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Fix issue #7: MultiModel.load_models fails on Windows #8

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Fix issue #7: MultiModel.load_models fails on Windows #8

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710c695
Fixed issue #7
Aug 1, 2024
79d0e60
Merge remote-tracking branch 'origin/master' into fix_issue7
Aug 1, 2024
ecb51a1
Add the column polymer to the output df (evaluate error)
Sep 11, 2024
fd108a7
hunk with space differences?
Sep 11, 2024
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18 changes: 10 additions & 8 deletions polyid/polyid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -499,7 +499,7 @@ def load_models(
, by default None
nmodels : Union[int, list], optional
Used to import models 0 through nmodels if value passed is an int. If value
passed is a list, then those models will be imported. Should be a list of
passed is a list, then those models will be imported. Should be a list of
integers. by default None

Returns
Expand Down Expand Up @@ -535,8 +535,9 @@ def load_models(

if nmodels == None:
for model_folder in model_folders:
model_path = Path(model_folder) / (model_folder.rsplit("/")[-1] + ".h5")
data_path = Path(model_folder) / (model_folder.rsplit("/")[-1] + "_data.pk")
model_folder_path = Path(model_folder)
model_path = model_folder_path / (model_folder_path.stem + ".h5")
data_path = model_folder_path / (model_folder_path.stem + "_data.pk")
mm.models.append(
SingleModel.load_model(
model_path, data_path, custom_objects=custom_objects_dict
Expand Down Expand Up @@ -690,7 +691,8 @@ def make_aggregate_predictions(
df_prediction = self.make_predictions(df_prediction)

# Required columns
groupby_columns = ["pm", "distribution"]
groupby_columns = ["pm", "polymer", "distribution"]
#groupby_columns = ["pm", "distribution"]
groupby_columns.extend(additional_groupby)
if not groupby_pm or "pm" not in df_prediction.columns:
groupby_columns.remove("pm")
Expand Down Expand Up @@ -756,7 +758,7 @@ def split_data(

data = self.df_polymer.copy()

# Assign a data_id column to aid in kfolds; data id acts as a unique identifer for creating stratified splits. It should be a unique integer.
# Assign a data_id column to aid in kfolds; data id acts as a unique identifer for creating stratified splits. It should be a unique integer.
if "data_id" not in data:
data["data_id"] = 0
#replacing nans for logical statements later
Expand All @@ -765,12 +767,12 @@ def split_data(

if "pm" in row:
idxs = data[
(data["smiles_monomer"] == row.smiles_monomer) &
(data["smiles_monomer"] == row.smiles_monomer) &
(data["distribution"] == row.distribution)&
(data["pm"]==row.pm)
].index.tolist()

else:
else:
idxs = data[(data["smiles_monomer"] == row.smiles_monomer) & (
data["distribution"] == row.distribution
)].index.tolist()
Expand Down Expand Up @@ -1017,7 +1019,7 @@ def load_training_data(cls, fname: Union[Path, str]) -> MultiModel:

class RenameUnpickler(pk.Unpickler):
"""For handling the renaming of modules previously named polyml. Backwards compatibilty for older models.

example:

params = RenameUnpickler.load_pickle(filepath_of_picklefile)
Expand Down