Merge branch 'develop' into api-optimize-user-data-optional

app/layout_elements.py

@@ -314,7 +314,9 @@ def display_and_edit_input_data(
         missing_index_name = "parameter_code"
         missing_index_value = "interest rate"
         column_config = {
-            c: st.column_config.NumberColumn(format="%.3f", min_value=0, max_value=1)
+            c: st.column_config.NumberColumn(
+                format="%.2f %%", min_value=0, max_value=100
+            )
             for c in df.columns
         }
 

app/plot_functions.py

@@ -129,11 +129,11 @@ def plot_input_data_on_map(
     """
     input_data = get_data_type_from_input_data(api, data_type=data_type, scope=None)
 
-    units = {"CAPEX": "USD/kW", "full load hours": "h/a", "interest rate": ""}
+    units = {"CAPEX": "USD/kW", "full load hours": "h/a", "interest rate": "%"}
 
     if data_type == "interest rate":
         assert color_col == "interest rate"
-        custom_data_func_kwargs = {"float_precision": 3}
+        custom_data_func_kwargs = {"float_precision": 2}
     if data_type == "full load hours":
         assert color_col in [
             "PV tilted",
@@ -155,6 +155,10 @@ def plot_input_data_on_map(
     custom_data_func_kwargs["data_type"] = data_type
     custom_data_func_kwargs["map_variable"] = color_col
 
+    # transform data to % for interest rate
+    if data_type == "interest rate":
+        input_data = input_data * 100
+
     if scope == "world":
         # Create a choropleth world map:
         fig = _choropleth_map_world(
@@ -310,15 +314,18 @@ def _make_inputs_hoverdata(df, data_type, map_variable, unit, float_precision):
     custom_hover_data = []
     if data_type == "interest rate":
         for idx, row in df.iterrows():
-            hover = f"<b>{idx} | {data_type} </b><br><br>{row['interest rate']}"
+            hover = (
+                f"<b>{idx} | {data_type} </b><br><br>"
+                f"{row['interest rate']:.{float_precision}f} {unit}"
+            )
             custom_hover_data.append(hover)
     else:
         for idx, row in df.iterrows():
             hover = f"<b>{idx} | {data_type} </b><br>"
             for i, v in zip(row.index, row):
-                hover += f"<br><b>{i}</b>: {v:.{float_precision}f}{unit}"
+                hover += f"<br><b>{i}</b>: {v:.{float_precision}f} {unit}"
                 if i == map_variable:
-                    hover += " (displayed on map)"
+                    hover += " ← <i>displayed on map</i>"
             custom_hover_data.append(hover)
     return [custom_hover_data]
 

app/ptxboa_functions.py

@@ -421,6 +421,13 @@ def get_data_type_from_input_data(
     if scope in ["Argentina", "Morocco", "South Africa"]:
         df = select_subregions(df, scope)
 
+    # transform data to match unit [%] for 'interest_rate' and 'efficieny'
+    if data_type == "interest rate":
+        df = df * 100
+
+    if "efficiency" in df.columns:
+        df["efficiency"] = df["efficiency"] * 100
+
     return df
 
 
@@ -526,7 +533,7 @@ def get_column_config() -> dict:
         "CAPEX": st.column_config.NumberColumn(format="%.0f USD/kW", min_value=0),
         "OPEX (fix)": st.column_config.NumberColumn(format="%.0f USD/kW", min_value=0),
         "efficiency": st.column_config.NumberColumn(
-            format="%.2f", min_value=0, max_value=1
+            format="%.2f %%", min_value=0, max_value=100
         ),
         "lifetime / amortization period": st.column_config.NumberColumn(
             format="%.0f a",

app/tab_costs.py

@@ -78,8 +78,14 @@ def content_costs(
     with st.container(border=True):
         display_costs(
             remove_subregions(api, costs_per_region, st.session_state["country"]),
-            remove_subregions(
-                api, costs_per_region_without_user_changes, st.session_state["country"]
+            (
+                remove_subregions(
+                    api,
+                    costs_per_region_without_user_changes,
+                    st.session_state["country"],
+                )
+                if st.session_state["user_changes_df"] is not None
+                else None
             ),
             "region",
             "Costs by region",

