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from .dataset import Dataset
class ShapeDataset(Dataset):
"""# Shape Dataset"""
def __init__(
self,
dataset_filename,
data_columns=[
"Area",
"MjrAxisLength",
"MnrAxisLength",
"Eccentricity",
"ConvexArea",
"EquivDiameter",
"Solidity",
"Extent",
"Perimeter",
"ConvexPerim",
"FibLen",
"InscribeR",
"BlebLen",
],
label_columns=["Class"],
batch_size=None,
shuffle=False,
val_split=0.0,
scaler=None,
sort_columns=None,
random_seed=4332,
pre_scale=10,
**kwargs
):
"""# Initialize Dataset
self.dataset = dataset (N, ...)
self.labels = labels (N, ...)
Optional Arguments:
- prescale_function: The function that takes the ratio and transforms
the dataset by multiplying the prescale_function output
- sort_columns: The columns to sort the data by initially
- equal_split: If the classifications should be equally split in
training"""
super().__init__(
dataset_filename,
data_columns=data_columns,
label_columns=label_columns,
batch_size=batch_size,
shuffle=shuffle,
val_split=val_split,
scaler=scaler,
sort_columns=sort_columns,
random_seed=random_seed,
pre_scale=pre_scale,
**kwargs
)
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