import os import pandas as pd import matplotlib as mpl import numpy as np import matplotlib.pyplot as plt from spec_functions import find_marker,norm_spectra,norm_spectra_c1,baseline_correction,calculate_mol_spectra,calc_k,id_spectra,part_specs,SlicedRamanshift,voigt_paras,pseudo_voigt from thermo_functions import Calculate_gamma,GibbsExcess from matplotlib.ticker import MultipleLocator from matplotlib.lines import Line2D import matplotlib.gridspec as gridspec basepoints_dict = { 'Acetone-Cyclohexane' : [660,1900, 2150,2400,3900], 'Acetone-Water' : [660,1900,2150, 2400, 3900], 'Acetone-Acetic acid' : [660,1900,2150,2400,3900], 'Acetone-ACN' : [660,1900,2150,2400, 3900], } # all datapaths have to be adjusted so that they match your directroy base_path='Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA' foldernames=os.listdir(base_path) ramanshift=np.loadtxt('Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/ramanshift.txt') rs=np.loadtxt('Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/rs.txt') preprocessed_data_path = 'Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/data_spec-pkl' voigt_data_path = 'Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/data_spec_voigt.pkl' #data_show_path = 'Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/data_spec_show.pkl' pure_voigt_data_path='Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/pure_paras.pkl' rs_start=575 # wavenumber where spectrum starts idx_start= int((np.abs(ramanshift - rs_start)).argmin()) rs_end=3800 # wavenumber where spectrum ends idx_end = int((np.abs(ramanshift - rs_end)).argmin()) read_all_mixtures=False fit_voigt=False slicestart=[1590,3189] sliceend=[2500,rs_end] idx_slicestart=np.zeros_like(slicestart) idx_sliceend=np.zeros_like(slicestart) for i in range(len(slicestart)): idx_slicestart[i]=np.argmin(np.abs(rs-slicestart[i])) idx_sliceend[i]=np.argmin(np.abs(rs-sliceend[i])) if os.path.isfile(preprocessed_data_path) and not read_all_mixtures : data_spec=pd.read_pickle(preprocessed_data_path) data_exist=True else: data_exist=False #%% read spectra from txt files\ real compositions from excel files data_spec_list = [] if read_all_mixtures or data_exist==False: for foldername in foldernames: if (os.path.isdir(foldername)) and (not foldername=='__pycache__'): raw_folder = os.path.join(base_path, foldername.replace("-", "_")) if not os.path.isdir(raw_folder): continue filenames = os.listdir(raw_folder) if len(filenames) == 0: continue x1_list = [] compound_1 = [] compound_2 = [] mixture = [] spectra = np.empty([len(filenames), 1043]) for i, filename in enumerate(filenames): fpath = os.path.join(raw_folder, filename) with open(fpath, "r", encoding="utf-8", errors="ignore") as f: first_line = f.readline().strip() x1_val = float(first_line) x1_list.append(x1_val) df = pd.read_csv(f, header=None, delimiter=r"\s+") spectra[i,:] = df.iloc[:-1,1].to_numpy() mixture_name_raw = foldername.replace("_data_raw", "") parts = mixture_name_raw.split("_", 1) compound_1_val = parts[0] compound_2_val = parts[1].replace("_", " ") if len(parts) > 1 else "" mixture_name = f"{compound_1_val}-{compound_2_val}" compound_1.append(compound_1_val) compound_2.append(compound_2_val) mixture.append(mixture_name) dict_data_spec = { 'Mixture': mixture, 'compound_1': compound_1, 'compound_2': compound_2, 'x1': x1_list, 'spectra': list(spectra) } data_spec = pd.DataFrame(dict_data_spec) data_spec['T'] = 298.15 # Ramanshift-Indizes idx_start = int((np.abs(ramanshift - rs_start)).argmin()) idx_end = int((np.abs(ramanshift - rs_end)).argmin()) data_spec['ramanshift'] = pd.Series([ramanshift]*len(data_spec)) data_spec['ramanshift_sliced'] = data_spec['ramanshift'].apply(SlicedRamanshift, idx_start=idx_start, idx_end=idx_end) data_spec = data_spec.sort_values(by=['x1']).reset_index(drop=True) mixturename = data_spec['Mixture'].iloc[0] basepoints = np.array(basepoints_dict[mixturename]) data_spec['spectra_bc'] = data_spec['spectra'].apply(baseline_correction, ramanshift=ramanshift, basepoints=basepoints) # Methode A data_spec[['spectra_norm_c1','J']] = norm_spectra_c1(data_spec['spectra_bc'], ramanshift, idx_start, idx_end) data_spec['spectra_norm_c1_id'] = id_spectra(data_spec['x1'], data_spec['spectra_norm_c1']) data_spec['spectra_norm_c1_ex'] = data_spec['spectra_norm_c1'] - data_spec['spectra_norm_c1_id'] # Methode