Enhance plot

proteobench/modules/dda_quant_ion/dda_quant_ion_module.py

@@ -54,7 +54,7 @@ def is_implemented(self) -> bool:
         return True
 
     def benchmarking(
-        self, input_file: str, input_format: str, user_input: dict, all_datapoints, default_cutoff_min_prec: int = 3
+        self, input_file_loc: any, input_format: str, user_input: dict, all_datapoints, default_cutoff_min_prec: int = 3
     ) -> tuple[DataFrame, DataFrame, DataFrame]:
         """
         Main workflow of the module. Used to benchmark workflow results.
@@ -81,7 +81,7 @@ def benchmarking(
         # Parse workflow output file
 
         try:
-            input_df = load_input_file(input_file, input_format)
+            input_df = load_input_file(input_file_loc, input_format)
         except pd.errors.ParserError as e:
             raise ParseError(
                 f"Error parsing {input_format} file, please make sure the format is correct and the correct software tool is chosen: {e}"
@@ -128,10 +128,10 @@ def benchmarking(
         #    raise DatapointGenerationError(f"Error generating datapoint: {e}")
 
         # add current data point to all datapoints
-        try:
-            all_datapoints = self.add_current_data_point(current_datapoint, all_datapoints=all_datapoints)
-        except Exception as e:
-            raise DatapointAppendError(f"Error adding current data point: {e}")
+        # try:
+        all_datapoints = self.add_current_data_point(current_datapoint, all_datapoints=all_datapoints)
+        # except Exception as e:
+        #    raise DatapointAppendError(f"Error adding current data point: {e}")
 
         # return intermediate data structure, all datapoints, and input DataFrame
         # TODO check why there are NA and inf/-inf values

proteobench/modules/quant_base/quant_base_module.py

@@ -100,13 +100,18 @@ def add_current_data_point(
         if not isinstance(all_datapoints, pd.DataFrame):
             all_datapoints = self.github_repo.read_results_json_repo()
 
-        all_datapoints["old_new"] = "old"
         all_datapoints = all_datapoints.T
 
         current_datapoint["old_new"] = "new"
-        all_datapoints = pd.concat([all_datapoints, current_datapoint], axis=1)
-        all_datapoints = all_datapoints.T.reset_index(drop=True)
-        return all_datapoints
+
+        if current_datapoint["intermediate_hash"] not in all_datapoints.loc["intermediate_hash", :].values:
+            all_datapoints.loc["old_new", :] = "old"
+            all_datapoints_new = pd.concat([all_datapoints, current_datapoint], axis=1)
+            all_datapoints_new = all_datapoints_new.T.reset_index(drop=True)
+        else:
+            all_datapoints_new = all_datapoints.T.reset_index(drop=True)
+
+        return all_datapoints_new
 
     def obtain_all_data_points(self, all_datapoints: Optional[pd.DataFrame] = None):
         """
@@ -147,6 +152,7 @@ def filter_data_point(all_datapoints: pd.DataFrame, default_val_slider: int = 3)
         pd.DataFrame
             All data points with the filtered data points.
         """
+        print(all_datapoints)
 
         all_datapoints["median_abs_epsilon"] = [
             filter_df_numquant_median_abs_epsilon(v, min_quant=default_val_slider) for v in all_datapoints["results"]

proteobench/plotting/plot_quant.py

@@ -84,6 +84,7 @@ def plot_metric(
         },
         mapping={"old": 10, "new": 20},
         highlight_color: str = "#d30067",
+        label: str = "None",
     ) -> go.Figure:
         """
         Plot mean metrics in a scatterplot with plotly.
@@ -151,24 +152,45 @@ def plot_metric(
                 for item, highlight in zip(colors, benchmark_metrics_df["Highlight"])
             ]
 
