Revise visualisations

app/pages/1_Scenario_comparison.py

@@ -25,13 +25,24 @@ def main():
     df = helper.get_df_for_parameter(
         network_map, option, helper.add_values_for_statistics, helper.get_stats_col_names
     )
-    _,plot_col,_=st.columns([1,80,1])
+    _, plot_col,_ = st.columns([1, 80, 1])
     with plot_col:
-        st.plotly_chart(px.bar(df, y=df.columns,labels={
-            "value":get_stat_unit(option),
-            "index":"scenarios"
-        }, title=option),use_cointainer_width=True
-                    )
+        if option == "Capacity Factor":
+            st.plotly_chart(px.scatter(df, y=df.columns,
+                # TODO Would be nice to adjust markers
+                # size=[20],
+                labels={
+                    "value":get_stat_unit(option),
+                    "index":"scenarios"
+                }, title=option),use_cointainer_width=True
+            )
+        else:
+            st.plotly_chart(px.bar(df, y=df.columns, 
+                labels={
+                    "value":get_stat_unit(option),
+                    "index":"scenarios"
+                }, title=option),use_cointainer_width=True
+            )    
 
     ##### second dropdown plotting n.carrier #####
     option = st.selectbox(

app/pages/2_Spatial_configuration.py

@@ -30,7 +30,7 @@
 
 
 data=helper.make_return_dict()
-st.title("System operation")
+st.title("Spatial configuration")
 
 
 _, main_col, _ = st.columns([1,90,1])
@@ -80,7 +80,7 @@ def spatial_param_formatter(param):
 
     colorpeth_param = st.selectbox(
             "Regions", colorpeth_nodes_param, 
-            format_func=  spatial_param_formatter,
+            format_func = spatial_param_formatter,
             key="colorpeth_param_carrier"
 
         )
@@ -121,7 +121,7 @@ def spatial_param_formatter(param):
 with col3:
     points_param = st.selectbox(
             "Nodes", colorpeth_nodes_param,
-            format_func=  spatial_param_formatter,
+            format_func = spatial_param_formatter,
            key="points_param_carrier"
         )
 

app/pages/3_System_operation.py

@@ -27,10 +27,15 @@
 from shapely.geometry import Point, LineString, shape
 import datetime
 
+non_empth_links_keys=[param for param in helper.config["links_t_parameter"]]
+non_empth_loads_keys=[param for param in helper.config["loads_t_parameter"]]
+non_empth_stores_keys=[param for param in helper.config["stores_t_parameter"]]
 
-gen_df=helper.get_gen_t_dict()
-storage_df=helper.get_storage_t_dict()
-links_df=helper.get_links_t_dict()
+gen_df = helper.get_gen_t_dict()
+storage_df = helper.get_storage_t_dict()
+links_df = helper.get_links_t_dict("links_t", non_empth_links_keys)
+loads_df = helper.get_links_t_dict("loads_t", non_empth_loads_keys)
+stores_df = helper.get_links_t_dict("stores_t", non_empth_stores_keys)
 
 res_choices = helper.config["operation"]["resolution"]
 
@@ -46,7 +51,7 @@
 
 st.title("System operation")
 
-_, main_col, _ = st.columns([1,90,1])
+_, main_col, _, suppl_col, _ = st.columns([1, 35, 1, 20, 1])
 
 def scenario_formatter(scenario):
     return helper.config["scenario_names"][scenario]
@@ -55,33 +60,38 @@ def scenario_formatter(scenario):
     selected_network = st.selectbox(
         "Select which scenario's plot you want to see :",
         list(gen_df.keys()),
-        format_func=scenario_formatter,
+        format_func = scenario_formatter,
     )
+with suppl_col:
+    choices = res_choices
+    res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x], key="gen_res") 
+
 
 country_data=gen_df.get(selected_network)
 
 
 ##################### generators #####################
-st.subheader("Generators plot is here.")
+# st.subheader("Generators plot is here.")
 
 def gen_formatter(gen):
-    return helper.config["gen_t_parameter"][gen]["nice_name"] + " "+helper.config["gen_t_parameter"][gen]["unit"]
+    return helper.config["gen_t_parameter"][gen]["nice_name"]
 
-_, gen_param_col,_,res_param_col,_,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
-_, gen_plot_col, _ = st.columns([1,80,1])
+# _, gen_param_col, _, res_param_col,_ ,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
+_, date_range_param, _ = st.columns([1, 50, 1])
+_, gen_plot_col, _ = st.columns([1, 80, 1])
 
-with gen_param_col:
-    selected_gen = st.selectbox(
-        "options",
-        options=list(country_data.keys()),
-        format_func=gen_formatter
-    )
+# with gen_param_col:
+#     selected_gen = st.selectbox(
+#         "options",
+#         options=list(country_data.keys()),
+#         format_func=gen_formatter
+#     )
 
-gen_df=country_data[selected_gen]
+gen_df=country_data["p"].drop("Load", axis=1, errors="ignore")
 
