.25,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg025.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(3.0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha3.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-1.0,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg075.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(0,beta,theta, q3, mu1, rho1)
+ # Angle_alpha0.append(angle)
+ # # G, angle, Type, curvature = classifyMin_ana(-0.125,beta,theta, q3, mu1, rho1)
+ # # Angle_alphaNeg0125.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.7,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0125.append(angle)
+ #
+ # G, angle, Type, curvature = classifyMin_ana(-0.625,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0625.append(angle)
+ # G, angle, Type, curvature = classifyMin_ana(-0.875,beta,theta, q3, mu1, rho1)
+ # Angle_alphaNeg0875.append(angle)
+
+#
+#
+# print("(Output) Values of angle: ", Y_Values)
+#
+#
+# idx = find_nearestIdx(Y_Values, 0)
+# print(' Idx of value closest to 0', idx)
+# ValueClose = Y_Values[idx]
+# print('GammaValue(Idx) with mu_gamma closest to q_3^*', ValueClose)
+#
+#
+#
+# # Find Indices where the difference between the next one is larger than epsilon...
+# jump_idx = []
+# jump_xValues = []
+# jump_yValues = []
+# tmp = X_Values[0]
+# for idx, x in enumerate(X_Values):
+# print(idx, x)
+# if idx > 0:
+# if abs(Y_Values[idx]-Y_Values[idx-1]) > 1:
+# print('jump candidate')
+# jump_idx.append(idx)
+# jump_xValues.append(x)
+# jump_yValues.append(Y_Values[idx])
+#
+#
+#
+#
+#
+#
+#
+# print("Jump Indices", jump_idx)
+# print("Jump X-values:", jump_xValues)
+# print("Jump Y-values:", jump_yValues)
+#
+# y_plotValues = [Y_Values[0]]
+# x_plotValues = [X_Values[0]]
+# # y_plotValues.extend(jump_yValues)
+# for i in jump_idx:
+# y_plotValues.extend([Y_Values[i-1], Y_Values[i]])
+# x_plotValues.extend([X_Values[i-1], X_Values[i]])
+#
+#
+# y_plotValues.append(Y_Values[-1])
+# # x_plotValues = [X_Values[0]]
+# # x_plotValues.extend(jump_xValues)
+# x_plotValues.append(X_Values[-1])
+#
+#
+# print("y_plotValues:", y_plotValues)
+# print("x_plotValues:", x_plotValues)
+
+
+# Y_Values[np.diff(y) >= 0.5] = np.nan
+
+
+#get values bigger than jump position
+# gamma = infty
+# x_rest = X_Values[X_Values>x_plotValues[1]]
+# Y_Values = np.array(Y_Values) #convert the np array
+# y_rest = Y_Values[X_Values>x_plotValues[1]]
+#
+#
+# # gamma = 0
+# x_rest = X_Values[X_Values>x_plotValues[3]]
+# Y_Values = np.array(Y_Values) #convert the np array
+# y_rest = Y_Values[X_Values>x_plotValues[3]]
+
+# gamma between
+# Y_Values = np.array(Y_Values) #convert the np array
+# X_Values = np.array(X_Values) #convert the np array
+#
+# x_one = X_Values[X_Values>x_plotValues[3]]
+# # ax.scatter(X_Values, Y_Values)
+# y_rest = Y_Values[X_Values>x_plotValues[3]]
+# ax.plot(X_Values[X_Values>0.135], Y_Values[X_Values<0.135])
+#
+#
+#
+
+
+# y_rest = Y_Values[np.nonzero(X_Values>x_plotValues[1]]
+# print('X_Values:', X_Values)
+# print('Y_Values:', Y_Values)
+# print('x_rest:', x_rest)
+# print('y_rest:', y_rest)
+# print('np.nonzero(X_Values>x_plotValues[1]', np.nonzero(X_Values>x_plotValues[1]) )
+
+
+
+
+# --- Convert to numpy array
+Y_Values = np.array(Y_Values)
+X_Values = np.array(X_Values)
+Theta_Values = np.array(Theta_Values)
+
+Angle_alphaNeg05 = np.array(Angle_alphaNeg05)
+Angle_alphaNeg055 = np.array(Angle_alphaNeg055)
+Angle_alphaNeg06 = np.array(Angle_alphaNeg06)
+Angle_alphaNeg065 = np.array(Angle_alphaNeg065)
+Angle_alphaNeg07 = np.array(Angle_alphaNeg07)
+Angle_alphaNeg075 = np.array(Angle_alphaNeg075)
+Angle_alphaNeg08 = np.array(Angle_alphaNeg08)
+Angle_alphaNeg085 = np.array(Angle_alphaNeg085)
+Angle_alphaNeg09 = np.array(Angle_alphaNeg09)
+Angle_alphaNeg095 = np.array(Angle_alphaNeg095)
+
+
+Angle_alphaNeg1 = np.array(Angle_alphaNeg1)
+Angle_alphaNeg3 = np.array(Angle_alphaNeg3)
+
+Angle_alphaNeg025 = np.array(Angle_alphaNeg025)
+Angle_alphaNeg075 = np.array(Angle_alphaNeg075)
+Angle_alpha3 = np.array(Angle_alpha3)
+Angle_alphaNeg0 = np.array(Angle_alpha0)
+Angle_alphaNeg0125 = np.array(Angle_alphaNeg0125)
+
+Angle_alphaNeg0625 = np.array(Angle_alphaNeg0625)
+Angle_alphaNeg0875 = np.array(Angle_alphaNeg0875)
+# ---------------- Create Plot -------------------
+
+#--- change plot style: SEABORN
+# plt.style.use("seaborn-paper")
+
+
+#--- Adjust gobal matplotlib variables
+# mpl.rcParams['pdf.fonttype'] = 42
+# mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+
+
+# plt.rc('font', family='serif', serif='Times')
+# plt.rc('font', family='serif')
+# # plt.rc('text', usetex=True) #also works...
+# plt.rc('xtick', labelsize=8)
+# plt.rc('ytick', labelsize=8)
+# plt.rc('axes', labelsize=8)
+
+
+
+
+
+#---- Scale Figure apropriately to fit tex-File Width
+# width = 452.9679
+
+# width as measured in inkscape
+width = 6.28 *0.5
+width = 6.28
+height = width / 1.618
+
+#setup canvas first
+fig = plt.figure() #main
+# fig, ax = plt.subplots()
+# fig, (ax, ax2) = plt.subplots(ncols=2)
+# fig,axes = plt.subplots(nrows=1,ncols=2,figsize=(width,height)) # more than one plot
+
+
+# fig.subplots_adjust(left=.15, bottom=.16, right=.99, top=.97) #TEST
+
+
+# TEST
+# mpl.rcParams['figure.figsize'] = (width+0.1,height+0.1)
+# fig = plt.figure(figsize=(width+0.1,height+0.1))
+
+
+# mpl.rcParams['figure.figsize'] = (width,height)
+# fig = plt.figure(figsize=(10,6)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=(width,height)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=set_size(width))
+# fig = plt.subplots(1, 1, figsize=set_size(width))
+
+# --- To create a figure half the width of your document:#
+# fig = plt.figure(figsize=set_size(width, fraction=0.5))
+
+
+
+#--- You must select the correct size of the plot in advance
+# fig.set_size_inches(3.54,3.54)
+
+# ax = plt.axes((0.15,0.18,0.8,0.8))
+ax = plt.axes((0.15,0.18,0.6,0.6))
+# ax = plt.axes((0.1,0.1,0.5,0.8))
+# ax = plt.axes((0.1,0.1,1,1))
+# ax = plt.axes()
+
+# ax.spines['right'].set_visible(False)
+# ax.spines['left'].set_visible(False)
+# ax.spines['bottom'].set_visible(False)
+# ax.spines['top'].set_visible(False)
+# ax.tick_params(axis='x',which='major',direction='out',length=10,width=5,color='red',pad=15,labelsize=15,labelcolor='green',
+# labelrotation=15)
+# ax.tick_params(axis='x',which='major', direction='out',pad=5,labelsize=10)
+# ax.tick_params(axis='y',which='major', length=5, width=1, direction='out',pad=5,labelsize=10)
+ax.tick_params(axis='x',which='major', direction='out',pad=3)
+ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.05))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.025))
+ax.xaxis.set_major_locator(MultipleLocator(0.1))
+ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+
+#---- print data-types
+print(ax.xaxis.get_major_locator())
+print(ax.xaxis.get_minor_locator())
+print(ax.xaxis.get_major_formatter())
+print(ax.xaxis.get_minor_formatter())
+
+#---- Hide Ticks or Labels
+# ax.yaxis.set_major_locator(plt.NullLocator())
+# ax.xaxis.set_major_formatter(plt.NullFormatter())
+
+#---- Reducing or Increasing the Number of Ticks
+# ax.xaxis.set_major_locator(plt.MaxNLocator(3))
+# ax.yaxis.set_major_locator(plt.MaxNLocator(3))
+
+
+#----- Fancy Tick Formats
+ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 4))
+ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+
+
+
+
+
+
+
+# --- manually change ticks&labels:
+# ax.set_xticks([0.2,1])
+# ax.set_xticklabels(['pos1','pos2'])
+
+# ax.set_yticks([0, np.pi/8, np.pi/4 ])
+# labels = ['$0$',r'$\pi/8$', r'$\pi/4$']
+# ax.set_yticklabels(labels)
+
+a=ax.yaxis.get_major_locator()
+b=ax.yaxis.get_major_formatter()
+c = ax.get_xticks()
+d = ax.get_xticklabels()
+print('xticks:',c)
+print('xticklabels:',d)
+
+ax.grid(True,which='major',axis='both',alpha=0.3)
+
+
+
+
+
+
+# plt.figure()
+
+# f,ax=plt.subplots(1)
+
+# plt.title(r''+ yName + '-Plot')
+# plt.plot(X_Values, Y_Values,linewidth=2, '.k')
+# plt.plot(X_Values, Y_Values,'.k',markersize=1)
+# plt.plot(X_Values, Y_Values,'.',markersize=0.8)
+
+# plt.plot(X_Values, Y_Values)
+
+# ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+
+
+
+# Gamma = '0'
+# ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
+#
+# ax.plot([x_plotValues[1],x_plotValues[3]], [y_plotValues[2],y_plotValues[3]] , 'b')
+#
+# ax.plot(x_rest, y_rest, 'b')
+
+
+# Gamma between
+
+# x jump values (gamma 0): [0.13606060606060608, 0.21090909090909093]
+
+# ax.plot([[0,jump_xValues[0]], [0, 0]] , 'b')
+# ax.plot([jump_xValues[0],xmin], [y_plotValues[2],y_plotValues[2]] , 'b')
+
+# ax.plot([[0,0.13606060606060608], [0, 0]] , 'b')
+# ax.plot([[0.13606060606060608,xmin], [(math.pi/2),(math.pi/2)]], 'b')
+
+# jump_xValues[0]
+
+
+
+# --- leave out jumps:
+# ax.scatter(X_Values, Y_Values)
+
+ax.set_xlabel(r"volume fraction $\theta$")
+ax.set_ylabel(r"angle $\alpha$")
+
+
+if Jumps:
+
+ # --- leave out jumps:
+ if gamma == 'infinity':
+ ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]] , 'royalblue')
+ ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+
+
+
+ # ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]])
+ # ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]])
+
+
+
+
+ # ax.plot(X_Values[X_Values>0.136], Y_Values[X_Values>0.136])
+ # ax.plot(X_Values[X_Values<0.135], Y_Values[X_Values<0.135])
+ # ax.scatter(X_Values, Y_Values)
+ # ax.plot(X_Values, Y_Values)
+
+ # plt.plot(x_plotValues, y_plotValues,'.')
+ # plt.scatter(X_Values, Y_Values, alpha=0.3)
+ # plt.scatter(X_Values, Y_Values)
+ # plt.plot(X_Values, Y_Values,'.')
+ # plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+ # plt.axis([0, 6, 0, 20])
+
+ # ax.set_xlabel(r"volume fraction $\theta$", size=11)
+ # ax.set_ylabel(r"angle $\angle$", size=11)
+ # ax.set_xlabel(r"volume fraction $\theta$")
+ # # ax.set_ylabel(r"angle $\angle$")
+ # ax.set_ylabel(r"angle $\alpha$")
+ # plt.ylabel('$\kappa$')
+
+ # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+ # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+ # Plot every other line.. not the jumps...
