import numpy as np from matplotlib import gridspec from charged_shells.rotational_path import PairRotationalPath, PathEnergyPlot from charged_shells import interactions, charge_distributions from charged_shells.parameters import ModelParams from config import * from plot_settings import * Array = np.ndarray zero_to_pi_half = np.linspace(0, np.pi/2, 100, endpoint=True) pi_half_to_pi = np.linspace(np.pi/2, np.pi, 100, endpoint=True) pi_to_three_halves_pi = np.linspace(np.pi, 3 * np.pi / 2, 100, endpoint=True) DipolePath = PairRotationalPath() DipolePath.set_default_x_axis(zero_to_pi_half) DipolePath.add_euler(beta2=pi_half_to_pi[::-1]) DipolePath.add_euler(beta2=zero_to_pi_half[::-1]) DipolePath.add_euler(beta2=zero_to_pi_half, beta1=zero_to_pi_half) DipolePath.add_euler(beta2=np.pi/2, beta1=np.pi/2, alpha2=zero_to_pi_half) DipolePath.add_euler(beta2=np.pi/2, alpha2=np.pi/2, beta1=pi_half_to_pi) DipolePath.add_euler(beta2=np.pi/2, beta1=pi_half_to_pi[::-1], alpha1=np.pi) DipolePath.add_euler(beta2=zero_to_pi_half[::-1], beta1=pi_half_to_pi, alpha1=np.pi) DipolePath.add_euler(beta2=zero_to_pi_half, beta1=pi_half_to_pi[::-1], alpha1=np.pi) DipolePath.add_euler(beta2=pi_half_to_pi, beta1=zero_to_pi_half[::-1], alpha1=np.pi) DipolePath2 = PairRotationalPath() DipolePath2.set_default_x_axis(zero_to_pi_half) DipolePath2.add_euler(beta2=pi_half_to_pi[::-1]) DipolePath2.add_euler(beta2=zero_to_pi_half[::-1]) DipolePath2.add_euler(beta2=zero_to_pi_half, beta1=zero_to_pi_half) DipolePath2.add_euler(beta2=np.pi/2, beta1=np.pi/2, alpha2=zero_to_pi_half) DipolePath2.add_euler(beta2=np.pi/2, alpha2=np.pi/2, beta1=pi_half_to_pi) DipolePath2.add_euler(beta2=zero_to_pi_half[::-1], beta1=pi_half_to_pi[::-1]) DipolePath2.add_euler(beta2=zero_to_pi_half[::-1], beta1=np.pi) DipolePath2.add_euler(beta2=zero_to_pi_half, beta1=pi_half_to_pi[::-1], alpha1=np.pi) DipolePath2.add_euler(beta2=pi_half_to_pi, beta1=zero_to_pi_half[::-1], alpha1=np.pi) DipolePath3 = PairRotationalPath() DipolePath3.set_default_x_axis(zero_to_pi_half) DipolePath3.add_euler(beta2=np.pi/2, beta1=zero_to_pi_half, start_name="EP", end_name="EE") DipolePath3.add_euler(beta2=pi_half_to_pi, beta1=pi_half_to_pi, end_name="PP") DipolePath3.add_euler(beta2=pi_half_to_pi[::-1], beta1=np.pi, end_name="EP") DipolePath3.add_euler(beta2=pi_half_to_pi, beta1=pi_to_three_halves_pi, end_name="EP") DipolePath3.add_euler(beta1=3 * np.pi/2, beta2=pi_half_to_pi[::-1], alpha2=np.pi/2, end_name="tEE") DipolePath3.add_euler(beta1=3 * np.pi/2, beta2=np.pi/2, alpha1=zero_to_pi_half[::-1], end_name="EE") DipolePath3.add_euler(beta1=3 * np.pi/2, beta2=pi_half_to_pi, end_name="EP") def sections_plot(kappaR: float = 3, abar: float = 0.5, sigma_tilde=0.001, save_as=None): params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) path_plot.plot_sections(save_as=save_as) def kappaR_dependence(kappaR: Array, abar: float, sigma_tilde=0.001, save_as=None): params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=0) path_plot.plot(labels=[rf'$\kappa R$={kR}' for kR in kappaR], # norm_euler_angles={'beta2': np.pi}, save_as=save_as) def abar_dependence(abar: Array, kappaR: float, sigma_tilde=0.001, save_as=None): params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) path_plot.plot(labels=[rf'$\bar a$={a}' for a in abar], # norm_euler_angles={'beta2': np.pi}, save_as=save_as) def sigma0_dependence(sigma0: Array, kappaR: float, abar: float, sigma_tilde=0.001, save_as=None): params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30, sigma0=sigma0) ex2 = ex1.clone() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) path_plot.plot(labels=[rf'$\eta={s0 / sigma_tilde}$' for s0 in sigma0], # norm_euler_angles={'beta2': np.pi}, save_as=save_as) def model_comparison(save_as=None, save_data=False): kappaR = 3 params = ModelParams(R=150, kappaR=kappaR) a_bar = 0.5 sigma_tilde = 0.001 ex1 = charge_distributions.create_mapped_dipolar_expansion(a_bar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign() # matching other models to the mapped CSp model based on equal patch size in potential # ex_gauss = quadrupole_model_mappings.ic_to_gauss(sigma_tilde, a_bar, params, l_max=30, sigma0=0) # ex_gauss2 = ex_gauss.clone() # ex_cap = quadrupole_model_mappings.ic_to_cap(sigma_tilde, a_bar, params, l_max=30, sigma0=0) # ex_cap2 = ex_cap.clone() # path plots for all models path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params) energy = path_plot.evaluate_path() x_axis = path_plot.rot_path.stack_x_axes() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params) energy_inv = path_plot_inv.evaluate_path() # path_plot_gauss = PathEnergyPlot(ex_gauss, ex_gauss2, DipolePath3, dist=2., params=params) # energy_gauss = path_plot_gauss.evaluate_path() # # path_plot_cap = PathEnergyPlot(ex_cap, ex_cap2, DipolePath3, dist=2., params=params) # energy_cap = path_plot_cap.evaluate_path() # peak_energy_sanity_check # ex1new = expansion.MappedExpansionQuad(abar, params.kappaR, sigma_tilde, l_max=30) # ex2new = ex1new.clone() # pp_energy = interactions.charged_shell_energy(ex1new, ex2new, params) # print(f'PP energy: {pp_energy}') # ICi data em_data = np.load(ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_A").joinpath("pathway.npz"))['arr_0'] # em_data = np.load(ICI_DATA_PATH.joinpath("FIG_7").joinpath("pathway.npz"))['arr_0'] # em_data_path = (ICI_DATA_PATH.joinpath("FIG_8").joinpath("FIXEDCHARGE") # .joinpath("FIX_A").joinpath("ECC_0.25")) # em_data = np.load(em_data_path.joinpath(f"EMME_{kappaR}.").joinpath("pathway.npz"))['arr_0'] em_data, em_data_inv = em_data[:int(len(em_data) / 2)], em_data[int(len(em_data) / 2):] # if save_data: # np.savez(Path(config_data["figure_data"]).joinpath(f"fig_5_janus_kR{kappaR}.npz"), # ICi=em_data, # CSp=np.stack((x_axis, np.squeeze(energy))).T, # CSp_gauss=np.stack((x_axis, np.squeeze(energy_gauss))).T, # CSp_cap=np.stack((x_axis, np.squeeze(energy_cap))).T) fig, ax = plt.subplots(figsize=0.5 * np.array([8.25, 4.125])) ax.plot(em_data[:, 0], em_data[:, 1], label='ICi', c='tab:blue') ax.plot(em_data_inv[:, 0], em_data_inv[:, 1], ls='--', c='tab:blue') ax.plot(x_axis, np.squeeze(energy), label='CSp', c='tab:orange') ax.plot(x_axis, np.squeeze(energy_inv), ls='--', c='tab:orange') # ax.plot(x_axis, np.squeeze(energy_gauss), label='CSp - Gauss') # ax.plot(x_axis, np.squeeze(energy_cap), label='CSp - cap') # ax.plot(x_axis, em_data[:, 1] / np.squeeze(energy), label='CSp') path_plot.plot_style(fig, ax) if save_as is not None: plt.savefig(save_as, dpi=300) plt.show() def combined_kappaR_dependence(kappaR: list[int], abar: float, sigma_tilde=0.001, save_as=None): em_data_path = (ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_C") .joinpath("FIX_A").joinpath(f"ECC_{np.round(abar/2, 4)}")) ic_data = [] ic_data_inv = [] for kR in kappaR: em_data = np.load(em_data_path.joinpath(f"EMME_{kR}.").joinpath("pathway.npz"))['arr_0'] em_data, em_data_inv = em_data[:int(len(em_data) / 2)], em_data[int(len(em_data) / 2):] ic_data.append(em_data) ic_data_inv.append(em_data_inv) params = ModelParams(R=150, kappaR=np.asarray(kappaR)) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=0) energy = path_plot.evaluate_path() x_axis = path_plot.rot_path.stack_x_axes() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=0) energy_inv = path_plot_inv.evaluate_path() labels = [rf'$\kappa R = {kR}$' for kR in [1, 3, 10]] fig, ax = plt.subplots() for d, d_inv, en, en_inv, label, c in zip(ic_data, ic_data_inv, energy.T, energy_inv.T, labels, COLORS): ax.plot(d[:, 0], d[:, 1], label=label, c=c) ax.plot(d_inv[:, 0], d_inv[:, 1], c=c) ax.plot(x_axis, en, ls='--', c=c) ax.plot(x_axis, en_inv, ls='--', c=c) DipolePath3.plot_style(fig, ax) if save_as is not None: plt.savefig(save_as, dpi=300) plt.show() def combined_abar_dependence(kappaR: int, abar: list[float], sigma_tilde=0.001, save_as=None): em_data_path = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_B").joinpath("FIX_M") ic_data = [] ic_data_inv = [] for ab in abar: em_data = np.load(em_data_path.joinpath(f"ECC_{np.round(ab/2, 4)}").joinpath(f"EMME_{kappaR}.").joinpath("pathway.npz"))['arr_0'] em_data, em_data_inv = em_data[:int(len(em_data) / 2)], em_data[int(len(em_data) / 2):] ic_data.append(em_data) ic_data_inv.append(em_data_inv) params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(np.asarray(abar), params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign() path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy = path_plot.evaluate_path() x_axis = path_plot.rot_path.stack_x_axes() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_inv = path_plot_inv.evaluate_path() labels = [rf'$\bar a={a}$' for a in [0.3, 0.4, 0.5]] fig, ax = plt.subplots() for d, d_inv, en, en_inv, label, c in zip(ic_data, ic_data_inv, energy.T, energy_inv.T, labels, COLORS): ax.plot(d[:, 0], d[:, 1], label=label, c=c) ax.plot(d_inv[:, 0], d_inv[:, 1], c=c) ax.plot(x_axis, en, ls='--', c=c) ax.plot(x_axis, en_inv, ls='--', c=c) DipolePath3.plot_style(fig, ax) if save_as is not None: plt.savefig(save_as, dpi=300) plt.show() def combined_sigma0_dependence(kappaR=3., abar=0.5, sigma0=(-0.0002, 0.00, 0.0002), sigma_tilde=0.001, save_as=None): em_data_path = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_D").joinpath("CHANGE_ZC") undercharged = np.load(em_data_path.joinpath("ZC_-56").joinpath("pathway.npz"))['arr_0'] overcharged = np.load(em_data_path.joinpath("ZC_56").joinpath("pathway.npz"))['arr_0'] neutral_path = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_B").joinpath("FIX_M") neutral = np.load(neutral_path.joinpath(f"ECC_{np.round(abar/2, 4)}").joinpath(f"EMME_{int(kappaR)}.").joinpath("pathway.npz"))['arr_0'] undercharged, undercharged_inv = undercharged[:int(len(undercharged) / 2)], undercharged[int(len(undercharged) / 2):] overcharged, overcharged_inv = overcharged[:int(len(overcharged) / 2)], overcharged[int(len(overcharged) / 2):] neutral, neutral_inv = neutral[:int(len(neutral) / 2)], neutral[int(len(neutral) / 2):] ic_data = [undercharged, neutral, overcharged] ic_data_inv = [undercharged_inv, neutral_inv, overcharged_inv] params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30, sigma0=np.asarray(sigma0)) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign(exclude_00=True) path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy = path_plot.evaluate_path() x_axis = path_plot.rot_path.stack_x_axes() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_inv = path_plot_inv.evaluate_path() labels = [rf'$\eta={s0/sigma_tilde}$' for s0 in sigma0] fig, ax = plt.subplots() for d, d_inv, en, en_inv, label, c in zip(ic_data, ic_data_inv, energy.T, energy_inv.T, labels, COLORS): ax.plot(d[:, 