violin plot added

finalcode/extract_work.py

@@ -98,7 +98,7 @@ def ExtractWork(IODet, SimDet, param1, param2, param3):
 	WD = np.array([-1.0*np.trapz(sff[:,i]*0.0075, eff[:,i]) for i in range(0,len(sff[1,:]))])
 	print len(WD)
 
-	uDG2.vector()[:] = WD 
+	uDG2.vector()[:] = WD*0.1323 
 	print uDG2.vector().array()
 	fdatamean << uDG2
 

main/10.ahaplot_WithoutDisarray.py

@@ -180,7 +180,7 @@ def aha_wd(directory1, case3, Case1, case4):
 LVbullseyemulti(data = aharraythick, filename = "Thickness", Stimulus = "Thickness", DirectorY = directory, maxm=1.75, minm=0.30 )
 LVbullseyemulti(data = aharraystrain, filename = "Long_strain", Stimulus = "Long_strain", DirectorY = directory, maxm = 25.0, minm=10.0)
 LVbullseyemulti(data = aharraystress, filename = "Pk2_stress", Stimulus = "Pk2_stress", DirectorY = directory, maxm = 100.0, minm = 25.0)
-LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm=145.0, minm=35.0)
+LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm=20.0, minm=3.0)
 
 
 

main/11.ahaplot_With_disarray_nonobstructive.py

@@ -179,7 +179,7 @@ def aha_wd(directory1, case3, Case1, case4):
 
 LVbullseyemulti(data = aharraystrain, filename = "Long_strain", Stimulus = "Long_strain", DirectorY = directory, maxm = 30, minm=5)
 LVbullseyemulti(data = aharraystress, filename = "Pk2_stress", Stimulus = "Pk2_stress", DirectorY = directory, maxm =75 , minm = 25)
-LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm =140 , minm = 5)
+LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm =20.0 , minm = 0.0)
 
 
 

main/11.ahaplot_With_disarray_obstructive.py

@@ -180,7 +180,7 @@ def aha_wd(directory1, case3, Case1, case4):
 
 LVbullseyemulti(data = aharraystrain, filename = "Long_strain", Stimulus = "Long_strain", DirectorY = directory, maxm = 30, minm=5)
 LVbullseyemulti(data = aharraystress, filename = "Pk2_stress", Stimulus = "Pk2_stress", DirectorY = directory, maxm =75 , minm = 25)
-LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm =140 , minm = 5)
+LVbullseyemulti(data = aharrayworkdensity_f, filename = "Work_density_fiber", Stimulus = "Work_density", DirectorY = directory, maxm =20.0 , minm = 0.0)
 
 
 

main/14. Multiple_violin_plot.py

@@ -0,0 +1,91 @@
+#########################################################
+
+import sys
+import vtk
+import os
+from dolfin import *
+import pdb
+import vtk.util.numpy_support as vtk_support
+#sys.path.append("/home/fenics/shared/")
+sys.path.append("/mnt/home/mojumder/HPCC_HCM/github/HCM")
+import vtk_py as vtk_py
+import numpy as np
+import math
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+import scipy.stats as stats
+
+############################################################
+from finalcode.mean_dev import StimulusDev2
+
+################################################################
+
+
+
+
+def DataExtraction(directory, casename,stimuli):
+
+	filename = directory+casename + ".vtp"
+
+	pdata_reader = vtk.vtkXMLPolyDataReader()
+	pdata_reader.SetFileName(filename)
+	pdata_reader.Update()
+	pdata = pdata_reader.GetOutput()
+
+	array = (vtk_support.vtk_to_numpy(pdata.GetPointData().GetArray(stimuli)))
+
+	return array	
+
+
+
+
+
+
+
+
+
+
+case1 = ['P1' , 'P2', 'P3']
+
+
+
+
+Stimulus = 'fstressPk2_'+'max'
+DataName = 'f_22'
+for l in range(len(case1)):
+	directory1 = './with_dispersion/'+ case1[l]+"/k0/simulation/mechanics/ME/"
+
+	vtufilename = directory1+ 'fstressPk2_'+'max'
+	filename = "data_set_"+Stimulus
+	fdatadev3 = open(directory1+case1[l]+"_thickness.txt", "w+")
+	StimulusDev2(STIMULUS=Stimulus,VTUfilename = vtufilename, fdatadev3 =fdatadev3,  dataname = DataName, DirectorY = directory1, field_type="point")
+
+
+	if l==0:
+		P1_array = DataExtraction(directory1, Stimulus,stimuli= "Thickness")
+	elif l==1:
+		P2_array = DataExtraction(directory1, Stimulus,stimuli= "Thickness")
+	else:
+		P3_array = DataExtraction(directory1, Stimulus,stimuli= "Thickness")
+
+
+fig, ax = plt.subplots(figsize = (8,6))	
+ax.violinplot([P1_array, P2_array, P3_array][::-1], positions = [3,2,1], showmeans = True)
+
+def set_axis_style2(ax, labels):
+	ax.get_yaxis().set_tick_params(labelsize = 14, direction = 'out')
+	ax.get_xaxis().set_tick_params(labelsize = 14)
+	ax.xaxis.set_ticks_position('bottom')
+	ax.set_xticks(np.arange(1, len(labels)+1))
+	ax.set_xticklabels(labels, fontsize = 14)
+	ax.set_xlim(0.25, len(labels)+0.75)
+	ax.set_ylabel('Thickness (cm)', fontsize = 14)
+set_axis_style2(ax, ['Control', 'Non-Obstructive','Obstructive'])
+#plt.show()	
+plt.savefig('thicknessall' +"_1.png")
+#plt.show()
+plt.close()
+
+
+
+

