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Merge pull request #18 from ekatef/add_viz
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Revise visualisations
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@pz-max
pz-max authored Aug 15, 2023
2 parents 905d1df + 14475f9 commit 264eb52
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Showing 6 changed files with 226 additions and 160 deletions.
23 changes: 17 additions & 6 deletions app/pages/1_Scenario_comparison.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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(
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6 changes: 3 additions & 3 deletions app/pages/2_Spatial_configuration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@


data=helper.make_return_dict()
st.title("System operation")
st.title("Spatial configuration")


_, main_col, _ = st.columns([1,90,1])
Expand Down Expand Up @@ -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"

)
Expand Down Expand Up @@ -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"
)

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224 changes: 118 additions & 106 deletions app/pages/3_System_operation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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"]

Expand All @@ -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]
Expand All @@ -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]
Expand All @@ -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)
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