+        benchmark_metrics_df["color"] = colors
+        benchmark_metrics_df["hover_text"] = hover_texts
+        benchmark_metrics_df["scatter_size"] = scatter_size
+
         fig = go.Figure(
-            data=[
-                go.Scatter(
-                    x=benchmark_metrics_df["median_abs_epsilon"],
-                    y=benchmark_metrics_df["nr_prec"],
-                    mode="markers",
-                    text=hover_texts,
-                    marker=dict(color=colors, showscale=False),
-                    marker_size=scatter_size,
-                )
+            layout_yaxis_range=[
+                min(all_nr_prec) - min(max(all_nr_prec) * 0.05, 2000),
+                max(all_nr_prec) + min(max(all_nr_prec) * 0.05, 2000),
             ],
-            layout_yaxis_range=[min(all_nr_prec) - min(all_nr_prec) * 0.05, max(all_nr_prec) + min(all_nr_prec) * 0.05],
             layout_xaxis_range=[
                 min(all_median_abs_epsilon) - min(all_median_abs_epsilon) * 0.05,
                 max(all_median_abs_epsilon) + min(all_median_abs_epsilon) * 0.05,
             ],
         )
 
+        # Get all unique color-software combinations (necessary for highlighting)
+        color_software_combinations = benchmark_metrics_df[["color", "software_name"]].drop_duplicates()
+
+        # plot the data points, one trace per software tool
+        for _, row in color_software_combinations.iterrows():
+            color = row["color"]
+            software = row["software_name"]
+
+            tmp_df = benchmark_metrics_df[
+                (benchmark_metrics_df["color"] == color) & (benchmark_metrics_df["software_name"] == software)
+            ]
+            fig.add_trace(
+                go.Scatter(
+                    x=tmp_df["median_abs_epsilon"],
+                    y=tmp_df["nr_prec"],
+                    mode="markers" if label == "None" else "markers+text",
+                    hovertext=tmp_df["hover_text"],
+                    text=tmp_df[label] if label != "None" else None,
+                    marker=dict(color=tmp_df["color"], showscale=False),
+                    marker_size=tmp_df["scatter_size"],
+                    name=tmp_df["software_name"].iloc[0],
+                )
+            )
+
         fig.update_layout(
             width=700,
             height=700,

webinterface/.streamlit/pages.toml

@@ -6,14 +6,6 @@ name = "Home"
 path = "pages/DDA_Quant_ion.py"
 name = "DDA Quant Ion Level -BETA-"
 
- [[pages]]
- path = "pages/DDA_Quant_peptidoform.py"
- name = "DDA Quant Peptidoform Level -BETA-"
-
- [[pages]]
- path = "pages/DIA_Quant_ion.py"
- name = "DIA Quant Ion Level -BETA-"
-
- [[pages]]
- path = "pages/DIA_Quant_peptidoform.py"
- name = "DIA Quant Peptidoform Level -BETA-"
+[[pages]]
+path = "pages/DIA_Quant_ion.py"
+name = "DIA Quant Ion Level -BETA-"

webinterface/pages/DDA_Quant_ion.py

@@ -36,19 +36,74 @@ def __init__(self):
     def _main_page(self) -> None:
         """
         Sets up the main page layout for the Streamlit application.
-        This includes the title, module descriptions, input forms, and configuration settings.
         """
-        self.quant_uiobjects.create_text_header()
-        self.quant_uiobjects.create_main_submission_form()
+        # Create tabs
+        (
+            tab_description,
+            tab_results_all,
+            tab_submission_details,
+            tab_indepth_plots,
+            tab_results_new,
+            tab_public_submission,
+        ) = st.tabs(
+            [
+                "Module description",
+                "Results (All Data)",
+                "Submission form",
+                "In-depth submission",
+                "Results (New Submissions)",
+                "Public Submission",
+            ]
+        )
 
-        self.quant_uiobjects.init_slider()
+        # Tab 0: Description
+        with tab_description:
+            self.quant_uiobjects.create_text_header()
 
-        if self.quant_uiobjects.variables_quant.fig_logfc in st.session_state:
-            self.quant_uiobjects.populate_results()
+        # Tab 1: Results (All Data)
+        with tab_results_all:
+            st.title(self.variables_dda_quant.texts.ShortMessages.title)
+            if self.variables_dda_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.display_results_all_data()
 