+
+ if gamma == '0':
+ tmp = 1
+ for idx, x in enumerate(x_plotValues):
+ if idx > 0 and tmp == 1:
+ # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
+ ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]], 'royalblue', zorder=2)
+ tmp = 0
+ else:
+ tmp = 1
+
+ # plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
+ # plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
+ # plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
+ # plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
+
+
+ for x in jump_xValues:
+ plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1, zorder=1)
+ # plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', label=r'$\theta_*$')
+
+ # plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+ # plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+ # plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+ # plt.legend()
+
+
+ # -- SETUP LEGEND
+ # ax.legend(prop={'size': 11})
+ # ax.legend()
+
+ # ------------------ SAVE FIGURE
+ # tikzplotlib.save("TesTout.tex")
+ # plt.close()
+ # mpl.rcParams.update(mpl.rcParamsDefault)
+
+ # plt.savefig("graph.pdf",
+ # #This is simple recomendation for publication plots
+ # dpi=1000,
+ # # Plot will be occupy a maximum of available space
+ # bbox_inches='tight',
+ # )
+ # plt.savefig("graph.pdf")
+
+
+
+ # ---- ADD additional scatter:
+ # ax.scatter(X_Values,Y_Values,s=1,c='black',zorder=4)
+
+ # Find transition point
+ lastIdx = len(Y_Values)-1
+
+ for idx, y in enumerate(Y_Values):
+ if idx != lastIdx:
+ if abs(y-0) < 0.01 and abs(Y_Values[idx+1] - 0) > 0.05:
+ transition_point1 = X_Values[idx+1]
+ print('transition point1:', transition_point1 )
+ if abs(y-0.5*np.pi) < 0.01 and abs(Y_Values[idx+1] -0.5*np.pi)>0.01:
+ transition_point2 = X_Values[idx]
+ print('transition point2:', transition_point2 )
+ if abs(y-0) > 0.01 and abs(Y_Values[idx+1] - 0) < 0.01:
+ transition_point3 = X_Values[idx+1]
+ print('transition point3:', transition_point3 )
+
+ # Add transition Points:
+ if gamma == '0':
+ ax.scatter([transition_point1, transition_point2],[np.pi/2,np.pi/2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2+0.012 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+ else:
+ ax.scatter([transition_point1, transition_point2, transition_point3 ],[np.pi/2,np.pi/2,0 ],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+ ax.text(transition_point1-0.02 , np.pi/2-0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point2 +0.011 , np.pi/2-0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(transition_point3 +0.009 , 0+0.08, r"$3$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+else:
+ # ax.scatter(X_Values,Y_Values,s=1, marker='o', cmap=None, norm=None, facecolor = 'blue',
+ # edgecolor = 'none', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alpha0,s=1, marker='o', edgecolor = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=0.75, linewidths=None, zorder=4)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1, label=r"$\theta_\rho = -1.0$")
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg05,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg025,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0125,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ #
+ # line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = 3.0$"]
+ # ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ # labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ # ax.set_yticklabels(labels)
+ #
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7],
+ # labels= [ r"$\theta_\rho = 0$", r"$\theta_\rho = -0.125$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.75$", r"$\theta_\rho = -1.0$", r"$\theta_\rho = 3.0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ # ---------------------------------------------------------------
+ # l1 = ax.scatter(X_Values,Angle_alphaNeg1,s=2, marker='s', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=1)
+ # l2 = ax.scatter(X_Values,Angle_alphaNeg0875,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l3 = ax.scatter(X_Values,Angle_alphaNeg075,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l4 = ax.scatter(X_Values,Angle_alphaNeg0625,s=2, marker='o',cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg05,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l6 = ax.scatter(X_Values,Angle_alphaNeg025,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alphaNeg0125,s=2, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l8 = ax.scatter(X_Values,Angle_alpha0,s=2, marker='s', edgecolor = 'black', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+
+ # l1 = ax.plot(X_Values,Angle_alphaNeg05, color='blue', linewidth=1.5, zorder=3, label=r"$\theta_\rho=-0.5$")
+ # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ # l3 = ax.plot(X_Values,Angle_alphaNeg06,color='orangered', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.6$")
+ # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ # l5 = ax.plot(X_Values,Angle_alphaNeg07,color='orange', linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.7$")
+ # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ # l7 = ax.plot(X_Values,Angle_alphaNeg08, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.8$")
+ # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ # l9 = ax.plot(X_Values,Angle_alphaNeg09, color='teal',linestyle = '--', linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.9$")
+ # l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.95$")
+ # l11 = ax.plot(X_Values,Angle_alphaNeg1, color='red', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-1.0$")
+
+
+ # l1 = ax.plot(X_Values,Angle_alphaNeg05, color='blue', linewidth=1.5, zorder=3, label=r"$\theta_\rho=-0.5$")
+ # # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ # l3 = ax.plot(X_Values,Angle_alphaNeg06,color='orangered', linewidth=1.5 ,zorder=3, label=r"$\theta_\rho=-0.6$")
+ # # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ # l5 = ax.plot(X_Values,Angle_alphaNeg07,color='orange', linewidth=1.5 ,zorder=3, label=r"$\theta_\rho=-0.7$")
+ # # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ # l7 = ax.plot(X_Values,Angle_alphaNeg08, linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.8$")
+ # # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ # l9 = ax.plot(X_Values,Angle_alphaNeg09, color='teal', linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.9$")
+ # # l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.95$")
+ # l11 = ax.plot(X_Values,Angle_alphaNeg1, color='red', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-1.0$")
+ #
+ # l12 = ax.plot(X_Values,Angle_alphaNeg3, color='black', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-3.0$")
+ #
+
+ #TEST
+
+ l1 = ax.plot(Theta_Values,Angle_alphaNeg05, color='blue', linewidth=1.5, zorder=3, label=r"$\theta_\rho=-0.5$")
+ # l2 = ax.plot(X_Values,Angle_alphaNeg055, linewidth=1.5, linestyle = '--', zorder=3,label=r"$\theta_\rho=-0.55$")
+ l3 = ax.plot(Theta_Values,Angle_alphaNeg06,color='orangered', linewidth=1.5 ,zorder=3, label=r"$\theta_\rho=-0.6$")
+ # l4 = ax.plot(X_Values,Angle_alphaNeg065, linewidth=1.5 ,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.65$")
+ l5 = ax.plot(Theta_Values,Angle_alphaNeg07,color='orange', linewidth=1.5 ,zorder=3, label=r"$\theta_\rho=-0.7$")
+ # l6 = ax.plot(X_Values,Angle_alphaNeg075, linewidth=1.5,linestyle = '--' ,zorder=3, label=r"$\theta_\rho=-0.75$")
+ l7 = ax.plot(Theta_Values,Angle_alphaNeg08, linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.8$")
+ # l8 = ax.plot(X_Values,Angle_alphaNeg085, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.85$")
+ l9 = ax.plot(Theta_Values,Angle_alphaNeg09, color='teal', linewidth=1.5 , zorder=3, label=r"$\theta_\rho=-0.9$")
+ # l10 = ax.plot(X_Values,Angle_alphaNeg095, linewidth=1.5,linestyle = '--' , zorder=3, label=r"$\theta_\rho=-0.95$")
+ l11 = ax.plot(Theta_Values,Angle_alphaNeg1, color='red', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-1.0$")
+
+ l12 = ax.plot(Theta_Values,Angle_alphaNeg3, color='black', linewidth=1.5 ,zorder=1, label=r"$\theta_\rho=-3.0$")
+
+
+
+
+ # ax.legend(handles=[l1[0],l2[0],l3[0],l4[0], l5[0], l6[0], l7[0], l8[0], l9[0], l10[0], l11[0]],
+ # # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ ax.legend(handles=[l1[0],l3[0], l5[0], l7[0], l9[0], l11[0], l12[0]],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ loc='upper left',
+ bbox_to_anchor=(1,1))
+
+
+
+# ax.plot(X_Values, Y_Values, marker='o', markerfacecolor='orange', markeredgecolor='black', markeredgewidth=1, linewidth=1, zorder=3)
+ # l7 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', facecolor = 'none',edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=5)
+ # l4 = ax.scatter(X_Values,Angle_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Angle_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+
+
+ # line_labels = [r"$\theta_\rho = -1.0$",r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = - \frac{3}{4}$", r"$\theta_\rho = - \frac{5}{8}$",r"$\theta_\rho = - 0.5 $" ,r"$\theta_\rho = - 0.25", r"$\theta_\rho = - \frac{1}{8}" , r"$\theta_\rho = 0$"]
+ ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
+ labels = ['$0$',r'$\pi/8$', r'$\pi/4$' ,r'$3\pi/8$' , r'$\pi/2$',r'$5\pi/8$']
+ ax.set_yticklabels(labels)
+
+ # ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7, l8],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+
+ #
+ # ax.legend(handles=[l1,l3, l5, l7, l8],
+ # labels= [r"$\theta_\rho = -1.0$", r"$\theta_\rho = - \frac{7}{8}$", r"$\theta_\rho = -\frac{3}{4}$" , r"$\theta_\rho = - \frac{5}{8}$", r"$\theta_\rho = - \frac{1}{2} $" , r"$\theta_\rho = - \frac{1}{4}$", r"$\theta_\rho = - \frac{1}{8}$" , r"$\theta_\rho = 0$"],
+ # loc='upper left',
+ # bbox_to_anchor=(1,1))
+ #
+
+
+
+
+
+ # fig.legend([l1, l2, l3, l4], # The line objects
+ # labels=line_labels, # The labels for each line
+ # # loc="upper center", # Position of legend
+ # loc='upperleft', bbox_to_anchor=(1,1),
+ # borderaxespad=0.15 # Small spacing around legend box
+ # # title="Legend Title" # Title for the legend
+ # )
+
+pdf_outputName = 'Plot-Angle-Theta_Gamma'+ str(gamma)+ '.pdf'
+
+fig.set_size_inches(width, height)
+# fig.savefig('Plot-Angle-Theta.pdf')
+fig.savefig(pdf_outputName)
+
+
+
+
+# tikz_save('someplot.tex', figureheight='5cm', figurewidth='9cm')
+
+# tikz_save('fig.tikz',
+# figureheight = '\\figureheight',
+# figurewidth = '\\figurewidth')
+
+# ----------------------------------------
+
+
+plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot_Curvature_Alpha.py b/src/Plot_Curvature_Alpha.py
index e62edb94139c76ccf01c60e5f113b80e8af0f284..862bd66457db80a01885fc446ff29466b036cf6c 100644
--- a/src/Plot_Curvature_Alpha.py
+++ b/src/Plot_Curvature_Alpha.py
@@ -180,9 +180,15 @@ theta= 1/8
theta = 0.5
+theta = 0.1
-theta = 0.1
+#TEST
+beta = 2.0
+theta = 0.5
+
+beta=10.0
+
gamma = 'infinity' #Elliptic Setting
gamma = '0' #Hyperbolic Setting
@@ -206,16 +212,23 @@ print('----------------------------')
xmin = -2.0
+# xmin = -1.5
xmax = 1.0
-xmin = -5.0
-xmax = 5.0
-Jumps = False
+# compare with interpolant between endpoints
+# xmin = -0.7014028056112225
+# xmax = 0.70
+compare_interpolant = False
+# xmin = -5.0
+# xmax = 5.0
+
+Jumps = False
+Jumps = True
-numPoints = 2000
-# numPoints = 100
+numPoints = 15
+numPoints = 500
X_Values = np.linspace(xmin, xmax, num=numPoints)
print(X_Values)
@@ -239,7 +252,7 @@ Curvature_alphaNeg5 = []
for alpha in X_Values:
- print('Situation of Lemma1.4')
+ # print('Situation of Lemma1.4')
q12 = 0.0
q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
@@ -275,7 +288,9 @@ print(' Idx of value closest to 0', idx)
ValueClose = Y_Values[idx]
print('GammaValue(Idx) with mu_gamma closest to q_3^*', ValueClose)
-
+# jumpThreshold = 0.5
+jumpThreshold = 0.05
+# jumpThreshold = 0.01
# Find Indices where the difference between the next one is larger than epsilon...
jump_idx = []
@@ -285,7 +300,7 @@ tmp = X_Values[0]
for idx, x in enumerate(X_Values):
print(idx, x)
if idx > 0:
- if abs(Y_Values[idx]-Y_Values[idx-1]) > 0.5:
+ if abs(Y_Values[idx]-Y_Values[idx-1]) > jumpThreshold :
print('jump candidate')
jump_idx.append(idx)
jump_xValues.append(x)
@@ -398,7 +413,7 @@ mpl.rcParams["font.size"] = "9"
# width as measured in inkscape
width = 6.28 *0.5
-width = 6.28
+# width = 6.28
height = width / 1.618
#setup canvas first
@@ -431,7 +446,8 @@ fig = plt.figure() #main
# fig.set_size_inches(3.54,3.54)
# ax = plt.axes((0.15,0.18,0.8,0.8))
-ax = plt.axes((0.15,0.18,0.6,0.6))
+# ax = plt.axes((0.15,0.18,0.6,0.6))
+ax = plt.axes((0.15,0.2,0.75,0.75))
# ax = plt.axes((0.1,0.1,0.5,0.8))
# ax = plt.axes((0.1,0.1,1,1))
# ax = plt.axes()
@@ -454,8 +470,8 @@ ax.xaxis.set_minor_locator(MultipleLocator(0.05))
ax.xaxis.set_major_locator(MultipleLocator(0.5))
ax.xaxis.set_minor_locator(MultipleLocator(0.25))
-ax.xaxis.set_major_locator(MultipleLocator(1.0))
-ax.xaxis.set_minor_locator(MultipleLocator(0.5))
+
+
#---- print data-types
print(ax.xaxis.get_major_locator())
@@ -555,28 +571,57 @@ if Jumps:
# ax.plot(X_Values[X_Values>=jump_xValues[0]], Y_Values[X_Values>=jump_xValues[0]] , 'royalblue')
# ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
- # Plot every other line.. not the jumps...
+ ## Plot every other line.. not the jumps..
+ # if gamma == '0':
+ # tmp = 1
+ # for idx, x in enumerate(x_plotValues):
+ # if idx > 0 and tmp == 1:
+ # # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
+ # ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]], 'royalblue', zorder=2)
+ # tmp = 0
+ # else:
+ # tmp = 1
- if gamma == '0':
- tmp = 1
- for idx, x in enumerate(x_plotValues):
- if idx > 0 and tmp == 1:
- # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
- ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]], 'royalblue', zorder=2)
- tmp = 0
- else:
- tmp = 1
- # plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
- # plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
- # plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
- # plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
for x in jump_xValues:
plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1, zorder=1)
# plt.axvline(x,ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', label=r'$\theta_*$')
+
+ # print('jump_idx[0]:',jump_idx[0])
+ # print('X_Values[jump_idx[0]]',X_Values[jump_idx[0]])
+ # print('X_Values[jump_idx[1]]',X_Values[jump_idx[1]])
+ # print('Y_Values[jump_idx[0]]',Y_Values[jump_idx[0]])
+ # print('Y_Values[jump_idx[1]]',Y_Values[jump_idx[1]])
+
+ # Better use for-loop!!
