SPATZ migration + proper directory structure

spatz/sensors/sensor.py

@@ -0,0 +1,64 @@
+import math
+import numpy as np
+
+from abc import abstractmethod
+from typing import List, AnyStr
+from numpy.typing import ArrayLike
+
+from spatz.transforms import *
+from spatz.logger import *
+from spatz.dataset import *
+
+
+class Sensor:
+    def __init__(self, dataset: Dataset, logger: Logger, transforms: List[Transform] = []):
+        self._dataset = dataset
+        self._logger = logger
+        self._transforms = transforms
+
+    def set_dataset(self, dataset: Dataset):
+        self._dataset = dataset
+
+    def set_logger(self, logger: Logger):
+        self._logger = logger
+
+    def _log(self, name: AnyStr, value: Any):
+        self._logger.write(name, value, self._get_name())
+
+    @abstractmethod
+    def _get_name(self) -> AnyStr:
+        raise NotImplementedError()
+
+    @abstractmethod
+    def _sensor_specific_effects(self, x: ArrayLike | float) -> ArrayLike | float:
+        raise NotImplementedError()
+
+    @abstractmethod
+    def _get_data(self) -> ArrayLike | float:
+        raise NotImplementedError()
+
+    def __call__(self) -> ArrayLike | float:
+        out = self._get_data()
+        out = self._sensor_specific_effects(out)
+
+        for transform in self._transforms:
+            out = transform(out)
+
+        # Log the outputs of the sensor.
+        if np.isscalar(out):
+            self._log('out', out)
+        else:
+            for i in range(len(out)):
+                self._log(f'out_{i}', out[i])
+
+        return out
+    
+
+class CompoundSensor(Sensor):
+    def __init__(self, sensors: List[Sensor]):
+        super(CompoundSensor, self).__init__(None)
+
+        self.__sensors = sensors
+
+    def _get_data(self) -> ArrayLike:
+        return np.stack([sensor() for sensor in self.__sensors])