298 bug on speedup plot

src/feelpp/benchmarking/dashboardRenderer/core/treeBuilder.py

@@ -134,7 +134,7 @@ def render( self, base_path:str ) -> None:
         super().render(base_path,None,renderLeaves=False)
         self.leaf_repository.render(base_path)
 
-    def patchTemplateInfo( self, patches:list[str], targets:str, prefix:str, save:bool = False ):
+    def patchTemplateInfo( self, patches:List[str], targets:str, prefix:str, save:bool = False ):
         """
         Applies template patches to specific leaf components based on the given target criteria.
 

src/feelpp/benchmarking/dashboardRenderer/repository/leafLoader.py

@@ -59,7 +59,7 @@ def __init__(self, location:str, template_info: TemplateInfo) -> None:
         if not os.path.exists( location ):
             warnings.warn(f"{location} does not contain any files")
 
-    def load(self,repository:Repository, parent_ids:list[str]) -> None:
+    def load(self,repository:Repository, parent_ids:List[str]) -> None:
         """
         Load local leaf components (in the filesystem) into the repository.
         It iterates over subdirectories in the `self.location`, treating each as a separate leaf component, and uses the `ViewFactory` to create a view for it.

src/feelpp/benchmarking/dashboardRenderer/schemas/dashboardSchema.py

@@ -124,11 +124,11 @@ def castNodeTemplateInfo(cls,v):
 
 
 class DashboardSchema(BaseModel):
-    dashboard_metadata:Optional[Union[dict[str,str],TemplateInfo]] = TemplateInfo(data={})
+    dashboard_metadata:Optional[Union[Dict[str,str],TemplateInfo]] = TemplateInfo(data={})
     component_map: Union[ComponentMap,Dict]
-    components: Dict[str,Dict[str, Union[dict[str,str],TemplateInfo]]]
+    components: Dict[str,Dict[str, Union[Dict[str,str],TemplateInfo]]]
     views : Optional[Dict[str,Union[Dict,str]]] = None
-    repositories : Optional[Dict[str,Union[dict[str,str],TemplateInfo]]] = None
+    repositories : Optional[Dict[str,Union[Dict[str,str],TemplateInfo]]] = None
     template_defaults: Optional[TemplateDefaults] = TemplateDefaults()
 
     @model_validator(mode="after")

src/feelpp/benchmarking/json_report/figures/schemas/plot.py

@@ -4,7 +4,7 @@
 class PlotAxis(BaseModel):
     parameter: str
     label:Optional[str] = None
-    filter:Optional[Union[str,list[str],dict[str,str],list[dict[str,str]]]] = []
+    filter:Optional[Union[str,List[str],Dict[str,str],List[Dict[str,str]]]] = []
 
     @field_validator("filter",mode="after")
     @classmethod

src/feelpp/benchmarking/json_report/figures/templates/tikz/groupedBarChart.tex.j2

@@ -23,9 +23,9 @@
       ybar,
       legend style={at={(0.5,-0.1)},anchor=north}
     ]
-    {% for var,name in zip(variables,names) %}
+    {% for var in variables %}
       \addplot table [x expr=\coordindex, y={{ var }}] {{'{#2}'}} ;
-      \addlegendentry{ {{name}} }
+      \addlegendentry{ {{var}} }
     {% endfor %}
 
     \end{axis}

src/feelpp/benchmarking/json_report/figures/templates/tikz/scatterChart.tex.j2

@@ -21,10 +21,10 @@
       xticklabels from table={{'{#2}'}}{{'{'}}{{xaxis.parameter}}{{'}'}},
       cycle list name=color list, legend style={at={(0.5,-0.1)},anchor=north}
     ]
-    {% for var,name in zip(variables,names) %}
+    {% for var in variables %}
       {% if var not in fill_lines %}
       \addplot table [x expr=\coordindex, y={{ var }}] {{'{#2}'}} ;
-      \addlegendentry{ {{name}} }
+      \addlegendentry{ {{var}} }
       {% endif %}
     {% endfor %}
 

src/feelpp/benchmarking/json_report/figures/templates/tikz/stackedBarChart.tex.j2

@@ -41,10 +41,10 @@
       {% if i > 1 %}
       \resetstackedplots
       {% endif %}
-      {% for var,name,color in zip(variables,names, colors) %}
+      {% for var,color in zip(variables, colors) %}
       \addplot+[ybar, bar width=0.2,point meta=y,draw=black,fill={{color}}{% if i > 1 %}, forget plot{% endif %} ] table [x expr=\coordindex+0.25*{{i}}, y={{ var }}] {\data{{i | inttouniquestr}}} ;
       {% if i == 1%}
-      \addlegendentry{ {{name}} }
+      \addlegendentry{ {{var}} }
       {% endif %}
       {% endfor %}
     {% endfor %}

src/feelpp/benchmarking/json_report/figures/tikzFigures.py

@@ -47,6 +47,7 @@ def createMultiindexFigure(self, df, **args):
             xaxis = self.config.xaxis,
             yaxis = self.config.yaxis,
             caption = self.config.title,
+            variables = df.columns.to_list(),
             secondary_axis = self.config.secondary_axis,
             anim_dimension_values = [str(dim) for dim in anim_dim_values],
             csv_filenames = [f"{dim}.csv" for dim in anim_dim_values],
@@ -64,6 +65,7 @@ def createSimpleFigure(self, df, **args):
             xaxis = self.config.xaxis,
             yaxis = self.config.yaxis,
             caption = self.config.title,
+            variables = df.columns.to_list(),
             csv_filenames = [f"{self.config.title}.csv"],
             **args
         )

src/feelpp/benchmarking/json_report/figures/transformationFactory.py

@@ -1,4 +1,5 @@
 import pandas as pd
+import numpy as np
 
 
 class TransformationStrategy:
@@ -153,8 +154,26 @@ def calculate(self,df):
             return pd.DataFrame(columns=["optimal","half-optimal"])
 
         if isinstance(pivot.index, pd.MultiIndex):
-            pivot = pivot.xs(pivot.index.get_level_values(self.dimensions["xaxis"].parameter).min(),level=self.dimensions["xaxis"].parameter,axis=0) / pivot
-            pivot["optimal"] = pivot.index.get_level_values(self.dimensions["xaxis"].parameter) / pivot.index.get_level_values(self.dimensions["xaxis"].parameter).min()
+            lvl = self.dimensions["xaxis"].parameter
+            outer = [n for n in pivot.index.names if n != lvl]
+            group_level = outer[0] if len(outer) == 1 else outer
+
+            results = []
+
+            for key, subdf in pivot.groupby(level=group_level):
+                vals = subdf.index.get_level_values(lvl)
+                ref = np.nanmin(vals)
+
+                base = subdf.xs(ref, level=lvl, axis=0)
+                speed = base / subdf
+
+                speed["optimal"] = vals / ref
+                speed["half-optimal"] = (speed["optimal"] - 1) / 2 + 1
+
+                results.append(speed)
+
+            pivot = pd.concat(results)
+
         else:
             pivot = pivot.loc[pivot.index.min(),:] / pivot
             pivot["optimal"] = pivot.index / pivot.index.min()

src/feelpp/benchmarking/json_report/schemas/jsonReport.py

@@ -117,7 +117,7 @@ def coerceListInput( cls, values ):
         else:
             raise TypeError(f"Expected dict or list at root, got {type(values)}")
 
-    def flattenContent(self, contents = None) -> list[Node]:
+    def flattenContent(self, contents = None) -> List[Node]:
         flattened = []
         if contents is None:
             contents = self.contents