From 5e41283d19ef43b1563e8532dc688bbd65788356 Mon Sep 17 00:00:00 2001 From: rabii-chaarani Date: Fri, 17 May 2024 13:49:30 +0930 Subject: [PATCH] fix: use correct variable name --- FoldOptLib/fold_modelling/base_engine.py | 14 -------------- FoldOptLib/fold_modelling/engine.py | 6 +++--- 2 files changed, 3 insertions(+), 17 deletions(-) diff --git a/FoldOptLib/fold_modelling/base_engine.py b/FoldOptLib/fold_modelling/base_engine.py index 7dd5a01..eb7608e 100644 --- a/FoldOptLib/fold_modelling/base_engine.py +++ b/FoldOptLib/fold_modelling/base_engine.py @@ -11,20 +11,6 @@ def initialise_model(self): """ pass - # @abstractmethod - # def import_data(self): - # """ - # Import the data from the input file - # """ - # pass - # - # @abstractmethod - # def setup_fold_frame_interpolation(self): - # """ - # Setup the fold frame interpolation - # """ - # pass - @abstractmethod def build_fold_frame(self, axial_normal: np.ndarray) -> None: """ diff --git a/FoldOptLib/fold_modelling/engine.py b/FoldOptLib/fold_modelling/engine.py index be4ffcc..4e34b10 100644 --- a/FoldOptLib/fold_modelling/engine.py +++ b/FoldOptLib/fold_modelling/engine.py @@ -10,7 +10,7 @@ ) from ..builders import FoldFrameBuilder from ..datatypes import DataType, CoordinateType, FitType -from ..input import InumpyutDataProcessor, OptData +from ..input import InumpyutDataProcessor, OptData, InputData from ..from_loopstructural._fold import FoldEvent from ..from_loopstructural._fold_frame import FoldFrame from .base_engine import BaseEngine @@ -56,7 +56,7 @@ class FoldModel(BaseEngine): No methods defined yet. """ - def __init__(self, data: InumpyutData, dimensions: int = 2, **kwargs: Dict[str, Any]): + def __init__(self, data: InputData, dimensions: int = 2, **kwargs: Dict[str, Any]): """ Constructs all the necessary attributes for the FoldModel object. @@ -84,7 +84,7 @@ def __init__(self, data: InumpyutData, dimensions: int = 2, **kwargs: Dict[str, self.scaled_points = None self.kwargs = kwargs - def set_data(self, data: InumpyutData) -> None: + def set_data(self, data: InputData) -> None: """ Process the data by extracting the gradient data from the data DataFrame.