Add new model and test scaffolds

src/muse/data/example/default_new_input/agent_objectives.csv

@@ -0,0 +1,3 @@
+agent,objective,objective_data,objective_sort
+Agent1,LCOE,1,TRUE
+Agent2,LCOE,1,TRUE

src/muse/data/example/default_new_input/agent_pairs.csv

@@ -0,0 +1,2 @@
+name,new_agent,retrofit_agent,quantity
+A1,Agent1,Agent2,1

src/muse/data/example/default_new_input/agent_regions.csv

@@ -0,0 +1,2 @@
+agent_pair,region
+A1,R1

src/muse/data/example/default_new_input/agents.csv

@@ -0,0 +1,3 @@
+agent,description,type,maturity_threshold,annual_cost_limit,search_rule,decision_rule
+Agent1,New agent for A1,new,-1,inf,all,single
+Agent2,Retrofit agent for A1,retrofit,-1,inf,all,single

src/muse/data/example/default_new_input/assets.csv

@@ -0,0 +1,8 @@
+process_name,region,agent,capacity,year
+gassupply1,R1,Agent2,15,2020
+gassupply1,R1,Agent2,15,2025
+gassupply1,R1,Agent2,7.5,2030
+gasCCGT,R1,Agent2,1,2020
+gasCCGT,R1,Agent2,1,2025
+gasboiler,R1,Agent2,10,2020
+gasboiler,R1,Agent2,5,2025

src/muse/data/example/default_new_input/commodities.csv

@@ -0,0 +1,6 @@
+commodity_name,description,type,unit
+electricity,Electricity,energy,PJ
+gas,Gas,energy,PJ
+heat,Heat,energy,PJ
+wind,Wind,energy,PJ
+C02f,Carbon dioxide,energy,kt

src/muse/data/example/default_new_input/commodity_costs.csv

@@ -0,0 +1,58 @@
+year,region,commodity_name,value
+2010,R1,electricity,14.81481472
+2015,R1,electricity,17.89814806
+2020,R1,electricity,19.5
+2025,R1,electricity,21.93518528
+2030,R1,electricity,26.50925917
+2035,R1,electricity,26.51851861
+2040,R1,electricity,23.85185194
+2045,R1,electricity,23.97222222
+2050,R1,electricity,24.06481472
+2055,R1,electricity,25.3425925
+2060,R1,electricity,25.53703694
+2065,R1,electricity,25.32407417
+2070,R1,electricity,23.36111111
+2075,R1,electricity,22.27777778
+2080,R1,electricity,22.25925917
+2085,R1,electricity,22.17592583
+2090,R1,electricity,22.03703694
+2095,R1,electricity,21.94444444
+2100,R1,electricity,21.39814806
+2010,R1,gas,6.6759
+2015,R1,gas,6.914325
+2020,R1,gas,7.15275
+2025,R1,gas,8.10645
+2030,R1,gas,9.06015
+2035,R1,gas,9.2191
+2040,R1,gas,9.37805
+2045,R1,gas,9.193829337
+2050,R1,gas,9.009608674
+2055,R1,gas,8.832625604
+2060,R1,gas,8.655642534
+2065,R1,gas,8.485612708
+2070,R1,gas,8.315582883
+2075,R1,gas,8.152233126
+2080,R1,gas,7.988883368
+2085,R1,gas,7.831951236
+2090,R1,gas,7.675019103
+2095,R1,gas,7.524252461
+2100,R1,gas,7.373485819
+2010,R1,CO2f,0
+2015,R1,CO2f,0.052913851
+2020,R1,CO2f,0.08314119
+2025,R1,CO2f,0.120069795
+2030,R1,CO2f,0.156998399
+2035,R1,CO2f,0.214877567
+2040,R1,CO2f,0.272756734
+2045,R1,CO2f,0.35394801
+2050,R1,CO2f,0.435139285
+2055,R1,CO2f,0.542365578
+2060,R1,CO2f,0.649591871
+2065,R1,CO2f,0.780892624
+2070,R1,CO2f,0.912193378
+2075,R1,CO2f,1.078321687
+2080,R1,CO2f,1.244449995
+2085,R1,CO2f,1.4253503
+2090,R1,CO2f,1.606250604
+2095,R1,CO2f,1.73877515
+2100,R1,CO2f,1.871299697

src/muse/data/example/default_new_input/commodity_trade.csv

@@ -0,0 +1 @@
+commodity,region,net_import,year

src/muse/data/example/default_new_input/demand.csv

@@ -0,0 +1,3 @@
+year,commodity_name,region,demand
+2020,heat,R1,10
+2050,heat,R1,30

