Merge pull request #169 from agoenergy/various_small_issues

Various small issues

app/plot_functions.py

@@ -75,13 +75,6 @@ def plot_costs_on_map(
     -------
     go.Figure
     """
-    # define title:
-    title_string = (
-        f"{cost_component} cost of exporting "
-        f"{st.session_state['chain']} to "
-        f"{st.session_state['country']}"
-    )
-
     if scope == "world":
         # Create a choropleth world map:
         fig = _choropleth_map_world(
@@ -99,9 +92,7 @@ def plot_costs_on_map(
             custom_data_func=_make_costs_hoverdata,
         )
 
-    return _set_map_layout(
-        fig, title=title_string, colorbar_title=st.session_state["output_unit"]
-    )
+    return _set_map_layout(fig, colorbar_title=st.session_state["output_unit"])
 
 
 def plot_input_data_on_map(
@@ -111,7 +102,6 @@ def plot_input_data_on_map(
         "PV tilted", "Wind Offshore", "Wind Onshore", "Wind-PV-Hybrid", "interest rate"
     ],
     scope: Literal["world", "Argentina", "Morocco", "South Africa"] = "world",
-    title: str = "",
 ) -> go.Figure:
     """
     Plot input data on a map.
@@ -192,9 +182,7 @@ def plot_input_data_on_map(
             custom_data_func_kwargs=custom_data_func_kwargs,
         )
 
-    return _set_map_layout(
-        fig, title=title, colorbar_title=custom_data_func_kwargs["unit"]
-    )
+    return _set_map_layout(fig, colorbar_title=custom_data_func_kwargs["unit"])
 
 
 def _choropleth_map_world(
@@ -278,7 +266,7 @@ def _choropleth_map_deep_dive_country(
     return fig
 
 
-def _set_map_layout(fig: go.Figure, title: str, colorbar_title: str) -> go.Figure:
+def _set_map_layout(fig: go.Figure, colorbar_title: str) -> go.Figure:
     """
     Apply a unified layout for all maps used in the app.
 
@@ -319,7 +307,7 @@ def _set_map_layout(fig: go.Figure, title: str, colorbar_title: str) -> go.Figur
             "len": 0.5,
         },  # colorbar
         margin={"t": 20, "b": 20, "l": 20, "r": 20},  # reduce margin around figure
-        title=title,
+        height=500,
     )
 
     # Set the hover template to use the custom data
@@ -403,7 +391,7 @@ def create_bar_chart_costs(
         marker={"size": 10, "color": "black"},
         name="Total",
         text=res_costs["Total"].apply(
-            lambda x: f"{x:.2f}"
+            lambda x: f"{x:.0f}"
         ),  # Use 'total' column values as text labels
         textposition="top center",  # Position of the text label above the marker
     )

app/ptxboa_functions.py

@@ -1,5 +1,6 @@
 # -*- coding: utf-8 -*-
 """Utility functions for streamlit app."""
+from pathlib import Path
 from typing import Literal
 
 import pandas as pd
@@ -209,8 +210,10 @@ def subset_and_pivot_input_data(
 def get_data_type_from_input_data(
     api: PtxboaAPI,
     data_type: Literal[
+        "electricity_generation",
         "conversion_processes",
         "transportation_processes",
+        "reconversion_processes",
         "CAPEX",
         "full load hours",
         "interest rate",
@@ -230,8 +233,8 @@ def get_data_type_from_input_data(
         api class instance
     data_type : str
         the data type which should be selected. Needs to be one of
-        "conversion_processes", "transportation_processes", "CAPEX", "full load hours",
-        and "interest rate".
+        "electricity_generation", "conversion_processes", "transportation_processes",
+        "reconversion_processes", "CAPEX", "full load hours", and "interest rate".
     scope : Literal[None, "world", "Argentina", "Morocco", "South Africa"]
         The regional scope. Is automatically set to None for data of
         data type "conversion_processes" and "transportation_processes" which is not
@@ -246,13 +249,29 @@ def get_data_type_from_input_data(
         user_data=st.session_state["user_changes_df"],
     )
 
-    if data_type in ["conversion_processes", "transportation_processes"]:
+    if data_type in [
+        "electricity_generation",
+        "conversion_processes",
+        "transportation_processes",
+        "reconversion_processes",
+    ]:
         scope = None
         source_region_code = [""]
         index = "process_code"
         columns = "parameter_code"
         processes = api.get_dimension("process")
 