app/tab_deep_dive_countries.py

@@ -53,7 +53,11 @@ def content_deep_dive_countries(
 
         display_costs(
             select_subregions(costs_per_region, ddc),
-            select_subregions(costs_per_region_without_user_changes, ddc),
+            (
+                select_subregions(costs_per_region_without_user_changes, ddc)
+                if st.session_state["user_changes_df"] is not None
+                else None
+            ),
             key="region",
             titlestring="Costs per subregion",
             key_suffix=ddc,

app/tab_input_data.py

@@ -80,7 +80,7 @@ def content_input_data(api: PtxboaAPI) -> None:
             if data_selection == "full load hours":
                 ylabel = "full load hours (h/a)"
             if data_selection == "interest rate":
-                ylabel = "interest rate (per unit)"
+                ylabel = "interest rate (%)"
             fig = px.box(df)
             fig.update_layout(xaxis_title=None, yaxis_title=ylabel)
             st.plotly_chart(fig, use_container_width=True)

app/user_data.py

@@ -57,6 +57,13 @@ def register_user_changes(
         # Replace the 'id' values with the corresponding index elements from df_tab
         res[index] = res[index].map(lambda x: df_tab.index[x])
 
+        # convert the interest rate from [%] to [decimals]
+        res["value"] = res["value"].astype(float)
+        for param_code in ["interest rate", "efficiency"]:
+            res.loc[res["parameter_code"] == param_code, "value"] = (
+                res.loc[res["parameter_code"] == param_code, "value"] / 100
+            )
+
         if st.session_state["user_changes_df"] is None:
             st.session_state["user_changes_df"] = pd.DataFrame(
                 columns=[
@@ -70,7 +77,7 @@ def register_user_changes(
 
         # only track the last changes if a duplicate entry is found.
         st.session_state["user_changes_df"] = pd.concat(
-            [st.session_state["user_changes_df"], res]
+            [st.session_state["user_changes_df"].astype(res.dtypes), res]
         ).drop_duplicates(
             subset=[
                 "source_region_code",
@@ -95,6 +102,13 @@ def display_user_changes(api):
     """Display input data changes made by user."""
     if st.session_state["user_changes_df"] is not None:
         df = st.session_state["user_changes_df"].copy()
+
+        # convert the values for 'interest rate' and 'efficiency' from [decimals] to [%]
+        for param_code in ["interest rate", "efficiency"]:
+            df.loc[df["parameter_code"] == param_code, "value"] = (
+                df.loc[df["parameter_code"] == param_code, "value"] * 100
+            )
+
         parameters = api.get_dimension("parameter")
         df["Unit"] = df["parameter_code"].map(
             pd.Series(parameters["unit"].tolist(), index=parameters["parameter_name"])

ptxboa_streamlit.py

@@ -153,14 +153,14 @@
 if st.session_state["tab_key"] not in st.session_state:
     st.session_state[st.session_state["tab_key"]] = "Costs"
 
-sac.tabs(
-    [sac.TabsItem(label=i, icon=tabs_icons.get(i, None)) for i in tabs],
+sac.buttons(
+    [sac.ButtonsItem(label=i, icon=tabs_icons.get(i, None)) for i in tabs],
     index=tabs.index(st.session_state[st.session_state["tab_key"]]),
     format_func="title",
     align="center",
     key=st.session_state["tab_key"],
 )
-
+st.divider()
 # create sidebar:
 make_sidebar(api)
 
@@ -169,56 +169,85 @@
     colors = pd.read_csv("data/Agora_Industry_Colours.csv")
     st.session_state["colors"] = colors["Hex Code"].to_list()
 
-# calculate results over different data dimensions:
-costs_per_region = calculate_results_list(
-    api, parameter_to_change="region", parameter_list=None
-)
-costs_per_scenario = calculate_results_list(
-    api,
-    parameter_to_change="scenario",
-    parameter_list=None,
-)
-costs_per_res_gen = calculate_results_list(
-    api,
-    parameter_to_change="res_gen",
-    # TODO: here we remove PV tracking manually, this needs to be fixed in data
-    parameter_list=[
-        x for x in api.get_dimension("res_gen").index.to_list() if x != "PV tracking"
-    ],
-)
-costs_per_chain = calculate_results_list(
-    api,
-    parameter_to_change="chain",
-    parameter_list=None,
-    override_session_state={"output_unit": "USD/MWh"},
-)
+if st.session_state[st.session_state["tab_key"]] in [
+    "Costs",
+    "Market scanning",
+    "Input data",
+    "Deep-dive countries",
+]:
+    # calculate results over different data dimensions:
+    costs_per_region = calculate_results_list(
+        api, parameter_to_change="region", parameter_list=None
+    )
+    costs_per_scenario = calculate_results_list(
+        api,
+        parameter_to_change="scenario",
+        parameter_list=None,
+    )
+    costs_per_res_gen = calculate_results_list(
+        api,
+        parameter_to_change="res_gen",
+        # TODO: here we remove PV tracking manually, this needs to be fixed in data
+        parameter_list=[
+            x
+            for x in api.get_dimension("res_gen").index.to_list()
+            if x != "PV tracking"
+        ],
+    )
+    costs_per_chain = calculate_results_list(
+        api,
+        parameter_to_change="chain",
+        parameter_list=None,
+        override_session_state={"output_unit": "USD/MWh"},
+    )
 
