def _img_method(x):
return "data:image/png;base64,{}".format(
b64_mol(self.mol_method(x)))
def html_grid(
df,
title="MolFrame",
drop=[],
keep=[],
smiles_col="Smiles",
mol_col="Mol",
id_col=None,
b64_col=None,
fp_col=None,
size=IMG_GRID_SIZE,
**kwargs,
):
"""Creates a HTML grid out of the MolFrame.data input.
Parameters:
df (MolFrame): list of RDKit molecules
highlight (dict): dict of properties (a.t.m only one) and values to highlight cells,
e.g. {"activity": "< 50"}
order (list): a list of substrings to match with the field names for ordering in the table header
img_dir (str): if None, the molecule images are embedded in the HTML doc.
Otherwise the images will be stored in img_dir and linked in the doc.
interactive (bool)
link_templ, link_col (str) (then interactive is false)
Returns:
HTML table as TEXT with molecules in grid-like layout to embed in IPython or a web page."""
interact = kwargs.get("interactive", False)
link_templ = kwargs.get("link_templ", None)
link_col = kwargs.get("link_col", None)
if link_col is not None:
interact = (
False
) # interact is not avail. when clicking the image should open a link
highlight = kwargs.get("highlight", None)
mols_per_row = kwargs.get("mols_per_row", 4)
hlsss = kwargs.get(
"hlsss", None
) # colname with Smiles (,-separated) for Atom highlighting
truncate = kwargs.get("truncate", 12)
img_dir = None
if len(keep) > 0:
keep.append(mol_col)
if id_col is not None and id_col not in keep:
keep.append(id_col)
df = df[keep]
drop.extend([smiles_col, b64_col, fp_col])
df = drop_cols(df, drop)
props = []
for x in list(df.keys()):
if x != mol_col and x != id_col and x != hlsss:
props.append(x)
time_stamp = time.strftime("%y%m%d%H%M%S")
# td_opt = {"align": "center"}
td_opt = {"style": "text-align: center;"}
header_opt = {"bgcolor": BGCOLOR}
table_list = []
guessed_id = id_col
if interact and guessed_id is not None:
table_list.append(templ.TBL_JAVASCRIPT.format(ts=time_stamp, bgcolor=BGCOLOR))
if len(props) > 0:
td_opt["colspan"] = "2"
prop_row_cells = {k: [] for k, _ in enumerate(props)}
rows = []
id_cells = []
mol_cells = []
for idx, (_, rec) in enumerate(df.iterrows(), 1):
mol = rec[mol_col]
if guessed_id:
id_prop_val = str(rec[guessed_id])
img_id = id_prop_val
cell_opt = {"id": "{}_{}".format(id_prop_val, time_stamp)}
cell_opt.update(td_opt)
cell_opt.update(header_opt)
id_cells.extend(templ.td(id_prop_val, cell_opt))
else:
img_id = idx
if not mol:
cell = ["no structure"]
else:
if hlsss is not None:
hlsss_smi = rec[hlsss]
else:
hlsss_smi = None
if img_dir is None: # embed the images in the doc
img_src = b64_mol(mol, size * 2, hlsss=hlsss_smi)
if interact and guessed_id is not None:
img_opt = {
"title": "Click to select / unselect",
"onclick": "toggleCpd('{}')".format(id_prop_val),
}
elif link_col is not None:
img_opt = {"title": "Click to open link"}
# "onclick": "location.href='{}';".format(link)}
# '<a target="_blank" href="{}" title="{}">{}</a>'
else:
img_opt = {"title": str(img_id)}
img_opt["style"] = f"max-width: {size}px; max-height: {size}px;"
# img_opt["height"] = "{}px".format(size)
cell = templ.img(img_src, img_opt)
if link_col is not None:
link = link_templ.format(rec[link_col])
a_opt = {"href": link}
cell = templ.a(cell, a_opt)
# td_opt = {"align": "center"}
td_opt = {"style": "text-align: center;", "bgcolor": "#FFFFFF"}
if len(props) > 0:
td_opt["colspan"] = "2"
if highlight is not None:
eval_str = None
prop = highlight.keys()[0] # only one highlight key supported a.t.m.
prop_val = str(rec[prop])
eval_str = " ".join([prop_val, highlight[prop]])
if eval_str and eval(eval_str):
td_opt["bgcolor"] = "#99ff99"
mol_cells.extend(templ.td(cell, td_opt))
if len(props) > 0:
for prop_no, prop in enumerate(props):
prop_opt = {"style": "text-align: left;"}
val_opt = {"style": "text-align: left;"}
prop_cells = []
prop_val = ""
if prop in rec:
prop_val = str(rec[prop])
if (
prop == "Pure_Flag"
and prop_val != ""
and prop_val != "n.d."
and "Purity" in rec
and "LCMS_Date" in rec
):
val_opt["title"] = "{}% ({})".format(
rec["Purity"], rec["LCMS_Date"]
)
prop_cells.extend(templ.td(prop[:25], prop_opt))
prop_cells.extend(templ.td(prop_val[:truncate], val_opt))
prop_row_cells[prop_no].extend(prop_cells)
if idx % mols_per_row == 0 or idx == len(df):
if guessed_id:
rows.extend(templ.tr(id_cells))
rows.extend(templ.tr(mol_cells))
if len(props) > 0:
colspan_factor = 2
for prop_no in sorted(prop_row_cells):
rows.extend(templ.tr(prop_row_cells[prop_no]))
prop_row_cells = {k: [] for k, _ in enumerate(props)}
else:
colspan_factor = 1
empty_row_options = {"colspan": mols_per_row * colspan_factor}
empty_row_options["style"] = "border: none;"
empty_row = templ.tr(templ.td(" ", options=empty_row_options))
rows.extend(empty_row)
id_cells = []
mol_cells = []
table_list.extend(templ.table(rows))
if interact and guessed_id is not None:
table_list.append(templ.ID_LIST.format(ts=time_stamp))
# print(table_list)
return "".join(table_list)