+    if data_type == "electricity_generation":
+        parameter_code = [
+            "CAPEX",
+            "OPEX (fix)",
+            "lifetime / amortization period",
+            "efficiency",
+        ]
+        process_code = processes.loc[
+            processes["is_re_generation"], "process_name"
+        ].to_list()
+
     if data_type == "conversion_processes":
         parameter_code = [
             "CAPEX",
@@ -261,7 +280,7 @@ def get_data_type_from_input_data(
             "efficiency",
         ]
         process_code = processes.loc[
-            ~processes["is_transport"], "process_name"
+            ~processes["is_transport"] & ~processes["is_re_generation"], "process_name"
         ].to_list()
 
     if data_type == "transportation_processes":
@@ -272,7 +291,18 @@ def get_data_type_from_input_data(
             # FIXME: add bunker fuel consumption
         ]
         process_code = processes.loc[
-            processes["is_transport"], "process_name"
+            processes["is_transport"] & ~processes["is_transformation"], "process_name"
+        ].to_list()
+
+    if data_type == "reconversion_processes":
+        parameter_code = [
+            "CAPEX",
+            "OPEX (fix)",
+            "lifetime / amortization period",
+            "efficiency",
+        ]
+        process_code = processes.loc[
+            processes["is_transport"] & processes["is_transformation"], "process_name"
         ].to_list()
 
     if data_type in ["CAPEX", "full load hours", "interest rate"]:
@@ -463,9 +493,10 @@ def config_number_columns(df: pd.DataFrame, **kwargs) -> {}:
 def display_and_edit_input_data(
     api: PtxboaAPI,
     data_type: Literal[
+        "electricity_generation",
         "conversion_processes",
         "transportation_processes",
-        "CAPEX",
+        "reconversion_processes" "CAPEX",
         "full load hours",
         "interest rate",
     ],
@@ -484,8 +515,8 @@ def display_and_edit_input_data(
         an instance of the api class
     data_type : str
         the data type which should be selected. Needs to be one of
-        "conversion_processes", "transportation_processes", "CAPEX", "full load hours",
-        and "interest rate".
+        "electricity_generation", "conversion_processes", "transportation_processes",
+        "reconversion_processes", "CAPEX", "full load hours", and "interest rate".
     scope : Literal[None, "world", "Argentina", "Morocco", "South Africa"]
         The regional scope. Is automatically set to None for data of
         data type "conversion_processes" and "transportation_processes" which is not
@@ -499,14 +530,23 @@ def display_and_edit_input_data(
     """
     df = get_data_type_from_input_data(api, data_type=data_type, scope=scope)
 
-    if data_type in ["conversion_processes", "transportation_processes"]:
+    if data_type in [
+        "electricity_generation",
+        "conversion_processes",
+        "transportation_processes",
+        "reconversion_processes",
+    ]:
         index = "process_code"
         columns = "parameter_code"
         missing_index_name = "source_region_code"
         missing_index_value = None
         column_config = None
 
-    if data_type == "conversion_processes":
+    if data_type in [
+        "electricity_generation",
+        "conversion_processes",
+        "reconversion_processes",
+    ]:
         column_config = {
             "CAPEX": st.column_config.NumberColumn(format="%.0f USD/kW", min_value=0),
             "OPEX (fix)": st.column_config.NumberColumn(
@@ -522,18 +562,15 @@ def display_and_edit_input_data(
 
     if data_type == "transportation_processes":
         column_config = {
-            "levelized_costs": 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
+            "levelized costs": st.column_config.NumberColumn(
+                format="%.2e USD/(kW km)", min_value=0
             ),
             "lifetime / amortization period": st.column_config.NumberColumn(
                 format="%.0f a", min_value=0
             ),
+            "losses (own fuel, transport)": st.column_config.NumberColumn(
+                format="%.2e fraction per km", min_value=0
+            ),
         }
 
     if data_type == "interest rate":
@@ -605,7 +642,6 @@ def display_and_edit_input_data(
             use_container_width=True,
             column_config=column_config,
         )
-
     return df
 
 
@@ -622,3 +658,18 @@ def move_to_tab(tab_name):
     old_tab_key_nb = int(st.session_state["tab_key"].replace("tab_key_", ""))
     st.session_state["tab_key"] = f"tab_key_{old_tab_key_nb + 1}"
     st.session_state[st.session_state["tab_key"]] = tab_name
+
+
+def read_markdown_file(markdown_file: str) -> str:
+    """Import markdown file as string."""
+    return Path(markdown_file).read_text(encoding="UTF-8")
+
+
+def get_region_from_subregion(subregion: str) -> str:
+    """
+    For a subregion, get the name of the region it belongs to.
+
+    If subregion is not a subregion, return its own name.
+    """
+    region = subregion.split(" (")[0]
+    return region

