def plot_bar_charts(runtypes, ligands):
series_data = {i: {} for i in ligands}
for rt in runtypes:
rtd = runtypes[rt]
for ser in series_data:
a_energy = rtd['energies'][f'{ser.lower()}_A']
b_energy = rtd['energies'][f'{ser.lower()}_B']
c_energy = rtd['energies'][f'{ser.lower()}_C']
d_energy = rtd['energies'][f'{ser.lower()}_D']
energy_sep = c_energy - min([a_energy, b_energy, d_energy])
energy_sep = -1 * energy_sep * 2625.5
series_data[ser][rt] = energy_sep
bar_chart(
energies=[series_data[s]['xtb'] for s in series_data],
filename='previous_xtb.pdf',
x_labels=[s for s in series_data],
y_title=r'xTB $cis$ energy preference [kJmol$^{-1}$]',
facecolor=colors_i_like()[4],
)
bar_chart(
energies=[series_data[s]['pbenoecp'] for s in series_data],
filename='previous_dft.pdf',
x_labels=[s for s in series_data],
y_title=r'DFT $cis$ energy preference [kJmol$^{-1}$]',
facecolor=colors_i_like()[3],
)
def opposing_bar_chart(
xtbenergies,
dftenergies,
filename,
x_labels,
):
c_expt = colors_i_like()[3]
c_selec = colors_i_like()[4]
xs = [1, 2, 3, 4]
fig, ax = plt.subplots(nrows=2, sharex=True, figsize=(8, 10))
ax[0].bar(xs,
xtbenergies,
width=1,
color=c_selec,
edgecolor='k',
linewidth=1.5,
label='GFN2-xTB')
ax[1].bar(xs,
dftenergies,
width=1,
color=c_expt,
edgecolor='k',
linewidth=1.5,
label='PBE0-D3/def2-SVP/SDD/PCM(DMSO) [CHKTHIS]')
ax[1].set_xticks(xs)
ax[1].set_xticklabels(x_labels)
ax[0].tick_params(axis='both', which='major', labelsize=16)
ax[0].set_ylabel(r'xTB $cis$ energy preference [kJmol$^{-1}$]',
fontsize=16)
ax[0].set_xlim(0, 5)
ax[0].set_ylim(None, None)
# ax[0].legend(fontsize=16)
ax[1].tick_params(axis='both', which='major', labelsize=16)
ax[1].set_ylabel(r'DFT $cis$ energy preference [kJmol$^{-1}$]',
fontsize=16)
ax[1].set_xlim(0, 5)
ax[1].set_ylim(None, None)
# ax[1].legend(fontsize=16)
ax[1].invert_yaxis()
# ax[0].set(yticks=df_male_1['age'])
# ax[0].xaxis.tick_right()
fig.tight_layout()
fig.savefig(filename, dpi=720, bbox_inches='tight')
plt.close()
def main():
if (not len(sys.argv) == 1):
print("""
Usage: plot_experimental_cases.py
""")
sys.exit()
raise Exception('This script is outdated.')
experimental_cases = {
'5D1': {
'new': False,
'p': 1
},
'4D2': {
'new': False,
'p': 2
},
'5D3': {
'new': False,
'p': 3
},
'3D1': {
'new': False,
'p': 4
},
'5A3': {
'new': True,
'p': 5
},
'5A1': {
'new': True,
'p': 6
},
'4B3': {
'new': True,
'p': 7
},
'4B1': {
'new': True,
'p': 8
},
'5C2': {
'new': True,
'p': 9
},
'4C2': {
'new': True,
'p': 10
},
'5D7': {
'new': True,
'p': 11
},
'5B4': {
'new': True,
'p': 12
},
}
print(experimental_cases)
data = pd.read_csv('all_cage_results.txt')
data = data[data['lig'].isin(experimental_cases)]
print(data)
print(data.columns)
plot_properties = {
'energies': {
'ylim': (0, 40),
'ytitle': 'energy separation [kJmol$^{-1}$]',
'data_f': get_energy_sep,
'ycut': 6,
},
'pds': {
'ylim': (0, 0.2),
'ytitle': r'max. plane deviation [$\mathrm{\AA}$]',
'data_f': get_C_pd,
'ycut': 0.3,
},
'qsps': {
'ylim': (0.9, 1),
'ytitle': r'min. $q_{\mathrm{sp}}$',
'data_f': get_C_op,
'ycut': 0.95,
}
}
fig, (ax0, ax1, ax2) = plt.subplots(