main/2.Nonobstructive_k1.py

@@ -82,6 +82,7 @@
 		  "Q_mv" : 0.0124479080844,
     		  "stop_iter" : 6,
 		  "V_LV_target": 82.1,
+		  }
 
 SimDetails = {    
                   "diaplacementInfo_ref": False,

main/Matlabplot/active_tension_dispersion_P2.m

@@ -0,0 +1,97 @@
+function active_tension()
+lamda = 1.5
+%I = Invariant(lamda)
+timevariantformulation()
+
+end
+function timevariantformulation()
+%Constant values
+lr = 1.85;
+lo = 1.55 ;
+CaoMax = 4.35;
+Cao = 4.35;
+B = 4.75;
+to = 400 ; 
+ttrans = 430; 
+tau = 35; 
+BCL = 910; 
+
+% c = [0.93, 0.96, 1.0, 1.1, 1.2, 1.6 ]
+% T = 95E03; %400E03;  
+
+c  = [1.0,1.05,1.1,1.25,2.1] %,4.0] %,18.0 ]
+T = 400E03;
+
+
+%variables 
+lamda = 1.0;
+lambda = 1.0;
+timepoint =linspace(0, BCL, BCL/2);
+sigma_active = zeros(1, length(timepoint));
+dlamda = lamda/to;
+actmax = zeros(1, length(c));
+for j = 1:length(c)
+    Tmax = c(j)*T;
+
+for i = 1:length(timepoint)
+    ta = timepoint(i);
+%     if ta<to
+%         lambda = lambda + dlamda;
+%     else
+%         lambda = lambda - dlamda;
+%     end
+    lambda = lamda;
+
+    lso = ActiveLength(lambda, lr, lo);
+
+    deno = sqrt(exp((B*lso)-1));
+    ECa50 = CaoMax/deno;
+
+    if ta<ttrans
+        Ct = 0.5*(1-cos(pi*ta/to));
+    else
+        Ct = 0.5*(1-cos(pi*ttrans/to))*exp(-((ta-ttrans)/tau));
+    end
+
+
+    CaTerm = Cao^2 /(Cao^2 + ECa50^2);
+    Pact = Tmax*CaTerm*Ct;
+    sigma_active(i) = Pact;
+
+end
+
+figure(1)
+hold on
+plot(timepoint, sigma_active/1000,'LineWidth',1.5)
+hold on
+actmax(j) = max(sigma_active)/1000.0
+
+end
+
+grid on
+legend({'\kappa = 0','\kappa = 0.07','\kappa = 0.1','\kappa = 0.14','\kappa=0.18'}, 'FontSize',16, 'Fontname','Times New Roman')%,'17','18','19')%,'change','pp') %,'0.35,0.05','0.35,0.09','0.35,0.5')
+%legend({'Control','Non-Obstructive', 'Obstructive'}, 'FontSize',16)
+title('Non-obstructive HCM','FontSize',18,  'Fontname','Times New Roman','Fontweight','normal')
+xlabel('Time (ms)','FontSize',18,  'Fontname','Times New Roman')
+ylabel('Tension (kPa)','FontSize',18,  'Fontname','Times New Roman')
+hold off
+ax = gca;
+%ax.FontSize = 12;
+%ax.FontWeight = 'bold';
+% ax.XLim = [25 60];
+%pbaspect([1 1 1])
+%grid minor
+%plot_func (list, sigma_total_xx)
+saveas(gcf, 'activetension_p2_dispersion_new', 'png')
+actmax
+end
+
+function lso = ActiveLength(lamda, lr, lo)
+ls = lamda*lr;
+if ls<=lo
+    lso = 0.002;
+else 
+    lso = ls-lo;
+
+end
+end