-with res_param_col:
-    choices = res_choices
-    res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x],key="gen_res")
+# with res_param_col:
+#     choices = res_choices
+#     res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x], key="gen_res")
 
 with date_range_param:
     min_index=gen_df.index[0]
@@ -98,122 +108,124 @@ def gen_formatter(gen):
         )
 
 
-gen_df=gen_df.loc[values[0]:values[1]].resample(res).mean()
+gen_df = gen_df.loc[values[0]:values[1]].resample(res).mean()
 
-gen_area_plot=gen_df.hvplot.area(**kwargs,group_label=helper.config["gen_t_parameter"][selected_gen]["legend_title"]
-) 
-gen_area_plot=gen_area_plot.opts(ylabel=helper.config["gen_t_parameter"][selected_gen]["unit"],
-   )
-s=hv.render(gen_area_plot,backend='bokeh')
+ylab = helper.config["gen_t_parameter"]["p"]["nice_name"] + " ["+str(helper.config["gen_t_parameter"]["p"]["unit"] + "]")
+# Not sure we really need a title, as there is still a header
+gen_area_plot = gen_df.hvplot.area(**kwargs, group_label=helper.config["gen_t_parameter"]["p"]["legend_title"]) 
+gen_area_plot = gen_area_plot.opts(xlabel="", ylabel=ylab)
+s=hv.render(gen_area_plot, backend='bokeh')
 
 with gen_plot_col:
     st.bokeh_chart(s, use_container_width=True)
 
 
 ##################### links #####################
 
-st.subheader("Links plot is here.")
-_, links_param_col,_,res_param_col,_,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
-_, links_plot_col, _ = st.columns([1,80,1])
+# st.subheader("Links plot is here.")
+# _, links_param_col,_,res_param_col,_,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
+_, links_plot_col, _ = st.columns([1, 80, 1])
 
 links_country_data=links_df.get(selected_network)
+loads_country_data=loads_df.get(selected_network)
+stores_country_data=stores_df.get(selected_network)
 
 def links_formatter(link):
     return helper.config["links_t_parameter"][link]["nice_name"] + " "+helper.config["links_t_parameter"][link]["unit"]
 
-with links_param_col:
-    selected_link = st.selectbox(
-        "Select which link's plot you want to see :",
-        list(links_country_data.keys()),
-        format_func=links_formatter
-    )
-
-links_df=links_country_data[selected_link]
-
-with res_param_col:
-    choices = res_choices
-    res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x], key="links_res")
-
-with date_range_param:
-    min_index=links_df.index[0]
-    max_index=links_df.index[-1]
-    min_value = datetime.datetime(min_index.year, min_index.month, min_index.day,max_index.hour,max_index.minute)
-    max_value = datetime.datetime(max_index.year, max_index.month, max_index.day,max_index.hour,max_index.minute)
-    values = st.slider(
-            'Select a range of values',
-            min_value, max_value, (min_value, max_value),
-            # step=datetime.timedelta(hours=int(res[:-1])),
-            format="D MMM, HH:mm",
-            label_visibility='hidden',
-            key="links_date"
-        )
+# with links_param_col:
+#     selected_link = st.selectbox(
+#         "Select which link's plot you want to see :",
+#         list(links_country_data.keys()),
+#         format_func=links_formatter
+#     )
+
+links_df = links_country_data["p0"]
+loads_df = loads_country_data["p"]
+stores_df = stores_country_data["p"]
+
+# TODO Remove hard-coding
+h2_cols = [col for col in stores_df.columns if "H2" in col]
+battery_cols = [col for col in stores_df.columns if "battery" in col]
+
+demand_df=pd.DataFrame({"load": loads_df.sum(axis=1)})
+demand_df["H2"]=stores_df[h2_cols].sum(axis=1)
+demand_df["battery"]=stores_df[battery_cols].sum(axis=1)
+
+# with res_param_col:
+#     choices = res_choices
+#     res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x], key="links_res")
+
+# with date_range_param:
+#     min_index = links_df.index[0]
+#     max_index = links_df.index[-1]
+#     min_value = datetime.datetime(min_index.year, min_index.month, min_index.day, max_index.hour, max_index.minute)
+#     max_value = datetime.datetime(max_index.year, max_index.month, max_index.day, max_index.hour, max_index.minute)
+#     values = st.slider(
+#             'Select a range of values',
+#             min_value, max_value, (min_value, max_value),
+#             # step=datetime.timedelta(hours=int(res[:-1])),
+#             format="D MMM, HH:mm",
+#             label_visibility='hidden',
+#             key="links_date"
+#         )
 
 links_df=links_df.loc[values[0]:values[1]].resample(res).mean()
 