+
+ if gamma == '0':
+ ax.scatter([X_Values[jump_idx[0]], X_Values[jump_idx[1]]],[Y_Values[jump_idx[0]],Y_Values[jump_idx[1]]],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=5)
+
+ # ax.text(X_Values[jump_idx[0]]+0.05, Y_Values[jump_idx[0]]+0.02, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+ #
+ # ax.text(X_Values[jump_idx[1]]+0.05, Y_Values[jump_idx[1]]+0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
+ ax.text(X_Values[jump_idx[0]]+0.075, Y_Values[jump_idx[0]]+0.04, r"$2$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ ax.text(X_Values[jump_idx[1]]+0.075, Y_Values[jump_idx[1]]+0.04, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
+
+ else :
+ ax.scatter([X_Values[jump_idx[0]]],[Y_Values[jump_idx[0]]],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=5)
+
+ # ax.text(X_Values[jump_idx[0]]+0.05, Y_Values[jump_idx[0]]+0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ # )
+
+ ax.text(X_Values[jump_idx[0]]+0.075, Y_Values[jump_idx[0]]+0.04, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
+ )
+
+ # ax.text(X_Values[jump_idx[1]]+0.05, Y_Values[jump_idx[1]]+0.02, r"$1$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
# plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
# plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
@@ -607,19 +652,19 @@ if Jumps:
# ax.scatter(X_Values,Y_Values,s=1,c='black',zorder=4)
# Find transition point
- lastIdx = len(Y_Values)-1
-
- for idx, y in enumerate(Y_Values):
- if idx != lastIdx:
- if abs(y-0) < 0.01 and abs(Y_Values[idx+1] - 0) > 0.05:
- transition_point1 = X_Values[idx+1]
- print('transition point1:', transition_point1 )
- if abs(y-0.5*np.pi) < 0.01 and abs(Y_Values[idx+1] -0.5*np.pi)>0.01:
- transition_point2 = X_Values[idx]
- print('transition point2:', transition_point2 )
- if abs(y-0) > 0.01 and abs(Y_Values[idx+1] - 0) < 0.01:
- transition_point3 = X_Values[idx+1]
- print('transition point3:', transition_point3 )
+ # lastIdx = len(Y_Values)-1
+ #
+ # for idx, y in enumerate(Y_Values):
+ # if idx != lastIdx:
+ # if abs(y-0) < 0.01 and abs(Y_Values[idx+1] - 0) > 0.05:
+ # transition_point1 = X_Values[idx+1]
+ # print('transition point1:', transition_point1 )
+ # if abs(y-0.5*np.pi) < 0.01 and abs(Y_Values[idx+1] -0.5*np.pi)>0.01:
+ # transition_point2 = X_Values[idx]
+ # print('transition point2:', transition_point2 )
+ # if abs(y-0) > 0.01 and abs(Y_Values[idx+1] - 0) < 0.01:
+ # transition_point3 = X_Values[idx+1]
+ # print('transition point3:', transition_point3 )
# Add transition Points
if gamma == '0':
@@ -630,9 +675,13 @@ if Jumps:
plt.axvline(jump_xValues[0],ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
- ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
- ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]], 'royalblue')
+ # ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+ # ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]], 'royalblue')
+ # l1 = ax.scatter(X_Values,Y_Values,s=1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ l1 = ax.scatter(X_Values,Y_Values,s=0.1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l1 = ax.plot(X_Values,Y_Values,s=1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l1 = ax.plot(X_Values,Y_Values, color='forestgreen', linewidth=1.5, zorder=3, label = 'test')
# plt.axvline(jump_xValues[0],ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
#
# ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
@@ -648,11 +697,14 @@ if Jumps:
# ax.text(transition_point2+0.012 , jump_yValues[1]+0.02, r"$5$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
# )
+
else :
plt.axvline(jump_xValues[0],ymin=0, ymax= 1, color = 'orange',alpha=0.5, linestyle = 'dashed', linewidth=1)
- ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
- ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]], 'royalblue')
+ # ax.plot(X_Values[X_Values<jump_xValues[0]], Y_Values[X_Values<jump_xValues[0]], 'royalblue')
+ # ax.plot(X_Values[X_Values>jump_xValues[0]], Y_Values[X_Values>jump_xValues[0]], 'royalblue')
+ # l1 = ax.scatter(X_Values,Y_Values,s=1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ l1 = ax.scatter(X_Values,Y_Values,s=0.1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
# idx1 = find_nearestIdx(X_Values, transition_point1)
# idx2 = find_nearestIdx(X_Values, transition_point2)
# print('idx1', idx1)
@@ -663,15 +715,17 @@ if Jumps:
# print('Y_TP2', Y_TP2)
+
+
# ax.scatter([transition_point1, transition_point2],[Y_TP1, Y_TP2],s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
# edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
# ax.text(transition_point1-0.02 , Y_TP1-0.02, r"$6$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5)
# ax.text(transition_point2+0.015 , Y_TP2+0.020, r"$7$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
- ax.scatter(jump_xValues,jump_yValues,s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
- edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- ax.text(jump_xValues[0]+0.05 , jump_yValues[0]+0.02, r"$6$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
+ # ax.scatter(jump_xValues,jump_yValues,s=6, marker='o', cmap=None, norm=None, facecolor = 'black',
+ # edgecolor = 'black', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # ax.text(jump_xValues[0]+0.05 , jump_yValues[0]+0.02, r"$6$", size=6, bbox=dict(boxstyle="circle",facecolor='white', alpha=1.0, pad=0.1, linewidth=0.5))
else:
@@ -716,9 +770,15 @@ else:
- # l1 = ax.plot(X_Values,Y_Values, color='red', linewidth=1.5, zorder=3, label = 'test')
- l1 = ax.scatter(X_Values,Y_Values,s=1, marker='o', edgecolor = 'red', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ # l1 = ax.plot(X_Values,Y_Values, color='forestgreen', linewidth=1.5, zorder=3, label = 'test')
+ l1 = ax.scatter(X_Values,Y_Values,s=1, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+
+
+ # l1 = ax.scatter(X_Values,Y_Values,s=6, marker='o', edgecolor = 'forestgreen', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=4)
+ #compare with interpolant between endpoints
+ if compare_interpolant:
+ ax.plot([X_Values[0],X_Values[-1]],[Y_Values[0],Y_Values[-1]])
fig.set_size_inches(width, height)
diff --git a/src/Plot_Curvature_Lemma1.4V3.py b/src/Plot_Curvature_Lemma1.4V3.py
index 171664aca8a2b163898d37f75f4ec84c44315c84..d21c3eb4212c8f63941458f4165730aee9244eb0 100644
--- a/src/Plot_Curvature_Lemma1.4V3.py
+++ b/src/Plot_Curvature_Lemma1.4V3.py
@@ -173,12 +173,13 @@ alpha=3.0;
# # INTERESTING!:
-alpha = 3
+# alpha = 3
beta = 10.0
-theta= 1/8
-
+# theta= 1/8
+#Test
+# beta = 2.0
@@ -206,8 +207,8 @@ xmax = 0.99
Jumps = False
-numPoints = 2000
-numPoints = 100
+numPoints = 400
+# numPoints = 100
X_Values = np.linspace(xmin, xmax, num=numPoints)
print(X_Values)
@@ -530,7 +531,7 @@ ax.grid(True,which='major',axis='both',alpha=0.3)
# ax.scatter(X_Values, Y_Values)
ax.set_xlabel(r"volume fraction $\theta$")
-ax.set_ylabel(r"Curvature $\alpha$")
+ax.set_ylabel(r"Curvature $\kappa$")
if Jumps:
@@ -635,18 +636,25 @@ if Jumps:
else:
# ax.scatter(X_Values,Y_Values,s=1, marker='o', cmap=None, norm=None, facecolor = 'blue',
- # edgecolor = 'none', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- l1 = ax.scatter(X_Values,Curvature_alphaNeg5,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=3)
- l2 = ax.scatter(X_Values,Curvature_alphaNeg1,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3, label=r"$\theta_\rho = -1.0$")
- l3 = ax.scatter(X_Values,Curvature_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- l4 = ax.scatter(X_Values,Curvature_alphaNeg05,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- l5 = ax.scatter(X_Values,Curvature_alphaNeg025,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- l6 = ax.scatter(X_Values,Curvature_alphaNeg0125,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
- l7 = ax.scatter(X_Values,Curvature_alpha0,s=1, marker='o', edgecolor = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=0.75, linewidths=None, zorder=4)
- l8 = ax.scatter(X_Values,Curvature_alpha3,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=4)
- # l4 = ax.scatter(X_Values,Curvature_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
-
-
+ # # edgecolor = 'none', vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l1 = ax.scatter(X_Values,Curvature_alphaNeg5,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=3)
+ # l2 = ax.scatter(X_Values,Curvature_alphaNeg1,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3, label=r"$\theta_\rho = -1.0$")
+ # l3 = ax.scatter(X_Values,Curvature_alphaNeg075,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l4 = ax.scatter(X_Values,Curvature_alphaNeg05,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l5 = ax.scatter(X_Values,Curvature_alphaNeg025,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l6 = ax.scatter(X_Values,Curvature_alphaNeg0125,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ # l7 = ax.scatter(X_Values,Curvature_alpha0,s=1, marker='o', edgecolor = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=0.75, linewidths=None, zorder=4)
+ # l8 = ax.scatter(X_Values,Curvature_alpha3,s=1, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=4)
+ # # # l4 = ax.scatter(X_Values,Curvature_alpha3,s=1, marker='o', markerfacecolor='red',markeredgecolor='black',markeredgewidth=2, cmap=None, norm=None, vmin=None, vmax=None, alpha=0.5, linewidths=None, zorder=3)
+
+ l1 = ax.scatter(X_Values,Curvature_alphaNeg5,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=3)
+ l2 = ax.scatter(X_Values,Curvature_alphaNeg1,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3, label=r"$\theta_\rho = -1.0$")
+ l3 = ax.scatter(X_Values,Curvature_alphaNeg075,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ l4 = ax.scatter(X_Values,Curvature_alphaNeg05,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ l5 = ax.scatter(X_Values,Curvature_alphaNeg025,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ l6 = ax.scatter(X_Values,Curvature_alphaNeg0125,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=None, linewidths=None, zorder=3)
+ l7 = ax.scatter(X_Values,Curvature_alpha0,s=0.25, color = 'black',cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=4)
+ l8 = ax.scatter(X_Values,Curvature_alpha3,s=0.25, marker='o', cmap=None, norm=None, vmin=None, vmax=None, alpha=1.0, linewidths=None, zorder=4)
# line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = 3.0$"]
# ax.set_yticks([0, np.pi/8, np.pi/4, 3*np.pi/8 , np.pi/2, 5*np.pi/8 ])
@@ -655,11 +663,22 @@ else:
# ax.set_yticks([1.570786327, np.pi/2 ])
# labels = [r'$\pi/2-0.0005 $' , r'$\pi/2$']
# ax.set_yticklabels(labels)
- ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7, l8],
+ lgnd = ax.legend(handles=[l1,l2,l3,l4, l5, l6, l7, l8],
labels= [r"$\theta_\rho = -5.0$", r"$\theta_\rho = -1.0$",r"$\theta_\rho = -0.75$", r"$\theta_\rho = -0.5$", r"$\theta_\rho = -0.25$", r"$\theta_\rho = -0.125$", r"$\theta_\rho = 0$", r"$\theta_\rho = 3.0$" ],
loc='upper left',
+ # fontsize=10,
+ # scatterpoints=1,
bbox_to_anchor=(1,1))
+ lgnd.legendHandles[0]._sizes = [10]
+ lgnd.legendHandles[1]._sizes = [10]
+ lgnd.legendHandles[2]._sizes = [10]
+ lgnd.legendHandles[3]._sizes = [10]
+ lgnd.legendHandles[4]._sizes = [10]
+ lgnd.legendHandles[5]._sizes = [10]
+ lgnd.legendHandles[6]._sizes = [10]
+ lgnd.legendHandles[7]._sizes = [10]
+
# fig.legend([l1, l2, l3, l4], # The line objects
# labels=line_labels, # The labels for each line
# # loc="upper center", # Position of legend
diff --git a/src/Plot_MinVec_v2.py b/src/Plot_MinVec_v2.py
new file mode 100644
index 0000000000000000000000000000000000000000..8fc808395b76261877748d5baccaf5568a642f66
--- /dev/null
+++ b/src/Plot_MinVec_v2.py
@@ -0,0 +1,581 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import sympy as sym
+import math
+import os
+import subprocess
+import fileinput
+import re
+import matlab.engine
+from HelperFunctions import *
+from ClassifyMinVec import *
+import matplotlib.cm as cm
+from matplotlib.colors import Normalize
+
+import matplotlib.ticker as ticker
+# from subprocess import Popen, PIPE
+#import sys
+
+###################### makePlot.py #########################
+# Generalized Plot-Script giving the option to define
+# quantity of interest and the parameter it depends on
+# to create a plot
+#
+# Input: Define y & x for "x-y plot" as Strings
+# - Run the 'Cell-Problem' for the different Parameter-Points
+# (alternatively run 'Compute_MuGamma' if quantity of interest
+# is q3=muGamma for a significant Speedup)
+
+###########################################################
+
+def format_func(value, tick_number):
+ # find number of multiples of pi/2
+ N = int(np.round(2 * value / np.pi))
+ if N == 0:
+ return "0"
+ elif N == 1:
+ return r"$\pi/2$"
+ elif N == 2:
+ return r"$\pi$"
+ elif N % 2 > 0:
+ return r"${0}\pi/2$".format(N)
+ else:
+ return r"${0}\pi$".format(N // 2)
+
+
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+InputFile = "/inputs/cellsolver.parset"
+OutputFile = "/outputs/output.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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+# mu1 = 10.0
+# # lambda1 = 10.0
+rho1 = 1.0
+# alpha = 5.0
+# beta = 10.0
+# theta = 1.0/4.0
+
+
+mu1 = 10.0
+# lambda1 = 10.0
+# rho1 = 10.0
+alpha = 5.0
+# beta = 2.0
+beta = 10.0
+theta = 1.0/4.0
+
+theta = 1.0/2.0
+# theta = 1.0/12.0
+
+
+lambda1 = 0.0
+gamma = 1.0/4.0
+
+gamma = 'infinity'
+# gamma = '0'
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+# TODO? : Ask User for Input ...
