# To reproduce Figure 1 in the associated Physiome paper, # execute this script from the command line: # # cd [PathToThisFile] # [PathToOpenCOR]/pythonshell Figure4.py import matplotlib.pyplot as plt import opencor as opencor import numpy as np simulation = opencor.open_simulation("model.sedml") data = simulation.data() data.set_ending_point(10000) data.set_point_interval(10) # simulation.reset(True) def run_sim1(n_sglt1, glucose_m): simulation.reset(True) simulation.clear_results() data.constants()["Cell_concentration/L_A"] = 6e-5 data.constants()["Cell_concentration/L_B"] = 6e-5 data.constants()["Blood_concentrations/v_B"] = 1e-16 data.constants()["Blood_concentrations/glucose_in"] = 0.004 data.constants()["A_GLUT2/n_GLUT"] = 1e8 data.constants()["Blood_concentrations/Q_in"] = 9e-18 # data.constants()["Blood_concentrations/v_w1"] = 1.8e-4 # data.constants()["phenomonological_constants/n_SGLT"] = 3e7 data.constants()["parameters/k0_12"] = 12000 data.constants()["parameters/k0_61"] = 15 # data.constants()["phenomonological_constants/n_SGLT"] = 1e7 data.constants()["Apical_concentrations/glucose_m"] = glucose_m data.constants()["phenomonological_constants/n_SGLT"] = n_sglt1 simulation.run() ds = simulation.results().data_store() v_cell = (ds.voi_and_variables()["Cell_concentration/v_cell"].values()[-1]*1e18) glucose_i = (ds.voi_and_variables()["Cell_concentration/glucose_i"].values()[-1]*1e3) J_Gl_SGLT = (ds.voi_and_variables()["phenomonological_constants/J_Gl_SGLT"].values()[-1]) J_A_GLUT = (ds.voi_and_variables()["A_GLUT2/J_A_GLUT"].values()[-1]) J_GLUT = (ds.voi_and_variables()["GLUT2/J_GLUT"].values()[-1]*(-1)) return (v_cell, glucose_i, J_Gl_SGLT, J_A_GLUT, J_GLUT) def run_sim2(n_glut_A, glucose_m): simulation.reset(True) simulation.clear_results() data.constants()["Cell_concentration/L_A"] = 6e-5 data.constants()["Cell_concentration/L_B"] = 6e-5 data.constants()["Blood_concentrations/v_B"] = 1e-16 data.constants()["Blood_concentrations/glucose_in"] = 0.004 # data.constants()["A_GLUT2/n_GLUT"] = 1e8 data.constants()["Blood_concentrations/Q_in"] = 9e-18 # data.constants()["Blood_concentrations/v_w1"] = 1.8e-4 # data.constants()["phenomonological_constants/n_SGLT"] = 3e7 data.constants()["parameters/k0_12"] = 12000 data.constants()["parameters/k0_61"] = 15 data.constants()["phenomonological_constants/n_SGLT"] = 4e7 data.constants()["Apical_concentrations/glucose_m"] = glucose_m data.constants()["A_GLUT2/n_GLUT"] = n_glut_A simulation.run() ds = simulation.results().data_store() v_cell = (ds.voi_and_variables()["Cell_concentration/v_cell"].values()[-1]*1e18) glucose_i = (ds.voi_and_variables()["Cell_concentration/glucose_i"].values()[-1]*1e3) J_Gl_SGLT = (ds.voi_and_variables()["phenomonological_constants/J_Gl_SGLT"].values()[-1]) J_A_GLUT = (ds.voi_and_variables()["A_GLUT2/J_A_GLUT"].values()[-1]) J_GLUT = (ds.voi_and_variables()["GLUT2/J_GLUT"].values()[-1]*(-1)) return (v_cell, glucose_i, J_Gl_SGLT, J_A_GLUT, J_GLUT) def run_sim3(n_glut_B, glucose_m): simulation.reset(True) simulation.clear_results() data.constants()["Cell_concentration/L_A"] = 6e-5 data.constants()["Cell_concentration/L_B"] = 6e-5 data.constants()["Blood_concentrations/v_B"] = 1e-16 data.constants()["Blood_concentrations/glucose_in"] = 0.004 data.constants()["A_GLUT2/n_GLUT"] = 1e8 data.constants()["Blood_concentrations/Q_in"] = 9e-18 # data.constants()["Blood_concentrations/v_w1"] = 1.8e-4 # data.constants()["phenomonological_constants/n_SGLT"] = 3e7 data.constants()["parameters/k0_12"] = 12000 data.constants()["parameters/k0_61"] = 15 data.constants()["phenomonological_constants/n_SGLT"] = 4e7 data.constants()["Apical_concentrations/glucose_m"] = glucose_m data.constants()["GLUT2/n_GLUT"] = n_glut_B simulation.run() ds = simulation.results().data_store() v_cell = (ds.voi_and_variables()["Cell_concentration/v_cell"].values()[-1] * 1e18) glucose_i = (ds.voi_and_variables()["Cell_concentration/glucose_i"].values()[-1] * 1e3) J_Gl_SGLT = (ds.voi_and_variables()["phenomonological_constants/J_Gl_SGLT"].values()[-1]) J_A_GLUT = (ds.voi_and_variables()["A_GLUT2/J_A_GLUT"].values()[-1]) J_GLUT = (ds.voi_and_variables()["GLUT2/J_GLUT"].values()[-1] * (-1)) return (v_cell, glucose_i, J_Gl_SGLT, J_A_GLUT, J_GLUT) # # if __name__ == '__main__': # different values for y_shift sglt1 = [1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7] gl_l = [0.005, 0.01, 0.02, 0.05, 0] y_label = ["V_cell", "Glucose_i", "J_SGLT1", "J_A_GLUT2", "J_B_GLUT2"] X1 = [[1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7], [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8], [1e8, 1.5e8, 2e8, 2.5e8, 3e8], [1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7], [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8], [1e8, 1.5e8, 