Merge pull request #625 from Dessia-tech/fix/reference-path

Patch 0.14.1

.pyenchant_dessia.dict

@@ -55,6 +55,7 @@ lte
 Mahalanobis
 matplotlib
 Minkowski
+Multiplot
 nbv
 ndarray
 networkx

CHANGELOG.md

@@ -5,8 +5,18 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## 0.14.0
 
+## 0.14.1
+
+## Changed
+
+- Multiplot block takes selector as a string
+
+### Fixed
+
+- 'reference_path' is now passed on by Display block while evaluating
+
+## 0.14.0
 
 ### Added
 

code_pylint.py

@@ -28,7 +28,7 @@
 MAX_ERROR_BY_TYPE = {
     "protected-access": 48,  # Highly dependant on our "private" conventions. Keeps getting raised
     "arguments-differ": 1,
-    "too-many-locals": 7,  # Reduce by dropping vectored objects
+    "too-many-locals": 6,  # Reduce by dropping vectored objects
     "too-many-branches": 10,  # Huge refactor needed. Will be reduced by schema refactor
     "unused-argument": 6,  # Some abstract functions have unused arguments (plot_data). Hence cannot decrease
     "cyclic-import": 2,  # Still work to do on Specific based DessiaObject

dessia_common/forms.py

@@ -261,13 +261,7 @@ def __init__(self, standalone_subobject: StandaloneBuiltinsSubobject, embedded_s
         self.subclass_arg = subclass_arg
         self.array_arg = array_arg
 
-        self.samples = []
-        for i in range(500):
-            abscissa = round((i % 17) / 2.3, 3)
-            sample = {"cx": abscissa,
-                      "cy": 100 + abscissa * i / 100,
-                      "label": f"label{i % 5}"}
-            self.samples.append(plot_data.Sample(values=sample, name=f"Point{i}"))
+        self._samples = None
 
         MovingObject.__init__(self, name=name)
 
@@ -389,29 +383,44 @@ def primitives(self):
         return plot_data.PrimitiveGroup(primitives=[contour], name="Contour")
 
     @plot_data_view("Scatter Plot")
-    def scatter_plot(self):
+    def scatter_plot(self, **kwargs):
         """ Test plot data decorator for scatter plots. """
+        reference_path = kwargs.get("reference_path", "#")
         attributes = ["cx", "cy"]
         tooltip = plot_data.Tooltip(attributes=attributes, name="Tooltips")
-
-        return plot_data.Scatter(elements=self.samples, tooltip=tooltip, x_variable=attributes[0],
+        samples = self._random_samples(reference_path)
+        return plot_data.Scatter(elements=samples, tooltip=tooltip, x_variable=attributes[0],
                                  y_variable=attributes[1], name="Scatter Plot")
 
     @plot_data_view("Parallel Plot")
-    def parallel_plot(self):
+    def parallel_plot(self, reference_path: str = "#"):
         """ Test plot data decorator for parallel plots. """
-        return plot_data.ParallelPlot(elements=self.samples, axes=["cx", "cy", "label"], name="Parallel Plot")
+        samples = self._random_samples(reference_path)
+        return plot_data.ParallelPlot(elements=samples, axes=["cx", "cy", "label"], name="Parallel Plot")
 
     @plot_data_view("Multiplot", load_by_default=True)
-    def multiplot(self):
+    def multiplot(self, reference_path: str = "#"):
         """ Test plot data decorator for multiple plots. """
-        scatter_plot = self.scatter_plot()
-        parallel_plot = self.parallel_plot()
+        scatter_plot = self.scatter_plot(reference_path=reference_path)
+        parallel_plot = self.parallel_plot(reference_path=reference_path)
         objects = [scatter_plot, parallel_plot]
         sizes = [plot_data.Window(width=560, height=300), plot_data.Window(width=560, height=300)]
-        return plot_data.MultiplePlots(elements=parallel_plot.elements, plots=objects, sizes=sizes,
+        samples = self._random_samples(reference_path=reference_path)
+        return plot_data.MultiplePlots(elements=samples, plots=objects, sizes=sizes,
                                        coords=[(0, 0), (300, 0)], name="Multiple Plot")
 
+    def _random_samples(self, reference_path: str = "#"):
+        """ A dummy method to generate plot_data Samples for testing purpose. """
+        if self._samples is None:
+            samples = []
+            for i in range(500):
+                abscissa = round((i % 17) / 2.3, 3)
+                values = {"cx": abscissa, "cy": 100 + abscissa * i / 100, "label": f"label{i % 5}"}
+                samples.append(plot_data.Sample(values=values, reference_path=f"{reference_path}/path/to/element/{i}",
+                                                name=f"Point{i}"))
+            self._samples = samples
+        return self._samples
+
     def ill_defined_method(self, arg0, arg1=1, arg2: int = 10, arg3=3):
         """ Define a docstring for testing parsing purpose. """
         nok_string = "This is a bad coding behavior"
@@ -658,7 +667,7 @@ class Generator(DessiaObject):
 
