# Source code for scm.conformers.plams.plot

```
import scm.plams
from scm.conformers.plams.interface import ConformersJob
import matplotlib.pyplot as plt
import numpy as np
def get_main_results(job: ConformersJob, temperature=298, unit="kcal/mol", return_molecules: bool = True):
molecules = None
if return_molecules:
molecules = job.results.get_conformers()
energies = job.results.get_relative_energies(unit)
populations = job.results.get_boltzmann_distribution(temperature)
return molecules, energies, populations
[docs]def plot_conformers(job: ConformersJob, indices=None, temperature=298, unit="kcal/mol", lowest=True):
"""
Function for plotting conformers in a Jupyter notebook
job: ConformersJob
Finished ConformersJob
indices: None, int or list of int
If None, will plot at most 3 conformers.
If int, will plot at most the given number of conformers.
If list of int (zero-based indices), plot those conformers.
temperature: float
Temperature for relative population (printed above the figure).
unit: str
Unit for relative energies (printed above the figure)
lowest: bool
Only used if ``indices`` is an integer. If True, plot the N lowest energy conformers. If False, plot conformers evenly distributed from the most stable to the least stable.
"""
molecules, energies, populations = get_main_results(job, unit=unit)
if isinstance(indices, int):
N_plot = min(indices, len(energies))
if lowest:
indices = list(range(N_plot))
else:
indices = np.linspace(0, len(energies) - 1, N_plot, dtype=np.int32)
if indices is None:
indices = list(range(min(3, len(energies))))
fig, axes = plt.subplots(1, len(indices), figsize=(12, 3))
if len(indices) == 1:
axes = [axes]
for ax, i in zip(axes, indices):
mol = molecules[i]
E = energies[i]
population = populations[i]
scm.plams.plot_molecule(mol, ax=ax)
ax.set_title(f"#{i+1}\nΔE = {E:.2f} {unit}\nPop.: {population:.3f} (T = {temperature} K)")
return axes
```