3,
1,
figsize=(8, 10),
sharex=True,
)
ax0_dict = plot_properties['energies']
ax0_data = [(row['lig'], ax0_dict['data_f'](row))
for i, row in data.iterrows()]
ax0.bar(
x=[experimental_cases[i[0]]['p'] for i in ax0_data],
height=[i[1] for i in ax0_data],
width=0.9,
color=[get_c(experimental_cases[i[0]]['new']) for i in ax0_data],
tick_label=[get_xtick(i[0]) for i in ax0_data],
)
ax0.axhline(y=ax0_dict['ycut'], c='k', lw=2)
ax0.tick_params(axis='both', which='major', labelsize=16)
ax0.set_ylabel(ax0_dict['ytitle'], fontsize=16)
ax0.set_ylim(ax0_dict['ylim'])
ax1_dict = plot_properties['pds']
ax1_data = [(row['lig'], ax1_dict['data_f'](row))
for i, row in data.iterrows()]
ax1.bar(
x=[experimental_cases[i[0]]['p'] for i in ax1_data],
height=[i[1] for i in ax1_data],
width=0.9,
color=[get_c(experimental_cases[i[0]]['new']) for i in ax1_data],
tick_label=[get_xtick(i[0]) for i in ax1_data],
)
ax1.axhline(y=ax1_dict['ycut'], c='k', lw=2)
ax1.tick_params(axis='both', which='major', labelsize=16)
ax1.set_ylabel(ax1_dict['ytitle'], fontsize=16)
ax1.set_ylim(ax1_dict['ylim'])
ax2_dict = plot_properties['qsps']
ax2_data = [(row['lig'], ax2_dict['data_f'](row))
for i, row in data.iterrows()]
ax2.bar(
x=[experimental_cases[i[0]]['p'] for i in ax2_data],
height=[i[1] for i in ax2_data],
width=0.9,
color=[get_c(experimental_cases[i[0]]['new']) for i in ax2_data],
tick_label=[get_xtick(i[0]) for i in ax2_data],
)
ax2.axhline(y=ax2_dict['ycut'], c='k', lw=2)
ax2.tick_params(axis='both', which='major', labelsize=16)
ax2.set_xlabel('ligand', fontsize=16)
ax2.set_ylabel(ax2_dict['ytitle'], fontsize=16)
ax2.set_ylim(ax2_dict['ylim'])
legend_elements = [
Patch(facecolor=colors_i_like()[4], edgecolor='none', label='new'),
Patch(facecolor=colors_i_like()[3],
edgecolor='none',
label='published'),
]
plt.xticks(rotation=45)
ax0.legend(handles=legend_elements, fontsize=16)
fig.tight_layout()
fig.savefig('experimental_tests.pdf', dpi=720, bbox_inches='tight')
def get_c(b):
if b:
return colors_i_like()[4]
else:
return colors_i_like()[3]
def plot(
x, y, xlabel, ylabel, xlim, ylim,
expt_x, expt_y, sele_x, sele_y, filename,
exam_x, exam_y,
):
fig, ax = plt.subplots(figsize=(8, 5))
full = ax.scatter(
x,
y,
c=colors_i_like('IBM')[2],
edgecolors='none',
marker='o',
alpha=1,
s=150,
# label='new in this work'
)
exam = ax.scatter(
exam_x,
exam_y,
c=colors_i_like('IBM')[2],
edgecolors='black',
linewidths=2,
marker='o',
alpha=1,
s=150,
# label='highlighted examples'
)
sele2 = ax.scatter(
sele_x,
sele_y,
c='white',
edgecolors='black',
linewidths=2,
marker='o',
alpha=1,
s=190,
# label='synthesised in this work'
)
sele = ax.scatter(
sele_x,
sele_y,
c=colors_i_like('IBM')[2],
edgecolors='white',
linewidths=2,
marker='o',
alpha=1,
s=150,
# label='synthesised in this work'
)
publ = ax.scatter(
expt_x,
expt_y,
c=colors_i_like('IBM')[4],
edgecolors='white',
marker='D',
alpha=1,
s=120,
# label='published examples'
)
# ax.axhline(y=0, lw=2, linestyle='--', c='k')
ax.legend(
[
publ,
full,
exam,
(sele2, sele)
],
[
'published examples',
'new in this work',
'highlighted examples',