+# function = input("Enter value you want to plot (y-value):\n")
+# print(f'You entered {function}')
+# parameter = input("Enter Parameter this value depends on (x-value) :\n")
+# print(f'You entered {parameter}')
+
+# Add Option to change NumberOfElements used for computation of Cell-Problem
+
+
+# --- Define Quantity of interest:
+# Options: 'q1', 'q2', 'q3', 'q12' ,'q21', 'q31', 'q13' , 'q23', 'q32' , 'b1', 'b2' ,'b3'
+# TODO: EXTRA (MInimization Output) 'Minimizer (norm?)' 'angle', 'type', 'curvature'
+# yName = 'q12'
+# # yName = 'b1'
+# yName = 'q3'
+yName = 'angle'
+yName = 'curvature'
+yName = 'MinVec'
+
+# --- Define Parameter this function/quantity depends on:
+# Options: mu1 ,lambda1, rho1 , alpha, beta, theta, gamma
+# xName = 'theta'
+# xName = 'gamma'
+# xName = 'lambda1'
+xName = 'theta'
+# xName = 'alpha'
+
+
+# --- define Interval of x-values:
+xmin = 0
+xmax = 30
+
+# xmin = 0.245
+# xmax = 0.99
+#
+#
+# xmin = 0.14
+# xmax = 0.19
+
+# xmin = 0.01
+# xmax = 3.0
+
+xmin = 0.125
+xmax = 0.250
+
+xmin = 0.05
+xmax = 0.3
+
+xmin = 0.15
+xmax = 0.3
+
+xmin = 0.193
+xmax = 0.24
+
+xmin=0.05
+xmax=0.4
+
+numPoints =100
+X_Values = np.linspace(xmin, xmax, num=numPoints)
+print('X_values:', X_Values)
+
+
+Y_Values = []
+Angle_Values = []
+
+
+other = False
+
+
+
+for theta in X_Values:
+# for alpha in X_Values:
+
+ print('Situation of Lemma1.4')
+ q12 = 0.0
+ q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
+ q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+ b1 = prestrain_b1(rho1, beta, alpha,theta)
+ b2 = prestrain_b2(rho1, beta, alpha,theta)
+ b3 = 0.0
+ if gamma == '0':
+ q3 = q2
+ if gamma == 'infinity':
+ q3 = q1
+
+ if yName == 'q1': # TODO: Better use dictionary?...
+ print('q1 used')
+ Y_Values.append(q1)
+ elif yName =='q2':
+ print('q2 used')
+ Y_Values.append(q2)
+ elif yName =='q3':
+ print('q3 used')
+ Y_Values.append(q3)
+ elif yName =='q12':
+ print('q12 used')
+ Y_Values.append(q12)
+ elif yName =='b1':
+ print('b1 used')
+ Y_Values.append(b1)
+ elif yName =='b2':
+ print('b2 used')
+ Y_Values.append(b2)
+ elif yName =='b3':
+ print('b3 used')
+ Y_Values.append(b3)
+ elif yName == 'angle' or yName =='type' or yName =='curvature' or yName =='MinVec':
+ G, angle, Type, curvature = classifyMin_ana(alpha,beta,theta, q3, mu1, rho1)
+ if yName =='angle':
+ print('angle used')
+ Y_Values.append(angle)
+ if yName =='type':
+ print('angle used')
+ Y_Values.append(type)
+ if yName =='curvature':
+ print('angle used')
+ Y_Values.append(curvature)
+ if yName =='MinVec':
+ print('Minvec used')
+ Y_Values.append(G)
+ Angle_Values.append(angle)
+
+
+print("(Output) Values of " + yName + ": ", Y_Values)
+
+
+# idx = find_nearestIdx(Y_Values, 0)
+# print(' Idx of value closest to 0', idx)
+# ValueClose = Y_Values[idx]
+# print('GammaValue(Idx) with mu_gamma closest to q_3^*', ValueClose)
+#
+#
+#
+# # Find Indices where the difference between the next one is larger than epsilon...
+# jump_idx = []
+# jump_xValues = []
+# jump_yValues = []
+# tmp = X_Values[0]
+# for idx, x in enumerate(X_Values):
+# print(idx, x)
+# if idx > 0:
+# if abs(Y_Values[idx]-Y_Values[idx-1]) > 1:
+# print('jump candidate')
+# jump_idx.append(idx)
+# jump_xValues.append(x)
+# jump_yValues.append(Y_Values[idx])
+#
+
+
+
+
+#
+#
+# print("Jump Indices", jump_idx)
+# print("Jump X-values:", jump_xValues)
+# print("Jump Y-values:", jump_yValues)
+#
+# y_plotValues = [Y_Values[0]]
+# x_plotValues = [X_Values[0]]
+# # y_plotValues.extend(jump_yValues)
+# for i in jump_idx:
+# y_plotValues.extend([Y_Values[i-1], Y_Values[i]])
+# x_plotValues.extend([X_Values[i-1], X_Values[i]])
+#
+#
+# y_plotValues.append(Y_Values[-1])
+# # x_plotValues = [X_Values[0]]
+# # x_plotValues.extend(jump_xValues)
+# x_plotValues.append(X_Values[-1])
+#
+#
+# print("y_plotValues:", y_plotValues)
+# print("x_plotValues:", x_plotValues)
+# # Y_Values[np.diff(y) >= 0.5] = np.nan
+
+#
+# #get values bigger than jump position
+# x_rest = X_Values[X_Values>x_plotValues[1]]
+#
+# Y_Values = np.array(Y_Values) #convert the np array
+#
+# y_rest = Y_Values[X_Values>x_plotValues[1]]
+# # y_rest = Y_Values[np.nonzero(X_Values>x_plotValues[1]]
+# print('X_Values:', X_Values)
+# print('Y_Values:', Y_Values)
+# print('x_rest:', x_rest)
+# print('y_rest:', y_rest)
+# print('np.nonzero(X_Values>x_plotValues[1]', np.nonzero(X_Values>x_plotValues[1]) )
+
+
+print('X_values:', X_Values)
+print('Y_values:', Y_Values)
+
+
+
+# ---------------- Create Plot -------------------
+plt.figure()
+
+f,ax=plt.subplots(1)
+
+# plt.title(r''+ yName + '-Plot')
+# plt.plot(X_Values, Y_Values,linewidth=2, '.k')
+# plt.plot(X_Values, Y_Values,'.k',markersize=1)
+# plt.plot(X_Values, Y_Values,'.',markersize=0.8)
+
+# plt.plot(X_Values, Y_Values)
+
+# ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+# ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
+# ax.plot(x_rest, y_rest, 'b')
+
+ #Define jump
+JumpVal = 0.19
+X_Values = np.array(X_Values)
+Y_Values = np.array(Y_Values)
+Angle_Values = np.array(Angle_Values)
+X_one = X_Values[X_Values<0.19]
+Y_one = Y_Values[X_Values<0.19]
+Angle_one=Angle_Values[X_Values<0.19]
+X_two = X_Values[X_Values>=0.19]
+Y_two = Y_Values[X_Values>=0.19]
+Angle_two=Angle_Values[X_Values>=0.19]
+
+# X_Values = X_two
+# Y_Values = Y_two
+# Angle_Values = Angle_two
+print('X_one:', X_one)
+
+
+X_Values = np.asarray(X_Values, dtype=float)
+
+color=['r','b','g']
+cmap = cm.get_cmap(name='rainbow')
+Y_two = np.asarray(Y_two, dtype=float)
+Angle_Values = np.asarray(Angle_Values, dtype=float)
+Angle_two = np.asarray(Angle_two, dtype=float)
+X_two = np.asarray(X_two, dtype=float)
+
+Y_one = np.asarray(Y_one, dtype=float)
+Angle_one = np.asarray(Angle_one, dtype=float)
+X_one = np.asarray(X_one, dtype=float)
+
+
+
+print('X_one:', X_one)
+print('Y_one:', Y_one)
+print('Angle_one:', Angle_one)
+
+print('X_two:', X_two)
+print('Y_two:', Y_two)
+print('Angle_two:', Angle_two)
+
+# print('X_Values:', X_Values)
+# print('Y_arr:', Y_arr)
+#
+#
+# print('Angle_two:', Angle_two)
+
+
+
+
+# Or = np.zeros_like(Y_arr)
+# Or_tmp = np.ones_like(X_Values)
+
+# Or = np.concatenate(([X_Values],[Or_tmp]) ,axis=1)
+# Or = np.array([X_Values,Or_tmp])
+
+# print('np.transpose(X_Values)', np.transpose(X_Values))
+# print('X_Values.shape', X_Values.shape[0] )
+# print('reshape X_Values', X_Values.reshape(X_Values.shape[0],1).shape)
+#
+# print('ones.', np.ones((5,1),dtype=float))
+
+
+
+
+
+# Or = np.hstack([np.transpose(X_Values),np.transpose(Or_tmp)])
+# Or = np.hstack((X_Values,np.ones((X_Values.shape[0],1), dtype=X_Values.dtype)))
+X_two= X_two.reshape(X_two.shape[0],1)
+X_one= X_one.reshape(X_one.shape[0],1)
+
+Or_one = np.hstack((X_one,np.zeros((X_one.shape[0],1),dtype=float)))
+Or = np.hstack((X_two,np.zeros((X_two.shape[0],1),dtype=float)))
+print('Or:', Or)
+print('Or_one:', Or_one)
+# -----------------------------------------------------------------------------
+
+#normalize
+sum_of_rows = Y_two.sum(axis=1)
+Y_twoN = Y_two / sum_of_rows[:,np.newaxis]
+# Y_arrN = Y_arr / np.sqrt(np.sum(Y_arr**2))
+print('normalized Y_twoN:', Y_twoN)
+
+sum_of_rows_one = Y_one.sum(axis=1)
+Y_oneN = Y_one / sum_of_rows_one[:,np.newaxis]
+print('normalized Y_one:', Y_oneN)
+
+plt.grid(b=True, which='major')
+
+
+# plt.quiver([Or[:,0], Or[:,1]] , Y_arrN[:,0], Y_arrN[:,1])
+print(Or[:,1])
+print(Or[:,0])
+print(Y_twoN[:,0])
+
+
+
+print('Or_one[:,1]',Or_one[:,1])
+print(Or_one[:,0])
+print(Y_oneN[:,0])
+
+
+print('Angle_values', Angle_Values)
+norm = Normalize()
+norm.autoscale(Angle_Values) #here full array needed?!
+# norm.autoscale(Angle_one)
+
+colormap = cm.RdBu
+
+
+
+
+
+
+
+# Plot only every second one
+skip = (slice(None,None,2))
+# skip = (slice(None,None,2))
+
+# Q = ax.quiver(Or[:,0][skip], Or[:,1][skip] , Y_arrN[:,0][skip], Y_arrN[:,1][skip], color = colormap(norm(Angle_arr)), angles='xy', scale=5, units='xy', alpha=0.8,
+# headwidth=2)
+Q_one = ax.quiver(Or_one[:,0][skip], Or_one[:,1][skip] , Y_one[:,0][skip], Y_one[:,1][skip], color = colormap(norm(Angle_Values)), angles='xy', scale=5, units='xy', alpha=0.8,
+headwidth=2)
+
+Q = ax.quiver(Or[:,0], Or[:,1] , Y_twoN[:,0], Y_twoN[:,1], color = colormap(norm(Angle_Values)), angles='xy', scale=8, units='xy', alpha=0.8,
+headwidth=2)
+
+# f.colorbar(Q,extend='max')
+# ax.quiver(Or[:,0], Or[:,1] , Y_arrN[:,0], Y_arrN[:,1], scale=5, units='xy')
+# ax.quiver(Or[:,0], Or[:,1] , Y_arrN[:,0], Y_arrN[:,1], Angle_arr, angles='xy', scale=5, units='xy')
+# ax.quiver(Or[:,0], Or[:,1] , Y_arrN[:,0], Y_arrN[:,1], color = colormap(norm(Angle_arr)), angles='xy', scale=15, units='xy')
+# ax.quiver(Or[:,0], Or[:,1] , Y_arrN[:,0], Y_arrN[:,1], color = colormap(norm(Angle_arr)), angles='xy', scale=5, units='xy', alpha=0.8,
+# headwidth=2)
+
+
+ax.scatter(Or[:,0], Or[:,1], c='black', s=10)
+ax.scatter(Or_one[:,0], Or_one[:,1], c='black', s=10)
+# ax.set_aspect('equal')
+# ax.set_aspect('auto')
+# ax.axis([0.1,0.4 , -0.1, 0.75])
+# plt.quiver(Or[:,0], Or[:,1] , Y_arrN[:,0], Y_arrN[:,1], scale=1)
+
+# ax.set_xlim((0.1, X_Values[:,0].max()))
+# ax.set_ylim((-0.1, Y_arrN[:,1].max()))
+
+
+ax.set_xlim((0.1, X_two[:,0].max()+0.2))
+ax.set_ylim((-0.1, 0.2 ))
+ax.set(aspect=1, title='Quiver Plot')
+# ax.tick_params(labelleft = False)
+
+
+plt.show()
+# plt.quiver(Or , Y_arrN[:,0], Y_arrN[:,1])
+
+
+
+if other:
+ for i, y in enumerate(Y_Values):
+ maxes = 1.1*np.amax(abs(Y_Values[i]), axis = 0)
+ tmp = Y_Values[i]
+ print('tmp:', tmp)
+
+ tmp_normalized = tmp / np.sqrt(np.sum(tmp**2))
+ print('tmp_normalized:', tmp_normalized)
+ # origin = np.array([[0, 0, 0],[0, 0, 0]]) # origin point
+ origin = np.array([X_Values[i], 1])
+ # origin = np.array([0,0])
+ print('origin:', origin)
+ plt.scatter(origin[0],origin[1])
+ # plt.plot(origin, 'ok')
+ # plt.axis('equal')
+ # plt.axis('auto')
+ plt.xlim([-0.1, 0.4])
+ plt.ylim([0, 4])
+ # plt.xlim([-maxes[0], maxes[0]])
+ # plt.ylim([-maxes[1], maxes[1]])
+ # plt.quiver(*origin, tmp[0], tmp[1], headlength=4)
+ # plt.axes().arrow(*origin, tmp[0], tmp[1],head_width=0.05, head_length = 0.1, color = color[1])
+ # plt.arrow(*origin, tmp[0], tmp[1],head_width=0.05, head_length = 0.1, color = color[1])
+ # plt.arrow(*origin, tmp_normalized[0], tmp_normalized[1], color = color[1])
+ # plt.arrow(*origin, tmp_normalized[0], tmp_normalized[1], head_width=0.05, head_length = 0.1, color = color[1])
+ plt.arrow(*origin, tmp_normalized[0], tmp_normalized[1], head_width=0.05, head_length = 0.1, color = cmap(i))
+ plt.grid(b=True, which='major')
+ # plt.quiver(*origin, test[0], test[1], color=['r','b','g'], scale=21)
+ # plt.quiver(*origin, Y_Values[0][:,0], Y_Values[0][:,1], color=['r','b','g'], scale=21)
+ # plt.quiver(*origin, Y_Values[:,0], V[:,1], color=['r','b','g'], scale=21)
+ # plt.quiver(*origin, Y_Values[:,0], V[:,1], color=['r','b','g'], scale=21)
+
+
+
+
+
+ plt.show()
+ # ax.plot(X_Values, Y_Values)
+ # ax.scatter(X_Values, Y_Values)
+ # plt.plot(x_plotValues, y_plotValues,'.')