     _standalone_in_db = True
 
-    def __init__(self, parameter: int, nb_solutions: int = 25, models: List[StandaloneObject] = None, name: str = ''):
+    def __init__(self, parameter: int, nb_solutions: int = 25, models: List[StandaloneObject] = None, name: str = ""):
         self.parameter = parameter
         self.nb_solutions = nb_solutions
         self.models = models

dessia_common/models/workflows/forms_workflow.py

@@ -2,8 +2,8 @@
 from dessia_common.workflow.core import TypedVariable, TypedVariableWithDefaultValue, Pipe, Workflow
 from dessia_common.workflow.blocks import InstantiateModel, ModelMethod, GetModelAttribute, ForEach,\
     MultiPlot, Unpacker, WorkflowBlock
-from dessia_common.forms import Generator, Optimizer, StandaloneObject
-from dessia_common.typings import MethodType, AttributeType, PlotDataType
+from dessia_common.forms import Generator, Optimizer
+from dessia_common.typings import MethodType, AttributeType
 
 instanciate_generator = InstantiateModel(model_class=Generator, name='Instantiate Generator')
 
@@ -33,8 +33,7 @@
 parallel_optimization = ForEach(workflow_block=optimization_workflow_block, iter_input_index=0, name='ForEach')
 
 multiplot_attributes = ['standalone_subobject/intarg', 'standalone_subobject/name', 'standalone_subobject/floatarg']
-multiplot_selector = PlotDataType(class_=StandaloneObject, name="Multiplot")
-multiplot = MultiPlot(selector=multiplot_selector, attributes=multiplot_attributes, name='Multiplot')
+multiplot = MultiPlot(selector_name="Multiplot", attributes=multiplot_attributes, name='Multiplot')
 
 unpacker = Unpacker(indices=[0], name="Unpacker")
 

dessia_common/models/workflows/workflow_exports.py

@@ -4,7 +4,7 @@
 from dessia_common.workflow.blocks import InstantiateModel, ModelMethod, ModelAttribute, WorkflowBlock, ForEach,\
     Export, Unpacker, Archive, MultiPlot
 from dessia_common.forms import Generator, Optimizer, StandaloneObject
-from dessia_common.typings import MethodType, PlotDataType
+from dessia_common.typings import MethodType
 
 inst = InstantiateModel(model_class=Generator, name='Instantiate Generator')
 
@@ -32,8 +32,7 @@
 parallel_optimization = ForEach(workflow_block=optimization_workflow_block, iter_input_index=0, name='ForEach')
 
 display_attributes = ['intarg', 'strarg', 'standalone_subobject/floatarg']
-multiplot_selector = PlotDataType(class_=StandaloneObject, name="Multiplot")
-display_ = MultiPlot(selector=multiplot_selector, attributes=display_attributes, name='Display')
+display_ = MultiPlot(selector_name="Multiplot", attributes=display_attributes, name='Display')
 
 unpack_results = Unpacker(indices=[0], name="Unpack Results")
 

dessia_common/workflow/blocks.py

@@ -637,7 +637,7 @@ class Display(Block):
     """ Abstract block class for display behaviors. """
 
     _displayable_input = 0
-    _non_editable_attributes = ['inputs']
+    _non_editable_attributes = ["inputs"]
     _type = None
     serialize = False
 
@@ -667,7 +667,19 @@ def evaluate(self, values, **kwargs):
         """ Run method defined by selector's display_setting and compute corresponding DisplayObject. """
         object_ = values[self.inputs[0]]
         settings = object_._display_settings_from_selector(self.selector.name)
-        return [attrmethod_getter(object_, settings.method)()]
+        method = settings.method
+        if "progress_callback" in kwargs:
+            # User methods do not necessarily implement progress callback
+            del kwargs["progress_callback"]
+        try:
+            return [attrmethod_getter(object_, method)(**kwargs)]
+        except TypeError as exc:
+            arguments = list(kwargs.keys())
+            warnings.warn(f"Workflow : method '{method}' was called without generic arguments "
+                          f"('{', '.join(arguments)}') because one of them is not set in method's signature.\n\n "
+                          f"Original exception : \n{repr(exc)}")
+            # Cover cases where kwargs do not correspond to method signature (missing reference_path, for ex)
+            return [attrmethod_getter(object_, method)()]
 
     def _to_script(self, _) -> ToScriptElement:
         """ Write block config into a chunk of script. """
@@ -736,8 +748,9 @@ def _to_script(self, _) -> ToScriptElement:
 
 class MultiPlot(Display):
     """
-    Generate a Multi plot which axes will be the given attributes.
+    Generate a Multiplot which axes will be the given attributes. Will show a Scatter and a Parallel Plot.
 