'synthesised in this work'
],
fontsize=16
)
# Set number of ticks for x-axis
ax.tick_params(axis='both', which='major', labelsize=16)
ax.set_xlabel(xlabel, fontsize=16)
ax.set_ylabel(ylabel, fontsize=16)
ax.set_xlim(xlim)
ax.set_ylim(ylim)
# ax.legend(fontsize=16)
fig.tight_layout()
fig.savefig(filename, dpi=720, bbox_inches='tight')
plt.close()
def bar_figure(selected_ligands, experimental_ligands, data):
c_expt = colors_i_like()[3]
c_selec = colors_i_like()[4]
x_expt = {}
x_selec = {}
for i, li in enumerate(selected_ligands):
row = data[data['lig'] == li]
print(row)
print(row['energy_C'])
energy_sep = min([
float(row['energy_A']),
float(row['energy_B']),
float(row['energy_D']),
])
C_qsp = float(row['sqpl_op_C'])
short_name = li
if li in experimental_ligands:
x_expt[i] = (short_name, energy_sep, C_qsp)
else:
x_selec[i] = (short_name, energy_sep, C_qsp)
x_ticks = [i for i in x_expt]+[i for i in x_selec]
x_ticklabels = (
[x_expt[i][0] for i in x_expt]+[x_selec[i][0] for i in x_selec]
)
print(x_ticks, x_ticklabels)
width = 0.9
fig, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize=(8, 8))
ax1.barh(
y=[i for i in x_expt],
width=[x_expt[i][1] for i in x_expt],
height=width,
facecolor=c_expt,
edgecolor='none',
alpha=1,
label='published examples'
)
ax1.barh(
y=[i for i in x_selec],
width=[x_selec[i][1] for i in x_selec],
height=width,
facecolor=c_selec,
edgecolor='none',
alpha=1,
label='selected cage ligands'
)
# Set number of ticks for x-axis
ax1.tick_params(axis='both', which='major', labelsize=16)
# ax.set_xlabel(names[name]['xtitle'], fontsize=16)
# ax1.set_xticks(x_ticks)
# ax1.set_xticklabels(x_ticklabels)
ax1.set_xlabel('stability of C isomer [kJmol$^{-1}$]', fontsize=16)
# ax.set_xlim(names[name]['xlim'])
ax1.set_xlim(0, 30)
ax1.axvline(x=6.0, c='k', alpha=0.6, lw=2)
ax2.barh(
y=[i for i in x_expt],
height=width,
width=[x_expt[i][2] for i in x_expt],
facecolor=c_expt,
edgecolor='none',
alpha=1,
)
ax2.barh(
y=[i for i in x_selec],
height=width,
width=[x_selec[i][2] for i in x_selec],
facecolor=c_selec,
edgecolor='none',
alpha=1,
)
# Set number of ticks for x-axis
ax2.tick_params(axis='both', which='major', labelsize=16)
ax2.set_xticks([0.9, 1])
ax2.set_xticklabels(['0.9', '1.0'])
ax2.set_yticks(x_ticks)
ax2.set_yticklabels(x_ticklabels, rotation=45)
ax2.set_xlabel(r'$q_{\mathrm{sqp,min}}$', fontsize=16)
ax2.set_xlim(0.9, 1)
ax1.legend(fontsize=16)
fig.tight_layout()
fig.savefig(
'selected_ligands.pdf',
dpi=720,
bbox_inches='tight'
)
plt.close()
def single_bar_figure(selected_ligands, experimental_ligands, data):
c_expt = 'lightgray'
c_selec = colors_i_like('IBM')[3]
x_expt = {}
x_selec = {}
for i, li in enumerate(selected_ligands):
row = data[data['lig'] == li]
print(row, row['energy_C'])
energy_sep = min([
float(row['energy_A']),
float(row['energy_B']),
float(row['energy_D']),
])
C_qsp = float(row['sqpl_op_C'])
short_name = (
li.replace(
'_li', '-'
).replace('_lk', '-').replace('li', '')
)
if li in experimental_ligands:
x_expt[i] = (short_name, energy_sep, C_qsp)
else:
x_selec[i] = (short_name, energy_sep, C_qsp)