+ # plt.scatter(X_Values, Y_Values, alpha=0.3)
+ # plt.scatter(X_Values, Y_Values)
+ # plt.plot(X_Values, Y_Values,'.')
+ # plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+ # plt.axis([0, 6, 0, 20])
+
+ plt.xlabel(xName)
+ # plt.ylabel(yName)
+
+ plt.ylabel('$\kappa$')
+
+ # ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+ # ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+ ax.grid(True)
+
+# # if angle PLOT :
+# ax.yaxis.set_major_locator(plt.MultipleLocator(np.pi / 2))
+# ax.yaxis.set_minor_locator(plt.MultipleLocator(np.pi / 12))
+#
+# ax.yaxis.set_major_formatter(plt.FuncFormatter(format_func))
+#
+# # Plot every other line.. not the jumps...
+# tmp = 1
+# for idx, x in enumerate(x_plotValues):
+# if idx > 0 and tmp == 1:
+# # plt.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] )
+# ax.plot([x_plotValues[idx-1],x_plotValues[idx]] ,[y_plotValues[idx-1],y_plotValues[idx]] ,'b')
+# tmp = 0
+# else:
+# tmp = 1
+
+# plt.plot([x_plotValues[0],x_plotValues[1]] ,[y_plotValues[0],y_plotValues[1]] )
+# plt.plot([x_plotValues[2],x_plotValues[3]] ,[y_plotValues[2],y_plotValues[3]] )
+# plt.plot([x_plotValues[4],x_plotValues[5]] ,[y_plotValues[4],y_plotValues[5]] )
+# plt.plot([x_plotValues[6],x_plotValues[7]] ,[y_plotValues[6],y_plotValues[7]] )
+
+#
+# for x in jump_xValues:
+# plt.axvline(x,ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+# plt.axvline(x_plotValues[1],ymin=0, ymax= 1, color = 'g',alpha=0.5, linestyle = 'dashed')
+
+# plt.axhline(y = 1.90476, color = 'b', linestyle = ':', label='$q_1$')
+# plt.axhline(y = 2.08333, color = 'r', linestyle = 'dashed', label='$q_2$')
+# plt.legend()
+# plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot_Prestrain_Lemma1.4.py b/src/Plot_Prestrain_Lemma1.4.py
index 839cbe0b3f82ad72831fe4fae53bcef2b9da86c8..6adc9961efbda66491ea357b8dffdc574ccc9acc 100644
--- a/src/Plot_Prestrain_Lemma1.4.py
+++ b/src/Plot_Prestrain_Lemma1.4.py
@@ -65,7 +65,10 @@ mu1 = 1.0
# lambda1 = 10.0
rho1 = 1.0
alpha = 2.0
-beta = 5.0
+
+# beta = 5.0
+beta = 2.0 #TEST
+
theta = 1.0/4.0
lambda1 = 0.0
@@ -90,7 +93,7 @@ xmin = 0.0
xmax = 1.0
-numPoints = 20
+numPoints = 200
Theta_Values = np.linspace(xmin, xmax, num=numPoints)
print('Theta_Values:', Theta_Values)
@@ -105,13 +108,21 @@ b1_Vec = np.vectorize(prestrain_b1)
b2_Vec = np.vectorize(prestrain_b2)
Theta_Values = np.array(Theta_Values)
+
+B1_Values_alpha0 = b1_Vec(rho1, beta, 0.0,Theta_Values)
+B1_Values_alphaNeg2 = b1_Vec(rho1, beta, -2.0,Theta_Values)
B1_Values_alphaNeg1 = b1_Vec(rho1, beta, -1.0,Theta_Values)
B1_Values_alphaNeg10 = b1_Vec(rho1, beta, -10.0,Theta_Values)
+B1_Values_alpha1= b1_Vec(rho1, beta, 1.0 ,Theta_Values)
B1_Values_alpha2= b1_Vec(rho1, beta, 2.0 ,Theta_Values)
B1_Values_alpha10= b1_Vec(rho1, beta, 10.0 ,Theta_Values)
# B2_Values = b2_Vec(rho1, beta, alpha,Theta_Values)
+
+B2_Values_alpha0 = b2_Vec(rho1, beta, 0.0,Theta_Values)
+B2_Values_alphaNeg2 = b2_Vec(rho1, beta, -2.0,Theta_Values)
B2_Values_alphaNeg1 = b2_Vec(rho1, beta, -1.0,Theta_Values)
B2_Values_alphaNeg10 = b2_Vec(rho1, beta, -10.0,Theta_Values)
+B2_Values_alpha1= b2_Vec(rho1, beta, 1.0 ,Theta_Values)
B2_Values_alpha2= b2_Vec(rho1, beta, 2.0 ,Theta_Values)
B2_Values_alpha10= b2_Vec(rho1, beta, 10.0 ,Theta_Values)
@@ -123,10 +134,16 @@ B2_Values_alpha10= b2_Vec(rho1, beta, 10.0 ,Theta_Values)
# --- Convert to numpy array
# B1_Values = np.array(B1_Values)
# B2_Values = np.array(B2_Values)
+B1_Values_alpha0 = np.array(B1_Values_alpha0)
+B1_Values_alphaNeg2 = np.array(B1_Values_alphaNeg2)
+B1_Values_alpha1 = np.array(B1_Values_alpha1)
B1_Values_alphaNeg1 = np.array(B1_Values_alphaNeg1)
B1_Values_alphaNeg10 = np.array(B1_Values_alphaNeg10)
B1_Values_alpha2 = np.array(B1_Values_alpha2)
B1_Values_alpha10 = np.array(B1_Values_alpha10)
+B2_Values_alpha0 = np.array(B2_Values_alpha0)
+B2_Values_alphaNeg2 = np.array(B2_Values_alphaNeg2)
+B2_Values_alpha1 = np.array(B2_Values_alpha1)
B2_Values_alphaNeg1 = np.array(B2_Values_alphaNeg1)
B2_Values_alphaNeg10 = np.array(B2_Values_alphaNeg10)
B2_Values_alpha2 = np.array(B2_Values_alpha2)
@@ -217,21 +234,28 @@ ax[1].grid(True,which='major',axis='both',alpha=0.3)
# ax.plot(Theta_Values,B1_Values , 'royalblue')
# ax.plot(Theta_Values,B2_Values , 'royalblue')
-l1 = ax[0].plot(Theta_Values,B1_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
-l2 = ax[0].plot(Theta_Values,B1_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
-l3 = ax[0].plot(Theta_Values,B1_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
-l4 = ax[0].plot(Theta_Values,B1_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+l1 = ax[0].plot(Theta_Values,B1_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
+l2 = ax[0].plot(Theta_Values,B1_Values_alphaNeg2 , label=r"$\theta_\rho = -2.0$")
+l3 = ax[0].plot(Theta_Values,B1_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
+l4 = ax[0].plot(Theta_Values,B1_Values_alpha0 , label=r"$\theta_\rho = 0.0$")
+l5 = ax[0].plot(Theta_Values,B1_Values_alpha1 , label=r"$\theta_\rho = 1.0$")
+l6 = ax[0].plot(Theta_Values,B1_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
+l7 = ax[0].plot(Theta_Values,B1_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+
ax[0].set_xlabel(r"volume fraction $\theta$")
ax[0].set_ylabel(r"prestrain $b_1$")
# Labels to use in the legend for each line
-line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -10.0$", r"$\theta_\rho = 2.0$", r"$\theta_\rho = 10.0$"]
+line_labels = [r"$\theta_\rho = -10.0$",r"$\theta_\rho = -2.0$",r"$\theta_\rho = -1.0$",r"$\theta_\rho = 0.0$" ,r"$\theta_\rho = 1.0$", r"$\theta_\rho = 2.0$", r"$\theta_\rho = 10.0$"]
-
-ax[1].plot(Theta_Values,B2_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
ax[1].plot(Theta_Values,B2_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
+ax[1].plot(Theta_Values,B2_Values_alphaNeg2 , label=r"$\theta_\rho = -2.0$")
+ax[1].plot(Theta_Values,B2_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
+ax[1].plot(Theta_Values,B2_Values_alpha0 , label=r"$\theta_\rho = 0.0$")
+ax[1].plot(Theta_Values,B2_Values_alpha1 , label=r"$\theta_\rho = 1.0$")
ax[1].plot(Theta_Values,B2_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
ax[1].plot(Theta_Values,B2_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+
ax[1].set_xlabel(r"volume fraction $\theta$")
ax[1].set_ylabel(r"prestrain $b_2$")
@@ -327,7 +351,7 @@ plt.tight_layout()
fig.legend([l1, l2, l3, l4], # The line objects
labels=line_labels, # The labels for each line
loc="center right", # Position of legend
- borderaxespad=0.15 # Small spacing around legend box
+ borderaxespad=0.15, # Small spacing around legend box
# title="Legend Title" # Title for the legend
)
diff --git a/src/Plot_Prestrain_Lemma1.4_Betas.py b/src/Plot_Prestrain_Lemma1.4_Betas.py
new file mode 100644
index 0000000000000000000000000000000000000000..10564f7da5e5f6d0ad0c669ba746bd50cd8bc4cd
--- /dev/null
+++ b/src/Plot_Prestrain_Lemma1.4_Betas.py
@@ -0,0 +1,389 @@
+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
+from HelperFunctions import *
+from ClassifyMin import *
+
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+
+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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+
+mu1 = 1.0
+# mu1 = 10.0
+# lambda1 = 10.0
+rho1 = 1.0
+alpha = 2.0
+
+# beta = 5.0
+beta = 2.0 #TEST
+
+theta = 1.0/4.0
+
+lambda1 = 0.0
+# gamma = 1.0/4.0
+
+gamma = 'infinity' #Elliptic Setting
+# gamma = '0' #Hyperbolic Setting
+# gamma = 0.5
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+# --- define Interval of x-va1ues:
+xmin = 0.0
+xmax = 1.0
+
+
+numPoints = 1000
+Theta_Values = np.linspace(xmin, xmax, num=numPoints)
+print('Theta_Values:', Theta_Values)
+
+
+B1_Values = []
+B2_Values = []
+
+b1 = prestrain_b1(rho1, beta, alpha,theta)
+b2 = prestrain_b2(rho1, beta, alpha,theta)
+
+b1_Vec = np.vectorize(prestrain_b1)
+b2_Vec = np.vectorize(prestrain_b2)
+
+Theta_Values = np.array(Theta_Values)
+B1_Values_alphaNeg1 = b1_Vec(rho1, beta, -1.0,Theta_Values)
+B1_Values_alphaNeg10 = b1_Vec(rho1, beta, -10.0,Theta_Values)
+B1_Values_alpha2= b1_Vec(rho1, beta, 2.0 ,Theta_Values)
+B1_Values_alpha10= b1_Vec(rho1, beta, 10.0 ,Theta_Values)
+# B2_Values = b2_Vec(rho1, beta, alpha,Theta_Values)
+B2_Values_alphaNeg1 = b2_Vec(rho1, beta, -1.0,Theta_Values)
+B2_Values_alphaNeg10 = b2_Vec(rho1, beta, -10.0,Theta_Values)
+B2_Values_alpha2= b2_Vec(rho1, beta, 2.0 ,Theta_Values)
+B2_Values_alpha10= b2_Vec(rho1, beta, 10.0 ,Theta_Values)
+
+
+B1_Values_beta05 = b1_Vec(rho1, 0.5, alpha ,Theta_Values)
+B1_Values_beta1 = b1_Vec(rho1, 1.0, alpha ,Theta_Values)
+B1_Values_beta2 = b1_Vec(rho1, 2.0, alpha ,Theta_Values)
+B1_Values_beta10 = b1_Vec(rho1, 10, alpha ,Theta_Values)
+# ---
+
+B2_Values_beta01 = b2_Vec(rho1, 0.1, alpha ,Theta_Values)
+B2_Values_beta05 = b2_Vec(rho1, 0.5, alpha ,Theta_Values)
+B2_Values_beta1 = b2_Vec(rho1, 1.0, alpha ,Theta_Values)
+B2_Values_beta2 = b2_Vec(rho1, 2.0, alpha ,Theta_Values)
+B2_Values_beta10 = b2_Vec(rho1, 10, alpha ,Theta_Values)
+
+
+# print('B1_Values:', B1_Values)
+# print('B2_Values:', B2_Values)
+
+
+
+# --- Convert to numpy array
+# B1_Values = np.array(B1_Values)
+# B2_Values = np.array(B2_Values)
+B1_Values_alphaNeg1 = np.array(B1_Values_alphaNeg1)
+B1_Values_alphaNeg10 = np.array(B1_Values_alphaNeg10)
+B1_Values_alpha2 = np.array(B1_Values_alpha2)
+B1_Values_alpha10 = np.array(B1_Values_alpha10)
+B2_Values_alphaNeg1 = np.array(B2_Values_alphaNeg1)
+B2_Values_alphaNeg10 = np.array(B2_Values_alphaNeg10)
+B2_Values_alpha2 = np.array(B2_Values_alpha2)
+B2_Values_alpha10 = np.array(B2_Values_alpha10)
+
+
+
+B1_Values_beta05= np.array(B1_Values_beta05)
+B1_Values_beta1 = np.array(B1_Values_beta1 )
+B1_Values_beta2 = np.array(B1_Values_beta2 )
+B1_Values_beta10 = np.array(B1_Values_beta10 )
+B2_Values_beta01 = np.array(B2_Values_beta01)
+B2_Values_beta05 = np.array(B2_Values_beta05)
+B2_Values_beta1 = np.array(B2_Values_beta1)
+B2_Values_beta2 = np.array(B2_Values_beta2 )
+B2_Values_beta10 = np.array(B2_Values_beta10)
+# ---------------- Create Plot -------------------
+
+#--- change plot style: SEABORN
+# plt.style.use("seaborn-paper")
+
+
+#--- Adjust gobal matplotlib variables
+# mpl.rcParams['pdf.fonttype'] = 42
+# mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+# mpl.rcParams['axes.grid'] = True
+
+# plt.rc('font', family='serif', serif='Times')
+# plt.rc('font', family='serif')
+# # plt.rc('text', usetex=True) #also works...