2e8, 2.5e8, 3e8], [1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7], [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8], [1e8, 1.5e8, 2e8, 2.5e8, 3e8], [1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7], [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8], [1e8, 1.5e8, 2e8, 2.5e8, 3e8], [1.5e7, 2.25e7, 3e7, 3.75e7, 4.5e7], [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8], [1e8, 1.5e8, 2e8, 2.5e8, 3e8]] n_glut_A = [0.5e8, 0.75e8, 1e8, 1.25e8, 1.5e8] n_glut_B = [1e8, 1.5e8, 2e8, 2.5e8, 3e8] plt.figure(figsize=(14,16)) plt.subplot(5,3,1) v_cell_1 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[0])[0] v_cell_1.append(result) v_cell_2 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[1])[0] v_cell_2.append(result) v_cell_3 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[2])[0] v_cell_3.append(result) v_cell_4 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[3])[0] v_cell_4.append(result) v_cell_5 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[4])[0] v_cell_5.append(result) plt.plot(X1[0], v_cell_1, color= 'orange', label = "G$_L$ = 5 mM") plt.plot(X1[0], v_cell_2, color= 'green', label = "G$_L$ = 10 mM") plt.plot(X1[0], v_cell_3, color= 'red', label = "G$_L$ = 20 mM") plt.plot(X1[0], v_cell_4, color= 'purple', label = "G$_L$ = 50 mM") plt.plot(X1[0], v_cell_5, color= 'blue', label = "G$_L$ = 0 mM") plt.xlim(1.5e7, 4.5e7) plt.xticks(np.arange(1.5e7, 4.6e7, 0.75e7)) plt.ylabel(y_label[0], fontsize=12) plt.ylim(1350,1750) plt.yticks(np.arange(1400, 1750, 100)) plt.legend(bbox_to_anchor=(0.025, 0.30, 0.75, 0.28), loc='best', fontsize=10, ncol=2, labelspacing=0.) plt.subplot(5,3,2) v_cell_1 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[0])[0] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[1])[0] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[2])[0] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[3])[0] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[4])[0] v_cell_5.append(result) plt.plot(X1[1], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[1], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[1], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[1], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[1], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(0.5e8, 1.5e8) plt.xticks(np.arange(0.5e8, 1.6e8, 0.25e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(1350, 1750) plt.yticks(np.arange(1400, 1750, 100)) plt.subplot(5, 3, 3) v_cell_1 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[0])[0] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[1])[0] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[2])[0] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[3])[0] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[4])[0] v_cell_5.append(result) plt.plot(X1[2], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[2], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[2], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[2], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[2], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1e8, 3e8) plt.xticks(np.arange(1e8, 3e8, 0.5e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(1350, 1750) plt.yticks(np.arange(1400, 1750, 100)) plt.subplot(5, 3, 4) glucose_i_1 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[0])[1] glucose_i_1.append(result) glucose_i_2 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[1])[1] glucose_i_2.append(result) glucose_i_3 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[2])[1] glucose_i_3.append(result) glucose_i_4 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[3])[1] glucose_i_4.append(result) glucose_i_5 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[4])[1] glucose_i_5.append(result) plt.plot(X1[0], glucose_i_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[0], glucose_i_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[0], glucose_i_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[0], glucose_i_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[0], glucose_i_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1.5e7, 4.5e7) plt.xticks(np.arange(1.5e7, 4.6e7, 0.75e7)) plt.ylabel(y_label[1], fontsize=12) plt.ylim(-1, 45) plt.yticks(np.arange(0, 45, 10)) plt.subplot(5, 3, 5) glucose_i_1 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[0])[1] glucose_i_1.append(result) glucose_i_2 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[1])[1] glucose_i_2.append(result) glucose_i_3 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[2])[1] glucose_i_3.append(result) glucose_i_4 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[3])[1] glucose_i_4.append(result) glucose_i_5 