x_ticks = [i for i in x_expt]+[i for i in x_selec]
x_ticklabels = (
[x_expt[i][0] for i in x_expt]+[x_selec[i][0] for i in x_selec]
)
print(x_ticks, x_ticklabels)
hatch_patterns = [
'' if x_selec[i][0] != '4B3' else '//'
for i in x_selec
]
width = 0.9
fig, ax = plt.subplots(figsize=(4, 8))
ex = ax.barh(
y=[i for i in x_expt],
width=[x_expt[i][1] for i in x_expt],
height=width,
facecolor=c_expt,
# hatch='none',
edgecolor='k',
alpha=1,
# label='published examples'
)
for i, j in enumerate(x_selec):
if x_selec[j][0] == '4B3':
ssel = ax.barh(
y=j,
width=x_selec[j][1],
height=width,
facecolor=c_selec,
hatch=hatch_patterns[i],
edgecolor='k',
alpha=1,
# label='selected cage ligands'
)
else:
sel = ax.barh(
y=j,
width=x_selec[j][1],
height=width,
facecolor=c_selec,
hatch=hatch_patterns[i],
edgecolor='k',
alpha=1,
# label='selected cage ligands'
)
ax.axvline(x=6.0, c='k', alpha=0.6, lw=2)
# Set number of ticks for x-axis
ax.tick_params(axis='both', which='major', labelsize=16)
# ax.set_xlabel(names[name]['xtitle'], fontsize=16)
# ax1.set_xticks(x_ticks)
# ax1.set_xticklabels(x_ticklabels)
# ax.set_xlabel(
# r'stability of $cis$ isomer [kJmol$^{-1}$]',
# fontsize=16,
# )
ax.set_xlabel(
r'$\Delta E_{\mathrm{cis}}$ [kJmol$^{-1}$]',
fontsize=16,
)
# ax.set_xlim(names[name]['xlim'])
ax.set_xlim(0, 30)
# Set number of ticks for x-axis
ax.set_yticks(x_ticks)
ax.set_yticklabels(x_ticklabels)
ax.legend(
[ex, sel, ssel],
['published examples', 'forms single isomer', 'forms mixture'],
fontsize=16
)
fig.tight_layout()
fig.savefig(
'selected_ligands_energysep.pdf',
dpi=720,
bbox_inches='tight'
)
plt.close()
def main():
cage_data = pd.read_csv('all_cage_results.txt')
mA = 'o'
cA = colors_i_like()[4]
# mB = 's'
# cB = colors_i_like()[3]
# mC = 'X'
# cC = colors_i_like()[0]
# mD = 'D'
# cD = colors_i_like()[2]
X_A = []
Y_A = []
X_B = []
Y_B = []
X_C = []
Y_C = []
X_D = []
Y_D = []
for i, row in cage_data.iterrows():
X_A.append(float(row['sqpl_op_A']))
Y_A.append(float(row['plane_dev_A']))
X_B.append(float(row['sqpl_op_B']))
Y_B.append(float(row['plane_dev_B']))
X_C.append(float(row['sqpl_op_C']))
Y_C.append(float(row['plane_dev_C']))
X_D.append(float(row['sqpl_op_D']))
Y_D.append(float(row['plane_dev_D']))
fig, ax = plt.subplots(figsize=(8, 5))
ax.scatter(
X_A + X_B + X_C + X_D,
Y_A + Y_B + Y_C + Y_D,
c=cA,
edgecolors='black',
marker=mA,
alpha=1,
s=80,
# label='a',
)
# ax.scatter(
# X_B,
# Y_B,
# c=cB,
# edgecolors='white',
# marker=mB,
# alpha=1,
# s=60,
# label='b',
# )
# ax.scatter(
# X_C,
# Y_C,
# c=cC,
# edgecolors='white',
# marker=mC,
# alpha=1,
# s=60,
# label='c',
# )
# ax.scatter(
# X_D,
# Y_D,
# c=cD,
# edgecolors='white',
# marker=mD,
# alpha=1,
# s=60,
# label='d',
# )
# Set number of ticks for x-axis
ax.tick_params(axis='both', which='major', labelsize=16)
ax.set_xlabel(r'$q_{\mathrm{sqp,min}}$', fontsize=16)
ax.set_ylabel(r'$D_{\mathrm{max}}$ [$\mathrm{\AA}$]', fontsize=16)
ax.set_xlim(0, 1)
ax.set_ylim(0, None)
# ax.legend(fontsize=16)
fig.tight_layout()
fig.savefig('all_cages_geom_parity.pdf', dpi=720, bbox_inches='tight')
plt.close()