add example for data handlers to docs too

docs/_source/customise.rst

@@ -248,6 +248,53 @@ Custom Data Handler
 * (optionally) Overwrite the base class :py:`self.get_coordinates()` method to return coordinates as dictionary with
   keys *lon* and *lat*.
 
+.. code-block:: python
+
+    import datetime as dt
+    import numpy as np
+    import pandas as pd
+    import xarray as xr
+
+    from mlair.data_handler import AbstractDataHandler
+
+    class DummyDataHandler(AbstractDataHandler):
+
+        def __init__(self, name, number_of_samples=None):
+            """This data handler takes a name argument and the number of samples to generate. If not provided, a random
+            number between 100 and 150 is set."""
+            super().__init__()
+            self.name = name
+            self.number_of_samples = number_of_samples if number_of_samples is not None else np.random.randint(100, 150)
+            self._X = self.create_X()
+            self._Y = self.create_Y()
+
+        def create_X(self):
+            """Inputs are random numbers between 0 and 10 with shape (no_samples, window=14, variables=5)."""
+            X = np.random.randint(0, 10, size=(self.number_of_samples, 14, 5))  # samples, window, variables
+            datelist = pd.date_range(dt.datetime.today().date(), periods=self.number_of_samples, freq="H").tolist()
+            return xr.DataArray(X, dims=['datetime', 'window', 'variables'], coords={"datetime": datelist,
+                                                                                     "window": range(14),
+                                                                                     "variables": range(5)})
+
+        def create_Y(self):
+            """Targets are normal distributed random numbers with shape (no_samples, window=5, variables=1)."""
+            Y = np.round(0.5 * np.random.randn(self.number_of_samples, 5, 1), 1)  # samples, window, variables
+            datelist = pd.date_range(dt.datetime.today().date(), periods=self.number_of_samples, freq="H").tolist()
+            return xr.DataArray(Y, dims=['datetime', 'window', 'variables'], coords={"datetime": datelist,
+                                                                                     "window": range(5),
+                                                                                     "variables": range(1)})
+
+        def get_X(self, upsampling=False, as_numpy=False):
+            """Upsampling parameter is not used for X."""
+            return np.copy(self._X) if as_numpy is True else self._X
+
+        def get_Y(self, upsampling=False, as_numpy=False):
+            """Upsampling parameter is not used for Y."""
+            return np.copy(self._Y) if as_numpy is True else self._Y
+
+        def __str__(self):
+            return self.name
+
 
 Customised Run Module and Workflow
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