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[4])[1] glucose_i_5.append(result) plt.plot(X1[1], glucose_i_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[1], glucose_i_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[1], glucose_i_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[1], glucose_i_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[1], glucose_i_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(0.5e8, 1.5e8) plt.xticks(np.arange(0.5e8, 1.6e8, 0.25e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1, 45) plt.yticks(np.arange(0, 45, 10)) plt.subplot(5, 3, 6) glucose_i_1 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[0])[1] glucose_i_1.append(result) glucose_i_2 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[1])[1] glucose_i_2.append(result) glucose_i_3 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[2])[1] glucose_i_3.append(result) glucose_i_4 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[3])[1] glucose_i_4.append(result) glucose_i_5 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[4])[1] glucose_i_5.append(result) plt.plot(X1[2], glucose_i_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[2], glucose_i_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[2], glucose_i_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[2], glucose_i_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[2], glucose_i_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1e8, 3e8) plt.xticks(np.arange(1e8, 3.1e8, 0.5e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1, 45) plt.yticks(np.arange(0, 45, 10)) plt.subplot(5, 3, 7) v_cell_1 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[0])[2] v_cell_1.append(result) v_cell_2 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[1])[2] v_cell_2.append(result) v_cell_3 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[2])[2] v_cell_3.append(result) v_cell_4 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[3])[2] v_cell_4.append(result) v_cell_5 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[4])[2] v_cell_5.append(result) plt.plot(X1[0], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[0], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[0], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[0], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[0], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1.5e7, 4.5e7) plt.xticks(np.arange(1.5e7, 4.6e7, 0.75e7)) plt.ylabel(y_label[2], fontsize=12) plt.ylim(-1e-12,8e-11) plt.yticks(np.arange(0,8.1e-11, 2e-11)) plt.subplot(5, 3, 8) v_cell_1 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[0])[2] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[1])[2] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[2])[2] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[3])[2] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[4])[2] v_cell_5.append(result) plt.plot(X1[1], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[1], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[1], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[1], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[1], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(0.5e8, 1.5e8) plt.xticks(np.arange(0.5e8, 1.6e8, 0.25e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1e-12, 8e-11) plt.yticks(np.arange(0, 8.1e-11, 2e-11)) plt.subplot(5, 3, 9) v_cell_1 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[0])[2] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[1])[2] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[2])[2] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[3])[2] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[4])[2] v_cell_5.append(result) plt.plot(X1[2], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[2], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[2], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[2], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[2], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1e8, 3e8) plt.xticks(np.arange(1e8, 3e8, 0.5e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1e-12, 8e-11) plt.yticks(np.arange(0, 8.1e-11, 2e-11)) plt.subplot(5, 3, 10) v_cell_1 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[0])[3] v_cell_1.append(result) v_cell_2 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[1])[3] v_cell_2.append(result) v_cell_3 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[2])[3] v_cell_3.append(result) v_cell_4 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[3])[3] v_cell_4.append(result) v_cell_5 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[4])[3] v_cell_5.append(result) plt.plot(X1[0], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[0], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[0], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[0], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[0], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1.5e7, 