From 2670973facce3222e1abd34ce67e86269da5c956 Mon Sep 17 00:00:00 2001
From: Gaurav S Deshmukh <deshmukg@gilbreth-fe00.rcac.purdue.edu>
Date: Fri, 22 Sep 2023 23:22:36 -0400
Subject: [PATCH 1/2] Added RandomSampler

---
 src/samplers.py | 86 +++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 86 insertions(+)
 create mode 100644 src/samplers.py

diff --git a/src/samplers.py b/src/samplers.py
new file mode 100644
index 0000000..699bbf1
--- /dev/null
+++ b/src/samplers.py
@@ -0,0 +1,86 @@
+"""Samplers for training, validation, and testing."""
+
+import numpy as np
+import pandas as pd
+import abc
+
+class Sampler(abc.ABC):
+    """Abstract base class for data samplers."""
+    def __init__(self):
+        """Blank constructor."""
+        pass
+
+    @abc.abstractmethod
+    def create_samplers(self):
+        """Create training, test, and validation samplers.
+        
+        This should return a dictionary with "train", "val", "test" as keys and
+        indices of datapoints as values.
+        """
+        pass
+
+    @abc.abstractstaticmethod
+    def name():
+        """Name of the sampling method."""
+        pass
+
+class RandomSampler(Sampler):
+    """Perform uniform random sampling on datapoints."""
+    def __init__(self, seed, dataset_size):
+        """Initialize sampler.
+
+        Parameters
+        ----------
+        seed: int
+            Seed for random sampling.
+        dataset_size: int
+            Number of points in dataset
+        """
+        self.seed = seed
+        self.dataset_size = dataset_size
+
+    def create_samplers(self, sample_config):
+        """Randomly sample training, validation, and test datapoints.
+
+        Parameters
+        ----------
+        sample_config: dict
+            Dictionary with "train", "val", "test" as values and corresponding
+            fractions as values (must sum up to 1).
+
+        Returns
+        -------
+        samples: dict
+            Dictionary with indices for train, val, and test points.
+        """
+        # Create randomizer
+        randomizer = np.random.default_rng(self.seed)
+
+        # Create array of indices
+        idx_array = np.arange(self.dataset_size)
+
+        # Shuffle array
+        np.random.shuffle(idx_array)
+
+        # Get indices
+        train_size = int(np.ceil(sample_config["train"] * self.dataset_size))
+        train_idx = idx_array[:train_size]
+        val_size = int(np.ceil(sample_config["val"] * self.dataset_size))
+        val_idx = idx_array[train_size: train_size + val_size]
+        test_idx = idx_array[train_size + val_size:]
+
+        # Create samples
+        samples = {"train": train_idx, "val": val_idx, "test": test_idx}
+        
+        return samples
+    
+    @staticmethod
+    def name():
+        return "random"
+
+if __name__ == "__main__":
+    rs = RandomSampler(0, 100)
+    samples = rs.create_samplers({"train": 0.6, "val": 0.2, "test": 0.2})
+    print(samples)
+
+

From 2e0aa869eb1620b0a64432d162389d2afc77a55b Mon Sep 17 00:00:00 2001
From: Gaurav S Deshmukh <deshmukg@gilbreth-fe00.rcac.purdue.edu>
Date: Fri, 22 Sep 2023 23:28:14 -0400
Subject: [PATCH 2/2] Fixed codestyle

---
 src/samplers.py | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/src/samplers.py b/src/samplers.py
index 699bbf1..7723ae1 100644
--- a/src/samplers.py
+++ b/src/samplers.py
@@ -1,11 +1,13 @@
 """Samplers for training, validation, and testing."""
 
-import numpy as np
-import pandas as pd
 import abc
 
+import numpy as np
+
+
 class Sampler(abc.ABC):
     """Abstract base class for data samplers."""
+
     def __init__(self):
         """Blank constructor."""
         pass
@@ -13,7 +15,7 @@ def __init__(self):
     @abc.abstractmethod
     def create_samplers(self):
         """Create training, test, and validation samplers.
-        
+
         This should return a dictionary with "train", "val", "test" as keys and
         indices of datapoints as values.
         """
@@ -24,8 +26,10 @@ def name():
         """Name of the sampling method."""
         pass
 
+
 class RandomSampler(Sampler):
     """Perform uniform random sampling on datapoints."""
+
     def __init__(self, seed, dataset_size):
         """Initialize sampler.
 
@@ -66,21 +70,21 @@ def create_samplers(self, sample_config):
         train_size = int(np.ceil(sample_config["train"] * self.dataset_size))
         train_idx = idx_array[:train_size]
         val_size = int(np.ceil(sample_config["val"] * self.dataset_size))
-        val_idx = idx_array[train_size: train_size + val_size]
-        test_idx = idx_array[train_size + val_size:]
+        val_idx = idx_array[train_size : train_size + val_size]
+        test_idx = idx_array[train_size + val_size :]
 
         # Create samples
         samples = {"train": train_idx, "val": val_idx, "test": test_idx}
-        
+
         return samples
-    
+
     @staticmethod
     def name():
+        """Name of the sampling method."""
         return "random"
 
+
 if __name__ == "__main__":
     rs = RandomSampler(0, 100)
     samples = rs.create_samplers({"train": 0.6, "val": 0.2, "test": 0.2})
     print(samples)
-
-