0], d[:, 1], label=label, c=c) ax.plot(d_inv[:, 0], d_inv[:, 1], c=c) ax.plot(x_axis, en, ls='--', c=c) ax.plot(x_axis, en_inv, ls='--', c=c) DipolePath3.plot_style(fig, ax) if save_as is not None: plt.savefig(save_as, dpi=300) plt.show() def combined_all(save_as=None): sigma_tilde = 0.00099 kappaR_list = [1, 3, 10] abar_list = [0.5, 0.4, 0.3] sigma0_list = [-0.000198, 0.00, 0.000198] kappaR = 3 abar = 0.5 em_data_kappaR = (ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_C") .joinpath("FIX_A").joinpath(f"ECC_{np.round(abar / 2, 4)}")) ic_data_kappaR = [] ic_data_kappaR_inv = [] for kR in kappaR_list: em_data = np.load(em_data_kappaR.joinpath(f"EMME_{kR}.").joinpath("pathway.npz"))['arr_0'] em_data, em_data_inv = em_data[:int(len(em_data) / 2)], em_data[int(len(em_data) / 2):] ic_data_kappaR.append(em_data) ic_data_kappaR_inv.append(em_data_inv) params = ModelParams(R=150, kappaR=np.asarray(kappaR_list)) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign(exclude_00=True) path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=0) energy_kappaR = path_plot.evaluate_path() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=0) energy_kappaR_inv = path_plot_inv.evaluate_path() x_axis_kappaR = path_plot.rot_path.stack_x_axes() labels_kappaR = [rf'$\kappa R={kR}$' for kR in [1, 3, 10]] em_data_abar = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_B").joinpath("FIX_M") ic_data_abar = [] ic_data_abar_inv = [] for ab in abar_list: em_data = np.load( em_data_abar.joinpath(f"ECC_{np.round(ab / 2, 4)}").joinpath(f"EMME_{kappaR}.").joinpath("pathway.npz"))[ 'arr_0'] em_data, em_data_inv = em_data[:int(len(em_data) / 2)], em_data[int(len(em_data) / 2):] ic_data_abar.append(em_data) ic_data_abar_inv.append(em_data_inv) params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(np.asarray(abar_list), params.kappaR, sigma_tilde, l_max=30) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign(exclude_00=True) path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_abar = path_plot.evaluate_path() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_abar_inv = path_plot_inv.evaluate_path() x_axis_abar = path_plot.rot_path.stack_x_axes() labels_abar = [rf'$\bar a={a}$' for a in abar_list] em_data_charge = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_D").joinpath("CHANGE_ZC") undercharged = np.load(em_data_charge.joinpath("ZC_-56").joinpath("pathway.npz"))['arr_0'] overcharged = np.load(em_data_charge.joinpath("ZC_56").joinpath("pathway.npz"))['arr_0'] neutral_path = ICI_DATA_PATH.joinpath("FIG_5_JANUS").joinpath("FIG_5_JANUS_B").joinpath("FIX_M") neutral = np.load( neutral_path.joinpath(f"ECC_{np.round(abar / 2, 4)}").joinpath(f"EMME_{int(kappaR)}.").joinpath("pathway.npz"))[ 'arr_0'] undercharged, undercharged_inv = undercharged[:int(len(undercharged) / 2)], undercharged[ int(len(undercharged) / 2):] overcharged, overcharged_inv = overcharged[:int(len(overcharged) / 2)], overcharged[int(len(overcharged) / 2):] neutral, neutral_inv = neutral[:int(len(neutral) / 2)], neutral[int(len(neutral) / 2):] ic_data_sigma0 = [undercharged, neutral, overcharged] ic_data_sigma0_inv = [undercharged_inv, neutral_inv, overcharged_inv] params = ModelParams(R=150, kappaR=kappaR) ex1 = charge_distributions.create_mapped_dipolar_expansion(abar, params.kappaR, sigma_tilde, l_max=30, sigma0=np.asarray(sigma0_list)) ex2 = ex1.clone() ex3 = ex1.clone().inverse_sign(exclude_00=True) path_plot = PathEnergyPlot(ex1, ex2, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_sigma0 = path_plot.evaluate_path() path_plot_inv = PathEnergyPlot(ex1, ex3, DipolePath3, dist=2., params=params, match_expansion_axis_to_params=None) energy_sigma0_inv = path_plot_inv.evaluate_path() x_axis_sigma0 = path_plot.rot_path.stack_x_axes() labels_sigma0 = [rf'$\eta={s0/sigma_tilde:.1f}$' for s0 in sigma0_list] # fig, axs = plt.subplots(3, 1, figsize=(6, 7.8)) fig = plt.figure(figsize=(4, 3.6)) gs = gridspec.GridSpec(2, 1, figure=fig) # gs.update(left=0.12, right=0.975, top=0.96, bottom=0.04, hspace=0.3) gs.update(left=0.12, right=0.975, top=0.94, bottom=0.06, hspace=0.3) # axs = [fig.add_subplot(gs[0, 0]), fig.add_subplot(gs[1, 0]), fig.add_subplot(gs[2, 0])] axs = [fig.add_subplot(gs[0, 0]), fig.add_subplot(gs[1, 0])] for d, d_inv, en, en_inv, label, c in zip(ic_data_kappaR, ic_data_kappaR_inv, energy_kappaR.T, energy_kappaR_inv.T, labels_kappaR, COLOR_LIST): axs[0].set_title('Screening', fontsize=11, y=0.98) axs[0].plot(d[:, 0], d[:, 1], label=label, c=c) axs[0].plot(x_axis_kappaR, en, ls='--', c=c) axs[0].plot(d_inv[:, 0], d_inv[:, 1], c=c) axs[0].plot(x_axis_kappaR, en_inv, ls='--', c=c) DipolePath3.plot_style(fig, axs[0], size=None) axs[0].get_legend().set_bbox_to_anchor((0.65, 1.03)) # for d, d_inv, en, en_inv, label, c in zip(ic_data_abar, ic_data_abar_inv, energy_abar.T, energy_abar_inv.T, labels_abar, COLOR_LIST): # axs[1].set_title('Eccentricity', fontsize=11, y=0.98) # axs[1].plot(d[:, 0], d[:, 1], label=label, c=c) # axs[1].plot(x_axis_abar, en, ls='--', c=c) # axs[1].plot(d_inv[:, 0], d_inv[:, 1], c=c) # axs[1].plot(x_axis_abar, en_inv, ls='--', c=c) # DipolePath3.plot_style(fig, axs[1], size=None) # axs[1].get_legend().set_bbox_to_anchor((0.65, 1.02)) for d, d_inv, en, en_inv, label, c in reversed(list(zip(ic_data_sigma0, ic_data_sigma0_inv, energy_sigma0.T, energy_sigma0_inv.T, labels_sigma0, COLOR_LIST[:3][::-1]))): axs[1].set_title('Net charge', fontsize=11, y=0.98) axs[1].plot(d[:, 0], d[:, 1], label=label, c=c) axs[1].plot(x_axis_sigma0, en, ls='--', c=c) axs[1].plot(d_inv[:, 0], d_inv[:, 1], c=c) axs[1].plot(x_axis_sigma0, en_inv, ls='--', c=c) DipolePath3.plot_style(fig, axs[1], size=None) axs[1].get_legend().set_bbox_to_anchor((0.65, 1.02)) for ax in axs: ax.yaxis.set_label_coords(-0.08, 0.5) # axs[-1].set_xlabel('rotational path', fontsize=15) # plt.tight_layout() if save_as is not None: plt.savefig(save_as, dpi=300) plt.show() if __name__ == '__main__': # sections_plot(save_as=Path("/home/andraz/ChargedShells/Figures/dipole_test_path.png")) # kappaR_dependence(np.array([3, 5]), 0.5, # # save_as=Path("/home/andraz/ChargedShells/Figures/quadrupole_kappaR_dep.png") # ) # abar_dependence(np.array([0.3, 0.4, 0.5]), 3, # save_as=Path("/home/andraz/ChargedShells/Figures/quadrupole_abar_dep.png") # ) # sigma0_dependence(np.array([-0.0002, 0.00, 0.0002]), 3, 0.5, # save_as=Path("/home/andraz/ChargedShells/Figures/quadrupole_charge_dep_abar05_kappaR3.png") # ) # model_comparison( # # save_as=FIGURES_PATH.joinpath("ICi_data").joinpath('IC_CS_janus_path.pdf') # ) # combined_kappaR_dependence(kappaR=[1, 3, 10], abar=0.5, # # save_as=FIGURES_PATH.joinpath("final_figures").joinpath('janus_kappaR_dep.png') # ) # # combined_abar_dependence(kappaR=3, abar=[0.3, 0.4, 0.5], # # save_as=FIGURES_PATH.joinpath("final_figures").joinpath('janus_abar_dep.png') # ) # # combined_sigma0_dependence( # # save_as=FIGURES_PATH.joinpath("final_figures").joinpath('janus_charge_dep.png') # ) # combined_all( # save_as=FIGURES_PATH.joinpath("final_figures").joinpath('janus_combined_dep.png') )