+    :param selector_name: Name of the selector to be displayed in object page. Must be unique throughout workflow.
     :param attributes: A List of all attributes that will be shown on axes in the ParallelPlot window.
         Can be deep attributes with the '/' separator.
     :param name: Name of the block.
@@ -747,13 +760,17 @@ class MultiPlot(Display):
     _type = "plot_data"
     serialize = True
 
-    def __init__(self, selector: PlotDataType[Type], attributes: List[str], load_by_default: bool = True,
+    def __init__(self, selector_name: str, attributes: List[str], load_by_default: bool = True,
                  name: str = "", position: Tuple[float, float] = None):
         self.attributes = attributes
         Display.__init__(self, inputs=[TypedVariable(List[DessiaObject])], load_by_default=load_by_default,
-                         name=name, selector=selector, position=position)
+                         name=name, selector=PlotDataType(class_=DessiaObject, name=selector_name), position=position)
         self.inputs[0].name = "Input List"
 
+    def __deepcopy__(self, memo=None):
+        return MultiPlot(selector_name=self.selector.name, attributes=self.attributes,
+                         load_by_default=self.load_by_default, name=self.name, position=self.position)
+
     def equivalent(self, other):
         """ Return whether if the block is equivalent to the other given. """
         same_attributes = self.attributes == other.attributes
@@ -792,17 +809,32 @@ def _to_script(self, _) -> ToScriptElement:
         script = f"MultiPlot(attributes={self.attributes}, {self.base_script()})"
         return ToScriptElement(declaration=script, imports=[self.full_classname])
 
+    def to_dict(self, use_pointers: bool = True, memo=None, path: str = '#',
+                id_method=True, id_memo=None) -> JsonSerializable:
+        """ Overwrite to_dict method in order to handle difference of behaviors about selector. """
+        dict_ = super().to_dict(use_pointers=use_pointers, memo=memo, path=path, id_method=id_method, id_memo=id_memo)
+        dict_.update({"selector_name": self.selector.name, "attributes": self.attributes, "name": self.name,
+                      "load_by_default": self.load_by_default, "position": self.position})
+        return dict_
+
     @classmethod
     def dict_to_object(cls, dict_: JsonSerializable, force_generic: bool = False, global_dict=None,
                        pointers_memo: Dict[str, Any] = None, path: str = '#'):
         """ Backward compatibility for old versions of Display blocks. """
-        selector = dict_.get("selector", "Multiplot")
-        if isinstance(selector, str):
+        selector_name = dict_.get("selector_name", None)
+        selector = dict_.get("selector", None)
+        if selector is None and selector_name is None:
+            # Backward compatibility < 0.14.0
             load_by_default = dict_.get("load_by_default", False)
             return DeprecatedMultiPlot(attributes=dict_["attributes"], name=dict_["name"],
                                        load_by_default=load_by_default, position=dict_["position"])
-        selector = PlotDataType.dict_to_object(selector)
-        return MultiPlot(selector=selector, attributes=dict_["attributes"], name=dict_["name"],
+        if selector is not None and selector_name is None:
+            if isinstance(selector, str):
+                selector_name = selector
+            else:
+                # Backward compatibility 0.14.0 < v < 0.14.1
+                selector_name = selector["name"]
+        return MultiPlot(selector_name=selector_name, attributes=dict_["attributes"], name=dict_["name"],
                          load_by_default=dict_["load_by_default"], position=dict_["position"])
 
 

dessia_common/workflow/core.py

@@ -516,9 +516,6 @@ def _equivalent_imposed_variables_values(self, other_wf) -> bool:
 
     def __deepcopy__(self, memo=None):
         """ Return the deep copy. """
-        if memo is None:
-            memo = {}
-
         blocks = [b.__deepcopy__() for b in self.blocks]
         output_adress = self.variable_indices(self.output)
         if output_adress is None:

scripts/ci_scripts.py

@@ -21,7 +21,6 @@
 
     # Workflows
     "workflow/power_simulation.py",
-    "workflow/pipes.py",
     "workflow/workflow_diverge_converge.py",
     "workflow/workflow_clustering.py",
     "workflow/workflow_filtering.py",

tests/test_workflow/test_copy.py

@@ -0,0 +1,28 @@
+import unittest
+from parameterized import parameterized
+from dessia_common.models.workflows.forms_workflow import workflow_
+
+
+class TestWorkflowCopy(unittest.TestCase):
+    def setUp(self) -> None:
+        self.workflow_copy = workflow_.copy()
+
+    def test_check_platform(self):
+        workflow_.check_platform()
+        self.workflow_copy.check_platform()
+
+    @parameterized.expand([
+        "pipes",
+        "nonblock_variables"
+    ])
+    def test_attributes_len(self, name):
+        value = getattr(workflow_, name)
+        copied_value = getattr(self.workflow_copy, name)
+        self.assertEqual(len(value), len(copied_value))
+
+    def variable_names(self):
+        variable_names_are_equal = [p.input_variable.name == cp.input_variable.name
+                                    for p, cp in zip(workflow_.pipes, self.workflow_copy.pipes)]
+        self.assertTrue(all(variable_names_are_equal))
+
+