+# plt.rc('xtick', labelsize=8)
+# plt.rc('ytick', labelsize=8)
+# plt.rc('axes', labelsize=8)
+
+
+
+
+
+#---- Scale Figure apropriately to fit tex-File Width
+# width = 452.9679
+
+# width as measured in inkscape
+width = 6.28 *0.5
+# width = 6.28
+
+height = width / 1.618
+# height = width / 2.5
+#setup canvas first
+fig = plt.figure() #main
+# fig, ax = plt.subplots()
+# fig, (ax, ax2) = plt.subplots(ncols=2)
+
+# fig,ax = plt.subplots(nrows=1,ncols=2,figsize=(width,height)) # more than one plot
+# fig,ax = plt.subplots(nrows=1,ncols=1,figsize=(width,height)) # more than one plot
+# fig,ax = plt.subplots(nrows=1,ncols=1,figsize=(width,height)) # more than one plot
+# --- set overall Title
+# fig.suptitle('Example of a Single Legend Shared Across Multiple Subplots')
+
+# fig.subplots_adjust(left=.15, bottom=.16, right=.99, top=.97) #TEST
+
+
+# TEST
+# mpl.rcParams['figure.figsize'] = (width+0.1,height+0.1)
+# fig = plt.figure(figsize=(width+0.1,height+0.1))
+
+
+# mpl.rcParams['figure.figsize'] = (width,height)
+# fig = plt.figure(figsize=(10,6)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=(width,height)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=set_size(width))
+# fig = plt.subplots(1, 1, figsize=set_size(width))
+
+# --- To create a figure half the width of your document:#
+# fig = plt.figure(figsize=set_size(width, fraction=0.5))
+
+
+
+#--- You must select the correct size of the plot in advance
+# fig.set_size_inches(3.54,3.54)
+
+
+# ---- TODO ?:
+# ax[0] = plt.axes((0.15,0.18,0.8,0.8))
+
+
+# ax.tick_params(axis='x',which='major', direction='out',pad=3)
+# ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+# ax.xaxis.set_major_locator(MultipleLocator(0.1))
+# ax.xaxis.set_minor_locator(MultipleLocator(0.05))
+# a=ax.yaxis.get_major_locator()
+# b=ax.yaxis.get_major_formatter()
+# c = ax.get_xticks()
+# d = ax.get_xticklabels()
+# print('xticks:',c)
+# print('xticklabels:',d)
+
+
+ax = plt.axes((0.15,0.18,0.8,0.8))
+# ax = plt.axes((0.1,0.1,0.5,0.5))
+ax.grid(True,which='major',axis='both',alpha=0.3)
+# ax[0].grid(True,which='major',axis='both',alpha=0.3)
+# ax[1].grid(True,which='major',axis='both',alpha=0.3)
+# ax.plot(Theta_Values,B1_Values , 'royalblue')
+# ax.plot(Theta_Values,B2_Values , 'royalblue')
+
+# l1 = ax[0].plot(Theta_Values,B1_Values_beta05 , label=r"$\theta_\mu = 0.5$")
+# l2 = ax[0].plot(Theta_Values,B1_Values_beta1 , label=r"$\theta_\mu = 1.0$")
+# l3 = ax[0].plot(Theta_Values,B1_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+# l4 = ax[0].plot(Theta_Values,B1_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+# ax[0].set_xlabel(r"volume fraction $\theta$")
+# ax[0].set_ylabel(r"prestrain $b_1$")
+
+# Labels to use in the legend for each line
+# line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -10.0$", r"$\theta_\rho = 2.0$", r"$\theta_\rho = 10.0$"]
+# line_labels = [r"$\theta_\mu = 0.5$", r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 10.0$"]
+
+# ax[1].plot(Theta_Values,B2_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
+# ax[1].plot(Theta_Values,B2_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
+# ax[1].plot(Theta_Values,B2_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
+# ax[1].plot(Theta_Values,B2_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+
+
+# ---------------
+# ax[1].plot(Theta_Values,B2_Values_beta05 , label=r"$\theta_\mu = 0.5$")
+# ax[1].plot(Theta_Values,B2_Values_beta1 , label=r"$\theta_\mu = 1.0$")
+# ax[1].plot(Theta_Values,B2_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+# ax[1].plot(Theta_Values,B2_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+# ax[1].set_xlabel(r"volume fraction $\theta$")
+# ax[1].set_ylabel(r"prestrain $b_2$")
+
+
+l1 = ax.plot(Theta_Values,B2_Values_beta01 , label=r"$\theta_\mu = 0.1$")
+l2 = ax.plot(Theta_Values,B2_Values_beta05 , label=r"$\theta_\mu = 0.5$")
+l3 = ax.plot(Theta_Values,B2_Values_beta1 , label=r"$\theta_\mu = 1.0$")
+l4 = ax.plot(Theta_Values,B2_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+l5 = ax.plot(Theta_Values,B2_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+ax.set_xlabel(r"volume fraction $\theta$")
+ax.set_ylabel(r"prestrain $b_2$")
+line_labels = [r"$\theta_\mu = 0.1$",r"$\theta_\mu = 0.5$", r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 10.0$"]
+
+
+# plt.tight_layout()
+
+
+# plt.subplots_adjust(wspace=0.4, hspace=0)
+
+
+# ax.plot(X_Values[X_Values>0.136], Y_Values[X_Values>0.136])
+# ax.plot(X_Values[X_Values<0.135], Y_Values[X_Values<0.135])
+# ax.scatter(X_Values, Y_Values)
+# ax.plot(X_Values, Y_Values)
+
+# plt.plot(x_plotValues, y_plotValues,'.')
+# plt.scatter(X_Values, Y_Values, alpha=0.3)
+# plt.scatter(X_Values, Y_Values)
+# plt.plot(X_Values, Y_Values,'.')
+# plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+# plt.axis([0, 6, 0, 20])
+
+# ax.set_xlabel(r"volume fraction $\theta$", size=11)
+# ax.set_ylabel(r"angle $\angle$", size=11)
+
+
+# plt.ylabel('$\kappa$')
+
+# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+
+# -- SETUP LEGEND
+# ax.legend(prop={'size': 11})
+# ax[0].legend()
+# ax[1].legend(
+# loc='upper left',
+# bbox_to_anchor=(1,1))
+
+# Create the legend
+# handles, labels = ax.get_legend_handles_labels()
+
+# fig.legend([l1, l2, l3, l4], # The line objects
+# labels=line_labels, # The labels for each line
+# loc="upper right", # Position of legend
+# borderaxespad=0.15, # Small spacing around legend box
+# # title="Legend Title" # Title for the legend
+# bbox_to_anchor=(0.95,0.98)
+# )
+
+# fig.legend([l1, l2, l3, l4], # The line objects
+# labels=line_labels, # The labels for each line
+# loc="upper left", # Position of legend
+# borderaxespad=0.1,
+# # title="Legend Title" # Title for the legend
+# bbox_to_anchor=(0.8,0.7)
+# )
+
+lg = ax.legend(bbox_to_anchor=(1.0, 0.75), loc='upper left')
+# ax.tight_layout()
+
+# Adjust the scaling factor to fit your legend text completely outside the plot
+# (smaller value results in more space being made for the legend)
+plt.subplots_adjust(right=0.8)
+plt.tight_layout()
+
+# ------------------ SAVE FIGURE
+# tikzplotlib.save("TesTout.tex")
+# plt.close()
+# mpl.rcParams.update(mpl.rcParamsDefault)
+
+# plt.savefig("graph.pdf",
+# #This is simple recomendation for publication plots
+# dpi=1000,
+# # Plot will be occupy a maximum of available space
+# bbox_inches='tight',
+# )
+# plt.savefig("graph.pdf")
+
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Prestrain-Theta_AlphaFix.pdf',dpi=300,bbox_extra_artists=(lg,),
+ bbox_inches='tight')
+
+
+
+
+# tikz_save('someplot.tex', figureheight='5cm', figurewidth='9cm')
+
+# tikz_save('fig.tikz',
+# figureheight = '\\figureheight',
+# figurewidth = '\\figurewidth')
+
+# ----------------------------------------
+
+
+plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot_Prestrain_Lemma1.4_SubPlots.py b/src/Plot_Prestrain_Lemma1.4_SubPlots.py
new file mode 100644
index 0000000000000000000000000000000000000000..efd86c3dc9461385902827558dd7eb2c08dd7827
--- /dev/null
+++ b/src/Plot_Prestrain_Lemma1.4_SubPlots.py
@@ -0,0 +1,417 @@
+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
+from HelperFunctions import *
+from ClassifyMin import *
+
+import matplotlib.ticker as tickers
+import matplotlib as mpl
+from matplotlib.ticker import MultipleLocator,FormatStrFormatter,MaxNLocator
+import pandas as pd
+
+
+
+def find_nearest(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return array[idx]
+
+
+def find_nearestIdx(array, value):
+ array = np.asarray(array)
+ idx = (np.abs(array - value)).argmin()
+ return idx
+
+
+
+# TODO
+# - Fallunterscheidung (Speedup) falls gesuchter value mu_gamma = q3
+# - Also Add option to plot Minimization Output
+
+
+# ----- Setup Paths -----
+# InputFile = "/inputs/cellsolver.parset"
+# OutputFile = "/outputs/output.txt"
+
+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)
+
+#---------------------------------------------------------------
+
+print('---- Input parameters: -----')
+
+mu1 = 10.0
+# mu1 = 10.0
+# lambda1 = 10.0
+rho1 = 1.0
+alpha = 2.0
+beta = 5.0
+theta = 1.0/4.0
+
+lambda1 = 0.0
+# gamma = 1.0/4.0
+
+gamma = 'infinity' #Elliptic Setting
+# gamma = '0' #Hyperbolic Setting
+# gamma = 0.5
+
+
+print('mu1: ', mu1)
+print('rho1: ', rho1)
+print('alpha: ', alpha)
+print('beta: ', beta)
+print('theta: ', theta)
+print('gamma:', gamma)
+print('----------------------------')
+
+
+# --- define Interval of x-va1ues:
+xmin = 0.0
+xmax = 1.0
+
+
+numPoints = 20
+Theta_Values = np.linspace(xmin, xmax, num=numPoints)
+print('Theta_Values:', Theta_Values)
+
+
+B1_Values = []
+B2_Values = []
+
+b1 = prestrain_b1(rho1, beta, alpha,theta)
+b2 = prestrain_b2(rho1, beta, alpha,theta)
+
+b1_Vec = np.vectorize(prestrain_b1)
+b2_Vec = np.vectorize(prestrain_b2)
+
+Theta_Values = np.array(Theta_Values)
+B1_Values_alphaNeg1 = b1_Vec(rho1, beta, -1.0,Theta_Values)
+B1_Values_alphaNeg10 = b1_Vec(rho1, beta, -10.0,Theta_Values)
+B1_Values_alpha2= b1_Vec(rho1, beta, 2.0 ,Theta_Values)
+B1_Values_alpha10= b1_Vec(rho1, beta, 10.0 ,Theta_Values)
+# B2_Values = b2_Vec(rho1, beta, alpha,Theta_Values)
+B2_Values_alphaNeg1 = b2_Vec(rho1, beta, -1.0,Theta_Values)
+B2_Values_alphaNeg10 = b2_Vec(rho1, beta, -10.0,Theta_Values)
+B2_Values_alpha2= b2_Vec(rho1, beta, 2.0 ,Theta_Values)
+B2_Values_alpha10= b2_Vec(rho1, beta, 10.0 ,Theta_Values)
+
+
+B1_Values_beta05 = b1_Vec(rho1, 0.5, alpha ,Theta_Values)
+B1_Values_beta1 = b1_Vec(rho1, 1.0, alpha ,Theta_Values)
+B1_Values_beta2 = b1_Vec(rho1, 2.0, alpha ,Theta_Values)
+B1_Values_beta10 = b1_Vec(rho1, 10, alpha ,Theta_Values)
+# ---
+B2_Values_beta05 = b2_Vec(rho1, 0.5, alpha ,Theta_Values)
+B2_Values_beta1 = b2_Vec(rho1, 1.0, alpha ,Theta_Values)
+B2_Values_beta2 = b2_Vec(rho1, 2.0, alpha ,Theta_Values)
+B2_Values_beta10 = b2_Vec(rho1, 10, alpha ,Theta_Values)
+
+
+# print('B1_Values:', B1_Values)
+# print('B2_Values:', B2_Values)
+
+
+
+# --- Convert to numpy array
+# B1_Values = np.array(B1_Values)
+# B2_Values = np.array(B2_Values)
+B1_Values_alphaNeg1 = np.array(B1_Values_alphaNeg1)
+B1_Values_alphaNeg10 = np.array(B1_Values_alphaNeg10)
+B1_Values_alpha2 = np.array(B1_Values_alpha2)
+B1_Values_alpha10 = np.array(B1_Values_alpha10)
+B2_Values_alphaNeg1 = np.array(B2_Values_alphaNeg1)
+B2_Values_alphaNeg10 = np.array(B2_Values_alphaNeg10)
+B2_Values_alpha2 = np.array(B2_Values_alpha2)
+B2_Values_alpha10 = np.array(B2_Values_alpha10)
+
+
+
+B1_Values_beta05= np.array(B1_Values_beta05)
+B1_Values_beta1 = np.array(B1_Values_beta1 )
+B1_Values_beta2 = np.array(B1_Values_beta2 )
+B1_Values_beta10 = np.array(B1_Values_beta10 )
+B2_Values_beta05 = np.array(B2_Values_beta05)
+B2_Values_beta1 = np.array(B2_Values_beta1)
+B2_Values_beta2 = np.array(B2_Values_beta2 )
+B2_Values_beta10 = np.array(B2_Values_beta10)
+# ---------------- Create Plot -------------------
+
+#--- change plot style: SEABORN
+# plt.style.use("seaborn-paper")
+
+
+#--- Adjust gobal matplotlib variables
+# mpl.rcParams['pdf.fonttype'] = 42
+# mpl.rcParams['ps.fonttype'] = 42
+mpl.rcParams['text.usetex'] = True
+mpl.rcParams["font.family"] = "serif"
+mpl.rcParams["font.size"] = "9"
+# mpl.rcParams['axes.grid'] = True
+
+# plt.rc('font', family='serif', serif='Times')
+# plt.rc('font', family='serif')
+# # plt.rc('text', usetex=True) #also works...