main/Matlabplot/active_tension_dispersion_P3_otg.m

@@ -0,0 +1,96 @@
+function active_tension()
+lamda = 1.5
+%I = Invariant(lamda)
+timevariantformulation()
+
+end
+function timevariantformulation()
+%Constant values
+lr = 1.85;
+lo = 1.55 ;
+CaoMax = 4.35;
+Cao = 4.35;
+B = 4.75;
+to = 350; %800 ; 
+ttrans = 420; %410; 
+tau = 35; %40; 
+BCL = 1180; %910; 
+
+c = [1.05, 1.125, 1.15, 1.3, 1.45, 1.75]
+T = 95E03; %400E03;  
+
+% c  = [2.0,2.6,2.7, 3.0,7.0,18.0 ]
+% T = 400E03;
+
+
+%variables 
+lamda = 1.0;
+lambda = 1.0;
+timepoint =linspace(0, BCL, BCL/2);
+sigma_active = zeros(1, length(timepoint));
+dlamda = lamda/to;
+actmax = zeros(1, length(c));
+for j = 1:length(c)
+    Tmax = c(j)*T;
+
+for i = 1:length(timepoint)
+    ta = timepoint(i);
+%     if ta<to
+%         lambda = lambda + dlamda;
+%     else
+%         lambda = lambda - dlamda;
+%     end
+    lambda = lamda;
+
+    lso = ActiveLength(lambda, lr, lo);
+
+    deno = sqrt(exp((B*lso)-1));
+    ECa50 = CaoMax/deno;
+
+    if ta<ttrans
+        Ct = 0.5*(1-cos(pi*ta/to));
+    else
+        Ct = 0.5*(1-cos(pi*ttrans/to))*exp(-((ta-ttrans)/tau));
+    end
+
+
+    CaTerm = Cao^2 /(Cao^2 + ECa50^2);
+    Pact = Tmax*CaTerm*Ct;
+    sigma_active(i) = Pact;
+
+end
+
+figure(1)
+hold on
+plot(timepoint, sigma_active/1000,'LineWidth',1.5)
+hold on
+actmax(j) = max(sigma_active)/1000.0
+
+end
+
+grid on
+legend({'\kappa = 0','\kappa = 0.07','\kappa = 0.1','\kappa = 0.14','\kappa=0.18','\kappa=0.22' }, 'FontSize',16, 'Fontname','Times New Roman')%,'17','18','19')%,'change','pp') %,'0.35,0.05','0.35,0.09','0.35,0.5')
+%legend({'Control','Non-Obstructive', 'Obstructive'}, 'FontSize',16)
+title('Obstructive HCM','FontSize',18, 'Fontname','Times New Roman', 'Fontweight' , 'normal')
+xlabel('Time (ms)','FontSize',18, 'Fontname','Times New Roman')
+ylabel('Tension (kPa)','FontSize',18, 'Fontname','Times New Roman')
+hold off
+ax = gca;
+%ax.FontWeight = 'bold';
+% ax.XLim = [25 60];
+%pbaspect([1 1 1])
+%grid minor
+%plot_func (list, sigma_total_xx)
+saveas(gcf, 'activetension_p3_dispersion_otg', 'png')
+actmax
+end
+
+function lso = ActiveLength(lamda, lr, lo)
+ls = lamda*lr;
+if ls<=lo
+    lso = 0.002;
+else 
+    lso = ls-lo;
+
+end
+end