B data_spec['spectra_norm'] = data_spec['spectra_bc'].apply(norm_spectra, ramanshift=ramanshift, idx_start=idx_start, idx_end=idx_end) data_spec[['spectra_id_norm','k']] = calc_k(ramanshift, data_spec['spectra_norm'], data_spec['x1'], idx_start, idx_end) data_spec['spectra_mol'] = calculate_mol_spectra(data_spec['x1'], data_spec['k'], data_spec['spectra_norm']) data_spec['I'] = (data_spec['x1'] + (1 - data_spec['x1']) * data_spec['k']) data_spec['spectra_mol_id'] = id_spectra(data_spec['x1'], data_spec['spectra_mol']) data_spec['spectra_mol_ex'] = data_spec['spectra_mol'] - data_spec['spectra_mol_id'] # Partial spectra data_spec[['spectra_ex_part_c1','spectra_ex_part_c2']] = part_specs(data_spec['spectra_mol_ex'], data_spec['x1']) data_spec[['spectra_part_c1','spectra_part_c2']] = part_specs(data_spec['spectra_mol'], data_spec['x1']) # Thermodynamics NRTL_paras_all={'Acetone-Cyclohexane':[5957.1,12049.7,-12363,-42410.6,337.8,4950.4,0.4212], 'Acetone-Water':[3489.3,-13165.1,3477.2,73040.1,-1582.2,-5699.4,0.5466], 'Acetone-ACN':[1.84173,-373.389,-55.8721,1299.95,1088.62,-855.896,0.3], 'Acetone-Acetic acid':[-841.993,210.766,2178.95,1798.66,0,0,0.3]} NRTL_paras = np.array(NRTL_paras_all[mixturename][:-1]) alpha=NRTL_paras_all[mixturename][-1] data_spec = pd.concat([data_spec,Calculate_gamma(298.15,data_spec['x1'],NRTL_paras,alpha)],axis=1) data_spec['gibbs_excess'] = GibbsExcess(data_spec['gamma_1'], data_spec['gamma_2'], data_spec['x1'], data_spec['T']) # Daten speichern if not data_exist: data_spec.to_pickle(preprocessed_data_path) data_exist = True else: data_old = pd.read_pickle(preprocessed_data_path) data_spec = pd.concat([data_old, data_spec]) data_spec.to_pickle(preprocessed_data_path) data_spec = data_spec.reset_index(drop=True) data_spec = data_spec[data_spec['Mixture'] != 'Acetone-Ethanol'] data_spec.to_pickle(preprocessed_data_path) #%% #general settings for plotting plt.rcParams.update({ #"text.usetex": True, 'font.size':'12' }) #%% Fit of voigt profiles # peakcenters that shall be excluded in mixture fit fit_dict_c1={'Acetone-Acetic acid':[900,1570,1750,2730,2855,3082],#1750, 'Acetone-Cyclohexane':[900,1550,1750,2730,2855,3082], 'Acetone-Water':[900,1550,1750,2730,2855,3082], 'Acetone-ACN':[900,1550,1750,2730,2855,3082]} fit_dict_c2={'Acetone-Acetic acid':[1515,2623], 'Acetone-Cyclohexane':[1100,2458,2575,2606,2805,2970,3014],#1348, 'Acetone-Water':[], 'Acetone-ACN':[3100]} voigt_mix_path = 'Y:\Publications\ITUN journal publications\Industrial and Chemical Engineering Research\Miriam 2025\OpARA/voigt.pkl' if os.path.isfile(voigt_mix_path): old_voigt_frame=pd.read_pickle(voigt_mix_path) first=False else: first=True mixtures=data_spec.groupby(['Mixture']) n_mix=mixtures.ngroups fp_start = rs[0] fp_end = 1900 CH_OH_start = 2550 CH_OH_end = rs[-1] idx_fp_start = np.argmin(np.abs(rs - fp_start)) idx_fp_end = np.argmin(np.abs(rs - fp_end)) idx_CH_OH_start = np.argmin(np.abs(rs - CH_OH_start)) idx_CH_OH_end = np.argmin(np.abs(rs - CH_OH_end)) mult_fact=4 i=0 for mixturename, mixture in mixtures: mixture=mixture.reset_index(drop=True) colors=plt.get_cmap('jet', 101) peaks_fixed_c1= np.array(fit_dict_c1[mixturename]) peaks_fixed_c2= np.array(fit_dict_c2[mixturename]) if first==False: if mixturename not in old_voigt_frame['Mixture'].values: print(mixturename) voigt_frame=voigt_paras(mixture['spectra_mol'],rs,mixture['x1'],peaks_fixed_c1,peaks_fixed_c2) voigt_frame_complete_new=mixture.join(voigt_frame) comp_frame=pd.concat([old_voigt_frame,voigt_frame_complete_new]) comp_frame.to_pickle(voigt_mix_path) old_voigt_frame=comp_frame else: print(mixturename) voigt_frame=voigt_paras(mixture['spectra_mol'],rs,mixture['x1'],peaks_fixed_c1,peaks_fixed_c2) voigt_frame_complete_new=mixture.join(voigt_frame) voigt_frame_complete_new.to_pickle(voigt_mix_path) old_voigt_frame=voigt_frame_complete_new first=False data_voigt=pd.read_pickle(voigt_mix_path) #%% Figure 1 mixtures=data_spec.groupby(['Mixture']) plot=True if plot==True: plt.rcParams.update({ #"text.usetex": True, 'font.size':'22' }) mult_fact=4 for mixturename, mixture in mixtures: mixture = mixture.reset_index(drop=True) fig, axes = plt.subplots(1, 