+# plt.rc('xtick', labelsize=8)
+# plt.rc('ytick', labelsize=8)
+# plt.rc('axes', labelsize=8)
+
+
+
+
+
+#---- Scale Figure apropriately to fit tex-File Width
+# width = 452.9679
+
+# width as measured in inkscape
+# width = 6.28 *0.5
+width = 6.28
+
+height = width / 1.618
+# height = width / 2.5
+#setup canvas first
+fig = plt.figure() #main
+# fig, ax = plt.subplots()
+# fig, (ax, ax2) = plt.subplots(ncols=2)
+# fig,ax = plt.subplots(nrows=2,ncols=2,figsize=(width,height)) # more than one plot
+fig,ax = plt.subplots(nrows=2,ncols=2, figsize=(width,height)) # more than one plot
+
+# --- set overall Title
+# fig.suptitle('Example of a Single Legend Shared Across Multiple Subplots')
+# fig.supxlabel(r'common')
+# fig.supylabel(r'common')
+# fig.subplots_adjust(left=.15, bottom=.16, right=.99, top=.97) #TEST
+
+
+# TEST
+# mpl.rcParams['figure.figsize'] = (width+0.1,height+0.1)
+# fig = plt.figure(figsize=(width+0.1,height+0.1))
+
+
+# mpl.rcParams['figure.figsize'] = (width,height)
+# fig = plt.figure(figsize=(10,6)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=(width,height)) # default is [6.4,4.8] 6.4 is the width, 4.8 is the height
+# fig = plt.figure(figsize=set_size(width))
+# fig = plt.subplots(1, 1, figsize=set_size(width))
+
+# --- To create a figure half the width of your document:#
+# fig = plt.figure(figsize=set_size(width, fraction=0.5))
+
+
+
+#--- You must select the correct size of the plot in advance
+# fig.set_size_inches(3.54,3.54)
+
+
+# ---- TODO ?:
+# ax[0] = plt.axes((0.15,0.18,0.8,0.8))
+
+
+ax[0][0].tick_params(axis='x',which='major', direction='out',pad=3)
+ax[0][0].tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
+ax[0][0].xaxis.set_major_locator(MultipleLocator(0.25))
+ax[0][0].xaxis.set_minor_locator(MultipleLocator(0.125))
+ax[0][0].yaxis.set_major_locator(MultipleLocator(25))
+# ax[0][0].yaxis.set_minor_locator(MultipleLocator(12.5))
+# a=ax.yaxis.get_major_locator()
+# b=ax.yaxis.get_major_formatter()
+# c = ax.get_xticks()
+# d = ax.get_xticklabels()
+# print('xticks:',c)
+# print('xticklabels:',d)
+
+ax[0][0].grid(True,which='major',axis='both',alpha=0.3)
+ax[0][1].grid(True,which='major',axis='both',alpha=0.3)
+ax[1][0].grid(True,which='major',axis='both',alpha=0.3)
+ax[1][1].grid(True,which='major',axis='both',alpha=0.3)
+# ax.plot(Theta_Values,B1_Values , 'royalblue')
+# ax.plot(Theta_Values,B2_Values , 'royalblue')
+
+l1 = ax[0][0].plot(Theta_Values,B1_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
+l2 = ax[0][0].plot(Theta_Values,B1_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
+l3 = ax[0][0].plot(Theta_Values,B1_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
+l4 = ax[0][0].plot(Theta_Values,B1_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+ax[0][0].set_xlabel(r"volume fraction $\theta$")
+ax[0][0].set_ylabel(r"prestrain $b_1$")
+# l1 = ax[0].plot(Theta_Values,B1_Values_beta05 , label=r"$\theta_\mu = -1.0$")
+# l2 = ax[0].plot(Theta_Values,B1_Values_beta1 , label=r"$\theta_\mu = -10.0$")
+# l3 = ax[0].plot(Theta_Values,B1_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+# l4 = ax[0].plot(Theta_Values,B1_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+l5 = ax[1][0].plot(Theta_Values,B1_Values_beta05 , label=r"$\theta_\mu = -1.0$")
+l6 = ax[1][0].plot(Theta_Values,B1_Values_beta1 , label=r"$\theta_\mu = -10.0$")
+l7 = ax[1][0].plot(Theta_Values,B1_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+l8 = ax[1][0].plot(Theta_Values,B1_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+ax[1][0].set_xlabel(r"volume fraction $\theta$")
+ax[1][0].set_ylabel(r"prestrain $b_1$")
+
+# Labels to use in the legend for each line
+# line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -10.0$", r"$\theta_\rho = 2.0$", r"$\theta_\rho = 10.0$"]
+line_labels = [r"$\theta_\rho = -1.0$", r"$\theta_\rho = -10.0$", r"$\theta_\rho = 2.0$", r"$\theta_\rho = 10.0$",
+r"$\theta_\mu = -1.0$", r"$\theta_\mu = -10.0$", r"$\theta_\mu = 2.0$",r"$\theta_\mu = 10.0$" ]
+
+ax[0][1].plot(Theta_Values,B2_Values_alphaNeg1 , label=r"$\theta_\rho = -1.0$")
+ax[0][1].plot(Theta_Values,B2_Values_alphaNeg10 , label=r"$\theta_\rho = -10.0$")
+ax[0][1].plot(Theta_Values,B2_Values_alpha2 , label=r"$\theta_\rho = 2.0$")
+ax[0][1].plot(Theta_Values,B2_Values_alpha10 , label=r"$\theta_\rho = 10.0$")
+ax[0][1].set_xlabel(r"volume fraction $\theta$")
+ax[0][1].set_ylabel(r"prestrain $b_2$")
+# ---------------
+ax[1][1].plot(Theta_Values,B2_Values_beta05 , label=r"$\theta_\mu = -1.0$")
+ax[1][1].plot(Theta_Values,B2_Values_beta1 , label=r"$\theta_\mu = -10.0$")
+ax[1][1].plot(Theta_Values,B2_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+ax[1][1].plot(Theta_Values,B2_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+ax[1][1].set_xlabel(r"volume fraction $\theta$")
+ax[1][1].set_ylabel(r"prestrain $b_2$")
+
+plt.subplots_adjust(wspace=0.2, hspace=0)
+plt.tight_layout()
+# ax.plot(Theta_Values,B2_Values_alphaNeg1 )
+# ax.plot(Theta_Values,B2_Values_alphaNeg10 )
+# ax.plot(Theta_Values,B2_Values_alpha2 )
+# ax.plot(Theta_Values,B2_Values_alpha10 )
+
+
+# plt.figure()
+
+# f,ax=plt.subplots(1)
+
+# plt.title(r''+ yName + '-Plot')
+# plt.plot(X_Values, Y_Values,linewidth=2, '.k')
+# plt.plot(X_Values, Y_Values,'.k',markersize=1)
+# plt.plot(X_Values, Y_Values,'.',markersize=0.8)
+
+# plt.plot(X_Values, Y_Values)
+
+# ax.plot([[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+
+
+
+# Gamma = '0'
+# ax.plot([x_plotValues[0],x_plotValues[1]], [y_plotValues[0],y_plotValues[1]] , 'b')
+#
+# ax.plot([x_plotValues[1],x_plotValues[3]], [y_plotValues[2],y_plotValues[3]] , 'b')
+#
+# ax.plot(x_rest, y_rest, 'b')
+
+
+# Gamma between
+
+# x jump values (gamma 0): [0.13606060606060608, 0.21090909090909093]
+
+# ax.plot([[0,jump_xValues[0]], [0, 0]] , 'b')
+# ax.plot([jump_xValues[0],xmin], [y_plotValues[2],y_plotValues[2]] , 'b')
+
+# ax.plot([[0,0.13606060606060608], [0, 0]] , 'b')
+# ax.plot([[0.13606060606060608,xmin], [(math.pi/2),(math.pi/2)]], 'b')
+
+# jump_xValues[0]
+
+
+
+# --- leave out jumps:
+# ax.scatter(X_Values, Y_Values)
+
+
+
+
+
+
+
+# ax.plot(X_Values[X_Values>0.136], Y_Values[X_Values>0.136])
+# ax.plot(X_Values[X_Values<0.135], Y_Values[X_Values<0.135])
+# ax.scatter(X_Values, Y_Values)
+# ax.plot(X_Values, Y_Values)
+
+# plt.plot(x_plotValues, y_plotValues,'.')
+# plt.scatter(X_Values, Y_Values, alpha=0.3)
+# plt.scatter(X_Values, Y_Values)
+# plt.plot(X_Values, Y_Values,'.')
