Remove `matplotlib.use("agg")` workarounds.

examples/Cheminformatics/chem_utils.py

@@ -17,9 +17,6 @@ from rdkit.rdBase import BlockLogs
 import pandas as pd
 from rdkit.Chem.rdMMPA import FragmentMol
 from rdkit.Chem.rdRGroupDecomposition import RGroupDecompose
-import matplotlib
-
-matplotlib.use("agg")
 
 
 def smi2mol_with_errors(smi: str) -> Tuple[Mol, str]:

examples/Cheminformatics/cheminfo_tools.py

@@ -19,9 +19,6 @@ from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error
 from sklearn.model_selection import train_test_split
 import numpy as np
 from rdkit.Chem import MACCSkeys
-import matplotlib
-
-matplotlib.use("agg")
 
 
 @op("LynxKite Graph Analytics", "View mol filter", view="matplotlib", slow=True)

examples/Cheminformatics/rcsb_api.py

@@ -1,4 +1,3 @@
-import matplotlib
 import pandas as pd
 import matplotlib.pyplot as plt
 import pypdb
@@ -10,8 +9,6 @@ import os
 import numpy as np
 from Bio.PDB import PDBList, PDBParser, Superimposer
 
-matplotlib.use("agg")
-
 
 def calc_rmsd(A, B):
     """