2, sharey=True, figsize=(10, 8))#, figsize=(20, 15) fig.subplots_adjust(left=0.12,right=0.93, wspace=0.02) ax1_left, ax1_right, = axes # Achsen zuweisen for j in range(len(mixture)): c = mixture['x1'].iloc[j] * 100 ax1_left.plot(rs[:idx_fp_end], mult_fact * mixture['spectra_mol'].iloc[j][:idx_fp_end], color=colors(int(c))) ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol'].iloc[j][idx_CH_OH_start:], color=colors(int(c))) # X-Limits setzen ax1_left.set_xlim(rs[0], fp_end) ax1_right.set_xlim(CH_OH_start, rs[-1]) norm = mpl.colors.Normalize(vmin=0,vmax=1) sm = plt.cm.ScalarMappable(cmap=colors, norm=norm) sm.set_array([]) cbar=plt.colorbar(sm, ticks=np.linspace(0,1,11), boundaries=np.arange(0,1,0.05)) comp_1=mixture['compound_1'].iloc[0] cbar.set_label(f'x$_\mathregular{{{comp_1}}}$') # Achsenstile anpassen (gebrochene x-Achse) for ax_left, ax_right in [(ax1_left, ax1_right)]: ax_left.spines.right.set_visible(False) ax_right.spines.left.set_visible(False) ax_left.yaxis.tick_left() ax_right.yaxis.tick_right() ax_right.tick_params(labelleft=False) # Labels nur links # Schrägstriche einfügen, um den Bruch zu visualisieren d = .015 # Neigung der Trennlinie kwargs = dict(transform=ax_left.transAxes, color='k', clip_on=False) ax_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax_right.transAxes) ax_right.plot((-d, +d), (-d, +d), **kwargs) ax_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax_left.text(0.95, 0.9, f"x {mult_fact}", transform=ax_left.transAxes, verticalalignment='top', horizontalalignment='right') ax_right.text(0.95, 0.9, "x 1", transform=ax_right.transAxes, verticalalignment='top', horizontalalignment='right') # Labels setzen ax1_left.set_ylabel("Intensity") fig.text(0.5, 0.03, "Raman shift / $cm^{-1}$", ha='center', va='center') plt.show() #%% Figure 2 mixtures=data_spec.groupby(['Mixture']) plot=True if plot==True: plt.rcParams.update({ #"text.usetex": True, 'font.size':'26' }) mult_fact=3 show_mixtures=['Acetone-Cyclohexane','Acetone-Acetic acid']#, fig, axes = plt.subplots(len(show_mixtures),2, sharey=True, figsize=(12, 15))#, figsize=(20, 15) fig.subplots_adjust(left=0.16,right=0.93,top=0.97,bottom=0.1, wspace=0.02,hspace=0.1) i=0 for mixturename, mixture in mixtures: if mixturename in show_mixtures: mixture = mixture.reset_index(drop=True) ax1_left, ax1_right, = axes[i,:] # Achsen zuweisen for j in range(len(mixture)): c = mixture['x1'].iloc[j] * 100 ax1_left.plot(rs[:idx_fp_end], mult_fact * mixture['spectra_mol_ex'].iloc[j][:idx_fp_end], color=colors(int(c))) ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol_ex'].iloc[j][idx_CH_OH_start:], color=colors(int(c))) # X-Limits setzen ax1_left.set_xlim(rs[0], fp_end) ax1_right.set_xlim(CH_OH_start, rs[-1]) # Achsenstile anpassen (gebrochene x-Achse) for ax_left, ax_right in [(ax1_left, ax1_right)]: ax_left.spines.right.set_visible(False) ax_right.spines.left.set_visible(False) ax_left.yaxis.tick_left() ax_right.yaxis.tick_right() ax_right.tick_params(labelleft=False) # Labels nur links # Schrägstriche einfügen, um den Bruch zu visualisieren d = .015 # Neigung der Trennlinie kwargs = dict(transform=ax_left.transAxes, color='k', clip_on=False) ax_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax_right.transAxes) ax_right.plot((-d, +d), (-d, +d), **kwargs) ax_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax_left.text(0.95, 0.9, f"x {mult_fact}", transform=ax_left.transAxes, verticalalignment='top', horizontalalignment='right') ax_right.text(0.95, 0.9, "x 1", transform=ax_right.transAxes, verticalalignment='top', horizontalalignment='right') ax1_left.set_ylabel("Intensity") fig.text(0.5, 0.05, "Raman shift / $cm^{-1}$", ha='center', va='center',) y_min=-0.005 y_max=0.005 ax1_left.set_ylim(y_min,y_max) ax1_right.set_ylim(y_min,y_max) i+=1 axes[0,0].text(0.05, 0.95, "a)", transform=axes[0,0].transAxes, fontsize=22, verticalalignment='top', horizontalalignment='left') axes[1,0].text(0.05, 0.95, "b)", transform=axes[1,0].transAxes, fontsize=22, verticalalignment='top', horizontalalignment='left') norm = mpl.colors.Normalize(vmin=0,vmax=1) sm = plt.cm.ScalarMappable(cmap=colors, norm=norm) sm.set_array([]) #cbar=plt.colorbar(sm, ticks=np.linspace(0,1,11), #boundaries=np.arange(0,1,0.05)) cbar = fig.colorbar(sm, ax=axes.ravel().tolist(), location='right', shrink=0.95) comp_1=mixture['compound_1'].iloc[0] cbar.set_label(f'x$_\mathregular{{{comp_1}}}$') plt.show() #%% Figure 3 mixtures=data_spec.groupby(['Mixture']) plot=True if plot==True: plt.rcParams.update({ #"text.usetex": True, 'font.size':'26' }) mult_fact=3 show_mixtures=['Acetone-Water']#,'Acetone-Acetic acid' fig, axes = plt.subplots(2,2, sharey=True, figsize=(12, 15))#, figsize=(20, 15) fig.subplots_adjust(left=0.16,right=0.93,top=0.97,bottom=0.1, wspace=0.02,hspace=0.1) for mixturename, mixture in mixtures: if mixturename in show_mixtures: mixture = mixture.reset_index(drop=True) ax1_left, ax1_right, ax2_left, ax2_right= axes[0,0],axes[0,1],axes[1,0],axes[1,1] # Achsen zuweisen for j in range(len(mixture)): c = mixture['x1'].iloc[j] * 100 ax1_left.plot(rs[:idx_fp_end], mult_fact * mixture['spectra_ex_part_c1'].iloc[j][:idx_fp_end], color=colors(int(c))) ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_ex_part_c1'].iloc[j][idx_CH_OH_start:], color=colors(int(c))) ax2_left.plot(rs[:idx_fp_end], mult_fact * mixture['spectra_ex_part_c2'].iloc[j][:idx_fp_end], color=colors(int(c))) ax2_right.plot(rs[idx_CH_OH_start:], mixture['spectra_ex_part_c2'].iloc[j][idx_CH_OH_start:], color=colors(int(c))) # X-Limits setzen ax1_left.set_xlim(rs[0], fp_end) ax1_right.set_xlim(CH_OH_start, rs[-1]) ax2_left.set_xlim(rs[0], fp_end) ax2_right.set_xlim(CH_OH_start, rs[-1]) # Achsenstile anpassen (gebrochene x-Achse) for ax_left, ax_right in [(ax1_left, ax1_right)]: ax_left.spines.right.set_visible(False) ax_right.spines.left.set_visible(False) ax_left.yaxis.tick_left() ax_right.yaxis.tick_right() ax_right.tick_params(labelleft=False) # Labels nur links # Schrägstriche einfügen, um den Bruch zu visualisieren d = .015 # Neigung der Trennlinie kwargs = dict(transform=ax_left.transAxes, color='k', clip_on=False) ax_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax_right.transAxes) ax_right.plot((-d, +d), (-d, +d), **kwargs) ax_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) for ax_left, ax_right in [(ax2_left, ax2_right)]: ax_left.spines.right.set_visible(False) ax_right.spines.left.set_visible(False) ax_left.yaxis.tick_left() ax_right.yaxis.tick_right() ax_right.tick_params(labelleft=False) # Labels nur links # Schrägstriche einfügen, um den Bruch zu visualisieren d = .015 # Neigung der Trennlinie kwargs = dict(transform=ax_left.transAxes, color='k', clip_on=False) ax_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax_right.transAxes) ax_right.plot((-d, +d), (-d, +d), **kwargs) ax_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax1_left.text(0.95, 0.9, f"x {mult_fact}", transform=ax1_left.transAxes, verticalalignment='top', horizontalalignment='right') ax1_right.text(0.95, 0.9, "x 1", transform=ax1_right.transAxes, verticalalignment='top', horizontalalignment='right') ax1_left.set_ylabel("Intensity") ax2_left.text(0.95, 0.9, f"x {mult_fact}", transform=ax2_left.transAxes, verticalalignment='top', horizontalalignment='right') ax2_right.text(0.95, 0.9, "x 1", transform=ax2_right.transAxes, verticalalignment='top', horizontalalignment='right') ax2_left.set_ylabel("Intensity") fig.text(0.5, 0.05, "Raman shift / $cm^{-1}$", ha='center', va='center',) y_min=-0.02 y_max=0.02 ax1_left.set_ylim(y_min,y_max) ax1_right.set_ylim(y_min,y_max) ax2_left.set_ylim(y_min,y_max) ax2_right.set_ylim(y_min,y_max) i+=1 axes[0,0].text(0.05, 0.95, "a)", transform=axes[0,0].transAxes, fontsize=22, verticalalignment='top', horizontalalignment='left') axes[1,0].text(0.05, 0.95, "b)", transform=axes[1,0].transAxes, fontsize=22, verticalalignment='top', horizontalalignment='left') norm = mpl.colors.Normalize(vmin=0,vmax=1) sm = plt.cm.ScalarMappable(cmap=colors, norm=norm) sm.set_array([]) #cbar=plt.colorbar(sm, ticks=np.linspace(0,1,11), #boundaries=np.arange(0,1,0.05)) cbar = fig.colorbar(sm, ax=axes.ravel().tolist(), location='right', shrink=0.95) comp_1=mixture['compound_1'].iloc[0] cbar.set_label(f'x$_\mathregular{{{comp_1}}}$') plt.show() #%% Figure 4+5 plot=True mixtures=data_spec.groupby(['Mixture']) if plot==True: plt.rcParams.update({'font.size': '17'}) fig, ax1 = plt.subplots(figsize=(11, 11)) fig.subplots_adjust(left=0.2,right=0.77,bottom=0.15) ax2 = ax1.twinx() for mixturename, mixture in mixtures: marker, color = find_marker(mixturename) ax1.plot(mixture['x1'],mixture['gibbs_excess'],color=color) ax2.scatter(mixture['x1'],np.sum(np.abs(np.vstack(np.array(mixture['spectra_mol_ex']))),axis=1),marker=marker,color=color,label=mixturename) mL, ML = ax1.get_ylim() mR, MR = ax2.get_ylim() wL = abs(mL)/(ML+abs(mL)) wR = abs(mR)/(MR+abs(mR)) MR = (mR*ML/mL if wL<=wR else MR ) mR = (mR if wL<=wR else MR*mL/ML) ratio=np.abs(ML-mL)/(MR-mR) fac=0.25 ax1.set_ylim(mL,ML+ML*fac) ax2.set_ylim(mR,MR+ML*fac/ratio) ax1.set_xlabel('$x_1$') ax1.set_ylabel('$g^E$/ kJ / mol') ax2.set_ylabel(r"$\left|I^E\right|$") #ax2.legend(loc='upper right', frameon=True, framealpha=0.8) markerslist=['o','D'] legend_elements = [ Line2D([0], [0], linestyle='-', color='black', label='$g^E$'), Line2D([0], [0], marker='o', color='w',markersize=10, markerfacecolor='w',label=r"$\left|I^E\right|$"), Line2D([0], [0], marker='o', color='w',markersize=10, markerfacecolor='w',label=''), Line2D([0], [0], marker='o', color='w',markersize=10, markerfacecolor='w',label='')] for mixturename, (marker, color) in zip([m[0] for m in mixtures], [find_marker(m[0]) for m in mixtures]): legend_elements.append(Line2D([0], [0], marker=marker, color='w', markersize=10, markerfacecolor=color, label=mixturename if mixturename !="Acetone-ACN" else "Acetone-Acetonitrile" )) ax2.legend(handles=legend_elements, loc='upper center',framealpha=0.8, ncol=2,frameon=False) ax1.set_xlim(0,1) ax2.set_xlim(0,1) fig, ax1 = plt.subplots(figsize=(11, 7)) fig.subplots_adjust(left=0.2,right=0.77,bottom=0.15) ax2 = ax1.twinx() for mixturename, mixture in mixtures: marker, color = find_marker(mixturename) ax1.plot(mixture['x1'],np.log(mixture['gamma_1']),color=color) ax1.plot(mixture['x1'],np.log(mixture['gamma_2']),color=color) ax2.scatter(mixture['x1'],np.sum(np.abs(np.vstack(np.array(mixture['spectra_ex_part_c1']))),axis=1),marker=marker,color=color,label=mixturename) ax2.scatter(mixture['x1'],np.sum(np.abs(np.vstack(np.array(mixture['spectra_ex_part_c2']))),axis=1),marker=marker,color=color,label=mixturename) mL, ML = ax1.get_ylim() mR, MR = ax2.get_ylim() wL = abs(mL)/(ML+abs(mL)) wR = abs(mR)/(MR+abs(mR)) ML = (mL*MR/mR if wR<=wL else ML ) mL = (mL if wR<=wL else ML*mR/MR) ax1.set_ylim(mL,6.2) ax2.set_ylim(mR,0.51) #ax2.set_ylim(mR,MR) ax1.set_xlim(0,1) ax2.set_xlim(0,1) ax1.set_xlabel('$x_1$') ax1.set_ylabel('ln($\gamma_i$)') ax2.set_ylabel(r"$\left|\bar{I}_i^{\ E}\right|$") legend_elements = [ Line2D([0], [0], linestyle='-', color='black', label='ln($\gamma_i$)'), Line2D([0], [0], marker='D', color='w',markersize=10, markerfacecolor='w',label=r"$\left|\bar{I}_i^{\ E}\right|$"), Line2D([0], [0], marker='o', color='w',markersize=10, markerfacecolor='w',label=''), Line2D([0], [0], marker='o', color='w',markersize=10, markerfacecolor='w',label='')] for mixturename, (marker, color) in zip([m[0] for m in mixtures], [find_marker(m[0]) for m in mixtures]): legend_elements.append(Line2D([0], [0], marker=marker, color='w', markersize=10, markerfacecolor=color, label=mixturename)) ax2.legend(handles=legend_elements, loc='upper center', framealpha=0.8, ncol=2,frameon=False) #%% Figure 6 mixtures=data_voigt.groupby(['Mixture']) plot=True if plot==True: for mixturename,mixture in mixtures: plt.rcParams.update({'font.size': '14'}) fp_start = rs[0] fp_end = 1900 CH_OH_start = 2550 CH_OH_end = rs[-1] idx_fp_start = np.argmin(np.abs(rs - fp_start)) idx_fp_end = np.argmin(np.abs(rs - fp_end)) idx_CH_OH_start = np.argmin(np.abs(rs - CH_OH_start)) idx_CH_OH_end = np.argmin(np.abs(rs - CH_OH_end)) fig, axes = plt.subplots(1,2, sharey=True, figsize=(6, 5)) fig.subplots_adjust(left=0.15,right=0.97, wspace=0.02) """ compound 1""" ax1_left, ax1_right, = axes[0],axes[1] ax1_left.plot(rs[:idx_fp_end],mult_fact *mixture['spectra_mol'].iloc[-1][:idx_fp_end],color='k',label='spectrum') ax1_left.plot(rs[:idx_fp_end],mult_fact *mixture['voigt_fit'].iloc[-1][:idx_fp_end],color='k',linestyle='dashed',label='voigt fit') ax1_left.plot(rs[:idx_fp_end],mult_fact *(mixture['spectra_mol'].iloc[-1][:idx_fp_end]-mixture['voigt_fit'].iloc[-1][:idx_fp_end]),color='b',label='error') ax1_left.legend(handlelength=1,loc='upper right', frameon=False) ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol'].iloc[-1][idx_CH_OH_start:],color='k') ax1_right.plot(rs[idx_CH_OH_start:], mixture['voigt_fit'].iloc[-1][idx_CH_OH_start:],color='k',linestyle='dashed') ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol'].iloc[-1][idx_CH_OH_start:]-mixture['voigt_fit'].iloc[-1][idx_CH_OH_start:],color='b') first_fixed=True first=True for i in range(len(mixture['paras_c1'].iloc[-1][0][:,0])): single_peak=pseudo_voigt(rs,mixture['paras_c1'].iloc[-1][0][i,:],1) if mixture['fitted_c1'].iloc[i]=='True': ax1_left.plot(rs[:idx_fp_end], mult_fact * single_peak[:idx_fp_end],color='dimgrey',linestyle='dashed') if first==True: first=False ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='dimgrey',linestyle='dashed',label='fitted') else: ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='dimgrey',linestyle='dashed') else: if first_fixed==True: first_fixed=False ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='r',linestyle='dashed',label='fixed') else: ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='r',linestyle='dashed') ax1_left.plot(rs[:idx_fp_end], mult_fact * single_peak[:idx_fp_end],color='r',linestyle='dashed') ax1_left.set_xlim(rs[0], fp_end) ax1_left.set_ylabel('Intensity') ax1_right.set_xlim(CH_OH_start, rs[-1]) for ax_left, ax_right in [(ax1_left, ax1_right)]: ax_left.spines.right.set_visible(False) ax_right.spines.left.set_visible(False) ax_left.yaxis.tick_left() ax_right.yaxis.tick_right() ax_right.tick_params(labelleft=False) d = .015 kwargs = dict(transform=ax_left.transAxes, color='k', clip_on=False) ax_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax_right.transAxes) ax_right.plot((-d, +d), (-d, +d), **kwargs) ax_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax_left.text(0.95, 0.5, f"x {mult_fact}", transform=ax_left.transAxes, verticalalignment='top', horizontalalignment='right') ax_right.text(0.95, 0.5, "x 1", transform=ax_right.transAxes, verticalalignment='top', horizontalalignment='right') ax1_left.yaxis.set_major_locator(MultipleLocator(0.01)) fig.text(0.5, 0.03, "Raman shift / $cm^{-1}$", ha='center', va='center') ax1_right.legend(handlelength=1,loc='upper right',frameon=False) plt.show() #%% Figure 7 """ Plot for peakcenters compound 1 """ mixtures=data_voigt.groupby(['Mixture']) plot==True if plot==True: plt.rcParams.update({'font.size': '15'}) visible_ranges = [(3000, 3021), (2955, 2985), (2913, 2937), (1695, 1725), (1425, 1440.5), (1350, 1379), (1217, 1245), (1062, 1082), (770, 805)] legend_range = (visible_ranges[0][1], visible_ranges[0][1] + 0.63) visible_ranges.insert(0, legend_range) fig, axes = plt.subplots(len(visible_ranges), 1, sharex=True, figsize=(6, 18), gridspec_kw={'hspace': 0.05}) fig.subplots_adjust(left=0.14,right=0.93,top=0.99,bottom=0.08) legend_handles=[] for mixturename, mixture in mixtures: marker, color = find_marker(mixturename) x1 = np.array(mixture['x1']) centers_list_c1 = np.vstack(np.array(mixture['paras_c1'])).astype(np.float64)[:, :, 1] if mixturename !='Acetone-ACN': line =Line2D(x1, centers_list_c1[:, 2], linestyle='--', color=color, label=mixturename) else: line =Line2D(x1, centers_list_c1[:, 2], linestyle='--', color=color, label='Acetone-Acetonitrile' ) legend_handles.append(line) # Speichern des Handles for ax, (ymin, ymax) in zip(axes, visible_ranges): print(ymin) for i in range(len(centers_list_c1[0, :])): if not len(set(centers_list_c1[:, i])) == 1: if i==0: if mixturename !='Acetone-ACN': ax.plot(x1, centers_list_c1[:, i],linestyle='--',marker=marker, color=color,label=mixturename ) else: ax.plot(x1, centers_list_c1[:, i],linestyle='--',marker=marker, color=color,label='Acetone-Acetonitrile' ) else: ax.plot(x1, centers_list_c1[:, i], linestyle='--',marker=marker, color=color) ax.set_ylim(ymin, ymax) ax.spines['top'].set_visible(False) ax.spines['bottom'].set_visible(False) d = 0.01 # Abstand der Striche kwargs = dict(transform=ax.transAxes, color='k', clip_on=False, linewidth=1) if ax!=axes[-1]: ax.plot((-d, +d), (-d, +d), **kwargs) ax.plot((1 - d, 1 + d), (-d, +d), **kwargs) if ax!=axes[0] and ax!=axes[1]: ax.