-        self.quant_uiobjects.create_results()
+        # Tab 2: Submission Details
+        with tab_submission_details:
+            self.quant_uiobjects.create_text_header()
+            self.quant_uiobjects.create_main_submission_form()
+            # self.quant_uiobjects.display_submission_details()
 
-        self.quant_uiobjects.render_download_container()
+        # Tab 2.5: in-depth plots current data
+        with tab_indepth_plots:
+            st.title(self.variables_dda_quant.texts.ShortMessages.title)
+            if self.variables_dda_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.plots_for_current_data(True)
+
+        # Tab 3: Results (New Submissions)
+        with tab_results_new:
+            st.title(self.variables_dda_quant.texts.ShortMessages.title)
+            if self.variables_dda_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.display_results_all_data_submitted()
+            # self.quant_uiobjects.display_results_new_submissions()
+
+        # Tab 4: Public Submission
+        with tab_public_submission:
+            st.title(self.variables_dda_quant.texts.ShortMessages.title)
+            if self.variables_dda_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.wrap_public_submission_form()
+            # self.quant_uiobjects.create_main_submission_form()
+            # self.quant_uiobjects.display_public_submission_form()
 
 
 if __name__ == "__main__":

webinterface/pages/DIA_Quant_ion.py

@@ -36,17 +36,74 @@ def __init__(self):
     def _main_page(self) -> None:
         """
         Sets up the main page layout for the Streamlit application.
-        This includes the title, module descriptions, input forms, and configuration settings.
         """
-        self.quant_uiobjects.create_text_header()
-        self.quant_uiobjects.create_main_submission_form()
+        # Create tabs
+        (
+            tab_description,
+            tab_results_all,
+            tab_submission_details,
+            tab_indepth_plots,
+            tab_results_new,
+            tab_public_submission,
+        ) = st.tabs(
+            [
+                "Module description",
+                "Results (All Data)",
+                "Submission form",
+                "In-depth submission",
+                "Results (New Submissions)",
+                "Public Submission",
+            ]
+        )
 
-        self.quant_uiobjects.init_slider()
+        # Tab 0: Description
+        with tab_description:
+            self.quant_uiobjects.create_text_header()
 
-        if self.quant_uiobjects.variables_quant.fig_logfc in st.session_state:
-            self.quant_uiobjects.populate_results()
+        # Tab 1: Results (All Data)
+        with tab_results_all:
+            st.title(self.variables_dia_quant.texts.ShortMessages.title)
+            if self.variables_dia_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.display_results_all_data()
 
-        self.quant_uiobjects.create_results()
+        # Tab 2: Submission Details
+        with tab_submission_details:
+            self.quant_uiobjects.create_text_header()
+            self.quant_uiobjects.create_main_submission_form()
+            # self.quant_uiobjects.display_submission_details()
+
+        # Tab 2.5: in-depth plots current data
+        with tab_indepth_plots:
+            st.title(self.variables_dia_quant.texts.ShortMessages.title)
+            if self.variables_dia_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.plots_for_current_data(True)
+
+        # Tab 3: Results (New Submissions)
+        with tab_results_new:
+            st.title(self.variables_dia_quant.texts.ShortMessages.title)
+            if self.variables_dia_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.display_results_all_data_submitted()
+            # self.quant_uiobjects.display_results_new_submissions()
+
+        # Tab 4: Public Submission
+        with tab_public_submission:
+            st.title(self.variables_dia_quant.texts.ShortMessages.title)
+            if self.variables_dia_quant.beta_warning:
+                st.warning(
+                    "This module is in BETA phase. The figure presented below and the metrics calculation may change in the near future."
+                )
+            self.quant_uiobjects.wrap_public_submission_form()
+            # self.quant_uiobjects.create_main_submission_form()
+            # self.quant_uiobjects.display_public_submission_form()
 
 
 if __name__ == "__main__":