Add examples for presentation

.gitignore

@@ -4,5 +4,8 @@
 src/cpdbench-log.txt
 src/cpdbench-result.json
 
+*.txt
+*.json
+
 venv
 venv-new

src/cpdbench/examples/ExampleAlgorithms.py

@@ -1,6 +1,29 @@
+from changepoynt.algorithms.sst import SST
+
+
 def numpy_array_accesses(dataset, array_indexes):
     indexes = []
     for i in array_indexes:
         indexes.append(dataset[i])
     confidences = [1 for _ in range(len(indexes))]
     return indexes, confidences
+
+
+def algorithm_execute_single_esst(signal):
+    """Uses SST as implemented in the changepoynt library as algorithm."""
+    detector = SST(90, method='rsvd')
+    sig = signal[0]
+    res = detector.transform(sig)
+    indexes = [res.argmax()]
+    confidences = [1.0]
+    return indexes, confidences
+
+
+def algorithm_execute_single_esst(signal, window_length):
+    """Uses SST as implemented in the changepoynt library as algorithm."""
+    detector = SST(window_length, method='rsvd')
+    sig = signal[0]
+    res = detector.transform(sig)
+    indexes = [res.argmax()]
+    confidences = [1.0]
+    return indexes, confidences

src/cpdbench/examples/ExampleDatasets.py

@@ -1,10 +1,26 @@
 import pathlib
 
+import numpy as np
+
 from cpdbench.dataset.CPD2DFromFileDataset import CPD2DFromFileDataset
+from cpdbench.dataset.CPD2DNdarrayDataset import CPD2DNdarrayDataset
 
 
 def get_extreme_large_dataset_from_file():
     path = pathlib.Path(__file__).parent.resolve()
     path = path.joinpath("data", "very_big_numpy_file.dat")
     dataset = CPD2DFromFileDataset(str(path), "float32", [5, 245, 255, 256, 25])
     return dataset
+
+def dataset_get_apple_dataset():
+    raw_data = np.load("../../../data/apple.npy")
+    timeseries = raw_data[:, 0]
+    reshaped_ts = np.reshape(timeseries, [1, timeseries.size])
+    return CPD2DNdarrayDataset(reshaped_ts, [337])
+
+
+def dataset_get_bitcoin_dataset():
+    raw_data = np.load("../../../data/bitcoin.npy")
+    timeseries = raw_data[:, 0]
+    reshaped_ts = np.reshape(timeseries, [1, timeseries.size])
+    return CPD2DNdarrayDataset(reshaped_ts, [569])

src/cpdbench/examples/Example_Parameters.py

@@ -0,0 +1,30 @@
+from cpdbench.CPDBench import CPDBench
+import cpdbench.examples.ExampleDatasets as example_datasets
+import cpdbench.examples.ExampleAlgorithms as example_algorithms
+import cpdbench.examples.ExampleMetrics as example_metrics
+
+cpdb = CPDBench()
+
+
+@cpdb.dataset
+def get_apple_dataset():
+    return example_datasets.dataset_get_apple_dataset()
+
+
+@cpdb.dataset
+def get_bitcoin_dataset():
+    return example_datasets.dataset_get_bitcoin_dataset()
+
+
+@cpdb.algorithm
+def execute_esst_test(signal, *, window_length):
+    return example_algorithms.algorithm_execute_single_esst(signal, window_length)
+
+
+@cpdb.metric
+def calc_accuracy(indexes, scores, ground_truth, *, window_size):
+    return example_metrics.metric_accuracy_in_allowed_windows(indexes, scores, ground_truth, window_size=window_size)
+
+
+if __name__ == '__main__':
+    cpdb.start("configs/parametersConfig.yml")

src/cpdbench/examples/Example_Simple.py

@@ -0,0 +1,30 @@
+from cpdbench.CPDBench import CPDBench
+import cpdbench.examples.ExampleDatasets as example_datasets
+import cpdbench.examples.ExampleAlgorithms as example_algorithms
+import cpdbench.examples.ExampleMetrics as example_metrics
+
+cpdb = CPDBench()
+
+
+@cpdb.dataset
+def get_apple_dataset():
+    return example_datasets.dataset_get_apple_dataset()
+
+
+@cpdb.dataset
+def get_bitcoin_dataset():
+    return example_datasets.dataset_get_bitcoin_dataset()
+
+
+@cpdb.algorithm
+def execute_esst_test(signal):
+    return example_algorithms.algorithm_execute_single_esst(signal)
+
+
+@cpdb.metric
+def calc_accuracy(indexes, scores, ground_truth):
+    return example_metrics.metric_accuracy_in_allowed_windows(indexes, scores, ground_truth, window_size=25)
+
+
+if __name__ == '__main__':
+    cpdb.start()

src/cpdbench/examples/configs/parametersConfig.yml

@@ -0,0 +1,19 @@
+logging:
+  filename: cpdbench-log-parameters.txt
+  log-level: DEBUG
+  log-level-console: WARNING
+multiprocessing: True
+
+result:
+  filename: cpdbench-result-parameters.json
+
+
+user:
+  algorithm-executions:
+    - window_length: 90
+    - window_length: 45
+    - window_length: 70
+
+  metric-executions:
+    - window_size: 50
+    - window_size: 20

src/cpdbench/task/AlgorithmExecutionTask.py

@@ -38,4 +38,4 @@ def execute(self, data: ndarray) -> tuple[Iterable, Iterable]:
         return alg_res_index, alg_res_scores
 
     def get_task_name(self) -> str:
-        return f"algorithm: {self._task_name}"
+        return f"algorithm:{self._task_name}"

src/cpdbench/task/DatasetFetchTask.py

@@ -36,4 +36,4 @@ def execute(self) -> CPDDataset:
         return dataset
 
     def get_task_name(self) -> str:
-        return f"dataset: {self._task_name}"
+        return f"dataset:{self._task_name}"

src/cpdbench/task/MetricExecutionTask.py

@@ -33,4 +33,4 @@ def validate_input(self, indexes: Iterable, scores: Iterable, ground_truths: Ite
             return res
 
     def get_task_name(self) -> str:
-        return f"metric: {self._task_name}"
+        return f"metric:{self._task_name}"