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) ax.tick_params(axis='x', which='both', bottom=False, top=False, labelbottom=False) axes[-1].set_xlabel('$x_{acetone}$') axes[-1].tick_params(axis='x', which='both', bottom=True, top=False, labelbottom=True) axes[len(visible_ranges) // 2].set_ylabel('Raman shift/ $cm^{-1}$', loc='center') axes[-1].set_xlim([0, 1]) axes[0].set_yticks([]) axes[0].tick_params(axis='x', which='both', bottom=False, labelbottom=False) pos0 = axes[0].get_position() pos1 = axes[1].get_position() axes[0].set_position([pos0.x0, pos1.y1, pos0.width, pos0.height * 0.7]) axes[-1].spines['bottom'].set_visible(True) axes[0].spines['top'].set_visible(True) axes[0].spines['bottom'].set_visible(False) axes[0].legend(handles=legend_handles, loc='lower center', fancybox=True, framealpha=0.6, ncol=2,handlelength=1,frameon=False) plt.show() #%% Figure 8/ Figure S3 mixtures=data_voigt.groupby(['Mixture']) plot=True if plot==True: plt.rcParams.update({'font.size': '26'}) show_mixtures=['Acetone-Cyclohexane','Acetone-Acetic acid'] #show_mixtures=['Acetone-Water','Acetone-ACN'] fig, ax = plt.subplots(len(show_mixtures),1, figsize=(12, 13))#, figsize=(12, 13) fig.subplots_adjust(left=0.1, right=0.95, bottom=0.1, top=0.95, wspace=0.02,hspace=0.02) k=0 for mixturename, mixture in mixtures: if mixturename in show_mixtures: mixture = mixture.reset_index(drop=True) marker, color = find_marker(mixturename) x1 = np.array(mixture['x1']) x1_unique, unique_indices = np.unique(x1[:-1], return_index=True) x1_unique = np.append(x1_unique, x1[-1]) unique_indices = np.append(unique_indices, len(x1) - 1) """compound 2""" centers_list_c2 = np.vstack(np.array(mixture['paras_c2'])).astype(np.float64)[:, :, 1] centers_list_c2 = centers_list_c2[unique_indices, :] centers_list_c2[centers_list_c2 == 0] = np.nan centers_list_diff_c2 = centers_list_c2 - centers_list_c2[0, :] j=0 for i in range(len(centers_list_diff_c2[0, :])): if not np.all((centers_list_diff_c2[:, i] == 0) | np.isnan(centers_list_diff_c2[:, i])): ax[k].plot(x1_unique, centers_list_diff_c2[:, i],linestyle= '--', color=color,marker=marker) ax[k].text(x1_unique[-1] + 0.17, centers_list_diff_c2[-3, i], f"{centers_list_c2[0, i]:.2f}", horizontalalignment='right' ) ax[k].set_xlim([0, 1.2]) ax[k].set_ylabel('Peak shift / $cm^{-1}$') k+=1 ax[0].tick_params(axis='x', which='both', bottom=False, labelbottom=False) ax[1].set_xlabel('x$_{1}$') ax[0].text(0.05, 0.95, "a)", transform=ax[0].transAxes, verticalalignment='top', horizontalalignment='left') ax[1].text(0.05, 0.95, "b)", transform=ax[1].transAxes, verticalalignment='top', horizontalalignment='left') plt.show() #%% Figure S2 plot=False if plot==True: plt.rcParams.update({'font.size': '14'}) fp_start = rs[0] fp_end = 1900 CH_OH_start = 2550 CH_OH_start_ACN = 2100 CH_OH_end = rs[-1] idx_fp_start = np.argmin(np.abs(rs - fp_start)) idx_fp_end = np.argmin(np.abs(rs - fp_end)) idx_CH_OH_start = np.argmin(np.abs(rs - CH_OH_start)) idx_CH_OH_start_ACN = np.argmin(np.abs(rs - CH_OH_start_ACN)) idx_CH_OH_end = np.argmin(np.abs(rs - CH_OH_end)) fig = plt.figure(figsize=(15, 10)) gs = gridspec.GridSpec(2, 5, wspace=0.02) # 2 Zeilen, 4 Spalten (2 pro Mischung) positions = [(0, 0), (0, 3), (1, 0), (1, 3)] mix_nr_i=0 mix_nr_j=0 mixturen = list(mixtures) # Falls mixtures ein Generator ist first=True first_fixed=True for idx, (mixturename, mixture) in enumerate(mixturen): row, col = positions[idx] ax1_left = fig.add_subplot(gs[row, col]) ax1_right = fig.add_subplot(gs[row, col + 1], sharey=ax1_left) if mixturename=='Acetone-Water': mult_fact=1 else: mult_fact=4 if mixturename=='Acetone-ACN': idx_CH_OH_start=np.argmin(np.abs(rs - CH_OH_start_ACN)) else: idx_CH_OH_start=np.argmin(np.abs(rs - CH_OH_start)) """ compound 2""" ax1_left.plot(rs[:idx_fp_end],mult_fact *mixture['spectra_mol'].iloc[0][:idx_fp_end],color='k',label='spectrum') ax1_left.plot(rs[:idx_fp_end],mult_fact *mixture['voigt_fit'].iloc[0][:idx_fp_end],color='k',linestyle='dashed',label='voigt fit') ax1_left.plot(rs[:idx_fp_end],mult_fact *(mixture['spectra_mol'].iloc[0][:idx_fp_end]-mixture['voigt_fit'].iloc[0][:idx_fp_end]),color='b',label='error') if mix_nr_i==0 and mix_nr_j==0: ax1_left.legend(handlelength=1,frameon=False) ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol'].iloc[0][idx_CH_OH_start:],color='k') ax1_right.plot(rs[idx_CH_OH_start:], mixture['voigt_fit'].iloc[0][idx_CH_OH_start:],color='k',linestyle='dashed') ax1_right.plot(rs[idx_CH_OH_start:], mixture['spectra_mol'].iloc[0][idx_CH_OH_start:]-mixture['voigt_fit'].iloc[0][idx_CH_OH_start:],color='b') for i in range(len(mixture['paras_c2'].iloc[0][0][:,0])): single_peak=pseudo_voigt(rs,mixture['paras_c2'].iloc[0][0][i,:],1) if mixture['fitted_c2'].iloc[i]=='True': ax1_left.plot(rs[:idx_fp_end], mult_fact * single_peak[:idx_fp_end],color='dimgrey',linestyle='dashed') if first==True: first=False ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='dimgrey',linestyle='dashed',label='fitted') else: ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='dimgrey',linestyle='dashed') else: if first_fixed==True: first_fixed=False ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='r',linestyle='dashed',label='fixed') else: ax1_right.plot(rs[idx_CH_OH_start:], single_peak[idx_CH_OH_start:],color='r',linestyle='dashed') ax1_left.plot(rs[:idx_fp_end], mult_fact * single_peak[:idx_fp_end],color='r',linestyle='dashed') if mix_nr_i==0 and mix_nr_j==0: ax1_right.legend(handlelength=1,frameon=False,loc='upper left') # X-Limits setzen ax1_left.set_xlim(rs[0], fp_end) # X-Limits setzen ax1_left.set_xlim(rs[0], fp_end) if mixturename=='Acetone-ACN': ax1_right.set_xlim(CH_OH_start_ACN, rs[-1]) else: ax1_right.set_xlim(CH_OH_start, rs[-1]) ax1_left.spines['right'].set_visible(False) ax1_left.yaxis.set_ticks_position('left') ax1_right.spines['left'].set_visible(False) ax1_right.yaxis.set_ticks_position('none') ax1_right.get_yaxis().set_visible(False) # Schrägstriche einfügen, um den Bruch zu visualisieren d = .015 # Neigung der Trennlinie kwargs = dict(transform=ax1_left.transAxes, color='k', clip_on=False) ax1_left.plot((1 - d, 1 + d), (-d, +d), **kwargs) ax1_left.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs) kwargs.update(transform=ax1_right.transAxes) ax1_right.plot((-d, +d), (-d, +d), **kwargs) ax1_right.plot((-d, +d), (1 - d, 1 + d), **kwargs) ax1_left.text(0.95, 0.8, f"x {mult_fact}", transform=ax1_left.transAxes, fontsize=16, verticalalignment='top', horizontalalignment='right') ax1_right.text(0.95, 0.8, "x 1", transform=ax1_right.transAxes, fontsize=16, verticalalignment='top', horizontalalignment='right') fig.text(0.75, 0.05, "Raman shift / $cm^{-1}$", ha='center', va='center') fig.text(0.28, 0.05, "Raman shift / $cm^{-1}$", ha='center', va='center') if mix_nr_i==0 and mix_nr_j==0: ax1_left.set_ylabel("Intensity") mix_nr_j=2 ax1_left.text(0.05, 0.95, "a)", transform=ax1_left.transAxes,verticalalignment='top', horizontalalignment='left') elif mix_nr_i==0 and mix_nr_j==2: mix_nr_j=0 mix_nr_i=1 ax1_left.text(0.05, 0.95, "b)", transform=ax1_left.transAxes,verticalalignment='top', horizontalalignment='left') elif mix_nr_i==1 and mix_nr_j==0: ax1_left.set_ylabel("Intensity") mix_nr_j=2 ax1_left.text(0.05, 0.95, "c)", transform=ax1_left.transAxes,verticalalignment='top', horizontalalignment='left') else: ax1_left.text(0.05, 0.95, "d)", transform=ax1_left.transAxes,verticalalignment='top', horizontalalignment='left') plt.show() #%% Figure S4 """ Plot for peakwidths compound 1 """ mixtures=data_voigt.groupby(['Mixture']) plot=False if plot==True: plt.rcParams.update({'font.size': '15', 'axes.labelweight': 'normal', 'font.family': 'DejaVu Sans'}) visible_ranges_width = [(40, 55), (5, 55), (10, 42), (15, 40), (37, 62), (10, 50), (23, 37), (20, 37), (22, 53)] legend_range = (visible_ranges_width[0][1], visible_ranges_width[0][1] + 0.63) visible_ranges_width.insert(0, legend_range) fig, axes = plt.subplots(len(visible_ranges_width), 1, sharex=True,gridspec_kw={'hspace': 0.05}, figsize=(6, 18))# #fig.subplots_adjust(left=0.14,right=0.93,top=0.99,bottom=0.08) legend_handles=[] for mixturename, mixture in mixtures: marker, color = find_marker(mixturename) x1 = np.array(mixture['x1']) width_list_c1 = np.flip(np.vstack(np.array(mixture['paras_c1'])).astype(np.float64)[:, :, 2],axis=1) if mixturename !='Acetone-ACN': line =Line2D(x1, width_list_c1[:, 2], linestyle='--', color=color, label=mixturename) else: line =Line2D(x1, width_list_c1[:, 2], linestyle='--', color=color, label='Acetone-Acetonitrile' ) legend_handles.append(line) j=0 i=0 axes_right=[] for ax, (ymin, ymax) in (zip(axes, visible_ranges_width)): if i==0: pass elif j