-# calculate results over different data dimensions (without user changes):
-costs_per_region_without_user_changes = calculate_results_list(
-    api, parameter_to_change="region", parameter_list=None, apply_user_data=False
-)
-costs_per_scenario_without_user_changes = calculate_results_list(
-    api, parameter_to_change="scenario", parameter_list=None, apply_user_data=False
-)
-costs_per_res_gen_without_user_changes = calculate_results_list(
-    api,
-    parameter_to_change="res_gen",
-    # TODO: here we remove PV tracking manually, this needs to be fixed in data
-    parameter_list=[
-        x for x in api.get_dimension("res_gen").index.to_list() if x != "PV tracking"
-    ],
-    apply_user_data=False,
-)
-costs_per_chain_without_user_changes = calculate_results_list(
-    api,
-    parameter_to_change="chain",
-    parameter_list=None,
-    override_session_state={"output_unit": "USD/MWh"},
-    apply_user_data=False,
-)
+    if st.session_state["user_changes_df"] is not None:
+        # calculate results over different data dimensions (without user changes):
+        costs_per_region_without_user_changes = calculate_results_list(
+            api,
+            parameter_to_change="region",
+            parameter_list=None,
+            apply_user_data=False,
+        )
+        costs_per_scenario_without_user_changes = calculate_results_list(
+            api,
+            parameter_to_change="scenario",
+            parameter_list=None,
+            apply_user_data=False,
+        )
+        costs_per_res_gen_without_user_changes = calculate_results_list(
+            api,
+            parameter_to_change="res_gen",
+            # TODO: here we remove PV tracking manually, this needs to be fixed in data
+            parameter_list=[
+                x
+                for x in api.get_dimension("res_gen").index.to_list()
+                if x != "PV tracking"
+            ],
+            apply_user_data=False,
+        )
+        costs_per_chain_without_user_changes = calculate_results_list(
+            api,
+            parameter_to_change="chain",
+            parameter_list=None,
+            override_session_state={"output_unit": "USD/MWh"},
+            apply_user_data=False,
+        )
+    else:
+        costs_per_region_without_user_changes = None
+        costs_per_scenario_without_user_changes = None
+        costs_per_res_gen_without_user_changes = None
+        costs_per_chain_without_user_changes = None
 
-# import context data:
-cd = load_context_data()
+if st.session_state[st.session_state["tab_key"]] in [
+    "Country fact sheets",
+    "Certification schemes",
+    "Sustainability",
+    "Literature",
+    "Market scanning",
+]:
+    # import context data:
+    cd = load_context_data()
 
 # costs:
 if st.session_state[st.session_state["tab_key"]] == "Costs":

tests/test_ptxboa_streamlit.py

@@ -16,3 +16,30 @@ def running_app():
 def test_app_smoke(running_app):
     """Test if the app starts up without errors."""
     assert not running_app.exception
+
+
+@pytest.fixture(
+    params=(
+        "Info",
+        "Costs",
+        "Market scanning",
+        "Input data",
+        "Deep-dive countries",
+        "Country fact sheets",
+        "Certification schemes",
+        "Sustainability",
+        "Literature",
+        "Optimization",
+    )
+)
+def running_app_on_tab(request):
+    tab = request.param
+    at = AppTest.from_file("ptxboa_streamlit.py")
+    at.session_state["tab_key"] = "tab_key_0"
+    at.session_state[at.session_state["tab_key"]] = tab
+    at.run(timeout=60)
+    return at
+
+
+def test_tabs_smoke(running_app_on_tab):
+    assert not running_app_on_tab.exception