feat: Add validation number of patches parameters

src/careamics_napari/signals/training_signal.py

@@ -142,3 +142,9 @@ class TrainingSignal:
 
     num_conv_filters: int = 32
     """Number of convolutional filters in the first layer."""
+
+    val_percentage: float = 0.1
+    """Percentage of the training data used for validation."""
+
+    val_minimum_split: int = 1
+    """Minimum number of patches or images in the validation set."""

src/careamics_napari/widgets/configuration_window.py

@@ -19,7 +19,14 @@
 
 from careamics_napari.signals import TrainingSignal
 
-from .qt_widgets import create_int_spinbox
+try:
+    from .qt_widgets import create_double_spinbox, create_int_spinbox
+except ImportError:
+    # to run the __name__ == "main" block
+    from careamics_napari.widgets.qt_widgets import (
+        create_double_spinbox,
+        create_int_spinbox,
+    )
 
 # TODO missing:
 # structn2v
@@ -78,6 +85,30 @@ def __init__(
         experiment_widget.setLayout(experiment_layout)
         self.layout().addWidget(experiment_widget)
 
+        ##################
+        # validation
+        validation = QGroupBox("Validation")
+        validation_layout = QFormLayout()
+
+        self.validation_perc = create_double_spinbox(
+            0.01, 1, self.configuration_signal.val_percentage, 0.01, n_decimal=2
+        )
+        self.validation_perc.setToolTip(
+            "Percentage of the training data used for validation."
+        )
+
+        self.validation_split = create_int_spinbox(
+            1, 100, self.configuration_signal.val_minimum_split, 1
+        )
+        self.validation_perc.setToolTip(
+            "Minimum number of patches or images in the validation set."
+        )
+
+        validation_layout.addRow("Percentage", self.validation_perc)
+        validation_layout.addRow("Minimum split", self.validation_split)
+        validation.setLayout(validation_layout)
+        self.layout().addWidget(validation)
+
         ##################
         # augmentations group box, with x_flip, y_flip and rotations
         augmentations = QGroupBox("Augmentations")
@@ -253,6 +284,8 @@ def _save(self: Self) -> None:
         # Update the parameters
         if self.configuration_signal is not None:
             self.configuration_signal.experiment_name = self.experiment_name.text()
+            self.configuration_signal.val_percentage = self.validation_perc.value()
+            self.configuration_signal.val_minimum_split = self.validation_split.value()
             self.configuration_signal.x_flip = self.x_flip.isChecked()
             self.configuration_signal.y_flip = self.y_flip.isChecked()
             self.configuration_signal.rotations = self.rotations.isChecked()
@@ -281,7 +314,7 @@ def _save(self: Self) -> None:
     myalgo = TrainingSignal(use_channels=False)  # type: ignore
 
     # Instantiate widget
-    widget = AdvancedConfigurationWindow(training_signal=myalgo)  # type: ignore
+    widget = AdvancedConfigurationWindow(None, training_signal=myalgo)  # type: ignore
 
     # Show the widget
     widget.show()

src/careamics_napari/workers/training_worker.py

@@ -234,6 +234,8 @@ def _train(
             val_source=val_data,
             train_target=train_data_target,
             val_target=val_data_target,
+            val_minimum_split=config_signal.val_minimum_split,
+            val_percentage=config_signal.val_percentage,
         )
 
         # # TODO can we use this to monkey patch the training process?