src/muse/data/example/default_new_input/demand_slicing.csv

@@ -0,0 +1,7 @@
+commodity,region,timeslice,fraction,year
+heat,R1,night,0.1,
+heat,R1,morning,0.15,
+heat,R1,afternoon,0.1,
+heat,R1,early-peak,0.15,
+heat,R1,late-peak,0.3,
+heat,R1,evening,0.2,

src/muse/data/example/default_new_input/process_availabilities.csv

@@ -0,0 +1,6 @@
+process_name,timeslice,lim_type,value,year,region
+gassupply1,ALL,UP,0.9,,
+gasCCGT,ALL,UP,0.9,,
+windturbine,ALL,UP,0.4,,
+gasboiler,ALL,UP,1,,
+heatpump,ALL,UP,1,,

src/muse/data/example/default_new_input/process_flows.csv

@@ -0,0 +1,12 @@
+process_name,commodity_name,flow,year,region
+gassupply1,gas,1,,
+gasCCGT,gas,-1.67,,
+gasCCGT,electricity,1,,
+gasCCGT,CO2f,91.67,,
+windturbine,wind,-1,,
+windturbine,electricity,1,,
+gasboiler,gas,-1.16,,
+gasboiler,heat,1,,
+gasboiler,CO2f,64.71,,
+heatpump,electricity,-0.4,,
+heatpump,heat,1,,

src/muse/data/example/default_new_input/process_parameters.csv

@@ -0,0 +1,6 @@
+process,cap_par,cap_exp,fix_par,fix_exp,var_par,var_exp,max_capacity_addition,max_capacity_growth,total_capacity_limit,life,scaling_size,efficiency,discount_rate,year,region
+gassupply1,0,1,0,1,2.55,1,5,1,60,35,0.00000189,86,0.1,,
+gasCCGT,23.78234399,1,0,1,0,1,2,1,60,35,0.00000189,86,0.1,,
+windturbine,36.30771182,1,0,1,0,1,2,1,60,25,0.00000189,86,0.1,,
+gasboiler,3.8,1,0,1,0,1,10,0.02,60,10,0.00000189,86,0.1,,
+heatpump,8.866667,1,0,1,0,1,10,0.02,60,10,0.00000189,86,0.1,,

src/muse/data/example/default_new_input/process_regions.csv

@@ -0,0 +1,6 @@
+process,region
+gassupply1,R1
+gasCCGT,R1
+windturbine,R1
+gasboiler,R1
+heatpump,R1

src/muse/data/example/default_new_input/processes.csv

@@ -0,0 +1,6 @@
+name,type,fuel,end_use,level,sector
+gassupply1,energy,gas,gas,fixed,gas
+gasCCGT,energy,gas,electricity,fixed,power
+windturbine,energy,wind,electricity,fixed,power
+gasboiler,energy,gas,heat,fixed,residential
+heatpump,energy,electricity,heat,fixed,residential

src/muse/data/example/default_new_input/regions.csv

@@ -0,0 +1,2 @@
+name,description
+R1,Region 1

src/muse/data/example/default_new_input/sectors.csv

@@ -0,0 +1,4 @@
+name,description
+gas,Gas sector
+power,Power sector
+residential,Residential sector

src/muse/data/example/default_new_input/time_slices.csv

@@ -0,0 +1,7 @@
+season,day,time_of_day,fraction
+all,all,night,0.1667
+all,all,morning,0.1667
+all,all,afternoon,0.1667
+all,all,early-peak,0.1667
+all,all,late-peak,0.1667
+all,all,evening,0.1667

src/muse/examples.py

@@ -47,7 +47,12 @@ def example_data_dir() -> Path:
 
 def available_examples() -> list[str]:
     """List examples available in the examples folder."""
-    return [d.stem for d in example_data_dir().iterdir() if d.is_dir()]
+    # temporary skip for default_new_input as this is not yet working
+    return [
+        d.stem
+        for d in example_data_dir().iterdir()
+        if d.is_dir() and d.name != "default_new_input"
+    ]
 
 
 def model(name: str = "default") -> MCA:
@@ -108,6 +113,8 @@ def copy_model(
         _copy_minimum_service(path)
     elif name.lower() == "trade":
         _copy_trade(path)
+    elif name.lower() == "default_new_input":
+        _copy_default_new_input(path)
     return path
 
 
@@ -288,6 +295,12 @@ def _copy_default(path: Path):
     copyfile(example_data_dir() / "default" / "settings.toml", path / "settings.toml")
 
 
+def _copy_default_new_input(path: Path):
+    from shutil import copytree
+
+    copytree(example_data_dir() / "default_new_input", path)
+
+
 def _copy_default_timeslice(path: Path):
     from shutil import copyfile, copytree
 

tests/test_readers.py

@@ -5,7 +5,7 @@
 import numpy as np
 import toml
 import xarray as xr
-from pytest import fixture, mark, raises
+from pytest import approx, fixture, mark, raises
 
