Enhance parameter defaults in various datasets (strict validation)

Author: PierreRaybaut

plotpy/styles/image.py

@@ -433,7 +433,7 @@ class MaskedImageParamMixin(DataSet):
     """Mixin for masked image parameters."""
 
     g_mask = BeginGroup(_("Mask"))
-    filling_value = FloatItem(_("Filling value"))
+    filling_value = FloatItem(_("Filling value"), allow_none=True)
     show_mask = BoolItem(_("Show image mask"), default=False)
     alpha_masked = FloatItem(_("Masked area alpha"), default=0.7, min=0, max=1)
     alpha_unmasked = FloatItem(_("Unmasked area alpha"), default=0.0, min=0, max=1)

plotpy/styles/label.py

@@ -47,7 +47,7 @@ class LabelParam(DataSet):
     ___cont = BeginGroup(_("Contents")).set_prop(
         "display", icon="label.png", hide=GetAttrProp("_no_contents")
     )
-    contents = TextItem("").set_prop("display", hide=GetAttrProp("_no_contents"))
+    contents = TextItem("", "").set_prop("display", hide=GetAttrProp("_no_contents"))
     ___econt = EndGroup(_("Contents")).set_prop(
         "display", hide=GetAttrProp("_no_contents")
     )

plotpy/tools/image.py

@@ -447,9 +447,11 @@ def update_status(self, plot: BasePlot) -> None:
 class AspectRatioParam(DataSet):
     """Dataset containing aspect ratio parameters."""
 
-    lock = BoolItem(_("Lock aspect ratio"))
-    current = FloatItem(_("Current value")).set_prop("display", active=False)
-    ratio = FloatItem(_("Lock value"), min=1e-3)
+    lock = BoolItem(_("Lock aspect ratio"), default=True)
+    current = FloatItem(_("Current value"), default=1.0).set_prop(
+        "display", active=False
+    )
+    ratio = FloatItem(_("Lock value"), min=1e-3, default=1.0)
 
 
 class AspectRatioTool(CommandTool):

plotpy/widgets/fit.py

@@ -83,8 +83,8 @@
 class AutoFitParam(DataSet):
     """Automatic fit parameters"""
 
-    xmin = FloatItem("xmin")
-    xmax = FloatItem("xmax")
+    xmin = FloatItem("xmin", default=0.0)
+    xmax = FloatItem("xmax", default=1.0)
     method = ChoiceItem(
         _("Method"),
         [
@@ -99,7 +99,7 @@ class AutoFitParam(DataSet):
     )
     err_norm = StringItem(
         "enorm",
-        default=2.0,
+        default="2.0",
         help=_("for simplex, powel, cg and bfgs norm used by the error function"),
     )
     xtol = FloatItem(
@@ -117,7 +117,7 @@ class AutoFitParam(DataSet):
 class FitParamDataSet(DataSet):
     """Fit parameter dataset"""
 
-    name = StringItem(_("Name"))
+    name = StringItem(_("Name"), default="")
     value = FloatItem(_("Value"), default=0.0)
     min = FloatItem(_("Min"), default=-1.0)
     max = FloatItem(_("Max"), default=1.0).set_pos(col=1)