+ylab = helper.config["links_t_parameter"]["p0"]["nice_name"] + " ["+str(helper.config["links_t_parameter"]["p0"]["unit"] + "]")
+
 with links_plot_col:
-    supply_df=pd.DataFrame(index=links_df.index)
-    demand_df=pd.DataFrame(index=links_df.index)
-    supply_df["battery charger"]=links_df["battery charger"]
-    supply_df["H2 Electrolysis"]=links_df["H2 Electrolysis"]
-    demand_df["battery discharger"]=links_df["battery discharger"]
-    demand_df["Fuel Cell"]=links_df["Fuel Cell"]
-    supply_area_plot=supply_df.hvplot.area(**kwargs,ylabel=helper.config["links_t_parameter"][selected_link]["unit"],
-    group_label=helper.config["links_t_parameter"][selected_link]["legend_title"])
-    demand_area_plot=demand_df.hvplot.area(**kwargs,ylabel=helper.config["links_t_parameter"][selected_link]["unit"],
-    group_label=helper.config["links_t_parameter"][selected_link]["legend_title"])  
-    s=hv.render(supply_area_plot,backend='bokeh')
-    s2=hv.render(demand_area_plot,backend='bokeh')
-    st.subheader("Supply")
-    st.bokeh_chart(s, use_container_width=True)
-    st.subheader("Consumption")
+    demand_area_plot=demand_df.hvplot.area(**kwargs, ylabel=ylab,
+    group_label=helper.config["links_t_parameter"]["p0"]["legend_title"])  
+    s2=hv.render(demand_area_plot, backend='bokeh')
     st.bokeh_chart(s2, use_container_width=True)
 
 
 
-##################### storage #####################
+# ##################### storage #####################
 
-st.subheader("Storage plot is here.")
+# st.subheader("Storage plot is here.")
 
-_, storage_param_col,_,res_param_col,_,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
-_, storage_plot_col, _ = st.columns([1,80,1])
+# _, storage_param_col,_,res_param_col,_,date_range_param, _ = st.columns([1,20,1,20,1,50,1])
+# _, storage_plot_col, _ = st.columns([1,80,1])
 
-storage_country_data=storage_df.get(selected_network)
+# storage_country_data=storage_df.get(selected_network)
 
-def storage_formatter(storage):
-    return helper.config["storage_t_parameter"][storage]["nice_name"] + " "+helper.config["storage_t_parameter"][storage]["unit"]
+# def storage_formatter(storage):
+#     return helper.config["storage_t_parameter"][storage]["nice_name"] + " "+helper.config["storage_t_parameter"][storage]["unit"]
 
-with storage_param_col:
-    selected_storage = st.selectbox(
-        "options",
-        list(storage_country_data.keys()),
-        format_func=storage_formatter
-    )
+# with storage_param_col:
+#     selected_storage = st.selectbox(
+#         "options",
+#         list(storage_country_data.keys()),
+#         format_func=storage_formatter
+#     )
 
-storage_df=storage_country_data[selected_storage]
+# storage_df=storage_country_data[selected_storage]
 
-with res_param_col:
-    choices = res_choices
-    res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x],key="storage_res")
+# with res_param_col:
+#     choices = res_choices
+#     res = st.selectbox("Resolution", choices, format_func=lambda x: choices[x],key="storage_res")
 
-with date_range_param:
-    min_index=storage_df.index[0]
-    max_index=storage_df.index[-1]
-    min_value = datetime.datetime(min_index.year, min_index.month, min_index.day,max_index.hour,max_index.minute)
-    max_value = datetime.datetime(max_index.year, max_index.month, max_index.day,max_index.hour,max_index.minute)
-    values = st.slider(
-            'Select a range of values',
-            min_value, max_value, (min_value, max_value),
-            # step=datetime.timedelta(hours=int(res[:-1])),
-            format="D MMM, HH:mm",
-            label_visibility='hidden',
-            key="storage_date"
-        )
+# with date_range_param:
+#     min_index=storage_df.index[0]
+#     max_index=storage_df.index[-1]
+#     min_value = datetime.datetime(min_index.year, min_index.month, min_index.day,max_index.hour,max_index.minute)
+#     max_value = datetime.datetime(max_index.year, max_index.month, max_index.day,max_index.hour,max_index.minute)
+#     values = st.slider(
+#             'Select a range of values',
+#             min_value, max_value, (min_value, max_value),
+#             # step=datetime.timedelta(hours=int(res[:-1])),
+#             format="D MMM, HH:mm",
+#             label_visibility='hidden',
+#             key="storage_date"
+#         )
 
-storage_df=storage_df.loc[values[0]:values[1]].resample(res).mean()
+# storage_df=storage_df.loc[values[0]:values[1]].resample(res).mean()
 
-with storage_plot_col:
-    storage_area_plot=storage_df.hvplot.area(**kwargs,
-    ylabel=helper.config["storage_t_parameter"][selected_storage]["unit"],
-    group_label=helper.config["storage_t_parameter"][selected_storage]["legend_title"])
-    s=hv.render(storage_area_plot,backend='bokeh')
-    st.bokeh_chart(s, use_container_width=True)
+# with storage_plot_col:
+#     storage_area_plot=storage_df.hvplot.area(**kwargs,
+#     ylabel=helper.config["storage_t_parameter"][selected_storage]["unit"],
+#     group_label=helper.config["storage_t_parameter"][selected_storage]["legend_title"])
+#     s=hv.render(storage_area_plot,backend='bokeh')
+#     st.bokeh_chart(s, use_container_width=True)