def test_param_effect():
adjustment = {"Business Tax Parameters": {"CIT_rate": 0.35},
"Individual and Payroll Tax Parameters": {}}
comp_dict = functions.run_model({}, adjustment)
df1 = pd.read_csv(io.StringIO(comp_dict['downloadable'][0]['data']))
df2 = pd.read_csv(io.StringIO(comp_dict['downloadable'][1]['data']))
assert max(np.absolute(df1['rho_mix']-df2['rho_mix'])) > 0
def run_model():
meta_param_dict = {
"year": [{
"value": 2020
}],
"data_source": [{
"value": "CPS"
}],
"time_path": [{
"value": True
}],
}
adjustment_dict = {
"OG-USA Parameters": {
"frisch": 0.39,
"initial_debt_ratio": 1.1,
"g_y_annual": 0.029,
"tG1": 22,
},
"Tax-Calculator Parameters": {},
}
comp_dict = functions.run_model(meta_param_dict, adjustment_dict)
pickle.dump(comp_dict, open("ogusa_cs_test_dict.pkl", "wb"))
s = io.StringIO(comp_dict["downloadable"][0]["data"])
with open("ogusa_test_output.csv", "w") as f:
for line in s:
f.write(line)
def test_param_effect():
adjustment = {
"Business Tax Parameters": {
"CIT_rate": 0.35
},
"Individual and Payroll Tax Parameters": {}
}
comp_dict = functions.run_model({}, adjustment)
df = pd.read_csv(io.StringIO(comp_dict['downloadable'][0]['data']))
assert df.loc[0, 'Change from Baseline (pp)'] != 0
def sim(self, meta_param_dict, adjustment):
if os.environ.get("DASK_SCHEDULER_ADDRESS") is not None:
from distributed import Client
from dask import delayed
print("submitting data")
with Client() as c:
print("c", c)
fut = c.submit(functions.run_model, meta_param_dict, adjustment)
print("waiting on result", fut)
return fut.result()
return functions.run_model(meta_param_dict, adjustment)
def sim(self, meta_param_dict, adjustment):
return functions.run_model(meta_param_dict, adjustment)
from cs_config import functions
import cs_storage
from cs_storage.screenshot import write_template
"""
This script is useful to testing the outputs from the cs_config/functions.py
script.
"""
# outputs = functions.run_model(meta_param_dict, adjustment_dict)
outputs = functions.run_model(
{},
{
"mycicd": {
"title": "ParamTools",
"user_or_org": "PSLmodels",
"ref": "master",
"cmds": ["py.test paramtools -v"],
}
},
)
i = 1
for output in outputs["renderable"]:
serializer = cs_storage.get_serializer(output["media_type"])
ser = serializer.serialize(output["data"])
deserialized = dict(output,
data=serializer.deserialize(ser,
json_serializable=True))
deserialized["id"] = f"test-{i}" # Need this output id.
res = write_template(deserialized)
with open(f"{output['title']}.html", "w") as f:
def sim(meta_param_dict, adjustment):
outputs = functions.run_model(meta_param_dict, adjustment)
print("got result")
return cs_storage.serialize_to_json(outputs)