app/tab_certification_schemes.py

@@ -3,6 +3,8 @@
 import numpy as np
 import streamlit as st
 
+from app.ptxboa_functions import read_markdown_file
+
 
 def _render_scheme_info(context_data, scheme_name):
     df = context_data["certification_schemes"]
@@ -68,14 +70,7 @@ def _render_scheme_info(context_data, scheme_name):
 
 def content_certification_schemes(context_data: dict):
     with st.expander("What is this?"):
-        st.markdown(
-            """
-**Get supplementary information on H2-relevant certification frameworks**
-
-This sheet provides you with an overview of current governmental regulations
-and voluntary standards for H2 products.
-            """
-        )
+        st.markdown(read_markdown_file("md/whatisthis_certification_schemes.md"))
 
     helptext = "Select the certification scheme you want to know more about."
     scheme_name = st.selectbox(

app/tab_country_fact_sheets.py

@@ -2,6 +2,8 @@
 """Content of country fact sheets tab and functions to create it."""
 import streamlit as st
 
+from app.ptxboa_functions import get_region_from_subregion, read_markdown_file
+
 
 def _create_fact_sheet_demand_country(context_data: dict):
     # select country:
@@ -67,61 +69,38 @@ def _create_fact_sheet_demand_country(context_data: dict):
 
 def _create_fact_sheet_supply_country(context_data: dict):
     """Display information on a chosen supply country."""
-    # select country:
+    # select region:
     country_name = st.session_state["region"]
-    df = context_data["supply"]
-    data = df.loc[df["country_name"] == country_name].iloc[0].to_dict()
-
-    st.subheader(f"Fact sheet for {country_name}")
-    text = (
-        "**Technical potential for renewable electricity generation:**\n"
-        f"- {data['source_re_tech_pot_EWI']}: "
-        f"\t{data['re_tech_pot_EWI']:.0f} TWh/a\n"
-        f"- {data['source_re_tech_pot_PTXAtlas']}: "
-        f"\t{data['re_tech_pot_PTXAtlas']:.0f} TWh/a\n"
-    )
 
-    st.markdown(text)
-
-    text = (
-        "**LNG infrastructure:**\n"
-        f"- {data['lng_export']} export terminals\n"
-        f"- {data['lng_import']} import terminals.\n\n"
-        f"*Source: {data['source_lng']}*"
-    )
+    # for subregions, select name of region they belong to:
+    region_name = get_region_from_subregion(country_name)
+    df = context_data["supply"]
+    data = df.loc[df["country_name"] == region_name].iloc[0].to_dict()
+
+    st.subheader(f"Fact sheet for {region_name}")
+    with st.expander("**Technical potential for renewable electricity generation**"):
+        text = (
+            f"- {data['source_re_tech_pot_EWI']}: "
+            f"\t{data['re_tech_pot_EWI']:.0f} TWh/a\n"
+            f"- {data['source_re_tech_pot_PTXAtlas']}: "
+            f"\t{data['re_tech_pot_PTXAtlas']:.0f} TWh/a\n"
+        )
+        st.markdown(text)
 
-    st.markdown(text)
+    with st.expander("**LNG infrastructure**"):
+        text = (
+            f"- {data['lng_export']} export terminals\n"
+            f"- {data['lng_import']} import terminals.\n\n"
+            f"*Source: {data['source_lng']}*"
+        )
+        st.markdown(text)
 
     st.write("TODO: CCS pot, elec prices, H2 strategy")
 
 
 def content_country_fact_sheets(context_data):
     with st.expander("What is this?"):
-        st.markdown(
-            """
-**Country fact sheets**
-
-This sheet provides you with additional information on the production and import of
- hydrogen and derivatives in all PTX BOA supply and demand countries.
-For each selected supply and demand country pair, you will find detailed
- country profiles.
-
- For demand countries, we cover the following aspects:
- country-specific projected hydrogen demand,
- target sectors for hydrogen use,
- hydrogen-relevant policies and competent authorities,
- certification and regulatory frameworks,
- and country-specific characteristics as defined in the demand countries'
- hydrogen strategies.
-
- For the supplying countries, we cover the country-specific technical potential
- for renewables (based on various data sources),
- LNG export and import infrastructure,
- CCS potentials,
- availability of an H2 strategy
- and wholesale electricity prices.
-            """
-        )
+        st.markdown(read_markdown_file("md/whatisthis_country_fact_sheets.md"))
     with st.container(border=True):
         _create_fact_sheet_demand_country(context_data)
     with st.container(border=True):