4.5e7) plt.xticks(np.arange(1.5e7, 4.6e7, 0.75e7)) plt.ylabel(y_label[3], fontsize=12) plt.ylim(-4.5e-11, 4.5e-11) plt.yticks(np.arange(-4e-11, 4.1e-11, 2e-11)) plt.subplot(5, 3, 11) v_cell_1 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[0])[3] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[1])[3] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[2])[3] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[3])[3] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[4])[3] v_cell_5.append(result) plt.plot(X1[1], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[1], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[1], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[1], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[1], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(0.5e8, 1.5e8) plt.xticks(np.arange(0.5e8, 1.6e8, 0.25e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-4.5e-11, 4.5e-11) plt.yticks(np.arange(-4e-11, 4.1e-11, 2e-11)) plt.subplot(5, 3, 12) v_cell_1 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[0])[3] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[1])[3] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[2])[3] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[3])[3] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[4])[3] v_cell_5.append(result) plt.plot(X1[2], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[2], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[2], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[2], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[2], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1e8, 3e8) plt.xticks(np.arange(1e8, 3e8, 0.5e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-4.5e-11, 4.5e-11) plt.yticks(np.arange(-4e-11, 4.1e-11, 2e-11)) plt.subplot(5, 3, 13) v_cell_1 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[0])[4] v_cell_1.append(result) v_cell_2 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[1])[4] v_cell_2.append(result) v_cell_3 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[2])[4] v_cell_3.append(result) v_cell_4 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[3])[4] v_cell_4.append(result) v_cell_5 = [] for i in range(len(sglt1)): result = run_sim1(sglt1[i], gl_l[4])[4] v_cell_5.append(result) plt.plot(X1[0], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[0], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[0], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[0], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[0], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1.5e7, 4.5e7) plt.xticks(np.arange(1.5e7, 4.6e7, 0.75e7)) plt.ylabel(y_label[4], fontsize=12) plt.ylim(-1e-10,5e-11) plt.yticks(np.arange(-1e-10,5.1e-11, 0.25e-10)) plt.subplot(5, 3, 14) v_cell_1 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[0])[4] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[1])[4] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[2])[4] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[3])[4] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_A)): result = run_sim2(n_glut_A[i], gl_l[4])[4] v_cell_5.append(result) plt.plot(X1[1], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[1], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[1], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[1], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[1], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(0.5e8, 1.5e8) plt.xticks(np.arange(0.5e8, 1.6e8, 0.25e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1e-10,5e-11) plt.yticks(np.arange(-1e-10,5.1e-11, 0.25e-10)) plt.subplot(5, 3, 15) v_cell_1 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[0])[4] v_cell_1.append(result) v_cell_2 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[1])[4] v_cell_2.append(result) v_cell_3 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[2])[4] v_cell_3.append(result) v_cell_4 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[3])[4] v_cell_4.append(result) v_cell_5 = [] for i in range(len(n_glut_B)): result = run_sim3(n_glut_B[i], gl_l[4])[4] v_cell_5.append(result) plt.plot(X1[2], v_cell_1, color='orange', label="G$_L$ = 5 mM") plt.plot(X1[2], v_cell_2, color='green', label="G$_L$ = 10 mM") plt.plot(X1[2], v_cell_3, color='red', label="G$_L$ = 20 mM") plt.plot(X1[2], v_cell_4, color='purple', label="G$_L$ = 50 mM") plt.plot(X1[2], v_cell_5, color='blue', label="G$_L$ = 0 mM") plt.xlim(1e8, 3e8) plt.xticks(np.arange(1e8, 3e8, 0.5e8)) # plt.ylabel(y_label[i], fontsize=12) plt.ylim(-1e-10, 5e-11) plt.yticks(np.arange(-1e-10, 5.1e-11, 0.25e-10)) plt.savefig('Figure04.png') plt.show()