 
 @fixture
@@ -854,3 +854,148 @@ def test_check_utilization_and_minimum_service_factors_fail_missing_utilization(
 
     with raises(ValueError):
         check_utilization_and_minimum_service_factors(df, "file.csv")
+
+
+@fixture
+def default_new_input(tmp_path):
+    from muse.examples import copy_model
+
+    copy_model("default_new_input", tmp_path)
+    return tmp_path
+
+
+@mark.xfail
+def test_read_new_global_commodities(default_new_input):
+    from muse.new_input.readers import read_inputs
+
+    all_data = read_inputs(default_new_input)
+    data = all_data["global_commodities"]
+
+    assert isinstance(data, xr.Dataset)
+    assert set(data.dims) == {"commodity"}
+    assert dict(data.dtypes) == dict(
+        type=np.dtype("str"),
+        unit=np.dtype("str"),
+    )
+
+    assert list(data.coords["commodity"].values) == [
+        "electricity",
+        "gas",
+        "heat",
+        "wind",
+        "CO2f",
+    ]
+    assert list(data.data_vars["type"].values) == ["energy"] * 5
+    assert list(data.data_vars["unit"].values) == ["PJ"] * 4 + ["kt"]
+
+
+@mark.xfail
+def test_read_demand(default_new_input):
+    from muse.new_input.readers import read_inputs
+
+    all_data = read_inputs(default_new_input)
+    data = all_data["demand"]
+
+    assert isinstance(data, xr.DataArray)
+    assert data.dtype == np.float64
+
+    assert set(data.dims) == {"year", "commodity", "region", "timeslice"}
+    assert list(data.coords["region"].values) == ["R1"]
+    assert list(data.coords["timeslice"].values) == list(range(1, 7))
+    assert list(data.coords["year"].values) == [2020, 2050]
+    assert set(data.coords["commodity"].values) == {
+        "electricity",
+        "gas",
+        "heat",
+        "wind",
+        "CO2f",
+    }
+
+    assert data.sel(year=2020, commodity="electricity", region="R1", timeslice=0) == 1
+
+
+@mark.xfail
+def test_new_read_initial_market(default_new_input):
+    from muse.new_input.readers import read_inputs
+
+    all_data = read_inputs(default_new_input)
+    data = all_data["initial_market"]
+
+    assert isinstance(data, xr.Dataset)
+    assert set(data.dims) == {"region", "year", "commodity", "timeslice"}
+    assert dict(data.dtypes) == dict(
+        prices=np.float64,
+        exports=np.float64,
+        imports=np.float64,
+        static_trade=np.float64,
+    )
+    assert list(data.coords["region"].values) == ["R1"]
+    assert list(data.coords["year"].values) == list(range(2010, 2105, 5))
+    assert list(data.coords["commodity"].values) == [
+        "electricity",
+        "gas",
+        "heat",
+        "CO2f",
+        "wind",
+    ]
+    month_values = ["all-year"] * 6
+    day_values = ["all-week"] * 6
+    hour_values = [
+        "night",
+        "morning",
+        "afternoon",
+        "early-peak",
+        "late-peak",
+        "evening",
+    ]
+
+    assert list(data.coords["timeslice"].values) == list(
+        zip(month_values, day_values, hour_values)
+    )
+    assert list(data.coords["month"]) == month_values
+    assert list(data.coords["day"]) == day_values
+    assert list(data.coords["hour"]) == hour_values
+
+    assert all(var.coords.equals(data.coords) for var in data.data_vars.values())
+
+    prices = data.data_vars["prices"]
+    assert approx(
+        prices.sel(
+            year=2010,
+            region="R1",
+            commodity="electricity",
+            timeslice=("all-year", "all-week", "night"),
+        )
+        - 14.81481,
+        abs=1e-4,
+    )
+
+    exports = data.data_vars["exports"]
+    assert (
+        exports.sel(
+            year=2010,
+            region="R1",
+            commodity="electricity",
+            timeslice=("all-year", "all-week", "night"),
+        )
+    ) == 0
+
+    imports = data.data_vars["imports"]
+    assert (
+        imports.sel(
+            year=2010,
+            region="R1",
+            commodity="electricity",
+            timeslice=("all-year", "all-week", "night"),
+        )
+    ) == 0
+
+    static_trade = data.data_vars["static_trade"]
+    assert (
+        static_trade.sel(
+            year=2010,
+            region="R1",
+            commodity="electricity",
+            timeslice=("all-year", "all-week", "night"),
+        )
+    ) == 0