From b85ee9d64a536937912544c7bbd5b98b635b7e8d Mon Sep 17 00:00:00 2001
From: Christian C <cc@localhost>
Date: Mon, 11 Nov 2024 12:29:32 -0800
Subject: Initial commit
---
code/sunlab/sunflow/data/__init__.py | 1 +
code/sunlab/sunflow/data/utilities.py | 53 +++++++++++++++++++++++++++++++++++
2 files changed, 54 insertions(+)
create mode 100644 code/sunlab/sunflow/data/__init__.py
create mode 100644 code/sunlab/sunflow/data/utilities.py
(limited to 'code/sunlab/sunflow/data')
diff --git a/code/sunlab/sunflow/data/__init__.py b/code/sunlab/sunflow/data/__init__.py
new file mode 100644
index 0000000..b9a32c0
--- /dev/null
+++ b/code/sunlab/sunflow/data/__init__.py
@@ -0,0 +1 @@
+from .utilities import *
diff --git a/code/sunlab/sunflow/data/utilities.py b/code/sunlab/sunflow/data/utilities.py
new file mode 100644
index 0000000..dcdc36e
--- /dev/null
+++ b/code/sunlab/sunflow/data/utilities.py
@@ -0,0 +1,53 @@
+from sunlab.common import ShapeDataset
+from sunlab.common import MaxAbsScaler
+
+
+def process_and_load_dataset(
+ dataset_file, model_folder, magnification=10, scaler=MaxAbsScaler
+):
+ """# Load a dataset and process a models' Latent Space on the Dataset"""
+ from ..models import load_aae
+ from sunlab.common import import_full_dataset
+
+ model = load_aae(model_folder, normalization_scaler=scaler)
+ dataset = import_full_dataset(
+ dataset_file, magnification=magnification, scaler=model.scaler
+ )
+ latent = model.encoder(dataset.dataset).numpy()
+ assert len(latent.shape) == 2, "Only 1D Latent Vectors Supported"
+ for dim in range(latent.shape[1]):
+ dataset.dataframe[f"Latent-{dim}"] = latent[:, dim]
+ return dataset
+
+
+def process_and_load_datasets(
+ dataset_file_list, model_folder, magnification=10, scaler=MaxAbsScaler
+):
+ from pandas import concat
+ from ..models import load_aae
+
+ dataframes = []
+ datasets = []
+ for dataset_file in dataset_file_list:
+ dataset = process_and_load_dataset(
+ dataset_file, model_folder, magnification, scaler
+ )
+ model = load_aae(model_folder, normalization_scaler=scaler)
+ dataframe = dataset.dataframe
+ for label in ["ActinEdge", "Filopodia", "Bleb", "Lamellipodia"]:
+ if label in dataframe.columns:
+ dataframe[label.lower()] = dataframe[label]
+ if label.lower() not in dataframe.columns:
+ dataframe[label.lower()] = 0
+ latent_columns = [f"Latent-{dim}" for dim in range(model.latent_size)]
+ datasets.append(dataset)
+ dataframes.append(
+ dataframe[
+ dataset.data_columns
+ + dataset.label_columns
+ + latent_columns
+ + ["Frames", "CellNum"]
+ + ["actinedge", "filopodia", "bleb", "lamellipodia"]
+ ]
+ )
+ return datasets, concat(dataframes)
--
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