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1 files changed, 119 insertions, 0 deletions

diff --git a/code/sunlab/common/data/utilities.py b/code/sunlab/common/data/utilities.py
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+++ b/code/sunlab/common/data/utilities.py
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+from .shape_dataset import ShapeDataset
+from ..scaler.max_abs_scaler import MaxAbsScaler
+
+
+def import_10x(
+    filename,
+    magnification=10,
+    batch_size=None,
+    shuffle=False,
+    val_split=0.0,
+    scaler=None,
+    sort_columns=None,
+):
+    """# Import a 10x Image Dataset
+    
+    Pixel-to-micron: ???"""
+    magnification = 10
+    dataset = ShapeDataset(
+        filename,
+        batch_size=batch_size,
+        shuffle=shuffle,
+        pre_scale=magnification,
+        val_split=val_split,
+        scaler=scaler,
+        sort_columns=sort_columns,
+    )
+    return dataset
+
+
+def import_20x(
+    filename,
+    magnification=10,
+    batch_size=None,
+    shuffle=False,
+    val_split=0.0,
+    scaler=None,
+    sort_columns=None,
+):
+    """# Import a 20x Image Dataset
+    
+    Pixel-to-micron: ???"""
+    magnification = 20
+    dataset = ShapeDataset(
+        filename,
+        batch_size=batch_size,
+        shuffle=shuffle,
+        pre_scale=magnification,
+        val_split=val_split,
+        scaler=scaler,
+        sort_columns=sort_columns,
+    )
+    return dataset
+
+
+def import_dataset(
+    filename,
+    magnification,
+    batch_size=None,
+    shuffle=False,
+    val_split=0.0,
+    scaler=None,
+    sort_columns=None,
+):
+    """# Import a dataset
+
+    Requires a magnificaiton to be specified"""
+    dataset = ShapeDataset(
+        filename,
+        pre_scale=magnification,
+        batch_size=batch_size,
+        shuffle=shuffle,
+        val_split=val_split,
+        scaler=scaler,
+        sort_columns=sort_columns,
+    )
+    return dataset
+
+
+def import_full_dataset(fname, magnification=20, scaler=None):
+    """# Import a Full Dataset
+
+    If a classification file exists(.txt with a 'Class' header and 'frame','cellnumber' headers), also import it"""
+    from os.path import isfile
+    import pandas as pd
+    import numpy as np
+
+    cfname = fname
+    tfname = cfname[:-3] + "txt"
+    columns = [
+        "frame",
+        "cellnumber",
+        "x-cent",
+        "y-cent",
+        "actinedge",
+        "filopodia",
+        "bleb",
+        "lamellipodia",
+    ]
+    if isfile(tfname):
+        dataset = import_dataset(cfname, magnification=magnification, scaler=scaler)
+        class_df = np.loadtxt(tfname, skiprows=1)
+        class_df = pd.DataFrame(class_df, columns=columns)
+        full_df = pd.merge(
+            dataset.dataframe,
+            class_df,
+            left_on=["Frames", "CellNum"],
+            right_on=["frame", "cellnumber"],
+        )
+        full_df["Class"] = np.argmax(
+            class_df[["actinedge", "filopodia", "bleb", "lamellipodia"]].to_numpy(),
+            axis=-1,
+        )
+        dataset.labels = full_df["Class"].to_numpy()
+    else:
+        dataset = import_dataset(cfname, magnification=magnification, scaler=scaler)
+        full_df = dataset.dataframe
+    dataset.dataframe = full_df
+    dataset.filter_off()
+    return dataset