+# plt.plot([X_Values[0],X_Values[-1]], [Y_Values[0],Y_Values[-1]])
+# plt.axis([0, 6, 0, 20])
+
+# ax.set_xlabel(r"volume fraction $\theta$", size=11)
+# ax.set_ylabel(r"angle $\angle$", size=11)
+
+
+# plt.ylabel('$\kappa$')
+
+# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%g $\pi$'))
+# ax.yaxis.set_major_locator(ticker.MultipleLocator(base=0.1))
+
+
+
+
+
+# -- SETUP LEGEND
+# ax.legend(prop={'size': 11})
+# ax[0].legend()
+# ax[1].legend(
+# loc='upper left',
+# bbox_to_anchor=(1,1))
+
+# Create the legend
+# handles, labels = ax.get_legend_handles_labels()
+
+fig.legend([l1, l2, l3, l4, l5, l6 ,l7 ,l8], # The line objects
+ labels=line_labels, # The labels for each line
+ loc="center right", # Position of legend
+ borderaxespad=0.15 # Small spacing around legend box
+ # title="Legend Title" # Title for the legend
+ )
+
+# Adjust the scaling factor to fit your legend text completely outside the plot
+# (smaller value results in more space being made for the legend)
+plt.subplots_adjust(right=0.8)
+
+# ------------------ SAVE FIGURE
+# tikzplotlib.save("TesTout.tex")
+# plt.close()
+# mpl.rcParams.update(mpl.rcParamsDefault)
+
+# plt.savefig("graph.pdf",
+# #This is simple recomendation for publication plots
+# dpi=1000,
+# # Plot will be occupy a maximum of available space
+# bbox_inches='tight',
+# )
+# plt.savefig("graph.pdf")
+
+
+
+
+fig.set_size_inches(width, height)
+fig.savefig('Plot-Prestrain-Theta.pdf')
+
+
+
+
+# tikz_save('someplot.tex', figureheight='5cm', figurewidth='9cm')
+
+# tikz_save('fig.tikz',
+# figureheight = '\\figureheight',
+# figurewidth = '\\figurewidth')
+
+# ----------------------------------------
+
+
+plt.show()
+# #---------------------------------------------------------------
diff --git a/src/Plot_elasticQuantities.py b/src/Plot_elasticQuantities.py
index c9aa66c31a74b8c2c662399a2d9ae04569a9ec9d..9e9f8462a41cd16c141227d45d49b187c61fc9c6 100644
--- a/src/Plot_elasticQuantities.py
+++ b/src/Plot_elasticQuantities.py
@@ -123,11 +123,15 @@ Theta_Values = np.array(Theta_Values)
# B2_Values_alpha2= b2_Vec(rho1, beta, 2.0 ,Theta_Values)
# B2_Values_alpha10= b2_Vec(rho1, beta, 10.0 ,Theta_Values)
+Q1_Values_beta05 = (1.0/6.0)*harmonicMeanVec(mu1, 0.5, Theta_Values)
+
Q1_Values_beta1 = (1.0/6.0)*harmonicMeanVec(mu1, 1.0, Theta_Values)
Q1_Values_beta2 = (1.0/6.0)*harmonicMeanVec(mu1, 2.0, Theta_Values)
Q1_Values_beta5 = (1.0/6.0)*harmonicMeanVec(mu1, 5.0, Theta_Values)
Q1_Values_beta10 = (1.0/6.0)*harmonicMeanVec(mu1, 10.0, Theta_Values)
+Q2_Values_beta05 = (1.0/6.0)*arithmeticMeanVec(mu1, 0.5, Theta_Values)
+
Q2_Values_beta1 = (1.0/6.0)*arithmeticMeanVec(mu1, 1.0, Theta_Values)
Q2_Values_beta2 = (1.0/6.0)*arithmeticMeanVec(mu1, 2.0, Theta_Values)
Q2_Values_beta5 = (1.0/6.0)*arithmeticMeanVec(mu1, 5.0, Theta_Values)
@@ -138,11 +142,15 @@ print("Q1_Values_beta1 ", Q1_Values_beta1 )
# --- Convert to numpy array
# B1_Values = np.array(B1_Values)
# B2_Values = np.array(B2_Values)
+Q1_Values_beta05 = np.array(Q1_Values_beta05 )
+
Q1_Values_beta1 = np.array(Q1_Values_beta1 )
Q1_Values_beta2 = np.array(Q1_Values_beta2 )
Q1_Values_beta5 = np.array(Q1_Values_beta5 )
Q1_Values_beta10 = np.array(Q1_Values_beta10 )
+Q2_Values_beta05 = np.array(Q2_Values_beta05 )
+
Q2_Values_beta1 = np.array(Q2_Values_beta1 )
Q2_Values_beta2 = np.array(Q2_Values_beta2 )
Q2_Values_beta5 = np.array(Q2_Values_beta5 )
@@ -235,18 +243,20 @@ ax[2].grid(True,which='major',axis='both',alpha=0.3)
# ax.plot(Theta_Values,B1_Values , 'royalblue')
# ax.plot(Theta_Values,B2_Values , 'royalblue')
-l1 = ax[0].plot(Theta_Values,Q1_Values_beta1 , label=r"$\theta_\mu = 1.0$")
-l2 = ax[0].plot(Theta_Values,Q1_Values_beta2 , label=r"$\theta_\mu = 2.0$")
-l3 = ax[0].plot(Theta_Values,Q1_Values_beta5 , label=r"$\theta_\mu = 5.0$")
-l4 = ax[0].plot(Theta_Values,Q1_Values_beta10 , label=r"$\theta_\mu = 10.0$")
+l1 = ax[0].plot(Theta_Values,Q1_Values_beta05 , label=r"$\theta_\mu = 0.5$")
+l2 = ax[0].plot(Theta_Values,Q1_Values_beta1 , label=r"$\theta_\mu = 1.0$")
+l3 = ax[0].plot(Theta_Values,Q1_Values_beta2 , label=r"$\theta_\mu = 2.0$")
+l4 = ax[0].plot(Theta_Values,Q1_Values_beta5 , label=r"$\theta_\mu = 5.0$")
+l5 = ax[0].plot(Theta_Values,Q1_Values_beta10 , label=r"$\theta_\mu = 10.0$")
ax[0].set_xlabel(r"volume fraction $\theta$")
ax[0].set_ylabel(r" $q_1$")
ax[0].xaxis.set_major_locator(MultipleLocator(0.25))
# Labels to use in the legend for each line
-line_labels = [r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 5.0$", r"$\theta_\mu = 10.0$"]
-
+# line_labels = [r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 5.0$", r"$\theta_\mu = 10.0$"]
+line_labels = [r"$\theta_\mu = 0.5$",r"$\theta_\mu = 1.0$", r"$\theta_\mu = 2.0$", r"$\theta_\mu = 5.0$", r"$\theta_\mu = 10.0$"]
+ax[1].plot(Theta_Values,Q2_Values_beta05 , label=r"$\theta_\rho = 0.5$")
ax[1].plot(Theta_Values,Q2_Values_beta1 , label=r"$\theta_\rho = 1.0$")
ax[1].plot(Theta_Values,Q2_Values_beta2 , label=r"$\theta_\rho = 2.0$")
ax[1].plot(Theta_Values,Q2_Values_beta5 , label=r"$\theta_\rho = 5.0$")
@@ -258,6 +268,8 @@ ax[1].xaxis.set_major_locator(MultipleLocator(0.25))
# ax[1].xaxis.set_minor_locator(MultipleLocator(0.05))
+ax[2].plot(Theta_Values,Q1_Values_beta05/Q2_Values_beta05 , label=r"$\theta_\rho = 0.5$",zorder=5)
+
ax[2].plot(Theta_Values,Q1_Values_beta1/Q2_Values_beta1 , label=r"$\theta_\rho = 1.0$")
ax[2].plot(Theta_Values,Q1_Values_beta2/Q2_Values_beta2 , label=r"$\theta_\rho = 2.0$")
ax[2].plot(Theta_Values,Q1_Values_beta5/Q2_Values_beta5 , label=r"$\theta_\rho = 5.0$")
@@ -276,10 +288,15 @@ plt.tight_layout()
+# fig.legend([l1, l2, l3, l4], # The line objects
+# labels=line_labels, # The labels for each line
+# loc="center right", # Position of legend
+# borderaxespad=0.15 # Small spacing around legend box
+# # title="Legend Title" # Title for the legend
+# )
-
-fig.legend([l1, l2, l3, l4], # The line objects
+fig.legend([l1, l2, l3, l4,l5], # The line objects
labels=line_labels, # The labels for each line
loc="center right", # Position of legend
borderaxespad=0.15 # Small spacing around legend box
diff --git a/src/TestAngle.py b/src/TestAngle.py
new file mode 100644
index 0000000000000000000000000000000000000000..77641b3ae1365dedd762d2dea75b11f051d8c2a9
--- /dev/null
+++ b/src/TestAngle.py
@@ -0,0 +1,32 @@
+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
+
+
+
+e_1 = [1,0]
+e_2 = [0,1]
+e_3 = [-1,1]
+e_4 = [1,-1]
+e_5 = [-1,-1]
+
+
+
+print("e_1:", e_1)
+print("e_2:", e_2)
+print("e_3:", e_3)
+print("e_2:", e_4)
+print("e_3:", e_5)
+print("math.atan2(e_1[1], e_1[0]):", math.atan2(e_1[1], e_1[0]))
+
+print("math.atan2(e_2[1], e_2[0]):", math.atan2(e_2[1], e_2[0]))
+print("math.atan2(e_3[1], e_3[0]):", math.atan2(e_3[1], e_3[0]))
+print("math.atan2(e_4[1], e_4[0]):", math.atan2(e_4[1], e_4[0]))
+print("math.atan2(e_5[1], e_5[0]):", math.atan2(e_5[1], e_5[0]))
diff --git a/src/plot-q3-gamma.py b/src/plot-q3-gamma.py
index 0cd0425a7c0bc6266b3574daf4fa01d91e1de275..b3141be159114a6c925f500f318b63e7db6923b2 100644
--- a/src/plot-q3-gamma.py
+++ b/src/plot-q3-gamma.py
@@ -57,26 +57,33 @@ rho1 = 1.0
# alpha = 2.8
alpha = 2.0
beta = 2.0
-# theta = 1.0/4.0
-theta = 1.0/8.0
+# beta = 10.0
+theta = 1.0/4.0
+# theta = 1.0/8.0
# lambda1 = 0.0
-gamma = 1.0/4.0
+# gamma = 1.0/4.0
# gamma = 'infinity'
+
+#TEST
+# theta = 0.1
+
+
print('mu1: ', mu1)
print('rho1: ', rho1)
print('alpha: ', alpha)
print('beta: ', beta)
print('theta: ', theta)
-print('gamma:', gamma)
+# print('gamma:', gamma)
print('----------------------------')
yName = 'q3'
xName = 'gamma'
# --- Define Interval of x-values:
xmin = 0.01
+# xmin = 1.0
xmax = 3.0
-numPoints = 15
+numPoints = 10
X_Values = np.linspace(xmin, xmax, num=numPoints)
print(X_Values)
Y_Values = []
@@ -84,10 +91,16 @@ Y_Values = []
q1 = (1.0/6.0)*harmonicMean(mu1, beta, theta)
q2 = (1.0/6.0)*arithmeticMean(mu1, beta, theta)
+print('q1=', q1)
+print('q2=',q2)
+
for x in X_Values:
# fist replace old parameters in parset
# SetParametersCellProblem(alpha,beta,theta,gamma,mu1,rho1,lambda1,InputFilePath)
- SetParametersComputeMuGamma(beta,theta,gamma,mu1,rho1, InputFilePath)
+
+
+ # SetParametersComputeMuGamma(beta,theta,gamma,mu1,rho1, InputFilePath)
+ SetParametersComputeMuGamma(beta,theta,x,mu1,rho1, InputFilePath)
# replace the sought after x value in the parset
with open(path+"/inputs/computeMuGamma.parset", 'r') as file:
@@ -107,6 +120,8 @@ for x in X_Values:
s = re.findall(r"[-+]?\d*\.\d+|\d+", tmp)
Y_Values.append(float(s[0]))
+ print('Error(q3-q1):', float(s[0])-q1)
+
# ------------end of for-loop -----------------
print("(Output) Values of " + yName + ": ", Y_Values)
# ----------------end of if-statement -------------
@@ -135,6 +150,7 @@ ax.tick_params(axis='x',which='major', direction='out',pad=3)
ax.tick_params(axis='y',which='major', length=3, width=1, direction='out',pad=3)
ax.xaxis.set_major_locator(MultipleLocator(0.5))
ax.xaxis.set_minor_locator(MultipleLocator(0.25))
+
# ax.plot(X_Values, Y_Values)
ax.plot(X_Values, Y_Values, # data
diff --git a/src/plot_ElasticRatio.py b/src/plot_Elastic_and_PrestrainRatio.py
similarity index 88%
rename from src/plot_ElasticRatio.py
rename to src/plot_Elastic_and_PrestrainRatio.py
index 1da41871db5a2da9f64bb8f628d0c9abc7d92ae6..6604a58eecb3b5b462e96810ed7f50592fe8c418 100644
--- a/src/plot_ElasticRatio.py
+++ b/src/plot_Elastic_and_PrestrainRatio.py
@@ -46,7 +46,7 @@ theta = 1.0/4.0
#set gamma either to 1. '0' 2. 'infinity' or 3. a numerical positive value
gamma = '0'
-# gamma = 'infinity'
+gamma = 'infinity'
# gamma = 0.5
# gamma = 0.25
# gamma = 1.0
@@ -85,7 +85,7 @@ print('type of gamma:', type(gamma))
# # #
# Gamma_Values = ['0', 'infinity']
Gamma_Values = ['infinity']
-Gamma_Values = ['0']
+# Gamma_Values = ['0']
print('(Input) Gamma_Values:', Gamma_Values)
for gamma in Gamma_Values:
@@ -125,7 +125,7 @@ for gamma in Gamma_Values:
# SamplePoints_3D = 400 # Number of sample points in each direction
# SamplePoints_2D = 7500 # Number of sample points in each direction
SamplePoints_2D = 4000 # 4000 # Number of sample points in each direction
- SamplePoints_2D = 10 # 4000 # Number of sample points in each direction
+ SamplePoints_2D = 500 # 4000 # Number of sample points in each direction
# if make_3D_PhaseDiagram:
# alphas_ = np.linspace(-20, 20, SamplePoints_3D)
@@ -167,18 +167,21 @@ for gamma in Gamma_Values:
# alphas_ = np.linspace(-20, 20, SamplePoints_2D)
# alphas_ = np.linspace(0, 1, SamplePoints_2D)
thetas_ = np.linspace(0.01,0.99,SamplePoints_2D)
- alphas_ = np.linspace(-5, 5, SamplePoints_2D)
+ # alphas_ = np.linspace(-5, 5, SamplePoints_2D)
# alphas_ = np.linspace(-5, 15, SamplePoints_2D)
# thetas_ = np.linspace(0.05,0.25,SamplePoints_2D)
- betas_ = 10.0
- # alphas_ = -0.5
- # betas_ = np.linspace(1.01,10.01,SamplePoints_3D) #TEST !!!!! For Beta <1 weird tings happen...
+ # betas_ = 10.0
+ alphas_ = -0.5
+ betas_ = np.linspace(1.01,10.01,SamplePoints_3D) #TEST !!!!! For Beta <1 weird tings happen...
alphas, betas, thetas = np.meshgrid(alphas_, betas_, thetas_, indexing='ij')
harmonicMeanVec = np.vectorize(harmonicMean)
arithmeticMeanVec = np.vectorize(arithmeticMean)
+ prestrain_b1Vec = np.vectorize(prestrain_b1)
+ prestrain_b2Vec = np.vectorize(prestrain_b2)
+
#
# q1 = (1.0/6.0)*harmonicMean(mu_1, beta, theta)
# q2 = (1.0/6.0)*arithmeticMean(mu_1, beta, theta)
@@ -189,6 +192,9 @@ for gamma in Gamma_Values:
q1 = harmonicMeanVec(mu1, betas, thetas)
q2 = arithmeticMeanVec(mu1, betas, thetas)
+ b1 = prestrain_b1Vec(rho1, betas, alphas, thetas)
+ b2 = prestrain_b2Vec(rho1, betas, alphas, thetas)
+
# G, angles, Tq1 = harmonicMeanVec(mu1, betas, thetas)ypes, curvature = classifyMin_anaVec(alphas,betas,thetas, muGammas, mu1, rho1) # Sets q12 to zero!!!
# print('size of G:', G.shape)
# print('G:', G)
@@ -199,6 +205,7 @@ for gamma in Gamma_Values:
# VTKOutputName = + path + "./PhaseDiagram2DNEW"
elasticRatio = q1/q2
+ prestrainRatio = b1/b2
print('type( q1) :', type(q1))
@@ -208,7 +215,20 @@ for gamma in Gamma_Values:
GammaString = str(gamma)
VTKOutputName = "outputs/ElasticRatio" #+ "Gamma_" + GammaString
- gridToVTK(VTKOutputName , alphas, betas, thetas, pointData = {'elasticRatio': elasticRatio} )
+
+
+ classifyMin_anaVec = np.vectorize(classifyMin_ana)
+ GetMuGammaVec = np.vectorize(GetMuGamma)
+ muGammas = GetMuGammaVec(betas,thetas,gamma,mu1,rho1,InputFilePath ,OutputFilePath )
+ G, angles, Types, curvature = classifyMin_anaVec(alphas,betas,thetas, muGammas, mu1, rho1) # Sets q12 to zero!!!
+
+
+
+
+
+
+
+ gridToVTK(VTKOutputName , alphas, betas, thetas, pointData = {'elasticRatio': elasticRatio, 'prestrainRatio': prestrainRatio, 'Type': Types, 'angles': angles, 'curvature': curvature} )
print('Written to VTK-File:', VTKOutputName )